Uma Chandran, PhD, MSIS

Room 513
5607 Baum Boulevard
Pittsburgh, PA 15206
412-648-9326
Admin Support: 
Alias: 
chandranu
Peer-reviewed Publications: 
44
Biography
I have extensive experience in both bench research and bioinformatics and co-direct the Cancer Bioinformatics Service (CBS), a translational core service at the University of Pittsburgh Cancer Institute. CBS is an interdisciplinary collaboration between my core team, the Department of Biomedical Informatics faculty, UPCI, the Institute for Personalized Medicine, the Pittsburgh Supercomputing Center and the University of Pittsburgh's Simulation and Modeling Center. The CBS aims are to 1) provide data analysis, 2) develop high performance computing (HPC) infrastructure and 3) develop research databases to integrate clinical and genomic data for biomarker discovery. I have deep experience working with all genomic platforms and applications including next generation sequencing (NGS) based RNA Seq, Whole Exome Seq (WXS) and Whole Genome Seq (WGS). I have also performed integrative analysis across multiple platforms and from large consortia datasets such as The Cancer Genome Atlas (TCGA) project. I am a key member of several data science projects in DBMI including the Pittsburgh Genome Resource Repository (PGRR), a regulatory, hardware and software infrastructure for TCGA data and the PACURE projects in breast and lung cancers. CBS supports all CCCG's disease specific programs and has performed somatic variant analysis in melanoma, lung, mesothelioma and renal cell cancers, copy number analysis to understand the differences and similarities between pediatric gliomas to adult gliomas, and RNA seq expression and integrative analysis of TCGA breast tumor samples. My team of analysts and I also support non-cancer genomic studies including development of methods for de novo transcriptome assembly. The combination of experience in bench science and bioinformatics allows me to not only provide data analysis services but also biological insight into the results of high throughput data such as integrative analysis of ChIP Seq and RNA seq data. We have partnered closely with the PSC and SaM to develop the HPC infrastructure to meet the computational demands of next generation sequencing analysis and have been awarded NSF's XSEDE award for computation and storage. With this team approach to bioinformatics, I have built a shared resource which can quickly meet the bioinformatics requirements of rapidly changing genomics landscape and a computing infrastructure which scales easily to terabytes of data.
Academic Appointments: 
12/2015 - present
Visiting Research Associate Professor, Department of Biomedical Informatics, University of Pittsburgh
12/2015 - present
Co-director, Cancer Bioinformatics Services, UPCI, University of Pittsburgh
Grants & Contracts: 
02/1/2016 - 01/31/2017
NIH 5R01HD072189
Molecular Bases Committing Primate Spermatogonia to a Pathway of Differentiation
Role: Co-Investigator
06/1/2015 - 05/31/2018
PA DOH SAP4100070287
Big Data for Better Health (BD4BH) in Pennsylvania
Role: Co-Investigator
07/15/2013 - 06/30/2017
NIH 5R01DK099320
Regulation of HNF4 in Hepatic Failure in Cirrhosis
Role: Co-Investigator
07/1/2006 - 06/30/2018
NIH P50 CA121973
Spore in Skin Cancer
Role: Co-Investigator
09/1/1998 - 01/31/2017
NIH 5R01NS037704
Molecular Markers as Predictors of Outcome in Gliomas
Role: Research Associate
09/10/1997 - 07/31/2020
NIH/NCI 2P30CA047904
Cancer Center Support (CCSG)
Role: Core Lead
12/18/1996 - 02/28/2019
NIH 5R01CA186780
Roles of EAF2 in Androgen Action in the Prostate
Role: Co-Investigator
Teaching Activities: 
2013 - presentIntro to Bioinformatics
03/2007 - presentIntroduction to Microarray Analysis
07/2002 - presentIntroduction to Bioinformatics to Pathology Residents
Service Activities: 
Department
presentTraining Program Member, Training Program Committee
Other
presentReviewer, Pathology Informatics
presentReviewer, AMIA conference on Translational Bioinformatics
Presentations: 
- Chandran U, Chakka A. Variant Analysis for Cancer Genomics. Presented at: AACR. San Diego, CA.
- Chandran U. PGRR - Intro to the Cancer Genome Atlas. Presented at: UPCI Annual Retreat 2014 2014 Jun 18 - 19. University of Pittsburgh Greensburg.
