Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous subtype of breast cancer. miRNAs play an essential role in TNBC pathogenesis and prognosis. Obesity is linked with an increased risk for several cancers, including breast cancer. Obesity is also related to the dysregulation of miRNA expression in adipose tissues. However, there is limited knowledge about race- and obesity-specific differential miRNA expression in TNBC. We performed miRNA sequencing of 48 samples (24 tumor and 24 adjacent non-tumor tissues) and RNA sequencing of 24 tumors samples from Black (AA) and White (EA) TNBC patients with or without obesity. We identified 55 miRNAs exclusively associated with tumors in obese EA patients and 33 miRNAs in obese AA patients, each capable of distinguishing tumor tissues from obese from lean individuals within their respective racial groups. In EA, we detected 41 significant miRNA–mRNA correlations. Notably, miR-181b-5p and miR-877-5p acted as negative regulators of tumor-suppressor genes (e.g., HEY2, MCL2, HAND2), while miR-204-5p and miR-143-3p appeared to indirectly target oncogenes (e.g., RAB10, DR1, PTBP3, NCBP1). Among AA patients, we found 28 significant miRNA–mRNA interactions. miR-195-5p, miR-130a-3p, miR-130a-5p, miR-424-5p, miR-148a-3p, miR-374-5p, and miR-30a-5p each potentially downregulated two or more genes (e.g., CLCN4, PLCB1, CDC25B, AEBP2, ERBB4). Pathway enrichment analysis highlighted KRAS, ESR1, ESR2, RAB10, TNRC6C, and NCAN as the most commonly differentially expressed in EA, whereas ERBB4, PLCB1, and SERPINE1 were most frequently in AA. These findings highlight the importance of considering race-specific miRNA–mRNA signatures in understanding TNBC in the context of obesity, offering insights into biomarker-driven patient stratification for targeted therapeutic strategies.

Intrinsically disordered proteins (IDPs) lack stable three-dimensional structures, yet play vital roles in key biological processes, including signaling, transcription regulation, and molecular scaffolding. Their structural flexibility presents significant challenges for experimental characterization and contributes to diseases such as cancer and neurodegenerative disorders. Accurate computational prediction of IDPs is important for advancing research and drug discovery, structural biology, and protein engineering. In this study, we introduce ESMDisPred, a novel structure-aware disorder predictor that builds on the representational power of Evolutionary Scale Modeling-2 (ESM2) protein language models. ESMDisPred integrates sequence embeddings with structural information from the Protein Data Bank (PDB) to deliver state-of-the-art prediction accuracy. Model performance is further enhanced through feature engineering strategies, including terminal residue encoding, statistical summarization, and sliding-window analysis. To capture both local sequence motifs and long-range dependencies, we designed a hybrid CNN-Transformer architecture that balances convolutional efficiency with the representational power of self-attention. On CAID3 benchmarks, our latest model achieves ROC-AUC 0.895, AP 0.778, and a max F1 of 0.759, outperforming recent methods. Our results highlight the importance of integrating protein language model embeddings with explicit structural information for improved disorder prediction.

The mammary gland is a heterogeneous organ that modulates ductal morphogenesis and alveolar differentiation. Obesity is a significant risk factor for several cancers, including postmenopausal breast cancer. We and others have described an association between obesity and increased breast cancer growth. However, the effects of obesity on the mammary fat pad microenvironment (MFPME) remain understudied. Here, we investigated the effect of the Western Diet (WD) on immunocompetent female mice and on their MFPME. Our data suggest that the WD increased body, liver, and perigonadal white adipose tissue (pWAT) weight, as well as myeloid cell infiltration into these tissues. Interestingly, we did not find any significant change in CD4⁺ and CD8⁺ T cells in the liver, blood, and pWAT. NanoString data demonstrates that various cellular processes, including the complement system, innate immune system, phagocytic activity, immune metabolism, and NOD-like receptor (NLR) signaling, were upregulated in the MFPME of obese mice. RNA-Seq data suggest that WD significantly modulated MFPME physiology through regulation of gene expression, cellular processes, and signaling pathways. Further investigation is necessary to determine how WD-mediated changes in MFPME modulate breast cancer biology.