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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Pathology to enhance precision medicine in oncology: lessons from landscape ecology
Mark C Lloyd1, Katarzyna A Rejniak, Joel S Brown
1Departments of *Analytic Microscopy ‡Integrated Mathematical Oncology ∥Radiology ¶Anatomic Pathology, H. Lee Moffitt Cancer Center and Research Institute §Department of Oncologic Sciences, College of Medicine, University of South Florida, Tampa, FL †Department of Biological Sciences, University of Chicago at Illinois, Chicago, IL.
Abstract:
A major goal of modern medicine is increasing patient specificity so that the right treatment is administered to the right patient at the right time with the right dose. While current cancer studies have largely focused on identification of genetic or epigenetic properties of tumor cells, emerging evidence has clearly demonstrated substantial genetic heterogeneity between tumors in the same patient and within subclones of a single tumor. Thus, molecular analysis from populations of cells (either a whole tumor or small biopsy of that tumor) is, at best, an incomplete representation of the underlying biology. These observations indicate a significant need to define intratumoral evolutionary dynamics that yield the observed spatial variations in cellular properties. It is generally accepted that genetic heterogeneity among cancer cells is a manifestation of intratumoral evolution, and this is typically viewed as a consequence of random mutations generated by genomic instability within the cancer cells. We suggest that this represents an incomplete view of Darwinian dynamics, which typically are governed by phenotypic variations in response to spatial and temporal heterogeneity in environmental selection forces. We propose that pathologic feature analysis can provide precise information regarding regional variations in environmental selection forces and phenotypic adaptations. These observations can be integrated using quantitative, spatially explicit methods developed in landscape ecology to interrogate heterogenous biological processes in tumors within individual patients. The ability to investigate tumor heterogeneity has been shown to inform physicians regarding critical aspects of cancer progression including invasion, metastasis, drug resistance, and disease relapse.
Insights
Cancer evolution is driven by environmental pressures, not just random mutations. Analyzing tumor pathology reveals spatial variations, improving treatment specificity and predicting cancer progression.
Area of Science:
- Oncology
- Evolutionary Biology
- Computational Biology
Background:
- Cancer treatment aims for patient specificity but faces challenges due to tumor heterogeneity.
- Current molecular analyses of bulk tumor samples provide incomplete biological insights.
- Intratumoral genetic heterogeneity is observed within tumors and between tumors in the same patient.
Purpose of the Study:
- To investigate intratumoral evolutionary dynamics and spatial variations in cellular properties.
- To propose a new framework for understanding cancer evolution beyond random mutations.
- To integrate pathologic feature analysis with quantitative methods for studying tumor heterogeneity.
Main Methods:
- Analysis of pathologic features to identify regional environmental selection forces.
- Application of quantitative, spatially explicit methods from landscape ecology.
- Interrogation of heterogeneous biological processes within individual patient tumors.
Main Results:
- Pathologic feature analysis can precisely define regional environmental variations.
- Spatial and temporal environmental heterogeneity drives phenotypic adaptations in cancer cells.
- Understanding intratumoral heterogeneity informs predictions of invasion, metastasis, drug resistance, and relapse.
Conclusions:
- Cancer evolution is influenced by Darwinian dynamics driven by environmental selection pressures.
- Integrating pathologic and ecological methods offers a novel approach to studying tumor heterogeneity.
- Investigating intratumoral evolutionary dynamics is crucial for personalized cancer medicine.
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