Adjuvant Hepatic Arterial Infusion Pump Chemotherapy After Resection of Colorectal Liver Metastases: Results of a Safety and Feasibility Study in The Netherlands

Background: The 10-year overall survival with adjuvant hepatic arterial infusion pump (HAIP) chemotherapy after resection of colorectal liver metastases (CRLMs) was 61% in clinical trials from Memorial Sloan Kettering Cancer Center. A pilot study was performed to evaluate the safety and feasibility of adjuvant HAIP chemotherapy in patients with resectable CRLMs. Study Design: A phase II study was performed in two centers in The Netherlands. Patients with resectable CRLM without extrahepatic disease were eligible. All patients underwent complete resection and/or ablation of CRLMs and pump implantation. Safety was determined by the 90-day HAIP-related postoperative complications from the day of pump placement (Clavien–Dindo classification, grade III or higher) and feasibility by the successful administration of the first cycle of HAIP chemotherapy. Results: A total of 20 patients, with a median age of 57 years (interquartile range [IQR] 51–64) were included. Grade III or higher HAIP-related postoperative complications were found in two patients (10%), both of whom had a reoperation (without laparotomy) to replace a pump with a slow flow rate or to reposition a flipped pump. No arterial bleeding, arterial dissection, arterial thrombosis, extrahepatic perfusion, pump pocket hematoma, or pump pocket infections were found within 90 days after surgery. After a median of 43 days (IQR 29–52) following surgery, all patients received the first dose of HAIP chemotherapy, which was completed un

Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer

The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomarkers are imperfect. Here, we used an end-to-end deep learning algorithm to identify risk factors for lymph node metastasis (LNM) status in digitized histopathology slides of the primary CRC and its surrounding tissue. In two large population-based cohorts, we show that this system can predict the presence of more than one LNM in pT2 CRC patients with an area under the receiver operating curve (AUROC) of 0.733 (0.67-0.758) and patients with any LNM with an AUROC of 0.711 (0.597-0.797). Similarly, in pT1 CRC patients, the presence of more than one LNM or any LNM was predictable with an AUROC of 0.733 (0.644-0.778) and 0.567 (0.542-0.597), respectively. Based on these findings, we used the deep learning system to guide human pathology experts towards highly predictive regions for LNM in the whole slide images. This hybrid human observer and deep learning approach identified inflamed adipose tissue as the highest predictive feature for LNM presence. Our study is a first proof of concept that artificial intelligence (AI) systems may be able to discover potentially new biological mechanisms in cancer progression. Our deep learning algorithm is publicly available and can be used for biomarker discovery in any disease setting. (c) 2021 The Pathological Society of Great Britain and Ireland

Variations in chemical and physical properties of Amazon forest soils in relation to their genesis

Soil samples were collected in six South American countries in a total of 71 different 1 ha forest plots across the Amazon Basin as part of the RAINFOR project. They were analysed for total and exchangeable cations, C, N, pH with various P fractions also determined. Physical properties were also examined and an index of soil physical quality proposed. A diverse range of soils was found. For the western areas near the Andean cordillera and the southern and northern fringes, soils tend to be distributed among the lower pedogenetic levels, while the central and eastern areas of Amazonia have more intensely weathered soils. This gives rise to a large variation of soil chemical and physical properties across the Basin, with soil properties varying predictably along a gradient of pedogenic development. Nutrient pools generally increased slightly in concentration from the youngest to the intermediate aged soils after which a gradual decline was observed with the lowest values found in the most weathered soils. Soil physical properties were strongly correlated with soil fertility, with favourable physical properties occurring in highly weathered and nutrient depleted soils and with the least weathered, more fertile soils having higher incidence of limiting physical properties. Soil phosphorus concentrations varied markedly in accordance with weathering extent and appear to exert an important influence on the nitrogen cycle of Amazon forest soil