Search

Observed genome equivalents, wild-type DNA fragments, mutant DNA fragments, and mutant allele frequency in K2EDTA tubes at 4{degree sign}C and Streck{trade mark, serif} BCT tubes at room temperature.

Average DNA Yield and Range of Plasma Isolated in Healthy Donors vs. Diseased Donors

Schematic of sample collection and analyses for the comparative studies between K2EDTA (EDTA) and Streck{trade mark, serif} BCT (Streck{trade mark, serif}) tubes.

Circulating cell-free DNA (cfDNA) is rapidly transitioning from discovery research to an important tool in clinical decision making. However, the lack of harmonization of preanalytic practices across institutions may compromise the reproducibility of cfDNA-derived data and hamper advancements in cfDNA testing in the clinic. Differences in cellular genomic contamination, cfDNA yield, integrity, and fragment length have been attributed to different collection tube types and anticoagulants, processing delays and temperatures, tube agitation, centrifugation protocols and speeds, plasma storage duration and temperature, the number of freeze-thaw events, and cfDNA extraction and quantification methods, all of which can also ultimately impact subsequent downstream analysis. Thus, there is a pressing need for widely applicable standards tailored for cfDNA analysis that include all preanalytic steps from blood draw to analysis. The NCI's Biorepositories and Biospecimen Research Branch has developed cfDNA-specific guidelines that are based upon published evidence and have been vetted by a panel of internationally recognized experts in the field. The guidelines include optimal procedures as well as acceptable alternatives to facilitate the generation of evidence-based protocols by individual laboratories and institutions. The aim of the document, which is entitled “Biospecimen Evidence-based Best Practices for Cell-free DNA: Biospecimen Collection and Processing,” is to improve the accuracy of cfDNA analysis in both basic research and the clinic by improving and harmonizing practices across institutions.

Purpose: Analysis of genomic alterations in cell-free DNA (cfDNA) is evolving as an approach to detect, monitor, and genotype malignancies. Methods to separate the liquid from the cellular fraction of whole blood for circulating tumor DNA (ctDNA) analyses have been largely unstudied, although these may be a critical consideration for assay performance.Experimental Design: To evaluate the influence of blood processing on cfDNA and ctDNA quality and yield, we compared the cfDNA levels in serum with those in plasma. Given the limitations of serum for ctDNA analyses, we evaluated the effects of two plasma processing approaches, K2EDTA and Cell-Free DNA BCT (BCT) tubes, on cfDNA and ctDNA recovery. A total of 45 samples from nine patients with cancer were collected in both tube types. Once collected, blood was processed into plasma immediately or kept at room temperature and processed into plasma at 1, 3, 5, or 7 days.Results: As early as 24 hours after collection, plasma isolated from blood collected in K2EDTA tubes contained an elevated level of cfDNA that increased over time compared with BCT tubes where no significant increase in cfDNA levels was observed. When samples from an additional six patients with cancer, collected in the same manner, were stored at 4°C in K2EDTA tubes over the course of 3 days, total cfDNA and ctDNA levels were comparable between samples collected in BCT tubes. At day 3, there was a trend toward a decrease in ctDNA levels in both tubes that was more pronounced when measuring the mutant allele fraction for cases stored at 4°C in K2EDTA tubes.Conclusions: In summary, methods of blood processing have a strong influence on cfDNA and ctDNA levels and should be a consideration when evaluating ctDNA in peripheral circulation. Clin Cancer Res; 23(10); 2471–7. ©2016 AACR.

Summary of clinical characteristics, plasma volume and DNA yield in 15 cancer patients.

Guidelines discussed in article

Next-Generation Sequencing Performance of Plasma Isolated in Different Blood Collection Tubes

Circulating cell-free DNA (cfDNA) is rapidly transitioning from discovery research to an important tool in clinical decision making. However, the lack of harmonization of preanalytic practices across institutions may compromise the reproducibility of cfDNA-derived data and hamper advancements in cfDNA testing in the clinic. Differences in cellular genomic contamination, cfDNA yield, integrity, and fragment length have been attributed to different collection tube types and anticoagulants, processing delays and temperatures, tube agitation, centrifugation protocols and speeds, plasma storage duration and temperature, the number of freeze-thaw events, and cfDNA extraction and quantification methods, all of which can also ultimately impact subsequent downstream analysis. Thus, there is a pressing need for widely applicable standards tailored for cfDNA analysis that include all preanalytic steps from blood draw to analysis. The NCI's Biorepositories and Biospecimen Research Branch has developed cfDNA-specific guidelines that are based upon published evidence and have been vetted by a panel of internationally recognized experts in the field. The guidelines include optimal procedures as well as acceptable alternatives to facilitate the generation of evidence-based protocols by individual laboratories and institutions. The aim of the document, which is entitled “Biospecimen Evidence-based Best Practices for Cell-free DNA: Biospecimen Collection and Processing,” is to improve the accuracy of cfDNA analysis in both basic research and the clinic by improving and harmonizing practices across institutions.

