Identification of TNF-α as Major Susceptible Risk Locus for Vitiligo: A Systematic Review and Meta-Analysis Study in the Asian Population.

INTRODUCTION: Vitiligo is a common depigmentation disorder characterized by defined white patches on the skin and affecting around 0.5% to 2% of the general population. Genetic association studies have identified several pre-disposing genes and single nucleotide polymorphisms (SNPs) for vitiligo pathogenesis; nonetheless, the reports are often conflicting and rarely conclusive. This comprehensive meta-analysis study was designed to evaluate the effect of the risk variants on vitiligo aetiology and covariate stratified vitiligo risk in the Asian population, considering all the studies published so far. METHODS: We followed a systematic and comprehensive search to identify the relevant vitiligo-related candidate gene association studies in PubMed using specific keywords. After data extraction, we calculated, for the variants involved, the study-level unadjusted odds ratio, standard errors, and 95% confidence intervals by using logistic regression with additive, dominant effect, and recessive models using R software package (R, 3.4.2) "metafor." Subgroup analysis was performed using logistic regression (generalized linear model; "glm") of disease status on subgroup-specific genotype counts. For a better understanding of the likely biological function of vitiligo-associated variant obtained through the meta-analysis, in silico functional analyses, through standard publicly available web tools, were also conducted. RESULTS: Thirty-one vitiligo-associated case-control studies on eleven SNPs were analysed in our study. In the fixed-effect meta-analysis, one variant upstream of TNF-α gene: rs1800629 was found to be associated with vitiligo risk in the additive (p = 4.26E-06), dominant (p = 1.65E-7), and recessive (p = 0.000453) models. After Benjamini-Hochberg false discovery rate (FDR) correction, rs1800629/TNF-α was found to be significant at 5% FDR in the dominant (padj = 1.82E-6) and recessive models (padj = 0.0049). In silico characterization revealed the prioritized variant to be regulatory in nature and thus having potential to contribute towards vitiligo pathogenesis. CONCLUSION: Our study constitutes the first comprehensive meta-analysis of candidate gene-based association studies reported in the whole of the Asian population, followed by an in silico analysis of the vitiligo-associated variant. According to the findings of our study, TNF-α single nucleotide variant rs1800629G>A has a risk association, potentially contributing to vitiligo pathogenesis in the Asian population.

A framework for pathway knowledge driven prioritization in genome-wide association studies.

Many variants with low frequencies or with low to modest effects likely remain unidentified in genome-wide association studies (GWAS) because of stringent genome-wide thresholds for detection. To improve the power of detection, variant prioritization based on their functional annotations and epigenetic landmarks has been used successfully. Here, we propose a novel method of prioritization of a GWAS by exploiting gene-level knowledge (e.g., annotations to pathways and ontologies) and show that it further improves power. Often, disease associated variants are found near genes that are coinvolved in specific biological pathways relevant to disease process. Utilization of this knowledge to conduct a prioritized scan increases the power to detect loci that map to genes clustered in a few specific pathways. We have developed a computationally scalable framework based on penalized logistic regression (termed GKnowMTest-Genomic Knowledge-guided Multiplte Testing) to enable a prioritized pathway-guided GWAS scan with a very large number of gene-level annotations. We demonstrate that the proposed strategy improves overall power and maintains the Type 1 error globally. Our method works on genome-wide summary level data and a user-specified list of pathways (e.g., those extracted from large pathway databases without reference to biology of a specific disease). It automatically reweights the input p values by incorporating the pathway enrichments as "adaptively learned" from the data using a cross-validation technique to avoid overfitting. We used whole-genome simulations and some publicly available GWAS data sets to illustrate the application of our method. The GKnowMTest framework has been implemented as a user-friendly open-source R package.

Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass.

