Search

A thickened, white patch - leukoplakia - in the oral cavity is usually benign, but sometimes (in ~9% of individuals) it progresses to malignant tumour. Because the genomic basis of this progression is poorly understood, we undertook this study and collected samples of four tissues - leukoplakia, tumour, adjacent normal, and blood - from each of 28 patients suffering from gingivobuccal oral cancer. We performed multiomics analysis of the 112 collected tissues (four tissues per patient from 28 patients) and integrated information on progressive changes in the mutational and transcriptional profiles of each patient to create this genomic narrative. Additionally, we generated and analysed whole-exome sequence data from leukoplakia tissues collected from 11 individuals not suffering from oral cancer. Nonsynonymous somatic mutations in the CASP8 gene were identified as the likely events to initiate malignant transformation, since these were frequently shared between tumour and co-occurring leukoplakia. CASP8 alterations were also shown to enhance expressions of genes that favour lateral spread of mutant cells. During malignant transformation, additional pathogenic mutations are acquired in key genes (TP53, NOTCH1, HRAS) (41% of patients); chromosomal-instability (arm-level deletions of 19p and q, focal-deletion of DNA-repair pathway genes and NOTCH1, amplification of EGFR) (77%), and increased APOBEC-activity (23%) are also observed. These additional alterations were present singly (18% of patients) or in combination (68%). Some of these alterations likely impact immune-dynamics of the evolving transformed tissue; progression to malignancy is associated with immune suppression through infiltration of regulatory T-cells (56%), depletion of cytotoxic T-cells (68%), and antigen-presenting dendritic cells (72%), with a concomitant increase in inflammation (92%). Patients can be grouped into three clusters by the estimated time to development of cancer from precancer by acquiring additional mutations (range: 4-10 years). Our findings provide deep molecular insights into the evolutionary processes and trajectories of oral cancer initiation and progression. © 2022 The Authors. The Journal of Pathology published by John WileySons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The following article is reproduced with permission from The Telegraph, Kolkata (Guest Column, Published on 25 March 2020).

BackgroundDNA methylation (DNAm) may play an important role in birth outcomes.Material and MethodsGenome wide DNAm was analysed in peripheral blood DNA of women at multiple time points during gestation. A novel empirical method was used to identify CpG sites with high temporal variance in methylation associating with preterm birth.ResultsHigh variability at 1296 CpG sites from the promoter regions of 1197 genes significantly associated with PTB. These genes belonged to pathways involved in signalling by platelet derived growth factor, platelet homeostasis, collagen degradation, extracellular matrix and circadian clock.ConclusionsThe findings provide novel information which might help in development of predictive biomarkers of preterm birth outcome.

The underrepresentation of non-Europeans in human genetic studies so far has limited the diversity of individuals in genomic datasets and led to reduced medical relevance for a large proportion of the world’s population. Population-specific reference genome datasets as well as genome-wide association studies in diverse populations are needed to address this issue. Here we describe the pilot phase of the GenomeAsia 100K Project. This includes a whole-genome sequencing reference dataset from 1,739 individuals of 219 population groups and 64 countries across Asia. We catalogue genetic variation, population structure, disease associations and founder effects. We also explore the use of this dataset in imputation, to facilitate genetic studies in populations across Asia and worldwide., Using whole-genome sequencing data from 1,739 individuals, the GenomeAsia 100K Project catalogues genetic variation, population structure and disease associations to facilitate genetic studies in Asian populations and increase representation in genetics studies worldwide.

To decipher the genetic architecture of human disease, various types of omics data are generated. Two common omics data are genotypes and gene expression. Often genotype data for a large number of individuals and gene expression data for a few individuals are generated due to biological and technical reasons, leading to unequal sample sizes for different omics data. Unavailability of standard statistical procedure for integrating such datasets motivates us to propose a two-step multi-locus association method using latent variables. Our method is powerful than single/separate omics data analysis and it unravels comprehensively deep-seated signals through a single statistical model. Extensive simulation confirms that it is robust to various genetic models as its power increases with sample size and number of associated loci. It provides p-values very fast. Application to real dataset on psoriasis identifies 17 novel SNPs, functionally related to psoriasis-associated genes, at much smaller sample size than standard GWAS.