Introduction: cfDNA-based tests have the potential to facilitate earlier detection of cancer and provide greater opportunity for curative intervention. Previously, we demonstrated that a cfDNA-based targeted methylation multi-cancer early detection (MCED) test can detect multiple cancers across all stages with high specificity, and predict the signal origin (SO; ie, tissue of origin) with high accuracy; we also validated the repeatability and reproducibility of its performance. Here, we validate a recent version of this MCED test planned for use as a screening tool. Methods: In the Circulating Cell-free Genome Atlas study (NCT02889978), cfDNA was analyzed using targeted methylation sequencing and machine learning to classify samples as cancer or non-cancer, and predict SO. Dilutions of cfDNA samples from participants with early-stage lung, head and neck, sarcoma, upper gastrointestinal, colorectal, or ovarian cancer into cfDNA from individuals without cancer were analyzed to establish the limit of detection (LOD95%) defined by the lowest variant allele frequency (VAF) at which accurate classification of cancer signals was attained in at least 95% of replicates. Analytical specificity was assessed by the true negative rate in 66 non-cancer cfDNA samples. Classification performance was evaluated as a function of cfDNA input (0.5-100 ng) using cancer samples (liver/bile duct, lung, head and neck, ovarian, breast, bladder/urothelial, uterine). Repeatability within-run and reproducibility between-runs were characterized by pairwise comparisons among 53 cancer samples (anorectal, breast, head and neck, uterine) and among 62 non-cancer samples processed across multiple reagent lots, instruments, and operators. The effects of high levels of potential interferents hemoglobin, bilirubin, triglycerides, and genomic DNA on classification when spiked into 88 plasma samples along with cfDNA from individuals with cancer (liver/bile duct or lung) or when spiked into 87 non-cancer samples were evaluated. Results: LOD95% was 0.11% VAF. No false positives were detected in non-cancer samples (100% analytical specificity). Across all input cfDNA levels tested, in 50/50 (100%) cancer samples, a cancer signal was detected with a correct SO prediction. All sample pairs in within-run (n=110) and between-run (n=696) analyses were concordant with respect to cancer/non-cancer classification and SO prediction (100% repeatability and reproducibility). None of the tested interferents affected cancer signal detection (100% correct) or SO prediction (100% accuracy). Conclusions: These results suggest that the analytical performance of a cfDNA-based targeted methylation MCED screening test is robust for clinical implementation. This MCED test can be a complementary tool to the existing repertoire of cancer screening options currently available for clinical use. Citation Format: Gregory E. Alexander, Byoungsok Jung, Lijuan Ji, Ekaterina Revenkova, Payal Shah, Jacqueline Brooks, Jeremy Carter, Zhao Dong, Lane Eubank, Maryam Hosseini, Xinyi Hou, Hannah Kiarie, Neda Ronaghi, Fabian E. Ortega, Madhuvanthi Ramaiah, Kate Rhodes, Rita Shaknovich, Seyedmehdi Shojaee, Sonya Parpart-Li, Nathan Hunkapiller. Analytical performance of a cfDNA-based targeted methylation multi-cancer early detection test for population-scale screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 112.

Introduction: A blood-based test using cell-free DNA (cfDNA) may address an unmet need for earlier detection of multiple cancers. Here, we report the analytical validation of a targeted methylation-based cfDNA test to detect cancer and tissue of origin (TOO). Methods: Since detection was determined by a machine-learning classifier based on methylation patterns of >105 genomic targets, defining analytical sensitivity by a single common limit of detection (LOD) for each genomic target was not applicable. Thus, we characterized sensitivity with respect to tumor fraction using dilution series of contrived cancer samples containing mixtures of cfDNA from 6 individuals without cancer and 6 participants in the Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) with cancer (breast, colorectal, head and neck, lung, lymphoid neoplasm). Each dilution series was performed at 3 levels near the expected LOD95% (lowest admixture fraction predicted to have 95% detection probability). Analytical specificity was determined by the false positive (FP) rate in 1,204 samples without cancer. Reproducibility and repeatability were characterized by within- and between-run variability in 81 cancer samples and 45 noncancer samples across multiple reagent lots, instruments, and operators. Test performance as a function of cfDNA input (3-100 ng) was assessed by an input titration study with cfDNA from 6 CCGA participants with cancer (colorectal, lung, esophageal, renal, multiple myeloma, lymphoid neoplasm) and 5 individuals not known to have cancer. The effect of 4 potential interferents (hemoglobin, bilirubin, triglycerides, white blood cell genomic DNA) on test performance was also evaluated. Results: In the assessment of sensitivity by tumor fraction, LOD95% ranged from 0.2% (upper bound) to 0.5% across the 5 individual solid tumor cases and was 1.9% for the blood cancer case. Among noncancer samples from CCGA participants, 9 FPs were detected (99.3% specificity; 95% CI, 98.6%-99.7%). Repeatability and reproducibility results were correct in 31/34 (91.2%) and 17/17 (100%) sample pairs with or without cancer in within-run tests and in 77/81 (95.1%) and 45/45 (100%) cancer and noncancer samples in between-run tests. For the input titration study, cancer was detected in 5/6 cancer specimens (156/183 samples) and not detected in any noncancer samples (n = 62) across all input cfDNA levels tested. TOO was correctly localized in all but 2 samples with a cancer signal. None of the tested interferents affected test performance. Conclusions: A targeted methylation-based cfDNA test repeatedly and reproducibly detected cancer with high analytical sensitivity and specificity and localized TOO with high accuracy, which are critical for multi-cancer early detection applications. This validation study supports clinical development of this multi-cancer early detection test. Citation Format: Gregory Alexander, Wendy Lin, Madhuvanthi Ramaiah, Byoungsok Jung, Lijuan Ji, Ekaterina Revenkova, Payal Shah, Christian Croisetiere, Jennifer Berman, Lane Eubank, Gunjan Naik, Jacqueline Brooks, Andrea Mich, Seyedmehdi Shojaee, Neda Ronaghi, Hemanshi Chawla, Xinyi Hou, Qinwen Liu, Christopher Yakym, Patriss Wais Moradi, Meredith Halks-Miller, Nathan Hunkapiller, Sonya Parpart-Li, Alexander Aravanis. Analytical validation of a multi-cancer early detection test with tissue localization using a cell-free DNA-based targeted methylation assay [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 721.

