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Related Concept Videos

Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...

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Related Experiment Video

Updated: Jun 11, 2026

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer
08:12

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Published on: March 14, 2019

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer

Ji-Yeon Lee1, Jumi Kim2, Taehan Yoon1

  • 1Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|June 9, 2026
PubMed
Summary

Metabolic profiling of serum amino acids using 19F NMR reveals distinct patterns in colorectal cancer (CRC) progression. Network analysis and machine learning improve prediction of CRC recurrence and metastasis.

Keywords:
19F NMRcirculating amino acidscolorectal cancermetabolic alterationsprediction of progression risk

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Published on: August 19, 2025

Area of Science:

  • Biochemistry
  • Metabolomics
  • Oncology

Background:

  • Systemic metabolic pathway dynamics during cancer progression are crucial for developing prognostic tools and therapies.
  • Analytical platforms for liquid biospecimens and robust serum-based biomarker discovery frameworks are needed.

Purpose of the Study:

  • To establish a network-based metabolic profiling framework using 19F NMR serum amino acid analysis.
  • To characterize systemic metabolic remodeling during colorectal cancer (CRC) progression.
  • To identify robust serum-based biomarkers for CRC prognosis.

Main Methods:

  • Utilized a 19F NMR-based serum amino acid analysis protocol optimized for clinical samples.
  • Quantified circulating amino acids in 152 CRC patients.
  • Implemented ratio-based normalization and correlation network analysis.
  • Developed machine-learning models integrating amino acid levels and network features.

Main Results:

  • Advanced-stage CRC showed decreased valine and increased glycine levels.
  • Correlation network analysis revealed stage-dependent remodeling of amino acid interactions, forming a glycine-centered architecture.
  • Machine-learning models integrating individual amino acid levels and network features significantly improved prediction of recurrence or metastasis (AUROC = 0.806), outperforming carcinoembryonic antigen.

Conclusions:

  • Remodeling of the circulating amino acid network is a promising strategy for prognostic stratification in CRC.
  • This approach aids in postoperative monitoring of CRC patients.
  • Network-based metabolic profiling offers enhanced predictive power compared to individual biomarkers.