BACKGROUND: Most often, the patients with pancreatic diseases are presented with a mass in pancreatic head region and existing methods of diagnosis fail to confirm whether the head mass is malignant or benign. As subsequent management of the disease hugely depends on the correct diagnosis, we wanted to explore possible biomarkers which could distinguish benign and malignant pancreatic head masses. METHODS: In order to address that gap, we performed a case-control study to identify genome-wide differentially expressed coding and noncoding genes between pancreatic tissues collected from benign and malignant head masses. These genes were next shortlisted using stringent criteria followed by selection of top malignancy specific genes. They subsequently got validated by quantitative RT-PCR and also in other patient cohorts. Survival analysis and ROC analysis were also performed. RESULTS: We identified 55 coding and 13 noncoding genes specific for malignant pancreatic head masses. Further shortlisting and validation, however, resulted in 5 coding genes as part of malignancy specific multi-gene signature, which was validated in three independent patient cohorts of 145 normal and 153 PDAC patients. We also found that overexpression of these genes resulted in survival disadvantage in the patients and ROC analysis identified that combination of 5 coding genes had the AUROC of 0.94, making them potential biomarker. CONCLUSIONS: Our study identified a multi-gene signature comprising of 5 coding genes (CDCA7, DLGAP5, FOXM1, TPX2 and OSBPL3) to distinguish malignant head masses from benign ones.

A meta-analysis and in silico analysis of polymorphic variants conferring breast cancer risk in the Indian subcontinent.

Background: Genetic association studies on breast cancer on the Indian subcontinent have yielded conflicting results, and the precise effect of these variants on breast cancer pathogenesis is not known. Methods: Genomic variants, as obtained from selected studies from the Indian subcontinent, were subjected to random-effects and fixed-effect meta-analysis. Functional annotation of the relevant variants was done through a tried and tested in silico pipeline. Results: We found rs4646903/CYP1A1, rs1799814/CYP1A1, rs61886492/GCPII, del2/GSTM1, rs4680/COMT and rs1801394/MTRR to be associated with breast cancer. The del2/GSTM1 holds the association in premenopausal women. Conclusions: This is the first study of its kind from the Indian subcontinent analysing the extent of association of variants across populations followed by their functional annotation in the disease pathway.

A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits.

Pooling genome-wide association studies (GWASs) increases power but also poses methodological challenges because studies are often heterogeneous. For example, combining GWASs of related but distinct traits can provide promising directions for the discovery of loci with small but common pleiotropic effects. Classical approaches for meta-analysis or pooled analysis, however, might not be suitable for such analysis because individual variants are likely to be associated with only a subset of the traits or might demonstrate effects in different directions. We propose a method that exhaustively explores subsets of studies for the presence of true association signals that are in either the same direction or possibly opposite directions. An efficient approximation is used for rapid evaluation of p values. We present two illustrative applications, one for a meta-analysis of separate case-control studies of six distinct cancers and another for pooled analysis of a case-control study of glioma, a class of brain tumors that contains heterogeneous subtypes. Both the applications and additional simulation studies demonstrate that the proposed methods offer improved power and more interpretable results when compared to traditional methods for the analysis of heterogeneous traits. The proposed framework has applications beyond genetic association studies.

Genetic polymorphisms in the 9p21 region associated with risk of multiple cancers.

The chromosome 9p21 region has been implicated in the pathogenesis of multiple cancers. We analyzed 9p21 single nucleotide polymorphisms (SNPs) from eight genome-wide association studies (GWAS) with data deposited in dbGaP, including studies of esophageal squamous cell carcinoma (ESCC), gastric cancer (GC), pancreatic cancer, renal cell carcinoma (RCC), lung cancer (LC), breast cancer (BrC), bladder cancer (BC) and prostate cancer (PrC). The number of subjects ranged from 2252 (PrC) to 7619 (LC). SNP-level analyses for each cancer were conducted by logistic regression or random-effects meta-analysis. A subset-based statistical approach (ASSET) was performed to combine SNP-level P values across multiple cancers. We calculated gene-level P values using the adaptive rank truncated product method. We identified that rs1063192 and rs2157719 in the CDKN2A/2B region were significantly associated with ESCC and rs2764736 (3' of TUSC1) was associated with BC (P ≤ 2.59 × 10(-6)). ASSET analyses identified four SNPs significantly associated with multiple cancers: rs3731239 (CDKN2A intronic) with ESCC, GC and BC (P = 3.96 × 10(-) (4)); rs10811474 (3' of IFNW1) with RCC and BrC (P = 0.001); rs12683422 (LINGO2 intronic) with RCC and BC (P = 5.93 × 10(-) (4)) and rs10511729 (3' of ELAVL2) with LC and BrC (P = 8.63 × 10(-) (4)). At gene level, CDKN2B, CDKN2A and CDKN2B-AS1 were significantly associated with ESCC (P ≤ 4.70 × 10(-) (5)). Rs10511729 and rs10811474 were associated with cis-expression of 9p21 genes in corresponding cancer tissues in the expression quantitative trait loci analysis. In conclusion, we identified several genetic variants in the 9p21 region associated with the risk of multiple cancers, suggesting that this region may contribute to a shared susceptibility across different cancer types.

