Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

Localized radiotherapy (RT) induces an immunogenic antitumor response that is in part counterbalanced by activation of immune evasive and tissue remodeling processes, e.g., via upregulation of programmed cell death-ligand 1 (PD-L1) and transforming growth factor β (TGF-β). We report that a bifunctional fusion protein that simultaneously inhibits TGF-β and PD-L1, bintrafusp alfa (BA), effectively synergizes with radiotherapy, leading to superior survival in multiple therapy-resistant murine tumor models with poor immune infiltration. The BA + RT (BART) combination increases tumor-infiltrating leukocytes, reprograms the tumor microenvironment, and attenuates RT-induced fibrosis, leading to reconstitution of tumor immunity and regression of spontaneous lung metastases. Consistently, the beneficial effects of BART are in part reversed by depletion of cytotoxic CD8⁺ T cells. Intriguingly, targeting of the TGF-β trap to PD-L1⁺ endothelium and the M2/lipofibroblast-like cell compartment by BA attenuated late-stage RT-induced lung fibrosis. Together, the results suggest that the BART combination has the potential to eradicate therapy-resistant tumors while sparing normal tissue, further supporting its clinical translation.

Reliable entity subtyping is paramount for therapy stratification in lung cancer. Morphological evaluation remains the basis for entity subtyping and directs the application of additional methods such as immunohistochemistry (IHC). The decision of whether to perform IHC for subtyping is subjective, and access to IHC is not available worldwide. Thus, the application of additional methods to support morphological entity subtyping is desirable. Therefore, the ability of convolutional neuronal networks (CNNs) to classify the most common lung cancer subtypes, pulmonary adenocarcinoma (ADC), pulmonary squamous cell carcinoma (SqCC), and small-cell lung cancer (SCLC), was evaluated. A cohort of 80 ADC, 80 SqCC, 80 SCLC, and 30 skeletal muscle specimens was assembled; slides were scanned; tumor areas were annotated; image patches were extracted; and cases were randomly assigned to a training, validation or test set. Multiple CNN architectures (VGG16, InceptionV3, and InceptionResNetV2) were trained and optimized to classify the four entities. A quality control (QC) metric was established. An optimized InceptionV3 CNN architecture yielded the highest classification accuracy and was used for the classification of the test set. Image patch and patient-based CNN classification results were 95% and 100% in the test set after the application of strict QC. Misclassified cases mainly included ADC and SqCC. The QC metric identified cases that needed further IHC for definite entity subtyping. The study highlights the potential and limitations of CNN image classification models for tumor differentiation.

Desmoplasia describes the deposition of extensive extracellular matrix and defines primary pancreatic ductal adenocarcinoma (PDA). The acellular component of this stroma has been implicated in PDA pathogenesis and is being targeted therapeutically in clinical trials. By analyzing the stromal content of PDA samples from numerous annotated PDA data sets and correlating stromal content with both anatomic site and clinical outcome, we found PDA metastases in the liver, the primary cause of mortality to have less stroma, have higher tumor cellularity than primary tumors. Experimentally manipulating stromal matrix with an anti–lysyl oxidase like-2 (anti-LOXL2) antibody in syngeneic orthotopic PDA mouse models significantly decreased matrix content, led to lower tissue stiffness, lower contrast retention on computed tomography, and accelerated tumor growth, resulting in diminished overall survival. These studies suggest an important protective role of stroma in PDA and urge caution in clinically deploying stromal depletion strategies.

Objective: CD8+ T cells contribute to rheumatoid arthritis (RA) by releasing proinflammatory and cytolytic mediators, even in a challenging hypoxic and nutrient‐poor microenvironment such as the synovial membrane. This study was undertaken to explore the mechanisms through which CD8+ T cells meet their metabolic demands in the blood and synovial membrane of patients with RA.Methods: Purified blood CD8+ T cells from patients with RA, patients with psoriatic arthritis (PsA), and patients with spondyloarthritis (SpA), as well as healthy control subjects, and CD8+ T cells from RA synovial membrane were stimulated in medium containing ¹³C‐labeled metabolic substrates in the presence or absence of metabolic inhibitors, under conditions of normoxia or hypoxia. The production of metabolic intermediates was quantified by ¹H‐nuclear magnetic resonance. The expression of metabolic enzymes, transcription factors, and immune effector molecules was assessed at both the messenger RNA (mRNA) and protein levels. CD8+ T cell functional studies were performed.Results: RA blood CD8+ T cells met their metabolic demands through aerobic glycolysis, production of uniformly ¹³C‐enriched lactate in the RA blood (2.6 to 3.7–fold higher than in patients with SpA, patients with PsA, and healthy controls; P < 0.01), and induction of glutaminolysis. Overexpression of Warburg effect–linked enzymes in all RA CD8+ T cell subsets maintained this metabolic profile, conferring to the cells the capacity to proliferate under hypoxia and low‐glucose conditions. In all RA CD8+ T cell subsets, lactate dehydrogenase A (LDHA) was overexpressed at the mRNA level (P < 0.03 versus controls; n = 6 per group) and protein level (P < 0.05 versus controls; n = 17 RA patients, n = 9 controls). In RA blood, inhibition of LDHA with FX11 led to reductions in lipogenesis, migration and proliferation of CD8+ T cells, and CD8+ T cell effector functions, while production of reactive oxygen species was increased by 1.5‐fold (P < 0.03 versus controls). Following inhibition of LDHA with FX11, RA CD8+ T cells lost their capacity to induce healthy B cells to develop a proinflammatory phenotype. Similar metabolic alterations were observed in RA CD8+ T cells from the synovial membrane.Conclusion: Remodeling glucose and glutamine metabolism in RA CD8+ T cells by targeting LDHA activity can reduce the deleterious inflammatory and cytolytic contributions of these cells to the development of autoimmunity.