BACKGROUND: Rare diseases collectively affect up to 10% of the population, but often lack effective treatment, and typically little is known about their pathophysiology. Major challenges include suboptimal phenotype mapping and limited statistical power. Population biobanks, such as the UK Biobank, recruit many individuals who can be affected by rare diseases; however, investigation into their utility for rare disease research remains limited. We hypothesized the UK Biobank can be used as a unique population assay for rare diseases in the general population. METHODS: We constructed a consensus mapping between ICD-10 codes and ORPHA codes for rare diseases, then identified individuals with each rare condition in the UK Biobank, and investigated their age at recruitment, sex bias, and comorbidity distributions. Using exome sequencing data from 167,246 individuals of European ancestry, we performed genetic association controlling for case/control imbalance (SAIGE) to identify potential rare pathogenic variants for each disease. RESULTS: Using our mapping approach, we identified and characterized 420 rare diseases affecting 23,575 individuals in the UK Biobank. Significant genetic associations included JAK2 V617F for immune thrombocytopenic purpura (p = 1.24 × 10-13) and a novel CALR loss of function variant for essential thrombocythemia (p = 1.59 × 10-13). We constructed an interactive resource highlighting demographic information ( http://www-personal.umich.edu/~mattpat/rareDiseases.html ) and demonstrate transferability by applying our mapping to a medical claims database. CONCLUSIONS: Enhanced disease mapping and increased power from population biobanks can elucidate the demographics and genetic associations for rare diseases.

Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular features that drive malignancies. Precision medicine has exploited next-generation sequencing and matched targeted therapy/immunotherapy deployment to successfully transform the outlook for several fatal cancers. Tumor and liquid biopsy genomic profiling and transcriptomic, immunomic, and proteomic interrogation can now all be leveraged to optimize therapy. Multiple new trial designs, including basket and umbrella trials, master platform trials, and N-of-1 patient-centric studies, are beginning to supplant standard phase I, II, and III protocols, allowing for accelerated drug evaluation and approval and molecular-based individualized treatment. Furthermore, real-world data, as well as exploitation of digital apps and structured observational registries, and the utilization of machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials have evolved, shifting from tumor type-centered to gene-directed and histology-agnostic trials, with innovative adaptive designs and personalized combination treatment strategies tailored to individual biomarker profiles. Some, but not all, novel trials now demonstrate that matched therapy correlates with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To further improve the precision medicine paradigm, the strategy of matching drugs to patients based on molecular features should be implemented earlier in the disease course, and cancers should have comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) tumor profiling. To overcome cancer complexity, moving from drug-centric to patient-centric individualized combination therapy is critical. This review focuses on the design, advantages, limitations, and challenges of a spectrum of clinical trial designs in the era of precision oncology.

Comment in Trends Cancer. 2022 Dec;8(12):973-975.

BACKGROUND: Central conventional chondrosarcoma (CS) is the most common subtype of primary malignant bone tumour in adults. Treatment options are usually limited to surgery, and prognosis is challenging. These tumours are characterised by the presence and absence of IDH1 and IDH2 mutations, and recently, TERT promoter alterations have been reported in around 20% of cases. The effect of these mutations on clinical outcome remains unclear. The purpose of this study was to determine if prognostic accuracy can be improved by the addition of genomic data, and specifically by examination of IDH1, IDH2, and TERT mutations. METHODS: In this study, we combined both archival samples and data sourced from the Genomics England 100,000 Genomes Project (n = 356). Mutations in IDH1, IDH2, and TERT were profiled using digital droplet PCR (n = 346), whole genome sequencing (n=68), or both (n = 64). Complex events and other genetic features were also examined, along with methylation array data (n = 84). We correlated clinical features and patient outcomes with our genetic findings. RESULTS: IDH2-mutant tumours occur in older patients and commonly present with high-grade or dedifferentiated disease. Notably, TERT mutations occur most frequently in IDH2-mutant tumours, although have no effect on survival in this group. In contrast, TERT mutations are rarer in IDH1-mutant tumours, yet they are associated with a less favourable outcome in this group. We also found that methylation profiles distinguish IDH1- from IDH2-mutant tumours. IDH wild-type tumours rarely exhibit TERT mutations and tend to be diagnosed in a younger population than those with tumours harbouring IDH1 and IDH2 mutations. A major genetic feature of this group is haploidisation and subsequent genome doubling. These tumours evolve less frequently to dedifferentiated disease and therefore constitute a lower risk group. CONCLUSIONS: Tumours with IDH1 or IDH2 mutations or those that are IDHwt have significantly different genetic pathways and outcomes in relation to TERT mutation. Diagnostic testing for IDH1, IDH2, and TERT mutations could therefore help to guide clinical monitoring and prognostication.

