The Construction of a Nomogram Using the Pan-Immune-Inflammation Value Combined with a PILE Score for Immunotherapy Prediction Prognosis in Advanced NSCLC.

Purpose: The purpose of this study was to investigate the predictive value of Pan-Immune-Inflammation Value (PIV) combined with the PILE score for immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) and to construct a nomogram prediction model to provide reference for clinical work. Patients and Methods: Patients with advanced NSCLC who received ICIs treatment in Qingdao Municipal Hospital from January 2019 to December 2021 were selected as the study subjects. The chi-square test, Kaplan-Meier survival analysis, and Cox proportional risk regression analysis were used to evaluate the prognosis. The results were visualized by a nomogram, and the performance of the model was judged by indicators such as the area under the subject operating characteristic curve (AUC) and C-index. The patients were divided into high- and low-risk groups by PILE score, and the prognosis of patients in different risk groups was evaluated. Results: Multivariate Cox regression analysis showed that immune-related adverse events (irAEs) were prognostic factors for overall survival (OS) improvement, and ECOG PS score ≥2, bone metastases before treatment, and high PIV expression were independent risk factors for OS. The C index of OS predicted by the nomogram model is 0.750 (95% CI: 0.677-0.823), and the Calibration and ROC curves show that the model has good prediction performance. Compared with the low-risk group, patients in the high-risk group of PILE were associated with a higher inflammatory state and poorer physical condition, which often resulted in a poorer prognosis. Conclusion: PIV can be used as a prognostic indicator for patients with advanced NSCLC treated with ICIs, and a nomogram prediction model can be constructed to evaluate the survival prediction of patients, thus contributing to better clinical decision-making and prognosis assessment.

Fibrinogen-to-albumin ratio (FAR) is the best biomarker for the overall survival of patients with non-small-cell lung cancer.

Objective: The inflammatory response and the nutritional status are associated with overall survival (OS) in patients with non-small cell lung cancer (NSCLC), but it is unclear which biomarkers are better suited to predict prognosis. This study sought to determine which of the commonly existing inflammatory and nutritional indicators best predicted the OS. Methods: This study included 15 compound indicators based on inflammation or nutrition, with cutoff points obtained through the receiver operating characteristic (ROC) curve. Univariate and multivariate Cox proportional risk models were used to evaluate the relationship between these predictors and OS. Kaplan-Meier curves were used for survival analysis, and log-rank tests were used to compare differences between groups. The C-index was calculated to evaluate the predictive ability of the different indicators. Results: The study included 899 patients with NSCLC. In the univariate analysis, all 15 measures were significantly associated with the OS of patients (all p < 0.05). The results of the C-index analysis showed that the fibrinogen-to-albumin ratio (FAR), the systemic immune-inflammation index (SII), and the albumin-to-alkaline phosphatase ratio (AAPR) were the three indices with the best predictive performance. Among them, FAR (C-index = 0.639) had the best predictive power for OS in patients with NSCLC. In the different subgroups, FAR had the highest C-index in male, non-smoking, adenocarcinoma, and stage II patients. The C-index of the platelet-to-lymphocyte ratio (PLR) in female patients was the highest. SII was the highest in smokers, in those aged <65 and ≥65 years, and in stage III patients. The C-index of AAPR was the highest in non-adenocarcinomas. The C-index of the pan-immune-inflammation value (PIV) was the highest in stage I patients. In the multivariate Cox regression analysis, among FAR, SII, and AAPR, only FAR was an independent predictor of OS in patients with NSCLC. A high FAR was associated with a higher risk of death in patients with NSCLC (HR = 1.601, 95% CI = 1.028-2.495). In order to further evaluate the potential prognostic value of FAR, SII, and AAPR in patients with different stages, Cox regression analysis was performed for those with stage I-II and stage III NSCLC. The results showed that FAR was an independent prognostic factor for OS in patients with stage I-II NSCLC. Conclusion: For all patients with NSCLC, the prognostic power of FAR was superior to that of other inflammatory and nutritional indicators.

