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Two tumor (Classical/Basal) and stroma (Inactive/active) subtypes of Pancreatic adenocarcinoma (PDAC) with prognostic and theragnostic implications have been described. These molecular subtypes were defined by RNAseq, a costly technique sensitive to sample quality and cellularity, not used in routine practice. To allow rapid PDAC molecular subtyping and study PDAC heterogeneity, we develop PACpAInt, a multi-step deep learning model. PACpAInt is trained on a multicentric cohort (n = 202) and validated on 4 independent cohorts including biopsies (surgical cohorts n = 148; 97; 126 / biopsy cohort n = 25), all with transcriptomic data (n = 598) to predict tumor tissue, tumor cells from stroma, and their transcriptomic molecular subtypes, either at the whole slide or tile level (112 µm squares). PACpAInt correctly predicts tumor subtypes at the whole slide level on surgical and biopsies specimens and independently predicts survival. PACpAInt highlights the presence of a minor aggressive Basal contingent that negatively impacts survival in 39% of RNA-defined classical cases. Tile-level analysis ( > 6 millions) redefines PDAC microheterogeneity showing codependencies in the distribution of tumor and stroma subtypes, and demonstrates that, in addition to the Classical and Basal tumors, there are Hybrid tumors that combine the latter subtypes, and Intermediate tumors that may represent a transition state during PDAC evolution.
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Adenocarcinoma , Aprendizado Profundo , Neoplasias Pancreáticas , Humanos , Adenocarcinoma/genética , Neoplasias Pancreáticas/genética , Agressão , Neoplasias PancreáticasRESUMO
RNA sequencing (RNA-Seq) appears as a great tool with huge clinical potential, particularly in oncology. However, sufficient sample size is often a limiting factor and the vast majority of samples from patients with cancer are formalin-fixed paraffin-embedded (FFPE). To date, several sequencing kits are proposed for FFPE samples yet no comparison on low quantities were performed. To select the most reliable, cost-effective, and relevant RNA-Seq approach, we applied five FFPE-compatible kits (based on 3' capture, exome-capture and ribodepletion approaches) using 8 ng to 400 ng of FFPE-derived RNA and compared them to Nanostring on FFPE samples and to a reference PolyA (Truseq) approach on flash-frozen samples of the same tumors. We compared gene expression correlations and reproducibility. The Smarter Pico V3 ribodepletion approach appeared systematically the most comparable to Nanostring and Truseq (p < 0.001) and was a highly reproducible technique. In comparison with exome-capture and 3' kits, the Smarter appeared more comparable to Truseq (p < 0.001). Overall, our results suggest that the Smarter is the most robust RNA-Seq technique to study small FFPE samples and 3' Lexogen presents an interesting quality−price ratio for samples with less limiting quantities.
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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 .
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Adenocarcinoma , Neoplasias Pancreáticas , Algoritmos , Benchmarking , Biologia Computacional , Humanos , Neoplasias Pancreáticas/genéticaRESUMO
PURPOSE: The consensus molecular subtypes (CMS) represent a significant advance in the understanding of intertumor heterogeneity in colon cancer. Intratumor heterogeneity (ITH) is the new frontier for refining prognostication and understanding treatment resistance. This study aims at deciphering the transcriptomic ITH of colon cancer and understanding its potential prognostic implications. EXPERIMENTAL DESIGN: We deconvoluted the transcriptomic profiles of 1,779 tumors from the PETACC8 trial and 155 colon cancer cell lines as weighted sums of the four CMSs, using the Weighted In Silico Pathology (WISP) algorithm. We assigned to each tumor and cell line a combination of up to three CMS subtypes with a threshold above 20%. RESULTS: Over 55% of tumors corresponded to mixtures of at least two CMSs, demonstrating pervasive ITH in colon cancer. Of note, ITH was associated with shorter disease-free survival (DFS) and overall survival, [HR, 1.34; 95% confidence interval (CI; 1.12-1.59), 1.40, 95% CI (1.14-1.71), respectively]. Moreover, we uncovered specific combinations of CMS associated with dismal prognosis. In multivariate analysis, ITH represents the third parameter explaining DFS variance, after T and N stages. At a cellular level, combined WISP and single-cell transcriptomic analysis revealed that most colon cancer cell lines are a mixture of cells falling into different CMSs, indicating that ITH may correspond to distinct functional statuses of colon cancer cells. CONCLUSIONS: This study shows that CMS-based transcriptomic ITH is frequent in colon cancer and impacts its prognosis. CMS-based transcriptomic ITH may correspond to distinct functional statuses of colon cancer cells, suggesting plasticity between CMS-related cell populations. Transcriptomic ITH deserves further assessment in the context of personalized medicine.