BACKGROUND: Small intestinal neuroendocrine tumors (SI-NETs) are the most common neoplasms of the small bowel. The majority of tumors are located in the distal ileum with a high incidence of multiple synchronous primary tumors. Even though up to 50% of SI-NET patients are diagnosed with multifocal disease, the mechanisms underlying multiple synchronous lesions remain elusive. METHODS: We performed whole genome sequencing of 75 de-identified synchronous primary tumors, 15 metastases, and corresponding normal samples from 13 patients with multifocal ileal NETs to identify recurrent somatic genomic alterations, frequently affected signaling pathways, and shared mutation signatures among multifocal SI-NETs. Additionally, we carried out chromosome mapping of the most recurrent copy-number alterations identified to determine which parental allele had been affected in each tumor and assessed the clonal relationships of the tumors within each patient. RESULTS: Absence of shared somatic variation between the synchronous primary tumors within each patient was observed, indicating that these tumors develop independently. Although recurrent copy-number alterations were identified, additional chromosome mapping revealed that tumors from the same patient can gain or lose different parental alleles. In addition to the previously reported CDKN1B loss-of-function mutations, we observed potential loss-of-function gene alterations in TNRC6B, a candidate tumor suppressor gene in a small subset of ileal NETs. Furthermore, we show that multiple metastases in the same patient can originate from either one or several primary tumors. CONCLUSIONS: Our study demonstrates major genomic diversity among multifocal ileal NETs, highlighting the need to identify and remove all primary tumors, which have the potential to metastasize, and the need for optimized targeted treatments.

BACKGROUND: The "HER2-low" nomenclature identifies breast carcinomas (BCs) displaying a HER2 score of 1+/2+ in immunohistochemistry and lacking ERBB2 amplification. Whether HER2-low BCs (HLBCs) constitute a distinct entity is debated. METHODS: We performed DNA and RNA high-throughput analysis on 99 HLBC samples (n = 34 cases with HER2 score 1+/HLBC-1, n = 15 cases with HER2 score 2+ and ERBB2 not amplified/HLBC-2N, and n = 50 cases with score 2+ and ERBB2 copy number in the equivocal range/HLBC-2E). We compared the mutation rates with data from 1317 samples in the Memorial Sloan-Kettering Cancer Center (MSKCC) BC cohort and gene expression data with those from an internal cohort of HER2-negative and HER2-positive BCs. RESULTS: The most represented mutations affected PIK3CA (31/99, 31%), GATA3 (18/99, 18%), TP53 (17/99, 17%), and ERBB2 (8/99, 8%, private to HLBC-2E). Tumor mutational burden was significantly higher in HLBC-1 compared to HLBC-2E/N (P = 0.04). Comparison of mutation spectra revealed that HLBCs were different from both HER2-negative and HER2-positive BCs, with HLBC-1 resembling more HER2-negative tumors and HLBC-2 mutationally related to HER2-addicted tumors. Potentially actionable alterations (annotated by using OncoKB/ESCAT classes) affected 52 patients. Intra-group gene expression revealed overlapping features between HLBC-1 and control HER2-negative BCs, whereas the HLBC-2E tumors showed the highest diversity overall. The RNA-based class discovery analysis unveiled four subsets of tumors with (i) lymphocyte activation, (ii) unique enrichment in HER2-related features, (iii) stromal remodeling alterations, and (iv) actionability of PIK3CA mutations (LAURA classification). CONCLUSIONS: HLBCs harbor distinct genomic features when compared with HER2-positive and HER2-negative BCs; however, differences across IHC classes were also unveiled thus dissecting the full picture of heterogeneity across HER2-low disease. The HLBC-2E category harbors most distinctive features, whereas HLBC-1 seems superimposable to HER2-negative disease. Further studies are needed to ascertain whether the four genomic-driver classes of the LAURA classification hold prognostic and/or predictive implications.

