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Using Circulating Tumor DNA (ctDNA) in Cancer Detection
Mary Margaret Daniel Fall 2017
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Objectives What is ctDNA? Cancer genome-sequencing study design
Benefits of using ctDNA Benefits of using Next-generation sequencing (NGS) to study ctDNA Cancer genome-sequencing study design NGS of ctDNA for early cancer detection NGS of ctDNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy Future Directions Questions
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What is Circulating Tumor DNA?
Found in serum and plasma fractions from blood Originates directly from the tumor or from circulating tumor cells (CTCs) Precise mechanism of ctDNA release is unclear. Apoptosis, necrosis, and active secretions from tumor cells have been hypothesized. Once ctDNA is isolated it can be sequenced for mutational analysis. Figure 1: Diagram of how CTCs escape the primary tumor and incorporate into the bloodstream Reference: Friedrich M. Going With the Flow: The Promise and Challenge of Liquid Biopsies. JAMA. 2017;318(12):1095–1097. doi: /jama
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ctDNA Detection ctDNA is present in early cancers
ctDNA detection shows the genomic alterations and is a direct measurement of tumors ctDNA has potential to be more specific to the presence of tumors NGS DNA sequencing allows a high degree of target multiplexing Figure 2: ctDNA detection via liquid biopsies Reference: Bettegowda, Chetan & Sausen, Mark & J Leary, Rebecca & Kinde, Isaac & Wang, Yuxuan & Agrawal, Nishant & Bartlett, Bjarne & Wang, Hao & Luber, Brandon & M Alani, Rhoda & Antonarakis, Emmanuel & S Azad, Nilofer & Bardelli, Alberto & Brem, Henry & L Cameron, John & Lee, Clarence & Fecher, Leslie & L Gallia, Gary & Gibbs, Peter & A Diaz, Luis. (2014). Detection of Circulating Tumor DNA in Early- and Late-Stage Human Malignancies. Science translational medicine ra /scitranslmed
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Finding a Noninvasive Cancer Biomarker
Conventional biopsies are invasive and cannot be used when there is no visible tumor. Liquid biopsies noninvasively monitor tumor progression and response to treatments via NGS. NGS identify the genetic changes in ctDNA that make human tumors grow and progress. Virtually all cancers carry somatic DNA mutations. Somatic mutations form in the DNA of individual cells during a person's life. These somatic mutations are only present in tumor cell DNA Provides specific biomarker that can be detected and tracked. Figure 3: Conventional Biopsy vs Liquid Biopsy References: Liquid Biopsies Remain Wait and See For Some Clinicians. Genetic Engineering & Biotechnology News 37, 26–28 (2017).
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Applications for ctDNA Biomarkers
Tumors have unique set of somatic alterations ‘‘Liquid biopsy’’ of ctDNA is used to identify the tumor genotypes instead of tissue biopsy tests Liquid biopsy shows that the genotypes are not common in the plasma of individuals that are presumably cancer-free Tumor-derived RNA and DNA methylation patterns also detected in plasma Provides insight to somatic alterations detected in ctDNA Figure 4: Overview of ctDNA applications Reference: Wang, J. & Bettegowda, C. Applications of DNA-Based Liquid Biopsy for Central Nervous System Neoplasms. (2017).
