Commentary For reprint orders, please contact: [email protected]
Dynamic sequencing of circulating tumor DNA: novel noninvasive cancer biomarker “
...multiple basic science insights into cancer genomics underlying therapeutic resistance and new clinical trials are essential before wide clinical application of liquid biopsy and DNA sequencing.
”
Keywords: biomarker • cancer • circulating tumor DNA • clonal evolution • clonal selection • recurrence coding and noncoding genetic variation • regulatory networks • resistance • transcription • tumor heterogeneity
Georgios D Lianos1,2, Alberto Mangano3, Gregory Kouraklis 4 & Dimitrios H Roukos*,1,2,5 Centre for Biosystems & Genomic Network Medicine, University of Ioannina, Ioannina, Greece 2 Dept. of Surgery, Ioannina University Hospital, Ioannina, Greece 3 Dept. of Surgical Sciences & Human Morphology, Insubria University Hospital, Varese, Italy 4 Second Department of Propedeutic Surgery, Athens University Medical School, ‘Laiko’ Hospital, Athens, Greece 5 Biomedical Research Foundation of Academy of Athens (BRFAA), Systems Biology, Athens, Greece *Author for correspondence: droukos@ uoi.gr 1
Despite high-throughput technological and computational advances, progress in discovering robust biomarkers for personalized monitoring of cancer patients with potentially curable or metastatic disease is modest. Genome sequencing of ‘fluid’ biopsy may be a novel robust biomarker in monitoring cancer patients after treatment. In this article, we highlight the proof of principle for circulating tumor DNA (ctDNA) sequencing provided by a recent study [1] and the challenges for clinical implementation. If confirmed, this new method will change clinical trials’ design. The combination of this new technique for ctDNA detection in plasma and the subsequent next-generation sequencing (NGS) can provide a dual advantage. First, it can early predict recurrence or disease progression before this event occurs. Second, this ctDNA-NGS-based approach can guide a new therapeutic decision selecting drug(s) to disrupt cellular pathways deregulated by initial therapy-resistant emerging mutations and clonal selection rather than primary tumor genetic analysis. Single biopsy-based modern oncology Understanding therapeutic resistance and recurrence is central in emerging research. Alterations of the cancer genome can lead to gene expression and signaling pathways network aberration. This cellular network deregulation results in transformation of normal or benign cells to cancer cells. Following this initial tumorigenesis, the next step,
10.2217/BMM.14.35 © 2014 Future Medicine Ltd
usually after several years if tumor remains untreated, is tumor progression and acquisition of metastatic ability in a small population of cells within an individual tumor. The molecular mechanisms of this metastatic selection and survival advantage of these cells as a response to current systemic therapy is crucial for understanding resistance to modern chemotherapy and tumor cells’ specific mutations-targeted agents. Currently, decision-making therapy by oncologists is based on traditional clinicopathologic criteria and a single cancer tissue sample-based genetic testing. This therapeutic approach uses genetic analysis information from patient-derived primary tumor obtained sample after surgical resection, endoscopic biopsy or needle biopsy. Current clinical models are based on a single biopsy ignoring intratumor heterogeneity and cancer genome evolution. Indeed, despite complete tumor resection by surgery, radiotherapy in selected cases and systemic treatment with chemotherapy and trastuzumab for human HER2-positive breast cancer, 23% of this selected patients’ subpoulation develops recurrence at a median follow-up of 8 years after treatment [2] . Identifying possible explanations and molecular mechanisms underlying this high recurrence rate despite targeting specific therapy in selected patients is a high priority of current research. Hot topics for explaining this treatment resistance are intratumor spatial heterogeneity [3] and dynamics of clonal selection and mutational evolution as a response to therapy [4–6] .
