Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, with heme metabolism playing a critical role in tumor progression and treatment resistance. This study investigates the clinical implications of heme metabolism in LUAD, focusing on its link to ferroptosis and drug sensitivity. Using multi-omics data from TCGA-LUAD, GEO databases, and a single-cell RNA-seq cohort, we identified two molecular subtypes based on heme metabolism-related genes. We further developed a prognostic panel, termed the heme metabolism risk score (HMRS), using LASSO and multivariate Cox regression analyses. The HMRS panel effectively stratified patients into high- and low-risk groups, with high-risk patients showing enhanced tumor proliferation, suppressed ferroptosis, and resistance to chemotherapy. Single-cell analysis revealed elevated heme metabolism risk in epithelial cells correlated with tumor progression. Drug sensitivity predictions were validated in platinum-based chemotherapy cohorts, confirming HMRS as a robust prognostic tool. ABCC2 was identified as a key regulator of ferroptosis and cisplatin resistance, with in vitro experiments demonstrating that ABCC2 knockdown enhanced cisplatin-induced ferroptosis. These findings highlight HMRS as a critical tool for patient stratification and ABCC2 as a promising therapeutic target to overcome cisplatin resistance.

Galectin-3 (Gal-3) plays a multifaceted role in the development and progression of pancreatic adenocarcinoma (PAAD), which is associated with a poor prognosis. Its interaction with tumor microenvironment cells has been reported. However, the Gal-3-mediated tumor–stromal interaction and induced energy metabolism associated with drug resistance remain unknown. Our previous study has reported that Gal-3 secretion from tumor cells and inflammatory cytokine dependency are therapeutic targets. In this study, we revealed that the expression of Gal-3 was not only remarkably up-regulated in tumors but also significantly associated with the tumor-associated fibroblasts of PAAD patients. A coculture model of PAAD cells and pancreatic stellate cells revealed that Gal-3 mediated the Ca²⁺/−calcineurin–NFAT pathway to increase the transcription of CCL2 and BSG in tumor-associated fibroblasts. These findings ultimately lead to the observation of low energy metabolism in tumor cells. Particularly, mitochondrial oxidative phosphorylation was functionally arrested in Gal-3-high tumor cells, as demonstrated by a lower oxygen consumption rate and mitochondrial ATP production through abnormal mitochondrial morphology. The inhibition of the CCL2-CCR2 and PPIA-BSG pathways indicated the restoration of gemcitabine sensitivity when drug resistance was elicited by Gal-3. Oral administration of the natural Gal-3 inhibitor modified citrus pectin extract (MCP) showed therapeutic effect for Gal-3-activated tumors and stromal cells in orthotopic pancreatic xenograft models. Hence, our findings offer insights into the fact that low mitochondrial metabolism is dependent on Gal-3 activation-mediated gemcitabine resistance through tumor–stromal interactions.

Background: Efferocytosis (ER) plays a crucial role in the programmed clearance of dead cells, a process that is mediated by phagocytic immune cells. However, further exploration is needed to determine the full extent of its impact on the progression of pancreatic ductal adenocarcinoma (PDAC), particularly through interactions among tumor cells, stromal cells, and immune cells within the tumor microenvironment (TME). Methodology and Results: In this study, we comprehensively analyzed the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as additional databases from multiple bioinformatics websites, utilizing 167 ER features derived from the integration of single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data. A set of 14 ER-associated prognostic signatures, referred to as the “14-gene panel” genes, was identified based on overall survival (OS)/disease-free survival (DFS) data, Pearson correlation coefficients, and multivariate Cox regression analyses. The model pathways enriched by the four-gene combination represented by “LEAF” and the 14-gene combination represented by the “14-gene panel” presented a high degree of similarity, including among the adhesion, mitotic, G2/M checkpoint, and epithelial‒mesenchymal transition (EMT) signaling pathways. Least absolute shrinkage and selection operator (LASSO) regression was subsequently employed to construct an ER risk scoring system using deep learning, based on the following formula: LGALS3, EMP1, ASPH, and FNDC3B, collectively termed the “LEAF” panel. Additionally, random survival forest (RSF) algorithms facilitated the identification of a key panel of genes, designated “LEAP” genes, including LGALS3, EREG, ASPH, and PLS3; three of which genes (ASPH, LGALS3, and EREG) were identified as key factors influencing the behaviors of PDAC tumors, tumor-associated stroma, and macrophages. Finally, we utilized experimental methods, including Boyden chamber analyses, immunohistochemical staining, and cell cycle analyses, to demonstrate that interference with ASPH suppresses the malignant properties of tumors, including proliferation and migration. Multiplex immunofluorescence staining was employed to identify EREG as highly relevant to the M2 macrophage subpopulation. Conclusion: Our findings underscore the importance of considering a novel prognostic signature comprising 14 ER genes in the context of the TME when investigating the biology of PDAC. Future studies may explore how modulating these interactions could lead to novel therapeutic opportunities.