AIMC Topic: Microsatellite Instability

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A deep learning model to predict RNA-Seq expression of tumours from whole slide images.

Nature communications
Deep learning methods for digital pathology analysis are an effective way to address multiple clinical questions, from diagnosis to prediction of treatment outcomes. These methods have also been used to predict gene mutations from pathology images, b...

Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning.

Gastroenterology
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 and dMMR in tumor samples on routine histology slides faster and le...

Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Tumor genomic features have been of particular interest because of their potential impact on the tumor immune microenvironment and response to immunotherapy. Due to the substantial heterogeneity, an integrative approach incorporating diverse...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BMC genomics
BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation, transcriptional regulation, post-transcriptional regulation and other aspects, thus participating ...

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.

Nature medicine
Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohis...

Computed Tomography-Based Radiomic Features Could Potentially Predict Microsatellite Instability Status in Stage II Colorectal Cancer: A Preliminary Study.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate whether quantitative radiomics features extracted from computed tomography (CT) can predict microsatellite instability (MSI) status in an Asian cohort of patients with stage Ⅱ colorectal cancer (CRC).

MSIpred: a python package for tumor microsatellite instability classification from tumor mutation annotation data using a support vector machine.

Scientific reports
Microsatellite instability (MSI) is characterized by high degree of polymorphism in microsatellite lengths due to deficiency in mismatch repair (MMR) system. MSI is associated with several tumor types and its status can be considered as an important ...

[Progress in neoadjuvant immunotherapy for locally advanced rectal cancer].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (LARC), yet the pathological complete response (pCR) rates remain suboptimal. The introduction of immunotherapy has opened new avenues for LARC managem...