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BACKGROUND: CD155 is a transmembrane protein that inhibits antitumor immune response and represents a predictor of worse prognosis in non-small-cell lung cancer (NSCLC). However, it remains unexplored its association with clinical characteristics and genomic status of Latin American patients. This study characterizes the CD155 expression and its clinical implications in this population. METHODS: Tissue biopsies from 86 patients with locally-advanced or metastatic NSCLC were assessed for CD155 protein expression, ALK rearrangements and EGFR mutations. Cutoff values for high CD155 expression (CD155high) were determined from receiver operating characteristic (ROC) curves according to 2-year survival. It was evaluated its association with clinicopathological features, median progression-free survival (mPFS) and overall survival (mOS). RESULTS: the cutoff score for CD155high was 155 in the entire cohort and in patients without oncogenic alterations, and it was 110 in patients with oncogenic alterations. Eighty-four patients (97.7%) were CD155 positive, of which fifty-six (65.0%) had CD155high. EGFR L858R mutation related to lower CD155 IHC score than exon 19 deletion. Individuals with CD155high showed a shorter mOS (13.0 vs. 30.8 months; HR: 1.96 [95% CI, 1.15-3.35]; p = 0.014). Patients without oncogenic alterations having a CD155high displayed shorter mPFS (1.6 vs. 6.4 months, HR: 2.09 [95% CI, 1.06-4.20]; p = 0.034) and mOS (2.9 vs. 23.1 months; HR: 1.27 [95% CI, 1.07- 4.42]; p = 0.032). Patients with oncogenic alterations having CD155high only showed a trend to shorter mOS (26.3 vs. 52.0 months; HR: 2.39 [95% CI, 0.98-5.83]; p = 0.058). CONCLUSION: CD155high is a predictor of worse outcomes in patients with advanced NSCLC, predominantly among those without oncogenic alterations. CD155 could be a potential biomarker and a molecular target in patients with poor responses to current therapies.
Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Receptores Virais , Humanos , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma Pulmonar de Células não Pequenas/metabolismo , Masculino , Feminino , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/metabolismo , Pessoa de Meia-Idade , Prognóstico , Idoso , Receptores Virais/genética , Receptores Virais/metabolismo , Mutação/genética , Adulto , Receptores ErbB/metabolismo , Receptores ErbB/genética , Idoso de 80 Anos ou mais , Curva ROCRESUMO
INTRODUCTION: Lung cancer in never-smoker (LCINS) patients accounts for 20% of lung cancer cases, and its biology remains poorly understood, particularly in genetically admixed populations. We elucidated the molecular profile of driver genes in Brazilian LCINS. METHODS: The mutational and gene fusion status of 119 lung adenocarcinomas from self-reported never-smoker patients, was assessed using targeted sequencing (NGS), nCounter, and immunohistochemistry. A panel of 46 ancestry-informative markers determined patients' genetic ancestry. RESULTS: The most frequently mutated gene was EGFR (49.6%), followed by TP53 (39.5%), ALK (12.6%), ERBB2 (7.6%), KRAS (5.9%), PIK3CA (1.7%), and less than 1% alterations in RET, NTRK1, MET∆ex14, PDGFRA, and BRAF. Except for TP53 and PIK3CA, all other alterations were mutually exclusive. Genetic ancestry analysis revealed a predominance of European (71.1%), and a higher African ancestry was associated with TP53 mutations. CONCLUSION: Brazilian LCINS exhibited a similar molecular profile to other populations, except the increased ALK and TP53 alterations. Importantly, 73% of these patients have actionable alterations that are suitable for targeted treatments.
