A growing body of evidence suggests that a subset of human cancers grows as single clonal expansions. In such a nearly neutral evolution scenario, it is possible to infer the early ancestral tree of a full-grown tumor. We hypothesized that early tree reconstruction can provide insights into the mobility phenotypes of tumor cells during their first few cell divisions. We explored this hypothesis by means of a computational multiscale model of tumor expansion incorporating the glandular structure of colorectal tumors. After calibrating the model to multiregional and single gland data from 19 human colorectal tumors using approximate Bayesian computation, we examined the role of early tumor cell mobility in shaping the private mutation patterns of the final tumor. The simulations showed that early cell mixing in the first tumor gland can result in side-variegated patterns where the same private mutations could be detected on opposite tumor sides. In contrast, absence of early mixing led to nonvariegated, sectional mutation patterns. These results suggest that the patterns of detectable private mutations in colorectal tumors may be a marker of early cell movement and hence the invasive and metastatic potential of the tumor at the start of the growth. In alignment with our hypothesis, we found evidence of early abnormal cell movement in 9 of 15 invasive colorectal carcinomas ("born to be bad"), but in none of 4 benign adenomas. If validated with a larger dataset, the private mutation patterns may be used for outcome prediction among screen-detected lesions with unknown invasive potential.
PurposeGastric cancer (GC) is the third-leading cause of cancer-related deaths. Several pivotal clinical trials of adjuvant treatments were performed during the previous decade; however, the optimal regimen for adjuvant treatment of GC remains controversial.Patients and MethodsWe developed a novel deep learning–based survival model (survival recurrent network [SRN]) in patients with GC by including all available clinical and pathologic data and treatment regimens. This model uses time-sequential data only in the training step, and upon being trained, it receives the initial data from the first visit and then sequentially predicts the outcome at each time point until it reaches 5 years. In total, 1,190 patients from three cohorts (the Asian Cancer Research Group cohort, n = 300; the fluorouracil, leucovorin, and radiotherapy cohort, n = 432; and the Adjuvant Chemoradiation Therapy in Stomach Cancer cohort, n = 458) were included in the analysis. In addition, we added Asian Cancer Research Group molecular classifications into the prediction model. SRN simulated the sequential learning process of clinicians in the outpatient clinic using a recurrent neural network and time-sequential outcome data.ResultsThe mean area under the receiver operating characteristics curve was 0.92 ± 0.049 at the fifth year. The SRN demonstrated that GC with a mesenchymal subtype should elicit a more risk-adapted postoperative treatment strategy as a result of its high recurrence rate. In addition, the SRN found that GCs with microsatellite instability and GCs of the papillary type exhibited significantly more favorable survival outcomes after capecitabine plus cisplatin chemotherapy alone.ConclusionOur SRN predicted survival at a high rate, reaching 92% at postoperative year 5. Our findings suggest that SRN-based clinical trials or risk-adapted adjuvant trials could be considered for patients with GC to investigate more individualized adjuvant treatments after curative gastrectomy.
Backgrounds: Obesity is an established risk factor for erosive esophagitis. Yet, the associations of sarcopenia and obesity with erosive esophagitis remain unclear. We studied the associations of obesity, sarcopenia, and sarcopenic obesity with the risk of erosive esophagitis in a large number of asymptomatic men and women. Materials and Methods: We conducted a cross-sectional study of 32,762 asymptomatic adults undergoing routine health checkups including screening endoscopy, between August 2006 and December 2011. Sarcopenia was defined as an appendicular skeletal muscle mass (ASM) /body weight value beyond two standard deviations below the mean for healthy young adults. The ASM was estimated using bioelectrical impedance analysis. Results: Participants were categorized into four groups according to their obesity and sarcopenic status: normal, obese, sarcopenic, and sarcopenic obese. In a multivariable model adjusted for age, sex, smoking status, alcohol intake, regular exercise, and metabolic variables, the risk of erosive esophagitis was higher in obese [adjusted odds ratio(aOR), 1.38; 95% confidence interval (CI), 1.26-1.52], sarcopenic (aOR, 2.20; 95% CI, 1.48-3.29), and sarcopenic obese participants (aOR, 1.68; 95% CI, 1.39-2.03) than in normal participants. Comparing sarcopenic and sarcopenic obese participants to obese participants, the ORs for erosive esophagitis were 1.59 (95% CI, 1.06-2.38) and 1.22 (95% CI, 1.02-1.47), respectively. In dose-response analyses, increasing sarcopenia severity showed a positive and graded relationship with overall, LAB or higher grade, and LA-C erosive esophagitis. Conclusions: Our findings suggest that sarcopenia, regardless of obesity status, is strongly and progressively associated with the risk of erosive esophagitis. IntroductIon Gastroesophageal reflux disease is a widespread gastrointestinal disorder that frequently occurs in primary care settings, imposing considerable burdens on global health and economics [1]. Disease prevalence is 18.1-27.8% in North America, 8.8-25.9% in Europe, and 2.5-7.8% in East Asia, with rising rates worldwide [2]. Obesity is considered a significant contributing factor for a spectrum of reflux-related esophageal disorders ranging from
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