Genetic Polymorphisms Along with Dietary and Environmental Factors Enhance the Susceptibility to Nasopharyngeal Carcinoma in Nagaland of Northeast India.

This study investigated the association of seven widely known DNA repair gene polymorphisms (hOGG1 Ser326Cys, XRCC1 Arg194Trp, XRCC1 Arg280His, XRCC1 Arg399Gln, XPC Val499Ala, XPD Lys751Gln and ERCC1 Cys8092Ala) with dietary and environmental factors for Nasopharyngeal Carcinoma (NPC) susceptibility in Nagaland of Northeast India. The genotypes were determined in 128 NPC patients and 180 healthy controls by PCR-RFLP. XRCC1 Arg280His, XPC Val499Ala and ERCC1 Cys8092Ala were found to be associated with NPC risk. Tobacco smoking and burning of firewood for cooking were also found to be a risk factor for NPC. The haplotype analysis of five single-nucleotide polymorphisms (SNPs) XRCC1 Arg194Trp, XRCC1 Arg280His, XRCC1 Arg399Gln, XPD Lys751Gln and ERCC1 Cys8092Ala identified haplotype TGAAC to be significantly associated with NPC. Multifactor dimensionality reduction (MDR) analysis suggested ERCC1 Cys8092Ala to be the best one-factor model that could predict NPC risk. From this study, we conclude that examining the synergistic interactions of various gene-environmental factors together is a better approach to understand NPC susceptibility, instead of their individual effects.

Description of the novel null allele, HLA-DPA1*01:29N in a Lotha individual from Nagaland, North-East India.

A single nucleotide change in HLA-DPA1*01:03:01:01 results in the novel null allele, HLA-DPA1*01:29N.

Identification and Preliminary Validation of Radiation Response Protein(s) in Human Blood for a High-throughput Molecular Biodosimetry Technology for the Future.

The absence of a rapid and high-throughput technology for radiation biodosimetry has been a great obstacle in our full preparedness to cope with large-scale radiological incidents. The existing cytogenetic technologies have limitations, primarily due to their time-consuming methodologies, which include a tissue culture step, and the time required for scoring. This has seriously undermined its application in a mass casualty scenario under radiological emergencies for timely triage and medical interventions. Recent advances in genomics and proteomics in the postgenomic era have opened up new platforms and avenues to discover molecular biomarkers for biodosimetry in the future. Using a genomic-to-proteomic approach, we have identified a basket of twenty "candidate" radiation response genes (RRGs) using DNA microarray and tools of bioinformatics immediately after ex vivo irradiation of freshly drawn whole blood of consenting and healthy human volunteers. The candidate RRGs have partially been validated using real-time quantitative polymerase chain reaction (RT-qPCR or qPCR) to identify potential "candidate" RRGs at mRNA level. Two potential RRGs, CDNK1A and ZNF440, have so far been identified as genes with potentials to form radiation response proteins in liquid biopsy of blood, which shall eventually form the basis of fluorescence- or ELISA-based quantitative immunoprobe assay for a high-throughput technology of molecular biodosimetry in the future. More work is continuing.

Evaluation of endogenous control gene(s) for gene expression studies in human blood exposed to 60Co γ-rays ex vivo.

In gene expression studies, it is critical to normalize data using a stably expressed endogenous control gene in order to obtain accurate and reliable results. However, we currently do not have a universally applied endogenous control gene for normalization of data for gene expression studies, particularly those involving (60)Co γ-ray-exposed human blood samples. In this study, a comparative assessment of the gene expression of six widely used housekeeping endogenous control genes, namely 18S, ACTB, B2M, GAPDH, MT-ATP6 and CDKN1A, was undertaken for a range of (60)Co γ-ray doses (0.5, 1.0, 2.0 and 4.0 Gy) at 8.4 Gy min(-1) at 0 and 24 h post-irradiation time intervals. Using the NormFinder algorithm, real-time PCR data obtained from six individuals (three males and three females) were analyzed with respect to the threshold cycle (Ct) value and abundance, ΔCt pair-wise comparison, intra- and inter-group variability assessments, etc. GAPDH, either alone or in combination with 18S, was found to be the most suitable endogenous control gene and should be used in gene expression studies, especially those involving qPCR of γ-ray-exposed human blood samples.

Consensus reference gene(s) for gene expression studies in human cancers: end of the tunnel visible?

BACKGROUND: Gene expression studies are increasingly used to provide valuable information on the diagnosis and prognosis of human cancers. Also, for in vitro and in vivo experimental cancer models gene expression studies are widely used. The complex algorithms of differential gene expression analyses require normalization of data against a reference or normalizer gene, or a set of such genes. For this purpose, mostly invariant housekeeping genes are used. Unfortunately, however, there are no consensus (housekeeping) genes that serve as reference or normalizer for different human cancers. In fact, scientists have employed a wide range of reference genes across different types of cancer for normalization of gene expression data. As a consequence, comparisons of these data and/or data harmonizations are difficult to perform and challenging. In addition, an inadequate choice for a reference gene may obscure genuine changes and/or result in erroneous gene expression data comparisons. METHODS: In our effort to highlight the importance of selecting the most appropriate reference gene(s), we have screened the literature for gene expression studies published since the turn of the century on thirteen of the most prevalent human cancers worldwide. CONCLUSIONS: Based on the analysis of the data at hand, we firstly recommend that in each study the suitability of candidate reference gene(s) should carefully be evaluated in order to yield reliable differential gene expression data. Secondly, we recommend that a combination of PPIA and either GAPDH, ACTB, HPRT and TBP, or appropriate combinations of two or three of these genes, should be employed in future studies, to ensure that results from different studies on different human cancers can be harmonized. This approach will ultimately increase the depth of our understanding of gene expression signatures across human cancers.