Impact of ANXA5 polymorphisms on glioma risk and patient prognosis

Combined Effects of Annexin A5 Overexpression, 5-Fluorouracil Treatment, and Irradiation on Cell Viability of Caski Cervical Cancer Cell Line

Cervical cancer is the fourth leading cause of cancer deaths in women globally. Combining gene therapy with chemo- and radiotherapy may improve cervical cancer treatment outcomes. This study evaluated the effects of Annexin A5(ANXA5) overexpression alongside 5-fluorouracil (5-FU) and irradiation on the viability of CaSki cervical squamous cell carcinoma (SCC) cells. pAdenoVator-CMV-ANXA5-IRES-GFP-plasmid and mock plasmid were transfected into CaSki cells using calcium-phosphate. Seventy-two hours post-transfection, GFP expression was quantified by fluorescence microscopy and flow cytometry to evaluate transfection efficiency. ANXA5 overexpression was confirmed via qPCR. Twenty-four hours post-transfection, cells received a single dose of 8 Gy and were treated with 1 and 2 µg/ml of 5-FU (IC50 = 2.783 µg/ml). Cell viability, apoptosis, cell cycle stage, and Bcl-2 and Bax gene expression were assessed via MTT, annexin V/7-AAD, PI staining, and qPCR assays, respectively. ANXA5 was overexpressed 31.5-fold compared to control (p < 0.0001). MTT assays showed ANXA5 overexpression dose-dependently reduced CaSki cell viability (p < 0.001). IC50 of 5-FU was reduced from 2.783 μg/mL to 1.794 μg/mL when combined with ANXA5 overexpression. Additive effects on cell death were observed for ANXA5 plus 5-FU or irradiation versus ANXA5 alone. Apoptosis assays indicated combinatorial treatment increased CaSki cell apoptosis over ANXA5 alone. Cell cycle analysis revealed ANXA5 arrested cell cycle at G1/S phases; the percentage of cells in the S phase further rose with combination treatment. Finally, combination therapy significantly decreased Bcl-2 expression and increased Bax versus control (p < 0.001). Altogether, ANXA5 overexpression alongside 5-FU and irradiation may improve cervical squamous cell carcinoma (SCC) treatment efficacy. Further, in vivo investigations are warranted to confirm these in vitro results.

Association of NID2 SNPs with Glioma Risk and Prognosis in the Chinese Population

Glioma is the most common primary intracranial tumor with high mortality and poor prognosis. The purpose of this study was to investigate how single-nucleotide polymorphisms (SNPs) of the NID2 gene affect glioma risk and prognosis. Four candidate SNPs of NID2 in 529 glioma patients and 478 healthy controls were successfully genotyped by Agena MassARRAY mass spectrometer. Logistic regression was utilized to assess the associations between NID2 SNPs and glioma risk under different genetic models. Furthermore, the relationship between risk-related SNPs in NID2 and the prognosis of glioma patients was explored through Kaplan-Meier (KM) survival curve and Cox proportional hazard regression analysis. The results showed that rs11846847 (OR 1.24, p = 0.017) and rs1874569 (OR 1.22, p = 0.026) were significantly associated with an increased risk of glioma, and rs11846847 also had a risk-increasing effect on glioma in participants ≤ 40 years old. The interaction model of rs11846847 and rs1874569 could be more suitable for forecasting glioma risk. We also discovered a significant association between rs1874569 and poor prognosis in glioma patients (HR 1.32, p = 0.039) and especially CC genotype was relevant to shorter overall survival (OS) and progression-free survival (PFS) in patients with high-grade glioma. Additionally, the study demonstrated that gross total resection or chemotherapy improve glioma prognosis in the Chinese Han population. This study is the first to provide evidence for the association of NID2 SNPs with glioma risk and prognosis, suggesting that NID2 variants might be potential factors for glioma.

Identification of a Novel CD8+ T cell exhaustion-related gene signature for predicting survival in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a major health concern, necessitating a deeper understanding of its prognosis and underlying mechanisms. This study aimed to investigate the mechanism and prognostic value of CD8+ T Cell exhaustion (CD8+ TEX)-related genes in HCC and construct a survival prognosis prediction model for patients with HCC.

