Risk factors of postoperative recurrence and potential candidate of adjuvant radiotherapy in lung adenosquamous carcinoma

Comprehensive analysis of clinicopathological profiles in adenosquamous carcinoma of the lung

OBJECTIVES

Adenosquamous carcinoma (ASC), an uncommon subtype within non-small cell lung cancer (NSCLC), manifests distinctive traits of aggressiveness, embodying a fusion of both adenocarcinoma (AC) and squamous cell carcinoma (SCC) components. The clinicopathological characteristics of distinct subtypes of ASC remain unclear.

METHODS

This retrospective study included 226 patients diagnosed with lung ASC who consecutively underwent surgical resection at Shanghai Pulmonary Hospital, Tongji University, between January 2015 and March 2021. Data regarding the clinical features and pathological features were collected.

RESULTS

Out of this study cohort, 125 patients exhibited AC-predominant ASC, while 81 had SCC-predominant ASC. No significant differences were observed between the two subgroups in terms of age, gender, smoking history, primary site, and T, N classification. AC-Predominant ASC displayed a higher susceptibility to genetic alterations compared to SCC-Predominant ASC (P=0.02). Additionally, we showed that irrespective of the predominant pathological subtype in ASC, when lymph node metastasis occurred, the lymph node biopsies were more likely to exhibit AC, and a chi-square test confirmed that the primary predominant pathological subtype was not associated with the lymph node metastasis subtype.

CONCLUSIONS

In conclusion, we describe an overview of ASC in the Chinese population, and upon stratifying into predominant pathological subgroups, we observed a higher frequency of driver gene mutations in AC-predominant ASC. We found that the AC component in ASC has a higher propensity for lymph node metastasis. These findings may suggest the predominant role of the AC component within the context of ASC.

Role of radiotherapy in the management of rare solid thoracic tumors of the adults

Thoracic tumors include more than one hundred histopathological subtypes. Rare thoracic malignancies can be defined as representing less than 1% of all thoracic tumors. The European Rare Cancer Surveillance Project (RARECARE) identified rarity as an incidence less than 6 for 100,000 people, with significant difference of prevalence between them. Modalities of treatment for these pathologies include surgery, radiotherapy, and systemic therapies. In this article, we aim to discuss role and techniques of radiotherapy in management of rare solid thoracic tumors in adults, focusing on different anatomical locations such as lung parenchyma, mediastinum, vessels, chest wall and pleural cavity.

Construction and Validation of a Recurrent Risk Nomogram Model for Non-Small Cell Lung Cancer within 1 Year after Radical Resection

Objective

To explore the risk factors of recurrence within 1 year after radical resection of non-small cell lung cancer (NSCLC) and construct the nomogram model.

Methods

The clinical data of 186 patients with NSCLC treated with radical surgery in Affiliated Hospital of Youjiang Medical University for Nationalities of Baise were retrospectively analyzed. Multivariate logistic regression was applied to analyze the risk factors of recurrence within 1 year after radical resection of NSCLC. The R language (R 4.0.3 software package) was used in constructing the nomogram model, and the predictive value of the model was evaluated.

Results

The recurrence rate of 186 patients within 1 year after radical surgery was 29.57%. After multivariate logistic regression analysis, pathological stage, number of lymph node metastasis, chronic obstructive pulmonary disease (COPD), postoperative plasma D-dimer, and carcinoembryonic antigen were independent factors for recurrence within 1 year after radical resection of NSCLC (P < 0.05). Based on the above independent risk factors, a nomogram model was established, with the distinction of AUC = 0.891 (95% CI: 0.819–0.964) and sensitivity and specificity of 70.3% and 97.8%, respectively. The calibration curve was close to the ideal curve. External validation of the model showed AUC = 0.801 (95% CI: 0.674–0.928), and sensitivity and specificity were 66.7% and 84.2%, respectively.

Conclusion

The recurrence of NSCLC within 1 year after radical surgery was related to a variety of factors, and the nomogram model constructed based on risk factors had good goodness of fit, calibration, consistency of prediction, and prediction efficiency.

