BACKGROUND: Breast cancer (BC) ranks as the most prevalent malignancy affecting women globally, with apoptosis playing a pivotal role in its pathological progression. Despite the crucial role of apoptosis in BC development, there is limited research exploring the relationship between BC prognosis and apoptosis-related genes (ARGs). Therefore, this study aimed to establish a BC-specific risk model centered on apoptosis-related factors, presenting a novel approach for predicting prognosis and immune responses in BC patients.
METHODS: Utilizing data from The Cancer Gene Atlas (TCGA), Cox regression analysis was employed to identify differentially prognostic ARGs and construct prognostic models. The accuracy and clinical relevance of the model, along with its efficacy in predicting immunotherapy outcomes, were evaluated using independent datasets, Receiver Operator Characteristic (ROC) curves, and nomogram. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were used to predict potential mechanical pathways. The CellMiner database is used to assess drug sensitivity of model genes.
RESULTS: A survival risk model comprising eight prognostically relevant apoptotic genes (PMAIP1, TP53AIP1, TUBA3D, TUBA1C, BCL2A1, EMP1, GSN, F2) was established based on BC patient samples from TCGA. Calibration curves validated the ROC curve and nomogram, demonstrating excellent accuracy and clinical utility. In samples from the Gene Expression Omnibus (GEO) datasets and immunotherapy groups, the low-risk group (LRG) demonstrated enhanced immune cell infiltration and improved immunotherapy responses. Model genes also displayed positive associations with sensitivity to multiple drugs, including vemurafenib, dabrafenib, PD-98059, and palbociclib.
CONCLUSIONS: This study successfully developed and validated a prognostic model based on ARGs, offering new insights into prognosis and immune response prediction in BC patients. These findings hold promise as valuable references for future research endeavors in this field.

The prognostic roles of apoptosis-related genes (ARGs) in lung adenocarcinoma (LUAD) have not been fully elucidated. In this study, differentially expressed genes (DEGs) associated with apoptosis and the hub genes were further identified. The prognostic values of the ARGs were evaluated using the LASSO Cox regression method. Prognostic values were determined using Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves in the TCGA and GEO datasets. The correlations, mutation data, and protein expression of the 10 ARGs predictive models were also analyzed. We identified 130 differentially expressed ARGs. DEGs were used to split LUAD cases into two subtypes whose overall survival (OS) were significantly different (P = 0.025). We developed a novel 10-gene signature using LASSO Cox regression. In both TCGA and GEO datasets, the results of the K-M curve and log-rank test showed significant difference in the survival rate of patients in the high-risk group and low-risk group (P < 0.0001). According to the GO and KEGG analyses, ARGs were enriched in cancer-related terms. In both cohorts, the immune status of the high-risk group was significantly lower than that of the low-risk group. Based on the differential expression of the ARGs, we established a new risk model to predict the prognosis of patients with LUAD.

Osteoarthritis (OA) progression involves multiple factors, including cartilage erosion as the basic pathological mechanism of degeneration, and is closely related to chondrocyte apoptosis. To analyze the correlation between apoptosis and OA development, we selected apoptosis genes from the differentially expressed genes (DEGs) between OA and normal samples from the Gene Expression Omnibus (GEO) database, used lasso regression analysis to identify characteristic genes, and performed consensus cluster analysis to further explore the pathogenesis of this disease.
The Gene expression profile datasets of OA samples, GSE12021 and GSE55235, were downloaded from GEO. The datasets were combined and analyzed for DEGs. Apoptosis-related genes (ARGs) were collected from the GeneCards database and intersected with DEGs for apoptosis-related DEGs (ARDEGs). Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to obtain characteristic genes, and a nomogram was constructed based on these genes. A consensus cluster analysis was performed to divide the patients into clusters. The immune characteristics, functional enrichment, and immune infiltration statuses of the clusters were compared. In addition, a protein-protein interaction network of mRNA drugs, mRNA-transcription factors (TFs), and mRNA-miRNAs was constructed.
A total of 95 DEGs were identified, of which 47 were upregulated and 48 were downregulated, and 31 hub genes were selected as ARDEGs. LASSO regression analysis revealed nine characteristic genes: growth differentiation factor 15 (GDF15), NAMPT, TLR7, CXCL2, KLF2, REV3L, KLF9, THBD, and MTHFD2. Clusters A and B were identified, and neutrophil activation and neutrophil activation involved in the immune response were highly enriched in Cluster B, whereas protein repair and purine salvage signal pathways were enriched in Cluster A. The number of activated natural killer cells in Cluster B was significantly higher than that in Cluster A. GDF15 and KLF9 interacted with 193 and 32 TFs, respectively, and CXCL2 and REV3L interacted with 48 and 82 miRNAs, respectively.
ARGs could predict the occurrence of OA and may be related to different degrees of OA progression.

