Smruthy Sivakumar

Genomic Landscape of Atypical Adenomatous Hyperplasia Reveals Divergent Modes to Lung Adenocarcinoma

There is a dearth of knowledge about the pathogenesis of premalignant lung lesions, especially for atypical adenomatous hyperplasia (AAH), the only known precursor for the major lung cancer subtype adenocarcinoma (LUAD). In this study, we performed deep DNA and RNA sequencing analyses of a set of AAH, LUAD, and normal tissues. Somatic BRAF variants were found in AAHs from 5 of 22 (23%) patients, 4 of 5 of whom had matched LUAD with driver EGFR mutations. KRAS mutations were present in AAHs from 4 of 22 (18%) of patients. KRAS mutations in AAH were only found in ever-smokers and were exclusive to BRAF-mutant cases. Integrative analysis revealed profiles expressed in KRAS-mutant cases (UBE2C, REL) and BRAF-mutant cases (MAX) of AAH, or common to both sets of cases (suppressed AXL). Gene sets associated with suppressed antitumor (Th1; IL12A, GZMB) and elevated protumor (CCR2, CTLA-4) immune signaling were enriched in AAH development and progression. Our results reveal potentially divergent BRAF or KRAS pathways in AAH as well as immune dysregulation in the pathogenesis of this premalignant lung lesion. Cancer Res; 77(22); 6119-30. ©2017 AACR.

Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq

Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data. Results: Our method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA. Availability and Implementation: hapLOHseq is available at scheet.org/software, distributed under an open source MIT license. Contact: pscheet@alum.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

TBX2 subfamily suppression in lung cancer pathogenesis: a high-potential marker for early detection

The TBX2 subfamily (TBXs 2, 3, 4 and 5) transactivates or represses genes involved in lung organogenesis. Yet TBX2 subfamily expression in pathogenesis of non-small cell lung cancer (NSCLC), the most common lung malignancy, remains elusive. We sought to probe the expression profile of the TBX2 subfamily in early phases of NSCLC. Expression of TBX2 subfamily was analyzed in datasets of pan-normal specimens as well as NSCLCs and normal lung tissues. TBX2 subfamily expression in matched normal lungs, premalignant hyperplasias and NSCLCs was profiled by transcriptome sequencing. TBX2 subfamily expression was evaluated in the cancerization field consisting of matched NSCLCs and adjacent cytologically-normal airways relative to distant normal lungs and in a dataset of normal bronchial samples from smokers with indeterminate nodules suspicious for malignancy. Statistical analysis was performed using R. TBX2 subfamily expression was markedly elevated in normal lungs relative to other organ-specific normal tissues. Expression of the TBXs was significantly suppressed in NSCLCs relative to normal lungs (P < 10−9). TBX2 subfamily was significantly progressively decreased across premalignant lesions and NSCLCs relative to normal lungs (P < 10−4). The subfamily was significantly suppressed in NSCLCs and adjacent normal-appearing airways relative to distant normal lung tissues (P < 10−15). Further, suppressed TBX2 subfamily expression in normal bronchi was associated with lung cancer status (P < 10−5) in smokers. Our findings suggest that the TBX2 subfamily is notably suppressed in human NSCLC pathogenesis and may serve as a high-potential biomarker for early lung cancer detection in high-risk smokers.

Genome-Wide Gene Expression Changes in the Normal-Appearing Airway during the Evolution of Smoking-Associated Lung Adenocarcinoma

Smoking perpetuates in cytologically normal airways a molecular “field of injury” that is pertinent to lung cancer and early detection. The evolution of airway field changes prior to lung oncogenesis is poorly understood largely due to the long latency of lung cancer in smokers. Here, we studied airway expression changes prior to lung cancer onset in mice with knockout of the Gprc5a gene (Gprc5a−/−) and tobacco carcinogen (NNK) exposure and that develop the most common type of lung cancer, lung adenocarcinoma, within 6 months following exposure. Airway epithelial brushings were collected from Gprc5a−/− mice before exposure and at multiple times post-NNK until time of lung adenocarcinoma development and then analyzed by RNA sequencing. Temporal airway profiles were identified by linear models and analyzed by comparative genomics in normal airways of human smokers with and without lung cancer. We identified significantly altered profiles (n = 926) in the NNK-exposed mouse normal airways relative to baseline epithelia, a subset of which were concordantly modulated with smoking status in the human airway. Among airway profiles that were significantly modulated following NNK, we found that expression changes (n = 22) occurring as early as 2 months following exposure were significantly associated with lung cancer status when examined in airways of human smokers. Furthermore, a subset of a recently reported human bronchial gene classifier (Percepta; n = 56) was enriched in the temporal mouse airway profiles. We underscore evolutionarily conserved profiles in the normal-appearing airway that develop prior to lung oncogenesis and that comprise viable markers for early lung cancer detection in suspect smokers. Cancer Prev Res; 11(4); 237–48. ©2018 AACR.

Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform

Background‘Next-generation’ (NGS) sequencing has wide application in medical genetics, including the detection of somatic variation in cancer. The Ion Torrent-based (IONT) platform is among NGS technologies employed in clinical, research and diagnostic settings. However, identifying mutations from IONT deep sequencing with high confidence has remained a challenge. We compared various computational variant-calling methods to derive a variant identification pipeline that may improve the molecular diagnostic and research utility of IONT.ResultsUsing IONT, we surveyed variants from the 409-gene Comprehensive Cancer Panel in whole-section tumors, intra-tumoral biopsies and matched normal samples obtained from frozen tissues and blood from four early-stage non-small cell lung cancer (NSCLC) patients. We used MuTect, Varscan2, IONT’s proprietary Ion Reporter, and a simple subtraction we called “Poor Man’s Caller.” Together these produced calls at 637 loci across all samples. Visual validation of 434 called variants was performed, and performance of the methods assessed individually and in combination. Of the subset of inspected putative variant calls (n=223) in genomic regions that were not intronic or intergenic, 68 variants (30%) were deemed valid after visual inspection. Among the individual methods, the Ion Reporter method offered perhaps the most reasonable tradeoffs. Ion Reporter captured 83% of all discovered variants; 50% of its variants were visually validated. Aggregating results from multiple packages offered varied improvements in performance.ConclusionsOverall, Ion Reporter offered the most attractive performance among the individual callers. This study suggests combined strategies to maximize sensitivity and positive predictive value in variant calling using IONT deep sequencing.