Aberrant TIMP-1 production in tumor-associated fibroblasts drives the selective benefits of nintedanib in lung adenocarcinoma.

The fibrotic tumor microenvironment is a pivotal therapeutic target. Nintedanib, a clinically approved multikinase antifibrotic inhibitor, is effective against lung adenocarcinoma (ADC) but not squamous cell carcinoma (SCC). Previous studies have implicated the secretome of tumor-associated fibroblasts (TAFs) in the selective effects of nintedanib in ADC, but the driving factor(s) remained unidentified. Here we examined the role of tissue inhibitor of metalloproteinase-1 (TIMP-1), a tumor-promoting cytokine overproduced in ADC-TAFs. To this aim, we combined genetic approaches with in vitro and in vivo preclinical models based on patient-derived TAFs. Nintedanib reduced TIMP-1 production more efficiently in ADC-TAFs than SCC-TAFs through a SMAD3-dependent mechanism. Cell culture experiments indicated that silencing TIMP1 in ADC-TAFs abolished the therapeutic effects of nintedanib on cancer cell growth and invasion, which were otherwise enhanced by the TAF secretome. Consistently, co-injecting ADC cells with TIMP1-knockdown ADC-TAFs into immunocompromised mice elicited a less effective reduction of tumor growth and invasion under nintedanib treatment compared to tumors bearing unmodified fibroblasts. Our results unveil a key mechanism underlying the selective mode of action of nintedanib in ADC based on the excessive production of TIMP-1 in ADC-TAFs. We further pinpoint reduced SMAD3 expression and consequent limited TIMP-1 production in SCC-TAFs as key for the resistance of SCC to nintedanib. These observations strongly support the emerging role of TIMP-1 as a critical regulator of therapy response in solid tumors.

Multiplex Digital Spatial Profiling in Breast Cancer Research: State-of-the-Art Technologies and Applications across the Translational Science Spectrum.

While RNA sequencing and multi-omic approaches have significantly advanced cancer diagnosis and treatment, their limitation in preserving critical spatial information has been a notable drawback. This spatial context is essential for understanding cellular interactions and tissue dynamics. Multiplex digital spatial profiling (MDSP) technologies overcome this limitation by enabling the simultaneous analysis of transcriptome and proteome data within the intact spatial architecture of tissues. In breast cancer research, MDSP has emerged as a promising tool, revealing complex biological questions related to disease evolution, identifying biomarkers, and discovering drug targets. This review highlights the potential of MDSP to revolutionize clinical applications, ranging from risk assessment and diagnostics to prognostics, patient monitoring, and the customization of treatment strategies, including clinical trial guidance. We discuss the major MDSP techniques, their applications in breast cancer research, and their integration in clinical practice, addressing both their potential and current limitations. Emphasizing the strategic use of MDSP in risk stratification for women with benign breast disease, we also highlight its transformative potential in reshaping the landscape of breast cancer research and treatment.