Oxnard, Geoffrey R.

PURPOSE Poly ADP-ribose polymerase inhibitors (PARPi) are approved for patients with human epidermal growth factor receptor 2–negative metastatic breast cancer (mBC) and germline pathogenic/likely pathogenic variant (hereafter mutation) in the BRCA1/ 2 genes (g BRCA); however, clinical benefit has also been demonstrated in mBC with somatic BRCA1/ 2 mutations (s BRCA) or germline PALB2 mutations (g PALB2). This study aims to describe the genomic landscape of homologous recombination repair (HRR) gene alterations in mBC and assess PARPi treatment outcomes for patients with g BRCA compared with other HRR genes and by status of a novel homologous recombination deficiency signature (HRDsig). METHODS A real-world (RW) clinico-genomic database (CGDB) of comprehensive genomic profiling (CGP) linked to deidentified, electronic health record–derived clinical data was used. CGP was analyzed for HRR genes and HRDsig. The CGDB enabled cohort characterization and outcomes analyses of 177 patients exposed to PARPi. RW progression-free survival (rwPFS) and RW overall survival (rwOS) were compared. RESULTS Of 28,920 patients with mBC, g BRCA was detected in 3.4%, whereas the population with any BRCA alteration or g PALB2 increased to 9.5%. HRDsig+ represented 21% of patients with mBC. BRCA and g PALB2 had higher levels of biallelic loss and HRDsig+ than other HRR alterations. Outcomes on PARPi were assessed for 177 patients, and g BRCA and s BRCA/ gPALB2 cohorts were similar: g BRCA versus s BRCA/g PALB2 rwPFS was 6.3 versus 5.4 months (hazard ratio [HR], 1.37 [0.77-2.43]); rwOS was 16.2 versus 21.2 months (HR, 1.45 [0.74-2.86]). Additionally, patients with HRDsig+ versus HRDsig– had longer rwPFS (6.3 v 2.8 months; HR, 0.62 [0.42-0.92]) and numerically longer rwOS (17.8 v 13.0 months; HR, 0.72 [0.46-1.14]). CONCLUSION Patients with s BRCA and g PALB2 derive similar benefit from PARPi as those with g BRCA alterations. In combination, HRDsig+, s BRCA, and g PALB2 represent an additional 19% of mBC that can potentially benefit from PARPi. Randomized trials exploring a more inclusive biomarker such as HRDsig are warranted.

PURPOSE Pancreatic ductal adenocarcinoma (PDAC) is largely considered a nonimmunogenic malignancy; however, approximately 1%, of patients may have tumors with deficient mismatch repair, high microsatellite instability, or high tumor mutational burden (TMB ≥10 mutations/Mb), which may be predictive of response to immune checkpoint inhibitor (ICI) therapy. We sought to analyze outcomes of patients with high-TMB and pathogenic genomic alterations observed in this population. METHODS This study included patients with PDAC who underwent comprehensive genomic profiling (CGP) at Foundation Medicine (Cambridge, MA). Clinical data were obtained from a US-wide real-world clinicogenomic pancreatic database. We report genomic alterations in those with high and low TMB, and compare outcomes on the basis of receipt of single-agent ICI or therapy regimens not containing ICI. RESULTS We evaluated 21,932 patients with PDAC who had tissue CGP data available, including 21,639 (98.7%) with low-TMB and 293 (1.3%) with high-TMB. Among patients with high-TMB, a greater number of alterations were observed in BRCA2, BRAF, PALB2, and genes of the mismatch repair pathway, whereas fewer alterations were observed in KRAS. Among patients who received an ICI (n = 51), those with high-TMB had more favorable median overall survival when compared with the low-TMB subset (25.7 v 5.2 months; hazard ratio, 0.32; 95% CI, 0.11 to 0.91; P = .034). CONCLUSION Longer survival was observed in patients with high-TMB receiving ICI compared with those with low-TMB. This supports the role of high-TMB as a predictive biomarker for efficacy of ICI therapy in PDAC. Additionally, we report higher rates of BRAF and BRCA2 mutations and lower rates of KRAS mutation among patients with PDAC and high-TMB, which to our knowledge, is a novel finding.

