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PURPOSEAlthough the majority of patients with metastatic non–small-cell lung cancer (mNSCLC) lacking a detectable targetable mutation will receive pembrolizumab-based therapy in the frontline setting, predicting which patients will experience a durable clinical benefit (DCB) remains challenging.MATERIALS AND METHODSPatients with mNSCLC receiving pembrolizumab monotherapy or in combination with chemotherapy underwent a 74-gene next-generation sequencing panel on blood samples obtained at baseline and at 9 weeks. The change in circulating tumor DNA levels on-therapy (molecular response) was quantified using a ratio calculation with response defined by a > 50% decrease in mean variant allele fraction. Patient response was assessed using RECIST 1.1; DCB was defined as complete or partial response or stable disease that lasted > 6 months. Progression-free survival and overall survival were recorded.RESULTSAmong 67 patients, 51 (76.1%) had > 1 variant detected at a variant allele fraction > 0.3% and thus were eligible for calculation of molecular response from paired baseline and 9-week samples. Molecular response values were significantly lower in patients with an objective radiologic response (log mean 1.25% v 27.7%, P < .001). Patients achieving a DCB had significantly lower molecular response values compared to patients with no durable benefit (log mean 3.5% v 49.4%, P < .001). Molecular responders had significantly longer progression-free survival (hazard ratio, 0.25; 95% CI, 0.13 to 0.50) and overall survival (hazard ratio, 0.27; 95% CI, 0.12 to 0.64) compared with molecular nonresponders.CONCLUSIONMolecular response assessment using circulating tumor DNA may serve as a noninvasive, on-therapy predictor of response to pembrolizumab-based therapy in addition to standard of care imaging in mNSCLC. This strategy requires validation in independent prospective studies.

Purpose: Tumor mutational burden (TMB) has been shown to be predictive of survival benefit in patients with non–small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. Measuring TMB in the blood (bTMB) using circulating cell-free tumor DNA (ctDNA) offers practical advantages compared with TMB measurement in tissue (tTMB); however, there is a need for validated assays and identification of optimal cutoffs. We describe the analytic validation of a new bTMB algorithm and its clinical utility using data from the phase III MYSTIC trial. Patients and Methods: The dataset used for the clinical validation was from MYSTIC, which evaluated first-line durvalumab (anti–PD-L1 antibody) ± tremelimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody) or chemotherapy for metastatic NSCLC. bTMB and tTMB were evaluated using the GuardantOMNI and FoundationOne CDx assays, respectively. A Cox proportional hazards model and minimal P value cross-validation approach were used to identify the optimal bTMB cutoff. Results: In MYSTIC, somatic mutations could be detected in ctDNA extracted from plasma samples in a majority of patients, allowing subsequent calculation of bTMB. The success rate for obtaining valid TMB scores was higher for bTMB (809/1,001; 81%) than for tTMB (460/735; 63%). Minimal P value cross-validation analysis confirmed the selection of bTMB ≥20 mutations per megabase (mut/Mb) as the optimal cutoff for clinical benefit with durvalumab + tremelimumab. Conclusions: Our study demonstrates the feasibility, accuracy, and reproducibility of the GuardantOMNI ctDNA platform for quantifying bTMB from plasma samples. Using the new bTMB algorithm and an optimal bTMB cutoff of ≥20 mut/Mb, high bTMB was predictive of clinical benefit with durvalumab + tremelimumab versus chemotherapy.