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired tumor-normal exome data from 1368 TCGA (The Cancer Genome Atlas) samples using this method revealed concordance for 74% of mutation calls but also identified likely false-positive and false-negative changes in TCGA data, including in clinically actionable genes. Determination of high-quality somatic mutation calls improved tumor mutation load-based predictions of clinical outcome for melanoma and lung cancer patients previously treated with immune checkpoint inhibitors. Integration of high-quality machine learning mutation detection in clinical next-generation sequencing (NGS) analyses increased the accuracy of test results compared to other clinical sequencing analyses. These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of cancer patients.

Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.

Background Comprehensive genomic profiling in NSCLC has become increasingly important for clinical management of advanced stage patients. Alteration status of EGFR, ALK, BRAF, and ROS1 are validated biomarkers linked to approved drugs, with many clinical trials enrolling on the basis of additional biomarkers, including Tumor Mutation Burden (TMB). It is therefore important to develop accurate and sensitive tools for tumor profiling, particularly in NSCLC where biopsy materials are limited. Here, we present results from ongoing analytical performance studies with the PGDx elio tissue complete - IUO assay, verifying our capabilities to accurately identify a range of genomic alteration types, comprising SNVs, indels, translocations, and TMB. Methods >300 specimens in NSCLC, comprising FFPE tissue and characterized cell lines were analyzed on our >500-gene targeted panel. Accuracy of the results were compared to orthogonal methods, such as whole exome sequencing (WES), IHC, FISH, and on-market IVD assays. Results were analyzed for the positive percent agreement (PPA) and negative percent agreement (NPA) for all variants assessed. Analytical studies were performed to assess the limit of blank, limit of detection, and repeatability for detection of these variants. Results Clinical FFPE and characterized cell line specimens (representing EGFR and BRAF SNVs, EGFR exon 19 deletions, and ALK and ROS1 translocations) were evaluated and demonstrated high concordance between PGDx elio tissue complete - IUO and orthogonal methods, with high PPA and NPA for SNV, indel, and translocation alterations analyzed. Repeatability studies demonstrated 100% PPA and 100% NPA for all variants assessed across operators, instruments, and days. The accuracy for panel-wide sequence mutations were assessed by comparing the results of >50 clinical samples (representing >500 SNVs and ~40 indels) run on PGDx elio tissue complete IUO and a validated NGS method, resulting in high PPA and NPA across all alterations analyzed. Reported alterations between PGDx elio tissue complete IUO and the independent NGS method displayed high sensitivity for analyzed SNVs (≥4% MAF) and indels (≥6% MAF). Finally, comparison of TMB results to WES data demonstrated TMB can be accurately and consistently reported from this panel, across a range of DNA inputs (50-200 ng) and tumor purities (10-30%). Conclusions The PGDx elio tissue complete - IUO >500-gene assay system, including our proprietary bioinformatics, provides accurate and reproducible results for the detection of clinically relevant genetic alterations in this NSCLC study. Further verification and validation studies of this gene panel are ongoing. The PGDx elio tissue complete assay will employ a decentralized, kitted model, increasing clinical accessibility to NGS and allow for delivery of highly accurate and timely results. Citation Format: Kelly Gerding, Laurel Keefer, Christine McCord, Amy Greer, Shantanu Shewale, Nicole Barkley, Eileen Sagini, Dorhyun Johng, Kenneth Valkenburg, Caitlin Gilley, Colby Ganey, Alvis Hu, Diandra Denier, Lorenzo Jones, Christina Oliveras, Gregory Joseph, Kartikeya Joshi, James Hernandez, Christopher Gault, Eniko Papp, Peibing Qin, Sonya Parpart-Li, James White, Mark Sausen, Siân Jones. Analytical performance of a comprehensive genomic profiling system to detect actionable genetic alterations in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3534.

