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Abstract We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Abstract Background Microsatellite instability (MSI) due to mismatch repair deficiency (dMMR) is common in colorectal cancer (CRC). These cancers are associated with somatic coding events, but the noncoding pathophysiological impact of this genomic instability is yet poorly understood. Here, we perform an analysis of coding and noncoding MSI events at the different steps of colorectal tumorigenesis using whole exome sequencing and search for associated splicing events via RNA sequencing at the bulk-tumor and single-cell levels. Results Our results demonstrate that MSI leads to hundreds of noncoding DNA mutations, notably at polypyrimidine U2AF RNA-binding sites which are endowed with cis-activity in splicing, while higher frequency of exon skipping events are observed in the mRNAs of MSI compared to non-MSI CRC. At the DNA level, these noncoding MSI mutations occur very early prior to cell transformation in the dMMR colonic crypt, accounting for only a fraction of the exon skipping in MSI CRC. At the RNA level, the aberrant exon skipping signature is likely to impair colonic cell differentiation in MSI CRC affecting the expression of alternative exons encoding protein isoforms governing cell fate, while also targeting constitutive exons, making dMMR cells immunogenic in early stage before the onset of coding mutations. This signature is characterized by its similarity to the oncogenic U2AF1-S34F splicing mutation observed in several other non-MSI cancer. Conclusions Overall, these findings provide evidence that a very early RNA splicing signature partly driven by MSI impairs cell differentiation and promotes MSI CRC initiation, far before coding mutations which accumulate later during MSI tumorigenesis.

Abstract Background The mesenchymal subtype of colorectal cancer (CRC), associated with poor prognosis, is characterized by abundant expression of the cellular prion protein PrPC, which represents a candidate therapeutic target. How PrPC is induced in CRC remains elusive. This study aims to elucidate the signaling pathways governing PrPC expression and to shed light on the gene regulatory networks linked to PrPC. Methods We performed in silico analyses on diverse datasets of in vitro, ex vivo and in vivo models of mouse CRC and patient cohorts. We mined ChIPseq studies and performed promoter analysis. CRC cell lines were manipulated through genetic and pharmacological approaches. We created mice combining conditional inactivation of Apc in intestinal epithelial cells and overexpression of the human prion protein gene PRNP. Bio-informatic analyses were carried out in two randomized control trials totalizing over 3000 CRC patients. Results In silico analyses combined with cell-based assays identified the Wnt-β-catenin and glucocorticoid pathways as upstream regulators of PRNP expression, with subtle differences between mouse and human. We uncover multiple feedback loops between PrPC and these two pathways, which translate into an aggravation of CRC pathogenesis in mouse. In stage III CRC patients, the signature defined by PRNP-CTNNB1-NR3C1, encoding PrPC, β-catenin and the glucocorticoid receptor respectively, is overrepresented in the poor-prognosis, mesenchymal subtype and associates with reduced time to recurrence. Conclusions An unleashed PrPC-dependent vicious circle is pathognomonic of poor prognosis, mesenchymal CRC. Patients from this aggressive subtype of CRC may benefit from therapies targeting the PRNP-CTNNB1-NR3C1 axis.

Abstract Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced-stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment tumors from the PURE01 neoadjuvant pembrolizumab immunotherapy trial, using a consolidative approach that combined transcriptional and genetic profiling with digital spatial profiling. We identify five distinctive genetic and transcriptomic programs and validate these in an independent neoadjuvant CPI trial to identify the features of response or resistance to CPI. By modeling the regulatory network, we identify the histone demethylase KDM5B as a repressor of tumor immune signaling pathways in one resistant subtype (S1, Luminal-excluded) and demonstrate that inhibition of KDM5B enhances immunogenicity in FGFR3-mutated BCa cells. Our study identifies signatures associated with response to CPI that can be used to molecularly stratify patients and suggests therapeutic alternatives for subtypes with poor response to neoadjuvant immunotherapy.