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Benefits to using ctDNA as a Cancer Biomarker
Identification of tumor-specific mutations and detection of tumor heterogeneity in primary and metastatic disease Assessment of tumor burden and response to treatment in primary and metastatic disease Detection of minimal residual disease (MRD) for early detection of recurrence Early detection of primary disease Figure 5: Benefits of liquid biopsy vs standard biopsy Reference: Liquid Biopsy. Liquid Biopsy Available at:
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Figure 6: Example of How ctDNA is Tested in a Lab
Reference: Wardlow, J. (2017, June 27). The Use of Circulating Tumour DNA as a Liquid Biopsy. Retrieved October 04, 2017,
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Specific Aims for Cancer Genome-Sequencing Study Design
Determine which somatic mutations contribute to cancer phenotype Will lead to greater understanding of basic cancer biology and better quality treatments/developments Identify somatic mutation signatures Will show the mutational process and DNA repair mechanisms aiding somatic mutations Characterize clonal evolution Achieved using NGS at nucleotide level Advance medicine Can use NGS to sequence cancer genomes Reduce toxicity Improve effectiveness by selecting the appropriate treatment for each patient and utilizing the correct dosage
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Figure 7: Cancer Genome NGS Sequencing Study Designs
Study design choices are in yellow, green, and blue boxes -choosing a path along these boxes connected by arrows represents a possible cancer genome sequence study design yellow boxes highlight that single-patient studies are well-suited for personalized medicine blue boxes highlight that discovery cohorts are well-suited for discovering driver mutations dark grey boxes represent choices for analyses or methods specific to the box that they are connected to. Light grey boxes secondary aims Reference: Mwenifumbo, J. C. & Marra, M. A. Cancer genome-sequencing study design. Nature Reviews Genetics 14, 321–332 (2013).
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Study Types Single-patient studies Genome discovery cohort
NGS cancer genome sequencing can show the somatic mutation signature for a given cancer type Objective aid physicians decisions regarding treatment Genome discovery cohort NGS of discovery cohorts can aid in identification of mutant somatic signatures that help characterize cancer type/subtypes Potential to detect recurring somatic mutations of genes and pathways Multi-ome discovery cohort Uses NGS to sequence genomes, exomes, and transcriptomes in cancer type/subtypes Can indicate if the somatic mutation in a gene is from pathogenic increase, decrease, or change in function Advantage Reduces the cost/resources needed to discover recurrent and high-impact mutations Disadvantage Lack of bioinformatic tools for NGS analyses
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NGS of Circulating Tumor DNA for Early Cancer Detection
Locating cancer cells early allows a greater chance at curing the disease Early diagnosis gives patients a 5-10 times higher survival rate compared to late stage diagnosis Early detection methods allows patients to receive early diagnosis and localized treatments These methods have contributed to the decrease in mortality for cervical and colorectal caners Need to create a screening platform that provides direct, sensitive, and specific measurements of cancer cells NGS of ctDNA shows promising results for developing safe and effective cancer screenings
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Challenges for Cancer Screening
Early stage tumors are small/difficult to non-invasively detect Can result in a large amount of missed cancer cells as well as over diagnosing and over treating Detection algorithms can either miss invasive cancers or over diagnose/treat Examples: High false positives from mammogram screenings and prostate-specific antigen (PSA) Early stage cancers detected via mammogram or PSA typically show clinical insignificance or non lethality Mammograms and PSA are not sensitive towards lethal cancers Sensitive towards indolent tumors Some localized diagnosed tumors may have already disseminated with metastatic disease Making local treatment with surgery/radiation ineffective
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Challenges of Developing a ctDNA Based Screening Test
Test needs to address the challenges for early stage disease sensitivity and heterogeneity of the cancer genome For sensitivity: Low level signal or early detection and heterogeneity must be overcome to gain efficacy For targeted tumors: Needs several hundred early stage cancer examples needed to adequately show the potential for observations in plasma To achieve clinical specificity: ctDNA screening must distinguish between background signal of non-cancer vs pre-cancer and invasive malignancy
