Data documento
07/05/2024

Título
Significance of Chr9p22.1-p21.3 Deletion in Cancer Development: A Pan-cancer In Silico Analysis

Autor(es)
Gonçalves PG, Reis RM, Bidinotto LT.

Palavras chave
locus - In silico analysis - TCGA - gene expression - prognostic value

Resumo
Background/aim: Deletions in chr9p22.1-21.3 locus have been related to the development of several types of cancer, mainly due to the presence of CDKN2A and CDKN2B genes. However, there are several other genes in the region with potential importance in tumorigenesis. We, therefore, aimed to analyze in silico the potential prognostic significance of alterations in copy number and expression of genes present in the chr9p22.1-21.3 locus in 33 TCGA datasets (approximately 10,000 patients). Materials and methods: We analyzed which of the 27 genes are expressed in the datasets. Additionally, we associated the deletion of the locus with survival (log rank analysis) and hazard ratio (HR) (univariate cox regression). Finally, we performed univariate, multivariate, and overall survival analyses in 13 datasets considering the expression of 10 genes present in the locus. Results: We identified 10 genes of the chr9p22.1-21.3 locus expressed in the datasets (MLLT3, FOCAD, PTPLAD2, KLHL9, IFNE, MTAP, CDKN2A, CDKN2B, DMRTA1 and ELAVL2). Moreover, we found that deletion in at least 1 of these genes was associated with poor survival and increased HR in 13 datasets: adrenocortical carcinoma (ACC), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), low-grade glioma (LGG), lung adenocarcinoma (LUAD), mesothelioma (MESO), pancreatic adenocarcinoma (PAAD), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), sarcoma (SARC) and uterine corpus endometrial carcinoma (UCEC). Finally, we found an association of survival/HR and altered expression of MLLT3 in the MESO dataset, of FOCAD in the READ dataset, of PTPLAD2 in the KIRP dataset, of KLHL9 in the LGG and UCEC datasets, of IFNE in ACC, GBM, KIRC and LUAD datasets, of MTAP in LGG, LUAD and MESO datasets, of CDKN2A in the HNSC, KIRC and MESO datasets, of CDKN2B in the LGG and READ datasets, of DMRTA1 in SARC datasets and of ELAVL2 in the LGG dataset (p<0.01 for all associations). Conclusion: Besides CDKN2A and CDKN2B, numerous other genes are possibly related to cancer development, requiring further investigation.

Citação
Gonçalves PG, Reis RM, Bidinotto LT. Significance of Chr9p22.1-p21.3 Deletion in Cancer Development: A Pan-cancer In Silico Analysis. Anticancer Res. 2022 Nov;42(11):5291-5304. doi: 10.21873/anticanres.16036. PMID: 36288884.

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.