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Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics

BACKGROUND: To investigate the correlation between computed tomography (CT) radiomic characteristics and key genes for cervical lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC). METHODS: The region of interest was annotated at the edge of the primary tumor on enhanced CT images fro...

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Autores principales: Jin, Nenghao, Qiao, Bo, Zhao, Min, Li, Liangbo, Zhu, Liang, Zang, Xiaoyi, Gu, Bin, Zhang, Haizhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557859/
https://www.ncbi.nlm.nih.gov/pubmed/37635388
http://dx.doi.org/10.1002/cam4.6474
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author Jin, Nenghao
Qiao, Bo
Zhao, Min
Li, Liangbo
Zhu, Liang
Zang, Xiaoyi
Gu, Bin
Zhang, Haizhong
author_facet Jin, Nenghao
Qiao, Bo
Zhao, Min
Li, Liangbo
Zhu, Liang
Zang, Xiaoyi
Gu, Bin
Zhang, Haizhong
author_sort Jin, Nenghao
collection PubMed
description BACKGROUND: To investigate the correlation between computed tomography (CT) radiomic characteristics and key genes for cervical lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC). METHODS: The region of interest was annotated at the edge of the primary tumor on enhanced CT images from 140 patients with OSCC and obtained radiomic features. Ribonucleic acid (RNA) sequencing was performed on pathological sections from 20 patients. the DESeq software package was used to compare differential gene expression between groups. Weighted gene co‐expression network analysis was used to construct co‐expressed gene modules, and the KEGG and GO databases were used for pathway enrichment analysis of key gene modules. Finally, Pearson correlation coefficients were calculated between key genes of enriched pathways and radiomic features. RESULTS: Four hundred and eighty radiomic features were extracted from enhanced CT images of 140 patients; seven of these correlated significantly with cervical LNM in OSCC (p < 0.01). A total of 3527 differentially expressed RNAs were screened from RNA sequencing data of 20 cases. original_glrlm_RunVariance showed significant positive correlation with most long noncoding RNAs. CONCLUSIONS: OSCC cervical LNM is related to the salivary hair bump signaling pathway and biological process. Original_glrlm_RunVariance correlated with LNM and most differentially expressed long noncoding RNAs.
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spelling pubmed-105578592023-10-07 Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics Jin, Nenghao Qiao, Bo Zhao, Min Li, Liangbo Zhu, Liang Zang, Xiaoyi Gu, Bin Zhang, Haizhong Cancer Med Research Articles BACKGROUND: To investigate the correlation between computed tomography (CT) radiomic characteristics and key genes for cervical lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC). METHODS: The region of interest was annotated at the edge of the primary tumor on enhanced CT images from 140 patients with OSCC and obtained radiomic features. Ribonucleic acid (RNA) sequencing was performed on pathological sections from 20 patients. the DESeq software package was used to compare differential gene expression between groups. Weighted gene co‐expression network analysis was used to construct co‐expressed gene modules, and the KEGG and GO databases were used for pathway enrichment analysis of key gene modules. Finally, Pearson correlation coefficients were calculated between key genes of enriched pathways and radiomic features. RESULTS: Four hundred and eighty radiomic features were extracted from enhanced CT images of 140 patients; seven of these correlated significantly with cervical LNM in OSCC (p < 0.01). A total of 3527 differentially expressed RNAs were screened from RNA sequencing data of 20 cases. original_glrlm_RunVariance showed significant positive correlation with most long noncoding RNAs. CONCLUSIONS: OSCC cervical LNM is related to the salivary hair bump signaling pathway and biological process. Original_glrlm_RunVariance correlated with LNM and most differentially expressed long noncoding RNAs. John Wiley and Sons Inc. 2023-08-27 /pmc/articles/PMC10557859/ /pubmed/37635388 http://dx.doi.org/10.1002/cam4.6474 Text en © 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Jin, Nenghao
Qiao, Bo
Zhao, Min
Li, Liangbo
Zhu, Liang
Zang, Xiaoyi
Gu, Bin
Zhang, Haizhong
Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics
title Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics
title_full Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics
title_fullStr Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics
title_full_unstemmed Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics
title_short Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics
title_sort predicting cervical lymph node metastasis in oscc based on computed tomography imaging genomics
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557859/
https://www.ncbi.nlm.nih.gov/pubmed/37635388
http://dx.doi.org/10.1002/cam4.6474
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