Overview of patients' cohorts in the French National rare disease registry.

In France, all patients followed by Rare Disease (RD) expert centers have to be registered in the National Rare Disease Registry (BNDMR). This database collects a minimum data set including diagnosis coded using the Orphanet nomenclature. Overall, 753,660 patients were recorded from 2007 to March 2022 including 493,740 with at least one rare disease diagnosis. Among these rare disease diagnoses, 1,300 diagnoses gathered between 10 and 70 patients and 792 gathered more than 70 patients, corresponding to more than one patient per million inhabitants. A total of 47 rare disease diagnoses with point prevalence or incidence reported in the literature below 1/1,000,000 have more than 70 patients in the BNDMR, suggesting larger BNDMR cohorts than expected from reported literature. As a conclusion, our national RD registry is a great resource to facilitate patients' recruitment in clinical research and a better understanding of RD natural history and epidemiology.

A Truncated NRIP1 Mutant Amplifies Microsatellite Instability of Colorectal Cancer by Regulating MSH2/MSH6 Expression, and Is a Prognostic Marker of Stage III Tumors.

Microsatellite instability (MSI) is related to the alteration of mismatch repair (MMR) genes and plays a key role in colorectal cancer (CRC) pathogenesis. We previously reported that the transcription factor Nuclear Receptor Interacting Protein 1 (NRIP1) is involved in sporadic intestinal tumorigenesis. The aim of this study was to decipher its role in MSI CRC. By using different mouse models and engineered cell lines, we demonstrated that NRIP1 increased MSH2 and MSH6 MMR gene transcription and mRNA/protein levels. In human CRC cells, NRIP1 expression was associated with decreased MSI and the hypermutator phenotype, and with resistance to chemotherapy drugs. Using a cohort of 194 CRC patients, we detected in 22% of the cases a MSI-induced frameshift mutation in the NRIP1 coding sequence. This genetic alteration generates a truncated protein with a dominant negative activity that increased human CRC cell proliferation and impaired the regulation of MSH2 and MSH6 gene expression. Moreover, the NRIP1 mutant correlated with a decreased overall survival of patients with advanced CRC, especially when MLH1-deficient. By decreasing the expression of MSH2 and MSH6 gene expression, the NRIP1 variant may amplify MLH1-dependent CRC progression and behave as a new prognostic marker of advanced MSI CRC.

A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression.

Retinoblastoma is the most frequent intraocular malignancy in children, originating from a maturing cone precursor in the developing retina. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using multi-omics data, we demonstrate the existence of two retinoblastoma subtypes. Subtype 1, of earlier onset, includes most of the heritable forms. It harbors few genetic alterations other than the initiating RB1 inactivation and corresponds to differentiated tumors expressing mature cone markers. By contrast, subtype 2 tumors harbor frequent recurrent genetic alterations including MYCN-amplification. They express markers of less differentiated cone together with neuronal/ganglion cell markers with marked inter- and intra-tumor heterogeneity. The cone dedifferentiation in subtype 2 is associated with stemness features including low immune and interferon response, E2F and MYC/MYCN activation and a higher propensity for metastasis. The recognition of these two subtypes, one maintaining a cone-differentiated state, and the other, more aggressive, associated with cone dedifferentiation and expression of neuronal markers, opens up important biological and clinical perspectives for retinoblastomas.

The PAX-FOXO1s trigger fast trans-differentiation of chick embryonic neural cells into alveolar rhabdomyosarcoma with tissue invasive properties limited by S phase entry inhibition.

The chromosome translocations generating PAX3-FOXO1 and PAX7-FOXO1 chimeric proteins are the primary hallmarks of the paediatric fusion-positive alveolar subtype of Rhabdomyosarcoma (FP-RMS). Despite the ability of these transcription factors to remodel chromatin landscapes and promote the expression of tumour driver genes, they only inefficiently promote malignant transformation in vivo. The reason for this is unclear. To address this, we developed an in ovo model to follow the response of spinal cord progenitors to PAX-FOXO1s. Our data demonstrate that PAX-FOXO1s, but not wild-type PAX3 or PAX7, trigger the trans-differentiation of neural cells into FP-RMS-like cells with myogenic characteristics. In parallel, PAX-FOXO1s remodel the neural pseudo-stratified epithelium into a cohesive mesenchyme capable of tissue invasion. Surprisingly, expression of PAX-FOXO1s, similar to wild-type PAX3/7, reduce the levels of CDK-CYCLIN activity and increase the fraction of cells in G1. Introduction of CYCLIN D1 or MYCN overcomes this PAX-FOXO1-mediated cell cycle inhibition and promotes tumour growth. Together, our findings reveal a mechanism that can explain the apparent limited oncogenicity of PAX-FOXO1 fusion transcription factors. They are also consistent with certain clinical reports indicative of a neural origin of FP-RMS.

