Using RNA Sequencing Data to Detect Variants of Interest

The primary function for RNA sequencing (RNA-seq) is to investigate the transcriptome through differential gene expression. For cancer and other genetic diseases, detecting variants in the genome is critical for our understanding of how these diseases begin and progress. Here, I will present computational methods focused on using RNA-seq to detect disease-associated variants. We developed RNA-VACAY, a containerized high-throughput pipeline that automates somatic variant calling in RNA-seq data. We analyzed 1,349 RNA-seq samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Project and found that RNA-VACAY can accurately identify somatic variants of interest using tumor RNA-seq, alone. Our pipeline also does not require a matched normal sample to detect somatic variants, which is commonly unavailable in research or clinical settings. RNA-VACAY can also successfully identify 5’ and 3’ UTR variants, which are overlooked when using WES data. Additionally, we analyzed RNA-seq data to characterize splicing variants. We found a splice site variant associated with a previously detected variant of uncertain significance in a patient with an undiagnosed genetic disorder. We also developed a computational method for efficiently designing guide RNAs for a CRISPR/Cas9 screen to detect exon skipping events associated with tumor formation. Our work demonstrates the impact of RNA-seq for detecting functional variants in genetic diseases

Sustained MEK inhibition abrogates myeloproliferative disease in Nf1 mutant mice.

Children with neurofibromatosis type 1 (NF1) are predisposed to juvenile myelomonocytic leukemia (JMML), an aggressive myeloproliferative neoplasm (MPN) that is refractory to conventional chemotherapy. Conditional inactivation of the Nf1 tumor suppressor in hematopoietic cells of mice causes a progressive MPN that accurately models JMML and chronic myelomonocytic leukemia (CMML). We characterized the effects of Nf1 loss on immature hematopoietic populations and investigated treatment with the MEK inhibitor PD0325901 (hereafter called 901). Somatic Nf1 inactivation resulted in a marked expansion of immature and lineage-committed myelo-erythroid progenitors and ineffective erythropoiesis. Treatment with 901 induced a durable drop in leukocyte counts, enhanced erythropoietic function, and markedly reduced spleen sizes in mice with MPN. MEK inhibition also restored a normal pattern of erythroid differentiation and greatly reduced extramedullary hematopoiesis. Remarkably, genetic analysis revealed the persistence of Nf1-deficient hematopoietic cells, indicating that MEK inhibition modulates the proliferation and differentiation of Nf1 mutant cells in vivo rather than eliminating them. These data provide a rationale for performing clinical trials of MEK inhibitors in patients with JMML and CMML

Sustained MEK inhibition abrogates myeloproliferative disease in Nf1 mutant mice.

Children with neurofibromatosis type 1 (NF1) are predisposed to juvenile myelomonocytic leukemia (JMML), an aggressive myeloproliferative neoplasm (MPN) that is refractory to conventional chemotherapy. Conditional inactivation of the Nf1 tumor suppressor in hematopoietic cells of mice causes a progressive MPN that accurately models JMML and chronic myelomonocytic leukemia (CMML). We characterized the effects of Nf1 loss on immature hematopoietic populations and investigated treatment with the MEK inhibitor PD0325901 (hereafter called 901). Somatic Nf1 inactivation resulted in a marked expansion of immature and lineage-committed myelo-erythroid progenitors and ineffective erythropoiesis. Treatment with 901 induced a durable drop in leukocyte counts, enhanced erythropoietic function, and markedly reduced spleen sizes in mice with MPN. MEK inhibition also restored a normal pattern of erythroid differentiation and greatly reduced extramedullary hematopoiesis. Remarkably, genetic analysis revealed the persistence of Nf1-deficient hematopoietic cells, indicating that MEK inhibition modulates the proliferation and differentiation of Nf1 mutant cells in vivo rather than eliminating them. These data provide a rationale for performing clinical trials of MEK inhibitors in patients with JMML and CMML

Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia.

Juvenile myelomonocytic leukemia (JMML) is a myeloproliferative disorder of childhood caused by mutations in the Ras pathway. Outcomes in JMML vary markedly from spontaneous resolution to rapid relapse after hematopoietic stem cell transplantation. Here, we hypothesized that DNA methylation patterns would help predict disease outcome and therefore performed genome-wide DNA methylation profiling in a cohort of 39 patients. Unsupervised hierarchical clustering identifies three clusters of patients. Importantly, these clusters differ significantly in terms of 4-year event-free survival, with the lowest methylation cluster having the highest rates of survival. These findings were validated in an independent cohort of 40 patients. Notably, all but one of 14 patients experiencing spontaneous resolution cluster together and closer to 22 healthy controls than to other JMML cases. Thus, we show that DNA methylation patterns in JMML are predictive of outcome and can identify the patients most likely to experience spontaneous resolution