METHODS

CD8+ TEX-related genes associated with HCC prognosis were analysed and identified, and a prognostic prediction model was constructed using the 'least absolute shrinkage and selection operator' Cox regression model. Immunohistochemistry was used to verify the expression of the model genes in HCC tissues. A nomogram was constructed based on risk scores and clinical features, and its predictive efficacy was verified. The expression of STAM, ANXA5, and MAD2L2 in HCC cell lines was detected by western blotting; subsequently, these genes were knocked down in HCC cell lines by small interfering RNA, and their effects on the proliferation and migration of HCC cell lines were detected by colony formation assay, cck8, wound healing, and transwell assays.

RESULTS

Six genes related to CD8+ TEX were included in the risk-prediction model. The prognosis of patients with HCC in the low-risk group was significantly better than that of those in the high-risk group. Cox regression analysis revealed that the risk score was an independent risk factor for the prognosis of patients with HCC. The differentially expressed genes in patients with high-risk HCC were mainly enriched in the nucleotide-binding oligomerization domain-containing protein-like receptor, hypoxia-inducible factor-1, and tumour programmed cell death protein (PD)-1/PD-L1 immune checkpoint pathways. The CD8+ TEX-related genes STAM, ANXA5, and MAD2L2 were knocked down in HCC cell lines to significantly inhibit cell proliferation and migration. The prediction results of the nomogram based on the risk score showed a good fit and application value.

CONCLUSION

The prediction model based on CD8+ TEX-related genes can predict the prognosis of HCC and provide a theoretical basis for the early identification of patients with poor HCC prognosis.

Reanalysis of single-cell data reveals macrophage subsets associated with the immunotherapy response and prognosis of patients with endometrial cancer

Endometrial cancer (EC) is an aggressive gynecological malignancy with an increased incidence rate. The immune landscape crucially affects immunotherapy efficacy and prognosis in EC patients. Here, we characterized the distinct tumor microenvironment signatures of EC tumors by analyzing single-cell RNA sequencing data from Gene Expression Omnibus and bulk RNA sequencing data from The Cancer Genome Atlas, which were compared with normal endometrium. Three macrophage subsets were identified, and two of them showed tissue-specific distribution. One of the macrophage subsets was dominant in macrophages derived from EC and exhibited characteristic behaviors such as promoting tumor growth and metastasis. One of the other macrophage subsets was mainly found in normal endometrium and served functions related to antigen presentation. We also identified a macrophage subset that was found in both EC and normal endometrial tissue. However, the pathway and cellular cross-talk of this subset were completely different based on the respective origin, suggesting a tumor-related differentiation mechanism of macrophages. Additionally, the tumor-enriched macrophage subset was found to predict immunotherapy responses in EC. Notably, we selected six genes from macrophage subset markers that could predict the survival of EC patients, SCL8A1, TXN, ANXA5, CST3, CD74 and NANS, and constructed a prognostic signature. To verify the signature, we identified immunohistochemistry for the tumor samples of 83 EC patients based on the selected genes and further followed up with the survival of the patients. Our results provide strong evidence that the signature can effectively predict the prognosis of EC patients.