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression.

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases. While numerous methods can quantify immune or stromal cells in human tissue samples from transcriptomic data, few are available for mouse studies. We introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that accurately quantify 16 immune and stromal murine cell populations. We validated mMCP-counter with flow cytometry data and showed that mMCP-counter outperforms existing methods. We showed that mMCP-counter scores are predictive of response to immune checkpoint blockade in cancer mouse models and identify early immune impacts of Alzheimer's disease.

Large-scale pan-cancer analysis reveals broad prognostic association between TGF-ß ligands, not Hedgehog, and GLI1/2 expression in tumors.

GLI1 expression is broadly accepted as a marker of Hedgehog pathway activation in tumors. Efficacy of Hedgehog inhibitors is essentially limited to tumors bearing activating mutations of the pathway. GLI2, a critical Hedgehog effector, is necessary for GLI1 expression and is a direct transcriptional target of TGF-ß/SMAD signaling. We examined the expression correlations of GLI1/2 with TGFB and HH genes in 152 distinct transcriptome datasets totaling over 23,500 patients and representing 37 types of neoplasms. Their prognostic value was measured in over 15,000 clinically annotated tumor samples from 26 tumor types. In most tumor types, GLI1 and GLI2 follow a similar pattern of expression and are equally correlated with HH and TGFB genes. However, GLI1/2 broadly share prognostic value with TGFB genes and a mesenchymal/EMT signature, not with HH genes. Our results provide a likely explanation for the frequent failure of anti-Hedgehog therapies in tumors, as they suggest a key role for TGF-ß, not Hedgehog, ligands, in tumors with elevated GLI1/2-expression.

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer.

BACKGROUND: A significant gap in pancreatic ductal adenocarcinoma (PDAC) patient's care is the lack of molecular parameters characterizing tumours and allowing a personalized treatment. METHODS: Patient-derived xenografts (PDX) were obtained from 76 consecutive PDAC and classified according to their histology into five groups. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n = 598) of resected tumours; ii/ 60 advanced tumours obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumours. FINDINGS: A unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumours (e.g. 308 consecutive resected PDAC, uHR=0.321 95% CI [0.207-0.5] and 60 locally-advanced or metastatic PDAC, uHR=0.308 95% CI [0.113-0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumour response: -0.67, p-value < 0.001). INTERPRETATION: PAMG unify all PDAC pre-existing classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient. FUNDING: Project funding was provided by INCa (Grants number 2018-078 and 2018-079, BACAP BCB INCa_6294), Canceropole PACA, DGOS (labellisation SIRIC), Amidex Foundation, Fondation de France, INSERM and Ligue Contre le Cancer.

Identification of Four Immune Subtypes Characterized by Distinct Composition and Functions of Tumor Microenvironment in Intrahepatic Cholangiocarcinoma.

BACKGROUND AND AIMS: Intrahepatic cholangiocarcinoma (ICC) is a severe malignant tumor in which the standard therapies are mostly ineffective. The biological significance of the desmoplastic tumor microenvironment (TME) of ICC has been stressed but was insufficiently taken into account in the search for classifications of ICC adapted to clinical trial design. We investigated the heterogeneous tumor stroma composition and built a TME-based classification of ICC tumors that detects potentially targetable ICC subtypes. APPROACH AND RESULTS: We established the bulk gene expression profiles of 78 ICCs. Epithelial and stromal compartments of 23 ICCs were laser microdissected. We quantified 14 gene expression signatures of the TME and those of 3 functional indicators (liver activity, inflammation, immune resistance). The cell population abundances were quantified using the microenvironment cell population-counter package and compared with immunohistochemistry. We performed an unsupervised TME-based classification of 198 ICCs (training set) and 368 ICCs (validation set). We determined immune response and signaling features of the different immune subtypes by functional annotations. We showed that a set of 198 ICCs could be classified into 4 TME-based subtypes related to distinct immune escape mechanisms and patient outcomes. The validity of these immune subtypes was confirmed over an independent set of 368 ICCs and by immunohistochemical analysis of 64 ICC tissue samples. About 45% of ICCs displayed an immune desert phenotype. The other subtypes differed in nature (lymphoid, myeloid, mesenchymal) and abundance of tumor-infiltrating cells. The inflamed subtype (11%) presented a massive T lymphocyte infiltration, an activation of inflammatory and immune checkpoint pathways, and was associated with the longest patient survival. CONCLUSION: We showed the existence of an inflamed ICC subtype, which is potentially treatable with checkpoint blockade immunotherapy.

