Datopotamab deruxtecan: A novel antibody drug conjugate for triple-negative breast cancer

How has the field of immunogenic cell death in breast cancer evolved and impacted clinical practice over the past eleven years?

This study elucidates the research landscape of immunogenic cell death (ICD) in breast cancer through a bibliometric analysis of 457 Web of Science articles. Contributions from China and the USA are particularly prominent, with notable international collaborations. Core journals such as Biomaterials published influential studies, while researchers like Huang Y made impactful contributions. High-frequency keyword analysis identified key research hotspots, including immunotherapy, the tumor microenvironment, and nanomedicine. The integration of chemotherapy with immunotherapy and the identification of key proteins have driven recent advancements. Fundamental research on immunotherapy, photodynamic therapy (PDT), and triple-negative breast cancer (TNBC) points to future trends and potential breakthroughs. This study offers a strategic overview of ICD in breast cancer, providing insights into clinical practice and guiding future research in the field.

TRAIL induces cytokine production via the NFkB2 pathway promoting neutrophil chemotaxis and neutrophil-mediated immune-suppression in triple negative breast cancer cells

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a potential cancer therapeutic that induces apoptosis in cancer cells while sparing the non-malignant cells in preclinical models. However, its efficacy in clinical trials has been limited, suggesting unknown mechanisms modulating TRAIL activity in patients. We hypothesized that TRAIL treatment elicits transcriptional changes in triple negative breast cancer (TNBC) cells that alter the immune milieu. RNAseq analysis of MDA-MB-231 cells along with validation in additional cell lines demonstrated that TRAIL induced cytokines such as CXCLs 1, 2, 3, 8,11 and IL-6, which are known to modify neutrophil function. Mechanistically, TRAIL dependent induction of the cytokines was predominantly mediated by death receptor 5, caspase-8 and the non-canonical NFKB2 pathway. These cytokines produced by TRAIL-treated TNBC cells enhanced chemotaxis of normal human donor isolated neutrophils. Using TNBC xenograft models, TRAIL induced activation of NFkB2 pathway, cytokine production and increased neutrophil recruitment into the tumors. Moreover, preincubation of neutrophils in supernatants from TRAIL-treated TNBC cells significantly impaired neutrophil function as measured by reduced respiratory burst and cytotoxic effect against TNBC cells. Transcriptomic analysis of neutrophils incubated with either TRAIL alone or supernatant of TRAIL-treated TNBC cells revealed increased expression of inflammatory cytokines, immune modulatory genes, immune checkpoint genes, and genes implicated in delayed neutrophil apoptosis. Functional studies showed that these neutrophils suppress T cell proliferation and augment Treg suppressive phenotype. Collectively, our study demonstrates a novel role of TRAIL-induced NFKB2-dependent cytokine production that promotes neutrophil chemotaxis and neutrophil-mediated immune suppression.

Identification of chromatin remodeling-related gene signature to predict the prognosis in breast cancer

Growing evidence highlights the critical role of chromatin remodeling in tumor development and progression. This study explores the relationship between chromatin remodeling-related genes (CRRGs) and breast cancer (BRCA). Public databases were used to retrieve the TCGA-BRCA and GSE20685 datasets. CRRGs were sourced from prior studies. Prognosis-associated CRRGs were identified using univariate Cox regression analysis. TCGA-BRCA BRCA samples were grouped into CRRG-related subtypes through consensus clustering analysis. Differential expression analysis was conducted in TCGA-BRCA (BRAC vs. control) and among subtypes to identify differentially expressed genes (DEGs). Candidate genes were obtained through the intersection of these DEGs. Prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Independent prognostic factors were identified, and a nomogram model was developed. Functional enrichment, immune infiltration, clinical relevance, and drug sensitivity analyses were subsequently performed. TCGA-BRCA BRCA samples were classified into two CRRG-related subtypes (clusters 1 and 2) based on prognosis-associated CRRGs. A total of 141 candidate genes were identified by intersecting 250 DEGs (cluster 1 vs. cluster 2) with 3,145 DEGs (BRCA vs. control). Five prognostic genes-LHX5, ZP2, GABRQ, APOA2, and CLCNKB-were selected, and a prognostic risk model was developed. In clinical samples, APOA2 (P = 0.0290) and GABRQ (P = 0.0132) expression were significantly up-regulated, CLCNKB (P < 0.0001) and ZP2 (P = 0.0445) expression were significantly down-regulated, while LHX5 (P = 0.1508) expression did not present a significant difference. A nomogram was created, and calibration and Receiver Operating Characteristic (ROC) curves demonstrated its superior predictive ability for BRCA. Gene Set Variation Analysis (GSVA) revealed 16 pathways, such as "mTORC1 signaling" and "E2F targets," were enriched in the high-risk group, while 9 pathways, including "estrogen response early" and "myogenesis," were enriched in the low-risk group. Additionally, significant differences in immune cell types, including CD8+ T cells and follicular helper T cells, were observed between the two risk groups. The risk score was also significantly associated with six drugs, including AZD1332 1463 and SB505124 1194. This study presents a prognostic model based on five genes (LHX5, ZP2, GABRQ, APOA2, and CLCNKB) for BRCA, offering a novel perspective on the link between CRRGs and BRCA.