Abstract Background Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data. Results We present DECONbench, a standardized unbiased benchmarking resource, applied to the evaluation of computational methods quantifying cell-type heterogeneity in cancer. DECONbench includes gold standard simulated benchmark datasets, consisting of transcriptome and methylome profiles mimicking pancreatic adenocarcinoma molecular heterogeneity, and a set of baseline deconvolution methods (reference-free algorithms inferring cell-type proportions). DECONbench performs a systematic performance evaluation of each new methodological contribution and provides the possibility to publicly share source code and scoring. Conclusion DECONbench allows continuous submission of new methods in a user-friendly fashion, each novel contribution being automatically compared to the reference baseline methods, which enables crowdsourced benchmarking. DECONbench is designed to serve as a reference platform for the benchmarking of deconvolution methods in the evaluation of cancer heterogeneity. We believe it will contribute to leverage the benchmarking practices in the biomedical and life science communities. DECONbench is hosted on the open source Codalab competition platform. It is freely available at: https://competitions.codalab.org/competitions/27453 .

Retinoblastoma is the most frequent intraocular paediatric malignancy whose molecular basis remains poorly understood. Here, the authors perform multi-omic analysis and identify two subtypes; one in a cone differentiated state and one more aggressive showing cone dedifferentiation and expressing neuronal markers.

Multiple molecular profiling methods are required to study urothelial non-muscle-invasive bladder cancer (NMIBC) due to its heterogeneity. Here the authors integrate multi-omics data of 834 NMIBC patients, identifying a molecular subgroup associated with multiple alterations and worse outcomes.

Abstract 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.

Chondrosarcomas are heterogenous tumours of the bone cartilage and have highly variable prognoses. Here, the authors perform a multi-omics analysis, revealing molecular features that can stratify clinical outcomes.

Malignant pleural mesothelioma (MPM) is a rare and aggressive form of cancer. Here, the authors show MPM is heterogeneously composed of epithelioid and sarcomatoid components and their proportions associate with prognosis and could inform therapeutic strategies.

Activation of the PPARγ/RXRα pathway in luminal bladder cancers has mainly been linked to PPARG gene amplifications and activating point mutations in RXRα. Here, the authors identify recurrent PPARγ mutations with similar effects and elucidate the structural basis for this mutational PPARγ activation.

Context: The number of prognostic markers for clear cell renal cell carcinoma (ccRCC) has been increasing regularly over the last 15 years, without being integrated and compared.Objective: Our goal was to perform a review of prognostic markers for ccRCC to lay the ground for their use in the clinics.Evidence Acquisition: PubMed database was searched to identify RNA and protein markers whose expression level was reported as associated with survival of ccRCC patients. Relevant studies were selected through cross-reading by two readers.Evidence Synthesis: We selected 249 studies reporting an association with prognostic of either single markers or multiple-marker models. Altogether, these studies were based on a total of 341 distinct markers and 13 multiple-marker models. Twenty percent of these markers were involved in four biological pathways altered in ccRCC: cell cycle, angiogenesis, hypoxia, and immune response. The main genes (VHL, PBRM1, BAP1, and SETD2) involved in ccRCC carcinogenesis are not the most relevant for assessing survival.Conclusion: Among single markers, the most validated markers were KI67, BIRC5, TP53, CXCR4, and CA9. Of the multiple-marker models, the most famous model, ClearCode34, has been highly validated on several independent datasets, but its clinical utility has not yet been investigated.Patient Summary: Over the years, the prognosis studies have evolved from single markers to multiple-marker models. Our review highlights the highly validated prognostic markers and multiple-marker models and discusses their clinical utility for better therapeutic care.

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.

