Study of lung cancer regulatory network that involves erbB4 and tumor marker gene

Preoperative prediction of occult lymph node metastasis in patients with non-small cell lung cancer: a simple and widely applicable model

OBJECTIVE

Lymph node metastasis (LNM) is one of the most common pathways of metastasis in non-small cell lung cancer (NSCLC). Preoperative assessment of occult lymph node metastasis (OLNM) in NSCLC patients is beneficial for selecting appropriate treatment plans and improving patient prognosis.

METHOD

A total of 370 NSCLC patients were included in the study. Univariate and multivariate logistic regression analysis were used to screen potential risk factors for OLNM in preoperative NSCLC patients. And establish a nomogram for OLNM in NSCLC patients before surgery. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the established nomogram.

RESULT

Both univariate and multivariate logistic regression analyses suggested that multiple tumors, ERBB2 missense mutation, CA125 levels, CA153 levels, tumor site, tumor length, and serum ferritin are potential risk factors for OLNM in NSCLC patients. The constructed nomogram was evaluated, and the consistency index (C-index) and area under the ROC curve of the model were both 0.846. The calibration curve showed that the predicted values of the model had a high degree of fit with the actual observed values, and DCA suggested that the above indicators had good utility.

CONCLUSION

The personalized scoring prediction model constructed based on multiple tumors, ERBB2 miss mutation, CA125 levels, CA153 levels, tumor site, tumor length, and serum ferritin can screen NSCLC patients who may have OLNM.

Serum lncRNA THRIL predicts benign and malignant pulmonary nodules and promotes the progression of pulmonary malignancies

BACKGROUND

This project aimed to research the significance of THRIL in the diagnosis of benign and malignant solitary pulmonary nodules (SPNs) and to investigate the role of THRIL/miR-99a in malignant SPNs.

METHODS

The study groups consisted of 169 patients with SPN and 74 healthy subjects. The differences in THRIL levels were compared between the two groups and the healthy group. The receiver operating characteristic curve (ROC) was utilized to analyze the THRIL's significance in detecting benign and malignant SPN. Pearson correlation and binary regression coefficients represented the association between THRIL and SPN. CCK-8 assay, Transwell assay, and flow cytometry were utilized to detect the regulatory effect of THRIL silencing. The interaction between THRIL, miR-99a, and IGF1R was confirmed by the double luciferase reporter gene.

RESULTS

There were differences in THRIL expression in the healthy group, benign SPN group, and malignant SPN group. High accuracy of THRIL in the diagnosis of benign SPN and malignant SPN was observed. THRIL was associated with the development of SPN. The expression of THRIL was upregulated and miR-99a was downregulated in lung cancer cells. The double luciferase report experiment confirmed the connections between THRIL/miR-99a/IGF1R. Silencing THRIL could suppress cell proliferation, migration, and invasion and promote cell apoptosis by binding miR-99a.

CONCLUSION

The detection of THRIL in serum is useful for the assessment of malignant SPN. THRIL can regulate the expression of IGF1R through miR-99a, thereby promoting the growth of lung cancer cells and inhibiting apoptosis.

Dynamic monitoring serum tumor markers to predict molecular features of EGFR-mutated lung cancer during targeted therapy

To reveal the correlation of dynamic serum tumor markers (STMs) and molecular features of epidermal growth factor receptor‐mutated (EGFR‐mutated) lung cancer during targeted therapy, we retrospectively reviewed 303 lung cancer patients who underwent dynamic STM tests [neuron‐specific enolase (NSE), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), the soluble fragment of cytokeratin 19 (CYFRA21‐1), and squamous cell carcinoma antigen (SCC)] and circulating tumor DNA (ctDNA) testing with a panel covering 168 genes. At baseline, patients with EGFR mutation trended to have abnormal CEA, abnormal CA153, and normal SCC levels. Additionally, patients with Thr790Met (T790M) mutation were more likely to have abnormal CEA levels than patients without T790M mutation. Among patients with secondary resistance to EGFR tyrosine kinase inhibitors (TKI), the dynamic STMs showed a descending trend in the responsive stage and a rising trend in the resistant stage. However, the changing slopes differed between T790M subgroup and the non‐T790M subgroup in individual STMs. Our study demonstrated that the combination of baseline levels and variations of STMs (including the responsive stage and resistant stage) can be suggestive of secondary EGFR‐T790M mutation [area under the curve (AUC) = 0.897] and that changing trends of STMs (within 8 weeks after initiating the TKI therapy) can be potential predictors for the clearance of EGFR ctDNA [AUC = 0.871]. In conclusion, dynamic monitoring STMs can help to predict the molecular features of EGFR‐mutated lung cancer during targeted therapy.

Construction of a mitochondrial-associated protein DRP1 and a lung cancer-associated protein Erbb4 combined regulatory network

Objective

This research was to establish a mitochondrial-related Drp1 gene and a lung cancer-related Erbb4 gene to participate in the regulatory network of lung cancer cell apoptosis, and to provide theoretical support for mitochondria to participate in tumor regulation.

Method

The GO and KEGG methods were used to construct the regulatory networks of lung cancer related Drp1 and Erbb4 proteins that involved in the apoptosis of tumor cells, and to combine with the Bayesian network theory to screen out the largest possible action path acting on this network; The information about Drp1 in Oncomine database was collected, and the data in current database were analyzed twice. The role of Drp1 in lung cancer was meta-analyzed.

Result

A regulatory network of Drp1 and Erbb4 involved in the apoptosis of tumor cells was successfully constructed; the optimal pathway was optimized using Bayesian theory; a total of 446 different types of research results were collected in the Oncomine database, of which there were 18 studies with statistical differences in Drp1 expression, 13 studies with increased Drp1’s expression, and 5 studies with decreased expression. Compared with the control group, Drp1 was expressed in lung cancer tissues highly (P < 0.05).

Conclusion

Establishment and optimization of mitochondrial-related Drp1 and tumor-related Erbb4 genes involved in the regulation of apoptosis of cancer cells. It was proposed that Drp1 was expressed in lung cancer tissues highly through in-depth excavation of tumor-associated gene information in the Oncomine gene chip database.