Molecular-guided therapy for the treatment of patients with relapsed and refractory childhood cancers: a Beat Childhood Cancer Research Consortium trial.

CNS tumors Genomic sequencing Molecular-guided therapy Neuroblastoma Orphan diseases Pediatric oncology Rare tumors

Journal

Genome medicine

ISSN: 1756-994X

Titre abrégé: Genome Med

Pays: England

ID NLM: 101475844

Informations de publication

Date de publication:
12 Feb 2024

Historique:

received: 17 08 2023

accepted: 24 01 2024

medline: 13 2 2024

pubmed: 13 2 2024

entrez: 12 2 2024

Statut: epublish

Résumé

Children with relapsed central nervous system (CNS tumors), neuroblastoma, sarcomas, and other rare solid tumors face poor outcomes. This prospective clinical trial examined the feasibility of combining genomic and transcriptomic profiling of tumor samples with a molecular tumor board (MTB) approach to make real‑time treatment decisions for children with relapsed/refractory solid tumors. Subjects were divided into three strata: stratum 1-relapsed/refractory neuroblastoma; stratum 2-relapsed/refractory CNS tumors; and stratum 3-relapsed/refractory rare solid tumors. Tumor samples were sent for tumor/normal whole-exome (WES) and tumor whole-transcriptome (WTS) sequencing, and the genomic data were used in a multi-institutional MTB to make real‑time treatment decisions. The MTB recommended plan allowed for a combination of up to 4 agents. Feasibility was measured by time to completion of genomic sequencing, MTB review and initiation of treatment. Response was assessed after every two cycles using Response Evaluation Criteria in Solid Tumors (RECIST). Patient clinical benefit was calculated by the sum of the CR, PR, SD, and NED subjects divided by the sum of complete response (CR), partial response (PR), stable disease (SD), no evidence of disease (NED), and progressive disease (PD) subjects. Grade 3 and higher related and unexpected adverse events (AEs) were tabulated for safety evaluation. A total of 186 eligible patients were enrolled with 144 evaluable for safety and 124 evaluable for response. The average number of days from biopsy to initiation of the MTB-recommended combination therapy was 38 days. Patient benefit was exhibited in 65% of all subjects, 67% of neuroblastoma subjects, 73% of CNS tumor subjects, and 60% of rare tumor subjects. There was little associated toxicity above that expected for the MGT drugs used during this trial, suggestive of the safety of utilizing this method of selecting combination targeted therapy. This trial demonstrated the feasibility, safety, and efficacy of a comprehensive sequencing model to guide personalized therapy for patients with any relapsed/refractory solid malignancy. Personalized therapy was well tolerated, and the clinical benefit rate of 65% in these heavily pretreated populations suggests that this treatment strategy could be an effective option for relapsed and refractory pediatric cancers. ClinicalTrials.gov, NCT02162732. Prospectively registered on June 11, 2014.

Sections du résumé

BACKGROUND BACKGROUND

METHODS METHODS

Subjects were divided into three strata: stratum 1-relapsed/refractory neuroblastoma; stratum 2-relapsed/refractory CNS tumors; and stratum 3-relapsed/refractory rare solid tumors. Tumor samples were sent for tumor/normal whole-exome (WES) and tumor whole-transcriptome (WTS) sequencing, and the genomic data were used in a multi-institutional MTB to make real‑time treatment decisions. The MTB recommended plan allowed for a combination of up to 4 agents. Feasibility was measured by time to completion of genomic sequencing, MTB review and initiation of treatment. Response was assessed after every two cycles using Response Evaluation Criteria in Solid Tumors (RECIST). Patient clinical benefit was calculated by the sum of the CR, PR, SD, and NED subjects divided by the sum of complete response (CR), partial response (PR), stable disease (SD), no evidence of disease (NED), and progressive disease (PD) subjects. Grade 3 and higher related and unexpected adverse events (AEs) were tabulated for safety evaluation.

RESULTS RESULTS

A total of 186 eligible patients were enrolled with 144 evaluable for safety and 124 evaluable for response. The average number of days from biopsy to initiation of the MTB-recommended combination therapy was 38 days. Patient benefit was exhibited in 65% of all subjects, 67% of neuroblastoma subjects, 73% of CNS tumor subjects, and 60% of rare tumor subjects. There was little associated toxicity above that expected for the MGT drugs used during this trial, suggestive of the safety of utilizing this method of selecting combination targeted therapy.

CONCLUSIONS CONCLUSIONS

This trial demonstrated the feasibility, safety, and efficacy of a comprehensive sequencing model to guide personalized therapy for patients with any relapsed/refractory solid malignancy. Personalized therapy was well tolerated, and the clinical benefit rate of 65% in these heavily pretreated populations suggests that this treatment strategy could be an effective option for relapsed and refractory pediatric cancers.