Tumor cells constantly interact with their microenvironment, which comprises a variety of immune cells together with endothelial cells and fibroblasts. The composition of the tumor microenvironment (TME) has been shown to influence response to immune checkpoint blockade (ICB). ICB takes advantage of immune cell infiltration in the tumor to reinvigorate an efficacious antitumoral immune response. In addition to tumor cell intrinsic biomarkers, increasing data pinpoint the importance of the TME in guiding patient selection and combination therapies. Here, we review recent efforts in determining how various components of the TME can influence response and resistance to ICB. Although a large body of evidence points to the extent and functional orientation of the T cell infiltrate as important in therapy response, recent studies also confirm a role for other components of the TME, such as B cells, myeloid lineage cells, cancer-associated fibroblasts, and vasculature. If the ultimate goal of curative cancer therapies is to induce a long-term memory T cell response, the other components of the TME may positively or negatively modulate the induction of efficient antitumor immunity. The emergence of novel high-throughput methods for analyzing the TME, including transcriptomics, has allowed tremendous developments in the field, with the expansion of patient cohorts, and the identification of TME-based markers of therapy response. Together, these studies open the possibility of including TME-based markers for selecting patients that are likely to respond to specific therapies, and pave the way to personalized medicine in oncology.

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease and its underlying epigenomic heterogeneity is not fully understood. Here, the authors utilize patient-derived PDAC xenografts to define the epigenomic landscape of PDAC, highlighting chromatin states linked to differing disease aggressiveness and survival.

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). Keywords: Colorectal Cancer, Microsatellite Instability, Tumorigenic Process, Driver Gene Mutations, Positive and Negative Selection

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.

We determined the proportions of epithelioid-like and sarcomatoid-like cellular entities within malignant pleural mesothelioma samples, by deconvolution of their transcriptomes. These proportions are associated with prognosis and may guide therapeutic strategies. This novel approach describes both intra- and inter-tumor heterogeneity and provides a new way of thinking about cancer pathology.

Oligodendroglial tumours are characterized into three different molecular subtypes. Here, the authors use genomic data to identify a further three subgroups of 1p/19q co-deleted tumours and demonstrate an association with an aggressive phenotype.

Tumors are formed by aggregates of cells of various origins including malignant, stromal and immune cells. The number of therapies targeting the microenvironment is increasing as the tumor microenvironment is more and more recognized as playing an essential role in tumor control. In the era of precision medicine, it is essential to precisely estimate the composition, organization and functionality of the individual patient tumor microenvironment and to find ways to therapeutically modulate it. To quantify the cell populations present in the tumor microenvironment, many tools are now available and the most recent approaches will be reviewed herein. We provide an overview of experimental and computational methodologies used to quantify tumor-associated cellular populations, including immunohistochemistry, flow and mass cytometry, bulk and single-cell transcriptomic approaches. We illustrate their respective contribution to characterize the microenvironment. We also discuss how these methods allow to guide therapeutic choices, in relation to the predictive value of some characteristics of the microenvironment.

Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applying ICA to nine cancer types identified cancer-shared and bladder-cancer-specific components. We characterized the luminal and basal-like subtypes of muscle-invasive bladder cancers according to the components identified. The study of the urothelial differentiation component, specific to the luminal subtypes, showed that a molecular urothelial differentiation program was maintained even in those luminal tumors that had lost morphological differentiation. Study of the genomic alterations associated with this component coupled with functional studies revealed a protumorigenic role for PPARG in luminal tumors. Our results support the inclusion of ICA in the exploitation of multiscale data sets.

Insulin-like growth factor 2 (IGF2) overexpression is an important molecular marker of adrenocortical carcinoma (ACC), which is a rare but devastating endocrine cancer. It is not clear whether IGF2 overexpression modifies the biology and growth of this cancer, thus more studies are required before IGF2 can be considered as a major therapeutic target. We compared the phenotypical, clinical, biological, and molecular characteristics of ACC with or without the overexpression of IGF2, to address these issues. We also carried out a similar analysis in an ACC cell line (H295R) in which IGF2 expression was knocked down with si- or shRNA. We found no significant differences in the clinical, biological and molecular (transcriptomic) traits between IGF2-high and IGF2-low ACC. The absence of IGF2 overexpression had little influence on the activation of tyrosine kinase pathways both in tumors and in H295 cells that express low levels of IGF2. In IGF2-low tumors, other growth factors (FGF9, PDGFA) are more expressed than in IGF2-high tumors, suggesting that they play a compensatory role in tumor progression. In addition, IGF2 knock-down in H295R cells substantially impaired growth (>50% inhibition), blocked cells in G1 phase, and promoted apoptosis (>2-fold). Finally, analysis of the 11p15 locus showed a paternal uniparental disomy in both IGF2-high and IGF2-low tumors, but low IGF2 expression could be explained in most IGF2-low ACC by an additional epigenetic modification at the 11p15 locus. Altogether, these observations confirm the active role of IGF2 in adrenocortical tumor growth, but also suggest that other growth promoting pathways may be involved in a subset of ACC with low IGF2 expression, which creates opportunities for the use of other targeted therapies.

