Impact of NR5A2 and RYR2 3'UTR polymorphisms on the risk of breast cancer in a Chinese Han population

NR5A2 gene affects the overall survival of LUAD patients by regulating the activity of CSCs through SNP pathway by OCLR algorithm and immune score

Objective

Differentially expressed genes (DEGs) in lung adenocarcinoma (LUAD) tumor stem cells were screened, and the biological characteristics of NR5A2 gene were investigated.

Methods

The expression and prognosis of NR5A2 in human LUAD were predicted and analyzed through bioinformatics analysis from a human cancer database. Gene expression and clinical data of LUAD tumor and normal lung tissues were obtained from The Cancer Genome Atlas (TCGA) database, and DEGs associated with lung cancer tumor stem cells (CSCs) were screened. Univariate and multivariate Cox regression models were used to screen and establish prognostic risk prediction models. The immune function of the patients was scored according to the model, and the relative immune functions of the high- and low-risk groups were compared to determine the difference in survival prognosis between the two groups. In addition, we calculated the index of stemness based on the transcriptome of the samples using one-class linear regression (OCLR).

Results

Bioinformatics analysis of a clinical cancer database showed that NR5A2 was significantly decreased in human LUAD tissues than in normal lung tissues, and the decrease in NR5A2 gene expression shortened the overall survival and progression-free survival of patients with LUAD.

Conclusion

The NR5A2 gene may regulate LUAD tumor stem cells through selective splicing mutations, thereby affecting the survival and prognosis of patients with lung cancer, and the NR5A2 gene may regulate CSCs through single nucleotide polymorphism.

Construction of a risk scoring system using clinical factors and RYR2 polymorphisms for bleeding complications in patients on direct oral anticoagulants

Introduction: Bleeding is one of the most undesirable complications of direct oral anticoagulants (DOACs). While the ryanodine receptor (RYR2) has been related to cardiac diseases, research on bleeding complications is lacking. This study aimed to elucidate the association between RYR2 and bleeding risk to develop the risk scoring system in patients treated with DOACs. Methods: This study was a retrospective analysis of prospectively collected samples. We selected ten SNPs within the RYR2 gene, and two models were constructed (Model I: demographic factors only, Model II: demographic and genetic factors) in multivariable analysis. Independent risk factors for bleeding were used to develop a risk scoring system. Results: A total of 447 patients were included, and 49 experienced either major bleeding or clinically relevant non-major bleeding. In Model I, patients using rivaroxaban and experiencing anemia exhibited an increased bleeding risk after adjusting for covariates. Upon incorporating genetic factors into Model I, a significant association with bleeding was also observed in cases of overdosing on DOACs and in patients with a creatinine clearance (CrCl) < 30 mL/min, in addition to rivaroxaban and anemia (Model II). Among genetic factors, RYR2 rs12594 GG, rs17682073 AA, rs3766871 GG, and rs6678625 T alleles were associated with bleeding complications. The area under the receiver operating characteristic curve (AUROC) of Model I was 0.670, whereas that of Model II increased to 0.803, demonstrating better performance with the inclusion of genetic factors. Using the significant variables in Model II, a risk scoring system was constructed. The predicted bleeding risks for scores of 0, 1-2, 3-4, 5-6, 7-8, and 9-10 points were 0%, 1.2%, 4.6%, 15.7%, 41.7%, and 73.3%, respectively. Conclusion: This study revealed an association between RYR2 and bleeding complications among patients taking DOACs and established a risk scoring system to support individualized DOAC treatment for these patients.

NR5A2 as a potential target for exercise to improve metabolic syndrome

BACKGROUND

Metabolic syndrome is a syndrome of a variety of metabolic disorders. Exercise is beneficial to the human body. However, the association of NR5A2 and exercise with metabolic syndrome remains unclear.

