Loss of ALK4 promotes cancer progression through regulating TGF-β receptor N-glycosylation

Domain: biology
Published: 2025-12-17
Editorial outcome: major_revision

Abstract
The transforming growth factor-β (TGF-β) pathway typically inhibits tumorigenesis but can promote metastasis during cancer progression. Activin receptor-like kinase 4 (ALK4), a type I TGF-β family receptor, is frequently downregulated or mutated in cancers, and reduced ALK4 expression correlates with poorer outcomes. However, its role and mechanism of action in cancer progression remains unclear. We demonstrate that ALK4 loss enhances anchorage-independent growth, migration, invasion, and epithelial-mesenchymal transition in vitro, as well as cancer progression in breast and pancreatic cancer models in vivo. Importantly, ALK4 loss promotes canonical TGF-β signaling by increasing TGF-β receptor N-linked glycosylation and stabilizing these receptors at the cell surface. Mechanistically, ALK4 loss upregulates β1,6 N-acetylglucosaminyltransferase V (MGAT5) and galectin-3, which binds MGAT5-modified glycoproteins to stabilize surface receptors. Consistent with prior observations that galectin-3 preferentially binds to MGAT5-modified glycoproteins to stabilize cell surface receptors like TGF-β receptors, we demonstrate that ALK4 loss enhances MGAT5-mediated glycosylation of TGF-β receptors, promoting their stabilization and signal transduction. Depleting MGAT5 or inhibiting N-glycosylation effectively suppresses ALK4-loss-induced TGF-β signaling and cancer progression.

Introduction
The transforming growth factor-β (TGF-β) family, which includes TGF-βs, activins, growth and differentiation factors (GDFs), bone morphogenetic proteins, and inhibins, plays essential roles in embryonic development and regulates key cellular processes such as proliferation, differentiation, apoptosis, and migration. These proteins signal by binding and activating their respective cell surface receptors1–4.

TGF-β signaling begins with TGF-β binding to the type III TGF-β receptor (TβRIII), which facilitates ligand presentation to the type II TGF-β receptor (TβRII)5,6. This interaction recruits the type I TGF-β receptor (TβRI) to form a receptor complex. TβRII phosphorylates and activates TβRI7–9, which subsequently phosphorylates the transcription factors Smad2 and/or Smad3. The activated Smads complex with Smad4 translocates to the nucleus, where they regulate the transcription of TGF-β target genes. TGF-β signaling has a dichotomous role in cancer progression. In early stages, it suppresses tumorigenesis by inhibiting proliferation and promoting differentiation and apoptosis8,9. Conversely, in advanced stages, elevated TGF-β signaling drives epithelial-to-mesenchymal transition (EMT), immune evasion, chemotherapy resistance, and metastasis10–13, making TGF-β signaling an attractive therapeutic target.

Common strategies to inhibit TGF-β signaling include blocking ligand–receptor interaction and inhibiting receptor kinase activity14. Although preclinical studies show potent antitumor effects of TGF-β-targeting agents15–17, clinical outcomes have been less encouraging. To effectively suppress TGF-β signaling and prevent cancer, the mechanisms regulating this pathway must be fully understood.

Another approach focuses on reducing TGF-β1 responsiveness, including promoting endocytosis to destabilize cell surface receptors, a process regulated by β1,6 N-acetylglucosaminyltransferase V (MGAT5)-glycosylation18. Notably, MGAT5 depletion in cancer models reduces metastasis and cell proliferation19–21. Furthermore, understanding factors that regulate TGF-β signaling is crucial for selecting patients who may benefit from TGF-β inhibition and for identifying biomarkers to assess treatment efficacy6.

Activin-like kinase 4 (ALK4), encoded by ACVR1B, is a type I receptor that primarily mediates activin A signaling. Loss of heterozygosity and somatic biallelic inactivation of the ACVR1B locus have been observed in pancreatic cancer cell lines and clinical samples22,23. A Sleeping Beauty Transposon Screen identified Acvr1b as a gene whose disruption, in combination with oncogenic KRAS, promotes pancreatic adenocarcinoma in vivo24. Consistent with this, genetically engineered mouse models show that ALK4 deletion in combination with oncogenic KRAS drives pancreatic tumorigenesis25,26, and CRISPR-Cas9-mediated ALK4 depletion enhances colon cancer tumorigenicity in the presence of APC and KRAS mutations27. Although ALK4 loss has been linked to pancreatic and colon cancer, its role and mechanism in cancer progression remain poorly understood.

Here, we investigate and identify a mechanism by which ALK4 loss enhances TGF-β signaling and promotes cancer progression in pancreatic and triple-negative breast cancers, offering new insights into potential therapeutic approaches targeting TGF-β signaling pathways in these cancer types.

Results
Low ACVR1B expression correlates with poor outcomes in breast and pancreatic cancer
We initially assessed alterations in the ACVR1B gene in human cancer patient cohorts. Mutation rates and loss of copy number variation for ACVR1B across cancer types ranged from 0.44% to 4.92% and from 0.90% to 33.95%, respectively (Table 1). Notably, both breast and pancreatic cancers exhibited high mutation and copy number loss rates for ACVR1B. ACVR1B mRNA levels were significantly reduced in breast and pancreatic tumors compared to normal tissues (Fig. 1a, b). Consistent with these data, we found that ACVR1B expression was significantly lower in primary pancreatic tumors relative to adjacent normal tissue (Fig. 1c).

Low ACVR1B expression was significantly associated with reduced recurrence-free survival in breast cancer patients (Fig. 1d) and with significantly decreased overall survival in pancreatic cancer patients (Fig. 1e, Supplementary Fig. 1a). Moreover, reduced ACVR1B expression correlated with poorer recurrence-free survival in breast cancer patients with high Ki67 proliferation indices (Supplementary Fig. 1b). Importantly, ACVR1B expression was significantly lower in basal-like breast cancer compared to Luminal A (LumA), LumB, and HER2-enriched subtypes (Fig. 1f). Furthermore, lower ACVR1B expression was associated with worse recurrence-free survival in basal-like breast cancer patients (Fig. 1g). Consistent with patient data, ALK4 expression at the mRNA level was more frequently decreased in basal-like breast cancer cell lines, including the MDA-MB-231 cell line, compared to luminal breast cancer cell lines (Supplementary Fig. 2a). ALK4 expression was particularly low in the MDA-MB-231 LM2 subline, a derivative selected for increased lung metastatic capability in vivo28 (Supplementary Fig. 2b). These findings highlight the potential of ACVR1B as a prognostic marker for poor outcomes in both breast and pancreatic cancers. They also suggest that the loss of ALK4 expression is a common event in these cancers and may contribute to their progression.

The downregulation of ACVR1B in tumor samples is, at least in part, attributed to epigenetic regulation, particularly DNA methylation, a well-established mechanism for silencing gene expression in cancer. In both breast and pancreatic cancer cells, we observed a significant negative correlation between ACVR1B expression and ACVR1B methylation levels (Supplementary Fig. 2c, d), suggesting that ACVR1B methylation is a critical mechanism driving ACVR1B silencing. Notably, the MDA-MB-231 LM2 subline exhibited higher ACVR1B methylation levels than the parental MDA-MB-231 cells (Supplementary Fig. 2e). Treatment of LM2 cells with 5-Azacitidine (5-AZA), a demethylating agent, significantly increased ACVR1B expression (Supplementary Fig. 2f). Similarly, in pancreatic cancer, tumor samples exhibited significantly higher ACVR1B methylation levels compared to adjacent normal tissues (Supplementary Fig. 2g), and 5-AZA treatment also significantly upregulated ACVR1B expression in pancreatic cancer cells (Supplementary Fig. 2h).

Loss of ALK4 promotes cancer progression
We investigated the functional role of ALK4 in cancer progression using in vivo models. Silencing ALK4 expression in MDA-MB-231 cells (Supplementary Fig. 3a) significantly increased pulmonary lesion formation following tail vein injection into immunodeficient mice (Fig. 2a). This effect was reversed by re-expressing a shRNA-resistant ALK4 construct (Supplementary Fig. 3a, Fig. 2a). Conversely, restoring ALK4 expression in the MDA-MB-231 LM2 subline (Supplementary Fig. 3b) significantly reduced pulmonary lesion formation (Fig. 2b–e) and prolonged overall survival (Fig. 2f). Similarly, restoring ALK4 expression in the 4T1 mammary carcinoma line (Supplementary Fig. 3c) did not affect primary orthotopic tumor growth (Supplementary Fig. 3d, e). However, it significantly suppressed the development of spontaneous pulmonary metastases (Supplementary Fig. 3f–h) and extended overall survival (Supplementary Fig. 3i). Similarly, in the HPNE orthotopic pancreatic cancer model, silencing ALK4 reduced primary tumor growth (Fig. 2g, h, Supplementary Fig. 3j) but increased the incidence of both local invasiveness (Fig. 2i) and distant metastasis (Fig. 2j–k).

To further elucidate the impact of ALK4 during cancer progression, we utilized an autochthonous mouse model. In KrasLSL-G12D;Acvr1bfl/fl;Pdx1-Cre (AKC) mice, ALK4 depletion in the KRASG12D-expressing pancreata significantly reduced overall survival compared to KrasLSL-G12D;Pdx1-Cre (KC) controls (Supplementary Fig. 4a). Consistent with previous studies25,29, ALK4 depletion in the KRASG12D-expressing pancreata significantly promoted pancreatic cyst formation (Supplementary Fig. 4b). By 8–9 months of age, the pancreatic weight of AKC mice was significantly higher than that of KC mice, with no significant differences in body weight (Supplementary Fig. 4c, d). Notably, all AKC mice at 8–9 months of age developed pancreatic ductal adenocarcinoma (PDAC) with variable degrees of differentiation, whereas most KC mice exhibited low- or high-grade pancreatic intraepithelial neoplasias (PanINs), of which only 3/10 progressed to PDAC (Supplementary Fig. 4b, e; Table 2). These in vivo studies demonstrated that loss of ALK4 promotes cancer progression.

ALK4 loss promotes epithelial-to-mesenchymal transition, migration, and invasion
We next investigated how loss of ALK4 contributes to cancer progression. Silencing ALK4 in MDA-MB-231 and PANC-1 cells (Supplementary Figs. 3a and 5a–b) induced EMT (Fig. 3a, b, Supplementary Fig. 5c), a pattern also observed in MCF10A cells (Supplementary Fig. 5d–f). Consistent with EMT induction, ALK4 loss significantly enhanced anchorage-independent growth (Fig. 3c), cell migration (Fig. 3d–f), invasion (Fig. 3g, h), and the formation of invasive structures in 3D collagen assays (Supplementary Fig. 5g). Restoring ALK4 expression in MDA-MB-231 LM2 cells reversed these changes, reducing mesenchymal marker expression (Supplementary Fig. 5h), cell migration (Fig. 3i), invasion (Fig. 3j), and invasive structure formation (Supplementary Fig. 5i, j). These effects were independent of cell proliferation, as ALK4 loss showed neutral to suppressive effects on proliferation (Supplementary Fig. 6). Mechanistically, increased directional persistence partially accounted for the enhanced migration following ALK4 loss (Fig. 3k, l).

The in vitro findings were corroborated by in silico data. Using data from TCGA, CPTAC-PAAD, QCMG-PAAD, and METABRIC-BRCA, we stratified patients with pancreatic cancer (PAAD) and breast cancer (BRCA) into top and bottom quartiles of ACVR1B expression and then performed gene set enrichment analysis (GSEA) using EMT and cancer-associated gene signatures. We observed significant enrichment of multiple gene signatures of EMT and invasive cancer phenotypes in the ALK4 low patient group (Fig. 3m, n), underscoring the clinical relevance of these phenotypes. Together, these results establish a role for ALK4 loss in driving EMT, migration, and invasion in both breast and pancreatic cancers.

ALK4 loss promotes TGF-β signaling
ALK4, a type I receptor for activin A, also mediates signaling by Nodal and GDF5 ligands9,30,31. To explore the mechanism underlying ALK4 loss-driven cancer progression, we examined its effect on signaling pathways activated by these ligands. While reducing ALK4 expression did not consistently alter activin A- or Nodal-induced Smad2/3 phosphorylation, it significantly enhanced TGF-β1-mediated Smad2/3 phosphorylation in both breast and pancreatic cancer models (Fig. 4a–c). In addition to increasing Smad2/3 phosphorylation, ALK4 loss also promoted nuclear accumulation of phospho-Smad2 following TGF-β1 stimulation (Fig. 4d) and upregulated TGF-β target genes in PANC-1 and MDA-MB-231 cells (Supplementary Fig. 7a, b). MDA-MB-231 cells lacking ALK4 exhibited TGF-β-responsive reporter gene expression at levels comparable to those induced by exogenous TGF-β (Supplementary Fig. 7c). In vivo, orthotopic injection of HPNE cells with ALK4 knockdown into mice corroborated these findings, showing elevated phospho-Smad2 levels in the absence of ALK4 expression (Supplementary Fig. 7d).

Consistent with our in vitro findings, we observed that low ALK4 expression strongly correlated with active TGF-β signaling, whereas high ALK4 expression inversely correlated with TGF-β signaling in breast and pancreatic cancer specimens (Fig. 4e). Specifically, reduced ALK4 expression correlated with increased expression of TGF-β target genes, including key effectors and mediators of EMT (Fig. 4f, g, Supplementary Fig. 7e, f). Single-cell RNA sequencing (scRNA-seq) data from breast cancer32 further revealed lower ALK4 expression in basal-like breast tumor cells, with reduced ALK4 expression negatively correlating with TGF-β-regulated gene expression (Supplementary Fig. 7g).

To determine whether the downstream effects of ALK4 loss were driven by enhanced TGF-β signaling, we inhibited TGF-β signaling using a dominant-negative type II TGF-β receptor (DN-TβRII) (Supplementary Fig. 8a). This effectively reversed both the increase in TGF-β signaling (Fig. 4h, i) and migration induced by ALK4 loss (Fig. 4j). Similarly, silencing the type I TGF-β receptor (TβRI/ALK5) through siRNA or expressing a dominant-negative TβRI blocked the increased migration and TGF-β signaling caused by ALK4 loss (Supplementary Fig. 8b–d).

Next, we examined whether ALK4 loss affects TGF-β signaling through suppression of activin A signaling. Using sActRIIB-Fc, a soluble activin receptor that sequesters activin A33, we assessed whether this could replicate the effects of loss of ALK4. While sActRIIB-Fc inhibited activin A-induced Smad2 phosphorylation (Supplementary Fig. 9a), sActRIIB-Fc did not recapitulate the effects of loss of ALK4, including inducing TGF-β-induced Smad2 phosphorylation and promoting EMT (reduction of E-cadherin, induction of Slug and α-SMA) (Supplementary Fig. 9b). Instead, sActRIIB-Fc promoted an epithelial phenotype (decreased Slug and increased E-cadherin), suggesting that ALK4 loss mediates its effects on TGF-β signaling and EMT independently of activin signaling suppression.

ALK4 loss increases TβRI and TβRII surface expression and complex formation via regulated receptor glycosylation and stability
To explore the mechanism by which ALK4 loss enhances TGF-β signaling, we examined the effect of ALK4 expression on TβRI or TβRII at the mRNA level, finding no significant changes (Supplementary Fig. 10). We then assessed whether ALK4 loss promotes TGF-β signaling by increasing the cell surface expression of TGF-β receptors. Using an I125-TGF-β binding and crosslinking assay, we found that ALK4 loss led to increased surface expression of TβRI and TβRII in breast and pancreatic cancer cells (Fig. 5a, b, Supplementary Fig. 11a, b). This was further confirmed by cell surface biotinylation assay (Supplementary Fig. 11c, d). Since TβRI cannot bind I125-TGF-β without forming a complex with ligand-bound TβRII34, increased levels of I125-TGF-β-bound TβRI with loss of ALK4 also support increased complex formation between TβRII and TβRI in this context. Conversely, overexpressing wild-type ALK4 or constitutively active ALK4 significantly reduced the surface expression of TβRI and TβRII, whereas kinase-inactive ALK4 had no such effect (Fig. 5c, d), suggesting that ALK4’s kinase activity is critical for regulating TβRI/TβRII cell surface expression. Additionally, restoring ALK4 expression in ALK4-deficient LM2 breast cancer cells decreased both TβRI and TβRII surface expression and complex formation (Fig. 5e).

