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1. Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following neoadjuvant immunochemotherapy: a multicenter study

Author

Feng Li, Yu Qi, Kuo Li, Zhenwei Shi, Guanchao Ye, Guangyao Wu, Mingliang Wang, Chunyang Zhang, Leonard Wee, Andre Dekker, Chu Han, Zaiyi Liu, and Yongde Liao

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Objectives Although neoadjuvant immunochemotherapy has been widely applied in non-small cell lung cancer (NSCLC), predicting treatment response remains a challenge. We used pretreatment multimodal CT to explore deep learning-based immunochemotherapy response image biomarkers.Methods This study retrospectively obtained non-contrast enhanced and contrast enhancedbubu CT scans of patients with NSCLC who underwent surgery after receiving neoadjuvant immunochemotherapy at multiple centers between August 2019 and February 2023. Deep learning features were extracted from both non-contrast enhanced and contrast enhanced CT scans to construct the predictive models (LUNAI-uCT model and LUNAI-eCT model), respectively. After the feature fusion of these two types of features, a fused model (LUNAI-fCT model) was constructed. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. SHapley Additive exPlanations analysis was used to quantify the impact of CT imaging features on model prediction. To gain insights into how our model makes predictions, we employed Gradient-weighted Class Activation Mapping to generate saliency heatmaps.Results The training and validation datasets included 113 patients from Center A at the 8:2 ratio, and the test dataset included 112 patients (Center B n=73, Center C n=20, Center D n=19). In the test dataset, the LUNAI-uCT, LUNAI-eCT, and LUNAI-fCT models achieved AUCs of 0.762 (95% CI 0.654 to 0.791), 0.797 (95% CI 0.724 to 0.844), and 0.866 (95% CI 0.821 to 0.883), respectively.Conclusions By extracting deep learning features from contrast enhanced and non-contrast enhanced CT, we constructed the LUNAI-fCT model as an imaging biomarker, which can non-invasively predict pathological complete response in neoadjuvant immunochemotherapy for NSCLC.

Published
2024
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2. CT-based quantification of intratumoral heterogeneity for predicting pathologic complete response to neoadjuvant immunochemotherapy in non-small cell lung cancer

Author

Guanchao Ye, Guangyao Wu, Chunyang Zhang, Mingliang Wang, Hong Liu, Enmin Song, Yuzhou Zhuang, Kuo Li, Yu Qi, and Yongde Liao

Subjects
non-small cell lung cancer, neoadjuvant immunochemotherapy, pathological complete response, radiomics, intratumoral heterogeneity, Immunologic diseases. Allergy, RC581-607
Abstract

ObjectivesTo investigate the prediction of pathologic complete response (pCR) in patients with non-small cell lung cancer (NSCLC) undergoing neoadjuvant immunochemotherapy (NAIC) using quantification of intratumoral heterogeneity from pre-treatment CT image.MethodsThis retrospective study included 178 patients with NSCLC who underwent NAIC at 4 different centers. The training set comprised 108 patients from center A, while the external validation set consisted of 70 patients from center B, center C, and center D. The traditional radiomics model was contrasted using radiomics features. The radiomics features of each pixel within the tumor region of interest (ROI) were extracted. The optimal division of tumor subregions was determined using the K-means unsupervised clustering method. The internal tumor heterogeneity habitat model was developed using the habitats features from each tumor sub-region. The LR algorithm was employed in this study to construct a machine learning prediction model. The diagnostic performance of the model was evaluated using criteria such as area under the receiver operating characteristic curve (AUC), accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV).ResultsIn the training cohort, the traditional radiomics model achieved an AUC of 0.778 [95% confidence interval (CI): 0.688-0.868], while the tumor internal heterogeneity habitat model achieved an AUC of 0.861 (95% CI: 0.789-0.932). The tumor internal heterogeneity habitat model exhibits a higher AUC value. It demonstrates an accuracy of 0.815, surpassing the accuracy of 0.685 achieved by traditional radiomics models. In the external validation cohort, the AUC values of the two models were 0.723 (CI: 0.591-0.855) and 0.781 (95% CI: 0.673-0.889), respectively. The habitat model continues to exhibit higher AUC values. In terms of accuracy evaluation, the tumor heterogeneity habitat model outperforms the traditional radiomics model, achieving a score of 0.743 compared to 0.686.ConclusionThe quantitative analysis of intratumoral heterogeneity using CT to predict pCR in NSCLC patients undergoing NAIC holds the potential to inform clinical decision-making for resectable NSCLC patients, prevent overtreatment, and enable personalized and precise cancer management.

