A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis.

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories.

Unraveling ETC complex I function in ferroptosis reveals a potential ferroptosis-inducing therapeutic strategy for LKB1-deficient cancers.

The role of the mitochondrial electron transport chain (ETC) in regulating ferroptosis is not fully elucidated. Here, we reveal that pharmacological inhibition of the ETC complex I reduces ubiquinol levels while decreasing ATP levels and activating AMP-activated protein kinase (AMPK), the two effects known for their roles in promoting and suppressing ferroptosis, respectively. Consequently, the impact of complex I inhibitors on ferroptosis induced by glutathione peroxidase 4 (GPX4) inhibition is limited. The pharmacological inhibition of complex I in LKB1-AMPK-inactivated cells, or genetic ablation of complex I (which does not trigger apparent AMPK activation), abrogates the AMPK-mediated ferroptosis-suppressive effect and sensitizes cancer cells to GPX4-inactivation-induced ferroptosis. Furthermore, complex I inhibition synergizes with radiotherapy (RT) to selectively suppress the growth of LKB1-deficient tumors by inducing ferroptosis in mouse models. Our data demonstrate a multifaceted role of complex I in regulating ferroptosis and propose a ferroptosis-inducing therapeutic strategy for LKB1-deficient cancers.