Risk factor analysis and nomogram prediction model construction of postoperative complications of thoracoscopic non-small cell lung cancer.

Background: A series of complications will inevitably occur after thoracoscopic pulmonary resection. How to avoid or reduce postoperative complications is an important research area in the perioperative treatment of thoracic surgery. This study analyzed the risk factors for thoracoscopic postoperative complications of non-small cell lung cancer (NSCLC) and established a nomogram prediction model in order to provide help for clinical decision-making. Methods: Patients with NSCLC who underwent thoracoscopic surgery from January 2017 to December 2021 were selected as study subjects. The relationship between patient characteristics, surgical factors, and postoperative complications was collected and analyzed. Based on the results of the statistical regression analysis, a nomogram model was constructed, and the predictive performance of the nomogram model was evaluated. Results: A total of 872 patients who met the study criteria were included in the study. A total of 171 patients had complications after thoracoscopic surgery, accounting for 19.6% of the study population. Logistic regression analysis showed that thoracic adhesion, history of respiratory disease, and lymphocyte-monocyte ratio (LMR) were independent risk factors for complications after thoracoscopic surgery (P<0.05). Variables with P<0.1 in logistic regression analysis were included in the nomogram model. The verification results showed that the area under curve (AUC) of the model was 0.734 [95% confidence interval (CI): 0.693-0.775], and the calibration curve showed that the model had good differentiation. The decision curve analysis (DCA) curve showed that this model has good clinical application value. In subgroup analysis of complications, gender, history of respiratory disease, body mass index (BMI), type of surgical procedure, thoracic adhesion, and Time of operation were identified as significant risk factors for prolonged air leak (PAL) after surgery. Tumor location and forced expiratory volume in the first second (FEV1) were identified as important risk factors for postoperative pulmonary infection. N stage and thoracic adhesion were identified as significant risk factors for postoperative pleural effusion. The AUC for PAL was 0.823 (95% CI: 0.768-0.879). The AUC of postoperative pulmonary infection was 0.714 (95% CI: 0.627-0.801). The AUC of postoperative pleural effusion was 0.757 (95% CI: 0.650-0.864). The calibration curve and DCA curve indicated that the model had good predictive performance and clinical application value. Conclusions: This study analyzed the risk factors affecting the postoperative complications of NSCLC through thoracoscopic surgery, and the nomogram model built based on the influencing factors has certain significance for the identification and reduction of postoperative complications.

Prognostic factors and predictive model construction in patients with non-small cell lung cancer: a retrospective study.

Objective: The purpose of this study was to construct a nomogram model based on the general characteristics, histological features, pathological and immunohistochemical results, and inflammatory and nutritional indicators of patients so as to effectively predict the overall survival (OS) and progression-free survival (PFS) of patients with non-small cell lung cancer (NSCLC) after surgery. Methods: Patients with NSCLC who received surgical treatment in our hospital from January 2017 to June 2021 were selected as the study subjects. The predictors of OS and PFS were evaluated by univariate and multivariable Cox regression analysis using the Cox proportional risk model. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling for 1 000 times) was used to internally verify the nomogram model, and C-index was used to represent the prediction performance of the nomogram model. The calibration graph method was used to visually represent its prediction compliance, and decision curve analysis (DCA) was used to evaluate the application value of the model. Results: Univariate and multivariate analyses were used to identify independent prognostic factors and to construct a nomogram of postoperative survival and disease progression in operable NSCLC patients, with C-index values of 0.927 (907-0.947) and 0.944 (0.922-0.966), respectively. The results showed that the model had high predictive performance. Calibration curves for 1-year, 2-year, and 3-year OS and PFS show a high degree of agreement between the predicted probability and the actual observed probability. In addition, the results of the DCA curve show that the model has good clinical application value. Conclusion: We established a predictive model of survival prognosis and disease progression in patients with non-small cell lung cancer after surgery, which has good predictive performance and can guide clinicians to make the best clinical decision.

The advanced lung cancer inflammation index (ALI) predicted the postoperative survival rate of patients with non-small cell lung cancer and the construction of a nomogram model.

