GWAS in cancer: progress and challenges

Rare variant association studies: Significance, methods, and applications in chronic pain studies

Rare genetic variants, characterized by their low frequency in a population, have emerged as essential components in the study of complex disease genetics. The biology of rare variants underscores their significance, as they can exert profound effects on phenotypic variation and disease susceptibility. Recent advancements in sequencing technologies have yielded the availability of large-scale sequencing data such as the UK Biobank whole-exome sequencing (WES) cohort empowered researchers to conduct rare variant association studies (RVASs). This review paper discusses the significance of rare variants, available methodologies, and applications. We provide an overview of RVASs, emphasizing their relevance in unraveling the genetic architecture of complex diseases with special focus on chronic pain and Arthritis. Additionally, we discuss the strengths and limitations of various rare variant association testing methods, outlining a typical pipeline for conducting rare variant association. This pipeline encompasses crucial steps such as quality control of WES data, rare variant annotation, and association testing. It serves as a comprehensive guide for researchers in the field of chronic pain diseases interested in rare variant association studies in large-scale sequencing datasets like the UK Biobank WES cohort. Lastly, we discuss how the identified variants can be further investigated through detailed experimental studies in animal models to elucidate their functional impact and underlying mechanisms.

Methodologies underpinning polygenic risk scores estimation: a comprehensive overview

Polygenic risk scores (PRS) have emerged as a promising tool for predicting disease risk and treatment outcomes using genomic data. Thousands of genome-wide association studies (GWAS), primarily involving populations of European ancestry, have supported the development of PRS models. However, these models have not been adequately evaluated in non-European populations, raising concerns about their clinical validity and predictive power across diverse groups. Addressing this issue requires developing novel risk prediction frameworks that leverage genetic characteristics across diverse populations, considering host-microbiome interactions and a broad range of health measures. One of the key aspects in evaluating PRS is understanding the strengths and limitations of various methods for constructing them. In this review, we analyze strengths and limitations of different methods for constructing PRS, including traditional weighted approaches and new methods such as Bayesian and Frequentist penalized regression approaches. Finally, we summarize recent advances in PRS calculation methods development, and highlight key areas for future research, including development of models robust across diverse populations by underlining the complex interplay between genetic variants across diverse ancestral backgrounds in disease risk as well as treatment response prediction. PRS hold great promise for improving disease risk prediction and personalized medicine; therefore, their implementation must be guided by careful consideration of their limitations, biases, and ethical implications to ensure that they are used in a fair, equitable, and responsible manner.

Reproductive decision-making in cancer susceptibility syndromes

Cancer susceptibility syndromes confer an increased lifetime risk of cancer and occur due to germline likely-pathogenic or pathogenic variants in a cancer susceptibility gene. Clinical Genetics services advise patients of ways to manage their future cancer risks, often prefaced with uncertainties due to poor understandings of individualised risk. For individuals/couples whose future offspring are at risk of a cancer susceptibility syndrome, different options are available depending on their preferences and circumstances, including prenatal diagnosis and preimplantation genetic testing. This review provides an overview of the most common cancer susceptibility syndromes, available reproductive options and a genetic counselling framework recommended to support individuals/couples in their decision-making. We describe complexities of decision-making involving moderate penetrance and sex-specific variable penetrance genes and explore associated ethical issues arising in this complex area of medicine.

Combination of transcriptome and Mendelian inheritance reveals novel prognostic biomarker of CTLA-4-related lncRNAs and protective role of nitrogen metabolism pathway in lung adenocarcinoma development

OBJECTIVE

Since in the cancer setting, tumor cells may use cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to evade the immune system. This study aimed to identify CTLA-4-related long non-coding RNAs (lncRNAs) and assess their roles in lung adenocarcinoma (LUAD) development.

METHODS

Clinical and genomic data were obtained from The Cancer Genome Atlas (TCGA), MSigDB and Gene Weaver. CTLA-4-related lncRNA-based gene signatures (CTLA4LncSigs) were identified using Cox regression, establishing a risk score model and an independent prognostic model. Enrichment analysis (GO/KEGG) was performed. Mendelian randomization (MR) analysis investigated the nitrogen metabolism and lung cancer relationship, with Bayesian weighted MR (BWMR) addressing uncertainties. Correlations with tumor microenvironment and drug sensitivity were explored.

RESULTS

Nineteen CTLA4LncSigs significantly influenced LUAD prognosis. The risk score demonstrated independence as a prognostic factor. Functional analysis revealed lncRNAs' impact on nitrogen metabolism. MR and BWMR confirmed the protective role of the nitrogen metabolism pathway in lung cancer.

CONCLUSION

Our study identifies CTLA-4-related lncRNAs associated with LUAD prognosis and uncovers a previously undiscovered protective role of the nitrogen metabolism pathway in combating LUAD development, providing new insights into potential therapeutic targets and prognostic biomarkers for this aggressive cancer subtype.

The intricate dance of tumor evolution: Exploring immune escape, tumor migration, drug resistance, and treatment strategies

Recent research has unveiled fascinating insights into the intricate mechanisms governing tumor evolution. These studies have illuminated how tumors adapt and proliferate by exploiting various factors, including immune evasion, resistance to therapeutic drugs, genetic mutations, and their ability to adapt to different environments. Furthermore, investigations into tumor heterogeneity and chromosomal aberrations have revealed the profound complexity that underlies the evolution of cancer. Emerging findings have also underscored the role of viral influences in the development and progression of cancer, introducing an additional layer of complexity to the field of oncology. Tumor evolution is a dynamic and complex process influenced by various factors, including immune evasion, drug resistance, tumor heterogeneity, and viral influences. Understanding these elements is indispensable for developing more effective treatments and advancing cancer therapies. A holistic approach to studying and addressing tumor evolution is crucial in the ongoing battle against cancer. The main goal of this comprehensive review is to explore the intricate relationship between tumor evolution and critical aspects of cancer biology. By delving into this complex interplay, we aim to provide a profound understanding of how tumors evolve, adapt, and respond to treatment strategies. This review underscores the pivotal importance of comprehending tumor evolution in shaping effective approaches to cancer treatment.

Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease

Both cancer and cardio-metabolic disease disparities exist among specific populations in the US. For example, African Americans experience the highest rates of breast and prostate cancer mortality and the highest incidence of obesity. Native and Hispanic Americans experience the highest rates of liver cancer mortality. At the same time, Pacific Islanders have the highest death rate attributed to type 2 diabetes (T2D), and Asian Americans experience the highest incidence of non-alcoholic fatty liver disease (NAFLD) and cancers induced by infectious agents. Notably, the pathologic progression of both cancer and cardio-metabolic diseases involves innate immunity and mechanisms of inflammation. Innate immunity in individuals is established through genetic inheritance and external stimuli to respond to environmental threats and stresses such as pathogen exposure. Further, individual genomes contain characteristic genetic markers associated with one or more geographic ancestries (ethnic groups), including protective innate immune genetic programming optimized for survival in their corresponding ancestral environment(s). This perspective explores evidence related to our working hypothesis that genetic variations in innate immune genes, particularly those that are commonly found but unevenly distributed between populations, are associated with disparities between populations in both cancer and cardio-metabolic diseases. Identifying conventional and unconventional innate immune genes that fit this profile may provide critical insights into the underlying mechanisms that connect these two families of complex diseases and offer novel targets for precision-based treatment of cancer and/or cardio-metabolic disease.

Identify Candidate Genes Associated with the Weight and Egg Quality Traits in Wenshui Green Shell-Laying Chickens by the Copy Number Variation-Based Genome-Wide Association Study

Copy number variation (CNV), as an essential source of genetic variation, can have an impact on gene expression, genetic diversity, disease susceptibility, and species evolution in animals. To better understand the weight and egg quality traits of chickens, this paper aimed to detect CNVs in Wenshui green shell-laying chickens and conduct a copy number variation regions (CNVRs)-based genome-wide association study (GWAS) to identify variants and candidate genes associated with their weight and egg quality traits to support related breeding efforts. In our paper, we identified 11,035 CNVRs in Wenshui green shell-laying chickens, which collectively spanned a length of 13.1 Mb, representing approximately 1.4% of its autosomal genome. Out of these CNVRs, there were 10,446 loss types, 491 gain types, and 98 mixed types. Notably, two CNVRs showed significant correlations with egg quality, while four CNVRs exhibited significant associations with body weight. These significant CNVRs are located on chromosome 4. Further analysis identified potential candidate genes that influence weight and egg quality traits, including FAM184B, MED28, LAP3, ATOH8, ST3GAL5, LDB2, and SORCS2. In this paper, the CNV map of the Wenshui green shell-laying chicken genome was constructed for the first time through population genotyping. Additionally, CNVRs can be employed as molecular markers to genetically improve chickens' weight and egg quality traits.

Genomic Variants and Worldwide Epidemiology of Breast Cancer: A Genome-Wide Association Studies Correlation Analysis

Breast cancer (BCa) is the most common cancer and leading cause of cancer death among women globally. This can be explained by the genetic factor of this disease. This article aims to correlate the epidemiological data, worldwide incidence, and mortality of BCa with the Single-Nucleotide Polymorphisms (SNPs) associated with the susceptibility and severity in different populations. Two hundred and forty genetic variants associated with BCa susceptibility/severity were selected from the literature through Genome-Wide Association Studies (GWAS). The allele frequencies were obtained from the 1000 Genomes Project, and the epidemiological data were obtained from the World Health Organization (WHO). The BCa incidence, mortality rates, and allele frequencies of the variants were evaluated using Pearson's correlation. Our study demonstrated that 11 SNPs (rs3817578, rs4843437, rs3754934, rs61764370, rs780092, rs2290203, rs10411161, rs6001930, rs16886165, rs8051542 and rs4973768) were significantly correlated with the epidemiological data in different ethnic groups. Seven polymorphisms (rs3817578, rs3754934, rs780092, rs2290203, rs10411161, rs6001930 and rs16886165) were inversely correlated with the incidence rate and four polymorphisms (rs4843437, rs61764370, rs8051542 and rs4973768) were directly correlated with the incidence rate. African and South-East Asian populations have a lower risk of developing BCa when evaluated in terms of genetic factors since they possess variants characterized as protective, as their higher incidence is associated with a lower frequency of BCa cases. The genetic variants investigated here are likely to predispose individuals to BCa. The genetic study described here is promising for implementing personalized strategies to screen for breast cancer in diverse populations.

The largest genome-wide association study for breast cancer in Taiwanese Han population

PURPOSE

Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap.

METHODS

A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched.

RESULTS

The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79-7.66) and 3.55 (2.13-6.14), respectively.

CONCLUSION

In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women.

Causal association between inflammatory bowel disease and 32 site-specific extracolonic cancers: a Mendelian randomization study

BACKGROUND

The risk of extracolonic cancer is increased in inflammatory bowel disease (IBD) patients, but it is not clear whether there is a causal relationship. We aimed to systematically estimate the causal relationship between IBD and extracolonic cancers.

METHODS

Independent genetic variants strongly associated with IBD were extracted as instrumental variables from genome-wide association study (GWAS) conducted by the International IBD Genetics Consortium including 12,882 IBD patients, 5956 Crohn's disease (CD) patients, and 6968 ulcerative colitis (UC) patients. Three sources of cancer GWAS were selected as outcome data. Two-sample Mendelian randomization (MR) analysis was conducted to assess the causal effects of IBD on 32 extracolonic cancers. The meta-analysis was applied to assess the combined causal effect with multiple MR results.

RESULTS

IBD, CD, and UC have potential causal associations with oral cavity cancer (IBD: OR = 1.180, 95% CI: 1.059 to 1.316, P = 0.003; CD: OR = 1.112, 95% CI: 1.008 to 1.227, P = 0.034; UC: OR = 1.158, 95% CI: 1.041 to 1.288, P = 0.007). Meta-analysis showed a significant positive causal relationship between IBD and breast cancer (OR = 1.059; 95% CI: 1.033 to 1.086; P < 0.0001) as well as a potential causal relationship between CD and breast cancer (OR = 1.029; 95% CI: 1.002 to 1.055; P = 0.032) based on combining multiple MR results.

CONCLUSIONS

This comprehensive MR analysis suggested that genetically predicted IBD, as well as its subtypes, may be a risk factor in the development of oral cavity and breast cancer.

Heritable Traits and Lung Cancer Risk: A Two-Sample Mendelian Randomization Study

INTRODUCTION

Lung cancer is a complex polygenic disorder. Analysis with Mendelian randomization (MR) allows for genetically predicted risks to be estimated between exposures and outcomes.