The Comprehensive Analysis of m6A-Associated Anoikis Genes in Low-Grade Gliomas

The relationship between N6-methyladenosine (m6A) regulators and anoikis and their effects on low-grade glioma (LGG) is not clear yet. The TCGA-LGG cohort, mRNAseq 325 dataset, and GSE16011 validation set were separately obtained via the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Altas (CGGA), and Gene Expression Omnibus (GEO) databases. In total, 27 m6A-related genes (m6A-RGs) and 508 anoikis-related genes (ANRGs) were extracted from published articles individually. First, differentially expressed genes (DEGs) between LGG and normal samples were sifted out by differential expression analysis. DEGs were respectively intersected with m6A-RGs and ANRGs to acquire differentially expressed m6A-RGs (DE-m6A-RGs) and differentially expressed ANRGs (DE-ANRGs). A correlation analysis of DE-m6A-RGs and DE-ANRGs was performed to obtain DE-m6A-ANRGs. Next, univariate Cox and least absolute shrinkage and selection operator (LASSO) were performed on DE-m6A-ANRGs to sift out risk model genes, and a risk score was gained according to them. Then, gene set enrichment analysis (GSEA) was implemented based on risk model genes. After that, we constructed an independent prognostic model and performed immune infiltration analysis and drug sensitivity analysis. Finally, an mRNA-miRNA-lncRNA regulatory network was constructed. There were 6901 DEGs between LGG and normal samples. Six DE-m6A-RGs and 214 DE-ANRGs were gained through intersecting DEGs with m6A-RGs and ANRGs, respectively. A total of 149 DE-m6A-ANRGs were derived after correlation analysis. Four genes, namely ANXA5, KIF18A, BRCA1, and HOXA10, composed the risk model, and they were involved in apoptosis, fatty acid metabolism, and glycolysis. The age and risk scores were finally sifted out to construct an independent prognostic model. Activated CD4 T cells, gamma delta T cells, and natural killer T cells had the largest positive correlations with risk model genes, while activated B cells were significantly negatively correlated with KIF18A and BRCA1. AT.9283, EXEL.2280, Gilteritinib, and Pracinostat had the largest correlation (absolute value) with a risk score. Four risk model genes (mRNAs), 12 miRNAs, and 21 lncRNAs formed an mRNA-miRNA-lncRNA network, containing HOXA10-hsa-miR-129-5p-LINC00689 and KIF18A-hsa-miR-221-3p-DANCR. Through bioinformatics, we constructed a prognostic model of m6A-associated anoikis genes in LGG, providing new ideas for research related to the prognosis and treatment of LGG.

Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma

Background

The ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.

Methods

CAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression was used to build a risk signature. With microarray data from the GEO database, prognostic characteristics were externally verified. For high and low CAF-risk categories, immune cells and immunotherapy responses were analyzed. Finally, a nomogram model based on the risk signature and prospective chemotherapeutic drugs were examined.

Results

Combining scRNA-seq and bulk-seq data analysis yielded a total of 124 CAF-related genes. LRP1, ANXA5, SERPINE2, ECM1, RBP1, GJA1, and FKBP10 were the seven BLCA prognostic genes that remained after univariate Cox regression and LASSO regression analyses. Then, based on these genes, prognostic characteristics were created and validated to predict survival in BLCA patients. Additionally, risk signature had a strong correlation with known CAF scores, stromal scores, and certain immune cells. The CAF-risk signature was identified as an independent prognostic factor for BLCA using multifactorial analysis, and its usefulness in predicting immunotherapy response was confirmed. Based on risk classification, we projected six highly sensitive anticancer medicines for the high-risk group.

Conclusion

The prognosis of BLCA may be accurately predicted using CAF-based risk signature. With a thorough understanding of the BLCA CAF-signature, it might be able to explain the BLCA patients' response to immunotherapy and identify a potential target for BLCA treatment.

ARRDC3 polymorphisms may affect the risk of glioma in Chinese Han

This study ascertained to explore the potential contribution of ARRDC3 polymorphisms in the risk and prognosis of glioma. One thousand sixty-one patients and healthy controls were conducted to assess whether ARDC3 polymorphism was associated with glioma risk and prognosis. Four sites in ARRDC3 were selected and genotyped in MassARRAY platform. The calculated odd ratios and 95% confidence intervals from logistic regression were applied for risk assessment. The relationship between ARRDC3 variants and glioma prognosis was evaluated using log-rank test, Kaplan-Meier analysis, and so on. Also, false-positive report probability (FPRP) and statistical power were also assessed. Our findings suggested the negative role of ARRDC3 polymorphisms in the glioma risk. We also found the effect of candidate SNPs in ARRDC3 on the susceptibility to glioma was dependent on the age, gender, and histology of glioma patients. The results suggested that the genetic polymorphisms of ARRDC3 were related to an increased risk of glioma.

