Screening and Identification of Key Common and Specific Genes and Their Prognostic Roles in Different Molecular Subtypes of Breast Cancer

Marine-derived EGFR inhibitors: novel compounds targeting breast cancer growth and drug resistance

Breast cancer (BC) continues to be a major health challenge globally, ranking as the fifth leading cause of cancer mortality among women, despite advancements in cancer detection and treatment. In this study, we identified four novel compounds from marine organisms that effectively target and inhibit the Epidermal Growth Factor Receptor (EGFR), crucial for BC cell growth and proliferation. These compounds not only induced early apoptosis through Caspase-3 activation but also showed significant inhibitory effects on EGFR mutations associated with drug resistance (T790M, L858R, and L858R/T790M), demonstrating high EGFR kinase selectivity. Cell Thermal Shift Assay (CETSA) experiments indicated that Tandyukisin stabilizes EGFR in a concentration-dependent manner. Furthermore, binding competition assays using surface plasmon resonance technology revealed that Tandyukisin and Trichoharzin bound to distinct sites on EGFR and that their combined use enhanced apoptosis in BC cells. This discovery may pave the way for developing new marine-derived EGFR inhibitors, offering a promising avenue for innovative cancer treatment strategies and addressing EGFR-mediated drug resistance.

GPR81-mediated reprogramming of glucose metabolism contributes to the immune landscape in breast cancer

BACKGROUND

Local tumor microenvironment (TME) plays a crucial role in immunotherapy for breast cancer (BC). Whereas, the molecular mechanism responsible for the crosstalk between BC cells and surrounding immune cells remains unclear. The present study aimed to determine the interplay between GPR81-mediated glucometabolic reprogramming of BC and the immune landscape in TME.

MATERIALS AND METHODS

Immunohistochemistry (IHC) assay was first performed to evaluate the association between GPR81 and the immune landscape. Then, several stable BC cell lines with down-regulated GPR81 expression were established to directly identify the role of GPR81 in glucometabolic reprogramming, and western blotting assay was used to detect the underlying molecular mechanism. Finally, a transwell co-culture system confirmed the crosstalk between glucometabolic regulation mediated by GPR81 in BC and induced immune attenuation.

RESULTS

IHC analysis demonstrated that the representation of infiltrating CD8⁺ T cells and FOXP3⁺ T cells were dramatically higher in BC with a triple negative (TN) subtype in comparison with that with a non-TN subtype (P < 0.001). Additionally, the ratio of infiltrating CD8⁺ to FOXP3⁺ T cells was significantly negatively associated with GPR81 expression in BC with a TN subtype (P < 0.001). Furthermore, GPR81 was found to be substantially correlated with the glycolytic capability (P < 0.001) of BC cells depending on a Hippo-YAP signaling pathway (P < 0.001). In the transwell co-culture system, GPR81-mediated reprogramming of glucose metabolism in BC significantly contributed to a decreased proportion of CD8⁺ T (P < 0.001) and an increased percentage of FOXP3⁺ T (P < 0.001) in the co-cultured lymphocytes.

CONCLUSION

Glucometabolic reprogramming through a GPR81-mediated Hippo-YAP signaling pathway was responsible for the distinct immune landscape in BC. GPR81 was a potential biomarker to stratify patients before immunotherapy to improve BC's clinical prospect.

Breast Cancer Prognostic Hub Genes Identified by Integrated Transcriptomic and Weighted Network Analysis: A Road Toward Personalized Medicine

Breast cancer (BC) is the second-most common type and among the leading causes of worldwide cancer-related deaths. There is marked person-to-person variability in susceptibility to, and phenotypic expression and prognosis of BC, a predicament that calls for personalized medicine and individually tailored therapeutics. In this study, we report new observations on prognostic hub genes and key pathways involved in BC. We used the data set GSE109169, comprising 25 pairs of BC and adjacent normal tissues. Using a high-throughput transcriptomic approach, we selected data on 293 differentially expressed genes to establish a weighted gene coexpression network. We identified three age-linked modules where the light-gray module strongly correlated with BC. Based on the gene significance and module membership features, peptidase inhibitor 15 (PI15) and KRT5 were identified as our hub genes from the light-gray module. These genes were further verified at transcriptional and translational levels across 25 pairs of BC and adjacent normal tissues. Their promoter methylation profiles were assessed based on various clinical parameters. In addition, these hub genes were used for Kaplan-Meier survival analysis, and their correlation with tumor-infiltrating immune cells was investigated. We found that PI15 and KRT5 may be potential biomarkers and potential drug targets. These findings call for future research in a larger sample size, which could inform diagnosis and clinical management of BC, thus paving the way toward personalized medicine.

