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Optimization of a WGA-Free Molecular Tagging-Based NGS Protocol for CTCs Mutational Profiling
Giuseppa De Luca1, Barbara Cardinali2, Lucia Del Mastro2,3
1Molecular Diagnostic Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.
International Journal of Molecular Sciences
|June 25, 2020
Summary
This study introduces a new Next-Generation Sequencing (NGS) method using molecular tagging to detect mutations in circulating tumor cells (CTCs) without Whole Genome Amplification (WGA). This approach reliably identifies CTC mutations, offering a promising tool for clinical applications.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Molecular characterization of Circulating Tumor Cells (CTCs) is crucial for cancer research and treatment.
- Whole Genome Amplification (WGA) is often required for low-input DNA samples like CTCs, but it can introduce amplification biases and artifacts.
- Existing methods for CTC analysis face challenges in accurately detecting mutations due to WGA limitations.
Purpose of the Study:
- To develop and validate an optimized Next-Generation Sequencing (NGS) protocol for detecting mutations in CTCs.
- To eliminate the need for Whole Genome Amplification (WGA) in CTC analysis by employing molecular tagging technology.
- To assess the feasibility and reliability of the proposed NGS workflow for clinical applications.
Main Methods:
- Utilized molecular tagging technology for NGS library preparation, bypassing the WGA step.
- Optimized reagent volumes for preparing libraries from limited DNA templates derived from cell lysates.
- Sorted CTCs and leukocytes into small pools (2-5 cells) using a DEPArray™ system for method setup and validation.
- Tested the protocol on MDA-MB-231 and MCF-7 cell lines, known variants in TP53, KRAS, and PIK3CA genes, and CTCs from breast cancer patients.
Main Results:
- Successfully detected known variants in TP53, KRAS, and PIK3CA genes in 94.6% of cell line pools.
- No unexpected alterations were found in cell line pools, and no mutations were detected in leukocytes.
- The optimized NGS workflow demonstrated translational value by successfully detecting variants in CTC pools from breast cancer patients.
Conclusions:
- The proposed NGS molecular tagging approach is technically feasible for CTC mutation detection.
- This method effectively filters out artifacts generated during library amplification, unlike traditional NGS approaches.
- The protocol enables reliable mutation detection in CTCs, showing significant promise for clinical use in cancer diagnostics and monitoring.