Post-GWAS functional analyses of CNTNAP5 suggests its role in glaucomatous neurodegeneration.

Primary angle closure glaucoma (PACG) affects more than 20 million people worldwide, with an increased prevalence in south-east Asia. In a prior haplotype-based GWAS, we identified a novel CNTNAP5 genic region, significantly associated with PACG. In the current study, we have extended our perception of CNTNAP5 involvement in glaucomatous neurodegeneration in a zebrafish model, through investigating phenotypic consequences pertinent to retinal degeneration upon knockdown of cntnap5 by translation-blocking morpholinos. While cntnap5 knockdown was successfully validated using an antibody, immunofluorescence followed by western blot analyses in cntnap5-morphant (MO) zebrafish revealed increased expression of acetylated tubulin indicative of perturbed cytoarchitecture of retinal layers. Moreover, significant loss of Nissl substance is observed in the neuro-retinal layers of cntnap5-MO zebrafish eye, indicating neurodegeneration. Additionally, in spontaneous movement behavioural analysis, cntnap5-MO zebrafish have a significantly lower average distance traversed in light phase compared to mismatch-controls, whereas no significant difference was observed in the dark phase, corroborating with vision loss in the cntnap5-MO zebrafish. This study provides the first direct functional evidence of a putative role of CNTNAP5 in visual neurodegeneration.

Using principal components of genetic variation for robust and powerful detection of gene-gene interactions in case-control and case-only studies.

Many popular methods for exploring gene-gene interactions, including the case-only approach, rely on the key assumption that physically distant loci are in linkage equilibrium in the underlying population. These methods utilize the presence of correlation between unlinked loci in a disease-enriched sample as evidence of interactions among the loci in the etiology of the disease. We use data from the CGEMS case-control genome-wide association study of breast cancer to demonstrate empirically that the case-only and related methods have the potential to create large-scale false positives because of the presence of population stratification (PS) that creates long-range linkage disequilibrium in the genome. We show that the bias can be removed by considering parametric and nonparametric methods that assume gene-gene independence between unlinked loci, not in the entire population, but only conditional on population substructure that can be uncovered based on the principal components of a suitably large panel of PS markers. Applications in the CGEMS study as well as simulated data show that the proposed methods are robust to the presence of population stratification and are yet much more powerful, relative to standard logistic regression methods that are also commonly used as robust alternatives to the case-only type methods.

Polymorphisms in genes related to one-carbon metabolism are not related to pancreatic cancer in PanScan and PanC4.

PURPOSE: The evidence of a relation between folate intake and one-carbon metabolism (OCM) with pancreatic cancer (PanCa) is inconsistent. In this study, the association between genes and single-nucleotide polymorphisms (SNPs) related to OCM and PanCa was assessed. METHODS: Using biochemical knowledge of the OCM pathway, we identified thirty-seven genes and 834 SNPs to examine in association with PanCa. Our study included 1,408 cases and 1,463 controls nested within twelve cohorts (PanScan). The ten SNPs and five genes with lowest p values (<0.02) were followed up in 2,323 cases and 2,340 controls from eight case-control studies (PanC4) that participated in PanScan2. The correlation of SNPs with metabolite levels was assessed for 649 controls from the European Prospective Investigation into Cancer and Nutrition. RESULTS: When both stages were combined, we observed suggestive associations with PanCa for rs10887710 (MAT1A) (OR 1.13, 95 %CI 1.04-1.23), rs1552462 (SYT9) (OR 1.27, 95 %CI 1.02-1.59), and rs7074891 (CUBN) (OR 1.91, 95 %CI 1.12-3.26). After correcting for multiple comparisons, no significant associations were observed in either the first or second stage. The three suggested SNPs showed no correlations with one-carbon biomarkers. CONCLUSIONS: This is the largest genetic study to date to examine the relation between germline variations in OCM-related genes polymorphisms and the risk of PanCa. Suggestive evidence for an association between polymorphisms and PanCa was observed among the cohort-nested studies, but this did not replicate in the case-control studies. Our results do not strongly support the hypothesis that genes related to OCM play a role in pancreatic carcinogenesis.

