The major histocompatibility complex (MHC) region plays a crucial role in immune function; therefore, any genetic or epigenetic polymorphisms within the MHC locus may result in various diseases, as well as cancer immunoediting. Given its high polymorphism, accurately profiling the MHC region using conventional reference genomes is a challenge. Yet, generating complete, high-quality haplotype-resolved assemblies of the MHC region for commonly used cell lines is both a necessity and a valuable resource for the research community.

Current cancer screening methods are limited in scope, often detecting only a few cancer types with low positive predictive value and suboptimal patient adherence. In recent years, liquid biopsy-based multi-cancer early detection (MCED) has emerged as a promising approach to revolutionize cancer control. Despite several MCED tests reaching clinical trial phases and seeking regulatory approval, none have yet been approved for clinical use, highlighting uncertainties regarding their efficacy and applicability. This review comprehensively examines the advancements in MCED technologies and offers insights into the selection of cancer types for inclusion in MCED panels. Researchers explore the clinical development pathway for MCED, from biomarker discovery and analytical validation to large-scale randomized controlled trials, emphasizing the importance of selecting appropriate endpoints such as reducing late-stage cancer incidence or cancer-specific mortality. Key challenges, including achieving optimal sensitivity for early-stage cancers, minimizing false positives and negatives, and ensuring equitable access to MCED tests, are also addressed. Finally, they evaluate the added value and health economic benefits of integrating MCED into established healthcare systems through widespread implementation. By providing a thorough analysis of these aspects, this review aims to advance the field of cancer screening and guide future research and development efforts.

A new study by researchers at the Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, and collaborators, suggests that artificial intelligence (AI) could significantly improve how doctors determine the best treatment for cancer patients—by enhancing how tumor samples are analyzed in the lab. The findings, published in the July 9 online edition of Nature Medicine, showed that AI can accurately predict genetic mutations from routine pathology slides—potentially reducing the need for rapid genetic testing in certain cases.

A new study, led by experts at the University of Nottingham, provides the strongest evidence to date that cancer is extremely rare in turtles, a finding that could offer valuable clues for preventing or fighting cancer in humans.

While previous research had hinted that cancer might be uncommon in turtles, the new analysis, published in BioScience, shows that only about 1% of individuals are affected, far less than in mammals or birds. The study was led by Dr Ylenia Chiari from the School of Life Sciences at the University of Nottingham, alongside Dr Scott Glaberman from the University of Birmingham, in collaboration with a team of researchers from zoos across the US, UK, and Europe.

The team analysed medical records and necropsies (autopsies) from hundreds of zoo turtles, including individuals from Chester Zoo in the UK.