METHODS

Download the GSE10540 and GSE12385 from GEO database. Bioinformatics analysis was used to screen the hub molecular of the metabolic syndrome. Forty 3-week-old C57BL/6J male mice were used in this study. The mean body weight was (17.5 ± 2.1) g. After 10 days of adaptive feeding, they were randomly divided into 4 groups according to the random number table method: Model + Exercise (n = 10), Model (n = 10), Model/NR5A2-OE (n = 10), Model/NR5A2-KO (n = 10). Western Blotting was performed to detect the expression of hub genes and signaling pathway.

RESULTS

There were 349 DEGs in GSE10540 and 49 DEGs in GSE12385. 10 core genes were obtained. GO showed that differentially expressed genes were mainly enriched in vascular morphogenesis, contractile fiber fraction, chemotaxis, and MAPK cascade regulation. KEGG showed that MAPK signaling pathway was a significant section in the metabolic syndrome. PIK3R2, STRA8, FLT1, DMRT1, FGF22, NR5A2, and FLT were up-regulated and PRDM14, POU5F1, and KDR were down-regulated in metabolic syndrome after exercise.

CONCLUSION

The expression of NR5A2 is down-regulated in metabolic syndrome, and exercise can increase the expression level of NR5A2. NR5A2 might be used as a potential target for exercise to improve metabolic syndrome.

Comprehensive Analysis of Genomic and Expression Data Identified Potential Markers for Predicting Prognosis and Immune Response in CRC

Colorectal cancer (CRC) is the most prevalent type of malignant tumor of the gastrointestinal tract. In the current study, we characterized the landscape of genomic alterations in CRC patients. Based on the results of whole-exome sequencing (WES), we identified 31 significantly mutated genes. Among them, several genes including TP53, KRAS, APC, PI3KCA, and BRAF were reported as significantly mutated genes in previous studies. In the current study, the most frequently mutated gene was TP53, which encodes tumor suppressor p53, affecting approximately 60% of CRC patients. In addition, we performed the expression profiles of significantly mutated genes between the normal group and tumor groups and identified 20 differentially expressed genes (DEGs); among them, CSMD3, DCHS2, LRP2, RYR2, and ZFHX4 were significantly negatively correlated with PFS. Moreover, consensus clustering analysis for CRC based on the expression of significantly somatic mutated genes was performed. In total, three subtypes of CRC were identified in CRC, including cluster1 (n = 453), cluster2 (n = 158), and cluster 3 (n = 9), based on expression level of significantly somatic mutated genes. Clinicopathological features analysis showed subtype C1 had the longest progression-free survival (PFS) with median time of 8.2 years, while subtypes C2 and C3 had 4.1 and 2.7 years of PFS, respectively. Moreover, we found three subtypes related to tumor infiltration depth, lymph node metastasis, and distant metastasis. Immune infiltration analysis showed the tumor infiltration levels of B cell native, T cell CD8+, T cell CD4+ memory activated, T cell gamma delta, NK cell resting, macrophage M0, macrophage M2, myeloid dendritic cell activated, mast cell activated, and mast cell resting significantly changed among the three groups, demonstrating the three subgroups classified by 22 somatically significantly mutated genes had a high capacity to differentiate patients with different immune statuses, which is helpful for the prediction of immunotherapy response of CRC patients. Our findings could provide novel potential predictive indicators for CRC prognosis and therapy targets for CRC immunotherapy.

A Novel Artificial Neural Network Prognostic Model Based on a Cancer-Associated Fibroblast Activation Score System in Hepatocellular Carcinoma

Introduction

Hepatocellular carcinoma (HCC) ranks fourth as the most common cause of cancer-related death. It is vital to identify the mechanism of progression and predict the prognosis for patients with HCC. Previous studies have found that cancer-associated fibroblasts (CAFs) promote tumor proliferation and immune exclusion. However, the information about CAF-related genes is still elusive.