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Adenocarcinoma de Pulmão , Neoplasias Pulmonares , Mutação , Humanos , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/patologia , Adenocarcinoma de Pulmão/tratamento farmacológico , Masculino , Feminino , Brasil/epidemiologia , Pessoa de Meia-Idade , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Idoso , Adulto , Terapia de Alvo Molecular , Idoso de 80 Anos ou mais , Biomarcadores Tumorais/genéticaRESUMO
BACKGROUND: Programmed death ligand-1 (PD-L1) expression is a well-known predictive biomarker of response to immune checkpoint blockade in non-small cell lung cancer (NSCLC). However, there is limited evidence of the relationship between PD-L1 expression, clinicopathological features, and their association with major driver mutations in NSCLC patients in Latin America. METHODS: This retrospective study included patients from Argentina with advanced NSCLC, and centralized evaluation of PD-L1 expression concurrently with genomic alterations in the driver genes EGFR, ALK, ROS1, BRAF, and/or KRAS G12C in FFPE tissue samples. RESULTS: A total of 10 441 patients with advanced NSCLC were analyzed. Adenocarcinoma was the most frequent histological subtype (71.1%). PD-L1 expression was categorized as PD-L1 negative (45.1%), PD-L1 positive low-expression 1%-49% (32.3%), and PD-L1 positive high-expression ≥50% (22.6%). Notably, current smokers and males were more likely to have tumors with PD-L1 tumor proportion score (TPS) ≥50% and ≥ 80% expression, respectively (p < 0.001 and p = 0.013). Tumors with non-adenocarcinoma histology had a significantly higher median PD-L1 expression (p < 0.001). Additionally, PD-L1 in distant nodes was more likely ≥50% (OR 1.60 [95% CI: 1.14-2.25, p < 0.01]). In the multivariate analysis, EGFR-positive tumors were more commonly associated with PD-L1 low expression (OR 0.62 [95% CI: 0.51-0.75], p < 0.01), while ALK-positive tumors had a significant risk of being PD-L1 positive (OR 1.81 [95% CI: 1.30-2.52], p < 0.01). CONCLUSIONS: PD-L1 expression was associated with well-defined clinicopathological and genomic features. These findings provide a comprehensive view of the expression of PD-L1 in patients with advanced NSCLC in a large Latin American cohort.
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Adenocarcinoma , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Masculino , Humanos , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/patologia , Proteínas Tirosina Quinases/genética , Antígeno B7-H1/genética , Antígeno B7-H1/metabolismo , Estudos Retrospectivos , Quinase do Linfoma Anaplásico/genética , Proteínas Proto-Oncogênicas/genética , Adenocarcinoma/genética , Mutação , Receptores ErbB/genéticaRESUMO
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 ß-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.
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Neoplasias Pulmonares , Fosfatidilinositol 3-Quinases , Humanos , Fosfatidilinositol 3-Quinases/metabolismo , Proteínas Proto-Oncogênicas c-met/metabolismo , Neoplasias Pulmonares/patologia , Éxons , Transdução de SinaisRESUMO
Identifying the genes and mutations that drive the emergence of tumors is a critical step to improving our understanding of cancer and identifying new directions for disease diagnosis and treatment. Despite the large volume of genomics data, the precise detection of driver mutations and their carrying genes, known as cancer driver genes, from the millions of possible somatic mutations remains a challenge. Computational methods play an increasingly important role in discovering genomic patterns associated with cancer drivers and developing predictive models to identify these elements. Machine learning (ML), including deep learning, has been the engine behind many of these efforts and provides excellent opportunities for tackling remaining gaps in the field. Thus, this survey aims to perform a comprehensive analysis of ML-based computational approaches to identify cancer driver mutations and genes, providing an integrated, panoramic view of the broad data and algorithmic landscape within this scientific problem. We discuss how the interactions among data types and ML algorithms have been explored in previous solutions and outline current analytical limitations that deserve further attention from the scientific community. We hope that by helping readers become more familiar with significant developments in the field brought by ML, we may inspire new researchers to address open problems and advance our knowledge towards cancer driver discovery.