The effect of CYP7B1 polymorphisms on the risk of coronary heart disease in Hainan Han population

BACKGROUND

Coronary heart disease (CHD) is the leading cause of human death worldwide. Genetic factors play an important role in the occurrence of CHD. Our study is designed to investigate the influence of CYP7B1 polymorphisms on CHD risk.

METHODS

In this case-control study, 508 CHD patients and 510 healthy individuals were recruited to determine the correlation between CYP7B1 polymorphisms (rs7836768, rs6472155, and rs2980003) and CHD risk. The associations were evaluated by computing odds ratios (OR) and 95% confidence intervals (CI) with logistic regression analysis. The association between SNP-SNP interaction and CHD susceptibility was carried out by multifactor dimensionality reduction analyses.

RESULTS

Our study found that rs6472155 is significantly associated with an increased risk of CHD in age > 60 years (OR 2.20, 95% CI = 1.07-4.49, p = 0.031), women (OR 3.17, 95% CI = 1.19-8.44, p = 0.021), and non-smokers (3.43, 95% CI = 1.16-10.09, p = 0.025). Rs2980003 polymorphism has a lower risk of CHD in drinkers (OR 0.47, 95% CI = 0.24-0.91, p = 0.025). Further analyses based on false-positive report probability validated these significant results. Besides, it was found that rs6472155 polymorphism was associated with uric acid level (p = 0.034).

CONCLUSION

Our study indicated that CYP7B1 polymorphisms are related to the risk of CHD, which provides a new perspective for prevent of CHD.

Role of PVT1 polymorphisms in the glioma susceptibility and prognosis

BACKGROUND

Genetic factors play a crucial role in the glioma risk and prognosis of glioma patients. To explore the role of plasmacytoma variant translocation 1 (PVT1) polymorphism in the susceptibility and survival of glioma in the Chinese Han population, we conducted a case-control study.

METHODS

The three single-nucleotide polymorphisms (SNPs) in PVT1 were genotyped using Agena MassARRAY from 575 patients with glioma and 500 healthy controls. We used the χ2 test to analyze the differences in distribution of allele and genotype between the cases and controls. Odds ratio and 95% confidence interval (CI) were calculated by logistic regression analysis to evaluate the association SNPs with glioma risk. The effects of polymorphisms and clinical features on survival of glioma patients were evaluated using the log-rank test, Kaplan-Meier and Cox regression analysis.

RESULTS

We found that rs13255292 was associated with a decreased risk of glioma in the recessive model in overall or male; and rs4410871 was significantly associated with an increased the risk of glioma in age ≤40 years old or female. Moreover, the extent of resection and chemotherapy were found to be key prognostic factors in survival of glioma patients. However, the gender, age, tumor grade, radiotherapy and PVT1 polymorphisms have no effect on prognosis of glioma patients.

CONCLUSIONS

Our results indicated that PVT1 polymorphisms (rs13255292 and rs4410871) were associated with glioma susceptibility, but have no effect on prognosis of glioma patients. Further studies with large samples are required to confirm the results.

Prognostic factors in adult brainstem glioma: a tertiary care center analysis and review of the literature

Introduction

Adult brainstem gliomas (BSGs) are rare central nervous system tumours characterized by a highly heterogeneous clinical course. Median survival times range from 11 to 84 months. Beyond surgery, no treatment standard has been established. We investigated clinical and radiological data to assess prognostic features providing support for treatment decisions.

Methods

34 BSG patients treated between 2000 and 2019 and aged ≥ 18 years at the time of diagnosis were retrospectively identified from the databases of the two largest Austrian Neuro-Oncology centres. Clinical data including baseline characteristics, clinical disease course, applied therapies, the outcome as well as neuroradiological and neuropathological findings were gathered and analysed. The tumour apparent diffusion coefficient (ADC), volumetry of contrast-enhancing and non-contrast-enhancing lesions were determined on magnetic resonance imaging scans performed at diagnosis.

