Serum amyloid A1: Innocent bystander or active participant in cell migration in triple-negative breast cancer?

Inflammation and Tumor Progression: The Differential Impact of SAA in Breast Cancer Models

Background: Previous research has shown that the Serum Amyloid A (SAA) protein family is intricately involved in inflammatory signaling and various disease pathologies. We have previously demonstrated that SAA is associated with increased colitis disease severity and the promotion of tumorigenesis. However, the specific role of SAA proteins in breast cancer pathology remains unclear. Therefore, we investigated the role of systemic SAA1 and SAA2 (SAA1/2) in a triple-negative breast cancer mouse model. Methods: Syngeneic breast tumors were established in wild-type mice, and mice lacking the SAA1/2 (SAADKO). Subsequently, tumor volume was monitored, species survival determined, the inflammatory profiles of mice assessed with a multiplex assay, and tumor molecular biology and histology characterized with Western blotting and H&E histological staining. Results: WT tumor-bearing mice had increased levels of plasma SAA compared to wild-type control mice, while SAADKO control and tumor-bearing mice presented with lower levels of SAA in their plasma. SAADKO tumor-bearing mice also displayed significantly lower concentrations of systemic inflammatory markers. Tumors from SAADKO mice overall had lower levels of SAA compared to tumors from wild-type mice, decreased apoptosis and inflammasome signaling, and little to no tumor necrosis. Conclusions: We demonstrated that systemic SAA1/2 stimulates the activation of the NLRP3 inflammasome in breast tumors, leading to the production of pro-inflammatory cytokines. This, in turn, promoted apoptosis and tumor necrosis but did not significantly impact tumor growth or histological grading.

Bioinformatic analysis and experimental validation of six cuproptosis-associated genes as a prognostic signature of breast cancer

Background

Breast carcinoma (BRCA) is a life-threatening malignancy in women and shows a poor prognosis. Cuproptosis is a novel mode of cell death but its relationship with BRCA is unclear. This study attempted to develop a cuproptosis-relevant prognostic gene signature for BRCA.

Methods

Cuproptosis-relevant subtypes of BRCA were obtained by consensus clustering. Differential expression analysis was implemented using the 'limma' package. Univariate Cox and multivariate Cox analyses were performed to determine a cuproptosis-relevant prognostic gene signature. The signature was constructed and validated in distinct datasets. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were also conducted using the prognostic signature to uncover the underlying molecular mechanisms. ESTIMATE and CIBERSORT algorithms were applied to probe the linkage between the gene signature and tumor microenvironment (TME). Immunotherapy responsiveness was assessed using the Tumor Immune Dysfunction and Exclusion (TIDE) web tool. Real-time quantitative PCR (RT-qPCR) was performed to detect the expressions of cuproptosis-relevant prognostic genes in breast cancer cell lines.

Results

Thirty-eight cuproptosis-associated differentially expressed genes (DEGs) in BRCA were mined by consensus clustering and differential expression analysis. Based on univariate Cox and multivariate Cox analyses, six cuproptosis-relevant prognostic genes, namely SAA1, KRT17, VAV3, IGHG1, TFF1, and CLEC3A, were mined to establish a corresponding signature. The signature was validated using external validation sets. GSVA and GSEA showed that multiple cell cycle-linked and immune-related pathways along with biological processes were associated with the signature. The results ESTIMATE and CIBERSORT analyses revealed significantly different TMEs between the two Cusig score subgroups. Finally, RT-qPCR analysis of cell lines further confirmed the expressional trends of SAA1, KRT17, IGHG1, and CLEC3A.

Conclusion

Taken together, we constructed a signature for projecting the overall survival of BRCA patients and our findings authenticated the cuproptosis-relevant prognostic genes, which are expected to provide a basis for developing prognostic molecular biomarkers and an in-depth understanding of the relationship between cuproptosis and BRCA.

SAA1-dependent reprogramming of adipocytes by tumor cells is associated with triple negative breast cancer aggressiveness

Triple negative breast cancers (TNBC) are characterized by a poor prognosis and a lack of targeted treatments. Their progression depends on tumor cell intrinsic factors, the tumor microenvironment and host characteristics. Although adipocytes, the primary stromal cells of the breast, have been determined to be plastic in physiology and cancer, the tumor-derived molecular mediators of tumor-adipocyte crosstalk have not been identified yet. In this study, we report that the crosstalk between TNBC cells and adipocytes in vitro beyond adipocyte dedifferentiation, induces a unique transcriptional profile that is characterized by inflammation and pathways that are related to interaction with the tumor microenvironment. Accordingly, increased cancer stem-like features and recruitment of pro-tumorigenic immune cells are induced by this crosstalk through CXCL5 and IL-8 production. We identified serum amyloid A1 (SAA1) as a regulator of the adipocyte reprogramming through CD36 and P2XR7 signaling. In human TNBC, SAA1 expression was associated with cancer-associated adipocyte infiltration, inflammation, stimulated lipolysis, stem-like properties, and a distinct tumor immune microenvironment. Our findings constitute evidence that the interaction between tumor cells and adipocytes through the release of SAA1 is relevant to the aggressiveness of TNBC.

A Novel Five-Gene Signature Related to Clinical Outcome and Immune Microenvironment in Breast Cancer

Breast cancer (BC) is the most frequent cancer in women and the main cause of cancer-related deaths in the globe, according to the World Health Organization. The need for biomarkers that can help predict survival or guide treatment decisions in BC patients is critical in order to provide each patient with an individualized treatment plan due to the wide range of prognoses and therapeutic responses. A reliable prognostic model is essential for determining the best course of treatment for patients. Patients’ clinical and pathological data, as well as their mRNA expression levels at level 3, were gleaned from the TCGA databases. Differentially expressed genes (DEGs) between BC and non-tumor specimens were identified. Tumor immunity analyses have been utilized in order to decipher molecular pathways and their relationship to the immune system. The expressions of KIF4A in BC cells were determined by RT-PCR. To evaluate the involvement of KIF4A in BC cell proliferation, CCK-8 tests were used. In this study, utilizing FC > 4 and p < 0.05, we identified 140 upregulated genes and 513 down-regulated genes. A five-gene signature comprising SFRP1, SAA1, RBP4, KIF4A and COL11A1 was developed for the prediction of overall survivals of BC. Overall survival was distinctly worse for patients in the high-risk group than those in the low-risk group. Cancerous and aggressiveness-related pathways and decreased B cell, T cell CD4⁺, T cell CD8⁺, Neutrophil and Myeloid dendritic cells levels were seen in the high-risk group. In addition, we found that KIF4A was highly expressed in BC and its silence resulted in the suppression of the proliferation of BC cells. Taken together, as a possible prognostic factor for BC, the five-gene profile created and verified in this investigation could guide the immunotherapy selection.