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Biologia Computacional , Neoplasias , Algoritmos , Biologia Computacional/métodos , Humanos , Aprendizado de Máquina , Mutação , Neoplasias/diagnóstico , Neoplasias/genética , Neoplasias/patologia , OncogenesRESUMO
Background: Next-generation sequencing (NGS) based assay for finding an actionable driver in non-small-cell lung cancer is a less used modality in clinical practice. With a long list of actionable targets, limited tissue, arduous single-gene assays, the alternative of NGS for broad testing in one experiment looks attractive. We report here our experience with NGS for biomarker testing in hundred advanced lung cancer patients. Methods: Predictive biomarker testing was performed using the Ion AmpliSeq™ Cancer Hotspot Panel V2 (30 tumors) and Oncomine™ Solid Tumor DNA and Oncomine™ Solid Tumor Fusion Transcript kit (70 tumors) on IonTorrent sequencing platform. Results: One-seventeen distinct aberrations were detected across 29 genes in eighty-six tumors. The most commonly mutated genes were TP53 (43% cases), EGFR (23% cases) and KRAS (17% cases). Thirty-four patients presented an actionable genetic variant for which targeted therapy is presently available, and fifty-two cases harbored non-actionable variants with the possibility of recruitment in clinical trials. NGS results were validated by individual tests for detecting EGFR mutation, ALK1 rearrangement, ROS1 fusion, and c-MET amplification. Compared to single test, NGS exhibited good agreement for detecting EGFR mutations and ALK1 fusion (sensitivity- 88.89%, specificity- 100%, Kappa-score 0.92 and sensitivity- 80%, specificity- 100%, Kappa-score 0.88; respectively). Further, the response of patients harboring tyrosine kinase inhibitor (TKI) sensitizing EGFR mutations was assessed. The progression-free-survival of EGFR positive patients on TKI therapy, harboring a concomitant mutation in PIK3CAmTOR and/or RAS-RAF-MAPK pathway gene and/or TP53 gene was inferior to those with sole-sensitizing EGFR mutation (2 months vs. 9.5 months, P = 0.015). Conclusions: This is the first study from South Asia looking into the analytical validity of NGS and describing the mutational landscape of lung cancer patients to study the impact of co-mutations on cancer biology and treatment outcome. Our study demonstrates the clinical utility of NGS testing for identifying actionable variants and making treatment decisions in advanced lung cancer
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Humanos , Masculino , Feminino , Proto-Oncogenes/genética , Biomarcadores Tumorais/genética , Carcinoma Pulmonar de Células não Pequenas/genética , Sequenciamento de Nucleotídeos em Larga Escala , Neoplasias Pulmonares/genética , Mutação/genética , Reprodutibilidade dos TestesRESUMO
Cancer is a complex disease caused by the accumulation of genetic alterations during the individual's life. Such alterations are called genetic mutations and can be divided into two groups: (1) Passenger mutations, which are not responsible for cancer and (2) Driver mutations, which are significant for cancer and responsible for its initiation and progression. Cancer cells undergo a large number of mutations, of which most are passengers, and few are drivers. The identification of driver mutations is a key point and one of the biggest challenges in Cancer Genomics. Many computational methods for such a purpose have been developed in Cancer Bioinformatics. Such computational methods are complex and are usually described in a high level of abstraction. This tutorial details some classical computational methods, from a computational perspective, with the transcription in an algorithmic format towards an easy access by researchers.
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Biologia Computacional/métodos , Genômica/métodos , Mutação , Neoplasias/genética , Algoritmos , Redes Reguladoras de Genes , HumanosRESUMO
Objectives: Approximately 60% of lung adenocarcinomas (LAs) carry mutations that can guide treatment with tyrosine-kinase inhibitors (TKI) and other targeted therapies. Data on activating mutations in EGFR and other tyrosine-kinase receptor (TKR) genes in highly admixed populations, such as that of Brazil, are scarce. In this study, we comprehensively analyzed the actionable alteration profile of LA in Brazilian patients. Materials and Methods: EGFR driver mutation data were collected from a large Brazilian LA cohort covering an 8-year period of molecular testing in a single institution. Tests were performed using three distinct methods, and demographic and histopathological data were analyzed. For a subset of patients, driver mutations in KRAS, NRAS, and BRAF and gene fusions involving TKR genes (before TKI treatment) and EGFR T790M (after TKI treatment) were assessed. Results: EGFR mutations were detected in 25% of 1,316 LAs evaluated, with exon 19 deletions and exon 21 L858R TKI sensitizing mutations representing 72.5% of all mutations. Mutation rates were higher in women and non-smokers (p < 0.001). Next-generation sequencing was very sensitive, with a lower rate of inconclusive results compared with Sanger sequencing and pyrosequencing. EGFR/RAS/BRAF hotspot gene panels were applied in 495 LA cases and detected oncogenic mutations in 51.3% of samples, most frequently in EGFR (22.4%) and KRAS (26.9%). In subgroups of 36 and 35 patients, gene fusions were detected in 11.1% of tumors and EGFR T790M resistance mutations were detected in 59% of plasma samples from patients previously treated with TKI, respectively. Conclusion: This report provides the first comprehensive actionable alteration portrait of LA in Brazil. The high rate of actionable alterations in EGFR and other driver genes in LA reinforces the need to incorporate TKI guided by molecular diagnostics into clinical routines for patients in both public and private healthcare systems.