Receptor surface expression is often regulated by glycosylation in the Golgi apparatus35,36. Consistently, mutations in the N-glycosylation sites of TβRII significantly impaired TGF-β-induced Smad2 phosphorylation and downstream signaling37. Overexpressing active ALK4 reduced TβRII glycosylation and shifted most TβRII to a less- or non-glycosylated form (Fig. 5f, Supplementary Fig 11e), which was confirmed by PNGase F treatment that removes all N-linked glycosylation (Fig. 5f). In contrast, silencing ALK4 increased the levels of both glycosylated and non-glycosylated TβRII in pancreatic and breast cancer models and enhanced resistance to endoglycosidase H (EndoH) (Fig. 5g), supporting preferential accumulation of glycosylated TβRII. Supporting this, N-glycosylation inhibition with tunicamycin reduced TβRI and TβRII surface expression (Fig. 5h) and attenuated the effects of ALK4 loss on TβRII expression (Fig. 5i).

Proteomic analysis reveal potential mechanisms by which ALK4 loss promotes TGF-β signaling and cancer progression
To assess how ALK4 loss enhances TGF-β signaling, we conducted proteomic analyses of whole-cell lysates from Panc1 control (NTC) and two independent Panc1 ALK4 CRISPR knockout (KO) lines. Both ALK4 KO lines exhibited similar patterns of differentially expressed proteins (DEPs) (Fig. 6a, Supplementary Fig. 12a). Functional annotation and pathway enrichment analyses using Database for Annotation, Visualization, and Integrated Discovery (DAVID) of the most upregulated DEPs revealed a strong association between ALK4 loss and N-linked glycosylation, with many of these proteins localized to the plasma membrane and extracellular region (Fig. 6b, Supplementary Fig. 12b). These proteins were enriched in pathways related to TGF-β signaling, integrin-mediated signaling, and extracellular matrix organization (Fig. 6b).

Consistent with our previously described findings linking ALK4 loss to enhanced EMT, GSEA identified positive enrichment of EMT and cell migration pathways in ALK4 KO cells (Fig. 6c, Supplementary Fig. 12c). Furthermore, genes commonly upregulated in pancreatic cancer were significantly enriched in ALK4 KO cells (Supplementary Fig. 12d). Multiple TGF-β signaling signatures correlated positively with ALK4 KO cells (Fig. 6d, e, Supplementary Fig. 12e), whereas retained ALK4 expression was associated with the downregulation of a TGF-β EMT signature (Fig. 6f).

To investigate how ALK4 loss affects TGF-β receptor glycosylation and stability, we constructed a protein-protein interaction network of the top 125 upregulated DEPs using STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) analysis. The network revealed three distinct clusters (Supplementary Fig. 12f), with the largest cluster predominantly composed of glycoproteins and cell surface receptors (Fig. 6g). Notably, several TGF-β pathway target genes or coreceptors, including FN1, matrix metallopeptidase 2 (MMP2), CD44, and endoglin (ENG), were found to interact with the extracellular scaffolding protein galectin-3 (LGALS3) (Supplementary Data 2). These findings suggest that galectin-3 may play a critical role in the upregulation of TGF-β signaling observed with ALK4 loss.

ALK4 loss drives cancer progression via galectin-3 and MGAT5-dependent pathways
Previous studies have demonstrated that branching of N-glycans catalyzed by MGAT5 on cell surface receptors promotes their binding to galectin-3, resulting in prolonged receptor activation18,38. Consistent with proteomics screen results, we found that ALK4 loss upregulated galectin-3 expression at both mRNA and protein levels in PANC-1 cells (Fig. 7a) and MDA-MB-231 cells (Supplementary Fig. 13a). Next, we specifically evaluated levels of MGAT5-catalyzed β1,6-branch on N-glycans using Phaseolus Vulgaris Leucoagglutinin (PHA-L) lectin in ALK4 KO and control cells. ALK4 loss significantly increased MGAT5-modified glycans in PANC-1 and MDA-MB-231 cells (Fig. 7b, Supplementary Fig. 13b), due to elevated MGAT5 expression (Fig. 7c, Supplementary Fig. 13c) and increased availability of the MGAT5 substrate UDP-GlcNAc (Supplementary Fig. 13d). The increased UDP-GlcNAc was likely due to the increased expression of GFPT2, the rate-limiting enzyme in the hexosamine biosynthesis pathway (HBP) (Supplementary Fig. 13e–g). We next examine whether ALK4 specifically increased MGAT5-catalyzed branched N-glycan. Among the 10 N-branching enzymes tested, only MGAT5 was specifically upregulated in both cell lines following ALK4 loss (Supplementary Fig. 13h, i). An unbiased lectin assay confirmed an increase in β1,6 GlcNAc-branched N-glycans, as detected by PHA-L, while other N-glycan types were not similarly affected (Supplementary Fig. 13j, k).

In ALK4 KO cells, MGAT5-catalyzed glycans on TβRII were significantly increased, as shown by PHA-L lectin pulldown assays (Fig. 7d). Silencing galectin-3 or MGAT5 expression reduced TGF-β-induced Smad2 phosphorylation in ALK4 KO cells (Fig. 7e, f, Supplementary Fig. 14a, b), suggesting that MGAT5 and galectin-3, at least in part, mediate the effects of ALK4 loss. Additionally, MGAT5 knockdown significantly lowered galectin-3 protein levels induced by ALK4 loss (Fig. 7e). Galectin-3 stabilization of TGF-β receptors, which inhibits their internalization, was consistent with the observed reduction in TβRII internalization following ALK4 (Fig. 7g). In a reciprocal manner, restoring ALK4 expression in LM2 cells increased the downregulation of TβRII and TβRI (Fig. 5e).

We next explored the functional consequences of increased MGAT5 expression and activity in the absence of ALK4. Consistent with our previous finding, MGAT5 depletion suppressed the activation of TGF-β signaling (Supplementary Fig. 14c, d). Depletion of MGAT5 significantly inhibited anchorage-independent growth induced by ALK4 loss (Fig. 7h). In vivo, ALK4 loss in PANC-1 cells increased pulmonary lesion formation after tail vein injection into immunodeficient mice (Fig. 7i). MGAT5 KO significantly reduced pulmonary lesion development (Fig. 7i–k). Silencing galectin-3 or MGAT5 also impaired ALK4 KO cell migration while having minimal effects on control cells (Supplementary Fig. 14e, f). Furthermore, knockdown of either galectin-3 or MGAT5 reduced mesenchymal marker expression and TGF-β target gene induced by ALK4 loss (Supplementary Fig. 14g, h). These observations provide new insights into how ALK4 loss drives cancer progression and identify galectin-3 and MGAT5 as potential therapeutic targets in the context of ALK4 loss.

ETS1 mediates ALK4 loss-induced upregulation of MGAT5
To elucidate how ALK4 loss drives MGAT5 upregulation, we first investigated the involvement of elevated TGF-β signaling. As shown in Supplementary Fig. 15a–i, silencing TβRI or treating cells with the small molecule inhibitor LY2157299 had no significant effect on ALK4 loss-mediated induction of MGAT5 and galectin-3 or MGAT5-modified glycans in PANC-1 and MDA-MB-231 cells. Similarly, SMAD2 knockdown did not alter galectin-3 or MGAT5 expression (Supplementary Fig. 15j, k). We next examined the role of non-canonical TGF-β signaling pathways in MGAT5 regulation in the absence of ALK4. Acute ALK4 inhibition significantly elevated phospho-p38 levels (Supplementary Fig. 16a–c). However, blocking the P38-MAPK pathway with the small molecule inhibitor SB203580 did not affect TGF-β signaling or MGAT5 expression (Supplementary Fig. 16d–f).

Previous studies identified ETS1, ETS2, and JUN as direct regulators of MGAT539–41. Among these, only ETS1 showed a strong negative correlation with ACVR1B and a positive correlation with MGAT5 in TCGA pancreatic and breast cancer cohorts (Fig. 8a–c), implicating ETS1 in ALK4 loss-mediated MGAT5 upregulation. Indeed, in ALK4 KO cells, ETS1 expression was significantly elevated, and ETS1 knockdown significantly reduced MGAT5 levels induced by ALK4 loss (Fig. 8d–f). These findings establish ETS1 as a key mediator of MGAT5 upregulation following ALK4 loss. Consistent with our previous findings, we observed a significant increase in the expression of Ets1, Galectin-3, and Mgat5 in ALK4-deficient KC mice (Supplementary Fig. 17a–c). We also observed increased expression of several TGF-β-regulated genes that are involved in EMT in the pancreas from AKC mice compared to the pancreas from KC mice (Supplementary Fig. 17d–h). These findings further support our model that loss of ALK4-activated TGF-β signaling results from regulating MGAT5 expression.

Inhibiting N-linked glycosylation effectively suppresses TGF-β signaling and tumor metastasis driven by ALK4 loss
We investigated whether inhibiting ALK4 loss-induced N-glycosylation could mitigate cancer progression. Two N-glycosylation inhibitors, N-linked glycosylation inhibitor 1 (NGI-1)42 and glucosamine43,44, were tested. Both inhibitors reduced MGAT5-catalyzed glycans, as detected by PHA-L staining (Supplementary Fig. 18a, b), to levels similar to those observed in MGAT5 CRISPR KO cells (Supplementary Fig. 14c). NGI-1 reduced TGF-β-induced signaling in both control and ALK4 KO cells, while glucosamine exhibited a stronger suppressive effect, particularly in ALK4 KO cells (Supplementary Fig. 18c, d). NGI-1 treatment also significantly decreased cell invasion in ALK4 KO cells (Supplementary Fig. 18e, f). In addition, both NGI-1 and glucosamine suppressed anchorage-independent growth in control and ALK4 KO cells, whereas the TβRI inhibitor LY2157299 had more modest effects in vitro (Supplementary Fig. 18g, h). Importantly, these effects were not attributable to changes in the number of viable cells (Supplementary Fig. 18i).

A major consequence of ALK4 loss is the promotion of cancer progression. To determine whether inhibiting N-glycosylation could counteract this effect, we assessed pulmonary lesion formation, using LY2157299 as a positive control. In line with the in vitro results and prior data, ALK4 loss significantly increased pulmonary lesions. Treatment with NGI-1 or LY2157299 significantly reduced lesion formation, underscoring the potential of N-glycosylation inhibition to suppress cancer progression (Supplementary Fig. 19a−d). In mice injected with ALK4 KO cells, we observed more cell surface PHA-L stain in the neoplastic region, and this signal was reduced by treatment with NGI-1 (Supplementary Fig. 19e).

These findings support a model in which ALK4 loss promotes MGAT5-mediated N-glycosylation of cell surface proteins, including canonical TGF-β receptors. This modification stabilizes the receptors at the cell surface by facilitating galectin-3 binding, thereby reducing receptor internalization. The resulting elevated receptor levels enhance TGF-β receptor complex formation, driving EMT, migration, invasion, and cancer progression. ETS1 at least partially mediates the upregulation of MGAT5 following ALK4 loss. Importantly, N-glycosylation inhibitors effectively suppress ALK4 loss-induced tumor progression.

Methods
All animal experiments were conducted under protocols approved by the Duke University Institutional Animal Care and Use Committee (Protocol Number A130-23-06). In the tumorigenicity study, the tumor size didn’t exceed the maximal tumor burden allowable (2000 mm3). All recombinant DNA experiments were conducted under protocols approved by the Duke Institutional Biosafety Committee.

Cell lines and reagents
The human breast cancer cell line MDA-MB-231 was obtained from the American Type Culture Collection (ATCC). LM2 cells, a derivative of MDA-MB-231, were provided by Dr. Joan Massagué (Memorial Sloan Kettering Cancer Institute). Both MDA-MB-231 and LM2 cells were cultured in Dulbecco’s modified Eagle medium (DMEM, Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (FBS) (Corning) and 1% penicillin/streptomycin (Thermo Fisher Scientific). The MCF-10A human breast cancer progression series of cell lines were provided by Dr. William Schiemann (Case Western Reserve University) and maintained in DMEM/F12 medium (Thermo Fisher Scientific) supplemented with 5% horse serum (Corning), 10 μg/ml insulin (Thermo Fisher Scientific), 20 ng/ml epidermal growth factor (Sigma), 100 ng/ml hydrocortisone (Sigma), 100 ng/ml cholera toxin (Sigma), and 1% penicillin/streptomycin. The 4T1 mouse breast cancer cell line series was also provided by Dr. William Schiemann and maintained in DMEM supplemented with 10% FBS. The human pancreatic cell lines PANC-1 and HPNE (ATCC) were maintained in DMEM medium supplemented with 10% FBS and 1% penicillin/streptomycin. The ALK4 WT (Cat# 80879), ALK4 CA (Cat# 27223), TβRII DN (Cat# 12640), TβRI (Cat# 14831), and TβRII (Cat# 11766) DNA plasmids were purchased from Addgene. The ALK4 DN DNA plasmid77 was provided by Dr. Anne Klibanski. The inhibitors SB431542, LY2157299, SB203580, and NGI-1 were purchased from Selleckchem. Glucosamine was purchased from Sigma.

Patient sample analysis
mRNA from pancreatic adjacent healthy tissue (n=13) and primary pancreatic tumor tissue (n=20) was acquired from the Duke Biorepository & Precision Pathology Center (Supplementary Data 3), with informed patient consent and approved by the Duke University IRB (deidentified, exempt). All samples were reviewed and approved by board-certified pathologists. Quantitative reverse transcription polymerase chain reactions (qRT-PCR) were performed using primers specific for ACVR1B and GAPDH (Supplementary Data 1). ACVR1B mRNA expression was normalized to GAPDH using the ΔΔCt method. Statistical significance was assessed using the Mann–Whitney test, assuming a non-Gaussian distribution for comparisons between two groups.

Generation of stable cell populations
PT67 packaging cells (Clontech) were transfected with shNTC, shALK4, or shALK4-rALK4 constructs to produce retroviral stock, which was subsequently used to infect HPNE, PANC-1, MD-MB-231, and MCF10A, following previously described protocols78. LM2 cells were transfected with pBABE or pBABE-ALK4 using Lipofectamine 3000 (Thermo Fisher Scientific), and stable cell populations were selected as recommended79.

CRISPR-mediated ALK4 knockout cells were generated using the pLentiCRISPRv2-puro vector (Addgene, Cat# 98290). Three gRNA sequences were annealed separately into BsmBI-digested pLentiCRISPRv2-puro vector using T4 ligase, and gRNA insertion was confirmed by Sanger sequencing. The finalized pLentiCRISPRv2-puro-gRNA vector was co-transfected into 293T cells along with psPAX2 (Addgene) and pMD2.G (Addgene) plasmids. Lentiviral-conditioned medium, supplemented with polybrene (Sigma, Cat# TR-1003-G), was used to infect parental Panc1 or MDA-MB-231 cells, followed by puromycin selection (1 μg/ml). All newly generated materials (stable cell lines) are available upon request. The shRNA and gRNA sequences used in this study are listed in Supplementary Data 1.

In vivo tumorigenicity and metastasis model
All mice used in this study are housed in IVCs (Individually ventilated cages) under positive air pressure in a barrier facility. The light cycle is 12 on and 12 off; typically, lights are on from 7 a.m. to 7 p.m. Temperature is 72°C ± 2 on either side, and humidity can range from 30% to 70%.

HPNE cells (5×106) stably expressing shNTC or shALK4 in RPMI medium with 10% Matrigel were orthotopically injected into the pancreata of 6-week-old male nude mice (NU/J, JAX:002019). After 15 weeks, mice were euthanized for analysis of primary tumors and metastases. All metastatic lesions noted were detected in different mice (one metastatic lesion per mouse). 4T1-luc cells stably expressing pBABE or pBABE-ALK4 (106 in 50 μl DPBS) were orthotopically injected into the fourth mammary pad of 6–8-week-old male C57BL/6J mice (JAX:000664). Tumor growth was monitored every other day until day 18. Primary tumors were removed, and metastases were assessed on days 10 and 20 post-resection.

