Abstract 3375: Ultrasensitive ctDNA minimal residual disease monitoring in early NSCLC with PhasED-Seq

Background: Circulating tumor DNA (ctDNA) minimal residual disease (MRD) detection is a promising approach for personalization of adjuvant therapy in non-small cell lung cancer (NSCLC). First generation ctDNA MRD assays that employ tumor-informed approaches to track single nucleotide variants (SNVs) have limits of detection (LOD95) of ~1E-4 and have high positive predictive values for recurrence. However, they have suboptimal clinical sensitivity, with false negative results at the completion of therapy in most patients who will ultimately recur. PhasED-Seq is a novel ctDNA MRD method that tracks multiple “phased” variants (PVs) within individual DNA fragments with a LOD95 ~100-fold better than first generation assays. Here we report PhasED-Seq ctDNA MRD results for the first prospective cohort of early stage NSCLC patients.

Methods: Tumor tissues (n=46), PBMCs (n=46) and plasma samples (n=169) from 46 Stage I-III NSCLC patients treated with curative intent were prospectively collected at Memorial Sloan Kettering Cancer Center. All patients underwent resection and received neoadjuvant +/- adjuvant therapy (n=14), adjuvant therapy only (n=17), or neither (n=15). Samples were analyzed in Foresight Diagnostics' CLIA laboratory (Aurora, CO) using personalized PhasED-Seq. Briefly, PVs were identified via whole genome sequencing of tumors and matched blood germline DNA. Custom capture panels targeting PVs were synthesized and used to assess MRD status in pre-, on- and post-treatment plasma samples. Detection of ctDNA MRD was assessed at a post-treatment landmark, defined as the first post-therapy sample or when not available the last post-surgical sample taken during therapy. To enable comparisons, the same plasma samples were analyzed using an SNV-based ctDNA MRD approach.

Results: PVs were identified in tumor tissue from all 46 patients. Across all plasma samples PhasED-Seq achieved a median LOD95 of 1.3E-6 and as low as 2.5E-7. Of 74 plasma samples with detectable ctDNA, 38 (51%) contained concentrations below 1E-4 and the lowest level of ctDNA MRD detected was 1.7E-7. For post-treatment landmark samples (n=45), the median time from end of therapy was 2 months. Cancer recurred in all patients (n=10) with detectable MRD at the landmark. Furthermore, PhasED-Seq better stratified freedom from recurrence (log-rank p=3E-8, Cox HR=10.8) than the SNV-based approach (log-rank p=0.08, Cox HR=2.5) and detected MRD at the landmark in more patients who ultimately recurred (56% vs 28%). PhasED-Seq also achieved longer lead times, including detecting MRD in 66% of samples collected 12 to 24 months prior to recurrence versus only 33% using SNV-based monitoring.

Conclusion: PhasED-Seq achieves ctDNA detection below 1 part per million and appears to be significantly more sensitive than SNV-based MRD monitoring. These results suggest that PhasED-Seq is a promising approach for use in risk adapted trials in early stage NSCLC.

Citation Format: James M. Isbell, Bob T. Li, Pedram Razavi, Jorge Reis-Filo, Si-Yang Liu, Pier Selenica, Prasad Adusumilli, Matthew Bott, David R. Jones, Valerie W. Rusch, Smita Sihag, Darren J. Buonocore, Justin Jee, Emily Lebow, Daniel Gomez, Andreas Rimner, Fernando C. Santini, Charles M. Rudin, Jordan E. Eichholz, Andres Martinez, Daphne Alerte, Gregory J. Hogan, Andre Schultz, Ronald P. Schuyler, Alanna Roff, Dustin Hite, Jacob J. Chabon, David M. Kurtz, Ash A. Alizadeh, Maximilian Diehn. Ultrasensitive ctDNA minimal residual disease monitoring in early NSCLC with PhasED-Seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3375.

Genomic Profiling of Bronchoalveolar Lavage Fluid in Lung Cancer

Genomic profiling of bronchoalveolar lavage (BAL) samples may be useful for tumor profiling and diagnosis in the clinic. Here, we compared tumor-derived mutations detected in BAL samples from subjects with non-small cell lung cancer (NSCLC) to those detected in matched plasma samples. Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) was used to genotype DNA purified from BAL, plasma, and tumor samples from patients with NSCLC. The characteristics of cell-free DNA (cfDNA) isolated from BAL fluid were first characterized to optimize the technical approach. Somatic mutations identified in tumor were then compared with those identified in BAL and plasma, and the potential of BAL cfDNA analysis to distinguish lung cancer patients from risk-matched controls was explored. In total, 200 biofluid and tumor samples from 38 cases and 21 controls undergoing BAL for lung cancer evaluation were profiled. More tumor variants were identified in BAL cfDNA than plasma cfDNA in all stages (P < 0.001) and in stage I to II disease only. Four of 21 controls harbored low levels of cancer-associated driver mutations in BAL cfDNA [mean variant allele frequency (VAF) = 0.5%], suggesting the presence of somatic mutations in nonmalignant airway cells. Finally, using a Random Forest model with leave-one-out cross-validation, an exploratory BAL genomic classifier identified lung cancer with 69% sensitivity and 100% specificity in this cohort and detected more cancers than BAL cytology. Detecting tumor-derived mutations by targeted sequencing of BAL cfDNA is technically feasible and appears to be more sensitive than plasma profiling. Further studies are required to define optimal diagnostic applications and clinical utility.

SIGNIFICANCE

Hybrid-capture, targeted deep sequencing of lung cancer mutational burden in cell-free BAL fluid identifies more tumor-derived mutations with increased allele frequencies compared with plasma cell-free DNA. See related commentary by Rolfo et al., p. 2826.

Inferring gene expression from cell-free DNA fragmentation profiles

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

Enhanced detection of minimal residual disease by targeted sequencing of phased variants in circulating tumor DNA

Circulating tumor-derived DNA (ctDNA) is an emerging biomarker for many cancers, but the limited sensitivity of current detection methods reduces its utility for diagnosing minimal residual disease. Here we describe phased variant enrichment and detection sequencing (PhasED-seq), a method that uses multiple somatic mutations in individual DNA fragments to improve the sensitivity of ctDNA detection. Leveraging whole-genome sequences from 2,538 tumors, we identify phased variants and their associations with mutational signatures. We show that even without molecular barcodes, the limits of detection of PhasED-seq outperform prior methods, including duplex barcoding, allowing ctDNA detection in the ppm range in participant samples. We profiled 678 specimens from 213 participants with B cell lymphomas, including serial cell-free DNA samples before and during therapy for diffuse large B cell lymphoma. In participants with undetectable ctDNA after two cycles of therapy using a next-generation sequencing-based approach termed cancer personalized profiling by deep sequencing, an additional 25% have ctDNA detectable by PhasED-seq and have worse outcomes. Finally, we demonstrate the application of PhasED-seq to solid tumors.