Oral squamous cell carcinoma (OSCC) is highly prevalent in south and southeast Asia. Many (30-50%) OSCC patients develop lymph node metastasis (LNM), which is the most important prognostic factor in OSCC. To identify genomic correlates of LNM, we compared exome sequences and copy number variation data of blood and tumor DNA from highly contrasting subgroups of patients to reduce false inferences-(i) patients with LNM and (ii) patients with late stage disease but without LNM. We found that LNM is associated with (i) specific hotspot somatic mutations in TP53 and CASP8; (ii) rare nonsilent germline mutations in BRCA2 and FAT1; (iii) mutations in mito-G2/M and nonhomologous end joining (NHEJ) pathways; (iv) recurrent deletion of genes for DNA repair by homologous recombination; and (v) chromosomal instability. LN+ patients with NHEJ pathway mutations have longer disease-free survival. Five genomic features have a high predictive value of LNM.

Multiple host genes determine susceptibility or resistance to tuberculosis. In an exome-wide association study conducted among tuberculosis patients and their exposed but clinically asymptomatic household contacts, we found that the SNP rs61104666 located in the fifth exon of SIGLEC15 gene is associated with the disease. No other variant in SIGLEC15 has been reported previously to be associated with tuberculosis. The associated polymorphism results in a synonymous change (E292E) and therefore is unlikely to be involved in disease pathogenesis. Bioinformatic analysis of epigenetic marks in the genomic region reveals an enhancer mark present in lung and blood, downstream to the SIGLEC15 gene may harbor candidate causal SNPs which are in strong LD with the index SNP. This region overlaps with the 3′UTR region of the neighboring gene EPG5. EPG5 has role in autophagy, a phenomenon relevant to clearing of the infection. The region also harbors DNAse I sensitive sites with SNPs of low RegulomeDB score indicative of potential transcription binding sites. All these evidences suggest further exploration of the enhancer region to understand its role in disease manifestation.

Oral cancer is highly prevalent in India and is the most frequent cancer type among Indian males. It is also very common in southeast Asia. India has participated in the International Cancer Genome Consortium (ICGC) and some national initiatives to generate large-scale genomic data on oral cancer patients and analyze to identify associations and systematically catalog the associated variants. We have now created an open, web-accessible database of these variants found significantly associated with Indian oral cancer patients, with a user-friendly interface to enable easy mining. We have value added to this database by including relevant data collated from various sources on other global populations, thereby providing opportunities of comparative geographical and/or ethnic analyses. Currently, no other database of similar nature is available on oral cancer. We have developed Database of GENomic Variants of Oral Cancer, a browsable online database framework for storage, retrieval and analysis of large-scale data on genomic variants and make it freely accessible to the scientific community. Presently, the web-accessible database allows potential users to mine data on ∼24 million clinically relevant somatic and germline variants derived from exomes (n = 100) and whole genomes (n = 5) of Indian oral cancer patients; all generated by us. Variant data from The Cancer Genome Atlas and data manually curated from peer-reviewed publications were also incorporated into the database for comparative analyses. It allows users to query the database by a single gene, multiple genes, multiple variant sites, genomic region, patient ID and pathway identities. Database URL: http://research.nibmg.ac.in/dbcares/dbgenvoc/

