Esophageal squamous cell carcinoma （ESCC） has a high mortality rate. To determine the molecular basis of ESCC development, this study sought to identify characteristic genome-wide alterations in ESCC, including exonic mutations and structural alterations. The clinical implications of these genetic alterations were also analyzed. Exome sequencing and verification were performed for nine pairs of ESCC and the matched blood samples, followed by validation with additional sam- ples using Sanger sequencing. Whole-genomc SNP arrays were employed to detect copy number alteration （CNA） and loss of heterozygosity （LOH） in 55 cases, including the nine ESCC samples subjected to exome sequencing. A total of 108 non-synonymous somatic mutations （NSSMs） in 102 genes were verified in nine patients. The chromatin modification process was found to be enriched in our gene ontology （GO） analysis. Tumor genomes with TP53 mutations were signifi- cantly more unstable than those without TP53 mutations. In terms of the landscape of genomic alterations, deletion of 9p21.3 covering CDKN2A/2B （30.9%）, amplification of 1 1q13.3 covering CCND1 （30.9%）, and TP53 point mutation （50.9%） occurred in two-thirds of the cases. These results suggest that the deregulation of the G1 phase during the cell cycle is a key event in ESCC. Furthermore, six minimal common regions were found to be significantly altered in ESCC samples and three of them, 9p21.3, 7p 11.2, and 3p 12.1, were associated with lymph node metastasis. With the high correlation of TP53 mutation and genomic instability in ESCC, the amplification of CCND1, the deletion of CDKN2A/2B, and the somatic mutation of TP53 appear to play pivotal roles via G1 deregulation and therefore helps to classify this cancer into different genomic subtypes. These findings provide clinical significance that could be useful in future molecular diagnoses and therapeutic targeting.
Objective: To evaluate the accuracy of identifying cancer patients by use of medical claims data in a health insurance system in China, and provide the basis for establishing the claims-based cancer surveillance system in China.Methods: We chose Hua County, Henan Province as the study site, and randomly selected 300 and 1,200 qualified inpatient electronic medical records(EMRs) as well as the New Rural Cooperative Medical Scheme(NCMS) claims records for cancer patients in Hua County People’s Hospital(HCPH) and Anyang Cancer Hospital(ACH) in 2017. Diagnostic information for NCMS claims was evaluated on an individual level, and sensitivity and positive predictive value(PPV) were calculated taking the EMRs as the gold standard.Results: The sensitivity of NCMS was 95.2%(93.8%-96.3%) and 92.0%(88.3%-94.8%) in ACH and HCPH,respectively. The PPV of the NCMS was 97.8%(96.7%-98.5%) in ACH and 89.0%(84.9%-92.3%) in HCPH.Overall, the weighted and combined sensitivity and PPV of NCMS in Hua County was 93.1% and 92.1%,respectively. Significantly higher sensitivity and PPV in identifying patients with common cancers than noncommon cancers were detected in HCPH and ACH separately(P<0.01).Conclusions: Identification of cancer patients by use of the NCMS is accurate on individual level, and it is therefore feasible to conduct claims-based cancer surveillance in areas not covered by cancer registries in China.
Objective:We aimed to prospectively evaluate the association of oral microbiome with malignant esophageal lesions and its predictive potential as a biomarker of risk.Methods:We conducted a case-control study nested within a population-based cohort with up to 8 visits of oral swab collection for each subject over an 11-year period in a high-risk area for esophageal cancer in China.The oral microbiome was evaluated with 16 S ribosomal RNA(rRNA)gene sequencing in 428 pre-diagnostic oral specimens from 84 cases with esophageal lesions of severe squamous dysplasia and above(SDA)and 168 matched healthy controls.DESeq analysis was performed to identify taxa of differential abundance.Differential oral species together with subject characteristics were evaluated for their potential in predicting SDA risk by constructing conditional logistic regression models.Results:A total of 125 taxa including 37 named species showed significantly different abundance between SDA cases and controls(all P<0.05&false discovery rate-adjusted Q<0.10).A multivariate logistic model including 11 SDA lesion-related species and family history of esophageal cancer provided an area under the receiver operating characteristic curve(AUC)of 0.89(95%CI,0.84-0.93).Cross-validation and sensitivity analysis,excluding cases diagnosed within 1 year of collection of the baseline specimen and their matched controls,or restriction to screenendoscopic-detected or clinically diagnosed case-control triads,or using only bacterial data measured at the baseline,yielded AUCs>0.84.Conclusions:The oral microbiome may play an etiological and predictive role in esophageal cancer,and it holds promise as a non-invasive early warning biomarker for risk stratification for esophageal cancer screening programs.
