Patterns of genomic instability in gastric cancer: clinical implications and perspectives

Analysis of biopsies of gastric cancer, intestinal and diffuse, and non-atrophic gastritis: an overview of loss of heterozygosity in Mexican patients

This study analyzed the loss of heterozygosity (LOH) effect on gastric cancer (GC) tumor samples from 21 Mexican patients, including diffuse (DGC) and intestinal (IGC) subtypes, as well as non-atrophic gastritis (NAG, control). Whole-genome high-density arrays were performed, and LOH regions were identified among the tissue samples. The differences in affected chromosomes were established among groups, with chromosomes 6 and 8 primarily affected in DGC and chromosomes 3, 16, and 17 in IGC. Functional pathway analysis revealed involvement in cancer-associated processes, such as signal transduction, immune response, and cellular metabolism. Five LOH-genes (IRAK1, IKBKG, PAK3, TKTL1, PRPS1) shared between GC and NAG suggest an early role in carcinogenesis. Specific genes were highlighted for Hallmarks of Cancer NAG-related genes (PTPRJ and NDUFS) were linked to cell proliferation and growth; IGC genes (GNAI2, RHOA, MAPKAPK3, MST1R) to genomic instability, metastasis, and arrest of cell death; and DGC genes to energy metabolism and immune evasion. These findings emphasize the role of LOH in GC pathogenesis and underscore the need for further research to understand LOH-affected genes and their diagnostic or evolution potential in cancer management. Portions of this text were previously published as part of a preprint (https://www.medrxiv.org/content/10.1101/2024.07.29.24311063v1).

Evolving Strategies in the Management of Microsatellite Instability-High/Mismatch Repair Deficient Esophagogastric Adenocarcinoma

PURPOSE OF REVIEW

This review addresses the current treatment paradigm and new advancements in the management of microsatellite instability-high/mismatch repair deficient (MSI-H/dMMR) esophagogastric cancer (EGC).

RECENT FINDINGS

While chemotherapy and surgery remain the cornerstone of EGC treatment, MSI-H/dMMR tumors harbor high tumor mutational burden and represent a subset of patients who benefit from immune checkpoint inhibitors (ICI). ICI has been incorporated in the front line setting with and without chemotherapy for advanced disease. Recently, ICI has been studied in the perioperative setting for resectable disease. Though perioperative ICI results in improved response rates, it is not yet clear whether this translates to a survival benefit. Despite high response rates with ICI in this patient population, many do not respond to therapy, representing a major challenge in treatment. Preclinical studies have highlighted potential mechanisms of resistance which will guide drug development and clinical trials.

Potent therapeutic strategy in gastric cancer with microsatellite instability-high and/or deficient mismatch repair

Gastric cancer (GC) is a common malignancy that presents challenges in patient care worldwide. The mismatch repair (MMR) system is a highly conserved DNA repair mechanism that protects genome integrity during replication. Deficient MMR (dMMR) results in an increased accumulation of genetic errors in microsatellite sequences, leading to the development of a microsatellite instability-high (MSI-H) phenotype. Most MSI-H/dMMR GCs arise sporadically, mainly due to MutL homolog 1 (MLH1) epigenetic silencing. Unlike microsatellite-stable (MSS)/proficient MMR (pMMR) GCs, MSI-H/dMMR GCs are relatively rare and represent a distinct subtype with genomic instability, a high somatic mutational burden, favorable immunogenicity, different responses to treatment, and prognosis. dMMR/MSI-H status is a robust predictive biomarker for treatment with immune checkpoint inhibitors (ICIs) due to high neoantigen load, prominent tumor-infiltrating lymphocytes, and programmed cell death ligand 1 (PD-L1) overexpression. However, a subset of MSI-H/dMMR GC patients does not benefit from immunotherapy, highlighting the need for further research into predictive biomarkers and resistance mechanisms. This review provides a comprehensive overview of the clinical, molecular, immunogenic, and therapeutic aspects of MSI-H/dMMR GC, with a focus on the impact of ICIs in immunotherapy and their potential as neoadjuvant therapies. Understanding the complexity and diversity of the molecular and immunological profiles of MSI-H/dMMR GC will drive the development of more effective therapeutic strategies and molecular targets for future precision medicine.

Exploring Novel Genome Instability-associated lncRNAs and their Potential Function in Pan-Renal Cell Carcinoma

OBJECTIVE

Genomic instability can drive clonal evolution, continuous modification of tumor genomes, and tumor genomic heterogeneity. The molecular mechanism of genomic instability still needs further investigation. This study aims to identify novel genome instabilityassociated lncRNAs (GI-lncRNAs) and investigate the role of genome instability in pan-Renal cell carcinoma (RCC).

MATERIALS AND METHODS

A mutator hypothesis was employed, combining the TCGA database of somatic mutation (SM) information, to identify GI-lncRNAs. Subsequently, a training cohort (n = 442) and a testing cohort (n = 439) were formed by randomly dividing all RCC patients. Based on the training cohort dataset, a multivariate Cox regression analysis lncRNAs risk model was created. Further validations were performed in the testing cohort, TCGA cohort, and different RCC subtypes. To confirm the relative expression levels of lncRNAs in HK-2, 786-O, and 769-P cells, qPCR was carried out. Functional pathway enrichment analyses were performed for further investigation.

RESULTS

A total of 170 novel GI-lncRNAs were identified. The lncRNA prognostic risk model was constructed based on LINC00460, AC073218.1, AC010789.1, and COLCA1. This risk model successfully differentiated patients into distinct risk groups with significantly different clinical outcomes. The model was further validated in multiple independent patient cohorts. Additionally, functional and pathway enrichment analyses revealed that GI-lncRNAs play a crucial role in GI. Furthermore, the assessments of immune response, drug sensitivity, and cancer stemness revealed a significant relationship between GI-lncRNAs and tumor microenvironment infiltration, mutational burden, microsatellite instability, and drug resistance.

CONCLUSIONS

In this study, we discovered four novel GI-lncRNAs and developed a novel signature that effectively predicted clinical outcomes in pan-RCC. The findings provide valuable insights for pan-RCC immunotherapy and shed light on potential underlying mechanisms.

Mutation-derived, genomic instability-associated lncRNAs are prognostic markers in gliomas

Background

Gliomas are the most commonly-detected malignant tumors of the brain. They contain abundant long non-coding RNAs (lncRNAs), which are valuable cancer biomarkers. LncRNAs may be involved in genomic instability; however, their specific role and mechanism in gliomas remains unclear. LncRNAs that are related to genomic instability have not been reported in gliomas.

Methods

The transcriptome data from The Cancer Genome Atlas (TCGA) database were analyzed. The co-expression network of genomic instability-related lncRNAs and mRNA was established, and the model of genomic instability-related lncRNA was identified by univariate Cox regression and LASSO analyses. Based on the median risk score obtained in the training set, we divided the samples into high-risk and low-risk groups and proved the survival prediction ability of genomic instability-related lncRNA signatures. The results were verified in the external data set. Finally, a real-time quantitative polymerase chain reaction assay was performed to validate the signature.

Results

The signatures of 17 lncRNAs (LINC01579, AL022344.1, AC025171.5, LINC01116, MIR155HG, AC131097.3, LINC00906, CYTOR, AC015540.1, SLC25A21.AS1, H19, AL133415.1, SNHG18, FOXD3.AS1, LINC02593, AL354919.2 and CRNDE) related to genomic instability were identified. In the internal data set and Gene Expression Omnibus (GEO) external data set, the low-risk group showed better survival than the high-risk group (P < 0.001). In addition, this feature was identified as an independent risk factor, showing its independent prognostic value with different clinical stratifications. The majority of patients in the low-risk group had isocitrate dehydrogenase 1 (IDH1) mutations. The expression levels of these lncRNAs were significantly higher in glioblastoma cell lines than in normal cells.

Conclusions

Our study shows that the signature of 17 lncRNAs related to genomic instability has prognostic value for gliomas and could provide a potential therapeutic method for glioblastoma.

Genome instability-related LINC02577, LINC01133 and AC107464.2 are lncRNA prognostic markers correlated with immune microenvironment in pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is a leading cause of malignancy-related deaths worldwide, and the efficacy of immunotherapy on PAAD is limited. Studies report that long non-coding RNAs (lncRNAs) play an important role in modulating genomic instability and immunotherapy. However, the identification of genome instability-related lncRNAs and their clinical significance has not been investigated in PAAD.

