Zhigang Zhuang

Background: Improving the response rate of single-agent immune checkpoint blockade (ICB) urgently requires the discovery of new therapeutic targets for combinatorial regimens. Analyses of tumor microenvironment (TME)-associated biomarkers have verified that KIAA1467 drives the formation of an immune-excluded, non-inflamed TME in breast cancer (BRCA). This study systematically explores the expression pattern, prognostic value, immune regulatory function, biological effects, and drug resistance relevance of FAM234B (also known as KIAA1467) in BRCA. Methods: We performed pan-cancer survival analysis using The Cancer Genome Atlas (TCGA) datasets. Multi-omics bioinformatics analyses were conducted to evaluate KIAA1467 expression across malignancies. Single-cell RNA sequencing (scRNA-seq) data from GSE176078 was utilized to localize KIAA1467 expression at the cellular level. Immunohistochemistry and western blot assays validated KIAA1467 expression in BRCA clinical specimens. Correlation analyses were implemented to assess relationships between KIAA1467 expression, clinicopathological features, immune modulators, tumor-infiltrating immune cells, and p53 mutation status. Functional enrichment analysis uncovered relevant signaling pathways. Bioinformatic half maximal inhibitory concentration (IC50) prediction and in vitro cellular experiments were applied to evaluate associations between KIAA1467 and chemotherapeutic drug sensitivity. Results: TCGA pan-cancer survival analysis demonstrated that elevated KIAA1467 expression significantly predicted shortened overall survival in BRCA and multiple other tumor types. KIAA1467 displayed distinct expression patterns across cancers, with prominent upregulation in BRCA. scRNA-seq confirmed enriched KIAA1467 expression within BRCA cells, and its upregulation in BRCA tissues was further verified by immunohistochemistry and western blot. High KIAA1467 expression was positively correlated with advanced tumor grade and lymphatic metastasis. KIAA1467 showed negative correlations with most immune modulators and core immune checkpoint molecules, as well as tumor-infiltrating immune cells in the TME, implying its potential function in tumor immune evasion. Low KIAA1467 expression was tightly linked to p53 mutations. Enrichment analysis indicated participation of KIAA1467 in epithelial-mesenchymal transition, apoptosis and cell cycle arrest. Furthermore, high KIAA1467 expression corresponded to higher estimated IC50 values of cisplatin, gefitinib, paclitaxel and gemcitabine, consistent with reduced chemosensitivity observed in vitro. Conclusions: This study reveals the multifaceted oncogenic role of KIAA1467 in BRCA. KIAA1467 participates in remodeling an immunosuppressive TME, correlates with malignant progression and chemoresistance, and may serve as a promising candidate target to optimize ICB-based combination therapy for BRCA. These findings offer new perspectives for the clinical treatment and comprehensive management of BRCA.

Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis and limited treatment options. Synthetic lethality (SL) represents a significant therapeutic strategy that selectively kills cancer cells without affecting normal cells by targeting the synergistic interaction of two genes. The SL strategy offers new avenues for targeted therapy in TNBC. Although challenges remain—such as drug resistance and biomarker selection—advancing research in SL activity holds promise for delivering clinical benefits to patients. Methods: Multi-omics data, including single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), and bulk RNA sequencing (bulkRNA-seq), were utilized to characterize TNBC heterogeneity and identify genes driving SL activity. Additionally, CytoTRACE analysis assessed tumor differentiation potential in high SL (HSL) activity cell subpopulations, Slingshot reconstructed pseudo-temporal trajectories, and CellChat constructed intercellular communication networks to evaluate interactions among TNBC microenvironment cell subpopulations. Combining high-dimensional weighted gene co-expression network analysis (hdWGCNA) with machine learning, key regulatory genes associated with the HSL cell phenotype were identified. Finally, a benchmarking framework was employed to select the most predictive algorithmic model, with feature contributions evaluated via SHapley Additive Explanations (SHAP) analysis. The identified genes were analyzed in vivo and in vitro through molecular biology experiments and animal experiments. Results: A novel HSL subtype of TNBC malignant cells has been identified, exhibiting enhanced stem cell-like properties, stronger intercellular communication capabilities, and involvement in more tumor-associated signaling pathways. Ten characteristic genes identified through five machine learning (PGP, KIF22, CCNB1, RPA3, BCL2L12, SMC2, MKI67, PBK, CDK1, and MIS18A) are significantly upregulated in TNBC malignant cells, and their high expression correlates with poor prognosis in TNBC patients. Benchmarking validated the superior performance of the random forest algorithm. Finally, through experimental verification, it was concluded that KIF22 and KRAS are synthetic lethal pairs for TNBC. Conclusion: In conclusion, this study systematically characterized the heterogeneity of TNBC and explored the association between SL activity and disease progression through a comprehensive analysis of the interactions between SL pairs and malignant TNBC cells. Our findings contribute to a deeper understanding of the molecular mechanisms underlying TNBC initiation and development. Based on bioinformatics analyses, we experimentally validated KIF22 and KRAS as a synthetic lethal gene pair in TNBC. Functional experiments demonstrated that the knockdown of KIF22 in KRAS-mutated TNBC cells or the knockdown of KRAS in TNBC cells with low expression of KIF22 gene significantly inhibited cell proliferation. Given the high prevalence of KRAS mutations in TNBC, KIF22 represents a promising therapeutic target for synthetic lethal intervention. Furthermore, in vivo xenograft models confirmed that concurrent knockdown of murine KIF22 and KRAS effectively inhibited tumor progression. Collectively, these results establish KIF22 and KRAS as a TNBC-specific synthetic lethal pair with strong potential for guiding future SL-based drug discovery efforts.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with poor prognosis and limited therapeutic options. DNA damage-based radiotherapy plays a significant role in the treatment of TNBC. However, radioresistance continues to pose a significant challenge, often resulting in the unsuccessful outcome of radiation therapy for patients with TNBC. Type I gamma phosphatidylinositol phosphate kinase (PIPKIγ), a key enzyme in phosphoinositide metabolism, is associated with poor prognostic outcomes in TNBC. Here, we discovered that PIPKIγ overexpression significantly boosts nonhomologous end joining (NHEJ), a principal mechanism for repairing DNA double-strand breaks (DSBs). This enhancement of NHEJ confers increased radioresistance in TNBC. At the molecular level, PIPKIγ directly interacts with LIG4, a crucial NHEJ component, and strengthens its interaction with XRCC4, a key regulator of LIG4 nuclear translocation. This facilitates LIG4’s nuclear translocation, improving DNA repair efficiency and genomic stability in TNBC cells. Furthermore, elevated PIPKIγ levels enhance radioresistance in TNBC cells and tumors in xenograft models, whereas depleting PIPKIγ has the opposite effects. These insights reveal a new mechanism by which PIPKIγ promotes radioresistance through the facilitation of DSBs repair in TNBC. Collectively, our findings suggest that the PIPKIγ-LIG4 interaction represents a potential therapeutic target for improving radiotherapy efficacy in TNBC patients.

Background: Recently, interleukin 17 (IL-17) has been found to play a critical role in the development of breast cancer. However, its prognostic significance in invasive breast cancer (IBC) remains unclear. This study aims to determine the role of IL-17-related signatures in IBC to identify novel therapeutic options. Methods: IBC data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used to identify IL-17-related prognostic genes. A predictive model was developed using TCGA data and validated using METABRIC data. The relationship between IL-17 scores and immune landscape, chemotherapy drug sensitivity [half maximal inhibitory concentration (IC50)], and immune checkpoint gene expression was analyzed. The quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate key gene expression in breast tumor and normal tissue samples. Results: The predictive model identified core IL-17-related prognostic genes and successfully estimated the prognosis of IBC patients. The model's validity was confirmed using METABRIC data. Patients with high IL-17 scores had worse overall survival (OS) compared to those with low IL-17 scores. Low IL-17 scores were associated with higher immune checkpoint gene expression and predicted enhanced responses to cytotoxic T-lymphocyte-associated protein 4 (CTLA4) and programmed cell death protein 1 (PD-1) therapies. Patients with low IL-17 scores exhibited a higher abundance of immune microenvironment components. Furthermore, qRT-PCR confirmed the lower expression of OR51E1, NDRG2, RGS2, and TSPAN7 in breast tumors compared to normal tissue. Conclusions: IL-17-related signatures are promising biomarkers for predicting the prognosis of IBC patients. These findings suggest that IL-17-related markers could be used to guide individualized therapeutic strategies, potentially improving outcomes for IBC patients.

As a leading prevalent malignancy, breast cancer remains a significant worldwide health issue. Recent research indicates that neutrophils play a crucial role in breast cancer development. The prognostic significance of neutrophil-related genes (NRGs) or the immune landscape of the neutrophil-related signature in invasive breast cancer (IBC) is, nevertheless, unknown. To uncover innovative therapy alternatives, the significance of the neutrophil-related signatures in IBC was evaluated here. Briefly, a prediction model based on neutrophil-related core prognostic genes and The Cancer Genome Atlas data was created (TCGA). The model may assess IBC patients' prognosis. The IBC data from the Gene Expression Omnibus (GEO) confirmed the prognostic accuracy of the model. The overall survival (OS) of patients was worse in the group with a high NRGs score compared to the group with a low NRGs score. In addition, patients with low NRGs scores were considerably more sensitive to vinorelbine, cyclophosphamide, epirubicin, gemcitabine, paclitaxel, 5-fluorouracil, docetaxel, and cisplatin. Patients with low NRGs scores responded better to CTLA-4 and PD-1 treatments. Additionally, the immune microenvironment components were more abundant in patients with low NRGs scores. Moreover, qRT-PCR results confirmed that LEF1 had a higher expression level in tumor samples compared to normal samples, whereas NRG1 and STX11 exhibited lower expression levels in tumor samples than in normal samples. These results suggest that NRGs might be utilized as biomarkers to predict the prognosis of individuals with IBC, thereby paving the way for the creation of customized therapies for IBC.