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Neoplasias do Colo/genética , Neoplasias do Colo/patologia , Perfilação da Expressão Gênica , Microambiente Tumoral , Idoso , Linhagem Celular Tumoral , Neoplasias do Colo/classificação , Neoplasias do Colo/mortalidade , Feminino , Humanos , Masculino , Prognóstico , Taxa de SobrevidaRESUMO
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.
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BACKGROUND & AIMS: Next-generation sequencing (NGS) was recently approved by the United States Food and Drug Administration to detect microsatellite instability (MSI) arising from defective mismatch repair (dMMR) in patients with metastatic colorectal cancer (mCRC) before treatment with immune checkpoint inhibitors (ICI). In this study, we aimed to evaluate and improve the performance of NGS to identify MSI in CRC, especially dMMR mCRC treated with ICI. METHODS: CRC samples used in this post hoc study were reassessed centrally for MSI and dMMR status using the reference methods of pentaplex polymerase chain reaction and immunohistochemistry. Whole-exome sequencing (WES) was used to evaluate MSISensor, the Food and Drug Administration-approved and NGS-based method for assessment of MSI. This was performed in (1) a prospective, multicenter cohort of 102 patients with mCRC (C1; 25 dMMR/MSI, 24 treated with ICI) from clinical trials NCT02840604 and NCT033501260, (2) an independent retrospective, multicenter cohort of 113 patients (C2; 25 mCRC, 88 non-mCRC, all dMMR/MSI untreated with ICI), and (3) a publicly available series of 118 patients with CRC from The Cancer Genome Atlas (C3; 51 dMMR/MSI). A new NGS-based algorithm, namely MSICare, was developed. Its performance for assessment of MSI was compared with MSISensor in C1, C2, and C3 at the exome level or after downsampling sequencing data to the MSK-IMPACT gene panel. MSICare was validated in an additional retrospective, multicenter cohort (C4) of 152 patients with new CRC (137 dMMR/MSI) enriched in tumors deficient in MSH6 (n = 35) and PMS2 (n = 9) after targeted sequencing of samples with an optimized set of microsatellite markers (MSIDIAG). RESULTS: At the exome level, MSISensor was highly specific but failed to diagnose MSI in 16% of MSI/dMMR mCRC from C1 (4 of 25; sensitivity, 84%; 95% confidence interval [CI], 63.9%-95.5%), 32% of mCRC (8 of 25; sensitivity, 68%; 95% CI, 46.5%-85.1%), and 9.1% of non-mCRC from C2 (8 of 88; sensitivity, 90.9%; 95% CI, 82.9%-96%), and 9.8% of CRC from C3 (5 of 51; sensitivity, 90.2%; 95% CI, 78.6%-96.7%). Misdiagnosis included 4 mCRCs treated with ICI, of which 3 showed an overall response rate without progression at this date. At the exome level, reevaluation of the MSI genomic signal using MSICare detected 100% of cases with true MSI status among C1 and C2. Further validation of MSICare was obtained in CRC tumors from C3, with 96.1% concordance for MSI status. Whereas misdiagnosis with MSISensor even increased when analyzing downsampled WES data from C1 and C2 with microsatellite markers restricted to the MSK-IMPACT gene panel (sensitivity, 72.5%; 95% CI, 64.2%-79.7%), particularly in the MSH6-deficient setting, MSICare sensitivity and specificity remained optimal (100%). Similar results were obtained with MSICare after targeted NGS of tumors from C4 with the optimized microsatellite panel MSIDIAG (sensitivity, 99.3%; 95% CI, 96%-100%; specificity, 100%). CONCLUSIONS: In contrast to MSISensor, the new MSICare test we propose performs at least as efficiently as the reference method, MSI polymerase chain reaction, to detect MSI in CRC regardless of the defective MMR protein under both WES and targeted NGS conditions. We suggest MSICare may rapidly become a reference method for NGS-based testing of MSI in CRC, especially in mCRC, where accurate MSI status is required before the prescription of ICI.