METHODS

The current study developed a computational framework for mutation hypothesis based on lncRNA expression profile and somatic mutation spectrum in pancreatic adenocarcinoma genome. We explored the potential of GInLncRNAs(genome instability-related lncRNAs) through co-expression analysis and function enrichment analysis. We further analyzed GInLncRNAs by Cox regression and used the results to construct a prognostic lncRNA signature. Finally, we analyzed the relationship between GILncSig (genomic instability derived 3-lncRNA signature) and immunotherapy.

RESULTS

A GILncSig was developed using bioinformatics analyses. It could divide patients into high-risk and low-risk groups, and there was a significant difference in OS between the two groups. In addition, GILncSig was associated with genome mutation rate in pancreatic adenocarcinoma, indicating its potential value as a marker for genomic instability. The GILncSig accurately grouped wild type patients of KRAS into two risk groups. The prognosis of the low-risk group was significantly improved. GILncSig was significantly correlated with the level of immune cell infiltration and immune checkpoint.

CONCLUSIONS

In summary, the current study provides a basis for further studies on the role of lncRNA in genomic instability and immunotherapy. The study provides a novel method for identification of cancer biomarkers related to genomic instability and immunotherapy.

The Roles of Immune Cells in Gastric Cancer: Anti-Cancer or Pro-Cancer?

Simple Summary

Gastric cancer is still one of the leading causes of death caused by cancer in developing countries. The emerging role of immunotherapy in cancer treatment has led to more research to elucidate the roles of essential immune cells in gastric cancer prognosis. We reviewed the roles of immune cells including T cells, B cells, dendritic cells, macrophages and natural killer cells in gastric cancer. Although the studies conducted on the roles of immune cells in gastric cancer pathogenesis produced conflicting results, understanding the roles of immune cells in gastric cancer will help us to harness them for application in immunotherapy for better prognosis and management of gastric cancer patients.

Abstract

Despite the fact that the incidence of gastric cancer has declined over the last decade, it is still the world’s leading cause of cancer-related death. The diagnosis of early gastric cancer is difficult, as symptoms of this cancer only manifest at a late stage of cancer progression. Thus, the prognosis of gastric cancer is poor, and the current treatment for improving patients’ outcomes involves the application of surgery and chemotherapy. Immunotherapy is one of the most recent therapies for gastric cancer, whereby the immune system of the host is programmed to combat cancer cells, and the therapy differs based upon the patient’s immune system. However, an understanding of the role of immune cells, namely the cell-mediated immune response and the humoral immune response, is pertinent for applications of immunotherapy. The roles of immune cells in the prognosis of gastric cancer have yielded conflicting results. This review discusses the roles of immune cells in gastric cancer pathogenesis, specifically, T cells, B cells, macrophages, natural killer cells, and dendritic cells, as well as the evidence presented thus far. Understanding how cancer cells interact with immune cells is of paramount importance in designing treatment options for gastric cancer immunotherapy.

Microsatellite Instability: From the Implementation of the Detection to a Prognostic and Predictive Role in Cancers

Microsatellite instability (MSI) has been identified in several tumors arising from either germline or somatic aberration. The presence of MSI in cancer predicts the sensitivity to immune checkpoint inhibitors (ICIs), particularly PD1/PD-L1 inhibitors. To date, the predictive role of MSI is currently used in the selection of colorectal cancer patients for immunotherapy; moreover, the expansion of clinical trials into other cancer types may elucidate the predictive value of MSI for non-colorectal tumors. In clinical practice, several assays are used for MSI testing, including immunohistochemistry (IHC), polymerase chain reaction (PCR) and next-generation sequencing (NGS). In this review, we provide an overview of MSI in various cancer types, highlighting its potential predictive/prognostic role and the clinical trials performed. Finally, we focus on the comparison data between the different assays used to detect MSI in clinical practice.

Genome Instability-Associated Long Non-Coding RNAs Reveal Biomarkers for Glioma Immunotherapy and Prognosis

Genome instability is a hallmark of tumors and is involved in proliferation, invasion, migration, and treatment resistance of many tumors. However, the relationship of genome instability with gliomas remains unclear. Here, we constructed genome instability-derived long non-coding RNA (lncRNA)-based gene signatures (GILncSig) using genome instability-related lncRNAs derived from somatic mutations. Multiple platforms were used to confirm that the GILncSig were closely related to patient prognosis and clinical characteristics. We found that GILncSig, the glioma microenvironment, and glioma cell DNA methylation-based stemness index (mDNAsi) interacted with each other to form a complex regulatory network. In summary, this study confirmed that GILncSig was an independent prognostic indicator for patients, distinguished high-risk and low-risk groups, and affected immune-cell infiltration and tumor-cell stemness indicators (mDNAsi) in the tumor microenvironment, resulting in tumor heterogeneity and immunotherapy resistance. GILncSig are expected to provide new molecular targets for the clinical treatment of patients with gliomas.

Comprehensive Analyses of Mutation-Derived Long-Chain Noncoding RNA Signatures of Genome Instability in Kidney Renal Papillary Cell Carcinoma

Background: The role of long-chain noncoding RNA (lncRNA) in genomic instability has been demonstrated to be increasingly importance. Therefore, in this study, lncRNAs associated with genomic instability were identified and kidney renal papillary cell carcinoma (KIRP)-associated predictive features were analysed to classify high-risk patients and improve individualised treatment.

Methods: The training (n = 142) and test (n = 144) sets were created using raw RNA-seq and patient’s clinical data of KIRP obtained from The Cancer Genome Atlas (TCGA).There are 27 long-chain noncoding RNAs (lncRNAs) that are connected with genomic instability, these lncRNAs were identified using the ‘limma’ R package based on the numbers of somatic mutations and lncRNA expression profiles acquired from KIRP TCGA cohort. Furthermore, Cox regression analysis was carried out to develop a genome instability-derived lncRNA-based gene signature (GILncSig), whose prognostic value was confirmed in the test cohort as well as across the entire KIRP TCGA dataset.

Results: A GILncSig derived from three lncRNAs (BOLA3-AS1, AC004870, and LINC00839), which were related with poor KIRP survival, was identified, which was split up into high- and low-risk groups. Additionally, the GILncSig was found to be an independent prognostic predictive index in KIRP using univariate and multivariate Cox analysis. Furthermore, the prognostic significance and characteristics of GilncSig were confirmed in the training test and TCGA sets. GilncSig also showed better predictive performance than other prognostic lncRNA features.

Conclusion: The function of lncRNAs in genomic instability and the genetic diversity of KIRP were elucidated in this work. Moreover, three lncRNAs were screened for prediction of the outcome of KIRP survival and novel insights into identifying cancer biomarkers related to genomic instability were discussed.

Development of a Genomic Instability-Derived lncRNAs-Based Risk Signature as a Predictor of Prognosis for Endometrial Cancer

Endometrial cancer (EC) ranks fourth in the incidence rate among the most frequent gynaecological malignancies reported in the developed countries. Approximately 280,000 endometrial cancer cases are reported worldwide every year. Genomic instability and mutation are some of the favourable characteristics of human malignancies such as endometrial cancer. Studies have established that the majority of genomic mutations in human malignancies are found in the chromosomal regions that do not code for proteins. In addition, the majority of transcriptional products of these mutations are long non-coding RNAs (lncRNAs). In this study, 78 lncRNA genes were found on the basis of their mutation counts. Then, these lncRNAs were investigated to determine their relationship with genomic instability through hierarchical cluster analysis, mutation analysis, and differential analysis of driving genes responsible for genomic instability. The prognostic value of these lncRNAs was also assessed in patients with EC, and a risk factor score formula composed of 15 lncRNAs was constructed. We then identified this formula as genome instability-derived lncRNA-based gene signature (GILncSig), which stratified patients into high- and low-risk groups with significantly different outcome. And GILncSig was further validated in multiple independent patient cohorts as a prognostic factor of other clinicopathological features, such as stage, grade, overall survival rate. We observed that a high-risk score is often associated with an unfavourable prognosis in patients with EC.

Cost-effective low-coverage whole-genome sequencing assay for the risk stratification of gastric cancer

BACKGROUND

Gastric cancer (GC), a multifactorial disease, is caused by pathogens, such as Helicobacter pylori (H. pylori) and Epstein-Barr virus (EBV), and genetic components.

AIM

To investigate microbiomes and host genome instability by cost-effective, low-coverage whole-genome sequencing, as biomarkers for GC subtyping.

METHODS

Samples from 40 GC patients were collected from Taizhou Hospital, Zhejiang Province, affiliated with Wenzhou Medical University. DNA from the samples was subjected to low-coverage whole-genome sequencing with a median genome coverage of 1.86 × (range: 1.03 × to 3.17 ×) by Illumina × 10, followed by copy number analyses using a customized bioinformatics workflow ultrasensitive chromosomal aneuploidy detector.