- Chandran U. The Cancer Genome Atlas. Presented at: Magee Women's Research Institute Annual Retreat 2013 Nov 15 - 16. Nemacolin Woods, PA.
- Chandran U. Bioinformatics - Practical Applications in Pathology. Presented at: APIII 2010 2010 Sep 19 - 22. Boston, MA.
Selected Peer-Reviewed Publications: 
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Concha-Benavente F, Srivastava RM, Trivedi S, Lei Y, Chandran U, Seethala RR, Freeman GJ, Ferris RL. Identification of the Cell-Intrinsic and -Extrinsic Pathways Downstream of EGFR and IFN¿ That Induce PD-L1 Expression in Head and Neck Cancer. Cancer Research. 2016 Mar 1;76(5):1031-43. PMID:26676749. PMCID:PMC4775348.
Abstract: Many cancer types, including head and neck cancers (HNC), express programmed death ligand 1 (PD-L1). Interaction between PD-L1 and its receptor, programmed death 1 (PD-1), inhibits the function of activated T cells and results in an immunosuppressive microenvironment, but the stimuli that induce PD-L1 expression are not well characterized. Interferon gamma (IFNγ) and the epidermal growth factor receptor (EGFR) utilize Janus kinase 2 (JAK2) as a common signaling node to transmit tumor cell-mediated extrinsic or intrinsic signals, respectively. In this study, we investigated the mechanism by which these factors upregulate PD-L1 expression in HNC cells in the context of JAK/STAT pathway activation, Th1 inflammation, and HPV status. We found that wild-type, overexpressed EGFR significantly correlated with JAK2 and PD-L1 expression in a large cohort of HNC specimens. Furthermore, PD-L1 expression was induced in an EGFR- and JAK2/STAT1-dependent manner, and specific JAK2 inhibition prevented PD-L1 upregulation in tumor cells and enhanced their immunogenicity. Collectively, our findings suggest a novel role for JAK2/STAT1 in EGFR-mediated immune evasion, and therapies targeting this signaling axis may be beneficial to block PD-L1 upregulation found in a large subset of HNC tumors. Cancer Res; 76(5); 1031-43. ©2015 AACR.
Frahm KA, Peffer ME, Zhang JY, Luthra S, Chakka AB, Couger MB, Chandran UR, Monaghan AP, DeFranco DB. Research Resource: The Dexamethasone Transcriptome in Hypothalamic Embryonic Neural Stem Cells. Molecular Endocrinology (Baltimore, Md.). 2016 Jan;30(1):144-54. PMID:26606517. PMCID:PMC4695633.
Abstract: Exposure to excess glucocorticoids during fetal development has long-lasting physiological and behavioral consequences, although the mechanisms are poorly understood. The impact of prenatal glucocorticoids exposure on stress responses in juvenile and adult offspring implicates the developing hypothalamus as a target of adverse prenatal glucocorticoid action. Therefore, primary cultures of hypothalamic neural-progenitor/stem cells (NPSCs) derived from mouse embryos (embryonic day 14.5) were used to identify the glucocorticoid transcriptome in both males and females. NPSCs were treated with vehicle or the synthetic glucocorticoid dexamethasone (dex; 100nM) for 4 hours and total RNA analyzed using RNA-Sequencing. Bioinformatic analysis demonstrated that primary hypothalamic NPSC cultures expressed relatively high levels of a number of genes regulating stem cell proliferation and hypothalamic progenitor function. Interesting, although these cells express glucocorticoid receptors (GRs), only low levels of sex-steroid receptors are expressed, which suggested that sex-specific differentially regulated genes identified are mediated by genetic and not hormonal influences. We also identified known or novel GR-target coding and noncoding genes that are either regulated equivalently in male and female NPSCs or differential responsiveness in one sex. Using gene ontology analysis, the top functional network identified was cell proliferation and using bromodeoxyuridine (BrdU) incorporation observed a reduction in proliferation of hypothalamic NPSCs after dexamethasone treatment. Our studies provide the first characterization and description of glucocorticoid-regulated pathways in male and female embryonically derived hypothalamic NPSCs and identified GR-target genes during hypothalamic development. These findings may provide insight into potential mechanisms responsible for the long-term consequences of fetal glucocorticoid exposure in adulthood.