A Comprehensive Circulating Tumor DNA Assay for Detection of Translocation and Copy-Number Changes in Pediatric Sarcomas

Most circulating tumor DNA (ctDNA) assays are designed to detect recurrent mutations. Pediatric sarcomas share few recurrent mutations but rather are characterized by translocations and copy-number changes. We applied Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for detection of translocations found in the most common pediatric sarcomas. We also applied ichorCNA to the combined off-target reads from our hybrid capture to simultaneously detect copy-number alterations (CNA). We analyzed 64 prospectively collected plasma samples from 17 patients with pediatric sarcoma. Translocations were detected in the pretreatment plasma of 13 patients and were confirmed by tumor sequencing in 12 patients. Two of these patients had evidence of complex chromosomal rearrangements in their ctDNA. We also detected copy-number changes in the pretreatment plasma of 7 patients. We found that ctDNA levels correlated with metastatic status and clinical response. Furthermore, we detected rising ctDNA levels before relapse was clinically apparent, demonstrating the high sensitivity of our assay. This assay can be utilized for simultaneous detection of translocations and CNAs in the plasma of patients with pediatric sarcoma. While we describe our experience in pediatric sarcomas, this approach can be applied to other tumors that are driven by structural variants.

Leveraging phased variants for personalized minimal residual disease detection in localized non-small cell lung cancer

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Background: Detection of circulating tumor DNA (ctDNA) has prognostic value in lung cancer and could facilitate minimal residual disease (MRD) driven approaches. However, the sensitivity of ctDNA detection is suboptimal due to the background error rates of existing assays. We developed a novel method leveraging multiple mutations on a single cell-free DNA molecule (“phased variants” or PVs) resulting in an ultra-low error profile. Here we develop and apply this approach to improve MRD in localized NSCLC. Methods: To identify the prevalence of PVs, we reanalyzed whole genome sequencing (WGS) from 2,538 tumors and 24 cancer types from the pan-cancer analysis of whole genomes (PCAWG). We applied Phased Variant Enrichment and Detection Sequencing (PhasED-Seq) to track personalized PVs in localized NSCLC. We compared PhasED-Seq to a single nucleotide variant (SNV)-based ctDNA method. Results: In the PCAWG dataset, we found that PVs were common in both lung squamous cell carcinomas (LUSC, median 1,268/tumor; rank 2nd) and adenocarcinomas (LUAD, median 655.5/tumor; rank 3rd). However, PVs did not occur in stereotyped genomic regions. Thus, to leverage PhasED-Seq, we performed tumor/normal WGS to identify PVs, followed by design of personalized panels targeting PVs to allow deep cfDNA sequencing. We performed personalized PhasED-Seq for 5 patients with localized NSCLC. PVs were identified from WGS of tumor FFPE and validated by targeted resequencing in all cases (median 248/case). The background rate of PVs was lower than that of SNVs, even when considering duplex molecules (background: SNVs, 3.8e-5; duplex SNVs, 1.0e-5; PVs, 1.2e-6; P < 0.0001). We next assessed PhasED-Seq for MRD detection in 14 patient plasma samples. Both SNVs and PhasED-Seq had high specificity in healthy control cfDNA (95% and 97% respectively). Using SNVs, ctDNA was detected in 5/14 samples; PhasED-Seq detected all of these with nearly identical tumor fractions (Spearman rho = 0.97). However, PhasED-Seq also detected MRD in an additional 5 samples containing tumor fractions as low as 0.000094% (median 0.0004%). We analyzed serial samples from a patient with stage III LUAD treated with chemoradiotherapy (CRT) and durvalumab. SNV-based ctDNA and PhasED-Seq detected similar MRD levels (0.8%) prior to therapy. However, 3 samples collected during CRT, as well as before and during immunotherapy, were undetectable by SNVs. SNV-based ctDNA then re-emerged at disease recurrence. PhasED-Seq detected MRD in all 3 samples not detected by SNVs with tumor fractions as low as 0.00016%, including prior to immunotherapy (8 months prior to progression). Similar improvements were seen in samples not detected by SNVs from 2 additional patients. Conclusions: Personalized ctDNA monitoring via PVs is feasible and improves MRD detection in localized NSCLC. PhasED-Seq allows clinical studies testing personalized treatment based on MRD.

Phased variants improve DLBCL minimal residual disease detection at the end of therapy

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Background: Detection of circulating tumor DNA (ctDNA) has prognostic value in diverse tumors, including DLBCL. Despite uses for assessing molecular response to therapy, current methods using immunoglobulin or hybrid-capture sequencing have suboptimal sensitivity, particularly when disease-burden is low. This contributes to a high false negative rate at key milestones such as at the end of therapy (EOT; Kumar A, ASH 2020). We explored the utility of detecting multiple mutations (phased variants, PVs) on individual cell-free DNA (cfDNA) strands to improve MRD in DLBCL. Methods: We applied Phased Variant Enrichment and Detection Sequencing to track PVs from 485 specimens from 117 DLBCL patients undergoing first-line therapy. We sequenced cfDNA prior to, during, and after therapy to assess the prognostic value of MRD. We compared the performance of PhasED-Seq to current techniques, including SNV-based CAPP-Seq and duplex sequencing. Results: To establish its detection limit for ctDNA, we compared the background error-profile of of PVs and SNVs in cfDNA sequencing from healthy subjects. PV-detection by PhasED-Seq demonstrated a lower background profile than SNVs, even when considering duplex molecules (n = 12; 8.0e-7 vs 3.3e-5 and 1.2e-5; P < 0.0001). We also assessed analytical sensitivity within a ctDNA limiting dilution series from 3 patients, simulating tumor fractions from 0.1% to 0.00005% (1:2,000,000). PhasED-Seq outperformed SNV-based methods and duplex sequencing for recovery of expected tumor content below 0.01% (P < 0.0001 and P = 0.005 respectively by paired t-test). We then explored disease detection in clinical samples. We identified SNVs and PVs from pretreatment tumor or plasma and followed these variants in serial cfDNA. Using SNV-based methods, 40% and 59% of patients had undetectable ctDNA after 1 or 2 cycles (n = 82 and 88). However, 24% and 25% of these cases had detectable ctDNA by PhasED-Seq. Importantly, MRD detection by PhasED-Seq was prognostic for event-free survival even in patients with undetectable ctDNA by SNVs. We next explored the utility of PhasED-Seq at the EOT in 19 subjects, 5 of whom experienced eventual disease progression. While only 2/5 cases with progression had detectable disease at EOT using SNVs, PhasED-Seq detected all 5/5 cases. PhasED-Seq also correctly identified all patients (14/14) without clinical relapse as having no residual disease, including one patient who discontinued therapy after 1 cycle due to toxicity, but remains in remission > 5 years after this single treatment. This resulted in superior classification of patients for EFS using PVs compared with SNVs (C-statistic: 0.98 vs 0.60, P = 0.02). Conclusions: Tracking PVs results in significantly lower background rates than SNV-based approaches, enabling detection to parts per million range. PhasED-Seq improves on disease detection in DLBCL at the EOT, allowing possible MRD-driven consolidative approaches.

