Establishment of a prognostic risk prediction modelfor non-small cell lung cancer patients with brainmetastases: a retrospective study

Construction of nomogram model of poor prognosis for patients newly diagnosed with brain metastasis from non-small cell lung cancer based on clinical pathology and prognostic scores

Objective

To explore non-small cell lung cancer (NSCLC) patients with new diagnosis of brain metastasis and construct Logistic regression model based on clinical pathology and prognosis score, and verify.

Methods

A total of 158 patients newly diagnosed with brain metastasis in NSCLC were retrospectively selected from March 2020 to April 2022. The clinical data of patients were collected, and Logistic regression analysis was used to analyze the influencing factors of poor prognosis for newly diagnosed NSCLC with brain metastasis.

Results

The results of univariate analysis showed that the clinical pathological features including NLR>2.94, abnormal CEA, mediastinal lymph node metastasis, symptomatic treatment with therapeutic method, extracranial metastasis and GPS1-2 score were associated with the survival and prognosis of patients with newly diagnosed brain metastasis from NSCLC (P < 0.05). Multivariate Logistic regression analysis showed that NLR>2.94, mediastinal lymph node metastasis, CEA abnormality, extracranial metastasis, and newly diagnosed NSCLC with GPS1-2 score were independent risk factors for poor prognosis of brain metastasis (P < 0.05). Internal verification using the Bootstrap method showed that the predicted curve fitted well with the standard model curve, with the average absolute error of 0.029. The ROC curve result showed that the AUC was 0.887, and the 95%CI was 0.782-0.905, with the corresponding specificity and sensitivity of 90.50% and 80.00%, respectively. This indicates that the prediction accuracy of this Nomogram model is good.

Conclusion

NLR, mediastinal lymph node metastasis, CEA, extracranial metastasis and GPS are risk factors for poor prognosis of newly diagnosed brain metastasis in NSCLC. The risk factor model constructed based on these risk factors has excellent prediction value for the poor prognosis of newly diagnosed brain metastasis in NSCLC. In order to reduce the risk of newly diagnosed brain metastasis in NSCLC and improve the prognosis, targeted preventive measures are taken against the above risk factors in clinical practice.

Cerebral spinal fluid analyses and therapeutic implications for leptomeningeal metastatic disease

PURPOSE

To review applications of cerebral spinal fluid (CSF) biomarkers for the diagnosis, monitoring and treatment of leptomeningeal metastatic disease (LMD) among patients with metastatic solid tumors.

METHODS

A narrative review identified original research related to CSF biomarkers among patients with metastatic solid tumors and LMD. Pre-clinical research (e.g. studies conducted in animal models) was not included. A descriptive analysis of literature was undertaken, with a focus on clinical applications related to the diagnosis, monitoring and treatment of LMD.

RESULTS

The low cellularity of CSF in comparison to plasma is an advantage for liquid biopsy, given that circulating tumor DNA (ctDNA) is not significantly diluted by genomic DNA from non-cancer cells. This results in higher variant allelic frequencies and increased sensitivity in detecting ctDNA compared to plasma. However, the clinical significance of positive ctDNA and/or circulating tumor cells (CTCs) in the CSF, particularly in the absence of other signs of LMD (either clinical and/or radiological), remains unclear. While the use of CSF liquid biopsy to monitor treatment response is promising, this approach requires prospective validation using larger sample sizes prior to adoption in routine clinical care. Discovery efforts involving proteomics and metabolomics have potential to identify proteins involved in the regulation of energy metabolism, vasculature, and inflammation in LMD, which in turn, may offer insights into novel treatment approaches.

CONCLUSION

CSF liquid biopsy should be incorporated in prospective studies for patients with LMD to validate promising diagnostic and/or predictive biomarkers of treatment response, as well as new therapeutic targets.

Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters

Objective

This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model.

Methods

A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell's consistency was analyzed.

Results

Single-factor analysis revealed significant differences in PFS (P<0.05) between genders, body mass index (BMI), carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), treatment methods, treatment response evaluation, smoking status, presence of pericardial effusion, and programmed death ligand 1 (PD-L1) at 0 and 1-50%. Significant differences in OS (P<0.05) were observed for age, tumor location, treatment methods, White blood cells (WBC), uric acid (UA), CA125, pro-gastrin-releasing peptide (ProGRP), SCCA, cytokeratin fragment 21 (CYFRA21), and smoking status. COX analysis identified male gender, progressive disease (PD) as treatment response, and SCCA > 1.6 as risk factors for LC PFS. The consistency indices of the line chart models for predicting PFS and OS were 0.782 and 0.772, respectively.

Conclusion

Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.

Brain metastases and lung cancer: molecular biology, natural history, prediction of response and efficacy of immunotherapy

Brain metastases stemming from lung cancer represent a common and challenging complication that significantly impacts patients' overall health. The migration of these cancerous cells from lung lesions to the central nervous system is facilitated by diverse molecular changes and a specific environment that supports their affinity for neural tissues. The advent of immunotherapy and its varied combinations in non-small cell lung cancer has notably improved patient survival rates, even in cases involving brain metastases. These therapies exhibit enhanced penetration into the central nervous system compared to traditional chemotherapy. This review outlines the molecular mechanisms underlying the development of brain metastases in lung cancer and explores the efficacy of novel immunotherapy approaches and their combinations.

AS-IV enhances the antitumor effects of propofol in NSCLC cells by inhibiting autophagy

Non-small cell lung cancer (NSCLC) is one of the most lethal malignant tumors. It has been shown that the general anesthetic agents, propofol and astragaloside IV (AS-IV) both exert antitumor effects in NSCLC. However, the effects of the combination of propofol with AS-IV in NSCLC remain unclear. Cell counting kit-8, and EdU and Transwell assays were performed to evaluate NSCLC cell viability, proliferation, and migration. Cell apoptosis and autophagy were observed by flow cytometric analysis and TUNEL and LC3 staining, respectively. AS-IV notably enhanced the anti-proliferative, pro-apoptotic, and anti-migratory properties of propofol in NSCLC cells. Moreover, AS-IV remarkably facilitated the anti-autophagy effect of propofol in NSCLC cells by downregulating LC3, Beclin 1, and ATG5. Significantly, the pro-apoptotic ability of the AS-IV/propofol combination in NSCLC cells was further enhanced by the autophagy inhibitor 3-MA, suggesting that autophagy plays a tumor-promoting role in NSCLC cells. Collectively, AS-IV could facilitate the antitumor abilities of propofol in NSCLC cells by inhibiting autophagy. These findings may be beneficial for future studies on the use of AS-IV and propofol for the treatment of NSCLC.