Emerging therapies in cancer metabolism

Cell Metabolism, Год журнала: 2023, Номер 35(8), С. 1283 - 1303

Опубликована: Авг. 1, 2023

Язык: Английский

---

Applications of machine learning in metabolomics: Disease modeling and classification

Frontiers in Genetics, Год журнала: 2022, Номер 13

Опубликована: Ноя. 24, 2022

Metabolomics research has recently gained popularity because it enables the study of biological traits at biochemical level and, as a result, can directly reveal what occurs in cell or tissue based on health disease status, complementing other omics such genomics and transcriptomics. Like high-throughput experiments, metabolomics produces vast volumes complex data. The application machine learning (ML) to analyze data, recognize patterns, build models is expanding across multiple fields. In same way, ML methods are utilized for classification, regression, clustering highly metabolomic This review discusses how modeling diagnosis be enhanced via deep comprehensive profiling using ML. We discuss general layout metabolic workflow fundamental techniques used including support vector machines (SVM), decision trees, random forests (RF), neural networks (NN), (DL). Finally, we present advantages disadvantages various provide suggestions different data analysis scenarios.

Язык: Английский

---

Overview and countermeasures of cancer burden in China

Science China Life Sciences, Год журнала: 2023, Номер 66(11), С. 2515 - 2526

Опубликована: Апрель 13, 2023

Язык: Английский

---

Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment

Journal of Hematology & Oncology, Год журнала: 2023, Номер 16(1)

Опубликована: Ноя. 27, 2023

Research into the potential benefits of artificial intelligence for comprehending intricate biology cancer has grown as a result widespread use deep learning and machine in healthcare sector availability highly specialized datasets. Here, we review new approaches how they are being used oncology. We describe might be detection, prognosis, administration treatments introduce latest large language models such ChatGPT oncology clinics. highlight applications omics data types, offer perspectives on various types combined to create decision-support tools. also evaluate present constraints challenges applying precision Finally, discuss current may surmounted make useful clinical settings future.

Язык: Английский

---

Cancer metabolites: promising biomarkers for cancer liquid biopsy

Biomarker Research, Год журнала: 2023, Номер 11(1)

Опубликована: Июнь 30, 2023

Abstract Cancer exerts a multitude of effects on metabolism, including the reprogramming cellular metabolic pathways and alterations in metabolites that facilitate inappropriate proliferation cancer cells adaptation to tumor microenvironment. There is growing body evidence suggesting aberrant play pivotal roles tumorigenesis metastasis, have potential serve as biomarkers for personalized therapy. Importantly, high-throughput metabolomics detection techniques machine learning approaches offer tremendous clinical oncology by enabling identification cancer-specific metabolites. Emerging research indicates circulating great promise noninvasive detection. Therefore, this review summarizes reported abnormal cancer-related last decade highlights application liquid biopsy, specimens, technologies, methods, challenges. The provides insights into promising tool applications.

Язык: Английский

---

Plasma protein biomarkers for early prediction of lung cancer

EBioMedicine, Год журнала: 2023, Номер 93, С. 104686 - 104686

Опубликована: Июнь 26, 2023

Individual plasma proteins have been identified as minimally invasive biomarkers for lung cancer diagnosis with potential utility in early detection. Plasma proteomes provide insight into contributing biological factors; we investigated their future prediction.The Olink® Explore-3072 platform quantitated 2941 496 Liverpool Lung Project samples, including 131 cases taken 1-10 years prior to diagnosis, 237 controls, and 90 subjects at multiple times. 1112 significantly associated haemolysis were excluded. Feature selection bootstrapping differentially expressed proteins, subsequently modelled prediction validated UK Biobank data.For samples 1-3 pre-diagnosis, 240 different cases; 1-5 year 117 of these 150 further identified, mapping pathways. Four machine learning algorithms gave median AUCs 0.76-0.90 0.73-0.83 the respectively. External validation 0.75 (1-3 year) 0.69 (1-5 year), AUC 0.7 up 12 diagnosis. The models independent age, smoking duration, histology presence COPD.The proteome provides which may be used identify those greatest risk cancer. pathways are when is more imminent, indicating that both inherent identified.Janssen Pharmaceuticals Research Collaboration Award; Roy Castle Cancer Foundation.

Язык: Английский

---

Rhodiola crenulata alleviates hypobaric hypoxia-induced brain injury by maintaining BBB integrity and balancing energy metabolism dysfunction

Phytomedicine, Год журнала: 2024, Номер 128, С. 155529 - 155529

Опубликована: Март 11, 2024

Язык: Английский

---

Tumor metabolic regulators: key drivers of metabolic reprogramming and the promising targets in cancer therapy

Molecular Cancer, Год журнала: 2025, Номер 24(1)

Опубликована: Янв. 9, 2025

Metabolic reprogramming within the tumor microenvironment (TME) is a hallmark of cancer and crucial determinant progression. Research indicates that various metabolic regulators form network in TME interact with immune cells, coordinating response. dysregulation creates an immunosuppressive TME, impairing antitumor In this review, we discuss how affect cell crosstalk TME. We also summarize recent clinical trials involving challenges metabolism-based therapies translation. word, our review distills key regulatory factors their mechanisms action from complex metabolism, identified as regulators. These provide theoretical basis research direction for development new strategies targets therapy based on reprogramming. Refining Depicting between stromal cells during Emphasizing unresolved translation advantages personalized treatment. Providing support therapies.

Язык: Английский

---

Neutrophil extracellular traps in tumor metabolism and microenvironment

Biomarker Research, Год журнала: 2025, Номер 13(1)

Опубликована: Янв. 23, 2025

Neutrophil extracellular traps (NETs) are intricate, web-like formations composed of DNA, histones, and antimicrobial proteins, released by neutrophils. These structures participate in a wide array physiological pathological activities, including immune rheumatic diseases damage to target organs. Recently, the connection between NETs cancer has garnered significant attention. Within tumor microenvironment metabolism, exhibit multifaceted roles, such as promoting proliferation migration cells, influencing redox balance, triggering angiogenesis, driving metabolic reprogramming. This review offers comprehensive analysis link emphasizing areas that remain underexplored. include interaction with mitochondria, their effect on states within tumors, involvement reprogramming, contribution angiogenesis tumors. Such insights lay theoretical foundation for deeper understanding role development. Moreover, also delves into potential therapeutic strategies suggests future research directions, offering new perspectives treatment other related diseases.

Язык: Английский

---

Impacts of polypropylene microplastics on lipid profiles of mouse liver uncovered by lipidomics analysis and Raman spectroscopy

Journal of Hazardous Materials, Год журнала: 2023, Номер 458, С. 131918 - 131918

Опубликована: Июнь 22, 2023

Язык: Английский

---