Cancer heterogeneity: Implications for targeted therapeutics

1] University College London Cancer Institute, London, UK [2] Department of Medicine, Royal Marsden Hospital, London UK.
British Journal of Cancer (Impact Factor: 4.84). 01/2013; 108(3). DOI: 10.1038/bjc.2012.581
Source: PubMed


Developments in genomic techniques have provided insight into the remarkable genetic complexity of malignant tumours. There is increasing evidence that solid tumours may comprise of subpopulations of cells with distinct genomic alterations within the same tumour, a phenomenon termed intra-tumour heterogeneity. Intra-tumour heterogeneity is likely to have implications for cancer therapeutics and biomarker discovery, particularly in the era of targeted treatment, and evidence for a relationship between intra-tumoural heterogeneity and clinical outcome is emerging. Our understanding of the processes that exacerbate intra-tumoural heterogeneity, both iatrogenic and tumour specific, is likely to increase with the development and more widespread implementation of advanced sequencing technologies, and adaptation of clinical trial design to include comprehensive tissue collection protocols. The current evidence for intra-tumour heterogeneity and its relevance to cancer therapeutics will be presented in this mini-review.British Journal of Cancer advance online publication, 8 January 2013; doi:10.1038/bjc.2012.581

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Available from: Charles Swanton, Jul 22, 2014
    • "Ten of the sample pairs contained discordant mutations, of which two contained mutations in tDNA only, five had mutations in plasma ctDNA only, and three contained mutations in both tDNA and plasma ctDNA, but these mutations were not the same between the sampletypes. Because lung cancer tumors are heterogeneous with clonal sub-populations, it is possible that for mutations found in plasma ctDNA and not in tDNA, the individual tumor biopsy did not represent the entire tumor, which can be particularly problematic when biopsy samples are small293031. This factor may also account for the discrepancies found between the three matched sample pairs containing different mutations. "
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    ABSTRACT: Non-small cell lung cancers (NSCLC) have unique mutation patterns, and some of these mutations may be used to predict prognosis or guide patient treatment. Mutation profiling before and during treatment often requires repeated tumor biopsies, which is not always possible. Recently, cell-free, circulating tumor DNA (ctDNA) isolated from blood plasma has been shown to contain genetic mutations representative of those found in the primary tumor tissue DNA (tDNA), and these samples can readily be obtained using non-invasive techniques. However, there are still no standardized methods to identify mutations in ctDNA. In the current study, we used a targeted sequencing approach with a semi-conductor based next-generation sequencing (NGS) platform to identify gene mutations in matched tDNA and ctDNA samples from 42 advanced-stage NSCLC patients from China. We identified driver mutations in matched tDNA and ctDNA in EGFR, KRAS, PIK3CA, and TP53, with an overall concordance of 76%. In conclusion, targeted sequencing of plasma ctDNA may be a feasible option for clinical monitoring of NSCLC in the near future.
    No preview · Article · Nov 2015 · Cancer letters
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    • "However, obtaining sufficient tissue for mutation analysis in patients with advanced disease is challenging, as invasive interventions may be ineffective and unsafe. Moreover, detection of disease-relevant mutations from the biopsy of a single tumor lesion may not be reflective of the patient's complete disease burden, especially in heterogeneous cancers [1] [2]. "
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    ABSTRACT: Objectives: To assess the ability of different technology platforms to detect epidermal growth factor receptor (EGFR) mutations, including T790M, from circulating tumor DNA (ctDNA) in advanced non-small cell lung cancer (NSCLC) patients. Materials and methods: A comparison of multiple platforms for detecting EGFR mutations in plasma ctDNA was undertaken. Plasma samples were collected from patients entering the ongoing AURA trial (NCT01802632), investigating the safety, tolerability, and efficacy of AZD9291 in patients with EGFR-sensitizing mutation-positive NSCLC. Plasma was collected prior to AZD9291 dosing but following clinical progression on a previous EGFR-tyrosine kinase inhibitor (TKI). Extracted ctDNA was analyzed using two non-digital platforms (cobas(®) EGFR Mutation Test and therascreen™ EGFR amplification refractory mutation system assay) and two digital platforms (Droplet Digital™ PCR and BEAMing digital PCR [dPCR]). Results: Preliminary assessment (38 samples) was conducted using all four platforms. For EGFR-TKI-sensitizing mutations, high sensitivity (78-100%) and specificity (93-100%) were observed using tissue as a non-reference standard. For the T790M mutation, the digital platforms outperformed the non-digital platforms. Subsequent assessment using 72 additional baseline plasma samples was conducted using the cobas(®) EGFR Mutation Test and BEAMing dPCR. The two platforms demonstrated high sensitivity (82-87%) and specificity (97%) for EGFR-sensitizing mutations. For the T790M mutation, the sensitivity and specificity were 73% and 67%, respectively, with the cobas(®) EGFR Mutation Test, and 81% and 58%, respectively, with BEAMing dPCR. Concordance between the platforms was >90%, showing that multiple platforms are capable of sensitive and specific detection of EGFR-TKI-sensitizing mutations from NSCLC patient plasma. Conclusion: The cobas(®) EGFR Mutation Test and BEAMing dPCR demonstrate a high sensitivity for T790M mutation detection. Genomic heterogeneity of T790M-mediated resistance may explain the reduced specificity observed with plasma-based detection of T790M mutations versus tissue. These data support the use of both platforms in the AZD9291 clinical development program.
    Full-text · Article · Oct 2015 · Lung cancer (Amsterdam, Netherlands)
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    • "The same applies when disruptive alterations hit on the same gene, e.g., pten's mutations and deletions in prostate cancer [25]. An immediate consequence of this state of affair is the dramatic heterogeneity and temporality of cancer, both at the inter-tumor and at the intra-tumor levels [26]. The former manifests as different patients with the same cancer type can display few common alterations. "
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    DESCRIPTION: The evolutionary nature of cancer relates directly to a renewed focus on the voluminous NGS (next generation sequencing) data, aiming at the identification of explanatory models of how the (epi)genomic events are choreographed in cancer initiation and development. However, despite the increasing availability of multiple additional -omics data, this quest has been frustrated by various theoretical and technical hurdles, mostly related to the dramatic heterogeneity and temporality of the disease. In this paper, we build on our recent works on selectivity relation among driver mutations in cancer progression and investigate their applicability to the modeling problem - both at the population and individual levels. On one hand, we devise an optimal, versatile and modular pipeline to extract ensemble-level progression models from cross sectional sequenced cancer genomes. The pipeline combines state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent exclusive alterations and progression model inference. We demonstrate this pipeline's ability to reproduce much of the current knowledge on colorectal cancer progression, as well as to suggest novel experimentally verifiable hypotheses. On the other hand, we prove that our framework can be applied, mutatis mutandis, in reconstructing the evolutionary history of cancer clones in single patients, as illustrated by an example with multiple biopsy data from clear cell renal carcinomas.
    Full-text · Research · Sep 2015
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