SLC16A3 (Solute Carrier Family 16 Member 3)

Clinically, multiplex immunofluorescence of patient tumors demonstrated strong co-expression of EGFR, LC3, and SLC16A3, which correlated with poor disease-free survival. Our study reveals a previously unrecognized EGF-secretory autophagy axis that orchestrates metabolic remodeling in TNBC and highlights the therapeutic potential of targeting the secretory autophagy- SLC16A3-lactate pathway to restrain metastasis.

This study reveals that the synergistic expression pattern of PSMB5, PSMB7 and SLC16A3 is closely associated with lung adenocarcinoma metastasis and poor prognosis, confirming their potential value as prognostic biomarkers and therapeutic targets. The CT radiomics model offers a noninvasive tool for molecular phenotyping, aiding in preoperative precision assessment and advancing noninvasive clinical decision-making for LUAD.

By applying machine learning methods to analyze sequencing data, we identified core lactylation-related genes in UC and developed a diagnostic model with high predictive performance. Furthermore, based on scRNA-seq data, we investigated lactylation modifications across seven types of immune cells in UC patients, providing valuable insights into the interplay between lactylation and immune cells in UC.

In ATCs, ACSS2 was the only upregulated gene, suggesting further tumor adaptation to the metabolic stress of rapidly growing cancers. In conclusion, our study demonstrates a dysregulated expression pattern of multiple genes involved in acetate metabolism, which could be exploited for the development of new therapeutic strategies.

Additionally, SLC16A3 downregulation reduced cisplatin sensitivity in LUAD cells. Our study highlights the clinical translational potential of a five-gene zinc homeostasis network signature in predicting prognosis and guiding personalized therapeutic strategies for LUAD.

By targeting these transporters with small molecule inhibitors, it may be possible to disrupt essential metabolic pathways in cancer cells, thereby enhancing treatment efficacy and improving patient outcomes. This research establishes a foundation for the development of SLC-targeted therapies in precision oncology, aiming to improve survival rates for patients with OV.

Silencing SLC16A3 significantly reduced cell survival and promoted caspase-3-dependent apoptosis, which was further enhanced by ionizing radiation or cisplatin treatment. Phospho-kinase array profiling demonstrated activation of the p38-MAPK pathway upon SLC16A3 inhibition, and pharmacological blockade of p38 (SB203580) attenuated apoptosis, confirming that SLC16A3 knockdown-induced apoptosis is p38-dependent. Collectively, these findings uncover a previously unrecognized SLC16A3-p38-caspase signaling axis that promotes therapeutic resistance and highlight SLC16A3 as a promising therapeutic target for overcoming radioresistance and chemoresistance in lung cancer.

SLC16A3 in LUAD modulates the glycolysis pathway to facilitate M2 polarization of macrophages.

Key lactylation-related genes, including LDHA and SLC16A3, were associated with immune exhaustion and cisplatin resistance...Perturbation sensitivity and repurposing analyses revealed novel therapeutic vulnerabilities. This study establishes a precision oncology framework that integrates lactylation biology with AI-driven analytics to uncover druggable targets, enhance patient stratification, and inform the design of multi-target therapies in ovarian cancer.

Thus, BMI1 expression leads to increases in key features of early-stage, carcinogen-induced tumorigenesis, including metabolic reprogramming. Consequently, limiting BMI1 could be a potential target for cancer prevention approaches that merits further consideration and additional functional studies.

Alone or combined with inhibition of mitochondrial respiration by metformin and phenformin, the MCT4 inhibitor syrosingopine significantly inhibits lactate efflux, induces cell viability reduction in four different RCC cell lines and patient-derived 2D/3D models, and alterations in cellular metabolism and mitochondrial respiration. Six patient-derived RCC air-liquid interface models, mimicking the complex RCC architecture, corroborate these data. Beyond potential prediction of patient outcome using MCT4 expression and DNA methylation at specific CpG sites, drug targeting of MCT4 and inhibiting mitochondrial respiration synergistically is a novel treatment strategy for metastatic ccRCC.

Multivariate Cox analysis confirmed that the risk signature provided independent predictive information from clinical variables. In conclusion, the risk signature accurately identifies breast cancer patients at risk of lung metastasis, enabling clinicians to better assess risk and tailor treatment strategies effectively.