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Quitting smoking could potentially minimize the risk of a high neutrophil-to-lymphocyte ratio (NLR) among tobacco use-related (TUR) cancer survivors. A total of 1263 TUR cancer survivors aged 20 to 85 years old were investigated using data from the National Health and Nutritional Examination Survey 1999–2018. The primary outcome was the NLR, which was defined as having two levels: high-risk (≥ 3) and low-risk (p = 0.01) compared to NHB nonsmokers (n = 139). These findings suggest that the risk of a high NLR level is strongly associated with the time of smoking cessation in NHB TUR cancer survivors. As a result, NHB TUR cancer survivors should quit smoking as soon as possible because the benefits of quitting smoking were observed over the 5 year period following smoking cessation.

The common management practices of dairy calves leads to increased starch concentration in feed, which subsequently may cause rumen acidosis while on milk and during weaning. Until recently, few attempts were undertaken to understand the health risks of prolonged ruminal acidosis in post weaning calves. Resultantly, the molecular changes in the digestive tracts in post-weaning calves with ruminal acidosis remain largely unexplored. In this study, we investigated the liver transcriptome changes along with its correlation with the rumen microbial rRNA expression changes in young calves using our model of feed induced ruminal acidosis. In this model, new born calves were fed a highly processed, starch-rich diet starting from one week of age through 16 weeks. A total of eight calves were involved in this study. Four of them were fed the acidosis-inducing diet (Treated) and the rest of the four were fed a standard starter diet (Control). Liver and rumen epithelial tissues were collected at necropsy at 17 weeks of age. Transcriptome analyses were carried out in the liver tissues and rRNA meta-transcriptome analysis were done using the rumen epithelial tissues. The correlation analysis was performed by comparing the liver mRNA expression with the rumen epithelial rRNA abundance at genus level. Calves with induced ruminal acidosis had significantly lower ruminal pH in comparison to the control group, in addition to significantly less weight-gain over the course of the experiment. In liver tissues, a total of 428 differentially expressed genes (DEGs) (fold-change, FC ≥ 1.5; adjusted P ≤ 0.1) were identified in treated group in comparison to control. Biological pathways enriched by these DEGs included cellular component organization, indicating the impact of ruminal acidosis on liver development in young calves. Specifically, the up-regulated genes were enriched in acute phase response (P P P ≪ 0.001), indicating the liver’s response to feed induced acidosis at the transcriptome level. Twelve transferase activity related genes had significant correlation with rumen microbial rRNA expression changes. Among these genes, two up-regulated genes were reported with involvement in lipid metabolism in the liver, implying the direct effect of feed-induced acidosis on both the rumen microbial community and liver metabolism. Our study provides insight into the physiological remodeling in the liver resultant from the prolonged acidosis in post weaning calves, which may facilitate future RNA-seq based diagnosis and precision management of rumen acidosis in dairy calves.

Many common management practices used to raise dairy calves while on milk and during weaning can cause rumen acidosis. Ruminal pH has long been used to identify ruminal acidosis. However, few attempts were undertaken to understand the role of prolonged ruminal acidosis on rumen microbial community or host health in young calves long after weaning. Thus, the molecular changes associated with prolonged rumen acidosis in post weaning young calves are largely unknown. In this study, we induced ruminal acidosis by feeding a highly processed, starch-rich diet to calves starting from one week of age through 16 weeks. Rumen epithelial tissues were collected at necropsy at 17 weeks of age. Transcriptome analyses on the rumen epithelium and meta-transcriptome analysis of rumen epimural microbial communities were carried out. Calves with induced ruminal acidosis showed significantly less weight gain over the course of the experiment, in addition to substantially lower ruminal pH in comparison to the control group. For rumen epithelial transcriptome, a total of 672 genes (fold-change, FC ≥ 1.5; adjusted-p ≤ 0.05) showed significant differential expression in comparison to control. Biological pathways impacted by these differentially expressed genes included cell signaling and morphogenesis, indicating the impact of ruminal acidosis on rumen epithelium development. rRNA read-based microbial classification indicated significant increase in abundance of several genera in calves with induced acidosis. Our study provides insight into host rumen transcriptome changes associated with prolonged acidosis in post weaning calves. Shifts in microbial species abundance are promising for microbial species-based biomarker development and artificial manipulation. Such knowledge provides a foundation for future more precise diagnosis and preventative management of rumen acidosis in dairy calves.

