Molecular Tumor Board-Assisted Care in an Advanced Cancer Population: Results of a Phase II Clinical Trial

Rachel W Miller, Megan L Hutchcraft, Heidi L Weiss, Jianrong Wu, Chi Wang, Jinpeng Liu, Rani Jayswal, Mikayla Buchanan, Abigail Anderson, Derek B Allison, Riham H El Khouli, Reema A Patel, John L Villano, Susanne M Arnold, Jill M Kolesar, Rachel W Miller, Megan L Hutchcraft, Heidi L Weiss, Jianrong Wu, Chi Wang, Jinpeng Liu, Rani Jayswal, Mikayla Buchanan, Abigail Anderson, Derek B Allison, Riham H El Khouli, Reema A Patel, John L Villano, Susanne M Arnold, Jill M Kolesar

Abstract

Purpose: Multidisciplinary molecular tumor boards (MTBs) interpret next-generation sequencing reports and help oncologists determine best therapeutic options; however, there is a paucity of data regarding their clinical utility. The purpose of this study was to determine if MTB-directed therapy improves progression-free survival (PFS) over immediately prior therapy in patients with advanced cancer.

Methods: This single-arm, prospective phase II clinical trial enrolled patients with advanced cancer with an actionable mutation who received MTB-recommended targeted therapy between January 1, 2017, and October 31, 2020. MTB-recommended both on-label (level 1 evidence) and off-label (evidence levels 2 and 3) therapies. Of the 93 enrolled patients, 43 were treated frontline and 50 received second-line or greater-line therapy. The primary outcome was the probability of patients treated with second-line or greater-line MTB-directed therapy who achieved a PFS ratio ≥ 1.3 (PFS on MTB-directed therapy divided by PFS on the patient's immediately prior therapy). Secondary outcomes included PFS for patients treated frontline and overall survival and adverse effects for the entire study population.

Results: The most common disease sites were lung (35 of 93, 38%), gynecologic (17 of 93, 18%), GI (16 of 93, 17%), and head and neck (7 of 93, 8%). The Kaplan-Meier estimate of the probability of PFS ratio ≥ 1.3 was 0.59 (95% CI, 0.47 to 0.75) for patients treated with second-line or greater-line MTB-directed therapy. The median PFS was 449 (range 42-1,125) days for patients treated frontline. The median overall survival was 768 (range 22-1,240) days. There were four nontreatment-related deaths.

Conclusion: When treated with MTB-directed therapy, most patients experienced improved PFS compared with immediately prior treatment. MTB-directed targeted therapy may be a strategy to improve outcomes for patients with advanced cancer.

Trial registration: ClinicalTrials.gov NCT03089554.

Conflict of interest statement

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/po/author-center.

Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).

Figures

FIG 1.
FIG 1.
Study flow diagram. Flow diagram shows identification of patients who underwent MTB review and subsequent enrollment in this trial. MCC, Markey Cancer Center; MTB, molecular tumor board.
FIG 2.
FIG 2.
Genomic profiles, recommendations, and MTB-directed targeted therapy, and outcomes of patients enrolled in this trial. Genes and biomarkers are displayed in columns. Rows demonstrate individual tumor profiles, targeted therapy, and PFS ratio for each patient. GYN, gynecologic; LOH, loss of heterozygosity; MSI, microsatellite instability; MTB, molecular tumor board; PD-L1: programmed death-ligand 1; PFS, progression-free survival; TMB, tumor mutational burden.
FIG 3.
FIG 3.
Growth modulation index among patients treated with second-line or greater-line MTB-directed therapy (cohort 1; n = 50). (A) GMI analysis for 50 patients who had prior therapy PFS data. Larger GMI values represent higher PFS2/PFS1 ratios, indicating superior PFS on MTB-directed therapy (PFS2). Survival probability indicates the probability of obtaining or exceeding a particular GMI. A GMI ≥ 1.3 suggests the benefit of subsequent therapy. The simple proportion of patients experiencing GMI ≥ 1.3 (27 of 50) is 0.54. To provide an accurate estimation, the Kaplan-Meier method accounts for censoring of PFS2 and is 0.59. The Hall-Wellner band indicates the 95% CI, 0.466 to 0.746. (B) Individual patients' time to progression (days) on prior therapy (x axis) and MTB-directed therapy (y axis) is delineated by a circle. The blue line indicates GMI = 1.3. Patients to the left of the blue line demonstrated the most benefit from MTB-directed therapy with some long-term survivors. The red line indicates GMI = 1.0. Patients with GMI = 1.0 conferred the same benefit from MTB-directed therapy as they with their most recent therapy. GMI, growth modulation index; MTB, molecular tumor board; PFS, progression-free survival; TTP, time to progression.
FIG 4.
FIG 4.
Waterfall plot detailing individual PFS ratio (PFS2/PFS1) values for patients treated with second-line or greater-line MTB-directed therapy (cohort 1; n = 50). A larger PFS2/PFS1 value indicates a greater benefit of MTB-directed therapy. MTB, molecular tumor board; PFS, progression-free survival.