Methods

The data were obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus databases. On the basis of single-cell transcriptome and ligand–receptor interaction analysis, CAF-related genes were selected. By performing Cox regression and random forest, we filtered 12 CAF-related prognostic genes for the construction of the ANN model based on the CAF activation score (CAS). Then, functional, immune, mutational, and clinical analyses were performed.

Results

We constructed a novel ANN prognostic model based on 12 CAF-related prognostic genes. Cancer-related pathways were enriched, and higher activated cell crosstalk was identified in high-CAS samples. High immune activity was observed in high-CAS samples. We detected three differentially mutated genes (NBEA, RYR2, and FRAS1) between high- and low-CAS samples. In clinical analyses, we constructed a nomogram to predict the prognosis of patients with HCC. 5-Fluorouracil had higher sensitivity in high-CAS samples than in low-CAS samples. Moreover, some small-molecule drugs and the immune response were predicted.

Conclusion

We constructed a novel ANN model based on CAF-related genes. We revealed information about the ANN model through functional, mutational, immune, and clinical analyses.

LINC01194 recruits NUMA1 to promote ubiquitination of RYR2 to enhance malignant progression in triple-negative breast cancer

Long intergenic nonprotein coding RNA 1194 (LINC01194) has been reported as an oncogene in several cancer types, but its expression and potential role in triple-negative breast cancer (TNBC) are still unclear. We found that LINC01194 was significantly highly expressed in TNBC based on The Cancer Genome Atlas (TCGA) database. Data from in vitro experiments and in vivo assays demonstrated that LINC01194 promoted TNBC progression. Through bioinformatics prediction, mass spectrometry, and mechanical experiments, we found that LINC01194 could recruit nuclear mitotic apparatus protein 1 (NUMA1) to bind to the untranslated region (3'UTR) of ubiquitin-conjugating enzyme E2 C (UBE2C) 3' and stabilize UBE2C mRNA. Moreover, we found that UBE2C acted as an ubiquitin ligase to promote the ubiquitination and degradation of ryanodine receptor type 2 (RYR2) that inhibited the progression of TNBC by inhibiting the Wnt/β-catenin signaling pathway. In summary, LINC01194 activate the Wnt/β-catenin signaling pathway and accelerates the malignant progression of TNBC by recruiting NUMA1 to stabilize UBE2C mRNA and thus promotes RYR2 ubiquitination and degradation. These findings might provide a more effective therapeutic strategy for TNBC patients.

Resveratrol inhibits the expression of RYR2 and is a potential treatment for pancreatic cancer

Resveratrol is a polyphonous natural compound that has cardioprotective, anticancer, and anti-inflammatory properties. Studies have proved that resveratrol (RES) inhibits cancer cell proliferation, migration, and invasion and promotes apoptosis. Elevated expression of ryanodine receptor type 2 (RYR2) may participate in the pathway responsible for calcium metabolism as well as anti-apoptosis and anti-autophagy events in malignant tumor cells. However, the underlying molecular mechanisms of RES anticancer effects with RYR2 are not completely understood in pancreatic cancer. The aim of the present study was tantamount to study the effect of RES in human pancreatic cancer and investigate the underlying mechanisms of RES. We found that RES inhibits proliferation, migration, and invasion and suppresses RYR2 expression in pancreatic cancer cells. In addition, RYR2 knockdown impedes the proliferation, migration, and invasiveness of pancreatic cancer cells. RYR2 knockdown can also increase PTEN expression, while increased RYR2 expression can inhibit PTEN expression. Moreover, RES can upregulate PTEN expression. Taken together, these results indicate that RES could play an antitumor role by decreasing RYR2 expression.