OBJECTIVE: To investigate the prognostic significance of the advanced lung cancer inflammation index (ALI) in patients with operable non-small-cell lung carcinoma (NSCLC). By constructing the nomogram model, it can provide a reference for clinical work. METHODS: A total of 899 patients with non-small cell lung cancer who underwent surgery in our hospital between January 2017 and June 2021 were retrospectively included. ALI was calculated by body mass index (BMI) × serum albumin/neutrophil to lymphocyte ratio (NLR). The optimal truncation value of ALI was obtained using the receiver operating characteristic (ROC) curve and divided into two groups. Survival analysis was represented by the Kaplan-Meier curve. The predictors of Overall survival (OS) were evaluated by the Cox proportional risk model using single factor and stepwise regression multifactor analysis. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling 1 000 times) was used for internal verification of the nomogram model. The concordance index (C-index) was used to represent the prediction performance of the nomogram model, and the calibration graph method was used to visually represent its prediction conformity. The application value of the model was evaluated by decision curve analysis (DCA). RESULTS: The optimal cut-off value of ALI was 70.06, and the low ALI group (ALI < 70.06) showed a poor survival prognosis. In multivariate analyses, tumor location, pathological stage, neuroaggression, and ALI were independently associated with operable NSCLC-specific survival. The C index of OS predicted by the nomogram model was 0.928 (95% CI: 0.904-0.952). The bootstrap self-sampling method (B = 1000) was used for internal validation of the prediction model, and the calibration curve showed good agreement between the prediction and observation results of 1-year, 2-year, and 3-year OS. The ROC curves for 1-year, 2-year, and 3-year survival were plotted according to independent factors, and the AUC was 0.952 (95% CI: 0.925-0.979), 0.951 (95% CI: 0.916-0.985), and 0.939 (95% CI: 0.913-0.965), respectively. DCA shows that this model has good clinical application value. CONCLUSION: ALI can be used as a reliable indicator to evaluate the prognosis of patients with operable NSCLC, and through the construction of a nomogram model, it can facilitate better individualized treatment and prognosis assessment.

Association between immune-related adverse events and prognosis in patients with advanced non-small cell lung cancer: a systematic review and meta-analysis.

Background: The emergence of immune checkpoint inhibitors (ICIs) provides a variety of options for patients with advanced non-small-cell lung cancer (NSCLC). After the application of ICIs, the immune system of patients was highly activated, and immune-related adverse events (irAEs) could occur in some organ systems, and irAEs seemed to be associated with the survival prognosis of patients. Therefore, we evaluated the association between survival outcomes and irAEs in NSCLC patients and conducted a systematic review and meta-analysis. Methods: We conducted systematic reviews of PubMed, Embase, Cochrane, and Web of Science databases until December 2021. The forest map was constructed by combining the hazard ratio (HR) and 95% confidence interval (CI). I2 estimated the heterogeneity between studies. A meta-analysis was performed using R 4.2.1 software. Results: Eighteen studies included 4808 patients with advanced NSCLC. In pooled analysis, the occurrence of irAEs was found to be a favorable factor for improved prognosis (PFS: HR: 0.48, 95% CI: 0.41-0.55, P <0.01; OS: HR: 0.46, 95% CI: 0.42-0.52, P <0.01). In subgroup analyses, cutaneous irAE, gastrointestinal irAE, endocrine irAE and grade ≥3 irAEs were associated with improvements in PFS and OS, but pulmonary and hepatic irAEs were not. Conclusion: Existing evidence suggests that the occurrence of irAEs may be a prognostic biomarker for advanced NSCLC. However, further research is needed to explore the prospect of irAEs as a prognostic biomarker in patients undergoing immunotherapy. Systematic review registration: https://www.crd.york.ac.uk/PROSPEROFILES/405333_STRATEGY_20240502.pdf, identifier CRD42023405333.

Retraction: ET-1 promotes the growth and metastasis of esophageal squamous cell carcinoma via activating PI3K/Akt pathway.