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BackgroundTumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, demonstrates predictive biomarker potential for the identification of patients with cancer most likely to respond to immune checkpoint inhibitors. TMB is optimally calculated by whole exome sequencing (WES), but next-generation sequencing targeted panels provide TMB estimates in a time-effective and cost-effective manner. However, differences in panel size and gene coverage, in addition to the underlying bioinformatics pipelines, are known drivers of variability in TMB estimates across laboratories. By directly comparing panel-based TMB estimates from participating laboratories, this study aims to characterize the theoretical variability of panel-based TMB estimates, and provides guidelines on TMB reporting, analytic validation requirements and reference standard alignment in order to maintain consistency of TMB estimation across platforms.MethodsEleven laboratories used WES data from The Cancer Genome Atlas Multi-Center Mutation calling in Multiple Cancers (MC3) samples and calculated TMB from the subset of the exome restricted to the genes covered by their targeted panel using their own bioinformatics pipeline (panel TMB). A reference TMB value was calculated from the entire exome using a uniform bioinformatics pipeline all members agreed on (WES TMB). Linear regression analyses were performed to investigate the relationship between WES and panel TMB for all 32 cancer types combined and separately. Variability in panel TMB values at various WES TMB values was also quantified using 95% prediction limits.ResultsStudy results demonstrated that variability within and between panel TMB values increases as the WES TMB values increase. For each panel, prediction limits based on linear regression analyses that modeled panel TMB as a function of WES TMB were calculated and found to approximately capture the intended 95% of observed panel TMB values. Certain cancer types, such as uterine, bladder and colon cancers exhibited greater variability in panel TMB values, compared with lung and head and neck cancers.ConclusionsIncreasing uptake of TMB as a predictive biomarker in the clinic creates an urgent need to bring stakeholders together to agree on the harmonization of key aspects of panel-based TMB estimation, such as the standardization of TMB reporting, standardization of analytical validation studies and the alignment of panel-based TMB values with a reference standard. These harmonization efforts should improve consistency and reliability of panel TMB estimates and aid in clinical decision-making.

When People Die: Stories from Young People is a comic that tells numerous stories about death and resilience from a group of young people. The comic helps readers gain different and better perspectives on grief and what grieving means for young people. These stories and scenarios have been written by a group of young people selected from Children’s Hospices Across Scotland (Robin House), HMYOI Polmont, and Richmond’s Hope, and put together by the team at the Dundee Comics Creative Space. This comic will help people such as school teachers, guidance counsellors and anyone who reads it to learn more about how it feels to be in the position of a grieving young person, and how to act in situations that may come up with a grieving child.

Purpose: The role of plasma-based tumor mutation burden (pTMB) in predicting response to pembrolizumab-based first-line standard-of-care therapy for metastatic non–small cell lung cancer (mNSCLC) has not been explored. Experimental Design: A 500-gene next-generation sequencing panel was used to assess pTMB. Sixty-six patients with newly diagnosed mNSCLC starting first-line pembrolizumab-based therapy, either alone or in combination with chemotherapy, were enrolled (Clinicaltrial.gov identifier: NCT03047616). Response was assessed using RECIST 1.1. Associations were made for patient characteristics, 6-month durable clinical benefit (DCB), progression-free survival (PFS), and overall survival (OS). Results: Of 66 patients, 52 (78.8%) were pTMB-evaluable. Median pTMB was 16.8 mutations per megabase (mut/Mb; range, 1.9–52.5) and was significantly higher for patients achieving DCB compared with no durable benefit (21.3 mut/Mb vs. 12.4 mut/Mb, P = 0.003). For patients with pTMB ≥ 16 mut/Mb, median PFS was 14.1 versus 4.7 months for patients with pTMB < 16 mut/Mb [HR, 0.30 (0.16–0.60); P < 0.001]. Median OS for patients with pTMB ≥ 16 was not reached versus 8.8 months for patients with pTMB < 16 mut/Mb [HR, 0.48 (0.22–1.03); P = 0.061]. Mutations in ERBB2 exon 20, STK11, KEAP1, or PTEN were more common in patients with no DCB. A combination of pTMB ≥ 16 and absence of negative predictor mutations was associated with PFS [HR, 0.24 (0.11–0.49); P < 0.001] and OS [HR, 0.31 (0.13–0.74); P = 0.009]. Conclusions: pTMB ≥ 16 mut/Mb is associated with improved PFS after first-line standard-of-care pembrolizumab-based therapy in mNSCLC. STK11/KEAP1/PTEN and ERBB2 mutations may help identify pTMB-high patients unlikely to respond. These results should be validated in larger prospective studies.