KEAP1/NFE2L2 Mutations Predict Lung Cancer Radiation Resistance That Can Be Targeted by Glutaminase Inhibition

Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that KEAP1 and NFE2L2 mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in tumors with KEAP1/NFE2L2 mutations, indicating that they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate KEAP1/NFE2L2 mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes KEAP1-mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for KEAP1/NFE2L2 mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations. SIGNIFICANCE: This study shows that mutations in KEAP1 and NFE2L2 predict for LR after radiotherapy but not surgery in patients with NSCLC. Approximately half of all LRs are associated with these mutations and glutaminase inhibition may allow personalized radiosensitization of KEAP1/NFE2L2-mutant tumors.This article is highlighted in the In This Issue feature, p. 1775.

A mathematical model of ctDNA shedding predicts tumor detection size

Early cancer detection aims to find tumors before they progress to an incurable stage. To determine the potential of circulating tumor DNA (ctDNA) for cancer detection, we developed a mathematical model of tumor evolution and ctDNA shedding to predict the size at which tumors become detectable. From 176 patients with stage I to III lung cancer, we inferred that, on average, 0.014% of a tumor cell's DNA is shed into the bloodstream per cell death. For annual screening, the model predicts median detection sizes of 2.0 to 2.3 cm representing a ~40% decrease from the current median detection size of 3.5 cm. For informed monthly cancer relapse testing, the model predicts a median detection size of 0.83 cm and suggests that treatment failure can be detected 140 days earlier than with imaging-based approaches. This mechanistic framework can help accelerate clinical trials by precomputing the most promising cancer early detection strategies.

Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

Abstract 5666: A noninvasive approach for early prediction of therapeutic benefit from immune checkpoint inhibition for lung cancer

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICI) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we analyze 211 samples from 99 patients and demonstrate that pre-treatment circulating tumor DNA (ctDNA) and circulating immune profiles are independently associated with DCB. We further show that ctDNA dynamics after a single ICI infusion can identify the majority of patients who will achieve DCB. Integrating these determinants, we describe an entirely noninvasive multi-analyte assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA- On-treatment) that robustly predicted DCB, and that was validated in two independent cohorts (AUC = 0.89-0.93, PPV = 92-100%, HR = 0.04-0.11). Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICI.

Citation Format: Barzin Y. Nabet, Mohammad S. Esfahani, Emily G. Hamilton, Jacob J. Chabon, Everett J. Moding, Hira Rizvi, Chloe B. Steen, Aadel A. Chaudhuri, Chih Long Liu, Angela B. Hui, Henning Stehr, Linda Goljenola, Michael C. Jin, Young-Jun Jeon, Diane Tseng, Taha Merghoub, Joel W. Neal, Heather A. Wakelee, Sukhmani K. Padda, Kavitha J. Ramchandran, Millie Das, Rene F. Bonilla, Christopher Yoo, Emily L. Chen, Ryan B. Ko, Aaron M. Newman, Matthew D. Hellmann, Ash A. Alizadeh, Maximilian Diehn. A noninvasive approach for early prediction of therapeutic benefit from immune checkpoint inhibition for lung cancer [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 5666.

Abstract PR01: ctDNA shedding dynamics dictate early lung cancer detection potential

Early cancer detection aims to find tumors before they progress to an incurable stage. Prospective studies with tens of thousands of healthy participants are ongoing to determine whether asymptomatic cancers can be accurately detected by analyzing circulating tumor DNA (ctDNA) from blood samples. We developed a stochastic mathematical model of tumor evolution and ctDNA shedding to investigate the potential and the limitations of ctDNA-based cancer early detection tests. We inferred ctDNA shedding rates of early-stage lung cancers and calculated that a 15-mL blood sample contains on average only 1.5 genome equivalents (GE) of ctDNA for lung tumors with 1 billion cells (concentration of 0.19 GE per plasma mL; tumor fraction of 0.02%). This low level of ctDNA can be explained by the relatively low turnover rate of lung cancer cells. Similarly, fast-growing tumors led to lower levels of ctDNA because a lower number of cell death events decreases the amount of released ctDNA. We designed a detection test of virtual tumors that accounts for the varying plasma DNA concentrations in cancer and cancer-free patients and that incorporates various sources for technical and biologic errors. Two important considerations for disease detection are the expected number of mutations per tumor covered by the sequencing panel and the underlying error rate of the sequencing assay. To determine the potential performance of mutation-based ctDNA detection tests, we computed receiver operating characteristic (ROC) curves and calculated area under the curve (AUC) values. In the case of early relapse detection, we assumed that the sequencing panel covers 20 known clonal mutations per primary tumor with a background error-rate of 1.5 × 10−5 per base pair. For monthly relapse testing with a specificity of 99.5%, we found a median detection size of 0.19 cm3. Moreover, we observed a lead time of 180 days compared to monthly imaging-based relapse detection. While tracking fewer than 20 mutations drastically decreased the expected lead time, tracking more than 20 mutations only minimally increased the expected lead time. Similarly, the increases in lead time gained slowed down for more frequent testing than one month for relapsing tumors with a growth rate of 1%. In the case of cancer screening, we assumed that the sequencing panel has the same error rate as above and covers 2,000 base pairs, resulting in approximately one detectable mutation per lung cancer, which is similar to the CancerSEEK panel. For an annual screening test with a specificity of 99.5%, we found a median lung cancer detection size of 4.4 cm3. This detection size constitutes a more than 80% reduction from the current median detection size of 22.5 cm3 for lung cancers and suggests a potential lead time of 410 days. This mathematical framework provides a mechanistic interpretation of ctDNA-based test results and informs the design of future screening and relapse detection initiatives across cancer types and subpopulations with varying risks.

