Immunogenic cell death signatures from on-treatment tumor specimens predict immune checkpoint therapy response in metastatic melanoma.

Melanoma is a highly malignant form of skin cancer that typically originates from abnormal melanocytes. Despite significant advances in treating metastatic melanoma with immune checkpoint blockade (ICB) therapy, a substantial number of patients do not respond to this treatment and face risks of recurrence and metastasis. This study collected data from multiple datasets, including cohorts from Riaz et al., Gide et al., MGH, and Abril-Rodriguez et al., focusing on on-treatment samples during ICB therapy. We used the single-sample gene set enrichment analysis (ssGSEA) method to calculate immunogenic cell death scores (ICDS) and employed an elastic network algorithm to construct a model predicting ICB efficacy. By analyzing 18 ICD gene signatures, we identified 9 key ICD gene signatures that effectively predict ICB treatment response for on-treatment metastatic melanoma specimens. Results showed that patients with high ICD scores had significantly higher response rates to ICB therapy compared to those with low ICD scores. ROC analysis demonstrated that the AUC values for both the training and validation sets were around 0.8, indicating good predictive performance. Additionally, survival analysis revealed that patients with high ICD scores had longer progression-free survival (PFS). This study used an elastic network algorithm to identify 9 ICD gene signatures related to the immune response in metastatic melanoma. These gene features can not only predict the efficacy of ICB therapy but also provide references for clinical decision-making. The results indicate that ICD plays an important role in metastatic melanoma immunotherapy and that expressing ICD signatures can more accurately predict ICB treatment response and prognosis for on-treatment metastatic melanoma specimens, thus providing a basis for personalized treatment.

Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.

Background: Breast cancer (BC) constitutes a significant peril to global women's health. Contemporary research progressively suggests that mitochondrial dysfunction plays a pivotal role in both the inception and advancement of BC. However, investigations delving into the correlation between mitochondrial-related genes (MRGs) and the prognosis and metastasis of BC are still infrequent. Methods: Utilizing data from the TCGA database, we employed the "limma" R package for differential expression analysis. Subsequently, both univariate and multivariate Cox regression analyses were executed, alongside LASSO Cox regression analysis, to pinpoint prognostic MRGs and to further develop the prognostic model. External validation (GSE88770 merged GSE425680) and internal validation were further conducted. Our investigation delved into a broad spectrum of analyses that included functional enrichment, metabolic and immune characteristics, immunotherapy response prediction, intratumor heterogeneity (ITH), mutation, tumor mutational burden (TMB), microsatellite instability (MSI), cellular stemness, single-cell, and drug sensitivity analysis. We validated the protein and mRNA expressions of prognostic MRGs in tissues and cell lines through immunohistochemistry and qRT-PCR. Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. The division between training and validation cohorts was set at 70% and 30%, respectively. Results: A prognostic model was constructed by 9 prognostic MRGs, which were DCTPP1, FEZ1, KMO, NME3, CCR7, ISOC2, STAR, COMTD1, and ESR2. Patients within the high-risk group experienced more adverse outcomes than their counterparts in the low-risk group. The ROC curves and constructed nomogram showed that the model exhibited an excellent ability to predict overall survival (OS) for patients and the risk score was identified as an independent prognostic factor. The functional enrichment analysis showed a strong correlation between metabolic progression and MRGs. Additional research revealed that the discrepancies in outcomes between the two risk categories may be attributed to a variety of metabolic and immune characteristics, as well as differences in intratumor heterogeneity (ITH), tumor mutational burden (TMB), and cancer stemness indices. ITH, TIDE, and IPS analyses suggested that patients possessing a low-risk score may exhibit enhanced responsiveness to immunotherapy. Additionally, distant metastasis models were established by PDK4, NRF1, DCAF8, CHPT1, MARS2 and NAMPT. Among these, the XGBoost model showed the best predicting ability. Conclusion: In conclusion, MRGs significantly influence the prognosis and metastasis of BC. The development of dual clinical prediction models offers crucial insights for tailored and precise therapeutic strategies, and paves the way for exploring new avenues in understanding the pathogenesis of BC.

Plasmonic Supramolecular Nanozyme-Based Bio-Cockleburs for Synergistic Therapy of Infected Diabetic Wounds.