BACKGROUND: Resistance to third-generation cephalosporins, often mediated by extended-spectrum beta-lactamases (ESBLs), is a considerable issue in hospital-associated infections as few drugs remain for treatment. ESBL genes are often located on large plasmids that transfer horizontally between strains and species of Enterobacteriaceae and frequently confer resistance to additional drug classes. Whilst plasmid transmission is recognised to occur in the hospital setting, the frequency and impact of plasmid transmission on infection burden, compared to ESBL + strain transmission, is not well understood. METHODS: We sequenced the genomes of clinical and carriage isolates of Klebsiella pneumoniae species complex from a year-long hospital surveillance study to investigate ESBL burden and plasmid transmission in an Australian hospital. Long-term persistence of a key transmitted ESBL + plasmid was investigated via sequencing of ceftriaxone-resistant isolates during 4 years of follow-up, beginning 3 years after the initial study. RESULTS: We found 25 distinct ESBL plasmids. We identified one plasmid, which we called Plasmid A, that carried blaCTX-M-15 in an IncF backbone similar to pKPN-307. Plasmid A was transmitted at least four times into different Klebsiella species/lineages and was responsible for half of all ESBL episodes during the initial 1-year study period. Three of the Plasmid A-positive strains persisted locally 3-6 years later, and Plasmid A was detected in two additional strain backgrounds. Overall Plasmid A accounted for 21% of ESBL + infections in the follow-up period. CONCLUSIONS: Here, we systematically surveyed ESBL strain and plasmid transmission over 1 year in a single hospital network. Whilst ESBL plasmid transmission events were rare in this setting, they had a significant and sustained impact on the burden of ceftriaxone-resistant and multidrug-resistant infections. If onward transmission of Plasmid A-carrying strains could have been prevented, this may have reduced the number of opportunities for Plasmid A to transmit and create novel ESBL + strains, as well as reducing overall ESBL infection burden.

Author information: (1)Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany. (2)German Center for Infection Research (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany. (3)The Foundation for Medical Research, Mumbai, India. (4)Evolution of the Resistome, Research Center Borstel, Borstel, Germany. (5)CRyPTIC Consortium, Oxford, UK. (6)Department of Microbiology, P. D. Hinduja National Hospital and Medical Research Centre, Mumbai, India. (7)Nuffield Department of Medicine, University of Oxford, Oxford, UK. (8)Centre International de Recherche en Infectiologie, INSERM U1111, CNRS UMR5308, ENS Lyon, University of Lyon, Lyon, France. (9)Institut Des Agents Infectieux, Hospices Civils de Lyon, Lyon, France. (10)Institut de Systématique, Evolution, Biodiversité, UMR-CNRS 7205, Muséum National d'Histoire Naturelle, Université Pierre Et Marie Curie, Université Des Antilles, Ecole Pratique Des Hautes Etudes, Sorbonne Universités, Paris, France. (11)EPHE, PSL University, Paris, France. (12)Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany. sniemann@fz-borstel.de. (13)German Center for Infection Research (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany. sniemann@fz-borstel.de. (14)CRyPTIC Consortium, Oxford, UK. sniemann@fz-borstel.de. (#)Contributed equally

Since the start of the coronavirus disease 2019 (COVID-19) pandemic, important insights have been gained into virus biology and the host factors that modulate the human immune response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 displays a highly variable clinical picture that ranges from asymptomatic disease to lethal pneumonia. Apart from well-established general risk factors such as advanced age, male sex and chronic comorbidities, differences in host genetics have been shown to influence the individual predisposition to develop severe manifestations of COVID-19. These differences range from common susceptibility loci to rare genetic variants with strongly predisposing effects, or proven pathogenic variants that lead to known or novel inborn errors of immunity (IEI), which constitute a growing group of heterogeneous Mendelian disorders with increased susceptibility to infectious disease, auto-inflammation, auto-immunity, allergy or malignancies. The current genetic findings point towards a convergence of common and rare genetic variants that impact the interferon signalling pathways in patients with severe or critical COVID-19. Monogenic risk factors that impact IFN-I signalling have an expected prevalence between 1 and 5% in young, previously healthy individuals (<60 years of age) with critical COVID-19. The identification of these IEI such as X-linked TLR7 deficiency indicates a possibility for targeted genetic screening and personalized clinical management. This review aims to provide an overview of our current understanding of the host genetic factors that predispose to severe manifestations of COVID-19 and focuses on rare variants in IFN-I signalling genes and their potential clinical implications.

