Integrated analysis of 1804 samples of six centers to construct and validate a robust immune-related prognostic signature associated with stromal cell abundance in tumor microenvironment for gastric cancer

APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation

BACKGROUND

Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stress and their potential biological functions during acute rejection of kidney transplants.

METHODS

We identified Hub genes using five machine learning algorithms based on differentially expressed genes (DEGs) in the kidney transplant acute rejection dataset GSE50058 and oxidative stress-related genes (OS) obtained from the MSigDB database, and validated them with the datasets GSE1563 and GSE9493, as well as with animal experiments; Subsequently, we explored the potential biological functions of Hub genes using single-gene GSEA enrichment analysis; The Cibersort algorithm was used to explore the altered levels of infiltration of 22 immune cells during acute rejection of renal transplantation, and a correlation analysis between Hub genes and immune cells was performed; Finally, we also explored transcription factors (TFs), miRNAs, and potential drugs that regulate Hub genes.

RESULTS

We obtained a total of 57 genes, which we defined as oxidative stress-associated differential genes (DEOSGs), after intersecting DEGs during acute rejection of kidney transplants with OSs obtained from the MSigDB database; The results of enrichment analysis revealed that DEOSGs were mainly enriched in response to oxidative stress, response to reactive oxygen species, and regulation of oxidative stress and reactive oxygen species; Subsequently, we identified one Hub gene as APOD using five machine learning algorithms, which were validated by validation sets and animal experiments; The results of single-gene GSEA enrichment analysis revealed that APOD was closely associated with the regulation of immune signaling pathways during acute rejection of kidney transplants; The Cibersort algorithm found that the infiltration levels of a total of 10 immune cells were altered in acute rejection, while APOD was found to correlate with the expression of multiple immune cells; Finally, we also identified 154 TFs, 12 miRNAs, and 12 drugs or compounds associated with APOD regulation.

CONCLUSION

In this study, APOD was identified as a biomarker associated with oxidative stress during acute rejection of kidney transplants using multiple machine learning algorithms, which provides a potential therapeutic target for mitigating oxidative stress injury and reducing the incidence of acute rejection in kidney transplantation.

FAM19A5 in vascular aging and osteoporosis: Mechanisms and the "calcification paradox"

Aging induces a progressive decline in the vasculature's structure and function. Vascular aging is a determinant factor for vascular ailments in the elderly. FAM19A5, a recently identified adipokine, has demonstrated involvement in multiple vascular aging-related pathologies, including atherosclerosis, cardio-cerebral vascular diseases and cognitive deficits. This review summarizes the current understanding of FAM19A5' role and explores its putative regulatory mechanisms in various aging-related disorders, including cardiovascular diseases (CVDs), metabolic diseases, neurodegenerative diseases and malignancies. Importantly, we provide novel insights into the underlying therapeutic value of FAM19A5 in osteoporosis. Finally, we outline future perspectives on the diagnostic and therapeutic potential of FAM19A5 in vascular aging-related diseases.

Comprehensive analysis of disulfidptosis related genes and prognosis of gastric cancer

BACKGROUND

Gastric cancer (GC) is a common malignant tumor of the digestive system. Disulfidptosis is a new programmed cell death mechanism, although its specific mechanism in GC is incompletely understood.

AIM

In this study, we used bioinformatics analysis to explore a disulfidptosis-based predictive model related to GC prognosis and to identify potential therapeutic targets and sensitive drugs for GC.

METHODS

We extracted GC-related data from The Cancer Genome Atlas and Gene Expression Omnibus databases. R software (version 4.2.1) was used for correlation analysis.

RESULTS

Through the above analysis, we found that the disulfidptosis related gene may be related to the prognosis of GC. Six genes, namely, PLS3, GRP, APOD, SGCE, COL8A1, and VAMP7, were found to constitute a predictive model for GC prognosis. APOD is a potential therapeutic target for treating GC. Bosutinib and other drugs are sensitive for the treatment of GC.

CONCLUSION

The results of this study indicate that disulfidptosis is related to the prognosis and treatment of GC, while APOD represents a potential therapeutic target for GC.