Transcriptomics indicate nuclear division and cell adhesion not recapitulated in MCF7 and MCF10A compared to luminal A breast tumours

Breast cancer (BC) cell lines are useful experimental models to understand cancer biology. Yet, their relevance to modelling cancer remains unclear. To better understand the tumour-modelling efficacy of cell lines, we performed RNA-seq analyses on a combined dataset of 2D and 3D cultures of tumourigenic MCF7 and non-tumourigenic MCF10A. To our knowledge, this was the first RNA-seq dataset comprising of 2D and 3D cultures of MCF7 and MCF10A within the same experiment, which facilitates the elucidation of differences between MCF7 and MCF10A across culture types. We compared the genes and gene sets distinguishing MCF7 from MCF10A against separate RNA-seq analyses of clinical luminal A (LumA) and normal samples from the TCGA-BRCA dataset. Among the 1031 cancer-related genes distinguishing LumA from normal samples, only 5.1% and 15.7% of these genes also distinguished MCF7 from MCF10A in 2D and 3D cultures respectively, suggesting that different genes drive cancer-related differences in cell lines compared to clinical BC. Unlike LumA tumours which showed increased nuclear division-related gene expression compared to normal tissue, nuclear division-related gene expression in MCF7 was similar to MCF10A. Moreover, although LumA tumours had similar cell adhesion-related gene expression compared to normal tissues, MCF7 showed reduced cell adhesion-related gene expression compared to MCF10A. These findings suggest that MCF7 and MCF10A cell lines were limited in their ability to model cancer-related processes in clinical LumA tumours.

Radiogenomics, Breast Cancer Diagnosis and Characterization: Current Status and Future Directions

Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with -omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).

Screening of Specific and Common Pathways in Breast Cancer Cell Lines MCF-7 and MDA-MB-231 Treated with Chlorophyllides Composites

Our previous findings have shown that the chlorophyllides composites have anticancer activities to breast cancer cell lines (MCF-7 and MDA-MB-231). In the present study, microarray gene expression profiling was utilized to investigate the chlorophyllides anticancer mechanism on the breast cancer cells lines. Results showed that chlorophyllides composites induced upregulation of 43 and 56 differentially expressed genes (DEG) in MCF-7 and MDA-MB-231 cells, respectively. In both cell lines, chlorophyllides composites modulated the expression of annexin A4 (ANXA4), chemokine C-C motif receptor 1 (CCR1), stromal interaction molecule 2 (STIM2), ethanolamine kinase 1 (ETNK1) and member of RAS oncogene family (RAP2B). Further, the KEGG annotation revealed that chlorophyllides composites modulated DEGs that are associated with the endocrine system in MCF-7 cells and with the nervous system in MDA-MB-231 cells, respectively. The expression levels of 9 genes were validated by quantitative reverse transcription PCR (RT-qPCR). The expression of CCR1, STIM2, ETNK1, MAGl1 and TOP2A were upregulated in both chlorophyllides composites treated-MCF-7 and MDA-MB-231 cells. The different expression of NLRC5, SLC7A7 and PKN1 provided valuable information for future investigation and development of novel cancer therapy.

Parity and risk of developing breast cancer according to tumor subtype: A systematic review and meta-analysis

BACKGROUND

Clinical breast cancer subtypes are categorized basing on the expression of hormone receptors and overexpression of the human epidermal growth factor receptor 2 (HER2). It is still unclear whether parity impact the risk of different breast cancer subtypes.

METHODS

We searched eight mainstream databases for published epidemiologic studies that assessed the relationship between parity and risk of breast cancer subtypes up to January 12, 2021. Parity number were unified into nulliparity and ever parity. The random-effects or fixed-effect models were used to calculate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) among different subtypes. Restricted cubic spline analysis with four knots was applied to determine the relationship of parity number and risk of breast cancer subtypes.

RESULTS

We pooled sixteen case-control and four cohort studies, and performed an analysis including 7795 luminal A, 3576 luminal B, 1794 HER2-overexpressing, and 5192 triple-negative breast cancer cases among 1135131 participants. The combined ORs for ever parity versus nulliparity indicated a 34% reduction in luminal A risk (OR=0.66, 95% CI: 0.56-0.78), and a 29% reduction in luminal B risk (OR=0.71, 95% CI: 0.63-0.81), there was no significant association in HER2-overexpressing or TNBC risk. In the dose-response analysis, we observed a potentially non-linear and gradually increasing protective relationship between the number of parity and luminal breast cancer risk.

CONCLUSIONS

The effect of parity on breast cancer seems to vary among breast tumor subtypes, and it plays a protective role in luminal breast cancer.