HBHirendra Nath Banerjee

Hirendra Nath Banerjee

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Hirendra Nath Banerjee has a total of 6 co-authors. Here are the top co-authors by number of shared publications:

  • Mukesh Verma

    National Cancer Institute, National Institutes of Health

    4 shared publications
  • Mukesh Verma

    Department of Biological and Pharmaceutical Sciences, Elizabeth City State University/University of North Carolina, Elizabeth City, NC 27909, USA ; 2 Methods and Technologies Branch, Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute (NCI), National Institutes of Health (NIH), Rockville, MD 20850, USA

    2 shared publications
  • David Kinkebiel

    University of Nebraska Medical Center

    1 shared publication
  • Gwyneth Hyman

    Department of Biological Sciences and Pharmaceutical Sciences, Elizabeth City State University, University of North Carolina, Campus Box 930, 1704 Weeksville Road, Elizabeth City, NC, 27909, USA

    1 shared publication
  • Jeffrey M. Rousch

    Elizabeth City State University, University of North Carolina

    1 shared publication
  • Vinod Manglik

    Elizabeth City State University, University of North Carolina

    1 shared publication

Latest Publications

  • Open Access

    Metabolomic Approaches in Cancer Epidemiology

    by Mukesh Verma, Hirendra Nath Banerjee

    Metabolomics is the study of low molecular weight molecules or metabolites produced within cells and biological systems. It involves technologies such as mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) that can measure hundreds of thousands of unique chemical entities (UCEs). The metabolome provides one of the most accurate reflections of cellular activity at the functional level and can be leveraged to discern mechanistic information during normal and disease states. The advantages of metabolomics over other “omics” include its high sensitivity and ability to enable the analysis of relatively few metabolites compared with the number of genes and messenger RNAs (mRNAs). In clinical samples, metabolites are more stable than proteins or RNA. In fact, metabolomic profiling in basic, epidemiologic, clinical, and translational studies has revealed potential new biomarkers of disease and therapeutic outcome and has led to a novel mechanistic understanding of pathogenesis. These potential biomarkers include novel metabolites associated with cancer initiation, regression, and recurrence. Unlike genomics or even proteomics, however, the degree of metabolite complexity and heterogeneity within biological systems presents unique challenges that require specialized skills and resources to overcome. This article discusses epidemiologic studies of altered metabolite profiles in several cancers as well as challenges in the field and potential approaches to overcoming them.


  • Using 2D-DIGE-MS to Identify Biomarkers for Brain Cancer

    by Hirendra Nath Banerjee, Mukesh Verma

  • Epigenetic Approaches in Glioblastoma Multiforme and Their Implication in Screening and Diagnosis

    by Gwyneth Hyman, Vinod Manglik, Jeffrey M. Rousch, Mukesh Verma, David Kinkebiel, Hirendra Nath Banerjee

    Epigenetic modifications have been reported in a number of non-germ-line tumor types. Epigenetic modifications to the genome, especially DNA methylation and histone modifications, affect gene expression causing increased risk for cancers and other diseases. We have summarized information about DNA methylation percentages in Glioblastoma multiforme (GBM) line HTB-12, alveolar cell carcinoma, and acute lymphocytic leukemia samples and determined H3 (K27) methyltransferase activity in GBM and leukemia cells and made comparisons to H3 (K27) methyltransferase activity in normal astrocyte, lung, and lymphocyte cells. GBM and alveolar cell carcinoma gDNA possessed lower gDNA methylation percentages compared to normal cells. Methyl-sensitive cut counting analysis (MSCC) showed fold decreases in GBM CpG methylation sites for genes PBK, KIF23, COL6A3, and LOX. There was no significant difference in CpG DNA methylation, but less histone methyltransferase activity in acute lymphocytic leukemia compared to normal cells. GBM possessed increased histone methyltransferase activity compared to normal samples. Challenges in the field in diagnosis and prognosis for cancer risk especially with regard to the results of this work are discussed.


  • Epigenetic Inhibitors

    by Mukesh Verma, Hirendra Nath Banerjee

    Traditional treatments for cancer include chemotherapy, radiation therapy, and surgery. Recently, epigenetic inhibitors have been found to be very effective in cancer treatment. Epigenetic changes such as DNA methylation, histone deacetylation, and microRNA (miRNA) expression are capable of silencing the expression of tumor suppressor genes and inducing oncogenes, leading to clonal proliferation of tumor cells. Methyltransferase inhibitors and histone deacetylase inhibitors have attracted the attention of researchers and clinicians because they provide an alternative therapeutic regime in some diseases, including cancer. Epigenetic changes are characterized by altered gene expression without any changes in the nucleotide sequences of DNA. In addition, epigenetic changes are dynamic and can be reversed by epigenetic inhibitors. Drugs that inhibit DNA methylation or histone deacetylation have been studied for the reactivation of tumor suppressor genes and repression of cancer cell growth. Epigenetic inhibitors work alone or in combination with other therapeutic agents. To date, several epigenetic inhibitors have been approved for cancer treatment. The main challenge in the field of epigenetic inhibitors is their lack of specificity. Their mechanisms of action and potential in treating cancer are described in this article.


  • Open Access

    Using 2D-DIGE-MS to Identify Biomarkers for Brain Cancer

    by Hirendra Nath Banerjee, Mukesh Verma