Small molecule metabolites: discovery of biomarkers and therapeutic targets

Signal Transduction and Targeted Therapy, Journal Year: 2023, Volume and Issue: 8(1)

Published: March 20, 2023

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks diseases. Metabolite signatures that have close proximity subject's phenotypic informative dimension, are useful for predicting diagnosis prognosis diseases as well monitoring treatments. The lack early biomarkers could poor serious outcomes. Therefore, noninvasive methods with high specificity selectivity desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool biomarker pathway analysis, revealing possible mechanisms human various deciphering therapeutic potentials. It help identify functional related variation delineate biochemical changes indicators pathological damage prior disease development. Recently, scientists established large number profiles reveal underlying networks target exploration in biomedicine. This review summarized analysis on potential value small-molecule candidate metabolites clinical events, may better diagnosis, prognosis, drug screening treatment. We also discuss challenges need be addressed fuel next wave breakthroughs.

Language: Английский

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Early screening and diagnosis strategies of pancreatic cancer: a comprehensive review

Cancer Communications, Journal Year: 2021, Volume and Issue: 41(12), P. 1257 - 1274

Published: July 31, 2021

Abstract Pancreatic cancer is a highly malignant digestive system tumor with poor prognosis. Most pancreatic patients are diagnosed at an advanced stage or even metastasis due to its aggressive characteristics and lack of typical early symptoms. Thus, diagnosis crucial for improving Currently, screening often applied in high‐risk individuals achieve the cancer. Fully understanding risk factors pathogenesis could help us identify population timely treatment Notably, accumulating studies have been undertaken improve detection rate different imaging methods diagnostic accuracy endoscopic ultrasound‐guided fine‐needle aspiration (EUS‐FNA) which golden standard diagnosis. In addition, there currently no biomarkers sufficient sensitivity specificity be clinic. As only serum biomarker approved by United States Food Drug Administration, carbohydrate antigen 19‐9 (CA19‐9) not recommended used because limited specificity. Recently, increasing numbers focused on discovering novel exploring their combination CA19‐9 Besides, application liquid biopsy involving circulating cells (CTCs), DNA (ctDNA), microRNAs (miRNAs), exosomes blood urine, saliva drawing more attention. Furthermore, many innovative technologies such as artificial intelligence, computer‐aided system, metabolomics technology, ion mobility spectrometry (IMS) associated technologies, nanomaterials tested shown promising prospects. Hence, this review aims summarize recent progress development methods, including imaging, pathological examination, serological biopsy, well other potential strategies

Language: Английский

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Artificial intelligence-based multi-omics analysis fuels cancer precision medicine

Seminars in Cancer Biology, Journal Year: 2022, Volume and Issue: 88, P. 187 - 200

Published: Dec. 31, 2022

Language: Английский

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The Potential of Metabolomics in Biomedical Applications

Metabolites, Journal Year: 2022, Volume and Issue: 12(2), P. 194 - 194

Published: Feb. 19, 2022

The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed discovery relevant metabolites that characterize wide variety human phenotypes with respect to health, disease, drug monitoring, even aging. Metabolomics, parallel genomics, has led biomarkers aided in understanding diversity molecular mechanisms, highlighting its application precision medicine. This review focuses on metabolomics can be applied improve as well trends impacts metabolic neurodegenerative diseases, cancer, longevity, exposome, liquid biopsy development, pharmacometabolomics. identification distinct metabolomic profiles will help improvement clinical strategies treat disease. In years come, become tool routinely diagnose monitor health aging, or development. Biomedical applications already foreseen progression such obesity diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, genomics; these assess disease severity predict potential treatment. Future endeavors should focus determining applicability utility metabolomic-derived markers their appropriate implementation large-scale settings.

Language: Английский

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To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Signal Transduction and Targeted Therapy, Journal Year: 2023, Volume and Issue: 8(1)

Published: March 22, 2023

Abstract Tumour cells have exquisite flexibility in reprogramming their metabolism order to support tumour initiation, progression, metastasis and resistance therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic redox status sustain increased energetic demand cells. Over last decades, cancer field has seen an explosion new biochemical technologies giving more tools than ever before navigate this complexity. Within cell or tissue, metabolites constitute direct signature molecular phenotype thus profiling concrete clinical applications oncology. Metabolomics fluxomics, are key technological approaches that mainly revolutionized enabling researchers both qualitative mechanistic model cancer. Furthermore, upgrade from bulk single-cell analysis provided unprecedented opportunity investigate biology at cellular resolution allowing depth quantitative complex heterogenous diseases. More recently, advent functional genomic screening allowed identification pathways, processes, biomarkers novel therapeutic targets concert with other allow patient stratification treatment regimens. This review is intended be guide for metabolism, highlighting current emerging technologies, emphasizing advantages, disadvantages potential leading development innovative anti-cancer

