The genomic landscape of cutaneous SCC reveals drivers and a novel azathioprine associated mutational signature

Cutaneous squamous cell carcinoma (cSCC) has a high tumour mutational burden (50 mutations per megabase DNA pair). Here, we combine whole-exome analyses from 40 primary cSCC tumours, comprising 20 well-differentiated and 20 moderately/poorly differentiated tumours, with accompanying clinical data from a longitudinal study of immunosuppressed and immunocompetent patients and integrate this analysis with independent gene expression studies. We identify commonly mutated genes, copy number changes and altered pathways and processes. Comparisons with tumour differentiation status suggest events which may drive disease progression. Mutational signature analysis reveals the presence of a novel signature (signature 32), whose incidence correlates with chronic exposure to the immunosuppressive drug azathioprine. Characterisation of a panel of 15 cSCC tumour-derived cell lines reveals that they accurately reflect the mutational signatures and genomic alterations of primary tumours and provide a valuable resource for the validation of tumour drivers and therapeutic targets

Genome-wide analyses identify 68 new loci associated with intraocular pressure and improve risk prediction for primary open-angle glaucoma.

Glaucoma is the leading cause of irreversible blindness globally 1 . Despite its gravity, the disease is frequently undiagnosed in the community 2 . Raised intraocular pressure (IOP) is the most important risk factor for primary open-angle glaucoma (POAG)3,4. Here we present a meta-analysis of 139,555 European participants, which identified 112 genomic loci associated with IOP, 68 of which are novel. These loci suggest a strong role for angiopoietin-receptor tyrosine kinase signaling, lipid metabolism, mitochondrial function and developmental processes underlying risk for elevated IOP. In addition, 48 of these loci were nominally associated with glaucoma in an independent cohort, 14 of which were significant at a Bonferroni-corrected threshold. Regression-based glaucoma-prediction models had an area under the receiver operating characteristic curve (AUROC) of 0.76 in US NEIGHBORHOOD study participants and 0.74 in independent glaucoma cases from the UK Biobank. Genetic-prediction models for POAG offer an opportunity to target screening and timely therapy to individuals most at risk

Multimorbidity in people living with and beyond cancer: a scoping review.

Globally, both cancer incidence and survival are increasing. Early cancer detection and improved treatment means many people with cancer will survive for ten or more years following diagnosis. Multimorbidity, defined as two or more chronic conditions, is up to three times higher in people living with and beyond cancer (LWBC) compared to the general population. This scoping review summarises the research evidence on the association between cancer and multimorbidity in people LWBC. It explores five key domains in people LWBC: 1) prevalence of multimorbidity, 2) association between ethnicity and socio-economic status (SES) and multimorbidity, 3) association between health status and multimorbidity, 4) adverse health consequences of cancer and related treatments, and 5) whether being a cancer survivor impacts treatment received for multimorbidity. It focuses on ten common cancers with high survival rates: prostate, breast, non-Hodgkin lymphoma, bowel/colorectal, kidney, head and neck, bladder, leukaemia, uterine and myeloma. A search of Medline, CINAHL, Embase, PsychINFO and Web of Science databases identified 9,460 articles, 115 of which met the inclusion criteria. Articles were included in the review that involved multimorbidity in adult cancer patients. An evaluation of the evidence was performed, and a summary of findings was generated according to Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Extension for Scoping Reviews guidelines. This review included work from 20 countries, most studies were from the US (44%). The results showed that the most common long-term conditions in people LWBC were: hypertension, heart conditions, depression, COPD, and diabetes. The most reported incident comorbidities after a cancer diagnosis were congestive heart failure, chronic pain, and chronic fatigue. Multimorbidity tended to be higher amongst people LWBC from ethnic minority groups and those with lower SES. Quality of life was poorer in people LWBC with multimorbidity. The review identified the need for a uniform approach to measure multimorbidity in cancer patients across the world. Further research is required to compare multimorbidity before and after a cancer diagnosis, to explore the association of multimorbidity with ethnicity and socio-economic status and to determine whether a cancer diagnosis impacts care received for multimorbidity in people LWBC

Prevalence of multimorbidity in survivors of 28 cancer sites: an English nationwide cross-sectional study.