In mammals, microbial colonization of the digestive tract (GIT) occurs right after birth by several bacterial phyla. Numerous human and mouse studies have reported the importance of early gut microbial inhabitants on host health. However, few attempts have been undertaken to directly interrogate the role of early gut/rumen microbial colonization on GIT development or host health in neonatal ruminants through artificial manipulation of the rumen microbiome. Thus, the molecular changes associated with bacterial colonization are largely unknown in cattle. In this study, we dosed young calves with exogenous rumen fluid obtained from an adult donor cow, starting at birth, and repeated every other week until six weeks of age. Eight Holstein bull calves were included in this study and were separated into two groups of four: the first group was treated with rumen content freshly extracted from an adult cow, and the second group was treated with sterilized rumen content. Using whole-transcriptome RNA-sequencing, we investigated the transcriptional changes in the host liver, which is a major metabolic organ and vital to the calf’s growth performance. Additionally, the comparison of rumen epimural microbial communities between the treatment groups was performed using the rRNA reads generated by sequencing. Liver transcriptome changes were enriched with genes involved in cell signaling and protein phosphorylation. Specifically, up-regulation of SGPL1 suggests a potential increase in the metabolism of sphingolipids, an essential molecular signal for bacterial survival in digestive tracts. Notably, eight genera, belonging to four phyla, had significant increases in abundance in treated calves. Our study provides insight into host liver transcriptome changes associated with early colonization of the microbial communities in neonatal calves. Such knowledge provides a foundation for future probiotics-based research in microbial organism mediated rumen development and nutrition in ruminants.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

The causes underlying racial disparities in cancer are multifactorial. In addition to socioeconomic issues, biological factors may contribute to these inequities, especially in disease incidence and patient survival. To date, there have been few studies that relate the disparities in these aspects to genetic aberrations. In this work, we studied the impacts of race on the patient survival and tumor mutation burden using the data released by the Cancer Genome Atlas (TCGA). The potential relationship between mutation burden and disease incidence is further inferred by an integrative analysis of TCGA data and the data from the Surveillance, Epidemiology, and End Results (SEER) Program. The results show that disparities are present (p r = 0.46, p r = 0.88, p

Patients with HPV-positive head neck squamous cell carcinomas (HNSCC) usually have a better prognosis than the HPV-negative cases while the underlying mechanism remains far from being well understood. We investigated this issue by an integrative analysis of clinically-annotated multi-omics HNSCC data released by the Cancer Genome Atlas. As confirmatory results, we found: (1) Co-occurrence of mutant TP53 and HPV infection was rare; (2) Regardless of HPV status, HNSCCs of wild-type TP53 implied a good survival chance for patients and had fewer genome-wide somatic mutations than those with a mutation burden on the gene. Our analysis further led to some novel observations. They included: (1) The genes involved in “DNA mismatch repair” pathway were up-regulated in HPV-positive tumors compared to normal tissue samples and HPV-negative cases, and thus constituted a strong predictive signature for the identification of HPV infection; (2) HPV infection could disrupt some regulatory miRNA-mRNA correlations operational in the HPV-negative tumors. In light of these results, we proposed a hypothesis for the favorable clinical outcomes of HPV-positive HNSCC patients. That is, the replication of HPV genome and/or its invasion into the genomes of cancer cells may enhance DNA repair mechanisms, which in turn limit the accumulation of lethal somatic mutations.

The count of the nucleotides in a cloned, short genomic sequence has become an important criterion to annotate such a sequence as a miRNA molecule. While the majority of human mature miRNA sequences consist of 22 nucleotides, there exists discrepancy in the characteristic lengths of the miRNA sequences. There is also a lack of systematic studies on such length distribution and on the biological factors that are related to or may affect this length. In this paper, we intend to fill this gap by investigating the sequence structure of human miRNA molecules using statistics tools. We demonstrate that the traditional discrete probability distributions do not model the length distribution of the human mature miRNAs well, and we obtain the statistical distribution model with a decent fit. We observe that the four nucleotide bases in a miRNA sequence are not randomly distributed, implying that possible structural patterns such as dinucleotide (trinucleotide or higher order) may exist. Furthermore, we study the relationships of this length distribution to multiple important factors such as evolutionary conservation, tumorigenesis, the length of precursor loop structures, and the number of predicted targets. The association between the miRNA sequence length and the distributions of target site counts in corresponding predicted genes is also presented. This study results in several novel findings worthy of further investigation that include: (1) rapid evolution introduces variation to the miRNA sequence length distribution; (2) miRNAs with extreme sequence lengths are unlikely to be cancer-related; and (3) the miRNA sequence length is positively correlated to the precursor length and the number of predicted target genes.

Recent studies have shown the contribution of miRNAs to cancer pathogenesis. Prostate cancer is the most commonly diagnosed cancer in men. Unlike other major types of cancer, no single gene has been identified as being mutated in the majority of prostate tumors. This implies that the expression profiling of genes, including the non-coding miRNAs, may substantially vary across individual cases of this cancer. The within-class variability makes it possible to reconstruct or infer disease-specific miRNA-mRNA correlation and regulatory modular networks using high-dimensional microarray data of prostate tumor samples. Furthermore, since miRNAs and tumor suppressor genes are usually tissue specific, miRNA-mRNA modules could potentially differ between primary prostate cancer (PPC) and metastatic prostate cancer (MPC). We herein performed an in silico analysis to explore the miRNA-mRNA correlation network modules in the two tumor subtypes. Our analysis identified 5 miRNA-mRNA module pairs (MPs) for PPC and MPC, respectively. Each MP includes one positive-connection (correlation) module and one negative-connection (correlation) module. The number of miRNAs or mRNAs (genes) in each module varies from 2 to 8 or from 6 to 622. The modules discovered for PPC are more informative than those for MPC in terms of the implicated biological insights. In particular, one negative-connection module in PPC fits well with the popularly recognized miRNA-mediated post-transcriptional regulation theory. That is, the 3'UTR sequences of the involved mRNAs (∼620) are enriched with the target site motifs of the 7 modular miRNAs, has-miR-106b, -191, -19b, -92a, -92b, -93, and -141. About 330 GO terms and KEGG pathways, including TGF-beta signaling pathway that maintains tissue homeostasis and plays a crucial role in the suppression of the proliferation of cancer cells, are over-represented (adj.p