RESULTS

Of the 40 GC samples, 20 (50%) were found to be enriched with microbiomes. EBV DNA was detected in 5 GC patients (12.5%). H. pylori DNA was found in 15 (37.5%) patients. The other 20 (50%) patients were found to have relatively higher genomic instability. Copy number amplifications of the oncogenes, ERBB2 and KRAS, were found in 9 (22.5%) and 7 (17.5%) of the GC samples, respectively. EBV enrichment was found to be associated with tumors in the gastric cardia and fundus. H. pylori enrichment was found to be associated with tumors in the pylorus and antrum. Tumors with elevated genomic instability showed no localization and could be observed in any location. Additionally, H. pylori-enriched GC was found to be associated with the Borrmann type II/III and gastritis history. EBV-enriched GC was not associated with gastritis. No statistically significant correlation was observed between genomic instability and gastritis. Furthermore, these three different molecular subtypes showed distinct survival outcomes (P = 0.019). EBV-positive tumors had the best prognosis, whereas patients with high genomic instability (CIN+) showed the worst survival. Patients with H. pylori infection showed intermediate prognosis compared with the other two subtypes.

CONCLUSION

Thus, using low-coverage whole-genome sequencing, GC can be classified into three categories based on disease etiology; this classification may prove useful for GC diagnosis and precision medicine.

Identification and Validation of a Novel Genomic Instability-Associated Long Non-Coding RNA Prognostic Signature in Head and Neck Squamous Cell Carcinoma

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignant cancers worldwide, and accurate prognostic models are urgently needed. Emerging evidence revealed that long non-coding RNAs (lncRNAs) are related to genomic instability. We sought to identify and validate a genomic instability-associated lncRNA prognostic signature to assess HNSCC patient survival outcomes.

Methods: RNA-sequencing data, somatic mutation files, and patient clinical data were downloaded from The Cancer Genome Atlas database. A total of 491 patients with completely clinical files were randomly divided into training and testing sets. In the training set, genomic instability-associated lncRNAs were screened through univariate Cox regression analyses and least absolute shrinkage and selection operator regression analyses to build a genomic instability-associated lncRNA signature (GILncSig). In addition, time-dependent receiver operating characteristic (ROC) curve, Kaplan-Meier survival curve, and clinical stratification analyses were used to evaluate the signature’s reliability. Finally, in situ hybridization experiments were performed to validate GILncSig expression levels between adjacent non-tumor tissues and tumor tissues from HNSCC patients.

Results: Four genomic instability-associated lncRNAs (AC023310.4, AC091729.1, LINC01564, and MIR3142HG) were selected for the prognostic signature. The model was successfully validated using the testing cohort. ROC analysis demonstrated its strong predictive ability for HNSCC prognosis. Univariate and multivariate Cox analyses revealed that the GILncSig was an independent predictor of prognosis. HNSCC patients with a low-risk score showed a substantially better prognosis than the high-risk groups. The in situ hybridization experiments using human HNSCC tissue revealed high GILncSig expression in HNSCC tissues compared with adjacent non-tumor tissues.

Conclusion: We developed a novel GILncSig for prognosis prediction in HNSCC patients, and the components of that signature might be therapeutic targets for HNSCC.

A computational prognostic model of lncRNA signature for clear cell renal cell carcinoma with genome instability

Long non-coding RNAs (lncRNAs) play a critical role in genomic instability and prognosis of cancer patients, but the methods to identify genomic instability-related lncRNAs have yet to be established. In the present study, to assess the prognostic value of lncRNAs associated with genomic instability in clear cell renal cell carcinoma (ccRCC).A computational framework was established based on the mutation hypothesis and combined lncRNA expression and somatic mutation profiles of the ccRCC genome. Furthermore, a prognostic model was developed using the genome instability-derived lncRNA signature GILncSig based on three lncRNA genes (LINC02471, LINC01234, and LINC00460) and verified using multiple independent patient cohorts.This study established an effective computational method to study the role of lncRNAs in genomic instability, with potential applications in identifying new genomic instability-related cancer biomarkers.

Computational detection of a genome instability-derived lncRNA signature for predicting the clinical outcome of lung adenocarcinoma

Evidence has been emerging of the importance of long non-coding RNAs (lncRNAs) in genome instability. However, no study has established how to classify such lncRNAs linked to genomic instability, and whether that connection poses a therapeutic significance. Here, we established a computational frame derived from mutator hypothesis by combining profiles of lncRNA expression and those of somatic mutations in a tumor genome, and identified 185 candidate lncRNAs associated with genomic instability in lung adenocarcinoma (LUAD). Through further studies, we established a six lncRNA-based signature, which assigned patients to the high- and low-risk groups with different prognosis. Further validation of this signature was performed in a number of separate cohorts of LUAD patients. In addition, the signature was found closely linked to genomic mutation rates in patients, indicating it could be a useful way to quantify genomic instability. In summary, this research offered a novel method by through which more studies may explore the function of lncRNAs and presented a possible new way for detecting biomarkers associated with genomic instability in cancers.

Construction of a genome instability-derived lncRNA-based risk scoring system for the prognosis of hepatocellular carcinoma

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, genome instability-associated lncRNAs (GILncRNAs) and their performance in clinical prognostic significance in hepatocellular carcinoma (HCC) are rarely reported. Our study constructed a computational framework integrating somatic mutation information and lncRNA expression profiles of HCC genome and we identified 88 GILncRNAs of HCC. Function enrichment analysis revealed that GILncRNAs were involved in various metabolism processes and genome instability of cancer. A genome instability-derived lncRNA-based gene signature (GILncSig) was constructed using training set data. The performance of GILncSig for outcome prediction was validated in testing set and The Cancer Genome Atlas (TCGA) set. The multivariate cox regression analysis and stratification analysis demonstrated GILncSig could serve as an independent prognostic factor for the overall survival of HCC patients. The time-dependent Receiver Operating Characteristic (ROC) curve illustrated GILncSig outperformed two recently published lncRNA signatures for overall survival prediction. The combination of GILncSig and tumor protein p53 (TP53) mutation status exhibited better prognostic performance in survival evaluation compared to TP53 mutation status alone. AC145343.1 was further validated to be a risk factor for HCC in vitro among GILncSig. Overall, our study provided a novel approach for identification of genome instability-associated lncRNAs and established an independent risk score system for outcome prediction of HCC patients, which provided a new insight for exploring in-depth mechanism and potential therapy strategy.

Construction of a genome instability-derived lncRNA-based risk scoring system for the prognosis of hepatocellular carcinoma

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, genome instability-associated lncRNAs (GILncRNAs) and their performance in clinical prognostic significance in hepatocellular carcinoma (HCC) are rarely reported. Our study constructed a computational framework integrating somatic mutation information and lncRNA expression profiles of HCC genome and we identified 88 GILncRNAs of HCC. Function enrichment analysis revealed that GILncRNAs were involved in various metabolism processes and genome instability of cancer. A genome instability-derived lncRNA-based gene signature (GILncSig) was constructed using training set data. The performance of GILncSig for outcome prediction was validated in testing set and The Cancer Genome Atlas (TCGA) set. The multivariate cox regression analysis and stratification analysis demonstrated GILncSig could serve as an independent prognostic factor for the overall survival of HCC patients. The time-dependent Receiver Operating Characteristic (ROC) curve illustrated GILncSig outperformed two recently published lncRNA signatures for overall survival prediction. The combination of GILncSig and tumor protein p53 (TP53) mutation status exhibited better prognostic performance in survival evaluation compared to TP53 mutation status alone. AC145343.1 was further validated to be a risk factor for HCC in vitro among GILncSig. Overall, our study provided a novel approach for identification of genome instability-associated lncRNAs and established an independent risk score system for outcome prediction of HCC patients, which provided a new insight for exploring in-depth mechanism and potential therapy strategy.

Immunotherapy for gastric cancer: a 2021 update

Gastric cancer, the fifth most frequent cancer and the fourth leading cause of cancer deaths, accounts for a devastating death rate worldwide. Since the majority of patients with gastric cancer are diagnosed at advanced stages, they are not suitable for surgery and present with locally advanced or metastatic disease. Recent advances in immunotherapy have elicited a considerable amount of attention as viable therapeutic options for several cancer types. This work presents a summary of the currently ongoing clinical trials and critically addresses the efficacy of a large spectrum of immunotherapy approaches in the general population for gastric cancer as well as in relation to tumor genetic profiling.