METHODS

We analyzed 345 heritable traits from the United Kingdom Biobank and estimated their associated effects on lung cancer outcomes using two sample MR. In addition to estimating effects with overall lung cancer, adenocarcinoma, small cell lung cancer, and squamous cell lung cancers, we performed conditional effect modeling with multivariate MR (MVMR) and the traits of alcohol use, smoking initiation, average pre-tax income, and educational attainment.

RESULTS

Univariate MR provided evidence for increased age at first sexual intercourse (OR, 0.55; P = 6.15 × 10-13), educational attainment (OR, 0.24; P = 1.07 × 10-19), average household income (OR, 0.58; P = 7.85 × 10-05), and alcohol usually taken with meals (OR, 0.19; P = 1.06 × 10-06) associating with decreased odds of overall lung cancer development. In contrast, a lack of additional educational attainment (OR, 8.00; P = 3.48 × 10-12), body mass index (OR, 1.28; P = 9.00 × 10-08), pack years smoking as a proportion of life span (OR, 9.93; P = 7.96 × 10-12), and weekly beer intake (OR, 3.48; P = 4.08 × 10-07) were associated with an increased risk of overall lung cancer development.

CONCLUSIONS

Many heritable traits associated with an increased or inverse risk of lung cancer development. Effects vary based on histologic subtype and conditional third trait exposures.

IMPACT

We identified several heritable traits and presented their genetically predictable impact on lung cancer development, providing valuable insights for consideration.

A two-stage genome-wide association study identified four potential early-onset nonsmall cell lung cancer risk loci based on 26,652 participants in Chinese population

Early-onset lung cancer is rare with an increasing incidence rate. Although several genetic variants have been identified for it with candidate gene approaches, no genome-wide association study (GWAS) has been reported. In this study, a two-stage strategy was adopted: firstly we performed a GWAS to identify variants associated with early-onset nonsmall-cell lung cancer (NSCLC) risk using 2556 cases (age ≤ 50 years) and 13,327 controls by logistic regression model. To further discriminate younger cases from older ones, we took a case-case analysis for the promising variants with above early-onset cases and 10,769 cases (age > 50 years) by Cox regression model. After combining these results, we identified four early-onset NSCLC susceptibility loci at 5p15.33 (rs2853677, odds ratio [OR] = 1.48, 95% confidence interval [CI]: 1.36-1.60, Pcase-control  = 3.58 × 10-21 ; hazard ratio [HR] = 1.10, 95% CI: 1.04-1.16, Pcase-case  = 6.77 × 10-4 ), 5p15.1 (rs2055817, OR = 1.24, 95% CI: 1.15-1.35, Pcase-control  = 1.39 × 10-7 ; HR = 1.08, 95% CI: 1.02-1.14, Pcase-case  = 6.90 × 10-3 ), 6q24.2 (rs9403497, OR = 1.24, 95% CI: 1.15-1.35, Pcase-control  = 1.61 × 10-7 ; HR = 1.11, 95% CI: 1.05-1.17, Pcase-case  = 3.60 × 10-4 ) and 12q14.3 (rs4762093, OR = 1.31, 95% CI: 1.18-1.45, Pcase-control  = 1.90 × 10-7 ; HR = 1.10, 95% CI: 1.03-1.18, Pcase-case  = 7.49 × 10-3 ). Except for 5p15.33, other loci were found to be associated with NSCLC risk for the first time. All of them had stronger effects in younger patients than in older ones. These results provide a promising overview for early-onset NSCLC genetics.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma

INTRODUCTION

Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer.

AREAS COVERED

Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity.

EXPERT OPINION

Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.

Computational screening and analysis of deleterious nsSNPs in human p14ARF (CDKN2A gene) protein using molecular dynamic simulation approach

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments.Communicated by Ramaswamy H. Sarma.

Zinc Finger Protein 90 Knockdown Promotes Cisplatin Sensitivity via Nrf2/HO-1 Pathway in Ovarian Cancer Cell

Our study discussed the role of Zfp90 in ovarian cancer (OC) cell lines' sensitivity to cisplatin. We used two OC cell lines, SK-OV-3 and ES-2, to evaluate their role in cisplatin sensitization. The protein levels of p-Akt, ERK, caspase 3, Bcl-2, Bax, E-cadherin, MMP-2, MMP-9 and other drug resistance-related molecules, including Nrf2/HO-1, were discovered in the SK-OV-3 and ES-2 cells. We also used a human ovarian surface epithelial cell to compare the effect of Zfp90. Our outcomes indicated that cisplatin treatment generates reactive oxygen species (ROS) that modulate apoptotic protein expression. The anti-oxidative signal was also stimulated, which could hinder cell migration. The intervention of Zfp90 could greatly improve the apoptosis pathway and block the migrative pathway to regulate the cisplatin sensitivity in the OC cells. This study implies that the loss of function of Zfp90 might promote cisplatin sensitization in OC cells via regulating the Nrf2/HO-1 pathway to enhance cell apoptosis and inhibit the migrative effect in both SK-OV-3 and ES-2 cells.

Why does the X chromosome lag behind autosomes in GWAS findings?

The X-chromosome is among the largest human chromosomes. It differs from autosomes by a number of important features including hemizygosity in males, an almost complete inactivation of one copy in females, and unique patterns of recombination. We used data from the Catalog of Published Genome Wide Association Studies to compare densities of the GWAS-detected SNPs on the X-chromosome and autosomes. The density of GWAS-detected SNPs on the X-chromosome is 6-fold lower compared to the density of the GWAS-detected SNPs on autosomes. Differences between the X-chromosome and autosomes cannot be explained by differences in the overall SNP density, lower X-chromosome coverage by genotyping platforms or low call rate of X-chromosomal SNPs. Similar differences in the density of GWAS-detected SNPs were found in female-only GWASs (e.g. ovarian cancer GWASs). We hypothesized that the lower density of GWAS-detected SNPs on the X-chromosome compared to autosomes is not a result of a methodological bias, e.g. differences in coverage or call rates, but has a real underlying biological reason-a lower density of functional SNPs on the X-chromosome versus autosomes. This hypothesis is supported by the observation that (i) the overall SNP density of X-chromosome is lower compared to the SNP density on autosomes and that (ii) the density of genic SNPs on the X-chromosome is lower compared to autosomes while densities of intergenic SNPs are similar.