TRIAL REGISTRATION BACKGROUND

ClinicalTrials.gov, NCT02162732. Prospectively registered on June 11, 2014.

Identifiants

DOI: 10.1186/s13073-024-01297-5 PMID: 38347552

pubmed: 38347552

doi: 10.1186/s13073-024-01297-5

pii: 10.1186/s13073-024-01297-5

doi:

Banques de données

ClinicalTrials.gov

['NCT02162732']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

Informations de copyright

Références

Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7–33.

pubmed: 35020204 doi: 10.3322/caac.21708

Worst BC, van Tilburg CM, Balasubramanian GP, Fiesel P, Witt R, Freitag A, et al. Next-generation personalised medicine for high-risk paediatric cancer patients - the INFORM pilot study. Eur J Cancer. 2016;65:91–101.

pubmed: 27479119 doi: 10.1016/j.ejca.2016.06.009

Cancer Genome Atlas Research N. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455(7216):1061–8.

doi: 10.1038/nature07385

Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ, Angenendt P, et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science. 2008;321(5897):1801–6.

pubmed: 18772397 pmcid: 2848990 doi: 10.1126/science.1164368

Zhu X, Gerstein M, Snyder M. Getting connected: analysis and principles of biological networks. Genes Dev. 2007;21(9):1010–24.

pubmed: 17473168 doi: 10.1101/gad.1528707

Huang S. Back to the biology in systems biology: what can we learn from biomolecular networks? Brief Funct Genomic Proteomic. 2004;2(4):279–97.

pubmed: 15163364 doi: 10.1093/bfgp/2.4.279

Aranda-Anzaldo A. Cancer development and progression: a non-adaptive process driven by genetic drift. Acta Biotheor. 2001;49(2):89–108.

pubmed: 11450810 doi: 10.1023/A:1010215424196

Wang E, Lenferink A, O’Connor-McCourt M. Cancer systems biology: exploring cancer-associated genes on cellular networks. Cell Mol Life Sci. 2007;64(14):1752–62.

pubmed: 17415519 doi: 10.1007/s00018-007-7054-6

Michor F, Nowak MA, Iwasa Y. Evolution of resistance to cancer therapy. Curr Pharm Des. 2006;12(3):261–71.

pubmed: 16454743 doi: 10.2174/138161206775201956

Balakrishnan A, Bleeker FE, Lamba S, Rodolfo M, Daniotti M, Scarpa A, et al. Novel somatic and germline mutations in cancer candidate genes in glioblastoma, melanoma, and pancreatic carcinoma. Can Res. 2007;67(8):3545–50.

doi: 10.1158/0008-5472.CAN-07-0065

Heng HH. Cancer genome sequencing: the challenges ahead. BioEssays. 2007;29(8):783–94.

pubmed: 17621658 doi: 10.1002/bies.20610

Sjoblom T, Jones S, Wood LD, Parsons DW, Lin J, Barber TD, et al. The consensus coding sequences of human breast and colorectal cancers. Science. 2006;314(5797):268–74.

pubmed: 16959974 doi: 10.1126/science.1133427

Cheng DT, Mitchell TN, Zehir A, Shah RH, Benayed R, Syed A, et al. Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): a hybridization capture-based next-generation sequencing clinical assay for solid tumor molecular oncology. J Mol Diagn. 2015;17(3):251–64.

pubmed: 25801821 pmcid: 5808190 doi: 10.1016/j.jmoldx.2014.12.006

Mosse YP, Lim MS, Voss SD, Wilner K, Ruffner K, Laliberte J, et al. Safety and activity of crizotinib for paediatric patients with refractory solid tumours or anaplastic large-cell lymphoma: a Children’s Oncology Group phase 1 consortium study. Lancet Oncol. 2013;14(6):472–80.

pubmed: 23598171 pmcid: 3730818 doi: 10.1016/S1470-2045(13)70095-0

Barghi F, Shannon HE, Saadatzadeh MR, Bailey BJ, Riyahi N, Bijangi-Vishehsaraei K, et al. Precision medicine highlights dysregulation of the CDK4/6 cell cycle regulatory pathway in pediatric, adolescents and young adult sarcomas. Cancers (Basel). 2022;14(15). Article Number: 3611.