Genome Instability-Related miRNAs Predict Survival, Immune Landscape, and Immunotherapy Responses in Gastric Cancer

BACKGROUND

Increasing evidence suggests that microRNAs (miRNAs) are involved in genome instability (GI) and drive the occurrence of tumors. However, the role of GI-related miRNAs in gastric cancer (GC) remains largely unknown. Herein, we developed a novel GI-related miRNA signature (GIMiSig) and further investigated its role in prognosis, the immune landscape, and immunotherapy responses in GC patients.

METHODS

An analysis of somatic mutation data on 434 gastric cancer cases from The Cancer Genome Atlas (TCGA) database was performed, thereby generating genome stability (GS) and GI groups. By detecting differentially expressed miRNAs between the GS and GI groups that were associated with overall survival, 8 miRNAs were identified and used to construct the GIMiSig.

RESULTS

The GIMiSig showed high accuracy in detecting GC patients. Using GIMiSig to stratify the patients into the high- and low-risk subgroups to predict survival outperformed the use of regular clinical features such as age, gender, or disease stage. Patients with low risk had a more favorable survival time than those with high risk. More importantly, the high-risk patients were associated with decreased UBQLN4 expression, higher accumulation of immune cells, lower Titin (TTN) mutation frequency, worse immunotherapy efficacy, and cancer-associated pathways. Conversely, the low-risk patients were characterized by UBQLN4 overexpression, lower fraction of immune cells, higher TTN mutation frequency, better response to immunotherapy, and GI-related pathways.

CONCLUSION

In summary, we constructed a novel GIMiSig that could stratify GC patients into distinct risk groups that have different survival outcomes and immunotherapy efficacy. The results may provide new clues for improving GC outcomes.

Genomic Instability Promotes the Progression of Clear Cell Renal Cell Carcinoma Through Influencing the Immune Microenvironment

Background: Long non-coding RNAs (lncRNAs) are now under discussion as novel promising biomarkers for clear cell renal cell carcinoma (ccRCC). However, the role of genomic instability-associated lncRNA signatures in tumors has not been thoroughly uncovered. The purpose of our study is to probe the role of genomic instability-derived lncRNA signature (GILncSig) and to further investigate the mechanism of genomic instability-mediated ccRCC progression. Methods: The transcriptome data and somatic mutation profiles of ccRCC as well as clinical characteristics used in this study were obtained from The Cancer Genome Atlas database and Gene Expression Omnibus database. Lasso regression analysis was performed to construct the GILncSig. Gene set enrichment analysis (GSEA) was performed to elucidate the biological functions and relative pathways. CIBERSORT and EPIC algorithm were applied to calculate the proportion of immune cells in ccRCC. ESTIMATE algorithm was utilized to compute the immune microenvironment scores. Results: In total, 148 novel genomic instability-derived lncRNAs in ccRCC were identified. Immediately, on the basis of univariate cox analysis and lasso analysis, a GILncSig was appraised, through which the patients were allocated into High-Risk and Low-Risk groups with significantly different characteristics and prognoses. In addition, we confirmed that the somatic mutation count, tumor mutation burden, and the expression of UBQLN4, which were ascertainably associated with genomic instability, were significantly correlated with the GILncSig, indicating its reliability as a measurement of the genomic instability. Furthermore, the efficiency of GILncSig in prognostic aspects was better than the single mutation gene in ccRCC. In addition, MNX1-AS1 was defined to be a potential biomarker characterized by strong correlation with clinical features. Moreover, GSEA results indicated that the IL6/JAK/STAT3/SIGNALING pathway could be considered as a potential mechanism of genomic instability to influence tumor progression. Besides, the immune microenvironment showed significant differences between the GS-like group and the GU-like group, which was specifically manifested as high expression of CTLA4, GITR, TNFSF14, and regulatory T cells (Tregs) as well as low expression of endothelial cells (ECs) in the GU-like group. Finally, the prognostic value and clinical relevance of GILncSig were verified in GEO datasets and other urinary tumors in TCGA dataset. Conclusion: In conclusion, our study provided a new perspective for the role of lncRNAs in genomic instability and revealed that genomic instability may mediate tumor progression by affecting immunity. Besides, MNX1-AS1 played critical roles in promoting the progression of ccRCC, which may be a potential therapeutic target. What is more, the immune atlas of genomic instability was characterized by high expression of CTLA4, GITR, TNFSF14, and Tregs, and low expression of ECs.

Genomic Instability of Mutation-Derived Gene Prognostic Signatures for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the major cancer-related deaths worldwide. Genomic instability is correlated with the prognosis of cancers. A biomarker associated with genomic instability might be effective to predict the prognosis of HCC. In the present study, data of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used. A total of 370 HCC patients from the TCGA database were randomly classified into a training set and a test set. A prognostic signature of the training set based on nine overall survival (OS)–related genomic instability–derived genes (SLCO2A1, RPS6KA2, EPHB6, SLC2A5, PDZD4, CST2, MARVELD1, MAGEA6, and SEMA6A) was constructed, which was validated in the test and TCGA and ICGC sets. This prognostic signature showed more accurate prediction for prognosis of HCC compared with tumor grade, pathological stage, and four published signatures. Cox multivariate analysis revealed that the risk score could be an independent prognostic factor of HCC. A nomogram that combines pathological stage and risk score performed well compared with an ideal model. Ultimately, paired differential expression profiles of genes in the prognostic signature were validated at mRNA and protein level using HCC and paratumor tissues obtained from our institute. Taken together, we constructed and validated a genomic instability–derived gene prognostic signature, which can help to predict the OS of HCC and help us to explore the potential therapeutic targets of HCC.

Identification of a Four-lncRNA Prognostic Signature for Colon Cancer Based on Genome Instability

LncRNAs (long noncoding RNAs) are closely associated with genome instability. However, the identification of lncRNAs related to the genome instability and their relationship with the prognosis and clinical signature of cancer remains to be explored. In this paper, we analyzed differential lncRNA expression based on the somatic mutation profiles of colon cancer patients from TCGA database and finally identified 153 lncRNAs that are associated with genome instability in colon cancer. Taking four lncRNAs from these 153, we established a genome-instability-related prognostic signature (GIRlncPSig). By applying the GIRlncPSig, we calculated a risk score for each patient, and using their risk scores, we divided them into low- and high-risk groups. We found that the prognosis between the two risk groups was significantly different, and the results were further verified in different independent patient cohorts. Moreover, we observed that the GIRlncPSig was related to somatic mutation rates in colon cancer, indicating that it may be a potential means of measuring genome instability levels in colon cancer. We also revealed that the GIRlncPSig was correlated with BRAF and DPYD mutation rates and that it may be a potential mutation marker for the BRAF and DPYD gene. In summary, we constructed a genome-instability-related lncRNA prognostic signature (GIRlncPSig), which has a significant effect on prognosis prediction and may allow for the discovery of new colon cancer biomarkers.

Genomic instability-associated lncRNA signature predicts prognosis and distinct immune landscape in gastric cancer

Background

Characterized by multiple features, genomic stability-related markers, such as microsatellite instability (MSI), were regulated as an important predictor of chemotherapy and immunity responses in cancer treatment. The aim of our study was to identify a genomic instability-associated long non-coding RNA (lncRNA) signature to help predict the survival and therapy response of gastric cancers (GCs).

Methods

We used RNA sequencing and single nucleotide variant (SNV) data from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) datasets to explore genomic instability-associated lncRNAs. Hierarchical cluster analyses of 197 differentially expressed genomic instability-associated lncRNAs were performed to separate GC patients into two groups, namely, the genomically unstable (GU)-like group and the genomically stable (GS)-like group.

Results

Cox regression analysis was conducted to finally identify six lncRNAs (LINC02678, HOXA10-AS, RHOXF1-AS1, AC010789.1, LINC01150, and TGFB2-AS1) with independent prognostic value to establish the genomic instability-associated lncRNA signature (GILncSig). Based on the SNV analysis, GILncSig was correlated with accumulation of gene mutation counts. Further comparisons between different risk score groups were performed to assess chemotherapy drug sensitivity and immune landscape variations.

Conclusions

Our study not only revealed the genomic instability-associated lncRNAs in GCs, but provided a key method and resource for further studies of the role of these lncRNAs play, and introduced a potential new way to identify genomic instability-associated cancer biomarkers.