Genomic instability drives tumorigenesis and metastasis and its implications for cancer therapy

Genetic instability can be caused by external factors and may also be associated with intracellular damage. At the same time, there is a large body of research investigating the mechanisms by which genetic instability occurs and demonstrating the relationship between genomic stability and tumors. Nowadays, tumorigenesis development is one of the hottest research areas. It is a vital factor affecting tumor treatment. Mechanisms of genomic stability and tumorigenesis development are relatively complex. Researchers have been working on these aspects of research. To explore the research progress of genomic stability and tumorigenesis, development, and treatment, the authors searched PubMed with the keywords "genome instability" "chromosome instability" "DNA damage" "tumor spread" and "cancer treatment". This extracts the information relevant to this study. Results: This review introduces genomic stability, drivers of tumor development, tumor cell characteristics, tumor metastasis, and tumor treatment. Among them, immunotherapy is more important in tumor treatment, which can effectively inhibit tumor metastasis and kill tumor cells. Breakthroughs in tumorigenesis development studies and discoveries in tumor metastasis will provide new therapeutic techniques. New tumor treatment methods can effectively prevent tumor metastasis and improve the cure rate of tumors.

Boosting of tau protein aggregation by CD40 and CD48 gene expression in Alzheimer's disease

Neurodegenerative diseases result from the interplay of abnormal gene expression and various pathological factors. Therefore, a disease-specific integrative genetic approach is required to understand the complexities and causes of target diseases. Recent studies have identified the correlation between genes encoding several transmembrane proteins, such as the cluster of differentiation (CD) and Alzheimer's disease (AD) pathogenesis. In this study, CD48 and CD40 gene expression in AD, a neurodegenerative disease, was analyzed to infer this link. Total RNA sequencing was performed using an Alzheimer's disease mouse model brain and blood, and gene expression was determined using a genome-wide association study (GWAS). We observed a marked elevation of CD48 and CD40 genes in Alzheimer's disease. Indeed, the upregulation of both CD48 and CD40 genes was significantly increased in the severe Alzheimer's disease group. With the elevation of CD48 and CD40 genes in Alzheimer's disease, associations of protein levels were also markedly increased in tissues. In addition, overexpression of CD48 and CD40 genes triggered tau aggregation, and co-expression of these genes accelerated aggregation. The nuclear factor kappa B (NF-ĸB) signaling pathway was enriched by CD48 and CD40 gene expression: it was also associated with tau pathology. Our data suggested that the CD48 and CD40 genes are novel AD-related genes, and this approach may be useful as a diagnostic or therapeutic target for the disease.

Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis

BACKGROUND

There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression.

MAIN BODY

We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data.

CONCLUSION

We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer.

Typical Enhancers, Super-Enhancers, and Cancers

Simple Summary

The cancer genome has been exhaustively studied upon the advent of Next-Generation Sequencing technologies. Coding and non-coding sequences have been defined as hotspots of genomic variations that affect the naïve gene expression programs established in normal cells, thus working as endogenous drivers of carcinogenesis. In this review, we comprehensively summarize fundamental aspects of gene expression regulation, with emphasis on the impact of sequence and structural variations mapped across non-coding cis-acting elements of genes encoding for tumor-related transcription factors. Chromatin architecture, epigenome reprogramming, transcriptional enhancers and Super-enhancers, oncogene regulation, cutting-edge technologies, and pharmacological treatment are substantially highlighted.

Abstract

Non-coding segments of the human genome are enriched in cis-regulatory modules that constitute functional elements, such as transcriptional enhancers and Super-enhancers. A hallmark of cancer pathogenesis is the dramatic dysregulation of the “archetype” gene expression profiles of normal human cells. Genomic variations can promote such deficiencies when occurring across enhancers and Super-enhancers, since they affect their mechanistic principles, their functional capacity and specificity, and the epigenomic features of the chromatin microenvironment across which these regulatory elements reside. Here, we comprehensively describe: fundamental mechanisms of gene expression dysregulation in cancers that involve genomic abnormalities within enhancers’ and Super-enhancers’ (SEs) sequences, which alter the expression of oncogenic transcription factors (TFs); cutting-edge technologies applied for the analysis of variation-enriched hotspots of the cancer genome; and pharmacological approaches for the treatment of Super-enhancers’ aberrant function. Finally, we provide an intratumor meta-analysis, which highlights that genomic variations in transcription-factor-driven tumors are accompanied overexpression of genes, a portion of which encodes for additional cancer-related transcription factors.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

FN1 encoding fibronectin as a pivotal signaling gene for therapeutic intervention against pancreatic cancer

The delayed diagnosis of pancreatic cancer has resulted in rising mortality rate and low survival rate that can be circumvented using potent theranostics biomarkers. The treatment gets complicated with delayed detection resulting in lowered 5-year relative survival rate. In our present study, we employed systems biology approach to identify central genes that play crucial roles in tumor progression. Pancreatic cancer genes collected from various databases were used to construct a statistically significant interactome with 812 genes that was further analysed thoroughly using topological parameters and functional enrichment analysis. The significant genes in the network were then identified based on the maximum degree parameter. The overall survival analysis indicated through hazard ratio [HR] and gene expression [log Fold Change] across pancreatic adenocarcinoma revealed the critical role of FN1 [HR 1.4; log2(FC) 5.748], FGA [HR 0.78; log2(FC) 1.639] FGG [HR 0.9; log2(FC) 1.597], C3 [HR 1.1; log2(FC) 2.637], and QSOX1 [HR 1.4; log2(FC) 2.371]. The functional significance of the identified hub genes signified the enrichment of integrin cell surface interactions and proteoglycan syndecan-mediated cell signaling. The differential expression, low overall survival and functional significance of FN1 gene implied its possible role in controlling metastasis in pancreatic cancer. Furthermore, alternate splice variants of FN1 gene showed 10 protein coding transcripts with conserved cell attachment site and functional domains indicating the variants' potential role in pancreatic cancer. The strong association of the identified hub-genes can be better directed to design potential theranostics biomarkers for metastasized pancreatic tumor.

