Systematic interrogation of mutation groupings reveals divergent downstream expression programs within key cancer genes.

BACKGROUND: Genes implicated in tumorigenesis often exhibit diverse sets of genomic variants in the tumor cohorts within which they are frequently mutated. For many genes, neither the transcriptomic effects of these variants nor their relationship to one another in cancer processes have been well-characterized. We sought to identify the downstream expression effects of these mutations and to determine whether this heterogeneity at the genomic level is reflected in a corresponding heterogeneity at the transcriptomic level. RESULTS: By applying a novel hierarchical framework for organizing the mutations present in a cohort along with machine learning pipelines trained on samples' expression profiles we systematically interrogated the signatures associated with combinations of mutations recurrent in cancer. This allowed us to catalogue the mutations with discernible downstream expression effects across a number of tumor cohorts as well as to uncover and characterize over a hundred cases where subsets of a gene's mutations are clearly divergent in their function from the remaining mutations of the gene. These findings successfully replicated across a number of disease contexts and were found to have clear implications for the delineation of cancer processes and for clinical decisions. CONCLUSIONS: The results of cataloguing the downstream effects of mutation subgroupings across cancer cohorts underline the importance of incorporating the diversity present within oncogenes in models designed to capture the downstream effects of their mutations.

Predicting transcription factor activity using prior biological information.

Dysregulation of normal transcription factor activity is a common driver of disease. Therefore, the detection of aberrant transcription factor activity is important to understand disease pathogenesis. We have developed Priori, a method to predict transcription factor activity from RNA sequencing data. Priori has two key advantages over existing methods. First, Priori utilizes literature-supported regulatory information to identify transcription factor-target gene relationships. It then applies linear models to determine the impact of transcription factor regulation on the expression of its target genes. Second, results from a third-party benchmarking pipeline reveals that Priori detects aberrant activity from 124 single-gene perturbation experiments with higher sensitivity and specificity than 11 other methods. We applied Priori and other top-performing methods to predict transcription factor activity from two large primary patient datasets. Our work demonstrates that Priori uniquely discovered significant determinants of survival in breast cancer and identified mediators of drug response in leukemia.

The RNA-Binding Protein HuR Posttranscriptionally Regulates the Protumorigenic Activator YAP1 in Pancreatic Ductal Adenocarcinoma.

Yes-associated protein 1 (YAP1) is indispensable for the development of mutant KRAS-driven pancreatic ductal adenocarcinoma (PDAC). High YAP1 mRNA is a prognostic marker for worse overall survival in patient samples; however, the regulatory mechanisms that mediate its overexpression are not well understood. YAP1 genetic alterations are rare in PDAC, suggesting that its dysregulation is likely not due to genetic events. HuR is an RNA-binding protein whose inhibition impacts many cancer-associated pathways, including the "conserved YAP1 signature" as demonstrated by gene set enrichment analysis. Screening publicly available and internal ribonucleoprotein immunoprecipitation (RNP-IP) RNA sequencing (RNA-Seq) data sets, we discovered that YAP1 is a high-confidence target, which was validated in vitro with independent RNP-IPs and 3' untranslated region (UTR) binding assays. In accordance with our RNA sequencing analysis, transient inhibition (e.g., small interfering RNA [siRNA] and small-molecular inhibition) and CRISPR knockout of HuR significantly reduced expression of YAP1 and its transcriptional targets. We used these data to develop a HuR activity signature (HAS), in which high expression predicts significantly worse overall and disease-free survival in patient samples. Importantly, the signature strongly correlates with YAP1 mRNA expression. These findings highlight a novel mechanism of YAP1 regulation, which may explain how tumor cells maintain YAP1 mRNA expression at dynamic times during pancreatic tumorigenesis.

Erythrocytosis and thromboembolic events in transgender individuals receiving gender-affirming testosterone.

Erythrocytosis is a well-recognized consequence of exogenous testosterone, however its prevalence and contributions to thrombosis remain unknown in the context of gender-affirming hormonal therapy. We undertook a retrospective study of transgender and non-binary (TGNB) adults receiving exogenous testosterone. In the retrospective sample, 923 transgender individuals receiving testosterone were identified with 519 having documented pre- and post-testosterone hemoglobin and hematocrit (Hgb/Hct). The mean peak Hgb/Hct was 15.7 g/dL, and 47.0%. Mean time-to-peak Hgb/Hct was 31.2 months; 7.8% developed a hemoglobin >17.5 g/dL, whereas 20% developed a hematocrit of >50%. Testosterone dose reduction occurred in 42% of patients with erythrocytosis and 4.8% underwent phlebotomy. Thromboembolic events occurred in 0.9%, of which 80% had developed erythrocytosis by either Hgb or Hct, including two cases each of superficial and calf vein thrombosis as well as one ischemic stroke. We then performed an analysis of 14,294,784 hospitalizations from the 2016-17 US National Inpatient Sample (NIS), which identified 4141 admissions involving transgender individuals. Of those, seven had erythrocytosis with one concurrent venous thromboembolic event. Hematocrit >50% occurs in up to 20% of transgender individuals receiving testosterone. Despite the high incidence of erythrocytosis, thromboembolic events and hospitalizations involving erythrocytosis were uncommon.