Biomarkers Med. (2014) 8(5), 629–632
part of
ISSN 1752-0363
629
Commentary Lianos, Mangano, Kouraklis & Roukos Cancer genome evolution The macroscopic observations of Darwin’s theory on natural selection in the recent years of the postgenomics era have been confirmed using NGS. Although selection and adaption of species have been translated into the evolutionary concept of cancer by Nowell in 1976 [7] , only recently with the availability and application of high-throughput technology, it became feasible to analyze clinical samples and data. Such evidence obtained has made widely accepted the concept of resistance-emerging mutations leading to innovative techniques of noninvasive, patient-derived repeated plasma DNA genomic analysis over the course of diseases to assess clonal selection and evolution, monitoring and improving treatment and clinical outcomes of cancer patient [8] . Noninvasive diagnostics: from prenatal to cancer management The technique of maternal circulating cell-free fetal DNA analysis has already been established as an exciting noninvasive prenatal testing technique as early as the first trimester of pregnancy. It can be used not only for assessing genetic disorders but also to predict adults’ disease risk. For example, predisposition to common complex diseases such as diabetes or even cancer syndromes such as hereditary breast ovarian cancer syndrome by identifying heritable mutations in the predisposition cancer genes (BRCA1 and BRCA2) can be predicted. From this single-gene testing, NGS technologies have revolutionized genetics and genomics allowing either sequencing the protein coding region (∼22,000 genes) termed as whole-exome sequencing (WES) or even coding and noncoding regions (whole-genome sequencing (WGS). Exploiting this breakthrough technique, Fan and colleagues have recently reported WGS from maternal cell-free fetal DNA [9] .
“
...progress in discovering robust biomarkers for personalized monitoring of cancer patients with potentially curable or metastatic disease is modest.
”
This noninvasive ‘fluid’ concept is now successfully translated into cancer. Using a method developed at Rosenfeld Laboratory, Cambridge University, UK [10] , Murtaza et al. [1] have analyzed ctDNA released from dying tumor cells in six patients. Selecting patients with advanced disease (breast and ovarian lung cancer) and for repeated sampling serial analysis on two to five plasma samples (19 in total) at selected time points over 1–2 years of prospective evaluation of ctDNA during and after completion of treatment, the researchers managed for the first time to overcome two challenges at the
630
Biomarkers Med. (2014) 8(5)
same time. First, how to detect ctDNAs clones in early stage cancer with limited amount of ctDNA. Second, how to assess gene expression deregulation from these sequence data. This strategy has allowed the revealing of emerging mutations in parallel with the emergence of therapy resistance. Indeed, emergence of mutations and resistance to systemic chemotherapy and targeted therapy were found. Resistance to paclitaxel or cisplatin followed the emergence of activating mutations in PIK3CA and in RB1. Similar relationships were found following targeted therapy such as a mutation in MED1 after tamoxifen and trastuzumab and mutation in EGFR (T790M) following treatment with gefitinib [1] . Based on these findings, Murtaza et al. [1] reported on the establishment of cell-free ctDNA WES proof of principle that could, together with current invasive biopsy methods, understand the emergence of mutations with acquired therapeutic resistance and develop new therapeutic strategies to predict and prevent resistance. This exciting report creates a fascinating new research horizon but also raises a series of questions and problems about clinical integration of the fluid noninvasive concept in the clinical management of cancer patients. Dynamic noninvasive clinical diagnostics Discovering cancer genes and pathways in the disease course, which potentially are different than that of primary tumor diagnostics, can affect clinical outcome. Predicting resistance to therapy attributable to the emergence of mutations can change therapeutic strategy providing clinical utility. Metastasis is the primary cause of death. However, despite long-term effort and major funding, progress is too slow. In both settings, either to prevent metastasis in the adjuvant setting before clinical occurrence of secondary tumors or to improve survival in patients with established distant metastasis, clinical progress is modest despite advances in the multimodal treatment. With NGS-based evidence of cancer genomics heterogeneity, one pressing task is to develop robust biomarkers for personalized cancer medicine. Circulating biomarkers provide a series of advantages as compared with invasive biopsies of metastatic tumors. The recently developed method of ctDNA sequencing represents an exciting perspective for reaching the 3P; namely prognostic, predictive and personalized or precision medicine. Genomic changes over a dynamic course of disease can represent a key cause of resistance and treatment failure. Recent studies have demonstrated that genomic abnormalities such as somatic mutations and copy number alterations (CNAs) in ctDNA can reveal the treatment resistance [11,12] . Therefore, NGSbased analysis of ctDNA could be used as a reliable biomarker for monitoring disease. Indeed, ctDNA
