Association of personalized and tumor-informed ctDNA with patient survival outcomes in pancreatic adenocarcinoma - PubMed (original) (raw)

. 2024 Oct 3;29(10):859-869.

doi: 10.1093/oncolo/oyae155.

Maen Abdelrahim 2, Ronald L Drengler 3, Vasily N Aushev 4, Abdullah Esmail 2, George Laliotis 4, Chris M Brewer 4, Giby V George 4, Steven M Abbate 3, Sreenivasa R Chandana 5, Mohamedtaki A Tejani 6, Midhun Malla 7, Dhruv Bansal 8, Samuel Rivero-Hinojosa 4, Erik Spickard 4, Nicole McCormick 4, Michael Cecchini 9, Jill Lacy 9, Naomi Fei 10, Pashtoon Murtaza Kasi 11, Anup Kasi 12, Farshid Dayyani 13, Diana L Hanna 14, Shruti Sharma 4, Meenakshi Malhotra 4, Alexey Aleshin 4, Minetta C Liu 4, Adham Jurdi 4

Affiliations

Association of personalized and tumor-informed ctDNA with patient survival outcomes in pancreatic adenocarcinoma

Gregory P Botta et al. Oncologist. 2024.

Erratum in

Abstract

Introduction: Personalized and tumor-informed circulating tumor DNA (ctDNA) testing is feasible and allows for molecular residual disease (MRD) identification in patients with pancreatic ductal adenocarcinoma (PDAC).

Methods: In this retrospective analysis of commercial cases from multiple US institutions, personalized, tumor-informed, whole-exome sequenced, and germline-controlled ctDNA levels were quantified and analyzed in patients with PDAC. Plasma samples (n = 1329) from 298 clinically validated patients were collected at diagnosis, perioperatively (MRD-window; within 2-12 weeks after surgery, before therapy), and during surveillance (>12 weeks post-surgery if no ACT or starting 4 weeks post-ACT) from November 2019 to March 2023.

Results: Of the initially diagnosed patients with stages I-III PDAC who went for resection, the median follow-up time from surgery was 13 months (range 0.1-214). Positive ctDNA detection rates were 29% (29/100) and 29.6% (45/152) during the MRD and surveillance windows, respectively. Positive ctDNA detection was significantly associated with shorter DFS within the MRD window (median DFS of 6.37 months for ctDNA-positive vs 33.31 months for ctDNA-negative patients; HR: 5.45, P < .0001) as well as during the surveillance period (median DFS: 11.40 months for ctDNA-positive vs NR for ctDNA-negative; HR: 12.38, P < .0001). Additionally, DFS was significantly better with KRAS wildtype status followed by KRASG12R (HR: 0.99, P = .97), KRASG12D (HR: 1.42, P = .194), and worse with KRASG12V (HR: 2.19, P = .002) status. In multivariate analysis, ctDNA detection at surveillance was found to be the most significant prognostic factor for recurrence (HR: 24.28, P < .001).

Conclusions: Perioperative tumor-informed ctDNA detection in PDAC is feasible across all stages and is associated with patient survival outcomes.

Keywords: KRAS; ctDNA; molecular residual disease; pancreatic adenocarcinoma.

© The Author(s) 2024. Published by Oxford University Press.

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Conflict of interest statement

