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Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.
Literature Information
| DOI | 10.1038/nature22364 |
|---|---|
| PMID | 28445469 |
| Journal | Nature |
| Impact Factor | 48.5 |
| JCR Quartile | Q1 |
| Publication Year | 2017 |
| Times Cited | 913 |
| Keywords | circulating tumor DNA, lung cancer, phylogenetic analysis, recurrence monitoring, subclones |
| Literature Type | Journal Article, Research Support, Non-U.S. Gov't |
| ISSN | 0028-0836 |
| Pages | 446-451 |
| Issue | 545(7655) |
| Authors | Christopher Abbosh, Nicolai J Birkbak, Gareth A Wilson, Mariam Jamal-Hanjani, Tudor Constantin, Raheleh Salari, John Le Quesne, David A Moore, Selvaraju Veeriah, Rachel Rosenthal, Teresa Marafioti, Eser Kirkizlar, Thomas B K Watkins, Nicholas McGranahan, Sophia Ward, Luke Martinson, Joan Riley, Francesco Fraioli, Maise Al Bakir, Eva Grönroos, Francisco Zambrana, Raymondo Endozo, Wenya Linda Bi, Fiona M Fennessy, Nicole Sponer, Diana Johnson, Joanne Laycock, Seema Shafi, Justyna Czyzewska-Khan, Andrew Rowan, Tim Chambers, Nik Matthews, Samra Turajlic, Crispin Hiley, Siow Ming Lee, Martin D Forster, Tanya Ahmad, Mary Falzon, Elaine Borg, David Lawrence, Martin Hayward, Shyam Kolvekar, Nikolaos Panagiotopoulos, Sam M Janes, Ricky Thakrar, Asia Ahmed, Fiona Blackhall, Yvonne Summers, Dina Hafez, Ashwini Naik, Apratim Ganguly, Stephanie Kareht, Rajesh Shah, Leena Joseph, Anne Marie Quinn, Phil A Crosbie, Babu Naidu, Gary Middleton, Gerald Langman, Simon Trotter, Marianne Nicolson, Hardy Remmen, Keith Kerr, Mahendran Chetty, Lesley Gomersall, Dean A Fennell, Apostolos Nakas, Sridhar Rathinam, Girija Anand, Sajid Khan, Peter Russell, Veni Ezhil, Babikir Ismail, Melanie Irvin-Sellers, Vineet Prakash, Jason F Lester, Malgorzata Kornaszewska, Richard Attanoos, Haydn Adams, Helen Davies, Dahmane Oukrif, Ayse U Akarca, John A Hartley, Helen L Lowe, Sara Lock, Natasha Iles, Harriet Bell, Yenting Ngai, Greg Elgar, Zoltan Szallasi, Roland F Schwarz, Javier Herrero, Aengus Stewart, Sergio A Quezada, Karl S Peggs, Peter Van Loo, Caroline Dive, C Jimmy Lin, Matthew Rabinowitz, Hugo J W L Aerts, Allan Hackshaw, Jacqui A Shaw, Bernhard G Zimmermann, Charles Swanton |
TL;DR
This study demonstrates the potential of using tumor-specific phylogenetic profiling of circulating tumor DNA (ctDNA) to non-invasively track early-stage non-small-cell lung cancer evolution and identify patients at high risk for recurrence following primary surgery. The findings highlight the role of ctDNA in understanding chemotherapy resistance and the subclonal dynamics of metastasis, paving the way for novel therapeutic strategies to combat tumor recurrence.
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circulating tumor DNA · lung cancer · phylogenetic analysis · recurrence monitoring · subclones
Abstract
The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies.
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Primary Questions Addressed
- How does phylogenetic ctDNA analysis improve the understanding of tumor recurrence in early-stage lung cancer?
- What are the potential therapeutic implications of identifying subclonal dynamics in lung cancer through ctDNA profiling?
- In what ways can the findings from the TRACERx study influence future clinical trials for non-small-cell lung cancer?
- What challenges are associated with the non-invasive tracking of ctDNA in the context of lung cancer metastasis?
- How does the detection of adjuvant chemotherapy resistance via ctDNA analysis inform treatment strategies for lung cancer patients?
Key Findings
Research Background and Objectives
Lung cancer, particularly non-small cell lung cancer (NSCLC), is a leading cause of cancer mortality. Early detection of relapse after surgery could improve therapeutic outcomes. This study aims to explore the use of circulating tumor DNA (ctDNA) to track tumor evolution and predict recurrence in early-stage NSCLC. Specifically, it investigates the potential of a tumor-specific phylogenetic approach to ctDNA profiling in patients enrolled in the TRACERx study.