4146 Background: Currently, ICI therapy is recommended for patients with metastatic PDAC whose tumors exhibit dMMR, MSI-H, or high TMB (≥10 mutations/Mb). However, due to the low prevalence of high TMB in PDAC (~1%), few studies have evaluated the role of ICI therapy in this subpopulation. This study aimed to compare GA between PDAC patients with high TMB and low TMB ( < 10 mutations/Mb) and to evaluate the effectiveness of ICIs in real-world PDAC patients by TMB status. Methods: This study included PDAC patients who underwent genomic testing using Foundation Medicine tissue comprehensive genomic profiling (CGP) assays. GA were compared between tissue specimens with high and low TMB by chi-squared, adjusted for multiple comparisons. Patient clinical data was obtained by the US-wide de-identified Flatiron Health and Foundation Medicine real-world clinicogenomic pancreatic database (CGDB), originated from ~280 US cancer clinics between 01/2011 and 09/2022. Real-world overall survival (OS) and time to treatment discontinuation (TTD) were compared between patients receiving an ICI (high TMB versus low TMB) and between patients with high TMB (ICI versus other therapies) by Cox models. Results: We included 21,932 patients with PDAC with tissue CGP data available; 98.7% with low TMB and 1.3% with high TMB. Among actionable alterations, patients with high TMB had higher prevalence of mutations in BRCA2 (p < 0.0001), BRAF (p < 0.0001), PALB2 (p < 0.0001), and genes of the mismatch repair pathway ( MSH2, MSH6, MLH1, and PMS2, p < 0.0001), but lower prevalence of KRAS mutations (p < 0.0001). The most common KRAS mutation in both groups of patients was G12D. In CGDB, 51 patients received an ICI (10 with high TMB and 41 with low TMB) and 17 patients with high TMB received other therapies. Among patients receiving an ICI, those with high TMB had more favorable median OS compared to those with low TMB (25.7 versus 5.2 months, hazard ratio (HR) 0.27, 95% confidence interval (CI) 0.09 - 0.76, p = 0.01) and median TTD (20.7 versus 3.0 months, HR 0.33, 95% CI 0.13 - 0.82, p = 0.02). Among patients with high TMB, those receiving an ICI had more favorable OS compared to those receiving other therapies (25.7 versus 6.6 months, HR 0.31, 95% CI 0.10-0.96, p = 0.043), nominally favoring ICI use in this small cohort (n = 10 versus 17). Conclusions: There is no randomized clinical trial evaluating ICI versus other therapies in PDAC. To our knowledge, this is the largest cohort to date comparing ICI effectiveness in PDAC. We observed more favorable OS among PDAC patients with high TMB receiving ICI versus those with low TMB who received an ICI and more favorable to those with high TMB receiving other therapies. This study supports the FDA-approved use of ICIs in patients with PDAC and high TMB and demonstrates the importance of TMB assessment for patients with PDAC.

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer “signal”) and a cancer signal origin (i.e., tissue of origin). Participants with a “signal detected” will undergo further diagnostic evaluation per guiding physician discretion; those with a “signal not detected” will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a “signal detected” result is expected to be 106 (87–128). Subsequent diagnostic evaluation is expected to detect 52 (39–67) cancers. The positive predictive value of the MCED test is expected to be 49% (39–58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

Abstract Purpose: We recently reported the development of a cell-free DNA (cfDNA) targeted methylation (TM)-based sequencing approach for a multi-cancer early detection (MCED) test that includes cancer signal origin prediction. Here, we evaluated the prognostic significance of cancer detection by the MCED test using longitudinal follow-up data. Experimental Design: As part of a Circulating Cell-free Genome Atlas (CCGA) substudy, plasma cfDNA samples were sequenced using a TM approach, and machine learning classifiers predicted cancer status and cancer signal origin. Overall survival (OS) of cancer participants in the first 3 years of follow-up was evaluated in relation to cancer detection by the MCED test and clinical characteristics. Results: Cancers not detected by the MCED test had significantly better OS (P &lt; 0.0001) than cancers detected, even after accounting for other covariates, including clinical stage and method of clinical diagnosis (i.e., standard-of-care screening or clinical presentation with signs/symptoms). Additionally, cancers not detected by the MCED test had better OS than was expected when data were adjusted for age, stage, and cancer type from the Surveillance, Epidemiology, and End Results (SEER) program. In cancers with current screening options, the MCED test also differentiated more aggressive cancers from less aggressive cancers (P &lt; 0.0001). Conclusions: Cancer detection by the MCED test was prognostic beyond clinical stage and method of diagnosis. Cancers not detected by the MCED test had better prognosis than cancers detected and SEER-based expected survival. Cancer detection and prognosis may be linked by the underlying biological factor of tumor fraction in cfDNA.

