[Surgery for small-cell lung cancer]

Development and validation of a CT-based radiomics nomogram for predicting progression-free survival in patients with small cell lung cancer

PURPOSE

Small cell lung cancer (SCLC) is a highly aggressive form of lung cancer, representing about 15% of cases worldwide. Despite advances in imaging, such as low-dose CT, which have increased diagnostic rates, survival outcomes for SCLC patients have remained stagnant. Recent studies have only focused on radiomics, which extracts detailed quantitative features from imaging, with clinical risk factors to improve prognostic models. Therefore, this study aimed to develop a clinical-radiomics fusion nomogram based on computed tomography (CT) to estimate progression-free survival (PFS) in patients diagnosed with SCLC. By integrating radiomics features extracted from CT with clinical data, this model provides personalized prognostic assessment for clinicians. Its clinical utility lies in aiding treatment decision-making by offering more accurate prognostic evaluation, optimizing therapeutic strategies, and identifying high-risk patients at an early stage, ultimately improving overall survival and quality of life.

METHODS

To develop the nomogram model, 95 patients diagnosed with pathologically confirmed SCLC between January 1, 2013, and December 31, 2023, were included in the study cohort. Participants were randomly divided into training and validation cohorts in a 7:3 ratio. Radiomics features associated with PFS were generated using the least absolute shrinkage and selection operator (LASSO) along with univariate and multivariate analyses. Additionally, in the training cohort, both univariate and multivariate analyses using Cox regression were conducted to identify the significant clinical risk factors influencing PFS. The predictive performance of the clinical and clinical-radiomics fusion nomogram were evaluated using the concordance index, calibration plots, and decision curve analysis (DCA).

RESULTS

Five radiomics features were selected and used to calculate the radiomics score (Rad-score). The radiomics features were significantly associated with PFS (hazard ratio: 0.5765, 95% confidence interval: 0.3641-0.9128, p < 0.05). Three clinical risk factors significantly associated with PFS were identified: neuron-specific enolase (NSE), carbohydrate antigen 125 levels (CA125), and treatment type, such as surgery. The clinical-radiomics fusion nomogram model (C-index:0.744) demonstrated superior performance compared to the clinical nomogram model (C-index: 0.718) in the training cohort. DCA indicated that the clinical-radiomics fusion nomogram outperformed the clinical nomogram in terms of clinical usefulness.

CONCLUSIONS

A CT-based clinical-radiomics fusion nomogram was developed to predict PFS in patients with SCLC, which is useful in providing individualized information.

ADVANCES IN KNOWLEDGE

A clinical-radiomics fusion nomogram was constructed to estimate the probability of PFS based on clinical risk factors and the rad-score.

The effects of surgical resection in the treatment of limited-stage small cell lung cancer: a multicenter retrospective study

This study aimed to examine the effects of surgical resection on the treatment of limited-stage small cell lung cancer and identify patient characteristics that may indicate a benefit from surgical resection. We retrospectively reviewed medical data from patients diagnosed with small cell lung cancer between January 2013 and December 2020 at three hospitals. A total of 478 patients were included in the study, 153 patients received surgery treatment and 325 patients received non-surgery treatment. Survival differences between the surgical resection group and the nonsurgical resection group were analyzed using the Kaplan-Meier method and the log-rank test. The overall survival in the surgical resection group was significantly improved compared to that in the nonsurgical resection group (HR: 0.58, 95% CI: 0.370-0.876, p = 0.0126). Surgical resection significantly improved overall survival compared to nonsurgical resection in stage I disease (HR: 0.56, 95% CI: 0.34-0.94, p = 0.029) and stage IIA disease (HR: 0.60, 95% CI: 0.40-0.92, p = 0.019). However, no significant differences in overall survival were found between surgical resection and nonsurgical resection in stage IIB disease (HR: 0.86, 95% CI: 0.57-1.29, p = 0.46) and stage III disease (HR: 0.99, 95% CI: 0.71-1.39, p = 0.97). The overall survival of patients who underwent lobectomy was significantly better than that of patients who underwent sublobular resection (HR: 1.85, 95% CI: 1.15-4.16, p = 0.021) and who underwent pneumonectomy (HR: 2.04, 95% CI: 1.29-5.28, p = 0.009). Surgical resection should be recommended for patients diagnosed with stage I-IIA SCLC. When deciding on the surgical type, it is preferable to choose lobectomy over sublobar resection or pneumonectomy.

miR-657 Targets SRCIN1 via the Slug Pathway to Promote NSCLC Tumor Growth and EMT Induction

Background

MicroRNA- (miR-) 657 has been shown to regulate immunological and inflammatory activity, and it has also been defined to be dysregulated in both non-small-cell lung cancer (NSCLC) and hepatocellular carcinoma. The mechanistic role whereby miR-657 influences NSCLC progression, however, has yet to be clarified.

Methods

miR-657 and SRCIN1 expression levels were assessed via qPCR in the cell lines and tissues of NSCLC. Besides, correlations between the levels of miR-657 and NSCLC patient pathological characteristics were examined, and the Kaplan-Meier approach was employed for the evaluation of the prognostic utility of miR-657 in these patients. Moreover, the Pearson correlation analyses and dual-luciferase reporter assessments were used for detecting interactive relationships between miR-657 and SRCIN1. In addition, CCK-8, EdU, and Transwell assessments were employed for the appraisal of the ability of miR-657/SRCIN1 to regulate NSCLC cell proliferation and invasion. Western blotting was employed for the assessment of the levels of NSCLC cell proteins associated with the epithelial-mesenchymal transition (EMT) that were influenced by miR-657. The nude mice xenograft tumor model is established to observe the effect of miR-657 on NSCLC growth in vivo.

Results

NSCLC patient tissues and cell lines exhibited upregulated miR-657 expression that was closely related to tumor differentiation, lymphoid metastasis, and TNM stage. High levels of miR-657 were predictive of a poorer NSCLC patient prognosis, and overexpressing miR-657 resulted in the more rapid growth of NCI-H1650 and A549 cells, with a concomitant increase in their invasion. In addition, miR-657 overexpression raised the levels of Slug, N-cadherin, and Vimentin in these two cell lines while promoting E-cadherin downregulation. Dual-luciferase reporter assays confirmed that miR-657 was capable of binding to the SRCIN1 gene, and SRCIN1 expression levels were negatively associated with those of miR-657, indicating that it acts as a negative regulator of this gene. Knocking down SRCIN1 was capable to reverse the influences of miR-657 inhibitor treatment on NSCLC cell behavior. Finally, in vivo studies showed that miR-657 promoted NSCLC cell growth.

Conclusion

The obtained findings illuminate that miR-657 can promote the growth of tumors and the induction of the EMT in NSCLC cells by targeting SRCIN1 expression and modulating Slug pathway activation, highlighting this pathway as a promising therapeutic target in cases suffering from NSCLC.