Calculated identification of mutator-derived lncRNA signatures of genomic instability to predict the clinical outcome of muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) is one of the most important type of bladder cancer, with a high morbidity and mortality rate. Studies have found that long non-coding RNA (lncRNA) plays a key role in maintaining genomic instability. However, Identification of lncRNAs related to genomic instability (GIlncRNAs) and their clinical significance in cancers have not been extensively studied yet.

METHODS

Here, we downloaded the lncRNA expression profiles, somatic mutation profiles and clinical related data in MIBC patients from The Cancer Genome Atlas (TCGA) database. A lncRNA computational framework was used to find differentially expressed GIlncRNAs. Multivariate Cox regression analysis was used to construct a genomic instability-related lncRNA signature (GIlncSig). Univariate and multivariate Cox analyses were used to assess the independent prognostic for the GIlncSig and other key clinical factors.

RESULTS

We found 43 differentially expressed GIlncRNAs and constructed the GIlncSig with 6 GIlncRNAs in the training cohort. The patients were divided into two risk groups. The overall survival of patients in the high-risk group was lower than that in the low-risk group (P < 0.001), which were further verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression showed that the GIlncSig was an independent prognostic factor. In addition, the GIlncSig correlated with the genomic mutation rate of MIBC, indicating its potential as a measure of the degree of genomic instability. The GIlncSig was able to divide FGFR3 wild- and mutant-type patients into two risk groups, and effectively enhanced the prediction effect.

CONCLUSION

Our study introduced an important reference for further research on the role of GIlncRNAs, and provided prognostic indicators and potential biological therapy targets for MIBC.

Identification of a Novel Prognostic Signature of Genome Instability-Related LncRNAs in Early Stage Lung Adenocarcinoma

Background

Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) play a crucial part in maintaining genomic instability. We therefore identified genome instability-related lncRNAs and constructed a prediction signature for early stage lung adenocarcinoma (LUAD) as well in order for classification of high-risk group of patients and improvement of individualized therapies.

Methods

Early stage LUAD RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) were randomly divided into training set (n = 177) and testing set (n = 176). A total of 146 genomic instability-associated lncRNAs were identified based on somatic mutation profiles combining lncRNA expression profiles from TCGA by the “limma R” package. We performed Cox regression analysis to develop this predictive indicator. We validated the prognostic signature by an external independent LUAD cohort with microarray platform acquired from the Gene Expression Omnibus (GEO).

Results

A genome instability-related six-lncRNA-based gene signature (GILncSig) was established to divide subjects into high-risk and low-risk groups with different outcomes at statistically significant levels. According to the multivariate Cox regression and stratification analysis, the GILncSig was an independent predictive factor. Furthermore, the six-lncRNA signature achieved AUC values of 0.745, 0.659, and 0.708 in the training set, testing set, and TCGA set, respectively. When compared with other prognostic lncRNA signatures, the GILncSig also exhibited better prediction performance.

Conclusion

The prognostic lncRNA signature is a potent tool for risk stratification of early stage LUAD patients. Our study also provided new insights for identifying genome instability-related cancer biomarkers.

Alteration in stemness causes exclusivity between Epstein-Barr virus-positivity and microsatellite instability status in gastric cancer

BACKGROUND

Gastric cancer (GC) is a leading cause of cancer morbidity and mortality worldwide. This is due to the heterogeneous features of GC, which consist of a diverse molecular phenotype. Epstein-Barr virus (EBV)-positive GC and microsatellite instability (MSI)-high GC encompass similar epigenetic traits, including high levels of DNA methylation in CpG islands; however, EBV-positive and MSI-high GCs are mutually exclusive. We aimed to elucidate the underlying mechanism of this exclusivity.

METHODS

We knocked out MLH1 in EBV-positive GC cell lines SNU-719 and NCC24 via CRISPR-Cas9, and evaluated the modified cellular properties in vitro and in vivo. The MSI status of each cell line was screened with two marker capillary electrophoresis, and further diagnosed with five marker capillary electrophoresis and parallel sequencing using 21 markers.

RESULTS

Initial evaluation showed that cell growth, migration, invasion, and MSI status were not affected by MLH1 silencing. However, with prolonged passage, GC cell lines gradually gained MSI and NCC24 cells were transformed to EBV-positive/MSI-high GC cells after 12 months. Furthermore, MLH1 silencing reduced tumor stemness in SNU-719 and NCC24 regardless of the MSI status in vitro and in vivo.

CONCLUSIONS

Our findings suggest that EBV-positivity and MSI-high status are mutually exclusive due to the immediate disadvantage in tumor stemness when MLH1 is silenced, whereas the establishment of MSI-high status in EBV-positive GCs required a longer period.

Identification of the Prognostic Significance of Somatic Mutation-Derived LncRNA Signatures of Genomic Instability in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is a highly heterogeneous tumor with substantial somatic mutations and genome instability, which are emerging hallmarks of cancer. Long non-coding RNAs (lncRNAs) are promising cancer biomarkers that are reportedly involved in genomic instability. However, the identification of genome instability-related lncRNAs (GInLncRNAs) and their clinical significance has not been investigated in LUAD.

Methods: We determined GInLncRNAs by combining somatic mutation and transcriptome data of 457 patients with LUAD and probed their potential function using co-expression network and Gene Ontology (GO) enrichment analyses. We then filtered GInLncRNAs by Cox regression and LASSO regression to construct a genome instability-related lncRNA signature (GInLncSig). We subsequently evaluated GInLncSig using correlation analyses with mutations, external validation, model comparisons, independent prognostic significance analyses, and clinical stratification analyses. Finally, we established a nomogram for prognosis prediction in patients with LUAD and validated it in the testing set and the entire TCGA dataset.

Results: We identified 161 GInLncRNAs, of which seven were screened to develop a prognostic GInLncSig model (LINC01133, LINC01116, LINC01671, FAM83A-AS1, PLAC4, MIR223HG, and AL590226.1). GInLncSig independently predicted the overall survival of patients with LUAD and displayed an improved performance compared to other similar signatures. Furthermore, GInLncSig was related to somatic mutation patterns, suggesting its ability to reflect genome instability in LUAD. Finally, a nomogram comprising the GInLncSig and tumor stage exhibited improved robustness and clinical practicability for predicting patient prognosis.

Conclusion: Our study identified a signature for prognostic prediction in LUAD comprising seven lncRNAs associated with genome instability, which may provide a useful indicator for clinical stratification management and treatment decisions for patients with LUAD.

Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.

Multi-omics analysis at epigenomics and transcriptomics levels reveals prognostic subtypes of lung squamous cell carcinoma

In this study, we identified prognostic biomarkers for lung squamous cell carcinoma (LUSC) by integrating multiple sets of DNA copy number variants (CNV) and methylation variant (MET) data, and performing qPCR and immunohistochemical identification. We examined the expression of CNV and MET in 368 LUSC patients. Gene expression associated with DNA copy number or DNA methylation was identified and four LUSC gene subtypes were defined based on these correlations. The prognosis overall survival (OS) of the iC1 subtype was significantly lower than that in the iC2 and iC4 subtypes. We assessed the immune scores of each subtype and found that the six immune cell scores of the iC3 subtype were significantly higher than the other subtypes (p < 0.01). Three genes associated with prognosis, NFE2L2, ASAH2, and RIMBP2, were identified by comparing the expression of CNV and MET in subtypes. Analysis of mutational differences between subtypes revealed a group of genes with significant mutations between the iC1 and iC4 subtypes. The number of mutations in the NFE2L2 gene in LUSC was significantly higher than that in other genes, and the gene was prognostic. The number of mutations was significantly higher in the best iC4 subtype than the iC1 subtype with the worst prognosis; the other two genes, ASAH2 and RIMBP2, were only found in the worst prognosis of the iC1 subtype. This comprehensive multi-omics analysis of genomics, epigenomics, and transcriptomics data provides new insights into the molecular mechanisms of LUSC and may be helpful in identifying biomolecular markers for early disease diagnosis.

Differential microRNA expression profiles associated with microsatellite status reveal possible epigenetic regulation of microsatellite instability in gastric adenocarcinoma

Background

Although microsatellite instability (MSI) is a powerful predictive biomarker for the efficacy of immunotherapy, the mechanism of MSI in sporadic gastrointestinal cancer is not fully understood. However, epigenetics, particularly microRNAs, has been suggested as one of the main regulators that contribute to the MSI formation.

Methods

We used microRNA expression data of 386 gastric adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database to identify differential microRNA expression profiles by different MSI status. We also obtained putative common target genes of the top differential microRNAs with miRanda online tools, and we analyzed these data by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment (KEGG).

