Center for Craniofacial Molecular Biology, Norris Comprehensive Cancer Center, Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
Dr. Dechen Lin
Center for Craniofacial Molecular Biology, Norris Comprehensive Cancer Center, Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses. Maftools only requires somatic variants in Mutation Annotation Format (MAF) and is independent of larger alignment files. With the implementation of well-established statistical and computational methods, Maftools facilitates data-driven research and comparative analysis to discover novel results from publicly available data sets. In the present study, using three of the well-annotated cohorts from The Cancer Genome Atlas (TCGA), we describe the application of Maftools to reproduce known results. More importantly, we show that Maftools can also be used to uncover novel findings through integrative analysis.
De-Chen Lin, Ming-Rong Wang and colleagues report exome sequencing, RNA sequencing, and copy number analyses of esophageal squamous cell carcinoma. They identified recurrent mutations in FAT1, FAT2, ZNF750, EP300 and KMT2D. Esophageal squamous cell carcinoma (ESCC) is prevalent worldwide and particularly common in certain regions of Asia. Here we report the whole-exome or targeted deep sequencing of 139 paired ESCC cases, and analysis of somatic copy number variations (SCNV) of over 180 ESCCs. We identified previously uncharacterized mutated genes such as FAT1, FAT2, ZNF750 and KMT2D, in addition to those already known (TP53, PIK3CA and NOTCH1). Further SCNV evaluation, immunohistochemistry and biological analysis suggested their functional relevance in ESCC. Notably, RTK-MAPK-PI3K pathways, cell cycle and epigenetic regulation are frequently dysregulated by multiple molecular mechanisms in this cancer. Our approaches also uncovered many druggable candidates, and XPO1 was further explored as a therapeutic target because it showed both gene mutation and protein overexpression. Our integrated study unmasks a number of novel genetic lesions in ESCC and provides an important molecular foundation for understanding esophageal tumors and developing therapeutic targets.
The tumor microenvironment is a highly complex ecosystem of diverse cell types, which shape cancer biology and impact the responsiveness to therapy. Here, we analyze the microenvironment of esophageal squamous cell carcinoma (ESCC) using single-cell transcriptome sequencing in 62,161 cells from blood, adjacent nonmalignant and matched tumor samples from 11 ESCC patients. We uncover heterogeneity in most cell types of the ESCC stroma, particularly in the fibroblast and immune cell compartments. We identify a tumor-specific subset of CST1+ myofibroblasts with prognostic values and potential biological significance. CST1+ myofibroblasts are also highly tumor-specific in other cancer types. Additionally, a subset of antigen-presenting fibroblasts is revealed and validated. Analyses of myeloid and T lymphoid lineages highlight the immunosuppressive nature of the ESCC microenvironment, and identify cancer-specific expression of immune checkpoint inhibitors. This work establishes a rich resource of stromal cell types of the ESCC microenvironment for further understanding of ESCC biology.
Squamous cell carcinomas (SCCs) are aggressive malignancies. Previous report demonstrated that master transcription factors (TFs) TP63 and SOX2 exhibited overlapping genomic occupancy in SCCs. However, functional consequence of their frequent co-localization at super-enhancers remains incompletely understood. Here, epigenomic profilings of different types of SCCs reveal that TP63 and SOX2 cooperatively and lineage-specifically regulate long non-coding RNA (lncRNA) CCAT1 expression, through activation of its super-enhancers and promoter. Silencing of CCAT1 substantially reduces cellular growth both in vitro and in vivo, phenotyping the effect of inhibiting either TP63 or SOX2. ChIRP analysis shows that CCAT1 forms a complex with TP63 and SOX2, which regulates EGFR expression by binding to the super-enhancers of EGFR, thereby activating both MEK/ERK1/2 and PI3K/AKT signaling pathways. These results together identify a SCC-specific DNA/RNA/protein complex which activates TP63/SOX2-CCAT1-EGFR cascade and promotes SCC tumorigenesis, advancing our understanding of transcription dysregulation in cancer biology mediated by master TFs and super-enhancers.
Objectives Oesophageal squamous cell carcinoma (OSCC) is an aggressive malignancy and the major histological subtype of oesophageal cancer. Although recent large-scale genomic analysis has improved the description of the genetic abnormalities of OSCC, few targetable genomic lesions have been identified, and no molecular therapy is available. This study aims to identify druggable candidates in this tumour. Design High-throughput small-molecule inhibitor screening was performed to identify potent anti-OSCC compounds. Whole-transcriptome sequencing (RNA-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq) were conducted to decipher the mechanisms of action of CDK7 inhibition in OSCC. A variety of in vitro and in vivo cellular assays were performed to determine the effects of candidate genes on OSCC malignant phenotypes. Results The unbiased high-throughput small-molecule inhibitor screening led us to discover a highly potent anti-OSCC compound, THZ1, a specific CDK7 inhibitor. RNA-Seq revealed that low-dose THZ1 treatment caused selective inhibition of a number of oncogenic transcripts. Notably, further characterisation of the genomic features of these THZ1-sensitive transcripts demonstrated that they were frequently associated with super-enhancer (SE). Moreover, SE analysis alone uncovered many OSCC lineage-specific master regulators. Finally, integrative analysis of both THZ1-sensitive and SE-associated transcripts identified a number of novel OSCC oncogenes, including PAK4, RUNX1, DNAJB1, SREBF2 and YAP1, with PAK4 being a potential druggable kinase. Conclusions Our integrative approaches led to a catalogue of SE-associated master regulators and oncogenic transcripts, which may significantly promote both the understanding of OSCC biology and the development of more innovative therapies.