Impact of Large Granular Lymphocyte Leukemia on Blood DNA Methylation and Epigenetic Clock Modeling in Fischer 344 Rats.

Age-dependent differences in methylation at specific cytosine-guanine (CpG) sites have been used in "epigenetic clock" formulas to predict age. Deviations of epigenetic age from chronological age are informative of health status and are associated with adverse health outcomes, including mortality. In most cases, epigenetic clocks are performed on methylation from DNA extracted from circulating blood cells. However, the effect of neoplastic cells in the circulation on estimation and interpretation of epigenetic clocks is not well understood. Here, we explored this using Fischer 344 (F344) rats, a strain that often develops large granular lymphocyte leukemia (LGLL). We found clear histological markers of LGLL pathology in the spleens and livers of 27 out of 61 rats aged 17-27 months. We assessed DNA methylation by reduced representation bisulfite sequencing with coverage of 3 million cytosine residues. Although LGLL broadly increased DNA methylation variability, it did not change epigenetic aging. Despite this, the inclusion of rats with LGLL in clock training sets significantly altered predictor selection probability at 83 of 121 commonly utilized CpG sites. Furthermore, models trained on rat samples that included individuals with LGLL had greater absolute age error than those trained exclusively rats free of LGLL (39% increase; p < .0001). We conclude that the epigenetic signals for aging and LGLL are distinct, such that LGLL assessment is not necessary for valid measures of epigenetic age in F344 rats. The precision and architecture of constructed epigenetic clock formulas, however, can be influenced by the presence of neoplastic hematopoietic cells in training set populations.

Clinical significance of a microRNA signature for the identification and predicting prognosis in colorectal cancers with mucinous differentiation.

Accumulating evidence supports the fact that the mere presence of mucinous differentiation in colorectal cancer (CRC), rather than its proportion, is a more accurate representative of a particular CRC subtype with distinct clinical and molecular features. In addition, the prognostic significance of the mucinous carcinoma (MC) subtype remains poorly understood and biomarkers have been barely explored in this disease. Herein, we have performed a systematic and comprehensive analysis in MCs and non-MCs and identified a panel of microRNAs (miRNAs) that are differentially expressed between these two subtypes of CRC. Next, we interrogated their clinical significance and demonstrated their robust diagnostic and prognostic clinical ability in CRCs with mucinous differentiation. Finally, we established an integrative risk-assessment model by combining the miRNA-based risk scores together with TNM staging, which was a superior predictor of prognosis in mucinous CRC patients. Collectively, we report a novel miRNA biomarker panel for the identification and predicting survival in CRC patients with mucinous differentiation.

Genome-wide miRNA methylome analysis in oral cancer: possible biomarkers associated with patient survival.

AIM: The methylome associated with miRNA loci was investigated in oral cancer to explore tobacco specific methylation and potential biomarkers for patient survival. METHODS: Methylome data was generated from 16 pairs of cancer-normal tissues by reduced representation bisulfite sequencing method. Differentially methylated regions were identified using the DMAP pipeline. In silico validation and Kaplan-Meier survival analyses were performed on The Cancer Genome Atlas data based on our miRNA methylome data. RESULTS: A total of 4310 unique differentially methylated regions, mapping to 144 miRNA loci, were identified. Three distinct groups of miRNAs were differentially methylated in cancer tissues from smokers, chewers and mixed habitués. Hypermethylation of miR-503, miR-200a/b, miR-320b and miR-489 was associated with worse 5-year survival. CONCLUSION: Differential methylation patterns in miRNA loci are associated with poor survival underscoring their potential as predictive and prognostic biomarkers in oral cancer.

A comprehensive methylation signature identifies lymph node metastasis in esophageal squamous cell carcinoma.

Treatment modalities in esophageal squamous cell carcinoma (ESCC) depend largely on lymph node metastasis (LNM) status. With suboptimal detection sensitivity of existing imaging techniques, we propose a methylation signature which identifies patients with LNM with greater accuracy. This would allow precise stratification of high-risk patients requiring more aggressive treatment from low-risk ESCC patients who can forego radical surgery. An unbiased genome-wide methylation signature for LNM detection was established from an initial in silico discovery phase. The signature was tested in independent clinical cohorts comprising of 249 ESCC patients. The prognostic potential of the methylation signature was compared to clinical variables including LNM status. A 10-probe LNM associated signature (LNAS) was developed using stringent bioinformatics analyses. The area under the curve values for LNAS risk scores were 0.81 and 0.88 in the training and validation cohorts respectively, in association with lymphatic vessel invasion and tumor stage. High LNAS risk-score was also associated with worse overall survival [HR (95% CI) 3 (1.8-4.8), p < 0.0001 training and 3.9 (1.5-10.2), p = 0.001 validation cohort]. In conclusion, our novel methylation signature is a powerful biomarker that identifies LNM status robustly and is also associated with worse prognosis in ESCC patients.

