Inhibition of circulating glycocholic acid-regulated signaling potentiates immune checkpoint therapy in colorectal cancer

Domain: biology
Published: 2026-04-04
Editorial outcome: major_revision

Abstract
Serum bile acids (BAs) emerge as risk factors for cancer, but their roles in colorectal cancer (CRC) remain unclear.
We show that glycocholic acid (GCA), a primary BA, is elevated in the serum of CRC patients. In a mouse CRC
model, GCA promotes tumor programmed death-ligand 1 (PD-L1) expression in tumors, suppressing CD8⁺ T cell-
mediated antitumor immunity and facilitating tumor growth. Mechanistically, GCA inhibits the BA receptor farnesoid
X receptor (FXR), a transcriptional repressor for SRY-box transcription factor 14 (SOX14). Loss of FXR repression
upregulates SOX14-mediated expression of zinc finger DHHC-type palmitoyl transferase 9 (DHHC9), thereby
reducing PD-L1 palmitoylation and stabilization. Silencing SOX14 or DHHC9, or activating FXR, synergizes with
anti-PD-1 therapy, reducing tumor growth in GCA-treated mice. These findings uncover a mechanism that GCA
remodels the tumor microenvironment to mediate CRC resistance to immunotherapy, highlighting therapeutic
opportunities targeting the FXR-PD-L1 axis in CRC patients with elevated serum GCA.

Introduction
Colorectal cancer (CRC) represents one of the main causes of mortality.1, 2 Previous studies have shown that
programmed death-ligand 1 (PD-L1)-expressing tumor cells attenuate CD8+ T cell infiltration, which results in tumor
progression.3 Immune checkpoint blockade (ICB) therapies, including anti-programmed cell death protein 1 (PD-
1)/PD-L1 or anti-cytotoxic T-lymphocyte-associated protein 4 therapies, have changed the therapeutic landscape and
provided an unprecedented clinical response in various types of cancer.3, 4, 5 Although ICB therapy has durable effects
toward a subset of microsatellite instability-high (MSI-H) CRCs, accounting for ~15% of all CRC cases, only 30-50%
of these patients can benefit from this therapy.6 Regrettably, patients with microsatellite instability stable
(MSS)/proficient mismatch repair (pMMR) (~85%) merely have a 5-10% response rate. Metabolic reprogramming
contributes to tumor immune evasion and progression, which is also considered as an important hallmark in tumors.
It has been shown that metabolic reprogramming in CRC regulated by cholesterol or fatty acids is sufficient to reshape
the tumor microenvironment (TME), leading to resistance towards ICB therapy.7, 8, 9, 10 Therefore, the identification of
key metabolites in regulating resistance to PD-L1 therapy is necessary to combat an immunosuppressive TME in CRC.

The expression of PD-L1 in tumor cells is regulated by various processes, including transcription and post-
transcriptional modifications (PTMs).11 During cell malignant transformation and tumor initiation, the transcription
level of PD-L1 is associated with oncogenic pathways such as aberrant activation of WNT/β-catenin and RAS/MAPK
signaling.12, 13 Moreover, PATMs, including palmitoylation, are critical for regulating the protein stability and function
of PD-L1, and consequentially leading to reduced anti-tumor immunity in the TME. 14 It has been demonstrated that
metabolic stress alters palmitoyl transferase-induced protein palmitoylation.14, 15 Notably, the palmitoyl transferases
zinc finger DHHC-type palmitoyl transferase (DHHC)3 and DHHC9 have been reported as key regulators for
mediating the palmitoylation of PD-L1, which contributes to lysosome sorting during PD-L1 degradation in several
types of cancer.14, 16 Thus, to identify whether and how metabolic alterations in CRC regulate the effects of PD-L1
palmitoylation is important for improving ICB therapy.

Bile acids (BAs) are considered as important regulators of intestinal epithelial homeostasis in the gastrointestinal tract.
In addition to their detergent properties,17 BAs serve as ligands to nuclear (hormone) receptors such as the farnesoid
X receptor (FXR), thus controlling numerous important cellular metabolism, regulatory and signaling functions, as
well as immune responses.18 In CRC, circulating levels of BAs are strongly associated with tumor initiation and
progression.19, 20 However, activation of FXR negatively regulates intestinal cancer stem cell proliferation, leading to
a slower CRC progression.21 Therefore, the role of BAs in regulating tumor initiation and development is still
controversial, and it remains unknown whether alterations in BAs-mediated signaling in tumor cells may affect
immune surveillance and ICB sensitivity.

The present study demonstrated that FXR inactivation mediated by the serum primary BA glycocholic acid (GCA) in
CRC is necessary and sufficient to inhibit the antitumor response of CD8+ T cells. Mechanistically, GCA increased
the expression of the transcription factor (TF) SRY-box transcription factor 14 (SOX14) by inhibiting FXR
transcription-suppressing function, and consequentially promoted the DHHC9-induced palmitoylation and
stabilization of PD-L1. Notably, activation of FXR with the agonist GW4064 sensitized ICB-resistant CRC to anti-
PD-1/PD-L1 treatment. Taken together, the present findings indicate that targeting the FXR signaling pathway is a
potential strategy for alleviating immunosuppressive TME and enhancing the sensitivity to anti-PDL-1 treatment in
CRC.

Results
Increased serum GCA in patients with CRC is associated with poor clinical prognosis. It has been suggested that
the elevation of serum BAs is associated with higher risk for multiple cancer types22, however, the association between
BAs and CRC remains to be elucidated. To investigate whether BAs and which BA is associated with CRC
tumorigenesis, we collected serum samples from 80 patients with CRC (Cohort1) and 20 healthy individuals, and
measured the levels of 33 kinds of BAs including primary free, secondary free, primary conjugated and secondary
conjugated BAs by ultra performance LC-MS. It was found that only 6 BAs, that is, glycocholic acid (GCA),
taurochenodeoxycholic acid (TDCA), taurocholic acid (TCA), taurochenodeoxycholic acid (TCDCA),
glycochenodeoxycholic acid (GCDCA) and glycodeoxycholic acid (GDCAS) were differently expressed, what’s more,
all of these 6 BAs were significantly upregulated in the sera of patients with CRC compared with healthy individuals.
Notably, the concentration of GCA was mostly upregulated compared with the other five types of BAs in patients
with CRC (Fig. 1A). It was also found that the levels of GCA in patients with CRC with stage III/IV or distal metastasis
were higher than those found in patients with CRC with stage I/II or without metastasis (Fig. 1B and C). In addition,
increased levels of GCA were positively associated with poor 5-year disease-free and overall survival (Fig. 1D and
E). Univariate and multivariate survival analyses further indicated that serum GCA served as an independent
prognostic biomarker for poor outcome in patients with CRC (Fig. S1A and B). Furthermore, we validated our results
by using an additional CRAC cohort, and confirmed that the serum concentration of GCA was increased in patients
with stage III/IV or distal metastasis (Fig. S1C and D), leading to worse disease-free and overall survival (Fig. S1E
and F). In addition, higher serum GCA concentrations remained significantly associated with both shorter disease-
free survival (DFS) and overall survival (OS) in CRC patients without liver metastasis (Fig. S1G and H). Take together,
these results indicated that upregulated serum GCA in CRC patients was associated with poor prognosis.

GCA promotes tumor growth in a mouse model of CRC via inhibiting FXR activity. As BAs mainly function by
regulating FXR signaling in the intestine,17, 19 we then examined the effects of FXR with its agonist GW4064 on the
CRC cell lines MC38, CT26, HCT116 and SW620. As expected, activation of FXR by GW4064 significantly
promoted FXR activity (Fig. 1F and S2A). FXR was knocked out in MC38, CT26, HCT116 and SW620 cells with
the CRISPR/Cas9 system (Fig. S2B), and it was found that GW4064 failed to promote FXR activity in Fxr-deficient
mouse and human CRC cells (Fig. S2C). Next, we cultured MC38 cells with 0-200µM of GCA and observed that
GCA suppressed FXR activity in a dose dependent manner (Fig. S2D). Of note, 100nM of GCA robustly decreased
the activation of FXR without affecting the proliferation of MC38 cells, suggesting that this dosage of GCA is optimal
for in vitro experiments (Fig. S2D). Consistently, same tendency was observed in other CRC cells (Fig. 1F and S2A).
And GCA inhibited the transcriptional expression of the FXR downstream genes SHIP and IBABP in these CRC cell
lines confirmed by qPCR (Fig. 1G and S2E). Given that BAs regulate FXR function by altering the expression of FXR
or the ability binding to RXR, which is required for its downstream transcriptional activity23, we performed qPCR as
well as immunoprecipitation experiments, and found that GCA inhibited the interaction between FXR and RXR,
without affecting the mRNA level of FXR itself (Fig. S2F and G). In addition, we also observed that the FXR agonist
was sufficient to restore the expression of SHIP and IBABP in GCA treated MC38 and HCT116 cells (Fig. S2H),
suggesting a negative role of GCA in FXR signaling in CRC.

To further explore the roles of GCA in CRC, MC38, CT26, HCT116 and SW620 cells were incubated with GCA or
GW4064, and it was observed that the treatment had little effect on tumor cell proliferation in vitro (Fig. S2I).
Consistently, the proliferation rate was also comparable in both FXR-deleted (FXR-KO) and control CRC cells (Fig.
S2J). However, by using intestinal epithelial-specific Fxr-knockout (Fxr-ko, Fxr-/-) mice, it was found that Fxr was
successfully deleted in intestine tissues and AOM/DSS-induced tumors (Fig. S2K-L). Loss of FXR promoted the
development of CRC, as evidence by a decreased the colorectal length in the Fxr-ko mice, (Fig. 1H). Histological
analysis showed that tumors derived from Fxr-ko mice exhibited enlarged size and poor differentiation (Fig. 1I). We
also generated another orthotopic mice model of CRC by implanting Fxr-knockout and control MC38 cells into colon
mucosa. Consistently, mice with Fxr-knockout tumors showed an increased tumor growth and a worse overall survival
compared to that of control tumors (Fig. S3A), suggesting that FXR acted as a tumor suppressor in CRC tumorigenesis
in vivo. To further confirm this result, we inoculated MC38 cells into C57BL/6 mice and observed that 400 mg/kg of
GCA treatment (intragastric gavage; ig) robustly increased tumor burden without evident side effects as measured by
weight loss during the cause (Fig. S3B). We next measured the concentrations of BAs significantly elevated in the
serum of CRC patients in mice following GCA administration (400 mg/kg). While serum and tumoral GCA levels
were barely detectable in tumor-bearing mice without GCA treatment, GCA-treated mice exhibited measurable
accumulation, with serum levels reaching approximately 150 nM and tumoral concentrations around 82 nmol/g (Fig.
S3C-D). Notably, the median serum GCA concentrations in human Cohorts I and II were approximately 96.4 nM and
96.7 nM, respectively. These values are comparable to, or slightly lower than, those observed in GCA-treated mice,
supporting the physiological relevance of our experimental model.

Of note, GCA significantly increased the tumor growth in AOM/DSS-induced CRC models, as evidenced by an
increased tumor numbers and a short colon length in mice treated with GCA (Fig. S3E). However, GCA-treatment
could not further promote the tumorigenesis in Fxr-ko C57BL/6 mice, suggesting that FXR is the functional target of
GCA-induced tumorigenesis. While GCA significantly promoted tumor growth and decreased overall survival in
immunocompetent mice by subcutaneously inoculating MC38 or CT26 cells (Fig. S3F and G), no significant
difference was observed in terms of tumor size or survival rate between the GCA-treated and control groups when
MC38 or CT26 cells were inoculated in immunodeficient BALB/c nude mice (Fig. S3H and I). qRT-PCR showed that
GCA suppressed FXR signaling pathway in vivo, as shown by decreased expression of SHIP and IBABP in MC38 or
CT26 tumors derived from immune-competent or nude mice treated with GCA (Fig. S3J and K). To avoid the potential
effects of bacterial transformation of GCA in intestine, we intraperitoneal injected (i.p.ed) GCA twice a week in MC38
tumor-bearing mice and found an increased tumor growth in mice with GCA treatment (Fig. S3L). Collectively, our
data indicated that immune responses played an important role in the GCA-induced development of CRC.

Based on the ability of GCA to inhibit FXR-activity, the present study next investigated whether altering the function
of FXR could affect GCA-mediated tumor growth. Indeed, increased tumor size and decreased survival rate were
observed in immunocompetent mice, but not in BALB/c nude mice, when treating the animals with the FXR antagonist
T-βMCA (Fig. 1J and S4A-B), which mimics the behavior of tumor inoculated in immunocompetent mice or in
immunodeficient mice treated with GCA. Consistently, the suppressive role of FXR in cancer was confirmed when
immunocompetent, but not immunodeficient, BALB/c nude mice were treated with the FXR agonist GW4064 (Fig.
S4C-G). To explore whether impaired FXR signaling was critical for GCA-increased tumor growth in vivo, the mice
were treated with GCA in the absence or presence of the FXR-agonist GW4064 after inoculating MC38 or CT26 cells.
As expected, mice receiving GW4064 showed decreased tumor size and prolonged overall survival compared with
mice treated with GCA alone (Fig. 1K and S4H). Of note, GW4064 reverted the expression of FXR target genes I-
BABP and SHP that inhibited by GCA (S4I and J). Taken together, these data suggested that impairment of FXR-
mediated tumor suppression was critical for GCA-induced tumorigenesis, and immune responses were involved in
regulating the GCA-FXR axis mediated tumor development.

GCA treatment inhibits CD8+ T cell infiltration and antitumor response. To further investigate the effects of
tumor-infiltrated immune cells on GCA/FXR-mediated tumor progression, five independent cell clusters of CD45+
immune cells, including B cells, CD4+ and CD8+ T cells, macrophages and natural killer cells, were identified based
on scRNA-seq (Fig. 2A right). An increased total number of CD8+ T cells and macrophages was observed in tumors
treated with GW4064 compared with those without treatment (Fig. 2A left). The expression of markers of immune
subtypes was shown by using a panel of 21 markers (Fig. S5A). Next, MC38 tumors were isolated from mice receiving
GCA (i.g.) for 10 days, and the percentages of subpopulations in immune cells were analyzed by flow cytometry.
Consistently, CD8+ T cells and macrophages, but not CD4+ T cells or CD4+ Foxp3+ regulatory T cells (Treg), were
downregulated in tumors treated with GCA (Fig. 2B). To explore whether the suppressive effect of FXR on tumors
was dependent on CD8+ T cells or macrophages, CD8+ T cells or macrophages were depleted in mice by using an their
specific anti-CD8α antibody or clodronate liposomes (Fig. S5B), respectively, before inoculating the mice with MC38
cells with or without GCA or GW4064 treatment. Notably, GCA treatment did not further increase tumor growth in
CD8+ T cell-depleted mice compared with untreated controls (Fig. 2C). Moreover, it was also found that the FXR
agonist failed to inhibit CRC tumor progression in CD8+ T cell-depleted mice (Fig. 2D). However, tumor growth was
comparable in both macrophage-depleted and control mice regardless of GCA or GW4064 treatment (Fig. 2E and F).
In addition, MC38 or CT26 CRC cells were inoculated into Rag1-/- mice (which are deficient in T and B cells), and it
was observed that treatment with FXR antagonist or agonist had a limited effect on tumor growth in Rag1-/- mice (Fig.
S5 C and D). These data suggested that CD8+ T cells, but not macrophages, in the TME were involved in GCA/FXR-
mediated tumor growth.

We next explore the signaling pathway enriched in GCA-induced tumorigenesis, single-cell RNA sequencing analysis
revealed that genes upregulated in FXR signaling-mediated activated tumors were mainly associated with immune
responses, including type I/II IFN responses (Fig. S6A and B). We examined the expression of IFN-stimulated genes
(ISGs), including CXCL9, CXCL10, BST2, STAT1 and IFITM3, by qPCR. As expected, the mRNA levels of these
ISGs were significantly upregulated in MC38 and CT26 tumor tissues derived from immunocompetent mice treated
with GW4064 (Fig. S6C), whereas the expression of ISGs were decreased in tumors treated with GCA (Fig. S6D).
However, the alteration of the mRNA levels of ISGs was not observed in tumor tissues derived from immunodeficient
BALB/c nude mice when treating with GW4064 or GCA (Fig. S6E and F). Interestingly, MC38 and HCT116 cells
were also treated with GW4064 or GCA in culture, however, no significant increase in the transcriptional expression
of these ISGs was observed in GW4064- or GCA-treated CRC cells (Fig. S6G and H), suggesting a dependency on
IFN signaling associated immune responses in vivo.

As IFNγ is critical for tumor suppression mediated by CD8+ tumor-infiltrated T cells, we further used FACS analysis
to evaluate IFNγ-expressing CD8+ T cells. It was found that IFNγ-expressing CD8+ T cells were significantly
decreased in GCA-treated MC38 or CT26 tumors (Fig. 2G, S6I). However, an increased frequency of exhausted PD-
1+ TIM3+ CD8+ T cells was observed in tumors treated with GCA compared with controls (Fig. 2G and S6I). On the
contrary, tumors treated with FXR agonist GW4064 showed an enhanced population of CD8+ IFNγ+ T cells,
accompanied with attenuated exhausted CD8+ T cell infiltration (Fig. 2H and S6J). Thus, the present results suggested
that GCA-induced FXR impaired the antitumor activity of CD8+ T cells in the TME.

Increased expression of PD-L1 is required for GCA-mediated tumorigenesis. To investigate the underlying
molecular mechanisms of GCA-mediated suppression of T cell immune responses, data-independent acquisition MS-
based proteomics was performed in MC38 cells treated with or without GCA. Heatmap showed that PD-L1 was the
most significantly increased protein among the top 20 deferentially expressed proteins (FC≥2, p≤0.05) annotated to
both cytokine production and regulation of immune response pathways in GCA-treated MC38 cells (Fig.2I). Next,
CRC cells were treated with GCA or GW4064 in vitro, and the changes in the mRNA and protein levels of PD-L1
were evaluated. It was found that the levels of protein and cell surface expression of PD-L1, but not its mRNA levels,
were upregulated in tumor cells treated with GCA (Fig. 2J and S7A, C). By contrast, PD-L1 protein levels were
decreased in MC38 cells treated with the FXR agonist GW4064 compared with untreated cells (Fig. 2J, S7B and C),
which suggests that the GCA/FXR-mediated increase in PD-L1 was regulated in a post-transcriptional manner.
Functionally, tumor infiltrated CD8+ T cells were co-cultured with MC38 cells or CT26 cells that had been pre-
pretreated with GCA under anti-CD3 and anti-CD28-stimulating conditions, and it was found that FXR-inactivation
rendered CRC cells more resistant to CD8+ T cells in T cell-mediated tumor cell-killing assays (Fig. S7D). Furthermore,
tumor cell killing capacity was increased in wild-type (WT), but not in Cd274-KO, CRC cells pre-treated with a FXR
agonist (Fig. S7E). We further corroborated the results with in vivo subcutaneous tumor growth model and found that
knockout of Cd274 in MC38 cells or CT26 cells significantly reverted GCA-induced tumorigenesis (Fig. 2K and L).
qRT-PCR analysis revealed that CD274-knockout did not affect GCA-induced suppression of FXR downstream genes
I-BAPA and SHP (Fig. S7F and G). While low-dose anti-PD-L1 (10mg/kg) therapy have minimal effect on tumor
suppression in GCA-treated mice with subcutaneous tumors or in Fxr-/- mice of AOM/DSS-induced CRC model,
blockade of PD-L1/PD-1-signaling with a high-dose of anti-PD-L1 (100 mg/kg) effectively reversed GCA-induced
tumorigenesis (Fig. S7H-J), suggesting that increased PD-L1 expression in tumors is critical for GCA/FXR-mediated
dysfunction of CD8+ T cells during tumor growth.

GCA accelerates PD-L1 palmitoylation via DHHC9 in tumor cells. Since GCA treatment did not alter the
transcriptional levels of PD-L1 in CRC cells, we next suppressed the common degradation pathways that are involved
in the regulation of PD-L1. It was observed that GCA-mediated total and surface PD-L1 accumulation was reversed
by 2-bromopalmitate, a general palmitoylation inhibitor, not by the autophagy inhibitor 3-MA or the proteasome
inhibitor MG-132 in CRC cells (Fig. 3A and B). Similarly, increased expression of PD-L1 was observed in CRC cells
treated with palmostatin B, the inhibitor of acyl protein thioesterase 1, which promotes global palmitoylation, in a
dose-dependent manner (Fig. 3C). Moreover, GCA enhanced the palmitoylation modification of PD-L1 in CRC cells
according to the results of Click-iT labelling assay, indicating that GCA stabilized the PD-L1 protein via
palmitoylation (Fig. 3D).

To explore the key palmitoyltransferases for GCA-mediated PD-L1 accumulation, the transcriptional levels of
palmitoyltransferases were screened by RNA-sequencing analysis, and it was found that the expression levels of
DHHC9, DHHC1, DHHC1A2, DHHC18 and DHHC24 were on the top rank of differentially expressed genes in GCA-
treated cells compared with controls (Fig. 3E). Then we knocked down these candidates in MC38 and HCT116 CRC
cells by using specific siRNAs and found that GCA-induced accumulation of the total and cell surface PD-L1 protein
was significantly reduced in DHHC9-knockdown CRC cells but not in other palmitoyltransferases-knockdown CRC
cells (Fig. 3F and G). In addition, the transcriptional levels of DHHC9 were significantly upregulated in GCA-treated
CRC cells confirmed by qPCR (Fig. S8A). To further investigate the function of DHHC9 in regulating the
palmitoylation modification on PD-L1, DHHC9 was overexpressed in CRC cells. Increased protein, but not mRNA,
expression of PD-L1 was observed in DHHC9-ovexpressing CRC cells (Fig. 3H and S8B). Notably, the palmitoylation
modification on PD-L1 was significantly accumulated with the overexpression of DHHC9 (Fig. 3I). Next, we
evaluated whether DHHC9 was critical for GCA-mediated PD-L1 expression. As expected, a decreased protein
expression, but not transcriptional expression, of PD-L1 was observed in DHHC9-knockdown cells treated with GCA
(Fig. S8C and D). Functionally, it was found that the tumor cell killing capacity of tumor-derived CD8+ T cells was
significantly increased when co-cultured with DHHC9-knockdown CRC cells even without treatment with GCA (Fig.
3J). By contrast, overexpressing DHHC9 in MC38 or CT26 cells decreased the killing capacity of CD8+ T cells,
leading to increased tumor growth (Fig. 3K). Furthermore, this tumor promoting capacity could not be reversed by
treatment with the FXR agonist GW4064 (Fig. 3K). Collectively, these results indicated that DHHC9-mediated
palmitoylation modification was critical for the GCA/FXR-induced stabilization of PD-L1 and tumor growth.

