Potentially functional variants of HBEGF and ITPR3 in GnRH signaling pathway genes predict survival of non-small cell lung cancer patients

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohorts PCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Type 3 IP3 receptor: Its structure, functions, and related disease implications

Cell-fate decisions depend on the precise and strict regulation of multiple signaling molecules and transcription factors, especially intracellular Ca2+ homeostasis and dynamics. Type 3 inositol 1,4,5-triphosphate receptor (IP3R3) is an a tetrameric channel that can mediate the release of Ca2+ from the endoplasmic reticulum (ER) in response to extracellular stimuli. The gating of IP3R3 is regulated not only by ligands but also by other interacting proteins. To date, extensive research conducted on the basic structure of IP3R3, as well as its regulation by ligands and interacting proteins, has provided novel perspectives on its biological functions and pathogenic mechanisms. This review aims to discuss recent advancements in the study of IP3R3 and provides a comprehensive overview of the relevant literature pertaining to its structure, biological functions, and pathogenic mechanisms.

Tumor microenvironment characterization in colorectal cancer to identify prognostic and immunotherapy genes signature

BACKGROUND

The tumor microenvironment (TME) plays a crucial role in tumorigenesis, progression, and therapeutic response in many cancers. This study aimed to comprehensively investigate the role of TME in colorectal cancer (CRC) by generating a TMEscore based on gene expression.

METHODS

The TME patterns of CRC datasets were investigated, and the TMEscores were calculated. An unsupervised clustering method was used to divide samples into clusters. The associations between TMEscores and clinical features, prognosis, immune score, gene mutations, and immune checkpoint inhibitors were analyzed. A TME signature was constructed using the TMEscore-related genes. The results were validated using external and clinical cohorts.

RESULTS

The TME pattern landscape was for CRC was examined using 960 samples, and then the TMEscore pattern of CRC datasets was evaluated. Two TMEscore clusters were identified, and the high TMEscore cluster was associated with early-stage CRC and better prognosis in patients with CRC when compared with the low TMEscore clusters. The high TMEscore cluster indicated elevated tumor cell scores and tumor gene mutation burden, and decreased tumor purity, when compared with the low TMEscore cluster. Patients with high TMEscore were more likely to respond to immune checkpoint therapy than those with low TMEscore. A TME signature was constructed using the TMEscore-related genes superimposing the results of two machine learning methods (LASSO and XGBoost algorithms), and a TMEscore-related four-gene signature was established, which had a high predictive value for discriminating patients from different TMEscore clusters. The prognostic value of the TMEscore was validated in two independent cohorts, and the expression of TME signature genes was verified in four external cohorts and clinical samples.

CONCLUSION

Our study provides a comprehensive description of TME characteristics in CRC and demonstrates that the TMEscore is a reliable prognostic biomarker and predictive indicator for patients with CRC undergoing immunotherapy.

Inositol 1,4,5-trisphosphate receptor gene variants are related to the risk of breast cancer in a Chinese population

BACKGROUND

Mammalian inositol 1,4,5-trisphosphate receptor (ITPR) genes encode ubiquitously expressed endoplasmic reticulum Ca²⁺ channels that have recently been shown to be closely linked to the pathogenesis of several cancers. However, few studies to date have explored associations between ITPR gene family single nucleotide polymorphisms (SNPs) and breast cancer risk.

METHODS

In the present case-control study, 12 SNPs in the potential functional regions of the ITPR1, ITPR2, and ITPR3 genes were genotyped using an Illumina Infinium® Beadchip in 2095 Chinese women (1032 cases and 1063 controls).