Abstract Background: Early detection decreases patient mortality for many cancers, but prevailing paradigms focus on distinct screening modalities for each cancer type. A minimally invasive test that detects multiple tumor types could substantially reduce cancer mortality and improve screening efficiency. In preliminary studies, we showed that a targeted methylation cell-free DNA (cfDNA) test can detect cancer and determine the tissue of origin (TOO) of abnormally methylated cfDNA with high sensitivity and specificity; however, blood was collected at the time of diagnosis and results were not disclosed to inform care. The current study includes disclosure of results to the study investigator to understand the care pathways prompted by a “signal detected” test result, and the benefits, harms, and burdens associated with a multi-cancer detection test. Methods: PATHFINDER (NCT04241796) is a prospective, longitudinal, multi-center clinical study. Approximately 6,200 participants with varying levels of cancer risk will be enrolled at 5-10 clinical sites in the United States. Participants must be ≥50 years of age. If participants have at least 1 of the following–a smoking history of ≥100 cigarettes, a genetic cancer predisposition, or a history of invasive or hematologic malignancy with definitive treatment completed &gt;3 years prior to enrollment–they are eligible for the Elevated Risk Cohort (n = 4340); otherwise, they are eligible for the Non-Elevated Risk Cohort (n = 1860). Individuals being evaluated for cancer or who have a history of invasive or hematologic malignancy within 3 years of enrollment will be excluded. Blood drawn at study sites will be analyzed at GRAIL, Inc. (Menlo Park, CA). Participants and study investigators will be informed of the test results. Participants with “signal not detected” results will be advised to continue routine clinical care, including age- and risk-based cancer screening. Those with “signal detected” test results will be informed of the predicted origin and undergo diagnostic evaluation. The primary study objective is to determine the extent of diagnostic testing required to achieve diagnostic resolution following a “signal detected” test result, defined as the date when the study investigator determines to end diagnostic evaluation triggered by a “signal detected” test result. Health resource utilization, the number and types of tests and time required to reach this point, is the primary endpoint. Secondary objectives include evaluation of test performance (specificity, positive predictive value, and TOO accuracy), and assessment of participants' perceptions about the test and changes in anxiety and health-related quality of life. Exploratory aims include assessment of the number and types of invasive cancer diagnoses among participants with “signal not detected” test results and changes in attitude toward adherence to guideline-recommended screening. Citation Format: Lincoln Nadauld, Charles H. McDonnell III, Minetta C. Liu, Eric Klein, Tomasz M. Beer, Deborah Schrag, Andrew G. Hudnut, Richard Whittington, Bruce Taylor, Joanna Tierney, Catherine Marinac, Jafi Lipson, Margarita Lopatin, Karen C. Chung, Eric Fung, Anne-Renee Hartman, Geoffrey R. Oxnard. The PATHFINDER Study: Assessment of the implementation of an investigational multi-cancer early detection test into clinical practice [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 CT291.

Abstract Background: The Circulating Cell-free Genome Atlas study (NCT02889978) is a multi-center, case-control, observational study with longitudinal follow-up (n=15,254; 56% cancer, 44% non-cancer) to support development of a cell-free DNA (cfDNA) multi-cancer early detection test. Previously, we reported that a targeted methylation assay detected and localized &gt;20 cancer types at &gt;99% specificity in individuals with cancer.1,2 Here, we report prediction of cancer (presence/absence) and tissue of origin (TOO) in individuals enrolled with clinical suspicion of cancer but without pathologic diagnosis or treatment at time of enrollment. Methods: Plasma cfDNA from blood samples collected prior to clinical diagnosis was subjected to targeted methylation sequencing. Samples were divided into a training set and an independent validation set to train and validate a machine learning classifier to assess cancer and predict TOO. Performance was assessed in a subset of participants enrolled with suspicion of cancer; subsequently, cancer was confirmed by evaluating a pathologic specimen. Results: Participants being evaluated for suspicion of cancer were classified as confirmed cancer (&gt;20 cancer types; n=164 in training, n=75 in validation) or confirmed non-cancer (n=49 training, n=15 validation). In the confirmed non-cancer group, all training and validation samples were correctly predicted as non-cancer (100% specificity). In the confirmed cancer group, cancer detection across all stages was 40.2% (66/164; 95% confidence interval [CI], 32.7-48.2%) in training and 46.7% (35/75; 95% CI, 35.1-58.6%) in validation. Excluding stage I renal cancers (where detection/tumor fraction is low in plasma and which comprised 20% of participants in this subset) detection across stages was 50.4% (66/131; 95% CI, 41.5-59.2%) and 59.3% (35/59; 95% CI, 45.7-71.9%), respectively. In stages II and above, detection was 70.7% (58/82; 95% CI, 59.6-80.3%) and 78.9% (30/38; 95% CI, 62.7-90.4%), respectively. For detected cancers, TOO was predicted in 93.9% (62/66) samples in training and 100% (35/35) in validation. Of those with a TOO call, accuracy was 85.5% (53/62; 95% CI, 74.2-93.1%) and 97.1% (34/35; 95% CI, 85.1-99.9%), respectively. Conclusion: A cfDNA multi-cancer detection test has shown the potential to predict cancer and TOO in individuals with suspicion of cancer ahead of histologic diagnosis with performance comparable to those with confirmed cancer at the time of blood collection. This was achieved with high specificity and TOO accuracy. The high specificity suggests that the false positive rate could be comparable in populations with average versus higher risk (suspicion) of cancer. These findings suggest that a cfDNA multi-cancer detection test could accelerate the diagnostic resolution of suspicion of cancer. References: 1. Oxnard GR, et al. ASCO Breakthrough Meeting 2019; Abstract 44. 2. Oxnard GR, et al. ESMO Annual Meeting 2019; Abstract 5639. Citation Format: David D. Thiel, Xiaoji Chen, Kathryn N. Kurtzman, Jessica Yecies, Tony Wu, Quan Zhang, Hai Liu, Nan Zhang, Eric T. Fung, Michael V. Seiden, Minetta C. Liu, Geoffrey R. Oxnard, Earl Hubbell, Alexander M. Aravanis, Anne-Renee Hartman, Eric A. Klein. Prediction of cancer and tissue of origin in individuals with suspicion of cancer using a cell-free DNA multi-cancer early detection test [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 CT021.

