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Schneeberger, Kim, Geesdorf, Rajewsky, Heppner et al. tease IL-12 and IL-23 signaling apart in mouse models and human brain tissue to define a role for oligodendroglial and neuronal IL-12 signaling in neuroimmune crosstalk in Alzheimer’s disease.

It remains unclear whether machine learning methods can accurately identify cancer driver alterations. Here, the authors compare machine learning-based approaches to other computational methods to determine their utility for annotating variants of unknown significance and identifying driver alterations in real-world cancer patient data, demonstrating superior performance.

Comprehensive analyses of 178 lung squamous cell carcinomas by The Cancer Genome Atlas project show that the tumour type is characterized by complex genomic alterations, with statistically recurrent mutations in 11 genes, including TP53 in nearly all samples; a potential therapeutic target is identified in most of the samples studied.

This paper reports integrative molecular analyses of urothelial bladder carcinoma at the DNA, RNA, and protein levels performed as part of The Cancer Genome Atlas project; recurrent mutations were found in 32 genes, including those involved in cell-cycle regulation, chromatin regulation and kinase signalling pathways; chromatin regulatory genes were more frequently mutated in urothelial carcinoma than in any other common cancer studied so far.

A study generates a clinicogenomics dataset resource, MSK-CHORD, that combines natural language processing-derived clinical annotations with patient medical data from various sources to improve models of cancer outcome.

The genomic landscape of brain metastasis (BM) in patients with non-small cell lung cancer (NSCLC) remains to be explored. Here, the authors analyse a cohort of 233 patients with BM including 47 primary tumour, 42 extracranial metastatic matched samples and reveal distinct mutational patterns.

Analysis of pan-cancer clinical genomic sequencing finds that body mass index associates with driver mutations in certain cancer types, including most prominently lung adenocarcinoma. Obesity may thus influence tumor genetics.

Analysis of two large pan-cancer datasets highlights ancestry-specific differences in somatic alterations. These data argue for a more ancestry-sensitive approach to personalized medicine for patients with cancer.

AI models can extract clinical outcomes from electronic health records, but it is critical to ensure that such models preserve patient privacy. Here, the authors develop a teacher-student approach to produce shareable models for annotating cancer outcomes from imaging reports and oncologist notes while protecting patient privacy.

Ferber et al. present an autonomous artificial intelligence agent system for deployment of specialized medical oncology computational tools, validating their system across various clinical scenarios representative of typical patient care workflows.

The authors develop multimodal machine learning models to infer metastatic recurrence risk for early-stage, hormone receptor-positive breast cancer from H&E images using >6000 cases across three centers, outperforming a nomogram and unimodal methods.

The Cancer Genome Atlas Research Network report integrated genomic and molecular analyses of 164 squamous cell carcinomas and adenocarcinomas of the oesophagus; they find genomic and molecular features that differentiate squamous and adenocarcinomas of the oesophagus, and strong similarities between oesophageal adenocarcinomas and the chromosomally unstable variant of gastric adenocarcinoma, suggesting that gastroesophageal adenocarcinoma is a single disease entity.

An integrative genomic analysis of several hundred endometrial carcinomas shows that a minority of tumour samples carry copy number alterations or TP53 mutations and many contain key cancer-related gene mutations, such as those involved in canonical pathways and chromatin remodelling; a reclassification of endometrial tumours into four distinct types is proposed, which may have an effect on patient treatment regimes.

Analyses of clinical and genomic data from a cohort of 2,336 patients with pancreatic adenocarcinoma find that KRAS dosage gains are a hallmark of disease progression and are predictive of poor outcomes across different disease stages.

The Cancer Genome Atlas reports on molecular evaluation of 295 primary gastric adenocarcinomas and proposes a new classification of gastric cancers into 4 subtypes, which should help with clinical assessment and trials of targeted therapies.

An analysis of three multi-cancer cohorts shows that the detection of ctDNA using liquid biopsies has the potential to improve the risk prediction of cancer-associated venous thromboembolism.

An integrated transcriptome, genome, methylome and proteome analysis of over 200 lung adenocarcinomas reveals high rates of somatic mutations, 18 statistically significantly mutated genes including RIT1 and MGA, splicing changes, and alterations in MAPK and PI(3)K pathway activity.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Colitis-associated cancers (CACs) develop in patients with inflammatory bowel disease and have distinct genomic features compared to sporadic colorectal cancers. Here, the authors characterize the genomic alterations of CAC tumors and dysplasia, finding decreased Wnt signaling and a lack of shared early genetic steps.

In a prospective international cohort of 1,127 patients with non-small-cell lung cancer and ctDNA-guided therapy, ctDNA detection was associated with shorter survival, independently of clinicopathologic features and metabolic tumor volume.

Douglas Levine and colleagues identify recurrent inactivating mutations in the SWI/SNF complex member SMARCA4 in 12 of 12 samples of small cell carcinoma of the ovary, hypercalcemic type. These findings open the door for the development of targeted therapies to treat this rare but deadly cancer.

Walsh and colleagues use prospective sequencing in a large cohort of pediatric patients with solid tumors to detect mutations in cancer predisposition genes and guide downstream clinical care.

Understanding the molecular and phenotypic profile of colorectal cancer (CRC) in West Africa is important for early detection and treatment. Here, the authors use a multigene next-generation sequencing panel to identify genomic differences in Nigerian CRCs compared to those from TCGA and MSKCC cohorts.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

Cell lines are widely used in cancer research to study tumour biology. Here Domcke et al.compare genomic data from ovarian cancer cell lines with those from clinical ovarian tumour samples and identify cell lines that most closely resemble the genomic features of high-grade serous ovarian cancer.

The Cancer Genome Atlas Research Network reports an integrative analysis of more than 400 samples of clear cell renal cell carcinoma based on genomic, DNA methylation, RNA and proteomic characterisation; frequent mutations were identified in the PI(3)K/AKT pathway, suggesting this pathway might be a potential therapeutic target, among the findings is also a demonstration of metabolic remodelling which correlates with tumour stage and severity.

Cancer-associated fibroblasts are transcriptionally rewired by signals from the cancer cells, resulting in heterogeneous populations. Here the authors show that loss of BRCA function in pancreatic cancer cells leads to HSF1–dependent accumulation of immune-regulatory clusterin-positive cancer associated fibroblasts.

DNA and RNA sequencing in large cohorts of patients with rectal cancer treated with neoadjuvant therapies identifies biomarkers of response that could inform patient selection for non-operative treatment strategies.