Data documento
06/05/2024

Título
Comprehensive Molecular Landscape of Cetuximab Resistance in Head and Neck Cancer Cell Lines

Autor(es)
Gomes I.N.F. - da Silva-Oliveira R.J. - da Silva L.S. - Martinho O. - Evangelista A.F. - van Helvoort Lengert A. - Leal L.F. - Silva V.A.O. - Dos Santos S.P. - Nascimento F.C. - Lopes Carvalho A. - Reis R.M.

Palavras chave
EGFR - biomarkers - cetuximab - drug resistance - head and neck tumors - in vitro - pre-clinical

Resumo
Cetuximab is the sole anti-EGFR monoclonal antibody that is FDA approved to treat head and neck squamous cell carcinoma (HNSCC). However, no predictive biomarkers of cetuximab response are known for HNSCC. Herein, we address the molecular mechanisms underlying cetuximab resistance in an in vitro model. We established a cetuximab resistant model (FaDu), using increased cetuximab concentrations for more than eight months. The resistance and parental cells were evaluated for cell viability and functional assays. Protein expression was analyzed by Western blot and human cell surface panel by lyoplate. The mutational profile and copy number alterations (CNA) were analyzed using whole-exome sequencing (WES) and the NanoString platform. FaDu resistant clones exhibited at least two-fold higher IC50 compared to the parental cell line. WES showed relevant mutations in several cancer-related genes, and the comparative mRNA expression analysis showed 36 differentially expressed genes associated with EGFR tyrosine kinase inhibitors resistance, RAS, MAPK, and mTOR signaling. Importantly, we observed that overexpression of KRAS, RhoA, and CD44 was associated with cetuximab resistance. Protein analysis revealed EGFR phosphorylation inhibition and mTOR increase in resistant cells. Moreover, the resistant cell line demonstrated an aggressive phenotype with a significant increase in adhesion, the number of colonies, and migration rates. Overall, we identified several molecular alterations in the cetuximab resistant cell line that may constitute novel biomarkers of cetuximab response such as mTOR and RhoA overexpression. These findings indicate new strategies to overcome anti-EGFR resistance in HNSCC.

Citação
Gomes INF, da Silva-Oliveira RJ, da Silva LS, Martinho O, Evangelista AF, van Helvoort Lengert A, Leal LF, Silva VAO, Dos Santos SP, Nascimento FC, Lopes Carvalho A, Reis RM. Comprehensive Molecular Landscape of Cetuximab Resistance in Head and Neck Cancer Cell Lines. Cells. 2022 Jan 4;11(1):154. doi: 10.3390/cells11010154. PMID: 35011716; PMCID: PMC8750399.

Data documento
03/05/2024

Título
Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Autor(es)
Casagrande GMS, - Silva MO, - Reis RM, - Leal LF.

Palavras chave
biomarkers - liquid biopsy - lung cancer - precision medicine

Resumo
Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

Citação
Casagrande GMS, Silva MO, Reis RM, Leal LF. Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs. Int J Mol Sci. 2023 Jan 28;24(3):2505. doi: 10.3390/ijms24032505. PMID: 36768828; PMCID: PMC9917347.

Data documento
02/05/2024

Título
The digital expression profile of BMP7, CDKN2C, HIST1H3G, and PKMYT1 genes improves high‐grade cervical lesion detection in liquid‐based cytology

Autor(es)
Causin RL, - Sussuchi da Silva L, - Leal LF, - Possati-Resende JC, - Evangelista AF, - Matsushita GM, - Scapulatempo-Neto C, - Tavares Guerreiro Fregnani JH, - Antônio de Oliveira M, - Musselwhite LW, - Chiquitelli Marques MM, - Reis RM.

Palavras chave
biomarkers - cervical cancer - cervical intraepithelial neoplasia - gene expression - liquid‐based cytology

Resumo
Background: Some studies reported that differential gene expression could be used as a biomarker for high‐grade cervical lesion identification. The aim was to evaluate the gene expression profile of cervical intraepithelial neoplasia (CIN) to identify a gene expression signature of CIN2+ in liquid‐based cytology (LBC) samples. Methods: LBC samples (n = 85) obtained from women who underwent colposcopy were included with benign (n = 13), CIN1 (n = 26), CIN2 (n = 16), and CIN3 (n = 30) diagnoses. After RNA isolation, gene expression profiling was performed using the nCounter PanCancer Pathways, which consists of 730 cancer‐related genes. The genes identified were in silico expression evaluated using the UALCAN database. An accurate prediction model to discriminate CIN2+ from

Descrição

Citação
Causin RL, Sussuchi da Silva L, Leal LF, Possati-Resende JC, Evangelista AF, Matsushita GM, Scapulatempo-Neto C, Tavares Guerreiro Fregnani JH, Antônio de Oliveira M, Musselwhite LW, Chiquitelli Marques MM, Reis RM. The digital expression profile of BMP7, CDKN2C, HIST1H3G, and PKMYT1 genes improves high-grade cervical lesion detection in liquid-based cytology. Cancer Cytopathol. 2023 Jul;131(7):454-464. doi: 10.1002/cncy.22704. Epub 2023 Apr 17. PMID: 37069588.