future science group
Dynamic sequencing of circulating tumor DNA: novel noninvasive cancer biomarker
genomics is a novel paradigm not only for explaining resistance but also predicting disease progression before clinical manifestation of new metastasis, paving the way for application of emergence mutations-based therapy, which can be different from the initial primary tumor single biopsy-based treatment. For example, why do ER-positive and HER2-positive breast cancer women selected and treated with tamoxifen and trastuzumab, respectively, develop resistance when the combination of targeted drugs with cytotoxic chemotherapy should eliminate all cancer cells? Evidence is provided by the Murtaza et al. [1] report in which WES of ctDNA obtained from these ER-/HER2- postive patients showed that this resistance to tamoxifen plus trastuzumab was associated with the emergence of mutations in cancer genes other than ER and HER2. Therefore, using NGS in ctDNA is fundamental for early new targeted therapy to inhibit driver mutation cancer genes and biological pathways that are being activated during the course of disease as a response to systemic therapy.
marker for monitoring and personalizing decisionmaking treatment in most cancer types. Particularly in localized tumors without presence of distant metastasis, ctDNA represents a unique opportunity to predict resistance to chemotherapy and/or targeted agents and potentially apply a new more effective therapy in the follow-up after completion of multidisciplinary treatment. Recent studies have shown a significant advantage of ctDNA sequencing by revealing a landscape of driver mutations from multiple metastatic sites as compared with a single biopsy from a single metastatic tumor. Future studies in localized disease can predict relapse at any site before metastasis occurs and potentially development of new therapies to disrupt this fatal metastatic mechanism and prevent metastasis outcome.
Future perspective The latest developments in NGS platforms and further ctDNA technique improvements will create amazing perspectives over the next few years in the research arena. This year, the announcement of the commercial availability of new NGS platforms proving WGS data for US$1000 at a short time of 1-day results by a large genomic company in the USA shapes a new environment. More recently, WGS in ctDNA has been reported [13] . Progress in the method of ctDNA detection is rapid. In a more recent large study [14] , Bettegowda and colleagues used digital PCR-based technologies for detecting ctDNA on 640 patients with various cancer types. High ctDNA detection rates identify not only of patients with late-stage but also of those patients with early-stage disease. The ctDNA detection rates were >75% in patients with advanced cancer and for localized disease; these rates ranged from 48% for pancreatic cancer reaching to 73% for patients with colorectal cancer. Studying resistance to anti-EGFR therapy, the researchers found via ctDNA sequencing that 96% of patients who relapsed after this treatment had developed mutations in genes involved in the MAPK pathway. These results reveal the ability of ctDNA sequencing to be used widely for different cancer types as a biomarker to predict treatment resistance and relapse, but clearly clinical trials will be required to prove the clinical utility of cDNA-NGS genomic analysis for clinical applications. Taken together, ctDNA-NGS-based method represent an exciting perspective for clinical use as a bio-
However, despite these optimal expectations, multiple basic science insights into cancer genomics underlying therapeutic resistance and new clinical trials are essential before wide clinical application of liquid biopsy and DNA sequencing. In summary, these challenges include: first, the completion of cancer genes catalog over the next years through underway international large-scale genomic studies [15,16] . Because of genomic heterogeneity the number of cancer genes should be much larger than the currently estimated number of approximately 500 genes involved in cancer [17] . Second, a much bigger problem for the future is to understand how the 75–85% of noncoding region of the genome affects the expression of interacting proteincoding genes of the genome, which represent a highly complicated regulatory system, affect the expression of interacting tissue-specific protein-coding genes [18–23] . Third, long-term clinical trials with novel dynamic design for serial ctDNA sequencing (WES/WGS) will be required to assess whether patients with localized or metastatic tumor benefit from this personalizing monitoring of disease.
future science group
Commentary
“The latest developments in next-generation
sequencing platforms and further circulating tumor DNA technique improvements will create amazing perspectives over the next few years in the research arena.