The SOX14-DHHC9 axis regulates PD-L1 expression in CRC cells. To identify the TF(s) which is (are) responsible
for the GCA-mediated regulation of tumor PD-L1 expression, we analyzed all the differentially expressed
transcriptional factors with fold change (FC) ≥ 2 in CRC cells treated with GCA, and it was observed that SOX14 was
on the top list of the candidate TFs in terms of FC in expression (Fig. 4A). Loss-of-function screenings were then
performed using specific siRNAs target to top 5 candidate TFs. The results showed that knockdown of SOX14, but
not other candidates, could significantly diminish the expression of PD-L1 protein in CRC cells (Fig. 4B). Moreover,
the mRNA expression of FXR downstream gene IBABP was negatively associated with SOX14 expression in tumor
tissues derived from 80 patients with CRC (Fig. 4C upper). Subsequently, we explored whether FXR directly inhibited
SOX14 transcription. The promoter region of human SOX14 was screened for FXR-binding site by using the JASPAR
database, and ChIP assay was performed with an anti-FXR antibody under GCA or GW4064 treatment conditions. It
was observed that FXR directly bound to the promoter of SOX14 (site 2), as evidenced by the enrichment of the target
sequence (Fig. S9A). Moreover, GCA inhibited the DNA-binding capacity of FXR, whereas the FXR agonist GW4064
promoted its binding with DNA in CRC cells. (Fig. S9B). Finally, luciferase reporter constructs were generated to test
the transcriptional activity of WT and FXR-binding sequence deficiency mutated regions for FXR-binding sites (site
2). As expected, the luciferase activity was significantly increased in HCT116 and SW620 cells transfected with WT
region constructs upon GCA stimulation (Fig. S9C). By contrast, GW4064 significantly decreased the luciferase
activity of CRC cells with WT region constructs, but not of cells transfected with mut region constructs (Fig. S6C),
suggesting that FXR acts as a transcriptional suppressor for SOX14 expression. It was also found that knockdown of
SOX14 decreased PD-L1 expression by using shRNA targeting SOX14 in multiple CRC cell lines even though treated
with GCA (Fig. 4D left, E, and S9D-F). Of note, increased protein levels of PD-L1 were observed in SOX14-
overexpressing cells (Fig. 4F left and G, and S9E), suggesting that increased SOX14 expression may be involved in
GCA-induced PD-L1 expression. Moreover, we also investigated whether SOX14 was involved in regulating GCA-
mediated tumor promoting function by inoculating SOX14-knockdown cells into the subcutaneous tissue or colon
mucosa of mice treated with GCA. Then, we found that Sox14 deficiency inhibited GCA-induced tumor growth,
which was accompanied by an increased frequency of tumor-infiltrating total CD8+ T cells, as well as CD8+ IFNγ+ T
cell subset, but a decreased number of exhausted CD8+ T cells in both subcutaneous and orthotopic CRC model (Fig.
4H and I, S9G and H). The data indicated that SOX14 was a key TF in regulating GCA-mediated PD-L1 expression.

To identify whether SOX14 directly regulates DHHC9 expression, we firstly analyzed the correlation between the
mRNA expression of SOX14 and DHHC9 in 80 human CRC samples, and found that SOX14 was positively correlated
with DHHC9 mRNA expression (Fig. 4C down). It was also validated that GCA significantly increased the
transcription and protein expression of SOX14 and DHHC9, as well as PD-L1 protein expression, in murine MC38
and human HCT116 cells (Fig. 4D right and E). However, knockdown of SOX14 decreased the transcriptional
expression of DHHC9, as well as the protein levels of both DHHC9 and PD-L1 in CRC cells when treated with GCA
(Fig. 4D right and E). By contrast, increased DHHC9 and PD-L1 expressions were observed in CRC cells with SOX14
overexpression compared with control cells (Fig. 4F right and G). Most importantly, FXR-mediated DHHC9 and PD-
L1 inhibition could be reversed by overexpression of SOX14 in cells incubated with a FXR agonist (Fig. 4F right and
G), suggesting that SOX14 is a potent FXR downstream TF for inducing DHHC9 transcriptional expression. Next,
we analyzed the JASPAR database and identified two SOX14-binding sequences on the promoter region of human
DHHC9 by ChIP assay. Only the predicted site 1binding sequence was enriched in ChIP-enriched promoters (Fig. 4J
and K). Moreover, luciferase reporter constructs with SOX14-binding deficiency mutated regions for SOX14-binding
were generated to evaluate transcriptional activity, and found that luciferase activity was significantly increased in
SOX14-overexpressing MC38 and HCT116 cells transfected with DHHC9 WT region constructs, but not in cells
transfected with DHHC9mut region constructs (Fig. 4L). This indicated that SOX14 was critical for DHHC9
expression.

Next, we examined whether DHHC9 was involved in SOX14-mediated tumor progression by overexpressing DHHC9
in SOX14-knockdown CRC cells. We found that overexpression of DHHC9 increased the expression of PD-L1 in
CRC cells that exhibited downregulated PD-L1 expression by SOX14-knockdown (Fig. S9I). And overexpression of
DHHC9 blocked SOX14 deficiency-mediated tumor inhibition (Fig. S9I). In addition, overexpression of DHHC9 in
SOX14-deficient cells led to increased infiltration of total CD8+ T and CD8+ IFNγ+ T effector cells, but decreased
infiltration of exhausted PD-1+ TIM3+ CD8+ T cells (Fig. S9J). Taken together, these data revealed that DHHC9 was
the transcriptional and functional target of SOX14.

The GCA-mediated SOX14/DHHC9 axis correlates with decreased efficacy of immunotherapy in CRC patients.
To further understand the role of the GCA-regulated SOX14/DHHC9 axis in immunotherapy in patients with CRC,
LC-MS analysis was performed in the serum of 41 patients with MSI-H mCRC who received PD-1 blockade alone or
combination with chemotherapy. The majority of patients with mCRC (15/20) with high levels of GCA were predicted
non-responsive for immunotherapy, while patients with mCRC (19/21) with low concentrations of GCA showed
response to immunotherapy (Table S2). Magnetic resonance imaging and computed tomography showed that patient
27 had a relatively high level of serum GCA and tumor progression after PD-1 blockade treatment (Fig. 5A, left and
C), whereas patient 14, with a low concentration of serum GCA, showed tumor regression (Fig. 5A, right and C).
We also examined SOX14 and DHHC9 proteins by using IF in formalin-fixed paraffin-embedded tumor tissues from
patients with mCRC who received PD-1 blockade. The majority of mCRC patients with high concentrations of serum
GCA showed strong SOX14, DHHC9 and PD-L1 staining accompanied by low number of CD8+ T cells and often
insensitivity to anti-PD-1 therapy (Fig. 5B and C). On the contrary, patients with low levels of serum GCA exhibited
opposite results (Fig. 5B and C). Furthermore, Kaplan-Meier survival analysis revealed a significant correlation
between the high levels of GCA, SOX14, DHHC9 and PD-L1 and shorter progression-free survival (PFS) rates of
patients with mCRC who received anti-PD-1 therapy (Fig. 5D-G). Conversely, higher number of infiltrated intratumor
CD8+ T cells were accompanied by prolonged PFS rates in patients with CRC who received anti PD-1 therapy (Fig.
5H). Spearman correlation analysis showed that SOX14 protein expression was positively correlated with DHHC9
and PD-L1 protein expression in CRC tumor samples according to the IF staining scores (Fig. 5I and J). DHHC9
protein expression was also positively associated with PD-L1 protein (Fig.5K). We further confirmed our results that
the serum level of GCA was associated with the expression of DHHC9 or SOX14 in tumors of CRC patients in another
cohort (Fig.S10 A-B). Additionally, DHHC9 staining was correlated with SOX14 staining in these CRC tumors
(Fig.S10C). Altogether, these results suggested that GCA regulated SOX14/DHHC9/PD-L1 axis played significant
role on the efficacy of immunotherapy in mCRC, which may be useful as potential prognostic markers for PD-1
blockade in future.

Inhibition of GCA/FXR-induced SOX14 and DHHC9 expression sensitizes CRC to anti-PD-1 therapy. To
explore whether the SOX14-DHHC9-PD-L1 axis is critical for GCA/FXR-mediated immunosuppression, it was
hypothesized that Sox14-knockdown (Sox-KD) could ameliorate anti-PD-1 treatment in CRC under high levels of
GCA in the TME. Then, GCA-treated immunocompetent mice were engrafted with control or Sox14-KD CRC cells
and found that knockdown of Sox14 inhibited MC38 colon cancer outgrowth in the presence of anti-PD-1 therapy
(Fig. 6A). Moreover, increased infiltration of CD8+ T and CD8+ IFNγ+ T effector cells, while decreased exhausted
CD8+ T cells were observed in Sox14-KD cells compared with control cells in mice with and without anti-PD-1
antibody (Fig. 6B). Consistently, knockdown of Dhhc9 also significantly suppressed tumor growth in mice subjected
to anti-PD-1 therapy compared with mice with monotreatment. In addition, Dhhc9-deficiency enhanced the CD8+ T
cell anti-tumor function in the TME, as evidenced by the proportion of CD8+ T and IFNγ+ CD8+ T enriched in Dhhc9-
knockdown MC38 tumors with anti-PD-1 treatment (Fig. 6C and D). As GCA negatively regulated FXR activity, we
further investigated whether a FXR agonist could synergize CRC cells to anti-PD-1 therapy. As expected, combined
GW4064 and anti-PD-1 treatment robustly slowed the tumor growth, which as associated with a higher number of
CD8+ IFNγ+ T effector cell infiltration and lower percentage of exhausted T cells in tumors compared with those
receiving monotherapies, suggesting that the activation of FXR sufficiently promoted the antitumor effects of anti-
PD-1 therapy (Fig. S11A-D). In addition, anti-PD-1 therapy slightly decreased the AOM/DSS-mediated CRC
tumorigenesis in both C57ABL/6 and BALB/c mice (Fig. S11E-F). Of note, we observed that mice treated with
combined anti-PD-1 and GW4064 were most likely to benefit from therapy, as evidenced by an increased colon length
with a decreased tumor numbers and areas in mice receiving combined treatment compared to mono-treatment (Fig.
S11E and F). To strengthen the present conclusions, anti-PD-1-resistant MC38 (MC38R) colon cancer was generated
by three rounds of in vivo/in vitro selection. Anti-PD-1 antibody had a limited effect on the growth of MC38R cells
in both subcutaneous and orthotopic CRC models (Fig. 6E and F, S11G and H). However, GW4064 inhibited MC38R
tumor growth and sensitized MC38R cells to anti-PD-1 therapy, which was accompanied by a significantly increased
antitumor response of CD8+ T cells, as evidenced by increased infiltration of CD8+ T and CD8+ IFNγ+ T effector cells,
and decreased exhausted CD8+ T cells in tumors compared with GW4064 monotreatment (Fig. 6E and F, S11G and
H). The data indicated that combining FXR agonist with anti-PD-1 therapy enhanced the efficacy of anti-PD-1 in
resistant colon cancer.

Methods
Patient biopsies. A total of 80 paired CRC tissues, adjacent normal mucosa tissues and serum collected between
January 2018 and September 2018 from patients with CRC who were diagnosed at Fudan University Shanghai Cancer
Center (FUSCC) were used for measuring the concentrations of a series of BAs and for tissue immunofluorescence
staining (cohort Ⅰ). In addition, the serum of 20 normal healthy individuals was collected in October 2018. Furthermore,
41 patients with MSI-H or dMMR with recurrence or distant metastasis who received anti PD-1 immunotherapy
between February 2019 and September 2021 at FUSCC were enrolled in the present study (cohort Ⅱ). A cohort of 308
patients (Cohort III) with colorectal cancer (CRC) was enrolled between January 2008 and September 2009 at Fudan
University Shanghai Cancer Center. Their clinicopathological characteristics of the patients are summarized in
Supplementary Data 1-3. All patients from these 3 cohorts did not receive any treatment for cancer before surgery.
Human serum specimens were collected prior to tumor resection, while normal mucosa and paired cancer tissues, as
well as metastatic tissues, were collected immediately after surgical resection. Written informed consent was obtained
from each patient, and the study protocol both conformed to the ethical guidelines of the 1975 Declaration of Helsinki
and was approved by the Ethics Committee of FUSCC (approval no. 050432-4-2108).

Cell lines, plasmids, lentivirus production and transduction. The HCT116 and SW620 human colon cancer cell
lines, the CT26 mouse colon cancer cell line, and the 293T cell line were obtained from the American Type Culture
Collection, while the MC38 mouse colon cancer cell line was purchased from the Cell Bank of the Institute of
Biochemistry and Cell Biology of the Chinese Academy of Sciences. Cell lines were cultured at 37˚C in 5% CO2 in
DMEM or in RPMI1640 supplemented with 10% fetal calf serum, 100 U/ml penicillin and 100 µg/ml streptomycin.
Cells were tested monthly and found to be free of mycoplasm by PCR-based screening. Full-length SOX14 and
DHHC9 fused with Flag-tag were amplified via PCR from cDNA of HCT116 cells, and then recombined into the
pLVX plasmid (cat. no. 125839; Addgene, Inc.). The primers used are listed in Supplementary Data 4. Short hairpin
RNA (shRNA) sequences targeting SOX14 and DHHC9 were cloned into the pLKO.1 vector (cat. no. 10878; Addgene,
Inc.), and the primers used are listed in Supplementary Data 5. Single guide RNAs (sgRNAs) targeting FXR or CD274
were constructed into the lentiCRISPR v2 vector (cat. no. 52961; Addgene, Inc.). CRISPR/Cas9 targeting sequences
are listed in Supplementary Data 5. Lentivirus was produced by transiently transfecting 293T cells with
Lipofectamine® 3000 transfection reagent (cat. no. L3000075; Thermo Fisher Scientific, Inc.) according to the
manufacturer’s instructions. The viral supernatants were then incubated with 8 μg/ml Polybrene for 24 h, and the viral
supernatants were then exchanged for fresh media. Cells were incubated for 48 h before puromycin selection. For
small interfering RNA (siRNA) transfection, tumor cells were seeded into 6-well plates at ~1.5x105 cells per well and
incubated at 37˚C overnight. Specific siRNAs (5 nM; Thermo Fisher Scientific, Inc.) were transfected into cells and
incubated for 6 h. Next, the medium was replaced with complete DMEM for 48 h. The siRNA sequences are listed in
Supplementary Data 6. The anti-PD1-resistant MC38R tumor cells were developed as previously described.37 In brief,
6-week-old C57BL/6J mice were injected subcutaneously into the right flank with 1.0x106 MC38 cells (n=6). At 10
days post-injection, mice were treated twice weekly with 100 μg anti-PD-1α antibody (Bio X Cell) per mouse via
intraperitoneal (i.p.) injection for 1 week. Next, tumors were selected and transplanted into the right flank of 6-week-
old C57BL/6J mice. After 3 repeated cycles of tumor selection, nonresponsive tumors were digested into single tumor
cells, namely MC38R tumor cells.

Sample preparation and HPLC-MS/MS-based metabolomic approaches.
100 μl serum were spiked with 0.51 ml of ice-cold MeOH-ACN (1:1, v:v). The sample was vortexed and incubated
for 1h at - 20 °C, following by centrifuging at 14000 rcf at 4 °C for 15 min to precipitate proteins. The supernatant
was aspirated, evaporated using a vacuum concentrator (Thermo Scientific, Waltham, MA, USA). The extracts were
reconstituted in 100 μl of MeOH and deionized water (85:15, v:v), and centrifuged at at 15000 g at 4 °C for 15 min to
remove insoluble debris. The supernatant was collected at UPLC autosampler vials (Thermo Scientific, MA, USA)
and stored at - 80 °C prior to UPLC-MS analysis. Tumor samples were homogenized in 100% acetonitrile and were
centrifuged twice at 15,000g for 30 minutes at 4°C for removal of precipitated proteins and other particulates to remove
precipitated proteins and particulates. The supernatant was then diluted with 0.1% formic acid. The quality control
sample was pooled by mixing 5 μL of extracted solution from each sample.

Liquid chromatographic separation and mass spectrometric detection were conducted using the Thermo Scientific
TSQ Quantum Ultra LC-MS/MS system (Thermo Fisher, Palo Alto, CA). Chromatographic separation was achieved
on a Poroshell SB-C18 analytical column (particle size, 1.7 μm; 50 mm (length) × 2.1 mm (i.d.)) equipped with a BEH
C18 VanGuard pre-column (5 × 2.1 mm, i.d.; 1.7 μm). The mobile phase consisted of aqueous buffer containing 1 mM
ammonium formate and formic acid (pH 4.39) (A) and acetonitrile/isopropanol (1:1 v/v) (B), with a total flow rate of
0.4 ml/min. The gradient profile for the LC pumps was as follows: 20–30% B (0-3 min), 30-40% B (3-4 min), 50-70%
B (4-5 min), 70-90% B (5-5.2 min), continuing at 90% B up to 6 min. The injection volume for all samples was 2 μl.
The column temperature was set to 55 °C, and the sample tray temperature was maintained at 8 °C. For mass
spectrometric detection, the electrospray ionization (ESI) source was operated in negative ion mode to produce
MS/MS spectra (Thermo Fisher). The parameters were as follows: spray voltage 2 kV, cone voltage 30 V, source
temperature 120 °C, desolvation temperature 500 °C, cone gas flow 50 L/h, desolations gas flow 900 L/h.

For preparation of standard stock, 33 bile acid were dissolved to 1 mg/mL by appropriate amount of methanol as
standard stock solutions and then further diluted to obtain standard solutions containing 0.05, 0.5, 5, and 50 mg/mL
of each bile acid. The supernatant was collected and 70 μl was injected into the LC–MS/MS system for analysis.
Cholic acid (CA), chenodeoxycholic acid (CDCA), sodium glycochenodeoxycholate (GCDCA), sodium
taurochenodeoxycholate (TCDCA), glycocholic acid (GCA), taurolithocholic acid (TLCA), sodium
taurodeoxycholate hydrate (TDCA), and taurocholic acid sodium salt hydrate (TCA) was purchased from Sigma-
Aldrich (Saint Louis, MO). Ursodeoxycholic acid (UDCA), deoxycholic acid (DCA). Lithocholic acid (LCA) and
glycoursodeoxycholic acid (GUDCA) were procured from Cayman Chemical Company (Ann Arbor, MI, USA).
Glycodeoxycholic acid (GDCA) and glycolithocholic acid (GLCA) were acquired from Toronto Research Chemicals
(TRC, Canada).

Data‐independent acquisition mass spectrometry (MS)‐based proteomics. MC38 cells were treated with or
without GCA for 24 h and processed by Data Independent Acquisition6 individually to assess the proteome. In brief,
for sample preparation, cells were lysed in lysis buffer (1% SDS and 8 M urea) and digested with iST Sample
Preparation kit (PreOmics) following the manufacturer’s instructions. Peptides were eluted with elution buffer (2 x
100 µl) and then lyophilized by SpeedVac. Protein samples were reconstituted in 0.1% FA and subjected to UltiMate
3000 liquid chromatography (LC) (Thermo Fisher Scientific, Inc.). In total, 200 ng peptide was separated by an
analytical column with a 60 min gradient starting at 4% buffer B (80% ACN with 0.1% FA), followed by a stepwise
increase to 28% in 25 min, 44% in 10 min, 90% in 10 min, hold for 7 min, and then equilibration at 4% for 8 min. The
column flow rate was maintained at 500 nl/min with a column temperature of 50˚C. DIA data were acquired in the
diaPASEF mode. Raw data of DIA were analyzed by Spectronaut 17 (Biognosys AG) with default settings. The
normalization strategy was set to local normalization. Peptides which passed the 1% Q-value cut-off were used to
calculate the major group quantities with the MaxLFQ method. Differentially expressed proteins were selected based
on P<0.05, fold-change (FC)>1.5 or FC<1/1.5.

Dual Luciferase Reporter Assay. For measurement of FXR activity, cells were seeded into 24-well plates at ~1.5x104
cells per well and transfected with the FXR luciferase reporter plasmid FXRE-Luc (200 ng; cat. no. 11764ES03;
Shanghai Yeasen Biotechnology Co., Ltd.) and 20 ng Renilla pRL-SV40P plasmid (cat. no. 27163; Addgene, Inc.) per
well with Lipofectamine® 3000 according to the manufacturer’s instructions. Next, cells were treated with GCA
(100nM, cat. no. G2878; Sigma‐Aldrich; Merck KGaA) or GW4064 (5μM, cat. no. G5172; Sigma‐Aldrich; Merck
KGaA) for 24 h, and the relative luciferase units (RLUs) were measured using the Dual-Glo Luciferase Assay System
(Promega Corporation) according to the manufacturer’s instructions. For monitoring SOX9 or DHHC9 expression,
cells were seeded and transfected with 200 ng pGL3-SOX14, pGL3-SOX14-FXR mutant 15, pGL3-DHHC9 or pGL3-
DHHC9-SOX14 mut vector, along with 20 ng Renilla pRL-SV40P plasmid per well with Lipofectamine® 2000. After
24 h, the RLUs in cells were measured using the Dual-Glo Luciferase Assay System. The firefly RLUs were
normalized by the RLUs from the Renilla-containing vector.

Mice. Fxr floxed mice were purchased from Cyagen Biosciences, Inc. (cat. no. S-CKO-04890). Villin-Cre (#004586)
transgenic mice were purchased from the Jackson Laboratory (Bar Harbor, ME, USA) to create conditional knockout
mice and silenced the expression of Fxr in intestinal epithelial cells. Briefly, two synthesized sgRNAs targeting introns
3 and 4, Cas9 mRNA and LoxP-containing oligonucleotide flanking with 50-bp homology arms were injected into
mouse zygotes and then transferred into pseudo-pregnant mice. Fxr floxed mice were identified by genotyping and
sequencing. Fxr floxed mice were then crossed with villin-Cre transgenic mice to obtain intestinal epithelial-specific
Fxr knockout mouse models. The mice were randomly assigned into experimental groups. For primary mouse models,
animals were chosen based on correct genotypes and were co-allocated in the same cages and used for the studies. All
mice used in the study were gender- and age-matched. Investigators were blinded to the treatments during the
experiments. All mice were housed in the specific-pathogen free animal facility of FUSCC. Animals were observed
for general health and signs of distress (reduced weight, ruffled fur, or evidence of tumor ulceration/bleeding). Mice
were euthanized when body weight loss exceeded 20% or when tumor volume exceeded 1,500 mm³. Euthanasia was
performed in accordance with institutional and guidelines by CO₂ inhalation followed by cervical dislocation to ensure
death. The maximal tumor burden permitted by our ethics committee is 1,500 mm³, and this limit was not exceeded
in any experiment. All animal procedures were approved by the Animal care and Use Committee of FUSCC.
For tumor engraftment, 6-week-old C57BL/6J or BALB/c mice were injected subcutaneously into the right flank with
1.0x106 MC38 or CT26 cells, respectively. BALB/c nude mice were also used to establish a subcutaneous CRC model
by using MC38 or CT26 cells. The tumor volumes were calculated by using the formula ‘length x width x width/2’ at
the indicated days. Body weight was recorded at the time of tumor measurement. For survival analysis, mice were
considered moribund and euthanized when tumor volume reached approximately 1000 mm³ or when severe signs of
distress were observed. For endoscopy-guided orthotopic mouse model, wild-type 10-12 weeks old C57BL/6 mice
were examined by endoscopy Coloview® system (Storz, Tuttlingen, Germany) with a zero-degree optic (diameter 1.9
mm) to ensure the colonic mucosa was healthy prior to implantation after anesthesia. For tumor cell implantation, the
colon was first washed with PBS at 37 °C and 0.5×106 MC38 cells) diluted in 50 μL of PBS were injected very slowly
towards the lumen of lower mid and distal colon ~30 mm from the anal verge to induce tumor growth by using
endoscopic injection. The tumor volume was endoscopically monitored weekly by endoscopic score. For the
AOM/DSS-induced colitis-associated cancer model, 8 to 10-week-old male mice were injected i.p. with 10 mg/kg
AOM (cat. no. A5486; Sigma‐Aldrich; Merck KGaA). After 5 days, 2% DSS (cat. no. D8906; Sigma‐Aldrich; Merck
KGaA) was added to the drinking water for 5 days, followed by regular drinking water for 2 weeks. The mice were
sacrificed after 3 repeated cycles of DSS. For the macrophage-depletion experiment, the mice were pretreated with
clodronate liposome (150 μl; Max Scientific) 3 days before inoculating with tumor cells, and then the indicated mice
were administered with clodronate and control liposomes, with or without GCA [400 mµg/kg, intragastric gavage (ig)
or GW4064 (50 mg/kg, i.p.)] twice per week during the course of the experiments. For the CD8-depletion experiment,
mice were treated with an anti-CD8 antibody (200 µg per injection; clone 2.43; Bio X Cell) twice weekly during the
course of the experiments. For anti-PD-1 antibody treatment, mice were treated with 100 μg anti-PD-1α antibody (Bio
X Cell) per mouse twice weekly or the corresponding IgG control via i.p. injection for the indicated days. For anti-
PD-L1 antibody treatment, mice were treated with 10 mg/kg or 100mg/kg anti-PD-L1 antibody (Bio X Cell) per mouse
twice weekly or the corresponding IgG control via i.p. injection for the indicated days. For GCA (400 mg/kg,
intragastric gavage), GW4064 (50 mg/kg, i.p.) or T-βMCA (400 mg/kg, i.p.) treatment, mice were treated with
GW4064 or T-βMCA twice per week after 6 days of being inoculated with the indicated CRC cells.

mRNA extraction and reverse transcription-quantitative PCR (RT-qPCR). Total RNA was extracted from cells
or tumors by using TRizol® reagent (cat. no. 15596026CN; Thermo Fisher Scientific, Inc.) according to the
manufacturer’s instructions. Next, the extracted RNA was reversely transcribed to cDNA with PrimeScript® RT
Reagent Kit (cat. no. RR037B; Takara Bio, Inc.). RT-qPCR was conducted with a fast two-step amplification program
using FastStart Universal SYBR Green Master Mix (cat. no. 04913850001; Roche Diagnostics GmbH). Data were
normalized to GAPDH. The primers used are listed in Supplementary Data 7.