BACKGROUND: A variety of apoptosis genes have been confirmed to be related to the occurrence and development of bladder cancer patients, but few studies have paid attention to their significance in the prognosis of bladder cancer. Therefore, this study explored the value of apoptosis-related genes in the prognosis of BLCA by using the data in TCGA database.
METHODS: We downloaded the mRNA expression profiles and corresponding clinical data of bladder cancer patients from TCGA database, and obtained 2411 apoptosis-related genes from Deathbase database. Screening out differentially expressed apoptosis-related genes. Cox regression was used to determine the prognostic value of apoptosis-related genes, and then a prognostic risk model was developed. A nomogram based on risk model was constructed to predict the prognosis of bladder cancer patients. At the same time, immune infiltration correlation analysis of genes in the prognosis model.
RESULTS: A prognostic model composed of 12 apoptosis-related genes was constructed. According to the risk score calculated by the model, patients were divided into high-risk group and low-risk group. There are significant differences in the expression of immune cells, immune function and immune checkpoint molecules between high-risk group and low-risk group. P4HB may promote bladder cancer progression.
CONCLUSIONS: Based on the differential expression of apoptosis-related genes, we established a risk model to predict the prognosis of bladder cancer patients, in which P4HB promotes BLCA progression.

Acute kidney injury (AKI) is a common critical illness in hospitalized patients, characterized by a rapid decline in kidney function over a short period, which can seriously endanger the patient\'s life. Currently, there is a lack of precise and universal AKI diagnostic biomarkers in clinical practice. In this study, weighted gene coexpression network analysis (WGCNA), differential expression analysis, univariate and multivariate logistic regression analyses, receiver operating characteristic (ROC) curves, and immune cell infiltration were performed to identify apoptosis-related biomarkers that can be used for AKI diagnosis. Three core apoptosis-related genes (ARGs), CBFB, EGF and COL1A1, were identified as AKI biomarkers. More importantly, an apoptosis-related signature containing three hub ARGs was validated as a diagnostic model. The hub genes exhibited good correlations with glomerular filtration rate (GFR) and serum creatinine (SCr) in the Nephroseq kidney disease database. Additionally, CIBERSORT immune infiltration analysis indicated that these core ARGs may affect immune cell recruitment and infiltration in AKI patients. Subsequently, we investigated the alteration of the expression levels of three core ARGs in AKI samples using single-cell RNA sequencing analysis and analyzed the cell types that mainly expressed these ARGs. More importantly, the expression of core ARGs was validated in folic acid- and cisplatin-induced AKI mouse models. In summary, our study identified three diagnostic biomarkers for AKI, explored the roles of ARGs in AKI progression and provided new ideas for the clinical diagnosis and treatment of AKI.

In aging laying hens, reproductive changes reduce egg quality. Bacillus subtilis natto (B. subtilis) is a versatile bacterium with high vitamin K2 content, providing health benefits for animals and humans. This study investigated the effect of B. subtilis natto NB205 and its mutant NBMK308 on egg quality in aging laying hens. Results showed that NB205 and NBMK308 supplementation significantly improved albumen height (p < 0.001), Haugh units (p < 0.05), and eggshell thickness (p < 0.001) compared to the control group. Supplementation also increased ovalbumin expression, regulated tight junction (TJ) proteins, reduced pro-inflammatory cytokine levels, and improved the health and productivity of aging laying hens by regulating key apoptosis-related genes in the magnum part of the oviduct. There were differences in the expression of vitamin K-dependent proteins (VKDPs) in the magnum between NB205 and NBMK308, but no significant differences in the improvement of egg quality. Supplementation with NB205 and NBMK308 can improve egg quality in aging laying hens.

BACKGROUND: Genomic alterations play important roles in the development of cancer. We explored the impact of protein-coding genes and transcriptomic changes on clinical and molecular alterations in Taiwanese hepatocellular carcinoma (HCC) patients.
METHODS: We analyzed 147 whole-exome sequencing and 100 RNA sequencing datasets of HCC and compared them with The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma cohort and develop a panel of 81 apoptosis-related genes for molecular classification.
RESULTS: TERT (50%), TP53 (25%), CTNNB1 (14%), ARID1A (12%), and KMT2C (11%) were the most common genetic alterations of cancer-related genes. ALDH2 and KMT2C mutated at much higher frequencies in our cohort than in TCGA, whereas CTNNB1 was found only in 14% of our Taiwanese patients. A high germline mutation rate of ALDH2 in the APOBEC mutational signature and herb drug-related aristolochic acid-associated signature was also observed. Groups A and B of HCC were identified when we used apoptosis-related genes for molecular classification. The latter group, which had poorer survival outcomes, had significantly more aDC, CD4+ Tem, macrophages M2, NKT, plasma cells, and Th1 cells, and less CD4+ memory T cells, CD8+ Tcm, cDC, iDC, and Th2 cells, as well as more inter-chromosome fusion genes. Metatranscriptomic analysis revealed 54 cases of HBV infection. Moreover, we found that the main target gene of HBV integration is ALB.
CONCLUSIONS: Unique genomic alterations were observed in our Taiwanese HCC patients. Molecular classification using apoptosis-related genes could lead to new therapeutic approaches for HCC.