Chandran UR, Luthra S, Santana-Santos L, Mao P, Kim SH, Minata M, Li J, Benos PV, DeWang M, Hu B, Cheng SY, Nakano I, Sobol RW. Gene expression profiling distinguishes proneural glioma stem cells from mesenchymal glioma stem cells. Genomics Data. 2015 Sep 1;5:333-336. PMID:26251826. PMCID:PMC4523279.
Abstract: Tumor heterogeneity of high-grade glioma (HGG) is recognized by four clinically relevant subtypes based on core gene signatures. However, molecular signaling in glioma stem cells (GSCs) in individual HGG subtypes is poorly characterized. Previously we identified and characterized two mutually exclusive GSC subtypes with distinct activated signaling pathways and biological phenotypes. One GSC subtype presented with a gene signature resembling Proneural (PN) HGG, whereas the other was similar to Mesenchymal (Mes) HGG. Classical HGG-derived GSCs were sub-classified as either one of these two subtypes. Differential mRNA expression analysis of PN and Mes GSCs identified 5,796 differentially expressed genes, revealing a pronounced correlation with the corresponding PN or Mes HGGs. Mes GSCs displayed more aggressive phenotypes in vitro and as intracranial xenografts in mice. Further, Mes GSCs were markedly resistant to radiation compared with PN GSCs. Expression of ALDH1A3 - one of the most up-regulated Mes representative genes and a universal cancer stem cell marker in non-brain cancers - was associated with self-renewal and a multi-potent stem cell population in Mes but not PN samples. Moreover, inhibition of ALDH1A3 attenuated the growth of Mes but not PN GSCs in vitro. Lastly, radiation treatment of PN GSCs up-regulated Mes-associated markers and down-regulated PN-associated markers, whereas inhibition of ALDH1A3 attenuated an irradiation-induced gain of Mes identity in PN GSCs in vitro. Taken together, our data suggest that two subtypes of GSCs, harboring distinct metabolic signaling pathways, represent intertumoral glioma heterogeneity and highlight previously unidentified roles of ALDH1A3-associated signaling that promotes aberrant proliferation of Mes HGGs and GSCs. Inhibition of ALDH1A3-mediated pathways therefore might provide a promising therapeutic approach for a subset of HGGs with the Mes signature. Here, we describe the gene expression analysis, including pre-processing methods for the data published by Mao and colleagues in PNAS [1], integration of microarray data from this study with The Cancer Genome Atlas (TCGA) glioblastoma data and also with another published study.
Manohar R, Li Y, Fohrer H, Guzik L, Stolz DB, Chandran UR, LaFramboise WA, Lagasse E. Identification of a candidate stem cell in human gallbladder. Stem Cell Research. 2015 May;14(3):258-69. PMID:25765520. PMCID:PMC4439375.
Abstract: There are currently no reports of identification of stem cells in human gallbladder. The differences between human gallbladder and intrahepatic bile duct (IHBD) cells have also not been explored. The goals of this study were to evaluate if human fetal gallbladder contains a candidate stem cell population and if fetal gallbladder cells are distinct from fetal IHBD cells. We found that EpCAM+CD44+CD13+ cells represent the cell population most enriched for clonal self-renewal from primary gallbladder. Primary EpCAM+CD44+CD13+ cells gave rise to EpCAM+CD44+CD13+ and EpCAM+CD44+CD13- cells in vitro, and gallbladder cells expanded in vitro exhibited short-term engraftment in vivo. Last, we found that CD13, CD227, CD66, CD26 and CD49b were differentially expressed between gallbladder and IHBD cells cultured in vitro indicating clear phenotypic differences between the two cell populations. Microarray analyses of expanded cultures confirmed that both cell types have unique transcriptional profiles with predicted functional differences in lipid, carbohydrate, nucleic acid and drug metabolism. In conclusion, we have isolated a distinct clonogenic population of epithelial cells from primary human fetal gallbladder with stem cell characteristics and found it to be unique compared to IHBD cells.
Geskin A, Legowski E, Chakka A, Chandran UR, Barmada MM, LaFramboise WA, Berg J, Jacobson RS. Needs Assessment for Research Use of High-Throughput Sequencing at a Large Academic Medical Center. PloS One. 2015;10(6):e0131166. PMID:26115441. PMCID:PMC4483235.