Chromatin immunoprecipitation (ChIP) assay. HCT116- and SW620-expressing SOX14-Flag CRC cells, or CRC
cells treated with GCA or GW4064 for 24 h, were subjected to ChIP assay with SimpleChIP® Enzymatic Chromatin
IP Kit (cat. no. 9003S; Cell Signaling Technology, Inc.) following the manufacturer’s instructions. Mouse monoclonal
antibody specific for FXR (cat. no. 72105; Cell Signaling Technology, Inc.) and rabbit monoclonal antibody specific
for SOX14 (cat. no. PA1-28074; Thermo Fisher Scientific, Inc.) were used for ChIP assay. SYBR Green RT-qPCR
was performed by using the following primers: FXR binding site 1 forward: 5’-TTTGTATTTCAAGCCCTAA-3’ and
reverse: 5’-GACTTCGGTTCCACATTGT-3’; FXR binding site 2 forward: 5’-CAGTCTAGAGCTAGCCTCT-3’ and
reverse: 5’-CGCACCTGCCAACACGCCGG-3’; SOX14 binding site 1 forward: 5’-
AGGGAGATGGGTGGAGGAGT-3’ and reverse 5’-CGGCCGCCCCTATC-3’; and SOX14 binding site 2 forward:
5’-GGAGGCGCCGAGGCC-3’ and reverse: 5’-CCCACCACTGGCCAAAT-3’.

Immunoblotting. For immunoblotting, samples harvested form cells or tumors were lysed with RIPA buffer (cat. no.
89901; Thermo Fisher Scientific, Inc.) supplemented with a protease inhibitor (cat. no.
05892970001; Roche Diagnostics GmbH) and a phosphatase inhibitor cocktail (cat. no. 04906845001;
Roche Diagnostics GmbH) for 1 h. The lysates were centrifuged at 12,000 rpm for 15 min at 4˚C. The supernatants
were collected, and equal quantities of cell lysates (100 μg) were mixed with 5X SDS-PAGE loading dye. Next, the
samples were separated using 10% SDS-PAGE and transferred onto nitrocellulose membranes (MilliporeSigma). The
membranes were then incubated with the indicated primary and secondary antibodies and visualized using the
SuperSignal West Dura Extended Duration Substrate (cat. no. 34076; Thermo Fisher Scientific, Inc.). The antibodies
employed are listed in Supplementary Data 8.

Immunofluorescence microscopy and multiplex immunofluorescence staining. For immunofluorescence
microscopy assay, cells were fixed with 4% paraformaldehyde for 15 min, followed by permeabilization with 0.5%
Triton X-100 for 15 min. Samples were blocked with 1% goat serum for 30 min, and then incubated with the indicated
primary antibodies at 4˚C for 12 h before being incubated at room temperature with secondary antibodies conjugated
to Alexa Fluor 488/594. DAPI (cat. no. ab104139; Abcam) was used to stain the nuclei for 30 min before subjecting
the samples to Zeiss Axiovert-200 fluorescence microscope (Zeiss AG).

For multiplex staining, samples were treated following the Opal protocol staining method. The reagents used were as
follows: Anti-SOX14 (cat. no. #ab214041; 1:500; Abcam), anti-DHHC9, anti-PD-L1 and anti-CD8 (cat. no. 98941;
Cell Signaling Technology, Inc.; RRID: AB_2756376, 1:500) antibodies were visualized by using fluorescein-cyanine
(Cy) 7 (1:50), fluorescein-Cy5 (1:50) and fluorescein-Cy3 (1:50). In addition, DAPI (1:2,000) was used for nuclei
staining. All sections were cover slipped using VECTASHIELD Hardset Antifade Mounting Medium (cat. no. #H-
1400; Vector Laboratories). The slides were scanned, and the mean fluorescence intensity of the indicated markers
was analyzed with a Vectra slide scanner (PerkinElmer, Inc.) under fluorescence conditions.

Co-culture assay. MC38 or CT26 cells were injected (1.0x106 cells) subcutaneously into the right flank of C57BL/6
or BALB/c mice for 2 weeks. Next, the CD8+ T cells in MC38 or CT26 tumors were isolated by FACs. The number
of indicated MC38 cells or CT26 cells was counted after 3 days of co-culture with CD8+ T cells (1.0x104 cells) in the
presence of anti-CD3 (5 μg/ml) and anti-CD28 (5 μg/ml) antibody.

Tumor digestion, cell isolation and flow cytometry analysis. Tumors derived from the indicated mice were sheared
and digested by using digestion buffer [RPMI medium supplemented with 5% FBS, intravenous collagenase I (0.5
mg/mL, cat. no. C1-22; Sigma‐Aldrich; Merck KGaA) and DNase (1 µg/ml; cat. no. D5025; Sigma‐Aldrich; Merck
KGaA) for 30 min at 37˚C. Next, the mixture was filtered, and red blood cells (RBCs) were lysed using RBC lysis
buffer (cat. no. 00-4300-54; Thermo Fisher Scientific, Inc.). The precipitates were washed with buffer II (PBS with
2% FBS) and blocked with anti-CD16/32 antibody for 30 min. The single-cell suspensions were washed and incubated
with the indicated antibodies before being subjected to LSRII (BPD Biosciences) for analysis. Data were analyzed using
FlowJo. The antibodies used are listed in Table S8. Cell populations were identified based on the following expression
markers: CD4 T cells: CD45+/CD4+; CD8 T cells: CD45+/ CD8+; MDSC cells: CD45+/CD11b+/Gr-1+; and
macrophages: CD45+/CD11b+/F4/80+. For intracellular staining, cells were stimulated with phorbol 12-myristate 13-
acetate (20 ng/ml; cat. no. p8139; Sigma‐Aldrich; Merck KGaA), ionomycin (1 μg/ml; cat. no. 13909; Sigma‐Aldrich;
Merck KGaA) and brefeldin A (5 ng/ml; cat. no. B5936; Sigma‐Aldrich; Merck KGaA) for 4 h and then stained
according to the intracellular cytokine staining procedure. Gate strategy (Fig.S12) and representative image of tumors
(Fig.S13) were shown in supplementary Figures.

Single cell sorting, library preparation and sequencing and data preprocessing. Tumor single-cell suspensions
were prepared and filtered over 40-µm cell strainers. Next, cell concentration and viability were evaluated by Trypan
Blue staining. The isolated cells were subjected to single cell RNA analysis. In brief, cells were loaded to prepare
single-cell gel beads in emulsions (GEMs) by using Chromium Single Cell Controller Instrument (10x Genomics).
GEMs were encapsulated using the Single Cell 3’ Library & Cell Bead Kit (10x Genomics). Completed libraries were
sequenced by Illumina NovaSeq 6000 using high-output 75-cycle kits with 150-bp paired-end reads. The data files
were analyzed with the R package SingleR. Gene transcript counts per cell and was determined by the unique
molecular identifier (UMI; R package Seurat, version 3.1.1). After removing low-quality cells and likely multiplet
captures, Seurat (normalizeData function) was used to normalize the expression values for each cell by the total
expression and log-transformed the results. FindVariableGenes function in Seurat was performed to identify the highly
variable genes. Then, these genes were subjected to RunPCA function and FindClusters function of Seurat to calculate
the significant principal components. The clusters were visualized in a two-dimensional t-SNE algorithm using the
RunTSNE function in Seurat and the marker genes of each cluster were identified by The FindAllMarkers function in
Seurat. Additionally, differentially expressed genes (DEGs, P< 0.05 and |log2 (fold-change)| >0.58) was filtered by
the FindMarkers function. Then, SingleR, was used for unbiased cell type recognition of scRNA-seq, with the
reference transcriptomic datasets ‘Human Primary Cell Atlas’ to infer the origin of each single cell independently and
to identify cell types.38 Gene Ontology enrichment pathway enrichment analyses of DEGs were carried out using the
hypergeometric distribution of R software. For immune cells, CD45+ cells were gated, and five major clusters of
immune cells were identified, including CD4+ T cells, CD8+ T cells, macrophages, B cells, neutrophils and NK cells
by using markers for inferring immune cell populations in time-of-flight (CyTOF) analysis as previous study39.
Sequencing and bioinformatics analysis were performed by Shanghai OE Biotech Co., Ltd.

PD-L1 palmitoylation. Tumor cells were co-cultured with complete medium containing 100 μM Click-iT Palmitic
Acid-Azide (cat. no. C10265; Thermo Fisher Scientific, Inc.) at 37˚C and 5% CO2 for 6 h. Next, the cells were
harvested and lysed with lysis buffer (1% SDS in 50 mM Tris-HCl, pH 8.0) supplemented with a protease inhibitor
and phosphatase inhibitor cocktail on ice for 0.5 h. After sonication, the cell lysate was centrifuged at 12,000 x g at
4˚C for 10 min. The supernatants of cell lysates were collected and subject to Click-iT assay by using the Click-iT
Protein Reaction Buffer Kit (cat. no. C10276; Thermo Fisher Scientific, Inc.) following the manufacturer’s
instructions. The biotin-alkyne (cat. no. 901995; Sigma‐Aldrich; Merck KGaA) connected palmitic-protein complex
was followed by streptavidin (cat. no. 3419; Cell Signaling Technology, Inc.) pull-down and immunoblot assay for
PD-L1.