RESULTS

Multivariate logistic regression analyses indicated that a missense SNP in the ITPR3 coding region (rs2229642) was significantly related to breast cancer risk when using an additive model in this study (rs2229642-adjusted odds ratio = 1.40, 95% confidence interval = 1.12-1.74, p = 2.97 × 10^-3 ). Expression quantitative trait loci analyses indicated that the SNP rs2229642 was associated with reduced ITPR3 expression levels (p = 3.2 × 10^-7 ) and with marked reductions in the expressions of several proximal genes, including BAK1, GRM4, HLA-DOB, and UQCC2 (p = 0.013, 0.018, 3.4 × 10^-3 , 3.8 × 10^-5 ), suggesting that it may further regulate other genes associated with oncogenic susceptibility. Kaplan-Meier analyses indicated that the patients with higher ITPR3 expression exhibited significantly poorer outcomes compared to the patients with lower expression of this gene (hazard ratio = 1.11, 95% confidence interval = 1-1.23, p = 0.046).

CONCLUSIONS

The results indicated that genetic variant in the coding region of ITPR3 gene may regulate the expressions of its host and some other cancer-related genes, as well as act as potential predictive biomarker for susceptibility to breast cancer in the Chinese population.

Identification of an Immune-Related Gene Signature Associated with Prognosis and Tumor Microenvironment in Esophageal Cancer

Background

Esophageal cancer (EC) is a common malignant tumor of the digestive system with high mortality and morbidity. Current evidence suggests that immune cells and molecules regulate the initiation and progression of EC. Accordingly, it is necessary to identify immune-related genes (IRGs) affecting the biological behaviors and microenvironmental characteristics of EC.

Methods

Bioinformatics methods, including differential expression analysis, Cox regression, and immune infiltration prediction, were conducted using R software to analyze the Gene Expression Omnibus (GEO) dataset. The Cancer Genome Atlas (TCGA) cohort was used to validate the prognostic signature. Patients were stratified into high- and low-risk groups for further analyses, including functional enrichment, immune infiltration, checkpoint relevance, clinicopathological characteristics, and therapeutic sensitivity analyses.

Results

A prognostic signature was established based on 21 IRGs (S100A7, S100A7A, LCN1, CR2, STAT4, GAST, ANGPTL5, TRAV39, F2RL2, PGLYRP3, KLRD1, TRIM36, PDGFA, SLPI, PCSK2, APLN, TICAM1, ITPR3, MAPK9, GATA4, and PLAU). Compared with high-risk patients, better overall survival rates and clinicopathological characteristics were found in low-risk patients. The areas under the curve of the two cohorts were 0.885 and 0.718, respectively. Higher proportions of resting CD4⁺ memory T lymphocytes, M2 macrophages, and resting dendritic cells and lower proportions of follicular helper T lymphocytes, plasma cells, and neutrophils were found in the high-risk tumors. Moreover, the high-risk group showed higher expression of CD44 and TNFSF4, lower expression of PDCD1 and CD40, and higher TIDE scores, suggesting they may respond poorly to immunotherapy. High-risk patients responded better to chemotherapeutic agents such as docetaxel, doxorubicin, and gemcitabine. Furthermore, IRGs associated with tumor progression, including PDGFA, ITPR3, SLPI, TICAM1, and GATA4, were identified.

Conclusion

Our immune-related signature yielded reliable value in evaluating the prognosis, microenvironmental characteristics, and therapeutic sensitivity of EC and may help with the precise treatment of this patient population.

Potentially functional variants of MAP3K14 in the NF-κB signaling pathway genes predict survival of HBV-related hepatocellular carcinoma patients

Background

The NF-κB signaling pathway plays an important role in associating inflammation with tumor development and progression. However, few studies have reported that roles of genetic variants of the NF-κB signaling pathway genes in survival of patients with HBV-related hepatocellular carcinoma (HBV-HCC), especially with regards to potentially functional SNPs.

Methods

We used multivariate Cox proportional hazards regression to evaluate associations between 2,060 single nucleotide polymorphisms (SNPs) in 20 NF-κB signaling pathway genes and survival of 866 HBV-HCC patients, which were randomly split (1:1) into discovery and validation datasets. Expression quantitative trait loci (eQTL) analysis was conducted to identify associations between survival-associated SNPs and mRNA expression of corresponding genes. Furthermore, online database was used to assess mRNA expression of corresponding genes and survival. Finally, receiver operating characteristic (ROC) curves were used to assess the prediction accuracy of models integrating both clinical and genetic variables on HCC survival.