Background: Molecular response (MR) estimated as a change in circulating tumor (ctDNA) load between an early on treatment sample (usually 2-9 weeks post treatment start) and pre-treatment baseline has been shown to predict patient response and outcomes across solid tumors and therapy types in many retrospective studies. There is no consensus, however, regarding the best method for assessing molecular response. Therefore, we aimed to assess several molecular response calculations and determine the optimal method for predicting outcomes in individual advanced cancer patients. Method: Aggregate results of > 4,000 patient sample pairs (3-10 weeks apart), > 1000 patient sample technical replicates, > 100 contrived sample dilutions, and in silico simulations were analyzed with Guardant360TM or GuardantOMNITM. Baseline and on-treatment paired patient samples were collected from advanced cancer patients with over 12 tumor types, including lung, colon, and breast. MR calculations included variant allele fractions (VAFs) of somatic SNVs, indels and fusions. Methods including Ratio treatment/baseline (R) of Maximum VAF (maxVAF), Ratio of Mean VAF (mVAF), and Mean of VAF Ratios were compared, with consideration of VAF precision. Analytical accuracy, reproducibility and limit of detection (LoD) were assessed. Results: Comparison of methods for calculating net change in ctDNA load on > 1500 sample pairs showed high correlation (ρ ranged from 0.93 to 0.98) and categorical agreement split by the median (93%). Therefore selecting an optimal method based on outcome prediction would require prohibitively large patient cohorts. Analytical evaluation and in silico simulations can predict the behavior of each method. Simulations of changes in tumor fraction of real pre-treatment samples found that RmVAF or RmaxVAF are more accurate than mVAFR, which can be skewed by low VAF ratios. Almost 25% of sample pairs have a tumor driver or resistance mutation that is not the maxVAF, suggesting tumor dynamics are better captured by mVAF than maxVAF. Newly-detected on-treatment variants can be an important signal of rising ctDNA levels, impacting MR in approximately 2% of sample pairs. Importantly, MR accuracy for all methods decreases as maxVAF approaches or falls below the variant LoD, due to both stochastic detection and higher CV of variants at low VAF. Thus the assay variant LoD is a key determinant of the fraction of patients who can receive MR evaluation. Technical replicates identified the variant criteria at which a 50% change in tumor fraction differs significantly from technical variation, and could define analytical reporting limits. Conclusions: Comparison of MR methods in a large set of patient samples and simulations supports RmVAF with inclusion of newly-detected mutations. Clinical validation of these methods will support patient-specific MR prediction of outcomes. Citation Format: Allysia J. Mak, Katie J. Quinn, Carin Espenschied, Kyle Chang, Han-Yu Chuang, Elena Helman, Darya Chudova, Justin Odegaard, Becky Nagy, AmirAli Talasaz. Comparison of molecular response calculations for prediction of patient outcome [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 401.

5038 Background: Accurate analysis of the genomic alteration landscape within tissue- and plasma-derived tumor DNA using next-generation sequencing (NGS) may provide insights into specific patient populations that benefit from different therapies. The interchangeable use of tissue- and plasma-based assessments may benefit patients when tissue availability is limited, a common occurrence in individuals with mCRPC. To understand the potential sources of technical and biological variability in this setting, we performed comprehensive comparative analyses across 3 NGS platforms, using samples from patients enrolled in CheckMate 9KD, a phase 2 study of nivolumab combined with docetaxel, rucaparib, or enzalutamide for patients with confirmed mCRPC (NCT03338790). Methods: We performed retrospective integrated analyses of sequence and structural alterations identified through comprehensive genomic profiling (CGP) of DNA obtained from formalin-fixed, paraffin-embedded tissue specimens and cell-free DNA obtained from plasma. Tissue-based analysis was performed using the FoundationOne assay (F1, 395 genes), while the FoundationACT (FACT, 70 genes) and GuardantOMNI (OMNI, 500 genes) assays were used for plasma-based analysis. Analysis was performed on samples from 103 patients for which datasets from all 3 assays were available. Inter-platform analysis considered variants with ≥ 0.50% variant allele fraction and common to the shared pairwise targeted regions, while excluding synonymous variants. Results: Through broad profiling of DNA obtained from tissue and plasma, we uncovered previously identified recurrent alteration of AR, TP53, PTEN, and TMPRSS2 fusion with ETS genes. Additionally, we found that 42% (F1), 45% (FACT), and 34% (OMNI) of patients harbored a combination of germline and somatic mutations in homologous recombination repair pathway genes. Across all samples, median tumor mutational burden was 3.5 mutations per megabase (mut/Mb) by F1 and 8.6 mut/Mb by OMNI. Inter-platform variant analyses demonstrated concordance of 52% for F1 vs FACT, 40% for F1 vs OMNI, and 75% for FACT vs OMNI. Conclusions: Overall, these data demonstrate the value of integrated tissue and liquid biopsy profiling in mCRPC. Both technical and biological sources of variation, including panel size, mutation detection algorithms, variant annotation and reporting, analytical performance, circulating tumor DNA levels, and tumor heterogeneity, may be captured differently by tissue- and plasma-based techniques, accounting for the discordance in reported results. Clinical trial information: NCT03338790.

