Aberrant lipid metabolism is a well-recognized hallmark of cancer. Notably, breast cancer (BC) arises from a lipid-rich microenvironment and depends significantly on lipid metabolic reprogramming to fulfill its developmental requirements. In this review, we revisit the pivotal role of lipid metabolism in BC, underscoring its impact on the progression and tumor microenvironment. Firstly, we delineate the overall landscape of lipid metabolism in BC, highlighting its roles in tumor progression and patient prognosis. Given that lipids can also act as signaling molecules, we next describe the lipid signaling exchanges between BC cells and other cellular components in the tumor microenvironment. Additionally, we summarize the therapeutic potential of targeting lipid metabolism from the aspects of lipid metabolism processes, lipid-related transcription factors and immunotherapy in BC. Finally, we discuss the possibilities and problems associated with clinical applications of lipid‑targeted therapy in BC, and propose new research directions with advances in spatiotemporal multi-omics.

The primary chemotherapy of ovarian cancer (OC) often acquires chemoresistance. Sorcin (SRI), a soluble resistance-related calcium-binding protein, has been reported to be an oncogenic protein in cancer. However, the molecular mechanisms of SRI regulation and the role and aberrant expression of SRI in chemoresistant OC remain unclear. Here, we identified SRI as a key driver of paclitaxel (PTX)-resistance and explored its regulatory mechanism. Using transcriptome profiles, qRT-PCR, proteomics, Western blot, immunohistochemistry, and bioinformatics analyses, we found that SRI was overexpressed in PTX-resistant OC cells and the overexpression of SRI was related to the poor prognosis of patients. SRI was a key molecule required for growth, migration, and PTX-resistance in vitro and in vivo and was involved in epithelial–mesenchymal transition (EMT) and stemness. Mechanistic studies showed that miR-142-5p directly bound to the 3ʹ-UTR of SRI to suppress its expression, whereas a transcription factor zinc-finger E-box binding homeobox 1 (ZEB1) inhibited the transcription of miR-142-5p by directly binding to the E-box fragment in the miR-142 promoter region. Furthermore, ZEB1 was negatively regulated by SRI which physically interacted with Smad4 to block its translocation from the cytosol to the nucleus. Taken together, our findings unveil a novel homeostatic loop of SRI that drives the PTX-resistance and malignant progression via Smad4/ZEB1/miR-142-5p in human OC. Targeting this SRI/Smad4/ZEB1/miR-142-5p loop may reverse the PTX-resistance.

Immune checkpoint genes (ICGs) play pivotal roles in tumor immune microenvironment (TIME), and thus, targeting them represents a promising strategy for cancer immunotherapy. However, the genetic landscape of ICGs in lung adenocarcinoma (LUAD) is still unknown. Herein, we comprehensively evaluated the ICG expression profiles of 1439 LUAD samples and linked ICG expression patterns with infiltration of immune cells, clinical features, and response to immune checkpoint blockade (ICB). The ICGscore was developed to quantify ICG expression patterns of individual patient by principal component analysis algorithms. Three distinct ICG expression patterns and three ICG‐related genomic clusters were determined, which were implicated in different clinical outcomes, level of immune infiltrates, and biological process. LUAD patients were subdivided into high‐ and low‐ICGscore subgroups. Patients with higher ICGscore were characterized by favorable survival outcomes, increased immune cell infiltration, and enhanced expression of ICGs. Further analysis revealed that lower ICGscore was associated with greater tumor mutation loads and higher mutation rates of TTN, KEAP1, and ZFHX4. High ICGscore has the potential to be a robust indicator in clinical benefit of immunotherapy. Taken together, unraveling the ICG expression patterns will advance our understanding of heterogeneity of TIME and guides more effective immunotherapeutic strategies in LUAD.