Background: Apoptosis is a type of cell death, which can produce abundant mediators to modify the tumor microenvironment. However, relationships between apoptosis, immunosuppression, and immunotherapy resistance of gastric cancer (GC) remain unclear. Methods: Gene expression data and matching clinical information were extracted from TCGA-STAD, GSE84437, GSE34942, GSE15459, GSE57303, ACRG/GSE62254, GSE29272, GSE26253, and IMvigor210 datasets. A consensus clustering analysis based on six apoptosis-related genes (ARGs) was performed to determine the molecular subtypes, and then an apoptosisScore was constructed based on differentially expressed and prognostic genes between molecular subtypes. Estimate R package was utilized to calculate the tumor microenvironment condition. Kaplan-Meier analysis and ROC curves were performed to further confirm the apoptosisScore efficacy. Results: Based on six ARGs, two molecular subgroups with significantly distinct survival and immune cell infiltration were identified. Then, an apoptosisScore was built to quantify the apoptosis index of each GC patient. Next, we investigated the correlations between the clinical characteristics and apoptosisScore using logistic regression. Multivariate Cox analysis shows that low apoptosisScore was an independent predictor of poor overall survival in TCGA and ACRG datasets, and was associated with the higher pathological stage. Meanwhile, low apoptosisScore was associated with higher immune cell, higher ESTIMATEScore, higher immuneScore, higher stromalScore, higher immune checkpoint, and lower tumorpurity, which was consistent with the \"immunity tidal model theory\". Importantly, low apoptosisScore was sensitive to immunotherapy. In addition, GSEA indicated that several gene ontology and Kyoto Encyclopedia of Genes and Genomes items associated with apoptosis, several immune-related pathways, and JAK-STAT signal pathway were considerably enriched in the low apoptosisScore phenotype pathway. Conclusion: Our findings propose that low apoptosisScore is a prognostic biomarker, correlated with immune infiltrates, and sensitivity to immunotherapy in GC.

To identify an apoptosis-related gene (ARG) prediction model for oral squamous cell carcinoma (OSCC), we analyzed and validated the data from TCGA and GEO, respectively. Kaplan-Meier survival analysis and ROC curves showed a good prognostic ability of the model both in the internal training set and in the external testing set. Furthermore, we built a nomogram using these ARGs to forecast the survival probability of OSCC patients. Moreover, we evaluated the rate of immune cells infiltrating in the tumor samples and found obvious, different patterns between the high and low risk groups. GO and KEGG analyses demonstrated multiple molecular biological processes and signaling pathways connecting with this prognostic model in OSCC. The expression of these risk genes in clinical specimens was higher in the non-survival patients than in the well-survival patients by immunohistochemical staining analysis. In conclusion, we established a signature made up of six risk apoptosis-related genes to predict the survival rate of OSCC. These genes could also be targets for the treatment of OSCC.

The plateau zokor (Myospalax baileyi) is a native species of the Qinghai-Tibet Plateau that spends its entire life underground in sealed burrows with hypoxic conditions. The present study aimed to assess the sequence characteristics of apoptosis-related genes and the response to different oxygen partial pressures (pO2) in plateau zokor and Sprague-Dawley rats. The sequences of the p53-induced protein with a death domain (Pidd), p53-upregulated modulator of apoptosis (Puma), insulin-like growth factor binding protein 3 (Igfbp3), and apoptosis protease-activating factor 1 (Apaf1) were evaluated concerning homology and convergent evolution sites, and their mRNA levels were evaluated in different tissues under 14.13 (3,300 m) and 16.12 kPa (2,260 m) pO2 conditions. Our results showed that, (1) the sequences of the apoptosis-related genes in plateau zokor were highly similar to those of Nannospalax galili, followed by Rattus norvegicus; (2). Pidd, Puma, Igfbp3, and Apaf1 of plateau zokor were found to have five, one, two, and five convergent sites in functional domains with N. galili, respectively. Lastly (3), under low pO2, the expression of Pidd and Puma was downregulated in the lung of plateau zokors. In turn, Igfbp3 and Apaf1 were upregulated in the liver and lung, and Puma was upregulated in the skeletal muscle of plateau zokor under low pO2. In Sprague-Dawley rats, low pO2 downregulated Puma and Apaf1 expression in the liver and downregulated Igfbp3 and Puma in the lung and skeletal muscle separately. In contrast, low pO2 upregulated Pidd expression in the liver and skeletal muscle of Sprague-Dawley rats. Overall, the expression patterns of Apaf1, Igfbp3, and Puma showed the opposite pattern in the liver, lung, and skeletal muscle, respectively, of plateau zokor as compared with Sprague-Dawley rats. In conclusion, for the long-time adaptation to hypoxic environments, Pidd, Puma, Igfbp3, and Apaf1 of plateau zokor underwent convergent evolution, which we believe may have led to upregulation of their levels under low oxygen partial pressures to induce apoptosis, so as to suppress tumorigenesis under hypoxic environments in plateau zokor.