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KRAS mutation detection by liquid biopsy for pancreatic ductal adenocarcinoma

Journal of Hematology & Oncology volume 18, Article number: 44 (2025) Cite this article

Abstract

The clinical utility of liquid biopsy (LB) for pancreatic ductal adenocarcinoma (PDAC) remain understudied. Our single-institution cohort of 311 PDAC patients with non-tumor tissues informed LB found 81.2% positivity (N = 186) in metastatic cases and in 52.4% (N = 43) of localized disease. KRAS mutations were detected in 64.6% (N = 148) of metastatic cases and 16% (N = 13) for localized disease. Positive LB, especially KRAS mutation detection, is associated with worse overall survival (OS) in metastatic PDAC (median 14.5 vs. 31.3 months, HR = 2.7, 95%CI = 1.7–4.3, P < 0.0001). The positive concordance rates of KRAS and TP53 mutations were 63% and 68% in metastatic disease but only 7% (KRAS) and 33% (TP53) in localized disease, respectively. Among the 41 patients who underwent serial liquid biopsy testing, 25% tested positive after an initial negative result. LB detects therapeutically targetable mutations in 58.5% of PDAC patients and is associated with OS.

To the editor

KRAS is mutated in approximately 90% of pancreatic ductal adenocarcinoma (PDAC) including 35% KRASG12D, 30% KRASG12V, 15% KRASG12R, and 1-2% KRASG12C [1, 2]. KRASG12C inhibitors showed efficacy in PDAC and many KRAS inhibitors are in clinical development [3,4,5,6,7,8]. We previously reported the KRAS mutation by tissue testing with PDAC outcome which is associated with worse overall survival (OS) [9]. The utility of liquid biopsy (LB) is promising in PDAC [10, 11]. CtDNA positive rate was 29.48% by tumor-informed whole exome sequencing (WES) in post-surgical PDAC patients on surveillance [12]. There are few real-world data on the non-tumor tissue informed liquid biopsy testing.

Results

We analyzed 311 PDAC patients underwent in-house non tumor informed ctDNA testing from 2018 to 2023 at MD Anderson cancer center. 73% (N = 229) had metastatic disease (Supplemental Methods, Table S1). The median follow-up was 34.9 months with median OS 22.5 months (95% CI = 19.2–25.8). The median age at diagnosis was 64.9 years old. LB was positive in 81.2% (N = 186) of metastatic cases 52.4% (N = 43) of localized disease. KRAS mutations were detected in 64.6% (N = 148) metastatic disease, followed by TP53 (57.6%, N = 132, Fig. 1-A). However, for localized disease, the most detected mutation was TP53 (28%, N = 23), followed by KRAS (16%, N = 13) (Fig. 1-B). Median VAF in localized disease was significantly lower than metastatic disease, medians (interquartile range) = 0.29 (0.53) vs. 0.88 (3.78) respectively, P < 0.001, Fig. 1-C). LB detected actionable mutations in 58.5% (N = 182) of all patients tested according to the OncoKB therapeutic level of evidence classification, with 3.9% (N = 12) at level 2, 44.1% (N = 137) at level 3 A, 4.8% (N = 15) at level 3 B, and 5.8% (N = 18) at level 4 (Fig. 1-D). The positive concordance rate for the subset of patients underwent tissue biopsy testing (n = 116), was 63% (n = 50/80) for KRAS mutation, 68% (n = 43/63) for TP53 mutation, 26% (n = 5/19) for SMAD4, and 80% (n = 8/10) for CDKN2A in metastatic disease. Localized disease had lower positive concordance rate, with 7% (n = 2/27) for KRAS and 33% (n = 7/21) for TP53 (Table S2-3).