Published
2024
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3. An advanced nomogram model using deep learning radiomics and clinical data for predicting occult lymph node metastasis in lung adenocarcinoma

Author

Guanchao Ye, Chi Zhang, Yuzhou Zhuang, Hong Liu, Enmin Song, Kuo Li, and Yongde Liao

Subjects
Radiomics, Deep learning, Occult lymph node metastasis, Lung adenocarcinoma, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Purpose: To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing the occult lymph node metastasis (OLNM) status in clinical stage IA lung adenocarcinoma. Methods: A cohort of 473 cases of lung adenocarcinomas from two hospitals was included, with 404 cases allocated to the training cohort and 69 cases to the testing cohort. Clinical characteristics and semantic features were collected, and radiomics features were extracted from the computed tomography (CT) images. Additionally, deep transfer learning (DTL) features were generated using RseNet50. Predictive models were developed using the logistic regression (LR) machine learning algorithm. Moreover, gene analysis was conducted on RNA sequencing data from 14 patients to explore the underlying biological basis of deep learning radiomics scores. Result: The training and testing cohorts achieved AUC values of 0.826 and 0.775 for the clinical model, 0.865 and 0.801 for the radiomics model, 0.927 and 0.885 for the DTL-radiomics model, and 0.928 and 0.898 for the nomogram model. The nomogram model demonstrated superiority over the clinical model. The decision curve analysis (DCA) revealed a net benefit in predicting OLNM for all models. The investigation into the biological basis of deep learning radiomics scores identified an association between high scores and pathways related to tumor proliferation and immune cell infiltration in the microenvironment. Conclusions: The nomogram model, incorporating clinical-semantic features, radiomics, and DTL features, exhibited promising performance in predicting OLNM. It has the potential to provide valuable information for non-invasive lymph node staging and individualized therapeutic approaches.

Published
2024
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4. Immune characteristics analysis and construction of a four-gene prognostic signature for lung adenocarcinoma based on estrogen reactivity

Author

Yangwei Wang, Tong Yu, Jiaping Chen, Rong Zhao, Mingxin Diao, Peiyuan Mei, Shiwen He, Wenlin Qiu, Guanchao Ye, Lijuan Jiang, Han Xiao, and Yongde Liao

Subjects
Estrogen, Lung adenocarcinoma, Immune cell infiltration, Prognosis, Nomogram, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Lung adenocarcinoma (LUAD) is a common type of malignant tumor with poor prognosis and high mortality. In our previous studies, we found that estrogen is an important risk factor for LUAD, and different estrogen statuses can predict different prognoses. Therefore, in this study, we constructed a prognostic signature related to estrogen reactivity to determine the relationship between different estrogen reactivities and prognosis. We downloaded the LUAD dataset from The Cancer Genome Atlas (TCGA) database, calculated the estrogen reactivity of each sample, and divided them into a high-estrogen reactivity group and a low-estrogen reactivity group. The difference in overall survival between the groups was significant. We also analyzed the status of immune cell infiltration and immune checkpoint expression between the groups. We analyzed the differential gene expression between the groups and screened four key prognostic factors by the least absolute shrinkage and selection operator (LASSO) regression and univariable and multivariable Cox regression. Based on the four genes, a risk signature was established. To a certain extent, the receiver operating characteristic (ROC) curve showed the predictive ability of the risk signature, which was further verified using the GSE31210 dataset. We also determined the role of estrogen in LUAD using an orthotopic mouse model. Additionally, we developed a predictive nomogram combining the risk signature with other clinical characteristics. In conclusion, our four-gene prognostic signature based on estrogen reactivity had prognostic value and can provide new insights into the development of treatment strategies for LUAD.

