Role of hypoxia-inducible factor-1α and survivin in breast cancer recurrence and prognosis

Transcriptomic signatures of prostate cancer progression: a comprehensive RNA-seq study

Transcriptomics has been entirely transformed by RNA-sequencing (RNA-seq) due to its high sensitivity, accuracy, and precision. This study analyzed RNA-seq data to identify potential biomarkers for prostate cancer (PCa), a serious health issue among aging men. Despite several existing studies, biomarkers that effectively detect PCa or its prognosis have yet to be entirely determined. The differentially expressed genes (DEGs) that are critical and clinically informative were identified in PCa patient samples that had been progression stage categorized into medium risk (MR) and high risk (HR). A total of 174 DEGs were found to be shared between MR and HR samples. Functional enrichment analysis revealed their involvement in crucial biological processes, such as p53 signaling, mitotic nuclear division, and inflammation. To further examine their interactions, a Protein-Protein Interaction (PPI) network was constructed, where key genes, such as KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67, were found in significant modules, hubs, and motifs. Several transcription factors, including STAT5B, MYC, and SOX5 controlled these genes. Heatmap analysis indicates that the expression of the six crucial genes (KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67) increases with progression from benign state to medium-risk and high-risk states. Additionally, a nomogram model was constructed to predict the prognostic value of these biomarkers. Among the studied genes, BIRC5, MKI67, and KIF20A are suggested as potential prognostic biomarkers, while NIFK and PPP1CC are suggested as new therapeutic targets. These findings indicate that these biomarkers show considerable promise in improving early detection and prognosis of PCa.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04297-3.

Applying integrated transcriptome and single-cell sequencing analysis to develop a prognostic signature based on M2-like tumor-associated macrophages for breast cancer

BACKGROUND

M2-like tumor-associated macrophages (M2-like TAMs) function crucially in the tumor microenvironment (TME) and cancer development. This study developed a prognostic signature based on M2-like TAM-related genes for breast cancer (BRCA) applying transcriptome and scRNA-seq analysis.

METHODS

TCGA-BRCA, GSE20685, and GSE176078 datasets were downloaded from UCSC xena and GEO databases. AUCell score of immune-related genes (IRGs) was calculated using R package. Genes related to M2-like TAMs were screened by WGCNA. Prognostic genes were further identified by univariate Cox and LASSO regression analyses to form a RiskScore model, which was validated in external dataset. Furthermore, a nomogram was established by integrating RiskScore and clinical characteristics, and correlation analysis between the RiskScore and TME or chemotherapeutic drugs was conducted. Finally, the mRNA expression levels of the key genes identified were verified using quantitative real time polymerase chain reaction (qRT-PCR).

RESULTS

As macrophages exhibited the highest AUCell score of IRGs in single-cell transcriptomic atlas of BRCA, the cells were further classified into Macrophages C1 and C2 subtypes, with the C1 subtype showing a high expression of M2 macrophage marker genes. ARHGAP26, RILP, KLRB1, CSTA, KLHDC7B, PSMB8, KYNU, RNASE1, LONRF3, and TRPM2 were screened as the prognostic signature genes from a total of 903 M2-like TAM-related genes to establish a robust RiskScore model. Furthermore, a nomogram with a strong predictive performance was constructed combining stage, Age, and RiskScore, and we found that most immune cells showed a negative correlation with RiskScore. Multiple drugs were closely associated with the RiskScore, notably, Ribociclib_1632 had higher a half-maximal inhibitory concentration (IC50) value in high-risk group. Finally, qRT-PCR demonstrated that the mRNA expression levels of the 10 genes were significantly different in control and BRCA cell lines.

CONCLUSION

We identified 10 M2-like TAM-related prognostic signature genes for BRCA, providing potential therapeutic targets for the treatment of the cancer.

The prognostic role of survivin expression in breast cancer: A systematic review and meta-analysis

BACKGROUND

Breast cancer is a heterogeneous condition with variations in histopathological, genomic, and biological characteristics. Although clinicopathological prognostic factors and gene expression profiles are commonly used to guide treatment decisions in patients with breast cancer, there is still a need for new prognostic markers. One potential marker is survivin, a protein belonging to the apoptosis inhibitor family. However, studies examining the relationship between survivin and prognosis in breast cancer have yielded inconsistent results. This study aimed to evaluate the impact of survivin expression on the prognosis of breast cancer patients through a meta-analysis.

METHODS

Studies evaluating survivin expression were sourced from the PubMed, Embase, and Cochrane databases. We conducted a meta-analysis based on full-text articles that evaluated the relationship between survivin expression and survival by immunochemistry or polymerase chain reaction. The studies were initially divided into 2 groups based on the evaluation of overall survival (OS) and disease-free survival (DFS). Subsequently, each group was further categorized according to the method used to detect survivin expression. Statistical analyses for this study were conducted using Stata and JAMOVI.

