16 02 Base Architecture Metastasis Hepatocellular Carcinoma HCV-related

Hepatocellular carcinoma (HCC) represents the third leading cause of cancer-related mortality globally, withCTNNB1-mutant subtype comprising 20-40% of cases and exhibiting distinct metastatic patterns [Llovet etal., 2021, Zucman-Rossi et al., 2022]. Unlike other molecular subtypes, CTNNB1-mutant HCC demonstratespreferential metastasis to lung (30-35%), lymph nodes (30-35%), and intrahepatic sites (25-30%), with lowerbut clinically significant bone (10-12%) and adrenal (10-15%) involvement [Schulze et al., 2015].Current approaches lack quantitative frameworks to predict site-specific metastatic behavior and optimalintervention strategies. I address this gap through a first-principles mathematical model integrating threeanalytical scales: ecosystem dynamics, subcellular architecture, and metabolic network topology. Trying to Capture a snapshot of metastatic corelation dynamics and base architecutures derived from the original carcinoma.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-07
DOI
https://doi.org/10.5281/zenodo.18167454
Primary Topic
Cancer, Hypoxia, and Metabolism
Type
article
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article

16 02 Base Architecture Metastasis Hepatocellular Carcinoma HCV-related

Ionut Alexandru Stefan
Zenodo (CERN European Organization for Nuclear Research)
Cancer, Hypoxia, and Metabolism
article

16 02 Base Architecture Metastasis Hepatocellular Carcinoma HCV-related

Ionut Alexandru Stefan
article en

Abstract

Hepatocellular carcinoma (HCC) represents the third leading cause of cancer-related mortality globally, withCTNNB1-mutant subtype comprising 20-40% of cases and exhibiting distinct metastatic patterns [Llovet etal., 2021, Zucman-Rossi et al., 2022]. Unlike other molecular subtypes, CTNNB1-mutant HCC demonstratespreferential metastasis to lung (30-35%), lymph nodes (30-35%), and intrahepatic sites (25-30%), with lowerbut clinically significant bone (10-12%) and adrenal (10-15%) involvement [Schulze et al., 2015].Current approaches lack quantitative frameworks to predict site-specific metastatic behavior and optimalintervention strategies. I address this gap through a first-principles mathematical model integrating threeanalytical scales: ecosystem dynamics, subcellular architecture, and metabolic network topology. Trying to Capture a snapshot of metastatic corelation dynamics and base architecutures derived from the original carcinoma.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 94%
Cancer, Hypoxia, and Metabolism
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