Published
2023
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5. SPTBN2, a New Biomarker of Lung Adenocarcinoma

Author

Chunli Wu, Bo Dong, Lan Huang, Yafei Liu, Guanchao Ye, Shihao Li, and Yu Qi

Subjects
lung adenocarcinoma, bioinformatics analysis, SPTBN2, migration, proliferation, invasion, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

ObjectivesThe roles played by β-III-spectrin, also known as spectrin beta, non-erythrocytic 2 (SPTBN2), in the occurrence and development of lung adenocarcinoma (LUAD) have not been previously examined. Our study aimed to reveal the relationship between the SPTBN2 expression and LUAD.Materials and MethodsTwenty pairs of LUAD tissues and adjacent tissues were collected from patients diagnosed and treated at the Thoracic Surgery Department of The First Affiliated Hospital of Zhengzhou University from July 2019 to September 2020. RNA sequencing (RNA-seq) analysis determined that the expression of SPTBN2 was higher in LUAD samples than in adjacent normal tissues. The expression levels of SPTBN2 were examined in various databases, including the Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA). The Search Tool for the Retrieval of Interacting Genes (STRING) online website was used to examine protein–protein interactions involving SPTBN2, and the results were visualized by Cytoscape software. The Molecular Complex Detection (MCODE) plug-in for Cytoscape software was used to identify functional modules of the obtained protein–protein interaction (PPI) network. Gene enrichment analysis was performed, and survival analysis was conducted using the Kaplan–Meier plotter. The online prediction website TargetScan was used to predict SPTBN2-targeted miRNA sequences by searching for SPTBN2 sequences. Finally, we verified the expression of SPTBN2 in the obtained tissue samples using real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). The human lung cancer cell lines A549 and H1299 were selected for the transfection of small interfering RNA (siRNA) targeting SPTBN2 (si-SPTBN2), and the knockdown efficiency was evaluated by RT-qPCR. The cellular proliferation, migration, and invasion capacities of A549 and H1299 cells were determined using the cell counting kit-8 (CCK-8) proliferation assay; the wound-healing assay and the Transwell migration assay; and the Matrigel invasion assay, respectively.ResultsThe expression of SPTBN2 in non–small cell lung cancer (NSCLC) ranked 13th among cancer cell lines based on the CCLE database. At the mRNA and protein levels, the expression levels of SPTBN2 were higher in LUAD tissues than in normal lung tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that proteins related to SPTBN2 were enriched in apoptotic and phagosomal pathways. Kaplan–Meier survival analysis revealed that SPTBN2 expression was significantly related to the prognosis of patients with LUAD. The TargetScan database verified that miR-16 was a negative regulator of SPTBN2 mRNA expression. The results of the CCK-8 cell proliferation assay revealed that SPTBN2 knockdown significantly inhibited the cell proliferation abilities of A549 and H1299 cells. The wound-healing assay indicated that SPTBN2 knockdown resulted in reduced migration after 48 h compared with the control group. The Transwell migration and invasion test revealed that the migration and invasion abilities were greatly decreased by SPTBN2 knockdown compared with control conditions.ConclusionWe uncovered a novel gene, SPTBN2, that was significantly upregulated in LUAD tissues relative to normal tissue expression. SPTBN2 is highly expressed in LUAD, positively correlated with poor prognosis, and can promote the proliferation, migration, and invasion of LUAD cells.

Published
2021
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7. Comparison of bronchial methylene blue staining and modified inflation-deflation method in identifying the intersegmental plane during lung segmentectomy

Author

Mingliang, Wang, Zheng, Zhang, Peiyuan, Mei, Guanchao, Ye, Xiaojun, Wang, Quanfu, Huang, Jun, Nie, Qinghong, Long, and Yongde, Liao

Subjects
Cancer Research, Oncology, Radiology, Nuclear Medicine and imaging
Abstract

Identification of the intersegmental plane (ISP) is the critical step in lung segmentectomy because of the complicated anatomic variations. Bronchial methylene blue staining was developed by our team in 2015 and is now commonly used at our center, it could rapidly and accurately identify the ISP. In this study, we aimed to compare bronchial methylene blue staining with the modified inflation-deflation method in terms of their perioperative characteristics and to present our experience of the methylene blue method.From June 2020 to September 2021, the data of 112 patients with pulmonary ground-glass nodules who underwent segmentectomy by video-assisted thoracoscopic surgery were retrospectively reviewed. Sixty-two patients underwent bronchial methylene blue staining, and 50 patients underwent the modified inflation-deflation method.Both methods could accurately identify the ISP. The time taken to clearly display the ISP (82.94±28.08Compared with the modified inflation-deflation method, the bronchial methylene blue staining method can quickly display the ISP and shorten the surgical duration. This method is safe and feasible, can be widely applied during thoracoscopic anatomic segmentectomy.

