Circulating tumour DNA reflects treatment response and clonal evolution in chronic lymphocytic leukaemia

Yeh, Paul; Hunter, Tane; Sinha, Debajyoti; Ftouni, Sarah; Wallach, Elise; Jiang, Damian H S; Chan, Yih-Chih; Wong, Stephen Q.; Silva, Maria João; Vedururu, Ravikiran; Doig, Kenneth D.; Lam, Enid Y.N.; Arnau, Gisela Mir; Semple, Timothy; Wall, Meaghan; Zivanovic, Andjelija; Agarwal, Rishu; Petrone, Pasquale; Jones, K.L.; Westerman, David; Blombery, Piers; Seymour, John F.; Papenfuss, Anthony T.; Dawson, Mark A.; Tam, Constantine S.; Dawson, Sarah‐Jane

doi:10.1038/ncomms14756

Cited by 79 publications

(54 citation statements)

References 41 publications

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“…Current research has shown that ctDNA and CTC analysis can detect emerging mutations associated with treatment resistance, which includes the identification of T790M-EGFR mutations in NSCLC (Maheswaran et al 2008;Murtaza et al 2013;Oxnard et al 2014;Chabon et al 2016), KRAS mutations and mesenchymal-epithelial transition factor (MET) amplification in colorectal cancer patients receiving EGFR-based therapies (Diaz et al 2012;Misale et al 2012Misale et al , 2014Bardelli et al 2013;Siravegna et al 2015), the development of ESR1 mutations in hormone-resistant breast cancer (Yu et al 2014;Schiavon et al 2015), and the development of androgen receptor mutations and copy number changes, as well as the androgen receptor splice variant 7 (ARV7) in patients receiving treatment for advanced prostate cancer (Carreira et al 2014;Romanel et al 2015;Scher et al 2016). The application of serial ctDNA analysis through NGS of plasma DNA has also been shown to provide a comprehensive and unbiased assessment of genomic changes and tumor evolution during the acquisition of treatment resistance (Murtaza et al 2013(Murtaza et al , 2015Chabon et al 2016;Scherer et al 2016;Abbosh et al 2017;Yeh et al 2017b). Furthermore, the ability to isolate viable CTCs, culture CTCs ex vivo, and generate CTC-derived xenograft mouse models is opening up a vast array of new opportunities to perform drug sensitivity testing and study drug resistance mechanisms to guide personalized treatment approaches (Hodgkinson et al 2014;Yu et al 2014).…”

Section: Monitoring Tumor Burden and Therapeutic Responsesmentioning

confidence: 99%

Characterizing the Cancer Genome in Blood

Dawson

2018

Cold Spring Harb Perspect Med

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Cell-free circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) can be found in the bloodstream of individuals with cancer and are increasingly being explored as biomarkers in various aspects of cancer management. The application of next-generation sequencing (NGS) technologies to ctDNA and CTC analysis are providing new opportunities to characterize the cancer genome from a simple blood test and can facilitate the ease with which tumor-specific genomic changes can be followed over time. The serial analysis of ctDNA and CTCs has enormous potential to provide insights into intratumor heterogeneity and clonal evolution during disease progression, and may ultimately allow noninvasive molecular disease monitoring to guide therapeutic decisions and improve patient outcomes.

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Section: Monitoring Tumor Burden and Therapeutic Responsesmentioning

confidence: 99%

Characterizing the Cancer Genome in Blood

Dawson

2018

Cold Spring Harb Perspect Med

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“…The effect of aromatase inhibitors on clonal architecture was shown by WGS analysis of matched tumour-normal pairs before and after neoadjuvant therapy in oestrogen-receptorpositive breast cancers, 49 and resistance and clonal advantage after therapy was identified in circulating tumour DNA in chronic lymphocytic leukaemia. 50 Here we showed for the first time that the analysis of subclonal events in matched metastatic tumour samples can also be used for a retrospective analysis of the timing metastatic events, even using standardcoverage WGS data, contributing to our understanding of the evolution of oligometastatic disease, as well as of the genomic imprint of chemotherapeutic treatments.…”

Section: Discussionmentioning

confidence: 94%

The genomic imprint of cancer therapies helps timing the formation of metastases

Németh

Krzystanek

Reiniger

et al. 2019

Intl Journal of Cancer

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A retrospective determination of the time of metastasis formation is essential for a better understanding of the evolution of oligometastatic cancer. This study was based on the hypothesis that genomic alterations induced by cancer therapies could be used to determine the temporal order of the treatment and the formation of metastases. We analysed the whole genome sequence of a primary tumour sample and three metastatic sites derived from autopsy samples from a young never‐smoker lung adenocarcinoma patient with an activating EGFR mutation. Mutation detection methods were refined to accurately detect and distinguish clonal and subclonal mutations. In comparison to a panel of samples from untreated smoker or never‐smoker patients, we showed that the mutagenic effect of cisplatin treatment could be specifically detected from the base substitution mutations. Metastases that arose before or after chemotherapeutic treatment could be distinguished based on the allele frequency of cisplatin‐induced dinucleotide mutations. In addition, genomic rearrangements and late amplification of the EGFR gene likely induced by afatinib treatment following the acquisition of a T790M gefitinib resistance mutation provided further evidence to tie the time of metastasis formation to treatment history. The established analysis pipeline for the detection of treatment‐derived mutations allows the drawing of tumour evolutionary paths based on genomic data, showing that metastases may be seeded well before they become detectable by clinical imaging.

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“…LN, bone marrow and PB) it represents an averaging tool and assesses the presence of these mutations across different biological sites. Yeh et al () demonstrated that monitoring ctDNA did not correlate with PB lymphocyte count, a traditional method of monitoring treatment response, as it is reflective of the dynamic of different disease compartments. However, they demonstrated a good correlation between ctDNA levels and MRD testing in CLL.…”

Section: Clinical Applications Of Next Generation Sequencingmentioning

confidence: 99%

Molecular pathogenesis of chronic lymphocytic leukaemia

Crassini¹,

Stevenson²,

Mulligan

et al. 2019

Br J Haematol

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Summary Chronic lymphocytic leukaemia (CLL) is characterised by the clonal expansion of mature, CD5 positive, B lymphocytes in the blood, marrow, lymph nodes and spleen. For the majority of patients, CLL follows an indolent clinical course, while a proportion of patients experience rapid disease progression. Despite the strong correlation between certain genetic defects and prognosis, there remains no single unifying pathogenic lesion in CLL. With recent advances in therapy it is increasingly important to stratify CLL patients according to risk. This has been highlighted by two recent studies, the first showing that immunoglobulin heavy chain mutational status predicts a durable response to frontline chemoimmunotherapy and the second showing that complex karyotype is a stronger predictor of poor response to ibrutinib and venetoclax therapy than TP53 deletion. In this review we discuss the molecular features of CLL and how technological advances can identify patient subsets and stratify them according to risk.

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Circulating tumour DNA reflects treatment response and clonal evolution in chronic lymphocytic leukaemia

Cited by 79 publications

References 41 publications

Characterizing the Cancer Genome in Blood

Characterizing the Cancer Genome in Blood

The genomic imprint of cancer therapies helps timing the formation of metastases

Molecular pathogenesis of chronic lymphocytic leukaemia

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