BACKGROUND: Targeted therapies in oncology are promising but variants of uncertain significance (VUS) limit their use for clinical management and necessitate functional testing in vitro. Using BRCA1 and BRCA2 variants, which have consequences on PARP inhibitor sensitivity, and POLE variants, potential biomarkers of immunotherapy response, we developed a rapid functional assay based on CRISPR-Cas9 genome editing to determine the functional consequences of these variants having potentially direct implications on patients' access to targeted therapies. METHODS: We first evaluated the functional impact of 26 BRCA1 and 7 BRCA2 variants by editing and comparing NGS results between the variant of interest and a silent control variant. Ten of these variants had already been classified as benign or pathogenic and were used as controls. Finally, we extended this method to the characterization of POLE VUS. RESULTS: For the 23 variants that were unclassified or for which conflicting interpretations had been reported, 15 were classified as functionally normal and 6 as functionally abnormal. Another two variants were found to have intermediate consequences, both with potential impacts on splicing. We then compared these scores to the patients' responses to PARP inhibitors when possible. Finally, to prove the application of our method to the classification of variants from other tumor suppressor genes, we exemplified with three POLE VUS. Among them, two were classified with an intermediate functional impact and one was functionally abnormal. Eventually, four POLE variants previously classified in databases were also evaluated. However, we found evidence of a discordance with the classification, variant p.Leu424Val being found here functionally normal. CONCLUSIONS: Our new rapid functional assay can be used to characterize the functional implication of BRCA1 and BRCA2 variants, giving patients whose variants were evaluated as functionally abnormal access to PARP inhibitor treatment. Retrospective analysis of patients' responses to PARP inhibitors, where accessible, was consistent with our functional score evaluation and confirmed the accuracy of our protocol. This method could potentially be extended to the classification of VUS from all essential tumor suppressor genes and can be performed within a timeframe compatible with clinical applications, thereby having a direct theranostic impact.

BACKGROUND: Cardiorespiratory fitness (CRF) and physical activity (PA) are well-established predictors of morbidity and all-cause mortality. However, CRF is not routinely measured and PA not routinely prescribed as part of standard healthcare. The American Heart Association (AHA) recently presented a scientific case for the inclusion of CRF as a clinical vital sign based on epidemiological and clinical observation. Here, we leverage genetic data in the UK Biobank (UKB) to strengthen the case for CRF as a vital sign and make a case for the prescription of PA. METHODS: We derived two CRF measures from the heart rate data collected during a submaximal cycle ramp test: CRF-vo2max, an estimate of the participants' maximum volume of oxygen uptake, per kilogram of body weight, per minute; and CRF-slope, an estimate of the rate of increase of heart rate during exercise. Average PA over a 7-day period was derived from a wrist-worn activity tracker. After quality control, 70,783 participants had data on the two derived CRF measures, and 89,683 had PA data. We performed genome-wide association study (GWAS) analyses by sex, and post-GWAS techniques to understand genetic architecture of the traits and prioritise functional genes for follow-up. RESULTS: We found strong evidence that genetic variants associated with CRF and PA influenced genetic expression in a relatively small set of genes in the heart, artery, lung, skeletal muscle and adipose tissue. These functionally relevant genes were enriched among genes known to be associated with coronary artery disease (CAD), type 2 diabetes (T2D) and Alzheimer's disease (three of the top 10 causes of death in high-income countries) as well as Parkinson's disease, pulmonary fibrosis, and blood pressure, heart rate, and respiratory phenotypes. Genetic variation associated with lower CRF and PA was also correlated with several disease risk factors (including greater body mass index, body fat and multiple obesity phenotypes); a typical T2D profile (including higher insulin resistance, higher fasting glucose, impaired beta-cell function, hyperglycaemia, hypertriglyceridemia); increased risk for CAD and T2D; and a shorter lifespan. CONCLUSIONS: Genetics supports three decades of evidence for the inclusion of CRF as a clinical vital sign. Given the genetic, clinical and epidemiological evidence linking CRF and PA to increased morbidity and mortality, regular measurement of CRF as a marker of health and routine prescription of PA could be a prudent strategy to support public health.

