7062 Background: Cancer is a group of genetic diseases that result from changes in the genome of cells in the body, leading them to grow uncontrollably. Recent researches suggest Chromosome instability (CIN), which is defined as an increased rate of chromosome gains and losses, manifests as cell-to-cell karyotypic heterogeneity and drives cancer initiation and evolution. Methods: In the past two years, we initiated iStopCancer project, and characterized 4515 ‘best available’ minimal-invasive samples from cancer patients and 1501 plasma samples from non-tumor diseases by using low-pass whole genome sequencing. DNA from ‘best available’ minimal-invasive samples, including peripheral plasma, urines, pancreatic juice, bile and effusions were analyzed by low coverage whole genome sequencing followed by the UCAD Bioinformatics workflow to characterize the CINs. In total, 32T bp nucleotide (coverage =1.7X for each sample) were collected. All the data can be visualized on website: http://www.istopcancer.net/pgweb/cn/istopcancer.jsp . Results: 3748(83%) of tumors present detectable CIN (CIN score>1000) in minimal-invasive samples. The missed cancer patients were majorly from patients with either tumor size less than 2cm or less-aggressive cancers, including thyroid cancer, low-grade urothelial carcinoma, lung cancer in-situ, et al. Of the 1501 non-tumor individuals, 30(2.0%) present detectable CIN (|Z|>=3) at the time of sample collection, 24(80.0%) was diagnosed as tumor patient in 3-6 months follow-up. There were 9 (0.59%) of non-cancer individuals without detectable CIN were also reported as tumor patients during 6-month following up. In summary, the positive and negative prediction value is 80.0% and 99.4% respectively. The false alarms were majorly from patients with EBV activations, which indicates virus may interference chromosome stability and drove virus-associated carcinogenesis. For the patient with repeated detections, plasma cfDNA CIN dynamics predicted clinical responses and disease recurrences. Quick clearance of plasma cfDNA CIN in 2-3 weeks was found in 153 (83.6%) patients. Meanwhile, no quick clearance was found in majority of SDs/PDs (73/88=83.0%). Furthermore, cfDNA CIN predicts clinical response 2-8 weeks ahead of traditional biomarkers (CEA, CA15-3, CA199, AFP et al). Conclusions: Large-scale low coverage whole genome sequencing data provides useful information for cancer detection and managements.
Whole genome sequencing identifies rare germline variants enriched in cancer related genes in first‐degree relatives of familial pancreatic cancer patients
