Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors
Background: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcin...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-08-01
|
| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.944167/full |
| _version_ | 1828254312529133568 |
|---|---|
| author | Juxuan Zhang Jiaxing Deng Xiao Feng Yilong Tan Xin Li Yixin Liu Mengyue Li Haitao Qi Lefan Tang Qingwei Meng Haidan Yan Lishuang Qi |
| author_facet | Juxuan Zhang Jiaxing Deng Xiao Feng Yilong Tan Xin Li Yixin Liu Mengyue Li Haitao Qi Lefan Tang Qingwei Meng Haidan Yan Lishuang Qi |
| author_sort | Juxuan Zhang |
| collection | DOAJ |
| description | Background: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) belonging to non-NE tumors. This study aims to identify a transcriptional panel that could distinguish the histological subtypes of NE tumors to complement the morphology-based classification of an individual.Methods: A public dataset with NE subtypes, including 21 small-cell lung cancer (SCLC), 56 large-cell NE carcinomas (LCNECs), and 24 carcinoids (CARCIs), and non-NE subtypes, including 85 ADC and 61 SCC, was used as a training set. In the training set, consensus clustering was first used to filter out the samples whose expression patterns disagreed with their histological subtypes. Then, a rank-based method was proposed to develop a panel of transcriptional signatures for determining the NE subtype for an individual, based on the within-sample relative gene expression orderings of gene pairs. Twenty-three public datasets with a total of 3,454 samples, which were derived from fresh-frozen, formalin-fixed paraffin-embedded, biopsies, and single cells, were used for validation. Clinical feasibility was tested in 10 SCLC biopsy specimens collected from cancer hospitals via bronchoscopy.Results: The NEsubtype-panel was composed of three signatures that could distinguish NE from non-NE, CARCI from non-CARCI, and SCLC from LCNEC step by step and ultimately determine the histological subtype for each NE sample. The three signatures achieved high average concordance rates with 97.31%, 98.11%, and 90.63%, respectively, in the 23 public validation datasets. It is worth noting that the 10 clinic-derived SCLC samples diagnosed via immunohistochemical staining were also accurately predicted by the NEsubtype-panel. Furthermore, the subtype-specific gene expression patterns and survival analyses provided evidence for the rationality of the reclassification by the NEsubtype-panel.Conclusion: The rank-based NEsubtype-panel could accurately distinguish lung NE from non-NE tumors and determine NE subtypes even in clinically challenging samples (such as biopsy). The panel together with our previously reported signature (KRT5-AGR2) for SCC and ADC would be an auxiliary test for the histological diagnosis of lung cancer. |
| first_indexed | 2024-04-13T01:57:10Z |
| format | Article |
| id | doaj.art-69490701a4a548b481ee1444d95f1554 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-13T01:57:10Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-69490701a4a548b481ee1444d95f15542022-12-22T03:07:44ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-08-011310.3389/fgene.2022.944167944167Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumorsJuxuan Zhang0Jiaxing Deng1Xiao Feng2Yilong Tan3Xin Li4Yixin Liu5Mengyue Li6Haitao Qi7Lefan Tang8Qingwei Meng9Haidan Yan10Lishuang Qi11College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaBasic Medicine College, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, ChinaDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaBackground: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) belonging to non-NE tumors. This study aims to identify a transcriptional panel that could distinguish the histological subtypes of NE tumors to complement the morphology-based classification of an individual.Methods: A public dataset with NE subtypes, including 21 small-cell lung cancer (SCLC), 56 large-cell NE carcinomas (LCNECs), and 24 carcinoids (CARCIs), and non-NE subtypes, including 85 ADC and 61 SCC, was used as a training set. In the training set, consensus clustering was first used to filter out the samples whose expression patterns disagreed with their histological subtypes. Then, a rank-based method was proposed to develop a panel of transcriptional signatures for determining the NE subtype for an individual, based on the within-sample relative gene expression orderings of gene pairs. Twenty-three public datasets with a total of 3,454 samples, which were derived from fresh-frozen, formalin-fixed paraffin-embedded, biopsies, and single cells, were used for validation. Clinical feasibility was tested in 10 SCLC biopsy specimens collected from cancer hospitals via bronchoscopy.Results: The NEsubtype-panel was composed of three signatures that could distinguish NE from non-NE, CARCI from non-CARCI, and SCLC from LCNEC step by step and ultimately determine the histological subtype for each NE sample. The three signatures achieved high average concordance rates with 97.31%, 98.11%, and 90.63%, respectively, in the 23 public validation datasets. It is worth noting that the 10 clinic-derived SCLC samples diagnosed via immunohistochemical staining were also accurately predicted by the NEsubtype-panel. Furthermore, the subtype-specific gene expression patterns and survival analyses provided evidence for the rationality of the reclassification by the NEsubtype-panel.Conclusion: The rank-based NEsubtype-panel could accurately distinguish lung NE from non-NE tumors and determine NE subtypes even in clinically challenging samples (such as biopsy). The panel together with our previously reported signature (KRT5-AGR2) for SCC and ADC would be an auxiliary test for the histological diagnosis of lung cancer.https://www.frontiersin.org/articles/10.3389/fgene.2022.944167/fullrelative gene expression orderingstranscriptional signaturesindividualizationhistological classificationlung neuroendocrine tumors |
| spellingShingle | Juxuan Zhang Jiaxing Deng Xiao Feng Yilong Tan Xin Li Yixin Liu Mengyue Li Haitao Qi Lefan Tang Qingwei Meng Haidan Yan Lishuang Qi Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors Frontiers in Genetics relative gene expression orderings transcriptional signatures individualization histological classification lung neuroendocrine tumors |
| title | Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors |
| title_full | Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors |
| title_fullStr | Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors |
| title_full_unstemmed | Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors |
| title_short | Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors |
| title_sort | hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors |
| topic | relative gene expression orderings transcriptional signatures individualization histological classification lung neuroendocrine tumors |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.944167/full |
| work_keys_str_mv | AT juxuanzhang hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT jiaxingdeng hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT xiaofeng hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT yilongtan hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT xinli hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT yixinliu hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT mengyueli hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT haitaoqi hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT lefantang hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT qingweimeng hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT haidanyan hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors AT lishuangqi hierarchicalidentificationofatranscriptionalpanelforthehistologicaldiagnosisoflungneuroendocrinetumors |