Ensuring accordance with principles of healthcare ethics requires improved communication of pathogen genomic data. This could include educating healthcare professionals in communicating pathogen genomic information to individuals, developing ethical frameworks for reporting pathogen genomic results to individuals, responsible media reporting guidelines, and counselling for individuals ('pathogen genetic counselling').

BACKGROUND: Hundreds of thousands of cancer patients have had targeted (panel) tumor sequencing to identify clinically meaningful mutations. In addition to improving patient outcomes, this activity has led to significant discoveries in basic and translational domains. However, the targeted nature of clinical tumor sequencing has a limited scope, especially for germline genetics. In this work, we assess the utility of discarded, off-target reads from tumor-only panel sequencing for the recovery of genome-wide germline genotypes through imputation. METHODS: We developed a framework for inference of germline variants from tumor panel sequencing, including imputation, quality control, inference of genetic ancestry, germline polygenic risk scores, and HLA alleles. We benchmarked our framework on 833 individuals with tumor sequencing and matched germline SNP array data. We then applied our approach to a prospectively collected panel sequencing cohort of 25,889 tumors. RESULTS: We demonstrate high to moderate accuracy of each inferred feature relative to direct germline SNP array genotyping: individual common variants were imputed with a mean accuracy (correlation) of 0.86, genetic ancestry was inferred with a correlation of > 0.98, polygenic risk scores were inferred with a correlation of > 0.90, and individual HLA alleles were inferred with a correlation of > 0.80. We demonstrate a minimal influence on the accuracy of somatic copy number alterations and other tumor features. We showcase the feasibility and utility of our framework by analyzing 25,889 tumors and identifying the relationships between genetic ancestry, polygenic risk, and tumor characteristics that could not be studied with conventional on-target tumor data. CONCLUSIONS: We conclude that targeted tumor sequencing can be leveraged to build rich germline research cohorts from existing data and make our analysis pipeline publicly available to facilitate this effort.

BACKGROUND: Cancer is a somatic evolutionary disease and adenocarcinomas of the stomach and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer expansion, in which tumor subclones are not evenly mixed during tumor progression but rather spatially separated and diversified. We hypothesize that precision medicine efforts are compromised when clinical decisions are based on a single-sample analysis, which ignores the mechanisms of cancer evolution and resulting intratumoral heterogeneity. Using multiregional whole-exome sequencing, we investigated the effect of somatic evolution on intratumoral heterogeneity aiming to shed light on the evolutionary biology of GC. METHODS: The study comprised a prospective discovery cohort of 9 and a validation cohort of 463 GCs. Multiregional whole-exome sequencing was performed using samples form 45 primary tumors and 3 lymph node metastases (range 3-10 tumor samples/patient) of the discovery cohort. RESULTS: In total, the discovery cohort harbored 16,537 non-synonymous mutations. Intratumoral heterogeneity of somatic mutations and copy number variants were present in all tumors of the discovery cohort. Of the non-synonymous mutations, 53-91% were not present in each patient's sample; 399 genes harbored 2-4 different non-synonymous mutations in the same patient; 175 genes showed copy number variations, the majority being heterogeneous, including CD274 (PD-L1). Multi-sample tree-based analyses provided evidence for branched evolution being most complex in a microsatellite instable GC. The analysis of the mode of evolution showed a high degree of heterogeneity in deviation from neutrality within each tumor. We found evidence of parallel evolution and evolutionary trajectories: different mutations of SMAD4 aligned with different subclones and were found only in TP53 mutant GCs. CONCLUSIONS: Neutral and non-neutral somatic evolution shape the mutational landscape in GC along its lateral expansions. It leads to complex spatial intratumoral heterogeneity, where lymph node metastases may stem from different areas of the primary tumor, synchronously. Our findings may have profound effects on future patient management. They illustrate the risk of mis-interpreting tumor genetics based on single-sample analysis and open new avenues for an evolutionary classification of GC, i.e., the discovery of distinct evolutionary trajectories which can be utilized for precision medicine.