Published
2022

8. Single-cell transcriptome analysis demonstrates inter-patient and intra-tumor heterogeneity in primary and metastatic lung adenocarcinoma

Author

Lu Han, Yu Qi, Bo Dong, Sheng Yinliang, Bin Wu, Yafei Liu, Lan Huang, Chunyang Zhang, Guanchao Ye, and Chunli Wu

Subjects
Aging, Lung Neoplasms, Tumour heterogeneity, Adenocarcinoma of Lung, Biology, Transcriptome, Genetic Heterogeneity, Downregulation and upregulation, Predictive Value of Tests, single cell RNA sequencing, Databases, Genetic, Biomarkers, Tumor, medicine, Humans, RNA-Seq, Cell adhesion, Brain Neoplasms, Gene Expression Profiling, chemoresistance, Cell Biology, lung adenocarcinoma, medicine.disease, Primary tumor, Microvesicles, Biological Variation, Population, Drug Resistance, Neoplasm, Tumor progression, Disease Progression, Cancer research, tumour heterogeneity, Single-Cell Analysis, Research Paper, Brain metastasis
Abstract

In this study, we performed single-cell transcriptome data analysis of fifty primary and metastatic lung adenocarcinoma (LUAD) samples from the GSE123902 and GSE131907 datasets to determine the landscape of inter-patient and intra-tumoral heterogeneity. The gene expression profiles and copy number variations (CNV) showed significant heterogeneity in the primary and metastatic LUAD samples. We observed upregulation of pathways related to translational initiation, endoplasmic reticulum stress, exosomes, and unfolded protein response in the brain metastasis samples as compared to the primary tumor samples. Pathways related to exosomes, cell adhesion and metabolism were upregulated and the epithelial-to-mesenchymal-transition (EMT) pathway was downregulated in brain metastasis samples from chemotherapy-treated LUAD patients as compared to those from the untreated LUAD patients. Tumor cell subgroups in the brain metastasis samples showed differential expression of genes related to type II alveolar cells, chemoresistance, glycolysis and oxidative phosphorylation (metabolic reprogramming), and EMT. Thus, single-cell transcriptome analysis demonstrated intra-patient and intra-tumor heterogeneity in the regulation of pathways related to tumor progression, chemoresistance and metabolism in the primary and metastatic LUAD tissues. Moreover, our study demonstrates that single cell transcriptome analysis is a potentially useful tool for accurate diagnosis and personalized targeted treatment of LUAD patients.

Published
2020

9. PRDM5 suppresses oesophageal squamous carcinoma cells and modulates 14-3-3zeta/Akt signalling pathway

Author

Guanchao Ye, Yu Qi, Chunyang Zhang, Yanan Song, Ziyang Liu, Sheng Yinliang, Song Zhao, and Bin Wu

Subjects
Esophageal Neoplasms, Physiology, Carcinogenesis, Cell Survival, Mice, Nude, Mice, Physiology (medical), Cell Line, Tumor, Gene silencing, Animals, Humans, neoplasms, Protein kinase B, Cell Proliferation, Pharmacology, Gene knockdown, Chemistry, Akt/PKB signaling pathway, Cell growth, Cell migration, Neoplasms, Experimental, digestive system diseases, Squamous carcinoma, DNA-Binding Proteins, Gene Expression Regulation, Neoplastic, 14-3-3 Proteins, Cancer research, Carcinoma, Squamous Cell, Phosphorylation, Proto-Oncogene Proteins c-akt, Signal Transduction, Transcription Factors
Abstract