Statistical analysis. Statistical analyses were performed by using GraphPad Prism (GraphPad Software; Dotmatics).
No statistical method was used to predetermine sample size. No data was excluded from the analyses. For data showing
normal distribution, the statistically significant differences between 2 groups of samples were estimated by applying
an unpaired two-tailed Student’s t-tests. One-way ANOVA and Dunnett’s post hoc test were used for comparison
between ≥3 groups. The log-rank test was also applied to assess statistical significance in survival data. Statistical
significance (p-values) was defined as not significant (ns): p > 0.05; *: p < 0.05; **: p < 0.01; ***: p < 0.001. All of
the experiment was independently performed 3 times, each yielding similar results; data from one representative
independent experiment is presented as the mean ± SD.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Colorectal cancer (CRC) is a highly prevalent tumor type that is generally refractory to immunotherapy. Thus, elucidating mechanisms of CRC resistance to immunotherapy is of high importance. In this study, Zhao et al make use of a comprehensive range of clinical data, in vivo models, and in vitro cell biology assays to identify bile acids as potential regulators of CRC sensitivity to T cell attack. Mechanistically, this is proposed to occur through the bile acid nuclear receptor Fxr, which regulates expression of SOX14 and the palmitoyltransferase DHHC9 to control palmitoylation and stability of the immune checkpoint ligand PD-L1. Overall, the experiments appear to have been generally well-executed (although the methodological details are not always clear, nor is it clear how often experiments were reproduced). The connection between bile-acid/Fxr-dependent regulation of tumor PD-L1 expression is not well understood in the context of CRC, but a similar set of observations were recently published for hepatocellular carcinoma (Gong et al, Norcholic Acid Promotes Tumor Progression and Immune Escape by Regulating Farnesoid X Receptor in Hepatocellular Carcinoma, Front Oncol, 2021).\nOverall, the data are interesting and shed light on a mechanism of PD-L1 regulation that is not well understood. However, I have several concerns that should be addressed prior to publication.\nMajor concerns:\n1. Fig. 1b/c: GCA concentrations are noted on the y-axis as ‘relative concentration’, but what are they relative to? The median differences between early and late-stage disease (panel B) or localized vs metastatic disease (panel C) may be statistically significant but are less than 0.1 in log2 space, which equates to a <7% difference. Are these difference considered biologically or clinically meaningful? Is it possible to estimate bile acid concentrations in tumor tissue?\n2. Fig. 1d/e and Fig. S1a/b: elevated circulating bile acid concentrations are typically associated with hepatic dysfuncton(resulting in impaired clearance of bile acids from portal blood). This raises the question of whether the increased GCA concentrations observed in patients with metastatic CRC are due to liver metastases impairing hepatic functon(as opposed to a causative role of GCA in promoting CRC progression, as implied in this manuscript). It would be interesting/informative to compare BA concentrations in patients with liver vs non-liver metastases, and include liver metastasis specifically as a covariate in survival analysis (as distinct from other metastatic sites).\n3. Fig. 1f/h/i (DSS-AOM data): the DSS-AOM model data are intriguing, but somewhat challenging to interpret. The DSS-AOM regimen models colitis-associated CRC, which follows a distinct process of pathogenesis compared to the much more common sporadic CRCs (which are the principal focus of this manuscript). Most importantly, tumorigenesis in this system relies on repeated rounds of DSS-driven colitis, and tumor burden is associated with the severity of DSS-driven tissue damage. Because the authors appear to have used mice with constitutive loss of Fxr in intestinal epithelial cells (Fxr.flox crossed with Villin-Cre), it is not possible based on these data to determine whether Fxr function is associated with alterations in tumorigenesis, colitis, or both. One potential alternative is to use mice with inducible Villin-controlled Cre (Vill.Cre.ERT2) so that Fxr can be deleted in colon epithelial cells after the final round of DSS (to exclude effects on colitis). However, the challenge of interpreting colitis-associated CRC data in the context of a paper that's focused on sporadic CRC remains. If the authors' intent is simply to generate data using an orthotopic model of CRC, alternative systems could include direct implantation of CRC cell lines into colon mucosa, or delivery of CRC cells to the liver via hydrodynamic tail vein injection.\n4. Treatment with GCA apparently reduces activity of FXRE significantly in the luciferase reporter system (cell line assays). What is the source of the basal reporter signal? Is this an overexpression artifact, or are the cells exposed to bile acids in culture medium (possibly via serum)?\n5. Figure 2I: The authors report that treatment of MC38 cells with GCA significantly induced PDL1 expression at the protein level, but not at the mRNA level. PDL1 is well-known to be an interferon-inducible gene, and it is noteworthy that several other proteins identified by the authors as induced by GCA are also known to be interferon-inducible, including Ifi204, B2m, Mndal, and H2-M3. Is this merely a coincidence, or is it possible that GCA-treatment is inducing an autocrine type I IFN response? Have the authors performed an unbiased transcriptional analysis (e.g. bulk RNAseq) to determine if such an interferon-like response is indeed occurring?\n6. Fig. S4H/I: the apparent dependency of Fxr-driven tumor growth effects on tumor PDL1 expression is interesting and important to the overall message of the paper. To exclude the possibility that this phenotype is driven by clone-to-clone differences, can this observation be further supported by blocking PDL1 in tumors from wild type cells (e.g. with anti-PD-L1 blocking antibody) in the presence or absence of Fxr ligands?\n7. Figure 5: the authors propose that the Fxr-regulated SOX14/DHH-C9/PD-L1 axis is involved in resistance of MSI-H/dMMR CRC patients to anti-PD-1 therapy in the clinic. This conclusion seems potentially odd—if we assume that tumor-expressed PD-L1 acts by engaging PD-1 on T cells, and if the anti-PD-1 antibody (the specific identity of the treatment regimen should be stated in methods) was dosed adequately to fully inhibit PD-1, then why would increased expression of PD-L1 on tumor cells have any bearing on anti-PD-1 response? Is there any reason to believe that these patients did NOT receive a dose of anti-PD-1 sufficient for full target coverage?\n8. Figure 6 (and various associated statements in text): along a similar line, the authors propose that inhibition of SOX14 or DHHC9 expression in tumors causes an improved anti-tumor immune response and improved tumor control, presumably via reduced PD-L1 expression. While this makes sense under untreated conditions, they argue that this also applies during treatment with anti-PD-1. Similar to the clinical setting, unless PD-1 blockade is substantially incomplete, it is difficult to understand why alterations in tumor PD-L1 expression would enhance sensitivity to PD-1 blockade. The data instead raise the possibility that tumor-intrinsic SOX14/DHHC9 deficiency can act at least partially in a PD-L1-independent fashion to increase tumor sensitivity to immune surveillance and anti-PD1 treatment.\n9. The MC38 and CT26 models used extensively in this manuscript best represent the inflamed and potentially immunotherapy-responsive MSI/dMMR subset of CRC. Have the authors explored whether manipulation of the Fxr pathway impacts immune responses to 'colder' tumor models that are more representative of sporadic MSS/pMMR CRCs (which constitute the vast majority of CRC and the bulk of unmet clinical need). For example, this could include engineered colon organoids (e.g. Taraborelli et al, Nat Comm, 2023).\nMinor concerns:\n1. Extensive grammatical and spelling errors throughout manuscript. English-language editing recommended.\n2. Heatmap scales are generally missing units/labels throughout the figures.\n3. Page 8, lines 162-165: The statement here is confusing and should be clarified. Should it actually say, “FXR-mediated tumor suppression…”?", "reviewer_2": "Zhao et al. demonstrated that glycocholic acid (GCA) enhances tumor cell PD-L1 expression, thereby suppressing CD8+ T cell-mediated antitumor responses in the tumor microenvironment (TME) and promoting colorectal cancer tumor growth. This effect is mediated through the targeting of the FXR/SOX14/DHHC9 axis. The study also suggests a testable hypothesis: inhibiting GCA/FXR signaling could augment the effectiveness of anti-PD-L1 therapy. While this study presents a novel and intriguing perspective with potential implications for immunotherapy in colorectal cancer (CRC) patients, several major concerns need to be addressed, and the conclusion lacks robust evidence.\nSpecific comments are the following:\n1. The authors mention the measurement of 34 bile acids (BAs) in serum but fail to provide a detailed description of the method and BA profiling data. Additionally, the criteria for defining low and high GCA levels in the recruited population are not clearly explained. This GCA-based subgrouping method lacks validation in another cohort.\n2. The authors assert that GCA acts as an FXR antagonist based on the Luciferase reporter assay. However, intra-gastric gavage feeding in animal experiments with GCA or TβMCA treatment raises concerns about the potential impact of bacterial transformation of GCA in the gastrointestinal tract. Alternative administration methods, such as intraperitoneal injection, should be considered.\n3. The logical flow of the narrative appears disrupted with the introduction of Result 2 [GCA inhibits IFN signaling in vivo].\n4. The statement \"Since GCA-induced PD-L1 expression was dependent on post-transcriptional modification\" (Line 243) lacks a clear reference or supporting data.\n5. Inconsistencies between figure arrangement and subtitles of results and figure legends are noted. For instance, Figure 1F-K implies that GCA-increased CRC tumorigenesis is FXR-dependent, but this is not accurately reflected in the subtitle of Result 1 or Figure 1. Additionally, Figure 2, described as \"GCA impairs the antitumor effect of CD8 T cell by increasing tumor intrinsic PD-L1 expression,\" lacks validation data (Cd274-KO data should be rearranged).\n6. Line 377 mentions investigating whether inhibition of GCA/FXR could sensitize CRC to anti-PD-L1 therapy, but the subjects were treated with anti-PD1 therapy. Clarification is needed.\n7. Representative tumor graphs for all in vivo animal experiments should be provided by the authors.\n8. Lines 467-468 discuss the discussion of an FXR agonist with the antibiotic metronidazole enhancing GCA-induced resistant tumors to ICB therapy without presenting relevant data about the antibiotics.\n9. Detailed recruitment criteria information for the two cohorts, including healthy subjects, should be provided.\n10. The abstract mentions a \"GCA diet\" (Line 27), but there is no related information about it in the animal method, which relies on intragastric gavage of GCA.\n11. The rationale behind the test doses for BA-related agents in vivo and in vitro should be illustrated, and the method needs supplementation", "reviewer_3": "Zhao et al. demonstrated that GCA accumulates in the serum of patients with CRC. This accumulation leads to a reduced activity of the bile acid receptor FXR, resulting in a poor antitumor CD8+ T cell response. Mechanistically, GCA upregulates tumor PD-L1 expression through the FXR-SOX14-DHHC9 axis-mediated palmitoylation of PD-L1. While the study includes substantial experiments, it lacks novelty in terms of the role of GCA and its receptor in CRC and the palmitoylation of PD-L1 by DHHC9, as these have been reported in previous studies.\nMajor concerns:\n1.The prediagnostic plasma GCA levels and colon cancer risk have already been reported (PMID: 31435679), as well as the mechanism regarding the role of DHHC9 on the expression of PD-L1 (PMID: 30514902). In addition, the bile acid receptor FXR agonist GW4064 has already been reported to enhance anti-PD-L1 immunotherapy in colorectal cancer (PMID: 37261088). Thus, the key points of this study are already known with less novelty.\n2.The cluster identification by scRNA-seq in Figure 2 is not reasonable. The resolution seems very low and rough because no other myeloid clusters, such as dendritic cells, MDSCs, and neutrophils, or T-cell subsets (cytotoxic or exhausted), or tumor cells were found in the scRNA-seq. The cell population in scRNA-seq seems exactly the same as that found by flow cytometry. Especially, the macrophage population is the largest among tumor-infiltrating immune cells and is heterogeneous. What markers were used to identify the macrophages? No gene expression data were shown for each cluster.\n3.Other independent cohorts or public databases should be analyzed to verify the clinical relevance between GCA and patient outcome. Are SOX14, GCA, and DHHC9 expression associated with patient survival in other studies? They should provide more evidence to validate their results.\n4.Data quality is unsatisfactory. For example, all flow data of PD-L1 expression lack negative IgG control, such as Figure 2k, 2l, 3b, and 3g. The flow gating of exhausted T cells and interferon-gamma-producing T cells should be shown. Additionally, according to their method, why were the same colors used together (Tim-3-BV605 and PD1-BV605)?\n5.In figures 4 and 6, all the in vivo mouse models are performed by subcutaneous injection. The tumor microenvironment differs significantly in different organs, so orthotopic models should be performed to validate the authors' conclusions.\nMinor concerns:\n6.What is the reason for the difference in GCA levels between healthy individuals and patients with CRC?\n7.Macrophage depleted efficiency in Figure 2e should be detected.\n8. Line 195 lacks a space.", "reviewer_4": "This study shows that glycocholic acid (GCA) is associated with human colon cancer and that GCA promoted colon tumorigenesis in cultured colon cancer cell lines in immunocompetent xenograph mouse models through GCA inhibition of FXR signaling that altered the expression of target genes involved in immunomodulation of tumor growth by anti-PD-L1 and PD-1 drugs (such as nivolumab, pembrolizumab, atezolizumab, avelumab, aurvalumab, cemiplimab, dostarlimab and retifanlimab). While FXR has been shown to be involved in repression of colon and liver cancer in a number of earlier studies, this is a novel mechanism if it can be substantiated by experimentation. The authors propose that this effect is a result of GCA antagonism of FXR. However, GCA has never been shown to be an FXR antagonist while TCA (taurine conjugate of CA), found in mice, is a potent FXR agonist. And others showed that GCA is an FXR activator. In the human colon cancer correlative study, it is not clear whether is the result of colon cancer or in increased by other means such as lower gut bacterial deconjugation leading to increased tumor grown and lower therapeutic efficacy of the anti-PD-L1 and PD-1 drugs. This seems to be a therapeutic story where activation of FXR could increase the anti-tumor response to anti-PD-L1 drugs. The mechanism of the anti-tumor effect is dependent on FXR expression in the tumor cells where the authors suggest that when FXR signaling is inhibited by GCA, it leads to PD-L1 palmitoylation via DHHC9 and PD-L1 stabilization. While the data are interesting and the effect of FXR agonist clear and convincing, the data on GCA as an FXR antagonist is not convincing and not in agreement with earlier studies.\nComments:\n1. Figures 1 and 5: What are the concentrations of serum GCA in the low and high groups? What was the criteria for separating the low and high groups?\n2. What is the concentration of GCA in human serum? Is this concentration of GCA sufficient to antagonized FXR in intestine and MC38, CT26, HCT116 and SW620 cell lines. The reference values for GCA in human serum are around <2.17 umol/ml (https://genetics.testcatalog.org/show/BAPS). This seems to be more than sufficient bind to and antagonize FXR signaling based on the concentration of GCA used in cultured cells 100 ng/ml (about 0.2 nmol/ml). This is why it is important to precisely know the GCA levels in the human “Low GCA” and “High GCA” groups in Figures 1 and 5. If the Low GCA group is higher than 0.2 nmol/ml, it is hard to argue that FXR is not being antagonized in high survival (Figure 1) and highly response to immunotherapy patients.\n3. What is the concentration achieved in mice administered GCA (400 mg/kg p.o.) twice a week (from Figure 1 legend). A pharmacokinetic study should be done to determine if the serum levels obtained are withing the range of that found in humans and sufficient to modulate FXR in tumor cells.\n4. FXR protein levels should be quantified in tumors of patients that are sensitive and resistant to anti-PD-L1 and anti-PD-1 monoclonal Ab drugs.\n5. Mice are not a good model to study the effects of GCA since mice make trace amounts of GCA; they mostly make the taurine conjugate TCA. But they are a good model to study the therapeutic effects of GCA. This should be discussed.\n6. GCA should be measured in CRC tumor tissues. In tumor tissues, are different GCA levels also correlative with FXR transcriptional activity and PD-L1 expression?\n7. FXR silencing was found in tumor tissues by DNA methylation and KRAS signaling, hence cancer cells-induced xenograft is not proper for FXR inhibition studies (PMID: 24177031). FXR inhibition (GCA) studies should be done in WT and FXR-KO AOM/DSS-induced CRC models.\n8. The authors should verify their main findings in the AOM/DSS induced CRC mouse models or in human CRC organoids. Are Fxr-null mice more resistant than wild-type mice to anti-PD-L1 therapy?\n9. Quantitative western blots should be performed on wild-type and FXR knockout MC38, CT26, HCT116 and SW620 cells. In all experiments suing GCA, typical FXR tart genes mRNAs should be measured.\n10. Most of the experiments were performed in xenograft models, but the authors did not include FXR-KO in all the xenograft models. What is the tumor growth of FXR-knockout/knockdown cancer cells? GCA/TβMCA/GW4064 treatment should be done in both WT and FXR-KO cancer cells-injected xenograft models.\n11. GCA has never been shown to be an FXR antagonist. However, earlier studies found that GCA is an FXR agonist (See Figure 5 in PMID: 16230354). In addition, TCA is a potent FXR agonist (PMID: 23051670). What is the explanation for this stark difference between the results in this study and the earlier published data? In silico modeling studies should be done to explain why GCA antagonizes FXR while TCA activates FXR.\n12. As reviewed in PMID: 23603607 and PMID: 28249269, IBABP (FABP6) and ASBT (SLC10A2), respectively, are required for bile acid (FXR ligands) uptake into cells. Do MC38, CT26, HCT116 and SW620 cells express biologically significant levels of IBABP and ASBT? This should be determined by western blots. Tumor cells frequently lose expression of many genes and transporters found in normal colon/intestinal epithelial cells that not required for cell growth.\n13. I am not aware of any studies in nuclear receptors where an antagonist inhibits RXR dimerization to repress transcription. Most studies found that nuclear receptor antagonist bind to the ligand-binding site and inhibits the recruitment of transcriptional co-activators and/or recruit transcriptional co-repressors. Based on many years of FXR studies, the most likely explanation for GCA antagonist activity is that it displaces FXR agonist. The authors need to perform more definitive studies to show the mechanism by which GCA suppresses FXR signaling. Since the authors stated that GCA is a novel antagonist/inhibitor of FXR with a totally novel inhibition pattern, more structure-based evidence should be offered. Does GCA directly bind to FXR? What’s the binding site? How this GCA-FXR binding influence its activity?\n14. The studies showing increase in tumor growth in the xenograph MC38, CT26, HCT116 and SW620 cell lines and in the AOM-DSS mouse model should be done using a confirmed FXR antagonist (PMID: 33995909) given the concerns about whether GCA is a bona fide FXR antagonist.\n15. Guo and colleagues published in 2009 (PMID: 18981289) that inhibition/loss of intestinal FXR results in increase colon tumorigenesis, thus diminishing the novelty of this study. This paper should be cited and discussed.\n16. Others have shown that FXR agonist suppress colon cancer (PMID: 33436792). This paper should be cited and discussed.\n17. A number of papers have shown a role for bile acids in colon cancer (PMID: 30794774; PMID: 36765047). Notably, the gut microbiota, bile acids, and intestinal FXR signaling have been shown to influence colon cancer in mouse models of CRC. These papers and other relevant to the present study should be cited and discussed.\n18. It was reported that activation of FXR inhibited intestinal cancer stem cell proliferation and alleviated CRC progression (PMID: 30794774). However, the authors found that FXR did not influence the growth rate of cancer cells. This inconsistent conclusion should be discussed.\nMinor comments:\n19. What was the method for measuring bile acid concentration in humans and mice? Were standards used to precisely quantify the bile acid metabolites?\n20. Fxr floxed mice were purchased from Cyagen Biosciences, Inc. (cat. no. S-CKO- 555 04890). To my knowledge, this mouse line has never been published and there is no data showing that the intestinal epithelial-specific Fxr knockout (Fxrko) mice lack FXR expression in intestinal epithelial cells. These mice should be characterized by showing loss of FXR in intestinal epithelial cells.\n21. What is the source of the villin-Cre transgenic mice?\n22. The Fxr knockout efficiency and tissue specificity should be measured in all mouse models and cancer cell lines.\n23. How were the bile acids and GCA concentrations quantified? More details are needed on how GCA was measured and quantified.\n24. Figure S1A, B: Describe the meaning of M, N, and T in the legend.\n25. Figure S4A: Confirm the dosage GCA as 400 mg/kg p.o. Other GCA concentrations in Figure S3 is 400 ug/kg."}, "author_response": "The responses to the comments point by point:\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author): with expertise in cancer immunology,\ncolorectal cancer\nColorectal cancer (CRC) is a highly prevalent tumor type that is generally refractory to\nimmunotherapy. Thus, elucidating mechanisms of CRC resistance to immunotherapy is\nof high importance. In this study, Zhao et al make use of a comprehensive range of\nclinical data, in vivo models, and in vitro cell biology assays to identify bile acids as\npotential regulators of CRC sensitivity to T cell attack. Mechanistically, this is proposed\nto occur through the bile acid nuclear receptor Fxr, which regulates expression of\nSOX14 and the palmitoyltransferase DHHC9 to control palmitoylation and stability of\nthe immune checkpoint ligand PD-L1. Overall, the experiments appear to have been\ngenerally well-executed (although the methodological details are not always clear, nor\nis it clear how often experiments were reproduced). The connection between bile-\nacid/Fxr-dependent regulation of tumor PD-L1 expression is not well understood in the\ncontext of CRC, but a similar set of observations were recently published for\nhepatocellular carcinoma (Gong et al, Front Oncol, 2021).\nOverall, the data are interesting and shed light on a mechanism of PD-L1 regulation\nthat is not well understood. However, I have several concerns that should be addressed\nprior to publication.\nWe thank the reviewer for his/her positive comments on our paper and have addressed\nall the questions raised by the reviewer as outlined below.\nMajor concerns:\n1. Fig. 1b/c: GCA concentrations are noted on the y-axis as ‘relative concentration’, but\nwhat are they relative to? The median differences between early and late-stage disease\n(panel B) or localized vs metastatic disease (panel C) may be statistically significant\nbut are less than 0.1 in log2 space, which equates to a <7% difference. Are this\ndifference considered biologically or clinically meaningful? Is it possible to estimate\nbile acid concentrations in tumor tissue?\nR: We appreciate the reviewer’s careful reading of our manuscript and apologize for\nnot clearly describing this point in our first version of the manuscript and any confusion\nit might have caused. It is our mistake, we have deleted “relative” in the revised\nmanuscript; we also re-analyzed the serum GCA levels by using GCA concentration\nand showed in Fig. 1B, C of revised manusript.\nAs pointed out by the reviewer, the differences of GCA concentration in CRC\npatients with early- and late-stage or localized vs. metastatic disease CRC appears\nmarginal. Similar observations have been reported in other study, where serum GCA\nconcentration showed only marginal changes between early- and late-stage patients\nwith non-small cell lung cancer (NSCLC) (J Cancer Res Clin Oncol. 2023\nDec;149(19):17285-17296). In our study, we only recruit 80 CRC patients (Cohort 1)\ninitially; we have added another cohort of CRC patients (308 patients in total, Cohort\n2) in our revised manuscript. Our new data also demonstrated that high serum GCA\nconcentration not only was positively related with advanced tumor stage but also\npredict poor overall survival and disease-free survival. We have updated these results\nin our manuscript (Fig. SS1A-D, original Figure Fig. S1C-F).\nBile acids are released into the small intestine in response to cholecystokinin\nstimulus upon meal ingestion. In the gut lumen, bile acids facilitate transport, digestion\nand absorption of nutrients, particularly lipids and lipid-soluble vitamins. Up to 95 %\nof bile acids are actively re-absorbed in the terminal ileum and transported back to the\nliver and enter the systemic circulation. it has been suggested that blood levels of bile\nacids could be more useful to investigate associations with cancer risk than fecal bile\nacids, and small case-control studies have found increased serum bile acids levels in\npatients with colon cancer. We have previously evaluated the concentrations of bile acid\n(BA) concentrations in tumor tissue from small samples, the concentrations were very\nlow, thus we did not show these data and chose the blood levels of bile acids for further\nstudy.\nFig. SS1. (A) Serum GCA levels in stages I-II (n=117) and III-IV patients (n=191) with\nCRC (n=308, Cohort 2). (B) Serum GCA levels in patients with CRC patients with\nmetastatic disease (M1, n=59) or without metastatic disease (M0, n=249). (C and D)\nKaplan-Meier analyses with log-rank test were used to evaluate Disease-free survival\n(C) and overall survival (D) of 308 CRC patients based on their serum GCA levels\nusing the median GCA levels as cut-off value.\n2. Fig. 1d/e and Fig. S1a/b: elevated circulating bile acid concentrations are typically\nassociated with hepatic dysfunction (resulting in impaired clearance of bile acids from\nportal blood). This raises the question of whether the increased GCA concentrations\nobserved in patients with metastatic CRC are due to liver metastases impairing hepatic\nfunction (as opposed to a causative role of GCA in promoting CRC progression, as\nimplied in this manuscript). It would be interesting/informative to compare BA\nconcentrations in patients with liver vs non-liver metastases and include liver metastasis\nspecifically as a covariate in survival analysis (as distinct from other metastatic sites).