Purpose: Analysis of genomic alterations in cell-free DNA (cfDNA) is evolving as an approach to detect, monitor, and genotype malignancies. Methods to separate the liquid from the cellular fraction of whole blood for circulating tumor DNA (ctDNA) analyses have been largely unstudied, although these may be a critical consideration for assay performance. Experimental Design: To evaluate the influence of blood processing on cfDNA and ctDNA quality and yield, we compared the cfDNA levels in serum with those in plasma. Given the limitations of serum for ctDNA analyses, we evaluated the effects of two plasma processing approaches, K2EDTA and Cell-Free DNA BCT (BCT) tubes, on cfDNA and ctDNA recovery. A total of 45 samples from nine patients with cancer were collected in both tube types. Once collected, blood was processed into plasma immediately or kept at room temperature and processed into plasma at 1, 3, 5, or 7 days. Results: As early as 24 hours after collection, plasma isolated from blood collected in K2EDTA tubes contained an elevated level of cfDNA that increased over time compared with BCT tubes where no significant increase in cfDNA levels was observed. When samples from an additional six patients with cancer, collected in the same manner, were stored at 4°C in K2EDTA tubes over the course of 3 days, total cfDNA and ctDNA levels were comparable between samples collected in BCT tubes. At day 3, there was a trend toward a decrease in ctDNA levels in both tubes that was more pronounced when measuring the mutant allele fraction for cases stored at 4°C in K2EDTA tubes. Conclusions: In summary, methods of blood processing have a strong influence on cfDNA and ctDNA levels and should be a consideration when evaluating ctDNA in peripheral circulation. Clin Cancer Res; 23(10); 2471–7. ©2016 AACR.

Failure of the DNA mismatch repair (MMR) pathway during DNA replication in cancer leads to the increased accumulation of somatic mutations. The molecular hallmark of MMR deficiency is microsatellite instability (MSI), which presents as polymorphism of tandem nucleotide repeat lengths ubiquitously distributed throughout the genome. Furthermore, the presence of MMR-deficiency or MSI across solid tumors has been recently demonstrated to be a robust biomarker for immunotherapy response with checkpoint inhibition. We have previously developed technology to detect MSI in tumor tissue through hybrid-capture based targeted next-generation sequencing analyses of a 125 gene panel, with probes capturing mononucleotide repeat markers. Using a set of 32 MSI and 27 microsatellite stable (MSS) formalin-fixed paraffin-embedded tumor tissue specimens, we obtained 100% sensitivity and 100% specificity with a limit of detection of 20% tumor purity. The clinical importance of MSI status now requires a fast, objective, highly sensitive screening method, particularly in late-stage patients where tumor material may not be readily obtained. However, to extend this approach to a liquid biopsy panel requires technological advances to overcome the inherent challenges associated with low circulating tumor DNA (ctDNA) levels that are compounded by polymerase slippage in mononucleotide repeat regions during PCR amplification. To overcome these limitations, we applied a multifactorial error correction approach together with a novel peak finding algorithm to more accurately identify the specific mononucleotide sequences in cell-free DNA (cfDNA) analyses. By eliminating a significant majority of sequencing errors and polymerase slippage artifacts, we were able to reduce background error rates by > 90%. Combined with implementation of a distribution modeling and a peak finding algorithm, we were able to accurately sequence the mononucleotide tracts to minimize false discovery rates for cfDNA analyses. To evaluate the performance of this approach in clinical samples, for a cohort of plasma samples obtained from 13 late-stage clinical cases with matched tumor tissue data available (9 MSI and 4 MSS) together with 66 healthy donor plasma samples, we obtained 89% sensitivity and 100% specificity, with a lowest reported mutant allele fraction of 0.4%. Taken together, this integrated next-generation sequencing liquid biopsy approach is valuable for the determination of MSI status to inform immunotherapy treatment. Citation Format: Andrew Georgiadis, Derrick Wood, Derek Murphy, Sonya Parpart-Li, David Riley, Naomi Sengamalay, Marian Novak, Sian Jones, Samuel A. Angiuoli, Mark Sausen. Analytical validation of an integrated next-generation sequencing pan-cancer liquid biopsy approach for detection of microsatellite instability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1286.