”
Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
www.futuremedicine.com
631
Commentary Lianos, Mangano, Kouraklis & Roukos with whole-genome sequencing. Sci. Transl. Med. 4, 162 (2012).
References 1
Murtaza M, Dawson SJ, Tsui DW et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013).
2
Goldhirsch A, Gelber RD, Piccart-Gebhart MJ et al. 2 years versus 1 year of adjuvant trastuzumab for HER2-positive breast cancer (HERA): an open-label, randomised controlled trial. Lancet 382(9897), 1021–1028 (2013).
3
Gerlinger M, Rowan NJ, Horswell S et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366(10), 883–892 (2012).
4
Aparicio S, Caldas C. The implications of clonal genome evolution for cancer medicine. N. Engl. J. Med. 368, 842–851 (2013).
5
Klein CA. Selection and adaptation during metastatic cancer progression. Nature 501(7467), 365–372 (2013).
6
Bedard PL, Hansen AR, Ratain MJ, Siu LL et al. Tumour heterogeneity in the clinic. Nature 501, 355–364 (2013).
7
Nowell PC. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).
8
Pantel K, Diaz LA Jr, Polyak K. Tracking tumor resistance using ‘liquid biopsies’. Nat. Med. 19(6), 676–677 (2013).
9
Fan HC, Gu W, Wang J, Blumenfeld YJ, El-Sayed YY, Quake SR. Non-invasive prenatal measurement of the fetal genome. Nature 487, 320–324 (2012).
10
The Rosenfeld Lab: noninvasive cancer diagnostics. www.rosenfeldlab.org
11
Chan KC, Jiang P, Zheng YW et al. Cancer genome scanning in plasma: detection of tumorassociated copy number aberrations, single-nucleotide variants, and tumoral heterogeneity by massively parallel sequencing. Clin. Chem. 59, 211–224 (2013).
12
632
Leary RJ, Sausen M, Kinde I et al. Detection of chromosomal alterations in the circulation of cancer patients
Biomarkers Med. (2014) 8(5)
13
Leary RJ, Sausen M, Diaz LA Jr, Velculescu VE. Cancer detection using whole-genome sequencing of cell free DNA. Oncotarget 4(8), 1119–1120 (2013).
14
Bettegowda C, Sausen M, Leary RJ et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6(224), 224ra24 (2014).
15
The Cancer Genome Atlas – National Cancer Institute. http://cancergenome.nih.gov
16
International Cancer Genome Consortium. http://icgc.org
17
Lawrence MS, Stojanov P, Mermel CH et al. Discovery and saturation analysis of cancer genes across 21 tumor types. Nature 505(7484), 495–501 (2014).
18
Gerstein MB, Kundaje A, Hariharan M et al. Architecture of the human regulatory network derived from ENCODE data. Nature 489(7414), 91–100 (2012).
19
Neph S, Stergachis AB, Reynolds A, Sandstrom R, Borenstein E, Stamatoyannopoulos JA. Circuitry and dynamics of human transcription factor regulatory networks. Cell 150(6), 1274–1286 (2012).
20
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489(7414), 57–74 (2012).
21
Sanyal A, Lajoie B, Jain G, Dekker J. The long-range interaction landscape of gene promoters. Nature 489(7414), 109–113 (2012).
22
Yosef N, Shalek AK, Gaublomme JT et al. Dynamic regulatory network controlling Th17 cell differentiation. Nature 496(7446), 461–468 (2013).
