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Updated: May 17, 2026
07:54
Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
Cellular heterogeneity and molecular evolution in cancer
Vanessa Almendro1, Andriy Marusyk, Kornelia Polyak
1Department of Medical Oncology, Dana-Farber Cancer Institute, and Department of Medicine, Harvard Medical School, Boston, MA 02215, USA. Vanessa_Almendro@dfci.harvard.edu
Annual Review of Pathology
|October 25, 2012
Summary
Understanding intratumor heterogeneity at the single-cell level is key to improving cancer diagnosis and treatment. New technologies help monitor tumor cell changes, aiding personalized medicine and predicting treatment resistance.
Area of Science:
- Oncology
- Genomics
- Biomedical Engineering
Background:
- Intratumor heterogeneity (ITH) poses a significant challenge to successful cancer treatment and personalized medicine.
- Advancements in single-cell technologies are enabling detailed investigation of ITH.
- Understanding ITH is crucial for improving cancer diagnosis and therapeutic strategies.
Purpose of the Study:
- To summarize key aspects of intratumor heterogeneity during tumor evolution.
- To discuss experimental methods for assessing ITH.
- To explore the clinical translation of ITH measurement techniques.
Main Methods:
- Review of current literature on intratumor heterogeneity.
- Discussion of single-cell analysis technologies.
- Exploration of experimental approaches for inferring ITH.
Main Results:
- Single-cell level analysis provides deeper insights into tumor composition.
- Monitoring cell population dynamics aids in understanding disease progression and treatment response.
- ITH measurements show potential as biomarkers for predicting progression and resistance.
Conclusions:
- Elucidating ITH at the single-cell level is vital for advancing cancer care.
- Improved understanding and measurement of ITH can enhance diagnostic accuracy and therapeutic design.
- Translating ITH methodologies into clinical practice holds promise for personalized oncology.
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