Variability in the accuracy for somatic mutation detection may affect discovery of alterations and therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery method based on machine learning approaches that outperformed other methods using tumor alterations that were experimentally validated (sensitivity of 97% vs 90-99%; positive predictive value of 98% vs 34-92%). Analysis of tumor-normal exome data from 1,376 TCGA samples using this method revealed concordance for 74% of mutation calls but also identified likely false positive and negative changes in TCGA data, including in clinically actionable genes. For melanoma and lung cancer patients treated with immune checkpoint inhibitors, determination of high-quality somatic mutation calls improved mutation load-based predictions of clinical outcome. Integration of high-quality mutation detection in clinical NGS analyses improved the accuracy of test results compared to other clinical sequencing analyses not using these approaches (sensitivity of 100% vs 50-97%; positive predictive value of 100% vs 9-66%). These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of patients with cancer. Citation Format: Derrick Wood, James White, Andrew Georgiadis, Beth Van Emburgh, Sonya Parpart-Li, Jason Mitchell, Valsamo Anagnostou, Noushin Niknafs, Rachel Karchin, Eniko Papp, Christine McCord, Peter Loverso, David Riley, Luis A. Diaz, Sian Jones, Mark Sausen, Victor E. Velculescu, Samuel Angiuoli. A machine learning approach for somatic mutation discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3271.

Pancreatic adenocarcinoma has the worst mortality of any solid cancer. In this study, to evaluate the clinical implications of genomic alterations in this tumour type, we perform whole-exome analyses of 24 tumours, targeted genomic analyses of 77 tumours, and use non-invasive approaches to examine tumour-specific mutations in the circulation of these patients. These analyses reveal somatic mutations in chromatin-regulating genes MLL, MLL2, MLL3 and ARID1A in 20% of patients that are associated with improved survival. We observe alterations in genes with potential therapeutic utility in over a third of cases. Liquid biopsy analyses demonstrate that 43% of patients with localized disease have detectable circulating tumour DNA (ctDNA) at diagnosis. Detection of ctDNA after resection predicts clinical relapse and poor outcome, with recurrence by ctDNA detected 6.5 months earlier than with CT imaging. These observations provide genetic predictors of outcome in pancreatic cancer and have implications for new avenues of therapeutic intervention.

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients.

Tumor heterogeneity hinders the discovery of true cancer driver genes. The recently identified role for YY1-associated protein 1 (YY1AP1) as a critical oncoprotein that is activated in a particular subtype of hepatocellular carcinoma (HCC) was elucidated through integrative genomic profiling followed by functional studies. This strategy proved effective for finding a functional cancer driver with prognostic impact.

Precise identification and characterization of candidate neoantigens is important for the development of effective cancer vaccines, adoptive T-cell transfer, and prediction of response to checkpoint inhibitors. The candidate tumor neoantigens are actionable only when expressed, however, current prediction methods lack the capacity to evaluate neoantigen expression. Sequencing both DNA and RNA from a patient’s tumor tissue enables identification of mutations and evaluation of their expression leading to accurate identification of putative neoantigens. The purpose of this study was to develop and validate a methodology for co-extraction and sequencing of DNA and RNA from formalin-fixed paraffin-embedded (FFPE) samples to enable a robust neoantigen prediction protocol that integrates whole exome and transcriptome data to identify and prioritize tumor neoantigens for application in immuno-oncology research and clinical trials. In order to prepare high-quality sequencing libraries from FFPE specimens, the tissue was macrodissected to enrich for tumor-specific material, and improve the overall accuracy of next-generation sequencing for detection of somatic alterations. Total DNA and RNA was co-extracted and purified. The DNA was used to prepare whole exome sequencing (WES) libraries, while the co-extracted RNA was ribosome-depleted, and reverse-transcribed to prepare RNA sequencing (RNAseq) libraries. The WES and RNAseq data was then analyzed using a multi-algorithm HLA typing and neoantigen prediction protocol (ImmunoSelect-RTM). ImmunoSelect-R evaluates somatic genomic alterations identified from WES of tumor and matched normal tissue to ensure appropriate prediction of candidate neoantigens. The process of neoantigen prediction was then refined by integration of patient tumor-matched RNAseq data, which allowed for removal of non-expressed putative neoantigens. To further validate the approach, we applied the methodology to a set of experimentally validated neoantigens. In this setting, ImmunoSelect-R correctly classified 18 out of 19 as strong neoantigen candidates, suggesting a sensitivity of greater than 90%. Moreover, in a set of 10 patients, ImmunoSelect-R consistently ranked experimentally validated neoantigens within the top 20% of all neoantigen candidates derived from whole exome sequencing. In summary, our combined tissue processing, macrodissection, co-extraction, and neoantigen prediction methodology is able to identify and prioritize candidate neoantigens. Our approach is unique in combining high-fidelity sequencing (WES) and expression (RNAseq) data to accurately inform the selection of actionable tumor neoantigens for immuno-oncology applications. Citation Format: Marián Novak, Sam Angiuoli, Luis A. Diaz, Andrew Georgiadis, Sian Jones, Peter R. Loverso, Sonya Parpart-Li, Maria Sevdali, Victor E. Velculescu, Ellen L. Verner, James White, Theresa Zhang, Mark Sausen. Accurate identification and prioritization of candidate neoantigens from integrated cancer exome and transcriptome sequencing of FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 604. doi:10.1158/1538-7445.AM2017-604

