RESUMO
Epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancer (NSCLC) patients treated with EGFR-tyrosine kinase inhibitors (TKIs) inevitably develop resistance through several biological mechanisms. However, little is known on the molecular mechanisms underlying acquired resistance to suboptimal EGFR-TKI doses, due to pharmacodynamics leading to inadequate drug exposure. To evaluate the effects of suboptimal EGFR-TKI exposure on resistance in NSCLC, we obtained HCC827 and PC9 cell lines resistant to suboptimal fixed and intermittent doses of gefitinib and compared them to cells exposed to higher doses of the drug. We analyzed the differences in terms of EGFR signaling activation and the expression of epithelial-mesenchymal transition (EMT) markers, whole transcriptomes byRNA sequencing, and cell motility. We observed that the exposure to low doses of gefitinib more frequently induced a partial EMT associated with an induced migratory ability, and an enhanced transcription of cancer stem cell markers, particularly in the HCC827 gefitinib-resistant cells. Finally, the HCC827 gefitinib-resistant cells showed increased secretion of the EMT inducer transforming growth factor (TGF)-ß1, whose inhibition was able to partially restore gefitinib sensitivity. These data provide evidence that different levels of exposure to EGFR-TKIs in tumor masses might promote different mechanisms of acquired resistance.
Assuntos
Carcinoma Pulmonar de Células não Pequenas , Movimento Celular , Resistencia a Medicamentos Antineoplásicos , Transição Epitelial-Mesenquimal , Receptores ErbB , Gefitinibe , Neoplasias Pulmonares , Inibidores de Proteínas Quinases , Humanos , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Carcinoma Pulmonar de Células não Pequenas/metabolismo , Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma Pulmonar de Células não Pequenas/genética , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Receptores ErbB/metabolismo , Receptores ErbB/antagonistas & inibidores , Inibidores de Proteínas Quinases/farmacologia , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/genética , Gefitinibe/farmacologia , Transição Epitelial-Mesenquimal/efeitos dos fármacos , Linhagem Celular Tumoral , Movimento Celular/efeitos dos fármacos , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Antineoplásicos/farmacologia , Transdução de Sinais/efeitos dos fármacos , Fator de Crescimento Transformador beta1/metabolismoRESUMO
BACKGROUND: Although conflicting results emerged from different studies, the tumor mutational burden (TMB) appears as one of most reliable biomarkers of sensitivity to immune checkpoint inhibitors. Several laboratories are reporting TMB values when performing comprehensive genomic profiling (CGP) without providing a clinical interpretation, due to the lack of validated cut-off values. The International Quality Network for Pathology launched an initiative to harmonize TMB testing with CGP assay and favor the clinical implementation of this biomarker. METHODS: TMB evaluation was performed with three commercially available CGP panels, TruSight Oncology 500 (TSO500), Oncomine Comprehensive Plus Assay (OCA) and QIAseq Multimodal Panel (QIA), versus the reference assay FoundationOne CDx (F1CDx). Archived clinical samples derived from 60 patients with non-small cell lung cancer were used for TMB assessment. Adjusted cut-off values for each panel were calculated. RESULTS: Testing was successful for 91.7%, 100%, 96.7% and 100% of cases using F1CDx, TSO500, OCA and QIA, respectively. The matrix comparison analysis, between the F1CDx and CGP assays, showed a linear correlation for all three panels, with a higher correlation between F1CDx and TSO500 (rho=0.88) than in the other two comparisons (rho=0.77 for QIA; 0.72 for OCA). The TSO500 showed the best area under the curve (AUC, value 0.96), with a statistically significant difference when compared with the AUC of OCA (0.83, p value=0.01) and QIA (0.88, p value=0.028). The Youden Index calculation allowed us to extrapolate TMB cut-offs of the different panels corresponding to the 10 mutations/megabase (muts/Mb) cut-off of F1CDx: 10.19, 10.4 and 12.37 muts/Mb for TSO500, OCA and QIA, respectively. Using these values, we calculated the relative accuracy measures for the three panels. TSO500 showed 86% specificity and 96% sensitivity, while OCA and QIA had lower yet similar values of specificity and sensitivity (73% and 88%, respectively). CONCLUSION: This study estimated TMB cut-off values for commercially available CGP panels. The results showed a good performance of all panels on clinical samples and the calculated cut-offs support better accuracy measures for TSO500. The validated cut-off values can drive clinical interpretation of TMB testing in clinical research and clinical practice.