» Articles » PMID: 22408433

Tumor Heterogeneity: Mechanisms and Bases for a Reliable Application of Molecular Marker Design

Overview
Journal Int J Mol Sci
Publisher MDPI
Date 2012 Mar 13
PMID 22408433
Citations 70
Authors
Affiliations
Soon will be listed here.
Abstract

Tumor heterogeneity is a confusing finding in the assessment of neoplasms, potentially resulting in inaccurate diagnostic, prognostic and predictive tests. This tumor heterogeneity is not always a random and unpredictable phenomenon, whose knowledge helps designing better tests. The biologic reasons for this intratumoral heterogeneity would then be important to understand both the natural history of neoplasms and the selection of test samples for reliable analysis. The main factors contributing to intratumoral heterogeneity inducing gene abnormalities or modifying its expression include: the gradient ischemic level within neoplasms, the action of tumor microenvironment (bidirectional interaction between tumor cells and stroma), mechanisms of intercellular transference of genetic information (exosomes), and differential mechanisms of sequence-independent modifications of genetic material and proteins. The intratumoral heterogeneity is at the origin of tumor progression and it is also the byproduct of the selection process during progression. Any analysis of heterogeneity mechanisms must be integrated within the process of segregation of genetic changes in tumor cells during the clonal expansion and progression of neoplasms. The evaluation of these mechanisms must also consider the redundancy and pleiotropism of molecular pathways, for which appropriate surrogate markers would support the presence or not of heterogeneous genetics and the main mechanisms responsible. This knowledge would constitute a solid scientific background for future therapeutic planning.

Citing Articles

Combination of FDG PET/CT radiomics and clinical parameters for outcome prediction in patients with non-Hodgkin's lymphoma.

Ortega C, Anconina R, Joshi S, Metser U, Prica A, Johnson S Nucl Med Commun. 2024; 45(12):1039-1046.

PMID: 39412293 PMC: 11537470. DOI: 10.1097/MNM.0000000000001895.


The correlation between cancer stem cells and epithelial-mesenchymal transition: molecular mechanisms and significance in cancer theragnosis.

Lei Z, Teng Q, Koya J, Liu Y, Chen Z, Zeng L Front Immunol. 2024; 15:1417201.

PMID: 39403386 PMC: 11471544. DOI: 10.3389/fimmu.2024.1417201.


Multiregional transcriptomic profiling provides improved prognostic insight in localized non-small cell lung cancer.

Li C, Nguyen T, Li J, Song X, Fujimoto J, Little L NPJ Precis Oncol. 2024; 8(1):225.

PMID: 39369068 PMC: 11455871. DOI: 10.1038/s41698-024-00680-0.


Phenotyping Tumor Heterogeneity through Proteogenomics: Study Models and Challenges.

Piana D, Iavarone F, De Paolis E, Daniele G, Parisella F, Minucci A Int J Mol Sci. 2024; 25(16).

PMID: 39201516 PMC: 11354793. DOI: 10.3390/ijms25168830.


Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma.

Cheng Q, Zhao W, Song X, Jin T Genes Immun. 2024; 25(5):356-366.

PMID: 39075270 DOI: 10.1038/s41435-024-00289-0.


References
1.
Semenza G . Targeting HIF-1 for cancer therapy. Nat Rev Cancer. 2003; 3(10):721-32. DOI: 10.1038/nrc1187. View

2.
Baithun S, Naase M, Blanes A, Diaz-Cano S . Molecular and kinetic features of transitional cell carcinomas of the bladder: biological and clinical implications. Virchows Arch. 2001; 438(3):289-97. DOI: 10.1007/s004280000289. View

3.
Wachsman W, Morhenn V, Palmer T, Walls L, Hata T, Zalla J . Noninvasive genomic detection of melanoma. Br J Dermatol. 2011; 164(4):797-806. PMC: 3118279. DOI: 10.1111/j.1365-2133.2011.10239.x. View

4.
Reddig P, Juliano R . Clinging to life: cell to matrix adhesion and cell survival. Cancer Metastasis Rev. 2005; 24(3):425-39. DOI: 10.1007/s10555-005-5134-3. View

5.
Kinzler K, Vogelstein B . Lessons from hereditary colorectal cancer. Cell. 1996; 87(2):159-70. DOI: 10.1016/s0092-8674(00)81333-1. View