23
Cheng TM, Gulati S, Agius R, Bates PA. Understanding cancer mechanisms through network dynamics. Brief Funct. Genomics 11(6), 543–560 (2012).
future science group
Dynamic sequencing of circulating tumor DNA: novel noninvasive cancer biomarker “
...multiple basic science insights into cancer genomics underlying therapeutic resistance and new clinical trials are essential before wide clinical application of liquid biopsy and DNA sequencing.
”
Keywords: biomarker • cancer • circulating tumor DNA • clonal evolution • clonal selection • recurrence coding and noncoding genetic variation • regulatory networks • resistance • transcription • tumor heterogeneity
Georgios D Lianos1,2, Alberto Mangano3, Gregory Kouraklis 4 & Dimitrios H Roukos*,1,2,5 Centre for Biosystems & Genomic Network Medicine, University of Ioannina, Ioannina, Greece 2 Dept. of Surgery, Ioannina University Hospital, Ioannina, Greece 3 Dept. of Surgical Sciences & Human Morphology, Insubria University Hospital, Varese, Italy 4 Second Department of Propedeutic Surgery, Athens University Medical School, ‘Laiko’ Hospital, Athens, Greece 5 Biomedical Research Foundation of Academy of Athens (BRFAA), Systems Biology, Athens, Greece *Author for correspondence: droukos@ uoi.gr 1
Despite high-throughput technological and computational advances, progress in discovering robust biomarkers for personalized monitoring of cancer patients with potentially curable or metastatic disease is modest. Genome sequencing of ‘fluid’ biopsy may be a novel robust biomarker in monitoring cancer patients after treatment. In this article, we highlight the proof of principle for circulating tumor DNA (ctDNA) sequencing provided by a recent study [1] and the challenges for clinical implementation. If confirmed, this new method will change clinical trials’ design. The combination of this new technique for ctDNA detection in plasma and the subsequent next-generation sequencing (NGS) can provide a dual advantage. First, it can early predict recurrence or disease progression before this event occurs. Second, this ctDNA-NGS-based approach can guide a new therapeutic decision selecting drug(s) to disrupt cellular pathways deregulated by initial therapy-resistant emerging mutations and clonal selection rather than primary tumor genetic analysis. Single biopsy-based modern oncology Understanding therapeutic resistance and recurrence is central in emerging research. Alterations of the cancer genome can lead to gene expression and signaling pathways network aberration. This cellular network deregulation results in transformation of normal or benign cells to cancer cells. Following this initial tumorigenesis, the next step,
10.2217/BMM.14.35 © 2014 Future Medicine Ltd
usually after several years if tumor remains untreated, is tumor progression and acquisition of metastatic ability in a small population of cells within an individual tumor. The molecular mechanisms of this metastatic selection and survival advantage of these cells as a response to current systemic therapy is crucial for understanding resistance to modern chemotherapy and tumor cells’ specific mutations-targeted agents. Currently, decision-making therapy by oncologists is based on traditional clinicopathologic criteria and a single cancer tissue sample-based genetic testing. This therapeutic approach uses genetic analysis information from patient-derived primary tumor obtained sample after surgical resection, endoscopic biopsy or needle biopsy. Current clinical models are based on a single biopsy ignoring intratumor heterogeneity and cancer genome evolution. Indeed, despite complete tumor resection by surgery, radiotherapy in selected cases and systemic treatment with chemotherapy and trastuzumab for human HER2-positive breast cancer, 23% of this selected patients’ subpoulation develops recurrence at a median follow-up of 8 years after treatment [2] . Identifying possible explanations and molecular mechanisms underlying this high recurrence rate despite targeting specific therapy in selected patients is a high priority of current research. Hot topics for explaining this treatment resistance are intratumor spatial heterogeneity [3] and dynamics of clonal selection and mutational evolution as a response to therapy [4–6] .