Results

A total of 6 SNPs in MAP3K14 remained significantly associated with OS of HBV-HCC patients (P<0.05, BFDP<0.8). Further eQTL analysis demonstrated that significant correlations between the rs2074292 (G>A) A allele was associated with higher mRNA expression levels of MAP3K14 (P=0.044) in normal liver tissue, which was associated with worse survival of HBV-HCC patients. In the additive model, after adjusting for age, sex, smoking status, drinking status, AFP level, cirrhosis, embolus and BCLC stage, the combined dataset showed that HBV-HCC patients carrying the rs2074292 AA and GA genotypes (HR=1.71, 95%CI= 1.29-2.27, P=0.000) (HR=1.40, 95%CI=1.10-1.77, P=0.005) have worse OS than GG genotype, respectively. The addition of risk genotypes to the prediction models increased the AUC significantly from 71.15% to 73.11% (P=0.012) and from 72.55% to 74.21% (P=0.010) for 1-year and 3-year OS, respectively.

Conclusion

Our study indicated that MAP3K14 rs2074292 A allele may be a potential predictor of HBV-HCC survival, likely regulating MAP3K14 mRNA expression.

Genetic variants in DDO and PEX5L in peroxisome-related pathways predict non-small cell lung cancer survival

Peroxisomes play a role in lipid metabolism and regulation of reactive oxygen species, but its role in development and progression of non-small cell lung cancer (NSCLC) is not well understood. Here, we investigated the associations between 9708 single-nucleotide polymorphisms (SNPs) in 113 genes in the peroxisome-related pathways and survival of NSCLC patients from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and the Harvard Lung Cancer Susceptibility (HLCS) study. In 1185 NSCLC patients from the PLCO trial, we found that 213 SNPs were significantly associated with NSCLC overall survival (OS) (p ≤ 0.05, Bayesian false discovery probability [BFDP] ≤ 0.80), of which eight SNPs were validated in the HLCS data set. In a multivariate Cox proportional hazards regression model, two independent SNPs (rs9384742 DDO and rs9825224 PEX5L) were significantly associated with NSCLC survival (hazards ratios [HR] of 1.17 with 95% CI [confidence interval] of 1.06-1.28 and 0.86 with 95% CI of 0.77-0.96, respectively). Patients with one or two protective genotypes had a significantly higher OS (HR: 0.787 [95% CI: 0.620-0.998] and 0.691 [95% CI: 0.543-0.879], respectively). Further expression quantitative trait loci analysis using whole blood and lung tissue showed that the minor allele of rs9384742 DDO was significantly associated with decreased messenger RNA (mRNA) expression levels and that DDO expression was also decreased in NSCLC tumor tissue. Additionally, high PEX5L expression levels were significantly associated with lower survival of NSCLC. Our data suggest that variants in these peroxisome-related genes may influence gene regulation and are potential predictors of NSCLC OS, once validated by additional studies.

Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer

Inositol 1,4,5-Triphosphate Receptor Family (ITPRs) are necessary intracellular Ca2+-release channel encoders and participate in mammalian cell physiological and pathological processes. Previous studies have suggested that ITPRs participate in tumorigenesis of multiple cancers. Nevertheless, the diverse expression profiles and prognostic significance of three ITPRs in pancreatic cancer have yet to be uncovered. In this work, we examined the expression levels and survival dates of ITPRs in patients with pancreatic cancer. As a result, we identified that ITPR1 and ITPR3 expression levels are significantly elevated in cancerous specimens. Survival data revealed that over-expression of ITPR2 and ITPR3 resulted in unfavourable overall survival and pathological stage. The multivariate Cox logistic regression analysis showed that ITPR3 could be an independent risk factor for PAAD patient survival. Moreover, to investigate how ITPRs work, co-expressed genes, alterations, protein-protein interaction, immune infiltration, methylation, and functional enrichment of ITPRs were also analyzed. Then, we evaluated these findings in clinical samples. Moreover, the gain and loss of function of ITPR3 were also conducted. The electron microscope assay was employed to explore the role of ITPR3 in pancreatic cancer cell lines' endoplasmic reticulum stress. In summary, our findings demonstrated that ITPR3 has the potential to be drug targets and biomarkers for human pancreatic cancer.