\nR: We appreciate the reviewer's insightful question regarding the potential impact of\nliver metastases on circulating bile acid concentrations and their association with CRC\nprogression. In our initial study, we only recruit 80 cancer patients and only few patients\nwith liver metastasis, thus we did not compare BA concentrations in patients with liver\nvs non-liver metastases and include liver metastasis. In the new 308 CRC patients’\ncohort, 39 patients were diagnosed with liver metastases (35 patients with only liver\nmetastasis and 4 patients had liver and other organ metastasis). We found that the mean\nserum GCA concentrations, were significantly increased in the CRC patients with liver-\nmetastases compared to those without liver-metastasis (Fig. SS2A-D). Kaplan-Meier\nsurvival analyses with log-rank test showed that no significant difference was found\nbetween high and low GCA concentration patients’ overall survival who had only liver\nmetastasis, although there were poor trend for high GCA level’s patients (Fig. SS2A-\nD). This might be caused by small samples. Whether high GCA could affect the liver\nmetastasis and the specific mechanism need more detailed explorations, we will\nconduct another study in future. Thus, we did not supplement these results in our revised\nmanuscript.\nFig. SS2. (A). Different GCA concentrations in patients with all 39-liver vs non-liver\nmetastases(n=269) among CRC patients of Cohort 2. (B) Different GCA concentrations\nin patients with only liver(n=35) vs non-liver metastases(n=269) among CRC patients\nof Cohort 2. (C and D) Kaplan-Meier analyses with log-rank test were used to evaluate\noverall survival in patients with liver metastasis and other metastasis (C) and in patients\nwith only liver metastasis (D) among Cohort 2’s CRC patients.\n3. Fig. 1f/h/i (DSS-AOM data): the DSS-AOM model data are intriguing, but somewhat\nchallenging to interpret. The DSS-AOM regimen models colitis-associated CRC, which\nfollows a distinct process of pathogenesis compared to the much more common\nsporadic CRCs (which are the principal focus of this manuscript). Most importantly,\ntumorigenesis in this system relies on repeated rounds of DSS-driven colitis, and tumor\nburden is associated with the severity of DSS-driven tissue damage. Because the\nauthors appear to have used mice with constitutive loss of Fxr in intestinal epithelial\ncells (Fxr.flox crossed with Villin-Cre), it is not possible based on these data to\ndetermine whether Fxr function is associated with alterations in tumorigenesis, colitis,\nor both. One potential alternative is to use mice with inducible Villin-controlled Cre\n(Vill. Cre. ERT2) so that Fxr can be deleted in colon epithelial cells after the final round\nof DSS (to exclude effects on colitis). However, the challenge of interpreting colitis-\nassociated CRC data in the context of a paper that's focused on sporadic CRC remains.\nIf the authors' intent is simply to generate data using an orthotopic model of CRC,\nalternative systems could include direct implantation of CRC cell lines into colon\nmucosa, or delivery of CRC cells to the liver via hydrodynamic tail vein injection.\nR: The reviewer’s concern is thoughtful. Following your kind suggestion, we generated\nan orthotopic mice model of CRC by implanting MC38 tumors into colon mucosa. This\napproach provides a more relevant model for studying sporadic CRC and allows us to\nfocus specifically on the role of FXR in tumorigenesis without the confounding effects\nof colitis associated with the DSS-AOM model. In brief, wild-type 10-12 weeks old\nC57BL/6 mice were examined by endoscopy to ensure the colonic mucosa was healthy\nprior to implantation after anesthesia. For tumor cell implantation, 0.5×106 Fxr-\nknockout (sg FXR) MC38 cells or control cells (sg CON) diluted in 50 μL of PBS were\ninjected very slowly towards the lumen of lower mid and distal colon ~30 mm from the\nanal verge to induce tumor growth by using endoscopic injection. Consistently, the\ngrowth of Fxr-KO MC38 tumors by using this orthotopic mice model of CRC was\nsignificantly increased compared to that of control tumors (Fig. SS3A, original Figure\nFig. S3A). In addition, a worse overall survival was observed in mice with Fxr-KO\nMC38 tumors compared to those with controls (Fig. SS3B, original Figure Fig. S3A),\nwhich further confirmed our conclusion that FXR inhibits CRC tumorigenesis.\nFig. SS3. (A-B) 0.5×106 indicated MC38 cells were endoscopy-guided injected into the\nlumen of lower mid and distal colon ~30 mm from the anal verge of C57BL/6J mice\n(n=5). (A)Tumor volumes and (B)mortality within the observation period of the\nindicated mice were shown. All the experiments were repeated three times. The results\nare presented as the mean ± SD.\n4. Treatment with GCA apparently reduces activity of FXRE significantly in the\nluciferase reporter system (cell line assays). What is the source of the basal reporter\nsignal? Is this an overexpression artifact, or are the cells exposed to bile acids in culture\nmedium (possibly via serum)?\nR: We understand the reviewer’s point. In our study, CRC cells were cultured in DMEM\nsupplemented with 10% fetal bovine serum (FBS). To investigate whether serum\ncontributes to the basal activity of FXR signaling, we cultured MC38 cells transfected\nwith FXRE reporter system in DMEM supplemented with or without 10% FBS and\nobserved that luciferase activity was significantly upregulated in cells with FBS\ncompared to that in plain DMED (Fig. SS4). Our experiment provided clear evidence\nthat the basal FXR signaling activity in our luciferase assays is due to the presence of\nFBS in the culture medium, which was crucial for interpreting the effects of GCA on\nFXR activity.\nFig. SS4. MC38 cells transfected with reporter plasmids linked to an FXR-responsive\nelement (FXRE-Luc) were cultured in plain DMEM for 24h, followed cultured with\n10% FBS DMEM (Normal) or plain DMEM (Plain) for another 24h. Luciferase activity\nof MC38 cells was shown (n=5).\n5. Figure 2I: The authors report that treatment of MC38 cells with GCA significantly\ninduced PDL1 expression at the protein level, but not at the mRNA level. PDL1 is well-\nknown to be an interferon-inducible gene, and it is noteworthy that several other\nproteins identified by the authors as induced by GCA are also known to be interferon-\ninducible, including Ifi204, B2m, Mndal, and H2-M3. Is this merely a coincidence, or\nis it possible that GCA-treatment is inducing an autocrine type I IFN response?\nHave the authors performed an unbiased transcriptional analysis (e.g. bulk RNAseq) to\ndetermine if such an interferon-like response is indeed occurring?\nR: This is a thoughtful question. In our study, we made an intriguing observation that\nGCA did not affect the expression of interferon-stimulated genes in vitro (original\nFigure Fig.S5H). Of note, the mRNA level of PD-L1 was not altered in cells treated\nwith GCA, suggesting that GCA-mediated upregulation of PD-L1 is not dependent on\ninterferon signaling (original Figure Fig.S6E). To further validate our results, we\nmeasured the transcriptional level of type I interferon (IFNα and IFNβ), transcriptional\nfactors of IFN, including STAT1, STAT2, IRF1, IRF2, IRF5 and interferon-stimulated\ngene 15 (ISG15), essential for cellular IFN signaling transduction in GCA- or GW4064-\ntreated MC38 and HCT116 CRC cells. However, functionally suppression or activation\nof FXR signaling in CRC cells did not alter the mRNA level of IFNs or ISGs (Fig.SS5).\nOur data suggested that GCA does not affect IFN-response in vitro.\nFig. SS5.qRT-PCR measurement of the expression of indicated mRNA in MC38 (left)\nand HCT116 (right) cells treated with GCA or GW4064 for 24h. (B) GSEA analysis of\ntype I IFN response in MC38 cells treated with or without GCA for 24 h based on RNA-\nsequencing.\n6. Fig. S4H/I: the apparent dependency of Fxr-driven tumor growth effects on tumor\nPDL1 expression is interesting and important to the overall message of the paper. To\nexclude the possibility that this phenotype is driven by clone-to-clone differences,\ncan this observation be further supported by blocking PDL1 in tumors from wild type\ncells (e.g. with anti-PD-L1 blocking antibody) in the presence or absence of Fxr\nligands?\nR: Follow your kind suggesting, we used a subcutaneous wild-type MC38 or CT26\ntumor model to address this question. In brief, we subcutaneously injected 0.5×106\nMC38 or CT26 cells diluted in 100 μL of PBS in the right flank of C57BL/6 or BALB/c\nmice to induce tumor growth, respectively. Mice were treated with GCA (400 mg/kg\np.o.) and/or anti-PD-L1 (10mg/kg and 100mg/kg) twice a week at day 10 post injection.\nSimilarly, the results showed that functional impairment of FXR by GCA in CRC cells\nsignificantly promoted the growth of tumors. While low dose anti-PD-L1 therapy\n(10mg/kg), which was sufficiently prevent the growth of MC38 and CT26 tumors in\nmice under normal condition, did not inhibit the development of tumors in mice with\nGCA (Fig. SS6 A-B, original Fig.S7H-I), suggesting that 50mg/kg of anti-PD-L1\nantibody might not fully neutralizing PD-L1 in tumor microenvironment (TME). Of\nnote, blocking PD-L1/PD-1-signaling by treatment of high dose of anti-PD-L1\n(100mg/kg) was sufficiently reverted GCA-induced tumorigenesis (Fig. SS4 A-B),\nwhich further confirming our results that PD-L1 expression in tumors was critical for\nFXR-mediated tumor suppression.\nFig. SS6. (A-B) C57BL/6 (n=6) or BALB/c mice inoculated with MC38 (A) or CT26\n(B) tumor cells were treated with GCA (o.p) twice a week and/or with anti-PD-L1\nantibody or IgG 7 days post injection. The tumor volumes (left) and weights (right) are\nshown.\n7. Figure 5: the authors propose that the Fxr-regulated SOX14/DHH-C9/PD-L1 axis is\ninvolved in resistance of MSI-H/dMMR CRC patients to anti-PD-1 therapy in the clinic.\nThis conclusion seems potentially odd—if we assume that tumor-expressed PD-L1 acts\nby engaging PD-1 on T cells, and if the anti-PD-1 antibody (the specific identity of the\ntreatment regimen should be stated in methods) was dosed adequately to fully inhibit\nPD-1, then why would increase expression of PD-L1 on tumor cells have any bearing\non anti-PD-1 response? Is there any reason to believe that these patients did NOT\nreceive a dose of anti-PD-1 sufficient for full target coverage?\nR: We appreciate this insightful question Although ICB therapy has durable effects\ntoward a subset of microsatellite instability-high (MSI-H) CRCs, accounting for ~15%\nof all CRC cases, only 30-50% of these patients can benefit from this therapy. Anti-PD-\n1 antibodies work by blocking the interaction between PD-1 on T cells and PD-L1\nderived from cancer cells or cells in tumor microenvironments (TME), including\nmacrophages, MDSCs and fibroblast, thereby enhancing anti-tumor response of CD8+\nT cells (J Hematol Oncol. 2021 Jan 7;14(1):10.). Due to intertumoral heterogeneity in\nadvanced cancer, tumors or other cells may have heterogeneous expression of PD-L1\n(J Thorac Dis. 2020 May; 12(5): 1770–1775.). Accordingly, the identification of key\nmarkers in regulating resistance to PD-L1 therapy is necessary to combat an\nimmunosuppressive TME in CRC. In this study, we discovered that serum GCA/ FXR\nsignaling could regulate the aberrant expression of SOX14 or DHHC-9, which\npersistently induced PD-L1 expression in tumor microenvironments, then affecting the\nresponse to anti-PD-1 therapy. Our findings indicate that combination of targeting the\nFXR signaling pathway is a potential strategy for alleviating an immunosuppressive\nTME and enhancing the sensitivity to anti-PDL-1 treatment in CRC.\n8. Figure 6 (and various associated statements in text): along a similar line, the authors\npropose that inhibition of SOX14 or DHHC9 expression in tumors causes an improved\nanti-tumor immune response and improved tumor control, presumably via reduced PD-\nL1 expression. While this makes sense under untreated conditions, they argue that this\nalso applies during treatment with anti-PD-1. Similar to the clinical setting, unless PD-\n1 blockade is substantially incomplete, it is difficult to understand why alterations in\ntumor PD-L1 expression would enhance sensitivity to PD-1 blockade. The data instead\nraise the possibility that tumor-intrinsic SOX14/DHHC9 deficiency can act at least\npartially in a PD-L1-independent fashion to increase tumor sensitivity to immune\nsurveillance and anti-PD1 treatment.\nR: The reviewer’s comments is thoughtful. As mentioned in response of question 7,\ndosage, drug delivery, tumor microenvironment factors, the course of treatment might\naffect clinical benefits of anti-PD-1 treatment. To investigate whether the dosage of\nanti-PD-1 antibody (100mg/kg) we used could achieve full inhibition, mice\nsubcutaneous injected of MC38 cells were treated with anti-PD-1 (50mg/kg, 100mg/kg\nand 200mg/kg) twice a week starting at day 10 post injection. Our results showed that\nanti-PD-1 therapy inhibits MC38 tumorigenesis in a dose-dependent manner (Fig. SS7).\nOf note, CRC tumor growth was abolished in mice receiving 200mg/kg of anti-PD-1\nantibody treatment (Fig. SS7), suggesting that the dosage used in our in vivo\nexperiments incompletely in blocking PD-1 on T cells.\nFig. SS7 (A) C57BL/6 (n=6) inoculated with MC38 tumor cells were treated with\nindicated dose of anti-PD-1 antibody or IgG 7 days post injection. The tumor volumes\n(left) and weights (right) are shown.\n9. The MC38 and CT26 models used extensively in this manuscript best represent the\ninflamed and potentially immunotherapy-responsive MSI/dMMR subset of CRC.\nHave the authors explored whether manipulation of the Fxr pathway impacts immune\nresponses to 'colder' tumor models that are more representative of sporadic\nMSS/pMMR CRCs (which constitute the vast majority of CRC and the bulk of unmet\nclinical need). For example, this could include engineered colon organoids (e.g.\nTaraborelli et al, Nat Comm, 2023).\nR: We appreciate the reviewer’s suggestion. CT26 is often used as an MSS CRC model\ndue to the lack of mutations in MMR genes MLH1 and MLH2 and is considered to be\na 'cold' tumor model with lower immunogenicity and less responsiveness to\nimmunotherapy. (BMC Genomics. 2014 Mar 13;15(1):190. Cancer Cell. 2023 Jan\n9;41(1):196-209.e5.). In fact, mouse CRC cell lines CT26 and MC-38 exhibited high-\naffinity MHC-I-binding neoantigens, indicating that the tumors were susceptible to T-\ncell-mediated adaptive immunosurveillance (Nature. 2018 Feb 22;554(7693):538-543.)\nOur present study and other separate studies also observed that anti-PD-1 monotherapy\npartially limited the outgrowth of CT26 tumors (BMC Cancer. 2021 Nov 13;21(1):1222.\nJ Exp Clin Cancer Res. 2021 Sep 13;40(1):288.). Moreover, in our study we have also\nobserved a tumor-promoting role of GCA in both MSS (CT26) and MSI (MC38) CRC\ncells. To further validate our results, we used a most common CRC GEMM model by\nusing ApcMin/+ mouse, which was considered as a model of early MSS CRC (Br J Cancer.\nderived from ApcMin/+ mouse into the right flank of C57BL/6, then these mice were\ntreated with GCA or GW4064 (Fig. SS8). Consistent with our previous observation,\nFXR activation profoundly inhibit tumor development, as evidenced by a lower tumor\nvolume and a better of survival rate of the mice treated with GW4064 than control mice.\nFig. SS8. The tumor volumes of C57BL/6 mice (n=6) inoculated with CRC tumor\nsections derived from ApcMin/+ mouse with indicated treatment.\nMinor concerns:\n1. Extensive grammatical and spelling errors throughout manuscript. English-language\nediting recommended.\nR: We apologize for the mistakes and have refined the manuscript. In addition, we have\npreviously sent our revised manuscript for extensively editing.\n2. Heatmap scales are generally missing units/labels throughout the figures.\nR: We have added the labels of scale bars in our revised manuscript.\n3. Page 8, lines 162-165: The statement here is confusing and should be clarified.\nShould it actually say, “FXR-mediated tumor suppression…”?\nR: Yes, we have reedited this sentence in our revised manuscript.\nReviewer #2 (Remarks to the Author): with expertise in bile acids, FXR,\nmetabolomics\nZhao et al. demonstrated that glycocholic acid (GCA) enhances tumor cell PD-L1\nexpression, thereby suppressing CD8+ T cell-mediated antitumor responses in the\ntumor microenvironment (TME) and promoting colorectal cancer tumor growth. This\neffect is mediated through the targeting of the FXR/SOX14/DHHC9 axis. The study\nalso suggests a testable hypothesis: inhibiting GCA/FXR signaling could augment the\neffectiveness of anti-PD-L1 therapy. While this study presents a novel and intriguing\nperspective with potential implications for immunotherapy in colorectal cancer (CRC)\npatients, several major concerns need to be addressed, and the conclusion lacks robust\nevidence.\nWe are delighted that the reviewer finds our observations interesting. We have\nperformed point-by-point reply to reviewer as below.\nSpecific comments are the following:\n1. The authors mention the measurement of 33 bile acids (BAs) in serum but fail to\nprovide a detailed description of the method and BA profiling data. Additionally, the\ncriteria for defining low and high GCA levels in the recruited population are not clearly\nexplained. This GCA-based subgrouping method lacks validation in another cohort.\nR: We apologize for not clearly describing the detailed method of the measurement of\nBAs in our first version of the manuscript. In brief, for the measurement of bile acids\n(BAs), 0.1 mL serum sample of CRC patient was mixed with 0.51 ml of ice-cold\nMeOH-ACN (1:1, v:v) and sustained under -20 °C for 60 min to precipitate protein.\nAfter 15 min of centrifugation at 14000 rcf under 4℃, the supernatant was aspirated,\nand evaporated under vacuum. The residue was dissolved in 100 μl of MeOH and\ndeionized water (85:15, v:v), and centrifuged at 15000g and 4 °C for 15 min. The\naliquot from the supernatant was injected into the UPLC-MS system for analysis. We\nhave provided detailed methods in our revised manuscript.\nFor the definition of low and high GCA levels, we divided the CRC patients into\ntwo groups based on their serum GCA levels. The median concentration of GCA in the\nserum of the cohort (Cohort 1 n=80; Cohort 2 n=308) was used as the threshold.\nPatients with GCA levels above this mean were classified as GCAhigh, and those below as\nGCAlow. Then, Kaplan-Meier survival analyses with log-rank test were used to evaluate\nthe disease-free and overall survival. In our initial study, we only recruit 80 cancer\npatients, we have recruited new 308 CRC patients’ cohort. Our new data also\ndemonstrated that high serum GCA concentration not only was positively related with\nadvanced tumor stage but also predict poor overall survival and disease-free survival.\nWe have updated these results in our manuscript (Fig. SS1A-D, original Figure Fig.\nS1C-F).\n2. The authors assert that GCA acts as an FXR antagonist based on the Luciferase\nreporter assay. However, intra-gastric gavage feeding in animal experiments with GCA\nor TβMCA treatment raises concerns about the potential impact of bacterial\ntransformation of GCA in the gastrointestinal tract. Alternative administration methods,\nsuch as intraperitoneal injection, should be considered.\nR: We thank the reviewer’s kind comments. Follow the reviewer’s suggestion, we used\nMC38 subcutaneous tumor model to address this issue. In brief, we subcutaneously\ninjected 1.0×106 MC38 cells diluted in 100 μL of PBS in the right flank of C57BL/6\nmice to induce tumor growth. The tumor-bearing mice were i.p. with GCA twice a week\nstarted 7 days post injection. Similarly, our results showed that functional impairment\nof FXR by using GCA treatment promoted the tumorigenesis (Fig. SS9 A-B, original\nFigure Fig.S3J), suggesting that bacterial transformation of GCA in intestine was not\ninvolved in GCA-induced CRC tumorigenesis.\nFig. SS9. The tumor volumes (left) and tumor mass (right) of C57BL/6 mice (n=6)\ninoculated with MC38 tumor cells with or without GCA (i.p., 400mg/kg) treatment.\n3. The logical flow of the narrative appears disrupted with the introduction of Result 2\n[GCA inhibits IFN signaling in vivo].\nR: Thanks for your thoughtful comments. In Result 2, we focused on elucidating that\nGCA inhibits IFN signaling, which is crucial for anti-tumor immune response.\nTherefore, we reedited “To explore the underlying mechanism of GCA-regulated FXR\nsignaling in promoting CRC,” as follows: “To explore the signaling pathway enriched\nin GCA-induced tumorigenesis,”.\n4. The statement \"Since GCA-induced PD-L1 expression was dependent on post-\ntranscriptional modification\" (Line 243) lacks a clear reference or supporting data.\nR: Thanks for your kind commence. We have reedited this sentence in our revised\nmanuscript as follows: “Since GCA treatment did not alter the transcriptional levels of\nPD-L1 in CRC cells, ”.\n5. Inconsistencies between figure arrangement and subtitles of results and figure\nlegends are noted. For instance, figure 1F-K implies that GCA-increased CRC\ntumorigenesis is FXR-dependent, but this is not accurately reflected in the subtitle of\nResult 1 or Figure 1. Additionally, Figure 2, described as \"GCA impairs the antitumor\neffect of CD8 T cell by increasing tumor intrinsic PD-L1 expression,\" lacks validation\ndata (Cd274-KO data should be rearranged).\nR: Following your kind instruction, we re-edited our subtitle of Result 1 or Figure 1 as\nfollows: “GCA promotes tumor growth in a mouse model of CRC via inhibiting FXR\nactivity.” and “GCA is associated with poor clinical outcome in human CRC and\nincreases CRC tumorigenesis in immunocompetent mice by suppressing the activation\nof FXR.”, respectively. In addition, the results of investigating the function of CD274\non GCA-induced tumorigenesis (previous Fig.S4 H and I) were integrated into Figure\n2 (original Figure Fig.2 L and K).\n6. Line 377 mentions investigating whether inhibition of GCA/FXR could sensitize\nCRC to anti-PD-L1 therapy, but the subjects were treated with anti-PD1 therapy.\nClarification is needed.\nR: Thank you for pointing out this error. We used anti-PD-1 therapy in the series of\nexperiments for this section and reedited the sentence “Inhibition of GCA/FXR-induced\nSOX14 and DHHC9 expression sensitizes CRC to anti-PD-L1 therapy.” as follows:\n“Inhibition of GCA/FXR-induced SOX14 and DHHC9 expression sensitizes CRC to\nanti-PD-1 therapy.”\n7. Representative tumor graphs for all in vivo animal experiments should be provided\nby the authors.\nR: Thanks for your suggestion. While providing representative tumor graphs for all in\nvivo animal experiments can enhance credibility of our results, large-scale experiments\ninvolving a significant number of animals, resulting in an extensive amount of image\ndata. Due to the limitation of the space of our manuscripts, presenting all these images\nis impractical. In addition, we have, however, included key representative images of\ncolons in Fig.1H, I, that best illustrate our findings on the tumor promoting function of\nGCA.\n8. Lines 467-468 discuss the discussion of an FXR agonist with the antibiotic\nmetronidazole? enhancing GCA-induced resistant tumors to ICB therapy without\npresenting relevant data about the antibiotics.\nR: We apologize for our inadvertent proof. Antibiotic metronidazole treatment was not\ninvolved in our experiment and reedited the sentence “The current study highlights that\nan FXR agonist with the antibiotic metronidazole may enhance GCA-induced resistant\ntumors to ICB therapy.” As follows: “The current study highlights that an FXR agonist\nmay enhance GCA-induced resistant tumors to ICB therapy.”\n9. Detailed recruitment criteria information for the two cohorts, including healthy\nsubjects, should be provided.?\nR: Thank you for your thorough review of our manuscript. According to this comment,\nwe have described the detailed recruitment criteria information for all CRC patients’\ncohorts and healthy subjects in our revised manuscript as following: One cohort of 80\npaired CRC tissues (Cohort 1), adjacent normal mucosa tissues and serum collected\nbetween January 2018 and September 2018 from patients with CRC who were\ndiagnosed at Fudan University Shanghai Cancer Center (FUSCC) were recruited.\nAnother cohort of 308 patients (Cohort 2) with CRC between January 2008 and\nSeptember 2009, who were diagnosed at Fudan University Shanghai Cancer Center to\nvalidate our results that high serum GCA concentration not only was positively related\nwith advanced tumor stage but also predict poor overall survival and disease-free\nsurvival. The clinicopathological characteristics of all patients in these 2 cohorts were\nsummarized in Supplementary Tables S1-2. Morever,41 patients with MSI-H or dMMR\nwith recurrence or distant metastasis who received anti PD-1 immunotherapy between\nFebruary 2019 and September 2021 at FUSCC were enrolled in the present study\n(Cohort 3). All patients from these 3 cohorts did not receive any treatment for cancer\nbefore surgery and all these patients had no any other cancers. In addition, 20 health\ncontrols did not have any diseases and their detailed information has been enrolled .\nHuman serum specimens were collected prior to tumor resection, while normal mucosa\nand paired cancer tissues, as well as metastatic tissues, were collected immediately after\nsurgical resection. We have re-written this part in our revised manuscript.\n10. The abstract mentions a \"GCA diet\" (Line 27), but there is no related information\nabout it in the animal method, which relies on intragastric gavage of GCA.\nR: Thank you! Indeed, the tumor-bearing mice were treated with GCA via intragastric\ngavage. We have reedited the words \"GCA diet\" in line 27 as follows:” GCA treatment”.\n11. The rationale behind the test doses for BA-related agents in vivo and in vitro should\nbe illustrated, and the method needs supplementation\nR: The dosage for BA-related agents, including GW4064 and T-βMCA used in our in\nvitro experiments was primarily based on references from previous studies (Cell. 2019\nFeb 21; 176(5): 1098–1112.e18.). We have provided this information in the method\nsection of our revised manuscript. For the dosage of GCA used in vivo, we administered\nGCA at 0 mg/kg to 800 mg/kg p.o., twice a week, beginning at day that MC38 tumors\nreached ~100mm3 post subcutaneous injection of C57/BL6 mice. Tumorigenesis was\nrobustly promoted in mice treated with 400 mg/kg or 800 mg/kg of GCA (Fig. SS10 A,\noriginal Figure Fig.S3B). However, a high dose of GCA (800 mg/kg) treatment\nincreased tumor burden with evident side effects as measured by weight loss during the\ncause (Fig. SS10 A-B, original Figure Fig.S3B). Therefore, we used 400 mg/kg of GCA\nto perform our in vivo experiments. In addition, we cultured MC38 cells with 0-200µM\nof GCA and observed that GCA suppressed FXR activity in a dose dependent manner\n(Fig. SS10 C, original Figure Fig.S2D). Of note, 100µM of GCA robustly decreased\nthe activation of FXR without affecting the proliferation of MC38 cells (Fig. SS10 C\nand D, original Figure Fig.S2D), suggesting that this dosage of GCA is optimal for in\nvitro experiments. We have provided these results in our revised manuscript.\nFig. SS10. (A-B) The tumor volumes (A) and mice weight (B) of C57BL/6 mice (n=6)\ninoculated with MC38 tumor cells under indicated GCA (p.o.,) treatment. (C-D) FXRE-\nLuc MC38 cells were treated with indicated concentration of GCA for 24h. Luciferase\nactivity (C) and the MTT assay (D) was performed.\nReviewer #3 (Remarks to the Author): with expertise in PD-L1 regulation, cancer\nimmunology\nZhao et al. demonstrated that GCA accumulates in the serum of patients with CRC. This\naccumulation leads to a reduced activity of the bile acid receptor FXR, resulting in a\npoor antitumor CD8+ T cell response. Mechanistically, GCA upregulates tumor PD-L1\nexpression through the FXR-SOX14-DHHC9 axis-mediated palmitoylation of PD-L1.\nWhile the study includes substantial experiments, it lacks novelty in terms of the role\nof GCA and its receptor in CRC and the palmitoylation of PD-L1 by DHHC9, as these\nhave been reported in previous studies.\nWe appreciate the reviewer’s insight comments. We have addressed the specific\nquestion raised by the reviewer.