Multimorbidity, the presence of a chronic condition in addition to cancer, is of particular importance to cancer survivors. It has an impact on the progression, stage at diagnosis, prognosis, and treatment of cancer patients. Evidence is scarce on the prevalence of specific comorbidities in survivors of different cancers to inform prevention and management of multimorbidity. The objective of this study is to address this evidence gap by using large scale electronic health data from multiple linked UK healthcare databases to examine the prevalence of multimorbidity in 28 cancer sites. For this population-based cross-sectional study, we linked primary and secondary healthcare data from the UK Clinical Research Practice Datalink (CPRD) GOLD dataset and Hospital Episode Statistics (HES). We identified survivors of 28 common cancers aged 18 years or older at diagnosis who survived 2 years of cancer and compared their multimorbidity with matched controls without a history of cancer. To compare prevalence of individual comorbidity, multivariable logistic regression models, adjusted for confounding factors were used. Between January 1, 2010 and December 31, 2020, we identified 347,028 cancer survivors and 804,299 controls matched on age, sex and general practice. Cancer survivors had a higher prevalence of multimorbidity compared to non-cancer controls across all the cancer sites. Hypertension (56.2%), painful conditions (39.8%), osteoarthritis (38.0%), depression (31.8%) and constipation (31.4%) were the five most frequent chronic conditions reported. Compared to the controls, higher odds of constipation were found in survivors of 25 of the 28 cancer sites and higher odds of anaemia were found in 23 cancer sites. Prevalence of constipation, anaemia and painful conditions were higher after cancer diagnosis compared to before diagnosis. Since these comorbidities are not uniformly assessed as part of any of the comorbidity scales, they tend to be underreported among cancer survivors. The elevated risk of certain comorbidities in cancer survivors suggests the potential for preventative efforts in this population to lower disease burden and improve quality of life. Long-term conditions should not be viewed as the inevitable result of cancer diagnosis and treatment. We need to consider integrated management of chronic conditions tailored to specific cancers to improve cancer survivorship

Reconstituting development of pancreatic intraepithelial neoplasia from primary human pancreas duct cells

Development of systems that reconstitute hallmark features of human pancreatic intraepithelial neoplasia (PanINs), the precursor to pancreatic ductal adenocarcinoma, could generate new strategies for early diagnosis and intervention. However, human cell-based PanIN models with defined mutations are unavailable. Here, we report that genetic modification of primary human pancreatic cells leads to development of lesions resembling native human PanINs. Primary human pancreas duct cells harbouring oncogenic KRAS and induced mutations in CDKN2A, SMAD4 and TP53 expand in vitro as epithelial spheres. After pancreatic transplantation, mutant clones form lesions histologically similar to native PanINs, including prominent stromal responses. Gene expression profiling reveals molecular similarities of mutant clones with native PanINs, and identifies potential PanIN biomarker candidates including Neuromedin U, a circulating peptide hormone. Prospective reconstitution of human PanIN development from primary cells provides experimental opportunities to investigate pancreas cancer development, progression and early-stage detection

Genome-wide association study of individual differences of human lymphocyte profiles using large-scale cytometry data

Human immune systems are very complex, and the basis for individual differences in immune phenotypes is largely unclear. One reason is that the phenotype of the immune system is so complex that it is very difficult to describe its features and quantify differences between samples. To identify the genetic factors that cause individual differences in whole lymphocyte profiles and their changes after vaccination without having to rely on biological assumptions, we performed a genome-wide association study (GWAS), using cytometry data. Here, we applied computational analysis to the cytometry data of 301 people before receiving an influenza vaccine, and 1, 7, and 90 days after the vaccination to extract the feature statistics of the lymphocyte profiles in a nonparametric and data-driven manner. We analyzed two types of cytometry data: measurements of six markers for B cell classification and seven markers for T cell classification. The coordinate values calculated by this method can be treated as feature statistics of the lymphocyte profile. Next, we examined the genetic basis of individual differences in human immune phenotypes with a GWAS for the feature statistics, and we newly identified seven significant and 36 suggestive single-nucleotide polymorphisms associated with the individual differences in lymphocyte profiles and their change after vaccination. This study provides a new workflow for performing combined analyses of cytometry data and other types of genomics data