BackgroundDevelopment of methods to detect risk of preterm birth in pregnant women can result in reduction in occurrence of preterm birth. Our objective was to undertake a longitudinal study to investigate the association of telomere length shortening in peripheral blood DNA of women during pregnancy with preterm birth.MethodsTelomere length reduction in peripheral blood DNA was measured at two time points by Real Time PCR in pregnant women enrolled in a large prospective cohort (GARBH-Ini) in Gurugram, India. Out of 248 women who participated in this study, 60 mothers delivered preterm while 188 mothers delivered at term. ResultsTelomere length was found to be significantly reduced in preterm birth delivering mothers compared to those who delivered at term at less than 20 weeks (p=0.02) and at 26-28 weeks (p=0.84 x 10-15) of pregnancy. Predictive modelling by binary logistic regression analysis revealed that reduction of telomere length (T/S ratio) at 26-28 weeks was found to be significantly (p=7.7181 x 10-06) associated with enhanced risk of preterm birth. A mean odds ratio of 8.4 was found for association of T/S ratio with preterm birth outcome. There was no significant difference in maternal age between the mothers who delivered preterm and those who delivered at term. ConclusionsOur preliminary results indicate that telomere length reduction in maternal peripheral blood DNA might be a potential indicator of risk of preterm delivery.

South Asia was peopled on an early wave of human migration from out-of-Africa. This wave passed through the coastline of Saudi Arabia and India to Andaman and Nicobar archipelago and possibly to Australia as well. West Asia, on the other hand, served as a corridor for early and historical human migrations with various ancestries resulting in diverse settlements. At least four ancestral components are discernible in the extant populations of mainland Indian subcontinent. Some ancient tribal groups of Andaman and Nicobar archipelago carry signatures of an ancestry that is distinct from those found in India.

Background Studies of epigenomic alterations associated with diseases primarily focus on methylation profiles of promoter regions of genes, but not of other genomic regions. In our past work (Das et al. 2019) on patients suffering from gingivo-buccal oral cancer – the most prevalent form of cancer among males in India – we have also focused on promoter methylation changes and resultant impact on transcription profiles. Here, we have investigated alterations in non-promoter (gene-body) methylation profiles and have carried out an integrative analysis of gene-body methylation and transcriptomic data of oral cancer patients. Methods Tumor and adjacent normal tissue samples were collected from 40 patients. Data on methylation in the non-promoter (gene-body) regions of genes and transcriptome profiles were generated and analyzed. Because of high dimensionality and highly correlated nature of these data, we have used Random Forest (RF) and other data-analytical methods. Results Integrative analysis of non-promoter methylation and transcriptome data revealed significant methylation-driven alterations in some genes that also significantly impact on their transcription levels. These changes result in enrichment of the Central Carbon Metabolism (CCM) pathway, primarily by dysregulation of (a) NTRK3, which plays a dual role as an oncogene and a tumor suppressor; (b) SLC7A5 (LAT1) which is a transporter dedicated to essential amino acids, and is overexpressed in cancer cells to meet the increased demand for nutrients that include glucose and essential amino acids; and, (c) EGFR which has been earlier implicated in progression, recurrence, and stemness of oral cancer, but we provide evidence of epigenetic impact on overexpression of this gene for the first time. Conclusions In rapidly dividing cancer cells, metabolic reprogramming from normal cells takes place to enable enhanced proliferation. Here, we have identified that among oral cancer patients, genes in the CCM pathway – that plays a fundamental role in metabolic reprogramming – are significantly dysregulated because of perturbation of methylation in non-promoter regions of the genome. This result compliments our previous result that perturbation of promoter methylation results in significant changes in key genes that regulate the feedback process of DNA methylation for the maintenance of normal cell division.

