Tumor genomes from almost 2,400 patients with metastatic cancer revealed a range of somatic alterations, providing a foundation for clinical sequencing efforts.
The team identified six independent DNA methylation blocks that could potentially help to predict the formation of central nervous system metastases in lung cancer.
Machine learning and DNA methylation analyses helped distinguish between primary lung tumors and lung tumors stemming from head and neck cancer metastasis.
Researchers found that 14 percent of individuals with metastatic breast cancer had risky mutations germline mutations, including patients who did not meet testing criteria.
At the WIN Symposium, a researcher from Sheba Medical Center discussed ongoing efforts to develop a 22-gene signature for predicting brain metastasis in NSCLC.
A new analysis indicates that colorectal cancer metastases arise from a small number of cells before the primary tumor is large enough to be detected clinically.
With exome sequences from more than 600 metastatic breast tumors, researchers identified genomic alterations related to tumor progression, treatment response, and patient outcomes.
Using exome or transcriptome data from more than 400 metastatic, castration-resistant prostate cancer cases, researchers identified survival-related alterations in the RB1 gene.
A CTC and ctDNA analysis suggests that the number of alterations affecting the androgen receptor can offer survival insights for TP53 mutation-free advanced cancer cases.
The researchers are developing a web-based tool to help physicians predict their patients' relapse risk and are planning clinical trials to study outcomes.
The Washington Post reports that a US Senate committee voted this week to approve the nomination of Stephen Hahn to lead the Food and Drug Administration.
In Nature this week: resources for single-cell analysis, little overlap in the microRNAs used by Salmonella and Shigella to infect host cells, and more.