Peripheral T-cell lymphoma, not otherwise specified is a heterogeneous group of aggressive neoplasms with indistinct borders. By gene expression profiling we previously reported unsupervised clusters of peripheral T-cell lymphomas, not otherwise specified correlating with CD30 expression. In this work we extended the analysis of peripheral T-cell lymphoma molecular profiles to prototypical CD30+ peripheral T-cell lymphomas (anaplastic large cell lymphomas), and validated mRNA expression profiles at the protein level. Existing transcriptomic datasets from peripheral T-cell lymphomas, not otherwise specified and anaplastic large cell lymphomas were reanalyzed. Twenty-one markers were selected for immunohistochemical validation on 80 peripheral T-cell lymphoma samples (not otherwise specified, CD30+ and CD30−; anaplastic large cell lymphomas, ALK+ and ALK−), and differences between subgroups were assessed. Clinical follow-up was recorded. Compared to CD30− tumors, CD30+ peripheral T-cell lymphomas, not otherwise specified were significantly enriched in ALK− anaplastic large cell lymphoma-related genes. By immunohistochemistry, CD30+ peripheral T-cell lymphomas, not otherwise specified differed significantly from CD30− samples [down-regulated expression of T-cell receptor-associated proximal tyrosine kinases (Lck, Fyn, Itk) and of proteins involved in T-cell differentiation/activation (CD69, ICOS, CD52, NFATc2); upregulation of JunB and MUM1], while overlapping with anaplastic large cell lymphomas. CD30− peripheral T-cell lymphomas, not otherwise specified tended to have an inferior clinical outcome compared to the CD30+ subgroups. In conclusion, we show molecular and phenotypic features common to CD30+ peripheral T-cell lymphomas, and significant differences between CD30− and CD30+ peripheral T-cell lymphomas, not otherwise specified, suggesting that CD30 expression might delineate two biologically distinct subgroups.

BackgroundColon cancer (CC) pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Methods and findingsFresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like), and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after adjusting for age, sex, stage, and the emerging prognostic classifier Oncotype DX Colon Cancer Assay recurrence score (hazard ratio 1.5, 95% CI 1.1-2.1, p = 0.0097). However, a limitation of this study is that information on tumor grade and number of nodes examined was not available.ConclusionsWe describe the first, to our knowledge, robust transcriptome-based classification of CC that improves the current disease stratification based on clinicopathological variables and common DNA markers. The biological relevance of these subtypes is illustrated by significant differences in prognosis. This analysis provides possibilities for improving prognostic models and therapeutic strategies. In conclusion, we report a new classification of CC into six molecular subtypes that arise through distinct biological pathways.

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the "missing" heritability in cancer. This method is freely available and can be used online at the FounderTracker website.

IntroductionGermline BRCA1 or BRCA2 mutations account for 20-30% of familial clustering of breast cancer. The main indication for BRCA2 screening is currently the family history but the yield of mutations identified in patients selected this way is low.MethodsTo develop more efficient approaches to screening we have compared the gene expression and genomic profiles of BRCA2-mutant breast tumors with those of breast tumors lacking BRCA1 or BRCA2 mutations.ResultsWe identified a group of 66 genes showing differential expression in our training set of 7 BRCA2-mutant tumors and in an independent validation set of 19 BRCA2-mutant tumors. The differentially expressed genes include a prominent cluster of genes from chromosomes 13 and 14 whose expression is reduced. Gene set enrichment analysis confirmed that genes in specific bands on 13q and 14q showed significantly reduced expression, suggesting that the affected bands may be preferentially deleted in BRCA2-mutant tumors. Genomic profiling showed that the BRCA2-mutant tumors indeed harbor deletions on chromosomes 13q and 14q. To exploit this information we have created a simple fluorescence in situ hybridization (FISH) test and shown that it detects tumors with deletions on chromosomes 13q and 14q.ConclusionTogether with previous reports, this establishes that deletions on chromosomes 13q and 14q are a hallmark of BRCA2-mutant tumors. We propose that FISH to detect these deletions would be an efficient and cost-effective first screening step to identify potential BRCA2-mutation carriers among breast cancer patients without a family history of breast cancer.