The multi-molecular mechanisms of tumor-targeted drug resistance in precision medicine

Clinically, cancer drug therapy is still dominated by chemotherapy drugs. Although the emergence of targeted drugs has greatly improved the survival rate of patients with advanced cancer, drug resistance has always been a difficult problem in clinical cancer treatment. At the current level of medicine, most drugs cannot escape the fate of drug resistance. With the emergence and development of gene detection, liquid biopsy ctDNA technology, and single-cell sequencing technology, the molecular mechanism of tumor drug resistance has gradually emerged. Drugs can also be updated in response to drug resistance mechanisms and bring higher survival benefits. The use of new drugs often leads to new mechanisms of resistance. In this review, the multi-molecular mechanisms of drug resistance are introduced, and the overcoming of drug resistance is discussed from the perspective of the tumor microenvironment.

Polymorphisms of an oncogenic gene, mesothelin, predict the risk and prognosis of gastric cancer in a Chinese Han population

Mesothelin (MSLN) is a cell surface protein associated with tumor invasion and metastasis. This study aims to explore the biological function of MSLN in gastric cancer and to evaluate the association of MSLN polymorphism (rs3764247, rs3764246, rs12597489, rs1057147, rs3765319) with the risk and prognosis of gastric cancer. Small interfering RNA (siRNA) transfection and MSLN overexpression were performed in human gastric cancer cell lines, respectively. The proliferation of tumor cells was evaluated by Cell counting kit 8(CCK-8) and colony formation assay. Wound healing assay and transwell assay were used to elucidate gastric cancer cell migration and invasion rates. We conducted a case-control study involving 860 patients with gastric cancer and 870 controls. All mutation sites were genotyped by PCR-LDR sequencing. First, our study revealed the cancer-promoting role of MSLN in gastric cancer. Second, we also demonstrated that rs3764247 and rs3764246 were associated with a reduced risk of gastric cancer (OR = 0.83, p = 0.010; OR = 0.84, p = 0.011; respectively). The clinicopathological analysis further showed that rs3764247 was closely related to T stage, vascular infiltration, and HER2 expression. In addition, in the survival analysis of 392 patients with gastric cancer, patients with rs3764247 CC genotype had poorer survival than patients with AA + AC genotype after adjusting for age, sex, TNM stage, and Lauren classification (HR = 2.07, p = 0.029). Our findings indicated that MSLN could be an oncogene whose polymorphisms were closely related to the risk and prognosis of gastric cancer.

SNP characteristics and validation success in genome wide association studies

Genome wide association studies (GWASs) have identified tens of thousands of single nucleotide polymorphisms (SNPs) associated with human diseases and characteristics. A significant fraction of GWAS findings can be false positives. The gold standard for true positives is an independent validation. The goal of this study was to identify SNP features associated with validation success. Summary statistics from the Catalog of Published GWASs were used in the analysis. Since our goal was an analysis of reproducibility, we focused on the diseases/phenotypes targeted by at least 10 GWASs. GWASs were arranged in discovery-validation pairs based on the time of publication, with the discovery GWAS published before validation. We used four definitions of the validation success that differ by stringency. Associations of SNP features with validation success were consistent across the definitions. The strongest predictor of SNP validation was the level of statistical significance in the discovery GWAS. The magnitude of the effect size was associated with validation success in a non-linear manner. SNPs with risk allele frequencies in the range 30-70% showed a higher validation success rate compared to rarer or more common SNPs. Missense, 5'UTR, stop gained, and SNPs located in transcription factor binding sites had a higher validation success rate compared to intergenic, intronic and synonymous SNPs. There was a positive association between validation success and the level of evolutionary conservation of the sites. In addition, validation success was higher when discovery and validation GWASs targeted the same ethnicity. All predictors of validation success remained significant in a multivariate logistic regression model indicating their independent contribution. To conclude, we identified SNP features predicting validation success of GWAS hits. These features can be used to select SNPs for validation and downstream functional studies.

Genome-wide association studies for growth traits in broilers

BACKGROUND

The identification of markers and genes for growth traits may not only benefit for marker assist selection /genomic selection but also provide important information for understanding the genetic foundation of growth traits in broilers.

RESULTS

In the current study, we estimated the genetic parameters of eight growth traits in broilers and carried out the genome-wide association studies for these growth traits. A total of 113 QTNs discovered by multiple methods together, and some genes, including ACTA1, IGF2BP1, TAPT1, LDB2, PRKCA, TGFBR2, GLI3, SLC16A7, INHBA, BAMBI, APCDD1, GPR39, and GATA4, were identified as important candidate genes for rapid growth in broilers.

CONCLUSIONS

The results of this study will provide important information for understanding the genetic foundation of growth traits in broilers.

Emerging Biomarkers in Thyroid Practice and Research

Simple Summary

Tumor biomarkers are molecules at genetic or protein level, or certain evaluable characteristics. These help in perfecting patient management. Over the past decade, advanced and more sensitive techniques have led to the identification of many new biomarkers in the field of oncology. A knowledge of the recent developments is essential for their application to clinical practice, and furthering research. This review provides a comprehensive account of such various markers identified in thyroid carcinoma, the most common endocrine malignancy. While some of these have been brought into use in routine patient management, others are novel and need more research before clinical application.

Abstract

Thyroid cancer is the most common endocrine malignancy. Recent developments in molecular biological techniques have led to a better understanding of the pathogenesis and clinical behavior of thyroid neoplasms. This has culminated in the updating of thyroid tumor classification, including the re-categorization of existing and introduction of new entities. In this review, we discuss various molecular biomarkers possessing diagnostic, prognostic, predictive and therapeutic roles in thyroid cancer. A comprehensive account of epigenetic dysregulation, including DNA methylation, the function of various microRNAs and long non-coding RNAs, germline mutations determining familial occurrence of medullary and non-medullary thyroid carcinoma, and single nucleotide polymorphisms predisposed to thyroid tumorigenesis has been provided. In addition to novel immunohistochemical markers, including those for neuroendocrine differentiation, and next-generation immunohistochemistry (BRAF V600E, RAS, TRK, and ALK), the relevance of well-established markers, such as Ki-67, in current clinical practice has also been discussed. A tumor microenvironment (PD-L1, CD markers) and its influence in predicting responses to immunotherapy in thyroid cancer and the expanding arena of techniques, including liquid biopsy based on circulating nucleic acids and plasma-derived exosomes as a non-invasive technique for patient management, are also summarized.