Diabetic wounds are a major devastating complication of diabetes due to hyperglycemia, bacterial invasion, and persistent inflammation, and the current antibiotic treatments can lead to the emergence of multidrug-resistant bacteria. Herein, a bimetallic nanozyme-based biomimetic bio-cocklebur (GNR@CeO2@GNPs) is designed and synthesized for diabetic wound management by depositing spiky ceria (CeO2) shells and gold nanoparticles (GNPs) on a gold nanorod (GNR) nanoantenna. The plasmonic-enhanced nanozyme catalysis and self-cascade reaction properties simultaneously boost the two-step enzyme-mimicking catalytic activity of GNR@CeO2@GNPs, leading to a significant improvement in overall therapeutic efficacy rather than mere additive effects. Under the glucose activation and 808 nm laser irradiation, GNR@CeO2@GNPs material captures photons and promotes the transfer of hot electrons from GNR and GNPs into CeO2, realizing a "butterfly effect" of consuming local glucose, overcoming the limited antibacterial efficiency of an individual PTT modality, and providing substantial reactive oxygen species. In vitro and in vivo experiments demonstrate the material's exceptional antibacterial and antibiofilm properties against Gram-negative and Gram-positive bacteria, which can reduce inflammation, promote collagen deposition, and facilitate angiogenesis, thereby accelerating wound healing. This study provides a promising new strategy to develop plasmonic-enhanced nanozymes with a catalytic cascade mode for the antibiotic-free synergistic treatment of infected diabetic wounds.

Individualized prediction of non-sentinel lymph node metastasis in Chinese breast cancer patients with ≥ 3 positive sentinel lymph nodes based on machine-learning algorithms.

BACKGROUND: Axillary lymph node dissection (ALND) is a standard procedure for early-stage breast cancer (BC) patients with three or more positive sentinel lymph nodes (SLNs). However, ALND can lead to significant postoperative complications without always providing additional clinical benefits. This study aims to develop machine-learning (ML) models to predict non-sentinel lymph node (non-SLN) metastasis in Chinese BC patients with three or more positive SLNs, potentially allowing the omission of ALND. METHODS: Data from 2217 BC patients who underwent SLN biopsy at Shantou University Medical College were analyzed, with 634 having positive SLNs. Patients were categorized into those with ≤ 2 positive SLNs and those with ≥ 3 positive SLNs. We applied nine ML algorithms to predict non-SLN metastasis. Model performance was evaluated using ROC curves, precision-recall curves, and calibration curves. Decision Curve Analysis (DCA) assessed the clinical utility of the models. RESULTS: The RF model showed superior predictive performance, achieving an AUC of 0.987 in the training set and 0.828 in the validation set. Key predictive features included size of positive SLNs, tumor size, number of SLNs, and ER status. In external validation, the RF model achieved an AUC of 0.870, demonstrating robust predictive capabilities. CONCLUSION: The developed RF model accurately predicts non-SLN metastasis in BC patients with ≥ 3 positive SLNs, suggesting that ALND might be avoided in selected patients by applying additional axillary radiotherapy. This approach could reduce the incidence of postoperative complications and improve patient quality of life. Further validation in prospective clinical trials is warranted.

C188-9 reduces patient-specific primary breast cancer cells proliferation at the low, clinic-relevant concentration.

OBJECTIVES: STAT3 is a transcriptional activator of breast cancer oncogenes, suggesting that it could be a potential therapeutic target for breast cancer. Therefore, this study investigated the potential application of C188-9, a STAT3 signal pathway inhibitor, in the treatment of breast cancer through a novel pre-clinical platform with patient-specific primary cells (PSPCs). METHODS: PSPCs were isolated from breast cancer samples obtained via biopsy or surgery from fifteen patient donors with their full acknowledgements. PSPCs were treated with C188-9 or other chemotherapeutic agents, and then analyzed with cell viability assay. Western blot assay and real-time quantitative PCR were also used to determine the expression and activity of STAT3 signaling pathway of corresponding PSPCs. RESULTS: C188-9 treatment at normal (experimental) concentration had valid inhibition on PSPCs proliferation. Meanwhile, treatment at a low (clinic-relevant) concentration of C188-9 for an extended period reduced cell viability of PSPCs still more than some of other traditional chemotherapy drugs. In addition, C188-9 decreased expression level of pSTAT3 in PSPCs from some, but not all patient samples. The treatment of C188-9 reduced cell viability of the breast cancer samples through inhibiting the STAT3 to C-myc signaling pathway. CONCLUSIONS: In this study, we tested a novel drug C188-9 at a low, clinic-relevant concentration, together with several traditional chemotherapy agents. PSPCs from ten out of fifteen patient donors were sensitive to C188-9, while some of traditional chemotherapy agents failed. This finding suggested that C188-9 could have treatment effects only on those ten PSPC patient donors, indicating the future personalized utilization of PSPCs.