Results

The median age at diagnosis was 38.5 years (range 18–71 years). Tumour progression occurred in 26/34 (76.5%) patients after a median follow up time of 19 months (range 0.9–236.2). Median overall survival (OS) and progression-free survival (PFS) was 24.1 months (range 0.9–236.2; 95% CI 18.1–30.1) and 14.5 months (range 0.7–178.5; 95% CI 5.1–23.9), respectively. Low-performance status, high body mass index (BMI) at diagnosis and WHO grading were associated with shorter PFS and OS at univariate analysis (p < 0.05, log rank test, respectively). ADC values below the median were significantly associated with shorter OS (14.9 vs 44.2 months, p = 0.018).

Conclusion

ECOG, BMI, WHO grade and ADC values were associated with the survival prognosis of BSG patients and should be included in the prognostic assessment.

Novel Post-Translational Modifications and Molecular Substrates in Glioma Identified by Bioinformatics

Glioma is the most common type of brain cancer that originates from the glial cells. It constitutes about one-third of all brain cancers. Recently, transcriptomics, proteomics, and multiomics approaches have been harnessed to discover potential biomarkers and therapeutic targets in glioma. Moreover, post-translational modifications (PTMs) of proteins play a major role in cell biology and function and offer new avenues of research in cancer. Using unbiased multi-PTM bioinformatics analyses of two proteomic datasets of glioma available in the public domain, we identified 866 proteins with common PTMs from both studies. Out of these 866 proteins, 19 proteins were identified with the common PTMs, with the same site modifications pertaining to glioma. Importantly, the identified PTMs belonged to proteins involved in integrin PI3K/Akt/mTOR, JAK/STAT, and Ras/Raf/MAPK pathways. These pathways are essential for cell proliferation in tumor cells and thus involved in glioma progression. Taken together, these findings call for validation in larger datasets in glioma and brain cancers and with an eye to future drug discovery and diagnostic innovation. Bioinformatics-guided discovery of novel PTMs from the publicly available proteomic data can offer new avenues for innovation in cancer research.

Immune profiling of pituitary tumors reveals variations in immune infiltration and checkpoint molecule expression

PURPOSE

Pituitary tumors are the second most common primary brain tumors. Functional tumors demonstrate increased PD-L1 expression, but expression of other checkpoint regulators has not been characterized. We sought to characterize the immune microenvironment of human pituitary tumors to identify new treatment opportunities.

METHODS

72 pituitary tumors were evaluated for expression of the immune regulatory markers programmed death ligand 1 (PD-L1), programmed death ligand 2 (PD-L2), V-domain Ig suppressor of T cell activation (VISTA), lymphocyte activation gene 3 (LAG3) and tumor necrosis factor receptor superfamily member 4 (OX40) by immunohistochemistry (IHC). Lymphocyte infiltration, macrophage infiltration, and angiogenesis were analyzed using IHC. Expression of pituitary tumor initiating cell marker CD15 and mismatch repair proteins MutS protein homolog 2 (MSH2) and MutS protein homolog 6 (MSH6) was also assessed.

RESULTS

Pituitary tumors were infiltrated by macrophages and T cells, and they expressed varying levels of PD-L1, PD-L2, VISTA, LAG3, and OX40. Functional tumors and tumors with high expression of tumor stem cell markers had higher immune cell infiltration and greater expression of immunosuppressive checkpoint regulators. Increased PD-L1 and LAG3 and reduced VISTA were observed in primary tumors compared to recurrent tumors.

CONCLUSION

Immune cell infiltration and checkpoint regulator expression vary depending on functional status and presence of pituitary tumor initiating cells. Functional tumors may have a particularly immunosuppressive microenvironment. Further studies of immune checkpoint blockade of pituitary tumors, particularly functional tumors, are warranted, though combination therapy may be required.

Research and application of hydrostatic high pressure in tumor vaccines (Review)

It is well known that hydrostatic pressure (HP) is a physical parameter that is now regarded as an important variable for life. High hydrostatic pressure (HHP) technology has influenced biological systems for more than 100 years. Food and bioscience researchers have shown great interest in HHP technology over the past few decades. The development of knowledge related to this area can better facilitate the application of HHP in the life sciences. Furthermore, new applications for HHP may come from these current studies, particularly in tumor vaccines. Currently, cancer recurrence and metastasis continue to pose a serious threat to human health. The limited efficacy of conventional treatments has led to the need for breakthroughs in immunotherapy and other related areas. Research into tumor vaccines is providing new insights for cancer treatment. The purpose of this review is to present the main findings reported thus far in the relevant scientific literature, focusing on knowledge related to HHP technology and tumor vaccines, and to demonstrate the potential of applying HHP technology to tumor vaccine development.