Biomarkers Med. (2014) 8(5), 629–632
part of
ISSN 1752-0363
629
Commentary Lianos, Mangano, Kouraklis & Roukos Cancer genome evolution The macroscopic observations of Darwin’s theory on natural selection in the recent years of the postgenomics era have been confirmed using NGS. Although selection and adaption of species have been translated into the evolutionary concept of cancer by Nowell in 1976 [7] , only recently with the availability and application of high-throughput technology, it became feasible to analyze clinical samples and data. Such evidence obtained has made widely accepted the concept of resistance-emerging mutations leading to innovative techniques of noninvasive, patient-derived repeated plasma DNA genomic analysis over the course of diseases to assess clonal selection and evolution, monitoring and improving treatment and clinical outcomes of cancer patient [8] . Noninvasive diagnostics: from prenatal to cancer management The technique of maternal circulating cell-free fetal DNA analysis has already been established as an exciting noninvasive prenatal testing technique as early as the first trimester of pregnancy. It can be used not only for assessing genetic disorders but also to predict adults’ disease risk. For example, predisposition to common complex diseases such as diabetes or even cancer syndromes such as hereditary breast ovarian cancer syndrome by identifying heritable mutations in the predisposition cancer genes (BRCA1 and BRCA2) can be predicted. From this single-gene testing, NGS technologies have revolutionized genetics and genomics allowing either sequencing the protein coding region (∼22,000 genes) termed as whole-exome sequencing (WES) or even coding and noncoding regions (whole-genome sequencing (WGS). Exploiting this breakthrough technique, Fan and colleagues have recently reported WGS from maternal cell-free fetal DNA [9] .
“
...progress in discovering robust biomarkers for personalized monitoring of cancer patients with potentially curable or metastatic disease is modest.
”
This noninvasive ‘fluid’ concept is now successfully translated into cancer. Using a method developed at Rosenfeld Laboratory, Cambridge University, UK [10] , Murtaza et al. [1] have analyzed ctDNA released from dying tumor cells in six patients. Selecting patients with advanced disease (breast and ovarian lung cancer) and for repeated sampling serial analysis on two to five plasma samples (19 in total) at selected time points over 1–2 years of prospective evaluation of ctDNA during and after completion of treatment, the researchers managed for the first time to overcome two challenges at the
630
Biomarkers Med. (2014) 8(5)
same time. First, how to detect ctDNAs clones in early stage cancer with limited amount of ctDNA. Second, how to assess gene expression deregulation from these sequence data. This strategy has allowed the revealing of emerging mutations in parallel with the emergence of therapy resistance. Indeed, emergence of mutations and resistance to systemic chemotherapy and targeted therapy were found. Resistance to paclitaxel or cisplatin followed the emergence of activating mutations in PIK3CA and in RB1. Similar relationships were found following targeted therapy such as a mutation in MED1 after tamoxifen and trastuzumab and mutation in EGFR (T790M) following treatment with gefitinib [1] . Based on these findings, Murtaza et al. [1] reported on the establishment of cell-free ctDNA WES proof of principle that could, together with current invasive biopsy methods, understand the emergence of mutations with acquired therapeutic resistance and develop new therapeutic strategies to predict and prevent resistance. This exciting report creates a fascinating new research horizon but also raises a series of questions and problems about clinical integration of the fluid noninvasive concept in the clinical management of cancer patients. Dynamic noninvasive clinical diagnostics Discovering cancer genes and pathways in the disease course, which potentially are different than that of primary tumor diagnostics, can affect clinical outcome. Predicting resistance to therapy attributable to the emergence of mutations can change therapeutic strategy providing clinical utility. Metastasis is the primary cause of death. However, despite long-term effort and major funding, progress is too slow. In both settings, either to prevent metastasis in the adjuvant setting before clinical occurrence of secondary tumors or to improve survival in patients with established distant metastasis, clinical progress is modest despite advances in the multimodal treatment. With NGS-based evidence of cancer genomics heterogeneity, one pressing task is to develop robust biomarkers for personalized cancer medicine. Circulating biomarkers provide a series of advantages as compared with invasive biopsies of metastatic tumors. The recently developed method of ctDNA sequencing represents an exciting perspective for reaching the 3P; namely prognostic, predictive and personalized or precision medicine. Genomic changes over a dynamic course of disease can represent a key cause of resistance and treatment failure. Recent studies have demonstrated that genomic abnormalities such as somatic mutations and copy number alterations (CNAs) in ctDNA can reveal the treatment resistance [11,12] . Therefore, NGSbased analysis of ctDNA could be used as a reliable biomarker for monitoring disease. Indeed, ctDNA