A quantitative trait GWAS on lens thickness identifies novel risk loci on PTPRM in the narrow angle individuals susceptible to PACG.

PURPOSE: PACG is one of the leading causes of blindness where lens thickness is a major risk factor for narrow-angle individuals. To our knowledge, no literature has been reported on candidate gene for lens thickness as a quantitative trait (QT). Here, we performed a genome-wide association analysis on lens thickness in the narrow-angle individuals. MATERIALS AND METHODS: We conducted a genome-wide association study (GWAS) in the narrow angle individuals to investigate comprehensive genetic insights on lens thickness. RESULTS: In QT-GWAS, we identified 145 genome-wide suggestive significant loci in the discovery cohort. Subsequently, we observed 13 SNPs that showed statistical significance around the region of PTRRM. Regional association analysis for top significant genotyped variants identified PTPRM as the most likely candidate for increased LT. Integrative bioinformatic analyses confirmed that the associated genomic region has potential regulatory roles for modulating transcription as enhancers. In the replication cohort, the sentinel genotype SNP was further associated significantly (P-value =0.000448) with high LT individuals. In both cohorts, the T allele of rs1941137 in the PTPRM gene indicates as a risk allele for the increased LT. CONCLUSION: In this study, we discovered evidence of a genomic association between chromosomal areas around the PTPRM and increased lens thickness, resulting in a narrow angle. The regulatory components corresponding to PTPRM variations might have a role in the thicker lens. We report that the genomic region near PTPRM, a gene of potential interest, is associated with increased lens thickness.

Identifying polymorphic cis-regulatory variants as risk markers for lung carcinogenesis and chemotherapy responses in tobacco smokers from eastern India.

Aberrant expression of xenobiotic metabolism and DNA repair genes is critical to lung cancer pathogenesis. This study aims to identify the cis-regulatory variants of the genes modulating lung cancer risk among tobacco smokers and altering their chemotherapy responses. From a list of 2984 SNVs, prioritization and functional annotation revealed 22 cis-eQTLs of 14 genes within the gene expression-correlated DNase I hypersensitive sites using lung tissue-specific ENCODE, GTEx, Roadmap Epigenomics, and TCGA datasets. The 22 cis-regulatory variants predictably alter the binding of 44 transcription factors (TFs) expressed in lung tissue. Interestingly, 6 reported lung cancer-associated variants were found in linkage disequilibrium (LD) with 5 prioritized cis-eQTLs from our study. A case-control study with 3 promoter cis-eQTLs (p < 0.01) on 101 lung cancer patients and 401 healthy controls from eastern India with confirmed smoking history revealed an association of rs3764821 (ALDH3B1) (OR = 2.53, 95% CI = 1.57-4.07, p = 0.00014) and rs3748523 (RAD52) (OR = 1.69, 95% CI = 1.17-2.47, p = 0.006) with lung cancer risk. The effect of different chemotherapy regimens on the overall survival of lung cancer patients to the associated variants showed that the risk alleles of both variants significantly decreased (p < 0.05) patient survival.

Whole exome sequencing in dense families suggests genetic pleiotropy amongst Mendelian and complex neuropsychiatric syndromes.

Whole Exome Sequencing (WES) studies provide important insights into the genetic architecture of serious mental illness (SMI). Genes that are central to the shared biology of SMIs may be identified by WES in families with multiple affected individuals with diverse SMI (F-SMI). We performed WES in 220 individuals from 75 F-SMI families and 60 unrelated controls. Within pedigree prioritization employed criteria of rarity, functional consequence, and sharing by ≥ 3 affected members. Across the sample, gene and gene-set-wide case-control association analysis was performed with Sequence Kernel Association Test (SKAT). In 14/16 families with ≥ 3 sequenced affected individuals, we identified a total of 78 rare predicted deleterious variants in 78 unique genes shared by ≥ 3 members with SMI. Twenty (25%) genes were implicated in monogenic CNS syndromes in OMIM (OMIM-CNS), a fraction that is a significant overrepresentation (Fisher's Exact test OR = 2.47, p = 0.001). In gene-set SKAT, statistically significant association was noted for OMIM-CNS gene-set (SKAT-p = 0.005) but not the synaptic gene-set (SKAT-p = 0.17). In this WES study in F-SMI, we identify private, rare, protein altering variants in genes previously implicated in Mendelian neuropsychiatric syndromes; suggesting pleiotropic influences in neurodevelopment between complex and Mendelian syndromes.

