# Metastatic clear-cell renal cell carcinoma: a frequent NOTCH1 mutation predictive of response to anti-NOTCH1 CB-103 treatment

Thi Oanh Bui, Eurydice Angeli, Morad El Bouchtaoui, Guillaume Gapihan, Van Tu Dao, Justine Paris, Christophe Leboeuf, Michael Soussan, Patrick Villarese, Marianne Ziol, et al.

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## To cite this version:

Thi Oanh Bui, Eurydice Angeli, Morad El Bouchtaoui, Guillaume Gapihan, Van Tu Dao, et al. Metastatic clear-cell renal cell carcinoma: a frequent NOTCH1 mutation predictive of response to anti-NOTCH1 CB-103 treatment. Experimental Hematology & Oncology, 2023, 12 (1), pp.46. 10.1186/s40164-023-00408-z. inserm-04098698

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# Metastatic clear-cell renal cell carcinoma: a frequent *NOTCH1* mutation predictive of response to anti-NOTCH1 CB-103 treatment

Thi Oanh Bui¹,<fnref n="2" />,<fnref n="3" />, Eurydice Angeli<fnref n="2" />,<fnref n="4" />, Morad El Bouchtaoui<fnref n="2" />, Guillaume Gapihan<fnref n="2" />, Van Tu Dao¹,<fnref n="2" />,<fnref n="3" />, Justine Paris<fnref n="2" />, Christophe Leboeuf<fnref n="2" />, Michael Soussan<fnref n="2" />,<fnref n="4" />,<fnref n="5" />, Patrick Villarese<fnref n="6" />, Marianne Ziol<fnref n="4" />,<fnref n="7" />, Emmanuel Van Glabeke<fnref n="8" />, Thi Huong Le<fnref n="3" />, Jean-Paul Feugeas<fnref n="9" />,<fnref n="10" />, Anne Janin<fnref n="2" /> and Guilhem Bousquet<fnref n="2" />,<fnref n="4" />,<fnref n="11" />*

**Abstract**

**Background** Clear-cell renal cell carcinomas (ccRCCs) are malignant tumors with high metastatic potential and resistance to treatments occurs almost constantly. Compared to primary tumors, there are still limited genomic data that has been obtained from metastatic samples.

**Methods** We aimed to characterize metastatic ccRCC by way of whole-genome analyses of metastatic formalin-fixed samples, using OncoScan® technology. We identified a frequent, unexpected pL1575P *NOTCH1* mutation which we set out to characterize for translational purposes. We thus implemented patient-derived xenografts from metastatic samples of human ccRCC to explore its clinical significance.

**Results** We showed that pL1575P *NOTCH1* mutation was an activating mutation, leading to the expression of NOTCH1-intracellular domain-active fragments in both cancer cells and tumor endothelial cells, suggesting a trans-differentiation of cancer cells into tumor micro-vessels. We demonstrated that this mutation could be used as a predictive biomarker of response to CB-103, a specific NOTCH1-intracellular domain inhibitor. One striking result was the considerable anti-angiogenic effect, coherent with the presence of *NOTCH1* mutation in tumor micro-vessels.

**Conclusions** We identified a frequent, unexpected pL1575P_c4724T_C *NOTCH1* mutation as a new biomarker for ccRCC metastases, predictive of response to the CB103 NOTCH1-intracellular domain inhibitor.

**Keywords** NOTCH1 mutation, Metastatic clear-cell renal cell carcinoma, Anti-NOTCH1 treatment, CB-103, Biomarker

<footnote>*Correspondence:
Guilhem Bousquet
guilhem.bousquet@aphp.fr
¹National Cancer Hospital, Cancer Research and Clinical Trials Center, Hanoi, Vietnam</footnote>

<footnote n="2">²Université Paris Cité, INSERM, UMR_S942 MASCOT, F-75006 Paris, France</footnote>

<footnote n="3">³Hanoi Medical University, Hanoi, Vietnam</footnote>

<footnote n="4">⁴Université Sorbonne Paris Nord, 93439 Villetaneuse, France</footnote>

<footnote n="5">⁵Assistance Publique Hôpitaux de Paris, Hôpital Avicenne, Service de Médecine Nucléaire, 93000 Bobigny, France</footnote>