This abstract is also being presented as Poster A01.

Citation Format: Stefano Avanzini, David M. Kurtz, Jacob J. Chabon, Sharon S. Hori, Ash A. Alizadeh, Maximilian Diehn, Johannes G. Reiter. ctDNA shedding dynamics dictate early lung cancer detection potential [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR01.

Early ctDNA response assessment for prediction of platinum sensitivity in small cell lung cancer

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Background: Small cell lung cancer (SCLC) is an aggressive disease, characterized by inevitable chemotherapy resistance and rapid progression. We hypothesized that circulating tumor DNA (ctDNA) analysis can rapidly identify sensitivity to platinum-based therapy. Methods: Patients with SCLC at Memorial Sloan Kettering Cancer Center underwent serial plasma collections, including prior to the start of treatment and prior to Cycle 2 Day 1 of therapy (C2D1). Tumor mutations were identified from pre-treatment biopsies by MSK-IMPACT and/or pre-treatment plasma by CAncer Personalized Profiling by deep Sequencing (CAPP-Seq). Median variant allele fraction (VAF) of all mutations was monitored on subsequent blood draws using CAPP-Seq. Progression free survival (PFS) was measured from the time of first pre-treatment blood draw. Results: Plasma was collected from 19 patients treated with carboplatin and etoposide, including three who received concurrent atezolizumab. Seven were female, and mean age was 64.5 years. ctDNA was detected in 17 patients (89%), including in the two patients in our series with limited stage disease. The most common mutations were in TP53 and RB1 in 14 and 6 patients, respectively. Fourteen patients had available plasma at C2D1. At baseline prior to treatment, median VAF did not differ significantly between radiologic responders and non-responders (9.4% versus 30.3%, p = 0.35). After one cycle of chemotherapy, the VAF percent decrease was significantly more in responders versus non-responders (-96.9% versus -10.3%, p < 0.001). Median VAF was therefore significantly lower by C2D1 in patients who responded compared to non-responders (0.51% versus 27.2%, p = 0.02). Those who ultimately responded to therapy all had a > 2 fold decrease in VAF by C2D1. With a median follow-up of 180 days, PFS was significantly longer in patients with > 2 fold decrease in VAF by C2D1 (6.4 versus 1.9 months, log rank p < 0.001). Conclusions: A 2-fold decrease in plasma VAF by C2D1 predicted platinum-sensitivity in SCLC and was associated with longer PFS. ctDNA may permit early assessment of benefit and expedite alternative treatment options for those without significant decrease in median VAF after one cycle of therapy.

A mid-chemoradiation dynamic risk model integrating tumor features and ctDNA analysis for lung cancer outcome prediction

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Background: Circulating tumor DNA (ctDNA) molecular residual disease after curative intent therapy predicts disease progression in localized lung cancer. We hypothesized that integrating pre-CRT features and ctDNA levels during chemoradiation therapy (CRT) can predict patient outcomes earlier to enable response-adapted therapy. Methods: We identified pre-CRT features prognostic of disease progression after CRT for Stage II-III non-small cell lung cancer (NSCLC) in a historical “pre-CRT” training cohort of 109 patients. In addition, we applied CAPP-Seq ctDNA analysis pre-CRT and a median of 21 days into CRT (mid-CRT) to a “ctDNA” training cohort of 42 patients treated at MD Anderson and an independent validation cohort of 21 patients treated at Stanford. Prognostic pre-CRT features and mid-CRT ctDNA concentration were integrated using a Bayesian proportional hazards approach to generate a Continuous Individualized Risk Index (Kurtz et al. Cell 2019) for NSCLC (CIRI-NSCLC) to predict freedom from progression (FFP). Results: Adenocarcinoma histology (HR 2.6, P = 0.0005) and KEAP1 mutation (HR 2.7, P = 0.002) but not stage (P = 0.16), age (P = 0.60), or gender (P = 0.98) were significantly associated with FFP in the pre-CRT training cohort. Mid-CRT ctDNA concentration as a continuous variable was significantly associated with FFP in the ctDNA training cohort (HR 1.6, P = 0.04), and applying an optimal threshold identified in the training cohort (3.2 hGE/ml) significantly stratified FFP in the independent ctDNA validation cohort (HR 4.8, P = 0.02). CIRI-NSCLC enabled individualized real-time updating of the probability of FFP as model features became available over the course of CRT. CIRI-NSCLC outperformed individual model features in the independent validation cohort when compared by C-statistic (CIRI-NSCLC: 0.85; mid-CRT ctDNA: 0.76; histology: 0.66; KEAP1: 0.60). Across the whole cohort, patients with a greater than 66% risk of progression predicted by CIRI-NSCLC (n = 10) had an FFP of 10.0% at 12 months while patients with a less than 33% risk of progression predicted by CIRI-NSCLC (n = 22) had an FFP of 79.7% at 12 months (HR 15.0, P < 0.001). Conclusions: Our results suggest that CIRI-NSCLC can identify patients at very high and low risk of progression. Prospective evaluation will be necessary to test the potential utility of adapting treatment based on CIRI-NSCLC.

Integrating genomic features for non-invasive early lung cancer detection

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

Circulating Tumor DNA Analysis to Assess Risk of Progression after Long-term Response to PD-(L)1 Blockade in NSCLC

PURPOSE

Treatment with PD-(L)1 blockade can produce remarkably durable responses in patients with non-small cell lung cancer (NSCLC). However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression.

EXPERIMENTAL DESIGN

In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (progression-free survival ≥ 12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing. Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing (n = 18) or by targeted sequencing (n = 6).

RESULTS

Thirty-one patients with NSCLC with long-term benefit to PD-(L)1 blockade were identified, and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; in contrast, all 4 patients with detectable ctDNA eventually progressed [Fisher P < 0.0001; positive predictive value = 1, 95% confidence interval (CI), 0.51-1; negative predictive value = 0.93 (95% CI, 0.80-0.99)].

CONCLUSIONS

ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 blockade and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.