Robust score statistics for QTL linkage analysis.

The traditional variance components approach for quantitative trait locus (QTL) linkage analysis is sensitive to violations of normality and fails for selected sampling schemes. Recently, a number of new methods have been developed for QTL mapping in humans. Most of the new methods are based on score statistics or regression-based statistics and are expected to be relatively robust to non-normality of the trait distribution and also to selected sampling, at least in terms of type I error. Whereas the theoretical development of these statistics is more or less complete, some practical issues concerning their implementation still need to be addressed. Here we study some of these issues such as the choice of denominator variance estimates, weighting of pedigrees, effect of parameter misspecification, effect of non-normality of the trait distribution, and effect of incorporating dominance. We present a comprehensive discussion of the theoretical properties of various denominator variance estimates and of the weighting issue and then perform simulation studies for nuclear families to compare the methods in terms of power and robustness. Based on our analytical and simulation results, we provide general guidelines regarding the choice of appropriate QTL mapping statistics in practical situations.

Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India.

Several reports have highlighted the contributions of host factors such as age, gender and co-morbidities such as diabetes, hypertension and coronary heart disease in determining COVID-19 disease severity. However, inspite of initial efforts at understanding the contributions of SARS-CoV-2 variants, most were unable to delineate causality. Hence, in this study we re-visited the contributions of different clades of viruses (G, GR and GH) along with other attributes in explaining the disparity in mortality rates among countries. A total of 26,642 high quality SARS-CoV-2 sequences were included and the A23,403G (S:D614G) variant was found to be in linkage disequilibrium with C14,408 U (RdRp: P323L). Linear regression analyses revealed increase in age [Odds ratio: 1.055 (p-value 0.000358)] and higher frequency of clade-G viruses [Odds ratio: 1.029(p-value 0.000135)] could explain 37.43% of the differences in mortality rates across the 58 countries (Multiple R-squared: 0.3743). Next, Machine-Learning algorithms LogitBoost and AdaboostM1 were applied to determine whether countries belonging to high/low mortality groups could be classified using the same attributes and accurate classification was achieved in 70.69% and 62.07% of the countries, respectively. Further, evolutionary analyses of the Indian viral population (n = 662) were carried out. Allele frequency spectrum, nucleotide diversity (π) values and negative Tajima's D values across ORFs were indicative of population expansion. Network analysis revealed the presence of two major clusters of viral haplotypes, namely, clade-G and a variant of clade L [Lv] having the RdRp:A97V amino acid change. Clade-G genomes were found to be evolving more rapidly and were also found in higher proportions in three states with highest mortality rates namely, Gujarat, Madhya Pradesh and West Bengal. Thus, the findings of this study and results from in vitro studies highlighting the role of these variants in increasing transmissibility and altering response to antivirals reflect the role of viral factors in disease prognosis.

Haplotype-based genomic analysis reveals novel association of CNTNAP5 genic region with primary angle closure glaucoma.

Primary angle closure glaucoma (PACG) is one of the major causes of blindness worldwide. The underlying genetic aetiology is complex in nature and molecular mechanism remains elusive. Here, we identify genomic alterations using haplotype-based genome-wide association study in 148 PACG and 92 anatomically predisposed non-glaucomatous individuals. Logistic regression was performed on each common haplotype (within blocks of 3-8 SNPs) across the genotype and a total of 59 SNPs were found below genome wide suggestive threshold (p <1e-05). We found majority of these SNPs (n = 13) are located in CNTNAP5 genic region. The prioritized rs780010 of CNTNAP5 is also significantly associated with Cup to Disc ratio, which is a clinical parameter directly correlated with glaucomatous neurodegeneration. We further validated rs780010, present in all the significant haplotype blocks with p-value = 2.131e-06 (discovery phase), in a separate replication cohort (PACG, n = 50; control, n = 39) and observed significant association (p = 0.012, per G allele OR = 2.3079; 95 % CI: 1.23-4.33). Bioinformatics analyses also suggested neuronal expression of CNTNAP5 with active chromatin structure. KEGG pathway analysis indicates towards pathways related to apoptosis and neurodegeneration. Overall, these results not only indicate a strong genetic association of CNTNAP5 locus with PACG but also suggest its potential involvement in glaucomatous neurodegeneration.