HER2-positive is an independent indicator for predicting pathological complete response to neoadjuvant therapy and Ki67-changed after neoadjuvant chemotherapy predicts favorable prognosis in Chinese women with locally advanced breast cancer.

The growing body of evidence suggests that breast cancer (BC) who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) may experience a more favorable prognosis. The objective of this study is to investigate the correlation between clinicopathologic parameters of locally advanced breast cancer (LABC) patients and the outcomes of NAC, with the aim of identifying predictive indicators for pCR. Additionally, we seek to examine the conversion of IHC markers in pCR patients following NAC and its impact on the prognosis of BC patients. We conducted a study involving 126 patients with LABC. Clinicopathological parameters associated with pCR were subjected to univariate and multivariate analysis. Kaplan-Meier (KM) curves and the log-rank test were used to compare the statistical difference in prognosis in different groups of patients. Additionally, we used difference and consistency tests to examine the conversion of immunohistochemistry (IHC) markers following NAC. The status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and molecular subtypes of BC were associated with pCR in the univariate analysis (all P < .05), which may be potential markers to predict pCR. HER2 was identified as an independent factor for predicting pCR in the multivariate analysis. The pCR rate of HER2-positive patients who received NAC combined targeted therapy was higher than that of patients who only received NAC (P = .003). The disease-free survival (DFS) rate of TNBC patients who achieved pCR was significantly higher than that of non-pCR TNBC patients (P = .026). The IHC marker conversion after NAC mainly existed in PR (P = .041). Ki67 expression decreased in the luminal B subtype and increased in the HER2 enriched subtype after NAC (all P < .001). Patients with Ki67 expression change after NAC had longer overall survival (OS) and DFS than unchanged patients (all P < .05). HER2-positive is an independent indicator for predicting pCR, and HE2-positive patients who received NAC combined targeted therapy were favorable to achieving pCR. IHC markers of BC patients exhibit varying degrees of alterations after NAC, and changes in Ki67 expression after NAC could serve as a marker to predict a better prognosis.

Prognostic implication of novel immune-related signature in breast cancer.

Checkpoint inhibitor therapy has become increasingly important and has been endorsed as a treatment regimen in breast cancer. But benefits were limited to a small proportion of patients. We aimed to develop an improved signature on the basis of immune genes for detection of potential benefit from immunotherapy. Gene expression data of patients with breast cancer initially extracted from The Cancer Genome Atlas were analyzed. Ten genes were selected from the interaction of differentially expressed genes as well as immune-related genes to develop a survival signature. We compared the high-risk and low-risk groups by gene set enrichment analysis, immune infiltration, checkpoint molecule expression and immunophenoscore. Ten genes were extracted from interactions of differentially expressed and immune-related genes. The immune risk score was determined on the basis of the Cox regression coefficient of hub genes and validated with the GSE96058 dataset. Immune cell infiltrates, including CD8 + T cells, plasma cells, follicular helper T cells, CD4 + memory T cells, M1 macrophages, regulatory T cells and resting NK cells, were more highly infiltrated in the high-risk group as compared to the low-risk group. Checkpoint molecules, including CTLA-4, PD-L1, TIM-3, VISTA, ICOS, PD-1, and PD-L2, were expressed at markedly lower levels in the high-risk group as compared to the low-risk group. Immunophenoscores, as a surrogate of response to immune checkpoint therapy, was observed significant lower in the high-risk group. The 10-gene prognostic signature could identify patients' survival and was correlated with the biomarkers of immune checkpoint inhibitor therapy, which may guide precise therapeutic decisions in clinical practice.

Clinical significance and immune characteristics analysis of miR-221-3p and its key target genes related to epithelial-mesenchymal transition in breast cancer.