Dysregulation of PR (PRDI-BF1 and RIZ) domain protein 5 (PRDM5) expression has been shown to be associated with the progression of many malignancies. Nevertheless, the role and underlying mechanism of PRDM5 in oesophageal squamous cell carcinoma (ESCC) remain elusive. qRT-PCR was performed to analyze PRDM5 mRNA expression, and western blot was used to determine protein expression of PRDM5, MMP-2, MMP-9, 14-3-3zeta, pan-Akt and phosphorylated Akt expression. CCK-8 staining was employed to evaluate cell proliferation, while wound scratch assay and Transwell assay were carried out to detect cell migration. A tumour xenograft model of ESCC was also established to validate the effect of PRDM5. PRDM5 expression was downregulated in ESCC tissues and positively correlated with the overall survival of ESCC patients. Silencing PRDM5 expression promoted cell proliferation in ESCC cells, while overexpressing PRDM5 inhibited cell proliferation. Moreover, the migratory abilities of ESCC cells were promoted by PRDM5 knockdown but were attenuated by PRDM5 overexpression. Importantly, 14-3-3zeta expression, along with the phosphorylation of Akt, was suppressed by PRDM5 in ESCC cells. In the established tumour xenograft model, PRDM5 regulated ESCC tumour growth as well as the expression of 14-3-3zeta and phosphorylation of Akt protein. In conclusion, PRDM5 suppresses ESCC cell proliferation and migration and negatively regulates 14-3-3zeta/Akt signalling pathway in vitro and in vivo.

Published
2021

10. SPTBN2, a New Biomarker of Lung Adenocarcinoma

Author

Lan Huang, Bo Dong, Guanchao Ye, Shi-Hao Li, Yafei Liu, Yu Qi, and Chunli Wu

Subjects
Cancer Research, Gene knockdown, Small interfering RNA, bioinformatics analysis, Migration Assay, Matrigel Invasion Assay, Cell growth, proliferation, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Biology, lung adenocarcinoma, migration, invasion, SPTBN2, Real-time polymerase chain reaction, Oncology, microRNA, Cancer research, KEGG, RC254-282, Original Research
Abstract

ObjectivesThe roles played by β-III-spectrin, also known as spectrin beta, non-erythrocytic 2 (SPTBN2), in the occurrence and development of lung adenocarcinoma (LUAD) have not been previously examined. Our study aimed to reveal the relationship between the SPTBN2 expression and LUAD.Materials and MethodsTwenty pairs of LUAD tissues and adjacent tissues were collected from patients diagnosed and treated at the Thoracic Surgery Department of The First Affiliated Hospital of Zhengzhou University from July 2019 to September 2020. RNA sequencing (RNA-seq) analysis determined that the expression of SPTBN2 was higher in LUAD samples than in adjacent normal tissues. The expression levels of SPTBN2 were examined in various databases, including the Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA). The Search Tool for the Retrieval of Interacting Genes (STRING) online website was used to examine protein–protein interactions involving SPTBN2, and the results were visualized by Cytoscape software. The Molecular Complex Detection (MCODE) plug-in for Cytoscape software was used to identify functional modules of the obtained protein–protein interaction (PPI) network. Gene enrichment analysis was performed, and survival analysis was conducted using the Kaplan–Meier plotter. The online prediction website TargetScan was used to predict SPTBN2-targeted miRNA sequences by searching for SPTBN2 sequences. Finally, we verified the expression of SPTBN2 in the obtained tissue samples using real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). The human lung cancer cell lines A549 and H1299 were selected for the transfection of small interfering RNA (siRNA) targeting SPTBN2 (si-SPTBN2), and the knockdown efficiency was evaluated by RT-qPCR. The cellular proliferation, migration, and invasion capacities of A549 and H1299 cells were determined using the cell counting kit-8 (CCK-8) proliferation assay; the wound-healing assay and the Transwell migration assay; and the Matrigel invasion assay, respectively.ResultsThe expression of SPTBN2 in non–small cell lung cancer (NSCLC) ranked 13th among cancer cell lines based on the CCLE database. At the mRNA and protein levels, the expression levels of SPTBN2 were higher in LUAD tissues than in normal lung tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that proteins related to SPTBN2 were enriched in apoptotic and phagosomal pathways. Kaplan–Meier survival analysis revealed that SPTBN2 expression was significantly related to the prognosis of patients with LUAD. The TargetScan database verified that miR-16 was a negative regulator of SPTBN2 mRNA expression. The results of the CCK-8 cell proliferation assay revealed that SPTBN2 knockdown significantly inhibited the cell proliferation abilities of A549 and H1299 cells. The wound-healing assay indicated that SPTBN2 knockdown resulted in reduced migration after 48 h compared with the control group. The Transwell migration and invasion test revealed that the migration and invasion abilities were greatly decreased by SPTBN2 knockdown compared with control conditions.ConclusionWe uncovered a novel gene, SPTBN2, that was significantly upregulated in LUAD tissues relative to normal tissue expression. SPTBN2 is highly expressed in LUAD, positively correlated with poor prognosis, and can promote the proliferation, migration, and invasion of LUAD cells.