Franshaw L, Tsoli M, Byrne J, Mayoh C, Sivarajasingam S, Norris M, et al. Predictors of success of phase II pediatric oncology clinical trials. Oncologist. 2019;24(8):e765–74.

pubmed: 30808815 pmcid: 6693728 doi: 10.1634/theoncologist.2017-0666

Pfaff E, El Damaty A, Balasubramanian GP, Blattner-Johnson M, Worst BC, Stark S, et al. Brainstem biopsy in pediatric diffuse intrinsic pontine glioma in the era of precision medicine: the INFORM study experience. Eur J Cancer. 2019;114:27–35.

pubmed: 31022591 doi: 10.1016/j.ejca.2019.03.019

Sholler G, Ferguson W, Bergendahl G, Currier E, Lenox S, Bond J, et al. A pilot trial testing the feasibility of using molecular-guided therapy in patients with recurrent neuroblastoma. J Cancer Ther. 2012;3:602–12.

doi: 10.4236/jct.2012.35077

Chang W, Brohl AS, Patidar R, Sindiri S, Shern JF, Wei JS, et al. Multidimensional clinomics for precision therapy of children and adolescent young adults with relapsed and refractory cancer: a report from the center for cancer research. Clinical cancer research: an official journal of the American Association for Cancer Research. 2016;22(15):3810–20.

pubmed: 26994145 doi: 10.1158/1078-0432.CCR-15-2717

Wong M, Mayoh C, Lau LMS, Khuong-Quang DA, Pinese M, Kumar A, et al. Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk pediatric cancer. Nat Med. 2020;26(11):1742–53.

pubmed: 33020650 doi: 10.1038/s41591-020-1072-4

Langenberg KPS, Meister MT, Bakhuizen JJ, Boer JM, van Eijkelenburg NKA, Hulleman E, et al. Implementation of paediatric precision oncology into clinical practice: the Individualized Therapies for Children with cancer program ‘iTHER.’ Eur J Cancer. 2022;175:311–25.

pubmed: 36182817 pmcid: 9586161 doi: 10.1016/j.ejca.2022.09.001

Khater F, Vairy S, Langlois S, Dumoucel S, Sontag T, St-Onge P, et al. Molecular profiling of hard-to-treat childhood and adolescent cancers. JAMA Netw Open. 2019;2(4): e192906.

pubmed: 31026031 pmcid: 6487576 doi: 10.1001/jamanetworkopen.2019.2906

Mody RJ, Wu YM, Lonigro RJ, Cao X, Roychowdhury S, Vats P, et al. Integrative clinical sequencing in the management of refractory or relapsed cancer in youth. JAMA. 2015;314(9):913–25.

pubmed: 26325560 pmcid: 4758114 doi: 10.1001/jama.2015.10080

Eckstein OS, Allen CE, Williams PM, Roy-Chowdhuri S, Patton DR, Coffey B, et al. Phase II study of selumetinib in children and young adults with tumors harboring activating mitogen-activated protein kinase pathway genetic alterations: arm E of the NCI-COG Pediatric MATCH Trial. Journal of clinical oncology: official journal of the American Society of Clinical Oncology. 2022;40(20):2235–45.

pubmed: 35363510 doi: 10.1200/JCO.21.02840

Harris MH, DuBois SG, Glade Bender JL, Kim A, Crompton BD, Parker E, et al. Multicenter feasibility study of tumor molecular profiling to inform therapeutic decisions in advanced pediatric solid tumors: the Individualized Cancer Therapy (iCat) Study. JAMA Oncol. 2016;2(5):608–15.

pubmed: 26822149 doi: 10.1001/jamaoncol.2015.5689

Church AJ, Corson LB, Kao PC, Imamovic-Tuco A, Reidy D, Doan D, et al. Molecular profiling identifies targeted therapy opportunities in pediatric solid cancer. Nat Med. 2022;28(8):1581–9.

pubmed: 35739269 doi: 10.1038/s41591-022-01856-6

Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95: 103208.

pubmed: 31078660 pmcid: 7254481 doi: 10.1016/j.jbi.2019.103208

Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.

pubmed: 18929686 doi: 10.1016/j.jbi.2008.08.010

Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45(2):228–47.

pubmed: 19097774 doi: 10.1016/j.ejca.2008.10.026

Byron SA, Hendricks WPD, Nagulapally AB, Kraveka JM, Ferguson WS, Brown VI, et al. Genomic and transcriptomic analysis of relapsed and refractory childhood solid tumors reveals a diverse molecular landscape and mechanisms of immune evasion. Can Res. 2021;81(23):5818–32.

doi: 10.1158/0008-5472.CAN-21-1033

Byron SA HW, Nagulapally AB, et al. Genomic profiling of relapsed and refractory childhood cancers. phs002238.v1.p1, NCBI Database of Genotypes and Phenotypes (dbGaP). 2021. https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002238.v1.p1 .