Fig. 1
figure 1

Mutations detected in LB and OS. A- Oncoplot for mutations detected in metastatic disease at LB. B- Oncoplot for mutations detected in localized disease at LB. C- Difference in median VAF of mutations detected in LB between localized disease and metastatic disease. D-Rates of actionable mutations detected in LB by OncoKB therapeutic levels

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Positive LB was associated with worse OS (HR = 2.1, 95%CI = 1.3–3.3, P = 0.0015) in metastatic disease (Fig. 2A). The OS difference was not significant (HR = 1.3, 95%CI = 0.72–2.5, P = 0.36; Fig. 2B) in localized disease. Univariate COX regression analyses for OS in metastatic cases showed that mutations in KRAS (HR = 2.8, 95%CI = 1.9-4, P < 0.001), TP53 (HR = 2.19, 95%CI = 1.6–3.1, P < 0.001), and CDKN2A (HR = 1.85, 95%CI = 1.2–2.9, P = 0.006) were associated with worse OS (Fig. 2-C-D). KRAS mutation detection in LB for metastatic disease was associated with worse OS (median 14.5 vs. 31.3 months, HR = 2.7, 95%CI = 1.7–4.3, P < 0.001; Fig. 2-E) but the OS difference was not significant in localized disease (Figure S1-A). Notably, in metastatic cases with KRAS mutation detected by tumor tissue testing, KRAS detection in LB was associated with worse OS (HR = 2.57, 95%CI = 1.42–4.63, P = 0.002; Fig. 2-F). The most frequent KRAS mutation detected was KRASG12D (N = 66, 41%), followed by KRASG12V (N = 58, 36%, Fig. 2-G). KRASG12D and KRASQ61 detection was associated with poorer OS in patients with positive liquid biopsy (Fig. 2-H), which is consistent with our previous findings in patients who had tissues testing [9].

Fig. 2
figure 2

Outcomes with positivity of LB and with KRAS mutations detection. A- OS with positive LB in metastatic disease. B- OS with positive LB in localized disease. C- Hazard ratios (HRs) of OS with mutation detection by LB in metastatic disease. D- HRs of OS with mutation detection in LB in localized disease. E- OS of patients with positive KRAS mutation vs. other mutations in LB for metastatic disease. F- OS of metastatic disease patients with positive KRAS mutation detected by tissue NGS stratified by KRAS mutation detection in LB. G- Frequencies of detected KRAS mutation subtypes. H- OS of patients with KRAS mutation detected in LB by KRAS mutation subtypes

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Among 41 patients who underwent multiple LB tests, 25% were initially ctDNA-negative then subsequently tested positive. None of the 22 patients with positive results converted to negative in the subsequent tests. Among 35 patients who received systemic treatment, patients with increased number of detected mutations (n = 16) had a trend of worse OS (median OS 22.9 months vs. 26.4 months) compared with decreased number of mutations (n = 3; HR = 2.1, 95%CI = 0.48–15.02, P = 0.37, Figure S1-B). Patients with increased VAF for KRAS (n = 18, median OS = 18.7 months) or TP53 (n = 13, median OS = 22.9 months) showed a tendency towards worse OS compared to patients with decreased VAF of KRAS (n = 8, median OS = 44.8 months; HR = 2.02, 95%CI = 0.73–5.59, P = 0.18, Figure S2-A-C) or decreased VAF of TP53 (n = 4, median OS = 34 months; HR = 1.95, 95%CI = 0.54–7.04, P = 0.31, Figure S2-D-F).

Conclusion

We found that 81.2% (N = 186) were LB positive in patients with metastatic disease and 52.4% (N = 43) positivity rate in localized disease of PDAC. KRAS mutations were detected in 64.6% (N = 148) of patients with metastatic disease, while only 16% (N = 13) of patients had localized disease (Fig. 1). The detection of any mutation in LB was associated with worse OS in metastatic PDAC (Fig. 2). Moreover, KRAS mutations, especially KRASG12Dand KRASQ61, were associated with worse OS (Fig. 2).

Data availability

Individual patient-level data are not publicly available to maintain compliance with HIPAA regulations and IRB protocol. Anonymized data are available for non-commercial use from the corresponding author upon request, pending data usage agreement and/or IRB-approved collaboration.

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Acknowledgements

This work was supported by The University of Texas MD Anderson Cancer Center Context Engine and the Context Engine Team. The Context Engine is MD Anderson’s institutional Data Management System and Digital Architecture.

Funding

This work was supported by the Col. Daniel Connelly Memorial Fund, the National Cancer Institute (K22 CA234406 to J.P.S., and the Cancer Center Support Grant (P30 CA016672), the Cancer Prevention & Research Institute of Texas (RR180035 & RP240392 to J.P.S., J.P.S. is a CPRIT Scholar in Cancer Research), the Appendiceal Cancer Pseudomyxoma Peritonei Research Foundation, and the Conquer Cancer Career Development Award to J.P.S. Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Disclaimer: Any opinions, findings, and conclusions expressed in this material are those of the author(s) and do not necessarily reflect those of the American Society of Clinical Oncology or Conquer Cancer.