Circulating Tumor DNA Dynamics Predict Benefit from Consolidation Immunotherapy in Locally Advanced Non-Small Cell Lung Cancer

Circulating tumor DNA (ctDNA) molecular residual disease (MRD) following curative-intent treatment strongly predicts recurrence in multiple tumor types, but whether further treatment can improve outcomes in patients with MRD remains unclear. We applied CAPP-Seq ctDNA analysis to 218 samples from 65 patients receiving chemoradiation therapy (CRT) for locally advanced NSCLC, including 28 patients receiving consolidation immune checkpoint inhibition (CICI). Patients with undetectable ctDNA after CRT had excellent outcomes whether or not they received CICI. Among such patients, one died from CICI-related pneumonitis, highlighting the potential utility of only treating patients with MRD. In contrast, patients with MRD after CRT who received CICI had significantly better outcomes than patients who did not receive CICI. Furthermore, the ctDNA response pattern early during CICI identified patients responding to consolidation therapy. Our results suggest that CICI improves outcomes for NSCLC patients with MRD and that ctDNA analysis may facilitate personalization of consolidation therapy.

Circulating Tumor DNA Analysis for Detection of Minimal Residual Disease After Chemoradiotherapy for Localized Esophageal Cancer

BACKGROUND & AIMS

Biomarkers are needed to risk stratify after chemoradiotherapy for localized esophageal cancer. These could improve identification of patients at risk for cancer progression and selection of additional therapy.

METHODS

We performed deep sequencing (CAncer Personalized Profiling by deep Sequencing, [CAPP-Seq]) analyses of plasma cell-free DNA collected from 45 patients before and after chemoradiotherapy for esophageal cancer, as well as DNA from leukocytes and fixed esophageal tumor biopsy samples collected during esophagogastroduodenoscopy. Patients were treated from May 2010 through October 2015; 23 patients subsequently underwent esophagectomy, and 22 did not undergo surgery. We also sequenced DNA from blood samples from 40 healthy control individuals. We analyzed 802 regions of 607 genes for single-nucleotide variants previously associated with esophageal adenocarcinoma or squamous cell carcinoma. Patients underwent imaging analyses 6-8 weeks after chemoradiotherapy and were followed for 5 years. Our primary aim was to determine whether detection of circulating tumor DNA (ctDNA) after chemoradiotherapy is associated with risk of tumor progression (growth of local, regional, or distant tumors, detected by imaging or biopsy).

RESULTS

The median proportion of tumor-derived DNA in total cell-free DNA before treatment was 0.07%, indicating that ultrasensitive assays are needed for quantification and analysis of ctDNA from localized esophageal tumors. Detection of ctDNA after chemoradiotherapy was associated with tumor progression (hazard ratio, 18.7; P < .0001), formation of distant metastases (hazard ratio, 32.1; P < .0001), and shorter disease-specific survival times (hazard ratio, 23.1; P < .0001). A higher proportion of patients with tumor progression had new mutations detected in plasma samples collected after chemoradiotherapy than patients without progression (P = .03). Detection of ctDNA after chemoradiotherapy preceded radiographic evidence of tumor progression by an average of 2.8 months. Among patients who received chemoradiotherapy without surgery, combined ctDNA and metabolic imaging analysis predicted progression in 100% of patients with tumor progression, compared with 71% for only ctDNA detection and 57% for only metabolic imaging analysis (P < .001 for comparison of either technique to combined analysis).

CONCLUSIONS

In an analysis of cell-free DNA in blood samples from patients who underwent chemoradiotherapy for esophageal cancer, detection of ctDNA was associated with tumor progression, metastasis, and disease-specific survival. Analysis of ctDNA might be used to identify patients at highest risk for tumor progression.

ctDNA analysis for personalization of consolidation immunotherapy in localized non-small cell lung cancer

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Background: Detection of molecular residual disease via circulating tumor DNA (ctDNA) analysis after chemoradiation (CRT) in localized non-small cell lung cancer (NSCLC) predicts risk of relapse. We explored the hypotheses that (1) patients with undetectable ctDNA after CRT may not require consolidation immunotherapy (CI) and (2) ctDNA analysis could monitor the effectiveness of CI in patients with residual ctDNA after CRT. Methods: We applied CAPP-Seq ctDNA analysis to 88 plasma and matched leukocyte samples collected pre-CRT, post-CRT but pre-CI, and mid-CI in 22 patients with Stage IIB-IIIB NSCLC treated with CRT followed by CI. Identification of patient-specific tumor variants was performed using tumor tissue or pretreatment plasma, and ctDNA was quantified using a tumor mutation-informed bioinformatic strategy. Freedom from progression (FFP) defined radiographically by RECIST 1.1 criteria was compared in patients with ctDNA detected or not detected at pre-CI and mid-CI landmarks. Results: Median follow up from the start of CRT was 11 months. ctDNA detection was associated with inferior rates of FFP when compared to patients with ctDNA not detected both pre-CI (12-month 33% vs. 76%, P = 0.015, HR 7.51, 95% CI 1.47-38.24) and mid-CI (12-month 0% vs. 86%, P < 0.0001, HR 123.3, 95% CI 16.21-937.8). In patients with undetectable ctDNA after CRT, FFP was similar to a historical cohort of patients with undetectable ctDNA after CRT alone (12-month 88% vs. 87%, P = 0.56, HR 0.55, 95% CI 0.07-4.18), suggesting that such patients may not benefit from CI. All patients with detectable ctDNA pre-CI in whom ctDNA increased mid-CI developed progressive disease. Finally, in 2 patients with ctDNA detected after CRT, CI led to elimination of ctDNA at the mid-CI timepoint. One of these patients developed an isolated local recurrence 22 months after CRT and the other patient is currently disease free at 11 months, suggesting clinical benefit from CI. Conclusions: Our results suggest that ctDNA analysis may allow personalization and response monitoring of CI following CRT for NSCLC. Validation in more patients followed by prospective testing in clinical trials will be required to establish clinical utility of such an approach.

Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA

Current regimens for the detection and surveillance of bladder cancer are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage bladder cancer who had urine collected either prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per patient with bladder cancer and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of bladder cancer. We detected utDNA pretreatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, P = 0.02) and cytology and cystoscopy combined (P ≤ 0.006), detecting 100% of bladder cancer cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of bladder cancer. SIGNIFICANCE: This study shows that utDNA can be detected using HTS with high sensitivity and specificity in patients with early-stage bladder cancer and during post-treatment surveillance, significantly outperforming standard diagnostic modalities and facilitating noninvasive detection, genotyping, and monitoring.This article is highlighted in the In This Issue feature, p. 453.

Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma

PURPOSE

Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes.

PATIENTS AND METHODS

We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans.

RESULTS

Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival.

CONCLUSION

Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.

Combination Approach for Detecting Different Types of Alterations in Circulating Tumor DNA in Leiomyosarcoma

Purpose: The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA.Experimental Design: We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma.Results: We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles.Conclusions: Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. Clin Cancer Res; 24(11); 2688-99. ©2018 AACR.

Abstract A05: Circulating tumor DNA levels correlate with response to treatment in LMS patients

Circulating tumor DNA (ctDNA) has significant potential for several clinical applications, including assessment of treatment response and monitoring of recurrent/residual disease. We performed a pilot study to explore the feasibility of ctDNA monitoring in patients with leiomyosarcoma (LMS).

We profiled matching plasma and FFPE tumor specimens from 9 LMS patients. We analyzed between 2 to 6 longitudinal plasma samples (median of 5) and between 1 to 7 tumor specimens (median of 2) per patient. ctDNA analysis was performed on plasma samples collected pre-/post-surgery, throughout chemo-/radiotherapy and during follow-up. We used two separate approaches in our study: 1) targeted deep sequencing of ctDNA, tumor DNA and germline DNA to detect single nucleotide variants and indels using Cancer Personalized Profiling by deep Sequencing with integrated digital error suppression (CAPP-Seq; with a median deduplicated depth of sequencing of 2,136x); 2) copy number variant analysis in ctDNA by genome representation profiling (GRP; median coverage across the whole genome 0.23x) and in the matched tumors by SNP arrays. One patient was excluded from the analysis due to inadequate sequencing coverage in tumor specimen.

For CAPP-Seq analysis, we designed a custom 184kb capture panel targeting 89 genes that are recurrently mutated in LMS. Using strict variant calling criteria (requiring that variants be present on each strand of the original DNA “duplex” molecule) our panel identified a median of one nonsynonymous coding/splicing variant per tumor. We detected the same variants in TP53, RB1 and ATRX genes in ctDNA of 6/8 patients (with a baseline sensitivity of 87.5% and overall specificity of 98.96% calculated using plasma from 24 healthy donors). These six patients presented with advanced disease at the time of the first blood collection and were progressing throughout multiple lines of therapy. Two patients who did not have any variants detectable by CAPP-Seq in plasma had localized disease at the time of the first blood collection and/or responded well to the therapy. We found that changes in ctDNA levels appear to correspond with the extent of disease and response to treatment. Specifically, ctDNA levels decreased in a subset of patients after surgery or at the time of temporary response to chemo- and/or radiotherapy. Congruently, increases in ctDNA levels correlated with progression in most of the patients. There was a high correlation between ctDNA levels detected by CAPP-Seq (quantified as mutant molecules/mL plasma) and GRP (quantified as percent of genome showing copy number aberrations) across all plasma samples (Pearson's r= 0.88, p &lt; 0.0001), but in a few samples ctDNA was detected by only one of the two assays.

Our results suggest that serial analysis of ctDNA is a promising approach for evaluation of treatment response in LMS patients. Validation of these findings in a prospective study on a larger group of patients will be required to determine the use of this approach in a clinical setting.

References:

CAPP-Seq: PMIDs 24705333, 27018799

GRP: PMIDs 25585704, 26687610

Citation Format: Joanna Przybyl, Jacob J. Chabon, Lien Spans, Kristen Ganjoo, Sujay Vennam, Aaron M. Newman, Erna Forgó, Sushama Varma, Shirley Zhu, Maria Debiec-Rychter, Ash Alizadeh, Maximilian Diehn, Matt van de Rijn. Circulating tumor DNA levels correlate with response to treatment in LMS patients [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr A05.

Evolution and clinical impact of co-occurring genetic alterations in advanced-stage EGFR-mutant lung cancers

A widespread approach to modern cancer therapy is to identify a single oncogenic driver gene and target its mutant-protein product (for example, EGFR-inhibitor treatment in EGFR-mutant lung cancers). However, genetically driven resistance to targeted therapy limits patient survival. Through genomic analysis of 1,122 EGFR-mutant lung cancer cell-free DNA samples and whole-exome analysis of seven longitudinally collected tumor samples from a patient with EGFR-mutant lung cancer, we identified critical co-occurring oncogenic events present in most advanced-stage EGFR-mutant lung cancers. We defined new pathways limiting EGFR-inhibitor response, including WNT/β-catenin alterations and cell-cycle-gene (CDK4 and CDK6) mutations. Tumor genomic complexity increases with EGFR-inhibitor treatment, and co-occurring alterations in CTNNB1 and PIK3CA exhibit nonredundant functions that cooperatively promote tumor metastasis or limit EGFR-inhibitor response. This study calls for revisiting the prevailing single-gene driver-oncogene view and links clinical outcomes to co-occurring genetic alterations in patients with advanced-stage EGFR-mutant lung cancer.

Deactivated CRISPR Associated Protein 9 for Minor-Allele Enrichment in Cell-Free DNA

BACKGROUND

Cell-free DNA (cfDNA) diagnostics are emerging as a new paradigm of disease monitoring and therapy management. The clinical utility of these diagnostics is relatively limited by a low signal-to-noise ratio, such as with low allele frequency (AF) mutations in cancer. While enriching for rare alleles to increase their AF before sample analysis is one strategy that can greatly improve detection capability, current methods are limited in their generalizability, ease of use, and applicability to point mutations.

METHODS

Leveraging the robust single-base-pair specificity and generalizability of the CRISPR associated protein 9 (Cas9) system, we developed a deactivated Cas9 (dCas9)-based method of minor-allele enrichment capable of efficient single-target and multiplexed enrichment. The dCas9 protein was complexed with single guide RNAs targeted to mutations of interest and incubated with cfDNA samples containing mutant strands at low abundance. Mutation-bound dCas9 complexes were isolated, dissociated, and the captured DNA purified for downstream use.

RESULTS

Targeting the 3 most common epidermal growth factor receptor mutations (exon 19 deletion, T790M, L858R) found in non-small cell lung cancer (NSCLC), we achieved >20-fold increases in AF and detected mutations by use of qPCR at an AF of 0.1%. In a cohort of 18 NSCLC patient-derived cfDNA samples, our method enabled detection of 8 out of 13 mutations that were otherwise undetected by qPCR.