[This retracts the article DOI: 10.21037/tcr.2020.04.26.].

Rectosigmoid-Junction Squamous Cell Carcinoma With pMMR/MSS Achieved a Partial Response Following PD-1 Blockade Combined With Chemotherapy: A Case Report.

Colorectal squamous cell carcinoma (SCC) is extremely rare and associated with a poor prognosis. And the pMMR/MSS colorectal cancer is related to a limited response to programmed death ligand-1 (PD-1) blockade monotherapy. However, the clinical activity of PD-1 blockade monotherapy or combination therapy in colorectal SCC is unknown. One patient with rectosigmoid-junction SCC was treated with PD-1 blockade combined with chemotherapy. After 3 months of PD-1 blockade and chemotherapy, the computed tomography imaging showed that this patient achieved a partial response. The next generation sequencing and immunohistochemistry analysis showed that the patient had tumors with proficient mismatch repair (pMMR) and microsatellite stability (MSS), strong PD-L1 expression, and tumor mutational burden-high (TMB-High), respectively. This case suggests that PD-1 blockade combined with chemotherapy might be an effective therapy for colorectal SCC with pMMR/MSS status. Moreover, the PD-L1 expression and TMB might be the potential predictors of PD-1 blockade response for colorectal SCC patients.

Resibufogenin suppresses growth and metastasis through inducing caspase-1-dependent pyroptosis via ROS-mediated NF-κB suppression in non-small cell lung cancer.

The purpose of this study is to explore the antitumor properties of resibufogenin (RB) in non-small cell lung cancer (NSCLC) and elucidate its underlying mechanism. A549 and H520 cells were treated with various concentrations of RB with or without NLRP3 inhibitor (MCC950), caspase-1 inhibitor (VX765), or N-acetyl-l-cysteine (an ROS scavenger). Cell counting kit-8 and colony formation assays were conducted to determine cell viability. Cell invasion was detected by using the transwell assay. The release of lactate dehydrogenase (LDH) was determined by the LDH detection assay. The protein expression levels of related genes were measured by western blotting and immunohistochemistry. The reactive oxygen species (ROS) level was detected by using a 2,7-dichlorodihydrofluorescein diacetate ROS Assay Kit. The in vivo effects of RB were evaluated in a xenograft mouse model. RB treatment reduced cell viability and invasion in a dose-dependent manner. Furthermore, RB also enhanced pyroptosis levels in A549 and H520 cells, as indicated by the increased release of LDH and pyroptosis-related proteins. Interestingly, we also found that the antiproliferative and antimetastatic effects of RB were alleviated by the blockade of pyroptosis using NLRP3 inhibitor MCC950. Further study demonstrated that RB induced pyroptosis in a caspase-1-dependent manner, as evidenced by the finding that VX765 effectively reversed the effects of RB on A549 and H520 cells. We also found that RB could trigger caspase-1-dependent pyroptosis through ROS-mediated NF-κB suppression. In summary, our findings provide a potential antitumor agent and a novel insight into the mechanism of RB treatment of NSCLC.

ET-1 promotes the growth and metastasis of esophageal squamous cell carcinoma via activating PI3K/Akt pathway.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the prevalent and deadly cancers worldwide. Previous studies confirmed that endothelin-1 (ET-1) serves as an oncogene and therapeutic target in various tumors. However, the role and mechanism of ET-1 in the progression of ESCC remains largely unclear. METHODS: Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the mRNA level of ET-1 in ESCC tissues and cell lines. Cell counting kit-8 (CCK-8), flow cytometry and Transwell assay were performed to examine the proliferation, cell cycle arrest, invasion and migration capacity of ESCC cells. Western blot was applied to measure the expression of ET-1 and PI3K/Akt pathway-related proteins. Furthermore, we also assessed the effect of ET-1 on tumor growth in vivo. RESULTS: ET-1 was highly expressed in ESCC tissues and associated with poor outcomes. Knockdown of ET-1 significantly inhibited the proliferation, migration and invasion capacity of ESCC cells and promoted cell cycle arrest. Mechanistically, silencing of ET-1 exerts anti-proliferation and anti-metastasis activities via inactivation of the PI3K/Akt signaling pathway in ESCC in vitro and in vivo. CONCLUSIONS: These findings uncover the effective suppression of cell proliferation and metastasis through silencing of ET-1 and blocking the PI3K/Akt signaling pathway, which is an attractive therapeutic regimen for the treatment of ESCC.

miR-107 regulates cisplatin chemosensitivity of A549 non small cell lung cancer cell line by targeting cyclin dependent kinase 8.