Abstract: Next Generation Sequencing (NGS) methods are driving profound changes in biomedical research, with a growing impact on patient care. Many academic medical centers are evaluating potential models to prepare for the rapid increase in NGS information needs. This study sought to investigate (1) how and where sequencing data is generated and analyzed, (2) research objectives and goals for NGS, (3) workforce capacity and unmet needs, (4) storage capacity and unmet needs, (5) available and anticipated funding resources, and (6) future challenges. As a precursor to informed decision making at our institution, we undertook a systematic needs assessment of investigators using survey methods. We recruited 331 investigators from over 60 departments and divisions at the University of Pittsburgh Schools of Health Sciences and had 140 respondents, or a 42% response rate. Results suggest that both sequencing and analysis bottlenecks currently exist. Significant educational needs were identified, including both investigator-focused needs, such as selection of NGS methods suitable for specific research objectives, and program-focused needs, such as support for training an analytic workforce. The absence of centralized infrastructure was identified as an important institutional gap. Key principles for organizations managing this change were formulated based on the survey responses. This needs assessment provides an in-depth case study which may be useful to other academic medical centers as they identify and plan for future needs.
Liao S, Hartmaier RJ, McGuire KP, Puhalla SL, Luthra S, Chandran UR, Ma T, Bhargava R, Modugno F, Davidson NE, Benz S, Lee AV, Tseng GC, Oesterreich S. The molecular landscape of premenopausal breast cancer. Breast Cancer Research : BCR. 2015;17:104. PMID:26251034. PMCID:PMC4531812.
Abstract: Breast cancer in premenopausal women (preM) is frequently associated with worse prognosis compared to that in postmenopausal women (postM), and there is evidence that preM estrogen receptor-positive (ER+) tumors may respond poorly to endocrine therapy. There is, however, a paucity of studies characterizing molecular alterations in premenopausal tumors, a potential avenue for personalizing therapy for this group of women.
McDade KK, Chandran U, Day RS. Improving Cancer Gene Expression Data Quality through a TCGA Data-Driven Evaluation of Identifier Filtering. Cancer Informatics. 2015;14:149-61. PMID:26715829. PMCID:PMC4686346.
Abstract: Data quality is a recognized problem for high-throughput genomics platforms, as evinced by the proliferation of methods attempting to filter out lower quality data points. Different filtering methods lead to discordant results, raising the question, which methods are best? Astonishingly, little computational support is offered to analysts to decide which filtering methods are optimal for the research question at hand. To evaluate them, we begin with a pair of expression data sets, transcriptomic and proteomic, on the same samples. The pair of data sets form a test-bed for the evaluation. Identifier mapping between the data sets creates a collection of feature pairs, with correlations calculated for each pair. To evaluate a filtering strategy, we estimate posterior probabilities for the correctness of probesets accepted by the method. An analyst can set expected utilities that represent the trade-off between the quality and quantity of accepted features. We tested nine published probeset filtering methods and combination strategies. We used two test-beds from cancer studies providing transcriptomic and proteomic data. For reasonable utility settings, the Jetset filtering method was optimal for probeset filtering on both test-beds, even though both assay platforms were different. Further intersection with a second filtering method was indicated on one test-bed but not the other.
Gau DM, Lesnock JL, Hood BL, Bhargava R, Sun M, Darcy K, Luthra S, Chandran U, Conrads TP, Edwards RP, Kelley JL, Krivak TC, Roy P. BRCA1 deficiency in ovarian cancer is associated with alteration in expression of several key regulators of cell motility - A proteomics study. Cell Cycle (Georgetown, Tex.). 2015;14(12):1884-92. PMID:25927284. PMCID:PMC4614952.
Abstract: Functional loss of expression of breast cancer susceptibility gene 1(BRCA1) has been implicated in genomic instability and cancer progression. There is emerging evidence that BRCA1 gene product (BRCA1) also plays a role in cancer cell migration. We performed a quantitative proteomics study of EOC patient tumor tissues and identified changes in expression of several key regulators of actin cytoskeleton/cell adhesion and cell migration (CAPN1, 14-3-3, CAPG, PFN1, SPTBN1, CFN1) associated with loss of BRCA1 function. Gene expression analyses demonstrate that several of these proteomic hits are differentially expressed between early and advanced stage EOC thus suggesting clinical relevance of these proteins to disease progression. By immunohistochemistry of ovarian tumors with BRCA1(+/+) and BRCA1(null) status, we further verified our proteomic-based finding of elevated PFN1 expression associated with BRCA1 deficiency. Finally, we established a causal link between PFN1 and BRCA1-induced changes in cell migration thus uncovering a novel mechanistic basis for BRCA1-dependent regulation of ovarian cancer cell migration. Overall, findings of this study open up multiple avenues by which BRCA1 can potentially regulate migration and metastatic phenotype of EOC cells.
