RESUMO
Regulatory networks containing enhancer-gene edges define cellular states. Multiple efforts have revealed these networks for reference tissues and cell lines by integrating multi-omics data. However, the methods developed cannot be applied for large patient cohorts due to the infeasibility of chromatin immunoprecipitation sequencing (ChIP-seq) for limited biopsy material. We trained machine-learning models using chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture combined with chromatin immunoprecipitation (HiChIP) data that can predict connections using only assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq data as input, which can be generated from biopsies. Our method overcomes limitations of correlation-based approaches that cannot distinguish between distinct target genes of given enhancers or between active vs. poised states in different samples, a hallmark of network rewiring in cancer. Application of our model on 371 samples across 22 cancer types revealed 1,780 enhancer-gene connections for 602 cancer genes. Using CRISPR interference (CRISPRi), we validated enhancers predicted to regulate ESR1 in estrogen receptor (ER)+ breast cancer and A1CF in liver hepatocellular carcinoma.
Assuntos
Sequenciamento de Cromatina por Imunoprecipitação , Cromatina , Humanos , Cromatina/genética , Sequências Reguladoras de Ácido Nucleico , RNA-Seq , Linhagem CelularRESUMO
In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR) dependence leads to clinically aggressive tumors with few therapeutic options. We used ATAC-seq (assay for transposase-accessible chromatin sequencing), RNA-seq, and DNA sequencing to investigate 22 organoids, six patient-derived xenografts, and 12 cell lines. We identified the well-characterized AR-dependent and neuroendocrine subtypes, as well as two AR-negative/low groups: a Wnt-dependent subtype, and a stem cell-like (SCL) subtype driven by activator protein-1 (AP-1) transcription factors. We used transcriptomic signatures to classify 366 patients, which showed that SCL is the second most common subtype of CRPC after AR-dependent. Our data suggest that AP-1 interacts with the YAP/TAZ and TEAD proteins to maintain subtype-specific chromatin accessibility and transcriptomic landscapes in this group. Together, this molecular classification reveals drug targets and can potentially guide therapeutic decisions.
Assuntos
Cromatina , Terapia de Alvo Molecular , Neoplasias de Próstata Resistentes à Castração , Linhagem Celular Tumoral , Cromatina/genética , Perfilação da Expressão Gênica , Humanos , Masculino , Células-Tronco Neoplásicas/classificação , Células-Tronco Neoplásicas/metabolismo , Organoides/metabolismo , Organoides/patologia , Neoplasias de Próstata Resistentes à Castração/classificação , Neoplasias de Próstata Resistentes à Castração/tratamento farmacológico , Neoplasias de Próstata Resistentes à Castração/genética , Receptores Androgênicos/genética , Receptores Androgênicos/metabolismo , Fator de Transcrição AP-1/genética , Fator de Transcrição AP-1/metabolismoRESUMO
Ninety-seven percent of drug-indication pairs that are tested in clinical trials in oncology never advance to receive U.S. Food and Drug Administration approval. While lack of efficacy and dose-limiting toxicities are the most common causes of trial failure, the reason(s) why so many new drugs encounter these problems is not well understood. Using CRISPR-Cas9 mutagenesis, we investigated a set of cancer drugs and drug targets in various stages of clinical testing. We show that-contrary to previous reports obtained predominantly with RNA interference and small-molecule inhibitors-the proteins ostensibly targeted by these drugs are nonessential for cancer cell proliferation. Moreover, the efficacy of each drug that we tested was unaffected by the loss of its putative target, indicating that these compounds kill cells via off-target effects. By applying a genetic target-deconvolution strategy, we found that the mischaracterized anticancer agent OTS964 is actually a potent inhibitor of the cyclin-dependent kinase CDK11 and that multiple cancer types are addicted to CDK11 expression. We suggest that stringent genetic validation of the mechanism of action of cancer drugs in the preclinical setting may decrease the number of therapies tested in human patients that fail to provide any clinical benefit.
Assuntos
Antineoplásicos/toxicidade , Ensaios Clínicos como Assunto , Sistemas CRISPR-Cas/genética , Linhagem Celular Tumoral , Células Clonais , Quinases Ciclina-Dependentes/antagonistas & inibidores , Quinases Ciclina-Dependentes/metabolismo , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Técnicas de Inativação de Genes , Genoma Humano , Humanos , Terapia de Alvo Molecular , Quinolonas/farmacologia , Interferência de RNA/efeitos dos fármacos , Regulação para Cima/efeitos dos fármacosRESUMO
The Maternal Embryonic Leucine Zipper Kinase (MELK) has been identified as a promising therapeutic target in multiple cancer types. MELK over-expression is associated with aggressive disease, and MELK has been implicated in numerous cancer-related processes, including chemotherapy resistance, stem cell renewal, and tumor growth. Previously, we established that triple-negative breast cancer cell lines harboring CRISPR/Cas9-induced null mutations in MELK proliferate at wild-type levels in vitro (