A Genomic Signature Reflecting Fibroblast Infiltration Into Gastric Cancer Is Associated With Prognosis and Treatment Outcomes of Immune Checkpoint Inhibitors

Background: The immunotherapy efficacy in gastric cancer (GC) is limited. Cancer-associated fibroblasts (CAFs) induce primary resistance to immunotherapy. However, CAF infiltration in tumors is difficult to evaluate due to the lack of validated and standardized quantified methods. This study aimed to investigate the impact of infiltrating CAFs alternatively using fibroblast-associated mutation scoring (FAMscore). Methods: In a GC cohort from Affiliated Hospital of Jiangsu University (AHJU), whole exon sequencing of genomic mutations, whole transcriptome sequencing of mRNA expression profiles, and immunofluorescence staining of tumor-infiltrating immune cells were performed. GC data from The Cancer Genome Atlas were used to identify genetic mutations which were associated with overall survival (OS) and impacted infiltrating CAF abundance determined by transcriptome-based estimation. FAMscore was then constructed through a least absolute shrinkage and selection operator Cox regression model and further validated in AHJU. The predictive role of FAMscore for immunotherapy outcomes was tested in 1 GC, one melanoma, and two non-small-cell lung cancer (NSCLC-1 and -2) cohorts wherein participants were treated by immune checkpoint inhibitors. Results: FAMscore was calculated based on a mutation signature consisting of 16 genes. In both TCGA and AHJU, a high FAMscore was an independent predictor for poor OS of GC patients. FAMscore was associated with immune-associated genome biomarkers, immune cell infiltration, and signaling pathways of abnormal immunity. Importantly, patients with high FAMscore presented inferiority in the objective response rate of immunotherapy compared to those with low FAMscore, with 14.6% vs. 66.7% (p<0.001) in GC, 19.6% vs. 68.2% (p<0.001) in NSCLC-1, 23.1% vs 75% (p = 0.007) in NSCLC-2, and 40.9% vs 75% (p = 0.037) in melanoma. For available survival data, a high FAMscore was also an independent predictor of poor progression-free survival in NSCLC-1 (HR = 2.55, 95% CI: 1.16-5.62, p = 0.02) and NSCLC-2 (HR = 5.0, 95% CI: 1.13-22.19, p = 0.034) and poor OS in melanoma (HR = 3.48, 95% CI: 1.27-9.55, p = 0.015). Conclusions: Alternative evaluation of CAF infiltration in GC by determining the FAMscore could independently predict prognosis and immunotherapy outcomes. The FAMscore may be used to optimize patient selection for immunotherapy.

The biological behavior of tRNA-derived fragment tRF-Leu-AAG in pancreatic cancer cells