61 Background: Pembrolizumab was recently granted tissue agnostic FDA accelerated approval for metastatic cancers with TMB≥10 mut/Mb. However, limited data supports immunotherapy in microsatellite stable (MSS) mCRC with TMB≥10 mut/Mb. We assessed tissue TMB and contrasted it to plasma derived TMB in the CO.26 trial. Methods: CO.26 was a phase 2 trial (2-sided ⍺ = 0.1 and 80% power) that randomized 180 patients (pts) 2:1 to D+T or BSC in refractory mCRC. Pre-treatment plasma was sequenced with the GuardantOMNI assay and archival tissue underwent exome sequencing with TMB assessed per the TMB harmonization project. MSI-H cases were excluded. For plasma TMB, we used a previously published cut point (≥28). Results: Overall survival (OS) but not progression free survival (PFS) was improved with D+T in the entire population. Of 180 pts, 163 were evaluable for plasma and 110 for tissue TMB. Median time between archival tissue and plasma collection was 3.1 yrs (IQR 1.9-5.1). Median tissue TMB was 6.6 muts/Mb (IQR 4.1-12.0), while median plasma TMB was 16.3 muts/Mb (IQR 9.4-25.9). Tissue and plasma TMB (r = -0.039, P = 0.69) were not correlated. Tissue TMB≥10 was not prognostic in the BSC arm (HR 1.01, 90%CI 0.52-1.92, P = 0.99) and OS was not improved in pts with tissue TMB≥10 (32/110 pts) following D+T vs BSC. A test of interaction suggested this threshold was not predictive (P = 0.85). Using a minimum P-value approach, no threshold supported high tissue TMB as predictive in MSS mCRC. In fact, the optimal cut point suggested low tissue TMB ( < 4.1 muts/Mb) had the greatest benefit from D+T (P-interaction = 0.048) and pts with TMB ≥4.1 mut/Mb (HR 0.50, 90%CI 0.26-0.96, P = 0.083) trended to better OS in the BSC arm. In contrast, 35/163 pts (21%) were identified in a high plasma TMB group associated with worse OS (HR 2.56, 90%CI 1.45-4.54, P = 0.007) in the BSC arm but improved OS following D+T compared to BSC with P-interaction = 0.082. Only 1 response was noted following D+T in a pt with tissue TMB = 16 mut/Mb and plasma TMB = 13 mut/Mb. Conclusions: Archival tissue TMB≥10 mut/Mb does not appear predictive of D+T benefit in MSS mCRC. Plasma derived TMB may better reflect evolutionary changes following intervening therapy than archival tissue. Clinical trial information: NCT02870920. [Table: see text]