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Algoritmos , Biomarcadores Tumorais/genética , Neoplasias Colorretais/genética , Reparo de Erro de Pareamento de DNA , Sequenciamento do Exoma , Sequenciamento de Nucleotídeos em Larga Escala , Instabilidade de Microssatélites , Tomada de Decisão Clínica , Ensaios Clínicos como Assunto , Neoplasias Colorretais/tratamento farmacológico , Neoplasias Colorretais/imunologia , Bases de Dados Genéticas , França , Humanos , Inibidores de Checkpoint Imunológico/uso terapêutico , Imuno-Histoquímica , Reação em Cadeia da Polimerase Multiplex , Valor Preditivo dos Testes , Estudos Prospectivos , Reprodutibilidade dos Testes , Estudos RetrospectivosRESUMO
Metastatic colorectal cancers (mCRC) harboring microsatellite instability (MSI) are sensitive to immune checkpoint inhibitors (ICIs), but the mechanisms of resistance to ICIs remain unclear. Dissociated responses in patients with ICI-treated cancer suggest that certain organs may serve as sanctuary sites due to the tumor microenvironment. This case series describes five patients with ICI-treated MSI mCRC with disease progression limited to the adrenal glands. At ICI initiation, three patients were free of metastasis in the adrenal glands. Four patients experienced objective response per RECIST (Response Evaluation Criteria in Solid Tumors) while treated with ICI. ICI treatment was discontinued due to progressive disease limited to the adrenal glands (n=3) or toxicity (n=2). The time between ICI initiation and progression in the adrenal glands ranged from 11 to 39 months. Adrenalectomy (n=3) and stereotactic body radiation therapy (n=2) were performed. At the last follow-up, all patients were alive and progression free. Molecular analyses were performed in one patient. A significant impairment of the antigen presentation pathway was observed in the ICI-resistant lesion of the adrenal gland, which could be explained by the presence of glucocorticoids in the adrenal gland microenvironment. We also detected an overexpression of TSC22D3, a glucocorticoid-target gene that functions as a mediator of anti-inflammation and immunosuppression. This case series suggests that the adrenal glands may be the sanctuary sites for ICI-treated MSI mCRC through the glucocorticoid-induced impairment of the antigen presentation machinery.
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Neoplasias das Glândulas Suprarrenais/secundário , Neoplasias Colorretais/tratamento farmacológico , Resistencia a Medicamentos Antineoplásicos , Inibidores de Checkpoint Imunológico/uso terapêutico , Instabilidade de Microssatélites , Neoplasias das Glândulas Suprarrenais/genética , Neoplasias das Glândulas Suprarrenais/imunologia , Neoplasias das Glândulas Suprarrenais/terapia , Adrenalectomia , Adulto , Idoso , Neoplasias Colorretais/genética , Neoplasias Colorretais/imunologia , Progressão da Doença , Humanos , Inibidores de Checkpoint Imunológico/efeitos adversos , Masculino , Pessoa de Meia-Idade , Radiocirurgia , Fatores de Transcrição/genética , Resultado do Tratamento , Microambiente TumoralRESUMO
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.
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Microambiente Celular/genética , Leucócitos/metabolismo , Células Estromais/metabolismo , Transcriptoma , Doença de Alzheimer/etiologia , Doença de Alzheimer/metabolismo , Doença de Alzheimer/patologia , Animais , Biomarcadores , Microambiente Celular/efeitos dos fármacos , Microambiente Celular/imunologia , Biologia Computacional/métodos , Bases de Dados Genéticas , Feminino , Perfilação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Inibidores de Checkpoint Imunológico/farmacologia , Proteínas de Checkpoint Imunológico/metabolismo , Leucócitos/efeitos dos fármacos , Leucócitos/imunologia , Camundongos , Curva ROC , Análise de Célula Única , Células Estromais/efeitos dos fármacos , Células Estromais/patologiaRESUMO
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.
