Avinash Ramu

Convergent loss of PTEN leads to clinical resistance to a PI(3)Kα inhibitor

Broad and deep tumour genome sequencing has shed new light on tumour heterogeneity and provided important insights into the evolution of metastases arising from different clones. There is an additional layer of complexity, in that tumour evolution may be influenced by selective pressure provided by therapy, in a similar fashion to that occurring in infectious diseases. Here we studied tumour genomic evolution in a patient (index patient) with metastatic breast cancer bearing an activating PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha, PI(3)Kα) mutation. The patient was treated with the PI(3)Kα inhibitor BYL719, which achieved a lasting clinical response, but the patient eventually became resistant to this drug (emergence of lung metastases) and died shortly thereafter. A rapid autopsy was performed and material from a total of 14 metastatic sites was collected and sequenced. All metastatic lesions, when compared to the pre-treatment tumour, had a copy loss of PTEN (phosphatase and tensin homolog) and those lesions that became refractory to BYL719 had additional and different PTEN genetic alterations, resulting in the loss of PTEN expression. To put these results in context, we examined six other patients also treated with BYL719. Acquired bi-allelic loss of PTEN was found in one of these patients, whereas in two others PIK3CA mutations present in the primary tumour were no longer detected at the time of progression. To characterize our findings functionally, we examined the effects of PTEN knockdown in several preclinical models (both in cell lines intrinsically sensitive to BYL719 and in PTEN-null xenografts derived from our index patient), which we found resulted in resistance to BYL719, whereas simultaneous PI(3)K p110β blockade reverted this resistance phenotype. We conclude that parallel genetic evolution of separate metastatic sites with different PTEN genomic alterations leads to a convergent PTEN-null phenotype resistant to PI(3)Kα inhibition.

DeNovoGear: de novo indel and point mutation discovery and phasing

We present DeNovoGear software for analyzing de novo mutations from familial and somatic tissue sequencing data. DeNovoGear uses likelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analysis and fragment information to identify the parental origin of germ-line mutations. We used DeNovoGear on human whole-genome sequencing data to produce a set of predicted de novo insertion and/or deletion (indel) mutations with a 95% validation rate.

Human spermatogenic failure purges deleterious mutation load from the autosomes and both sex chromosomes, including the gene DMRT1.

Gonadal failure, along with early pregnancy loss and perinatal death, may be an important filter that limits the propagation of harmful mutations in the human population. We hypothesized that men with spermatogenic impairment, a disease with unknown genetic architecture and a common cause of male infertility, are enriched for rare deleterious mutations compared to men with normal spermatogenesis. After assaying genomewide SNPs and CNVs in 323 Caucasian men with idiopathic spermatogenic impairment and more than 1,100 controls, we estimate that each rare autosomal deletion detected in our study multiplicatively changes a mans risk of disease by 10% (OR 1.10 [1.04–1.16], p<2×10−3), rare X-linked CNVs by 29%, (OR 1.29 [1.11–1.50], p<1×10−3), and rare Y-linked duplications by 88% (OR 1.88 [1.13–3.13], p<0.03). By contrasting the properties of our case-specific CNVs with those of CNV callsets from cases of autism, schizophrenia, bipolar disorder, and intellectual disability, we propose that the CNV burden in spermatogenic impairment is distinct from the burden of large, dominant mutations described for neurodevelopmental disorders. We identified two patients with deletions of DMRT1, a gene on chromosome 9p24.3 orthologous to the putative sex determination locus of the avian ZW chromosome system. In an independent sample of Han Chinese men, we identified 3 more DMRT1 deletions in 979 cases of idiopathic azoospermia and none in 1,734 controls, and found none in an additional 4,519 controls from public databases. The combined results indicate that DMRT1 loss-of-function mutations are a risk factor and potential genetic cause of human spermatogenic failure (frequency of 0.38% in 1306 cases and 0% in 7,754 controls, p = 6.2×10−5). Our study identifies other recurrent CNVs as potential causes of idiopathic azoospermia and generates hypotheses for directing future studies on the genetic basis of male infertility and IVF outcomes.

CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer

CIViC is an expert-crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer describing the therapeutic, prognostic, diagnostic and predisposing relevance of inherited and somatic variants of all types. CIViC is committed to open-source code, open-access content, public application programming interfaces (APIs) and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.

A Phase I Trial of BKM120 (Buparlisib) in Combination with Fulvestrant in Postmenopausal Women with Estrogen Receptor-Positive Metastatic Breast Cancer.

Purpose: This trial was conducted to determine the maximum tolerated dose (MTD) and preliminary efficacy of buparlisib, an oral pan-class I PI3K inhibitor, plus fulvestrant in postmenopausal women with metastatic estrogen receptor positive (ER+) breast cancer. Experimental Design: Phase IA employed a 3+3 design to determine the MTD of buparlisib daily plus fulvestrant. Subsequent cohorts (phase IB and cohort C) evaluated intermittent (5/7-day) and continuous dosing of buparlisib (100 mg daily). No more than 3 prior systemic treatments in the metastatic setting were allowed in these subsequent cohorts. Results: Thirty-one patients were enrolled. MTD was defined as buparlisib 100 mg daily plus fulvestrant. Common adverse events (AE) included fatigue (38.7%), transaminases elevation (35.5%), rash (29%), and diarrhea (19.4%). C-peptide was significantly increased during treatment, consistent with on-target effect of buparlisib. Compared with intermittent dosing, daily buparlisib was associated with more frequent early onset AEs and higher buparlisib plasma concentrations. Among the 29 evaluable patients, the clinical benefit rate was 58.6% (95% CI, 40.7%–74.5%). Response was not associated with PIK3CA mutation or treatment cohort; however, loss of PTEN, progesterone receptor (PgR) expression, or mutation in TP53 was most common in resistant cases, and mutations in AKT1 and ESR1 did not exclude treatment response. Conclusions: Buparlisib plus fulvestrant is clinically active with manageable AEs in patients with metastatic ER+ breast cancer. Weekend breaks in buparlisib dosing reduced toxicity. Patients with PgR negative and TP53 mutation did poorly, suggesting buparlisib plus fulvestrant may not be adequately effective against tumors with these poor prognostic molecular features. Clin Cancer Res; 22(7); 1583–91. ©2015 AACR.

Dynamic landscape and regulation of RNA editing in mammals

Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules. Although many editing sites have recently been discovered, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.

Genome Modeling System: A Knowledge Management Platform for Genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

CIViC: A knowledgebase for expert-crowdsourcing the clinical interpretation of variants in cancer.

CIViC is an expert crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer (www.civicdb.org) describing the therapeutic, prognostic, and diagnostic relevance of inherited and somatic variants of all types. CIViC is committed to open source code, open access content, public application programming interfaces (APIs), and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.

A genomic case study of mixed fibrolamellar hepatocellular carcinoma

We report the first comprehensive genomic analysis of a case of mixed conventional and fibrolamellar HCC (mFL-HCC). This study confirms the expression of DNAJB1:PRKACA, a fusion previously associated with pure FL-HCC but not conventional HCC, in mFL-HCC. These results indicate the DNAJB1:PRKACA fusion has diagnostic utility for both pure and mixed FL-HCC.

Arnav: Site specific error models to identify variants in RNA

Summary We present Arnav (Analysis of RNA variants) a lightweight and easy-to-use statistical method for detecting mutations from RNA sequencing data. Site-specific error models allow Arnav to call variants with high specificity when the true variant allele fraction is unknown. We show the utility of Arnav by identifying variants using RNA sequencing data from the GTEx project. Availability and Implementation Arnav is implemented in C++ and is distributed under the GPL license at https://github.com/gatoravi/arnav. Contact aramu@wustl.edu