The cerebrospinal fluid (CSF) features a unique immune cell composition and is in constant contact with the brain borders, thus permitting insights into the brain to diagnose and monitor diseases. Recently, the meninges, which are filled with CSF, were identified as a neuroimmunological interface, highlighting the potential of exploring central nervous system (CNS) immunity by studying CNS border compartments. Here, we summarize how single-cell transcriptomics of such border compartments advance our understanding of neurological diseases, the challenges that remain, and what opportunities novel multi-omic methods offer. Single-cell transcriptomics studies have detected cytotoxic CD4+ T cells and clonally expanded T and B cells in the CSF in the autoimmune disease multiple sclerosis; clonally expanded pathogenic CD8+ T cells were found in the CSF and in the brain adjacent to β-amyloid plaques of dementia patients; in patients with brain metastases, CD8+ T cell clonotypes were shared between the brain parenchyma and the CSF and persisted after therapy. We also outline how novel multi-omic approaches permit the simultaneous measurements of gene expression, chromatin accessibility, and protein in the same cells, which remain to be explored in the CSF. This calls for multicenter initiatives to create single-cell atlases, posing challenges in integrating patients and modalities across centers. While high-dimensional analyses of CSF cells are challenging, they hold potential for personalized medicine by better resolving heterogeneous diseases and stratifying patients.

BACKGROUND: Colorectal cancer (CRC) ranks as the second-leading cause of cancer-related death worldwide with metastases being the main cause of cancer-related death. Here, we investigated the genomic and transcriptomic alterations in matching adjacent normal tissues, primary tumors, and metastatic tumors of CRC patients. METHODS: We performed whole genome sequencing (WGS), multi-region whole exome sequencing (WES), simultaneous single-cell RNA-Seq, and single-cell targeted cDNA Sanger sequencing on matching adjacent normal tissues, primary tumors, and metastatic tumors from 12 metastatic colorectal cancer patients (n=84 for genomes, n=81 for exomes, n=9120 for single cells). Patient-derived tumor organoids were used to estimate the anti-tumor effects of a PPAR inhibitor, and self-renewal and differentiation ability of stem cell-like tumor cells. RESULTS: We found that the PPAR signaling pathway was prevalently and aberrantly activated in CRC tumors. Blocking of PPAR pathway both suppressed the growth and promoted the apoptosis of CRC organoids in vitro, indicating that aberrant activation of the PPAR signaling pathway plays a critical role in CRC tumorigenesis. Using matched samples from the same patient, distinct origins of the metastasized tumors between lymph node and liver were revealed, which was further verified by both copy number variation and mitochondrial mutation profiles at single-cell resolution. By combining single-cell RNA-Seq and single-cell point mutation identification by targeted cDNA Sanger sequencing, we revealed important phenotypic differences between cancer cells with and without critical point mutations (KRAS and TP53) in the same patient in vivo at single-cell resolution. CONCLUSIONS: Our data provides deep insights into how driver mutations interfere with the transcriptomic state of cancer cells in vivo at a single-cell resolution. Our findings offer novel knowledge on metastatic mechanisms as well as potential markers and therapeutic targets for CRC diagnosis and therapy. The high-precision single-cell RNA-seq dataset of matched adjacent normal tissues, primary tumors, and metastases from CRCs may serve as a rich resource for further studies.