Prognostic value of PD-1, PD-L1 and P53 in patients with non-small cell lung cancer after postoperative adjuvant chemoradiotherapy

OBJECTIVE

To explore the value of programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1) and protein 53 (P53) in estimating the prognosis of patients with non-small cell lung cancer (NSCLC) after postoperative adjuvant chemoradiotherapy.

METHODS

The clinical data of 100 patients with NSCLC who were treated with adjuvant chemoradiotherapy after pulmonary lobectomy in our hospital were retrospectively analyzed. The expression levels of PD-1, PD-L1 and P53 in tumor tissues were detected by immumohistochemical staining. The efficacy of chemoradiotherapy and survival time between patients with positive and negative expression of PD-1, PD-L1 and P53 were compared respectively to evaluate the correlation of PD-1, PD-L1 and P53 with chemoradiotherapy results in NSCLC. General data of patients were analyzed by single factor analysis. Multivariate logistic regression analysis was used to identify independent risk factors impacting the prognosis of NSCLC patients with postoperative adjuvant chemoradiotherapy.

RESULTS

A significantly lower chemoradiotherapy effective rate and a remarkably shorter survival time were found in NSCLC patients with positive expression levels of PD-1, PD-L1 and P53 in tumor tissues as compared with those of negative results (all P<0.05). Single factor analysis revealed that gender, age, history of smoking, histological type, degree of differentiation, T stage, lymph node metastasis, expression levels of PD-1, PD-L1 and P53 showed significant correlations with the prognosis of NSCLC patients with postoperative adjuvant chemoradiotherapy (all P<0.05). High T stage (odds ratio (OR)=7.269), history of smoking (OR=5.128), lymph node metastasis (OR=4.647), PD-1 (+) (OR=7.556), PD-L1 (+) (OR=6.674), P53 (+) (OR=9.070), PD-1 (+) PD-L1 (+) (OR=6.095), PD-1 (+) P53 (+) (OR=6.752), PD-L1 (+) P53 (+) (OR=7.363), and PD-1 (+) PD-L1 (+) P53 (+) (OR=8.524) were determined by multiple logistic regression analysis to be independent risk factors influencing the effect of postoperative adjuvant chemoradiotherapy in NSCLC patients.

CONCLUSION

There are numerous risk factors affecting the effect of postoperative adjuvant chemoradiotherapy in NSCLC patients, of which NSCLC patients with positive expression of PD-1, PD-L1 and P53 had a worse prognosis than those with negative results. PD-1, PD-L1 and P53 can serve as effective prognostic indicators for NSCLC after chemoradiotherapy. In clinical practice, monitoring these three indicators contributes to the adjustment of therapeutic regimen and gives some guidance.

Bioinformatics Analysis of mRNAs and miRNAs for Identifying Potential Biomarkers in Lung Adenosquamous Carcinoma

Background

Lung adenosquamous carcinoma (LASC) is a special type of lung cancer. LASC is a malignant tumor with strong aggressiveness and a poor prognosis. Previous studies have revealed that microRNAs (miRNAs) are widely involved in the development of tumors by targeting mRNA. This study is aimed at identifying the key mRNAs and miRNAs of LASC and constructing miRNA-mRNA networks for deeply comprehending the latent molecular mechanisms.

Methods

mRNA dataset (GSE51852) and miRNA dataset (GSE51853) were extracted and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were picked out by the GEO2R web tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted in the DAVID database. The protein-protein interaction (PPI) network was performed and analyzed by using the STRING database and Cytoscape software, respectively. TransmiR v2.0 was applied to predict potential transcription factors of miRNAs. The target genes of DEMs were predicted in the miRWalk database.

Results

In comparison to normal tissues, a total of 1458 DEGs (511 upregulated and 947 downregulated) and 13 DEMs (5 upregulated and 8 downregulated) were screened out in LASC tissues. The PPI network of the DEGs displayed five key modules and seventeen hub genes. Six target genes of the DEMs were predicted, and five essential miRNA-mRNA regulatory pairs were established. Ensuingly, CENPF, one of the target genes, was also the hub genes of GSE51852, which was obtained from MCODE and cytoHubba and regulated by hsa-miR-205.

Conclusions

We constructed the miRNA-mRNA regulatory pairs, which are helpful to study the potential regulatory mechanisms and find out promising diagnosis biomarkers and therapeutic targets for LASC.