Non-invasive prediction of DCE-MRI radiomics model on CCR5 in breast cancer based on a machine learning algorithm

BackgroundNon-invasive methods with universal prognostic guidance for detecting breast cancer (BC) survival biomarkers need to be further explored.ObjectiveThis study aimed to investigate C-C motif chemokine receptor type 5 (CCR5) prognosis value in BC and develop a radiomics model for noninvasive prediction of CCR5 expression in BC.MethodsA total of 840 cases with genomic information were included and divided into CCR5 high- and low-expression groups for clinical characteristic differences exploration. Bioinformatics and survival analysis including Kaplan-Meier (KM) survival analysis, Cox regression, immunoinfiltration analysis, and tumor mutation load (TMB) were performed. For radiomics model development, 98 cases with dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI) scans were used. Radiomics features extracted were using Pyradiomics and filtered by maximum-relevance minimum-redundancy (mRMR) and recursive feature elimination (REF) algorithms. Support vector machine (SVM) and logistic regression (LR) models were developed to predict CCR5 expression, with the radiomics score (Rad_score) representing the predicted probability of CCR5 expression. The models' performance was compared using the Delong test, and the model with the superior area under the curve (AUC) values was selected to analyze the correlation between CCR5 expression, Rad_score, and immune genes.ResultsThe CCR5 high-expression group exhibited better overall survival (OS) (p < 0.01). Six radiomics features were selected for model development. The AUCs of the SVM model predicting CCR5 were 0.753 and 0.748 in the training and validation sets, respectively, while the AUCs of the LR model were 0.763 and 0.762. Calibration curves and decision curve analysis (DCA) validated the models' calibration and clinical utility. The SVM_Rad_score showed a strong association with immune-related genes.ConclusionsThe DCE-MRI radiomics model presents a novel, non-invasive tool for predicting CCR5 expression in BC and provides valuable insights to inform clinical decision-making.

Targeting Triple-Negative Breast Cancer: Resistance Mechanisms and Therapeutic Advancements

BACKGROUND

Triple-negative breast cancer (TNBC) is one of the most heterogeneous and menacing forms of breast cancer, with no sustainable cure available in the current treatment landscape. Its lack of targets makes it highly unresponsive to various treatment modalities, which is why chemotherapy continues to be the primary form of treatment, despite the high rates of patients developing chemoresistance. In recent years, however, there has been significant progress in identifying and understanding the role of several aspects that might contribute to genomic instability and other hallmarks of cancer, including cellular proteins, immune targets, and epigenetic mechanisms, which are desirable as they permit reversibility easier than the often-adamant genetic changes.

METHODS

A literature review was conducted on the role of various TNBC associated biomarkers, their therapeutic applications, and their role in tumorigenesis and tumor maintenance, with a focus on linking both the driving biological mechanisms and emerging treatment options for TNBC.

CONCLUSIONS

Shifting the focus of treatment to identify crucial tumor cell subpopulations and associated biomarkers, such as local immune cell populations and cancer stem cells, could potentially solve or simplify decades' worth of problems that are associated with TNBC, bolstering early detection and the evolution of precision medicine and treatment. The techniques that can be used here are epigenetic analysis and RNA sequencing. Biomarkers, such as PD-L1, survivin, and ABC transporters, are implicated in several crucial processes that maintain tumors, such as cell proliferation, metastasis, immunosuppression, and stemness. Complex treatment options such as, immunotherapy, pathway inhibition, PARP inhibition, virotherapy, and RNA targeting have been considered for TNBC. Phytochemicals are also being considered as a treatment modality for TNBC, as a supplement to chemotherapy and radiation therapy, or as sole treatment.