For tail vein injection models, MDA-MB-231-luc cells stably expressing shNTC, shALK4, or shALK4+rALK4 (106 cells in 100 μl PBS), LM2-luc cells expressing pBABE or pBABE-ALK4 (5×105 cells in 100 μl PBS) were injected into female nude mice (JAX:005557, 6–8-week-old). PANC-1-Luc cells stably expressing crNTC or crALK4, and their corresponding MGAT5 KO cells (5×105 cells in 50 μl PBS) were injected into NSG mice (JAX:005557, 6–8-week-old). An equal number of male and female mice were used. Bioluminescence imaging was performed at specified time points after intraperitoneal injection of D-luciferin (150 mg/kg) using a Caliper IVIS Spectrum in a blinded manner. For drug testing, PANC-1-luc-crNTC or PANC-1-luc-crALK4 KO cells (5×105 cells in 50 μl DPBS) were injected via tail vein into NSG mice. NGI-1 (20 mg/kg, i.p., every other day) and LY2157299 (75 mg/kg, oral, daily) were prepared in 10% DMSO, 40% PEG 300, 5% Tween 80, and 45% PBS. IVIS imaging began 5 weeks post-injection.

In the genetically engineered mouse model, ALK4 flox/flox mice were provided by Dr. Philippe Bertolino (Cancer Research Centre of Lyon), LSL-KRASG12D/+ mice were provided by Dr. David Kirsh from Duke University, and Pdx1-cre mice (JAX:014647) were purchased from Jackson Laboratory. LSL-KrasG12D/+ mice were crossed with Pdx1-Cre mice to generate the LSL-KRASG12D/+;Pdx-cre (KC) mice. LSL-KRASG12D/+;Pdx-cre mice were crossed with ALK4 flox/flox mice to generate the ALK4 flox/flox;LSL-KRASG12D/+;Pdx-cre (AKC) mice. KC and AKC were then followed until 8–9 months of age or until humane endpoints were reached. The pancreatic sections and liver sections were evaluated by a board-certified veterinary pathologist in a blinded manner (Table 2).

siRNA transfection
Silencer Select siRNA targeting ALK4 (S978 and S979), LGALS3 (S8150 and S8149), MGAT5 (S8738 and S8739), TGFBR1 (S14071 and S14073), ETS1 (S4847), SMAD2 (S8397), and a noncoding control (Thermo Fisher Scientific) were transfected at 10–30 nM using Lipofectamine RNAiMAX Transfection Reagent (Thermo Fisher Scientific), following the manufacturer’s instructions. For transfection experiments exceeding 3 days, cells were re-transfected every 2–3 days and incubated for an additional 36–60 h before subsequent experiments.

Transwell migration and invasion assays
Transwell migration was assessed by seeding 1.5–2.5×104 cells in serum-free medium into the upper chamber of a transwell insert with 8.0 μM pores (Corning). Cells were allowed to migrate overnight at 37°C toward a complete growth medium containing 10% serum in the lower chamber. For transwell invasion assays, 1–5×105 cells were seeded into the upper chamber of Matrigel-coated transwell inserts (Corning) with 8.0 μM pores. Invasion was assessed following incubation at 37°C for 14–24 h. Migrated or invaded cells were counted in a blinded manner by multiple lab members using ImageJ.

Cell proliferation assay
The 3H thymidine incorporation assay was performed as previously described80. Briefly, cells were incubated with 10 μCi of 3H thymidine (Amersham Biosciences) for 4 h. After gentle washing with 1× PBS and 5% trichloroacetic acid, cells were collected in 0.1 N NaOH. The amount of incorporated 3H thymidine was determined by scintillation counting.

3D morphogenesis assay
The three-dimensional culture of cells was carried out as described previously81. Briefly, single-cell suspensions of 5000 cells were seeded per well on solidified Matrigel (Corning, Cat# 356231) in the corresponding assay medium. The assay medium was replaced every 48 h. Images of the 3D structures were taken on Day 8. For LM2 cells, the 3D structures were stained with Phalloidin and DAPI.

Soft agar assay
Soft agar assays were performed in six-well plates (VWR). Each well contained a bottom layer of 0.5% agarose (VWR), a middle layer of 0.3% agarose containing 5×103 cells, and a top layer of DMEM media supplemented with 10% FBS. The top layer of medium was changed every 6 days. After 24 days of growth at 37°C/5% CO2, colonies were stained with a 0.005% crystal violet solution (Sigma). Colonies with a diameter >200 μm were counted using ImageJ in a blinded manner by multiple lab members.

Western blot
Preparation of cellular lysates and immunoblotting was performed as previously described82. SDS–PAGE was performed using gels ranging from 8% to 12% polyacrylamide that were loaded with 10–30 μg of protein, as calculated by the Bradford assay, following the manufacturer’s instructions (Bio-Rad). Proteins were transferred to 0.45 μm PVDF membranes (EMD Millipore) using a Trans-Blot Turbo Transfer System (Bio-Rad). Membranes were blocked in 5% bovine serum albumin (BSA, NEB), followed by incubation with primary antibodies at 4°C for 18 h. Membranes were then washed with TBS-Triton (pH 7.4, 10% Triton-X) and incubated with fluorophore-labeled or HRP-conjugated secondary antibodies. Fluorophore-labeled antibodies were developed using an Odyssey® DLx Imaging System (LI-COR). HRP-conjugated antibodies were incubated for 2 min in SuperSignal™ West Pico PLUS Chemiluminescent Substrate (Thermo Fisher Scientific) before imaging with a Bio-Rad ChemiDoc XRS+ Imaging System (Bio-Rad). Antibodies used are listed in Supplementary Data 1. Western blot qualification was performed using Image Studio or ImageJ.

Cell surface biotinylation and co-immunoprecipitation
For ALK4 knockdown/knockout validation, 6×106 cells were plated in 10-cm plates and incubated with NHS-Biotin (0.5 mg/ml in ice-cold PBS) for 30 min in the dark before being collected. ALK4 protein was pulled down using an ALK4 antibody (R&D) and detected using HRP-conjugated streptavidin (Thermo Fisher Scientific).

Cell surface biotinylation experiments were performed using a Cell Surface Biotinylation and Isolation Kit (Thermo Fisher Scientific) following the manufacturer’s instructions. Briefly, control or ALK4 KOs (12×106 cells/15-cm plates) were washed twice with ice-cold PBS. Cell surface biotinylation was conducted by adding 10 ml of sulfo-NHS-SS-biotin solution (0.25 mg/ml in ice-cold PBS) to each plate. The biotin labeling reaction was performed by incubation at 4°C and quenched after 30 min by washing twice with 20 ml of ice-cold TBS. Cells were collected in TBS, and cell pellets were lysed. The biotinylated proteins were captured with Pierce™ NeutrAvidin™ Agarose (Thermo Fisher Scientific) and eluted in elution buffer supplemented with dithiothreitol (DTT). Samples were stored at −80°C for future analysis.

Cell surface receptor internalization
Cells were washed with ice-cold PBS containing 1 mM MgCl and 0.1 mM CaCl (PBS++) and incubated for 30 min with 0.5 mg/ml EZ-Link Sulfo-NHS-SS-Biotin (Thermo Scientific) in PBS++ on ice. Cells were then incubated in complete growth medium in a 37°C incubator for the indicated times. Internalization was halted by transferring cells back to ice and washing them with ice-cold PBS. Remaining cell surface biotin was removed by washing three times with a mildly reducing buffer containing 50 mM glutathione, 75 mM NaCl, 75 mM NaOH, and 10% FBS in PBS++ for 15 min. Samples were then harvested and lysed, and biotinylated receptors were collected as described in the Cell surface biotinylation and co-immunoprecipitation section.

Immunofluorescence assay
Formaldehyde-fixed cells were permeabilized with 0.2% Triton X-100, blocked with 8% BSA, and stained with the appropriate antibodies, including anti-β-catenin (1:200), anti-ZO-1 antibody (1:200), anti-vimentin antibody (1:200), anti-fibronectin (1:200), and anti-Smad2 (1:100). Cells were then incubated with Alexa Fluor-488-conjugated anti-mouse IgG (1:200) or Alexa Fluor-488-conjugated anti-rabbit IgG (1:200). Images were acquired using a Leica SP5 inverted confocal microscope or an Olympus FV1000 confocal laser scanning microscope.

Lectin arrays
A Lectin Array 70 kit was purchased from RayBiotech (GA-Lectin-70). Assays were performed as per the manufacturer’s instructions using a label-based approach. The whole cell lysates from NTC and ALK4 KO cells were used in this assay. The intensity was detected and analyzed using a SensoSpot Fluorescence Microarray Analyzer.

UDP-GlcNAc assay
The UDP-GlcNAc assay was developed by Duke Proteomics and Metabolomics Core Facility. Briefly, PANC-1 crNTC and crALK4 KO cells and MDA-MB-231 crNTC and crALK4 KO cells (4 replicates for each condition) were lysed and dried down under nitrogen at room temperature. Samples were incubated with 13C -UDP-GlcNAc (Omicron Biochemicals, Inc.) in a 20% acetonitrile solution. Samples were analyzed with a multiple reaction monitoring (MRM) assay. Data was acquired using UPLC-MS/MS on a Sciex QTrap 6500+ mass spectrometer, including calibration curves for the analyte in a manner consistent with the FDA Guidance for Bioanalytical Method Validation. Data analysis was performed using Skyline.

Bioinformatic data analysis
RNA sequencing of level 3 data from human breast and pancreatic adenocarcinoma tumors was obtained from The Cancer Genome Atlas (TCGA)83–85 through the Firehose data portal (https://gdac.broadinstitute.org/). RNA-Seq by Expectation-Maximization values were log-transformed and median-centered. Genes present in fewer than 20% of patients were excluded. Illumina HT-29v3 expression data for the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) project were obtained from the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/) and median-centered86. Breast cancer subtypes were classified using the Prediction Analysis of Microarray (PAM) 50 classifier (PAM50)87.

Gene expression data from pancreatic cancer patients from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Queensland Clinical Molecular Genetics (QCMG) datasets were downloaded from cBioPortal (https://www.cbioportal.org/datasets).

To examine ACVR1B expression in breast cancer subtypes, gene expression data were z-scored and plotted according to PAM50 classifications. Statistical significance between subtypes was assessed using a two-way analysis of variance (ANOVA). For specific gene analysis relative to ACVR1B expression, z-scores were calculated for each gene, and a Student’s t-test compared expression levels in patients with high (top quartile) or low (bottom quartile) ACVR1B expression.

To identify breast cancer cell lines with low ACVR1B expression, ACVR1B mRNA expression was assessed in a panel of 51 breast cancer cell lines. Affymetrix U133+2 gene expression data (GSE12777)88 were acquired from the Gene Expression Omnibus (GEO). Data were Microarray Suite 5 (MAS5) normalized and log2-transformed using the Affymetrix Gene Expression Console. Gene-specific expression probes were collapsed to the median using GenePattern89, and z-scores were plotted (Supplementary Fig. 2a).

Gene expression profiles for breast and pancreatic cancer patients were retrieved from the GEO repository90. Expression values for genes of interest were log2-transformed and exported using the GEO2R analytical tool91. Kaplan–Meier survival curves for patient cohorts were generated using Kaplan–Meier Plotter (data last acquired on 1/19/2025; https://kmplot.com/analysis/)92 or the International Cancer Genome Consortium (ICGC) PACA-AU dataset and GSE6245293, with significance assessed by log-rank tests.

Immunohistochemical staining
Formalin-fixed, paraffin-embedded 5 μm lung or pancreatic sections were deparaffinized and rehydrated. Endogenous peroxidase activity was inactivated by incubation with 2% H2O2. Antigen retrieval was performed using an antigen unmasking solution, followed by blocking with 8% BSA. Primary antibody was applied overnight at 4°C. Sections were then incubated with a rabbit secondary antibody using a VECTASTAIN ABC-HRP Kit (Vector Laboratories). Immunoreactivity was detected using a 3,3′-diaminobenzidine (DAB) system (Vector Laboratories). The PHA-L staining protocol was developed and performed by the Duke Research Histology Lab.

Luciferase assay
Cells were plated in six-well plates at 105 cells/well. The following day, cells were transfected with 2.3 μg of pE2.1 luciferase reporter plasmid and 0.2 μg of pRL-SV40 Renilla plasmid. After 24 h, cells were treated with 10 μM SB431542 or 40 pM TGF-β1 for 20 h. Cells were lysed, and a dual-luciferase reporter assay (Promega) was performed according to the manufacturer’s protocol.

Binding and crosslinking assay
The binding and crosslinking assay was performed as described previously80. Briefly, cells were treated as specified and incubated with 40 pM [125I] TGF-β (PerkinElmer). After incubation, the ligand was chemically cross-linked using 0.5 mg/ml disuccinimidyl suberate and quenched with 1 M glycine. The resulting complexes were separated by SDS–PAGE, and dried gels were analyzed using Typhoon phosphorimaging and ImageJ software.

Methionine pulse-chase labeling
The methionine pulse-labeling assay was performed as previously described94. Briefly, cells were incubated in pre-warmed pulse-labeling medium for 20 min. After incubation, cells were washed and transferred to pre-warmed chase medium for the indicated duration at 37°C. Cells were collected, lysed, and immunoprecipitated with TβRII antibody. The immunoprecipitated samples were separated via SDS–PAGE, and the dried gels were analyzed using Typhoon phosphorimaging and ImageJ software.

Flow cytometry
Cells were harvested using 0.05% trypsin and resuspended in FACS buffer (0.1% BSA in PBS). A total of 3.5×10⁵ cells per sample were incubated in 1 ml FACS buffer with 2.5 μg/ml fluorescein-conjugated PHA-L (Vector Laboratories). Samples were rotated in a head-to-end manner at 4°C for 30 min in the dark. After incubation, samples were pelleted by centrifugation, resuspended in FACS buffer, and analyzed. Three replicates were prepared for each condition and analyzed on a BD FACSCanto™ II (BD Biosciences). Data were processed using FlowJo™ v10 (BD Biosciences).

Quantitative reverse transcription-PCR
RNA was isolated using Trizol™ Reagent (Thermo Fisher Scientific) and reverse-transcribed using an iScript cDNA Synthesis Kit (Bio-Rad). qRT-PCR was performed using iQ SYBR Green Supermix and a Real-Time PCR Detection System (Bio-Rad). Cycle threshold values were determined using the Bio-Rad CFX Manager. Primers used in this study are listed in Supplementary Data 1.

Quantitative proteomic analysis
The quantitative proteomic analysis was performed at The Center for Genomic & Computational Biology (GCB) at Duke University. PANC1-NTC and ALK4 KO cells (4 replicates for each condition) were used. Cell lysates (~400 μl) were thawed, followed by the addition of 100 μl of 10% (w/v) SDS in 50 mM triethylammonium bicarbonate (TEAB) buffer. This was followed by probe sonication and then incubation at 80°C to denature the proteins and facilitate complete lysis. Samples were then centrifuged, and the resulting pellet was undetectable. Protein (40 μg) was diluted with 5% (w/v) SDS in TEAB buffer, followed by the addition of 10 mM DTT and reduction at 80°C for 10 min. After cooling, samples were alkylated with 25 mM iodoacetamide. SDS was removed, and samples were digested with Sequencing Grade Modified Trypsin (1:20, Promega) using an S-trap mini device (ProtiFi), according to the manufacturer’s instructions. Recovered peptides were lyophilized to dryness and reconstituted in 40 μl of 1% trifluoroacetic acid (TFA) and 2% acetonitrile (MeCN).