<footnote n="6">⁶Laboratoire d'Onco-Hématologie, Assistance Publique Hôpitaux de Paris, Hôpital Necker, 75015 Paris, France</footnote>

<footnote n="7">⁷Assistance Publique Hôpitaux de Paris, Hôpital Avicenne, Service d'Anatomie Pathologique, 93000 Bobigny, France</footnote>

<footnote n="8">⁸Fédération d'Urologie de Seine-Saint-Denis, 93100 Montreuil, France</footnote>

<footnote n="9">⁹Université de Franche-Comté, 25000 Besançon, France</footnote>

<footnote n="10">¹⁰Université de Paris, INSERM, U1137, F-75006 Paris, France</footnote>

<footnote n="11">¹¹Assistance Publique Hôpitaux de Paris, Hôpital Avicenne, Service d'Oncologie Médicale, 93000 Bobigny, France</footnote>
**To the Editor,**

The incidence and deaths of kidney cancer world-
wide, and thus mainly of clear-cell renal cell carcinoma
(ccRCC), have doubled since three decades, particularly
in the elderly population of countries with high social-
demographic index [1]. Recent therapeutic advances
have considerably improved the prognosis of metastatic
ccRCCs. However, almost all patients develop resist-
ance to these treatments [2]. Metastases may derive from
minority clones in the heterogeneous primary tumor [3],
and there are still limited genomic data obtained from
metastases [4, 5].

Using OncoScan® technology [6], we aimed to charac-
terize metastatic ccRCCs by way of whole-genome analy-
ses of metastatic formalin-fixed samples.

Four patients were included in the first analysis (Addi-
tional file 1: Table S1). We identified copy number altera-
tions and loss of heterozygosity (LOH) (Additional file 1:
Fig. S1A). We compared this data obtained from the
recent meta-analysis we performed on ccRCCs (Addi-
tional file 1: Fig. S1B) [4] and found some abnormali-
ties not previously described like 9q11.2 amplification
(Additional file 1: Table S2). We also identified potential
mutations (File ExcelS1). Using a threshold of 9 for prob-
ability score, we retrieved 48 mutations (Additional file 1:
Table S3), several of them not yet described in ccRCC.
We focused on the pL1575P_c4724T_C NOTCH1 muta-
tion, located on chromosome 9q34.3, because it was pre-
sent in 3 of the 4 metastases, and because the NOTCH
pathway is a potential therapeutic target in ccRCC [7]. In
addition, the 9q arm is lost in 75% of RCCs (Additional
file 1: Fig. S1B) [4], and we found an allelic imbalance
9q34.3 cytoband for Patients 1 and 2 (Additional file 1:
File ExcelS1).

Using digital-droplet PCR (ddPCR) and specific probes
for the pL1575P_c4724T_C NOTCH1 mutation, we con-
firmed that it was present in the lymphoblastic acute
leukemia T (LAL-T) positive control sample and in the
3 metastatic samples from Patients 1, 2 and 4 with high
allele frequencies (Fig. 1A), but not in Patient 3. When we

tested 9 additional ccRCC metastatic samples, we identi-
fied pL1575P *NOTCH1* mutations in all samples, with a
mean mutant allele frequency of 53.5% (Fig. 1B).

Most *NOTCH1* mutations occur in the HD and/or PEST domains (Additional file 1: Fig. S2A). The pL1575P *NOTCH1* mutation is located in the HD-N domain and is responsible for NOTCH1 constitutive activation in LAL-T [8], through the release of the active NOTCH1 intracellular domain (NOTCH1-ICD) into the cytoplasm and its nucleus translocation (Additional file 1: Fig. S2B).

To identify NOTCH1-ICD, we performed immu-
nostaining using an anti-NOTCH1 antibody (aa1755-
1767-intracellular) which specifically recognizes an ICD
epitope. We found predominant nuclear staining in the
3 metastatic samples from Patients 1, 2 and 4 (Fig. 1C),
but not all cancer cells were stained. Using laser-micro-
dissection, the pL1575P *NOTCH1* mutation was mainly
present in cancer cells expressing NOTCH1-ICD (57%
vs.17%, *P*<0.01, Fig. 1D).