Integrated molecular characterization of chondrosarcoma reveals critical determinants of disease progression.

Chondrosarcomas are primary cancers of cartilaginous tissue with highly contrasting prognoses. These tumors are defined by recurrent mutations in the IDH genes and other genetic alterations including inactivation of CDKN2A and COL2A1; however, these have no clinical value. Here we use multi-omics molecular profiles from a series of cartilage tumors and find an mRNA classification that identifies two subtypes of chondrosarcomas defined by a balance in tumor differentiation and cell cycle activation. The microRNA classification reveals the importance of the loss of expression of the 14q32 locus in defining the level of malignancy. Finally, DNA methylation is associated with IDH mutations. We can use the multi-omics classifications to predict outcome. We propose an mRNA-only classifier to reproduce the integrated multi-omics classification, and its application to relapsed tumor samples shows the progressive nature of the classification. Thus, it may be possible to use mRNA-based signatures to detect patients with high-risk chondrosarcomas.

Dissecting heterogeneity in malignant pleural mesothelioma through histo-molecular gradients for clinical applications.

Malignant pleural mesothelioma (MPM) is recognized as heterogeneous based both on histology and molecular profiling. Histology addresses inter-tumor and intra-tumor heterogeneity in MPM and describes three major types: epithelioid, sarcomatoid and biphasic, a combination of the former two types. Molecular profiling studies have not addressed intra-tumor heterogeneity in MPM to date. Here, we use a deconvolution approach and show that molecular gradients shed new light on the intra-tumor heterogeneity of MPM, leading to a reconsideration of MPM molecular classifications. We show that each tumor can be decomposed as a combination of epithelioid-like and sarcomatoid-like components whose proportions are highly associated with the prognosis. Moreover, we show that this more subtle way of characterizing MPM heterogeneity provides a better understanding of the underlying oncogenic pathways and the related epigenetic regulation and immune and stromal contexts. We discuss the implications of these findings for guiding therapeutic strategies, particularly immunotherapies and targeted therapies.

Mutational Profile of Aggressive, Localised Prostate Cancer from African Caribbean Men Versus European Ancestry Men.

Causes of high mortality of prostate cancer in men of African ancestry living in the French West Indies are still debated, between suspicions of environmental factors and genetic susceptibility. We report an integrated genomic study of 25 tumour tissues from radical prostatectomy of aggressive (defined by International Society of Urological Pathology ≥3) prostate cancer patients (10 African Caribbean and 15 French Caucasian) using single nucleotide polymorphism arrays, whole-genome sequencing, and RNA sequencing. The results show that African Caribbean tumours are characterised by a more frequent deletion at 1q41-43 encompassing the DNA repair gene PARP1, and a higher proportion of intrachromosomal rearrangements including duplications associated with CDK12 truncating mutations. Transcriptome analyses show an overexpression of genes related to androgen receptor activity in African Caribbean tumours, and of PVT1, a long non-coding RNA located at 8q24 that confirms the strong involvement of this region in prostate tumours from men of African ancestry. Patient summary: Mortality of prostate cancer is higher in African Caribbean men than in French Caucasian men. Specificities of the former could be explained by genomic events linked with key genes such as DNA damage pathway genes PARP1, CDK12, and the oncogenic long non-coding RNA gene PVT1 at the 8q24 prostate cancer susceptibility locus.

Stratification of Pancreatic Ductal Adenocarcinomas Based on Tumor and Microenvironment Features.