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Ways to Overcome Challenges in Developing a ctDNA Based Screening Test
Non-invasive screening test ctDNA can show differences in somatic alterations between the tumor types Clinical insignificance Mutations in ctDNA can distinguish the clinical insignificant areas from malignant/lethal biological processes Signals from ctDNA can identify the routes for indolent vs lethal diseases Early stage tumors currently have no local therapy cure ctDNA levels can predict relapse ctDNA can minimize lead-time bias by targeting post-operative therapy GRAIL is creating a ctDNA library that contains cancer mutations in the blood
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Next-Generation Sequencing of Circulating Tumor DNA to Predict Recurrence in Triple-Negative Breast Cancer Patients with Residual Disease after Neoadjuvant Chemotherapy By: Yu-hsaing chen, Bradley a. hancock, Jeffrey p. solzak, dumitru brinza, Charles scafe, Kathy d. miller, and milan radovich
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What is Triple-Negative Breast Cancer (TNBC)
The absence of estrogen-receptor (ER), progesterone-receptor (PR), and human epidermal growth factor 2 (HER2) over expression TNBC comprises a minority of breast cancer cases (15-20%) Results in higher mortality rate Majority of TNBC patients are treated with neoadjuvant chemotherapy Compared to ER and HER2 positive disease, TNCBs have higher incidence of visceral metastasis, higher likelihood of relapse within first 3 years after chemotherapy/surgery, and shorter overall survival (OS) after the onset of metastatic disease
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Patients and Methods 135 patients enrolled on the BRE clinical trial Eligibility requirements: Residual tumor >2cm in the breast Lymph node involvement RCB classification of II or III Eligible patients randomized to Cisplatin for 4 cycles or Cisplatin plus the PARP inhibitor Rucaparib for 4 cycles followed by Rucaparib for 24 weeks Utilized phase II clinical trial to evaluate 2-year disease-free survival (DFS) in TNBC patients Reference: Chen, Y.-H. et al. Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant . Nature (2017).
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Patients and Methods Continued
For this study each patient had to have: At least 1 tumor sample with 60% greater tumor cellularity 1 whole blood sample 1 plasma sample submitted Tumor DNA isolated from formalin-fixed paraffin embedded (FFPE) tissue utilizing Qiagen AllPrep DNA/RNA FFPE kit Whole blood isolated via AutogenFlex Sciences Institute Specimen Storage Facility (ICTSI-SSF) Plasma DNA isolated from 1ml of plasma via Qiagen QIAmp Circulating Nucleic Acid Kit
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Figure 8: Trial Schema for BRE09-146
Treated with Cisplatin (Arm A) or Cisplatin in combination with PARP inhibitor Rucaparib (Arm B) after neoadjuvant chemotherapy. Collected tumor tissue, whole blood, and plasma from 4 time points after surgery. Plasma samples collected in Arm B (the area enclosed by the red rectangle). Samples collected at 4 timepoints Reference: Chen, Y.-H. et al. Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant . Nature (2017).
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Results: Patients/Sample Selection
Focused on 70 patients from Arm B 27 patients removed from study lacked matched tumor tissue, whole blood, and at least one plasma collection 5 additional patients removed No plasma DNA library 38 total patients reached standards for analysis Figure 9 CONSORT diagram Reference: Chen, Y.-H. et al. Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant . Nature (2017).
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Results: Somatic Mutations in Primary Tumors
33 of 38 patients had at least one somatic mutation identified (87%) 21 of them had two or more somatic mutations (55%) TP53 mutations were the most prevalent Followed by PIK3CA pathway mutations. 14 different mutations exclusively present in individual patients Represents genomic heterogeneity of TNBC patients Fig. 10 Somatic mutations identified from sequencing of tumor tissues. Reference: Chen, Y.-H. et al. Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant . Nature (2017).
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Results: Detection of ctDNA in Matched Plasma Samples
Patient (a) and patient (b), the increasing allele frequency of ctDNA was observed before clinical recurrence was diagnosed. Patient (c) and patient (d) had only one timepoint plasma sample available Able to detect the ctDNA before clinical recurrence as well. Lead-time range was 0.07 to 8.87 months Figure 11: Longitudinal allele frequency tracking of ctDNA mutations Reference: Chen, Y.-H. et al. Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant . Nature (2017).