Published
2021

11. Sepsis-associated severe interleukin-6 storm in critical coronavirus disease 2019

Author

Yu Qi, Jianjun Gou, Guanchao Ye, Lan Huang, Yafei Liu, Xuan Zhao, Hong Li, and Yi Zhang

Subjects
Coronavirus disease 2019 (COVID-19), Sepsis mortality, Critical Illness, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Pneumonia, Viral, Immunology, Sepsis, Prognostic markers, Betacoronavirus, Interferon-gamma, Lymphopenia, Correspondence, Pandemic, Humans, Immunology and Allergy, Medicine, Interleukin 6, Pandemics, biology, Interleukin-6, SARS-CoV-2, Tumor Necrosis Factor-alpha, business.industry, COVID-19, medicine.disease, biology.organism_classification, Survival Analysis, Virology, Interleukin-10, Infectious Diseases, Acute Disease, Critical illness, biology.protein, Interleukin-2, Interleukin-4, Infection, Coronavirus Infections, Cytokine Release Syndrome, business, Procalcitonin, Biomarkers
Published
2020

12. Catamenial pneumothorax with bubbling up on the diaphragmatic defects: a case report

Author

Lu Han, Yafei Liu, Guanchao Ye, Sheng Yinliang, Shi-Hao Li, Bin Wu, Bo Dong, Yu Qi, and Chunli Wu

Subjects
Adult, medicine.medical_specialty, Perforation (oil well), Endometriosis, Catamenial pneumothorax, Diaphragmatic breathing, Case Report, Thoracic endometriosis syndrome TES, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, 030212 general & internal medicine, 030219 obstetrics & reproductive medicine, Thoracic cavity, business.industry, Thoracic Surgery, Video-Assisted, Obstetrics and Gynecology, Pneumothorax, Gynecology and obstetrics, General Medicine, Pleural cavity, medicine.disease, Surgery, Diaphragm (structural system), Menstruation, medicine.anatomical_structure, Reproductive Medicine, RG1-991, Female, Public aspects of medicine, RA1-1270, business
Abstract

Background Catamenial pneumothorax is characterized by spontaneous recurring pneumothorax during menstruation, which is a common clinical manifestation of thoracic endometriosis syndrome. There are still controversies about its pathogenesis. Case presentation A 43-year-old woman with a history of endometriosis came to our hospital due to recurring pneumothorax during menstruation. Uniportal Video-assisted Thoracoscopic Surgery (VATS) exploration was performed on the eve of menstruating. We thoroughly explored the diaphragm, visceral and parietal pleura: The lung surface was scattered with yellowish-brown implants; no bullae were found; multiple diaphragmatic defects were found on the dome. And surprisingly, we caught a fascinating phenomenon: Bubbles were slipping into pleural cavity through diaphragmatic defects. We excised the diaphragmatic lesions and wedge resected the right upper lung lesion; cleared the deposits and flushed the thoracic cavity with pure iodophor. Diaphragmatic lesions confirmed the presence of endometriosis, and interestingly enough, microscopically, endometrial cells were shedding with impending menses. After a series of intraoperative operations and postoperative endocrine therapy, the disease did not recur after a period of follow-up. Conclusion We have witnessed the typical signs of catamenial pneumothorax at the accurate timing: Not only observed the process of gas migration macroscopically, but also obtained pathological evidence of diaphragmatic periodic perforation microscopically, which is especially precious and confirms the existing theory that retrograde menstruation leads to diaphragmatic endometriosis, and the diaphragmatic fenestration is obtained due to the periodic activities of ectopic endometrium.