Evaluation of Genetic Variants in MIR3142HG in Susceptibility to and Prognosis of Glioma

OBJECTIVES

Studies have demonstrated that genetic variants in the miRNA-coding genes might be associated with cancer susceptibility and survival. Here, we aimed to investigate the influence of MIR3142HG single-nucleotide polymorphisms on the individual's susceptibility to and patients' prognosis of glioma.

MATERIALS AND METHODS

Six variants were genotyped by Agena MassARRAY iPLEX Gold assay among 529 glioma patients and 502 healthy controls. Association of MIR3142HG polymorphisms with the risk for and prognosis of glioma was analyzed by logistic regression analysis and Cox proportional hazards model, respectively.

RESULTS

In the risk analysis, rs17057846 (odds ratio [OR]=1.93, P=0.047), rs2961920 (OR=1.53, P=0.019), and rs58747524 (OR=1.23, P=0.046) polymorphisms were associated with increased glioma risk, while rs7727115 (OR=0.76, P=0.030) and rs1582417 (female individuals, OR=0.49, P=0.017) variants were associated with decreased risk. In the survival analysis, rs1582417 polymorphism (hazard ratio=1.26, P=0.017) contributed to poorer prognosis overall. Rs17057846, rs1582417, and rs2431689 polymorphisms were associated with prognosis of astrocytoma, and rs1582417, rs17057846, and rs58747524 variants were associated with the survival rate in patients with low-grade glioma (I to II).

CONCLUSION

Our study provided the first evidence for the impact of rs1582417, rs17057846, rs2431689, rs2961920, rs58747524, and rs7727115 polymorphisms in MIR3142HG on the susceptibility to and/or prognosis of glioma in the Chinese Han population.

The Impact of PPARD and PPARG Polymorphisms on Glioma Risk and Prognosis

Recent studies showed that peroxisome proliferator-activated receptors (PPARs) had effects on the progression of multiple tumors, but the role of PPARD and PPARG in glioma remains poorly understand. We conducted a case-control study to investigate the association of polymorphisms in PPARD and PPARG with glioma risk and prognosis in the Chinese Han population. Seven polymorphisms (PPARD: rs2016520, rs67056409, rs1053049 and rs2206030; PPARG: rs2920503, rs4073770 and rs1151988) were genotyped using the Agena MassARRAY system in 568 glioma patients and 509 healthy controls. The odd ratios (OR) and 95% confidence interval (CI) were calculated to assess the association of PPARD and PPARG polymorphisms with glioma risk. The Multifactor dimensionality reduction (MDR) method was used to analysis interactions of genetic polymorphisms on glioma risk. Then, we conducted log-rank test, Kaplan-Meier analysis and Cox regression model to evaluate the relationship of PPARD and PPARG polymorphisms with glioma prognosis. We found PPARD polymorphisms (rs2016520, rs67056409, rs1053049) were significantly associated with glioma risk in multiple models (P < 0.05). Stratified analysis showed rs2016520, rs67056409, rs1053049 of PPARD significantly decreased risk of glioma in the subgroup of age > 40 and astrocytoma (P < 0.05). For male, PPARD rs1053049 had a strong relationship with glioma risk in allele (P = 0.041), dominant (P = 0.040) and additive (P = 0.040) models. The effect of PPARG rs2920503 on glioma risk was related to glioma grade (P < 0.05). MDR showed that a seven-locus model was the best polymorphisms interaction pattern. Moreover, surgery and chemotherapy had strongly impact on overall survival and progression free survival of glioma patients. Our findings suggested that PPARD and PPARG polymorphisms were associated with glioma risk and prognosis in the Chinese Han population, and further studies are need to confirm our results.