One-dimensional liquid chromatography, tandem mass spectrometry (1DLC-MS/MS) was performed in a block-randomized order. Samples were analyzed using a nanoACQUITY UPLC system (Waters) coupled to an Orbitrap Exploris 480 high-resolution, accurate-mass tandem mass spectrometer (Thermo Fisher Scientific) via a nanoelectrospray ionization source. Samples were first trapped on a Symmetry C18 180 μm × 20 mm trapping column (5 μl/min at 99.9/0.1 v/v H2O/MeCN), followed by an analytical separation using a 1.7 μm ACQUITY HSS T3 C18 75 μm × 250 mm column (Waters) with a 90-min gradient of 5–30% MeCN with 0.1% formic acid at a flow rate of 400 nl/min and column temperature of 55°C. Data collection was performed in a BoxCar data-independent acquisition (BoxCar DIA) mode with variable window BoxCar and DIA scans defined based on scouting runs. Each cycle utilized a full scan with a resolution of 120,000 resolution from m/z 400 to 1200 with a normalized AGC target of 300% and 50 ms IT, two BoxCar scans at 120,000 resolution with 10 windows each, 100% AGC and auto IT, and a 25 vw in DIA scan with 30,000 resolution, AGC target of 1000%, a 60 ms IT and NCE of 30. Run-start internal calibration was enabled. Data were collected in centroid mode. For spectral library generation, a single data-dependent acquisition run was performed on an SPQC sample.

Proteomic data analysis
A spectral library was generated using Spectronaut v. 14.10.201222.47784 (Biognosys). DIA files were converted to .htrms format using the HTRMS converter (Biognosys). Spectral library generation was performed using direct-DIA searching with Spectronaut Pulsar and a SwissProt database with Homo sapiens taxonomy, with the addition of BSA and porcine trypsin (20,385 entries). Database searching was conducted with default parameters, including trypsin/P specificity, up to two missed cleavages, N-terminal protein acetylation, Met oxidation, and Gln/Asn deamidation. This resulted in a study-specific library containing 101,6022 precursors, 79,042 modified peptides, and 5967 protein groups. Quantification was conducted using DIA-NN v. 1.7.16 (https://github.com/vdemichev/DiaNN). Non-default analysis settings included: spectral library (exported from Spectronaut Pulsar search) and .fasta files (as described above); generation of the spectral library and MBR checked; neural network classification in double-pass mode; protein inference using protein names (from FASTA); and quantification strategy based on robust LC (high accuracy). Additional analyses were performed in R/RShiny using limma/edgR2 and Quickomics (https://github.com/interactivereport/Quickomics/).

Functional annotation and pathway enrichment analysis
Pathway enrichment analysis was performed using the GSEA program (Broad Institute) following the developer’s instructions. Expression of the top 125 most upregulated proteins was extracted for functional annotation and pathway enrichment analyses using DAVID Bioinformatics Resources 202195,96.