BACKGROUND: Vaginal microbiota (VMB) composition is altered in women with cervical intra-epithelial neoplasia (CIN) compared to healthy controls and is associated with disease progression. However, the impact of CIN excision on the VMB and innate immunity is not known. This observational study aims to explore the impact of CIN excision on the VMB, antimicrobial peptides (AMP) and proinflammatory cytokines. METHODS: We sampled 103 non-pregnant, premenopausal women at the time of excisional treatment for CIN and at their 6-month follow-up visit. A further 39 untreated controls with normal cytology were also sampled. We used metataxonomics to group vaginal swab samples into community state types (CSTs) and ELISA to quantify cytokine and AMP levels in matched vaginal secretions. Analyses were performed to compare the bacterial composition and immune analyte levels before and after CIN excision and in healthy controls. RESULTS: Women with CIN had significantly higher rates of Lactobacillus species depletion pre-treatment compared to healthy controls (CST IV 21/103, 20% vs 1/39, 3%, p = 0.0081). Excision did not change the VMB composition, with CST IV remaining significantly more prevalent after excision compared to untreated, healthy controls (CST IV 19/103, 20% vs 1/39, 3%, p = 0.0142). Prevotella bivia and Sneathia amnii were significantly higher in samples before treatment compared to untreated controls, and Prevotella bivia remained significantly higher amongst the treated, with less Lactobacillus crispatus compared to untreated controls. IL-1β and IL-8 remained significantly elevated pre- (p < 0.0001 and p = 0.0014, respectively) and post-treatment (p < 0.0001 and p = 0.0035, respectively) compared to untreated controls. Levels of human beta-defensin-1 and secretory leukocyte protease inhibitor were both significantly reduced following CIN excision (p < 0.0001); however, their levels remained lower than controls post-treatment. CONCLUSIONS: Women with CIN have an increased prevalence of Lactobacillus sp. depletion, high-diversity VMB composition, and higher levels of proinflammatory cytokines and AMPs compared to normal controls. Surgical excision of the disease reduces levels of vaginal AMPs but does not alter VMB composition or cytokine levels. These findings suggest that women with CIN have an inherent predisposition to a high-diversity proinflammatory environment that is not corrected by disease excision. The failure to re-establish a Lactobacillus-enriched CST may explain why women remain at high risk of pre-invasive and invasive disease recurrence.

BACKGROUND: The human leukocyte antigen class I (HLA-I) genotype has been linked with differential immune responses to infectious disease and cancer. However, the clinical relevance of germline HLA-mediated immunity in gastrointestinal (GI) cancer remains elusive. METHODS: This study retrospectively analyzed the genomic profiling data from 84 metastatic GI cancer patients treated with immune checkpoint blockade (ICB) recruited from Peking University Cancer Hospital (PUCH). A publicly available dataset from the Memorial Sloan Kettering (MSK) Cancer Center (MSK GI cohort) was employed as the validation cohort. For the PUCH cohort, we performed HLA genotyping by whole exome sequencing (WES) analysis on the peripheral blood samples from all patients. Tumor tissues from 76 patients were subjected to WES analysis and immune oncology-related RNA profiling. We studied the associations of two parameters of germline HLA as heterozygosity and evolutionary divergence (HED, a quantifiable measure of HLA-I evolution) with the clinical outcomes of patients in both cohorts. RESULTS: Our data showed that neither HLA heterozygosity nor HED at the HLA-A/HLA-C locus correlated with the overall survival (OS) in the PUCH cohort. Interestingly, in both the PUCH and MSK GI cohorts, patients with high HLA-B HED showed a better OS compared with low HLA-B HED subgroup. Of note, a combinatorial biomarker of HLA-B HED and tumor mutational burden (TMB) may better stratify potential responders. Furthermore, patients with high HLA-B HED were characterized with a decreased prevalence of multiple driver gene mutations and an immune-inflamed phenotype. CONCLUSIONS: Our results unveil how HLA-B evolutionary divergence influences the ICB response in patients with GI cancers, supporting its potential utility as a combinatorial biomarker together with TMB for patient stratification in the future.

We discuss the current state of genomic medicine in Arab countries of the Middle East, a region with outsized contribution to Mendelian genetics due to inbreeding yet has poor representation in global variome datasets. We focus on genomic testing, clinical genetics, and genetic counseling services along with associated training and research programs. Finally, we highlight opportunities for improvement in genomic medicine services in this region.