G.P.B. reports advisory roles at Calibr, TumorGen, speakers fees and clinical trial support from Natera, publication assistance and clinical trial support from Carsgen; D.B. reports research funding from Boston Gene; P.M.K. reports grants paid to the institution by Merck, Agenus Bio, Novartis, Advanced Accelerator Applications, Tersera, and Boston Scientific; a consultancy and advisory board relationship with Elicio (scientific advisory board member/shares/stock ownership); consultancy/advisory board fees from Guardant Health, Natera, Foundation Medicine, Illumina, Boston Gene, Merck/MSD Oncology, Tempus, Bayer, Lilly, Delcath Systems, IPBA, QED Therapeutics, Boston Healthcare Associates, Servier, Taiho Oncology, Exact Sciences, Daiichi Sankyo/AstraZeneca, Eisai, Saga Diagnostics, Neogenomics, Do More Diagnostics AS, and Seattle Genetics; consulting fees paid to the institution by Taiho Pharmaceutical and Ipsen; receiving travel support from AstraZeneca for presentation of an investigator-initiated trial. A.K. reports Investigator-initiated trials sponsored by GSK, Astellas, Gilead, Lisata, Circio, Agenus, Research Funding for industry trials from Cardiff, Panavance, Novocure, Ability, Novita and Honorarium from Ipsen and Cardinal Health. M. Malla. reports Consulting at Natera, Exelexis, AstraZeneca. R.L.D. reports ownership of Natera stocks. F.D. reports receipt of research support to institution from AstraZeneca, BMS, Merck, Exelixis, Taiho, Trishula, Natera, Amgen, Genentech/Roche, Ipsen; honoraria from Exelixis, Sirtex Medical, Eisai, Astellas, Servier and consulting fees from Exelixis, Eisai, AstraZeneca. G Laliotis., V.N.A., C.M.B., S.R.-H., E.S., S.S., M.M., A.A., M.C.L. and A.J. are employees of Natera, Inc. and have stock/option to hold stock in the company. G.V.G. and N.M. are former employees of Natera, Inc. M.C.L. reports Grants/Contracts (Funding to Institution - Mayo Clinic) from: Eisai, Exact Sciences, Genentech, Genomic Health, GRAIL, Menarini Silicon Biosystems, Merck, Novartis, Seattle Genetics, Tesaro; Travel Support Reimbursement from AstraZeneca, Genomic Health, Ionis; Ad hoc advisory board meetings (all funds to Mayo Clinic, no personal compensation) from: AstraZeneca, Celgene, Roche/Genentech, Genomic Health, GRAIL, Ionis, Merck, Pfizer, Seattle Genetics, Syndax. All other authors have no conflicts of interest.

Figures

Figure 1.

Figure 1.

A. Consolidated standards of reporting trials (CONSORT) diagram illustrating patient inclusion and exclusion criteria for sub-analyses. B. Demographics heat map illustrating clinicopathologic features, most frequently observed genetic mutations, ctDNA detection in different settings and overall recurrence rate in this cohort.

Figure 2.

Figure 2.

ctDNA-based MRD testing is predictive of survival outcomes in postsurgical patients with pancreatic cancer. A. Kaplan-Meier estimates for DFS stratified by ctDNA-negative and ctDNA-positive status from 2 to 12 weeks after surgery. B. Kaplan-Meier estimates for DFS stratified by ctDNA-negative and ctDNA-positive status at MRD in patients who either received neoadjuvant therapy or up-front surgery. HRs and 95% CIs were calculated using the Cox proportional hazard model. P values were calculated using the 2-sided log-rank test.

Figure 3.

Figure 3.

ctDNA-based MRD testing is predictive of survival outcomes in postsurgical patients with pancreatic cancer. A. Kaplan-Meier estimates for DFS stratified by ctDNA-negative and ctDNA-positive status in patients who received neoadjuvant therapy with or without adjuvant therapy. B. Kaplan-Meier estimates for DFS stratified by ctDNA-negative and ctDNA-positive status in patients who received upfront surgery with or without adjuvant therapy. HRs and 95% CIs were calculated using the Cox proportional hazard model. P values were calculated using the 2-sided log-rank test. C. Stage-wise MRD positivity rate in patients receiving neoadjuvant therapy vs upfront surgery.

Figure 4.

Figure 4.

ctDNA-based testing during the surveillance window is predictive of survival outcomes in postsurgical patients with pancreatic cancer. A. Kaplan-Meier estimates for DFS stratified by ctDNA-negative and ctDNA-positive status from >12 weeks after surgery. HRs and 95% CIs were calculated using the Cox proportional hazard model. P values were calculated using the 2-sided log-rank test. B. Forest plot depicting the multivariate analysis for recurrence in patients with stages I-III pancreatic cancer. Various prognostic factors and their association with DFS, as indicated by HR, were analyzed across the cohort using the 2-sided Wald chi-squared test. The unadjusted HRs (squares) and 95% CIs (horizontal lines) are shown for each prognostic factor. Vertical dotted line, the null hypothesis.

Figure 5.

Figure 5.

ctDNA dynamics with patient outcomes. Kaplan-Meier estimates for DFS according to ctDNA dynamics in patients that had post-surgical MRD time point to any time during surveillance in patients receiving adjuvant chemotherapy or the first subsequent surveillance timepoint in patients with no adjuvant chemotherapy. HRs and 95% CIs were calculated using the Cox proportional hazard model. P values were calculated using the 2-sided log-rank test.

Figure 6.

Figure 6.

KRAS G12V and G12D were associated with worse DFS. Kaplan-Meier estimates for DFS stratified by KRAS wild-type and mutations (G12D, G12V, and G12). HRs and 95% CIs were calculated using the Cox proportional hazard model. P values were calculated using the 2-sided log-rank test.

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