Statistical analysis
Data from mouse experiments and patient samples were analyzed using the nonparametric two-tailed Mann–Whitney test. For multiple comparisons, nonparametric one-way ANOVA was performed using the Kruskal–Wallis test, followed by Dunn’s multiple comparisons test. Survival data were analyzed using the log-rank test. In vitro experiments comparing two groups were analyzed using two-tailed Student’s t-tests. For multiple comparisons within one independent variable, one-way ANOVA was followed by Tukey’s test. For experiments involving two independent variables, two-way ANOVA with interaction testing was used. The correlation between the expression of two genes was assessed using nonparametric two-tailed Spearman’s correlation. In all cases, data are presented as the mean ± standard error of the mean unless otherwise stated. Each experiment included at least three biological replicates. For Western blotting, one representative out of three independent replicates is shown in the figures. All statistical analyses were performed using GraphPad Prism v9.0.0.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this interesting and thoroughly investigated manuscript, the authors identify ALK4 down regulation as a common feature of solid cancers and provide compelling evidence that this leads to enhancement of EMT/invasion/metastasis via increased TGF  signaling as a result of enhanced TGF RI/II surface retention from up-regulated Mgat5 N-glycosylation and its ligand galectin-3. As it has been previously shown that Mgat5 N-glycosylation/galectin-3 interactions regulate EMT/invasion/metastasis by decreasing TGF RI/II endocytosis (to increase TGF  signaling)1-4, the novelty in this manuscript lies in the connection of ALK4 down regulation to Mgat5/galectin-3 up-regulation. However, as activin signaling is shown not to be impacted by ALK4 alteration, the mechanism by which this occurs is not clear. Additional investigations exploring this mechanism would greatly strengthen the manuscript. At the very least, the authors should look at non-canonical ALK signaling pathways5. This should include assessing short-term changes in canonical and non-canonical signaling pathways after acute blockage of ALK4. Other issues are below.\nOther Major issues\n- Fig. 8 and associated supplemental data needs to done using MGAT5 KO cells (or inhibitors that specifically target branching like swainsonine or kifunensine), rather than NGI-1 and glucosamine. This should also be presented as the main figure and the NGI-1 and glucosamine data moved to supplemental. Unlike Mgat5 KO, NGI-1 and glucosamine inhibit N-glycan attachment by blocking LLO biosynthesis leading to significant ER stress and unfolded protein responses (UPR). This can complicate interpretation. In contrast, Mgat5 KO is a much subtler change to N-glycans, does not induce ER stress or UPR, and most importantly is the precise change identified by loss of ALK4.\n- All metastasis models were via IV injection. A spontaneous metastasis model would strengthen the paper. At the very least the discussion and interpretation should be adjusted to reflect this.\n- The authors demonstrate regulation of Mgat5 and its product, B1,6 branched glycans. However, no attempt is made to further characterize the glycosylation changes. The branching pathway enzymes are often regulated in a coordinated fashion, or metabolically. At the very least the authors should examine gene expression for enzymes in the branching pathway (eg Mgat1, 2, Mgat4a,b, mannosidase 1a,b,c, mannosidase II/IIx) and the hexosamine biosynthetic pathway. In addition glycomic analysis, or at least a panel of lectins in addition to L-PHA, should be used to determine if the changes are restricted to the B1,6 branch.\n- the abstract, introduction and discussion should be updated to better reflect the published data that N-glycan branching and Mgat5 N-glycosylation regulate EMT/invasion/metastasis by decreasing TGF RI/II endocytosis (to increase TGF  signaling)1-4. The concept of the galectin-glycoprotein lattice as an overall regulator of glycoprotein endocytosis should also be mentioned in the discussion6-8.\nOther Minor Issues\n- Supplemental figures should be in the order they are described in the text.\n- P-values and statistical tests should be defined in figure legends.\n- Fig. 2C should have statistical analysis and sample size.\n- Sample size and number of times experiments repeated needs to be stated in the Figure legends.\n- Quantitation of western blots should be provided throughout the manuscript to allow comparison between experiments.\n- Blots should be consistently labelled, including addition of blot type to the panels (eg WB vs I-125-TGF-b cross-linking)\n- Fig. 5H top panel, Fig S9B left panel and Fig S9D upper right panel should all have longer exposures.\n- Unclear why switched to 293T cell in 5C,E ,F. Should be one of the cancer lines.\n- Were any measures taken to ensure that observers were blinded to the experimental conditions, for example in the case of counting metastatic nodules or gross metastases in Fig2D-M. If so these should be described in the manuscript.\n- Additional methodological detail should be provided. For example, in the TGFb treatment experiments, how was serum resting performed.\n- What is the rationale for pre-treating for 72 hours with soluble activin receptor prior to 30min activin treatment? A shorter term incubation would be more appropriate.\n- For Fig12H,I quantitation should be presented in bar graphs.\n- Mgat5 mRNA levels should be measured in siMgat5 condition. The decrease in LPHA staining suggests poor inhibition of Mgat5. Or use Mgat5 KO as suggested above.\n- Quantitation of Fig S14F is needed.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "The manuscript presents a curious observation that loss of the TGF-beta type one receptor, Alk4, actually increases TGF-beta1 signaling and promotes a unique EMT event, capable of increasing invasion while maintaining proliferation and therefore drives overall metastasis. Mechanistically, the work goes on to show that loss of Alk4, increases TBRI and drives TBRI/TBRII cell surface complexes. Proteomics is used nicely characterize the EMT phenotype that results following depletion of Alk4. This revealed a cohort of the glycoproteins. Use of N-linked glycosylation inhibitors prevented the increase in metastasis caused by loss of Alk4. Overall, the work presents extensive findings that support a highly novel concept that loss of Alk4, reduction of activin signaling and promotion of an epithelial phenotype is balanced by enhanced glycol signaling supporting a mesenchymal phenotype. Overall, these events result in the highly aggressive “hybrid” EMT. Overall, this is an extremely rigorous study that clearly presents highly innovative data that has the potential to lay the groundwork for a mechanistic understanding of EMT and metastasis not previously recognized. I would suggest a few minor critiques;\nSeveral pieces of data are presented establishing that Alk4 is decreased in breast and PANC and that this is associated with disease progression. Some discussion could be offered as to what events lead to the loss of Alk4, i.e. genetic, transcriptional, post-transcriptional.\nNGI-1 is a highly insoluble compound. Some level of PD from the in vivo studies (i.e. changes in TBR-I or other protein glycosylation) would help support on-target effects of the observed anti-tumor activity.\nThe use of the term metastasis in reference to pulmonary tumors established by tail vein inoculation should be modified to pulmonary lesions or something similar.", "reviewer_4": "In this manuscript the authors attempted to demonstrate that the loss of Activin receptor-like kinase 4 (ALK4) plays an instrumental role in breast and pancreatic cancer progression and metastasis. Through a comprehensive analysis of several public datasets, they showed that ACVR1B (the gene encoding ALK4) was significantly mutated or lost in breast and pancreatic cancers, and that low expression levels of ACVR1B were associated with the worst prognosis in these patients. Subsequent functional experiments showed that knocking down ALK4 expression in breast or pancreatic cell lines promoted anchorage-independent growth, cell migration/invasion, epithelial-mesenchymal transition, and metastasis. Mechanistically, loss of ALK4 was associated with increased TGF-β/Smad canonical signaling, presumably owing to increased N-glycosylation and stability of both TβRI and TβRII at the cell surface. Gene expression analysis revealed that loss of Alk4 culminated in increased expression of MGAT5 and galectin-3, which together facilitate the N-glycosylation of TβRI and TβRII and thereby activate TGF-β signaling. While at a first glance the hypothesis that the loss of ALK4 contributes to cancer progression might seem appealing, the study does not provide compelling evidence to support such claim. It also lacks the conceptual advance needed for establishing the relevance of this mechanism to the human diseases. Indeed, the vast majority of experiments are superficial in nature, relying mostly on in vitro cell systems, which could lead to all sorts of artifacts. Therefore, one would anticipate that this study would deliver an incremental impact in the field of breast and pancreatic cancers. A few issues are listed below.\nThe authors relied heavily on several public datasets to show that Alk4 is lost in breast and pancreatic cancers, with low levels of Alk4 correlating with poor prognosis. The authors might want to consider corroborating these data using qRT-PCR or immunohistochemistry with tissue microarrays. In any case, considering the possibility that Alk4 expression is lost in breast and pancreatic cancers, one would wonder what mechanisms could contribute to this phenomenon in the cancerous samples that do not display any mutation or loss of copy numbers? Is there any other genetic or epigenetic event that could compromise ALK4 expression? This information is important for understanding the exact contribution of ALK4 to cancer progression and metastasis.\nThe expression levels of ALK4 seem to be inversely correlated with the aggressiveness and metastatic potential of breast and pancreatic cancer cell lines. However, this correlation is based on very artificial invasion assays in vitro. To support their claim, the authors might want to consider characterizing these cell lines in vivo, both in terms of tumor growth and metastatic potential. Based on the literature, it is perplexing to see that MIA Paca-2 and AsPC-1, which display poorly differentiated architectures, are less aggressive than Panc1, which display a well differentiated epithelial architecture. In any event, to provide compelling evidence that the loss of ALK4 contributes to cancer progression, it is imperative to conduct in vivo experiments with autochthonous mouse models of breast and pancreatic cancer. It would be straightforward to delete AcvR1B in mouse models of breast and pancreatic cancer (such as in MMTV-PyMT or KC mice with conditional expression of KrasG12D in the pancreatic epithelium). These experimental approaches must be presented at his level of publication.\nALK4 seems to induce expression of TβRI and TβRII at the surface by a mechanism dependent on its kinase activity. What is the substrate of ALK4 under these conditions? This information is important for understanding how ALK4 fulfills its anti-tumor suppressive function in breast and pancreatic cancers. Also important is what signaling pathway functions downstream of ALK4 to suppress cancer progression and metastasis? Without providing this kind of data, the impact of the study will be just incremental.\nLoss of ALK4 correlates with increased expression of MGAT5 and galectin-3, which could provide a mechanistic explanation as to how ALK4 regulates the N-glycosylation and thereby stability of TβRI and TβRII at the cell surface. There are at least three issues with this observation. First, the mechanism leading to the accumulation MGAT5 and galectin-3 in cells deficient for Alk4 was not explored. Second, compelling evidence that TβRI and TβRII are direct substrate of MGAT5 and galectin-3 was not presented. Third, compelling evidence that MGAT5 and galectin-3 functions downstream of ALK4 in vivo under physiological conditions is missing. The latter could be easily achieved through using mice or cells co-deleted of MGAT5 /galectin-3 and Alk4 and treated with the two inhibitors NGI-1 and Glucosamine.\nOverall, the study lacks the mechanistic depth for firmly establishing a role for ALK4 in suppressing cancer progression and metastasis. It also lacks the mechanistic depth for firmly establishing how ALK4 regulates the stability of TβRI and TβRII at the cell surface and attendant activation of TGF-β/Smad signaling pathway. Expression of ALK4 at the cell surface might simply rely on the same mechanism as does localization of TβRI and TβRII, so one conceivable mechanism would be that ALK4 might compete with TβRI and TβRII for the machinery that drives their cell surface localization.", "reviewer_5": "In this manuscript, Zhang et al present three major findings: 1) low ALK4 (the type I receptor for activin) expression correlates with poor prognosis in human breast and pancreatic cancer patients as well as EMT, invasion and metastasis of cancer cells; 2) knock-down of ALK4 promotes TGF-b signaling, its cell surface receptor levels, and receptor glycosylation; and 3) the effects of ALK4 knock-down are likely mediated through increase in galectin-3 and MGAT5 (a N-acetylglucosaminyltransferase) function in promoting glycosylation of TGF-b receptors. Although each claim was supported individually by a large body of data, the mechanism that links loss of ALK4 function to Gal-3 and Mgat5 transcription and thereby glycosylation of TGF-b receptors is missing. This deficiency in the authors’ thesis is particularly troublesome in light of their own revelation that blocking activin signaling via a soluble Fc fragment of ActRIIB showed no effect on the enhancement of TGF-b signaling by ALK4 knockdown. Another major problem with this manuscript is with their data/experiment description, which are insufficient, imprecise/inaccurate, and often hard to follow. While this second problem can certainly be readily rectified through a careful rewrite, the lack of the underlying mechanism or a reasonable conceptual connection makes this work incomplete for publication. Some specific issues are as follows.\n1. Comparison of ALK4 levels in various cancer cell lines is not meaningful or superficial at best (sFig.2C-D), as underlying causal factors vary from one cell type to another. For the same reason, comparison in sFig.9A is also problematic, e.g. ALK4 level is similar between 168FARN and 4T07 (sFig 2D) but cell surface TGFbR are quite different (sFig 9A). Moreover, the data were too scarce to support the correlation.\n2. Authors made several lines of stable cells expressing shALK4 or ALK4 gRNA. These lines were used interchanged throughout the manuscript. It is not clear why some experiments using the shALK4 lines while others using the ALK4KO lines. Sometimes panels were labelled with ALK4KO while legend said otherwise.\n3. Experiments in (Fig.2G-M were inadequately described. Legend 2G says the cells were implanted in “the tail of pancreas”. Were they implanted in the pancreas or injected in tail vein? It appears that authors attempt to show that silencing ALK4 decreased primary tumor growth in the pancreas but increased invasiveness and distant metastasis, which is in line with the bimodal roles of TGF-b in cancer.\n4. It is known that both activin and TGF-b are capable of inducing Smad2 and Smad3 phosphorylation. And it appears that ALK4 KO by itself consistently induced Smad2 phosphorylation, and enhanced TGF-b-mediated Smad2/3 phosphorylation (Fig 4A-C). Again, the legend in Fig 4C was different from the panel label. These experiments were done in cancer cells, phosphorylation of Smad2/3 should also be examined in cancer models.\n5. “Clinically” is inappropriately used in describing results under “loss of ALK4 induces EMT….”, as the finding described was from analysis of human samples, not clinical studies. Fig.4E is poorly described and not clear what the conclusion was reached, and it is certainly not a dot-plot.\n6. Fig. 4H, why DN-TbRII did not block TGF-b induction of Smad2 phosphorylation (shNTC data group)?\n7. The sActRIIB-Fc experiments appear to show that effects of ALK4 KO on TGF-b signaling not due to activin signaling per se. Since ALK4 was once thought to mediate TGF-b signaling and it does possess some effect, could it be that there is a negative feedback loop connecting ALK4 to TGF-b signaling?\n8. Fig.5A lacks controls showing ALK4 levels after KO. Fig.5D missing ALK4 expression control. sFig.9E is a haphazard control for Fig.5D.\n9. Galectin-3 was singled out based on mapped interactions with TGF-b targeted genes, coreceptors, FN1, MMP2, CD44, and endoglin in the STRING analysis. However, there are quite a few other nodes in this interaction network that have not been examined or ruled out. No compelling reason was given to proceed with Gal-3. It appears to be cherry picked.\n10. More importantly, authors showed that knockdown or KO ALK4 increased Gal-3 and Mgat5 transcription, the increased Gal-3 and Mgat5 promoted glycosylation of TGF-b receptors and increased TGF-b signaling, however, siTbRI had no effect on Gal-3 and Mgat5 transcription (sFig 12). Then how did shALK4 (or ALK4KO) enhance Gal-3 and Mgat5 transcription? Did Smad2 or Smad3 play a role in their transcription?"}, "author_response": "Response to referees\nPoint-by-point response\nReviewer #1\nWe thank the reviewer for finding that the manuscript is “interesting and thoroughly\ninvestigated” and provides “compelling evidence” supporting its central claims, including\nthat the “novelty in this manuscript” lies in the connection of ALK4 down regulation to\nMgat5/galectin-3 up-regulation.\nConcern 1: Additional investigation exploring the mechanism by which ALK4 loss\nupregulates Mgat5/galectin-3. would greatly strengthen the manuscript. At the very\nleast, the authors should look at non-canonical ALK signaling pathways. This should\ninclude assessing short-term changes in canonical and non-canonical signaling\npathways after acute blockage of ALK4.\nWe appreciate this concern, and as suggested, we investigated whether non-canonical ALK\nsignaling was aFected after acute blockage of ALK4 via siRNA mediated silencing of ALK4\nexpression. As shown in new sFigure 16, siRNA mediated silencing of ALK4 expression\nincreased p38 phosphorylation, without altering ERK or Akt signaling (sFigure 16A-C).\nHowever, inhibiting the p38-MAPK pathway using the small molecule inhibitor SB203580\ndid not aFect TGF-β signaling (sFigure 16D) or expression of MGAT5/galectin-3 (sFigure 16E,\nF). We also investigated whether ALK4 loss mediated increases in TGF-β signaling were\nresponsible for upregulating Mgat5/galectin-3, and demonstrated that they were not\n(sFigure 15). Finally, we investigated whether ALK4 loss upregulates MGAT5/galectin-3\nthrough a specific transcription factor. As shown in new sFigure 17, we found that\nexpression of the transcription factor ETS1 is significantly increased by ALK4 loss, and that\nsilencing of ETS1 decreased MGAT5 induction mediated by ALK4 loss expression, supporting a role of ETS1 downstream of ALK4 loss.\nConcern 2: Fig. 8 and associated supplemental data needs to done using MGAT5 KO\ncells (or inhibitors that specifically target branching like swainsonine or kifunensine),\nrather than NGI-1 and glucosamine. This should also be presented as the main figure\nand the NGI-1 and glucosamine data moved to supplemental. Unlike Mgat5 KO, NGI-1\nand glucosamine inhibit N-glycan attachment by blocking LLO biosynthesis leading to\nsignificant ER stress and unfolded protein responses (UPR). This can complicate\ninterpretation. In contrast, Mgat5 KO is a much subtler change to N-glycans, does not\ninduce ER stress or UPR, and most importantly is the precise change identified by loss\nof ALK4.\nWe appreciate this concern, and as suggested, we developed two MGAT5 CRISPR KO lines\nusing the PANC-1 NTC and ALK4 KO cells respectively. The knockout of MGAT5 was\nconfirmed using flow cytometry (new sFigure 14c). As the reviewer recommended, using in\nvitro and in vivo analysis, we investigated whether loss of ALK4 promotes cancer\nprogression through branched N-glycan catalyzed by MGAT5. As shown in new Figure 7h-k,\nwe observed a significant decrease in anchorage-independent growth and development of\npulmonary lesions when MGAT5 is depleted in ALK4 KO cancer models, supporting a role\nfor MGAT5 mediated branched N-glycan modifications in mediating the eFects of ALK4 loss.