Genetic Variants of CLPP and M1AP Are Associated With Risk of Non-Small Cell Lung Cancer

Background

Single nucleotide polymorphisms (SNPs) are often associated with distinct phenotypes in cancer. The present study investigated associations of cancer risk and outcomes with SNPs discovered by whole exome sequencing of normal lung tissue DNA of 15 non-small cell lung cancer (NSCLC) patients, 10 early stage and 5 advanced stage.

Methods

DNA extracted from normal lung tissue of the 15 NSCLC patients was subjected to whole genome amplification and sequencing and analyzed for the occurrence of SNPs. The association of SNPs with the risk of lung cancer and survival was surveyed using the OncoArray study dataset of 85,716 patients (29,266 cases and 56,450 cancer-free controls) and the Prostate, Lung, Colorectal and Ovarian study subset of 1,175 lung cancer patients.

Results

We identified 4 SNPs exclusive to the 5 patients with advanced stage NSCLC: rs10420388 and rs10418574 in the CLPP gene, and rs11126435 and rs2021725 in the M1AP gene. The variant alleles G of SNP rs10420388 and A of SNP rs10418574 in the CLPP gene were associated with increased risk of squamous cell carcinoma (OR = 1.07 and 1.07; P = 0.013 and 0.016, respectively). The variant allele T of SNP rs11126435 in the M1AP gene was associated with decreased risk of adenocarcinoma (OR = 0.95; P = 0.027). There was no significant association of these SNPs with the overall survival of lung cancer patients (P > 0.05).

Conclusions

SNPs identified in the CLPP and M1AP genes may be useful in risk prediction models for lung cancer. The previously established association of the CLPP gene with cancer progression lends relevance to our findings.

Brilliant glycans and glycosylation: Seq and ye shall find

Proteoglycosylation is the addition of monosaccharides or glycans to the protein peptide chain. This is a common post-translational modification of proteins with a variety of biological functions. At present, more than half of all biopharmaceuticals in clinic are modified by glycosylation. Most glycoproteins are potential drug targets and biomarkers for disease diagnosis. Therefore, in-depth study of glycan structure of glycoproteins will ultimately improve the sensitivity and specificity of glycoproteins for clinical disease detection. With the deepening of research, the function and application value of glycans and glycosylation has gradually emerged. This review systematically introduces the latest research progress of glycans and glycosylation. It encompasses six cancers, four viruses, and their latest discoveries in Alzheimer's disease, allergic diseases, congenital diseases, gastrointestinal diseases, inflammation, and aging.

Mesenchymal stem cells: ideal seeds for treating diseases

Mesenchymal stem cells (MSCs), a kind of multipotent stem cells with self-renewal ability and multi-differentiation ability, have become the “practical stem cells” for the treatment of diseases. MSCs have immunomodulatory properties and can be used to treat autoimmune diseases, such as systemic lupus erythematosus (SLE) and Crohn’s disease. MSCs also can be used in cancer and aging. At present, many clinical experiments are using MSCs. MSCs can reduce the occurrence of inflammation and apoptosis of tissue cells, and promote the proliferation of endogenous tissue and organ cells, so as to achieve the effect of repairing tissue and organs. MSCs presumably also play an important role in Corona Virus Disease 2019 (COVID-19) infection.

How to Better Understand the Influence of Host Genetics on Developing an Effective Immune Response to Thoracic Cancers

Thoracic cancers pose a significant global health burden. Immune checkpoint blockade therapies have improved treatment outcomes, but durable responses remain limited. Understanding how the host immune system interacts with a developing tumor is essential for the rational development of improved treatments for thoracic malignancies. Recent technical advances have improved our understanding of the mutational burden of cancer cells and changes in cancer-specific gene expression, providing a detailed understanding of the complex biology underpinning tumor-host interactions. While there has been much focus on the genetic alterations associated with cancer cells and how they may impact treatment outcomes, how host genetics affects cancer development is also critical and will greatly determine treatment response. Genome-wide association studies (GWAS) have identified genetic variants associated with cancer predisposition. This approach has successfully identified host genetic risk factors associated with common thoracic cancers like lung cancer, but is less effective for rare cancers like malignant mesothelioma. To assess how host genetics impacts rare thoracic cancers, we used the Collaborative Cross (CC); a powerful murine genetic resource designed to maximize genetic diversity and rapidly identify genes associated with any biological trait. We are using the CC in conjunction with our asbestos-induced MexTAg mouse model, to identify host genes associated with mesothelioma development. Once genes that moderate tumor development and progression are known, human homologues can be identified and human datasets interrogated to validate their association with disease outcome. Furthermore, our CC-MexTAg animal model enables in-depth study of the tumor microenvironment, allowing the correlation of immune cell infiltration and gene expression signatures with disease development. This strategy provides a detailed picture of the underlying biological pathways associated with mesothelioma susceptibility and progression; knowledge that is crucial for the rational development of new diagnostic and therapeutic strategies. Here we discuss the influence of host genetics on developing an effective immune response to thoracic cancers. We highlight current knowledge gaps, and with a focus on mesothelioma, describe the development and application of the CC-MexTAg to overcome limitations and illustrate how the knowledge gained from this unique study will inform the rational design of future treatments of mesothelioma.

Modeling transcriptional regulation using gene regulatory networks based on multi-omics data sources

Background

Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features.

Results

We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression.

Conclusions

Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04126-3.

Clinical and Prognostic Pan-Cancer Analysis of N6-Methyladenosine Regulators in Two Types of Hematological Malignancies: A Retrospective Study Based on TCGA and GTEx Databases

N6-methyladenosine (m6A) is one of the most active modification factors of mRNA, which is closely related to cell proliferation, differentiation, and tumor development. Here, we explored the relationship between the pathogenesis of hematological malignancies and the clinicopathologic parameters. The datasets of hematological malignancies and controls were obtained from the TCGA [AML (n = 200), DLBCL (n = 48)] and GTEx [whole blood (n = 337), blood vascular artery (n = 606)]. We analyzed the m6A factor expression differences in normal tissue and tumor tissue and their correlations, clustered the express obvious clinical tumor subtypes, determined the tumor risk score, established Cox regression model, performed univariate and multivariate analysis on all datasets. We found that the AML patients with high expression of IGF2BP3, ALKBH5, and IGF2BP2 had poor survival, while the DLBCL patients with high expression of METTL14 had poor survival. In addition, "Total" datasets analysis revealed that IGF2BP1, ALKBH5, IGF2BP2, RBM15, METTL3, and ZNF217 were potential oncogenes for hematologic system tumors. Collectively, the expressions of some m6A regulators are closely related to the occurrence and development of hematologic system tumors, and the intervention of specific regulatory factors may lead to a breakthrough in the treatment in the future.

