Translational Research in the Era of Precision Medicine: Where We Are and Where We Will Go DOI Open Access

Ruggero De Maria Marchiano,

Gabriele Di Sante, Geny Piro

et al.

Journal of Personalized Medicine, Journal Year: 2021, Volume and Issue: 11(3), P. 216 - 216

Published: March 18, 2021

The advent of Precision Medicine has globally revolutionized the approach translational research suggesting a patient-centric vision with therapeutic choices driven by identification specific predictive biomarkers response to avoid ineffective therapies and reduce adverse effects. spread “multi-omics” analysis use sensors, together ability acquire clinical, behavioral, environmental information on large scale, will allow digitization state health or disease each person, creation global management system capable generating real-time knowledge new opportunities for prevention therapy in individual person (high-definition medicine). Real world data-based applications represent promising alternative traditional evidence-based medicine (EBM) approaches that are based randomized clinical trials test selected hypothesis. Multi-modality data integration is necessary example precision oncology where an Avatar interface allows several simulations order define best scheme cancer patient.

Language: Английский

Deep learning in cancer diagnosis, prognosis and treatment selection DOI Creative Commons
Khoa Tran, Olga Kondrashova, Andrew P. Bradley

et al.

Genome Medicine, Journal Year: 2021, Volume and Issue: 13(1)

Published: Sept. 27, 2021

Abstract Deep learning is a subdiscipline of artificial intelligence that uses machine technique called neural networks to extract patterns and make predictions from large data sets. The increasing adoption deep across healthcare domains together with the availability highly characterised cancer datasets has accelerated research into utility in analysis complex biology cancer. While early results are promising, this rapidly evolving field new knowledge emerging both learning. In review, we provide an overview techniques how they being applied oncology. We focus on applications for omics types, including genomic, methylation transcriptomic data, as well histopathology-based genomic inference, perspectives different types can be integrated develop decision support tools. specific examples may diagnosis, prognosis treatment management. also assess current limitations challenges application precision oncology, lack phenotypically rich need more explainable models. Finally, conclude discussion obstacles overcome enable future clinical utilisation

Language: Английский

Citations

593
Targeting the gut and tumor microbiota in cancer DOI
Elizabeth M. Park, Manoj Chelvanambi, Neal Bhutiani

et al.

Nature Medicine, Journal Year: 2022, Volume and Issue: 28(4), P. 690 - 703

Published: April 1, 2022

Language: Английский

Citations

334
Artificial intelligence-based multi-omics analysis fuels cancer precision medicine DOI Open Access
Xiujing He, Xiaowei Liu,

Fengli Zuo

et al.

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

Published: Dec. 31, 2022

Language: Английский

Citations

161
Immunological mechanisms of inflammatory diseases caused by gut microbiota dysbiosis: A review DOI Open Access

Min’an Zhao,

Jiayi Chu,

Shiyao Feng

et al.

Biomedicine & Pharmacotherapy, Journal Year: 2023, Volume and Issue: 164, P. 114985 - 114985

Published: June 11, 2023

The gut microbiota is indispensable for maintaining host health by enhancing the host's digestive capacity, safeguarding intestinal epithelial barrier, and preventing pathogen invasion. Additionally, exhibits a bidirectional interaction with immune system promotes of to mature. Dysbiosis microbiota, primarily caused factors such as genetic susceptibility, age, BMI, diet, drug abuse, significant contributor inflammatory diseases. However, mechanisms underlying diseases resulting from dysbiosis lack systematic categorization. In this study, we summarize normal physiological functions symbiotic in healthy state demonstrate that when occurs due various external factors, are lost, leading pathological damage lining, metabolic disorders, barrier damage. This, turn, triggers disorders eventually causes systems. These discoveries provide fresh perspectives on how diagnose treat unrecognized variables might affect link between illnesses need further studies extensive basic clinical research will still be required investigate relationship future.

Language: Английский

Citations

145
New Insights Into the Cancer–Microbiome–Immune Axis: Decrypting a Decade of Discoveries DOI Creative Commons
Tejeshwar Jain, Prateek Sharma,

Abhi C. Are

et al.

Frontiers in Immunology, Journal Year: 2021, Volume and Issue: 12

Published: Feb. 23, 2021

The past decade has witnessed groundbreaking advances in the field of microbiome research. An area where immense implications have been demonstrated is tumor biology. affects initiation and progression through direct effects on cells indirectly manipulation immune system. It can also determine response to cancer therapies predict disease survival. Modulation be harnessed potentiate efficacy immunotherapies decrease their toxicity. In this review, we comprehensively dissect recent evidence regarding interaction anti-tumor machinery outline critical questions which need addressed as further explore dynamic colloquy.

Language: Английский

Citations

132
A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy DOI
Christoph K. Stein‐Thoeringer, Neeraj Saini, Eli Zamir

et al.

