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. 2023 Jan-Dec:30:10732748231175256.
doi: 10.1177/10732748231175256.

Application of Comprehensive Genomic Profiling-Based Next-Generation Sequencing Assay to Improve Cancer Care in a Developing Country

Affiliations

Application of Comprehensive Genomic Profiling-Based Next-Generation Sequencing Assay to Improve Cancer Care in a Developing Country

Claudia Cifuentes et al. Cancer Control. 2023 Jan-Dec.

Abstract

Purpose: Identifying actionable oncogenic mutations have changed the therapeutic landscape in different types of tumors. This study investigated the utility of comprehensive genomic profiling (CGP), a hybrid capture-based next-generation sequencing (NGS) assay, in clinical practice in a developing country.

Methods: In this retrospective cohort study, CGP was performed on clinical samples from patients with different solid tumors recruited between December 2016 and November 2020, using hybrid capture-based genomic profiling, at the individual treating physicians' request in the clinical care for therapy decisions. Kaplan-Meier survival curves were estimated to characterize the time-to-event variables.

Results: Patients median age was 61 years (range: 14-87 years), and 64.7% were female. The most common histological diagnosis was lung primary tumors, with 90 patients corresponding to 52.9% of the samples (95% CI 45.4-60.4%). Actionable mutations with FDA-approved medications for specific alterations correspondent to tumoral histology were identified in 58 cases (46.4%), whereas other alterations were detected in 47 different samples (37.6%). The median overall survival was 15.5 months (95% CI 11.7 months-NR). Patients who were subjected to genomic evaluation at diagnosis reached a median overall survival of 18.3 months (95% CI 14.9 months-NR) compared to 14.1 months (95% CI 11.1 months-NR) in patients who obtained genomic evaluation after tumor progression and during standard treatment (P = .7).

Conclusion: CGP of different types of tumors identifies clinically relevant genomic alterations that have benefited from targeted therapy and improve cancer care in a developing country to guide personalized treatment to beneficial outcomes of cancer patients.

Keywords: actionable mutations; comprehensive genomic profiling; next-generation sequencing; precision medicine.

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Conflict of interest statement

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Oscar Arrieta reports personal fees from Pfizer, grants and individual fees from Astra Zeneca, grants and individual fees from Boehringer-Ingelheim, personal fees from Lilly, individual fees from Merck, personal fees from Bristol-Myers Squibb, grants and personal fees from Roche, outside the submitted work.

Christian Rolfo is a current employee of the Center for Thoracic Oncology at Tisch Cancer Institute, Mount Sinai Health System and Icahn School of Medicine. He reports receiving supported research funding from Lung Cancer Research Foundation-Pfizer; receiving non-financial research support from Guardant Health; providing advisory services to ARCHER, Inivata, EMD Serono, BMS, Novartis, Boston Pharmaceuticals, Pfizer, Mirati, and Eisai; providing speaker services to MSD, AstraZeneca, Roche, and Guardant Health; and participating in the Safety Monitoring Board for EMD Serono.

Andrés F. Cardona disclose financial research support from Merck Sharp and Dohme, Boehringer Ingelheim, Roche, Bristol-Myers Squibb and The Foundation for Clinical and Applied Cancer Research – FICMAC. Additionally, he was linked and received honoraria as advisor, participate in speakers' bureau and gave expert testimony to Merck Sharp and Dohme, Boehringer Ingelheim, Roche, Bristol-Myers Squibb, Pfizer, Novartis, Celldex Therapeutics, Foundation Medicine, Eli Lilly and Foundation for Clinical and Applied Cancer Research – FICMAC.

Figures

Figure 1.
Figure 1.
Absolute number of sampled lesions depending on organ and sex of patients.
Figure 2.
Figure 2.
CONSORT flow of included patients, organs of origin, and histological diagnosis.
Figure 3.
Figure 3.
TMB and microsatellite status according to the organ of origin. Points represent individual Tumoral mutational burden (TMB) measurements, whereas the red line depicts the mean (TMB) per individual organ origin. Abbreviations: CNS, central nervous system; IDT, inferior digestive tract; Unk Primary, primary of unknown origin; FRT, female reproductive tract.
Figure 4.
Figure 4.
Common and concurrent alterations among lung cancer patients.
Figure 5.
Figure 5.
OS based on genomic evaluation timing.
Figure 6.
Figure 6.
TTP of patients allocated to approved treatments based on genomic profile.

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