\nMajor concerns:\n1. The pre-diagnostic plasma GCA levels and colon cancer risk has already been\nreported (PMID: 31435679), as well as the mechanism regarding the role of DHHC9\non the expression of PD-L1 (PMID: 30514902). In addition, the bile acid receptor FXR\nagonist GW4064 has already been reported to enhance anti-PD-L1 immunotherapy in\ncolorectal cancer (PMID: 37261088). Thus, the key points of this study are already\nknown with less novelty.\nA: We truly appreciate the reviewer's insightful comments on our observation. In this\nstudy, we have identified GCA is a risk factor for colorectal cancer, and mechanistically\ndissected of GCA-induced tumorigenesis by promoting SOX14/DHHC9-mediated\npalmitoylation and stabilization of PD-L1. Based on these results, we are the first to\npropose and prove that the serum GCA is not only a pre-diagnostic marker, but also a\ndriver of CRC. Additionally, we observed that GCA increased SOX14 expression via\ninhibiting FXR activity, and resulted in a transcriptional regulation of DHHC9, which\nfilled the missing linkage on how FXR regulates immune suppressive environments\nthrough stabilizing PD-L1. We considered this to be one of the innovative aspects of\nour findings. As pointed out by the reviewer, it has been reported that FXR agonist\nGW4064 sensitized anti-PD-L1 immunotherapy in CRC, which reduces the originality\nof our manuscript (Oncoimmunology. 2023 May 25;12(1):2217024.). While totally\nagreeing with this reviewer, we would like to draw his or her attention to our result that\nthe combined therapy of GW4064 and anti-PD-1 antibody sufficiently attenuated\ntumorigenesis of anti-PD-1 resistant CRC or CRC in mice with high concentration of\nGCA, which further strengthened this point by broadening the range of indications for\nthis combined therapy.\n2.The cluster identification by scRNA-seq in Figure 2 is not reasonable. The resolution\nseems very low and rough because no other myeloid clusters, such as dendritic cells,\nMDSCs, and neutrophils, or T-cell subsets (cytotoxic or exhausted), or tumor cells were\nfound in the scRNA-seq. The cell population in scRNA-seq seems exactly the same as\nthat found by flow cytometry. Especially, the macrophage population is the largest\namong tumor-infiltrating immune cells and is heterogeneous. What markers were used\nto identify the macrophages? No gene expression data were shown for each cluster.\nR: We appreciate the reviewer’s careful reading of our manuscript and apologize for\nnot clearly describing the method that we defined clusters in our first version of the\nmanuscript and any confusion it might have caused. We have provided detailed methods\nfor scRNA-seq data preprocessing in our revised manuscript (Supplementary materials\nand methods/ Single-cell RNA-seq data preprocessing). In brief, highly variable genes\nwere selected by using Seurat’s FindVariableGenes function (mean.function =\nFastExpMean, dispersion.function = FastLogVMR) for Principal Component Analysis\n(PCA). We identified cell clones by performing graph-based clustering (FindNeighbors\nfunction in Seurat) and visualized the cells using a 2-dimensional t-distributed\nstochastic neighbor embedding (t-SNE, RunTSNE function in Seurat). FindAllMarkers\nfunction was performed to select positive or unique markers for cell clones compared\nwith other clones. Then, we used R package SingleR, with the reference transcriptomic\ndatasets ‘Human Primary Cell Atlas’ to identify five major clusters of immune cells,\nCD4+ T cells, CD8+ T cells, macrophages, B cells, neutrophils and NK cells (BMC\nGenomics. 2013 Sep 20; 14:632.). It seems that neutrophils were barely detectible based\non our scRNA-sequencing. Considering that deletion of macrophages had little effect\non GCA-mediated tumorigenesis, we did not re-cluster the identified macrophages to\nfurther analysis. In addition, we used a panel of 21 detectable genes in our system\n(Fig.SS11, original Figure Fig.S6A), which was reported as markers for inferring\nimmune cell populations in time-of-flight (CyTOF) analysis (Fig4A, Cancer Discovery.\nenriched in typical clusters of immune cells as shown below, including CD3ε and CD4α\nfor CD4+ T cells, CD3ε and CD8α for CD8+ T cells, ITGAM (CD11b) and ADGRE1\n(F4/80) for macrophages, CD19 and CD68 for B cells as well as NKG7 and XCL1 for\nNKs, suggesting the methods we used were suitable for characterizing the cell of origin\nof each of the single cells. Therefore, we analyzed these immune cell populations in\nMC38 tumors treated with GCA to validate our results that FXR promoted the tumor-\ninfiltrating CD8+ T cells observed in MC38 tumors treated with FXR agonist GW4064\nbased on scRNA-sequencing.\nFig. SS11 Tumors from C57BL/6 mice treated with GW4064 on day 16 were subjected\nto single-cell RNA sequencing analysis (n=3), markers of immune subtypes, including\nCD3ε and CD4α for CD4+ T cells, CD3ε and CD8α for CD8+ T cells, CD68 and C1QA\nfor macrophages, CD19 and CD68 for B cells as well as NKG7 and XCL1 for NKs,\nmarkers of immune activation and inflammatory markers were selected. Heatmap for\nthe average expression level of indicated immune markers were shown (Z-score\nnormalized).\n3.Other independent cohorts or public databases should be analyzed to verify the\nclinical relevance between GCA and patient outcome. Are SOX14, GCA, and DHHC9\nexpression associated with patient survival in other studies? They should provide more\nevidence to validate their results.\nR: Thanks for your kind suggestion. According to your advice, we have validated our\nresults in newly recruited CRC cohort (Cohort 2 n=308). We had divided CRC patients\ninto two groups by mean concentration of GCA in serum and found that high serum\nGCA concentration was not only positively related with advanced tumor stage but also\npredict poor overall survival and disease-free survival. Moreover, IHC staining assay\nand non-parametric spearman correlation analyses revealed that the serum\nconcentration of GCA was positively associated with the protein expression of SOX14\nor DHHC9, which further validate our results that high serum GCA concentration of\nCRC patients is linked to poorly prognosis (Fig. SS12, original Figure Fig.S10A-C).\nWe have supplemented these results in our revised manuscript.\nFig. SS12. (A-C) GCA levels of serum, and IHC staining of DHHC9 and SOX14 in\ntumors of another cohort with 308 CRC patients. Non-parametric spearman correlation\nscores were used to analysis the correlation of IHC score for DHHC9 and SOX14,\nas well as serum GCA levels. Each dot is colored by a two-dimensional kernel density\nestimation, where the purple-to-yellow color indicates greater density of data points.\n4. Data quality is unsatisfactory. For example, all flow data of PD-L1 expression lack\nnegative IgG control, such as Figure 2k, 2l, 3b, and 3g. The flow gating of exhausted T\ncells and interferon-gamma-producing T cells should be shown. Additionally, according\nto their method, why were the same colors used together (Tim-3-BV605 and PD1-\nBV605)?\nR: We totally agree with this reviewer for his or her expert view of the data. We repeated\nour experiment in Fig.2K, L and Fig. 3B, G by using anti-PD-L1 antibody and\nappropriate IgG control (Fig. SS13 A-D, original Figure Fig.S7A and B, Fig. 3B and\nG). The results validated that GCA, DHHC9 or SOX14 promoted the expression of PD-\nL1.\nFig. SS13. (A-B) MC38 and HCT116 tumor cells were treated with GCA (A) or with\nGW4064 (B) for 24 h. The protein level of PD-L1 was measured by FACS. (C) MC38\nand HCT116 cells were pretreated with or without GCA for 24 h, and then treated with\n2-bromopalmitate (5 μM), MG132 (10 nM) or 3-methyladenine (10 μM) for 8 h. The\nexpression of PD-L1 was measured by FACS. (D) MC38 (upper) and HCT116 (lower)\ncells transduced with the indicated siRNA or with control siRNA were treated with\nGCA for 24 h. The expression of PD-L1 was measured by FACS.\nIn addition, the flow gating strategy of exhausted CD8+T cells (PD-1+ and Tim3+)\nand IFNg+ CD8+T cells were shown and provided in our revised manuscript (Fig. SS14,\noriginal Figure Fig.S12). As for staining of exhausted CD8+T cells, we used anti-Tim-\n3-PE-LY7 and PD1-BV605 and reedited the method of FACS staining in our revised\nmanuscript. We apologize for not proofreading this point in our first version of the\nmanuscript.\nFig. SS14. Gate strategy for exhausted CD8+T cells (PD-1+ and Tim3+) and IFNg+\nCD8+T cells.\n5. In figures 4 and 6, all the in vivo mouse models are performed by subcutaneous\ninjection. The tumor microenvironment differs significantly in different organs, so\northotopic models should be performed to validate the authors' conclusions.\nR: As per your kind suggestion, we generated an orthotopic mice model of CRC by\ninjecting MC38 cells with Matrigel into colon mucosa. In brief, 0.5×106 SOX14-KD\n(knockdown) and control MC38 cells mixed with 10 μL of Matrigel were injected into\ncolon mucosa of C57BL/6 mice to induce tumor growth. GCA-treatment used in\nFigures 4 was started 10 days post injection. Tumor weights were measured at endpoint.\nWe found that SOX14-knockdown profoundly inhibited GCA-induced tumorigenesis\n(Fig. SS15A, original Figure Fig.S9G). In addition, tumors with SOX14-knockdown\nshowed an enhanced population of CD8+ and IFNγ+ CD8+ T cells, accompanied with\nattenuated exhausted CD8+ T cell infiltration (Fig. SS15B, original Figure Fig.S9H).\nFurthermore, we used this autochthonous mouse CRC tumor model to evaluate whether\nFXR agonist could sensitize CRC to anti-PD-L1 therapy. Similar to the results of\nsubcutaneous model in Fig.6E, we observed that treatment with combined GW4064\nand anti-PD-1 antibody significantly inhibited the tumorigenesis of anti-PD-1-resistant\nMC38 cells (Fig. SS15C, original Figure Fig.S11G). Of note, tumors receiving\ncombined therapy showed an increased population of infiltrating CD8+ IFNγ+ T effector\ncell and a decreased percentage of exhausted T cells compared to tumors with\nmonotherapies (Fig. SS15D, original Figure Fig.S11H), which further validate our\nconclusion that combined FXR agonist with anti-PD-1 therapy enhanced the efficacy\nof anti-PD-1 in CRC.\nFig. SS15 (A-D) 0.5×106 indicated MC38 (A-B) or anti-PD-1-resistant MC38 cells\nMC38R (C-D) cells were endoscopy-guided injected into C57BL/6J mice (n=6). (A, C)\nTumor volumes of the indicated mice were shown. (B, D) The percentages of CD8+ T\ncells from CD45+ cells (left), and frequencies of exhausted CD8+ T cells (TIM3+,\nPD1+ (middle) and IFNγ+ (right) in CD8+ T cells in the indicated tumors at end point were\nmeasured by FACS. All the experiments were repeated three times. The results are\npresented as the mean ± SD.\nMinor concerns:\n6. What is the reason for the difference in GCA levels between healthy individuals and\npatients with CRC?\nR: We are truly thankful to this reviewer for his or her interesting thoughts on\nglycocholic acid (GCA) GCA. GCA, a primary bile acid, is formed by cholic acid (CA)\namidated with glycine in liver, and then released into the intestine (Nat Rev\nGastroenterol Hepatol. 2024 Apr 4.). It is natural that the levels of GCA are tightly\nregulated by liver function. CRC can affect liver function either directly (through\nmetastasis) or indirectly (through systemic inflammation or metabolic changes),\npotentially leading to altered GCA levels. In addition, bile acids, including GCA, are\nabsorbed from the gastrointestinal tract and transported via the portal blood to the liver\n(Nat Rev Gastroenterol Hepatol. 2022 Jul;19(7):432-450.). CRC can affect the\ngastrointestinal tract's ability to absorb and excrete various metabolites, which may lead\nto differences in GCA levels between healthy individuals and CRC patients\n(Metabolites. 2021 Mar 10;11(3):159.). Of note, the gut microbiota plays a crucial role\nin bile acid metabolism (Nat Rev Microbiol. 2023 Apr;21(4):236-247.). Long-term\nantibiotic treatment significantly increased glycocholic acid (Front Microbiol. 2022 Jun\n29:13:832915.). It is known that composition of the gut microbiota is altered in faecal\nsamples and in tumor-associated communities of CRC patients compared to healthy\npeople, which may influence GCA levels (Front Physiol. 2022 May 4:13:854545.).\nCollectively, the difference in serum GCA levels between healthy individuals and\npatients with colorectal cancer (CRC) can be attributed to several factors, such as liver\nfunction, intestinal absorption and excretion as well as microbiota alterations.\n7.Macrophage depleted efficiency in Figure 2e should be detected.\nR: Following your kind suggestion, Fasc analysis was used to determine the depleted\nefficiency of macrophages in MC38 tumors. Our results showed that the percentage of\nmacrophages was significantly decreased in tumors derived from mice treated with\nclodronates compared to controls (Fig. SS16, original Figure Fig.S6B), suggesting that\nmacrophages was successfully deleted.\nFig. SS16 C57BL/6 mice (n=6) inoculated with MC38 tumors were i.p. injected with\nclodronate or control liposomes and then treated with GCA. The population of\nmacrophages (CD11b+ and F4/80+) in tumors at d18 post MC38 injection were\ndetermined by Facs.\n8. Line 195 lacks a space.\nR: Thank you for pointing out this error. We have reedited this in our revised manuscript.\nReviewer #4 (Remarks to the Author): with expertise in colorectal cancer, FXR,\nbile acids, metabolomics\nThis study shows that glycocholic acid (GCA) is associated with human colon cancer\nand that GCA promoted colon tumorigenesis in cultured colon cancer cell lines in\nimmunocompetent xenograph mouse models through GCA inhibition of FXR signaling\nthat altered the expression of target genes involved in immunomodulation of tumor\ngrowth by anti-PD-L1 and PD-1 drugs (such as nivolumab, pembrolizumab,\natezolizumab, avelumab, aurvalumab, cemiplimab, dostarlimab and retifanlimab).\nWhile FXR has been shown to be involved in repression of colon and liver cancer in a\nnumber of earlier studies, this is a novel mechanism if it can be substantiated by\nexperimentation. The authors propose that this effect is a result of GCA antagonism of\nFXR. However, GCA has never been shown to be an FXR antagonist while TCA\n(taurine conjugate of CA), found in mice, is a potent FXR agonist. And others showed\nthat GCA is an FXR activator. In the human colon cancer correlative study, it is not\nclear whether is the result of colon cancer or in increased by other means such as\nlower gut bacterial deconjugation leading to increased tumor grown and lower therapeutic\nefficacy of the anti-PD-L1 and PD-1 drugs. This seems to be a therapeutic story where\nactivation of FXR could increase the anti-tumor response to anti-PD-L1 drugs. The\nmechanism of the anti-tumor effect is dependent on FXR expression in the tumor cells\nwhere the authors suggest that when FXR signaling is inhibited by GCA, it leads to PD-\nL1 palmitoylation via DHHC9 and PD-L1 stabilization. While the data are interesting\nand the effect of FXR agonist clear and convincing, the data on GCA as an FXR\nantagonist is not convincing and not in agreement with earlier studies.\nComments:\n1. Figures 1 and 5: What are the concentrations of serum GCA in the low and high\ngroups? What was the criteria for separating the low and high groups?\nR: We are sorry for not describing this part in our previous manuscript. In our study, we\nonly recruit small samples with 80 cancer patients initially to further validate roles of\nGCA on progress of CRC, we have added another patients’ cohort (308 patients in total)\nin our revised manuscript. For the definition of low and high GCA levels, we divided\nthe CRC patients into two groups based on the median GCA levels. The median\nconcentration of GCA in the serum of the cohort (Cohort 1n=80; Cohort 2 n=308) was\nused as the threshold. Patients with GCA levels above this mean value were classified\nas high GCA group, and those below as low GCA group. We have re-written this part\nin our revised manuscript.\n2. What is the concentration of GCA in human serum? Is this concentration of GCA\nsufficient to antagonized FXR in intestine and MC38, CT26, HCT116 and SW620 cell\nlines. The reference values for GCA in human serum are around <2.17 umol/ml\n(https://genetics.testcatalog.org/show/BAPS). This seems to be more than sufficient\nbind to and antagonize FXR signaling based on the concentration of GCA used in\ncultured cells 100 ng/ml (about 0.2 nmol/ml). This is why it is important to precisely\nknow the GCA levels in the human “Low GCA” and “High GCA” groups in Figures 1\nand 5. If the Low GCA group is higher than 0.2 nmol/ml, it is hard to argue that FXR\nis not being antagonized in high survival (Figure 1) and highly response to\nimmunotherapy patients.\nR1-2: We appreciate the reviewer's insightful comments on our observations. Similar\nto the reports that Bile acids concentration was quantified by UPLC-MS system (Kühn\nT, et al. J Natl Cancer Inst. 2020 May 1;112(5):516-524.). And our data showed that the\nserum concentration of GCA in CRC and healthy individual used in new Fig.1B-C\n(Cohort 1) and Fig.S1C-D (Cohort 2), respectively. Based on the mean concentration\nof GCA, we divided CRC patients into two groups and observed that the patients with\nhigher serum GCA concentration than the mean was associated with poorer diagnosis\ncompared to those with lower concentration (new Fig.1D-E and FigS.1E-F). We totally\nagreed with this reviewer’s point that 100 ng/ml GCA was not sufficient to inhibit the\nfunction of FXR and apologized for this inadvertent error in labeling 100 ng/ml as\n100μM of GCA for culturing cells. As mentioned in reviewer2 Q11, GCA suppressed\nFXR function in a dose-dependent manner at the range of 0-200µM. Notably, the\nproliferation of MC38 cells did not inhibit when cells were culturing with 100μM of\nGCA. Therefore, we used this optimal concentration of GCA our in vitro experiments.\n3. What is the concentration achieved in mice administered GCA (400 mg/kg p.o.) twice\na week (from Figure 1 legend). A pharmacokinetic study should be done to determine\nif the serum levels obtained are withing the range of that found in humans and sufficient\nto modulate FXR in tumor cells.\nR: We truly appreciate the reviewer’s comments. In this study, we used a range of 0\nmg/kg to 800 mg/kg of GCA p.o. for twice a week on mice subcutaneous injected MC38\ncells to determine the optimal dosage in in vivo experiments. As mentioned in answer\nof reviewer2 Q11, 400 mg/kg of GCA treatment significantly suppressed the MC38\ntumor growth without evident side effects, such as weight loss, and therefore were used\nto perform our in vivo experiments. While totally agreeing with this reviewer that this\npoint needs to be further strengthened by new experiments on pharmacokinetic study\nof GCA, due to the time limitation of the current work and lack of relevant knowledge,\nwe did not capable to perform experiments. However, we would like to draw his or her\nattention to our result that the transcriptional level of FXR-downstream genes,\nincluding IBABP and SHP was clearly down-regulated in tumors treated with GCA,\nsuggesting that 400 mg/kg of GCA is sufficient to suppress FXR function in vivo.\n4. FXR protein levels should be quantified in tumors of patients that are sensitive and\nresistant to anti-PD-L1 and anti-PD-1 monoclonal Ab drugs.\nR: Following your kind suggestion, we performed western blotting analysis of the\nexpression of FXR in 41 human CRC tissues used in Figure 5 and observed that the\nprotein level of FXR was not significantly changed in tumors derived from the patients\nthat resistant or response to anti-PD-1 therapy (Fig. SS17 A-B), suggesting that the\nalteration of the activity, rather than the protein level of FXR, is associated with clinical\noutcomes of anti-PD-1 therapy.\nFig. SS17. A total of 41 patients with microsatellite instability-high mCRC were treated\nwith anti-programmed cell death protein 1 therapy. The protein level of FXR was\ndetermined by western blotting (left). The relative expression of FXR in tumors derived\nfrom CRC patients with complete response/partial response and stable disease/\nprogressive disease (CR/PR and PD/SD) was quantified by image J (normalized to\nnormalized to the expression of TUBULIN).\n5. Mice are not a good model to study the effects of GCA since mice make trace\namounts of GCA; they mostly make the taurine conjugate TCA. But they are a good\nmodel to study the therapeutic effects of GCA. This should be discussed.\nR: We appreciate the reviewer’s comments and the insightful thoughts provided. It is\nindeed true that humans and mice exhibit substantially different bile acid pool\ncompositions. In humans, bile acids in the liver are conjugated (N-acyl-amidated)\nwith glycine (G) or taurine (T) in a ratio of approximately 3 to 1. In contrast, mice\npredominantly use taurine for conjugation, with over 95% of their bile acids being\ntaurine conjugated. Humans produce a diverse mix of bile acids, including a substantial\namount of glycochenodeoxycholic acid (GCA). Conversely, mice predominantly\nsynthesize taurocholic acid (TCA), and only trace amounts of GCA are found in their\nsystem. This difference in endogenous bile acid composition presents a challenge when\nstudying the physiological effects of GCA in mice, as their natural bile acid\nenvironment differs significantly from that of humans. Due to the low endogenous\nlevels of GCA in mice, which are highly amenable to study the mechanisms,\nfunction or therapeutic effects of GCA by exogenously administered GCA. In our studies,\nwe observed that GCA inhibited the transcriptional function of the Farnesoid X Receptor\n(FXR) in both human and colorectal cancer (CRC) cells. Importantly, GCA was found\nto promote tumor growth in mice and is identified as a high-risk factor for CRC\ntumorigenesis, suggesting a tumor-promoting function in CRC. These results highlight\nthe relevance of using mouse models to study the therapeutic effects of GCA, despite\nthe differences in bile acid composition between species.\nWe have addressed this point in detail in our revised manuscript, discussing both the\nlimitations and the strengths of using mice as a model for GCA research in our revised\nmanuscripts.\n6. GCA should be measured in CRC tumor tissues. In tumor tissues, are different GCA\nlevels also correlative with FXR transcriptional activity and PD-L1 expression?\nR: This concern is reasonable. Bile acids are released into the small intestine in response\nto cholecystokinin stimulus upon meal ingestion. In the gut lumen, bile acids facilitate\ntransport, digestion and absorption of nutrients, particularly lipids and lipid-soluble\nvitamins. Up to 95 % of bile acids are actively re-absorbed in the terminal ileum and\ntransported back to the liver and enter the systemic circulation. it has been suggested\nthat blood levels of bile acids could be more useful to investigate associations with\ncancer risk than fecal bile acids, and small case-control studies have found increased\nserum bile acids levels in patients with colon cancer.10-12 In fact, we have already\nevaluated the concentrations of bile acid (BA) concentrations in tumor tissue from small\nsamples, the concentrations were very low, thus we did not show these data and chose\nthe blood levels of bile acids for further study.\n7. FXR silencing was found in tumor tissues by DNA methylation and KRAS signaling,\nhence cancer cells-induced xenograft is not proper for FXR inhibition studies (PMID:\n24177031). FXR inhibition (GCA) studies should be done in WT and FXR-KO\nAOM/DSS-induced CRC models.\nR: As per your kind suggestion, we investigated whether GCA could promote\ntumorigenesis in both wild-type and Fxrko C57BL/6 mice. Similar to our previous\nresults, GCA significantly increased the tumor growth in AOM/DSS-induced CRC\nmodels, as evidenced by an increased tumor numbers and a short colon length in mice\ntreated with GCA (Fig. SS18 A-B, original Figure Fig.S3C). Additionally, loss of FXR\naccelerated the development of CRC in the same CRC model, but GCA-treatment could\nnot further promote the tumorigenesis in Fxrko C57BL/6 mice, suggesting that FXR is\nthe functional target of GCA-induced tumorigenesis.\nFig.SS18 (A-B) Fxr-knockout mice (FXR-/-) and their litter mates were i.p. with GCA\n(400mg/kg) 3 days before AOM/DSS treatment (n=6 per group). Colon length (A),\ntumor numbers (B, left) and tumor areas (B, right) of colons were shown.\n8. The authors should verify their main findings in the AOM/DSS induced CRC mouse\nmodels or in human CRC organoids. Are Fxr-null mice more resistant than wild-type\nmice to anti-PD-L1 therapy?\nR: To address this concern, we generated the autochthonous CRC in both wild-type and\nFxrko C57BL/6 mice by using AOM/DSS-induced CRC model and treated these mice\nwith anti-PD-1 monotherapy. The results shown Fxr-deficiency ameliorated the\nsuppression of anti-PD-1 treatment, as evidenced by a decreased tumor numbers and\nlength of colon in Fxrko mice with anti-PD-1 monotherapy compared to that in wild-\ntype mice receiving same treatment (Fig. SS19 A-B), suggesting that activation of FXR\nsignaling is critical for sensitizing anti-PD-1 therapy.\nFig.SS19 (A-B) Fxr-knockout mice (Fxr-/-) and their litter mates were treated with anti-\nPD-1 antibody (100mg/kg) twice a week at 7 days after AOM injection and followed 3\nDSS cycles (n=6 per group). Colon length (A), tumor numbers (B, left) and tumor areas\n(B, right) of colons were shown.\n9. Quantitative western blots should be performed on wild-type and FXR knockout\nMC38, CT26, HCT116 and SW620 cells. In all experiments using GCA, typical FXR\ntart genes mRNAs should be measured.\nR: Following your kind suggestion, western blotting was used to determine the protein\nlevel of FXR in FXR-knockout (FXR-KO) MC38, CT26, HCT116 and SW620 cells\n(Fig.SS20A, original Figure Fig.S2B). We also measured the expression level of FXR\nin the tumor tissue derived from FXR-KO mice and their littermates in Fig. 1H\n(Fig.SS20B, original Figure Fig.S2L). Our results showed that FXR was successfully\ndeleted in these FXR-KO cells or tissues. In addition, we performed qRT-PCR to\nanalyze the expression level of FXR target genes I-BABP and SHP derived from cells\nor tumors in Fig.1K, Fig.S2A-D, Fig.S2L and Fig.S4H-I and observed that GCA\ninhibited I-BABP and SHP expression in indicated tissues (Fig.SS20 C-H, original\nFigure Fig.S3H and I, Fig.S4I and J, Fig.S7F and G).\nFig.SS20 (A) The protein level of FXR in indicated FXR-knockout (sg FXR) and\ncontrol (sg CON) cells. (B) The expression of FXR in tumors derived from Fxr-\nknockout mice (Fxr-/-) and their litter mates used in Fig. 1H. (C-D) Six-week-old male\nindicated mice (n=10) were injected subcutaneously with 1.0x106 MC38 (left) or CT26\ncells (right), and then treated with or without GCA (400 mg/kg p.o.) twice a week.\nThe expression of I-BABP and SHP in tumors was measured by qRT-PCR. (E-F) Six-week-\nold male indicated mice (n=10) treated with GCA along with or without GW4064 twice\na week were injected subcutaneously with 1.0x106 MC38 (E) or CT26 cells (F). The\nmRNA level of I-BABP (left) and SHP (right) was measured, (G-H) Indicated MC38\n(G) or CT26 cells (H) were injected in C57BL/6 or BALB/c mice, and then treated with\nor without GCA (400 mg/kg p.o.) twice a week. The transcript of I-BABP (left) and\nSHP (right) was determined by qRT-PCR.\n10. Most of the experiments were performed in xenograft models, but the authors did\nnot include FXR-KO in all the xenograft models. What is the tumor growth of FXR-\nknockout/knockdown cancer cells? GCA/TβMCA/GW4064 treatment should be done\nin both WT and FXR-KO cancer cells-injected xenograft models.\nR: As per your kind suggestion, we subcutaneously injected 0.5×106 FXR-knockout (sg\nFxr) or control (sg Con) MC38 cells in the right flank of C57BL/6 to induce tumor\ngrowth and treated mice with GCA, TβMCA or GW4064 10 days post injection,\nrespectively. As shown in our previous manuscript, GCA or TβMCA treatment\nsignificantly promoted the Wild-type MC38 tumors growth, whereas GW4064\ninhibited the tumorigenesis and development of MC38 cells (Fig. SS21 A-B). However,\nthe volumes of FXR-knockout MC38 tumor were similar in mice receiving GCA,\nTβMCA or GW4064 treatment compared to their controls, respectively. Our results\nsuggest that inhibition of FXR function is required for GCA-induced tumorigenesis.