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Adenocarcinoma/diagnóstico , Proteínas de Neoplasias/genética , Neoplasias Pancreáticas/diagnóstico , Transcriptoma/genética , Adenocarcinoma/genética , Adenocarcinoma/patologia , Adolescente , Adulto , Idoso , Animais , Protocolos de Quimioterapia Combinada Antineoplásica/efeitos adversos , Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Biomarcadores Tumorais/genética , Linhagem Celular Tumoral , Ensaios Clínicos como Assunto , Intervalo Livre de Doença , Resistencia a Medicamentos Antineoplásicos/genética , Aspiração por Agulha Fina Guiada por Ultrassom Endoscópico , Feminino , Fluoruracila/efeitos adversos , Fluoruracila/farmacologia , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Xenoenxertos , Humanos , Irinotecano/efeitos adversos , Irinotecano/farmacologia , Leucovorina/efeitos adversos , Leucovorina/farmacologia , Masculino , Camundongos , Pessoa de Meia-Idade , Metástase Neoplásica , Oxaliplatina/efeitos adversos , Oxaliplatina/farmacologia , Neoplasias Pancreáticas/genética , Neoplasias Pancreáticas/patologia , Medicina de Precisão , Prognóstico , Adulto Jovem , Neoplasias PancreáticasRESUMO
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.
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Neoplasias dos Ductos Biliares , Colangiocarcinoma , Imunofenotipagem/métodos , Transdução de Sinais/imunologia , Microambiente Tumoral/imunologia , Neoplasias dos Ductos Biliares/classificação , Neoplasias dos Ductos Biliares/tratamento farmacológico , Neoplasias dos Ductos Biliares/imunologia , Neoplasias dos Ductos Biliares/patologia , Ductos Biliares Intra-Hepáticos/patologia , Colangiocarcinoma/classificação , Colangiocarcinoma/tratamento farmacológico , Colangiocarcinoma/imunologia , Colangiocarcinoma/patologia , Descoberta de Drogas , Feminino , Humanos , Inibidores de Checkpoint Imunológico/farmacologia , Imunidade/imunologia , Imuno-Histoquímica , Inflamação/imunologia , Inflamação/patologia , Masculino , Pessoa de Meia-Idade , Prognóstico , TranscriptomaRESUMO
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.
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Neoplasias Ósseas/metabolismo , Condrossarcoma/metabolismo , Neoplasias Ósseas/genética , Ciclo Celular/genética , Diferenciação Celular/genética , Proliferação de Células/genética , Condrossarcoma/genética , Variações do Número de Cópias de DNA , Metilação de DNA , Progressão da Doença , Perfilação da Expressão Gênica , Humanos , MicroRNAs/metabolismo , Mutação Puntual , Recidiva , Estudos Retrospectivos , Análise de SobrevidaRESUMO
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.
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Heterogeneidade Genética , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Mesotelioma/genética , Mesotelioma/patologia , Neoplasias Pleurais/genética , Neoplasias Pleurais/patologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêutico , Análise por Conglomerados , Epigênese Genética/efeitos dos fármacos , Feminino , Heterogeneidade Genética/efeitos dos fármacos , Humanos , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/imunologia , Masculino , Mesotelioma/tratamento farmacológico , Mesotelioma/imunologia , Mesotelioma Maligno , Pessoa de Meia-Idade , Neoplasias Pleurais/tratamento farmacológico , Neoplasias Pleurais/imunologia , Prognóstico , Adulto JovemRESUMO
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).
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Carcinogênese/genética , Neoplasias Colorretais/genética , Instabilidade de Microssatélites , Mutação/genética , Sequências Repetitivas de Ácido Nucleico/genética , Animais , Sequência de Bases , Linhagem Celular Tumoral , Estudos de Coortes , Feminino , Xenoenxertos , Humanos , Masculino , Camundongos , Camundongos Nus , Modelos Estatísticos , Sequenciamento do ExomaRESUMO
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.
