Cancer as a global health crisis with deep evolutionary roots

Klement, Rainer Johannes

doi:10.1016/j.glt.2024.01.001

Cited by 7 publications

(1 citation statement)

References 242 publications

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“…play an important role in tumorigenesis [7]. For instance, many traditional communities that follow a hunter-gatherer diet and do not live in industrialized regions have a lower incidence of cancer [8]. Tumorigenesis observed in animal models provides a basis for understanding the mechanisms behind it.…”

Section: Introductionmentioning

confidence: 99%

Mitochondrial–Stem Cell Connection: Providing Additional Explanations for Understanding Cancer

Martinez,

Baghli,

Gourjon

et al. 2024

Metabolites

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The cancer paradigm is generally based on the somatic mutation model, asserting that cancer is a disease of genetic origin. The mitochondrial–stem cell connection (MSCC) proposes that tumorigenesis may result from an alteration of the mitochondria, specifically a chronic oxidative phosphorylation (OxPhos) insufficiency in stem cells, which forms cancer stem cells (CSCs) and leads to malignancy. Reviewed evidence suggests that the MSCC could provide a comprehensive understanding of all the different stages of cancer. The metabolism of cancer cells is altered (OxPhos insufficiency) and must be compensated by using the glycolysis and the glutaminolysis pathways, which are essential to their growth. The altered mitochondria regulate the tumor microenvironment, which is also necessary for cancer evolution. Therefore, the MSCC could help improve our understanding of tumorigenesis, metastases, the efficiency of standard treatments, and relapses.

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Section: Introductionmentioning

confidence: 99%

Mitochondrial–Stem Cell Connection: Providing Additional Explanations for Understanding Cancer

Martinez,

Baghli,

Gourjon

et al. 2024

Metabolites

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Design of Bionanomaterial of Chitosan Carbohydrate Polymer Composited with Broccoli Extract and Zinc Oxide Nanoparticles: Anticancer Activity in Human Osteosarcoma

Hussein,

Abdulhameed

2024

Appl Biochem Biotechnol

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Utilizing machine learning and molecular dynamics for enhanced drug delivery in nanoparticle systems

Jahandoost,

Dashti,

Houshmand

et al. 2024

Sci Rep

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Materials data science and machine learning (ML) are pivotal in advancing cancer treatment strategies beyond traditional methods like chemotherapy. Nanotherapeutics, which merge nanotechnology with targeted drug delivery, exemplify this advancement by offering improved precision and reduced side effects in cancer therapy. The development of these nanotherapeutic agents depends critically on understanding nanoparticle (NP) properties and their biological interactions, often analyzed through molecular dynamics (MD) simulations. This study enhances these analyses by integrating ML with MD simulations, significantly improving both prediction accuracy and computational efficiency. We introduce a comprehensive three-stage methodology for predicting the solvent-accessible surface area (SASA) of NPs, which is crucial for their therapeutic efficacy. The process involves training an ML model to forecast the many-body tensor representation (MBTR) for future time steps, applying data augmentation to increase dataset realism, and refining the SASA predictor with both augmented and original data. Results demonstrate that our methodology can predict SASA values 299 time steps ahead with a 40-fold speed improvement and a 25% accuracy increase over existing methods. Importantly, it provides a 300-fold increase in computational speed compared to traditional simulation techniques, offering substantial cost and time savings for nanotherapeutic research and development.

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Cancer as a global health crisis with deep evolutionary roots

Cited by 7 publications

References 242 publications

Mitochondrial–Stem Cell Connection: Providing Additional Explanations for Understanding Cancer

Mitochondrial–Stem Cell Connection: Providing Additional Explanations for Understanding Cancer

Design of Bionanomaterial of Chitosan Carbohydrate Polymer Composited with Broccoli Extract and Zinc Oxide Nanoparticles: Anticancer Activity in Human Osteosarcoma

Utilizing machine learning and molecular dynamics for enhanced drug delivery in nanoparticle systems

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