Nature Medicine, Journal Year: 2023, Volume and Issue: 29(4), P. 906 - 916

Published: March 13, 2023

Language: Английский

Citations

125
Drug-microbiota interactions: an emerging priority for precision medicine DOI Creative Commons
Qing Zhao, Yao Chen, Weihua Huang

et al.

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

Published: Oct. 9, 2023

Abstract Individual variability in drug response (IVDR) can be a major cause of adverse reactions (ADRs) and prolonged therapy, resulting substantial health economic burden. Despite extensive research pharmacogenomics regarding the impact individual genetic background on pharmacokinetics (PK) pharmacodynamics (PD), diversity explains only limited proportion IVDR. The role gut microbiota, also known as second genome, its metabolites modulating therapeutic outcomes human diseases have been highlighted by recent studies. Consequently, burgeoning field pharmacomicrobiomics aims to explore correlation between microbiota variation IVDR or ADRs. This review presents an up-to-date overview intricate interactions classical agents for systemic diseases, including cancer, cardiovascular (CVDs), endocrine others. We summarise how directly indirectly, modify absorption, distribution, metabolism, excretion (ADME) drugs. Conversely, drugs modulate composition function leading changes microbial metabolism immune response. discuss practical challenges, strategies, opportunities this field, emphasizing critical need develop innovative approach multi-omics, integrate various data types, genomic data, well translate lab into clinical practice. To sum up, represents promising avenue address improve patient outcomes, further is imperative unlock full potential precision medicine.

Language: Английский

Citations

90
Application of Artificial Intelligence in Lung Cancer DOI Open Access
Hwa‐Yen Chiu, Heng‐Sheng Chao, Yuh‐Min Chen

et al.

Cancers, Journal Year: 2022, Volume and Issue: 14(6), P. 1370 - 1370

Published: March 8, 2022

Lung cancer is the leading cause of malignancy-related mortality worldwide due to its heterogeneous features and diagnosis at a late stage. Artificial intelligence (AI) good handling large volume computational repeated labor work suitable for assisting doctors in analyzing image-dominant diseases like lung cancer. Scientists have shown long-standing efforts apply AI screening via CXR chest CT since 1960s. Several grand challenges were held find best model. Currently, FDA approved several programs reading, which enables systems take part detection. Following success application radiology field, was applied digitalized whole slide imaging (WSI) annotation. Integrating with more information, demographics clinical data, could play role decision-making by classifying EGFR mutations PD-L1 expression. also help clinicians estimate patient's prognosis predicting drug response, tumor recurrence rate after surgery, radiotherapy side effects. Though there are still some obstacles, deploying workflow vital foreseeable future.

Language: Английский

Citations

83
Machine Learning in Nutrition Research DOI Creative Commons
Daniel Kirk, E.J. Kok, Michele Tufano

et al.

Advances in Nutrition, Journal Year: 2022, Volume and Issue: 13(6), P. 2573 - 2589

Published: Sept. 27, 2022

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods data analysis. The characteristics machine learning (ML) make it suitable for such analysis thus lend itself as an alternative tool to deal this nature. ML has already been applied important problem areas nutrition, obesity, metabolic health, malnutrition. Despite this, experts often without understanding ML, which limits its application therefore potential solve open questions. current article aims bridge knowledge gap by supplying researchers a resource facilitate use their research. is first explained distinguished from existing solutions, key examples applications literature provided. Two case studies domains particularly applicable, precision metabolomics, then presented. Finally, framework outlined guide interested integrating into work. By acting can refer, we hope support integration modern

Language: Английский

Citations

79
Human Health during Space Travel: State-of-the-Art Review DOI Creative Commons
Chayakrit Krittanawong, Nitin K. Singh,

Richard A. Scheuring

et al.

Cells, Journal Year: 2022, Volume and Issue: 12(1), P. 40 - 40

Published: Dec. 22, 2022

The field of human space travel is in the midst a dramatic revolution. Upcoming missions are looking to push boundaries travel, with plans for longer distances and durations than ever before. Both National Aeronautics Space Administration (NASA) several commercial companies (e.g., Blue Origin, SpaceX, Virgin Galactic) have already started process preparing long-distance, long-duration exploration currently plan explore inner solar planets Mars) by 2030s. With emergence tourism, has materialized as potential new, exciting frontier business, hospitality, medicine, technology coming years. However, current evidence regarding health very limited, particularly pertaining short-term long-term travel. This review synthesizes developments across continuum including prior studies unpublished data from NASA related each individual organ system, medical screening We categorized extraterrestrial environment into exogenous radiation microgravity) endogenous processes alteration humans' natural circadian rhythm mental due confinement, isolation, immobilization, lack social interaction) their various effects on health. aim this challenges associated how they may be overcome order enable new paradigms health, well use emerging Artificial Intelligence based (AI) propel future research.

Language: Английский

Citations

77