Biology subjects

Neuzillet, C.

Publications and source records attributed to Neuzillet, C..

5 recordsLinked to original sources

bioRxiv2026

The methionine cycle sustains the mesenchymal phenotype of tumor cells and drives PDA progression

Mesenchymal traits are associated with poor prognosis in Pancreatic Ductal Adenocarcinoma (PDA), but direct targeting of mesenchymal tumor cells remains a challenge. Metabolic profiling of tumor cells isolated from murine PDA and liver metastases (LM) revealed that LM rely more on the methionine cycle than does primary PDA. This metabolic shift was specifically associated with increased activation of the methionine cycle in mesenchymal tumor cells compared to differentiated tumor cells. We show that the targeting of the key enzyme of the methionine cycle S-adenosylhomocysteine hydrolase (SAHH) in mesenchymal cells lowers the levels of homocysteine (Hcy) and glutathione, resulting in reduced antioxidant capacity, deregulated intracellular calcium homeostasis, and ultimately loss of mesenchymal markers. Together, these events decrease cell proliferation and invasion, blunting the tumorigenic and metastatic potential of SAHH-deficient cells, eventually impeding tumor growth and progression of the metastatic disease. Clinically, the high expression of SAHH in patients with mesenchymal PDA is correlated with poor survival, positioning SAHH as a potential therapeutic target to impede the pro-metastatic, mesenchymal phenotype of PDA.

cancer biology↗

bioRxiv2024

IKZF2-ERBB4 gene fusion leads to ERBB4 overexpression in Anal Squamous Cell Carcinoma but with no benefit for ERBB4 inhibition

Anal squamous cell carcinoma (ASCC) is a rare tumour, but with increasing incidence for local and metastatic tumours. Current therapy is based on chemoradiotherapy, associated with immunotherapy in advanced stages, with frequent side effects, poor results in advanced stages and recurrence. New therapeutics, including targeted therapies, are then needed. In this context, we identified here a IKZF2-ERBB4 gene fusion in a patient ASCC tumour, leading to overexpressed mRNA encoding a functional ERBB4 protein. This gene fusion has been already reported in other tumour types but not yet investigated as therapeutical target. The matched patient tumour-derived xenograft displays the same gene fusion and mRNA overexpression. It provided biological material for anti-ERBB4 testing in different cell models (in vivo xenograft, in vitro cell cultures). We used afatinib and lapatinib, 2 chemical pan-ERBB inhibitors approved in clinics, with anti-ERBB4 properties. ERBB4 inhibition did not lead to tumour growth inhibition although afatinib and lapatinib dramatically decreased ERBB4 phosphorylation with impact on downstream signalling MAPK/ERK but not PI3K/AKT pathways. Likewise, specific ERBB4 knock-outing did not affect tumour cell proliferation. These negative results must be put in line with reported potential crosstalk between PI3K/AKT and MAPK/ERK pathways in therapeutic resistance.

cancer biology↗

bioRxiv2023

Redefining phenotypic intratumor heterogeneity of pancreatic ductal adenocarcinoma: a bottom-up approach

BackgroundPancreatic ductal adenocarcinoma (PDAC) tumor inter-patient heterogeneity has been well described with two major prognostic subtypes (classical and basal-like). An important intra-patient heterogeneity has been reported but has not yet been extensively studied due to the lack of standardized, reproducible and easily accessible high throughput methods. Material and MethodsWe built an immunohistochemical (IHC) tool capable of differentiating RNA-defined classical and basal-like tumors by selecting relevant antibodies using a multi-step process. The successive stages of i) an in-silico selection from a review literature and a bulk transcriptome analysis of 309 PDACs, ii) a tumor-specific selection from 30 patient-derived xenografts followed by iii) the validation on tissue microarrays in 50 PDAC were conducted. We used our final IHC panel on two independent cohorts of resected PDAC (n=95, whole-slide, n=148, tissue microarrays) for external validation. After digitization and registration of pathology slides, we performed a tile-based-analysis in tumor and pre-neoplastic epithelial areas and a k-means clustering to identify relevant marker combinations. ResultsSequential marker selection led to the following panel: GATA6, CLDN18, TFF1, MUC16, S100A2, KRT17, PanBasal. Four different phenotypes were identified: 1 classical, 1 intermediate (KRT17+) and 2 basal-like (MUC16+ vs S100A2+) with specific biological properties. The presence of a minor basal contingent drastically reduced overall survival, even in classical predominant PDACs (HR=2.36, p=0.01). Analysis of preneoplastic lesions suggested that pancreatic carcinogenesis may follow a progressive evolution from classical toward a basal through an early intermediate phenotype. ConclusionOur IHC panel redefined and easily assessed the high degree of intra- and inter-tumoral heterogeneity of PDAC.

cancer biology↗

bioRxiv2022

PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides

Pancreatic ductal adenocarcinoma (PAC) is a highly heterogeneous and plastic tumor with different transcriptomic molecular subtypes that hold great prognostic and theranostic values. We developed PACpAInt, a multistep approach using deep learning models to determine tumor cell type and their molecular phenotype on routine histological preparation at a resolution enabling to decipher complete intratumor heterogeneity on a massive scale never achieved before. PACpAInt effectively identified molecular subtypes at the slide level in three validation cohorts and had an independent prognostic value. It identified an interslide heterogeneity within a case in 39% of tumors that impacted survival. Diving at the cell level, PACpAInt identified "pure" classical and basal-like main subtypes as well as an intermediary phenotype and hybrid tumors that co-carried both classical and basal-like phenotypes. These novel artificial intelligence-based subtypes, together with the proportion of basal-like cells within a tumor had a strong prognostic impact.

cancer biology↗

bioRxiv2020

Translatome-based classification reveals a dual metabolic dependency of a new tumor subtype of pancreatic cancer.

Molecular profiling of Pancreatic Ductal Adenocarcinoma (PDA), based on transcriptomic analyses, identifies two main prognostic subtypes (basal-like and classical), but does not allow personalized first-line treatment. To date, tumors have not been profiled based on protein synthesis rates, yet the step of mRNA translation is highly deregulated in both PDA cancer cells and their microenvironment. Using a collection of twenty-seven pancreatic Patient-Derived Xenografts (PDX), we performed genome-wide analysis of translated mRNA (translatome). Unsupervised bioinformatics analysis revealed a new tumor subtype harboring a low protein synthesis rate, but associated with a robust translation of mRNAs encoding effectors of the integrated stress response (ISR), including the transcription factor ATF4. Functional characterization of the "ISR-activated" human cancer cells revealed a high resistance to drugs, low autophagic capacities, and importantly, metabolic impairments in the serine synthesis and transsulfuration pathways. Overall, our study highlights the strength of translatomic profiling on PDA, which here revealed an unforeseen drug-resistant cancer cell phenotype, whose auxotrophy to both serine and cysteine may be amenable to targeted therapy.

cancer biology↗