Mayranpaa, M. I. | Search bioRxiv

bioRxiv2024

HHV-6B, HHV-7, and B19V Are Frequently Found DNA Viruses in the Human Thymus but Show No Definitive Link with Myasthenia Gravis

Myasthenia gravis (MG) is an autoimmune disorder characterised by autoantibodies that target components of the neuromuscular junction, primarily the acetylcholine receptor (AChR), resulting in muscle weakness. The thymus plays a significant role in MG pathogenesis, particularly in patients under the age of 50, who display pathological alterations and possess elements conducive to autoimmune reactions. Although viral infections are suspected drivers of thymic pathogenesis, the exact aetiology of MG remains elusive. This study investigates the potential link between MG and DNA viruses within the thymus. Using targeted next-generation sequencing and quantitative PCR, we analysed the presence of human parvovirus B19 (B19V) and nine human herpesviruses (HSV-1, HSV-2, VZV, EBV, CMV, HHV-6A, HHV-6B, HHV-7, and HHV-8) in fresh tissue samples from 19 non-thymomatous MG patients, 16 thymomas (3 with and 14 without MG), 41 normal thymus tissues, and 20 tonsils from healthy individuals. HHV-6B was the most common virus, found in over 50% of all tissue groups. B19V DNA was detected in 40% of adult control thymic tissue, 72% of MG thymus, 7.7% of non-MG thymoma, and 50% of tonsil samples. HHV-7 was present in 15-30% of thymus tissues and 95% of tonsils, while EBV was detected in less than 25% of all thymus samples but 85% of tonsils. In B19V seropositive individuals, B19V DNA was detected in 100% of thymic tissue from both MG patients and healthy individuals, except in thymomatous tissues, where it was found in only one of thirteen seropositive individuals. Immunohistochemistry for B19V protein expression did not show evident B19V VP1/VP2 protein expression, indicating dormant viral persistence. Laser capture microdissection (LCM) and RNAscope in situ hybridisation pinpointed B19V DNA localisation to the thymus medulla. This study is the first to demonstrate the persistence of various DNA viruses in the human thymus. However, neither B19V nor the nine human herpesviruses showed specific enrichment in MG thymic tissue compared to controls, suggesting that these viral infections are unlikely to be sole environmental triggers for MG.

immunology↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