Analysis of the whole transcriptome from gingivo-buccal squamous cell carcinoma reveals deregulated immune landscape and suggests targets for immunotherapy.

BACKGROUND: Gingivo-buccal squamous cell carcinoma (GBSCC) is one of the most common oral cavity cancers in India with less than 50% patients surviving past 5 years. Here, we report a whole transcriptome profile on a batch of GBSCC tumours with diverse tobacco usage habits. The study provides an entire landscape of altered expression with an emphasis on searching for targets with therapeutic potential. METHODS: Whole transcriptomes of 12 GBSCC tumours and adjacent normal tissues were sequenced and analysed to explore differential expression of genes. Expression changes were further compared with those in TCGA head and neck cohort (n = 263) data base and validated in an independent set of 10GBSCC samples. RESULTS: Differentially expressed genes (n = 2176) were used to cluster the patients based on their tobacco habits, resulting in 3 subgroups. Immune response was observed to be significantly aberrant, along with cell adhesion and lipid metabolism processes. Different modes of immune evasion were seen across 12 tumours with up-regulation or consistent expression of CD47, unlike other immune evasion genes such as PDL1, FUT4, CTLA4 and BTLA which were downregulated in a few samples. Variation in infiltrating immune cell signatures across tumours also indicates heterogeneity in immune evasion strategies. A few actionable genes such as ITGA4, TGFB1 and PTGS1/COX1 were over expressed in most samples. CONCLUSION: This study found expression deregulation of key immune evasion genes, such as CD47 and PDL1, and reasserts their potential as effective immunotherapeutic targets for GBSCC, which requires further clinical studies. Present findings reiterate the idea of using transcriptome profiling to guide precision therapeutic strategies.

Expression deregulation of mir31 and CXCL12 in two types of oral precancers and cancer: importance in progression of precancer and cancer.

Oral cancer generally progresses from precancerous lesions such as leukoplakia (LK), lichen planus (LP) and oral submucous fibrosis (OSMF). Since few of these precancers progress to cancers; it is worth to identify biological molecules that may play important roles in progression. Here, expression deregulation of 7 miRNAs (mir204, mir31, mir31*, mir133a, mir7, mir206 and mir1293) and their possible target genes in 23 cancers, 18 LK, 12 LP, 23 OSMF tissues compared to 20 healthy tissues was determined by qPCR method. Expression of mir7, mir31, mir31* and mir1293 was upregulated and that of mir133a, mir204 and mir206 was downregulated in cancer. Expression of most of these miRNAs was also upregulated in LK and LP tissues but not in OSMF. Expression deregulation of some of the target genes was also determined in cancer, LK and LP tissues. Significant upregulation of mir31 and downregulation of its target gene, CXCL12, in cancer, LK and LP tissues suggest their importance in progression of precancer to cancer. Expression upregulation of mir31 was also validated using GEO data sets. Although sample size is low, novelty of this work lies in studying expression deregulation of miRNAs and target genes in oral cancer and three types of precancerous lesions.

MicroRNA and target gene expression based clustering of oral cancer, precancer and normal tissues.

PURPOSE: Development of oral cancer is usually preceded by precancerous lesion. Despite histopathological diagnosis, development of disease specific biomarkers continues to be a promising field of study. Expression of miRNAs and their target genes was studied in oral cancer and two types of precancer lesions to look for disease specific gene expression patterns. METHODS: Expression of miR-26a, miR-29a, miR-34b and miR-423 and their 11 target genes were determined in 20 oral leukoplakia, 20 lichen planus and 20 cancer tissues with respect to 20 normal tissues using qPCR assay. Expression data were, then, used for cluster analysis of normal as well as disease tissues. RESULTS: Expression of miR-26a and miR-29a was significantly down regulated in leukoplakia and cancer tissues but up regulated in lichen planus tissues. Expression of target genes such as, ADAMTS7, ATP1B1, COL4A2, CPEB3, CDK6, DNMT3a and PI3KR1 was significantly down regulated in at least two of three disease types with respect to normal tissues. Negative correlations between expression levels of miRNAs and their targets were observed in normal tissues but not in disease tissues implying altered miRNA-target interaction in disease state. Specific expression profile of miRNAs and target genes formed separate clusters of normal, lichen planus and cancer tissues. CONCLUSION: Our results suggest that alterations in expression of selected miRNAs and target genes may play important roles in development of precancer to cancer. Expression profiles of miRNA and target genes may be useful to differentiate cancer and lichen planus from normal tissues, thereby bolstering their role in diagnostics.