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O câncer de pulmão não pequenas células (CPNPC) foi durante muito tempo descrito como uma única doença. A partir do maior conhecimento dos mecanismos de carcinogênese e dos avanços da biologia molecular, foram identificados subtipos moleculares específicos. Essas alterações moleculares são consideradas condutoras (drivers), quando são capazes de guiar o comportamento clínico dos tumores. Com esse conhecimento novas drogas foram desenvolvidas, capazes de inibir a ativação dessas proteínas mutantes. O primeiro exemplo de sucesso foi visto com os inibidores de tirosina quinase de EGFR, em pacientes com a presença de mutações específicas nesse gene. A partir daí muitas outras alterações vem sendo descritas e deparamo-nos com os benefícios clínicos impressionantes da medicina de precisão.
Non-small cell lung cancer has long been described as a unique disease. Since the last advances and better understanding of carcinogenesis mechanisms and molecular biology, specific molecular subtypes have been identified. These alterations are considered drivers, when they guide tumor clinical behavior. After driver mutations identification, new drugs have been developed to inhibit the activation of these mutant proteins. The first successful example was seen with tyrosine kinase EGFR inhibitors in patients with positive specific mutations in this gene. After this discovery many other molecular subtypes have been described and are resulting on these impressive clinical benefits from precision medicine.
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Humanos , Masculino , Feminino , Terapia de Alvo Molecular , Neoplasias Pulmonares/classificação , Neoplasias Pulmonares/terapiaRESUMO
El síndrome de Marfan (SM) es un trastorno sistémico causado por mutaciones en la proteína de la matriz extracelular fibrilina 1 (FBN1). Con un patrón de herencia autosómico dominante, los pacientes se caracterizan por presentar compromiso ocular, cardiovascular y esquelético dentro de un espectro clínico variable. Se ha sugerido que la variabilidad fenotípica intrafamiliar e interfamiliar característica del síndrome ocurre por la asociación de otras mutaciones denominadas modificadoras (driver mutations). Si bien hay claridad acerca de la causalidad genética clásica de la enfermedad, las mutaciones modificadoras descritas recientemente aún no están bien dilucidadas. Se presenta un caso de SM con una mutación no descrita previamente en el gen de la fibrilina 1; se aplica la nosología de Ghent revisada y se analiza el papel de esta mutación nueva y de las mutaciones modificadoras en la génesis de la enfermedad.
Marfan syndrome (MS) is a systemic disorder caused by mutations in the extracellular matrix protein fibrillin 1 (FBN1). With a dominant autosomal pattern, MS patients are characterized by ocular, cardiovascular and skeletal involvement, all within a variable clinical spectrum. It has been suggested that the intrafamilial and interfamilial phenotypic variability, characteristic of the syndrome, occurs by the association of other mutations called driver mutations. Even though there is a clear genetic causation, the recently described driver mutations are not yet fully elucidated. We present a MS case with a mutation not previously described in the fibrilin 1 gene, applying the revised Ghent nosology and analyzing the role of this new mutation and of the driver mutations in the genesis of the disease.