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Clinical Trial
. 2024 Sep;30(9):2508-2516.
doi: 10.1038/s41591-024-03091-7. Epub 2024 Jun 1.

Pembrolizumab for advanced urothelial carcinoma: exploratory ctDNA biomarker analyses of the KEYNOTE-361 phase 3 trial

Thomas Powles  1 , Yen-Hwa Chang  2 , Yoshiaki Yamamoto  3 , Jose Munoz  4 , Felipe Reyes-Cosmelli  5 , Avivit Peer  6 , Graham Cohen  7 , Evan Y Yu  8 , Anja Lorch  9   10 , Abhishek Bavle  11 , Blanca Homet Moreno  11 , Julia Markensohn  11 , Mackenzie Edmondson  11 , Cai Chen  11 , Razvan Cristescu  11 , Carol Peña  11 , Jared Lunceford  11 , Seyda Gunduz  12
Affiliations
Clinical Trial

Pembrolizumab for advanced urothelial carcinoma: exploratory ctDNA biomarker analyses of the KEYNOTE-361 phase 3 trial

Thomas Powles et al. Nat Med. 2024 Sep.

Abstract

Circulating tumor DNA (ctDNA) is emerging as a potential biomarker in early-stage urothelial cancer, but its utility in metastatic disease remains unknown. In the phase 3 KEYNOTE-361 study, pembrolizumab with and without chemotherapy was compared with chemotherapy alone in patients with metastatic urothelial cancer. The study did not meet prespecified efficacy thresholds for statistical significance. To identify potential biomarkers of response, we retrospectively evaluated the association of pre- and posttreatment ctDNA with clinical outcomes in a subset of patients who received pembrolizumab (n = 130) or chemotherapy (n = 130) in KEYNOTE-361. Baseline ctDNA was associated with best overall response (BOR; P = 0.009), progression-free survival (P < 0.001) and overall survival (OS; P < 0.001) for pembrolizumab but not for chemotherapy (all; P > 0.05). Chemotherapy induced larger ctDNA decreases from baseline to treatment cycle 2 than pembrolizumab; however, change with pembrolizumab (n = 87) was more associated with BOR (P = 4.39 × 10-5) and OS (P = 7.07 × 10-5) than chemotherapy (n = 102; BOR: P = 1.01 × 10-4; OS: P = 0.018). Tumor tissue-informed versions of ctDNA change metrics were most associated with clinical outcomes but did not show a statistically significant independent value for explaining OS beyond radiographic change by RECIST v.1.1 when jointly modeled (pembrolizumab P = 0.364; chemotherapy P = 0.823). These results suggest distinct patterns in early ctDNA changes with immunotherapy and chemotherapy and differences in their association with long-term outcomes, which provide preliminary insights into the utility of liquid biopsies for treatment monitoring in metastatic urothelial cancer. Clinical trial registration: NCT02853305 .

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Conflict of interest statement