The global prevalence of breast cancer necessitates the development of innovative prognostic markers and therapeutic strategies. This study investigated the prognostic implications of anoikis-related long non-coding RNAs (ARLs) in invasive breast cancer (IBC), which is an area that has not been extensively explored. By integrating the RNA sequence transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database and employing advanced regression analyses, we devised a novel prognostic model based on ARL scores. ARL scores correlated with diverse clinicopathological parameters, cellular pathways, distinct mutation patterns, and immune responses, thereby affecting both immune cell infiltration and anticipated responses to chemotherapy and immunotherapy. Additionally, the overexpression of a specific lncRNA, AL133467.1, significantly impeded the proliferation and migration, as well as possibly the anoikis resistance of breast cancer cells. These findings highlight the potential of the ARL signature as a robust prognostic tool and a promising basis for personalized IBC treatment strategies.

Original Article TPD52 is a prognostic biomarker and potential therapeutic target for ER⁺/PR⁺/HER2⁺ breast cancer Xiaolin Cheng, Zhengdong Li, Xiaoqing Jia, Zhiyuan Fan, Qizhi He, Zhigang Zhuang

Background: To summarize the clinicopathological characteristics, prognosis, and management of breast adenosquamous carcinoma (ASC).Methods: A population-based study was performed using retrospectively extracted data from the Surveillance, Epidemiology, and End Results database for breast cancer patients with histological diagnoses of ASC, infiltrating duct carcinoma (IDC) and squamous cell carcinoma (SCC) from 2004 to 2016.Results: ASC presented similar tumor size but low histological grade and less lymph node metastasis compared to IDC. ASC expressed less positive rate of hormone receptors and barely HER2, which was similar with SCC. ASC patients underwent the similar surgical and systematic treatment as IDC, only with less radiotherapy. Median follow-up data of 78 months showed that the prognosis of IDC patients was better than that of ASC patients (allp < 0.05 for BCSM and OS). ASC was not an independent prognosis factor of breast cancer. After propensity score matching (PSM), no significant difference in BCSM nor OS was observed between ASC and IDC groups. In HR-negative patients, the prognosis of ASC was similar with that of IDC, and both were superior to SCC. In HR-positive patients, the 5-year survival rate of ASC was 63.5%, which was far less than that in ASC of HR-negative (81.0%). Multivariate analysis showed that older age (age > 60) and advanced AJCC-stage were independent factors of poor prognosis in ASC, breast-conserving surgery was also ideally suited for ASC.Conclusions: ASC has unique clinicopathological characteristics and prognosis. It is imperative to focus on a more precise and personalized treatment management of ASC patients.

Background: The present study is aimed at summarizing the clinicopathological characteristics, prognosis, and management of breast adenosquamous carcinoma (ASC). Methods: A population-based study was performed using retrospectively extracted data from the Surveillance, Epidemiology and End Results database for breast cancer patients with histological diagnoses of ASC, infiltrating duct carcinoma (IDC) and squamous cell carcinoma (SCC) from 2004 to 2016. End-points were overall survival (OS) and breast cancer-specific mortality (BCSM). Propensity Score Matching (PSM) was employed to minimize selection bias of baseline characteristics. Univariable and multivariable analyses were used for identifying valuable prognostic factors. Results: ASC presented similar tumor size but low histological grade and less lymph node metastasis compared to IDC. ASC expressed less positive rate of hormone receptors and barely HER2, which was similar with SCC (estrogen receptor (ER): ASC 27.74% and SCC 21.53%, progesterone receptor (PR): ASC 18.06% and SCC 12.85%, HER2: ASC 4.44% and SCC 7.53%). ASC patients underwent the same treatment as IDC (chemotherapy 36.99% vs. 41.86%, BCS 50.58% vs 52.83%, P >0.05), only with less radiotherapy (39.88% vs. 48.34%, PP Cox proportional hazards models, ASC was no longer an independent poor prognosis factor. In matched groups, no significant difference in BCSM nor OS was observed between ASC and IDC groups. In HR-negative patients, the prognosis of ASC was similar with that of IDC, and both were superior to SCC. In HR-positive patients, the five-year survival rate of ASC was only about 60%, which was far less than that in ASC of HR-negative, the poor prognosis of ASC was closer to that of SCC. Multivariate analysis showed that older age (age≥60) and advanced AJCC stage (III and IV) were independent factors of poor prognosis in ASC, breast-conserving surgery was also ideally suited for ASC. Conclusions: ASC has unique clinicopathological characteristics and prognosis. To improve the clinical and biological understanding of ASC can make breast cancer patients get more individualized treatment.