SARS-CoV-2 was first reported from China. Within three months, it evolved to 10 additional subtypes. Two evolved subtypes (A2 and A2a) carry a non-synonymous Spike protein mutation (D614G). We conducted phylodynamic analysis of over 70,000 SARS-CoV-2 coronaviruses worldwide, sequenced until July2020, and found that the mutant subtype (614G) outcompeted the pre-existing type (614D), significantly faster in Europe and North-America than in East Asia. Bioinformatically and computationally, we identified a novel neutrophil elastase (ELANE) cleavage site introduced in the G-mutant, near the S1-S2 junction of the Spike protein. We hypothesised that elevation of neutrophil elastase level at the site of infection will enhance the activation of Spike protein thus facilitating host cell entry for 614G, but not the 614D, subtype. The level of neutrophil elastase in the lung is modulated by its inhibitor α1-antitrypsin (AAT). AAT prevents lung tissue damage by elastase. However, many individuals exhibit genotype-dependent deficiency of AAT. AAT deficiency eases host-cell entry of the 614G virus, by retarding inhibition of neutrophil elastase and consequently enhancing activation of the Spike protein. AAT deficiency is highly prevalent in European and North-American populations, but much less so in East Asia. Therefore, the 614G subtype is able to infect and spread more easily in populations of the former regions than in the latter region. Our analyses provide a molecular biological and evolutionary model for the higher observed virulence of the 614G subtype, in terms of causing higher morbidity in the host (higher infectivity and higher viral load), than the non-mutant 614D subtype.

Oral squamous cell carcinoma of the gingivo-buccal region (OSCC-GB) accounts for the highest cancer morbidity and mortality among men in India. It has been observed that about one-third of individuals with oral leukoplakia, a dysplastic precancerous lesion in the oral cavity, progress to oral cancer. We aimed to identify systematic transcriptomic changes as a normal tissue in the oral cavity progresses to frank OSCC-GB. Seventy-two OSCC-GB patients, from multiple hospitals, were recruited, and transcriptome analysis of tumor and adjacent normal tissue (of all patients) and adjacent leukoplakia tissue (of a subset of 25 unselected patients with concomitant leukoplakia) was performed. We have identified many differences in the transcriptomic profiles between OSCC-GB and squamous cell carcinoma of the head and neck regions. Compared to the normal/precancerous tissue, significant enrichment of ECM−receptor interaction, PI3K-Akt signaling, cytokine−cytokine receptor interaction, focal adhesion, and cell cycle pathways were observed in OSCC-GB. Using gene set enrichment analysis, we identified a profound role of interferon receptor signaling in tumor growth by activating immune evasion mechanisms. The role of tumor-infiltrating immune cells further supported the growth and immunosuppressive mechanism of tumor tissues. Some immune evasion genes—CD274, CD80, and IDO1—were found to be activated even in the precancerous tissue. Taken together, our findings provide a clear insight into the sequential genetic dysregulation associated with progression to oral cancer. This insight provides a window to the development of predictive biomarkers and therapeutic targets for gingivo-buccal oral cancer.

Background: Studies of epigenomic alterations associated with diseases primarily focus on methylation profiles of promoter regions of genes, but not of other genomic regions. In our past work (Das et al. 2019) on patients suffering from gingivo-buccal oral cancer – the most prevalent form of cancer among males in India – we have also focused on promoter methylation changes and resultant impact on transcription profiles. Here, we have investigated alterations in non-promoter (gene-body) methylation profiles and have carried out an integrative analysis of gene-body methylation and transcriptomic data of oral cancer patients. Methods: Tumor and adjacent normal tissue samples were collected from 40 patients. Data on methylation in the non-promoter (gene-body) regions of genes and transcriptome profiles were generated and analyzed. Because of high dimensionality and highly correlated nature of these data, we have used Random Forest (RF) and other data-analytical methods.Results: Our integrative analysis of non-promoter methylation and transcriptome data has revealed significant methylation-driven alterations in some genes that also significantly impact on their transcription levels. These changes result in enrichment of the Central Carbon Metabolism (CCM) pathway, primarily by dysregulation (overexpression) of (a) NTRK3, which plays a dual role as an oncogene and a tumor suppressor; (b) SLC7A5 (LAT1) which is a transporter dedicated to essential amino acids, and is overexpressed in cancer cells to meet the increased demand for nutrients that include glucose and essential amino acids; and, (c) EGFR which has been earlier implicated in progression, recurrence, and stemness of oral cancer, but we provide evidence of epigenetic impact on overexpression of this gene for the first time. Conclusions: In rapidly dividing cancer cells, metabolic reprogramming from normal cells takes place to enable enhanced proliferation. In the present analysis, we have identified that among oral cancer patients, genes in the CCM pathway – that plays a fundamental role in metabolic reprogramming – are significantly dysregulated because of perturbation of methylation in non-promoter regions of the genome. This result compliments our previous result that perturbation of promoter methylation results in significant changes in key genes that regulate the feedback process of DNA methylation for the maintenance of normal cell division.

