AIMC Topic: Killer Cells, Natural

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TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning.

BMC pregnancy and childbirth May 31, 2025
BACKGROUND: Recurrent pregnancy loss (RPL), characterized by multiple miscarriages, remains a condition with unclear etiology, posing significant challenges for affected women and couples. This study aims to explore the underlying mechanisms of RPL, ...
Biomarkers Pregnancy Female Adult Humans Machine Learning Killer Cells, Natural Macrophage Migration-Inhibitory Factors Abortion, Habitual TNF Receptor-Associated Factor 3 Decidua Gene Expression Profiling Transcriptome Case-Control Studies Single-Cell Analysis
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Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.

Frontiers in immunology May 27, 2025
BACKGROUND: Breast cancer (BC) remains a leading cause of cancer-related mortality among women worldwide. Natural killer (NK) cells play a crucial role in the innate immune system and exhibit significant anti-tumor activity. However, the role of NK c...
Gene Expression Regulation, Neoplastic Killer Cells, Natural Precision Medicine Prognosis Female Breast Neoplasms Tumor Microenvironment Biomarkers, Tumor Gene Expression Profiling Transcriptome Humans Machine Learning
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Cellular Senescence in Hepatocellular Carcinoma: Immune Microenvironment Insights via Machine Learning and In Vitro Experiments.

International journal of molecular sciences Jan 17, 2025
Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell cycle arrest, plays a crucial role in cancer biology, but its markers and roles in the HCC immune mic...
Gene Expression Regulation, Neoplastic Cellular Senescence Killer Cells, Natural Survivin Cell Line, Tumor Liver Neoplasms Carcinoma, Hepatocellular Single-Cell Analysis Humans Machine Learning Tumor Microenvironment Biomarkers, Tumor
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Predicting patients with septic shock and sepsis through analyzing whole-blood expression of NK cell-related hub genes using an advanced machine learning framework.

Frontiers in immunology Nov 28, 2024
BACKGROUND: Sepsis is a life-threatening condition that causes millions of deaths globally each year. The need for biomarkers to predict the progression of sepsis to septic shock remains critical, with rapid, reliable methods still lacking. Transcrip...
Sepsis Female Computational Biology Humans Male Shock, Septic Machine Learning Gene Expression Profiling Killer Cells, Natural Biomarkers Transcriptome Prognosis
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Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

Genes & genomics Oct 21, 2024
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenvironment and mechanisms remain elusive. Single-cell sequencing allows for the exploration of immune characteristics within tumor at the cellular level...
Tumor Microenvironment Biomarkers, Tumor Male Middle Aged Cell Line, Tumor Gene Expression Regulation, Neoplastic Humans Killer Cells, Natural Machine Learning Liver Neoplasms Prognosis Carcinoma, Hepatocellular Female Single-Cell Analysis Sequence Analysis, RNA
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Stem-cell based, machine learning approach for optimizing natural killer cell-based personalized immunotherapy for high-grade ovarian cancer.

The FEBS journal Oct 8, 2021
Advanced high-grade serous ovarian cancer continues to be a therapeutic challenge for those affected using the current therapeutic interventions. There is an increasing interest in personalized cancer immunotherapy using activated natural killer (NK)...
Humans Machine Learning Female Ovarian Neoplasms Stem Cells Killer Cells, Natural Tumor Microenvironment Immunotherapy
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Identification of novel biomarkers in Hunner's interstitial cystitis using the CIBERSORT, an algorithm based on machine learning.

BMC urology Aug 16, 2021
BACKGROUND:  Hunner's interstitial cystitis (HIC) is a complex disorder characterized by pelvic pain, disrupted urine storage, and Hunner lesions seen on cystoscopy. There are few effective diagnostic biomarkers. In the present study, we used the nov...
Humans Machine Learning Biomarkers Mast Cells T Follicular Helper Cells HLA-DR Antigens Plasma Cells Killer Cells, Natural CD3 Complex Cystitis, Interstitial Memory B Cells CD4 Antigens Memory T Cells
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Weakly supervised deep learning for determining the prognostic value of F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type.

European journal of nuclear medicine and molecular imaging Feb 20, 2021
PURPOSE: To develop a weakly supervised deep learning (WSDL) method that could utilize incomplete/missing survival data to predict the prognosis of extranodal natural killer/T cell lymphoma, nasal type (ENKTL) based on pretreatment F-FDG PET/CT resul...
Positron Emission Tomography Computed Tomography Fluorodeoxyglucose F18 Killer Cells, Natural Lymphoma, Extranodal NK-T-Cell Humans Prognosis Retrospective Studies Deep Learning
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Identifying prostate cancer and its clinical risk in asymptomatic men using machine learning of high dimensional peripheral blood flow cytometric natural killer cell subset phenotyping data.

eLife Jul 28, 2020
We demonstrate that prostate cancer can be identified by flow cytometric profiling of blood immune cell subsets. Herein, we profiled natural killer (NK) cell subsets in the blood of 72 asymptomatic men with Prostate-Specific Antigen (PSA) levels < 20...
Killer Cells, Natural Humans Asymptomatic Diseases Machine Learning Blood Circulation Aged Diagnostic Techniques, Urological Prostatic Neoplasms Prostate-Specific Antigen Flow Cytometry Practice Guidelines as Topic Aged, 80 and over Male Middle Aged Risk Assessment
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Single-cell transcriptome reveals the novel role of T-bet in suppressing the immature NK gene signature.

eLife May 14, 2020
The transcriptional activation and repression during NK cell ontology are poorly understood. Here, using single-cell RNA-sequencing, we reveal a novel role for T-bet in suppressing the immature gene signature during murine NK cell development. Based ...
T-bet Transcription Factor Mechanistic Target of Rapamycin Complex 2 Rapamycin-Insensitive Companion of mTOR Protein Regulatory-Associated Protein of mTOR T-Box Domain Proteins Bone Marrow Cells Cluster Analysis Transcriptome Gene Expression Regulation Killer Cells, Natural Mice, Inbred C57BL Single-Cell Analysis Forkhead Box Protein O1 Mice, Knockout RNA-Seq Machine Learning Proto-Oncogene Proteins c-akt Genotype Phenotype Animals Gene Expression Profiling
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