AIMC Topic: Lymphocytes, Tumor-Infiltrating

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The Predictive Value of Monocytes in Immune Microenvironment and Prognosis of Glioma Patients Based on Machine Learning.

Frontiers in immunology Apr 16, 2021
Gliomas are primary malignant brain tumors. Monocytes have been proved to actively participate in tumor growth. Weighted gene co-expression network analysis was used to identify meaningful monocyte-related genes for clustering. Neural network and SVM...
Computational Biology Humans Immunotherapy Machine Learning Monocytes Prognosis Treatment Outcome Reproducibility of Results Glioma Tumor Microenvironment Biomarkers, Tumor Gene Expression Profiling Transcriptome Lymphocytes, Tumor-Infiltrating ROC Curve Genomics Databases, Genetic Molecular Sequence Annotation Leukocyte Count
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Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT.

Oncoimmunology Mar 29, 2021
The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered f...
Prognosis Tumor Microenvironment Humans Deep Learning Lymphocytes, Tumor-Infiltrating Mouth Neoplasms
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LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer.

Cancer research and treatment Dec 29, 2020
PURPOSE: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning-based approach has not been widely s...
Aged Colorectal Neoplasms Male Risk Assessment ROC Curve Machine Learning Prospective Studies Prognosis Retrospective Studies Female Lymph Nodes Lymphocytes, Tumor-Infiltrating Lymphatic Metastasis Neoplasm Staging Immunohistochemistry Humans
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Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers.

Cancer research Dec 21, 2020
Whole-slide histology images contain information that is valuable for clinical and basic science investigations of cancer but extracting quantitative measurements from these images is challenging for researchers who are not image analysis specialists...
Humans Machine Learning Software Algorithms Prognosis Predictive Value of Tests Breast Neoplasms Female Melanoma, Cutaneous Malignant Biomedical Research Melanoma Image Interpretation, Computer-Assisted Neoplasms Skin Neoplasms Medical Oncology Image Processing, Computer-Assisted Reproducibility of Results Datasets as Topic Lymphocytes, Tumor-Infiltrating Sensitivity and Specificity
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Optimization of an automated tumor-infiltrating lymphocyte algorithm for improved prognostication in primary melanoma.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Oct 1, 2020
Tumor-infiltrating lymphocytes (TIL) have potential prognostic value in melanoma and have been considered for inclusion in the American Joint Committee on Cancer (AJCC) staging criteria. However, interobserver discordance continues to prevent the ado...
Lymphocytes, Tumor-Infiltrating Predictive Value of Tests Neoplasm Staging Biopsy Neoplasm Recurrence, Local Progression-Free Survival Male Microscopy Middle Aged Humans Image Interpretation, Computer-Assisted Risk Assessment Machine Learning Risk Factors Lymphocyte Count Disease Progression Automation, Laboratory Aged Databases, Factual Diagnosis, Computer-Assisted Adult Retrospective Studies Tumor Microenvironment Female Melanoma Skin Neoplasms Reproducibility of Results
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An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

Journal of cancer research and clinical oncology Sep 23, 2020
PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient ...
Humans Machine Learning Prognosis Female Sarcoma, Ewing Survival Rate Tumor Microenvironment Adolescent Biomarkers, Tumor Gene Expression Regulation, Neoplastic Male Follow-Up Studies Gene Expression Profiling Lymphocytes, Tumor-Infiltrating Bone Neoplasms
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Prognostic Significance of Immune Cell Populations Identified by Machine Learning in Colorectal Cancer Using Routine Hematoxylin and Eosin-Stained Sections.

Clinical cancer research : an official journal of the American Association for Cancer Research May 21, 2020
PURPOSE: Although high T-cell density is a well-established favorable prognostic factor in colorectal cancer, the prognostic significance of tumor-associated plasma cells, neutrophils, and eosinophils is less well-defined.
Staining and Labeling Lymphocytes, Tumor-Infiltrating Kaplan-Meier Estimate Cell Lineage Eosine Yellowish-(YS) Humans Hematoxylin Prognosis Machine Learning Female Colorectal Neoplasms Biomarkers, Tumor Male
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Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to whole-slide images.

Cancer medicine May 12, 2020
BACKGROUND: It is unclear whether clinical factors and immune microenvironment (IME) factors are associated with tumor mutation burden (TMB) in patients with nonsmall cell lung cancer (NSCLC).
Aged Carcinoembryonic Antigen Aged, 80 and over Smokers Carcinoma, Non-Small-Cell Lung Exome Sequencing Adult Middle Aged Keratin-19 Humans Lymphocytes, Tumor-Infiltrating Tumor Microenvironment Ex-Smokers Lung Neoplasms Machine Learning Non-Smokers Male Regression Analysis B7-H1 Antigen Female Mutation Carcinoma, Squamous Cell Antigens, Neoplasm Forkhead Transcription Factors Adenocarcinoma
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Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor-Infiltrating Lymphocytes in Invasive Breast Cancer.

The American journal of pathology Apr 8, 2020
Quantitative assessment of spatial relations between tumor and tumor-infiltrating lymphocytes (TIL) is increasingly important in both basic science and clinical aspects of breast cancer research. We have developed and evaluated convolutional neural n...
Deep Learning Humans Lymphocytes, Tumor-Infiltrating Female SEER Program Breast Neoplasms
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Artificial intelligence-guided tissue analysis combined with immune infiltrate assessment predicts stage III colon cancer outcomes in PETACC08 study.

Gut Nov 28, 2019
OBJECTIVE: Diagnostic tests, such as Immunoscore, predict prognosis in patients with colon cancer. However, additional prognostic markers could be detected on pathological slides using artificial intelligence tools.
Disease-Free Survival Adenocarcinoma Humans Lymphocytes, Tumor-Infiltrating Image Interpretation, Computer-Assisted Artificial Intelligence Neoplasm Invasiveness Prognosis Neoplasm Staging Antineoplastic Combined Chemotherapy Protocols Colonic Neoplasms
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