Objective: Triple-Negative Breast Cancer (TNBC) is known for its aggressiveness and treatment challenges due to the absence of ER, PR, and HER2 receptors. Our work emphasizes the prognostic value of LCP1 (Lymphocyte cytosolic protein 1), which plays a crucial role in cell processes and immune cell activity, to predict outcomes and guide treatments in TNBC. Methods: We explored LCP1 as a potential biomarker in TNBC and investigated the mRNA and protein expression levels of LCP1. We investigated different databases, including GTEX, TCGA, GEO, cBioPortal and Kaplan-Meier Plotter. Immunohistochemistry on TNBC and benign tumor samples was performed to examine LCP1's relationship with patient clinical characteristics and macrophage markers. We also assessed survival rates, immune cell infiltration, and drug sensitivity related to LCP1 using various bioinformatics tools. Results: The results indicated that LCP1 expression was higher in TNBC tissues compared to adjacent normal tissues. However, high expression of LCP1 was significantly associated with favorable survival outcomes in patients with TNBC. Enrichment analysis revealed that genes co-expressed with LCP1 were significantly enriched in various immune processes. LCP1 showed a positive correlation with the infiltration of resting dendritic cells, M1 macrophages, and memory CD4 T cells, and a negative correlation with M2 macrophages. Further analysis suggested a link between high levels of LCP1 and increased survival outcomes in cancer patients receiving immunotherapy. Conclusion: LCP1 may serve as a potential diagnostic and prognostic biomarker for TNBC, which was closely associated with immune cell infiltration, particularly M1 and M2 macrophages. Our findings may provide valuable insights into immunotherapeutic strategies for TNBC patients.

Recent breakthroughs in immune checkpoint inhibitors (ICIs) have shown promise in triple-negative breast cancer (TNBC). Due to the intrinsic heterogeneity among TNBC, clinical response to ICIs varies greatly among individuals. Thus, discovering rational biomarkers to select susceptible patients for ICIs treatment is warranted. A total of 422 TNBC patients derived from The Cancer Genome Atlas (TCGA) database and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were included in this study. High immunogenic gene modules were identified using weighted gene co-expression network analysis (WGCNA). Immune-related genes (IRGs) expression patterns were generated by consensus clustering. We developed a three-gene signature named immune-related gene panel (IRGP) by Cox regression method. Afterward, the associations of IRGP with survival outcomes, infiltration of immune cells, drug sensitivity, and the response to ICIs therapy were further explored. We found five high immunogenic gene modules. Two distinct IRGclusters and IRG-related genomic clusters were identified. The IRGP was constructed based on TAPBPL, FBP1, and GPRC5C genes. TNBC patients were then subdivided into high- and low-IRGriskscore subgroups. TNBC patients with low IRGriskscore had a better survival outcome, higher infiltration of immune cells, lower TP53 mutation rate, and more benefit from ICIs treatment than high IRGriskscore patients. These findings offer novel insights into molecular subtype of TNBC and provided potential indicators for guiding ICIs treatment.

SRY-box transcription factor 11 (SOX11), as a member of the SOX family, is a transcription factor involved in the regulation of specific biological processes and has recently been found to be a prognostic marker for certain cancers. However, the roles of SOX11 in cancer remain controversial. Our study aimed to explore the various aspects of SOX11 in pan-cancer. The expression of SOX11 was investigated by the Genotype Tissue-Expression (GTEX) dataset and the Cancer Genome Atlas (TCGA) database. The protein level of SOX11 in tumor tissues and tumor-adjacent tissues was verified by human pan-cancer tissue microarray. Additionally, we used TCGA pan-cancer data to analyze the correlations among SOX11 expression and survival outcomes, clinical features, stemness, microsatellite instability (MSI), tumor mutation burden (TMB), mismatch repair (MMR) related genes and the tumor immune microenvironment. Furthermore, the cBioPortal database was applied to investigate the gene alterations of SOX11. The main biological processes of SOX11 in cancers were analyzed by Gene Set Enrichment Analysis (GSEA). As a result, aberrant expression of SOX11 has been implicated in 27 kinds of cancer types. Aberrant SOX11 expression was closely associated with survival outcomes, stage, tumor recurrence, MSI, TMB and MMR-related genes. In addition, the most frequent alteration of the SOX11 genome was mutation. Our study also showed the correlations of SOX11 with the level of immune infiltration in various cancers. In summary, our findings underline the multifaceted role and prognostic value of SOX11 in pan-cancer.