BACKGROUND: MicroRNA-221-3p (miR-221-3p) facilitates the advancement of breast cancer (BC) through the induction of epithelial-mesenchymal transition (EMT). Our research aimed to utilize bioinformatics to discover possible EMT-related target genes (ETGs) of miR-221-3p and examine their roles in breast cancer. METHODS: We employed bioinformatics techniques to identify ten key ETGs of miR-221-3p. Subsequently, we conducted an extensive analysis of both miR-221-3p and the ten ETGs, including clinical significance and immune characteristics. RESULTS: The expression of miR-221-3p was notably higher in Basal-like BC compared to other subtypes and adjacent normal tissue. Our pathway analysis suggested that miR-221-3p might regulate EMT through the MAPK signaling pathway by targeting its ETGs. Among the ETGs, seven core genes (EGFR, IGF1, KDR, FGF2, KIT, FGFR1, and FGF1) exhibited downregulation in BC. Conversely, ERBB2, SDC1, and MMP14 showed upregulation in BC and displayed potential diagnostic value. The analysis of prognostication indicated that increased levels of SDC1 and MMP14 were correlated with an unfavorable prognosis, whereas elevated expression of KIT was associated with a more favorable prognosis. The infiltration of various immune cells and the expression of immune checkpoint genes (ICGs) exhibited positive correlations with most ETGs and miR-221-3p. SDC1 exhibited a greater tumor mutational burden (TMB) score, while ERBB2, KDR, FGF2, KIT, FGFR1, and FGF1 showed lower TMB scores. Furthermore, decreased ERBB2 and KDR expression levels were correlated with elevated microsatellite instability (MSI) scores. Elevated expression of ETGs was linked to decreased mRNA stemness indices (mRNAsi), whereas miR-221-3p displayed the opposite pattern. Most ETGs and miR-221-3p expression exhibited a negative correlation with IC50 values for drugs. Among the ETGs, amplification was the most significant genetic alteration, except for IGF1. CONCLUSION: In conclusion, miR-221-3p acts as a unique indicator for Basal-like BC. The examination revealed ten essential ETGs of miR-221-3p, some of which show potential as diagnostic and prognostic markers. The in-depth examination of these ten ETGs and miR-221-3p indicates their participation in the development of BC, emphasizing their promise as innovative targets for therapy in BC patients.

Construction and characterization of a magnetic nanoparticle-supported Cu complex: a stable and active nanocatalyst for synthesis of heteroaryl-aryl and di-heteroaryl sulfides.

Diaryl and di-heteroaryl sulfides exist in the structure of many drugs and important biological compounds, also these compounds are well-known in medicinal chemistry due to important biological and pharmaceutical activities. Therefore, the development of novel, ecofriendly and efficient catalytic systems for the preparation of diaryl and di-heteroaryl sulfides is a very attractive and important challenge in organic synthesis. In this attractive methodology, we wish to introduce Fe3O4-supported 3-amino-4-mercaptobenzoic acid copper complex (Fe3O4@AMBA-CuI) nanomaterials as a novel and efficient magnetically recoverable catalyst for the preparation of heteroaryl-aryl and di-heteroaryl sulfides with high yields through reaction of heteroaryl halides with aryl or heteroaryl boronic acids and S8 as the sulfur source under ecofriendly conditions. This catalytic system was very efficient and practical for a diverse range of heteroaryl substrates including benzothiazole, benzoxazole, benzimidazole, oxadiazole, benzofuran, and imidazo[1,2-a]pyridine, because the desired diaryl and di-heteroaryl sulfides were prepared with high yields. The reusability-experiments revealed that the Fe3O4@AMBA-CuI nanocatalyst can be magnetically separated and reused at least six times without a significant decrease in its catalytic activity. VSM and ICP-OES analyses confirmed that despite using the Fe3O4@AMBA-CuI nanocatalyst 6 times, the magnetic properties and stability of the catalyst were still maintained. Although all the obtained heteroaryl-aryl and di-heteroaryl sulfide products are known and previously reported, the synthesis of this number of heteroaryl-aryl and di-heteroaryl sulfides has never been reported by any previouse methods.

Identification and comprehensive analysis of epithelial-mesenchymal transition related target genes of miR-222-3p in breast cancer.