A study on the impact of neoadjuvant therapy on molecular subtype conversion in breast cancer

PURPOSE

The aim of this study was to examine molecular subtype conversions in patients who received neoadjuvant therapy.

METHODS AND MATERIALS

A retrospective analysis was performed on 316 patients who underwent neoadjuvant therapy at Zhongnan Hospital of Wuhan University between March 2017 and October 2024. The study included data from patients with confirmed pathological residual disease at the primary site post-surgery, alongside complete receptor status and detailed information on the neoadjuvant treatment regimen administered before and after therapy. Univariate and multivariate logistic regression analyses were employed to identify factors influencing molecular subtype heterogeneity before and after neoadjuvant therapy.

RESULTS

Of the 316 patients who received neoadjuvant therapy and underwent repeated pathological biopsies, 84 (26.6%) achieved a pathological complete response (pCR). Among the remaining 232 patients with confirmed pathological residual disease after surgery, 85 (36.6%) exhibited conversion of molecular subtypes, with 45 cases (19.3%) leading to alterations in the treatment plan. In breast cancer patients undergoing neoadjuvant chemotherapy (NAC), particularly those with HR-positive tumors prior to NAC, those demonstrating favorable treatment responses on imaging, and those undergoing breast-conserving surgery, molecular subtype heterogeneity before and after NAC was more commonly observed.

CONCLUSION

Neoadjuvant therapy can induce molecular subtype heterogeneity in patients with invasive breast cancer. The identification of factors contributing to this heterogeneity may be associated with variations in biological markers of residual disease post-NAC, sampling discrepancies between core needle biopsy (CNB) and surgical specimens, or the selective mutagenic pressure exerted by chemotherapeutic agents.

Subsequent primary cancer risk and mortality among premenopausal breast cancer survivors

Patients with premenopausal breast cancer (preBC) usually have long-term survivorship. However, less is known about the risk pattern of subsequent primary cancer (SPC) and noncancer diseases among them. Here, this study aimed to evaluate the risk of developing SPCs and mortality among preBC survivors. In this population-based, retrospective cohort study, 5-year preBC survivors diagnosed at age 20-59 years during 1992-2014, in the 11 Surveillance, Epidemiology and End Result registries were included. Standardized incidence ratio (SIR) and standardized mortality ratio (SMR) were estimated for SPCs and mortality by cause, respectively. Among 181,947 survivors (mean age at diagnosis, 49.1 years; 65.9% White), there were 12,503 SPC cases, 4,280 SPC-related deaths, and 10,591 noncancer-related deaths. SPC risk was increased compared with the general population (SIR 1.06, [95% CI, 1.04-1.08]). The elevated risk was primarily associated with soft tissue cancer, bones/joints cancer, and acute non-lymphocytic leukemia (SIRs 2.01 [95% CI, 1.73-2.33], 1.78 [95% CI, 1.21-2.53], and 1.68 [95% CI, 1.46-1.93], respectively). Young-onset, Asian survivors, those with hormone receptor-negative BC, and initially treated with chemo-radiotherapy were at high-risk. The risk of dying from SPCs was also increased (SMR 1.07, [95% CI, 1.04-1.10]) and featured with similarly vulnerable subpopulations. Survivors of non-White ethnicity had a higher risk of dying from noncancer diseases. This study highlighted the excess risk of developing and dying from SPCs among preBC survivors, suggesting that targeted healthcare is warranted. Strategies for SPCs and noncancer comorbidity management are in great demand to achieve better long-term survivorship among preBC patients.

Current and Novel Treatment Options in Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Metastatic Breast Cancer

Metastatic breast cancer (mBC) remains an incurable disease, and most patients will experience disease progression during their treatment course. Although endocrine therapy remains the mainstay of treatment for hormone receptor-positive/human epidermal growth factor receptor 2-negative mBC, significant progress has been and continues to be made in the treatment of this BC subtype. The discovery of molecular markers, mutations in key cellular pathways, and genomic signatures have led to the development of novel and targeted agents, such as antibody-drug conjugates, oral selective estrogen receptor downregulators, and inhibitors of the PI3K/AKT/mTOR pathway. This has resulted in significant improvements in the survival and quality of life of patients. With the increasing number of treatment options for patients, appropriate drug sequencing remains a challenge. Treatment discussions should involve patient-physician shared decision making, with consideration of genomic data, previous lines of therapy, side effect profiles, and clinical trial enrollment.

