Acquired mutations are pervasive across normal tissues. However, our understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMN). We find mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response (DDR) genes ( TP53, PPM1D, CHEK2 ). Sequential sampling provides definitive evidence that DDR clones outcompete other clones when exposed to certain therapies. Among cases where CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies.

C oronavirus disease 2019 (COVID-19), caused by the novel betacoronavirus severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is an unprecedented global pandemic. 1 Susceptibility to COVID-19 is a concern among patients with inflammatory bowel disease (IBD) who are at increased risk of infection due to immunosuppressive therapy. The receptor angiotensin-converting enzyme (ACE) 2, which mediates SARS-CoV-2 entry into cells, is upregulated in IBD 2 and may therefore increase host susceptibility. International cohorts have reported no increased risk of COVID-19 in patients with IBD 3,4 ; however, these studies do not report the prevalence of SARS-CoV-2 testing and COVID-19 in patients with IBD. Our institution was among the first to initiate large-scale SARS-CoV-2 RNA testing in northern California. We characterized the prevalence and clinical predictors of COVID-19 in patients with IBD.

Clonal hematopoiesis (CH) is frequent in cancer patients and associated with increased risk of therapy related myeloid neoplasms (tMN). To define the relationship between CH, oncologic 90 therapy, and tMN progression, we studied 24,439 cancer patients. We show that previously treated patients have increased rates of CH, with enrichment of mutations in DNA Damage Response (DDR) genes (TP53, PPM1D, CHEK2). Exposure to radiation, platinum and topoisomerase II inhibitors have the strongest association with CH with evidence of dose-dependence and genetreatment interactions. We validate these associations in serial sampling from 525 patients and 95show that exposure to cytotoxic and radiation therapy imparts a selective advantage specifically in hematopoietic cells with DDR mutations. In patients who progressed to tMN, the clone at CH demarcated the dominant clone at tMN diagnosis. CH mutational features predict risk of therapyrelated myeloid neoplasm in solid tumor patients with clinical implications for early detection and treatment decisions. 100

This paper presents the first report of an ongoing prospective randomised clinical trial in early T1T2N0 carcinoma of the oral tongue. The problems of regular follow-up in an indigent population from the vast rural expanse of India has been successfully overcome in this trial by close personal follow-up. The trial addresses itself specifically to prophylactic vs. therapeutic surgical management of the neck in T1T2N0 patients with cancer of the oral tongue. Overall disease, free survival (median follow-up 22 months) is higher (64% vs. 47%) in the group receiving prophylactic neck dissection. Disease-free survival for those with positive nodes at prophylactic neck dissection was twice that of those who underwent a subsequent therapeutic neck dissection (57% vs. 28%). Contralateral neck node metastasis has been identified as a significant factor in neck failures in those patients undergoing simultaneous prophylactic neck dissection.

Inflammatory bowel disease (IBD) is a complex and multifaceted disorder of the gastrointestinal tract that is increasing in incidence worldwide and associated with significant morbidity. The rapid accumulation of large datasets from electronic health records, high-definition multi-omics (including genomics, proteomics, transcriptomics, and metagenomics), and imaging modalities (endoscopy and endomicroscopy) have provided powerful tools to unravel novel mechanistic insights and help address unmet clinical needs in IBD. Although the application of artificial intelligence (AI) methods has facilitated the analysis, integration, and interpretation of large datasets in IBD, significant heterogeneity in AI methods, datasets, and clinical outcomes and the need for unbiased prospective validations studies are current barriers to incorporation of AI into clinical practice. The purpose of this review is to summarize the most recent advances in the application of AI and machine learning technologies in the diagnosis and risk prediction, assessment of disease severity, and prediction of clinical outcomes in patients with IBD.