Background: Epithelial-mesenchymal transition (EMT) is a crucial mechanism that microRNA-222-3p (miR-222-3p) promotes breast cancer (BC) progression. Our study aimed to identify EMT-associated target genes (ETGs) of miR-222-3p for further analysis of their roles in BC based on bioinformatics tools. Methods: Based on bioinformatics analysis, we identified 10 core ETGs of miR-222-3p. Then, we performed a comprehensive analysis of 10 ETGs and miR-222-3p, including pathway enrichment analysis of ETGs, differential expression, clinical significance, correlation with immune cell infiltration, immune checkpoint genes (ICGs) expression, tumor mutational burden (TMB), microsatellite instability (MSI), stemness, drug sensitivity, and genetic alteration. Results: The expression of miR222-3p in basal-like BC was significantly higher than in other subtypes of BC and the normal adjacent tissue. Pathway analysis suggested that the ETGs might regulate the EMT process via the PI3K-Akt and HIF-1 signaling pathway. Six of the 10 core ETGs of miR-222-3p identified were down-expressed in BC, which were EGFR, IL6, NRP1, NTRK2, LAMC2, and PIK3R1, and SERPINE1, MUC1, MMP11, and BIRC5 were up-expressed in BC, which also showed potential diagnostic values in BC. Prognosis analysis revealed that higher NTRK2 and PIK3R1 expressions were related to a better prognosis, and higher BIRC5 and miR-222-3p expressions were related to a worse prognosis. Most ETGs and miR-222-3p were positively correlated with various infiltration of various immune cells and ICGs expression. Lower TMB scores were correlated with higher expression of MUC1 and NTRK2, and higher BIRC5 was related to a higher TMB score. Lower expression of MUC1, NTRK2, and PIK3R1 were associated with higher MSI scores. Higher expression of ETGs was associated with lower mRNAsi scores, except BIRC5 and miR-222-3p conversely. Most ETGs and miR-222-3p expression were negatively correlated with the drug IC50 values. The analysis of the genetic alteration of the ETGs suggested that amplification was the main genetic alteration of eight ETGs except for NTRK2 and PIK3R1. Conclusion: MiR-222-3p might be a specific biomarker of basal-like BC. We successfully identify 10 core ETGs of miR-222-3p, some might be useful diagnostic and prognostic biomarkers. The comprehensive analysis of 10 ETGs and miR-222-3p indicated that they might be involved in the development of BC, which might be novel therapeutic targets for the treatment of BC.

Diagnostic and prognostic significance of SLC50A1 expression in patients with primary early breast cancer.

There is a lack of validated biomarkers for the diagnosis of early breast cancer (EBC). The current study aimed to determine the diagnostic and prognostic value of solute carrier family 50 member 1 (SLC50A1) in patients with EBC. Therefore, 123 patients with EBC, 30 patients with benign breast disease (BBD) and 26 healthy controls (HCs) were recruited. The serum levels of SLC50A1 in paired sera of 40 postoperative patients were assessed by ELISA. Immunohistochemical staining for SLC50A1 was performed in surgical tissue derived from 83 patients with EBC and 30 patients with BBD. mRNA expression of SLC50A1 and its diagnostic and prognostic value in patients with EBC was evaluated using an RNA-sequencing database. The results showed that serum levels of SLC50A1 in patients with EBC were significantly higher compared with those in patients with BBD and HCs (both P<0.001). Additionally, receiver operating characteristic curve analysis revealed that the serum levels of SLC50A1 distinguished patients with EBC from patients with BBD and HCs with a sensitivity of 76.42% and specificity of 76.79% [area under the curve (AUC)=0.783; P<0.001]. The diagnostic value of SLC50A1 was significantly greater than that of carcinoembryonic (P<0.005) and carbohydrate antigen 15-3 (P<0.029). Furthermore, the number of SLC50A1 positive cells significantly increased in tissue of patients with EBC compared with patients with BBD (P<0.001). A positive association between serum levels of SLC50A1 and its expression in tissue samples was observed in patients with EBC (ρ=0.700; P<0.001). Additionally, bioinformatics analysis verified the diagnostic value of SLC50A1, with an AUC of 0.983 (P<0.001). Multivariate analysis demonstrated that SLC50A1 was an independent prognostic factor in patients with EBC with a hazard ratio of 1.917 (P=0.013). These findings indicated that SLC50A1 may be a potential diagnostic biomarker for primary EBC and that SLC50A1 upregulation may be associated with unfavorable prognosis in patients with EBC.

HYAL3 as a potential novel marker of BLCA patient prognosis.

