Int J Surg. 2025 Jul 22. doi: 10.1097/JS9.0000000000002999. Online ahead of print.

ABSTRACT

BACKGROUND: Breast cancer remains the most prevalent malignancy among women, and patients presenting with both breast and lung cancer pose significant challenges in clinical diagnosis and treatment. Currently, comprehensive multi-omics analyses for such multiple malignancies are lacking.

METHODS: An integrated multi-omics analysis was performed, incorporating quantitative proteomics and radiomics data from patients with single primary breast cancer as well as those with multiple primary tumors (breast and lung cancer).

RESULTS: Quantitative proteomics analysis revealed four distinct molecular signatures (Types I-IV). Patients with single breast cancer exhibited driving pathways primarily linked to cell proliferation (e.g., HER2), whereas those with multiple breast cancers showed enrichment in ER-related and proliferative pathways. In contrast, patients with multiple lung cancers displayed pathways associated with immune response and immune escape. Additionally, immune subtyping identified three distinct immune landscapes (Types I-III). Radiomic analysis demonstrated strong correlations between these molecular/immune subtypes and imaging findings. Patients with high imaging information scores exhibited pronounced tumor heterogeneity and reduced immune infiltration.

CONCLUSIONS: This study provides new insights into the molecular pathogenesis of multiple primary malignancies, particularly breast and lung cancer.

PMID:40694032 | DOI:10.1097/JS9.0000000000002999

Cell Stem Cell. 2025 Jun 6:S1934-5909(25)00191-2. doi: 10.1016/j.stem.2025.05.011. Online ahead of print.

ABSTRACT

Deciphering interactions between tumor micro- and systemic immune macroenvironments is essential for developing more effective cancer diagnosis and therapeutic strategies. Here, we established a gel-liquid interface (GLI) co-culture model of lung cancer organoids (LCOs) and paired peripheral-blood mononuclear cells (PBMCs), featuring enhanced interactions between immune cells and tumor organoids for optimized simulation of in vivo systemic anti-tumor immunity. By constructing a cohort of lung cancer patients, we demonstrated that the responses of GLI models under αPD1 treatment reflected the immunotherapy outcomes of the corresponding patients precisely. Furthermore, we dissected the various tumor immune processes mediated by PBMC-derived T cells within GLI models through functional multi-omics analyses, along with the characterization of circulating tumor-reactive T cells (GNLY⁺CD44⁺CD9⁺) with effector memory-like phenotypes as a potential indicator of immunotherapy efficacy. Our findings indicate that the GLI co-culture model can be used to develop diagnostic strategies for precision immunotherapies, as well as understanding the underlying mechanisms.

PMID:40513558 | DOI:10.1016/j.stem.2025.05.011