Improving performance in colorectal cancer histology decomposition using deep and ensemble machine learning.

In routine colorectal cancer management, histologic samples stained with hematoxylin and eosin are commonly used. Nonetheless, their potential for defining objective biomarkers for patient stratification and treatment selection is still being explored. The current gold standard relies on expensive and time-consuming genetic tests.

The impact of preoperative treatments on the immune environment of rectal cancer.

To improve local disease control, the use of preoperative radiotherapy either alone or combined with chemotherapy has become standard practice in rectal cancer, but it is unclear how these treatments modify the antitumoral immune response. We aimed to evaluate tumor histopathologic features and the prognostic effect of host immune response in rectal cancer with variable treatment modalities. Ninety-five rectal cancers with short-course radiotherapy (SRT), 97 with long-course chemoradiotherapy (CRT), and 154 without preoperative treatments, were evaluated for histopathologic features including Crohn's-like reaction (CLR).

NGS of brush cytology samples improves the detection of high-grade dysplasia and cholangiocarcinoma in patients with primary sclerosing cholangitis: A retrospective and prospective study.

Background: Biliary dysplasia, a precursor of cholangiocarcinoma (CCA), is a common complication of primary sclerosing cholangitis. Patients with high-grade dysplasia (HGD) or early CCA who have received oncological treatment are candidates for liver transplantation. The preoperative diagnosis of CCA or HGD is challenging, and the sensitivity of biliary brush cytology (BC) is limited.