T.P. reports receiving grants from AstraZeneca, Roche, Bristol-Myers Squibb, Exelixis, Ipsen, Merck/MSD, Novartis, Pfizer, Seattle Genetics, Merck Serono, Astellas, Johnson & Johnson, and Eisai; consulting fees from AstraZeneca, Bristol-Myers Squibb, Exelixis, Incyte, Ipsen, Merck/MSD, Novartis, Pfizer, Seattle Genetics, Merck Serono, Astellas, Johnson & Johnson, Eisai, Roche, Mashup and Gilead; honoraria from AstraZeneca, Bristol-Myers Squibb, Exelixis, Incyte, Ipsen, Merck/MSD, Novartis, Pfizer, Seattle Genetics, Merck Serono, Astellas, Johnson & Johnson, Eisai, Roche, Mashup and Gilead; support for attending meetings and/or travel from Roche, Pfizer, MSD, AstraZeneca, Ipsen, Gilead and Astellas; holds a strategic advisory role for AstraZeneca, Bristol-Myers Squibb, Exelixis, Ipsen, Merck/MSD, Novartis, Pfizer, Seattle Genetics, Merck Serono, Astellas, Johnson & Johnson, Eisai and Roche; and holds a principal investigator role for Novartis, Pfizer, AstraZeneca, Roche/Genentech, Eisai and Merck. J. Munoz reports receiving honoraria for presentations from LEO pharma and GlaxoSmithKline and support for attending meetings and/or travel from LEP Pharma, GlaxoSmithKline and AstraZeneca. A.P. reports receiving consulting fees from Astellas Pharma, Janssen-Cilag, Bayer, Novartis, Merck Serono, Bristol-Myers Squibb, Eisai, MSD Oncology, Takeda, AstraZeneca and Pfizer; support for attending meetings and/or travel from Pfizer, Astellas Pharma, Bristol-Myers Squibb and MSD; and honoraria from Astellas Pharma, Janssen Oncology, Bayer, Merck Serono, Bristol-Myers Squibb, Exelixis, MSD, Medison, Roche and AstraZeneca. E.Y.Y. reports consulting for Jansen, Merck, AAA Novartis, Bayer, Aadi Bioscience, Oncternal, Bristol-Myers Squibb, Loxo, and Lantheus, and receiving research grants to his institution from Dendreon, Merck, SeaGen, Blue Earth, Bayer – DAROL and citDNA, Lantheus, Tyra, Oncternal, Daiichi-Sankyo, Taiho and Surface. A.L. reports receiving consulting fees from Astellas, AstraZeneca, Bayer, Bristol-Myers Squibb, Esai, Ipsen, Janssen, Merck, MSD, Novartis, Pfizer and Roche; honoraria from Astellas, Novartis and Healthbook Company Switzerland; support for attending meetings and/or travel from Ipsen, Janssen and Bayer; and holds a leadership or fiduciary role for European Association of Urology (EAU) guidelines bladder cancer, European Society Medical Oncology (ESMO) faculty nonprostate, German Society of Hematology and Medical Oncology (DGHO) guideline bladder and testis cancer, the Swiss Group for Clinical Cancer Research (SAKK) scientific board committee and the National Center for Tumors (NCT) scientific board committee. A.B. is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. B.H.M. is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. J. Markensohn is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. M.E. is an employee of MSD, a subsidiary of Merck & Co., Inc. C.C. is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. R.C. is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. C.P. is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. J.L. Is an employee of MSD, a subsidiary of Merck & Co., Inc., and holds stock in Merck & Co., Inc. Y.-H.C., Y.Y., F.R-C., G.P. and S.G. have no conflicts of interest to disclose.

