Featured
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Article
| Open Access
Data-driven grading of acute graft-versus-host disease
Acute GVHD severity grading is based on target organ assessments. Here, the authors show that data-driven grading can identify 12 distinct grades with specific aGVHD phenotypes, which are associated with clinical outcomes, and that their method outperformed conventional gradings.
- Evren Bayraktar
- , Theresa Graf
- & Amin T. Turki
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Article
| Open Access
Reconstructing disease dynamics for mechanistic insights and clinical benefit
Understanding disease progression dynamics is critical for diagnostics and treatment, but capturing dynamics is difficult. Here, the authors present a method for modelling disease progression from high dimensional molecular data that enables patient stratification and high-risk disease state identification, showcased in bladder cancer.
- Amit Frishberg
- , Neta Milman
- & Shai S. Shen-Orr
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| Open Access
Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients
Despite rapid and significant changes during the pandemic, prognostic models for COVID-19 patients do not currently account for data drifts. Here, the authors develop a framework for continuously monitoring and updating prognostic models and applied it to predict 28-day survival in COVID-19 patients.
- Todd J. Levy
- , Kevin Coppa
- & Theodoros P. Zanos
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Article
| Open Access
A lncRNA signature associated with tumor immune heterogeneity predicts distant metastasis in locoregionally advanced nasopharyngeal carcinoma
Long noncoding RNAs (lncRNAs) can be used for the development of prognostic signatures to predict tumour metastasis. Here the authors identify an immune-associated nine-lncRNA signature for predicting metastasis in a multicentre cohort of locoregionally advanced nasopharyngeal cancer patients.
- Ye-Lin Liang
- , Yuan Zhang
- & Na Liu
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Article
| Open Access
Deep neural network-estimated electrocardiographic age as a mortality predictor
The electrocardiogram (ECG) is the most commonly used exam for the screening and evaluation of cardiovascular diseases. Here, the authors propose that the age predicted by artificial intelligence from the raw ECG tracing can be a measure of cardiovascular health and provide prognostic information.
- Emilly M. Lima
- , Antônio H. Ribeiro
- & Antonio Luiz P. Ribeiro
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| Open Access
A community approach to mortality prediction in sepsis via gene expression analysis
Sepsis is characterized by deregulated host response to infection. Efficient therapies are still needed but a limitation for sepsis treatment is the heterogeneity in patients. Here Sweeney et al. generate prognostic models based on gene expression to improve risk stratification classification and prediction for 30-day mortality of patients.
- Timothy E. Sweeney
- , Thanneer M. Perumal
- & Raymond J. Langley
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Article
| Open Access
Rare disruptive mutations and their contribution to the heritable risk of colorectal cancer
The genetic factors that predispose individuals to familial colorectal cancer are poorly understood. In this study, the authors use whole exome sequencing of 1,006 patients and 1,609 healthy controls and show it is unlikely that further major high-penetrance susceptibility genes exist.
- Daniel Chubb
- , Peter Broderick
- & Richard S. Houlston
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Article
| Open Access
Early role of vascular dysregulation on late-onset Alzheimer’s disease based on multifactorial data-driven analysis
Late-onset Alzheimer's disease (LOAD) is a complex multi-factorial disorder. Here, the authors perform a data-driven analysis of LOAD progression, including multimodal brain imaging, plasma and CSF biomarkers, and find vascular dysfunction is among the earliest and strongest altered events.
- Y. Iturria-Medina
- , R. C. Sotero
- & Ansgar J. Furst
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Article
| Open Access
A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC
APC is a well-known tumour suppressor that is frequently inactivated in colorectal cancer. Here, the authors sequence more than 1000 cancer genes in 468 colorectal cancers and show that mutation signatures can be used to classify the tumours and that multiple mutations in APCare associated with a poor prognosis.
- Michael J. Schell
- , Mingli Yang
- & Timothy J. Yeatman
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Article
| Open Access
SURVIV for survival analysis of mRNA isoform variation
Clinical RNA-seq datasets can predict clinical outcomes. Here, Shen et al. report a statistical method for survival analysis of mRNA isoform variation using clinical RNA-seq datasets, and the identified isoform based survival predictors outperform gene expression based survival predictors using TCGA data on six cancer types.
- Shihao Shen
- , Yuanyuan Wang
- & Yi Xing
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Article
| Open Access
The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes
Much effort has recently been devoted to understanding the genomics of breast cancer. In this study, the authors integrate somatic mutation data with previously published copy number aberration and gene expression information for nearly 2,500 breast cancer samples.
- Bernard Pereira
- , Suet-Feung Chin
- & Carlos Caldas
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Article
| Open Access
Integrative analysis of breast cancer reveals prognostic haematopoietic activity and patient-specific immune response profiles
Tumour samples are heterogeneous and are comprised of multiple cell types in addition to cancer cells. Here, the authors devised a method to estimate the relative levels of haematopoietic cells in breast cancer samples and demonstrate that this correlates with prognosis.
