Body Composition Is a Predictor for Postoperative Complications After Gastrectomy for Gastric Cancer:a Prospective Side Study of the LOGICA Trial

PURPOSE: There is a lack of prospective studies evaluating the effects of body composition on postoperative complications after gastrectomy in a Western population with predominantly advanced gastric cancer. METHODS: This is a prospective side study of the LOGICA trial, a multicenter randomized trial on laparoscopic versus open gastrectomy for gastric cancer. Trial patients who received preoperative chemotherapy followed by gastrectomy with an available preoperative restaging abdominal computed tomography (CT) scan were included. The CT scan was used to calculate the mass (M) and radiation attenuation (RA) of skeletal muscle (SM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). These variables were expressed as Z-scores, depicting how many standard deviations each patient’s CT value differs from the sex-specific study sample mean. Primary outcome was the association of each Z-score with the occurrence of a major postoperative complication (Clavien-Dindo grade ≥ 3b). RESULTS: From 2015 to 2018, a total of 112 patients were included. A major postoperative complication occurred in 9 patients (8%). A high SM-M Z-score was associated with a lower risk of major postoperative complications (RR 0.47, 95% CI 0.28–0.78, p = 0.004). Furthermore, high VAT-RA Z-scores and SAT-RA Z-scores were associated with a higher risk of major postoperative complications (RR 2.82, 95% CI 1.52–5.23, p = 0.001 and RR 1.95, 95% CI 1.14–3.34, p = 0.015, respectively). VAT-M, SAT-M, and SM-RA Z-scores showed no significant associations. CONCLUSION: Preoperative low skeletal muscle mass and high visceral and subcutaneous adipose tissue radiation attenuation (indicating fat depleted of triglycerides) were associated with a higher risk of developing a major postoperative complication in patients treated with preoperative chemotherapy followed by gastrectomy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11605-022-05321-0

Optimizing Nanopore sequencing-based detection of structural variants enables individualized circulating tumor DNA-based disease monitoring in cancer patients

Here, we describe a novel approach for rapid discovery of a set of tumor-specific genomic structural variants (SVs), based on a combination of low coverage cancer genome sequencing using Oxford Nanopore with an SV calling and filtering pipeline. We applied the method to tumor samples of high-grade ovarian and prostate cancer patients and validated on average ten somatic SVs per patient with breakpoint-spanning PCR mini-amplicons. These SVs could be quantified in ctDNA samples of patients with metastatic prostate cancer using a digital PCR assay. The results suggest that SV dynamics correlate with and may improve existing treatment-response biomarkers such as PSA. https://github.com/UMCUGenetics/SHARC

Efeito da colheita seletiva de madeira sobre algumas características físicas de um latossolo amarelo sob floresta na Amazônia Central Effect of selective logging on some physical characteristics of a yellow latosol under rainforest in Central Amazonia State

A colheita seletiva de madeira pode vir a ser uma forma sustentável de uso da terra para ecossistemas florestais da Amazônia, uma vez que permite a manutenção de parte considerável da biomassa florestal, diminuindo, assim, a perturbação nas áreas exploradas. Neste sentido, o presente estudo teve como objetivo avaliar o efeito da exploração seletiva de madeira sobre as características físicas de um Latossolo Amarelo. A área de estudo localiza-se a cerca de 80 km ao norte de Manaus e a vegetação é do tipo Floresta Ombrófila Densa. O número de árvores retiradas com um trator de esteiras D6, por arraste, em 1993, variou de sete a dez árvores/ha (DAP > 55 cm). O delineamento experimental foi do tipo blocos ao acaso, com três repetições. Seis tratamentos foram avaliados, equivalendo às seguintes classes de perturbação identificadas na área: trilha de trator, centro de clareira, borda da clareira/floresta, borda da floresta/clareira, floresta remanescente e floresta-controle. A colheita seletiva de madeira provocou modificações nas características físicas do solo, principalmente nas trilhas de trator, e representou, em média, 13,8 % da área total explorada. Os valores de densidade do solo e resistência à penetração foram maiores para o solo sob estas áreas, enquanto a macroporosidade e o volume de água disponível para as plantas apresentaram-se menores do que nas demais classes de perturbação. Estas classes foram menos afetadas, não se estabelecendo diferenças significativas para as características físicas do solo entre estas e a floresta-controle, indicando, assim, a colheita seletiva como uma prática de menor impacto para o solo dos ecossistemas florestais da Amazônia.<br>Selective logging may become a form of sustainable use of Amazon forest ecosystems since most part of the forest biomass is maintained and the impacts on the exploited area are lower than in comparison to those under other land uses. The objective of this study was to evaluate the effects of selective logging on some soil physical characteristics. The study area lies about 80 km north of Manaus and the vegetation is a humid tropical rainforest. Seven to ten trees/ha (DAP > 55 cm) were felled and removed by a D6 bulldozer, in 1993. Six disturbance classes were defined in the logged plots, with three replicates each: tractor track, center of clearing, edge of clearing, edge of forest, remaining forest and control forest. Soil under tractor tracks represented 13.8 % of the exploited area, and showed higher values of bulk density, and penetration resistance, and lower macroporosity and available water for plants than the other disturbance classes. The other classes were less affected and no significant differences were observed between their soil properties and the control forest, indicating selective logging as a practice that causes less impact on soils of Amazon forest ecosystems