Previous studies demonstrated that the acquired drug resistance of non-small cell lung cancer (NSCLC) was related to deregulation of miRNAs. However, the effects of miR-107 and the mechanism through which miR-107 affects the cisplatin chemoresistance in NSCLC have not been reported. TaqMan RT-PCR or Western blot assay was performed to detect the expression of mature miR-107 and cyclin dependent kinase 8 (CDK8) protein. The viabilities of treated cells were analyzed using MTT assay. We found that the expression level of miR-107 in A549 cells was significantly lower than that in normal human bronchial epithelial cells (0.45 ± 0.26 vs. 1.00 ± 0.29, P = 0.032). The MTT assay showed that the A549 cells transfected with miR-107 mimics were significantly more sensitive to the therapy of cisplatin than control cells. A549 cells transfected with miR-107 mimics showed a decreased CDK8 protein expression. Downregulation of CDK8 expression by siRNAs, A549 cells became more sensitive to the therapy of cisplatin. In addition, the enhanced growth-inhibitory effect by the miR-107 mimic transfection was enhanced after the addition of CDK8 siRNA. In conclusion, the present study provides the first evidence that miR-107 plays a key role in cisplatin resistance by targeting the CDK8 protein in NSCLC cell lines, suggesting that miR-107 can be used to predict a patient's response to chemotherapy as well as serve as a novel potential maker for NSCLC therapy.

microRNA­802 promotes lung carcinoma proliferation by targeting the tumor suppressor menin.

microRNAs play important roles in numerous biological processes, including tumorigenesis, by modulating critical gene transcripts. In the present study, the role of microRNA­802 (miR­802) in lung cancer was investigated. The results of the quantitative polymerase chain reaction revealed that expression levels of miR­802 were significantly upregulated in lung cancer tissues. In vitro experiments demonstrated that miR­802 promoted cell proliferation in A549, NCI­H358 and NCI­H1299 cells. Furthermore, it was indicated that miR­802 promoted the proliferation of lung carcinoma by targeting the tumor suppressor menin. Therefore, these results suggest a previously unknown miR­802/menin molecular network controlling lung carcinoma development.

High-level C-X-C chemokine receptor type 4 expression correlates with brain-specific metastasis following complete resection of non-small cell lung cancer.

Brain-specific metastasis is one of the primary causes of recurrence following complete resection of non-small cell lung cancer (NSCLC) and the underlying mechanism remains unclear. The present study was designed to investigate the correlation between C-X-C chemokine receptor type 4 (CXCR4) expression and brain-specific metastasis of NSCLC. Lung cancer tissues from 105 patients who underwent complete tumor resection between January 1998 and June 2008 (sample group, 34 with brain metastasis during the follow-up period; control group 1, 34 without metastasis during the follow-up period; and control group 2, 37 with other organ metastasis, excluding brain metastasis, during the follow-up period) were examined by immunohistochemistry to detect the expression of CXCR4 protein. The differences in CXCR4 expression were compared using McNemar's χ2 test. Estimation of survival was calculated with the Kaplan-Meier method and the statistical differences were analyzed with the log-rank test. Overexpression of CXCR4 protein was observed in 31 (91.2%) NSCLC patients with brain metastasis, which was greater than that observed in the NSCLC patients with other organ metastases (73.0%; P=0.048) and without metastases (14.7%; P<0.001). CXCR4 protein was highly overexpressed in patients with brain-specific metastasis, which indicated that high-level CXCR4 expression correlates with brain-specific metastasis of NSCLC.