Identification of key genes associated with progression and prognosis for lung squamous cell carcinoma

Ma, Xu; Ren, Hongyi; Peng, Ruoyu; Li, Yi; Ming, Liang

doi:10.7717/peerj.9086

Cited by 17 publications

(13 citation statements)

References 51 publications

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“…More and more attention has been recently paid to the key role of gene signatures based on specific correlation in predicting the prognosis of LUAD because of the rapid advances in high-throughput technologies and bioinformatics methodology [ 30 – 33 ]. Moreover, the identification of novel gene signatures that predict the prognosis of patients is beneficial for the choice of treatment regimens and the improvement of survival rate [ 34 , 35 ].…”

Section: Discussionmentioning

confidence: 99%

Establishment and validation of a prognostic signature for lung adenocarcinoma based on metabolism‐related genes

et al. 2021

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Background Given that dysregulated metabolism has been recently identified as a hallmark of cancer biology, this study aims to establish and validate a prognostic signature of lung adenocarcinoma (LUAD) based on metabolism-related genes (MRGs). Methods The gene sequencing data of LUAD samples with clinical information and the metabolism-related gene set were obtained from The Cancer Genome Atlas (TCGA) and Molecular Signatures Database (MSigDB), respectively. The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate cox regression analysis was performed to identify MRGs that related to overall survival (OS). A prognostic signature was developed by multivariate Cox regression analysis. Furthermore, the signature was validated in the GSE31210 dataset. In addition, a nomogram that combined the prognostic signature was created for predicting the 1-, 3- and 5-year OS of LUAD. The accuracy of the nomogram prediction was evaluated using a calibration plot. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in LUAD. Results A total of 116 differentially expressed MRGs were detected in the TCGA dataset. We found that 12 MRGs were most significantly associated with OS by using the univariate regression analysis in LUAD. Then, multivariate Cox regression analyses were applied to construct the prognostic signature, which consisted of six MRGs-aldolase A (ALDOA), catalase (CAT), ectonucleoside triphosphate diphosphohydrolase-2 (ENTPD2), glucosamine-phosphate N-acetyltransferase 1 (GNPNAT1), lactate dehydrogenase A (LDHA), and thymidylate synthetase (TYMS). The prognostic value of this signature was further successfully validated in the GSE31210 dataset. Furthermore, the calibration curve of the prognostic nomogram demonstrated good agreement between the predicted and observed survival rates for each of OS. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. The high-risk group patients have higher levels of immune checkpoint molecules and are therefore more sensitive to immunotherapy. Finally, we confirmed six MRGs protein and mRNA expression in six lung cancer cell lines and firstly found that ENTPD2 might played an important role on LUAD cells colon formation and migration. Conclusions We established a prognostic signature based on MRGs for LUAD and validated the performance of the model, which may provide a promising tool for the diagnosis, individualized immuno-/chemotherapeutic strategies and prognosis in patients with LUAD.

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Section: Discussionmentioning

confidence: 99%

Establishment and validation of a prognostic signature for lung adenocarcinoma based on metabolism‐related genes

et al. 2021

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“…[3,4] On the other hand, further studies are needed to identify genes associated with rapid progression and a worse prognosis for lung squamous cell carcinoma. [5] In the future, when identifying this tumor, physicians and oncologists should be more aggressive and maybe initiate high-intensity chemotherapy earlier.…”

Section: Discussionmentioning

confidence: 99%

Rapid killer: Lung squamous cell cancer

Mitri

Nehme

2021

DCC

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Background: Lung cancer is one of the leading causes of death despite improvement in treatment modalities such as immunotherapy with chemotherapy and precise radiotherapy. NSCLC is a heterogeneous group of diseases that differs in cytology and includes adenocarcinoma, squamous cell carcinoma, bronchioloalveolar carcinoma, and poorly differentiated carcinoma. Usually, NSCLC, in contrast to SCLC, spreads locally, and the doubling time of squamous cell carcinoma is 133 days which classifies it as a relatively slow-growing tumor.Case presentation: We present the case of a 72-year-old male, recently diagnosed with squamous cell carcinoma in the right upper lobe along with secondary deposits. Few days after diagnosis, the patient had severe respiratory distress. This endobronchial tumor has increased significantly in size upon bronchoscopic visualization causing a complete obstruction of his right main bronchus and hypoxemic respiratory failure requiring intubation.Conclusion: To our knowledge, there are few reported cases where lung adenocarcinoma progressed rapidly over days. Squamous cell carcinoma usually takes 3 to 6 months to double in size, but in our case, the progression was very fast. In the last decade, it was confirmed that the doubling time of a tumor is an independent factor in the prognosis of lung cancer patients. On the other hand, further studies are needed to identify genes associated with rapid progression and a worse prognosis for lung squamous cell carcinoma. Hence, this aggressive tumor is a “rapid killer.”

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“…More and more attention has been recently paid to the key role of gene signatures based on speci c correlation in predicting the prognosis of LUAD because of the rapid advances in high-throughput technologies and bioinformatics methodology [27][28][29][30]. Moreover, the identi cation of novel gene signatures that predict the prognosis of patients is bene cial for the choice of treatment regimens and the improvement of survival rate [31,32].…”

Section: Discussionmentioning

confidence: 99%

Establishment and Validation of a Prognostic Signature for Lung Adenocarcinoma Based on Metabolism-related Genes

Wang

Embaye

Yang

et al. 2020

Preprint

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Background: Given that dysregulated metabolism has been recently identified as a hallmark of cancer biology, this study aims to establish and validate a prognostic signature of lung adenocarcinoma (LUAD) based on metabolism-related genes(MRGs).Methods: The gene sequencing data of LUAD samples with clinical information and the metabolism-related gene set were obtained from The Cancer Genome Atlas (TCGA) and Molecular Signatures Database (MSigDB), respectively. The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate Cox regression analysis were performed to identify MRGs that related to overall survival(OS). A prognostic signature was developed by multivariate Cox regression analysis. Furthermore, the signature was validated in the GSE31210 dataset. In addition, a nomogram that combined the prognostic signature was created for predicting the 1-, 3- and 5-year OS of LUAD.The accuracy of the nomogram prediction was evaluated using a calibration plot. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in LUAD.Results: A total of 116 differentially expressed MRGs were detected in the TCGA dataset. We found that 12 MRGs were most significantly associated with OS by using the univariate regression analysis in LUAD. Then, multivariate Cox regression analyses were applied to construct the prognostic signature, which consisted of six MRGs (ALDOA, CAT, ENTPD2, GNPNAT1, LDHA, and TYMS). The prognostic value of this signature was further successfully validated in the GSE31210 dataset. Furthermore, the calibration curve of the prognostic nomogram demonstrated good agreement between the predicted and observed survival rates for each of OS. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. The signature was found to be associated with various clinicopathological features. Finally, we confirmed six MRGs protein and mRNA expression in six lung cancer cells and firstly found that ENTPD2 might played an important role on lung adenocarcinoma cell lines clone formation and migration.Conclusions: We established a prognostic signature based on MRGs for LUAD and validated the performance of the model, which may provide a promising tool for the diagnosis and prognosis in patients with LUAD.

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Identification of key genes associated with progression and prognosis for lung squamous cell carcinoma

Cited by 17 publications

References 51 publications

Establishment and validation of a prognostic signature for lung adenocarcinoma based on metabolism‐related genes

Establishment and validation of a prognostic signature for lung adenocarcinoma based on metabolism‐related genes

Rapid killer: Lung squamous cell cancer

Establishment and Validation of a Prognostic Signature for Lung Adenocarcinoma Based on Metabolism-related Genes

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