AIMC Topic: Neoplastic Stem Cells
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Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy.
Frontiers in immunology
Aug 29, 2024
BACKGROUND: Cancer stem cells (CSCs) are a subset of cells within tumors that possess the unique ability to self-renew and give rise to diverse tumor cells. These cells are crucial in driving tumor metastasis, recurrence, and resistance to treatment....
A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.
Aging
Jul 30, 2024
Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in E...
Imaging Flow Cytometry and Convolutional Neural Network-Based Classification Enable Discrimination of Hematopoietic and Leukemic Stem Cells in Acute Myeloid Leukemia.
International journal of molecular sciences
Jun 12, 2024
Acute myeloid leukemia (AML) is a heterogenous blood cancer with a dismal prognosis. It emanates from leukemic stem cells (LSCs) arising from the genetic transformation of hematopoietic stem cells (HSCs). LSCs hold prognostic value, but their molecul...
Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.
Frontiers in immunology
Apr 17, 2024
OBJECTIVE: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therap...
Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer.
Aging
Apr 12, 2024
Gastric cancer presents a formidable challenge, marked by its debilitating nature and often dire prognosis. Emerging evidence underscores the pivotal role of tumor stem cells in exacerbating treatment resistance and fueling disease recurrence in gast...
Modeling 5-FU-Induced Chemotherapy Selection of a Drug-Resistant Cancer Stem Cell Subpopulation.
Current oncology (Toronto, Ont.)
Feb 25, 2024
(1) Background: Cancer stem cells (CSCs) are a subpopulation of cells in a tumor that can self-regenerate and produce different types of cells with the ability to initiate tumor growth and dissemination. Chemotherapy resistance, caused by numerous me...
Deep learning models for cancer stem cell detection: a brief review.
Frontiers in immunology
Jun 27, 2023
Cancer stem cells (CSCs), also known as tumor-initiating cells (TICs), are a subset of tumor cells that persist within tumors as a distinct population. They drive tumor initiation, relapse, and metastasis through self-renewal and differentiation into...
Deep Learning of Phase-Contrast Images of Cancer Stem Cells Using a Selected Dataset of High Accuracy Value Using Conditional Generative Adversarial Networks.
International journal of molecular sciences
Mar 10, 2023
Artificial intelligence (AI) technology for image recognition has the potential to identify cancer stem cells (CSCs) in cultures and tissues. CSCs play an important role in the development and relapse of tumors. Although the characteristics of CSCs h...
Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.
International journal of biological sciences
Jan 1, 2022
Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance...
Identification of biomarkers for acute leukemia via machine learning-based stemness index.
Gene
Aug 16, 2021
Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as r...
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