future science group
Dynamic sequencing of circulating tumor DNA: novel noninvasive cancer biomarker
genomics is a novel paradigm not only for explaining resistance but also predicting disease progression before clinical manifestation of new metastasis, paving the way for application of emergence mutations-based therapy, which can be different from the initial primary tumor single biopsy-based treatment. For example, why do ER-positive and HER2-positive breast cancer women selected and treated with tamoxifen and trastuzumab, respectively, develop resistance when the combination of targeted drugs with cytotoxic chemotherapy should eliminate all cancer cells? Evidence is provided by the Murtaza et al. [1] report in which WES of ctDNA obtained from these ER-/HER2- postive patients showed that this resistance to tamoxifen plus trastuzumab was associated with the emergence of mutations in cancer genes other than ER and HER2. Therefore, using NGS in ctDNA is fundamental for early new targeted therapy to inhibit driver mutation cancer genes and biological pathways that are being activated during the course of disease as a response to systemic therapy.
marker for monitoring and personalizing decisionmaking treatment in most cancer types. Particularly in localized tumors without presence of distant metastasis, ctDNA represents a unique opportunity to predict resistance to chemotherapy and/or targeted agents and potentially apply a new more effective therapy in the follow-up after completion of multidisciplinary treatment. Recent studies have shown a significant advantage of ctDNA sequencing by revealing a landscape of driver mutations from multiple metastatic sites as compared with a single biopsy from a single metastatic tumor. Future studies in localized disease can predict relapse at any site before metastasis occurs and potentially development of new therapies to disrupt this fatal metastatic mechanism and prevent metastasis outcome.
Future perspective The latest developments in NGS platforms and further ctDNA technique improvements will create amazing perspectives over the next few years in the research arena. This year, the announcement of the commercial availability of new NGS platforms proving WGS data for US$1000 at a short time of 1-day results by a large genomic company in the USA shapes a new environment. More recently, WGS in ctDNA has been reported [13] . Progress in the method of ctDNA detection is rapid. In a more recent large study [14] , Bettegowda and colleagues used digital PCR-based technologies for detecting ctDNA on 640 patients with various cancer types. High ctDNA detection rates identify not only of patients with late-stage but also of those patients with early-stage disease. The ctDNA detection rates were >75% in patients with advanced cancer and for localized disease; these rates ranged from 48% for pancreatic cancer reaching to 73% for patients with colorectal cancer. Studying resistance to anti-EGFR therapy, the researchers found via ctDNA sequencing that 96% of patients who relapsed after this treatment had developed mutations in genes involved in the MAPK pathway. These results reveal the ability of ctDNA sequencing to be used widely for different cancer types as a biomarker to predict treatment resistance and relapse, but clearly clinical trials will be required to prove the clinical utility of cDNA-NGS genomic analysis for clinical applications. Taken together, ctDNA-NGS-based method represent an exciting perspective for clinical use as a bio-
However, despite these optimal expectations, multiple basic science insights into cancer genomics underlying therapeutic resistance and new clinical trials are essential before wide clinical application of liquid biopsy and DNA sequencing. In summary, these challenges include: first, the completion of cancer genes catalog over the next years through underway international large-scale genomic studies [15,16] . Because of genomic heterogeneity the number of cancer genes should be much larger than the currently estimated number of approximately 500 genes involved in cancer [17] . Second, a much bigger problem for the future is to understand how the 75–85% of noncoding region of the genome affects the expression of interacting proteincoding genes of the genome, which represent a highly complicated regulatory system, affect the expression of interacting tissue-specific protein-coding genes [18–23] . Third, long-term clinical trials with novel dynamic design for serial ctDNA sequencing (WES/WGS) will be required to assess whether patients with localized or metastatic tumor benefit from this personalizing monitoring of disease.
future science group
Commentary
“The latest developments in next-generation
sequencing platforms and further circulating tumor DNA technique improvements will create amazing perspectives over the next few years in the research arena.