RYR2 mutation in non-small cell lung cancer prolongs survival via down-regulation of DKK1 and up-regulation of GS1-115G20.1: A weighted gene Co-expression network analysis and risk prognostic models

RYR2 mutation is clinically frequent in non-small cell lung cancer (NSCLC) with its function being elusive. We downloaded lung squamous cell carcinoma and lung adenocarcinoma samples from the TCGA database, split the samples into RYR2 mutant group (n = 337) and RYR2 wild group (n = 634), and established Kaplan-Meier curves. The results showed that RYR2 mutant group lived longer than the wild group (p = 0.027). Weighted gene co-expression network analysis (WGCNA) of differentially expressed genes (DEGs) yielded prognosis-related genes. Five mRNAs and 10 lncRNAs were selected to build survival prognostic models with other clinical features. The AUCs of 2 models are 0.622 and 0.565 for predicting survival at 3 years. Among these genes, the AUCs of DKK1 and GS1-115G20.1 expression levels were 0.607 and 0.560, respectively, which predicted the 3-year survival rate of NSCLC sufferers. GSEA identified an association of high DKK1 expression with TP53, MTOR, and VEGF expression. Several target miRNAs interacting with GS1-115G20.1 were observed to show the relationship with the phenotype, treatment, and survival of NSCLC. NSCLC patients with RYR2 mutation may obtain better prognosis by down-regulating DKK1 and up-regulating GS1-115G20.1.

Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer

BACKGROUND

Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood.

METHODS

Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions.

RESULTS

We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages.

CONCLUSION

RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.

Impacts of LOC105371267 Variants on Breast Cancer Susceptibility in Northern Chinese Han Females: A Population-Based Case-Control Study

Background

LOC105371267, also known as PR-lncRNA1, was reported to be a p53-regulated long noncoding RNA (lncRNA), which played an essential role in the pathogenesis of breast cancer (BC). We aimed to observe the potential association between LOC105371267 polymorphisms and BC risk in Northern Chinese Han females.

Methods

Totally, 555 healthy individuals and 561 patients with BC were recruited. Five candidate SNPs (rs6499221, rs3931698, rs8044565, rs3852740, and rs111577197) of LOC105371267 were genotyped with the Agena MassARRAY system. Odds ratio (OR) and 95% confidence intervals (CIs) were applied to evaluate the relationship of LOC105371267 genetic polymorphisms with BC susceptibility. Additionally, stratification analysis based on clinical features and haplotype analysis were also conducted. Finally, multifactor dimensionality reduction (MDR) analysis was performed to assess the SNP-SNP interaction among LOC105371267 variants, and false-positive report probability (FPRP) analysis was used to validate the result of this study.

Results

In this study, rs3931698 was a protective factor of BC in total (GG homozygote: OR = 0.30, 95% CI: 0.11–0.82, p=0.018; recessive model: OR = 0.30, 95% CI: 0.11–0.84, p=0.021). In stratification analysis based on the average age of 52 years and clinical characteristics (PR status, III-IV TNM stage), rs3931698 was also demonstrated to be associated with BC susceptibility. In addition, rs6499221 and rs3852740 were also associated with BC susceptibility among patients at age <52 years and patients with BC in a positive status. Thus, the haplotype analysis had a negative result for the incidence of BC (p > 0.05), and haplotype consisting of rs8044565 and rs111577197 was nonsignificantly associated with the BC risk. Finally, MDR and FPRP analyses also validated the result of this study.

Conclusion

Polymorphisms rs3931698, rs6499221, and rs3852740 of LOC105371267 were found to be associated with the risk of BC in total, and stratification analysis in the Northern Chinese Han females suggested that LOC105371267 variants might be helpful to predict BC progression.

Association of RYR2 Mutation With Tumor Mutation Burden, Prognosis, and Antitumor Immunity in Patients With Esophageal Adenocarcinoma

Background: Esophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, with the benefit in EAC thus far been limited to a small fraction of patients.

Methods: Using somatic mutation data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium, we delineated the somatic mutation landscape of EAC patients from US and England. Based on the expression data of TCGA cohort, multiple bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment.

Results: We found that RYR2 was a common frequently mutated gene in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC.

Conclusion: This study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.