\nFig. SS21. (A-B) The tumor volumes of C57BL/6 mice (n=6) inoculated with control\n(sg Con) MC38 tumor cells (A) or FXR-knockout (sg Fxr) MC38 tumor cells (B) with\nor without indicated treatment.\n11. GCA has never been shown to be an FXR antagonist. However, earlier studies found\nthat GCA is an FXR agonist (See Figure 5 in PMID: 16230354). In addition, TCA is\na potent FXR agonist (PMID: 23051670). What is the explanation for this stark difference\nbetween the results in this study and the earlier published data? In silico modeling\nstudies should be done to explain why GCA antagonizes FXR while TCA activates FXR.\nR: We truly appreciate the reviewer's insightful comments on our observation. In this\nstudy, we have provided evidence that GCA acted as an inhibitor for the activation of\nFXR. As pointed out by the reviewer, this novel function of GCA deviates from its\nprevious role in increasing FXR activity observed in IBAT-expressed HEK293 cells (J\nBiol Chem. 2005 Dec 23;280(51):42283-9.), which we consider to be one of the\ninnovative aspects of our findings. Of note, a study has revealed that GCA decreased\nthe transcriptional and protein level of FXR in human cholangiocarcinoma cell line\nQBC 939 at a dosage of 800μM (Cancer Invest. 2013 Feb;31(2):111-20.), suggesting a\npotent suppressive function of GCA in regulating the activation of FXR. In addition,\nthis difference of GCA on regulating FXR function may also be attributed to cell lines\nused, concentrations of the compounds, durations of treatments and the presence of\ndifferent co-regulators (co-activators or co-repressors) of FXR. While CA conjugated\nwith glycine or taurine in the liver to form GCA and TCA, difference of the structure-\nfunction relationships between these bile acids are still largely in mystery. Due to the\nspace and time limitation of the current work, we plan to initiate a separate project to\nfurther investigate the structure details on GCA- or TCA-binding properties of FXR,\nwith the findings published in a new article.\n12. As reviewed in PMID: 23603607 and PMID: 28249269, IBABP (FABP6) and\nASBT (SLC10A2), respectively, are required for bile acid (FXR ligands) uptake into\ncells. Do MC38, CT26, HCT116 and SW620 cells express biologically significant\nlevels of IBABP and ASBT? This should be determined by western blots. Tumor cells\nfrequently lose expression of many genes and transporters found in normal\ncolon/intestinal epithelial cells that not required for cell growth.\nR: Following your kind suggestion, we measured the protein level of IBABP (FABP6)\nand ASBT (SLC10A2) by western blotting in MC38, CT26, HCT116 and SW620 CRC\ncells, and observed that these proteins were detectable (Fig. SS22), suggesting these\nCRC tumor cells are suitable for explore the function of bile acids.\nFig. SS22. The protein level of IBABP (FABP6) and ASBT (SLC10A2) was measured\nby western blotting in MC38, CT26, HCT116 and SW620 CRC cells.\n13. I am not aware of any studies in nuclear receptors where an antagonist inhibits RXR\ndimerization to repress transcription. Most studies found that nuclear receptor\nantagonist bind to the ligand-binding site and inhibits the recruitment of transcriptional\nco-activators and/or recruit transcriptional co-repressors. Based on many years of FXR\nstudies, the most likely explanation for GCA antagonist activity is that it displaces FXR\nagonist. The authors need to perform more definitive studies to show the mechanism\nby which GCA suppresses FXR signaling. Since the authors stated that GCA is a novel\nantagonist/inhibitor of FXR with a totally novel inhibition pattern, more structure-based\nevidence should be offered. Does GCA directly bind to FXR? What’s the binding site?\nHow this GCA-FXR binding influence its activity?\nR: We totally agree with this reviewer for his or her expert view of the data related to\nFXR/RXR dimerization presented in Fig. S1H. The experiment discussed above was\ninitially performed to address whether GCA suppressed the function of FXR. A\nprevious study has revealed that FXR agonis, such as GW4064 or WAY362450, could\npromote the recruitment of RXR to FXR to form FXR/RXR dimer (ACS Chem Biol.\ntranscriptional activity (J Biol Chem. 2018 Nov 23;293(47):18180-18191.). Therefore,\nthe status of FXR/RXR dimerization was used as a readout in our experiments.\nCertainly, our results could not explain the detailed mechanism on how GCA prevents\nFXR activity. It could be due to antagonization on the binding site of FXR, or steric\nalterations of FXR that inhibits the interaction to co-regulator, transcriptional co-\nactivators/co-suppressors. As mentioned in Q11, a separate project will be sated out to\nexplore the structure details on FXR when it is binding with different BAs. However,\nin this article, based on the results that GCA inhibited FXR/RXR dimerization and the\nexpression of FXR related genes (I-BABP and SHP), we could at least conclude that\nGCA negatively regulated FXR-RXR dimerization and the transcriptional activity of\nFXR.\n14. The studies showing increase in tumor growth in the xenograph MC38, CT26,\nHCT116 and SW620 cell lines and in the AOM-DSS mouse model should be done\nusing a confirmed FXR antagonist (PMID: 33995909) given the concerns about\nwhether GCA is a bona fide FXR antagonist.\nR: Following your kind comments, we treated mice with glycine-β-muricholic acid (G-\nβ-MCA, 10mg/kg) orally, which was found selectively inhibited activation of the\nintestine FXR rather than the hepatic FXR (Nat Commun. 2015 Dec 15:6:10166.), in\nAOM/DSS-induced CRC model. As shown below, similar to the results of GCA, G-β-\nMCA significantly promoted the growth of CRC, as evidence by a decreased colon\nlength, an increased tumor numbers as well as areas in mice treated with this inhibitor\ncompared to their control (Fig. SS23 A-B), which further validate our results that\ninhibition of FXR in intestine cells is critical for CRC tumorigenesis.\nFig.SS23 (A-B) Wildtype of C57BL/6 mice were treated with glycine-β-muricholic\nacid (G-β-MCA, 10mg/kg) twice a week orally at 7 days after AOM injection and\nfollowed 3 DSS cycles (n=6 per group). Colon length (A), tumor numbers (B, left) and\ntumor areas (B, right) of colons were shown.\n15. Guo and colleagues published in 2009 (PMID: 18981289) that inhibition/loss of\nintestinal FXR results in increase colon tumorigenesis, thus diminishing the novelty of\nthis study. This paper should be cited and discussed.\n16. Others have shown that FXR agonist suppress colon cancer (PMID: 33436792).\nThis paper should be cited and discussed.\n17. A number of papers have shown a role for bile acids in colon cancer (PMID:\n30794774; PMID: 36765047). Notably, the gut microbiota, bile acids, and intestinal\nFXR signaling have been shown to influence colon cancer in mouse models of CRC.\nThese papers and other relevant to the present study should be cited and discussed.\n18. It was reported that activation of FXR inhibited intestinal cancer stem cell\nproliferation and alleviated CRC progression (PMID: 30794774). However, the authors\nfound that FXR did not influence the growth rate of cancer cells. This inconsistent\nconclusion should be discussed.\nR 15-18: We appreciate the reviewer's recommendations and have integrated the\nrelevant literature into our discussion to provide a comprehensive overview of our\nfindings in the context of existing research. Below is the revised discussion section\nincorporating the suggested references: “This difference in endogenous bile acid\ncomposition presents a challenge when studying the physiological effects of GCA in\nmice, as their natural bile acid environment differs significantly from that of humans\n(Biochim Biophys Acta Mol Basis Dis. 2019 May 1;1865(5):895-911. Microbiome.\nhighly amenable to study the mechanisms, function or therapeutic effects of GCA by\nexogenously administered GCA (Biochim Biophys Acta Mol Basis Dis. 2019 May\n1;1865(5):895-911.). Our studies revealed that GCA inhibited the transcriptional\nfunction of the Farnesoid X Receptor (FXR) in both human and colorectal cancer (CRC)\ncells, promoted tumor growth in mice, and acted as a high-risk factor for CRC\ntumorigenesis. These results highlight the relevance of using mouse models to study\nthe therapeutic effects of GCA, despite the differences in bile acid composition between\nspecies.\nThe most important pathway of BA signaling for regulating the development of\nintestinal cancer is through the nuclear receptor FXR, which suppresses colorectal\ntumorigenesis with a tumor cell intrinsic mechanism.21,26,27 In mouse models, loss of\nFXR expression was associated with increased size and number of CRC tumors via\npromoting Wnt signaling or increasing the proliferation of Lgr5+ intestinal stem\ncells.21,27 (PMID: 18981289) Conversely, the FXR agonist GW4064 counteracted\ntumorigenesis (PMID: 30794774, PMID: 33436792). However, knockout of FXR\n(FXR-KO) in CRC cells, such as HT29 cells, reduced proliferation and increased\napoptosis depended on decreased MYC protein (Nat Rev Gastroenterol Hepatol. 2021\nMay;18(5):335-347.). In addition, we did not observe a significant alteration in\nproliferation between FXR-KO and control MC38, CT28, HCT116 and SW620 CRC\ncells, suggesting a diverted function of FXR in regulating the growth of CRC cells with\ndifferent genetic backgrounds.\nGiven the difference in the growth of tumor cells between in culture and in vivo\nobserved in our previous studies, we found that inactivation of FXR significantly\npromoted CRC tumorigeneses in a cell extrinsic mechanism by suppressing the\ninfiltration and antitumor function of CD8+ T cells. IFNg secreted by CD8+ T cells\nsuppressed tumor cells through inhibiting proliferation and inducing apoptosis,\ndifferentiation, migration, and cell-surface antigen expression, which give at least\npartially explanation on the suppressive function of FXR in regulating cell proliferation\nin vivo.\nFurthermore, secondary bile acids like deoxycholic acid (DCA) and lithocholic acid\n(LCA) exacerbate CRC through cytotoxicity and genotoxicity, increasing oxidative\nstress and DNA damage in colonic epithelial cells (Nat Rev Microbiol. 2023\nApr;21(4):236-247.). Gut microbiota plays a critical role by converting primary to\nsecondary BAs, with dysbiosis linked to higher CRC risk (Nature. 2020\nJun;582(7813):566-570. Gut Microbes. 2022 Jan-Dec;14(1):2132903.). For example,\nBSH-expressing Bacteroides is often found in CRC patients with overweight and\ntrigger large amounts of unconjugated bile acids in the colon, leading to the progression\nof CRC (PMID: 36765047). GCA treatment significantly promoted tumor growth in\nour study. The role of gut microbiota in GCA-induced tumorigenesis is indeed a critical\nfield of interest for future research. Nevertheless, based on our findings, we exerted the\ntumor-inhibitory effects of FXR in vivo to the dependency of host conditions. In our\nstudy, it was found that the inactivation of FXR significantly suppressed the infiltration\nand antitumor function of CD8+ T cells by increasing the expression of PD-L1 in tumor\ncells. It has been reported that primary BAs and FXR ligands negatively regulate the\nIL-1β, IL-6 and TNF-α release from LPS-primed macrophages.28 Although increased\ninfiltration of F4/80+ macrophages was also observed in tumors with GCA treatment,\nthe faster growth of GCA-treated tumors was abolished only in CD8+ T cells-depleted,\nbut not in macrophages-depleted, mice. This indicated that impeding the antitumor\nfunction of CD8+ T cells in the TME was essential for GCA-mediated tumor outgrowth.”\n19. What was the method for measuring bile acid concentration in humans and mice?\nWere standards used to precisely quantify the bile acid metabolites?\nR: We apologize for not clearly describing this point in our first version of the\nmanuscript and have provided detailed methods and category for the standards of\nhuman bile acid in the Methods session of the current manuscript. In brief, 33 bile acid\nwere dissolved to 1 mg/mL by appropriate amount of methanol as standard stock\nsolutions and then further diluted to obtain standard solutions containing 0.05, 0.5,\n5, and 50 mg/mL of each bile acid. The supernatant was collected and 70 μl was injected\ninto the LC-MS/MS system for analysis as standards.\n20. Fxr floxed mice were purchased from Cyagen Biosciences, Inc. (cat. no. S-CKO-\n555 04890). To my knowledge, this mouse line has never been published and there is\nno data showing that the intestinal epithelial-specific Fxr knockout (Fxrko) mice lack\nFXR expression in intestinal epithelial cells. These mice should be characterized by\nshowing loss of FXR in intestinal epithelial cells.\n21. What is the source of the villin-Cre transgenic mice?\nR: 20-21. The villin-Cre we used here is C57/BL6 background. As per your kind\nsuggestion, we performed western blotting to explore the expression of FXR in\nintestinal epithelial cells derived from intestine specific Fxr-knockout (Fxr-/-) mice or\ntheir littermate (Fxrwt) and shown that FXR was successfully knocked out in these cells\n(Fig. SS24, Fig.S2L).\nFig.SS24 The protein level of FXR was measured in intestine tissues separated from\nFxr-knockout mice (Fxr-/-) and their litter mates (Fxrwt) (n= 3 per group).\n22. The Fxr knockout efficiency and tissue specificity should be measured in all mouse\nmodels and cancer cell lines.\nR: The reviewer’s concern is important. This question is related to Q9, please refer to\nour response to question 9.\n23. How were the bile acids and GCA concentrations quantified? More details are\nneeded on how GCA was measured and quantified.\nR: We apologize for not providing detailed methods for the quantification of bile acids,\nthis question is related to Q19, please refer to our response to question 19.\n24. Figure S1A, B: Describe the meaning of M, N, and T in the legend.\nR: M, N and T stand for Metastasis, Normal tissue and Tumor tissues, and we have\nprovided related information in our revised manuscript.\n25. Figure S4A: Confirm the dosage GCA as 400 mg/kg p.o. Other GCA concentrations\nin Figure S3 is 400 ug/kg. -\nR: Thank you for pointing out this error. We have reedited this in our revised manuscript.\nThe responses to the comments point by point:\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nColorectal cancer (CRC) is a highly prevalent tumor type that is generally refractory to immunotherapy. Thus, elucidating\nmechanisms of CRC resistance to immunotherapy is of high importance. In this study, Zhao et al make use of a comprehensive\nrange of clinical data, in vivo models, and in vitro cell biology assays to identify bile acids as potential regulators of CRC sensitivity\nto T cell attack. Mechanistically, this is proposed to occur through the bile acid nuclear receptor Fxr, which regulates expression\nof SOX14 and the palmitoyltransferase DHHC9 to control palmitoylation and stability of the immune checkpoint ligand PD-L1.\nOverall, the authors responded satisfactorily to my suggestions from the initial review, with several new experiments and analyses\nprovided to support their claims. However, I have some remaining suggestions that should be addressed prior to publication:\nA: We appreciate the reviewer’s acknowledgment of our additional experiments and analyses, and we are pleased that they find\nour revisions satisfactory overall. We carefully reviewed the remaining suggestions and have addressed each point.\n1. In Figure 1:\n• Units of the heatmap in panel A is not defined (z-scores?)\n• Panels B/C: y-axis label is misspelled (should be ‘concentration’)\n• Panels B/C: concentration units are not defined either in the figure or in the caption\n• Panels B/C: if the revised GCA concentrations shown are simply transformed from the original log2 values (now linear), the\nvalues do not seem to match up. For example, in panel B of the original manuscript, the range for stage I-II tumors is roughly 6.3-\n6.8 in log2 units, which corresponds to ~ 79-111 linear units as shown in the revised manuscript. However, while the range for\nstage III-IV tumors in the original manuscript of ~ 6.5-6.85 should correspond to ~ 91-115 in linear units, the numbers shown in\nthe revised manuscript for this group are considerably higher, lending the impression of much larger differences between tumor\nstages. The data for panel C are similarly discordant between manuscript versions (upper range of M0 group and the entire range\nof M1 is too high in revised version). The authors should explain this discrepancy and check the presented data for accuracy.\n• Panels D-E: authors should include information on the cutoff used for high vs low GCA and the sample size should be\nspecified for each group, either in the figures or in legends. Same suggestion applies to KM curves in supplementary figures.\nA: We thank the reviewer for the careful evaluation and insightful comments.\nPanel A (Heatmap):\nWe apologize for not defining the units in the heatmap. The heatmap in Panel A represents z-scores. This has now been clarified\nin both the figure legend and the revised manuscript text.\nPanels B/C:\nWe sincerely apologize for the confusion caused by the discrepancy in values of serum GCA concentration between the original\nand revised versions of Panels B and C. In our original manuscript, the log2 values on the y-axis reflected relative expression levels\nof serum GCA in CRC patients compared to healthy individuals. These were not absolute concentrations.\nIn the revised version, Panels B and C now display the absolute serum GCA concentrations (in nM) without transformation. We\nhave re-verified the dataset to ensure the accuracy of these values. The apparent mismatch between transformed and linear values\nwas due to the change in data representation, not a computational error. To avoid further confusion, we have updated the y-axis\nlabels to correctly read “GCA concentration (nM)” and corrected the spelling of “concentration” in both Panels B and C.\nPanels D-E and Kaplan-Meier Curves\nWe appreciate the reviewer’s suggestion. The cutoff for high vs. low GCA groups was determined based on the mean value of the\ndataset. We have now included this information in the figure legends for Panels D-E and all Kaplan–Meier curves in revised Figures.\nAll changes have been incorporated into the revised manuscript.\n2. Association of serum GCA concentrations with patient survival:\nIn my previous comments, I made the following suggestion: It would be interesting/informative to compare BA concentrations in\npatients with liver vs non-liver metastases and include liver metastasis specifically as a covariate in survival analysis (as distinct\nfrom other metastatic sites)\nThe authors have evaluated a larger (n=308) CRC cohort in an effort to address this question but concluded that the number of\npatients with liver metastasis (35 with liver only) is too small to enable robust conclusions. I agree that the small number of liver\nmets in this cohort is statistically limiting and makes it difficult to draw conclusions about the liver met+ patient segment. However,\nthe authors could additionally evaluate the relationship between PFS/OS and serum BA in patients without metastasis—if a PFS/OS\nassociation is observed in patients with earlier stage disease, it would increase confidence that the clinical observations are\nindependent of liver metastasis.\nA: We thank the reviewer for the insightful follow-up suggestion. In response, we have performed additional survival analyses\nfocusing on colorectal cancer (CRC) patients with documented disease-free survival (DFS) and no evidence of liver metastases (n\n= 247) to assess the association between serum GCA concentrations and clinical outcomes. Kaplan–Meier analyses demonstrated\nthat higher serum GCA concentrations remained significantly associated with both shorter disease-free survival (DFS) and overall\nsurvival (OS) in this subgroup. These results reinforce our original observation that elevated serum GCA levels are linked to poor\nclinical outcomes in CRC and suggest that this association is independent of the presence of liver metastases (Fig.SS1, original\nFig.S1G-H).\nFig. SS1. (A, B) Disease-free survival (A, DFS) and overall survival (B, OS) curves for 247 colorectal cancer (CRC) patients\nwithout liver metastases in cohort II. Patients were stratified based on the mean serum glycocholic acid (GCA) concentration as\nthe cut-off value.\nReviewer #2 (Remarks to the Author):\nAfter reviewing the revised manuscript, I am pleased to note that the authors have effectively addressed all the concerns raised.\nThe revisions have significantly enhanced the quality of the paper. I do not have any further questions or concerns at this time.\nA: We sincerely thank the reviewer for their thoughtful feedback and kind words. We are grateful for the constructive suggestions\nthroughout the review process, which have greatly improved the quality and clarity of our manuscript.\nReviewer #3 (Remarks to the Author):\nI appreciate the revisions to the manuscript resubmitted by the authors. With new experiments they have addressed many of\nmy concerns. Nevertheless, I still have the following concerns:\nA: We thank the reviewer for acknowledging the revisions and additional experiments we have performed. Below, we address the\nremaining concerns point by point.\n1. This manuscript demonstrates limited novelty, particularly regarding the clinical role of GW4064 in immunotherapy and the\nregulatory mechanisms of PD-L1.\nA: We appreciate the reviewer’s concern regarding the novelty of our findings. While it has been previously reported that FXR\nagonist GW4064 enhances anti-PD-L1 immunotherapy efficacy in CRC (Lu et al., Oncoimmunology, 2023), our study offers\nadditional mechanistic and translational insights that we believe add novel value to the field.\nBile acids (BAs) play a dual role in regulating tumorigenesis, and different bile acid species exert distinct effects. Recent studies\nhave provided emerging evidence that several BAs, including deoxycholic acid (DCA) and lithocholic acid (LCA), are critical for\nshaping tumor microenvironment to induce tumor evasion (Cong et al., Immunity, 2024; Varanasi et al., Science, 2025). Therefore,\ndistinguishing among BA species and elucidating their mechanism of regulating tumor-TME crosstalk is essential.\nIn our study, we identify GCA not only as a pre-diagnostic serum biomarker but also as a functional driver of colorectal\ntumorigenesis, acting through the SOX14/DHHC9/PD-L1 axis. We further demonstrate that GCA promotes PD-L1 stability via\nFXR inhibition and downstream transcriptional activation of SOX14 and DHHC9, providing a previously unrecognized\nmechanistic link between FXR signaling and PD-L1 palmitoylation.\nMoreover, we show that combined treatment with GW4064 and anti-PD-1 antibody effectively suppresses tumor growth even in\nanti-PD-1–resistant CRC models and in mice with elevated GCA levels. These findings not only support and extend prior\nobservations but also broaden the therapeutic applicability of FXR agonist-based immunotherapy, particularly in GCA-enriched\nCRC subsets. We believe this mechanistic and translational depth offers meaningful innovation beyond previously published work.\n2. Representative orthotopic tumor images should be presented to support the efficacy of GCA treatment on indicated groups in\nFig. S15.\nA: Thank you for this helpful suggestion. We believe there may have been a reference error, as Figure S15 was not included in our\nrevised manuscript. We assume the reviewer intended to refer to Figures S1–5, which present data on the efficacy of GCA treatment.\nIn response, we have now included representative tumor images from the indicated experimental groups in the revised Figure S1-\n5, to visually support the quantitative tumor burden data. We believe this addition provides stronger visual evidence of treatment\nefficacy. These images were integrated in the in Supplementary Figure 13 (Fig.S13) of the revised manuscript.\n3. The quality of the figures requires further improvement. For example, scale bars are absent from the immunofluorescence images\nin Fig. 5B. Molecular weight markers are not labeled on each Western blot result.\nA: We appreciate the reviewer’s comments and have made the following revisions to improve figure quality throughout the\nmanuscript. Scale bars have been added to “Merge” panel of Fig. 5B. Molecular weight markers have been labeled on each blot to\nindicate protein size.\nReviewer #4 (Remarks to the Author):\nTHe response to the reviewers are incomplete.\nQ1&2. There is no evidence that GCA as an FXR antagonist as established in many earlier studies. This critical issue is not\naddressed. GCA and other derived bile acids in serum and tumor tissues should be measured after GCA administration in vivo.\nWhat are the median concentrations of GCA in cohort 1 and cohort 2? Is it above 100 µM or below 100 µM? As shown in figure\nSS10C, there was no dose effect on FXR inhibition when GCA concentration was 100 µM or more.\nA: We sincerely thank the reviewer for these insightful and detailed comments and acknowledge the reviewer’s important point\nregarding the mechanistic classification of GCA.\n1. On GCA as an FXR antagonist:\nWe acknowledge the reviewer’s concern that the classification of GCA as an FXR antagonist remains a matter of ongoing\ninvestigation. While previous reports have demonstrated that GCA can inhibit FXR activity in human cancer cells (Dai et al.,\nJournal of Hematology & Oncology, 2011), there is limited direct evidence establishing this function at physiological\nconcentrations in vivo. Accordingly, we do not assert that GCA acts as a classical pharmacological antagonist. Instead, our data\nsuggests that GCA exposure is associated with reduced FXR activity in CRC, as indicated by downregulation of canonical FXR\ntarget genes (e.g., Shp, Fgf15) and concomitant increases in PD-L1 expression.\n2. On bile acid concentrations in vivo (serum and tumor):\nRegarding the in vivo GCA treatment, we agree that endogenous and systemic bile acid levels are critical to interpreting the data.\nAs suggested, we measured the concentrations of GCA and other bile acids, specifically TDCA, TCA, TCDCA, GCDCA, and\nGDCA, which are significantly elevated in the serum of CRC patients compared to healthy individuals (Fig.1A), following GCA\nadministration (400 mg/kg) in a subcutaneous MC38 tumor model. Consistent with previous reports, serum GCA levels were barely\ndetectable in healthy mice or in tumor-bearing mice without GCA treatment. In contrast, several serum levels of other bile acids\nwere elevated in MC38 tumor-bearing mice relative to healthy controls. Of note, a detectable accumulation of serum GCA\napproximately 150 nM was observed in serum of mice receiving GCA treatment. In tumor tissues, GCA levels remained low in\nmice untreated, while the concentration was measurable, with a concentration of approximately 82 nmol/g in GCA-treated tumors\n(Fig.SS2A, B, original Fig.S3C, D).\nAs shown in Figure SS10C of our previous response, we treated cultured cells with 1 mL of complete DMEM containing 100 nM\n(100 nmol/L) GCA. We have carefully reviewed our data and apologize for the earlier labeling error, where \"100 μM\" (equivalent\nto 100 nmol/mL) was mistakenly used instead of the correct \"100 nM\" (100 nmol/L), due to a unit conversion issue. At and above\n100 nM GCA-treatment in vitro, we observed effective FXR inhibition, evidenced by reduced FXRE-luciferase reporter activity\nin treated cells compared to untreated controls (Fig.S2B).\nImportantly, the median GCA concentration in mouse serum after GCA treatment (157.48 nM) falls within the range that has been\nshown to inhibit FXR signaling under experimental conditions (100-200nM). Furthermore, the median serum GCA concentrations\nin our human cohorts were approximately 96.4 nM in Cohort 1 and 96.7 nM in Cohort 2. These values are comparable to or slightly\nlower than those observed in GCA-treated mice and in vitro cultures, supporting the physiological relevance of our experimental\nmodels.