Early detection is a major goal for reducing mortality of human cancer. However, non-invasive detection of early stage tumors has remained a challenge. We have developed an approach called Targeted Error Correction Sequencing (TEC-Seq) for ultra-sensitive analyses of circulating cell-free tumor DNA (ctDNA). This methodology involves in-solution targeted capture of multiple regions of the genome and deep sequencing (~30,000x) of cell-free DNA fragments. Laboratory and bioinformatic methods were optimized to enrich for rare ctDNA molecules and to reduce potential amplification, sequencing, and contamination errors. We have used this approach to examine 58 cancer related genes, and demonstrated a limit of detection of mutant to wild-type DNA of 0.05% and a specificity >99.999% across targeted regions of interest. We applied this method to analyze plasma from healthy individuals as well as over 200 individuals with breast, lung, colorectal and ovarian cancers. Analysis of plasma from 44 healthy individuals revealed no tumor-related somatic mutations and identified alterations in genes related to myelodysplasia in a subset of cases. Among patients with cancer, we detected measurable ctDNA in 56%, 71%, 57%, and 56% of patients with early stage (I and II) breast, colorectal, lung and ovarian cancer. Over three quarters of patients with late stage (III and IV) disease had detectable ctDNA among all cases analyzed. Analyses of mutations in the circulation revealed a high concordance with alterations in the independently analyzed tumors of these patients. These analyses provide a widely applicable, ultra-sensitive, and non-invasive method for detection of ctDNA, and have important implications for detection of early stage disease and management of patients with cancer. Citation Format: Jillian A. Phallen, Mark Sausen, Vilmos Adleff, Alessandro Leal, Jacob Fiksel, Carolyn Hruban, Savannah Speir, Eniko Papp, Valsamo Anagnostou, Mai-Britt W. Orntoft, Thomas Reinert, Brian D. Woodward, Derek Murphy, Sonya Parpart-Li, David Riley, Monica Nesselbush, Naomi Sengamalay, Andrew Georgiadis, Rob Scharpf, Qing K. Li, Sian Jones, Samuel Angiuoli, Joost Huiskens, Cornelis Punt, Nicole van Grieken, Remond Fijneman, Gerrit Meijer, Hatim Husain, Luis Diaz, Torben Ørntoft, Hans J. Nielsen, Claus L. Anderson, Victor E. Velculescu. Detection of circulating tumor DNA in early stage cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-246. doi:10.1158/1538-7445.AM2017-LB-246

Clinical molecular profiling of advanced cancers enables the identification of actionable genomic alterations to guide therapeutic decisions. Although profiling of tissue samples is considered the gold standard, specimens may be unavailable or unsuitable for testing due to limited tumor purity or specimen quality. Further, genetically informed treatment decisions are increasingly necessary after disease progression and re-biopsy in this setting may not be feasible. Circulating tumor DNA (ctDNA) approaches for identification of genetic alterations in cancer patients may be more informative as the alterations reflect the current status of the tumor. ctDNA is representative of multiple tumor sites within a patient and may aid in the detection of alterations throughout the course of therapy. However, the fraction of ctDNA obtained from a blood sample is often very low (99% at MAFs of ≥20% and ≥0.50%, respectively. PlasmaSelect64 provides a non-invasive platform to enable detection of clinically relevant genetic alterations across a large number of genomic regions to aid in the therapeutic management of cancer patients. Citation Format: Monica Nesselbush, Samuel Angiuoli, Luis A. Diaz, Andrew Georgiadis, Shannon Glynn, Siân Jones, Laurel Keefer, Peter LoVerso, Derek Murphy, Sonya Parpart-Li, David Riley, Naomi Sengamalay, Manish Shukla, John Simmons, Snehal Talati, Rebecca Steinberg, Laura Tucker, Victor E. Velculescu, Ellen Verner, Angela Villarta, Mark Sausen. Clinical validation of a cell-free DNA liquid biopsy approach for noninvasive molecular profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4954. doi:10.1158/1538-7445.AM2017-4954