References

    1. Colomer R, Mondejar R, Romero-Laorden N, et al. When should we order a next generation sequencing test in a patient with cancer? EClinicalMedicine. 2020;25:100487.
    1. Zhao TT, Xu H, Xu HM, et al. The efficacy and safety of targeted therapy with or without chemotherapy in advanced gastric cancer treatment: A network meta-analysis of well-designed randomized controlled trials. Gastric Cancer. 2018;21:361–371.
    1. Schwaederle M, Zhao M, Lee JJ, et al. Association of biomarker-based treatment strategies with response rates and progression-free survival in refractory malignant neoplasms: A meta-analysis. JAMA Oncol. 2016;2:1452–1459.
    1. Jardim DL, Schwaederle M, Wei C, et al. Impact of a biomarker-based strategy on oncology drug development: A meta-analysis of clinical trials leading to FDA approval. J Natl Cancer Inst. 2015;107:djv253.
    1. Gray SW, Hicks-Courant K, Cronin A, et al. Physicians' attitudes about multiplex tumor genomic testing. J Clin Oncol. 2014;32:1317–1323.
    1. Kurzrock R, Colevas AD, Olszanski A, et al. NCCN oncology research program's investigator steering committee and NCCN best practices committee molecular profiling surveys. J Natl Compr Canc Netw. 2015;13:1337–1346.
    1. Bourret P, Cambrosio A. Genomic expertise in action: Molecular tumour boards and decision-making in precision oncology. Sociol Health Illn. 2019;41:1568–1584.
    1. Burkard ME, Deming DA, Parsons BM, et al. Implementation and clinical utility of an integrated academic-community regional molecular tumor board. JCO Precis Oncol. 2017
    1. Walko C, Kiel PJ, Kolesar J. Precision medicine in oncology: New practice models and roles for oncology pharmacists. Am J Health Syst Pharm. 2016;73:1935–1942.
    1. Freedman AN, Klabunde CN, Wiant K, et al. Use of next-generation sequencing tests to guide cancer treatment: Results from a nationally representative survey of oncologists in the United States. JCO Precis Oncol. 2018;2:1–13.
    1. Larson KL, Huang B, Weiss HL, et al. Clinical outcomes of molecular tumor boards: A systematic review. JCO Precis Oncol. 2021;5:1122–1132.
    1. Kato S, Kim KH, Lim HJ, et al. Real-world data from a molecular tumor board demonstrates improved outcomes with a precision N-of-One strategy. Nat Commun. 2020;11:4965.
    1. Huang B, Chen Q, Allison D, et al. Molecular tumor board review and improved overall survival in non-small-cell lung cancer. JCO Precis Oncol. 2021;5:1530–1539.
    1. Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–381.
    1. Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95:103208.
    1. Goodman AM, Kato S, Bazhenova L, et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol Cancer Ther. 2017;16:2598–2608.
    1. Von Hoff DD, Stephenson JJ, Jr., Rosen P, et al. Pilot study using molecular profiling of patients' tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol. 2010;28:4877–4883.
    1. Bailey CH, Jameson G, Sima C, et al. Progression-free survival decreases with each subsequent therapy in patients presenting for phase I clinical trials. J Cancer. 2012;3:7–13.
    1. Lichtman SM. Pharmacokinetics and pharmacodynamics in the elderly. Clin Adv Hematol Oncol. 2007;5:181–182.
    1. Jung SH, Kim KM. On the estimation of the binomial probability in multistage clinical trials. Stat Med. 2004;23:881–896.
    1. Koyama T, Chen H. Proper inference from Simon's two-stage designs. Stat Med. 2008;27:3145–3154.
    1. Wu J, Chen L, Wei J, et al. Phase II trial design with growth modulation index as the primary endpoint. Pharm Stat. 2019;18:212–222.
    1. Flaherty KT, Gray RJ, Chen AP, et al. Molecular landscape and actionable alterations in a genomically guided cancer clinical trial: National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) J Clin Oncol. 2020;38:3883–3894.
    1. Patel RA, Lin M, Harper MM, et al. Pediatric patient with peritoneal mesothelioma harboring ALK rearrangement. Curr Probl Cancer Case Rep. 2021;4:100074.
    1. United States Food and Drug Administration . FDA Approves Pembrolizumab for Adults and Children With TMB-H Solid Tumors. 2020.
    1. United States Food and Drug Administration . FDA Grants Accelerated Approval to Pembrolizumab for First Tissue/Site Agnostic Indication. 2017.
    1. United States Food and Drug Administration . FDA Approves Niraparib for HRD-Positive Advanced Ovarian Cancer. 2019.
    1. Yearley JH, Gibson C, Yu N, et al. PD-L2 expression in human tumors: Relevance to anti-PD-1 therapy in cancer. Clin Cancer Res. 2017;23:3158–3167.
    1. Wheler JJ, Moulder SL, Naing A, et al. Anastrozole and everolimus in advanced gynecologic and breast malignancies: Activity and molecular alterations in the PI3K/AKT/mTOR pathway. Oncotarget. 2014;5:3029–3038.
    1. Radovich M, Kiel PJ, Nance SM, et al. Clinical benefit of a precision medicine based approach for guiding treatment of refractory cancers. Oncotarget. 2016;7:56491–56500.
    1. Ettinger DS, Wood DE, Aisner DL, et al. NCCN Clinical Practice Guidelines in Oncology: Non-small Cell Lung Cancer. Version 7.2021. 2021.
    1. Koopman B, van der Wekken AJ, Elst A, et al. Relevance and effectiveness of molecular tumor board recommendations for patients with non–small-cell lung cancer with rare or complex mutational profiles. JCO Precis Oncol. 2020:393–410.
    1. Réda M, Richard C, Bertaut A, et al. Implementation and use of whole exome sequencing for metastatic solid cancer. EBioMedicine. 2020;51:102624.

Source: PubMed

3
Subskrybuj