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Biomarcadores Tumorais/genética , Carcinoma Ductal Pancreático/genética , Epigênese Genética/genética , Regulação Neoplásica da Expressão Gênica , Neoplasias Pancreáticas/genética , Idoso , Idoso de 80 Anos ou mais , Animais , Carcinoma Ductal Pancreático/mortalidade , Carcinoma Ductal Pancreático/patologia , Linhagem Celular Tumoral , Imunoprecipitação da Cromatina/métodos , Metilação de DNA/genética , Conjuntos de Dados como Assunto , Feminino , Histonas/genética , Humanos , Masculino , Camundongos , Camundongos Nus , Pessoa de Meia-Idade , Neoplasias Pancreáticas/mortalidade , Neoplasias Pancreáticas/patologia , Sequências Reguladoras de Ácido Nucleico/genética , Análise de Sequência de RNA/métodos , Ensaios Antitumorais Modelo de XenoenxertoRESUMO
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.
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Neoplasias Pancreáticas/tratamento farmacológico , Animais , Carcinoma Ductal Pancreático , Transformação Celular Neoplásica/efeitos dos fármacos , Conjuntos de Dados como Assunto , Ezetimiba/farmacologia , Ezetimiba/uso terapêutico , Humanos , Masculino , Camundongos , Neoplasias Pancreáticas/metabolismo , Esferoides Celulares/efeitos dos fármacos , Ensaios Antitumorais Modelo de Xenoenxerto , Neoplasias PancreáticasRESUMO
BACKGROUND: Colon 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 FINDINGS: Fresh-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, pâ=â0.0097). However, a limitation of this study is that information on tumor grade and number of nodes examined was not available. CONCLUSIONS: We 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.
Assuntos
Biomarcadores Tumorais/genética , Neoplasias do Colo/genética , Perfilação da Expressão Gênica , Testes Genéticos , Adulto , Idoso , Idoso de 80 Anos ou mais , Distribuição de Qui-Quadrado , Análise por Conglomerados , Neoplasias do Colo/classificação , Neoplasias do Colo/mortalidade , Neoplasias do Colo/patologia , Neoplasias do Colo/cirurgia , Feminino , França , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , Predisposição Genética para Doença , Testes Genéticos/métodos , Humanos , Estimativa de Kaplan-Meier , Modelos Logísticos , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Estadiamento de Neoplasias , Fenótipo , Medicina de Precisão , Valor Preditivo dos Testes , Prognóstico , Modelos de Riscos Proporcionais , RNA Mensageiro/análise , Reprodutibilidade dos Testes , Medição de Risco , Fatores de Risco , Fatores de Tempo , Adulto JovemRESUMO
Links between cancer and stem cells have been proposed for many years. As the cancer stem cell (CSC) theory became widely studied, new methods were developed to culture and expand cancer cells with conserved determinants of "stemness". These cells show increased ability to grow in suspension as spheres in serum-free medium supplemented with growth factors and chemicals. The physiological relevance of this phenomenon in established cancer cell lines remains unclear. Cell lines have traditionally been used to explore tumor biology and serve as preclinical models for the screening of potential therapeutic agents. Here, we grew cell-forming spheres (CFS) from 25 established colorectal cancer cell lines. The molecular and cellular characteristics of CFS were compared to the bulk of tumor cells. CFS could be isolated from 72 % of the cell lines. Both CFS and their parental CRC cell lines were highly tumorigenic. Compared to their parental cells, they showed similar expression of putative CSC markers. The ability of CRC cells to grow as CFS was greatly enhanced by prior treatment with 5-fluorouracil. At the molecular level, CFS and parental CRC cells showed identical gene mutations and very similar genomic profiles, although microarray analysis revealed changes in CFS gene expression that were independent of DNA copy-number. We identified a CFS gene expression signature common to CFS from all CRC cell lines, which was predictive of disease relapse in CRC patients. In conclusion, CFS models derived from CRC cell lines possess interesting phenotypic features that may have clinical relevance for drug resistance and disease relapse.