Washout DNA copy number analysis by low-coverage whole genome sequencing for assessment of thyroid FNAs.

Background: Papillary thyroid microcarcinoma (PTMC) is defined as a papillary carcinoma measuring ≤ 10 mm. The current management of PTMC has become more conservative; however, there are high-risk tumor features that can be revealed only postoperatively. For thyroid cancer, BRAF mutations and somatic copy number variation (CNV) are the most common genetic events. Molecular testing may contribute to clinical decision-making by molecular risk stratification, for example predicting lymph node (LN) metastasis. Here, we build a risk stratification model based on molecular profiling of thyroid fine needle aspiration (FNA) washout DNA (wDNA) for the differential diagnosis of thyroid nodules. Methods: Fifty-eight patients were recruited, FNA wDNA samples were analyzed using CNV profiling through low-coverage whole genome sequencing (LC-WGS) and BRAF mutation was analyzed using quantitative PCR. FNA pathology was reported as a Bethesda System for Reporting Thyroid Cytopathology (BSRTC) score. Ultrasound examination produced a Thyroid Imaging Reporting and Data System (TIRADS) score. Results: In total, 37 (63.8%) patients with a TIRADS score of 4A, 13 (22.4%) patients with a TIRADS score of 4B, and 8 (13.8%) patients with a TIRADS score of 4C were recruited after ultrasound examination. All patients underwent FNA with wDNA profiling. CNVs were identified in 17 (29.3%) patients. CNVs were frequent in patients with a BSRTC score of V or VI, including eight (47.1%) patients with a score of VI and five (29.4%) with a score of V, but not in patients with a score of III, II, or I (0%). BRAF mutation was not significantly correlated with BSRTC score. LN metastasis was found more frequently in CNV-positive (CNV+) than in CNV-negative (CNV-) patients (85.7% vs. 34.6%, odds ratio = 11.33, p = 0.002). In total, three molecular subtypes of thyroid nodules were identified in this study: 1) CNV+, 2) CNV- and BRAF positive (BRAF+), and 3) CNV- and BRAF negative (BRAF-). For the CNV+ subtype, 10 (83.3%) lesions with LN metastasis were found, including four (100%) small lesions (i.e. ≤ 5 mm). For the CNV- and BRAF+ nodules, LN metastases were detected in only seven (60.0%) larger tumors (i.e. > 5 mm). For CNV- and BRAF- tumors, LN metastasis was also frequently found in larger tumors only. Conclusions: It is feasible to identify high-risk LN metastasis thyroid cancer from FNA washout samples preoperatively using wDNA CNV profiling using LC-WGS.

Risk Prediction for Arrhythmias by Heart Rate Deceleration Runs in Patients with Chronic Obstructive Pulmonary Disease.

Purpose: Chronic obstructive pulmonary disease (COPD) is associated with increased incidence of arrhythmias, which has been attributed to autonomic dysregulation. Detection of autonomic function may facilitate stratification of COPD patients with respect to their risk of development of arrhythmias. Patients and Methods: A total of 151 COPD patients and 45 non-COPD patients were included in this study. Heart rate deceleration runs (DRs) were detected by dynamic electrocardiogram (ECG); DRs successively occurring in 2, 4, or 8 cardiac cycles were denoted as DR2, DR4, and DR8, respectively. Indicators of arrhythmias including isolated premature atrial contractions (PAC), supraventricular tachycardia (SVT), isolated premature ventricular contractions (PVC), and ventricular tachycardia (VT) were recorded. Occurrence of SVT or PAC ≥70/day was considered positive for supraventricular arrhythmias, while positive ventricular arrhythmias category (PVAC) was defined as occurrence of VT or PVC ≥10/hour. Results: Compared with non-COPD individuals, COPD patients were associated with increased number of PAC, PVC, higher incidence of PAC >70/d, SVT, PVAC, and decreased DRs (DR2, DR4, DR8) (P<0.05). In COPD patients, DRs showed a negative correlation with the incidence of PAC, PVC, SVT, and PVAC (P<0.05). In receiver operating characteristic curve analysis, all the DRs were found to be significant predictors of PAC >70/d, SVT, and PVAC. The predictive power of DRs was significantly different from one another with the order ranged as DR4>DR8>DR2 for PAC >70/d, DR8>DR4>DR2 for SVT, and DR8>DR4>DR2 for PVAC. Conclusion: Our study provides evidence of significant autonomic dysregulation in COPD patients. DRs may serve as a marker of the risk of arrhythmias in COPD patients.

Use of the combination of the preoperative platelet-to-lymphocyte ratio and tumor characteristics to predict peritoneal metastasis in patients with gastric cancer.

The aims of the present study were to evaluate the predictive value of the platelet-to-lymphocyte ratio for peritoneal metastasis in patients with gastric cancer and to construct an available preoperative prediction system for peritoneal metastasis. A total of 1080 patients with gastric cancer were enrolled in our study. The preoperative platelet-to-lymphocyte ratio and other serum markers and objective clinical tumor characteristics were evaluated by receiver operating characteristic curves. A logistic analysis was performed to determine the independent predictive indicators of peritoneal metastasis. A prediction system that included the independent predictive indicators was constructed and evaluated by receiver operating characteristic curves. Based on the receiver operating characteristic curves, the ideal platelet-to-lymphocyte ratio cutoff value to predict peritoneal metastasis was 131.00. The logistic analysis showed that the platelet-to-lymphocyte ratio was an independent indicator to predict peritoneal metastasis. The area under the receiver operating characteristic curve was 0.599. When integrating all independent indicators (i.e., platelet-to-lymphocyte ratio, invasion depth, lymphatic invasion, pathological type), the prediction system more reliably predicted peritoneal metastasis with a higher area under the receiver operating characteristic curve (0.769). The preoperative platelet-to-lymphocyte ratio was an indicator that could be used to predict peritoneal metastasis. Our prediction system could be a reliable instrument to discriminate between patients with gastric cancer with and those without peritoneal metastasis.