The metastasizing mechanisms of lung cancer: Recent advances and therapeutic challenges

Lung cancer is one of the common malignant tumors that threaten human life with serious incidence and high mortality. According to the histopathological characteristics, lung cancer is mainly divided into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC accounts for about 80-85% of lung cancers. In fact, lung cancer metastasis is a major cause of treatment failure in clinical patients. The underlying reason is that the mechanisms of lung cancer metastasis are still not fully understood. The metastasis of lung cancer cells is controlled by many factors, including the interaction of various components in the lung cancer microenvironment, epithelial-mesenchymal transition (EMT) transformation, and metastasis of cancer cells through blood vessels and lymphatics. The molecular relationships are even more intricate. Further study on the mechanisms of lung cancer metastasis and in search of effective therapeutic targets can bring more reference directions for clinical drug research and development. This paper focuses on the factors affecting lung cancer metastasis and connects with related molecular mechanisms of the lung cancer metastasis and mechanisms of lung cancer to specific organs, which mainly reviews the latest research progress of NSCLC metastasis. Besides, in this paper, experimental models of lung cancer and metastasis, mechanisms in SCLC transfer and the challenges about clinical management of lung cancer are also discussed. The review is intended to provide reference value for the future research in this field and promising treatment clues for clinical patients.

The role of gut microbiota in tumorigenesis and treatment

A large number of microbial communities exist in normal human intestinal tracts, which maintain a relatively stable dynamic balance under certain conditions. Gut microbiota are closely connected with human health and the occurrence of tumors. The colonization of certain intestinal bacteria on specific sites, gut microbiota disturbance and intestinal immune disorders can induce the occurrence of tumors. Meanwhile, gut microbiota can also play a role in tumor therapy by participating in immune regulation, influencing the efficacy of anti-tumor drugs, targeted therapy of engineered probiotics and fecal microbiota transplantation. This article reviews the role of gut microbiota in the occurrence, development, diagnosis and treatment of tumors. A better understanding of how gut microbiota affect tumors will help us find more therapies to treat the disease.

Imaging genomics for accurate diagnosis and treatment of tumors: A cutting edge overview

Imaging genomics refers to the establishment of the connection between invasive gene expression features and non-invasive imaging features. Tumor imaging genomics can not only understand the macroscopic phenotype of tumor, but also can deeply analyze the cellular and molecular characteristics of tumor tissue. In recent years, tumor imaging genomics has been a key in the field of medicine. The incidence of cancer in China has increased significantly, which is the main reason of disease death of urban residents. With the rapid development of imaging medicine, depending on imaging genomics, many experts have made remarkable achievements in tumor screening and diagnosis, prognosis evaluation, new treatment targets and understanding of tumor biological mechanism. This review analyzes the relationship between tumor radiology and gene expression, which provides a favorable direction for clinical staging, prognosis evaluation and accurate treatment of tumors.

How wide is the application of genetic big data in biomedicine

In the era of big data, massive genetic data, as a new industry, has quickly swept almost all industries, especially the pharmaceutical industry. As countries around the world start to build their own gene banks, scientists study the data to explore the origins and migration of humans. Moreover, big data encourage the development of cancer therapy and bring good news to cancer patients. Big datum has been involved in the study of many diseases, and it has been found that analyzing diseases at the gene level can lead to more beneficial treatment options than ordinary treatments. This review will introduce the development of extensive data in medical research from the perspective of big data and tumor, neurological and psychiatric diseases, cardiovascular diseases, other applications and the development direction of big data in medicine.

Breakthrough in targeted therapy for non-small cell lung cancer

Non-small cell lung cancer (NSCLC) remains by far the single most common malignancy of lung cancer which causes more and more mortality in recent years. NSCLC accounts for more than 80 % of lung cancers, and the vast majority of patients were found to be in advanced inoperable stages. Chemotherapy used to be the main treatment for NSCLC, but due to its obvious side effects. Chemotherapy gradually withdrew from the stage of history. In recent years, cellular and molecular biotechnology has developed rapidly, and researchers have begun to target key genes and regulatory molecules for treatment. Targeted drugs have also emerged. The purpose of this review is to introduce important research achievements in recent years and the treatment progress of new drugs.

Cancer evolution: A means by which tumors evade treatment

Although various methods have been tried to study and treat cancer, the cancer remains a major challenge for human medicine today. One important reason for this is the presence of cancer evolution. Cancer evolution is a process in which tumor cells adapt to the external environment, which can suppress the human immune system's ability to recognize and attack tumors, and also reduce the reproducibility of cancer research. Among them, heterogeneity of the tumor provides intrinsic motivation for this process. Recently, with the development of related technologies such as liquid biopsy, more and more knowledge about cancer evolution has been gained and interest in this topic has also increased. Therefore, starting from the causes of tumorigenesis, this paper introduces several tumorigenesis processes and pathways, as well as treatment options for different targets.

Tumor-infiltrating lymphocytes: Warriors fight against tumors powerfully

Tumor-infiltrating lymphocytes (TILs) are infiltrating lymphocytes in tumor tissues. After isolation, screening and amplification in vitro, they will be implanted into patients and play a specific killing effect on tumors. Since TILs have not been genetically modified and come from the body of patients, there will be relatively few adverse reactions. This is also the advantage of TIL treatment. In recent years, its curative effect on solid tumors began to show its sharpness. However, due to the limitations of the immune microenvironment and the mutation of antigens, TIL's development was slowed down. This article reviews the research progress, biological characteristics, preparation and methods of enhancing the therapeutic effect of tumor-infiltrating lymphocytes, their roles in different tumors and prognosis, and emphasizes the important value of tumor-infiltrating lymphocytes in anti-tumor.

