An integrated analysis of the epigenetic, genetic, and transcriptional patterns associated with outcome across cancer types

Abstract

Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed genomic profiles from 33,036 solid tumors with known patient outcomes. Contrary to expectations, we find that mutations in cancer driver genes are almost never associated with patient survival time. In contrast, copy number changes in these same genes are broadly prognostic. Analysis of methylation, microRNA, mRNA, and protein expression patterns in primary tumors define several additional prognostic patterns, including signatures of tumor mitotic activity and tissue de-differentiation. Co-expression analysis with a cell cycle meta-gene distinguished proliferation-dependent and -independent prognostic features, allowing us to construct multivariate survival models with improved stratification power.In total, our analysis provides a comprehensive resource for biomarker and therapeutic target identification, and suggests that copy number and methylation profiling should complement tumor sequencing efforts to improve patient risk assessment.

MELK expression correlates with tumor mitotic activity but is not required for cancer growth

“…Despite the conflicting in vitro data, MELK expression remains one of the strongest predictors of patient mortality in diverse cancer types ( Smith and Sheltzer, 2017 ). Additionally, MELK has been implicated in several other cancer-related processes, including cancer stem cell maintenance, chemotherapy resistance, anchorage-independent growth, and reactive oxygen species (ROS)-signaling ( Wang et al, 2014 ; Ganguly et al, 2014a ; Beke et al, 2015 ; Kim et al, 2015 ; Seong et al, 2016 ; Choi et al, 2011 ; Gu et al, 2013 ; Hebbard et al, 2010 ).…”

Combining CRISPR/Cas9 mutagenesis and a small-molecule inhibitor to probe the function of MELK in cancer

“…Moreover, rapid cell division in tumors is indicative of tissue de-differentiation and aggressive disease; therefore, most cell cycle-regulated genes are also associated with clinical outcome (17,46,47). We found that controlling for cell proliferation ablates the significance of MELK expression, suggesting that this link may explain its prognostic role in cancer.…”

“…If MELK plays no overt role in cancer biology, then why would MELK expression be linked with death from cancer? We note that MELK expression is cell cycleregulated, peaking in mitosis (4,45), and gene signatures that capture mitotic activity have been found to be prognostic in multiple cancer types (17,46,47). We therefore considered the possibility that, rather than functioning as an oncogene or a cancer dependency, MELK expression could report cell division within a tumor.…”

“…Probesets annotated to the same gene were collapsed by averaging. Data were cleaned and processed using python's pandas library, and cox proportional hazard models were constructed using the survival library in R and as described in (17). Several additional python packages were used for clarity, conciseness, and correctness 21 including numpy, getopt and rpy2.…”

“…Despite the conflicting in vitro data, MELK expression remains one of the strongest predictors of patient mortality in diverse cancer types (17). Additionally, MELK has been implicated in several other cancer-related processes, including cancer stem cell maintenance, chemotherapy resistance, anchorage-independent growth, and reactive oxygen species (ROS)signaling (4,5,13,(18)(19)(20)(21)(22).…”