BACKGROUND: It has been previously demonstrated that hyaluronan (HA) potentially regulates the initiation and propagation of bladder cancer (BLCA). HYAL3 encodes hyaluronidase and is a potential therapeutic target for BLCA. We aimed to explore the role that HYAL3 plays in BLCA pathogenesis. METHODS: HYAL3 expression in BLCA specimens was analyzed using The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) cohort as well as confirmed in cell lines and The Human Protein Atlas. Then, associations between HYAL3 expression and clinicopathological data were analyzed using survival curves and receiver-operating characteristic (ROC) curves. The functions of HYAL3 were further dissected using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the protein-protein interaction network. Finally, we harnessed the Tumor IMmune Estimation Resource and Gene Expression Profiling Interactive Analysis to obtain correlations between HYAL3 expression, infiltrating immunocytes, and the corresponding immune marker sets. RESULTS: HYAL3 expression varied greatly between many types of cancers. In addition, a higher HYAL3 expression level predicted a poor overall survival (OS) in both TCGA-BLCA and GEO gene chips (P < 0.05). HYAL3 also exhibited an acceptable diagnostic ability for the pathological stage of BLCA (area under the receiver-operating characteristic curve = 0.769). Furthermore, HYAL3 acted as an independent prognostic factor in BLCA patients and correlated with the infiltration of various types of immunocytes, including B cells, CD8+ T cells, cytotoxic cells, T follicular helper cells, and T helper (Th) 2 cells. CONCLUSION: HYAL3 might serve as a potential biomarker for predicting poor OS in BLCA patients and correlated with immunocyte infiltration in BLCA.

Overexpressed VDAC1 in breast cancer as a novel prognostic biomarker and correlates with immune infiltrates.

BACKGROUND: More and more evidence suggests that cancer is a mitochondrial metabolic disease recently and mitochondria dysfunction is critical to tumorigenesis. As a gatekeeper of mitochondria, the voltage-dependent anion channel 1 (VDAC1) is associated with the development of breast cancer (BC). However, its potential mechanism and clinical significance remain unclear; thus, in this research, we aimed to explore it. METHODS: VDAC1 expression in BC tissues and normal tissues was obtained from The Cancer Genome Atlas (TCGA) and validated by datasets from the gene expression omnibus (GEO) database. Then, the relationships between VDAC1 expression and clinicopathological features were analyzed. Receiver operating characteristics (ROC) curves were used to identify the diagnostic value of VDAC1. The prognostic value was evaluated by Kaplan-Meier survival curves and Cox regression analysis. VDAC1 with its co-expression genes were subjected to enrichment analysis to explore potential mechanisms in BC and the protein-protein interaction (PPI) network was constructed. At last, the association between VDAC1 expression and infiltration levels of immune cell infiltration by various methods, as well as their corresponding markers, was analyzed. We also analyzed the correction between VDAC1 expression and eight immune checkpoint genes and the tumor immune dysfunction and exclusion (TIDE) scores of each BC sample in TCGA were calculated and the differences between high and low VDAC1 expression groups were analyzed. RESULTS: VDAC1 expression was remarkably elevated in BC (p < 0.001), and high expression of VDAC1 was associated with the positive expression of ER (p = 0.004), PR (p = 0.033), and HER2 (p = 0.001). ROC analysis suggested that VDAC1 had diagnosed value in BC. The Kaplan-Meier analysis suggested that higher expression of VDAC1 was associated with shorter overall survival (OS), and further Cox regression analysis revealed that VDAC1 was an independent factor of unfavorable prognosis in BC patients. Enrichment analysis of VDAC1 and its co-expression suggested that VDAC1 was related to the regulation of mitochondrial energy metabolism and protein modification, and the HIF-1 singing pathway might be the potential mechanism in BC. Notably, we found that VDAC1 expression was infiltration levels of most types of immune cells, as well as the expression of marker genes of immune cells. The ICGs PDCD1, CTLA4, LAG3, SIGLEC15, and TIGIT were negatively corrected with VDAC1 expression in BC. TIDE scores between the low and high expression groups showed no difference. CONCLUSION: Overexpressed VDAC1 in BC could be severed as a novel biomarker for diagnosis and VDAC1 was an independent factor for adverse prognosis prediction. Our study revealed that VDAC1 might inhibit tumor immunity and might be a novel therapeutic target in BC.