Surprisingly, we found that some CD31-expressing
endothelial cells, but not all, co-expressed NOTCH1-ICD
(Fig. 1E). Using laser-micro-dissection, we also identified
the *NOTCH1* mutation with an allelic frequency of 48%
(Fig. 1E), suggesting vascular mimicry [9].

Five patient-derived xenograft models obtained from
ccRCC metastases were developed in our research unit
(XRCC1 to XRCC5). We identified the *NOTCH1* muta-
tion in all five models at Passage 1 (P1). Except for
the XRCC5 model, the allelic frequency significantly
increased between P1 and P5 (Additional file 1: Fig. S3).
We chose XRCC4 and XRCC5 because of the marked
enrichment for *NOTCH1* mutation in the XRCC4 xeno-
graft (48% allelic mutation frequency at P5) and a much
lower allele mutation frequency for the XRCC5 xeno-
graft (19% at P5). XRCC4 and XRCC5 were obtained
from patients responding to sunitinib (Additional file 1:
Fig. S4), predicting response to sunitinib in the two mod-
els [10]. We treated them with two NOTCH1 inhibi-
tors: LY411575, a γ-secretase inhibitor with an IC50 of
0.39 nM, and CB-103, a NOTCH1-ICD specific inhibitor
(Additional file 1: Table S4 and Additional file 1: Fig. S2B).
Using LY411575 administered daily by gavage, we did
not observe any anti-tumor effect. In contrast, CB-103
mono-therapy induced a significant anti-tumor effect for

(See figure on next page.)

**Fig. 1** ddPCR allelic discrimination for the pL1575P_c4724T_C NOTCH1 mutation, in 3 of the 4 metastatic samples processed via Oncoscan® analysis (A), and in ten additional metastatic samples (B). NOTCH1-ICD-expressing cancer cells and tumor endothelial cells in human samples, NOTCH1-ICD staining is mainly nuclear in the 3 metastatic samples from Patients 1, 2 and 4 (C). **D** Panel B illustrates the laser-microdissection of a cancer cell expressing NOTCH1-ICD (red circle and arrow) and of a cancer cell not expressing NOTCH1-ICD (yellow circle and arrow), with a significant difference in terms of percentage of NOTCH1 mutant allele frequency. *** *P* < 0.001. **E** The left panel shows the NOTCH1-ICD staining of a tumor endothelial cell (black arrow). Some tumor endothelial cells can be seen to co-express NOTCH1-ICD (red) and anti-CD31 (green) on immunofluorescence staining (middle panel). The right panel shows that laser-microdissected tumor endothelial cells expressing NOTCH1-ICD harbor the pL1575P NOTCH1 mutation with an allelic frequency of 48%
<figure><img src="image_4.png" /><figcaption>**Fig. 1** (See legend on previous page.)</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Fig. 2** In vivo anti-tumor effect of CB-103 in a XRCC4 xenograft model. A CB-103 monotherapy, sunitinib monotherapy, or the combination of CB-103 and sunitinib significantly inhibit tumor growth after 30 days of treatment (n=6 per treatment group). This is associated with a significant gradual increase in the percentage of necrotic areas (B), a significant decrease in microvessel density (C) and in cell proliferation (D). After 30 days of CB-103 monotherapy treatment, the pL1575P_c4724T_C NOTCH1 mutation and NOTCH1-ICD protein expression disappear on Western blot (E). (*P*<0.05, **P**<0.001) (F) NOTCH1 mutant allele frequency on laser-micro dissected cancer cells after treatment with CB103 or not, using ddPCR</figcaption></figure>
both models, more marked with XRCC4 (Fig. 2A, Additional file 1: Table S5, Fig. S5A). Unexpectedly, like with sunitinib, there was also a strong induction of necrosis with CB-103 mono-therapy. The additive effect of the combined treatment was low in terms of tumor growth inhibition (Fig. 2B and Additional file 1: Fig. S5B), but tissue effects were much more marked than with sunitinib or CB-103 mono-therapy, in particular for necrotic area extent with very low cell viability. There was also a significant gradual decrease in micro-vessel density and proliferation (P < 0.01, Fig. 2C–D). CB-103 tumor growth inhibition was stronger with XRCC4 than with XRCC5 (Additional file 1: Table S5), coherent with a higher allelic mutation frequency in XRCC4. Finally, when we assessed NOTCH1-ICD expression and *NOCTH1* allelic mutation frequency in tumors after treatment, we found a significant decrease for both markers. Model XRCC4 treated with CB-103 monotherapy, *NOTCH1* allelic frequency decreased from 64 to 1%, and NOTCH1-ICD was no longer seen to be expressed on western blot (Fig. 2E, F).