BACKGROUND & AIMS: Genomic studies have revealed subtypes of pancreatic ductal adenocarcinoma (PDA) based on their molecular features, but different studies have reported different classification systems. It is a challenge to obtain high-quality, freshly frozen tissue for clinical analysis and determination of PDA subtypes. We aimed to redefine subtypes of PDA using a large number of formalin-fixed and paraffin-embedded PDA samples, which are more amenable to routine clinical evaluation. METHODS: We collected PDA samples from 309 consecutive patients who underwent surgery from September 1996 through December 2010 at 4 academic hospitals in Europe; nontumor tissue samples were not included. Samples were formalin fixed and paraffin embedded. DNA and RNA were isolated; gene expression, targeted DNA sequencing, and immunohistochemical analyses were performed. We used independent component analysis to deconvolute normal, tumor, and microenvironment transcriptome patterns in samples. We devised classification systems from an unsupervised analysis using a consensus clustering approach of our data set after removing normal contamination components. We associated subtypes with overall survival and disease-free survival of patients using Cox proportional hazards regression with estimation of hazard ratios and 95% confidence interval. We used The Cancer Genome Consortium and International Cancer Genome Consortium PDA data sets as validation cohorts. RESULTS: We validated the previously reported basal-like and classical tumor-specific subtypes of PDAs. We identified features of the PDA, including microenvironment gene expression patterns, that allowed tumors to be categorized into 5 subtypes, called pure basal like, stroma activated, desmoplastic, pure classical, and immune classical. These PDA subtypes have features of cancer cells and immune cells that could be targeted by pharmacologic agents. Tumor subtypes were associated with patient outcomes, based on analysis of our data set and the International Cancer Genome Consortium and The Cancer Genome Consortium PDA data sets. We also observed an exocrine signal associated with acinar cell contamination (from pancreatic tissue). CONCLUSIONS: We identified a classification system based on gene expression analysis of formalin-fixed PDA samples. We identified 5 PDA subtypes, based on features of cancer cells and the tumor microenvironment. This system might be used to select therapies and predict patient outcomes. We found evidence that the previously reported exocrine-like (called ADEX) tumor subtype resulted from contamination with pancreatic acinar cells. ArrayExpress accession number: E-MTAB-6134.

Identification of Positively and Negatively Selected Driver Gene Mutations Associated With Colorectal Cancer With Microsatellite Instability.

Background & Aims: Recent studies have shown that cancers arise as a result of the positive selection of driver somatic events in tumor DNA, with negative selection playing only a minor role, if any. However, these investigations were concerned with alterations at nonrepetitive sequences and did not take into account mutations in repetitive sequences that have very high pathophysiological relevance in the tumors showing microsatellite instability (MSI) resulting from mismatch repair deficiency investigated in the present study. Methods: We performed whole-exome sequencing of 47 MSI colorectal cancers (CRCs) and confirmed results in an independent cohort of 53 MSI CRCs. We used a probabilistic model of mutational events within microsatellites, while adapting pre-existing models to analyze nonrepetitive DNA sequences. Negatively selected coding alterations in MSI CRCs were investigated for their functional and clinical impact in CRC cell lines and in a third cohort of 164 MSI CRC patients. Results: Both positive and negative selection of somatic mutations in DNA repeats was observed, leading us to identify the expected true driver genes associated with the MSI-driven tumorigenic process. Several coding negatively selected MSI-related mutational events (n = 5) were shown to have deleterious effects on tumor cells. In the tumors in which deleterious MSI mutations were observed despite the negative selection, they were associated with worse survival in MSI CRC patients (hazard ratio, 3; 95% CI, 1.1-7.9; P = .03), suggesting their anticancer impact should be offset by other as yet unknown oncogenic processes that contribute to a poor prognosis. Conclusions: The present results identify the positive and negative driver somatic mutations acting in MSI-driven tumorigenesis, suggesting that genomic instability in MSI CRC plays a dual role in achieving tumor cell transformation. Exome sequencing data have been deposited in the European genome-phenome archive (accession: EGAS00001002477).

Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma.

BACKGROUND: 1p/19q-codeleted anaplastic gliomas have variable clinical behavior. We have recently shown that the common 9p21.3 allelic loss is an independent prognostic factor in this tumor type. The aim of this study is to identify less frequent genomic copy number variations (CNVs) with clinical importance that may shed light on molecular oncogenesis of this tumor type. MATERIALS AND METHODS: A cohort of 197 patients with anaplastic oligodendroglioma was collected as part of the French POLA network. Clinical, pathological, and molecular information was recorded. CNV analysis was performed using single-nucleotide polymorphism arrays. Computational biology and feature selection based on the random forests method were used to identify CNV events associated with overall survival and other clinical-pathological variables. RESULTS: Recurrent chromosomal events were identified in chromosomes 4, 9, and 11. Forty-six focal amplification events and 22 focal deletion events were identified. Twenty-four focal CNV areas were associated with survival, and five of them were significantly associated with survival after multivariable analysis. Nine out of 24 CNV events were validated using an external cohort of The Cancer Genome Atlas. Five of the validated events contain a cancer-related gene or microRNA: CDKN2A deletion, SS18L1 amplification, RHOA/MIR191 copy-neutral loss of heterozygosity, FGFR3 amplification, and ARNT amplification. The CNV profile contributes to better survival prediction compared with clinical-based risk assessment. CONCLUSION: Several recurrent CNV events, detected in anaplastic oligodendroglioma, enable better survival prediction. More importantly, they help in identifying potential genes for understanding oncogenesis and for personalized therapy. IMPLICATIONS FOR PRACTICE: Genomic analysis of 197 anaplastic oligodendroglioma tumors reveals recurrent somatic copy number variation areas that may help in understanding oncogenesis and target identification for precision medicine. A machine learning multivariable model built using this genomic information enables better survival prediction.

Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes.

Recent studies have offered ample insight into genome-wide expression patterns to define pancreatic ductal adenocarcinoma (PDAC) subtypes, although there remains a lack of knowledge regarding the underlying epigenomics of PDAC. Here we perform multi-parametric integrative analyses of chromatin immunoprecipitation-sequencing (ChIP-seq) on multiple histone modifications, RNA-sequencing (RNA-seq), and DNA methylation to define epigenomic landscapes for PDAC subtypes, which can predict their relative aggressiveness and survival. Moreover, we describe the state of promoters, enhancers, super-enhancers, euchromatic, and heterochromatic regions for each subtype. Further analyses indicate that the distinct epigenomic landscapes are regulated by different membrane-to-nucleus pathways. Inactivation of a basal-specific super-enhancer associated pathway reveals the existence of plasticity between subtypes. Thus, our study provides new insight into the epigenetic landscapes associated with the heterogeneity of PDAC, thereby increasing our mechanistic understanding of this disease, as well as offering potential new markers and therapeutic targets.

The Cdx2 homeobox gene suppresses intestinal tumorigenesis through non-cell-autonomous mechanisms.

Developmental genes contribute to cancer, as reported for the homeobox gene Cdx2 playing a tumor suppressor role in the gut. In this study, we show that human colon cancers exhibiting the highest reduction in CDX2 expression belong to the serrated subtype with the worst evolution. In mice, mosaic knockout of Cdx2 in the adult intestinal epithelium induces the formation of imperfect gastric-type metaplastic lesions. The metaplastic knockout cells do not spontaneously become tumorigenic. However, they induce profound modifications of the microenvironment that facilitate the tumorigenic evolution of adjacent Cdx2-intact tumor-prone cells at the surface of the lesions through NF-κB activation, induction of inducible nitric oxide synthase, and stochastic loss of function of Apc This study presents a novel paradigm in that metaplastic cells, generally considered as precancerous, can induce tumorigenesis from neighboring nonmetaplastic cells without themselves becoming cancerous. It unveils the novel property of non-cell-autonomous tumor suppressor gene for the Cdx2 gene in the gut.

Pancreatic Adenocarcinoma Therapeutic Targets Revealed by Tumor-Stroma Cross-Talk Analyses in Patient-Derived Xenografts.

Preclinical models based on patient-derived xenografts have remarkable specificity in distinguishing transformed human tumor cells from non-transformed murine stromal cells computationally. We obtained 29 pancreatic ductal adenocarcinoma (PDAC) xenografts from either resectable or non-resectable patients (surgery and endoscopic ultrasound-guided fine-needle aspirate, respectively). Extensive multiomic profiling revealed two subtypes with distinct clinical outcomes. These subtypes uncovered specific alterations in DNA methylation and transcription as well as in signaling pathways involved in tumor-stromal cross-talk. The analysis of these pathways indicates therapeutic opportunities for targeting both compartments and their interactions. In particular, we show that inhibiting NPC1L1 with Ezetimibe, a clinically available drug, might be an efficient approach for treating pancreatic cancers. These findings uncover the complex and diverse interplay between PDAC tumors and the stroma and demonstrate the pivotal role of xenografts for drug discovery and relevance to PDAC.

Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression.

We introduce the Microenvironment Cell Populations-counter (MCP-counter) method, which allows the robust quantification of the absolute abundance of eight immune and two stromal cell populations in heterogeneous tissues from transcriptomic data. We present in vitro mRNA mixture and ex vivo immunohistochemical data that quantitatively support the validity of our method's estimates. Additionally, we demonstrate that MCP-counter overcomes several limitations or weaknesses of previously proposed computational approaches. MCP-counter is applied to draw a global picture of immune infiltrates across human healthy tissues and non-hematopoietic human tumors and recapitulates microenvironment-based patient stratifications associated with overall survival in lung adenocarcinoma and colorectal and breast cancer.