Peffer ME, Chandran UR, Luthra S, Volonte D, Galbiati F, Garabedian MJ, Monaghan AP, DeFranco DB. Caveolin-1 regulates genomic action of the glucocorticoid receptor in neural stem cells. Molecular and Cellular Biology. 2014 Jul;34(14):2611-23. PMID:24777604. PMCID:PMC4097667.
Abstract: While glucocorticoids (GCs) are used clinically to treat many conditions, their neonatal and prenatal usage is increasingly controversial due to reports of delayed adverse outcomes, especially their effects on brain development. Such alterations may reflect the impact of GCs on neural progenitor/stem cell (NPSC) function. We previously demonstrated that the lipid raft protein caveolin-1 (Cav-1) was required for rapid GC signaling in embryonic mouse NPSCs operating through plasma membrane-bound glucocorticoid receptors (GRs). We show here that genomic GR signaling in NPSCs requires Cav-1. Loss of Cav-1 impacts the transcriptional response of many GR target genes (e.g., the serum- and glucocorticoid-regulated kinase 1 gene) that are likely to mediate the antiproliferative effects of GCs. Microarray analysis of wild-type C57 or Cav-1-deficient NPSCs identified approximately 100 genes that are differentially regulated by GC treatment. These changes in hormone responsiveness in Cav-1 knockout NPSCs are associated with the loss of GC-regulated phosphorylation of GR at serine 211 but not at serine 226. Chromatin recruitment of total GR to regulatory regions of target genes such as Fkbp-5, RhoJ, and Sgk-1, as well as p211-GR recruitment to Sgk-1, are compromised in Cav-1 knockout NPSCs. Cav-1 is therefore a multifunctional regulator of GR in NPSCs influencing both rapid and genomic action of the receptor to impact cell proliferation.
Sikora MJ, Cooper KL, Bahreini A, Luthra S, Wang G, Chandran UR, Davidson NE, Dabbs DJ, Welm AL, Oesterreich S. Invasive lobular carcinoma cell lines are characterized by unique estrogen-mediated gene expression patterns and altered tamoxifen response. Cancer Research. 2014 Mar 1;74(5):1463-74. PMID:24425047. PMCID:PMC3955299.
Abstract: Invasive lobular carcinoma (ILC) is a histologic subtype of breast cancer that is frequently associated with favorable outcomes, as approximately 90% of ILC express the estrogen receptor (ER). However, recent retrospective analyses suggest that patients with ILC receiving adjuvant endocrine therapy may not benefit as much as patients with invasive ductal carcinoma. On the basis of these observations, we characterized ER function and endocrine response in ILC models. The ER-positive ILC cell lines MDA MB 134VI (MM134) and SUM44PE were used to examine the ER-regulated transcriptome via gene expression microarray analyses and ER ChIP-Seq, and to examine response to endocrine therapy. In parallel, estrogen response was assessed in vivo in the patient-derived ILC xenograft HCI-013. We identified 915 genes that were uniquely E2 regulated in ILC cell lines versus other breast cancer cell lines, and a subset of these genes were also E2 regulated in vivo in HCI-013. MM134 cells were de novo tamoxifen resistant and were induced to grow by 4-hydroxytamoxifen, as well as other antiestrogens, as partial agonists. Growth was accompanied by agonist activity of tamoxifen on ER-mediated gene expression. Though tamoxifen induced cell growth, MM134 cells required fibroblast growth factor receptor (FGFR)-1 signaling to maintain viability and were sensitive to combined endocrine therapy and FGFR1 inhibition. Our observation that ER drives a unique program of gene expression in ILC cells correlates with the ability of tamoxifen to induce growth in these cells. Targeting growth factors using FGFR1 inhibitors may block survival pathways required by ILC and reverse tamoxifen resistance.
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