\nConcern 3: All metastasis models were via IV injection. A spontaneous metastasis\nmodel would strengthen the paper. At the very least the discussion and interpretation\nshould be adjusted to reflect this.\nWe agree that spontaneous metastasis models more accurately reflect the entire\nmetastatic process. We had 2 such models in the original manuscript, an orthotopic\npancreatic cancer model using HPNE shNTC and shALK4 cells (Figure 2 g-k) and an\northotopic breast cancer model using LM2 pBabe and LM2 pBabe ALK4 cells (sFigure 3 c-i).\nBoth studies support the role of ALK4 in suppressing tumor metastasis. We have increased\nthe clarity in describing these experiments in the revised manuscript. In addition, for all tail\nvein injection models, we now refer to the resulting pulmonary nodules as pulmonary\nlesions.\nTo complement these studies, we also included a GEMM of spontaneous pancreatic cancer\nand pancreatic cancer metastasis, with oncogenic KRASG12D driven by Pdx1-Cre, with or\nwithout ALK4 (ALK4fl/fl loss), which demonstrated decreased survival, increased incidence\nof adenocarcinoma and increased development of ascites with loss of ALK4 (new sFigure\n4).\nConcern 4: The authors demonstrate regulation of Mgat5 and its product, B1,6\nbranched glycans. However, no attempt is made to further characterize the\nglycosylation changes. The branching pathway enzymes are often regulated in a\ncoordinated fashion, or metabolically. At the very least the authors should examine\ngene expression for enzymes in the branching pathway (eg Mgat1, 2, Mgat4a,b,\nmannosidase 1a,b,c, mannosidase II/IIx) and the hexosamine biosynthetic pathway. In\naddition, glycomic analysis, or at least a panel of lectins in addition to L-PHA, should\nbe used to determine if the changes are restricted to the B1,6 branch.\nWe appreciate this concern, and as suggested, we have investigated whether loss of ALK4\naFects expression of other enzymes involved in modifying N-glycan, and whether these\neFects are specific to the B1,6 branch. We found that ALK4 loss specifically upregulates\nexpression of MGAT5 in both PANC-1 and MDA-MB-231 cells as shown in new sFigure 13d-e.\nConsistent with the expression data, using a lectin array, we observed that among all lectins\nthat recognized N-glycans, only the intensity of lectin PHA-L was significantly increased\n(FC>2, p value<0.05) by loss of ALK4 (new sFigure 13f-g).\nIn addition, we found that loss of ALK4 specifically increased expression of GFPT2 at both\nthe protein and RNA level in PANC-1 and MDA-MB-231 cells (Figure L1 A-C). GFPT1/2 are\nimportant rate-limiting enzymes in the hexosamine biosynthetic pathway (HBP) [1] which\nproduces uridine diphosphate-N-acetyl glucosamine, UDP-GlcNAc, a key metabolite that is\nused for N/O-linked glycosylation. Indeed, using mass spectrometry, we found that the level\nof UPD-GlcNac is significantly increased in both PANC-1 and MDA-MB-231 cells with ALK4\nloss (Figure L2D). This is consistent with the previous finding that cell surface receptors with\nfour or less NXS/T sites require higher UDP-GlcNAc and branching to be retained by the\ngalectin lattice [2].\nThe reason we specifically focused on MGAT5 in this manuscript is because galectin-3,\nas a potential lead acquired from our proteomic analysis, has the highest binding aFinity with\nMGAT5 catalyzed mediation of β1–6-GlcNAc branching [3, 4]. In this manuscript, we\nprimarily focused on the function of ALK4, specifically its novel role in regulation TGF-β\nreceptor glycosylation and cell surface stability. Therefore, we think that reporting ALK4\nregulation more broadly is beyond the scope of the current studies. We are currently\ninvestigating ALK4 regulation of the HBP and metabolism in ongoing work.\nFigure L1: Loss of ALK4 increases production of UDP-GlcNac level in breast and pancreatic cancer. (A-B) qRT-PCR\nanalysis of mRNA expression for key enzymes of hexosamine biosynthetic pathway in PANC-1 (A) and MDA-MB-231 (B)\nNTC and ALK4 KO cells, with GAPDH as the reference control. (C) Western blot analysis of GFAT2 and β-actin levels in\nPANC-1 and MDA-MB-231 NTC and ALK4 KO cells. (D) Bar graph showing total amount of UDP-GlcNac in PANC-1 NTC\nand ALK4 KO cells and MDA-MB-231 NTC and ALK4 KO cells. For comparison between two groups, data were analyzed\nusing two-tail Student’s t tests. * p<0.05, **** p<0.0001.\nConcern 5: The abstract, introduction and discussion should be updated to better\nreflect the published data that N-glycan branching and Mgat5 N-glycosylation regulate\nEMT/invasion/metastasis by decreasing TGFbRI/II endocytosis (to increase TGFb\nsignaling)1-4. The concept of the galectin-glycoprotein lattice as an overall regulator\nof glycoprotein endocytosis should also be mentioned in the discussion6-8.\nThese previous findings have been further described in the abstract, introduction and\ndiscussion, and the corresponding references have been cited.\nOther Minor Issues\nConcern 6: Supplemental figures should be in the order they are described in the text.\nThis has been addressed throughout the manuscript.\nConcern 7: P-values and statistical tests should be defined in figure legends.\nP value and the statistical tests used have been defined in the figure legends as requested.\nConcern 8: Fig. 2C should have statistical analysis and sample size.\nThe p value and sample size for Fig. 2C has been added.\nConcern 9: Sample size and number of times experiments repeated needs to be stated\nin the Figure legends.\nSample size and the number of times experiments repeated are stated in the figure legends.\nConcern 10: Quantitation of western blots should be provided throughout the\nmanuscript to allow comparison between experiments.\nWe have performed quantification all western blots throughout the manuscript and this is\nnow included in Supplemental Table 4, or in the Figures and Supplemental Figures.\nConcern 11: Blots should be consistently labelled, including addition of blot type to\nthe panels (eg WB vs I-125-TGF-b cross-linking)\nAll blots have been labelled.\nConcern 12: Fig. 5H top panel, Fig S9B left panel and Fig S9D upper right panel should\nall have longer exposures.\nWe have adjusted the exposure of all panels as requested.\nConcern 13: Unclear why switched to 293T cell in 5C,E ,F. Should be one of the cancer\nlines.\nOur goal for performing these experiments was to determine whether ALK4 kinase activity is\ninvolved in regulating receptor stability. 293T cells are well known for their rapid growth,\nease of transfection, reproducibility and robust protein stability, allowing us to focus on the\neFects of the diFerent ALK4 mutants. Nonetheless, we repeated Figure 5c in MDA-MB-231\nLM2 cells and similar results were observed (Figure L2).\nFigure L2: MDA-MB-231 LM2 cells were transfected with TβRII along with pcDNA3.1, WT ALK4, or DN\nALK4. The cell surface level of TβRII and level of ALK4 and β-actin were assessed using western\nblotting.\nConcern 14: Were any measures taken to ensure that observers were blinded to the\nexperimental conditions, for example in the case of counting metastatic nodules or\ngross metastases in Fig2D-M. If so these should be described in the manuscript.\nIn general, wherever possible observers were blinded to the experimental conditions. For\nexample, in the evaluation of cell migration and invasion, these were all quantitated by\nobservers blinded to the experimental conditions. Similarly, for histology analysis, the\nobserver (a Duke certified pathologist) was blinded to the experimental conditions. This\npractice is noted in the material and methods section.\nConcern 15: Additional methodological detail should be provided. For example, in the\nTGFb treatment experiments, how was serum resting performed.\nThroughout the manuscript, we have increased the level of methodological details, including\ndetails of serum starvation, in the corresponding figure legends.\nConcern 16: What is the rationale for pre-treating for 72 hours with soluble activin\nreceptor prior to 30min activin treatment? A shorter term incubation would be more\nappropriate.\nWe agree with the reviewer that for determining whether signaling mediator pSmad2 is\nchanged, a short-term incubation would have been suFicient. However, we also wanted to\ninvestigate whether TGF-β signaling and TGF-β induced EMT were altered upon activin A\ninhibition, and given the high cost of the reagent (soluble activin receptor), we decided to\nperform a 3-day treatment to inhibit activin A in the serum throughout the 3 day experiment.\nConcern 17: For Fig12H,I quantitation should be presented in bar graphs.\nThis quantitation is now shown in Supplemental Figure 15 (h-i).\nConcern 18: Mgat5 mRNA levels should be measured in siMgat5 condition. The\ndecrease in LPHA staining suggests poor inhibition of Mgat5. Or use Mgat5 KO as\nsuggested above.\nThe high basal level of PHA-L stain in siMGAT5 condition is due to nonspecific background\nstaining. We did perform RT-qPCR to validate the siMGAT5 knockdown condition and now\ninclude this data (sFigure 14b). In addition, we have performed the experiment with Mgat5\nKO (new sFigure14c).\nConcern 19: Quantitation of Fig S14F is needed.\nQuantitative data for the lung lesions are shown in Figure 8m. We have removed sFigure\n14F to reduce redundancy.\nReviewer #2\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nReviewer #3 (Remarks to the Author):\nWe thank the reviewer for finding that the manuscript “presents extensive findings that\nsupport a highly novel concept,” and that this is “an extremely rigorous study that clearly\npresents highly innovative data that has the potential to lay the groundwork for a mechanistic\nunderstanding of EMT and metastasis not previously recognized.”\nConcern 1: Several pieces of data are presented establishing that Alk4 is decreased in\nbreast and PANC and that this is associated with disease progression. Some discussion\ncould be ogered as to what events lead to the loss of Alk4, i.e. genetic,\ntranscriptional, post-transcriptional.\nWe appreciate this concern. While ALK4 is mutated, there are other mechanisms\ncontributing to loss of ALK4 function, including loss of copy number/loss of heterozygosity.\nIn addition, we now provide evidence supporting epigenetic silencing of the ALK4 gene,\nincluding data demonstrating that treating pancreatic and breast cancer cells with 5-AZA\nincreased ALK4 expression, and that methylation of the ALK4 promoter in tumor samples\ncorrelates with decreased ALK4 expression (new sFigure 2c-h). These data and an overall\ndiscussion of mechanisms of loss of ALK4 function have been added to the revised\ndiscussion.\nConcern 2: NGI-1 is a highly insoluble compound. Some level of PD from the in vivo\nstudies (i.e. changes in TBR-I or other protein glycosylation) would help support on-\ntarget egects of the observed anti-tumor activity.\nWe appreciate this concern. Indeed, during the in vivo analysis presented, we had the\nsame concern and performed a thorough investigation to mitigate this challenge. As the\nPANC-1 NTC and ALK4 KO cells already carried the luciferase reporter system to assess for\npulmonary lesions, we were not able to use the original luciferase based reporter system\n[5, 6] to assess for changes in glycosylation. Therefore, we investigated alternative\napproaches for drug delivery. We prepared the solution right before injection based on a\nrecently published study [7]. In addition, to address the reviewer’s concern, we performed\nIHC staining for PHA-L to support the eFectiveness of NGI-1 treatment, demonstrating that\nNGI-1 decreased PHA-L levels. These data were have been added as new sFigure 18c.\nConcern 3: The use of the term metastasis in reference to pulmonary tumors\nestablished by tail vein inoculation should be modified to pulmonary lesions or\nsomething similar.\nWe appreciate this concern. In response, for all tail vein studies, the description of the\nresults has been changed to pulmonary lesions.\nReviewer #4\nWe thank the reviewer for their careful review of the manuscript.\nConcern 1: While at a first glance the hypothesis that the loss of ALK4 contributes to\ncancer progression might seem appealing, the study does not provide compelling\nevidence to support such claim. It also lacks the conceptual advance needed for\nestablishing the relevance of this mechanism to the human diseases. Indeed, the vast\nmajority of experiments are superficial in nature, relying mostly on in vitro cell systems,\nwhich could lead to all sorts of artifacts.\nIn this manuscript, we used diFerent knockdown and knockout models including transient\nknockdown using siRNA, stable knockdown using shRNA, CRISPR knockout and Cre\nrecombinase mediated genetic deletion to observe consistent eFects of ALK4 loss on\ncancer progression. We further used unbiased proteomic analysis to establish mechanistic\nleads, and validated this mechanism in epistatic experiments, including in vivo studies. In\naddition to extensive in vitro analysis, we performed in vivo mouse studies including tail vein\ninoculation and orthotopically injection using 4 diFerent cell lines with both loss and gain of\nfunction models, and now add a GEMM. We realize that any scientific method has its\nlimitations, but utilizing multiple complementary approaches, we have provided consistent\nresults.\nConcern 2: The authors relied heavily on several public datasets to show that ALK4 is\nlost in breast and pancreatic cancers, with low levels of ALK4 correlating with poor\nprognosis. The authors might want to consider corroborating these data using qRT-PCR\nor immunohistochemistry with tissue microarrays. In any case, considering the\npossibility that ALK4 expression is lost in breast and pancreatic cancers, one would\nwonder what mechanisms could contribute to this phenomenon in the cancerous\nsamples that do not display any mutation or loss of copy numbers? Is there any other\ngenetic or epigenetic event that could compromise ALK4 expression? This information\nis important for understanding the exact contribution of ALK4 to cancer progression and\nmetastasis.\nWe agree with the reviewer’s concern. For the presented in silico analysis, we investigated in\ntotal 192 PAAD GEO datasets and 1,464 BRCA GEO datasets, the presented datasets meet\nthe following criteria: 1) datasets that contain gene expression profile from normal tissue;\nand 2) datasets that contain a minimum of 3 samples in each group (normal tissue and\ntumor tissue). To corroborate our in silico data, as the reviewer suggested, we acquired RNA\nsamples from patients with pancreatic primary tumors and adjacent normal tissue from\nDuke BioRepository & Precision Pathology Center. Consistent with published database,\nACVR1B expression is significantly lower in tumor tissues (new Figure 1c).\nWhile somatic mutation of ALK4 have been identified in a small percentage of breast and\npancreatic cancers, there are other mechanisms contributing to loss of ALK4 function,\nincluding loss of copy number/loss of heterozygosity. In addition, we now provide evidence\nsupporting epigenetic silencing of the ALK4 gene, including data demonstrating that treating\npancreatic and breast cancer cells with the DNA methylation inhibitor 5-azacytidine (5-AZA)\nincreased ALK4 expression, and that methylation of the ALK4 promoter in tumor samples\ncorrelates with decreased ALK4 expression (new sFigure 2c-h). These data and an overall\ndiscussion of mechanisms of loss of ALK4 function have been added to the revised\ndiscussion.\nConcern 3: The expression levels of ALK4 seem to be inversely correlated with the\naggressiveness and metastatic potential of breast and pancreatic cancer cell lines.\nHowever, this correlation is based on very artificial invasion assays in vitro. To support\ntheir claim, the authors might want to consider characterizing these cell lines in vivo,\nboth in terms of tumor growth and metastatic potential.\nWe appreciate this concern of the reviewer. To evaluate the metastatic potential of these\ncell lines, we performed tail vein inoculation using PANC-1, HPNE, Mia Paca 2 and ASPC1\ncells expressing luciferase. Briefly, half million cells of each line were injected into 8 NSG\nmice and the average bioluminescence was detected every week for up to 6 weeks. As\nshown in Figure L3, we observed that ASPC1 was the most aggressive cells line, followed by\nMia Paca 2 and then HPNE/PANC-1. Accordingly, we agree with the reviewer’s concern and\nhave deleted this correlative data from the revised manuscript.\nFigure L3. Evaluation of metastatic potential of di_erent PDAC cells. 5×105 ASPC1, Mia Paca2, HPNE, or PANC-\n1 cells were injected into the tail vein of NSG mice (n=8 per group). Pulmonary lesions were detected using in\nvivo imaging. (A) The fold change of bioluminescence of each group is shown. (B) Overall survival of mice\ninjected with indicated PDAC cells.\nConcern 4: To provide compelling evidence that the loss of ALK4 contributes to cancer\nprogression, it is imperative to conduct in vivo experiments with autochthonous mouse\nmodels of breast and pancreatic cancer. It would be straightforward to delete AcvR1B\nin mouse models of breast and pancreatic cancer (such as in MMTV-PyMT or KC mice\nwith conditional expression of KrasG12D in the pancreatic epithelium). These\nexperimental approaches must be presented at his level of publication.\nWe agree with this concern, and in response, we have incorporated in vivo experiments with\nautochthonous mouse models of pancreatic cancer, with oncogenic KRASG12D driven by\nPdx1-Cre, with or without ALK4 (ALK4fl/fl loss), which demonstrated decreased survival and\nincreased spontaneous metastases with loss of ALK4 (new sFigure 4). The corresponding\nGEMM mouse data is now described and discussed in the revised manuscript.\nConcern 5: ALK4 seems to induce expression of TβRI and TβRII at the surface by a\nmechanism dependent on its kinase activity. What is the substrate of ALK4 under these\nconditions? This information is important for understanding how ALK4 fulfills its anti-\ntumor suppressive function in breast and pancreatic cancers. Also important is what\nsignaling pathway functions downstream of ALK4 to suppress cancer progression and\nmetastasis? Without providing this kind of data, the impact of the study will be just\nincremental.\nWe appreciate this concern. While we have not been able to define the precise substrate\ndirectly phosphorylated by ALK4 to mediate these eFects, we have investigated the\nmechanism by which loss of ALK4 mediates its eFects on increasing MGAT5 and galectin-3.\nAs another reviewer suggested, we first have investigated whether non-canonical ALK\nsignaling was aFected after acute blockage of ALK4 via siRNA mediated silencing of ALK4\nexpression. As shown in new sFigure 16, siRNA mediated silencing of ALK4 expression\nincreased p38 phosphorylation, without altering ERK or Akt signalling (sFigure 16a-c).\nHowever, inhibiting the p38 pathway using the small molecule inhibitor SB203580 did not\naFect TGF-β signaling or expression of MGAT5/galectin-3 (sFigure 16d-f). We also\ninvestigated whether ALK4 loss mediated increases in TGF-β signaling were responsible for\nupregulating Mgat5/galectin-3 to induce expression of TβRI and TβRII, and demonstrated\nthat they were not (sFigure 15). Finally, we investigated whether ALK4 loss upregulates\nMgat5/galectin-3 through a specific transcription factor. As shown in new sFigure 17, we\nfound that ETS1 expression is significantly increased by ALK4 loss, and that silencing of ETS1\ndecreased MGAT5 induction mediated by ALK4 loss expression, supporting a role of ETS1\ndownstream of ALK4 loss.\nConcern 6: Loss of ALK4 correlates with increased expression of MGAT5 and galectin-3,\nwhich could provide a mechanistic explanation as to how ALK4 regulates the N-\nglycosylation and thereby stability of TβRI and TβRII at the cell surface. There are at\nleast three issues with this observation. First, the mechanism leading to the\naccumulation MGAT5 and galectin-3 in cells deficient for Alk4 was not explored. Second,\ncompelling evidence that TβRI and TβRII are direct substrate of MGAT5 and galectin-3\nwas not presented. Third, compelling evidence that MGAT5 and galectin-3 functions\ndownstream of ALK4 in vivo under physiological conditions is missing. The latter could\nbe easily achieved through using mice or cells co-deleted of MGAT5 /galectin-3 and Alk4\nand treated with the two inhibitors NGI-1 and Glucosamine.