Professor Calyampudi Radhakrishna Rao - Dr. Rao to most of us - was in the first batch of Master’s students in Statistics of the Calcutta University. He graduated with marks that remain unsurpassed. His name is etched in the annals of statistical science through Cramer–Rao bound, Rao–Blackwell theorem and Rao’s Score Test. He has been elected to the Fellowship of The Royal Society, awarded the U.S. National Medal of Science and Padma Vibhushan by the Government of India. We celebrate his birth centenary because through his contributions he has elevated statistics as an indispensable applied tool in all walks of life, with firm theoretical foundations.

The tumor immune microenvironment is emerging as a critical player in predicting cancer prognosis and response to therapies. However, the prognostic value of tumor-infiltrating immune cells in Gingivo-Buccal Oral Squamous Cell Carcinoma (GBOSCC) and their association with tumor size or lymph node metastases status require further elucidation. To study the relationship of tumor-infiltrating immune cells with tumor size (T stage) and lymph node metastases (N stages), we analyzed the density of tumor-infiltrating immune cells in archived, whole tumor resections from 94 patients. We characterized these sections by immune-histochemistry using 12 markers and enumerated tumor-infiltrating immune cells at the invasive margins (IM) and centers of tumors (CT). We observed that a higher density of CD3+ cells in the IM and CT was associated with smaller tumor size (T1-T2 stage). Fewer CD3+ cells was associated with larger tumor size (T3-T4 stage). High infiltration of CD3+and CD8+ cells in IM and CT as well as high CD4+ cell infiltrates in the IM was significantly associated with the absence of lymph node metastases. High infiltrates of CD3+ and CD8+ cells in CT was associated with significantly improved survival. Our results illustrate that the densities and spatial distribution of CD3+ and CD8+ cell infiltrates in primary GBOSCC tumors is predictive of disease progression and survival. Based on our findings, we recommend incorporating immune cell quantification in the TNM classification and routine histopathology reporting of GBOSCC. Immune cell quantification in CT and IM may help predict the efficacy of future therapies.

Background & objectives: SARS-CoV-2 (Severe acute respiratory syndrome coronavirus-2) is evolving with the progression of the pandemic. This study was aimed to investigate the diversity and evolution of the coronavirus SARS-CoV-2 with progression of the pandemic over time and to identify similarities and differences of viral diversity and evolution across geographical regions (countries). Methods: Publicly available data on type definitions based on whole-genome sequences of the SARS-CoV-2 sampled during December and March 2020 from 3636 infected patients spread over 55 countries were collected. Phylodynamic analyses were performed and the temporal and spatial evolution of the virus was examined. Results: It was found that (i) temporal variation in frequencies of types of the coronavirus was significant; ancestral viruses of type O were replaced by evolved viruses belonging to type A2a; (ii) spatial variation was not significant; with the spread of SARS-CoV-2, the dominant virus was the A2a type virus in every geographical region; (iii) within a geographical region, there was significant micro-level variation in the frequencies of the different viral types, and (iv) the evolved coronavirus of type A2a swept rapidly across all continents. Interpretation & conclusions: SARS-CoV-2 belonging to the A2a type possesses a non-synomymous variant (D614G) that possibly eases the entry of the virus into the lung cells of the host. This may be the reason why the A2a type has an advantage to infect and survive and as a result has rapidly swept all geographical regions. Therefore, large-scale sequencing of coronavirus genomes and, as required, of host genomes should be undertaken in India to identify regional and ethnic variation in viral composition and its interaction with host genomes. Further, careful collection of clinical and immunological data of the host can provide deep learning in relation to infection and transmission of the types of coronavirus genomes.