BACKGROUND: Genetic testing (GT) for hereditary cancer predisposition is traditionally performed on selected genes based on established guidelines for each cancer type. Recently, expanded GT (eGT) using large hereditary cancer gene panels uncovered hereditary predisposition in a greater proportion of patients than previously anticipated. We sought to define the diagnostic yield of eGT and its clinical relevance in a broad cancer patient population over a 5-year period. METHODS: A total of 17,523 cancer patients with a broad range of solid tumors, who received eGT at Memorial Sloan Kettering Cancer Center between July 2015 to April 2020, were included in the study. The patients were unselected for current GT criteria such as cancer type, age of onset, and/or family history of disease. The diagnostic yield of eGT was determined for each cancer type. For 9187 patients with five common cancer types frequently interrogated for hereditary predisposition (breast, colorectal, ovarian, pancreatic, and prostate cancer), the rate of pathogenic/likely pathogenic (P/LP) variants in genes that have been associated with each cancer type was analyzed. The clinical implications of additional findings in genes not known to be associated with a patients' cancer type were investigated. RESULTS: 16.7% of patients in a broad cancer cohort had P/LP variants in hereditary cancer predisposition genes identified by eGT. The diagnostic yield of eGT in patients with breast, colorectal, ovarian, pancreatic, and prostate cancer was 17.5%, 15.3%, 24.2%, 19.4%, and 15.9%, respectively. Additionally, 8% of the patients with five common cancers had P/LP variants in genes not known to be associated with the patient's current cancer type, with 0.8% of them having such a variant that confers a high risk for another cancer type. Analysis of clinical and family histories revealed that 74% of patients with variants in genes not associated with their current cancer type but which conferred a high risk for another cancer did not meet the current GT criteria for the genes harboring these variants. One or more variants of uncertain significance were identified in 57% of the patients. CONCLUSIONS: Compared to targeted testing approaches, eGT can increase the yield of detection of hereditary cancer predisposition in patients with a range of tumors, allowing opportunities for enhanced surveillance and intervention. The benefits of performing eGT should be weighed against the added number of VUSs identified with this approach.

BACKGROUND: Crohn's disease (CD) patients demonstrate distinct intestinal microbial compositions and metabolic characteristics compared to unaffected controls. However, the impact of inflammation and underlying genetic risk on these microbial profiles and their relationship to disease phenotype are unclear. We used lavage sampling to characterize the colonic mucosal-luminal interface (MLI) microbiome of CD patients in endoscopic remission and unaffected controls relative to obesity, disease genetics, and phenotype. METHODS: Cecum and sigmoid colon were sampled from 110 non-CD controls undergoing screening colonoscopy who were stratified by body mass index and 88 CD patients in endoscopic remission (396 total samples). CD polygenic risk score (GRS) was calculated using 186 known CD variants. MLI pellets were analyzed by 16S ribosomal RNA gene sequencing, and supernatants by untargeted liquid chromatography-mass spectrometry. RESULTS: CD and obesity were each associated with decreased cecal and sigmoid MLI bacterial diversity and distinct bacterial composition compared to controls, including expansion of Escherichia/Shigella. Cecal and sigmoid dysbiosis indices for CD were significantly greater in obese controls than non-overweight controls. CD, but not obesity, was characterized by altered biogeographic relationship between the sigmoid and cecum. GRS was associated with select taxonomic shifts that overlapped with changes seen in CD compared to controls including Fusobacterium enrichment. Stricturing or penetrating Crohn's disease behavior was characterized by lower MLI bacterial diversity and altered composition, including reduced Faecalibacterium, compared to uncomplicated CD. Taxonomic profiles including reduced Parasutterella were associated with clinical disease progression over a mean follow-up of 3.7 years. Random forest classifiers using MLI bacterial abundances could distinguish disease state (area under the curve (AUC) 0.93), stricturing or penetrating Crohn's disease behavior (AUC 0.82), and future clinical disease progression (AUC 0.74). CD patients showed alterations in the MLI metabolome including increased cholate:deoxycholate ratio compared to controls. CONCLUSIONS: Obesity, CD in endoscopic remission, and high CD genetic risk have overlapping colonic mucosal-luminal interface (MLI) microbiome features, suggesting a shared microbiome contribution to CD and obesity which may be influenced by genetic factors. Microbial profiling during endoscopic remission predicted Crohn's disease behavior and progression, supporting that MLI sampling could offer unique insight into CD pathogenesis and provide novel prognostic biomarkers.

