Background & Aims Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR)
in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI …

Background Targeted germline testing is recommended for those with or at risk of breast,
ovarian, or colorectal cancer. The affordability of genetic sequencing has improved over the …

Predictive genetic testing can provide information about whether or not someone will
develop or is likely to develop a specific condition at a later stage in life. Economic …

Universal screening for defective mismatch repair (dMMR) in colorectal cancer utilizes
immunohistochemical staining for MLH1, MSH2, MSH6 and PSM2. Additionally, BRAF …

Translating evidence-based practices into real-world healthcare settings is challenging,
particularly in the rapidly evolving field of genomics. A pragmatic two-arm cluster …

Abstract Background Deep Learning (DL) can predict molecular alterations of solid tumors
directly from routine histopathology slides. Since the 2021 update of the World Health …

Universal mismatch repair deficiency (dMMR) testing of colorectal cancer (CRC) is promoted
as routine diagnostics to prescreen for Lynch syndrome. We evaluated the yield and …

Aims Traditionally, mismatch repair (MMR) status is determined by a panel of four antibodies
(MLH1, PMS2, MSH2, MSH6). If all proteins are retained, cases are MMR proficient (pMMR) …

Purpose Lynch syndrome-related colorectal cancer (CRC) risk substantially varies by
mismatch repair (MMR) gene. We evaluated the health impact and cost-effectiveness of …

Simple Summary The incidence of young people< 50 years old who are diagnosed with
colorectal cancer (CRC), termed as early onset colorectal cancer (EOCRC), accounted for …