Results

We found that 56 and 67 gastric adenocarcinoma samples were positive for low and high MSI, respectively, and that a high MSI status was associated with age, sex and subregion (P=0.049, 0.014 and 0.007, respectively). In the 67 samples with a high MSI status, expression levels of 14 microRNAs were upregulated but five microRNAs were downregulated as assessed by the fold change (FC), compared with that of the 56 samples with a low MSI status (P<0.05, |FC| >2). Further analysis suggested that the expression of miR-210-3p, miR-582-3p, miR-30a-3p and miR-105-5p predicted a high MSI status (P=4.93×10⁻¹⁰, 5.63×10⁻¹⁰, 3.23×10⁻⁹ and 7.64×10⁻⁴, respectively). Regulation of the transcription pathways ranked the top of lists from both GO and KEGG analyses, and these microRNAs might regulate DNA damage-repair genes that were also associated with a high MSI status.

Conclusions

MiR-30a-3p and miR-105-5p are potential biomarkers for the MSI-H gastric adenocarcinoma, possibly by altering expression of DNA damage-repair genes.

Correlations between microsatellite instability and the biological behaviour of tumours

Purpose

Microsatellites are widely distributed repetitive DNA motifs, accounting for approximately 3% of the genome. Due to mismatch repair system deficiency, insertion or deletion of repetitive units often occurs, leading to microsatellite instability. In this review, we aimed to explore the relationship between MSI and biological behaviour of colorectal carcinoma, gastric carcinoma, lymphoma/leukaemia and endometrial carcinoma, as well as the application of frameshift peptide vaccines in cancer therapy.

Methods

The relevant literature from PubMed and Baidu Xueshu were reviewed in this article. The ClinicalTrials.gov database was searched for clinical trials related to the specific topic.

Results

Microsatellite instability is divided into three subtypes: high-level, low-level microsatellite instability, and stable microsatellites. The majority of tumour patients with high-level microsatellite instability often show a better efficacy and prognosis than those with low-level microsatellite instability or stable microsatellites. In coding regions, especially for genes involved in tumourigenesis, microsatellite instability often results in inactivation of proteins and contributes to tumourigenesis. Moreover, the occurrence of microsatellite instability in coding regions can also cause the generation of frameshift peptides that are thought to be unknown and novel to the individual immune system. Thus, these frameshift peptides have the potential to be biomarkers to raise tumour-specific immune responses.

Conclusion

MSI has the potential to become a key predictor for evaluating the degree of malignancy, efficacy and prognosis of tumours. Clinically, MSI patterns will provide more valuable information for clinicians to create optimal individualized treatment strategies based on frameshift peptides vaccines.

Clustered protocadherins methylation alterations in cancer

Background

Clustered protocadherins (PCDHs) map in tandem at human chromosome 5q31 and comprise three multi-genes clusters: α-, β- and γ-PCDH. The expression of this cluster consists of a complex mechanism involving DNA hub formation through DNA-CCTC binding factor (CTCF) interaction. Methylation alterations can affect this interaction, leading to transcriptional dysregulation. In cancer, clustered PCDHs undergo a mechanism of long-range epigenetic silencing by hypermethylation.

Results

In this study, we detected frequent methylation alterations at CpG islands associated to these clustered PCDHs in all the solid tumours analysed (colorectal, gastric and biliary tract cancers, pilocytic astrocytoma), but not hematologic neoplasms such as chronic lymphocytic leukemia. Importantly, several altered CpG islands were associated with CTCF binding sites. Interestingly, our analysis revealed a hypomethylation event in pilocytic astrocytoma, suggesting that in neuronal tissue, where PCDHs are highly expressed, these genes become hypomethylated in this type of cancer. On the other hand, in tissues where PCDHs are lowly expressed, these CpG islands are targeted by DNA methylation. In fact, PCDH-associated CpG islands resulted hypermethylated in gastrointestinal tumours.

Conclusions

Our study highlighted a strong alteration of the clustered PCDHs methylation pattern in the analysed solid cancers and suggested these methylation aberrations in the CpG islands associated with PCDH genes as powerful diagnostic biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0695-0) contains supplementary material, which is available to authorized users.

Analysis of 8q24.21 miRNA cluster expression and copy number variation in gastric cancer

Aim: To analyze gene expression and copy number of five miRNAs (miR-1204, miR-1205, miR-1206, miR-1207 and miR-1208) localized in this chromosome region in gastric cancer (GC). Materials & methods: 65 paired neoplastic and non-neoplastic specimens collected from GC patients and 20 non-neoplastic gastric tissues from cancer-free individuals were included in this study. The expression levels of the five miRNAs were accessed by real time qPCR and were correlated. Results: MiR-1207-3p, miR-1205, miR-1207-5p and miR-1208 were upregulated in approximately 50% of GC tumors in relation to those of adjacent non-neoplastic tissues. MiR-1205 expression was associated with gain of gene copies and was upregulated in adjacent non-neoplastic samples relative to external controls. Conclusion: The coexpression of the 8q24 miRNAs indicated the role of miR-1205 in the initiation of gastric cancer development.

The significance of gene mutations across eight major cancer types

Mutations occur spontaneously, which can be induced by either chemicals (e.g. benzene) or biological factors (e.g. virus). Not all mutations cause noticeable changes in cellular functions. However, mutation in key cellular genes leads to developmental disorders. It is one of the main ways in which proto-oncogenes can be changed into their oncogenic state. The progressive accumulation of multiple mutations throughout life leads to cancer. In the past few decades, extensive research on cancer biology has discovered many genes and pathways having role in cancer development. In this review, we tried to summarize the current knowledge of mutational effect on different cancer types and its consequences in brief for future reference and guidance of researchers in cancer biology.

Mismatch Repair Status of Gastric Cancer and Its Association with the Local and Systemic Immune Response

BACKGROUND

Microsatellite instability (MSI)-high (MSI-H) colorectal cancer is known to be associated with increased tumor-infiltrating lymphocytes (TILs), elevated host systemic immune response, and a favorable prognosis. In gastric cancer, however, MSI status has rarely been evaluated in the context of TILs and systemic immune response.

MATERIALS AND METHODS

We evaluated data for 345 patients with gastric cancer who underwent gastrectomy with MSI typing. The numbers of TILs were counted after immunohistochemical staining with anti-CD3, CD4, CD8, forkhead box P3 (Foxp3), and granzyme B to quantify the subsets of TILs. To evaluate the systemic immune response, the differential white blood cell count and prognostic nutritional index (PNI) were obtained.

RESULTS

Of the 345 patients, 57 demonstrated MSI-H tumors and 288 demonstrated non-MSI-H tumors. MSI-H tumors carried significantly higher densities of CD8+ T cells, Foxp3+ T cells, and granzyme B+ T cells and a higher ratio of Foxp3/CD4 and granzyme B/CD8. The prognostic impact of TILs differed between patients with MSI-H tumors and those with non-MSI-H tumors. The TIL subsets were not found to be significant prognostic factors for recurrence-free survival (RFS) or overall survival (OS) in the MSI-H tumor group. In the non-MSI-H tumor group, multivariate analysis showed that stage, PNI, and CD4+ T cells were independent prognostic factors for RFS, and stage, PNI, and the Foxp3/CD4 ratio were independent prognostic factors for OS.

CONCLUSIONS

The association between systemic/local immune response and prognosis differed according to MSI status. Different tumor characteristics and prognoses according to MSI status could be associated with the immunogenicity caused by microsatellite instability and subsequent host immune response.

IMPLICATIONS FOR PRACTICE

This study demonstrates that the density of each subset of tumor-infiltrating lymphocytes (TILs) differed between microsatellite instability (MSI)-high and non-MSI-high tumors. Moreover, the prognostic effect of the preoperative systemic immune response status and TILs differed between the MSI-high (MSI-H) and non-MSI-H tumor groups. The present study may help to identify the mechanisms of cancer progression and develop treatment strategies for MSI-high gastric cancer.

Helicobacter pylori Infection, the Gastric Microbiome and Gastric Cancer

After a long period during which the stomach was considered as an organ where microorganisms could not thrive, Helicobacter pylori was isolated in vitro from gastric biopsies, revolutionising the fields of Microbiology and Gastroenterology. Since then, and with the introduction of high-throughput sequencing technologies that allowed deep characterization of microbial communities, a growing body of knowledge has shown that the stomach contains a diverse microbial community, which is different from that of the oral cavity and of the intestine. Gastric cancer is a heterogeneous disease that is the end result of a cascade of events arising in a small fraction of patients colonized with H. pylori. In addition to H. pylori infection and to multiple host and environmental factors that influence disease development, alterations to the composition and function of the normal gastric microbiome, also known as dysbiosis, may also contribute to malignancy. Chronic inflammation of the mucosa in response to H. pylori may alter the gastric environment, paving the way to the growth of a dysbiotic gastric bacterial community. This dysbiotic microbiome may promote the development of gastric cancer by sustaining inflammation and/or inducing genotoxicity. This chapter summarizes what is known about the gastric microbiome in the context of H. pylori-associated gastric cancer, introducing the emerging dimension of the microbiome into the pathogenesis of this highly incident and deadly disease.

