Dataset Information

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.

ABSTRACT: Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-passage, patient-derived xenograft models that were used to validate 35 patient-specific drug predictions. Both OncoTarget, which identifies high-affinity inhibitors of individual master regulator (MR) proteins, and OncoTreat, which identifies drugs that invert the transcriptional activity of hyperconnected MR modules, produced highly significant 30-day disease control rates (68% and 91%, respectively). Moreover, of 18 OncoTreat-predicted drugs, 15 induced the predicted MR-module activity inversion in vivo. Predicted drugs significantly outperformed antineoplastic drugs selected as unpredicted controls, suggesting these methods may substantively complement existing precision cancer medicine approaches, as also illustrated by a case study.

Significance

Complementary precision cancer medicine paradigms are needed to broaden the clinical benefit realized through genetic profiling and immunotherapy. In this first-in-class application, we introduce two transcriptome-based tumor-agnostic systems biology tools to predict drug response in vivo. OncoTarget and OncoTreat are scalable for the design of basket and umbrella clinical trials. This article is highlighted in the In This Issue feature, p. 1275.

SUBMITTER: Mundi PS

PROVIDER: S-EPMC10239356 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.

Mundi Prabhjot S PS Dela Cruz Filemon S FS Grunn Adina A Diolaiti Daniel D Mauguen Audrey A Rainey Allison R AR Guillan Kristina K Siddiquee Armaan A You Daoqi D Realubit Ronald R Karan Charles C Ortiz Michael V MV Douglass Eugene F EF Accordino Melissa M Mistretta Suzanne S Brogan Frances F Bruce Jeffrey N JN Caescu Cristina I CI Carvajal Richard D RD Crew Katherine D KD Decastro Guarionex G Heaney Mark M Henick Brian S BS Hershman Dawn L DL Hou June Y JY Iwamoto Fabio M FM Jurcic Joseph G JG Kiran Ravi P RP Kluger Michael D MD Kreisl Teri T Lamanna Nicole N Lassman Andrew B AB Lim Emerson A EA Manji Gulam A GA McKhann Guy M GM McKiernan James M JM Neugut Alfred I AI Olive Kenneth P KP Rosenblat Todd T Schwartz Gary K GK Shu Catherine A CA Sisti Michael B MB Tergas Ana A Vattakalam Reena M RM Welch Mary M Wenske Sven S Wright Jason D JD Canoll Peter P Hibshoosh Hanina H Kalinsky Kevin K Aburi Mahalaxmi M Sims Peter A PA Alvarez Mariano J MJ Kung Andrew L AL Califano Andrea A

Cancer discovery 20230601 6

Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-pas ...[more]

PMID: 37061969

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Project description:Next-generation sequencing (NGS) opens new options in clinical oncology, from therapy selection to genetic counseling. However, realization of this potential not only requires succeeding in the bioinformatics and interpretation of the results, but also in their integration into the clinical practice. We have developed a novel NGS diagnostic platform aimed at detecting (1) somatic genomic alterations associated with the response to approved targeted cancer therapies and (2) germline mutations predisposing to hereditary malignancies.Next-generation sequencing libraries enriched in the exons of 215 cancer genes (97 for therapy selection and 148 for predisposition, with 30 informative for both applications), as well as selected introns from 17 genes involved in drug-related rearrangements, were prepared from 39 tumors (paraffin-embedded tissues/cytologies), 36 germline samples (blood) and 10 cell lines using hybrid capture. Analysis of NGS results was performed with specifically developed bioinformatics pipelines.The platform detects single-nucleotide variants (SNVs) and insertions/deletions (indels) with sensitivity and specificity >99.5% (allelic frequency ?0.1), as well as copy-number variants (CNVs) and rearrangements. Somatic testing identified tailored approved targeted drugs in 35/39 tumors (89.74%), showing a diagnostic yield comparable to that of leading commercial platforms. A somatic EGFR p.E746_S752delinsA mutation in a mediastinal metastasis from a breast cancer prompted its anatomopathologic reassessment, its definite reclassification as a lung cancer and its treatment with gefitinib (partial response sustained for 15 months). Testing of 36 germline samples identified two pathogenic mutations (in CDKN2A and BRCA2). We propose a strategy for interpretation and reporting of results adaptable to the aim of the request, the availability of tumor and/or normal samples and the scope of the informed consent.With an adequate methodology, it is possible to translate to the clinical practice the latest advances in precision oncology, integrating under the same platform the identification of somatic and germline genomic alterations.

Dataset Information

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.

Significance

Publications

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.

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