Dhaygude, O. | Search bioRxiv

bioRxiv2026

3D, multi-omic imaging reveals molecular biomarkers of the pre-metastatic niche in lung cancer

The recurrence rate following complete surgical resection of primary non-small cell lung cancer is as high as 55%, yet no approach currently exists to evaluate the risk of local recurrence. The premetastatic paradigm is the recognition that metastasis is preceded by reprogramming naive tissues to prime a microenvironment for tumor cell survival and subsequent reactivation. Identification of biomarkers of the pre-metastatic niche would allow us to evaluate a patients risk of local relapse in the normal lung parenchyma surrounding the resected tumor. We designed a workflow incorporating in vivo modelling, radiology, and deep learning-guided three-dimensional (3D) imaging, spatial proteomics, and transcriptomics to identify previously unreported signals associated with the early transformation of the lung parenchyma announcing regional metastasis. We curated biorepository spanning timepoints before and after resection of primary Lewis Lung Carcinoma (LLC) tumors. Using radiology and cellular resolution 3D histology, we calculated the number and distribution of metastases in mouse lungs and developed an algorithm to guide placement of spatial proteomics and transcriptomics to regions containing early micro-metastases and the pre-metastatic microenvironment. Molecular and tissue features associated with presence, size, and location of metastases guided the identification of both myeloid (F4/80) and senescent (p16/p21) cell signatures in the premetastatic and metastatic environments. Finally, multiparametric flow cytometry of metastatic lungs in a senescence reporter GEMM (tdTomato-p16 INKA mice) resolved senescent cells including alveolar macrophages as the cellular phenotypes associated with these early premetastatic signatures. Altogether, this work highlights a novel AI-assisted approach for detection of biomarkers of tissue remodeling during lung cancer invasion.

bioengineering↗

bioRxiv2025

Synergistic role of riboflavin-auxotrophic Enterococcus for MR1 expression and intra-tumoral mucosal associated invariant T (MAIT) cell activation

The role of mucosal invariant T cells (MAITs), in the lung tumor microenvironment re-mains poorly understood, especially in the setting of immune checkpoint inhibitors. We identified intratumoral MAIT cells from paired single cell RNA and TCR sequencing datasets of tumor infil-trating CD3 T cells isolated from non-small cell lung cancer tumors in patients receiving neoadju-vant PD-1 blockade therapy. MAIT cells were subclustered to identify conventional MAIT-associ-ated TCR clonotypes predicted to recognize intratumoral bacteria, which we then tested for func-tional recognition using a MAIT TCR capture functional assay. Strikingly, although not directly recognized by MAIT cells, previously identified probiotic Enterococcus spp and detected in the intratumoral microbiome of lung cancer patients, selectively synergized with exogenous riboflavin biosynthesis-derived metabolites to induce expression of MR1 by antigen presenting cells, includ-ing dendritic cells, B cells and mononuclear phagocytes. Boosting of MR1 cell surface expression resulted from perturbation of endo-lysosomal vacuolar pathway by Enterococcus and recycling of early endosomal MR1 to the cytoplasmic membrane. Riboflavin auxotrophic Enterococcus spp may therefore exercise their beneficial immunomodulatory functions upon immune checkpoint blockade treatment, at least in part, by promoting intratumoral MR1 expression and innate like T cell activation. Our results indicate that composition of the intratumoral microbiome during im-mune checkpoint inhibitor treatment has the potential to impact the function of human intratumoral MAIT cells.

immunology↗