Analyses of genomic alterations in cell-free DNA (cfDNA) shed from tumors into the blood stream is rapidly advancing as a method to detect and genotype cancer. Liquid biopsy analyses are a favorable alternative to invasive tissue approaches, particularly for cancers in organs where tissue is difficult to obtain. As these methods become a clinical standard, the method for blood collection and plasma isolation will be an important consideration to ensure optimal assay performance with limited degradation of circulating tumor DNA (ctDNA). We compared blood collection and plasma isolation using both K2EDTA and cell-free DNA Streck™ BCT tubes to determine the stability of cfDNA and ctDNA in blood at room temperature or at 4°C. Blood was collected from nine cancer patients with KRAS mutations using K2EDTA and Streck™ BCT tubes. Over the course of seven days, cell lysis occurred in K2EDTA tubes at room temperature, releasing germline DNA into the blood (1300% increase over seven days), which significantly increased the number of total genomic equivalents. Additionally, we found that the volume of plasma collected from both tube types during blood fractionation decreased over time when tubes were at room temperature (an average of 3.5 mL vs. 1.0 mL, respectively). To evaluate the effect of storage conditions on performance of each tube type, blood was also collected from six cancer patients with KRAS or EGFR mutations and either maintained at room temperature or stored at 4°C for up to three days. Taken together, K2EDTA tubes stored at 4°C prevented cell lysis and preserved the ctDNA in a manner equivalent to Streck™ BCT tubes. These data demonstrate that liquid biopsies can be collected using either tube type with similar performance and appropriate consideration of storage conditions. Citation Format: Sonya T. Parpart-Li, Bjarne Bartlett, Maria Popoli, Vilmos Adleff, Julie Brahmer, Nilo Azad, Sarah Bonerigo, Ilene Browner, Amy Ryan, Victor Velculescu, Mark Sausen, Luis A. Diaz. Optimized plasma collection procedures for liquid biopsy analyses in cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3957.

Pancreatic adenocarcinoma has the worst overall mortality of any solid tumor, with only 6% of patients surviving after 5 years. To evaluate the clinical implications of genomic alterations in this low cellularity tumor type, we deeply sequenced the genomes of 134 enriched pancreatic adenocarcinomas from patients who underwent potentially curative resections. Given the low neoplastic cellularity of pancreatic cancers, we enriched for neoplastic cells either by macrodissection of primary tumors or by flow-sorting of tumor nuclei, and performed deep sequencing (high coverage) of these enriched samples using next-generation sequencing approaches. We obtained a total of >1Tb of sequence data, resulting in an average coverage within the target regions of >200-fold for each tumor analyzed by whole-exome sequencing and >750-fold for each tumor analyzed by targeted cancer gene sequencing. These approaches allowed us to identify sequence changes, including single base and small insertion or deletion mutations, as well as copy number alterations in >20,000 genes in the whole-exome analyses and in 116 specific genes in the targeted analyses. These analyses revealed that somatic mutation of chromatin remodeling genes were associated with improved progression-free and overall survival. Alterations in genes with potential clinical utility were observed in a majority of cases and included alterations of AKT1, AKT2, BRCA2, ERBB2, KIT, and PIK3CA. Non-invasive liquid biopsy analyses were performed before and after surgery to evaluate the presence of circulating tumor DNA in the plasma of 83 patients. Through these approaches, we were able to diagnose early stage pancreatic tumors in the majority of patients and to detect the presence of circulating tumor DNA prior to clinical relapse. These observations provide genetic markers of clinical outcome in pancreatic cancer and suggest new avenues for personalized therapy. Citation Format: Mark Sausen, Jillian Phallen, Vilmos Adleff, Siân Jones, Rebecca J. Leary, Karli Lytle, Sonya Parpart-Li, Derek Murphy, Michael T. Barrett, David C. Linehan, Anirban Maitra, Ralph Hruban, Daniel D. Von Hoff, Julia S. Johansen, Luis A. Diaz, Jeffrey A. Drebin, Victor E. Velculescu. Identification of clinically actionable genomic alterations in the tumor and circulation of pancreatic cancer patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 619. doi:10.1158/1538-7445.AM2015-619

The detection of tumor specific genomic alterations in circulating tumor DNA (ctDNA) has largely centered on point mutations. The identification of tumor-derived structural changes including rearrangements and amplifications has been more challenging. Approaches that analyze allelic imbalance are often not sufficiently specific to accurately define such events for solid tumor malignancies that shed low levels of DNA. Since some of the most robust clinical responses to targeted therapies have been those directed at gene products from amplified loci, we developed a method to detect such changes in a highly specific manner. One of the most attractive therapeutic targets in oncology is currently the MET/HGF pathway, which is activated as a result of gene amplification of the MET tyrosine kinase receptor. This pathway can be activated de novo or as a mechanism of acquired resistance to EGFR inhibition in a variety of cancers. We have developed an assay, termed METDetect, to capture and sequence the genomic regions corresponding to the MET gene, including coding and non-coding loci as well as control regions. Sequencing of these regions resulted an average of 33Gb of sequence data at a coverage of 3,125-fold per analyzed base. Validation analyses showed that amplification associated rearrangements resulting from focal amplification of the MET gene were readily detected to a level of 0.25% mutant DNA molecules while these were not present in tumors or ctDNA without such alterations. We applied METDetect to 205 plasma samples from patients with gastric, lung and esophageal cancer. MET amplification was also evaluated through either FISH or next-generation sequence approaches, and ranged from 2.2-fold to 30-fold in the tissue of patients with MET amplification. A concordance of >90% was achieved when MET amplification in plasma DNA was compared to MET amplification status in matched tumor tissue. We detected between 1 and 86 rearrangements associated with MET amplification in the plasma and calculated the global MET copy number to be 1.0-10.0 fold (average 2.2-fold) for each amplified case. Finally, no MET amplification associated rearrangements or amplified copy number results were noted in plasma samples from 19 patients whose tumors did not harbor MET amplification. METDetect is a noninvasive, ctDNA-based assay with high precision and accuracy for the detection of MET amplification in patients with cancer. Citation Format: Mark Sausen, Samuel V. Angiuoli, Bryan Chesnick, Kevin Galens, Siân Jones, Maura Kadan, Lisa Kann, Karli Lytle, Derek Murphy, Monica Nesselbush, Sonya Parpart-Li, David Riley, Manish Shukla, Theresa Zhang, Victor E. Velculescu, Luis A. Diaz. Noninvasive detection of MET gene amplification in the circulation of cancer patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5246. doi:10.1158/1538-7445.AM2015-5246