Christoforides A, Carpten JD, Weiss GJ, Demeure MJ, Von Hoff DD, Craig DW. Identification of somatic mutations in cancer through Bayesian-based analysis of sequenced genome pairs. BMC Genomics. 2013;14:302.

pubmed: 23642077 pmcid: 3751438 doi: 10.1186/1471-2164-14-302

Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.

pubmed: 24695404 pmcid: 4103590 doi: 10.1093/bioinformatics/btu170

Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21.

pubmed: 23104886 doi: 10.1093/bioinformatics/bts635

Lawrence M, Huber W, Pages H, Aboyoun P, Carlson M, Gentleman R, et al. Software for computing and annotating genomic ranges. PLoS Comput Biol. 2013;9(8): e1003118.

pubmed: 23950696 pmcid: 3738458 doi: 10.1371/journal.pcbi.1003118

Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.

pubmed: 25516281 pmcid: 4302049 doi: 10.1186/s13059-014-0550-8

Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847–9.

pubmed: 27207943 doi: 10.1093/bioinformatics/btw313

Hubschmann D, Jopp-Saile L, Andresen C, Kramer S, Gu Z, Heilig CE, et al. Analysis of mutational signatures with yet another package for signature analysis. Genes Chromosomes Cancer. 2021;60(5):314–31.

pubmed: 33222322 doi: 10.1002/gcc.22918

Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res. 2019;47(D1):D941–7.

pubmed: 30371878 doi: 10.1093/nar/gky1015

Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415–21.

pubmed: 23945592 pmcid: 3776390 doi: 10.1038/nature12477

Kraveka JM, Lewis EC, Bergendahl G, Ferguson W, Oesterheld J, Kim E, Nagulapally AB, Dykema KJ, Brown VI, Roberts WD, Mitchell D, Eslin D, Hanson D, Isakoff MS, Wada RK, Harrod VL, Rawwas J, Hanna G, Hendricks WPD, Byron SA, Snuderl M, Serrano J, Trent JM, Saulnier Sholler GL. A pilot study of genomic-guided induction therapy followed by immunotherapy with difluoromethylornithine maintenance for high-risk neuroblastoma. Cancer Rep (Hoboken). 2022;5(11):e1616. https://doi.org/10.1002/cnr2.1616 .

Common Terminology Criteria for Adverse Events (CTCAE) Version 4.03. US Department of Health and Human Services, National Institutes of Health, National Cancer Institute; 2010.

Shukla N, Levine MF, Gundem G, Domenico D, Spitzer B, Bouvier N, et al. Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers. Nat Commun. 2022;13(1):2485.

pubmed: 35585047 pmcid: 9117241 doi: 10.1038/s41467-022-30233-7

Mueller S, Jain P, Liang WS, Kilburn L, Kline C, Gupta N, et al. A pilot precision medicine trial for children with diffuse intrinsic pontine glioma-PNOC003: a report from the Pacific Pediatric Neuro-Oncology Consortium. International journal of cancer Journal international du cancer. 2019;145(7):1889–901.

pubmed: 30861105 doi: 10.1002/ijc.32258

Kline C, Jain P, Kilburn L, Bonner ER, Gupta N, Crawford JR, et al. Upfront biology-guided therapy in diffuse intrinsic pontine glioma: therapeutic, molecular, and biomarker outcomes from PNOC003. Clinical cancer research: an official journal of the American Association for Cancer Research. 2022;28(18):3965–78.

pubmed: 35852795 doi: 10.1158/1078-0432.CCR-22-0803

Grobner SN, Worst BC, Weischenfeldt J, Buchhalter I, Kleinheinz K, Rudneva VA, et al. The landscape of genomic alterations across childhood cancers. Nature. 2018;555(7696):321–7.

pubmed: 29489754 doi: 10.1038/nature25480

Harttrampf AC, Lacroix L, Deloger M, Deschamps F, Puget S, Auger N, et al. Molecular screening for cancer treatment optimization (MOSCATO-01) in pediatric patients: a single-institutional prospective molecular stratification trial. Clinical cancer research: an official journal of the American Association for Cancer Research. 2017;23(20):6101–12.

pubmed: 28733441 doi: 10.1158/1078-0432.CCR-17-0381

Pilati C, Shinde J, Alexandrov LB, Assie G, Andre T, Helias-Rodzewicz Z, et al. Mutational signature analysis identifies MUTYH deficiency in colorectal cancers and adrenocortical carcinomas. J Pathol. 2017;242(1):10–5.

pubmed: 28127763 doi: 10.1002/path.4880

Marengo B, Raffaghello L, Pistoia V, Cottalasso D, Pronzato MA, Marinari UM, Domenicotti C. Reactive oxygen species: biological stimuli of neuroblastoma cell response. Cancer Lett. 2005;228(1–2):111–6.

pubmed: 15916847 doi: 10.1016/j.canlet.2005.01.046

Berlanga P, Pierron G, Lacroix L, Chicard M, Adam de Beaumais T, Marchais A, et al. The European MAPPYACTS Trial: precision medicine program in pediatric and adolescent patients with recurrent malignancies. Cancer Discov. 2022;12(5):1266–81.

pubmed: 35292802 pmcid: 9394403 doi: 10.1158/2159-8290.CD-21-1136