”
Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
www.futuremedicine.com
631
Commentary Lianos, Mangano, Kouraklis & Roukos with whole-genome sequencing. Sci. Transl. Med. 4, 162 (2012).
References 1
Murtaza M, Dawson SJ, Tsui DW et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013).
2
Goldhirsch A, Gelber RD, Piccart-Gebhart MJ et al. 2 years versus 1 year of adjuvant trastuzumab for HER2-positive breast cancer (HERA): an open-label, randomised controlled trial. Lancet 382(9897), 1021–1028 (2013).
3
Gerlinger M, Rowan NJ, Horswell S et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366(10), 883–892 (2012).
4
Aparicio S, Caldas C. The implications of clonal genome evolution for cancer medicine. N. Engl. J. Med. 368, 842–851 (2013).
5
Klein CA. Selection and adaptation during metastatic cancer progression. Nature 501(7467), 365–372 (2013).
6
Bedard PL, Hansen AR, Ratain MJ, Siu LL et al. Tumour heterogeneity in the clinic. Nature 501, 355–364 (2013).
7
Nowell PC. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).
8
Pantel K, Diaz LA Jr, Polyak K. Tracking tumor resistance using ‘liquid biopsies’. Nat. Med. 19(6), 676–677 (2013).
9
Fan HC, Gu W, Wang J, Blumenfeld YJ, El-Sayed YY, Quake SR. Non-invasive prenatal measurement of the fetal genome. Nature 487, 320–324 (2012).
10
The Rosenfeld Lab: noninvasive cancer diagnostics. www.rosenfeldlab.org
11
Chan KC, Jiang P, Zheng YW et al. Cancer genome scanning in plasma: detection of tumorassociated copy number aberrations, single-nucleotide variants, and tumoral heterogeneity by massively parallel sequencing. Clin. Chem. 59, 211–224 (2013).
12
632
Leary RJ, Sausen M, Kinde I et al. Detection of chromosomal alterations in the circulation of cancer patients
Biomarkers Med. (2014) 8(5)
13
Leary RJ, Sausen M, Diaz LA Jr, Velculescu VE. Cancer detection using whole-genome sequencing of cell free DNA. Oncotarget 4(8), 1119–1120 (2013).
14
Bettegowda C, Sausen M, Leary RJ et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6(224), 224ra24 (2014).
15
The Cancer Genome Atlas – National Cancer Institute. http://cancergenome.nih.gov
16
International Cancer Genome Consortium. http://icgc.org
17
Lawrence MS, Stojanov P, Mermel CH et al. Discovery and saturation analysis of cancer genes across 21 tumor types. Nature 505(7484), 495–501 (2014).
18
Gerstein MB, Kundaje A, Hariharan M et al. Architecture of the human regulatory network derived from ENCODE data. Nature 489(7414), 91–100 (2012).
19
Neph S, Stergachis AB, Reynolds A, Sandstrom R, Borenstein E, Stamatoyannopoulos JA. Circuitry and dynamics of human transcription factor regulatory networks. Cell 150(6), 1274–1286 (2012).
20
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489(7414), 57–74 (2012).
21
Sanyal A, Lajoie B, Jain G, Dekker J. The long-range interaction landscape of gene promoters. Nature 489(7414), 109–113 (2012).
22
Yosef N, Shalek AK, Gaublomme JT et al. Dynamic regulatory network controlling Th17 cell differentiation. Nature 496(7446), 461–468 (2013).
23
Cheng TM, Gulati S, Agius R, Bates PA. Understanding cancer mechanisms through network dynamics. Brief Funct. Genomics 11(6), 543–560 (2012).
future science group