COVID-19 pandemic is a major human tragedy. Worldwide, SARS-CoV-2 has already infected over 3 million and has killed about 230,000 people. SARS-CoV-2 originated in China and, within three months, has evolved to an additional 10 subtypes. One particular subtype with a non-silent (Aspartate to Glycine) mutation at 614th position of the Spike protein (D614G) rapidly outcompeted other pre-existing subtypes, including the ancestral. We assessed that D614G mutation generates an additional serine protease (Elastase) cleavage site near the S1-S2 junction of the Spike protein. We also identified that a single nucleotide deletion (delC) at a known variant site (rs35074065) in a cis-eQTL of TMPRSS2, is extremely rare in East Asians but is common in Europeans and North Americans. The delC allele facilitates entry of the 614G subtype into host cells, thus accelerating the spread of 614G subtype in Europe and North America where the delC allele is common. The delC allele at the cis-eQTL locus rs35074065 of TMPRSS2 leads to overexpression of both TMPRSS2 and a nearby gene MX1. The cis-eQTL site, rs35074065 overlaps with a transcription factor binding site of an activator (IRF1) and a repressor (IRF2). IRF1 activator can bind to variant delC allele, but IRF2 repressor fails to bind. Thus, in an individual carrying the delC allele, there is only activation, but no repression. On viral entry, IRF1 mediated upregulation of MX1 leads to neutrophil infiltration and processing of 614G mutated Spike protein by neutrophil Elastase. The simultaneous processing of 614G spike protein by TMPRSS2 and Elastase serine proteases facilitates the entry of the 614G subtype into host cells. Thus, SARS-CoV-2, particularly the 614G subtype, has spread more easily and with higher frequency to Europe and North America where the delC allele regulating expression of TMPRSS2 and MX1 host proteins is common, but not to East Asia where this allele is rare.

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.

Prasanta Chandra Mahalanobis analysed large volumes of anthropometric data when he was founding statistical science in India. This experience enabled him to devise many innovative statistical methods and measures, notably D2. He also obtained seminal insights into diversity, affinities and structures of ethnic populations of India. However, anthropometric data did not provide the kind of insights he was seeking. Therefore, he initiated genetical studies in the Indian Statistical Institute (ISI). He received strong support from many internationally renowned scientists to initiate human genetics in ISI. His legacy has lived on and has gained strength over the years. ISI has made many seminal contributions to the understanding of structures and histories of Indian ethnic populations using genetical methods. This essay provides a historical perspective of the contributions of Mahalanobis and his legacy in this domain.

Introduction Variability in clinical outcome of tuberculosis infection is dependent, among other factors, on variation in host immunological response to the infection, which is modulated, in part by genetic variations present in the host. We undertook a study to identify host factors associated with such clinical variability. Study design and methods A comparative study between groups of active TB patients vs. clinically normal household contacts, family members living under the same roof with the patients for a long period of time, was carried out. We screened 22 candidate cytokines and chemokines in the plasma of 119 pairs (“discovery set”) of TB patients and their asymptomatic household contacts. Identified associations were validated in an independent cohort of 78 patient-household contact pairs (“validation set”). Validated associations were further cross-validated by gene expression assays using RT-PCR and in-vitro whole blood stimulation by mycobacterial antigens ESAT6 and Rv2031c, two well-characterized antigens that are expressed in active and latent phases of disease, respectively. In a concomitant SNP association study, we have sequenced the validated gene in these patients and household contacts. Result CXCL10 was found to be the most significantly (p = 0.0002) elevated chemokine – discovered and validated -- in patients' plasma compared to their household contacts. We found that CXCL10 was overexpressed by 5-fold at the RNA level in patients compared to asymptomatic household contacts (p = 0.004). On stimulation of whole blood collected from normal healthy volunteers with mycobacterial antigens ESAT6 and Rv2031c, we found that production of CXCL10 by ESAT6 was significantly higher (p = 2.8 × 10−12) than Rv2031c. The production of CXCL10 was 20-fold more than IFN-γ, the most widely validated cytokine, by ESAT6 stimulation (p = 4.6 × 10−8). One of the polymorphisms in promoter of CXCL10, rs4508917 (−1447 A > G), was identified as a proteinQTL (pQTL). Reduced expression of CXCL10 was observed among individuals with GG genotype, but the reduction was statistically significant only among controls, but not among patients. Among patients, the expression level was very high compared to the controls irrespective of the genotypes at this locus. Conclusion Plasma level of CXCL10 is predictive of the active phase of TB infection.