Gut microecology: Why our microbes could be key to our health

The human body contains a large number of microorganisms, and the gut microecology environment contains the largest number and types of microorganisms. The structure and function of gut microbiota are closely related to the health of the human body. In a cascade of studies, the diversity of gut microbiota and its metabolite often found changed in patients or mice model. What kind of gut microbiota that associated with the occurrence or treatment of diseases were also found in many studies. Gut microbiota and its products can affect the function of the human body. Short-chain fatty acids, bile acid, indoles and so on were found can regulate the inflammation, immune response to affect the process of diseases. Immune cells like natural killer T cells, CD3 + T cells were also found had a link to gut microbiota which associated with diseases. Changes in gut microbiota are associated with changes in the body's major systems, such as the digestive system, the endocrine system, the cardiovascular system, the endocrine and metabolic system, the urinary system diseases, the respiratory system and so on. It is of great significance to study gut microecology for the prevention and treatment of various human diseases.

Principles of RNA methylation and their implications for biology and medicine

RNA methylation is a post-transcriptional level of regulation. At present, more than 150 kinds of RNA modifications have been identified. They are widely distributed in messenger RNA (mRNA), transfer RNA (tRNA), ribosomal RNA (rRNA), noncoding small RNA (sncRNA) and long-chain non-coding RNA (lncRNA). In recent years, with the discovery of RNA methylation related proteins and the development of high-throughput sequencing technology, the mystery of RNA methylation has been gradually revealed, and its biological function and application value have gradually emerged. In this review, a large number of research results of RNA methylation in recent years are collected. Through systematic summary and refinement, this review introduced RNA methylation modification-related proteins and RNA methylation sequencing technologies, as well as the biological functions of RNA methylation, expressions and applications of RNA methylation-related genes in physiological or pathological states such as cancer, immunity and virus infection, and discussed the potential therapeutic strategies.

Cancer neoantigen: Boosting immunotherapy

Tumor neoantigen has a high degree of immunogenicity. As one of the emerging methods of tumor immunotherapy, the vaccine developed against it has served to clinical trials of various solid tumors, especially in the treatment of melanoma. Currently, a variety of immunotherapy methods have been applied to the treatment of the tumor. However, other therapeutic methods have the disadvantages of low specificity and prominent side effects. Treatments require tumor antigen with higher immunogenicity as the target of immune attack. This review will recommend the identification of neoantigen, the influencing factors of neoantigen, and the application of personalized vaccines for neoantigen in metastatic tumors such as malignant melanoma.

How to overcome the side effects of tumor immunotherapy

The incidence of cancer is increasing year by year. Cancer has become one of the health threats of modern people. Simply relying on the surgery, chemotherapy or radiotherapy, not only the survival rate is not high, but also the quality of life of patients is not much better. Fortunately, the emergence and rapid development of cancer immunotherapy have brought more and more exciting results. However, when scientists think it is possible to overcome cancer, they find that not all cancer patients can benefit from immunotherapy, that is to say, the overall efficiency of immunotherapy is not high. Drug resistance and side effects of immunotherapy cannot be ignored. In order to overcome these difficulties, scientists continue to improve the strategy of immunotherapy and find that combination therapy can effectively reduce the incidence of drug resistance. They also found that by reprogramming tumor blood vessels, activating ferroptosis, utilizing thioredoxin, FATP2 and other substances, the therapeutic effect can be improved and side effects can be alleviated. This article reviews the principles of immunotherapy, new strategies to overcome drug resistance of cancer immunotherapy, and how to improve the efficacy of immunotherapy and reduce side effects.

Bone metabolism regulation: Implications for the treatment of bone diseases

Bone cells in the human body are continuously engaged in cellular metabolism, including the interaction between bone cells, the interaction between the erythropoietic cells of the bone marrow and stromal cells, for the remodeling and reconstruction of bone. Osteoclasts and osteoblasts play an important role in bone metabolism. Diseases occur when bone metabolism is abnormal, but little is known about the signaling pathways that affect bone metabolism. The study of these signaling pathways will help us to use the relevant techniques to intervene, so as to improve the condition. The study of these signaling pathways will help us to use the relevant techniques to intervene, so as to improve the condition. I believe they will shine in the diagnosis and treatment of future clinical bone diseases.

Big data-driven precision medicine: Starting the custom-made era of iatrology

Precision medicine is a new therapeutic concept and method emerging in recent years. The rapid development of precision medicine is driven by the development of omics related technology, biological information and big data science. Precision medicine is provided to implement precise and personalized treatment for diseases and specific patients. Precision medicine is commonly used in the diagnosis, treatment and prevention of various diseases. This review introduces the application of precision medicine in eight systematic diseases of the human body, and systematically presenting the current situation of precision medicine. At the same time, the shortcomings and limitations of precision medicine are pointed out. Finally, we prospect the development of precision medicine.

The associations of hub gene polymorphisms in PI3K/AKT/mTOR pathway and Schistosomiasis Japonica infection and hepatic fibrosis

INTRODUCTION

Increasing evidence shows that the PI3K/AKT/mTOR pathway can be activated by a variety of stimulus in immune cells. Schistosomiasis Japonica is a serious threat to human health in some lakes of China.

METHODS

We analyzed the potential associations between the hub gene (PTEN, mTOR, AKT1 and AKT2) polymorphisms of PI3K/AKT/mTOR pathway and S. japonica risk, including infection risk, as well as immunological hepatic fibrosis risk. An immune database named Database of Immune Cell Expression, Expression quantitative trait loci and Epigenomics (DICE) was used to analyze the expression profiles of the hub genes in 15 types of immune cells.

RESULTS

Of them, two SNPs rs2295080 (mTOR) and rs7254617 (AKT2) were found associated with the risk of infection and fibrosis. We also performed a multivariant Cox regression analysis and found that HBV infection may increase hepatic fibrosis in chronic schistosomiasis patients, instead of genetic polymorphisms on PI3K/AKT/mTOR pathway or any other factors. We also found the expressions of mTOR (RICTOR) and AKT2 in T cells were higher than those in monocyte cells. And, the expressions of PTEN, mTOR (RICTOR) and AKT1 reduced both in activated CD4 T cells and activated CD8 T cells.

CONCLUSIONS

We concluded that rs2295080 may be an important marker in the diagnosis of susceptibility to schistosomiasis infection. But HBV infection not rs2295080 could promote immunological liver damage with fibrosis in patients with chronic schistosomiasis infection.