A comprehensive meta-analysis and a case-control study give insights into genetic susceptibility of lung cancer and subgroups.

Reports of genetic association of polymorphisms with lung cancer in the Indian subcontinent are often conflicting. To summarise and replicate published evidence for association with lung cancer and its subgroups. We performed a meta-analysis of candidate associations on lung cancer, its histological subtypes and smoking status in the Indian subcontinent following PRISMA guidelines. Multiple testing corrections were done by the Benjamini-Hochberg method through assessment of significance at a false discovery rate of 10%. We genotyped and investigated rs1048943/CYP1A1 in a case-control sample from eastern India, followed by its global meta-analysis using a similar protocol. Meta-analysis of 18 variants of 11 genes reported in 39 studies (7630 cases and 8169 controls) showed significant association of rs1048943/CYP1A1 [2.07(1.49-2.87)] and rs4646903/CYP1A1 [1.48(1.93-1.95)] with overall lung cancer risk at 10% FDR, while nominal association (p < 0.05) was observed for del1/GSTT1, del2/GSTM1, rs1695/GSTP1 and rs17037102/ DKK2. Subtype analysis showed a significant association of del1/GSTT1 with adenocarcinoma, rs4646903/CYP1A1 with squamous carcinoma, and rs1048943/CYP1A1 with both. Association of rs4646903/CYP1A1 in smokers and effect modification by meta-regression analysis was observed. Genotyping of rs1048943/CYP1A1 that presented significant heterogeneity (p < 0.1) revealed an association with adenocarcinoma among eastern Indian smokers, while a global meta-analysis in 10458 cases and 10871 controls showed association with lung cancer and its subgroups. This study identified the susceptibility loci for lung cancer and its covariate-subgroups.

A genomewide association study on individuals with occludable angles identifies potential risk loci for intraocular pressure.

Glaucoma is a heterogeneous group of optic neuropathies and is one of the leading causes of irreversible blindness worldwide. Primary angle closure glaucoma (PACG) is a major subtype, prevalent mostly in east and south Asia, where occludable anterior chamber angle is considered as a primary risk factor, which in turn could be responsible for high intraocular pressure (IOP) and subsequent neurodegeneration of retinal ganglion cells. Clinically, IOP is considered as a major risk factor for glaucoma and viewed as an important endophenotype to promote the disease severity. To investigate the comprehensive genomic insights, we conducted a genomewide association study (GWAS) on IOP in individuals with occludable angle (<15 degrees), thus anatomically predisposed to PACG. After performing GWAS on IOP, we identified 25 genomewide suggestive significant loci (P<1e-05, n = 240) of which, six were in complete linkage disequilibrium with the ABCA4 genic region. We successfully replicated the most significant discovery, SNPs of ABCA4 (rs2065712) in a separate cohort of 89 individuals (P =1.16e-09). We identified multiple SNPs in ABCA4 to be associated with IOP. Also, we obtained genes harbouring significantly associated SNPs, included in relevant biological pathways that could potentially be involved in IOP variation and glaucomatous neurodegeneration.

Two novel cell culture models of buccal mucosal oral cancer from patients with no risk-habits of tobacco smoking or chewing.