BACKGROUND: N6-methyladenosine (m6A) is the most abundant modification of RNA in eukaryotic cells and play critical roles in cancer. While most related studies focus on m6A modifications in linear RNA, transcriptome-wide profiling and exploration of m6A modification in circular RNAs in cancer is still lacking. METHODS: For the detection of m6A modification in circRNAs, we developed a new bioinformatics tools called Circm6A and applied it to the m6A-seq data of 77 tissue samples from 58 individuals with pancreatic ductal adenocarcinoma (PDAC). RESULTS: Circm6A performs better than the existing circRNA identification tools, which achieved highest F1 score among these tools in the detection of circRNAs with m6A modifications. By using Circm6A, we identified a total of 8807 m6A-circRNAs from our m6A-seq data. The m6A-circRNAs tend to be hypermethylated in PDAC tumor tissues compared with normal tissues. The hypermethylated m6A-circRNAs were associated with a significant gain of circRNA-mRNA coexpression network, leading to the dysregulation of many important cancer-related pathways. Moreover, we found the cues that hypermethylated m6A-circRNAs may promote the circularization and translation of circRNAs. CONCLUSIONS: These comprehensive findings further bridged the knowledge gaps between m6A modification and circRNAs fields by depicting the m6A-circRNAs genomic landscape of PDAC patients and revealed the emerging roles played by m6A-circRNAs in pancreatic cancer. Circm6A is available at https://github.com/canceromics/circm6a .

BACKGROUND: Clinical metagenomics (CMg) has the potential to be translated from a research tool into routine service to improve antimicrobial treatment and infection control decisions. The SARS-CoV-2 pandemic provides added impetus to realise these benefits, given the increased risk of secondary infection and nosocomial transmission of multi-drug-resistant (MDR) pathogens linked with the expansion of critical care capacity. METHODS: CMg using nanopore sequencing was evaluated in a proof-of-concept study on 43 respiratory samples from 34 intubated patients across seven intensive care units (ICUs) over a 9-week period during the first COVID-19 pandemic wave. RESULTS: An 8-h CMg workflow was 92% sensitive (95% CI, 75-99%) and 82% specific (95% CI, 57-96%) for bacterial identification based on culture-positive and culture-negative samples, respectively. CMg sequencing reported the presence or absence of β-lactam-resistant genes carried by Enterobacterales that would modify the initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus from 4 positive and 39 negative samples. Molecular typing using 24-h sequencing data identified an MDR-K. pneumoniae ST307 outbreak involving 4 patients and an MDR-C. striatum outbreak involving 14 patients across three ICUs. CONCLUSION: CMg testing provides accurate pathogen detection and antibiotic resistance prediction in a same-day laboratory workflow, with assembled genomes available the next day for genomic surveillance. The provision of this technology in a service setting could fundamentally change the multi-disciplinary team approach to managing ICU infections. The potential to improve the initial targeted treatment and rapidly detect unsuspected outbreaks of MDR-pathogens justifies further expedited clinical assessment of CMg.

Author information: (1)Montreal Heart Institute Research Centre, 5000 rue Bélanger, S-6201, Montreal, Quebec, Canada. (2)Université de Montréal, Montreal, Quebec, Canada. (3)Massachusetts General Hospital, Boston, MA, USA. (4)The Broad Institute, Cambridge, MA, USA. (5)Montreal Heart Institute Research Centre, 5000 rue Bélanger, S-6201, Montreal, Quebec, Canada. John.david.rioux@umontreal.ca. (6)Université de Montréal, Montreal, Quebec, Canada. John.david.rioux@umontreal.ca. (#)Contributed equally

Mutational signatures are key to understanding the processes that shape cancer genomes, yet their analysis requires relatively rich whole-genome or whole-exome mutation data. Recently, orders-of-magnitude sparser gene-panel-sequencing data have become increasingly available in the clinic. To deal with such sparse data, we suggest a novel mixture model, Mix. In application to simulated and real gene-panel sequences, Mix is shown to outperform current approaches and yield mutational signatures and patient stratifications that are in higher agreement with the literature. We further demonstrate its utility in several clinical settings, successfully predicting therapy benefit and patient groupings from MSK-IMPACT pan-cancer data. Availability: https://github.com/itaysason/Mix-MMM .