Published
2021

13. Key microRNAs and hub genes associated with poor prognosis in lung adenocarcinoma

Author

Lu Han, Guanchao Ye, Sheng Yinliang, Yu Qi, Yafei Liu, Chunli Wu, Lan Huang, Chunyang Zhang, Bin Wu, and Bo Dong

Subjects
Aging, differentially expressed genes, Lung Neoplasms, T cell, Adenocarcinoma of Lung, Kaplan-Meier Estimate, Biology, Immune system, microRNA, medicine, Humans, Gene Regulatory Networks, Protein Interaction Maps, RNA, Messenger, Gene, B cell, Proportional Hazards Models, differentially expressed miRNAs, PECAM1, Cell Biology, Dendritic cell, medicine.disease, Prognosis, lung adenocarcinoma, Platelet Endothelial Cell Adhesion Molecule-1, Survival Rate, MicroRNAs, medicine.anatomical_structure, miRNA-mRNA regulatory network, Multivariate Analysis, Cancer research, Adenocarcinoma, CD8, Research Paper
Abstract

In the study, we obtained 36 pairs of lung adenocarcinoma (LUAD) tissues and adjacent non-tumorous tissues. Then, we chose a specific hub-target gene of miRNA and used qRT-PCR to evaluate the expression of PECAM1. We found that the expression level of PECAM1 mRNA in LUAD was significantly lower than that in adjacent nontumor tissues (P

Published
2020

14. Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles

Author

Guanchao Ye, Sheng Yinliang, Chunli Wu, Yu Qi, Shi-Hao Li, Chunyang Zhang, Bo Dong, Yafei Liu, Bin Wu, and Lan Huang

Subjects
medicine.medical_treatment, non-small cell lung cancer (NSCLC), RNA, General Medicine, Methylation, Immunotherapy, Biology, medicine.disease, Immune system, medicine, Cancer research, Original Article, Lung cancer, Transcription factor, Gene
Abstract

BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with a poor prognosis. N6-methyladenosine (m6A) methylation, which is a reversible ribonucleic acid (RNA) modification, plays an important role in the occurrence and development of NSCLC. However, the potential effect of m6A methylation on immune infiltrates and prognosis remains unclear. METHODS: In this study, a weighted gene co-expression network analysis was used to screen out messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) that were co-expressed with m6A regulators. Additionally, 2 molecular subtypes (Clusters 1 and 2) were determined via consensus clustering. Subsequently, a prognostic risk model was constructed using both co-expressed mRNAs and ncRNAs. Based on the risk scores calculated by the prognostic model, the patients were divided into the high-risk group or low-risk group. Finally, the altered patterns of the tumor immune microenvironments (TIMEs) between the 2 stratification methods were thoroughly investigated, and a gene set enrichment analysis was conducted to further examine the potential mechanism. RESULTS: Patients in Cluster 1 had lower immunoscores, higher programmed death-ligand 1 (PD-L1) expression, and shorter overall survival (OS) compared to patients in Cluster 2. A further investigation based on the prognostic model revealed that the PD-L1 expression levels of patients in the high-risk group were significantly upregulated, and the immunoscores were lower than those in the low-risk group. The immune cells with a high infiltration in Cluster 1 showed a significant positive correlation with the risk score; those with low infiltration showed a significant negative correlation. The hallmarks of the Myelocytomatosis viral oncogene (MYC) targets, the second Gap/Mitosis (G2/M) checkpoint, E2 transcription Factor (E2F) targets, glycolysis, deoxyribonucleic acid (DNA) repair, and unfolded protein response were significantly enriched in Cluster 1, the low-immunoscore group, and the high-risk group. CONCLUSIONS: This study revealed that m6A methylation is closely related to the poor prognosis of NSCLC patients via interference with the TIME, which suggests that m6A may play a role in optimizing individualized immunotherapy management and improving prognosis.