Abstract Background: Earlier cancer detection could identify tumors when they are more treatable and thus may improve clinical outcomes. A blood-based multicancer early detection test using circulating tumor cell-free DNA (cfDNA) offers the potential to address this unmet need. Our previous discovery work identified whole-genome bisulfite sequencing as outperforming whole-genome and targeted sequencing approaches for multicancer detection across stages. We thus developed a targeted methylation (TM) assay for multicancer detection and tissue-of-origin (TOO) localization. Methods: Participants were from the Circulating Cell-free Genome Atlas (CCGA; NCT02889978) and STRIVE (NCT03085888) studies, both prospective, multicenter, observational studies with longitudinal follow-up. cfDNA samples spanning &gt;20 cancer types of all stages were divided into a cross-validated training set and an independent validation set; there were 3,583 evaluable samples in training (1,530 cancer; 2,053 noncancer) and 1,803 in validation (678 cancer; 1,125 noncancer). Performance in a prespecified set of 12 high-signal cancers was also reported (anus, bladder, colon/rectum, esophagus, head and neck, liver/bile-duct, lung, lymphoma, ovary, pancreas, plasma cell neoplasm, stomach). This multicancer early detection test evaluated cfDNA for the presence of cancer and localization of TOO; the TM classifier was trained to target &gt;99% specificity. Precision was defined as the fraction of correct calls. Results: Participants with and without cancer were similar in age. Specificity across all cancer types in the training and validation sets was 99.8% (95% CI, 99.2-99.9%) and 99.3% (98.3-99.8%), respectively, which reflects a consistent (P=0.292) false positive rate of &lt;1%. Across all cancer types, aggregate sensitivity was also consistent between the training and validation sets (55% [53-58%] and 55% [51-59], respectively; P=0.897). In the validation set, aggregate sensitivity in the prespecified group was 76% (73-78%); detection was 39% (27–52%) in stage I (n=62), 69% (56–80%) in stage II (n=62), 83% (75–90%) in stage III (n=102), and 92% (86–96%) in stage IV (n=130). Overall, the classifier assigned a TOO across &gt;20 cancer types in 96% of samples (344/359); of these, the TOO was correct in 93% (321/344) of cases, which was consistent with training set analyses. Conclusions: This multicancer early detection test detected cancer signal across &gt;20 cancer types with a single, fixed, low false positive rate and highly accurate TOO localization. Importantly, results in the independent validation set were consistent with the training set, demonstrating the robustness of machine learning classifier training, and confirms that data were not overfitted. These data support the feasibility of a single blood-based test that can detect multiple cancers, supporting further clinical development in preparation for the return of results. Citation Format: Anne-Renee Hartman, Geoffrey Oxnard, Eric Klein, Michael Seiden, Earl Hubbell, Oliver Venn, Arash Jamshidi, Nan Zhang, John Beausang, Samuel Gross, Kathryn Kurtzman, Eric Fung, Brian Allen, Alexander Fields, Hai Liu, Mikkael Sekeres, Donald Richards, Peter Yu, Alexander Aravanis, Minetta Liu. Multicancer detection of early-stage cancers with simultaneous tissue localization using a plasma cfDNA-based targeted methylation assay [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 IA02.