A 3-gene signature comprising CDH4, STAT4 and EBV-encoded LMP1 for early diagnosis and predicting disease progression of nasopharyngeal carcinoma

Purpose Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies. Methods The transcriptomic data of primary NPC cell strains were use...

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Published inDiscover. Oncology Vol. 14; no. 1; pp. 119 - 14
Main Authors Liu, Shu-Chen, Wang, Chun-I, Liu, Tzu-Tung, Tsang, Ngan-Ming, Sui, Yun-Hua, Juang, Jyh-Lyh
Format Journal Article
LanguageEnglish
Published New York Springer US 01.07.2023
Springer Nature B.V
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Abstract Purpose Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies. Methods The transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis. Results Three genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells ( p  < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively. Conclusion A model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.
AbstractList Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies.PURPOSENasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies.The transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis.METHODSThe transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis.Three genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells (p < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively.RESULTSThree genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells (p < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively.A model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.CONCLUSIONA model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.
Purpose Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies. Methods The transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis. Results Three genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells ( p  < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively. Conclusion A model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.
Abstract Purpose Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies. Methods The transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis. Results Three genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells (p < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively. Conclusion A model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.
Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies. The transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis. Three genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells (p < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively. A model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.
PurposeNasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies.MethodsThe transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis.ResultsThree genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells (p < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively.ConclusionA model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.
ArticleNumber 119
Author Tsang, Ngan-Ming
Juang, Jyh-Lyh
Sui, Yun-Hua
Liu, Tzu-Tung
Liu, Shu-Chen
Wang, Chun-I
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Issue 1
Keywords Nasopharyngeal carcinoma
STAT4
EBV-encoded LMP1
CYLD
CDH4
Language English
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Snippet Purpose Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient...
Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular...
PurposeNasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient...
Abstract Purpose Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly...
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StartPage 119
SubjectTerms Accuracy
Biopsy
Cancer
Cancer Research
CDH4
CYLD
Discriminant analysis
EBV-encoded LMP1
Epstein-Barr virus
Genes
Infections
Internal Medicine
Lymphoma
Medical diagnosis
Medical prognosis
Medicine
Medicine & Public Health
Molecular Medicine
Nasopharyngeal carcinoma
Oncology
Pathogenesis
Patients
Proteins
Radiotherapy
Regression analysis
STAT4
Surgical Oncology
Throat cancer
Tumorigenesis
Tumors
Viral infections
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Title A 3-gene signature comprising CDH4, STAT4 and EBV-encoded LMP1 for early diagnosis and predicting disease progression of nasopharyngeal carcinoma
URI https://link.springer.com/article/10.1007/s12672-023-00735-x
https://www.ncbi.nlm.nih.gov/pubmed/37393410
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Volume 14
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