3552 Background: MSI-H cancers are responsive to immune checkpoint blockade (ICB), but nearly half of all patients experience primary or early treatment resistance. Activation of the WNT/B-Catenin pathway can lead to immune exclusion and may drive resistance to ICB. Methods: 12 patients had stage III (N = 1) or IV (N = 11) MSI-H GI tract (small bowl, colon, or rectal) cancers. Blood samples were obtained after (N = 5) or during (N = 5) ICB. 2 patients did not receive ICB. Blood samples from 8 patients with microsatellite stable (MSS) metastatic colorectal cancer were included as controls. The Guardant Health (Redwood City, CA) Omni 2.0 mb panel was used to analyze cfDNA. We analyzed MSI-H status, TMB, and mutations within the WNT/B-Catenin pathway, including APC, RNF43 and CTNNB1. Results: Of 12 patients with MSI-H GI cancers, 1 sample failed enrichment due to hemolysis. MSI-H was not detected in 2 patients with a history of MSI-H in tissue; however these patients had a complete response to ICB at the time of blood collection. The Omni panel identified MSI-H in the remaining 9 patients with MSI-H disease in tissue. Among 8 control patients with MSS disease in tissue, MSI-H was not detected. Median TMB (mutations/Mb) was greater for MSI-H specimens (109; range 30-807) than for MSS specimens (13; range 6-24). All 8 patients with MSS GI cancers were identified to have APC mutations, and none were found to have CTNNB1 or RNF43 mutations. Of 9 evaluable MSI-H GI cancers, 2 had APC mutations alone. The remaining 7 carried RNF43 mutations (G659fs). All patients with RNF43 mutations were found to have disease progression while on ICB. Among these 7 patients with RNF43 mutations, 6 had additional mutations in APC or CTNNB1. Conclusions: Blood based genomic profiling can identify MSI-H cancers. Patients with MSI-H cancers resistant to ICB in this cohort have mutations in RNF43 as well as additional mutations in APC or CTNNB1, suggesting that co-activation of the WNT/B-Catenin pathway may be biologically important. Further study of the role of WNT/B-Catenin pathway activation in ICB resistance will be pursued using tumor tissue from this cohort.

3040 Background: Circulating tumor DNA next generation sequencing (ctDNA NGS) is increasingly being used to detect mutations (MT) in patients (pts) with metastatic (m) NSCLC. Limited data exist on the correlation of baseline ctDNA NGS profile and serial ctDNA NGS monitoring to response to immunotherapy. Methods: We conducted a prospective study in pts with mNSCLC receiving pembrolizumab monotherapy. Plasma was collected at weeks 0 (T0), 9 (T1), and 18 (T2). ctDNA NGS was performed using a 73 gene panel. Number of MTs and variant allelic fraction (VAF) were determined at baseline, and serially; change in mean VAF was calculated between T1-T0, and T2-T0. Response rate (RR) was assessed using RECIST 1.1. Correlations were made for pt characteristics, RR, progression free survival (PFS), and overall survival (OS). Results: We analyzed 95 samples from 33 pts, 21 female, median age 69 (range 51-89 years), smokers (n = 29), adenocarcinoma (n = 23), 25 pts enrolled at initial diagnosis, majority had high PD-L1 ≥50% (n = 29, 88%). At T0, 32 pts had detectable MT, median number of MTs was 4 (range 0-21), (non-synonymous MT = 3), most common MT was TP53 (n = 21). Confirmed PR was 27% (n = 9), clinical benefit rate (SD+PR) was 64% (n = 21), and 2 pts were not evaluable for response. Smokers were more likely to have higher number of MT at T0 (4 vs. 1 p = 0.003); there was no correlation with smoking and overall RR (p = 0.17). RR was not related to number of MT at T0, p = 0.37. A decrease in ctDNA VAF was seen in 6/9 pts with PR (mean VAF change range -0.11 to -0.001); 2/5 pts with PD showed an increase in mean VAF while 3 showed decrease. At median follow up of 9.26 months (mos), median PFS and OS were 7.4 and 10.5 mos, respectively. Median PFS was longer for pts with a decrease in ctDNA VAF at both T1-T0 (8.9 vs. 5 mos, p = 0.02) and T2-T0 (9.1 vs. 5.5 mos, p = 0.006). OS and additional biomarker analyses including correlation of response to a 2mb ctDNA plasma-based NGS panel will be reported at the meeting. Conclusions: Our results demonstrate that it is feasible to serially monitor plasma NGS, decline in mean ctDNA VAF correlates with radiographic response and PFS on immunotherapy with pembrolizumab.