Using two different methods, we showed that the pL1575P_c4724T_C NOTCH1 activating mutation is frequent in metastatic ccRCCs, and this may be explained by a high sensitivity of Oncoscan® technology using formalin-fixed samples [6, 11]. Like in LAL-T, we also evidenced the benefit of using CB-103 designed to block active forms of NOTCH1-ICD [12]. CB-103 is currently being evaluated in phase II clinical trials for various malignancies, with acceptable toxicity profile [13]. Since NOTCH signalling is closely linked to immune system regulation, further studies are required to determine if this *NOTCH1* mutation is associated with response to immune checkpoint inhibitors, which would be of high translational relevance [14]. Our study opens the way to further development in metastatic ccRCC.

**Abbreviations**

ccRCC Clear-cell renal cell carcinoma

LAL-T Lymphoblastic acute leukemia T

XRCC Xenograft renal cell carcinoma

FFPE Formalin-Fixed Paraffin-Embedded

**Supplementary Information**

The online version contains supplementary material available at https://doi.org/10.1186/s40164-023-00408-z.

**Additional file 1: Fig S1.** Copy number gains and losses in 4 metastatic RCC samples using Oncoscan® (A) compared with 433 metastatic RCC samples from our meta-analysis on genomic data of clear-cell RCC (B). Some of the abnormalities were not previously described, including 9q11.2 and 15q11.1–11.2 amplifications (red arrows on panel A). **Fig S2.** NOTCH1 protein structure and signaling pathway. (A) NOTCH1 protein structure, the mature NOTCH1 receptor is a heterodimer composed of an extracellular subunit (NOTCH1-EC) and a transmembrane and intracellular subunit (NOTCH1-TMIC). NOTCH1-EC includes epidermal growth factor (EGF)-like repeats, involved in ligand binding, three LIN-12/NOTCH repeats