Human presence in Southeast Asia dates back to at least 40,000 years ago, when the current islands formed a continental shelf called Sundaland. In the Philippine Islands, Peninsular Malaysia, and Andaman Islands, there exist indigenous groups collectively called Negritos whose ancestry can be traced to the “First Sundaland People.” To understand the relationship between these Negrito groups and their demographic histories, we generated genome-wide single nucleotide polymorphism data in the Philippine Negritos and compared them with existing data from other populations. Phylogenetic tree analyses show that Negritos are basal to other East and Southeast Asians, and that they diverged from West Eurasians at least 38,000 years ago. We also found relatively high traces of Denisovan admixture in the Philippine Negritos, but not in the Malaysian and Andamanese groups, suggesting independent introgression and/or parallel losses involving Denisovan introgressed regions. Shared genetic loci between all three Negrito groups could be related to skin pigmentation, height, facial morphology and malarial resistance. These results show the unique status of Negrito groups as descended from the First Sundaland People.

The Human Cell Atlas has been undergoing a massive effort to support global scientific equity. The co-leaders of its Equity Working Group share some lessons learned in the process.

It is hypothesized that same driver gene mutations should be present in both oral leukoplakia and cancer tissues. So, we attempted to find out mutations at one of the driver genes, CASP8, in cancer and adjacent leukoplakia tissues. Patients (n = 27), affected by both of cancer and adjacent leukoplakia, were recruited for the study. Blood and tissue DNA samples were used to identify somatic mutations at CASP8 by next generation sequencing method. In total, 56% (15 out of 27) cancer and 30% (8 out of 27) leukoplakia tissues had CASP8 somatic mutations. In 8 patients, both cancer and adjacent leukoplakia tissues, located within 2-5 cm of tumor sites, had identical somatic mutations. But, in 7 patients, cancer samples had somatic mutations but none of the leukoplakia tissues, located beyond 5cm of tumor sites, had somatic mutations. Mutated allele frequencies at CASP8 were found to be more in cancer compared to adjacent leukoplakia tissues. This study provides mutational evidence that oral cancer might have progressed from previously grown leukoplakia lesion. Leukoplakia tissues, located beyond 5cm of cancer sites, were free from mutation. The study implies that CASP8 mutation could be one of the signatures for some of the leukoplakia to progress to oral cancer.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

In a recent paper, we have derived three main conclusions: i) that all Asian and Pacific populations share a single origin and expansion out of Africa, contradicting an earlier proposal of two independent waves; ii) that populations from South and Southeast Asia harbor a small proportion of ancestry from an unknown extinct hominin, different from the Neanderthal and the Denisovan, which is absent in Europeans; and, iii) that the characteristic distinctive phenotypes (including very short stature) of Andamanese do not reflect an ancient African origin, but have resulted from strong natural selection on genes related to human body size. Although the single wave out of Africa and single origin for Asian and Pacific populations have been confirmed, the existence of admixture with an extinct hominin has been challenged by Skoglund et al., as they were unable to replicate our results in their data sets. While we had used a wide variety of statistical methods and data sets from diverse populations to draw our inference, Skoglund et al. have used only one method (Dstats, for the whole genome, not specifically for the relevant genomic regions) and compared only with the Asians, not even with the Europeans. Skoglund et al. have alleged that our statistical treatment of the data was faulty and have pointed out some possible sources of error. We have reexamined our data focusing on possible sources of error flagged by Skoglund et al. We have also performed new analyses. The reexamination and new analyses have bolstered our confidence that our earlier inferences were correct and have resulted in an improved model of introgression of modern humans with a hitherto unknown archaic ancestry. We also propose a possible reason for the inability of Skoglund et al. to validate our inference.

