Nature Medicine: Genome sequencing predicts the risk of esophageal cancer in advance, especially in patients with precancer lesions.

Pixabay esophageal cancer is the eighth most common cancer in the world and is usually developed by Barrett esophagealitis.
existing monitoring and treatment methods are highly invasive, many patients have to undergo cumbersome procedures to ensure that there is no risk of missing cancer tests, which are painful and at higher risk of complications.
early diagnosis of cancer is the best way to improve survival and slow the progression of the disease;
, accurate early cancer biomarkers are needed to stratide patients.
recently, a study reported a boon for patients with pre-cancerous lesions.
have now developed a statistical model that uses genomic data to accurately predict whether barrett's risk of cancer is high or low.
study was published in Nature Medicine.
in the study, researchers and collaborators from the University of Cambridge and EMBL's European Institute of Biometrics (EMBL-EBI) sequenced live tissue in Barrett esophageal patients to monitor early symptoms of esophageal cancer.
used the data to analyze the differences between patients who were eventually diagnosed with cancer and those who were not.
data were used to build a statistical model to measure individual risk per patient.
" study shows that non-thyx and drive gene mutations predate cancer diagnoses for many years.
example of precancer lesions Barrett's esophageal, we assessed whether these genomic signals could be used for early detection and preventive treatment of cancer.
took 777 biopsy samples from 88 patients in the Barrett esothobar monitoring program over a 15-year process and sequenced them with a shallow whole genome, showing that genomic signals could distinguish between progressive and stable diseases even 10 years before tissue pathological changes.
were validated in separate queues of 76 and 248 patients, respectively.
a. Genome-wide CN instability as a marker of progress risk was investigated in retrospective, demographically matched case control groups using shallow genome-wide sequencing (sWGS; average depth 0.4), and all available endoscope samples (n=777) (CN: copy number) were collected during clinical monitoring, referring to the number of genes (which can be granules) in the genome of a living organism.
single copy is that the gene has only one in the biological genome, and multiple copies mean multiple copies.
)b. Check CN patterns at multiple levels of the esopathy to see how progressing patients are different from non-progressing patients.
researchers observed that the genomes of individual progressing patients between these different samples and time genomes showed a widespread disorder c,d. In addition, cn changes were not limited to cytological heterogeneity, as similar contours were observed in non-degradable BE (NDBE) samples.
CN information and measurements of overall complexity were used to generate cross-validated, elastic network-corrected logistic regression models that end with highly heterogeneous growth (HGD) or mucosal cancer (IMC), which were subsequently validated in a separate queue of 76 patients (n-213 samples), and orthogonal verification (248 patients, n-1272 samples) of the SEATTLE BE study SNP array sample.
cancer risk over time: a. Cumulative risk average (x-axis) for each patient (y-axis) within a few months (time 0) of the initial endoscopy, according to endoscopy.
between each point in time is colored by the maximum (between initial and final endoscopy) risk classification.
to the right shows progressing patients, most of whom are classified as at high risk for endoscopy.
, in the left-hand chart showing patients without progress, a group of patients were consistently predicted to be low-risk.
are those who have been at high risk of non-progress.
continue to follow these patients, and they may eventually progress to HGD/IMC.
b. Progress patients with the highest risk (similar to current guidelines using the highest pathology rating) show that CN can identify 50 percent of high-risk endoscopy patients eight years in advance of progression to HGD or cancer.
shows that genomic risk stratation has real potential for early intervention in high-risk conditions, which are low-cost and suitable for standard clinical biopsy samples.
genome classification enables early treatment for high-risk patients and reduces unnecessary treatment and monitoring in patients who are less likely to develop cancer than current management guidelines based on histological pathology and clinical performance.
of course, while current studies provide good evidence that genomic changes can predict future cancer risks, they are limited by a relatively small number of patients in the queue, especially those in progress.
study, including more longitudinal genomic data, will improve the sensitivity and specificity of the model.
reference: Sarah Killcoyne, Eleanor Gregson, David C. Wedge, Dan J. Woodcock, Matthew D. Eldridge, Rachel de la Rue, Ahmad Miremadi, Sujath Abbas, Adrienne Blasko, Cassandra Kosmidou, Wladyslaw Januszewicz, Aikaterin Varanou Jenkins, Moritz Gerstung, Rebecca Fitzgerald. Genomic copy number predicts esophageal cancer years before transformation. Nature Medicine, 2020; DOI: 10.1038/s41591-020-1033-y Source: MedSci Original !-- Content Presentation Ends -- !-- Determines Whether login Ends.