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    MET Exon 14 Skipping and Novel Actionable Variants: Diagnostic and Therapeutic Implications in Latin American Non-Small-Cell Lung Cancer Patients
    (MDPI AG, 2024-12-22)
    RIVAS VERA, SOLANGE VERÓNICA  
    ;
    Romina V. Sepúlveda
    ;
    TAPIA DUFEY, JUAN IGNACIO
    ;
    Catalina Estay
    ;
    Vicente Soto
    <jats:p>Targeted therapy indications for actionable variants in non-small-cell lung cancer (NSCLC) have primarily been studied in Caucasian populations, with limited data on Latin American patients. This study utilized a 52-genes next-generation sequencing (NGS) panel to analyze 1560 tumor biopsies from NSCLC patients in Chile, Brazil, and Peru. The RNA sequencing reads and DNA coverage were correlated to improve the detection of the actionable MET exon 14 skipping variant (METex14). The pathogenicity of MET variants of uncertain significance (VUSs) was assessed using bioinformatic methods, based on their predicted driver potential. The effects of the predicted drivers VUS T992I and H1094Y on c-MET signaling activation, proliferation, and migration were evaluated in HEK293T, BEAS-2B, and H1993 cell lines. Subsequently, c-Met inhibitors were tested in 2D and 3D cell cultures, and drug affinity was determined using 3D structure simulations. The prevalence of MET variants in the South American cohort was 8%, and RNA-based diagnosis detected 27% more cases of METex14 than DNA-based methods. Notably, 20% of METex14 cases with RNA reads below the detection threshold were confirmed using DNA analysis. The novel actionable T992I and H1094Y variants induced proliferation and migration through c-Met/Akt signaling. Both variants showed sensitivity to crizotinib and savolitinib, but the H1094Y variant exhibited reduced sensitivity to capmatinib. These findings highlight the importance of RNA-based METex14 diagnosis and reveal the drug sensitivity profiles of novel actionable MET variants from an understudied patient population.</jats:p>
    Scopus© Citations 4  8
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    Treatments for non-small cell lung cancer: a systematic quality assessment of clinical practice guidelines
    (2023)
    Marcela Cortés-Jofré
    ;
    Meisser Madera
    ;
    Lesbia Tirado-Amador
    ;
    Claudia Asenjo-Lobos  
    ;
    Xavier Bonfill-Cosp
      4Scopus© Citations 3
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    Therapeutic vaccines for advanced non-small cell lung cancer
    (2019)
    Marcela Cortés-Jofré
    ;
    Rolando Uranga
    ;
    Ania Torres Pombert
    ;
    Maria del Carmen Arango Prado
    ;
    Iraida Caballero Aguirrechu
    Scopus© Citations 6  3
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    MET Signaling Pathways, Resistance Mechanisms, and Opportunities for Target Therapies
    (2022)
    RIVAS VERA, SOLANGE VERÓNICA  
    ;
    Arnaldo Marín
    ;
    Suraj Samtani
    ;
    Evelin González-Feliú
    ;
    ARMISEN YAÑEZ, RICARDO AMADO  
    <jats:p>The MET gene, known as MET proto-oncogene receptor tyrosine kinase, was first identified to induce tumor cell migration, invasion, and proliferation/survival through canonical RAS-CDC42-PAK-Rho kinase, RAS-MAPK, PI3K-AKT-mTOR, and β-catenin signaling pathways, and its driver mutations, such as MET gene amplification (METamp) and the exon 14 skipping alterations (METex14), activate cell transformation, cancer progression, and worse patient prognosis, principally in lung cancer through the overactivation of their own oncogenic and MET parallel signaling pathways. Because of this, MET driver alterations have become of interest in lung adenocarcinomas since the FDA approval of target therapies for METamp and METex14 in 2020. However, after using MET target therapies, tumor cells develop adaptative changes, favoring tumor resistance to drugs, the main current challenge to precision medicine. Here, we review a link between the resistance mechanism and MET signaling pathways, which is not only limited to MET. The resistance impacts MET parallel tyrosine kinase receptors and signals shared hubs. Therefore, this information could be relevant in the patient’s mutational profile evaluation before the first target therapy prescription and follow-up to reduce the risk of drug resistance. However, to develop a resistance mechanism to a MET inhibitor, patients must have access to the drugs. For instance, none of the FDA approved MET inhibitors are registered as such in Chile and other developing countries. Constant cross-feeding between basic and clinical research will thus be required to meet future challenges imposed by the acquired resistance to targeted therapies.</jats:p>
    Scopus© Citations 15  16
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    Total mutational load and clinical features as predictors of the metastatic status in lung adenocarcinoma and squamous cell carcinoma patients
    (2022)
    Karen Y. Oróstica
    ;
    Juan Saez-Hidalgo
    ;
    Pamela R. de Santiago
    ;
    RIVAS VERA, SOLANGE VERÓNICA  
    ;
    Sebastian Contreras
    <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Recently, extensive cancer genomic studies have revealed mutational and clinical data of large cohorts of cancer patients. For example, the Pan-Lung Cancer 2016 dataset (part of The Cancer Genome Atlas project), summarises the mutational and clinical profiles of different subtypes of Lung Cancer (LC). Mutational and clinical signatures have been used independently for tumour typification and prediction of metastasis in LC patients. Is it then possible to achieve better typifications and predictions when combining both data streams?</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>In a cohort of 1144 Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LSCC) patients, we studied the number of missense mutations (hereafter, the Total Mutational Load TML) and distribution of clinical variables, for different classes of patients. Using the TML and different sets of clinical variables (tumour stage, age, sex, smoking status, and packs of cigarettes smoked per year), we built Random Forest classification models that calculate the likelihood of developing metastasis.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>We found that LC patients different in age, smoking status, and tumour type had significantly different mean TMLs. Although TML was an informative feature, its effect was secondary to the "tumour stage" feature. However, its contribution to the classification is not redundant with the latter; models trained using both TML and tumour stage performed better than models trained using only one of these variables. We found that models trained in the entire dataset (i.e., without using dimensionality reduction techniques) and without resampling achieved the highest performance, with an F1 score of 0.64 (95%CrI [0.62, 0.66]).</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Clinical variables and TML should be considered together when assessing the likelihood of LC patients progressing to metastatic states, as the information these encode is not redundant. Altogether, we provide new evidence of the need for comprehensive diagnostic tools for metastasis.</jats:p> </jats:sec>
      2Scopus© Citations 3  1
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    Concordance Analysis of ALK Gene Fusion Detection Methods in Patients with Non–Small-Cell Lung Cancer from Chile, Brazil, and Peru
    (2021)
    Gonzalo Sepúlveda-Hermosilla
    ;
    Matías Freire
    ;
    Alejandro Blanco
    ;
    Javier Cáceres
    ;
    Rodrigo Lizana
      1Scopus© Citations 6
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    Clinical Experience With 75-mg Dose of Erlotinib for Mutated Metastatic EGFR Non-small Cell Lung Cancer
    (2019)
    Osvaldo Aren
    ;
    Suraj Samtani
    ;
    Micahel Frelinghuysen
    ;
    Mauricio Burotto
      2
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      3Scopus© Citations 7