Machine learning Nomogram for Predicting endometrial lesions after tamoxifen therapy in breast Cancer patients

Objective Endometrial lesions are a frequent complication following breast cancer, and current diagnostic tools have limitations. This study aims to develop a machine learning-based nomogram model for predicting the early detection of endometrial lesions in patients. The model is designed to assess risk and facilitate individualized treatment strategies for premenopausal breast cancer patients. Method A retrospective study was conducted on 224 patients who underwent diagnostic curettage post-tamoxifen (TAM) therapy between November 2012 and November 2023. These patients exhibited signs of endometrial abnormalities or symptoms such as colporrhagia. Clinical data were collected and analyzed using R software (version 4.3.2) to identify factors influencing the occurrence of endometrial lesions and evaluate their predictive values. Three machine learning methods were employed to develop a risk prediction model, and their performances were compared. The best-performing model was selected to construct a nomogram of endometrial lesions. Internal validation was conducted using the bootstrap method, and the model's accuracy and fit were assessed using the concordance index (C-index) and calibration curves. Results Independent risk factors for endometrial lesions included ultrasound characteristics, duration of TAM therapy, presence of colporrhagia, and endometrial thickness (P < 0.05). Among the machine learning methods compared, the LASSO regression integrated with a multifactorial logistic regression model demonstrated strong performance, with a concordance index (C-index) of 0.874 and effective calibration (mean absolute error of conformity: 0.014). This model achieved an accuracy of 0.853 and a precision of 0.917, with a training set AUC of 0.874 (95% CI: 0.794-0.831) and a test set AUC of 0.891 (95% CI: 0.777-1.000), closely aligning the predicted risk with the actual observed risk. Conclusion The developed prediction model is effective in evaluating endometrial lesions in premenopausal breast cancer patients. This model offers a theoretical foundation for improving clinical predictions and devising tailored treatment strategies for this patient group.

Recent Advances in Immunotherapy and Targeted Therapy of Triple Negative Breast Cancer

The truancy of representation of the estrogen, progesterone, and human epidermal growth factor receptors occurs during TNBC. TNBC is recognized for the upper reappearance and has a poorer diagnosis compared with rest breast cancer (BC) types. Presently, as such, no targeted therapy is approved for TNBC and treatment options are subjected to chemotherapy and surgery, which have high mortality rates. Hence, the current article focuses on the scenario of TNBC vital pathways and discusses the latest advances in TNBC treatment, including immune checkpoint inhibitors (ICIs), PARP suppressors, and cancer vaccines. Immunotherapy and ICIs, like PD 1 and PD L1 suppressors, displayed potential in clinical trials (CTs). These suppressors obstruct the mechanisms which allow tumor cells to evade the system thereby boosting the body's defense against TNBC. Immunotherapy, either alone or combined with chemotherapy has demonstrated patient outcomes such as increased survival rates and reduced treatment-related side effects. Additionally, targeted therapy approaches include BRCA/2 mutation poly ribose polymerase inhibitors, Vascular Endothelial Growth Factor Receptor (VEGFR) inhibitors, Epidermal growth factor receptor inhibitors, Fibroblast growth factor inhibitors, Androgen Receptor inhibitors, PIK3/AKT/mTOR pathway inhibitors, Cyclin-dependent kinase (CDK) inhibitors, Notch signaling pathway inhibitors, Signal transducer and activator of transcription 3 (STAT3) signaling pathway inhibitors, Chimeric antigen receptor T (CAR-T) cell therapy, Transforming growth factor (TGF) -β inhibitors, Epigenetic modifications (EPM), Aurora Kinase inhibitors and antibody-drug conjugates. We also highlight ongoing clinical trials and potential future directions for TNBC therapy. Despite the challenges in treating TNBC, recent developments in understanding the molecular and immune characteristics of TNBC have opened up new opportunities for targeted therapies, which hold promise for improving outcomes in this aggressive disease.

Emerging Therapies for Brain Metastases in NSCLC, Breast Cancer, and Melanoma: A Critical Review

PURPOSE OF REVIEW

Advancements in precision medicine have shifted the treatment paradigm of brain metastases (BM) from non-small cell lung cancer (NSCLC), breast cancer, and melanoma, especially through targeted therapies focused on specific molecular drivers. These novel agents have improved outcomes by overcoming challenges posed by the blood-brain barrier (BBB) and resistance mechanisms, enabling more effective treatment of BM.