In metazoans, miRNAs regulate gene expression primarily through binding to target sites in the 3′ UTRs (untranslated regions) of messenger RNAs (mRNAs). Cis-acting variants within, or close to, a gene are crucial in explaining the variability of gene expression measures. Single nucleotide polymorphisms (SNPs) in the 3′ UTRs of genes can affect the base-pairing between miRNAs and mRNAs, and hence disrupt existing target sites (in the reference sequence) or create novel target sites, suggesting a possible mechanism for cis regulation of gene expression. Moreover, because the alleles of different SNPs within a DNA sequence of limited length tend to be in strong linkage disequilibrium (LD), we hypothesize the variants of miRNA target sites caused by SNPs potentially function as bridges linking the documented cis-SNP markers to the expression of the associated genes. A large-scale analysis was herein performed to test this hypothesis. By systematically integrating multiple latest information sources, we found 21 significant gene-level SNP-involved miRNA-mediated post-transcriptional regulation modules (SNP-MPRMs) in the form of SNP-miRNA-mRNA triplets in lymphocyte cell lines for the CEU and YRI populations. Among the cognate genes, six including ALG8, DGKE, GNA12, KLF11, LRPAP1, and MMAB are related to multiple genetic diseases such as depressive disorder and Type-II diabetes. Furthermore, we found that ∼35% of the documented transcript intensity-related cis-SNPs (∼950) in a recent publication are identical to, or in significant linkage disequilibrium (LD) (p

Somatic mutation accumulation is a major cause of abnormal cell growth. However, some mutations in cancer cells may be deleterious to the survival and proliferation of the cancer cells, thus offering a protective effect to the patients. We investigated this hypothesis via a unique analysis of the clinical and somatic mutation datasets of ovarian carcinomas published by the Cancer Genome Atlas. We defined and screened 562 macro mutation signatures (MMSs) for their associations with the overall survival of 320 ovarian cancer patients. Each MMS measures the number of mutations present on the member genes (except for TP53) covered by a specific Gene Ontology (GO) term in each tumor. We found that somatic mutations favorable to the patient survival are predominant in ovarian carcinomas compared to those indicating poor clinical outcomes. Specially, we identified 19 (3) predictive MMSs that are, usually by a nonlinear dose-dependent effect, associated with good (poor) patient survival. The false discovery rate for the 19 "positive" predictors is at the level of 0.15. The GO terms corresponding to these MMSs include "lysosomal membrane" and "response to hypoxia", each of which is relevant to the progression and therapy of cancer. Using these MMSs as features, we established a classification tree model which can effectively partition the training samples into three prognosis groups regarding the survival time. We validated this model on an independent dataset of the same disease (Log-rank p-value < 2.3 × 10(-4)) and a dataset of breast cancer (Log-rank p-value < 9.3 × 10(-3)). We compared the GO terms corresponding to these MMSs and those enriched with expression-based predictive genes. The analysis showed that the GO term pairs with large similarity are mainly pertinent to the proteins located on the cell organelles responsible for material transport and waste disposal, suggesting the crucial role of these proteins in cancer mortality.

Single-nucleotide polymorphisms (SNPs) contribute to the between-individual expression variation of many genes. A regulatory (trait-associated) SNP is usually located near or within a (host) gene, possibly influencing the gene’s transcription or/and post-transcriptional modification. But its targets may also include genes that are physically farther away from it. A heuristic explanation of such multiple-target interferences is that the host gene transfers the SNP genotypic effects to the distant gene(s) by a transcriptional or signaling cascade. These connections between the host genes (regulators) and the distant genes (targets) make the genetic analysis of gene expression traits a promising approach for identifying unknown regulatory relationships. In this study, through a mixed model analysis of multi-source digital expression profiling for 140 human lymphocyte cell lines (LCLs) and the genotypes distributed by the international HapMap project, we identified 45 thousands of potential SNP-induced regulatory relationships among genes (the significance level for the underlying associations between expression traits and SNP genotypes was set at FDR < 0.01). We grouped the identified relationships into four classes (paradigms) according to the two different mechanisms by which the regulatory SNPs affect their cis- and trans- regulated genes, modifying mRNA level or altering transcript splicing patterns. We further organized the relationships in each class into a set of network modules with the cis- regulated genes as hubs. We found that the target genes in a network module were often characterized by significant functional similarity, and the distributions of the target genes in three out of the four networks roughly resemble a power-law, a typical pattern of gene networks obtained from mutation experiments. By two case studies, we also demonstrated that significant biological insights can be inferred from the identified network modules.