BACKGROUND: Lung cancer, one of the most common malignant tumors, exhibits high inter- and intra-tumor heterogeneity which contributes significantly to treatment resistance and failure. Single-cell RNA sequencing (scRNA-seq) has been widely used to dissect the cellular composition and characterize the molecular properties of cancer cells and their tumor microenvironment in lung cancer. However, the transcriptomic heterogeneity among various cancer cells in non-small cell lung cancer (NSCLC) warrants further illustration. METHODS: To comprehensively analyze the molecular heterogeneity of NSCLC, we performed high-precision single-cell RNA-seq analyses on 7364 individual cells from tumor tissues and matched normal tissues from 19 primary lung cancer patients and 1 pulmonary chondroid hamartoma patient. RESULTS: In 6 of 16 patients sequenced, we identified a significant proportion of cancer cells simultaneously expressing classical marker genes for two or even three histologic subtypes of NSCLC-adenocarcinoma (ADC), squamous cell carcinoma (SCC), and neuroendocrine tumor (NET) in the same individual cell, which we defined as mixed-lineage tumor cells; this was verified by both co-immunostaining and RNA in situ hybridization. These data suggest that mixed-lineage tumor cells are highly plastic with mixed features of different types of NSCLC. Both copy number variation (CNV) patterns and mitochondrial mutations clearly showed that the mixed-lineage and single-lineage tumor cells from the same patient had common tumor ancestors rather than different origins. Moreover, we revealed that patients with high mixed-lineage features of different cancer subtypes had worse survival than patients with low mixed-lineage features, indicating that mixed-lineage tumor features were associated with poorer prognosis. In addition, gene signatures specific to mixed-lineage tumor cells were identified, including AKR1B1. Gene knockdown and small molecule inhibition of AKR1B1 can significantly decrease cell proliferation and promote cell apoptosis, suggesting that AKR1B1 plays an important role in tumorigenesis and can serve as a candidate target for tumor therapy of NSCLC patients with mixed-lineage tumor features. CONCLUSIONS: In summary, our work provides novel insights into the tumor heterogeneity of NSCLC in terms of the identification of prevalent mixed-lineage subpopulations of cancer cells with combined signatures of SCC, ADC, and NET and offers clues for potential treatment strategies in these patients.

BACKGROUND: Genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only approach to rapidly monitor and tackle emerging variants of concern (VOC) of the COVID-19 pandemic. Such scrutiny is crucial to limit the spread of VOC that might escape the immune protection conferred by vaccination strategies or previous virus exposure. It is also becoming clear now that efficient genomic surveillance would require monitoring of the host gene expression to identify prognostic biomarkers of treatment efficacy and disease progression. Here we propose an integrative workflow to both generate thousands of SARS-CoV-2 genome sequences per week and analyze host gene expression upon infection. METHODS: In this study we applied an integrated workflow for RNA extracted from nasal swabs to obtain in parallel the full genome of SARS-CoV-2 and transcriptome of host respiratory epithelium. The RNA extracted from each sample was reverse transcribed and the viral genome was specifically enriched through an amplicon-based approach. The very same RNA was then used for patient transcriptome analysis. Samples were collected in the Campania region, Italy, for viral genome sequencing. Patient transcriptome analysis was performed on about 700 samples divided into two cohorts of patients, depending on the viral variant detected (B.1 or delta). RESULTS: We sequenced over 20,000 viral genomes since the beginning of the pandemic, producing the highest number of sequences in Italy. We thus reconstructed the pandemic dynamics in the regional territory from March 2020 to December 2021. In addition, we have matured and applied novel proof-of-principle approaches to prioritize possible gain-of-function mutations by leveraging patients' metadata and isolated patient-specific signatures of SARS-CoV-2 infection. This allowed us to (i) identify three new viral variants that specifically originated in the Campania region, (ii) map SARS-CoV-2 intrahost variability during long-term infections and in one case identify an increase in the number of mutations in the viral genome, and (iii) identify host gene expression signatures correlated with viral load in upper respiratory ways. CONCLUSION: In conclusion, we have successfully generated an optimized and cost-effective strategy to monitor SARS-CoV-2 genetic variability, without the need of automation. Thus, our approach is suitable for any lab with a benchtop sequencer and a limited budget, allowing an integrated genomic surveillance on premises. Finally, we have also identified a gene expression signature defining SARS-CoV-2 infection in real-world patients' upper respiratory ways.