Recent work has demonstrated that two archaic human groups (Neanderthals and Denisovans) interbred with modern humans and contributed to the contemporary human gene pool. These findings relied on the availability of high-coverage genomes from both Neanderthals and Denisovans. Here we search for evidence of archaic admixture from a worldwide panel of 1,667 individuals using an approach that does not require the presence of an archaic human reference genome. We find no evidence for archaic admixture in the Andaman Islands, as previously claimed, or on the island of Flores, where Homo floresiensis fossils have been found. However, we do find evidence for at least one archaic admixture event in sub-Saharan Africa, with the strongest signal in Khoesan and Pygmy individuals from Southern and Central Africa. The locations of these putative archaic admixture tracts are weighted against functional regions of the genome, consistent with the long-term effects of purifying selection against introgressed genetic material.

Background Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. Although genomic drivers of OSCC-GB have been identified by whole exome and whole genome sequencing, no epigenome-wide study has been conducted in OSCC-GB; our study has filled this gap, and has discovered and validated epigenomic hallmarks of gingivobuccal oral cancer. Methods We have carried out integrative analysis of epigenomic (n = 87) and transcriptomic (n = 72) profiles of paired tumor-normal tissues collected from OSCC-GB patients from India. Genome-wide DNA methylation assays and RNA-sequencing were performed on high-throughput platforms (Illumina) using a half-sample of randomly selected patients to discover significantly differentially methylated probes (DMPs), which were validated on the remaining half-sample of patients. Results About 200 genes showed significant inverse correlation between promoter methylation and expression, of which the most significant genes included genes that act as transcription factors and genes associated with other cancer types. Novel findings of this study include identification of (a) potential immunosuppressive effect in OSCC-GB due to significant promoter hypomethylation driven upregulation of CD274 and CD80, (b) significant dysregulation by epigenetic modification of DNMT3B (upregulation) and TET1 (downregulation); and (c) known drugs that can reverse the direction of dysregulation of gene expression caused by promoter methylation. Conclusions In OSCC-GB patients, there are significant alterations in expression of key genes that (a) regulate normal cell division by maintenance of balanced DNA methylation and transcription process, (b) maintain normal physiological signaling (PPAR, B cell receptor) and metabolism (arachidonic acid) pathways, and (c) provide immune protection against antigens, including tumor cells. These findings indicate novel therapeutic targets, including immunotherapeutic, for treatment of OSCC-GB.

Tuberculosis is a leading cause of death in India. To identify genetic variants associated with susceptibility or resistance to Mycobacterium tuberculosis infection, we have performed an exome-wide association study with 0.2 million exonic variants among 119 pairs of tuberculosis patients and their clinically asymptomatic household contacts. The strongest association was identified for rs61104666[A], a synonymous variant (p.E292E) of exon 5 of the gene SIGLEC15 (OR = 2.4, p = 1.49 × 10−5). We also found association of non-coding variants in the 3′UTR region of a gene encoding the class II human leukocyte antigens (HLAs), HLA-DRA. rs13209234[A] (minor allele frequency (MAF) = 13.8%) (OR = 0.35, P = 2.5 × 10−4) and rs3177928[A] (minor allele frequency (MAF) = 13.7%) (OR = 0.35, P = 3.3 × 10−4) were associated with protection from tuberculosis. These two SNPs, rs13209234 and rs3177928, are in complete linkage disequilibrium. These associations remained valid when additional data on freshly recruited individuals were jointly analyzed on 250 patient-control pairs. The identified gene, HLA-DRA, suggest involvement of immune regulation, indicating pathways associated with antigen presentation in tuberculosis infection.