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Discussion and Conclusions
Somatic mutations show specificity for nucleic acid material derived from tumor tissue Presence of ctDNA shows presence of disease Limitation of ctDNA low sensitivity for detecting distant and some rapid relapse Ability to detect ctDNA is proportional to plasma volume, disease, and number of somatic mutations in circulation These factors regulate the sensitivity NGS ctDNA sequencing of TNBC patients after neoadjuvant chemotherapy/surgery can detect rapid recurrence but sensitivity to detect distant recurrence is limited
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Overall benefits and Improvements for NGS and ctDNA Cancer Detection
ctDNA can be safely and repeatedly obtained through a “liquid biopsy” and tested using NGS NGS on ctDNA has the potential to detect early disease mutations Advantage of interrogating a larger number of genomic loci Can repeatedly sample ctDNA to analyze noninvasive blood draws Allows monitoring of tumor evolution over time and treatment Aids in identification of resistance mechanisms that may suggest subsequent lines of therapy. Figure 12: NGS benefits and needed improvments Reference: Serratì, Simona & De Summa, Simona & Pilato, Brunella & Petriella, Daniela & Lacalamita, Rosanna & Tommasi, Stefania & Pinto, Rosamaria. (2016). Next-generation sequencing: Advances and applications in cancer diagnosis. OncoTargets and Therapy. Volume
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Future Directions for ctDNA Research
Gain a better understanding of how ctDNA is released into the bloodstream Create one specific method for ctDNA collection and analysis Improve the sensitivity for ctDNA detection Greater number of clinical trials to asses the overall clinical value
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Questions?
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References A.M. Aravanis, M. Lee, R.D. Klausner, Next-generation sequencing of circulating tumor DNA for early cancer detection, Cell 168 (2017) 571e574. Bettegowda, Chetan & Sausen, Mark & J Leary, Rebecca & Kinde, Isaac & Wang, Yuxuan & Agrawal, Nishant & Bartlett, Bjarne & Wang, Hao & Luber, Brandon & M Alani, Rhoda & Antonarakis, Emmanuel & S Azad, Nilofer & Bardelli, Alberto & Brem, Henry & L Cameron, John & Lee, Clarence & Fecher, Leslie & L Gallia, Gary & Gibbs, Peter & A Diaz, Luis. (2014). Detection of Circulating Tumor DNA in Early- and Late-Stage Human Malignancies. Science translational medicine ra /scitranslmed Chen, Y.-H. et al. Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant . Nature (2017). Cummings, C. A., Peters, E., Lacroix, L., Andre, F. & Lackner, M. R. The Role of Next‐Generation Sequencing in Enabling Personalized Oncology Therapy. Clinical and Translational Science (2016) Friedrich M. Going With the Flow: The Promise and Challenge of Liquid Biopsies. JAMA. 2017;318(12):1095–1097. doi: /jama Han, X., Wang, J. & Sun, Y. Circulating Tumor DNA as Biomarkers for Cancer Detection. Circulating Tumor DNA as Biomarkers for Cancer Detection (2017). Liquid Biopsy. Liquid Biopsy Available at: Liquid Biopsies Remain Wait and See For Some Clinicians. Genetic Engineering & Biotechnology News 37, 26–28 (2017). Mwenifumbo, J. C. & Marra, M. A. Cancer genome-sequencing study design. Nature Reviews Genetics 14, 321–332 (2013). Serratì, Simona & De Summa, Simona & Pilato, Brunella & Petriella, Daniela & Lacalamita, Rosanna & Tommasi, Stefania & Pinto, Rosamaria. (2016). Next-generation sequencing: Advances and applications in cancer diagnosis. OncoTargets and Therapy. Volume Wang, J. & Bettegowda, C. Applications of DNA-Based Liquid Biopsy for Central Nervous System Neoplasms. (2017). Wardlow, J. (2017, June 27). The Use of Circulating Tumour DNA as a Liquid Biopsy. Retrieved October 04, 2017, Yi, X. et al. The feasibility of using mutation detection in ctDNA to assess tumor dynamics. International Journal of Cancer (2017).
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