Ubaldo E. Martinez-Outschoorn

The fibrotic subtype of the tumor microenvironment characterized by epithelial-mesenchymal transition, fibrosis, angiogenesis and immune exclusion, predicts poor outcomes across diverse malignancies, yet the role of miR-145 in this context remains unexplored. Leveraging The Cancer Genome Atlas head and neck squamous cell carcinoma (HNSCC) and breast cancer (BRCA) databases, we demonstrate that miR-145 reprogramming recapitulates a noninflamed fibrotic phenotype with immune exclusion. In high miR-145 tumors, EMT programs persist alongside abundant cancer-associated fibroblasts, matrix remodeling and angiogenesis, with upregulation of NOTCH, TGF-β, myogenesis, hypoxia, Hedgehog, and Wnt/β-catenin signaling and downregulation of interferon-γ and JAK–STAT pathways. Our findings illustrate that cancer–stromal juxtacrine interactions activate NOTCH signaling, forming a positive feedback loop that amplifies miR-145 expression and is reinforced by miR-145 promoter hypomethylation. High miR-145 promotes autophagy and mitochondrial oxidative phosphorylation (OXPHOS) metabolism in cancer cells, with GAPDH serving as a central hub linking metabolism, noninflamed immune modulation, and poor clinical outcomes. In vivo , high miR-145 carcinoma cells co-engrafted with fibroblasts drive tumor growth through enhanced metabolism, angiogenesis and immune evasion. This study establishes miR-145 as a driver and biomarker of the fibrotic tumor microenvironment to better inform future cancer therapy strategies.

Figure s6. Post-treatment changes in immune cell composition across spatial tumor compartments in responders and nonresponders

Figure s11. Carcinoma ecotype differences at baseline and after treatment in HPV+ HNSCC responders and non-responders. This figure illustrates differences in carcinoma ecotype composition before and after treatment in HPV+ HNSCC patients

Purpose:Immune checkpoint inhibitors (ICI) have demonstrated clinical benefit in head and neck squamous cell carcinoma (HNSCC); however, single-agent efficacy is limited, leaving significant unmet needs. Metformin may synergize with ICIs, offering promise to improve response rates. We leveraged multiomic data from a randomized, presurgical neoadjuvant trial (NCT03618654) evaluating a single infusion of the anti–PD-L1 ICI durvalumab with or without daily, standard dose metformin in previously untreated, nondiabetic patients with HNSCC to understand predictors of response and the effect of combination therapy.Patients and Methods:Clinical, pathologic, and correlative data were analyzed to investigate response and resistance mechanisms. We present an in-depth multiomic analysis of primary tumor specimens to study treatment response/resistance in human papillomavirus–positive HNSCC.Results:Baseline samples revealed that myofibroblastic cancer-associated fibroblast and extracellular matrix signatures were enriched in durvalumab plus metformin nonresponders, which were localized to the leading tumor edge on spatial transcriptomics. In contrast, baseline responder samples were enriched for the Langerhans-like dendritic cell (DC) state and IFN signatures. Treatment increased intratumoral CD8+ T-cell and IFN signatures and peripheral blood CCL2 levels. Responders demonstrated macrophage and DC enrichment and antigen processing and presentation upregulation. Enrichment of cell cycle–related gene sets, specifically the MYC targets V1 hallmark gene set, correlated with nonresponse.Conclusions:Early response and resistance dynamics for durvalumab plus metformin in human papillomavirus–positive HNSCC reveal baseline extracellular matrix–myofibroblastic cancer-associated fibroblast as predictive of nonresponse. In contrast, responders were distinguished by baseline enrichment in the Langerhans-like DC state and posttreatment antigen-presenting gene sets.

Figure s8: Identification and Functional Analysis of Unique Mutations in responders and non-Responders in HPV+ DM Using Whole-Exome Sequencing (WES)

Figure s2. CONSORT diagram. CONSORT diagram illustrating patient enrollment, allocation, treatment, follow-up, and analysis.

Figure s9: Integrated transcriptomic and pathway analyses reveal stress response, metabolic, and EMT-related differences in PanCK-enriched and treatment response subgroups

Figure s10. Hallmark pathway enrichment, cell cycle gene expression, and functional network analysis of differentially expressed genes in responders and nonresponders.