Microsatellite instability in gastric cancer: molecular bases, clinical perspectives, and new treatment approaches

Gastric cancer is one of the most aggressive malignancies, with limited treatment options in both locally advanced and metastatic setting, resulting in poor prognosis. Based on genomic characterization, stomach tumour has recently been described as a heterogeneous disease composed by different subtypes, each of them with peculiar molecular aspects and specific clinical behaviour. With an incidence of 22% among all western gastric tumour cases, stomach cancer with microsatellite instability was identified as one of these subgroups. Retrospective studies and limited prospective trials reported differences between gastric cancers with microsatellite stability and those with instability, mainly concerning clinical and pathological features, but also in regard to immunological microenvironment, correlation with prognostic value, and responses to treatment. In particular, gastric cancer with microsatellite instability constitutes a small but relevant subgroup associated with older age, female sex, distal stomach location, and lower number of lymph-node metastases. Emerging data attribute to microsatellite instability status a favourable prognostic meaning, whereas the poor outcomes reported after perioperative chemotherapy administration suggest a detrimental role of cytotoxic drugs in this gastric cancer subgroup. The strong immunogenicity and the widespread expression of immune-checkpoint ligands make microsatellite instability subtype more vulnerable to immunotherapeutic approach, e.g., with anti-PD-L1 and anti-CTLA4 antibodies. Since gastric cancer with microsatellite instability shows specific features and clinical behaviour not overlapping with microsatellite stable disease, microsatellite instability test might be suitable for inclusion in a diagnostic setting for all tumour stages to guarantee the most targeted and effective treatment to every patient.

Hypermethylation of CpG islands is associated with increasing chromosomal damage in chinese lead-exposed workers

Lead is a widely existing environmental pollutant with potential carcinogenicity. To investigate the association of blood lead level (B-Pb) with potential chromosomal damage and cancer, we analyzed micronucleus (MN) frequency of peripheral blood lymphocytes (PBLs) and the methylation status of six human tumor suppressor genes (TSGs) post lead exposure. In the study, 147 lead-exposed workers were divided into two groups according to their B-Pb P₅₀ value, with other 50 lead-unexposed workers as a control group. The cytokinesis-blocked micronucleus (CBMN) assay was performed to detect chromosomal damage of PBLs of both lead-exposed and -unexposed workers. The methylation-specific polymerase chain reaction (MSP-PCR) was further used to examine the methylation status of six TSGs (GSTP1, hMLH1, MGMT, p14, p15, and p16). Results showed that MN frequencies of high B-Pb workers 8.1 ± 3.1‰ and low B-Pb workers 5.7 ± 2.3‰ were significantly higher than that of control group 2.8 ± 1.9‰ (P < 0.01), while the MN frequency of high B-Pb workers was also higher than that of the low B-Pb workers (P < 0.01). The MN frequency in PBLs of lead-exposed group with the methylated TSGs was significantly higher than that in PBLs with the unmethylated TSGs (P < 0.05). Notably, the CpG island methylator phenotype (CIMP) correlated with chromosome damage (P < 0.05). Additionally, workers with high B-Pb had higher chromosome damage than those with low B-Pb (P < 0.05). Taken altogether, the results suggest that lead-exposed workers with CIMP positive and high B-Pb have a higher risk of being vulnerable to tumorigenesis. Environ. Mol. Mutagen. 59:549-556, 2018. © 2018 Wiley Periodicals, Inc.

Single nucleotide polymorphisms rs911160 in AURKA and rs2289590 in AURKB mitotic checkpoint genes contribute to gastric cancer susceptibility

BACKGROUND

Single nucleotide polymorphisms (SNPs) in mitotic checkpoint genes could confer increased susceptibility to gastric cancer (GC). We investigated the association of Aurora kinase A (AURKA), Aurora kinase B (AURKB), Aurora kinase C (AURKC), Polo-like kinase 1 (PLK1) and Budding uninhibited by benzimidazol 3, yeast (BUB3) gene polymorphisms with GC risk.

MATERIALS AND METHODS

Genotyping of 6 SNPs in AURKA (rs911160 and rs8173), AURKB (rs2289590), AURKC (rs11084490), PLK1 (rs42873), and BUB3 (rs7897156) was performed using TaqMan genotyping assays.

RESULTS

Our study demonstrated that rs911160 (AURKA) heterozygous genotype was associated with an increased GC risk (OR = 1.50, 95% CI = 1.01-2.22, P = 0.043). Analysis of rs911160 (AURKA) showed significant association with an increased risk for intestinal type GC (OR = 1.80, 95%CI = 1.01-3.21, P = 0.040) and the risk was significantly higher in women than men (OR = 2.65, 95%CI = 1.02-6.87, P = 0.033). SNP rs2289590 in AURKB might contribute to susceptibility for the development of gastric cancer, particularly in women (OR = 2.08, 95% CI = 1.05-4.09, P = 0.032).

CONCLUSION

Our findings suggested that AURKA (rs911160) and AURKB (rs2289590) polymorphisms could affect GC risk. Further validation studies in larger and multi-ethnical populations are needed to elucidate their functional impact on the development of GC. Environ. Mol. Mutagen. 58:701-711, 2017. © 2017 Wiley Periodicals, Inc.

Promoter methylation of tumor-related genes as a potential biomarker using blood samples for gastric cancer detection

Gene promoter methylation has been reported in gastric cancer (GC). However, the potential applications of blood-based gene promoter methylation as a noninvasive biomarker for GC detection remain to be evaluated. Hence, we performed this analysis to determine whether promoter methylation of 11 tumor-related genes could become a promising biomarker in blood samples in GC. We found that the cyclin-dependent kinase inhibitor 2A (p16), E-cadherin (CDH1), runt-related transcription factor 3 (RUNX3), human mutL homolog 1 (MLH1), RAS association domain family protein 1A (RASSF1A), cyclin-dependent kinase inhibitor 2B (p15), adenomatous polyposis coli (APC), Glutathione S-transferase P1 (GSTP1), TP53 dependent G2 arrest mediator candidate (Reprimo), and O6-methylguanine-DNAmethyl-transferase (MGMT) promoter methylation was notably higher in blood samples of patients with GC compared with non-tumor controls. While death-associated protein kinase (DAPK) promoter methylation was not correlated with GC. Further analyses demonstrated that RUNX3, RASSF1A and Reprimo promoter methylation had a good diagnostic capacity in blood samples of GC versus non-tumor controls (RUNX3: sensitivity = 63.2% and specificity = 97.5%, RASSF1A: sensitivity = 61.5% and specificity = 96.3%, Reprimo: sensitivity = 82.0% and specificity = 89.0%). Our findings indicate that promoter methylation of the RUNX3, RASSF1A and Reprimo genes could be powerful and potential noninvasive biomarkers for the detection and diagnosis of GC in blood samples in clinical practices, especially Reprimo gene. Further well-designed (multi-center) and prospective clinical studies with large populations are needed to confirm these findings in the future.

Pathogenesis of Gastric Cancer: Genetics and Molecular Classification

Gastric cancer is the fifth most incident and the third most common cause of cancer-related death in the world. Infection with Helicobacter pylori is the major risk factor for this disease. Gastric cancer is the final outcome of a cascade of events that takes decades to occur and results from the accumulation of multiple genetic and epigenetic alterations. These changes are crucial for tumor cells to expedite and sustain the array of pathways involved in the cancer development, such as cell cycle, DNA repair, metabolism, cell-to-cell and cell-to-matrix interactions, apoptosis, angiogenesis, and immune surveillance. Comprehensive molecular analyses of gastric cancer have disclosed the complex heterogeneity of this disease. In particular, these analyses have confirmed that Epstein-Barr virus (EBV)-positive gastric cancer is a distinct entity. The identification of gastric cancer subtypes characterized by recognizable molecular profiles may pave the way for a more personalized clinical management and to the identification of novel therapeutic targets and biomarkers for screening, prognosis, prediction of response to treatment, and monitoring of gastric cancer progression.