Main Methods/Materials/Experimental Design
The study employs a bespoke multiplex-PCR next-generation sequencing (NGS) approach to analyze ctDNA from plasma samples of 100 patients. The methodology is illustrated below using a flowchart in Mermaid syntax:
Key steps include:
- Patient Selection: 100 early-stage NSCLC patients from the TRACERx study.
- Sample Collection: Pre-operative and post-operative plasma samples were collected.
- ctDNA Extraction: Cell-free DNA was extracted from plasma.
- Assay Design: Patient-specific multiplex-PCR assays were designed targeting clonal and subclonal single nucleotide variants (SNVs).
- NGS and Analysis: The ctDNA was sequenced and analyzed to construct phylogenetic trees for tracking tumor evolution.
Key Results and Findings
- ctDNA Detection: ctDNA was detected in 48% of patients pre-operatively, with significant differences in detection rates based on histological subtype.
- Predictors of ctDNA Release: Factors such as non-adenocarcinoma histology, lymphovascular invasion, and high Ki67 proliferation index were identified as independent predictors of ctDNA detection.
- Correlation with Tumor Volume: There was a linear relationship between tumor volume and mean plasma variant allele frequency (VAF) of clonal SNVs.
- Relapse Prediction: In a subgroup of 24 patients, ctDNA profiling successfully detected relapse in 93% of confirmed cases before clinical imaging, with a median lead time of 70 days.
Main Conclusions/Significance/Innovation
This study demonstrates that phylogenetic ctDNA profiling can effectively track tumor evolution and predict relapse in early-stage NSCLC. The findings suggest that ctDNA can serve as a non-invasive biomarker for monitoring residual disease and guiding adjuvant therapy, potentially improving patient outcomes by targeting emerging subclones prior to clinical recurrence.
Research Limitations and Future Directions
- Cost and Accessibility: The bespoke ctDNA profiling approach is expensive, which may limit its widespread application.
- Sensitivity Constraints: The detection of small tumor burdens remains a challenge with current technologies.
- Future Directions: Further research is needed to refine ctDNA detection methods, reduce costs, and explore the integration of ctDNA profiling into routine clinical practice for better management of NSCLC.
| Section | Details |
|---|---|
| Research Background | Lung cancer is a leading cause of death; early detection of relapse is critical for outcomes. |
| Methods | Multiplex-PCR NGS approach; phylogenetic ctDNA profiling from plasma samples. |
| Key Findings | ctDNA detected in 48% of patients; significant predictors identified; successful relapse prediction. |
| Conclusions | Phylogenetic ctDNA profiling is effective for tracking tumor evolution and predicting relapse. |
| Limitations | High cost and sensitivity issues; need for further research to improve methods. |
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Literatures Citing This Work
- Lung cancer: Tracing tumour evolution. - Diana Romero - Nature reviews. Clinical oncology (2017)
- Cancer genomics: Tracking cancer evolution. - Carolina Perdigoto - Nature reviews. Genetics (2017)
- Medical research: Personalized test tracks cancer relapse. - Alberto Bardelli - Nature (2017)
- Circular RNAs: Biogenesis, Function and Role in Human Diseases. - John Greene;Anne-Marie Baird;Lauren Brady;Marvin Lim;Steven G Gray;Raymond McDermott;Stephen P Finn - Frontiers in molecular biosciences (2017)
- Cancer genomics: Human metastases under scrutiny. - G Steven Bova - Nature (2017)
- ALK Status Assessment with Liquid Biopsies of Lung Cancer Patients. - Paul Hofman - Cancers (2017)
- Circulating tumor DNA for personalized lung cancer monitoring. - Clare Fiala;Eleftherios P Diamandis - BMC medicine (2017)
- Unravelling biology and shifting paradigms in cancer with single-cell sequencing. - Timour Baslan;James Hicks - Nature reviews. Cancer (2017)
- Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes. - Jasmine A McQuerry;Jeffrey T Chang;David D L Bowtell;Adam Cohen;Andrea H Bild - Journal of molecular medicine (Berlin, Germany) (2017)
- Progress and prospects of early detection in lung cancer. - Sean Blandin Knight;Phil A Crosbie;Haval Balata;Jakub Chudziak;Tracy Hussell;Caroline Dive - Open biology (2017)
... (903 more literatures)
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