RESULTS

After screening with keywords, we identified 24 retrospective studies evaluating OS and 15 retrospective studies evaluating DFS, which were included in the analysis. We found that the studies in the meta-analysis were not heterogeneous, and this remained consistent when categorizing the groups by survivin expression detection. Survivin expression was associated with OS (HR 1.23, 95% CI 0.81-1.65) and DFS (HR 0.89, CI 0.42-1.36), indicating poor prognosis. This significant relationship between survivin expression and survival persisted when the studies were categorized by the detection method, either immunohistochemistry or polymerase chain reaction.

CONCLUSION

In this study, we evaluated the prognostic significance of survivin expression in patients with breast cancer through a meta-analysis. These results support the use of survivin expression as a prognostic marker in breast cancer, potentially guiding treatment decisions.

Hypoxia-induced epigenetic regulation of breast cancer progression and the tumour microenvironment

The events that control breast cancer progression and metastasis are complex and intertwined. Hypoxia plays a key role both in oncogenic transformation and in fueling the metastatic potential of breast cancer cells. Here we review the impact of hypoxia on epigenetic regulation of breast cancer, by interfering with multiple aspects of the tumour microenvironment. The co-dependent relationship between oxygen depletion and metabolic shift to aerobic glycolysis impacts on a range of enzymes and metabolites available in the cell, promoting posttranslational modifications of histones and chromatin, and changing the gene expression landscape to facilitate tumour development. Hormone signalling, particularly through ERα, is also tightly regulated by hypoxic exposure, with HIF-1α expression being a prognostic marker for therapeutic resistance in ER+ breast cancers. This highlights the strong need to understand the hypoxia-endocrine signalling axis and exploit it as a therapeutic target. Furthermore, hypoxia has been shown to enhance metastasis in TNBC cells, as well as promoting resistance to taxanes, radiotherapy and even immunotherapy through microRNA regulation and changes in histone packaging. Finally, several other mediators of the hypoxic response are discussed. We highlight a link between ionic dysregulation and hypoxia signalling, indicating a potential connection between HIF-1α and tumoural Na+ accumulation which would be worth further exploration; we present the role of Ca2+ in mediating hypoxic adaptation via chromatin remodelling, transcription factor recruitment and changes in signalling pathways; and we briefly summarise some of the findings regarding vesicle secretion and paracrine induced epigenetic reprogramming upon hypoxic exposure in breast cancer. By summarising these observations, this article highlights the heterogeneity of breast cancers, presenting a series of pathways with potential for therapeutic applications.

Assessing of case-cohort design: a case study for breast cancer patients in Xinjiang, China

Objective

To assess the effectiveness and clinical value of case-cohort design and determine prognostic factors of breast cancer patients in Xinjiang on the basis of case-cohort design.

Methods

The survival data with different sample characteristics were simulated by using Cox proportional risk models. To evaluate the effectiveness for the case-cohort, entire cohort, and simple random sampling design by comparing the mean, coefficient of variation, etc., of covariate parameters. Furthermore, the prognostic factors of breast cancer patients in Xinjiang were determined based on case-cohort sampling designs. The models were comprehensively evaluated by likelihood ratio test, the area under the receiver operating characteristic curve (AUC), and Akaike Information Criterion (AIC).

Results

In a simulations study, the case-cohort design shows better stability and improves the estimation efficiency when the censored rate is high. In the breast cancer data, molecular subtypes, T-stage, N-stage, M-stage, types of surgery, and postoperative chemotherapy were identified as the prognostic factors of patients in Xinjiang. These models based on the different sampling designs both passed the likelihood ratio test (p<0.05). Moreover, the model constructed under the case-cohort design had better fitting effect (AIC=3,999.96) and better discrimination (AUC=0.807).

Conclusion

Simulations study confirmed the effectiveness of case-cohort design and further determined the prognostic factors of breast cancer patients in Xinjiang based on this design, which presented the practicality of case-cohort design in actual data.

Breaking Barriers: The Promise and Challenges of Immune Checkpoint Inhibitors in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a highly aggressive malignancy with pronounced immunogenicity, exhibiting rapid proliferation and immune cell infiltration into the tumor microenvironment. TNBC's heterogeneity poses challenges to immunological treatments, inducing resistance mechanisms in the tumor microenvironment. Therapeutic modalities, including immune checkpoint inhibitors (ICIs) targeting PD-1, PD-L1, and CTLA-4, are explored in preclinical and clinical trials. Promising results emerge from combining ICIs with anti-TGF-β and VISTA, hindering TNBC tumor growth. TNBC cells employ complex evasion strategies involving interactions with stromal and immune cells, suppressing immune recognition through various cytokines, chemokines, and metabolites. The recent focus on unraveling humoral and cellular components aims to disrupt cancer crosstalk within the tumor microenvironment. This review identifies TNBC's latest resistance mechanisms, exploring potential targets for clinical trials to overcome immune checkpoint resistance and enhance patient survival rates.