Distribution of somatic mutations of cancer-related genes according to microsatellite instability status in Korean gastric cancer

In studies of the molecular basis of gastric cancer (GC), microsatellite instability (MSI) is one of the key factors. Somatic mutations found in GC are expected to contribute to MSI-high (H) tumorigenesis. We estimated somatic mutation distribution according to MSI status in 52 matched pair GC samples using the Ion Torrent Ion S5 XL with the AmpliSeq Cancer Hotspot panel.Seventy-five (9.8%) somatic variants consisting of 34 hotspot mutations and 41 other likely pathogenic variants were identified in 34 GC samples. The TP53 mutations was most common (35%, 26/75), followed by EGFR (8%, 6/75), HNF1A (8%, 6/75), PIK3CA (8%, 6/75), and ERBB2 (5%, 4/75). To determine MSI status, 52 matched pair samples were estimated using 15 MSI markers. Thirty-nine MS stable (S), 5 MSI-low (L), and 8 MSI-H were classified. GCs with MSI-H tended to have more variants significantly compared with GCs with MS stable (MSS) and MSI-L (standardized J-T statistic  =  3.161 for number of variants; P  =  .002). The mean number of all variants and hotspot mutations per tumor samples only in GCs with MSI-H were 3.9 (range, 1-6) and 1.1 (range, 0-3), respectively. Whereas, the mean number of all variants and hotspot mutations per tumor samples only in GCs with MSS/MSI-L were 1 (0-5)/0.8 (0-1) and 0.5 (0-3)/0.8 (0-1), respectively.In conclusion, GC with MSI-H harbored more mutations in genes that act as a tumor suppressor or oncogene compared to GC with MSS/MSI-L. This finding suggests that the accumulation of MSIs contributes to the genetic diversity and complexities of GC. In addition, targeted NGS approach allows for detection of common and also rare clinically actionable mutations and profiles of comutations in multiple patients simultaneously. Because GC shows distinctive patterns related to ethnics, further studies pertaining to different racial/ethnic groups or cancer types may reinforce our investigations.

Chromosomal Instability in Gastric Cancer Biology

Gastric cancer (GC) is the fifth most common cancer in the world and accounts for 7% of the total cancer incidence. The prognosis of GC is dismal in Western countries due to late diagnosis: approximately 70% of the patients die within 5 years following initial diagnosis. Recently, integrative genomic analyses led to the proposal of a molecular classification of GC into four subtypes, i.e.,microsatellite-instable, Epstein-Barr virus–positive, chromosomal-instable (CIN), and genomically stable GCs. Molecular classification of GC advances our knowledge of the biology of GC and may have implications for diagnostics and patient treatment. Diagnosis of microsatellite-instable GC and Epstein-Barr virus–positive GC is more or less straightforward. Microsatellite instability can be tested by immunohistochemistry (MLH1, PMS2, MSH2, and MSH6) and/or molecular-biological analysis. Epstein-Barr virus–positive GC can be tested by in situ hybridization (Epstein-Barr virus encoded small RNA). However, with regard to CIN, testing may be more complicated and may require a more in-depth knowledge of the underlying mechanism leading to CIN. In addition, CIN GC may not constitute a distinct subgroup but may rather be a compilation of a more heterogeneous group of tumors. In this review, we aim to clarify the definition of CIN and to point out the molecular mechanisms leading to this molecular phenotype and the challenges faced in characterizing this type of cancer.

Analysis of microsatellite instability in CRISPR/Cas9 editing mice

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR- associated (Cas) protein 9 system is a novel and powerful tool which is widely used for genome editing. CRISPR/Cas9 is RNA-guided and can lead to desired genomic modifications. However, whether the CRISPR/Cas9-mediated genome editing causes genomic alterations and genomic instability, such as microsatellite instability (MSI), is still unknown. Here we detected MSI in 21 CRISPR/Cas9 mouse strains using a panel of 42 microsatellite loci which were selected from our previous studies. Surprisingly, MSI occurrence was common in CRISPR/Cas9 modified genome, and most of the strains (19/21, 90.5%) examined showed MSI. Of 42 loci examined, 8 loci (8/42, 19.05%) exhibited MSI in the Cas9 editing mice. The Ttll9 (4/42, 9.5%) were the most unstable strains, and D10Mit3 and D10Mit198 (9/21, 42.9%) were considered to be the most "hot" loci in the Cas9 strains we tested. Through analyzing the mutation of microsatellite loci, we provide new insights into the genomic alterations of CRISPR/Cas9 models and it will help us for a better understanding of this powerful technology.

Genetic differences stratified by PCR-based microsatellite analysis in gastric intramucosal neoplasia

BACKGROUND

Although genetic alterations in patients with advanced gastric cancer have been extensively studied, those in patients with intramucosal neoplasia (IMN) are still poorly understood.

METHODS

We evaluated genetic differences in 158 IMNs, including 51 low-grade dysplasias, 58 high-grade dysplasias (HGDs), 30 intramucosal cancers (IMCs), and 19 mixed tumors (composed of IMC and HGD within the same tumor), using PCR-based microsatellite analysis [allelic imbalance (AI) and microsatellite instability (MSI)]. We classified the DNA methylation status as a hypermethylated epigenome, a moderately methylated epigenome, or a hypomethylated epigenome. In addition, p53 overexpression, β-catenin nuclear localization, and mucin expression were also examined.

RESULTS

From cluster analysis, the IMNs examined were categorized into four subgroups as follows. Tumors in subgroup 1 were characterized by MSI-high status, a hypermethylated epigenome, and loss or reduction of expression of MLH-1. Tumors in subgroup 2 showed a mixed pattern consisting of AI and MSI. In contrast, tumors in subgroup 3, which showed accumulation of multiple AIs, were closely associated with HGD, IMC, or mixed tumor and exhibited nuclear expression of β-catenin. Tumors in subgroup 4, which were generally low-grade dysplasias, exhibited a low frequency of AIs and no MSI. Although the mucin phenotype was not correlated with any subgroup, expression of mucin was associated with some subgroups. Overexpression of p53 was common in all subgroups.

CONCLUSION

The approach described herein was useful for studying genetic differences in IMNs. In addition, we suggest that stratification of genetic differences may help to identify genetic molecular profiles in IMNs.

Gastric cancer and related epigenetic alterations

Gastric cancer, a malignant and highly proliferative condition, has significantly affected a large population around the globe and is known to be caused by various factors including genetic, epigenetic, and environmental influences. Though the global trend of these cancers is declining, an increase in its frequency is still a threat because of changing lifestyles and dietary habits. However, genetic and epigenetic alterations related to gastric cancers also have an equivalent contribution towards carcinogenic development. DNA methylation is one of the major forms of epigenetic modification which plays a significant role in gastric carcinogenesis. Methylation leads to inactivation of some of the most important genes like DNA repair genes, cell cycle regulators, apoptotic genes, transcriptional regulators, and signalling pathway regulators; which subsequently cause uncontrolled proliferation of cells. Mutations in these genes can be used as suitable prognostic markers for early diagnosis of the disease, since late diagnosis of gastric cancers has a huge negative impact on overall patient survival. In this review, we focus on the important epigenetic mutations that contribute to the development of gastric cancer and the molecular pathogenesis underlying each of them. Methylation, acetylation, and histone modifications play an integral role in the onset of genomic instability, one of the many contributory factors to gastric cancer. This article also covers the constraints of incomplete knowledge of epigenetic factors influencing gastric cancer, thus throwing light on our understanding of the disease.

Pathogenesis of Gastric Cancer: Genetics and Molecular Classification

Gastric cancer is the fifth most incident and the third most common cause of cancer-related death in the world. Infection with Helicobacter pylori is the major risk factor for this disease. Gastric cancer is the final outcome of a cascade of events that takes decades to occur and results from the accumulation of multiple genetic and epigenetic alterations. These changes are crucial for tumor cells to expedite and sustain the array of pathways involved in the cancer development, such as cell cycle, DNA repair, metabolism, cell-to-cell and cell-to-matrix interactions, apoptosis, angiogenesis, and immune surveillance. Comprehensive molecular analyses of gastric cancer have disclosed the complex heterogeneity of this disease. In particular, these analyses have confirmed that Epstein-Barr virus (EBV)-positive gastric cancer is a distinct entity. The identification of gastric cancer subtypes characterized by recognizable molecular profiles may pave the way for a more personalized clinical management and to the identification of novel therapeutic targets and biomarkers for screening, prognosis, prediction of response to treatment, and monitoring of gastric cancer progression.