RECENT FINDINGS

In NSCLC, therapies such as osimertinib have improved efficacy in treating EGFR-mutant BM, with emerging combinations such as amivantamab and lazertinib offering promising alternatives for patients resistant to frontline therapies. In HER2-positive breast cancer, significant advancements with tucatinib and trastuzumab deruxtecan (T-DXd) have transformed the treatment landscape, achieving improved survival and intracranial control in patients with BM. Similarly, in triple-negative breast cancer (TNBC), novel therapies such as sacituzumab govitecan (SG) and datopotamab deruxtecan (Dato-DXd) offer new hope for managing BM. For melanoma, the combination of immune checkpoint inhibitors such as nivolumab and ipilimumab has proven effective in enhancing survival for patients with BM, both in BRAF-mutant and wild-type cases. Developing targeted therapies penetrating the BBB has revolutionized BM treatment by targeting key drivers like EGFR, ALK, HER2, and BRAF. Despite improved survival, challenges persist, particularly for patients with resistant genetic alterations. Future research should optimise combination therapies, overcome resistance, and refine treatment sequencing. Continued emphasis on personalized, biomarker-driven approaches offers the potential to further improve outcomes, even for complex cases.

Understanding the chemistry & pharmacology of antibody-drug conjugates in triple-negative breast cancer with special reference to exatecan derivatives

In the spectrum of breast malignancies, triple-negative breast cancer is the most widely spreading subtype of breast cancer due to a low availability of therapeutic remedies. Recently, antibody-drug conjugates dramatically resolved the landscape for the treatment of triple-negative breast cancer. This review mainly focuses on the chemistry, structure, mechanism of action, and role of antibody-drug conjugates in triple-negative breast cancer. Datopotecan Deruxtecan (Dato-DXd) is a new-generation ADC showing encouraging results for TNBC. In this review, we have also emphasized TROP-2-directed Datopotamab deruxtecan ADCs to treat triple-negative breast cancer, its synthesis, mechanism of action, pharmacokinetics, pharmacodynamics, adverse events, and their ongoing clinical trials.

Cysteine protease I29 propeptide from Calotropis procera R. Br. As a potent cathepsin L inhibitor and its suppressive activity in breast cancer metastasis

Breast cancer metastasis is associated with a poor prognosis and a high rate of mortality. Cathepsin L (CTSL) is a lysosomal cysteine protease that promotes tumor metastasis by degrading the extracellular matrix. Gene set enrichment analysis revealed that CTSL expression was higher in tumorous than in non-tumorous tissues of breast cancer patients and that high-level CTSL expression correlated positively with the epithelial-mesenchymal transition. Therefore, we hypothesized that inhibiting CTSL activity in tumor cells would prevent metastasis. In this study, we characterized the inhibitory activity of SnuCalCpI15, the I29 domain of a CTSL-like cysteine protease from Calotropis procera R. Br., and revealed that the propeptide stereoselectively inhibited CTSL in a reversible slow-binding manner, with an inhibitory constant (Ki) value of 1.38 ± 0.71 nM, indicating its potency as an exogenous inhibitor in anti-cancer therapy. SnuCalCpI15 was localized intracellularly in MDA-MB-231 breast cancer cells and suppressed tumor cell migration and invasion. These results demonstrate the potential of SnuCalCpI15 as a novel agent to prevent breast cancer metastasis.

Impact of neoadjuvant chemotherapy on perioperative immune function in breast cancer patients: a propensity score-matched retrospective study

To evaluate the impact of neoadjuvant chemotherapy on perioperative immune function in breast cancer patients, focusing on CD3+, CD4+, CD8+, and natural killer (NK) cells, as well as the CD4+/CD8+ ratio. We retrospectively reviewed medical records of breast cancer patients who underwent surgery with or without neoadjuvant chemotherapy at our medical center from January 2020 to December 2022. Patients were matched 1:1 based on propensity scores. Immune cell proportions and the CD4+/CD8+ ratio were compared on preoperative day one and postoperative days one and seven. Among matched patients, immune cell proportions and the CD4+/CD8+ ratio did not significantly differ between those who received neoadjuvant chemotherapy and those who did not at any of the three time points. Similar results were observed in chemotherapy-sensitive patients compared to the entire group of patients who did not receive neoadjuvant chemotherapy. However, chemotherapy-insensitive patients had significantly lower proportions of CD4+ and NK cells, as well as a lower CD4+/CD8+ ratio, at all three time points compared to patients who did not receive neoadjuvant chemotherapy. Neoadjuvant chemotherapy may impair immune function in chemotherapy-insensitive patients, but not in those who are sensitive to the treatment.