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to identify targeted therapies based on mutations identified. A major question in these analyses is the extent to which these methods identify clinically actionable alterations in patients and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated tumor-normal paired samples from 753 cancers from fourteen tumor types. We analyzed somatic alterations using whole exome or targeted next generation sequencing approaches that were validated with high sensitivity and specificity. These analyses revealed an average of 140 and 4.34 somatic changes per exome and targeted analyses, respectively. Approximately 65% of cases had somatic alterations in genes associated with known therapies or current clinical trials. In contrast, a tumor-only sequencing approach followed by bioinformatic removal of common germline variants from existing databases led to a 36% and 58% false discovery rate in alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic alterations and have important implications for the diagnostic and therapeutic management of cancer patients. Citation Format: Siân Jones, Mark Sausen, Valsamo Anagnostou, Samuel V. Angiuoli, Bryan Chesnick, Kevin Galens, Maura Kadan, Lisa Kann, Karli Lytle, Derek Murphy, Monica Nesselbush, Eniko Papp, Sonya Parpart-Li, David Riley, Manish Shukla, Theresa Zhang, Luis A. Diaz, Victor E. Velculescu. The importance of matched tumor and normal DNA for somatic mutation discovery and clinical interpretation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3894. doi:10.1158/1538-7445.AM2015-3894

Circulating tumor DNA (ctDNA) is released from tumor tissue into the blood, carries tumor specific genetic alterations, and can be analyzed through noninvasive “liquid biopsy” approaches to identify genetic alterations in cancer patients. Liquid biopsies offer a considerable advantage as they may eliminate the need for invasive tissue biopsies and allow for the detection of alterations in multiple metastatic lesions throughout the course of therapy. However, the fraction of ctDNA obtained from a blood sample is often very low (80,000 nucleotides spanning 63 well-established cancer genes. In addition to evaluation of exons in genes that are frequently mutated in cancer, PlasmaSelect also performs a comprehensive genomic analysis of translocations in 10 genes and the full coding regions of 18 tumor suppressor genes significant in cancer tumorigenesis. To evaluate the PlasmaSelect approach, we performed dilution series using tumor-derived DNA, containing well-characterized somatic mutations, in the presence with wild-type DNA. PlasmaSelect was able to detect genetic alterations with a lower level of detection of >0.1% with high specificity. We evaluated the utility of PlasmaSelect for detection of genetic alterations in the plasma and matched tissue biopsy specimens from late stage cancer patients. These analyses demonstrated high concordance between the somatic sequence mutations and translocations identified in the tumor sample and those identified directly in the plasma, including alterations in both driver genes as well as those related to acquired resistance to targeted therapies. PlasmaSelect provides a non-invasive platform to enable liquid biopsy detection of clinically relevant genetic alterations across a large number of genomic loci. Citation Format: Sonya T. Parpart-Li, Samuel V. Angiuoli, Bryan Chesnick, Kevin Galens, Siân Jones, Maura Kadan, Lisa Kann, Karli Lytle, Derek Murphy, Monica Nesselbush, Jillian Phallen, David Riley, Manish Shukla, Theresa Zhang, Hatim Husain, Victor E. Velculescu, Luis A. Diaz, Mark Sausen. A method for comprehensive genomic analysis of cell free DNA. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2405. doi:10.1158/1538-7445.AM2015-2405

11025 Background: Despite aggressive therapeutic interventions with pancreaticoduodenectomy and adjuvant chemo/chemoradiotherapy, recurrence rates remain high for patients with resectable pancreas ...

e19082 Background: Liquid biopsies of circulating tumor DNA (ctDNA) may eliminate the need for invasive tissue biopsies and allow the detection of alterations in multiple metastatic lesions through...

1529 Background: The anticipated widespread adoption of large scale genomic analyses in precision oncology mandates the development of a gene actionability framework. Previous efforts of clinical i...

e22086 Background: Cancer is a disease caused by the accumulation of genetic alterations which initiate and promote the uncontrolled growth and metastasis of cancer cells. These genetic alterations...

e22070 Background: Liquid biopsies of circulating tumor DNA (ctDNA) offer a considerable advantage as they may eliminate the need for invasive tissue biopsies and allow for the detection of alterat...