\nWe have investigated the mechanism by which loss of ALK4 mediates its eFects on\nincreasing MGAT5 and galectin-3, as addressed in Concern 5. In terms of whether TβRI and\nTβRII are direct substrates of MGAT5 and galectin-3, this connection was established by\nPartridge et al [8], so we did not re-address here. We did establish that MGAT5 modified\nbranched N- glycan were increased on TβRII (Figure 7d) and that internalization of TβRII level\nis decreased in the absence of ALK4 (Figure 7g) to further support this connection. To\naddress whether MGAT5 is downstream of ALK4, we developed isogenic MGAT5 CRISPR KO\ncells using the PANC-1 NTC and ALK4 KO cells respectively. The knockout of MAGT5 was\nconfirmed using flow cytometry (new sFigure 14c). As shown in new Figure 7h-k, we\nobserved a significant decrease in anchorage-independent growth and development of\npulmonary lesions when MGAT5 is depleted in ALK4 KO cancer models, supporting a role for\nMGAT5 mediated branched N-glycan modifications in mediating the eFects downstream of\nALK4 loss.\nConcern 7: Overall, the study lacks the mechanistic depth for firmly establishing a role\nfor ALK4 in suppressing cancer progression and metastasis. It also lacks the\nmechanistic depth for firmly establishing how ALK4 regulates the stability of TβRI and\nTβRII at the cell surface and attendant activation of TGF-β/Smad signaling pathway.\nExpression of ALK4 at the cell surface might simply rely on the same mechanism as\ndoes localization of TβRI and TβRII, so one conceivable mechanism would be that ALK4\nmight compete with TβRI and TβRII for the machinery that drives their cell surface\nlocalization.\nWe believe we have presented strong evidence for ALK4 in suppressing cancer progression,\nand mechanistic insight into how ALK4 regulates the stability of TβRI and TβRII, via MGAT5\nand galectin-3. In terms of whether ALK4 might compete with TβRI and TβRII for the\nmachinery that drives their cell surface localization, given the similarity between ALK4 and\nTβRI we considered that possibility, however our proteomic data and preliminary data\nsupport the upregulation of a broad spectrum of glycosylated cell surface\nproteins/receptors, including integrins in PANC-1 cells and VEGFR2 in endothelial cells\n(Figure 6g and Figure L4), making this less likely. This is now discussed.\nFigure L4. Loss of ALK4 promotes VEGFA-VEGFR2 signaling through regulating VEGFR2 glycosylation and stability. (A)\nMEEC cells expressing shNTC or shALK4 were treated with VEGF-A (50ng/ml) for the indicated times, and cell surface\nlevels of VEGFR2 were assessed by a cell surface biotinylation assay. (B) Beads were coated with PHA-L lectin and\nincubated with protein isolated from MEEC NTC and ALK4 KD cell lysate. Eluted samples and whole cell lysate were\nanalyzed for VEGFR2. (C) MEEC cell expressing shNTC and shALK4 were treated with or without VEGFA for 10min.\nProtein lysate from MEEC shNTC and shALK4 cells were analyzed for indicated protein using western blotting.\nReviewer #5\nWe thank the reviewer for finding that the manuscript presents three major findings, each\n“supported individually by a large body of data”\nConcern 1: The mechanism that links loss of ALK4 function to Gal-3 and Mgat5\ntranscription and thereby glycosylation of TGF-beta receptors is missing.\nWe appreciate this concern. In response we investigated whether non-canonical TGF-β\nsignaling was aFected after acute blockage of ALK4 via siRNA mediated silencing of ALK4\nexpression. As shown in new sFigure 16, siRNA mediated silencing of ALK4 expression\nincreased p38 phosphorylation, without altering ERK or Akt signaling (sFigure 16a-c).\nHowever, inhibiting the p38 pathway using the small molecule inhibitor SB203580 did not\naFect TGF-β signaling or expression of MGAT5/galectin-3 (sFigure 16d-f). We also\ninvestigated whether ALK4 loss mediated increases in TGF-β signaling were responsible for\nupregulating Mgat5/galectin-3, and demonstrated that they were not (sFigure 15). Finally, we\ninvestigated whether ALK4 loss upregulates Mgat5/galectin-3 through a specific\ntranscription factor. As shown in new sFigure 17, we found that ETS1 expression is\nsignificantly increased by ALK4 loss, and that silencing of ETS1 decreased MGAT5 induction\nmediated by ALK4 loss expression, supporting a role of ETS1 downstream of ALK4 loss.\nConcern 2: The data/experiment description are insugicient, imprecise/inaccurate,\nand often hard to follow.\nWe have worked with a professional scientific writer/editor to improve the detail and clarity\nof the description of data and experiments in the results, methods, and figure legends.\nConcern 3: Comparison of ALK4 levels in various cancer cell lines is not meaningful or\nsuperficial at best (sFig.2C-D), as underlying causal factors vary from one cell type to\nanother. For the same reason, comparison in sFig.9A is also problematic, e.g. ALK4 level\nis similar between 168FARN and 4T07 (sFig 2D) but cell surface TGFbR are quite digerent\n(sFig 9A). Moreover, the data were too scarce to support the correlation.\nWe appreciate this concern of the reviewer. To evaluate the metastatic potential of these\ncell lines, we performed tail vein inoculation using PANC-1, HPNE, Mia Paca 2 and ASPC1\ncells expressing luciferase. Briefly, half million cells of each line were injected into 8 NSG\nmice and the average bioluminescence was detected every week for up to 6 weeks. As\nshown in Figure L3, we observed that ASPC1 was the most aggressive cell line, followed by\nMia Paca 2 and then HPNE/PANC-1. Accordingly, we agree with the reviewer’s concern and\nhave deleted this correlative data from the revised manuscript.\nConcern 4: Authors made several lines of stable cells expressing shALK4 or ALK4 gRNA.\nThese lines were used interchanged throughout the manuscript. It is not clear why\nsome experiments using the shALK4 lines while others using the ALK4KO lines.\nSometimes panels were labelled with ALK4KO while legend said otherwise.\nThis is a study that has been going on for several years. The lab first started the investigation\nof ALK4 using cells stably expressing shRNA. With the emergence of CRISPR-Cas9 technique,\nwe then incorporated the CRISPR KO system into our study as the main approach to stably\nknockout ALK4 due to higher fidelity and eFiciency. Therefore, diFerent cell models were\npresented in this manuscript. The presented phenotypical evaluation has been tested using\nboth knockdown and knockout models. We have carefully examined the figures and\ncorresponding legends to make sure it is clear which model is being used in each study.\nConcern 5: Experiments in (Fig.2G-M were inadequately described. Legend 2G says the\ncells were implanted in “the tail of pancreas”. Were they implanted in the pancreas or\ninjected in tail vein?\nThese experiments (now Figure 2 g-k) are orthotopic injection into the tail of mouse pancreas,\nas recommended by the previously published protocols [9, 10]. Supplemental Figure 3 (c-i)\nare orthotopic injection to mouse 4th mammary gland. Both analyses support that ALK4\nsuppresses spontaneous metastasis in these orthotopic models. This is now clearly\nindicated in the manuscript.\nConcern 6: It is known that both activin and TGF-b are capable of inducing Smad2 and\nSmad3 phosphorylation. And it appears that ALK4 KO by itself consistently induced\nSmad2 phosphorylation, and enhanced TGF-b-mediated Smad2/3 phosphorylation (Fig\n4A-C). Again, the legend in Fig 4C was digerent from the panel label. These experiments\nwere done in cancer cells, phosphorylation of Smad2/3 should also be examined in\ncancer models.\nWe have corrected the figure legend for Figure 4c. We also examined pSmad2 in mouse\npancreas injected with HPNE shNTC and shALK4 cells as shown in Supplemental Figure 7D.\nConcern 7: “Clinically” is inappropriately used in describing results under “loss of ALK4\ninduces EMT….”, as the finding described was from analysis of human samples, not\nclinical studies. Fig.4E is poorly described and not clear what the conclusion was\nreached, and it is certainly not a dot-plot.\nWe have corrected the description as patient data/in silico data. Also Figure 4e has been\nrephrased to accurately reflect the data.\nConcern 8: Fig. 4H, why DN-TbRII did not block TGF-b induction of Smad2\nphosphorylation (shNTC data group)?\nThe original Figure 4H was performed with a 2 hour TGF-β treatment while all other WB\nassessing pSmad2 were performed with a 30 min TGF-β1 treatment. Therefore, we repeated\nthis study with 30min TGF-β1 treatment 3 times and a representative figure panel and\nquantification of pSmad2/tSmad2 is shown as new Figure 4H. The new control\ndemonstrating successful transfection of DN-RII is shown in sFigure 8a.\nConcern 9: The sActRIIB-Fc experiments appear to show that egects of ALK4 KO on TGF-\nb signaling not due to activin signaling per se. Since ALK4 was once thought to mediate\nTGF-b signaling and it does possess some egect, could it be that there is a negative\nfeedback loop connecting ALK4 to TGF-b signaling?\nWhile we have considered the possibility that there is negative feedback loop connecting\nALK4 to TGF-β signaling, given that loss of ALK4 function increases the levels of multiple cell\nsurface receptors beyond TGF-β receptors, and their downstream signaling, we believe that\nthe delineated pathway is the most likely explanation for the identified eFects. This is now\ndiscussed in the revised manuscript.\nConcern 10: Fig.5A lacks controls showing ALK4 levels after KO. Fig.5D missing ALK4\nexpression control. sFig.9E is a haphazard control for Fig.5D.\nThe ALK4 KD control for Fig. 5a is shown in new Supplemental Figure 11a. The ALK4 OE\ncontrol for Figure 5d is shown in Supplemental Figure 3b.\nConcern 11: Galectin-3 was singled out based on mapped interactions with TGF-b\ntargeted genes, coreceptors, FN1, MMP2, CD44, and endoglin in the STRING analysis.\nHowever, there are quite a few other nodes in this interaction network that have not\nbeen examined or ruled out. No compelling reason was given to proceed with Gal-3.\nIt appears to be cherry picked.\nWhile STRING analysis was used to identify potential interactors, we ranked all clustered\ngenes based on the number of interactions. The top 5 genes ranked in sequences were:\nFN1 (19), ITGB3 (14), THBS1 (13), LGALS3 (11), and CD44 (10). All of these genes, with the\nexception of galectin-3, were known to be regulated by TGF-beta signaling. In addition, many\nof the other genes linked to galectin-3 were TGF-beta regulated genes, thus our focus on\ngalectin-3. We didn’t ignore other important nodes like integrins (ITGA3, ITGB3, ITGB4),\nand we are now writing another manuscript focusing on ALK4 regulation of integrins in\npancreatic cancer. We have now described the rationale for focusing on galectin-3 in the\nresults section.\nConcern 12: More importantly, authors showed that knockdown or KO ALK4 increased\nGal-3 and Mgat5 transcription, the increased Gal-3 and Mgat5 promoted glycosylation\nof TGF-b receptors and increased TGF-b signaling, however, siTbRI had no egect on Gal-\n3 and Mgat5 transcription (sFig 12). Then how did shALK4 (or ALK4KO) enhance Gal-3\nand Mgat5 transcription? Did Smad2 or Smad3 play a role in their transcription?\nWe have tested the role of Smad2 by knocking down Smad2 with specific siRNA\n(Supplemental Figure 15j-k), demonstrating that induction of galectin-3 and MGAT5 was not\nchanged. However, we did find that loss of ALK4, at least partially, upregulates MGAT5\nexpression through the ETS1 transcription factor (new Supplemental Figure 17).\nReferences\n1. Zhang, H., et al., Common variants in glutamine:fructose-6-phosphate\namidotransferase 2 (GFPT2) gene are associated with type 2 diabetes, diabetic\nnephropathy, and increased GFPT2 mRNA levels. J Clin Endocrinol Metab, 2004.\n89(2): p. 748-55.\n2. Lau, K.S., et al., Complex N-glycan number and degree of branching cooperate to\nregulate cell proliferation and diHerentiation. Cell, 2007. 129(1): p. 123-34.\n3. Nielsen, M.I., et al., Galectin binding to cells and glycoproteins with genetically\nmodified glycosylation reveals galectin-glycan specificities in a natural context. J\nBiol Chem, 2018. 293(52): p. 20249-20262.\n4. Hirabayashi, J., et al., Oligosaccharide specificity of galectins: a search by frontal\naHinity chromatography. Biochim Biophys Acta, 2002. 1572(2-3): p. 232-54.\n5. Contessa, J.N., et al., Molecular imaging of N-linked glycosylation suggests glycan\nbiosynthesis is a novel target for cancer therapy. Clin Cancer Res, 2010. 16(12): p.\n3205-14.\n6. Baro, M., et al., Oligosaccharyltransferase Inhibition Reduces Receptor Tyrosine\nKinase Activation and Enhances Glioma Radiosensitivity. Clin Cancer Res, 2019.\n25(2): p. 784-795.\n7. Scheich, S., et al., Targeting N-linked Glycosylation for the Therapy of Aggressive\nLymphomas. Cancer Discov, 2023. 13(8): p. 1862-1883.\n8. Partridge, E.A., et al., Regulation of cytokine receptors by Golgi N-glycan processing\nand endocytosis. Science, 2004. 306(5693): p. 120-4.\n9. Jiang, Y.J., et al., Establishment of an orthotopic pancreatic cancer mouse model:\ncells suspended and injected in Matrigel. World J Gastroenterol, 2014. 20(28): p.\n9476-85.\n10. Pang, T.C.Y., et al., An Orthotopic Resectional Mouse Model of Pancreatic Cancer. J\nVis Exp, 2020(163)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have made a solid attempt to address our concerns, but some minor issues need to be addressed before publication:\nConcern 1: Recommend to put ETS1 data in main figure, and cite known regulation of Mgat5 by ETS1\nConcern 2: the new Mgat5KO data is convincing, but recommend that TGFb signaling be assessed as in Fig8A. Also again strongly recommend that Fig. 8 should be moved to supplemental figures and the new Mgat5KO data be its own Figure.\nConcern 3: The spontaneous metastatic data is limited (see issues below) and at the very least the interpretation should acknowledge that the effects on metastasis were less clear.\nIn Fig2k - Statistical analysis for this panel is confusing. 3/8 is 37.5% not 45%. The figure legend states that this was done by Mann-Whitney. Statistical analysis should be re-done as a contingency table and clarifying whether the same mouse had multiple mets or all mice with mets were different mice. Alternatively, the number of mets per mouse could be shown leaving aside location.\nIn FigS3g, lung mets should be quantitated.\nIn FigS4, ascites can reflect local invasion rather than metastasis and the two should not be grouped together.\nsFIG4a: x-axis should say days not months\nConcern 4: Please clarify the lectin array methodology in the manuscript. Is this using lysate or cells?\nFigure FigL1 should be included in the paper with a clear definition of the mass spec assay used. Is this UDP-HexNAc or UDP-GlcNAc? Discuss discrepancy between UDP-GlcNAc and lectin array. Why so few changes in lectin binding? Also, why no increases in Galectin staining as expected?\nConcern 5: The authors have largely updated the abstract, introduction and discussion to better reflect the published data that N-glycan branching, but a sentence in the abstract should be changed (as highlighted in red) below to be more accurate:\n“Consistent with prior observation that galectin-3 preferentially binds to MGAT5-modified glycoproteins to stabilize cell surface receptors like TGF-β receptors, we found that ALK4 loss enhanced MGAT5-mediated glycosylation of TGF-β receptors,…”\nConcern 6-8: Addressed.\nConcern 9: Some figure legends state that in vitro experiments were done with 3 biological replicates, but do not state if the experiments were independently replicated. This should be clarified. Some figure legends state the number of independent experiments but others do not. This should be clearly stated in all figure legends.\nConcern 10: Some WBs have been quantitated in the figures, others have been presented as a supplemental excel file. It would be best if all WB quantitation was present within the figures (at least the main figures).\nConcern 13: Figure L2 should be in the manuscript in the main figure as Fig5d.\nConcern 14: We could not find blinding in the methods section, this should be corrected. In addition, the figure legends should state when blinding was performed.\nOther Minor concerns:\nFigure 1 legend is incomplete or cut off in the PDF.\nThe figures often refer only to “KO”. These should be fixed to identify the specific KO (eg “ALK4 KO”)", "reviewer_3": "The authors have addressed my previous, minor, critiques. The authors should be commended on completion of this highly impactful, rigorous, and scientifically interesting manuscript.\nAbstract line 44; consistent with prior observations", "reviewer_4": "This second revision focuses solely on the original concerns raised by this reviewer.\nThe observation that ALK4 may function as a tumor suppressor in breast and pancreatic cancers by antagonizing TβRI/TβRII is intriguing and warrants further mechanistic and translational studies. However, the level of innovation may be limited, as TβRI and TΒRII themselves can act as tumor suppressors depending on the physiopathological context.\nAdditional unresolved issues include the absence of robust mechanistic studies, which may stem from the use of insufficiently advanced technologies. Overall, this paper does not present the conceptual advancements necessary to drive new discoveries suitable for publication in a high-profile journal.\nReviewer concern 1: While at a first glance the hypothesis that the loss of ALK4 contributes to cancer progression might seem appealing, the study does not provide compelling evidence to support such claim. It also lacks the conceptual advance needed for establishing the relevance of this mechanism to the human diseases. Indeed, the vast majority of experiments are superficial in nature, relying mostly on in vitro cell systems, which could lead to all sorts of artifacts.\nReviewer concern 2: The authors relied heavily on several public datasets to show that ALK4 is lost in breast and pancreatic cancers, with low levels of ALK4 correlating with poor prognosis. The authors might want to consider corroborating these data using qRT-PCR or immunohistochemistry with tissue microarrays. In any case, considering the possibility that ALK4 expression is lost in breast and pancreatic cancers, one would wonder what mechanisms could contribute to this phenomenon in the cancerous samples that do not display any mutation or loss of copy numbers? Is there any other genetic or epigenetic event that could compromise ALK4 expression? This information is important for understanding the exact contribution of ALK4 to cancer progression and metastasis.\nReviewer concern 3: The expression levels of ALK4 seem to be inversely correlated with the aggressiveness and metastatic potential of breast and pancreatic cancer cell lines. However, this correlation is based on very artificial invasion assays in vitro. To support their claim, the authors might want to consider characterizing these cell lines in vivo, both in terms of tumor growth and metastatic potential.\nReviewer concern 4: To provide compelling evidence that the loss of ALK4 contributes to cancer progression, it is imperative to conduct in vivo experiments with autochthonous mouse models of breast and pancreatic cancer. It would be straightforward to delete AcvR1B in mouse models of breast and pancreatic cancer (such as in MMTV-PyMT or KC mice with conditional expression of KrasG12D in the pancreatic epithelium). These experimental approaches must be presented at his level of publication.\nReviewer concern 5: ALK4 seems to induce expression of TβRI and TβRII at the surface by a mechanism dependent on its kinase activity. What is the substrate of ALK4 under these conditions? This information is important for understanding how ALK4 fulfills its anti-tumor suppressive function in breast and pancreatic cancers. Also important is what signaling pathway functions downstream of ALK4 to suppress cancer progression and metastasis? Without providing this kind of data, the impact of the study will be just incremental.\nReviewer concern 6: Loss of ALK4 correlates with increased expression of MGAT5 and galectin-3, which could provide a mechanistic explanation as to how ALK4 regulates the N-glycosylation and thereby stability of TβRI and TβRII at the cell surface. There are at least three issues with this observation. First, the mechanism leading to the accumulation MGAT5 and galectin-3 in cells deficient for Alk4 was not explored. Second, compelling evidence that TβRI and TβRII are direct substrate of MGAT5 and galectin-3 was not presented. Third, compelling evidence that MGAT5 and galectin-3 functions downstream of ALK4 in vivo under physiological conditions is missing. The latter could be easily achieved through using mice or cells co-deleted of MGAT5 /galectin-3 and Alk4 and treated with the two inhibitors NGI-1 and Glucosamine.