Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data
The likelihood of being diagnosed with thyroid cancer has increased in recent years; it is the fastest-expanding cancer in the United States and it has tripled in the last three decades. In particular, Papillary Thyroid Carcinoma (PTC) is the most common type of cancer affecting the thyroid. It is a...
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MDPI AG
2023-06-01
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| Series: | Genes |
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| Online Access: | https://www.mdpi.com/2073-4425/14/6/1250 |
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| author | Iván Petrini Rocío L. Cecchini Marilina Mascaró Ignacio Ponzoni Jessica A. Carballido |
| author_facet | Iván Petrini Rocío L. Cecchini Marilina Mascaró Ignacio Ponzoni Jessica A. Carballido |
| author_sort | Iván Petrini |
| collection | DOAJ |
| description | The likelihood of being diagnosed with thyroid cancer has increased in recent years; it is the fastest-expanding cancer in the United States and it has tripled in the last three decades. In particular, Papillary Thyroid Carcinoma (PTC) is the most common type of cancer affecting the thyroid. It is a slow-growing cancer and, thus, it can usually be cured. However, given the worrying increase in the diagnosis of this type of cancer, the discovery of new genetic markers for accurate treatment and prognostic is crucial. In the present study, the aim is to identify putative genes that may be specifically relevant in PTC through bioinformatic analysis of several gene expression public datasets and clinical information. Two datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) dataset were studied. Statistics and machine learning methods were sequentially employed to retrieve a final small cluster of genes of interest: <i>PTGFR</i>, <i>ZMAT3</i>, <i>GABRB2</i>, and <i>DPP6</i>. Kaplan–Meier plots were employed to assess the expression levels regarding overall survival and relapse-free survival. Furthermore, a manual bibliographic search for each gene was carried out, and a Protein–Protein Interaction (PPI) network was built to verify existing associations among them, followed by a new enrichment analysis. The results revealed that all the genes are highly relevant in the context of thyroid cancer and, more particularly interesting, <i>PTGFR</i> and <i>DPP6</i> have not yet been associated with the disease up to date, thus making them worthy of further investigation as to their relationship to PTC. |
| first_indexed | 2024-03-11T02:25:38Z |
| format | Article |
| id | doaj.art-a90c7dae49ea4e1aa6b8e1ca10ac71a9 |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-11T02:25:38Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-a90c7dae49ea4e1aa6b8e1ca10ac71a92023-11-18T10:34:53ZengMDPI AGGenes2073-44252023-06-01146125010.3390/genes14061250Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical DataIván Petrini0Rocío L. Cecchini1Marilina Mascaró2Ignacio Ponzoni3Jessica A. Carballido4Department of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca 8000, ArgentinaDepartment of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca 8000, ArgentinaDepartamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur, Bahía Blanca 8000, ArgentinaDepartment of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca 8000, ArgentinaDepartment of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca 8000, ArgentinaThe likelihood of being diagnosed with thyroid cancer has increased in recent years; it is the fastest-expanding cancer in the United States and it has tripled in the last three decades. In particular, Papillary Thyroid Carcinoma (PTC) is the most common type of cancer affecting the thyroid. It is a slow-growing cancer and, thus, it can usually be cured. However, given the worrying increase in the diagnosis of this type of cancer, the discovery of new genetic markers for accurate treatment and prognostic is crucial. In the present study, the aim is to identify putative genes that may be specifically relevant in PTC through bioinformatic analysis of several gene expression public datasets and clinical information. Two datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) dataset were studied. Statistics and machine learning methods were sequentially employed to retrieve a final small cluster of genes of interest: <i>PTGFR</i>, <i>ZMAT3</i>, <i>GABRB2</i>, and <i>DPP6</i>. Kaplan–Meier plots were employed to assess the expression levels regarding overall survival and relapse-free survival. Furthermore, a manual bibliographic search for each gene was carried out, and a Protein–Protein Interaction (PPI) network was built to verify existing associations among them, followed by a new enrichment analysis. The results revealed that all the genes are highly relevant in the context of thyroid cancer and, more particularly interesting, <i>PTGFR</i> and <i>DPP6</i> have not yet been associated with the disease up to date, thus making them worthy of further investigation as to their relationship to PTC.https://www.mdpi.com/2073-4425/14/6/1250gene expression analysisthyroid cancermicroarray gene expression dataRNA-seq gene expression dataGEOTCGA |
| spellingShingle | Iván Petrini Rocío L. Cecchini Marilina Mascaró Ignacio Ponzoni Jessica A. Carballido Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data Genes gene expression analysis thyroid cancer microarray gene expression data RNA-seq gene expression data GEO TCGA |
| title | Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data |
| title_full | Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data |
| title_fullStr | Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data |
| title_full_unstemmed | Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data |
| title_short | Papillary Thyroid Carcinoma: A thorough Bioinformatic Analysis of Gene Expression and Clinical Data |
| title_sort | papillary thyroid carcinoma a thorough bioinformatic analysis of gene expression and clinical data |
| topic | gene expression analysis thyroid cancer microarray gene expression data RNA-seq gene expression data GEO TCGA |
| url | https://www.mdpi.com/2073-4425/14/6/1250 |
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