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Authors and Affiliations

  1. Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Mahmoud Yousef, Abdelrahman Yousef, Saikat Chowdhury, Mohammad Fanaeian, Luca F. Castelnovo, Jennifer Peterson, Brandon G. Smaglo, Robert A. Wolff, Shubham Pant, Jason Willis, Ryan Huey, Michael Overman, Anthony Chen, Camila Lopez, John Paul Shen & Dan Zhao

  2. Sheikh Ahmed Center for Pancreatic Cancer Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Mark W. Hurd & Anirban Maitra

  3. Department of Hospital Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Ashwathy Pillai

  4. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Rebecca Snyder, Ching-Wei Tzeng, Michael P. Kim, Naruhiko Ikoma, Jess E. Maxwell & Matthew H. G. Katz

  5. Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Mark Knafl

  6. Department of Enterprise Data Engineering and Analytics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Ryan L. Lewis & Paul M. Roy

  7. Department of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, TX, USA

    Sali Albarouki

  8. Department of Anatomical Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Huamin Wang & Anirban Maitra

  9. Department of Gastrointestinal Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Eugene Koay & Ethan B. Ludmir

  10. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Ethan B. Ludmir

  11. Department of Molecular and Cellular Oncology, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Haoqiang Ying

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  1. Mahmoud Yousef
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  2. Abdelrahman Yousef
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  20. Ching-Wei Tzeng
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  33. Dan Zhao
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Contributions

D.Z. and M.Y. conceptualized the paper, data interpretation, and writing the manuscript. D. Z., A.Y., A. P., M.Y., S.C., JP.S conceived and designed the study, contributed to literature search, data acquisition, data analysis, data interpretation, and manuscript writing. S.C., M.K. R.L., P.R., M. F., S.A. contributed to data acquisition, data analysis, data interpretation. R.S., B.S., R.W., S.P., J.W., R.H., M.O., CW.T., M.K., N.I., J.M., M.K., E.K., E.L. contributed to patient enrollment, treatment, assessment, and data interpretation. H.W., H.Y. and A.M. contributed to data acquisition and data interpretation. M.K., L.C., S.C., J.P., A. C., C.L. and E.K. contributed to the statistical analysis and writing of the manuscript.

Corresponding author

Correspondence to Dan Zhao.

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Ethics approval and consent to participate

This study was approved by the MD Anderson Institutional Review Board (IRB), protocol number 2023-0091. A waiver of informed consent was granted per the USA federal regulation 45 CFR 46.116(f) for this retrospective study.

Competing interests

Brandon Smaglo: Consulting for Ipsen.Shubham Pant: Advisory for Zymeworks, Ipsen, Novartis, Janssen, Boehringer Ingelheim, and AskGene Pharma; and he receives research funding from Mirati Therapeutics, Lilly, Xencor, Novartis, Rgenix, Bristol-Myers Squibb, Astellas Pharma, Framewave, 4D Phar-ma, Boehringer Ingelheim, NGM Biopharmaceuticals, Janssen, Arcus Biosciences, Elicio Therapeutics, Bionte, Ipsen, Zymeworks, Pfizer, ImmunoMET, Imuneering, and Amal Therapeutics. Anirban Maitra: Consultant for Tezcat Biosciences is listed as an inventor of a patent licensed to Thrive Earlier Detection (an Exact Sciences Company) relevant to early detection of pancreatic cancer. John Paul Shen: Grant/research support/collaboration: Celsius Therapeutics, BostonGene, Caris Life Sciences, Natera, Xilis, Palantir, Genentech. Consulting/stock ownership: Engine Biosciences, NaDeNo Nanoscience.Dan Zhao: Clinical trials with hMirati/BMS, Phanes, CARsgen, TriSalus and Affini-T; Consulting for Ipsen.

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Yousef, M., Yousef, A., Hurd, M.W. et al. KRAS mutation detection by liquid biopsy for pancreatic ductal adenocarcinoma. J Hematol Oncol 18, 44 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13045-025-01696-0

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Journal of Hematology & Oncology

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