CONCLUSIONS

The dCas9 method provides an important application of the CRISPR/Cas9 system outside the realm of genome editing and can provide a step forward for the detection capability of cfDNA diagnostics.

Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling

Identifying molecular residual disease (MRD) after treatment of localized lung cancer could facilitate early intervention and personalization of adjuvant therapies. Here, we apply cancer personalized profiling by deep sequencing (CAPP-seq) circulating tumor DNA (ctDNA) analysis to 255 samples from 40 patients treated with curative intent for stage I-III lung cancer and 54 healthy adults. In 94% of evaluable patients experiencing recurrence, ctDNA was detectable in the first posttreatment blood sample, indicating reliable identification of MRD. Posttreatment ctDNA detection preceded radiographic progression in 72% of patients by a median of 5.2 months, and 53% of patients harbored ctDNA mutation profiles associated with favorable responses to tyrosine kinase inhibitors or immune checkpoint blockade. Collectively, these results indicate that ctDNA MRD in patients with lung cancer can be accurately detected using CAPP-seq and may allow personalized adjuvant treatment while disease burden is lowest.Significance: This study shows that ctDNA analysis can robustly identify posttreatment MRD in patients with localized lung cancer, identifying residual/recurrent disease earlier than standard-of-care radiologic imaging, and thus could facilitate personalized adjuvant treatment at early time points when disease burden is lowest. Cancer Discov; 7(12); 1394-403. ©2017 AACR.See related commentary by Comino-Mendez and Turner, p. 1368This article is highlighted in the In This Issue feature, p. 1355.

Noninvasive detection of clinically relevant copy number alterations in diffuse large B-cell lymphoma

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Background: Somatic copy number alterations (SCNAs) are common and clinically important genomic events in lymphomas. For example, MYC and BCL2 amplifications are associated with adverse outcomes (Quesada, ASH 2016), while PD-L1 ( CD274) amplifications are associated with improved response to checkpoint inhibitors (Ansell, NEJM 2015). However, noninvasive detection of these events from circulating tumor DNA (ctDNA) remains difficult. Using CAPP-Seq, a targeted high-throughput sequencing platform, we developed a method to profile both focal and broad SCNAs from plasma. Methods: We profiled plasmas from a cohort of 75 pretreatment diffuse large B-cell lymphoma patients and 48 healthy controls. Focal SCNAs were evaluated at ultra-high depths (~10,000x), allowing for detection of lesions at ~1% ctDNA fraction. Thresholds were tuned to allow a false positive rate of 1%, which was empirically validated in an independent healthy cohort (n = 15), yielding a panel-wide false discovery rate of ~2.3% (0% in our genes of interest). Sequencing reads outside the targeted regions were separately pooled and analyzed to evaluate arm and chromosome level SCNAs. Results: We detected SCNAs in clinically relevant genes at the frequencies reported in literature, including amplifications in MYC (8.0%), BCL2 (24.0%), and BCL6 (14.7%) and deletions in TP53 (13.3%) and CDKN2A (9.3%). Remarkably, 26.7% of the cohort demonstrated amplification of both PD-L1 and PD-L2 ( PDCD1LG2). Furthermore, we discovered amplifications in PD-L2, but not PD-L1, in 13.3% of our patients. Interestingly, PD-L1 amplifications were more common in patients with relapsed lymphoma than in those with treatment-naïve disease (43.5% vs 19.2%, p = 0.02). Most PD-L1 amplifications were focal (65%) while the remainder typically involved > 80% of Chr9p. Corresponding tissue profiling data is in progress and will also be presented. Conclusions: Noninvasive sampling of lymphoma ctDNA enables detection of both focal and broad SCNAs, including amplifications of MYC, BCL2, and PD-L1. The ability to noninvasively profile copy number altered regions allows for biopsy-free discovery of clinically significant structural alterations in lymphoma patients.

Analysis of circulating tumor DNA in localized lung cancer for detection of molecular residual disease and personalization of adjuvant strategies

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Background: Identifying localized non-small cell lung cancer (NSCLC) patients with residual disease following curative intent therapy is difficult due to normal tissue changes caused by surgery or radiation and an inability to detect microscopic disease. Analysis of circulating tumor DNA (ctDNA) might enable identification of molecular residual disease (MRD) and personalization of adjuvant treatment approaches but has not been explored in lung cancer. Methods: We applied CAPP-Seq, an ultra-sensitive next-generation sequencing based ctDNA quantitation method, to pre- and post-treatment blood samples from a cohort of 41 patients treated with chemoradiation, radiotherapy or surgery for stage I-III primary lung cancer. Detection of ctDNA at a single MRD time-point within 4 months of treatment completion was compared with surveillance by cross-sectional imaging. Furthermore, we developed an approach for identification of tumor mutation burden based on mutations detected in plasma, leveraging whole exome sequencing data from 1,177 NSCLCs sequenced by TCGA. Results: Median follow-up time was 35 months. Pre-treatment ctDNA was detected in 38 (93%) patients and 19 (46%) had detectable post-treatment ctDNA MRD. MRD+ patients displayed significantly inferior 3-year freedom from progression (0% vs. 92%; HR 38; P < 0.0001) and 3-year overall survival (8% vs. 75%; HR 12; P < 0.0001) than MRD- patients. Detection of ctDNA MRD had positive and negative predictive values for disease progression of 100% and 93%, respectively. Furthermore, we non-invasively identified activating EGFR mutations or high mutational burden (≥5 CAPP-Seq non-synonymous mutations, corresponding to > 200 non-synonymous mutations per exome or > 4 single nucleotide variants per megabase of exome) in 47% of patients with detectable ctDNA MRD, suggesting potentially favorable responses to TKIs and immune checkpoint inhibitors, respectively. Conclusions: Our results indicate that ctDNA analysis accurately detects MRD in localized lung cancer patients and could facilitate personalized adjuvant treatment at early time-points when disease burden is minimal.