BACKGROUND: The genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS-associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits. METHODS: To explore this scenario, we combined sex-specific whole blood RNA-seq eQTL data from 3447 European individuals included in BIOS Consortium and GWAS data from UK Biobank. Next, to test the presence of sex-biased causal effect of gene expression on complex traits, we performed sex-specific transcriptome-wide Mendelian randomization (TWMR) analyses on the two most sexually dimorphic traits, waist-to-hip ratio (WHR) and testosterone levels. Finally, we performed power analysis to calculate the GWAS sample size needed to observe sex-specific trait associations driven by sex-biased eQTLs. RESULTS: Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-biased cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-biased eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-biased trait-associations. In addition, we observed that sex-specific causal effects of gene expression on complex traits are not driven by sex-specific eQTLs. Power analyses using real eQTL- and causal-effect sizes showed that millions of samples would be necessary to observe sex-biased trait associations that are fully driven by sex-biased cis-eQTLs. Compensatory effects may further hamper their detection. CONCLUSIONS: Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations of complex diseases, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs.

BACKGROUND: Expansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads. RESULTS: We implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions and FlipBook, a companion image viewer designed for manual curation of large collections of REViewer images. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in short tandem repeat research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR. CONCLUSIONS: Read pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer and FlipBook to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions. REViewer and FlipBook are available under open-source licenses at https://github.com/illumina/REViewer and https://github.com/broadinstitute/flipbook respectively.

BACKGROUND: Subclonal evolution during primary breast cancer treatment is largely unexplored. We aimed to assess the dynamic changes in subclonal composition of treatment-naïve breast cancers during neoadjuvant chemotherapy. METHODS: We performed whole exome sequencing of tumor biopsies collected before, at therapy switch, and after treatment with sequential epirubicin and docetaxel monotherapy in 51 out of 109 patients with primary breast cancer, who were included in a prospectively registered, neoadjuvant single-arm phase II trial. RESULTS: There was a profound and differential redistribution of subclones during epirubicin and docetaxel treatment, regardless of therapy response. While truncal mutations and main subclones persisted, smaller subclones frequently appeared or disappeared. Reassessment of raw data, beyond formal mutation calling, indicated that the majority of subclones seemingly appearing during treatment were in fact present in pretreatment breast cancers, below conventional detection limits. Likewise, subclones which seemingly disappeared were still present, below detection limits, in most cases where tumor tissue remained. Tumor mutational burden (TMB) dropped during neoadjuvant therapy, and copy number analysis demonstrated specific genomic regions to be systematically lost or gained for each of the two chemotherapeutics. CONCLUSIONS: Sequential epirubicin and docetaxel monotherapy caused profound redistribution of smaller subclones in primary breast cancer, while early truncal mutations and major subclones generally persisted through treatment. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00496795 , registered on July 4, 2007.

BACKGROUND: The activation of the telomere maintenance mechanism (TMM) is one of the critical drivers of cancer cell immortality. In gliomas, TERT expression and TERT promoter mutation are considered to reliably indicate telomerase activation, while ATRX mutation and/or loss indicates an alternative lengthening of telomeres (ALT). However, these relationships have not been extensively validated in tumor tissues. METHODS: Telomerase repeated amplification protocol (TRAP) and C-circle assays were used to profile and characterize the TMM cross-sectionally (n = 412) and temporally (n = 133) across glioma samples. WES, RNA-seq, and NanoString analyses were performed to identify and validate the genetic characteristics of the TMM groups. RESULTS: We show through the direct measurement of telomerase activity and ALT in a large set of glioma samples that the TMM in glioma cannot be defined solely by the combination of telomerase activity and ALT, regardless of TERT expression, TERT promoter mutation, and ATRX loss. Moreover, we observed that a considerable proportion of gliomas lacked both telomerase activity and ALT. This telomerase activation-negative and ALT negative group exhibited evidence of slow growth potential. By analyzing a set of longitudinal samples from a separate cohort of glioma patients, we discovered that the TMM is not fixed and can change with glioma progression. CONCLUSIONS: This study suggests that the TMM is dynamic and reflects the plasticity and oncogenicity of tumor cells. Direct measurement of telomerase enzyme activity and evidence of ALT should be considered when defining TMM. An accurate understanding of the TMM in glioma is expected to provide important information for establishing cancer management strategies.