It still remains to be demonstrated that using molecular profiling to guide therapy improves patient outcome in oncology. Classification of somatic variants is not straightforward, rendering treatment decisions based on variants with unknown significance (VUS) hard to implement. The oncogenic activity of VUS and mutations identified in 12 patients treated with molecularly targeted agents (MTAs) in the frame of SHIVA01 trial was assessed using Functional Annotation for Cancer Treatment (FACT). MTA response prediction was measured in vitro, blinded to the actual clinical trial results, and survival predictions according to FACT were correlated with the actual PFS of SHIVA01 patients. Patients with positive prediction had a median PFS of 5.8 months versus 1.7 months in patients with negative prediction (P < 0.05). Our results highlight the role of the functional interpretation of molecular profiles to predict MTA response.
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http://dx.doi.org/10.1002/1878-0261.12180 | DOI Listing |
J Pathol
October 2024
Department of Pathology, Institut Curie, PSL Research University, Paris, France.
Tumor immunological characterization includes evaluation of tumor-infiltrating lymphocytes (TILs) and programmed cell death protein ligand-1 (PD-L1) expression. This study investigated TIL distribution, its prognostic value, and PD-L1 expression in metastatic and matched primary tumors (PTs). Specimens from 550 pan-cancer patients of the SHIVA01 trial (NCT01771458) with available metastatic biopsy and 111 matched PTs were evaluated for TILs and PD-L1.
View Article and Find Full Text PDFWorld J Pediatr
October 2023
Oncompass Medicine Hungary Kft, Retek Str. 34, Budapest, 1024, Hungary.
Background: The utility of routine extensive molecular profiling of pediatric tumors is a matter of debate due to the high number of genetic alterations of unknown significance or low evidence and the lack of standardized and personalized decision support methods. Digital drug assignment (DDA) is a novel computational method to prioritize treatment options by aggregating numerous evidence-based associations between multiple drivers, targets, and targeted agents. DDA has been validated to improve personalized treatment decisions based on the outcome data of adult patients treated in the SHIVA01 clinical trial.
View Article and Find Full Text PDFEur J Cancer
April 2023
Molecular Oncology, PSL Research University, CNRS, UMR 144, Institut Curie, Paris 75005, France; Paris Center for Microbiome Medicine, Fédération Hospitalo-Universitaire, Paris, France; Medical Oncology Department, Institut Curie, Saint-Cloud 92210, France.
Background: Data on the role of the microbiota in cancer have accumulated in recent years, with particular interest in intratumoral bacteria. Previous results have shown that the composition of intratumoral microbiome is different depending on the type of primary tumour and that bacteria from the primary tumour could migrate to metastatic sites.
Methods: Seventy-nine patients with breast, lung, or colorectal cancer and available biopsy samples from lymph node, lung, or liver site, treated in the SHIVA01 trial were analysed.
NPJ Precis Oncol
June 2021
Department of Drug Development and Innovation (D3i), Institute Curie, Paris & Saint-Cloud, France.
Precision oncology is currently based on pairing molecularly targeted agents (MTA) to predefined single driver genes or biomarkers. Each tumor harbors a combination of a large number of potential genetic alterations of multiple driver genes in a complex system that limits the potential of this approach. We have developed an artificial intelligence (AI)-assisted computational method, the digital drug-assignment (DDA) system, to prioritize potential MTAs for each cancer patient based on the complex individual molecular profile of their tumor.
View Article and Find Full Text PDFEur J Cancer
November 2019
Department of Drug Development and Innovation (D3i), Institut Curie, Paris, Saint-Cloud, France. Electronic address:
Background: A randomised trial SHIVA01 compared the efficacy of matched molecularly targeted therapy outside their indications based on a prespecified treatment algorithm versus conventional chemotherapy in patients with metastatic solid tumours who had failed standard of care. No statistical difference was reported between the two groups in terms of progression-free survival (PFS), challenging treatment algorithm. The European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets (ESCAT) recently defined criteria to prioritise molecular alterations (MAs) to select anticancer drugs.
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