Predicting master transcription factors from pan-cancer expression data

Abstract

The function of critical developmental regulators can be subverted by cancer cells to control expression of oncogenic transcriptional programs. These "master transcription factors" (MTFs) are often essential for cancer cell survival and represent vulnerabilities that can be exploited therapeutically. The current approaches to identify candidate MTFs examine super-enhancer associated transcription factor-encoding genes with high connectivity in network models. This relies on chromatin immunoprecipitation-sequencing (ChIP-seq) data, which is technically challenging to obtain from primary tumors, and is currently unavailable for many cancer types and clinically relevant subtypes. In contrast, gene expression data are more widely available, especially for rare tumors and subtypes where MTFs have yet to be discovered. We have developed a predictive algorithm called CaCTS (Cancer Core Transcription factor Specificity) to identify candidate MTFs using pancancer RNA-sequencing data from The Cancer Genome Atlas. The algorithm identified 273 candidate MTFs across 34 tumor types and recovered known tumor MTFs. We also made novel predictions, including for cancer types and subtypes for which MTFs have not yet been characterized. Clustering based on MTF predictions reproduced anatomic groupings of tumors that share 1-2 lineage-specific candidates, but also dictated functional groupings, such as a squamous group that comprised five tumor subtypes sharing 3 common MTFs. PAX8, SOX17, and MECOM were candidate factors in high-grade serous ovarian cancer (HGSOC), an aggressive tumor type where the core regulatory circuit is currently uncharacterized. PAX8, SOX17, and MECOM are required for cell viability and lie proximal to super-enhancers in HGSOC cells. ChIPseq revealed that these factors co-occupy HGSOC regulatory elements globally and co-bind at critical gene loci including MUC16 (CA-125). Addiction to these factors was confirmed in studies using THZ1 to inhibit transcription in HGSOC cells, suggesting early down-regulation of these genes may be responsible for cytotoxic effects of THZ1 on HGSOC models. Identification of MTFs across 34 tumor types and 140 subtypes, especially for those with limited understanding of transcriptional drivers paves the way to therapeutic targeting of MTFs in a broad spectrum of cancers.

PAX8 orchestrates an angiogenic program through interaction with SOX17

“…At the protein level, PAX8 knockdown led to an almost complete disappearance of SOX17, and SOX17 knockdown led to a significant decrease in PAX8 levels. These results are reinforced by our recent findings showing that PAX8 and SOX17 were found to be master transcription factors that occupy regulatory elements related to their own encoding genes in ovarian cancer (39). Globally, PAX8 and SOX17 genomic binding sites co-localize within candidate active enhancers in HGSOC cell lines.…”

Repurposing of KLF5 activates a cell cycle signature during the progression from a precursor state to Oesophageal Adenocarcinoma

“…KLF5 is also frequently amplified in gastric cancer (Chia et al, 2015; Zhang et al, 2018) and has recently been shown to regulate gene expression in OAC in combination with other transcription factors, GATA6, ELF3 and EHF (Chen et al, 2019). This was recently reinforced by a recent study that identified KLF5 as a master transcription factor on which OAC cell-lines were dependent (Reddy et al, 2019). Paradoxically, KLF5 has been shown to have a tumour suppressor role in oesophageal squamous cell carcinoma (Tarapore et al, 2013) and breast cancer (Chen et al, 2002).…”

Single-cell Transcriptomics Identifies Gene Expression Networks Driving Differentiation and Tumorigenesis in the Human Fallopian Tube

“…Epithelial factors included SOX17, BARX2 and BHLHE41 in secretory epithelial cells, plus KLF5, TTF3 and RFX3 in ciliated epithelial cells. We recently identified SOX17 as a master regulator in high-grade serous ovarian cancers (Reddy et al, 2019), but SOX17 is not known to be a marker in physiologically normal fallopian tube epithelial cells. To validate this finding we performed immunohistochemistry for SOX17 on 14 fallopian tubes from cancer-free women; strong SOX17 staining was observed in all specimens, and was independent of age, menopausal status, and BRCA1/2 mutation status ( Figure 2B, Table S1).…”

“…Consistent with the RUNX3 regulon being specifically enriched in transitioning unclassified clusters 2 and 3, RUNX3 gene expression was unique to these clusters ( Figure 4D,F). TFs that characterize fallopian tube secretory epithelial cells are PAX8 (Levanon et al, 2010;Ozcan et al, 2011), SOX17 (this study and Reddy et al, 2019) and WT1, a clinically used biomarker of HGSC (Köbel et al, 2008;Shimizu et al, 2000). To understand the relationship of RUNX3 to these major secretory cell transcription factors, we transiently knocked down PAX8, SOX17 and WT1 in normal fallopian tube epithelial cells (FT282) and a HGSOC cell line (OVCAR4).…”

“…One of the greatest insights emerging from this work is the identification of transcription factors regulating the different stages of tubal epithelial cell differentiation. SOX17 was enriched in secretory cells, this factor had not been implicated in HGSC or fallopian biology until we recently described this protein as a master transcription factor for HGSC and both a regulator of and binding partner for PAX8 (Reddy et al, 2019; Moreira and Drapkin, personal communication). NR2F2 and EGR1 regulons were enriched in 'early secretory' and 'secretory 1' clusters.…”