Pancreatic cancer (PC) is a life-threatening cancer with increasing incidence in developed countries. Reports indicate that tRNA-derived fragments (tRFs) are possible therapeutic targets and biomarkers for cancer treatment. Nonetheless, the effect of tRF-Leu-AAG on PC is unclear. This study aims to explore the role of tRF-Leu-AAG and upstream frameshift mutant 1 (UPF1) in the development of PC and its potential underlying mechanisms. High-throughput second-generation sequencing techniques were used to detect the expression of tRFs in cancerous and adjacent normal tissues from PC patients. The role of tRF-Leu-AAG proliferation in PC cells was investigated via the Cell Counting Kit-8 (CCK8) assay. The effect of tRF-Leu-AAG on the invasion and migration ability of PC cells was also determined by the transwell assay. Thereafter, the downstream target genes of tRF-Leu-AAG were comprehensively predicted using bioinformatics analysis databases. We also used the Dual-Luciferase Reporter assay to assess the nexus between tRF-Leu-AAG and UPF1. Eventually, Western Blot was used to validate the expression of UPF1 in PC cells. A total of 33 tRF expressions significantly varied from PC patients. RT-qPCR confirmed that the expression of tRF-Leu-AAG was observably up-regulated in PC cells as compared to the control cells. Importantly, knockdown of tRF-Leu-AAG observably inhibited cell proliferation, migration, and invasion. Furthermore, according to the predicted frameshift database results, the UPF1 acted as downstream target genes for tRF-Leu-AAG and significantly down-regulated UPF1 expression.

Bioinformatics approach to identify common gene signatures of patients with coronavirus 2019 and lung adenocarcinoma

Coronavirus disease 2019 (COVID-19) continues as a global pandemic. Patients with lung cancer infected with COVID-19 may develop severe disease or die. Treating such patients severely burdens overwhelmed healthcare systems. Here, we identified potential pathological mechanisms shared between patients with COVID-19 and lung adenocarcinoma (LUAD). Co-expressed, differentially expressed genes (DEGs) in patients with COVID-19 and LUAD were identified and used to construct a protein–protein interaction (PPI) network and to perform enrichment analysis. We used the NetworkAnalyst platform to establish a co-regulatory of the co-expressed DEGs, and we used Spearman’s correlation to evaluate the significance of associations of hub genes with immune infiltration and immune checkpoints. Analysis of three datasets identified 112 shared DEGs, which were used to construct a protein-PPI network. Subsequent enrichment analysis revealed co-expressed genes related to biological process (BP), molecular function (MF), and cellular component (CC) as well as to pathways, specific organs, cells, and diseases. Ten co-expressed hub genes were employed to construct a gene-miRNA, transcription factor (TF)-gene, and TF-miRNA network. Hub genes were significantly associated with immune infiltration and immune checkpoints. Finally, methylation level of hub genes in LUAD was obtained via UALCAN database. The present multi-dimensional study reveals commonality in specific gene expression by patients with COVID-19 and LUAD. These findings provide insights into developing strategies for optimising the management and treatment of patients with LUAD with COVID-19.

A Novel Tumor Suppressor Gene, ZNF24, Inhibits the Development of NSCLC by Inhibiting the WNT Signaling Pathway to Induce Cell Senescence

Objective

Understanding the characteristics of tumor suppressor genes (TSGs) is of great significance for the development of new targeted treatment strategies for non-small cell lung cancer (NSCLC). Therefore, this present article is to explore the underlying molecular mechanism of ZFN24 inhibiting the development of NSCLC.

Methods

We performed RT-PCR and Western blotting for evaluating associated RNA and protein expression. CCK8, colony forming and sphere-forming assays were used to evaluate the proliferation and stemness of NSCLC cells. NSCLC cell senescence was examined by β-galactosidase staining assay. Luciferase assay was performed to evaluate β-catenin transcriptional activity. The effect of ZNF24 on NSCLC cells in vivo was evaluated by the xenograft tumor experiment.

Results

Ectopic expression of ZNF24 significantly inhibited cell viability, colony forming ability, and stemness of NSCLC cells. WNT signaling pathway was inhibited by ZNF24 resulting in NSCLC cell senescence. β-catenin transcriptional activity was significantly inhibited by ZNF24 (P < 0.05). Ectopic expression of ZNF24 significantly inhibited xenotransplant tumors growth in vivo (P < 0.05).

Conclusion

ZNF24 could notably inhibit the development of NSCLC by inhibiting the WNT signaling pathway.

Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model

Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.