Published
2021

15. miRNA-218/FANCI is associated with metastasis and poor prognosis in lung adenocarcinoma: a bioinformatics analysis

Author

Chunyang Zhang, Bin Wu, Chunli Wu, Guanchao Ye, Yafei Liu, Sheng Yinliang, Yu Qi, and Lan Huang

Subjects
Messenger RNA, Microarray analysis techniques, Human Protein Atlas, General Medicine, Biology, medicine.disease, Metastasis, Real-time polymerase chain reaction, microRNA, medicine, Cancer research, Adenocarcinoma, Original Article, Gene
Abstract

BACKGROUND: In this study, tumor microarray analysis was used to screen the key messenger RNAs (mRNAs) and microRNAs related to the progression of lung adenocarcinoma (LUAD), in order to provide a theoretical basis for early diagnosis, therapeutic targets, and prognosis evaluation of patients with LUAD. METHODS: The mRNA and miRNA expression datasets came from the Gene Expression Omnibus (GEO) project database. Differentially expressed genes (DEGs) and microRNAs (DEMs) between LUAD tissues and adjacent lung tissue were obtained using GEO2R. The Search Tool for the Retrieval of Interacting Genes website was also employed to construct and visualize the interactions of overlapped DEGs. The overall survival of DEMs was investigated using the Kaplan-Meier plotter. The TargetScan website (http://www.targetscan.org/) was used to verify the relationship between FA Complementation Group I (FANCI) and the expression of miRNA-218 (miR-218). The expression of FANCI was verified using the GEO and Human Protein Atlas databases, as well as Real Time Quantitative PCR using our own samples. Next, we analyzed the relationship between the expression of FANCI and the clinicopathological characteristics as well as the prognosis of patients with LUAD. We also explored whether the FANCI was related to immune cell infiltration in LUAD. RESULTS: FANCI was identified as a hub gene and associated with poor OS. We found that miR-218 negatively regulates FANCI mRNA expression. At the mRNA expression and protein level, FANCI was more highly expressed in LUAD tissues. The expression of FANCI in LUAD was related to tumor size (χ(2)=13.96, P

Published
2021

16. A new technology for reducing anastomotic fistula in the neck after esophageal cancer surgery

Author

Ji-Lun Li, Lu Han, Sen-Lin Zhu, Zhanfeng He, Kai Wu, Chunyang Zhang, Dengyan Zhu, Yanan Song, Yan-Li Chen, Ting-Ting Shan, Yafei Liu, Lu-Bing Gao, Tianliang Zheng, Yang Yang, Fengbiao Wen, Jin-Wei Chen, Yu Qi, Sheng Yinliang, Qingyi Zhang, Song Zhao, Guanchao Ye, and Donglei Liu

Subjects
Pulmonary and Respiratory Medicine, medicine.medical_specialty, Univariate analysis, business.industry, Fistula, Retrospective cohort study, Anastomosis, Esophageal cancer, medicine.disease, Surgery, 03 medical and health sciences, Stenosis, 0302 clinical medicine, Cardiothoracic surgery, 030220 oncology & carcinogenesis, medicine, Balloon dilation, Original Article, 030211 gastroenterology & hepatology, business
Abstract

Background: To explore the risk factors and prevention methods of cervical mechanical anastomotic fistula and stenosis after the radical resection of esophageal cancer. Methods: From March 2018 to November 2018, 128 patients undergoing mechanical anastomosis of esophageal cancer were selected from the Department of Thoracic Surgery of The First Affiliated Hospital of Zhengzhou University. All the enrolled patients were operated on using the Mckeown method, and a retrospective study was conducted. Data for preoperative and postoperative test indices, intraoperative embedding materials, postoperative complications, and preoperative and postoperative treatment were collected, and the relationship between various factors and the incidence of cervical anastomotic fistula and stenosis was analysed. Univariate analysis was conducted using t tests or Fisher’s exact probability method, and multivariate analysis was conducted using logistic regression models. Results: All 128 patients successfully underwent surgery without dying. The enrolled patients were evaluated using the Stooler classification, with 28 patients having grade 0, 41 patients having grade 1, 34 patients having grade 2, 21 patients having grade 3, and 4 patients having grade 4 stenosis. Patients with stenosis of grade 3 or above had obvious choking sensation, which could only be relieved by balloon dilation. Symptoms in all patients with stenosis were relieved by balloon dilation. There were no significant differences between the two groups regarding embedding materials, preoperative choking history, history of alcohol consumption, history of hypertension, history of coronary heart disease, history of diabetes, postoperative calcium concentration, average albumin concentration, average platelet concentration, body mass index, anastomotic fistula, preoperative chemotherapy, postoperative chemotherapy, or postoperative cough (P>0.05). There were significant differences in postoperative reflux (χ 2 =11.338, P

Published
2019

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