Genetics and Genomics Commons^™

The E2f4 Prognostic Signature Predicts Pathological Response To Neoadjuvant Chemotherapy In Breast Cancer Patients, Kenneth M. K. Mark, Frederick S. Varn, Matthew H. Ung, Feng Qian, Chao Cheng

Dartmouth Scholarship

Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease. We applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in …

A Longitudinal Cline Characterizes The Genetic Structure Of Human Populations In The Tibetan Plateau, Choongwon Jeong, Benjamin M. Peter, Buddha Basnyat, Maniraj Neupane, Geoff Childs, Sienna Craig, John Novembre, Anna Di Rienzo

Dartmouth Scholarship

Indigenous populations of the Tibetan plateau have attracted much attention for their good performance at extreme high altitude. Most genetic studies of Tibetan adaptations have used genetic variation data at the genome scale, while genetic inferences about their de- mography and population structure are largely based on uniparental markers. To provide genome-wide information on population structure, we analyzed new and published data of 338 individuals from indigenous populations across the plateau in conjunction with world- wide genetic variation data. We found a clear signal of genetic stratification across the east- west axis within Tibetan samples. Samples from more eastern locations …

Genetic Variants Of Ptpn2 Are Associated With Lung Cancer Risk: A Re-Analysis Of Eight Gwass In The Tricl-Ilcco Consortium, Yun Feng, Yanru Wang, Hongliang Liu, Zhensheng Liu, Coleman Mills, Younghun Han, Rayjean J. Hung, Yonathan Brhane, John Mcclaughlin, Paul Brennan

Dartmouth Scholarship

The T-cell protein tyrosine phosphatase (TCPTP) pathway consists of signaling events mediated by TCPTP. Mutations and genetic variants of some genes in the TCPTP pathway are associated with lung cancer risk and survival. In the present study, we first investigated associations of 5,162 single nucleotide polymorphisms (SNPs) in 43 genes of this TCPTP pathway with lung cancer risk by using summary data of six published genome-wide association studies (GWAS) of 12,160 cases and 16,838 controls. We identified 11 independent SNPs in eight genes after correction for multiple comparisons by a false discovery rate < 0.20. Then, we performed in silico functional analyses for these 11 SNPs by eQTL analysis, two of which, PTPN2 SNPs rs2847297 and rs2847282, were chosen as tagSNPs. We further included two additional GWAS datasets of Harvard University (984 cases and 970 controls) and deCODE (1,319 cases and 26,380 controls), and the overall effects of these two SNPs among all eight GWAS studies remained significant (OR = 0.95, 95% CI = 0.92–0.98, and P = 0.004 for rs2847297; OR = 0.95, 95% CI = 0.92–0.99, and P = 0.009 for rs2847282). In conclusion, the PTPN2 rs2847297 and rs2847282 may be potential susceptible loci for lung cancer risk.

A Novel Multi-Network Approach Reveals Tissue-Specific Cellular Modulators Of Fibrosis In Systemic Sclerosis, Jaclyn N. Taroni, Casey S. Greene, Viktor Martyanov, Tammara A. Wood

Dartmouth Scholarship

Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement is heterogeneous. It is unknown whether disease mechanisms are common across all involved affected tissues or if each manifestation has a distinct underlying pathology.We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected tissues (skin, lung, esophagus, and peripheral blood) from patients with SSc, and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension, and derived a consensus disease-associate signature across all tissues. We used this signature to query tissue-specific functional genomic networks. We performed novel network analyses to contrast …

A Machine Learning Classifier Trained On Cancer Transcriptomes Detects Nf1 Inactivation Signal In Glioblastoma, Gregory P. Way, Robert J. Allaway, Stephanie J. J. Bouley, Camilo E. Fadul, Yolanda Sanchez, Casey Greene

Dartmouth Scholarship

We have identified molecules that exhibit synthetic lethality in cells with loss of the neurofibromin 1 (NF1) tumor suppressor gene. However, recognizing tumors that have inactivation of the NF1 tumor suppressor function is challenging because the loss may occur via mechanisms that do not involve mutation of the genomic locus. Degradation of the NF1 protein, independent of NF1 mutation status, phenocopies inactivating mutations to drive tumors in human glioma cell lines. NF1 inactivation may alter the transcriptional landscape of a tumor and allow a machine learning classifier to detect which tumors will benefit from synthetic lethal molecules. We …

Familial Lung Cancer: A Brief History From The Earliest Work To The Most Recent Studies, Anthony Musolf, Claire Simpson, Mariza De Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Yafang Li

Dartmouth Scholarship

Lung cancer is the deadliest cancer in the United States, killing roughly one of four cancer patients in 2016. While it is well-established that lung cancer is caused primarily by environmental effects (particularly tobacco smoking), there is evidence for genetic susceptibility. Lung cancer has been shown to aggregate in families, and segregation analyses have hypothesized a major susceptibility locus for the disease. Genetic association studies have provided strong evidence for common risk variants of small-to-moderate effect. Rare and highly penetrant alleles have been identified by linkage studies, including on 6q23–25. Though not common, some germline mutations have also been identified …

Inferring Condition-Specific Targets Of Human Tf-Tf Complexes Using Chip-Seq Data, Chia-Chun Yang, Min-Hsuan Chen, Sheng-Yi Lin, Erik H. Andrews, Chao Cheng, Jeremy J.W Chen

Dartmouth Scholarship

Background:

Transcription factors (TFs) often interact with one another to form TF complexes that bind DNA and regulate gene expression. Many databases are created to describe known TF complexes identified by either mammalian two-hybrid experiments or data mining. Lately, a wealth of ChIP-seq data on human TFs under different experiment conditions are available, making it possible to investigate condition-specific (cell type and/or physiologic state) TF complexes and their target genes.

Results:

Here, we developed a systematic pipeline to infer Condition-Specific Targets of human TF-TF complexes (called the CST pipeline) by integrating ChIP-seq data and TF motifs. In total, we predicted …