Artificial intelligence-enabled automated analysis of transmission electron micrographs to evaluate chemotherapy impact on mitochondrial morphology in triple negative breast cancer
ABSTRACT Advancements in transmission electron microscopy (TEM) have enabled in-depth studies of biological specimens, offering new avenues to large-scale imaging experiments with subcellular resolution. Mitochondrial structure is of growing interest in cancer biology due to its crucial role in regulating the multi-faceted functions of mitochondria. We and others have established the crucial role of mitochondria in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer with limited therapeutic options. Building upon our previous work demonstrating the functional role of mitochondrial structure dynamics in the metabolic adaptations and survival of chemotherapy-refractory TNBC cells, we sought to extend those findings to a large-scale analysis of transmission electron micrographs. Here we present a novel U-Net artificial intelligence (AI) model for automatic annotation and assessment of mitochondrial morphology and feature quantification. Our model is trained on 11,039 manually annotated mitochondria across 125 micrographs derived from a variety of orthotopic patient-derived xenograft (PDX) mouse model tumors and adherent cell cultures. The model achieves an F1 score of 0.85 on test micrographs at the pixel level. To validate the ability of our model to detect expected mitochondrial structural changes, we utilized micrographs from mouse primary skeletal muscle cells genetically modified to lack Dynamin-related protein 1 (Drp1). We subjected in vitro and in vivo TNBC models to conventional chemotherapy treatments commonly used for clinical management of TNBC, including doxorubicin, carboplatin, paclitaxel, and docetaxel (DTX). We found substantial within-sample heterogeneity of mitochondrial structure in both in vitro and in vivo TNBC models. In four of five PDX models, in vivo treatment with DTX elicited significant alteration in mitochondrial elongation and/or area. We went on to compare mammary tumors and matched lung metastases in a highly metastatic PDX model of TNBC, uncovering significant increase in mitochondrial elongation in metastatic lesions compared to their matched primary mammary tumor. The successful application of our AI model to capture mitochondrial structure marks a step forward in high-throughput analysis of mitochondrial structures, enhancing our understanding of how morphological changes may relate to chemotherapy efficacy and mechanism of action. Our large, manually curated electron micrograph dataset - now publicly available - serves as a unique resource for developing, benchmarking, and applying computational models, while further advancing investigations into mitochondrial morphology and its impact on breast cancer biology. This study provides proof of concept that mitochondrial structural remodeling is an additional layer of cellular reprogramming accompanying therapeutic resistance TNBC that merits further investigation.
Relationship Between Rheumatoid Arthritis and Pulmonary Function Measures on Spirometry in the UK Biobank
ObjectiveTo investigate the independent relationship of rheumatoid arthritis (RA) to the type and severity of pulmonary patterns on spirometry compared to the pulmonary patterns in general population controls.MethodsIn this cross‐sectional study, we investigated the association of RA with pulmonary function measures on spirometry among subjects in the UK Biobank who underwent spirometry for research purposes. RA cases were identified based on self‐report and current disease‐modifying antirheumatic drug/glucocorticoid use. Controls were subjects without RA from the general population. Outcome measures included continuous forced expiratory volume in 1 second percent predicted (FEV1%) and forced vital capacity percent predicted (FVC%), type of spirometric pattern (restrictive or obstructive), and severity of the restrictive or obstructive pattern. We used multivariable regression to estimate the effects in RA cases compared to the effects in controls, adjusting for age, sex, body mass index, and smoking status/pack‐years.ResultsAmong 350,776 analyzed subjects who underwent spirometry (mean age 56.3 years; 55.8% female; 45.5% ever smokers), we identified 2,008 cases of treated RA. In multivariable analyses, RA was associated with lower FEV1% (β = –2.93 [95% confidence interval (95% CI) –3.63, –2.24]), FVC% (β = –2.08 [95% CI –2.72, –1.45]), and FEV1/FVC (β = –0.008 [95% CI –0.010, –0.005]) compared to controls. RA was additionally associated with restrictive patterns (odds ratio [OR] 1.36 [95% CI 1.21, 1.52]) and obstructive patterns (OR 1.21 [95% CI 1.07, 1.37]) independent of confounders, and was most strongly associated with severe restrictive and obstructive patterns.ConclusionRA is associated with increased odds of restrictive and obstructive patterns, and this relationship is not explained by confounders, including smoking status. In addition to restrictive lung disease, clinicians should also be aware that airway obstruction may be a pulmonary manifestation of RA.