Figures

Fig. 1
Fig. 1. Baseline ctDNA assessment by tumor-informed maxVAF and association with clinical outcomes.
a, Patient-level baseline tumor-informed maxVAF by response status and treatment arm (pembrolizumab, n = 125; chemotherapy, n = 125). The center line corresponds to the median, and the box is delineated by first and third quartiles. Whiskers extend to any points within 1.5 times the interquartile range, with points lying beyond identified individually as potential outliers. b, Association between baseline ctDNA and clinical outcomes by tumor-informed maxVAF evaluated using logistic regression (BOR) and Cox proportional hazards regression (PFS and OS), with adjustment for ECOG PS. Multiplicity-adjusted P values were calculated. Significance was prespecified at α = 0.05. Asterisks indicate significance. Hypothesis: negative association.
Fig. 2
Fig. 2. C2/C1 ctDNA assessment for tumor-informed maxVAF and MR scores.
a, Overall C2/C1 tumor-informed maxVAF (pembrolizumab, n = 87; chemotherapy, n = 102) and MR score changes (pembrolizumab, n = 89; chemotherapy, n = 89) by treatment arm. b, Patient-level C2/C1 tumor-informed maxVAF changes (pembrolizumab, n = 87; chemotherapy, n = 102) by response status, BOR and treatment arm. c, MR score changes (pembrolizumab, n = 89; chemotherapy, n = 89) by response status, BOR and treatment arm. d,e, C2/C1 tumor-informed maxVAF ratio (d) and best 9-week percentage change (e) from baseline in tumor size for the pembrolizumab and the chemotherapy arms. In a–c, the center line corresponds to the median and the box is delineated by first and third quartiles. Whiskers extend to any points within 1.5 times the interquartile range, with points lying beyond identified individually as potential outliers. CR, complete response; PD, progressive disease; PR, partial response; SD, stable disease.
Fig. 3
Fig. 3. Survival by large and not large C2/C1 reductions within the pembrolizumab and chemotherapy arms.
a,b, Kaplan–Meier estimates of survival by C2/C1 tumor-informed maxVAF (a) and MR score changes (b). Large reduction = C2/C1 ratio below the median; not large = C2/C1 ratio above the median. Median cutoff 0.18 (a), 34 (b).
Fig. 4
Fig. 4. OS for pembrolizumab versus chemotherapy by large and not large reductions of C2/C1.
a,b, Kaplan–Meier estimates of OS by C2/C1 tumor-informed maxVAF (a) and MR score changes (b). Large reduction = C2/C1 ratio below the median; not large = C2/C1 ratio above the median. Median cutoff 0.18 (a), 34 (b).
Fig. 5
Fig. 5. Patient-level C2/C1 changes by tTMB and PD-L1 status and treatment arm.
a, Tumor-informed maxVAF (pembrolizumab, n = 87; chemotherapy, n = 102). b, MR score changes (pembrolizumab, n = 89; chemotherapy, n = 89). The center line corresponds to the median and the box is delineated by first and third quartiles. Whiskers extend to any points within 1.5 times the interquartile range, with points lying beyond identified individually as potential outliers.
Extended Data Fig. 1
Extended Data Fig. 1. Trial profile.
C1, cycle 1; C2, cycle 2; ctDNA, circulating tumor DNA; WES, whole-exome sequencing.
Extended Data Fig. 2
Extended Data Fig. 2. OncoPrint illustration of baseline ctDNA.
(a) OncoPrint illustration in the chemotherapy and pembrolizumabs arm and (b) prevalence in the chemotherapy arm versus pembrolizumab arm for the top 30 mutated genes (each dot below is one gene) from baseline ctDNA data.
Extended Data Fig. 3
Extended Data Fig. 3. Correlation between tumor burden and tumor-informed maxVAF and between bTMB and WES tTMB.
(a) Correlation between baseline tumor burden and baseline tumor-informed (N = 232) maxVAF; (b) correlation between baseline tumor burden and baseline tumor-uninformed (N = 240) maxVAF; (c) Correlation between tumor-uninformed bTMB versus WES tTMB (N = 218); (d) correlation between baseline ctDNA tumor informed bTMB versus WES tTMB (N = 218). maxVAF, maximum variant allele frequency; tTMB, tissue tumor mutational burden; WES, whole-exome sequencing.
Extended Data Fig. 4
Extended Data Fig. 4. Survival by low versus high baseline tumor-informed maxVAF, Kaplan-Meier estimates.
(a) PFS and (b) OS. maxVAF, maximum variant allele frequency; OS, overall survival; PFS, progression-free survival. Median cutoff 3.84.
Extended Data Fig. 5
Extended Data Fig. 5. Survival by low and high baseline tumor-informed maxVAF and tTMB and PD-L1 status.
Kaplan-Meier estimates of PFS and OS by low versus high baseline tumor-informed maxVAF by (a) tTMB and (b) PD-L1 status. (a) tTMB and (b) PD-L1 status.maxVAF, maximum variant allele frequency; OS, overall survival; PD-L1, programmed cell death ligand 1; PFS, progression-free survival; tTMB, tissue tumor mutational burden. Median cutoff 3.84.
Extended Data Fig. 6
Extended Data Fig. 6. Survival by large versus not large C2/21 tumor-informed maxVAF and tTMB and PD-L1 status.
Kaplan-Meier estimates of PFS and OS by C2/C1 by (a) tTMB and (b) PD-L1 status. C1, cycle 1; C2, cycle 2; CPS, combined positive score; maxVAF, maximum variant allele frequency; OS, overall survival; PD-L1, programmed cell death ligand 1; PFS, progression-free survival; tTMB, tissue tumor mutational burden. Median cutoff 0.18; Large reduction = C2/C1 ratio below the median; Not Large = C2/C1 ratio above the median.
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