- Frederick S. Varn
- , Erik H. Andrews
- & Chao Cheng
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Article
| Open Access
A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma
Using molecular markers is a useful way to predict the prognosis of cancer patients. Here, Wei et al.describe a five gene methylation signature that can predict the prognosis of renal clear cell cancer and validate its use in multiple patient cohorts.
- Jin-Huan Wei
- , Ahmed Haddad
- & Jun-Hang Luo
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| Open Access
Integrated genetic and epigenetic analysis defines novel molecular subgroups in rhabdomyosarcoma
Rhabdomyosarcoma is a common childhood soft-tissue cancer. Here Seki and Nishimura analyse the exome, transcriptome, copy number and DNA methylome of 60 sarcomas and identify distinct methylation subgroups associated with genetic and clinical features.
- Masafumi Seki
- , Riki Nishimura
- & Junko Takita
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APOBEC family mutational signatures are associated with poor prognosis translocations in multiple myeloma
Rearrangements of the Ig loci are essential for generating antibody diversity but abnormal translocations can be a driving event for myeloma. Here Walker et al. perform whole exome sequencing on myeloma patients to capture the diversity of mutational changes.
- Brian A. Walker
- , Christopher P. Wardell
- & Gareth J. Morgan
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Genomic landscape of paediatric adrenocortical tumours
Pediatric adrenocortical carcinoma is a rare malignancy with poor prognosis. Here the authors analyse the genomes, exomes and transcriptomes of 37 such tumours and identify genetic alterations whose nature, timing and potential interactions are key events with prognostic significance in pediatric adrenocortical tumorigenesis.
- Emilia M. Pinto
- , Xiang Chen
- & Gerard P. Zambetti
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Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value
Triple-negative breast cancers (TNBCs) are a heterogeneous group of cancers with varying prognoses. Here, the authors carry out whole-genome methylation capture sequencing from TNBC samples and matched normal samples, and identify differentially methylated regions that define a potentially novel TNBC signature.
- Clare Stirzaker
- , Elena Zotenko
- & Susan J. Clark
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Somatic mutations in arachidonic acid metabolism pathway genes enhance oral cancer post-treatment disease-free survival
Chemical inhibitors of the tumour-progression promoting arachidonic acid metabolism pathway prolong post-treatment survival of cancer patients. Here the authors analyse sequence variation in oral cancer patients and show that loss-of-function mutations in this pathway prolong survival.
- Nidhan K. Biswas
- , Subrata Das
- & Partha P. Majumder
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Integrated Omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact
Lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) are the two major subtypes of lung cancer. Here the authors integrate omic data sets, including gene copy number, mRNA expression and proteomics, to identify subtype-specific molecular signatures and candidate drivers linked to ADC and SCC.
- Lei Li
- , Yuhong Wei
- & Michael F. Moran
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Dynamic analyses of alternative polyadenylation from RNA-seq reveal a 3′-UTR landscape across seven tumour types
Alternative polyadenylation (APA) has been implicated in diverse physiological and pathological conditions including cancer. The authors present a new algorithm, DaPars, for APA analysis using available RNA-seq data and suggest CstF64 as a master regulator of 3′-UTR shortening across multiple tumour types.
- Zheng Xia
- , Lawrence A. Donehower
- & Wei Li
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Hypoxia promotes stem cell phenotypes and poor prognosis through epigenetic regulation of DICER
Reduced expression of DICER—responsible for the processing of microRNA precursors—was previously linked to poor clinical outcomes in cancer patients. Here, the authors uncover an epigenetic mechanism by which hypoxia suppresses DICER expression and deregulates the miR-200-Zeb1 circuit in breast cancer to promote the tumour phenotype.
- Twan van den Beucken
- , Elizabeth Koch
- & Bradly G. Wouters
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Article
| Open Access
2q36.3 is associated with prognosis for oestrogen receptor-negative breast cancer patients treated with chemotherapy
Studies have shown that breast cancer prognosis is hereditary. Here the authors show that a genetic variant in CCL20, a chemokine ligand involved in immune response, is significantly associated with breast cancer survival and may therefore represent an important therapeutic or prognostic target.
- Jingmei Li
- , Linda S. Lindström
- & Kamila Czene
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Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types
Many studies provide evidence of genes that are associated with cancer prognosis but a global view of these genes is lacking. Using data from ‘The Cancer Genome Atlas’, Yang et al.investigate the network properties of prognostic genes and show that these genes tend to be within highly interconnected groups but not the most connected nodes in the gene co-expression network.
- Yang Yang
- , Leng Han
- & Han Liang
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| Open Access
Low paternal dietary folate alters the mouse sperm epigenome and is associated with negative pregnancy outcomes
Paternal diet has been shown to influence the metabolism of offspring in rats and mice. Here Lambrot et al.report DNA and histone methylation changes in the sperm of male mice on a folate-deficient diet and observe developmental defects in their offspring.
- R. Lambrot
- , C. Xu
- & S. Kimmins
Systematic analysis of ChatGPT, Google search and Llama 2 for clinical decision support tasks