OBJECTIVE: Tobacco consumption is one of the major etiological factors for oral cancer, but it also develops in non-tobacco users, with unknown etiologies. Cellular models for tobacco associated oral cancer are available, however; reports of cellular models for studying non-tobacco associated oral cancer are limiting. We report here the establishment and characterization of two novel buccal mucosal cancer cell lines 'GBC02' and 'GBC035' derived from non-tobacco users. MATERIALS AND METHODS: Short tandem repeats (STR) profiling, Next-generation sequencing for whole-genome, exome and copy number alterations, immunofluorescence, flow-cytometry, proliferation, live-cell chemotaxis, 3D-spheroid formation, chemotherapy response, gene-expression microarray, gene-set enrichment analysis and xenograft development were performed. RESULTS: Sources of the established cultures were matched to their donors through STR profiling. Genome sequence analysis revealed somatic mutations in TP53, CASP8, CDKN2A for GBC02 with deletions and amplifications encompassing CDKN2A, FAT1 and CCND1, PIK3CA, SOX2, EGFR, MYC genes, respectively. GBC035 harbored mutations in FAT1, NOTCH1, HRAS, CDKN2A, HLA-B, HLA-A genes. While GBC035 cells showed higher E-Cadherin positive cell-cell junctions and collective cell migration in chemotaxis; GBC02 cells were vimentin-positive and demonstrated individual cell migration. Further, exhibiting their relevance to preclinical research, GBC02 3D-spheroids demonstrated enrichment of development-related gene-signatures in microarray transcriptome analysis and were resistant to Cisplatin, but showed sensitivity to cancer stem cells-targeting drug, Salinomycin. Additionally, tumorigenic ability of GBC02 was demonstrated. CONCLUSIONS: Altogether, we present here comprehensively characterized unique cell lines established from non-tobacco associated tumors, which may serve as models for preclinical investigations of oral cancers caused independent of tobacco usage.

Decreased expression of miR-125b and miR-100 in oral cancer cells contributes to malignancy.

Altered microRNA (miRNA) expression profiles have been observed in numerous malignancies, including oral squamous cell carcinoma (OSCC). However, their role in disease is not entirely clear. Several genetic aberrations are characteristic of OSCC, with amplification of chromosomal band 11q13 and loss of distal 11q being among the most prevalent. It is not known if the expression levels of miRNAs in these regions are altered or whether they play a role in disease. We hypothesize that the expression of miRNAs mapping to 11q are altered in OSCC because of loss or amplification of chromosomal material, and that this contributes to the development and progression of OSCC. We found that miR-125b and miR-100 are down-regulated in OSCC tumor and cell lines, and that transfecting cells with exogenous miR-125b and miR-100 significantly reduced cell proliferation and modified the expression of target and nontarget genes, including some that are overexpressed in radioresistant OSCC cells. In conclusion, the down-regulation of miR-125b and miR-100 in OSCC appears to play an important role in the development and/or progression of disease and may contribute to the loss of sensitivity to ionizing radiation.

Meta-Analysis of Polymorphic Variants Conferring Genetic Risk to Cervical Cancer in Indian Women Supports CYP1A1 as an Important Associated Locus

Objective: Association of multiple polymorphic variants with cervical cancer has been elucidated by several candidate gene based as well as genome-wide association studies. However, contradictory outcomes of those studies have failed to estimate the true effect of the polymorphic variants on cervical cancer. Methods: Literature mining of the PubMed database was done to gather all the publications related to genetic association with cervical cancer in India. Out of 98 PubMed hits only 29 genetic association studies were selected for meta-analysis based on specific inclusion criteria. A fixed-effect meta-analysis was performed to evaluate the overall association of the genetic polymorphisms with cervical cancer. Cochran's Q test was performed to assess between study heterogeneity. Publication bias was also estimated by funnel plots and Egger's regression test. Further, sub-group analysis was conducted by fixed-effect meta-regression to assess the impact of polymorphisms on cervical cancer in the presence of Human Papilloma Virus (HPV). Result: Following a fixed-effect model, meta-analysis was conducted that revealed 2 polymorphic variants viz. 'deletion polymorphism (Del2) (OR=1.79, 95% CI= 1.08-2.95, P=0.023) in GSTM1' and 'rs1048943 (OR = 2.34, 95% CI=1.37-3.99, P=0.0018) in CYP1A1' to be associated with cervical cancer. However, multiple testing correction showed only rs1048943 of CYP1A1 to be significantly associated (P-value=0.029) with cervical cancer with significant publication bias (P-value=0.0113) as estimated by Egger's regression test. The polymorphic variants 'rs1801131', 'rs1801133', 'rs2430561', 'rs1799782', 'rs25486' and 'rs25487' showed significant (p<0.05) evidence of heterogeneity between studies by Cochran's Q test and also by heterogeneity index (I2) calculation. Conclusion: Therefore, our study revealed significant association of rs1048943 in CYP1A1, but a nominal association of deletion polymorphism (Del2) in GSTM1 with cervical cancer, which provides a comprehensive insight on the true effect of the polymorphisms, reported in various case-control studies, on the risk of the development of cervical cancer in Indian women.