Research Themes

The McCormick Genomic and Proteomic Center’s goal is to reveal molecules or genetic events that will form the basis for translational advances in identifying novel therapeutic targets and biomarkers for stratification, as well as to make fundamental advances in cancer biology and other areas of high interest. The current research themes are focused on the genomic and epigenomic regulation of breast and liver cancers and hormone-responsive coregulators in cells from autistic individuals.

Molecular signatures of the breast cancer sub-types

Genomic basis of breast cancer sub-types is an active area of investigation and the nature of key regulators and pathways remain to be fully defined. The MGPC is revealing the genomic landscape and transcriptome of TNBC, HER2 positive, and ER/PR/HER2-positive breast cancers. For the first time, MGPC has decoded the transcriptome, differential splicing, and variances in breast cancer using RNA-sequencing platform. This approach is revealing the potential signature of breast cancer for a secondary confirmation in a larger prospective study, and surfacing the molecules and genotypic changes with diagnostic and prognostic values. The MGPC is also addressing one of the confounding issues in cancer genomics, the heterogeneous genetic backgrounds of breast tumors. More recently the team has started constructing epigenomic landscape of breast cancer cells. The center's effort in this direction is further strengthened by collaboration with Prof. Saraswati Sukumar's team at Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins.

Therapy-linked transcriptomic alterations in breast cancer

Surgical removal of breast tumor has been suggested to affect the overall treatment outcome presumably, through local physical disruption events that lead to secondary tumor formation over time. A recently completed clinical trial by Prof. Rajendra Badwe’s team at the Tata Memorial Center (TMC) in Mumbai has revealed beneficial effects of one-time pre-surgical hormonal treatment before breast cancer surgery of breast cancer. To highlight the genomic basis of potential significance of therapeutic intervention on the long-term outcome of breast cancer, the MGPC and TMC are applying the whole transcriptome RNA-sequencing on the matched pre- and post-treatment tumor samples. The goal here is to arrive to candidate pathways as possible underlying mechanisms behind the noticed clinical outcome.

Bilateral breast cancer transcriptome

At the moment, the nature of genomic changes leading to and or resulting from bilateral breast cancer remains undefined. The MGPC is addressing this question of paramount importance in collaboration with Prof. Luis Costa’s team from the Institute of Molecular Medicine in Lisbon. The center is delineating the transcriptome of naturally occurring bilateral cancer of different subtypes from the same individual. Comparing expression and variation signatures from the matched normal and tumor samples, the MGPC is studying subtype-unique features to better understand the initiation and progression of individual cancer type in the context of local microenvironment.

Integration of metadata to enhance its utility

The advent of genomics has revolutionized cancer research, but sequencing technologies have resulted in petabytes of scattered data and information (metadata), decentralized in archives and sometimes even in isolated hard-disks that are inaccessible for analysis. A greater access to this data is required by the research community in order to achieve significant progress in cancer biology. To address this challenge, we have implemented efficient next-gen sequence data and associated Big Data analysis pipelines. Using this pipeline we are currently performing comprehensive analysis of the effect of variations that are found in breast cancer data, available from The Cancer Genome Atlas (TCGA) Data Portal, Cancer Genome Hub (CGHub) and NCBI-SRA. This study will provide critical information to better understand cancer samples from different ethnicities, age groups, disease outcome. The goal is to identify and perform functional analysis of non-synonymous single nucleotide variation in cancer/controls and proteome-wide analysis of the effect of variation on post-translational modifications such as glycosylation. The above mentioned analysis pipeline is also used to analysis large-scale sequence and other related data from hepatitis viruses to better understand their pathogenicity.

Integrative genomics perspective of ASD

Autism spectrum disorders (ASD) are neurodevelopmental disorders that present as deficits in reciprocal social interactions and communication, and stereotyped, repetitive behaviors.  Currently, due to the heterogeneity in clinical manifestations of ASD, there are neither biomarker tests for ASD nor therapies targeting the ASD.  Integrative genomics in a systems biology context is being applied to  better understand the pathobiology underlying distinct subtypes of ASD..  This approach involves the integration of genome-wide data from gene expression, genetic, and epigenetic analyses with clinically-relevant phenotypes. Ongoing studies in Prof. Valerie’s Hu’s lab are utilizing genomics and bioinformatics tools to examine mechanisms of large-scale gene dysregulation in ASD as well as gene-environment interactions that elevate risk for ASD.

Whole genome sequencing characterization of a unique fungus

A microorganism of unknown species was identified 12 years ago due to its ability to survive and reproduce in a medium composed of exclusively antibiotics and water. This microorganism has been continuously cultivated and propagated in this medium since its discovery. Our recent 16S rRNA probe-based PCR analysis of the DNA suggests that it is a filamentous fungus. The ability of an eukaryotic organism to not only survive but also reproduce under these extreme conditions raises new biological questions concerning primitive metabolism essential for life and evolution - an emerging area with strong implications in therapeutic resistance. The team championed by Drs. Han and Kumar is now sequencing the whole genome of this organism to characterize molecular mechanisms allowing its survival and antibiotic resistance in antibiotic exclusive environment. The team hopes to utilize the generated genomics and metabolomics data in search of novel applied targets, including acquired resistance.

Hepto-cancer biology

Chronic infection with hepatotropic viruses (HBV and HCV) is a major cause of hepatocellular carcinoma (HCC). At MGPC, Prof. Ajit Kumar, working closely with Dr. Raja Mazumder, is delineating the genomic and epigenomic steps during hepatotropic viruses associated liver cancer development using physiologicall relevant human primary hepatocyte cultures, liver cancer cells, and mouse models. These comprehensive integrated studies at the interface of bioinformatics and genomics are designed to identify novel genomic pathways and/or therapeutic targets important for initiating and promoting liver cancer progression.


Epigenomic control of transcriptome and non-coding genome

Understanding mechanism of transcription is of fundamental importance for all processes. Although signaling networks are known to regulate about 2% of the coding regions, the impact of co-ordinated signaling on 98% of non-coding genome remains elusive. Recent studies have opened up an opportunity to understand the non-coding RNA-mediated regulation of the coding transcriptome. The MGPC team, led by Prof. Kumar in collaboration with Prof. Stefan Knapp from Oxford University, is creating a map encompassing the impact of a novel nucleosome interacting partner and a master coregulator on chromatin remodeling and functional output of coding and non-coding transcriptome using genome-wide approaches. In another MGPC project, we are defining the epigenomic regulation of breast cancer transcriptome. An increasing number of studies suggest that non-coding RNA expression patterns might be superior in distinguishing normal from tumor breast cells and classifying tumors’ types and stages. At MGPC, we explore multiple sources to build a comprehensive expression and variation map of non-coding breast cancer transcriptome  as such an approach may have an added value in early diagnosis and prognosis.