TRAIL-induced cytokine production via NFKB2 pathway promotes neutrophil chemotaxis and immune suppression in triple negative breast cancers

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a potential cancer therapeutic that induces apoptosis in cancer cells while sparing the non-malignant cells in preclinical models. However, its efficacy in clinical trials has been limited, suggesting unknown modulatory mechanisms responsible for the lack of TRAIL activity in patients. Here, we hypothesized that TRAIL treatment elicits transcriptional changes in triple negative breast cancer (TNBC) cells that alter the immune milieu. To test this, we performed an RNAseq analysis of MDA-MB-231 cells treated with TRAIL, followed by validation in additional TNBC cell lines. TRAIL significantly induces expression of multiple cytokines such as CXCLs 1, 2, 3, 8,11 and IL-6, which are known to modify neutrophil function. Mechanistically, the induction of these cytokines was predominantly mediated by death receptor 5, caspase 8 (but not caspase 8 enzymatic activity), and the non-canonical NFKB2 pathway. The cytokines produced by the TRAIL-treated TNBC cells enhanced chemotaxis of healthy human donor isolated neutrophils. In vivo , TRAIL treated TNBC murine xenograft tumors showed activation of the NFKB2 pathway, elevated production of CXCLs and IL-6, and increased neutrophil recruitment into the tumors. Moreover, donor isolated neutrophils preincubated in supernatants from TRAIL-treated TNBC cells exhibited impaired cytotoxic effect against TNBC cells. Transcriptomic analysis of neutrophils incubated with either TRAIL alone or supernatant of TRAIL-treated TNBC cells revealed increased expression of inflammatory cytokines, immune modulatory genes, immune checkpoint genes, and genes implicated in delayed neutrophil apoptosis. Functional studies with these neutrophils confirmed their suppressive effect on T cell proliferation and an increase in Treg suppressive phenotype. Collectively, our study demonstrates a novel role of TRAIL-induced NFKB2-dependent cytokine production that promotes neutrophil chemotaxis and immune suppression.

Identifying subtypes and developing prognostic models based on N6-methyladenosine and immune microenvironment related genes in breast cancer

Breast cancer (BC) is the most prevalent cancer in women globally. The tumor microenvironment (TME), comprising epithelial tumor cells and stromal elements, is vital for breast tumor development. N6-methyladenosine (m6A) modification plays a key role in RNA metabolism, influencing its various aspects such as stability and translation. There is a notable link between m6A methylation and immune cells in the TME, although this relationship is complex and not fully deciphered. In this research, BC expression and clinicopathological data from TCGA were scrutinized to assess expression profiles, mutations, and CNVs of 31 m6A genes and immune microenvironment-related genes, examining their correlations, functions, and prognostic impacts. Lasso and Cox regression identified prognostic genes for constructing a nomogram. Single-cell analyses mapped the distribution and patterns of these genes in BC cell development. We investigated associations between gene-derived risk scores and factors like immune infiltration, TME, checkpoints, TMB, CSC indices, and drug response. As a complement to computational analyses, in vitro experiments were conducted to confirm these expression patterns. We included 31 m6A regulatory genes and discovered a correlation between these genes and the extent of immune cell infiltration. Subsequently, a 7-gene risk score was generated, encompassing HSPA2, TAP1, ULBP2, CXCL1, RBP1, STC2, and FLT3. It was observed that the low-risk group exhibited better overall survival (OS) in BC, with higher immune scores but lower tumor mutational burden (TMB) and cancer stem cell (CSC) indices, as well as lower IC50 values for commonly used drugs. To enhance clinical applicability, age and stage were incorporated into the risk score, and a more comprehensive nomogram was constructed to predict OS. This nomogram was validated and demonstrated good predictive performance, with area under the curve (AUC) values for 1-year, 3-year, and 5-year OS being 0.848, 0.807, and 0.759, respectively. Our findings highlight the profound impact of prognostic-related genes on BC immune response and prognostic outcomes, suggesting that modulation of the m6A-immune pathway could offer new avenues for personalized BC treatment and potentially improve clinical outcomes.