\nFig. SS2. (A, B) The serum (A) or tumoral (B) concentration of indicated BAs in healthy mice or mice inoculated with MC38 cells\nfollowing indicated GCA treatment (400mg/kg, n=6).\n3. Although there is sufficient data showing that FXR signaling was suppressed in mice treated with 400 mg/kg GCA, it is unknown\nwhether the serum levels of GCA obtained under this treatment is within the range of that found in humans, which is very important\nto determine the translational value of this study.\nA: We appreciate the reviewer’s important point regarding the translational relevance of the GCA dosing used in our mouse model.\nAs outlined above, we have now quantified serum GCA concentrations in mice treated with 400 mg/kg GCA. The median GCA\nlevel was approximately 157.48 nM, which is slightly higher than the median serum GCA concentrations (~100nM) observed in\nCRC patients.\nThus, the serum GCA levels achieved in our mouse model are not only comparable to those in human CRC patients but also fall\nwithin the same order of magnitude. This concordance supports the translational relevance of our dosing regimen. Importantly, the\nobserved suppression of FXR signaling and associated immunological changes in GCA-treated mice occurred at physiologically\nrelevant concentrations, further underscoring the clinical significance of our findings.\n8. To determine if Fxr-null mice are more resistant than WT mice to anti-PD-L1 therapy, four groups of mice are needed, i.e. WT\nvehicle, WT anti-PD-L1, Fxr null vehicle, Fxr null anti-PD-L1. In addition to the comparisons between WT and Fxr null mice,\nlike the authors had done in Figure SS19, the comparisons between vehicle and anti-PD-L1 groups are needed to evaluate the effect of\nanti-PD-L1 treatment. In fact, if you compare the data in Figure SS18 and Figure SS19, there was almost no improvement in tumor\nnumber and tumor area between FXR WT mock group and FXR WT anti-PD-L1 group, suggesting that WT mice were almost\ncompletely resistant to anti-PD-L1 therapy.\nA: We thank the reviewer for the thoughtful and constructive comment. We fully agree that evaluating the effect of anti-PD-L1\ntherapy requires the inclusion of all four groups: Fxrwt + IgG, Fxrwt + anti-PD-L1, Fxr-/- + IgG, and Fxr-/- + anti-PD-L1, to allow\ndirect comparisons both within and between genotypes.\nIn our study, we utilized Fxr-knockout (Fxr-/-) and their littermate wild-type (Fxrwt) controls in the AOM/DSS-induced CRC model\nto assess the response to anti-PD-L1 treatment. While the comparisons of tumor number and tumor area in mice between Fxrwt\nmock group of Figure SS18 and Fxrwt anti-PD-1α group of Figure SS19 did not appear significantly different in our previous\nresponses, it is important to note that these data were derived from independent experiments, and minor discrepancies could be due\nto biological variability between mouse batches or age ranges.\nIn our repeated experiments using four groups, we observed that anti-PD-L1 treatment at dosage of 10mg/kg significantly reduced\ntumor burden in Fxrwt mice, indicating a robust response to therapy in the WT background. More importantly, anti-PD-L1 therapy\nin Fxr-/- mice resulted in marked acceleration in both tumor number and tumor area, as well as shorter colon length, compared to\nFxrwt mice receiving the same treatment (Fig.SS3, original Fig.S7J). This reduction of therapeutic efficacy in Fxr-deficient mice\nunderscores our central conclusion: Fxr-deficiency inhibits the response of the tumor microenvironment to PD-1/PD-L1 immune\ncheckpoint blockade.\nFig.SS3. Fxr-knockout mice (Fxr-/-) and their litter mates (Fxrwt) were injected with anti-PD-L1 antibody (10mg/kg) or IgG (i.g.)\nduring AOM/DSS treatment (n=6 per group). Colon length (left), tumor numbers (middle) and tumor areas (right) of colons were\nshown.\n21. This question is about the source of the villin-cre mice, not the background of this mouse strain. Is this mouse strain from the\nJackson Lab, or other sources? This should be clarified in the manuscript.\nA: We apologize for the omission of this detail. In the revised manuscript (Materials and Methods), we have clarified that:\nVillin-Cre (#004586) transgenic mice were purchased from the Jackson Laboratory (Bar Harbor, ME, USA) to create conditional\nknockout mice and silenced the expression of Fxr in intestinal epithelial cells.\nThe responses to the comments point by point:\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThe authors have effectively addressed the concerns previously raised. I have no further questions or suggestions at this time.\nA: We sincerely thank the reviewer for their positive evaluation of our revisions. We are pleased that our additional experiments\nand analyses have satisfactorily addressed the previous concerns. We greatly appreciate the reviewer’s constructive feedback\nthroughout the review process, which has helped us improve the quality and clarity of the manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have effectively addressed the concerns previously raised. I have no further questions or suggestions at this time.", "reviewer_4": "The responses to the comments point by point:\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author): with expertise in cancer immunology,\ncolorectal cancer\nColorectal cancer (CRC) is a highly prevalent tumor type that is generally refractory to\nimmunotherapy. Thus, elucidating mechanisms of CRC resistance to immunotherapy is\nof high importance. In this study, Zhao et al make use of a comprehensive range of\nclinical data, in vivo models, and in vitro cell biology assays to identify bile acids as\npotential regulators of CRC sensitivity to T cell attack. Mechanistically, this is proposed\nto occur through the bile acid nuclear receptor Fxr, which regulates expression of\nSOX14 and the palmitoyltransferase DHHC9 to control palmitoylation and stability of\nthe immune checkpoint ligand PD-L1. Overall, the experiments appear to have been\ngenerally well-executed (although the methodological details are not always clear, nor\nis it clear how often experiments were reproduced). The connection between bile-\nacid/Fxr-dependent regulation of tumor PD-L1 expression is not well understood in the\ncontext of CRC, but a similar set of observations were recently published for\nhepatocellular carcinoma (Gong et al, Front Oncol, 2021).\nOverall, the data are interesting and shed light on a mechanism of PD-L1 regulation\nthat is not well understood. However, I have several concerns that should be addressed\nprior to publication.\nWe thank the reviewer for his/her positive comments on our paper and have addressed\nall the questions raised by the reviewer as outlined below.\nMajor concerns:\n1. Fig. 1b/c: GCA concentrations are noted on the y-axis as ‘relative concentration’, but\nwhat are they relative to? The median differences between early and late-stage disease\n(panel B) or localized vs metastatic disease (panel C) may be statistically significant\nbut are less than 0.1 in log2 space, which equates to a <7% difference. Are this\ndifference considered biologically or clinically meaningful? Is it possible to estimate\nbile acid concentrations in tumor tissue?\nR: We appreciate the reviewer’s careful reading of our manuscript and apologize for\nnot clearly describing this point in our first version of the manuscript and any confusion\nit might have caused. It is our mistake, we have deleted “relative” in the revised\nmanuscript; we also re-analyzed the serum GCA levels by using GCA concentration\nand showed in Fig. 1B, C of revised manusript.\nAs pointed out by the reviewer, the differences of GCA concentration in CRC\npatients with early- and late-stage or localized vs. metastatic disease CRC appears\nmarginal. Similar observations have been reported in other study, where serum GCA\nconcentration showed only marginal changes between early- and late-stage patients\nwith non-small cell lung cancer (NSCLC) (J Cancer Res Clin Oncol. 2023\nDec;149(19):17285-17296). In our study, we only recruit 80 CRC patients (Cohort 1)\ninitially; we have added another cohort of CRC patients (308 patients in total, Cohort\n2) in our revised manuscript. Our new data also demonstrated that high serum GCA\nconcentration not only was positively related with advanced tumor stage but also\npredict poor overall survival and disease-free survival. We have updated these results\nin our manuscript (Fig. SS1A-D, original Figure Fig. S1C-F).\nBile acids are released into the small intestine in response to cholecystokinin\nstimulus upon meal ingestion. In the gut lumen, bile acids facilitate transport, digestion\nand absorption of nutrients, particularly lipids and lipid-soluble vitamins. Up to 95 %\nof bile acids are actively re-absorbed in the terminal ileum and transported back to the\nliver and enter the systemic circulation. it has been suggested that blood levels of bile\nacids could be more useful to investigate associations with cancer risk than fecal bile\nacids, and small case-control studies have found increased serum bile acids levels in\npatients with colon cancer. We have previously evaluated the concentrations of bile acid\n(BA) concentrations in tumor tissue from small samples, the concentrations were very\nlow, thus we did not show these data and chose the blood levels of bile acids for further\nstudy.\nFig. SS1. (A) Serum GCA levels in stages I-II (n=117) and III-IV patients (n=191) with\nCRC (n=308, Cohort 2). (B) Serum GCA levels in patients with CRC patients with\nmetastatic disease (M1, n=59) or without metastatic disease (M0, n=249). (C and D)\nKaplan-Meier analyses with log-rank test were used to evaluate Disease-free survival\n(C) and overall survival (D) of 308 CRC patients based on their serum GCA levels\nusing the median GCA levels as cut-off value.\n2. Fig. 1d/e and Fig. S1a/b: elevated circulating bile acid concentrations are typically\nassociated with hepatic dysfunction (resulting in impaired clearance of bile acids from\nportal blood). This raises the question of whether the increased GCA concentrations\nobserved in patients with metastatic CRC are due to liver metastases impairing hepatic\nfunction (as opposed to a causative role of GCA in promoting CRC progression, as\nimplied in this manuscript). It would be interesting/informative to compare BA\nconcentrations in patients with liver vs non-liver metastases and include liver metastasis\nspecifically as a covariate in survival analysis (as distinct from other metastatic sites).\nR: We appreciate the reviewer's insightful question regarding the potential impact of\nliver metastases on circulating bile acid concentrations and their association with CRC\nprogression. In our initial study, we only recruit 80 cancer patients and only few patients\nwith liver metastasis, thus we did not compare BA concentrations in patients with liver\nvs non-liver metastases and include liver metastasis. In the new 308 CRC patients’\ncohort, 39 patients were diagnosed with liver metastases (35 patients with only liver\nmetastasis and 4 patients had liver and other organ metastasis). We found that the mean\nserum GCA concentrations, were significantly increased in the CRC patients with liver-\nmetastases compared to those without liver-metastasis (Fig. SS2A-D). Kaplan-Meier\nsurvival analyses with log-rank test showed that no significant difference was found\nbetween high and low GCA concentration patients’ overall survival who had only liver\nmetastasis, although there were poor trend for high GCA level’s patients (Fig. SS2A-\nD). This might be caused by small samples. Whether high GCA could affect the liver\nmetastasis and the specific mechanism need more detailed explorations, we will\nconduct another study in future. Thus, we did not supplement these results in our revised\nmanuscript.\nFig. SS2. (A). Different GCA concentrations in patients with all 39-liver vs non-liver\nmetastases(n=269) among CRC patients of Cohort 2. (B) Different GCA concentrations\nin patients with only liver(n=35) vs non-liver metastases(n=269) among CRC patients\nof Cohort 2. (C and D) Kaplan-Meier analyses with log-rank test were used to evaluate\noverall survival in patients with liver metastasis and other metastasis (C) and in patients\nwith only liver metastasis (D) among Cohort 2’s CRC patients.\n3. Fig. 1f/h/i (DSS-AOM data): the DSS-AOM model data are intriguing, but somewhat\nchallenging to interpret. The DSS-AOM regimen models colitis-associated CRC, which\nfollows a distinct process of pathogenesis compared to the much more common\nsporadic CRCs (which are the principal focus of this manuscript). Most importantly,\ntumorigenesis in this system relies on repeated rounds of DSS-driven colitis, and tumor\nburden is associated with the severity of DSS-driven tissue damage. Because the\nauthors appear to have used mice with constitutive loss of Fxr in intestinal epithelial\ncells (Fxr.flox crossed with Villin-Cre), it is not possible based on these data to\ndetermine whether Fxr function is associated with alterations in tumorigenesis, colitis,\nor both. One potential alternative is to use mice with inducible Villin-controlled Cre\n(Vill. Cre. ERT2) so that Fxr can be deleted in colon epithelial cells after the final round\nof DSS (to exclude effects on colitis). However, the challenge of interpreting colitis-\nassociated CRC data in the context of a paper that's focused on sporadic CRC remains.\nIf the authors' intent is simply to generate data using an orthotopic model of CRC,\nalternative systems could include direct implantation of CRC cell lines into colon\nmucosa, or delivery of CRC cells to the liver via hydrodynamic tail vein injection.\nR: The reviewer’s concern is thoughtful. Following your kind suggestion, we generated\nan orthotopic mice model of CRC by implanting MC38 tumors into colon mucosa. This\napproach provides a more relevant model for studying sporadic CRC and allows us to\nfocus specifically on the role of FXR in tumorigenesis without the confounding effects\nof colitis associated with the DSS-AOM model. In brief, wild-type 10-12 weeks old\nC57BL/6 mice were examined by endoscopy to ensure the colonic mucosa was healthy\nprior to implantation after anesthesia. For tumor cell implantation, 0.5×106 Fxr-\nknockout (sg FXR) MC38 cells or control cells (sg CON) diluted in 50 μL of PBS were\ninjected very slowly towards the lumen of lower mid and distal colon ~30 mm from the\nanal verge to induce tumor growth by using endoscopic injection. Consistently, the\ngrowth of Fxr-KO MC38 tumors by using this orthotopic mice model of CRC was\nsignificantly increased compared to that of control tumors (Fig. SS3A, original Figure\nFig. S3A). In addition, a worse overall survival was observed in mice with Fxr-KO\nMC38 tumors compared to those with controls (Fig. SS3B, original Figure Fig. S3A),\nwhich further confirmed our conclusion that FXR inhibits CRC tumorigenesis.\nFig. SS3. (A-B) 0.5×106 indicated MC38 cells were endoscopy-guided injected into the\nlumen of lower mid and distal colon ~30 mm from the anal verge of C57BL/6J mice\n(n=5). (A)Tumor volumes and (B)mortality within the observation period of the\nindicated mice were shown. All the experiments were repeated three times. The results\nare presented as the mean ± SD.\n4. Treatment with GCA apparently reduces activity of FXRE significantly in the\nluciferase reporter system (cell line assays). What is the source of the basal reporter\nsignal? Is this an overexpression artifact, or are the cells exposed to bile acids in culture\nmedium (possibly via serum)?\nR: We understand the reviewer’s point. In our study, CRC cells were cultured in DMEM\nsupplemented with 10% fetal bovine serum (FBS). To investigate whether serum\ncontributes to the basal activity of FXR signaling, we cultured MC38 cells transfected\nwith FXRE reporter system in DMEM supplemented with or without 10% FBS and\nobserved that luciferase activity was significantly upregulated in cells with FBS\ncompared to that in plain DMED (Fig. SS4). Our experiment provided clear evidence\nthat the basal FXR signaling activity in our luciferase assays is due to the presence of\nFBS in the culture medium, which was crucial for interpreting the effects of GCA on\nFXR activity.\nFig. SS4. MC38 cells transfected with reporter plasmids linked to an FXR-responsive\nelement (FXRE-Luc) were cultured in plain DMEM for 24h, followed cultured with\n10% FBS DMEM (Normal) or plain DMEM (Plain) for another 24h. Luciferase activity\nof MC38 cells was shown (n=5).\n5. Figure 2I: The authors report that treatment of MC38 cells with GCA significantly\ninduced PDL1 expression at the protein level, but not at the mRNA level. PDL1 is well-\nknown to be an interferon-inducible gene, and it is noteworthy that several other\nproteins identified by the authors as induced by GCA are also known to be interferon-\ninducible, including Ifi204, B2m, Mndal, and H2-M3. Is this merely a coincidence, or\nis it possible that GCA-treatment is inducing an autocrine type I IFN response?\nHave\nthe authors performed an unbiased transcriptional analysis (e.g. bulk RNAseq) to\ndetermine if such an interferon-like response is indeed occurring?\nR: This is a thoughtful question. In our study, we made an intriguing observation that\nGCA did not affect the expression of interferon-stimulated genes in vitro (original\nFigure Fig.S5H). Of note, the mRNA level of PD-L1 was not altered in cells treated\nwith GCA, suggesting that GCA-mediated upregulation of PD-L1 is not dependent on\ninterferon signaling (original Figure Fig.S6E). To further validate our results, we\nmeasured the transcriptional level of type I interferon (IFNα and IFNβ), transcriptional\nfactors of IFN, including STAT1, STAT2, IRF1, IRF2, IRF5 and interferon-stimulated\ngene 15 (ISG15), essential for cellular IFN signaling transduction in GCA- or GW4064-\ntreated MC38 and HCT116 CRC cells. However, functionally suppression or activation\nof FXR signaling in CRC cells did not alter the mRNA level of IFNs or ISGs (Fig.SS5).\nOur data suggested that GCA does not affect IFN-response in vitro.\nFig. SS5.qRT-PCR measurement of the expression of indicated mRNA in MC38 (left)\nand HCT116 (right) cells treated with GCA or GW4064 for 24h. (B) GSEA analysis of\ntype I IFN response in MC38 cells treated with or without GCA for 24 h based on RNA-\nsequencing.\n6. Fig. S4H/I: the apparent dependency of Fxr-driven tumor growth effects on tumor\nPDL1 expression is interesting and important to the overall message of the paper. To\nexclude the possibility that this phenotype is driven by clone-to-clone differences, can\nthis observation be further supported by blocking PDL1 in tumors from wild type cells\n(e.g. with anti-PD-L1 blocking antibody) in the presence or absence of Fxr ligands?\nR: Follow your kind suggesting, we used a subcutaneous wild-type MC38 or CT26\ntumor model to address this question. In brief, we subcutaneously injected 0.5×106\nMC38 or CT26 cells diluted in 100 μL of PBS in the right flank of C57BL/6 or BALB/c\nmice to induce tumor growth, respectively. Mice were treated with GCA (400 mg/kg\np.o.) and/or anti-PD-L1 (10mg/kg and 100mg/kg) twice a week at day 10 post injection.\nSimilarly, the results showed that functional impairment of FXR by GCA in CRC cells\nsignificantly promoted the growth of tumors. While low dose anti-PD-L1 therapy\n(10mg/kg), which was sufficiently prevent the growth of MC38 and CT26 tumors in\nmice under normal condition, did not inhibit the development of tumors in mice with\nGCA (Fig. SS6 A-B, original Fig.S7H-I), suggesting that 50mg/kg of anti-PD-L1\nantibody might not fully neutralizing PD-L1 in tumor microenvironment (TME). Of\nnote, blocking PD-L1/PD-1-signaling by treatment of high dose of anti-PD-L1\n(100mg/kg) was sufficiently reverted GCA-induced tumorigenesis (Fig. SS4 A-B),\nwhich further confirming our results that PD-L1 expression in tumors was critical for\nFXR-mediated tumor suppression.\nFig. SS6. (A-B) C57BL/6 (n=6) or BALB/c mice inoculated with MC38 (A) or CT26\n(B) tumor cells were treated with GCA (o.p) twice a week and/or with anti-PD-L1\nantibody or IgG 7 days post injection. The tumor volumes (left) and weights (right) are\nshown.\n7. Figure 5: the authors propose that the Fxr-regulated SOX14/DHH-C9/PD-L1 axis is\ninvolved in resistance of MSI-H/dMMR CRC patients to anti-PD-1 therapy in the clinic.\nThis conclusion seems potentially odd—if we assume that tumor-expressed PD-L1 acts\nby engaging PD-1 on T cells, and if the anti-PD-1 antibody (the specific identity of the\ntreatment regimen should be stated in methods) was dosed adequately to fully inhibit\nPD-1, then why would increase expression of PD-L1 on tumor cells have any bearing\non anti-PD-1 response? Is there any reason to believe that these patients did NOT\nreceive a dose of anti-PD-1 sufficient for full target coverage?\nR: We appreciate this insightful question Although ICB therapy has durable effects\ntoward a subset of microsatellite instability-high (MSI-H) CRCs, accounting for ~15%\nof all CRC cases, only 30-50% of these patients can benefit from this therapy. Anti-PD-\n1 antibodies work by blocking the interaction between PD-1 on T cells and PD-L1\nderived from cancer cells or cells in tumor microenvironments (TME), including\nmacrophages, MDSCs and fibroblast, thereby enhancing anti-tumor response of CD8+\nT cells (J Hematol Oncol. 2021 Jan 7;14(1):10.). Due to intertumoral heterogeneity in\nadvanced cancer, tumors or other cells may have heterogeneous expression of PD-L1\n(J Thorac Dis. 2020 May; 12(5): 1770–1775.). Accordingly, the identification of key\nmarkers in regulating resistance to PD-L1 therapy is necessary to combat an\nimmunosuppressive TME in CRC. In this study, we discovered that serum GCA/ FXR\nsignaling could regulate the aberrant expression of SOX14 or DHHC-9, which\npersistently induced PD-L1 expression in tumor microenvironments, then affecting the\nresponse to anti-PD-1 therapy. Our findings indicate that combination of targeting the\nFXR signaling pathway is a potential strategy for alleviating an immunosuppressive\nTME and enhancing the sensitivity to anti-PDL-1 treatment in CRC.\n8. Figure 6 (and various associated statements in text): along a similar line, the authors\npropose that inhibition of SOX14 or DHHC9 expression in tumors causes an improved\nanti-tumor immune response and improved tumor control, presumably via reduced PD-\nL1 expression. While this makes sense under untreated conditions, they argue that this\nalso applies during treatment with anti-PD-1. Similar to the clinical setting, unless PD-\n1 blockade is substantially incomplete, it is difficult to understand why alterations in\ntumor PD-L1 expression would enhance sensitivity to PD-1 blockade. The data instead\nraise the possibility that tumor-intrinsic SOX14/DHHC9 deficiency can act at least\npartially in a PD-L1-independent fashion to increase tumor sensitivity to immune\nsurveillance and anti-PD1 treatment.\nR: The reviewer’s comments is thoughtful. As mentioned in response of question 7,\ndosage, drug delivery, tumor microenvironment factors, the course of treatment might\naffect clinical benefits of anti-PD-1 treatment. To investigate whether the dosage of\nanti-PD-1 antibody (100mg/kg) we used could achieve full inhibition, mice\nsubcutaneous injected of MC38 cells were treated with anti-PD-1 (50mg/kg, 100mg/kg\nand 200mg/kg) twice a week starting at day 10 post injection. Our results showed that\nanti-PD-1 therapy inhibits MC38 tumorigenesis in a dose-dependent manner (Fig. SS7).\nOf note, CRC tumor growth was abolished in mice receiving 200mg/kg of anti-PD-1\nantibody treatment (Fig. SS7), suggesting that the dosage used in our in vivo\nexperiments incompletely in blocking PD-1 on T cells.\nFig. SS7 (A) C57BL/6 (n=6) inoculated with MC38 tumor cells were treated with\nindicated dose of anti-PD-1 antibody or IgG 7 days post injection. The tumor volumes\n(left) and weights (right) are shown.\n9. The MC38 and CT26 models used extensively in this manuscript best represent the\ninflamed and potentially immunotherapy-responsive MSI/dMMR subset of CRC.\nHave the authors explored whether manipulation of the Fxr pathway impacts immune\nresponses to 'colder' tumor models that are more representative of sporadic\nMSS/pMMR CRCs (which constitute the vast majority of CRC and the bulk of unmet\nclinical need). For example, this could include engineered colon organoids (e.g.\nTaraborelli et al, Nat Comm, 2023).\nR: We appreciate the reviewer’s suggestion. CT26 is often used as an MSS CRC model\ndue to the lack of mutations in MMR genes MLH1 and MLH2 and is considered to be\na 'cold' tumor model with lower immunogenicity and less responsiveness to\nimmunotherapy. (BMC Genomics. 2014 Mar 13;15(1):190. Cancer Cell. 2023 Jan\n9;41(1):196-209.e5.). In fact, mouse CRC cell lines CT26 and MC-38 exhibited high-\naffinity MHC-I-binding neoantigens, indicating that the tumors were susceptible to T-\ncell-mediated adaptive immunosurveillance (Nature. 2018 Feb 22;554(7693):538-543.)\nOur present study and other separate studies also observed that anti-PD-1 monotherapy\npartially limited the outgrowth of CT26 tumors (BMC Cancer. 2021 Nov 13;21(1):1222.\nJ Exp Clin Cancer Res. 2021 Sep 13;40(1):288.). Moreover, in our study we have also\nobserved a tumor-promoting role of GCA in both MSS (CT26) and MSI (MC38) CRC\ncells. To further validate our results, we used a most common CRC GEMM model by\nusing ApcMin/+ mouse, which was considered as a model of early MSS CRC (Br J Cancer.\n2023 Oct 26; 129(9): 1442–1450.). We implanted 5-10 mm3 CRC tumor sections\nderived from ApcMin/+ mouse into the right flank of C57BL/6, then these mice were\ntreated with GCA or GW4064 (Fig. SS8). Consistent with our previous observation,\nFXR activation profoundly inhibit tumor development, as evidenced by a lower tumor\nvolume and a better of survival rate of the mice treated with GW4064 than control mice.\nFig. SS8. The tumor volumes of C57BL/6 mice (n=6) inoculated with CRC tumor\nsections derived from ApcMin/+ mouse with indicated treatment.\nMinor concerns:\n1. Extensive grammatical and spelling errors throughout manuscript. English-language\nediting recommended.\nR: We apologize for the mistakes and have refined the manuscript. In addition, we have\npreviously sent our revised manuscript for extensively editing.\n2. Heatmap scales are generally missing units/labels throughout the figures.\nR: We have added the labels of scale bars in our revised manuscript.\n3. Page 8, lines 162-165: The statement here is confusing and should be clarified.\nShould it actually say, “FXR-mediated tumor suppression…”?\nR: Yes, we have reedited this sentence in our revised manuscript.\nReviewer #2 (Remarks to the Author): with expertise in bile acids, FXR,\nmetabolomics\nZhao et al. demonstrated that glycocholic acid (GCA) enhances tumor cell PD-L1\nexpression, thereby suppressing CD8+ T cell-mediated antitumor responses in the\ntumor microenvironment (TME) and promoting colorectal cancer tumor growth. This\neffect is mediated through the targeting of the FXR/SOX14/DHHC9 axis. The study\nalso suggests a testable hypothesis: inhibiting GCA/FXR signaling could augment the\neffectiveness of anti-PD-L1 therapy. While this study presents a novel and intriguing\nperspective with potential implications for immunotherapy in colorectal cancer (CRC)\npatients, several major concerns need to be addressed, and the conclusion lacks robust\nevidence.\nWe are delighted that the reviewer finds our observations interesting. We have\nperformed point-by-point reply to reviewer as below.\nSpecific comments are the following:\n1. The authors mention the measurement of 33 bile acids (BAs) in serum but fail to\nprovide a detailed description of the method and BA profiling data. Additionally, the\ncriteria for defining low and high GCA levels in the recruited population are not clearly\nexplained. This GCA-based subgrouping method lacks validation in another cohort.\nR: We apologize for not clearly describing the detailed method of the measurement of\nBAs in our first version of the manuscript. In brief, for the measurement of bile acids\n(BAs), 0.1 mL serum sample of CRC patient was mixed with 0.51 ml of ice-cold\nMeOH-ACN (1:1"}, "author_response": ""}]

Decision letter