Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective anti-tumor strategies. Although concerns are frequently raised due to differences in sample processing and depth of coverage, next-generation sequencing of solid tumors have unraveled a highly variable degree of ITH across tumor types. Capturing the genetic relatedness between primary and metastatic lesions through the identification of clonal and subclonal populations is critical to the design of therapies for advance-stage diseases. Here, we report a method for comparative lesions analysis that allows for the identification of clonal and subclonal populations among different specimens from the same patient. The experimental approach described here integrates three well-established approaches: histological analysis, high-coverage multi-lesion sequencing, and immunophenotypic analyses. In order to minimize the effects on the detection of subclonal events by inappropriate sample processing, we subjected tissues to careful pathological examination and neoplastic cell enrichment. Quality controlled DNA from neoplastic lesions and normal tissues was then subjected to high coverage sequencing, targeting the coding regions of 409 relevant cancer genes. While only looking at a limited genomic space, our approach enables evaluating the extent of heterogeneity among somatic alterations (single-nucleotide mutations and copy-number variations) in distinct lesions from a given patient. Through comparative analysis of sequencing data, we were able to distinguish clonal vs. subclonal alterations. The majority of ITH is often ascribed to passenger mutations; therefore, we also used immunohistochemistry to predict functional consequences of mutations. While this protocol has been applied to a specific tumor type, we anticipate that the methodology described here is broadly applicable to other solid tumor types.
Comparative Lesions Analysis Through a Targeted Sequencing Approach
VICENTINI, CARLO ALBERTO;Fassan M.;Scarpa A.;
2019
Abstract
Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective anti-tumor strategies. Although concerns are frequently raised due to differences in sample processing and depth of coverage, next-generation sequencing of solid tumors have unraveled a highly variable degree of ITH across tumor types. Capturing the genetic relatedness between primary and metastatic lesions through the identification of clonal and subclonal populations is critical to the design of therapies for advance-stage diseases. Here, we report a method for comparative lesions analysis that allows for the identification of clonal and subclonal populations among different specimens from the same patient. The experimental approach described here integrates three well-established approaches: histological analysis, high-coverage multi-lesion sequencing, and immunophenotypic analyses. In order to minimize the effects on the detection of subclonal events by inappropriate sample processing, we subjected tissues to careful pathological examination and neoplastic cell enrichment. Quality controlled DNA from neoplastic lesions and normal tissues was then subjected to high coverage sequencing, targeting the coding regions of 409 relevant cancer genes. While only looking at a limited genomic space, our approach enables evaluating the extent of heterogeneity among somatic alterations (single-nucleotide mutations and copy-number variations) in distinct lesions from a given patient. Through comparative analysis of sequencing data, we were able to distinguish clonal vs. subclonal alterations. The majority of ITH is often ascribed to passenger mutations; therefore, we also used immunohistochemistry to predict functional consequences of mutations. While this protocol has been applied to a specific tumor type, we anticipate that the methodology described here is broadly applicable to other solid tumor types.Pubblicazioni consigliate
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