Divitum shows prognostic value in operable breast cancer

Biovica International AB, of Uppsala, Sweden, reported results from a retrospective analysis showing that its Divitum assay may be a valuable prognostic marker in operable breast cancer. The study analyzed serum samples from a randomized trial of 644 women with operable breast cancer (premenopausal with stage II-IIIB HR+ breast cancer) that were collected just prior to surgery. At the end of five years, patients with preoperative Divitum values of less than 25% had a disease-free survival rate of 81%, compared with 58% in patients whose Divitum values were greater than 75%. Divitum measures thymidine kinase activity (TKa), a well-known marker of tumor cell proliferation, but less well-documented for its prognostic ability. “We are thrilled with these new, interesting results,” said Luca Malorni, of Italy’s Prato Hospital and lead investigator in the study. “It demonstrates that preoperative Divitum values measured in serum is a strong prognostic marker in operable breast cancer with a potential to identify patients with the most aggressive tumors in order to personalize their therapy.” The results were presented this week at the San Antonio Breast Cancer Symposium.

AI teases out heart disease in lung scans

Coronary artery calcium (CAC) is an established measure of plaque in arteries and one that is visible on CT scans. However, clinicians doing low-dose scans for lung cancer screening in long-time smokers and other high-risk groups rarely measure these deposits. Doing so could help in early detection of people with artery buildup and get them on cholesterol-lowering preventive medications. A team of researchers at Massachusetts General Hospital and Brigham and Women’s Hospital developed and tested a deep learning technique that automatically measures CAC on chest CT images. They trained the system on cardiac and chest CTs where plaque had been measured manually and then tested it on CT scans from thousands of long-time heavy smokers who had participated in the National Lung Screening Trial. The results showed not only a close correlation between deep learning-derived CAC scores and those calculated by humans but also a strong link between deep learning calcium scores and cardiovascular death during a six and a half years of follow-up. The team said the system, which adds no time to the CT exam, could be beneficial outside the lung screening population, such as in people experiencing stable and acute chest pain. It could also be used to identify people at high and low risk of coronary artery disease. The researchers reported their findings at the recent Radiological Society of North America annual meeting in Chicago.

Psychiatric risk genes can have distinct effects in different disorders

Researchers from multiple psychiatric consortia have published a new analysis of risk genes for eight psychiatric disorders. The consortia performed a meta-analysis of previous genomic studies with more than 230,000 individuals with anorexia nervosa, attention-deficit/ hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome, and nearly half a million control subjects. They identified multiple new relationships between risk genes, and more than 100 genomic loci that were associated with more than one psychiatric disorder, “including 23 loci with … effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders.” More than 30 of the loci had not been associated with any of the individual disorders prior to the study. “These results highlight disparities between our clinically-defined classification of psychiatric disorders and underlying biology,” the authors wrote. “Future research is warranted to determine whether more genetically-defined influences on cross-diagnostic traits or subtypes of dissect may inform a biologically-informed reconceptualization of psychiatric [classification].” They reported their results in the Dec. 12, 2019, issue of Cell.

Improving early diagnosis of colon cancer

Lausanne, Switzerland-based Novigenix SA has developed a new immune cell type specific immune-transcriptomic signature for detecting colorectal cancer (CRC) in blood samples. In a study presented this week at the European Society for Medical Oncology in Geneva, RNA signatures specific for seven immune cell types – neutrophils, monocyte, T cells, CD4, CD8, B cells and NK cells – were tested on the RNA-sequencing transcriptome profiles of 561 peripheral blood mononuclear cell samples from 218 healthy individuals, 189 CRC patients, 115 patients with advanced adenomas and 39 other cancer patients. The analysis was performed using Novigenix’s Litoseek sequencing platform. What it showed was strong upregulation of monocyte and neutrophil cell RNA signatures in CRC versus controls, while T-cell signatures were greatly downregulated. The specificity of various RNA signatures was demonstrated via comparison with cell counts performed by traditional methods. “These are very encouraging data on the utility of immune cell type specific RNA signature as biomarkers for CRC detection in blood,” said G. Dorta, with the department of gastroenterology and hepatology at the University Hospital of Lausanne. “The correlation of the cell type specific RNA signature with traditional cell counting as well as the CRD discriminant power could be very valuable for the development of an early CRC detection test.” Jan Groen, Novigenix’s CEO, said he company is exploring how cell type specific RNA signatures and a CRC-specific profile could be combined in such a test.

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