A risk prediction model mediated by genes of APOD/APOC1/SQLE associates with prognosis in cervical cancer

Cervical cancer is one of the most common gynecological malignancies. Due to the high heterogeneity of cervical cancer accelerating cancer progression, it is necessary to identify new prognostic markers and treatment regimens for cervical cancer to improve patients' survival rates. We purpose to construct and verify a risk prediction model for cervical cancer patients. Based on the analysis of data from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA), differences of genes in normal and cancer samples were analyzed and then used analysis of WGCNA along with consistent clustering to construct single-factor + multi-factor risk models. After regression analysis, the target genes were obtained as prognostic genes and prognostic risk models were constructed, and the validity of the risk model was confirmed using the receiver operating characteristic curve (ROC) and Kaplan-Meier curve. Subsequently, the above model was verified on the GSE44001 data validation followed by independent prognostic analysis. Enrichment analysis was conducted by grouping the high and low risks of the model. In addition, differences in immune analysis (immune infiltration, immunotherapy), drug sensitivity, and other levels were counted by the high and low risks groups. In our study, three prognostic genes including APOD, APOC1, and SQLE were obtained, and a risk model was constructed along with validation based on the above-mentioned analysis. According to the model, immune correlation and immunotherapy analyses were carried out, which will provide a theoretical basis and reference value for the exploration and treatment of cervical cancer.

Comprehensive analysis of metabolic pathway activity subtypes derived prognostic signature in hepatocellular carcinoma

OBJECTIVE

Metabolic reprogramming is one of the hallmarks of cancer, but metabolic pathway activity-related subtypes of hepatocellular carcinoma (HCC) have not been identified.

METHODS

Based on the quantification results of 41 metabolic pathway activities by gene set variation analysis, the training cohort (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) with the nonnegative matrix factorization method. Totally 1371 differentially expressed genes among C1, C2, and C3 were identified, and an 8-gene risk score was established by univariable Cox regression analysis, least absolute shrinkage and selection operator method, and multivariable Cox regression analysis.

RESULTS

C1 had the strongest metabolic activity, good prognosis, the highest CTNNB1 mutation rate, with massive infiltration of eosinophils and natural killer cells. C2 had the weakest metabolic activity, poor prognosis, was younger, was inclined to vascular invasion and advanced stage, had the highest TP53 mutation rate, exhibited a higher expression level of immune checkpoints, accompanied by massive infiltration of regulatory T cells. C3 had moderate metabolic activity and prognosis, the highest LRP1B mutation rate, and a higher infiltration level of neutrophils and macrophages. Internal cohorts (TCGA, n = 370; GSE14520, n = 239), external cohorts (ICGC, n = 231; GSE116174, n = 64), and clinical subgroup validation showed that the risk score was applicable for patients with diverse clinical features and was effective in predicting the prognosis and malignant progression of patients with HCC. Compared with the low-risk group, the high-risk group had a poor prognosis, enhanced cancer stem cell characteristics, activated DNA damage repair, weakened metabolic activity, cytolytic activity, and interferon response.

CONCLUSION

We identified HCC subtypes from the perspective of metabolism-related pathway activity and proposed a robust prognostic signature for HCC.

Association of tumor deposits with tumor-infiltrating lymphocytes and prognosis in gastric cancer

Background

To investigate the relationship between tumor deposits (TDs) with the clinicopathological characteristics tumor-infiltrating lymphocytes (TILs) and prognosis of gastric cancer. Further analysis was done on the relationship between the number and maximum diameter of TDs with the clinicopathological characteristics and prognosis of gastric cancer.

Methods

The pathological findings of 369 patients with gastric cancer were retrospectively analyzed to observe the expression of TDs and the levels of stromal TILs. The relationship between TDs, clinicopathological characteristics, and levels of stromal TILs was compared using the chi-square test. Kaplan-Meier was used for survival analysis, and the log-rank test was used to determine the relationship between TDs and disease-free survival, cancer-specific survival, and overall survival. The prognostic value of TDs was assessed using multivariate Cox proportional hazards regression analysis. For further analysis, the optimal cutoff values for the number and maximum diameter of TDs were selected based on the receiver operating characteristic (ROC) curve.

Results

TDs were significantly associated with sex, lymphovascular invasion, perineural invasion, pathological T,N stage, and clinical stage (all P < 0.05). TILs levels are lower in TDs(+) group and higher in TDs(−) group. Compared with TDs(−) groups, TDs(+) group had poor disease-free survival, cancer-specific survival, and overall survival. TDs are negatively correlated with TILs, and TILs levels are lower in TDs(+) group and higher in TDs(−) group (P < 0.05). The samples are divided into the number of TDs (< 4 and ≥ 4) and the maximum diameter of TDs (< 7 mm and ≥ 7 mm). The number of TDs was significantly associated with pathological N stage (P < 0.05). The maximum diameter of TDs was significantly correlated with Lauren classification (P < 0.05) .TDs ≥ 4 had lower DFS, CSS, and OS (P < 0.05). The maximum diameter of TDs was not statistically significant with prognosis (P > 0.05).

Conclusion

TDs are independent prognosis predictors of gastric cancer. In the tumor microenvironment, TDs and TILs interact with each other to regulate the development of gastric cancer, thus affecting gastric cancer prognosis of patients. The number of TDs ≥ 4 has a worse prognosis compared to the number of TDs < 4.