4,987 research outputs found

    Divergent mutational processes distinguish hypoxic and normoxic tumours

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    Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer

    Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

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    This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987

    The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

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    The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma

    The effective nature of projective techniques in political brand image research

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    This study explores the effectiveness of qualitative projective techniques to explore the corporate political brand image of Pakistan Tehreek-I-Insaf party [PTI] from a multiple-stakeholder perspective. This study addresses core gaps in projective techniques research of eliciting responses from a large cross-section of multiple stakeholders in varied non-western contexts. A qualitative interpretivist approach was adopted. More specifically, expressive projective techniques were embedded within focus group discussions. Nine focus group discussions (comprising 37 participants) were carried out in Karachi and Lahore (Pakistan) from June to November 2020. Each focus group lasted 60 to 90 minutes. A six-phased contextualist thematic analytical approach was employed to interpret the findings generated from the projective techniques and subsequent discussions. Projective techniques were established as an efficient and effective tool for exploring corporate political brand image research in Pakistan. The leadership element of the corporate political brand trinity was revealed to be larger than policies and party and it had both positive associations as well as being perceived as opportunistic. Policies were associated with dissatisfaction and incompetence whereas, the party element of the brand was viewed as ineffective and a subordinate brand. This study addresses explicit calls for further insights and research on the use of projective techniques in dynamic contexts and settings. In addition, this research adds to the limited understanding of the choice of stimuli and appraisal of projective techniques. Finally, this study provides a systematic ten-step guide entitled the projective techniques toolkit which outlines how to successfully conduct research using projective techniques. This research and developed toolkit will benefit practitioners and academics alike

    Integrative pathway enrichment analysis of multivariate omics data

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    Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations

    Acceptability and retention of the key population‐led HIV treatment service for men who have sex with men and transgender women living with HIV in Thailand

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    Abstract Introduction In Thailand, where the HIV epidemic is concentrated among key populations (KPs), particularly men who have sex with men (MSM) and transgender women (TGW), an HIV service delivery model tailored to KPs was piloted. This study evaluated the acceptability and retention of clients who accepted and declined the KP‐led HIV treatment service. Methods A retrospective cohort study was conducted using secondary data from three community‐based organizations (CBOs) and three hospitals in Thailand. KP lay providers were trained to lead HIV treatment service in which MSM and TGW living with HIV received counselling and a 3‐month antiretroviral therapy (ART) supply at CBOs. Thai MSM and TGW who were at least 18 years, on ART for at least 6–12 months, without co‐morbidities/co‐infections, and virally suppressed were eligible and offered the service. Those who declined received ART via other service models offered by the hospitals and served as a comparison group. Results Of 220 clients screened between February 2019 and February 2020, 72% (159/220) were eligible of which 146 were MSM and 13 were TGW. Overall, 45% (72/159) accepted the KP‐led service. Of those who declined, 98% (85/87) preferred to see the physician at the hospital. After 12 months of follow‐up, among those accepted, 57% were in care at the CBO, 32% were referred back to and in care in other service models offered by the hospital, 10% were successfully transferred out to other hospital and 1% were lost to follow‐up (LTFU); among those declined, 92% were in care in any service models offered by the hospital, 5% were successfully transferred out to other hospital, 2% were LTFU and 1% died (p‐value<0.001). Conclusions Despite moderate acceptability and retention in care at the CBO among the clients accepting the KP‐led service, almost all clients were engaged in care overall. Multiple service models that meet the preferences and needs of KPs living with HIV should be available to optimize engagement in care

    The evolution of lung cancer and impact of subclonal selection in TRACERx

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    Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

    Negative selection in tumor genome evolution acts on essential cellular functions and the immunopeptidome.

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    BACKGROUND: Natural selection shapes cancer genomes. Previous studies used signatures of positive selection to identify genes driving malignant transformation. However, the contribution of negative selection against somatic mutations that affect essential tumor functions or specific domains remains a controversial topic. RESULTS: Here, we analyze 7546 individual exomes from 26 tumor types from TCGA data to explore the portion of the cancer exome under negative selection. Although we find most of the genes neutrally evolving in a pan-cancer framework, we identify essential cancer genes and immune-exposed protein regions under significant negative selection. Moreover, our simulations suggest that the amount of negative selection is underestimated. We therefore choose an empirical approach to identify genes, functions, and protein regions under negative selection. We find that expression and mutation status of negatively selected genes is indicative of patient survival. Processes that are most strongly conserved are those that play fundamental cellular roles such as protein synthesis, glucose metabolism, and molecular transport. Intriguingly, we observe strong signals of selection in the immunopeptidome and proteins controlling peptide exposition, highlighting the importance of immune surveillance evasion. Additionally, tumor type-specific immune activity correlates with the strength of negative selection on human epitopes. CONCLUSIONS: In summary, our results show that negative selection is a hallmark of cell essentiality and immune response in cancer. The functional domains identified could be exploited therapeutically, ultimately allowing for the development of novel cancer treatments
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