Language: Английский

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Metabolic dysfunction and obesity‐related cancer: Beyond obesity and metabolic syndrome

Obesity, Journal Year: 2022, Volume and Issue: 30(7), P. 1323 - 1334

Published: July 1, 2022

Abstract Objectives: The metabolic dysfunction driven by obesity, including hyperglycemia and dyslipidemia, increases risk for developing at least 13 cancer types. concept of “metabolic dysfunction” is often defined meeting various combinations criteria syndrome. However, the lack a unified definition makes it difficult to compare findings across studies. This review summarizes 129 studies that evaluated variable definitions in relation obesity‐related mortality after diagnosis. Strategies management are also discussed. Methods A comprehensive search relevant publications MEDLINE (PubMed) Google Scholar with references was conducted. Results Metabolic dysfunction, as syndrome diagnosis or any number out clinical range, inflammatory biomarkers, markers organ function, has been associated for, from, colorectal, pancreatic, postmenopausal breast, bladder cancers. associations breast colorectal have observed independently BMI, increased individuals metabolically unhealthy normal weight overweight/obesity compared healthy weight. Conclusion key factor cancer, regardless obesity status. Nonetheless, harmonized will further clarify magnitude relationship types, enable better comparisons studies, guide stratification.

Language: Английский

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Applications of machine learning in metabolomics: Disease modeling and classification

Frontiers in Genetics, Journal Year: 2022, Volume and Issue: 13

Published: Nov. 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.

Language: Английский

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Machine Learning: A New Prospect in Multi-Omics Data Analysis of Cancer

Frontiers in Genetics, Journal Year: 2022, Volume and Issue: 13

Published: Jan. 27, 2022

Cancer is defined as a large group of diseases that associated with abnormal cell growth, uncontrollable division, and may tend to impinge on other tissues the body by different mechanisms through metastasis. What makes cancer so important incidence rate growing worldwide which can have major health, economic, even social impacts both patients governments. Thereby, early prognosis, diagnosis, treatment play crucial role at front line combating cancer. The onset progression occur under influence complicated some alterations in level genome, proteome, transcriptome, metabolome etc. Consequently, advent omics science its broad research branches (such genomics, proteomics, transcriptomics, metabolomics, forth) revolutionary biological approaches opened new doors comprehensive perception landscape. Due complexities formation development cancer, study underlying has gone beyond just one field arena. Therefore, making connection between resultant data from examining them multi-omics pave way for facilitating discovery novel prognostic, diagnostic, therapeutic approaches. As volume complexity studies are increasing dramatically, use leading-edge technologies such machine learning promising assessments data. Machine categorized subset artificial intelligence aims parsing, classification, pattern identification applying statistical methods algorithms. This acquired knowledge subsequently allows computers learn improve accurate predictions experiences processing. In this context, application learning, computational technology offers opportunities achieving in-depth analysis studies. it be concluded roles fight against

Language: Английский

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Exploring the role of sphingolipid-related genes in clinical outcomes of breast cancer

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: Feb. 13, 2023

Background Despite tremendous advances in cancer research, breast (BC) remains a major health concern and is the most common affecting women worldwide. Breast highly heterogeneous with potentially aggressive complex biology, precision treatment for specific subtypes may improve survival patients. Sphingolipids are important components of lipids that play key role growth death tumor cells increasingly subject new anti-cancer therapies. Key enzymes intermediates sphingolipid metabolism (SM) an regulating further influencing clinical prognosis. Methods We downloaded BC data from TCGA database GEO database, on which we performed depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, selection operator (Lasso) regression to construct prognostic model Finally, function gene PGK1 verified by vitro experiments. Results This allows classification patients into high-risk low-risk groups, statistically significant difference time between two groups. The also able show high prediction accuracy both internal external validation sets. After immune microenvironment immunotherapy, it was found this risk grouping could be used as guide immunotherapy BC. proliferation, migration, invasive ability MDA-MB-231 MCF-7 cell lines dramatically reduced after knocking down through cellular Conclusion study suggests features based related SM associated outcomes, progression, alterations Our findings provide insights development strategies early intervention

Language: Английский

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Cancer metabolites: promising biomarkers for cancer liquid biopsy

Biomarker Research, Journal Year: 2023, Volume and Issue: 11(1)

Published: June 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.

Language: Английский

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