Genome-wide mitochondrial DNA sequence variations and lower expression of OXPHOS genes predict mitochondrial dysfunction in oral cancer tissue.

Several studies reported that mtDNA mutations may play important roles in carcinogenesis although the mechanism is not clear yet. Most of the studies compared mtDNA sequences in a tumor with those in normal tissues from different individuals ignoring inter-individual variations. In this study, 271 SNPs, 7 novel SNPs (or SNVs), and 15 somatic mutations were detected in mtDNA of 8 oral cancer tissues with respect to reference (rCRS) and adjacent normal tissues, respectively, using Ion PGM next generation sequencing method. Most of the sequence variations (76 SNPs and 1 somatic) are present in D-loop region followed by CyB (36 SNPs), ATP6 (24 SNPs), ND5 (17 SNPs and 5 somatic), ND4 (18 coding and 2 somatic) and other non-coding and coding DNA sequences. A total of 53 and 8 non-synonymous SNPs and somatic mutations, respectively, were detected in tumor tissues and some of these variations may have deleterious effects on the protein function as predicted by bioinformatic analysis. Moreover, significantly low mtDNA contents and expression of several mitochondrial genes in tumor compared to adjacent normal tissues may have also affected mitochondrial functions. Taken together, this study suggests that mtDNA mutations as well as low expression of mtDNA coded genes may play important roles in tumor growth. Although the sample size is low, an important aspect of the study is the use of adjacent control tissues to find out somatic mutations and a change in the expression of mitochondrial genes, to rule out inter-individual and inter-tissue variations which are important issues in the study of mitochondrial genomics.

Association of DNA sequence variation in mitochondrial DNA polymerase with mitochondrial DNA synthesis and risk of oral cancer.

Enzymes responsible for mitochondrial (mt) DNA synthesis and transcription are encoded by nuclear genome and inherited mutations in these genes may play important roles in enhancing risk of precancer and cancer. Here, genetic variations in 23 functionally relevant tagSNPs in 6 genes responsible for mtDNA synthesis and transcription were studied in 522 cancer and 241 precancer (i.e. leukoplakia) patients and 525 healthy controls using Illumina Golden Gate assay to explore association with risk of oral precancer and cancer. Two SNPs, rs41553913 at POLRMT and rs9905016 at POLG2, significantly increased risk of oral leukoplakia and cancer, respectively, at both genotypic and allelic levels. Gene-environment interaction models also revealed that tobacco habits and SNPs at POLG2 and TFAM may modulate risk of both leukoplakia and cancer. In silico analysis of published data-set also revealed that variant heterozygote (TC) significantly increased transcription of POLG2 compared to wild genotype (p=0.03). Cancer tissues having variant allele genotypes (TC+CC) at POLG2 contained 1.6 times (p<0.01) more mtDNA compared to cancer tissues having wild genotype (TT). In conclusion, polymorphisms at POLG2 and POLRMT increased risk of oral cancer and leukoplakia, respectively, probably modulating synthesis and activity of the enzymes. Enhanced synthesis of mtDNA in cancer tissues may have implication in carcinogenesis, but the mechanism is yet to be explored.

A quest for miRNA bio-marker: a track back approach from gingivo buccal cancer to two different types of precancers.

Deregulation of miRNA expression may contribute to tumorigenesis and other patho-physiology associated with cancer. Using TLDA, expression of 762 miRNAs was checked in 18 pairs of gingivo buccal cancer-adjacent control tissues. Expression of significantly deregulated miRNAs was further validated in cancer and examined in two types of precancer (leukoplakia and lichen planus) tissues by primer-specific TaqMan assays. Biological implications of these miRNAs were assessed bioinformatically. Expression of hsa-miR-1293, hsa-miR-31, hsa-miR-31* and hsa-miR-7 were significantly up-regulated and those of hsa-miR-206, hsa-miR-204 and hsa-miR-133a were significantly down-regulated in all cancer samples. Expression of only hsa-miR-31 was significantly up-regulated in leukoplakia but none in lichen planus samples. Analysis of expression heterogeneity divided 18 cancer samples into clusters of 13 and 5 samples and revealed that expression of 30 miRNAs (including the above-mentioned 7 miRNAs), was significantly deregulated in the cluster of 13 samples. From database mining and pathway analysis it was observed that these miRNAs can significantly target many of the genes present in different cancer related pathways such as "proteoglycans in cancer", PI3K-AKT etc. which play important roles in expression of different molecular features of cancer. Expression of hsa-miR-31 was significantly up-regulated in both cancer and leukoplakia tissues and, thus, may be one of the molecular markers of leukoplakia which may progress to gingivo-buccal cancer.