The Warburg effect describes how cancer cells down-regulate their aerobic respiration and preferentially use glycolysis to generate energy. To evaluate the link between hypoxia and Warburg effect, we studied mitochondrial electron transport, angiogenesis and glycolysis in pheochromocytomas induced by germ-line mutations in VHL, RET, NF1 and SDH genes. SDH and VHL gene mutations have been shown to lead to the activation of hypoxic response, even in normoxic conditions, a process now referred to as pseudohypoxia. We observed a decrease in electron transport protein expression and activity, associated with increased angiogenesis in SDH- and VHL-related, pseudohypoxic tumors, while stimulation of glycolysis was solely observed in VHL tumors. Moreover, microarray analyses revealed that expression of genes involved in these metabolic pathways is an efficient tool for classification of pheochromocytomas in accordance with the predisposition gene mutated. Our data suggest an unexpected association between pseudohypoxia and loss of p53, which leads to a distinct Warburg effect in VHL-related pheochromocytomas.

BackgroundIn breast cancers, only a minority of patients fully benefit from the different chemotherapy regimens currently in use. Identification of markers that could predict the response to a particular regimen would thus be critically important for patient care. In cell lines or animal models, tumor protein p53 (TP53) plays a critical role in modulating the response to genotoxic drugs. TP53 is activated in response to DNA damage and triggers either apoptosis or cell-cycle arrest, which have opposite effects on cell fate. Yet, studies linking TP53 status and chemotherapy response have so far failed to unambiguously establish this paradigm in patients. Breast cancers with a TP53 mutation were repeatedly shown to have a poor outcome, but whether this reflects poor response to treatment or greater intrinsic aggressiveness of the tumor is unknown.Methods and findingsIn this study we analyzed 80 noninflammatory breast cancers treated by frontline (neoadjuvant) chemotherapy. Tumor diagnoses were performed on pretreatment biopsies, and the patients then received six cycles of a dose-dense regimen of 75 mg/m(2) epirubicin and 1,200 mg/m(2) cyclophosphamide, given every 14 days. After completion of chemotherapy, all patients underwent mastectomies, thus allowing for a reliable assessment of chemotherapy response. The pretreatment biopsy samples were used to determine the TP53 status through a highly efficient yeast functional assay and to perform RNA profiling. All 15 complete responses occurred among the 28 TP53-mutant tumors. Furthermore, among the TP53-mutant tumors, nine out of ten of the highly aggressive basal subtypes (defined by basal cytokeratin [KRT] immunohistochemical staining) experienced complete pathological responses, and only TP53 status and basal subtype were independent predictors of a complete response. Expression analysis identified many mutant TP53-associated genes, including CDC20, TTK, CDKN2A, and the stem cell gene PROM1, but failed to identify a transcriptional profile associated with complete responses among TP53 mutant tumors. In patients with unresponsive tumors, mutant TP53 status predicted significantly shorter overall survival. The 15 patients with responsive TP53-mutant tumors, however, had a favorable outcome, suggesting that this chemotherapy regimen can overcome the poor prognosis generally associated with mutant TP53 status.ConclusionsThis study demonstrates that, in noninflammatory breast cancers, TP53 status is a key predictive factor for response to this dose-dense epirubicin-cyclophosphamide regimen and further suggests that the basal subtype is exquisitely sensitive to this association. Given the well-established predictive value of complete responses for long-term survival and the poor prognosis of basal and TP53-mutant tumors treated with other regimens, this chemotherapy could be particularly suited for breast cancer patients with a mutant TP53, particularly those with basal features.