(LNR), which prevent receptor activation in the absence of ligands, and the heterodimerization domain (HD) involved in non-covalent interactions between NOTCH1-EC and NOTCH1-TMIC. NOTCH1-TMIC comprises the transmembrane domain (TM) and the intracellular domain (ICD) (NOTCH1-ICD). NOTCH1-ICD comprises an RBPJ-associated molecule (RAM) domain, seven ankyrin (ANK) repeats, nuclear localization signals (NLS), a transactivation domain (TAD), and a PEST domain, in turn involved in proteasomal degradation of active NOTCH1-ICD. Most NOTCH1 mutations are located in the HD and PEST domains (red arrows), and the pL1575P_c4724T_C NOTCH1 mutation (highlighted in yellow) is located in the HDN domain. (B) Newly synthesized NOTCH1 precursor is cleaved by a furin-like convertase (Furin) in the Golgi apparatus to generate the mature receptor. NOTCH1 signaling occurs when a JAGGED or DELTA ligand expressed on a signal-sending cell interacts with NOTCH1 on a signalreceiving cell. This interaction triggers two sequential cleavages of NOTCH1: the first, by way of an a disintegrin and metalloproteinase (ADAM) metalloproteinase, generates the substrate for the second cleavage by γ-secretase, which releases the active NOTCH1-ICD. NOTCH1-ICD translocates to the nucleus where it forms a transcriptional activation complex by interacting with the transcription factor CSL/RBP-Jk, mastermind-like proteins, and other coactivators (CoA), leading to the expression of NOTCH1 target genes. In physiological conditions, NOTCH1 expression is controlled by ubiquitination and proteasomal degradation of NOTCH1-ICD. **Fig S3.** ddPCR allelic discrimination for the pL1575P_c4724T_C NOTCH1 mutation in 5 XRCC tumor xenografts at the first (in gray) and the fifth (in black) passages. **Fig S4.** Response to sunitinib treatment in first-line setting for two patients who provided metastatic samples for xenograft in murine models. (A) Patient corresponding to the XRCC4 model. (B) Patient corresponding to the XRCC5 model. **Fig S5.** In vivo anti-tumor effect of CB-103 in the XRCC5 xenograft model. (A) CB-103 monotherapy, sunitinib monotherapy, or the combination of CB-103 and sunitinib significantly inhibit tumor growth after 30 days of treatment (n=6 per treatment group). This is associated with a significant gradual increase in the percentage of necrotic areas (B), and significant decrease in microvessel density (C). For cell proliferation, the decrease is only significant with the combination of CB-103 and sunitinib compared to untreated mice (C). After 30 days of treatment with CB-103 monotherapy, the pL1575P_c4724T_C NOTCH1 mutation (D) has virtually disappeared. (*P* < 0.05, **P* < 0.001). **Fig S6.** Oncoscan® technology and the Molecular Inversion Probe: Target Generation and Hybridization Procedures. a) Annealing: Probe and gDNA hybridization; b) Gap filling with A/T or G/C nucleotides; c) Exonuclease selection for gap filled probes; d) Cleavage at site 1 for probe opening and inversion; e) Probe amplification and biotinylation; f) Cleavage at site 2 to release the tag sequence; f) Array hybridization followed by staining with phycoerythrin through the biotin-streptavidin interaction; g) Array scanning. Blue and gray colors indicate presence and absence of the phycoerythrin fluorescence signal respectively. **Fig S7.** Tumor growth inhibition coefficient in XRCC models. For a drug or a drug combination, the coefficient of inhibition is calculated as (a'-a)/a, a being the slope of the curve before the start of treatment (Day 0), and a' the slope of the curve between Day 0 and Day 30 of treatment. If this growth inhibition coefficient is found to be less than 0, the tumor is considered sensitive to the drug administered; if it is above 0, the tumor is considered resistant to the drug. **Table S1.** Characteristics of the four patients included in the initial study using Oncoscan® technology. **Table S2.** List of genes located in locus 9p11.2, 15q11.1, and 15q11.2. **Table S3.** Point mutation identified on RCC metastases before treatment. **Table S4.** NOTCH1 targeted therapeutics. **Table S5.** Growth inhibition coefficient for drugs tested in XRCC model. **Table S6.** Characteristics of the five patient-derived xenograft models.

**Acknowledgements**

We would like to thank Angela Swaine and Sarah Leyshon for the revision of the English language.

**Author contributions**

Conception and design: AJ, GB. Development of the methodology: TOB, MEB, GB. Data acquisition (provided animals, acquired and managed patients, provided facilities, etc.): TOB, EA, GG, TDV, JP, MS, PV, MZ, EVG, MEB, THL, AJ, GB. Data analysis and interpretation (e.g. statistical analysis, biostatistics,
computational analysis): TOB, MEB, CL, JPF, AJ, GB. Writing, review: TOB, GB. Revision of the manuscript: all authors. Administrative, technical, or material support (i.e. reporting or organizing data, constructing databases): CL, AJ, GB. Study supervision: GB. All authors read and approved the final manuscript.

**Funding**

Bourse d'Excellence de l'Ambassade de France au Viet Nam (Grant Number: 971522C).

**Availability of data and materials**

The gene expression data generated during the study are part of the supplementary information. All other datasets generated during the study will be made available upon reasonable request to the corresponding author, Prof. Guilhem Bousquet, email address: guilhem.bousquet@aphp.fr.

**Declarations**

**Ethics approval and consent to participate**

Five patient-derived clear-cell RCC xenograft models obtained from biopsies of metastases were implemented in our research unit. The NationalEthics Committee for experimental animal studies approved this study (APA FIS#17190-2018101814245111). The ethical guidelines that were followed met the standards required by the US guideline. Animals were maintained in pathogen-free housing at Sorbonne Paris Nord University (agreement number: C9300801).

**Consent for publication**

All subjects have written informed consent.

**Competing interests**

The authors declare no competing interest.

Received: 21 December 2022 Accepted: 26 April 2023

Published online: 15 May 2023

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