Association between risk of oral precancer and genetic variations in microRNA and related processing genes.

BACKGROUND: MicroRNAs have been implicated in cancer but studies on their role in precancer, such as leukoplakia, are limited. Sequence variations at eight miRNA and four miRNA processing genes were studied in 452 healthy controls and 299 leukoplakia patients to estimate risk of disease. RESULTS: Genotyping by TaqMan assay followed by statistical analyses showed that variant genotypes at Gemin3 and mir-34b reduced risk of disease [OR = 0.5(0.3-0.9) and OR = 0.7(0.5-0.9) respectively] in overall patients as well as in smokers [OR = 0.58(0.3-1) and OR = 0.68(0.5-0.9) respectively]. Among chewers, only mir29a significantly increased risk of disease [OR = 1.8(1-3)]. Gene-environment interactions using MDR-pt program revealed that mir29a, mir34b, mir423 and Xpo5 modulated risk of disease (p < 0.002) which may be related to change in expression of these genes as observed by Real-Time PCR assays. But association between polymorphisms and gene expressions was not found in our sample set as well as in larger datasets from open access platforms like Genevar and 1000 Genome database. CONCLUSION: Variations in microRNAs and their processing genes modulated risk of precancer but further in-depth study is needed to understand mechanism of disease process.

Genetic variations at microRNA and processing genes and risk of oral cancer.

Genetic variations at microRNA and microRNA processing genes are known to confer risk of cancer in different populations. Here, we studied variations at eight microRNA (miRNA) and four miRNA processing genes in 452 controls and 451 oral cancer patients by TaqMan genotyping assays. Variant allele-containing genotypes at mir-196a2 and variant allele homozygous genotype at Ran increased the risk of cancer significantly [adjusted odds ratio (OR) (95% confidence interval (CI)) = 1.3 (1-1.7) and 2.3 (1.1-4.6), respectively]. Conversely, variant allele-containing genotypes at mir-34b and variant allele homozygous genotype at Gemin3 reduced the risk of cancer significantly [adjusted OR (95% CI) = 0.7 (0.5-0.9) and 0.6 (0.4-1), respectively]. Cumulative risk was also increased by three times with increase in the number of risk alleles at these four loci. In tobacco stratified analysis, variant allele homozygous genotypes at mir-29a and Ran increased [adjusted OR (95% CI) = 1.5 (1-2.3) and 3 (1.1-8.4) respectively], while variant allele-containing genotypes at mir-34b decreased [adjusted OR (95% CI) = 0.6 (0.4-0.9)] the risk of cancer significantly. Thus, genetic variation at miRNA and processing genes altered the risk of oral cancer in this population thereby corroborating studies in other populations. However, it is necessary to validate this result in different Indian sub populations with larger sample sizes and examine the effect of these variations in tumour tissues to explain the mechanism of risk alteration.

Single nucleotide polymorphism network: a combinatorial paradigm for risk prediction.

Risk prediction for a particular disease in a population through SNP genotyping exploits tests whose primary goal is to rank the SNPs on the basis of their disease association. This manuscript reveals a different approach of predicting the risk through network representation by using combined genotypic data (instead of a single allele/haplotype). The aim of this study is to classify diseased group and prediction of disease risk by identifying the responsible genotype. Genotypic combination is chosen from five independent loci present on platelet receptor genes P2RY1 and P2RY12. Genotype-sets constructed from combinations of genotypes served as a network input, the network architecture constituting super-nodes (e.g., case and control) and nodes representing individuals, each individual is described by a set of genotypes containing M markers (M = number of SNP). The analysis becomes further enriched when we consider a set of networks derived from the parent network. By maintaining the super-nodes identical, each network is carrying an independent combination of M-1 markers taken from M markers. For each of the network, the ratio of case specific and control specific connections vary and the ratio of super-node specific connection shows variability. This method of network has also been applied in another case-control study which includes oral cancer, precancer and control individuals to check whether it improves presentation and interpretation of data. The analyses reveal a perfect segregation between super-nodes, only a fraction of mixed state being connected to both the super-nodes (i.e. common genotype set). This kind of approach is favorable for a population to classify whether an individual with a particular genotypic combination can be in a risk group to develop disease. In addition with that we can identify the most important polymorphism whose presence or absence in a population can make a large difference in the number of case and control individuals.