\nReviewer concern 7: Overall, the study lacks the mechanistic depth for firmly establishing a role for ALK4 in suppressing cancer progression and metastasis. It also lacks the mechanistic depth for firmly establishing how ALK4 regulates the stability of TβRI and TβRII at the cell surface and attendant activation of TGF-β/Smad signaling pathway. Expression of ALK4 at the cell surface might simply rely on the same mechanism as does localization of TβRI and TβRII, so one conceivable mechanism would be that ALK4 might compete with TβRI and TβRII for the machinery that drives their cell surface localization.\nReviewer #5\n(Remarks to the Author)\nThe authors made substantial improvement in the revised manuscript, and addressed most issues raised previously. With regard to the missing mechanism that accounts for the increased Mgat5 transcription/TbR glycosylation due to loss of ALK4, the authors performed some additional experiments to examine noncanonical TGF-b signaling. However, the results were inconclusive and the newly reported link to ETS1 is insufficiently informative. Given that a role of ActRIIB was also ruled out, the authors should acknowledge as such at least in the discussion to leave this issue open for future exploration.", "reviewer_author_response": "Point-by-point response\nReviewer #1\nWe thank the reviewer for finding that the original manuscript is “interesting and thoroughly\ninvestigated” and provides “compelling evidence” supporting its central claims, including that\nthe “novelty in this manuscript” lies in the connection of ALK4 down regulation to\nMgat5/galectin-3 up-regulation. For the revised manuscript, we thank the reviewer for finding\nthat “The authors have made a solid attempt to address our concerns.”\nConcern 1: Recommend to put ETS1 data in main figure, and cite known regulation of\nMgat5 by ETS1\nThis has been addressed, ETS1 data are now included in new Figure 8, and regulation of MGAT5\nby ETS1 is cited in the revised manuscript (lines 348-349).\nConcern 2: the new Mgat5KO data is convincing, but recommend that TGFb signaling be\nassessed as in Fig8A. Also again strongly recommend that Fig. 8 should be moved to\nsupplemental figures and the new Mgat5KO data be its own Figure.\nThe recommended evaluation of TGF-β signaling has been performed and is now shown as new\nsFig. 14D. We have also moved original Figure 8 to Supplementary figures (sFig. 18 and 19) as\nthe reviewer recommended.\nConcern 3: The spontaneous metastatic data is limited (see issues below) and at the very least\nthe interpretation should acknowledge that the effects on metastasis were less clear.\nIn Fig. 2k - Statistical analysis for this panel is confusing. 3/8 is 37.5% not 45%. The figure\nlegend states that this was done by Mann-Whitney. Statistical analysis should be re-done as\na contingency table and clarifying whether the same mouse had multiple mets or all mice\nwith mets were different mice. Alternatively, the number of mets per mouse could be\nshown leaving aside location.\nWe reformatted the panel and performed the statistical analysis as recommended. The updated p\nvalues are labeled in the figure, and the statistical analysis is updated in figure legends. These\nmice all have either an intrasplenic, mesenteric/diaphragm or liver metastasis, with no mouse\nhaving multiple sites of metastasis. This is now clarified in the revised manuscript (lines 531-\n532).\nIn Fig. S3g, lung mets should be quantitated.\nThe lung metastases were quantified by in vivo imaging in sFig. 3f and sFig. 3h. sFig.3g is\nrepresentative images of the development of lung metastatic lesions.\nIn Fig. S4, ascites can reflect local invasion rather than metastasis and the two should not\nbe grouped together.\nThank you, we agree, and this table has been revised based on both reviewer’s comments\naccordingly.\nsFIG4a: x-axis should say days not months\nThank you, this has been corrected.\nConcern 4: Please clarify the lectin array methodology in the manuscript. Is this using\nlysate or cells?\nThe lectin array was done using cell lysate. This is now specified in the methods section (lines\n642-646).\nFigure FigL1 should be included in the paper with a clear definition of the mass spec assay\nused. Is this UDP-HexNAc or UDP-GlcNAc? Discuss discrepancy between UDP-GlcNAc\nand lectin array. Why so few changes in lectin binding? Also, why no increases in Galectin\nstaining as expected?\n(1) “Figure FigL1 should be included in the paper with a clear definition of the mass\nspec assay used. Is this UDP-HexNAc or UDP-GlcNAc? ”\nThis data has now been added as new sFig. 13 d-g. The mass spec assay to detect levels of UDP-\nGlcNAc was developed by Duke Proteomics and Metabolomics Core Facility. Briefly, PANC-1\ncrNTC and crALK4 KO cells and MDA-MB-231 crNTC and crALK4 KO cells (3 million each,\n4 replicates for each condition) were lysed and incubated with 13C6- UDP-GlcNAc (Omicron\nBiochemicals, Inc.). Samples were analyzed with a multiple reaction monitoring (MRM) assay.\nData was acquired using UPLC-MS/MS on a Sciex QTrap 6500+ mass spectrometer, including\ncalibration curves for the analyte in a manner consistent with the FDA Guidance for\nBioanalytical Method Validation. Data analysis was done using Skyline. The methodology is\ndescribed in methods section. (lines 647-656)\n(2) “Discuss discrepancy between UDP-GlcNAc and lectin array. ” and question “Why\nso few changes in lectin binding? ”\nPreviously published reports have shown that the MGAT5 Km value for UDP-GlcNAc is\nconsiderably higher compared to that observed in other N-acetylglucosaminyltransferases (e.g.\nMGAT1, MGAT2, and MGAT4) [1, 2]. As for the lectin array, there are 7 lectins with\nsignificantly changed staining, but only two with a significant 2-fold change (increase).\n(3) “Also, why no increases in Galectin staining as expected?”\nThe intensity of galectin-3 stain is slightly increased in KOs compared to control group, while\nthis change is not significant. Galectin-3 recognizes poly LacNAc while PHA-L recognize\nGalβ4GlcNAcβ6(GlcNAcβ2MANα3)MANα3. Considering that ALK4 loss specifically\nincreased MGAT5-modified branched N-glycan, likely the change is “diluted” by other glycans\ncompeting for binding to galectin-3.\nConcern 5: The authors have largely updated the abstract, introduction and discussion to\nbetter reflect the published data that N-glycan branching, but a sentence in the abstract\nshould be changed (as highlighted in red) below to be more accurate:\n“Consistent with prior observation that galectin-3 preferentially binds to MGAT5-modified\nglycoproteins to stabilize cell surface receptors like TGF-β receptors, we found that ALK4\nloss enhanced MGAT5-mediated glycosylation of TGF-β receptors,…”\nThis change has been made to the abstract.\nConcern 6-8: Previously addressed.\nConcern 9: Some figure legends state that in vitro experiments were done with 3 biological\nreplicates, but do not state if the experiments were independently replicated. This should\nbe clarified. Some figure legends state the number of independent experiments but others\ndo not. This should be clearly stated in all figure legends.\nAll in vitro experiments were performed with at least 3 independent biological replicates, this is\nnow clearly stated in all figure legends.\nConcern 10: Some WBs have been quantitated in the figures, others have been presented as\na supplemental excel file. It would be best if all WB quantitation was present within the\nfigures (at least the main figures).\nWe sincerely appreciate the reviewer's insightful suggestion regarding the presentation of\nWestern blot quantitation. In accordance with this recommendation, we have carefully re-\nevaluated our data presentation strategy to optimize clarity while maintaining scientific rigor.\nThe quantitative analyses of comparative experiments evaluate Smads phosphorylation or TβRs\nlevel which need comparison between 2 blots (Figures 4a,b,c,h; 7d,e,f,g) and time-course studies\n(Figure 5a,b,e,i) have been retained in the main figures to increase clarity. For panels\ndemonstrating straightforward binary relationships (e.g., Figure 3a,b, Figure 7a) or mobility\nshifts (e.g., Figure 5c,d,f,g,h), we have opted to present these datasets in the supplementary Excel\nfile. This decision was guided by our concern that superimposing numerical quantitations on\nsuch panels might compromise visual clarity. For example, as shown in the figure below, we\nthink that the previous unlabeled version (right) is more straightforward. To ensure full\ntransparency, we described our strategy in methods section (lines 606-608). This balanced\napproach aims to maintain narrative focus while providing complete data accessibility.\nConcern 13: Figure L2 should be in the manuscript in the main figure as Fig5d.\nThis change has been incorporated into the revised manuscript.\nConcern 14: We could not find blinding in the methods section, this should be corrected. In\naddition, the figure legends should state when blinding was performed.\nThis is now mentioned in material and methods section (line 543, line 551, line 569, line 591)\nand describe in the figure legends.\nOther Minor concerns:\nFigure 1 legend is incomplete or cut off in the PDF.\nFigure 1 legend was cut off and we have fixed this issue.\nThe figures often refer only to “KO”. These should be fixed to identify the specific KO (eg\n“ALK4 KO”)\nThis has been performed across all figures to increase clarity.\nReviewer #2 (co-reviewer of Reviewer #1, withdrawn)\nReviewer #3 (Remarks to the Author):\nWe thank the reviewer for finding that the original manuscript “presents extensive findings that\nsupport a highly novel concept,” and that this is “ an extremely rigorous study that clearly\npresents highly innovative data that has the potential to lay the groundwork for a mechanistic\nunderstanding of EMT and metastasis not previously recognized.”\nWe thank the reviewer for finding that in the revised manuscript “The authors have addressed\nmy previous, minor, critiques. The authors should be commended on completion of this highly\nimpactful, rigorous, and scientifically interesting manuscript.”\nAbstract line 44; consistent with prior observations\nThis has been corrected.\nReviewer #4\nWe thank the reviewer for their careful review of the revised manuscript, for noting that “The\nobservation that ALK4 may function as a tumor suppressor in breast and pancreatic cancers by\nantagonizing TβRI/TβRII is intriguing and warrants further mechanistic and translational\nstudies” and that the “authors have made significant efforts to address the concerns raised by\nboth this reviewer and others.”\nReviewer concern 1: While at a first glance the hypothesis that the loss of ALK4\ncontributes to cancer progression might seem appealing, the study does not provide\ncompelling evidence to support such claim. It also lacks the conceptual advance needed for\nestablishing the relevance of this mechanism to the human diseases. Indeed, the vast\nmajority of experiments are superficial in nature, relying mostly on in vitro cell systems,\nwhich could lead to all sorts of artifacts.\nReviewer concern 2 has been resolved.\nReviewer concern 3: The expression levels of ALK4 seem to be inversely correlated with\nthe aggressiveness and metastatic potential of breast and pancreatic cancer cell lines.\nHowever, this correlation is based on very artificial invasion assays in vitro. To support\ntheir claim, the authors might want to consider characterizing these cell lines in vivo, both\nin terms of tumor growth and metastatic potential.\nReviewer concern 4: To provide compelling evidence that the loss of ALK4 contributes to\ncancer progression, it is imperative to conduct in vivo experiments with autochthonous\nmouse models of breast and pancreatic cancer. It would be straightforward to delete\nAcvR1B in mouse models of breast and pancreatic cancer (such as in MMTV-PyMT or KC\nmice with conditional expression of KrasG12D in the pancreatic epithelium). These\nexperimental approaches must be presented at his level of publication.\nReviewer concern 5: ALK4 seems to induce expression of TβRI and TβRII at the surface\nby a mechanism dependent on its kinase activity. What is the substrate of ALK4 under\nthese conditions? This information is important for understanding how ALK4 fulfills its\nanti- tumor suppressive function in breast and pancreatic cancers. Also important is what\nsignaling pathway functions downstream of ALK4 to suppress cancer progression and\nmetastasis? Without providing this kind of data, the impact of the study will be just\nincremental.\nReviewer concern 6: Loss of ALK4 correlates with increased expression of MGAT5 and\ngalectin-3, which could provide a mechanistic explanation as to how ALK4 regulates the N-\nglycosylation and thereby stability of TβRI and TβRII at the cell surface. There are at\nleast three issues with this observation. First, the mechanism leading to the\naccumulation MGAT5 and galectin-3 in cells deficient for Alk4 was not explored. Second,\ncompelling evidence that TβRI and TβRII are direct substrate of MGAT5 and galectin-3\nwas not presented. Third, compelling evidence that MGAT5 and galectin-3 functions\ndownstream of ALK4 in vivo under physiological conditions is missing. The latter could\nbe easily achieved through using mice or cells co-deleted of MGAT5 /galectin-3 and Alk4\nand treated with the two inhibitors NGI-1 and Glucosamine.\nReviewer concern 7: Overall, the study lacks the mechanistic depth for firmly establishing\na role for ALK4 in suppressing cancer progression and metastasis. It also lacks the\nmechanistic depth for firmly establishing how ALK4 regulates the stability of TβRI and\nTβRII at the cell surface and attendant activation of TGF-β/Smad signaling pathway.\nExpression of ALK4 at the cell surface might simply rely on the same mechanism as does\nlocalization of TβRI and TβRII, so one conceivable mechanism would be that ALK4\nmight compete with TβRI and TβRII for the machinery that drives their cell surface\nlocalization.\nReviewer #5\nWe thank the reviewer for finding that “The authors made substantial improvement in the revised\nmanuscript, and addressed most issues raised previously.”\nConcern 1: With regard to the missing mechanism that accounts for the increased Mgat5\ntranscription/TbR glycosylation due to loss of ALK4, the authors performed some\nadditional experiments to examine noncanonical TGF-b signaling. However, the results\nwere inconclusive and the newly reported link to ETS1 is insufficiently informative. Given\nthat a role of ActRIIB was also ruled out, the authors should acknowledge as such at least\nin the discussion to leave this issue open for future exploration.\nThis has been added to discussion as suggested (lines 451-457).\nReferences:\n1. Sasai, K., et al., UDP-GlcNAc concentration is an important factor in the\nbiosynthesis of beta1,6-branched oligosaccharides: regulation based on the kinetic\nproperties of N-acetylglucosaminyltransferase V. Glycobiology, 2002. 12(2): p. 119-\n27.\n2. Lau, K.S. and J.W. Dennis, N-Glycans in cancer progression. Glycobiology, 2008.\n18(10): p. 750-60.\n3. Chen, W.H., et al., Human pancreatic adenocarcinoma: in vitro and in vivo\nmorphology of a new tumor line established from ascites. In Vitro, 1982. 18(1): p.\n24-34.\n4. Loukopoulos, P., et al., Orthotopic transplantation models of pancreatic\nadenocarcinoma derived from cell lines and primary tumors and displaying varying\nmetastatic activity. Pancreas, 2004. 29(3): p. 193-203.\n5. Moore, P.S., et al., Genetic profile of 22 pancreatic carcinoma cell lines. Analysis of\nK-ras, p53, p16 and DPC4/Smad4. Virchows Arch, 2001. 439(6): p. 798-802.\n6. Caldas, C., et al., Frequent somatic mutations and homozygous deletions of the\np16 (MTS1) gene in pancreatic adenocarcinoma. Nat Genet, 1994. 8(1): p. 27-32.\n7. Huang, L., et al., Deletion and mutation analyses of the P16/MTS-1 tumor\nsuppressor gene in human ductal pancreatic cancer reveals a higher frequency of\nabnormalities in tumor-derived cell lines than in primary ductal adenocarcinomas.\nCancer Res, 1996. 56(5): p. 1137-41.\n8. Schutte, M., et al., DPC4 gene in various tumor types. Cancer Res, 1996. 56(11): p.\n2527-30.\n9. Freeman, J.W., C.A. Mattingly, and W.E. Strodel, Increased tumorigenicity in the\nhuman pancreatic cell line MIA PaCa-2 is associated with an aberrant regulation of\nan IGF-1 autocrine loop and lack of expression of the TGF-beta type RII receptor. 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Korc, Vascular endothelial growth factor-trap suppresses\ntumorigenicity of multiple pancreatic cancer cell lines. Clin Cancer Res, 2004.\n10(10): p. 3327-32.\n16. Kearney, C.J., et al., SUGAR-seq enables simultaneous detection of glycans,\nepitopes, and the transcriptome in single cells. Sci Adv, 2021. 7(8).\n17. Osuka, R.F., T. Yamasaki, and Y. Kizuka, Structure and function of N-\nacetylglucosaminyltransferase V (GnT-V). Biochim Biophys Acta Gen Subj, 2024.\n1868(11): p. 130709.\n18. Partridge, E.A., et al., Regulation of cytokine receptors by Golgi N-glycan processing\nand endocytosis. Science, 2004. 306(5693): p. 120-4.\n19. Granovsky, M., et al., Suppression of tumor growth and metastasis in Mgat5-\ndeficient mice. Nat Med, 2000. 6(3): p. 306-12.\n20. Guo, H.B., et al., Specific posttranslational modification regulates early events in\nmammary carcinoma formation. Proc Natl Acad Sci U S A, 2010. 107(49): p. 21116-\n21.\n21. Carvalho, S., et al., Preventing E-cadherin aberrant N-glycosylation at Asn-554\nimproves its critical function in gastric cancer. Oncogene, 2016. 35(13): p. 1619-31.\n22. Guo, H.B., et al., Regulation of homotypic cell-cell adhesion by branched N-\nglycosylation of N-cadherin extracellular EC2 and EC3 domains. J Biol Chem, 2009.\n284(50): p. 34986-97.\n23. Chaney, W., et al., The Lec4A CHO glycosylation mutant arises from\nmiscompartmentalization of a Golgi glycosyltransferase. J Cell Biol, 1989. 109(5): p.\n2089-96.\n24. Goebel, E.J., et al., Structures of activin ligand traps using natural sets of type I and\ntype II TGFbeta receptors. iScience, 2022. 25(1): p. 103590.\n25. Moustakas, A. and C.H. Heldin, The regulation of TGFbeta signal transduction.\nDevelopment, 2009. 136(22): p. 3699-714.\n26. Stauber, A.J., et al., Nonclinical Safety Evaluation of a Transforming Growth Factor β\nReceptor I Kinase Inhibitor in Fischer 344 Rats and Beagle Dogs. J Clin Pract, 2014.\n4(3)."}, "author_response": ""}, {"round": 3, "reviewer_comments": {"reviewer_1": "All major issues have been addressed. Two minor presentation/labelling issues are still recommended to be fixed prior to publication\nConcern 10 - again strongly recommend that all blots (other than shift in bands) be presented with quantitation.\nFig 7h,i,j still need to have the 'KO' label specified as 'ALK4 KO'.", "reviewer_6": "The authors have sufficiently addressed the comments of Reviewer 4. Because the evidence for a tumor suppressive role for ALK4 in breast cancer is much weaker than in PDAC, the authors should emphasize the limitations of current evidence in support of a tumor suppressive role in that tumor type, despite positive results in breast cancer cell lines."}, "author_response": "REVIEWERS' COMMENTS\nReviewer #1 (Remarks to the Author):\nAll major issues have been addressed. Two minor presentation/labelling issues are still\nrecommended to be fixed prior to publication\nConcern 10 - again strongly recommend that all blots (other than shift in bands) be presented\nwith quantitation.\nThank you, all blots have been labeled with quantitation.\nFig 7h,i,j still need to have the 'KO' label specified as 'ALK4 KO'.\nThe KO have been labeled as ALK4 KO in this figure as requested.\nReviewer #6 (Remarks to the Author):\nThe authors have sufficiently addressed the comments of Reviewer 4. Because the evidence for a\ntumor suppressive role for ALK4 in breast cancer is much weaker than in PDAC, the authors\nshould emphasize the limitations of current evidence in support of a tumor suppressive role in\nthat tumor type, despite positive results in breast cancer cell lines.\nThank you for reviewing our manuscript. We have emphasized this limitation as the reviewer\nrecommended in the revised discussion section."}]

Decision letter