Circulating tumor DNA analysis for outcome prediction in localized esophageal cancer

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Background: Blood-based biomarkers are not used in routine clinical practice in patients with esophageal carcinomas (ECs). Circulating tumor DNA (ctDNA) is an attractive biomarker that could be applied to ECs. We performed a study to explore pre- and post-treatment ctDNA analysis using the next generation sequencing-based CAPP-Seq method as a prognostic biomarker for localized EC. Methods: We prospectively enrolled 29 patients with localized EC treated with chemoradiotherapy (CRT) between June 2011 and October 2015. 12 (43%) patients were treated with CRT alone and 17 (57%) were treated with CRT followed by esophagectomy. Our cohort included patients with stage IB (1; 3.4%), II (7; 24.1%), and III (21; 72.4%) disease. Eight (27.6%) harbored squamous cell carcinoma (SCC) and 21 (72.4%) adenocarcinoma (AC). All patients received pre-treatment evaluation by thoracic CT, PET/CT, and esophagoduodenoscopy. ctDNA levels were quantitated in pre-treatment and post-treatment plasma samples using CAPP-Seq. Results: Median follow-up time was 21 months. We detected ctDNA pre-treatment in 72.4% of cases (N = 21) with a median concentration of 2.69 haploid genome equivalents per mL (hGE/mL; range 0.34-107.3). Pre-treatment ctDNA concentrations were strongly correlated with metabolic tumor volumes (MTV; R2= 0.74; p = 1.7e-07) and were significantly higher in SCC than AC patients (28.2 vs. 2.1 mean hGE/mL; p = 0.002). Overall survival (OS) at 2 years for pretreatment ctDNA+ vs. ctDNA- patients was 47% vs. 86% (HR = 6.0; 95% CI = 0.74-49.2; p < 0.05) and trended toward significance when accounting for stage, histology, and age (p = 0.09). A single post-treatment plasma sample was collected within 3 months of treatment and was available for 19 patients. Post-treatment ctDNA was detected in 3 (15.7%) patients with a median concentration of 11.5 hGE/mL (range 2.2–11.9). Post-treatment ctDNA detection was strongly predictive of poor event-free survival (p < 0.0001) and time to distant metastasis (p < 0.0001). Conclusions: Our data suggest that pre- and post-treatment ctDNA levels may be prognostic for patients with localized EC and could potentially guide risk-adapted adjuvant therapy approaches.

Capturing Genomic Evolution of Lung Cancers through Liquid Biopsy for Circulating Tumor DNA

Genetic sequencing of malignancies has become increasingly important to uncover therapeutic targets and capture the tumor's dynamic changes to drug sensitivity and resistance through genomic evolution. In lung cancers, the current standard of tissue biopsy at the time of diagnosis and progression is not always feasible or practical and may underestimate intratumoral heterogeneity. Technological advances in genetic sequencing have enabled the use of circulating tumor DNA (ctDNA) analysis to obtain information on both targetable mutations and capturing real-time Darwinian evolution of tumor clones and drug resistance mechanisms under selective therapeutic pressure. The ability to analyze ctDNA from plasma, CSF, or urine enables a comprehensive view of cancers as systemic diseases and captures intratumoral heterogeneity. Here, we describe these recent advances in the setting of lung cancers and advocate for further research and the incorporation of ctDNA analysis in clinical trials of targeted therapies. By capturing genomic evolution in a noninvasive manner, liquid biopsy for ctDNA analysis could accelerate therapeutic discovery and deliver the next leap forward in precision medicine for patients with lung cancers and other solid tumors.

Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA

Patients with diffuse large B cell lymphoma (DLBCL) exhibit marked diversity in tumor behavior and outcomes, yet the identification of poor-risk groups remains challenging. In addition, the biology underlying these differences is incompletely understood. We hypothesized that characterization of mutational heterogeneity and genomic evolution using circulating tumor DNA (ctDNA) profiling could reveal molecular determinants of adverse outcomes. To address this hypothesis, we applied cancer personalized profiling by deep sequencing (CAPP-Seq) analysis to tumor biopsies and cell-free DNA samples from 92 lymphoma patients and 24 healthy subjects. At diagnosis, the amount of ctDNA was found to strongly correlate with clinical indices and was independently predictive of patient outcomes. We demonstrate that ctDNA genotyping can classify transcriptionally defined tumor subtypes, including DLBCL cell of origin, directly from plasma. By simultaneously tracking multiple somatic mutations in ctDNA, our approach outperformed immunoglobulin sequencing and radiographic imaging for the detection of minimal residual disease and facilitated noninvasive identification of emergent resistance mutations to targeted therapies. In addition, we identified distinct patterns of clonal evolution distinguishing indolent follicular lymphomas from those that transformed into DLBCL, allowing for potential noninvasive prediction of histological transformation. Collectively, our results demonstrate that ctDNA analysis reveals biological factors that underlie lymphoma clinical outcomes and could facilitate individualized therapy.

Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients

Circulating tumour DNA (ctDNA) analysis facilitates studies of tumour heterogeneity. Here we employ CAPP-Seq ctDNA analysis to study resistance mechanisms in 43 non-small cell lung cancer (NSCLC) patients treated with the third-generation epidermal growth factor receptor (EGFR) inhibitor rociletinib. We observe multiple resistance mechanisms in 46% of patients after treatment with first-line inhibitors, indicating frequent intra-patient heterogeneity. Rociletinib resistance recurrently involves MET, EGFR, PIK3CA, ERRB2, KRAS and RB1. We describe a novel EGFR L798I mutation and find that EGFR C797S, which arises in ∼33% of patients after osimertinib treatment, occurs in <3% after rociletinib. Increased MET copy number is the most frequent rociletinib resistance mechanism in this cohort and patients with multiple pre-existing mechanisms (T790M and MET) experience inferior responses. Similarly, rociletinib-resistant xenografts develop MET amplification that can be overcome with the MET inhibitor crizotinib. These results underscore the importance of tumour heterogeneity in NSCLC and the utility of ctDNA-based resistance mechanism assessment.

Role of vascular endothelial growth factor signaling in Schistosoma-induced experimental pulmonary hypertension

There is significant evidence that Th2 (T helper 2)-mediated inflammation supports the pathogenesis of both human and experimental animal models of pulmonary hypertension (PH). A key immune regulator is vascular endothelial growth factor (VEGF), which is produced by Th2 inflammation and can itself contribute to Th2 pulmonary responses. In this study, we interrogated the role of VEGF signaling in a murine model of schistosomiasis-induced PH with a phenotype of significant intrapulmonary Th2 inflammation, vascular remodeling, and elevated right ventricular pressures. We found that VEGF receptor blockade partially suppressed the levels of the Th2 inflammatory cytokines interleukin (IL)-4 and IL-13 in both the lung and the liver after Schistosoma mansoni exposure and suppressed pulmonary vascular remodeling. These findings suggest that VEGF positively contributes to schistosomiasis-induced vascular inflammation and remodeling, and they also provide evidence for a VEGF-dependent signaling pathway necessary for pulmonary vascular remodeling and inflammation in this model.