Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses.

Immunotherapy has been a remarkable clinical advancement in cancer treatment, but only a few patients benefit from it. Metabolic reprogramming is tightly associated with immunotherapy efficacy and clinical outcomes. However, comprehensively analyzing their relationship is still lacking in lung adenocarcinoma (LUAD). Herein, we evaluated 84 metabolic pathways in TCGA-LUAD by ssGSEA. A matrix of metabolic pathway pairs was generated and a metabolic pathway-pair score (MPPS) model was established by univariable, LASSO, multivariable Cox regression analyses. The differences of metabolic reprogramming, tumor microenvironment (TME), tumor mutation burden and drug sensitivity in different MPPS groups were further explored. WGCNA and 117 machine learning algorithms were performed to identify MPPS-related genes. Single-cell RNA sequencing and in vitro experiments were used to explore the role of C1QTNF6 on TME. The results showed MPPS model accurately predicted prognosis and immunotherapy efficacy of LUAD patients regardless of sequencing platforms. High-MPPS group had worse prognosis, immunotherapy efficacy and lower immune cells infiltration, immune-related genes expression and cancer-immunity cycle scores than low-MPPS group. Seven MPPS-related genes were identified, of which C1QTNF6 was mainly expressed in fibroblasts. High C1QTNF6 expression in fibroblasts was associated with more infiltration of M2 macrophage, Treg cells and less infiltration of NK cells, memory CD8+ T cells. In vitro experiments validated silencing C1QTNF6 in fibroblasts could inhibit M2 macrophage polarization and migration. The study depicted the metabolic landscape of LUAD and constructed a MPPS model to accurately predict prognosis and immunotherapy efficacy. C1QTNF6 was a promising target to regulate M2 macrophage polarization and migration.

Targeting PKD2 aggravates ferritinophagy-mediated ferroptosis via promoting autophagosome-lysosome fusion and enhances efficacy of carboplatin in lung adenocarcinoma.

Ferroptosis is an iron-dependent cell death and affects efficacies of multiple antitumor regimens, showing a great potential in cancer therapy. Protein kinase D2 (PKD2) plays a crucial role in regulating necrosis and apoptosis. However, the relationship of PKD2 and ferroptosis is still elusive. In this study, we mainly analyzed the roles of PKD2 on ferroptosis and chemotherapy in lung adenocarcinoma (LUAD). We found PKD2 was highly expressed in LUAD and silencing PKD2 could promote erastin-induced reactive oxygen species (ROS), malondialdehyde (MDA) accumulation, intracellular iron content and LUAD cells death. Mechanistically, augmenting PKD2 could prevent autophagic degradation of ferritin, which could be impaired by bafilomycin A1. We further found that PKD2 overexpression would promote LC3B-II, p62/SQSTM1 accumulation and block autophagosome-lysosome fusion in a TFEB-independent manner, which could be impaired by bafilomycin A1. Bafilomycin A1 stimulation could weaken ferroptosis promotion by PKD2 abrogation. Silencing ferritin heavy chain-1 (FTH1) could reverse the resistance to ferroptosis by PKD2 overexpression. Additionally, in vitro and vivo experiments validated PKD2 promoted proliferation, migration and invasion of LUAD cells. PKD2 knockdown or pharmacological inhibition by CRT0066101 could enhance efficacy of carboplatin in LUAD via ferroptosis and apoptosis. Collectively, our study revealed that abrogation of PKD2 could aggravate ferritinophagy-mediated ferroptosis by promoting autophagosome-lysosome fusion and enhance efficacy of carboplatin in LUAD. Targeting PKD2 to induce ferroptosis may be a promising strategy for LUAD therapy.

Incidence and prognostic nomogram for resected non-small cell neuroendocrine tumor: A population-based respective study in China and the SEER database.

Background: Pulmonary neuroendocrine tumors, including small cell lung cancer (SCLC) and non-small cell neuroendocrine tumor (NSCLC-NET), have obvious heterogeneity. The comparison between SCLC and NSCLC-NET, and prognostic nomogram of resected NSCLC-NET have not been performed. Methods: We retrieved data from SEER database. The incidence and prognostic factors were compared between SCLC and NSCLC-NET. By Cox regression, we constructed prognostic nomogram of resected NSCLC-NET. The nomogram was evaluated by ROC, calibration plot and decision curve analysis (DCA) and compared with 8th TNM staging system. A Chinese cohort was used for external validation. Results: The age-adjusted incidence of SCLC declined after 1991 but the incidence of NSCLC-NET continuously rose. Patients with typical carcinoid had the best prognosis in both overall survival and lung cancer specific survival, followed by atypical carcinoid, large cell neuroendocrine tumor and SCLC after operation. Patients receiving sleeve resection in NSCLC-NET had longer survival but segmental resection was more recommended in SCLC. High-smoking index was associated with worse overall survival in both SCLC and NSCLC-NET. Histological subtype, age, surgery type, N, M stage and chemotherapy were independent prognostic factors and used to construct prognostic nomogram of resected NSCLC-NET. The nomogram performed well with good discrimination, calibration and clinical usefulness, which was validated by a Chinese cohort (1, 3, 5-year AUC: SEER cohort 0.873, 0.901, 0.875; Chinese cohort 0.867, 0.892, 0.874). Compared to the 8th staging system, the nomogram had higher C-index (0.87 vs 0.728, P < 0.001), clinical usefulness, increasing AUC value over time and improved 68%. Conclusion: The prognostic nomogram of resected NSCLC-NET performed better than the 8th TNM staging system. It may have certain value in risk stratification and survival prediction of patients with resected NSCLC-NET and help clinicians to take measures for high-risk patients in advance.

SLC7A5 is a lung adenocarcinoma-specific prognostic biomarker and participates in forming immunosuppressive tumor microenvironment.

Background: Amino acid metabolism participates in forming immunosuppressive tumor microenvironment. Amino acid transporters (AATs), as a gate for admission, remains to be studied. Materials and methods: We identified LUAD-specific prognostic AATs, SLC7A5 by differential expression analysis, logistic regression, machine learning, Kaplan-Meier analysis, AUC value filtrating and Cox regression. Then differential expression and distribution of SLC7A5 were depicted. Copy number variation, DNA methylation, transcriptional factors and ceRNA network were investigated to explore potential mechanism causing differential expression. The prognostic and clinical relation were evaluated by Kaplan-Meier analysis, Cox regression analysis. GSEA and GSVA were used to analyze altered pathways between SLC7A5 high- and low-groups. The expression of HLA-related genes and immune checkpoint genes, and immune cells infiltration were detected. SLC7A5 expression in immune cells was evaluated by single-cell sequencing data. IPS and an independent immunotherapy cohort assessed response rates of patients with distinct SLC7A5 expression. Proliferation assay and wound healing assay validated the effects of SLC7A5 on proliferation and migration of LUAD cells. Western blotting and cell viability assays were performed to detect mTORC1 pathway activity and sensitivity to rapamycin. Results: SLC7A5 was a LUAD-specific prognostic AAT and had significant differential expression in transcription and translation level. Methylation levels of cg00728300, cg00858400, cg12408911, cg08710629 were negative correlation with SLC7A5 expression. FOXP3 and TFAP2A were possible transcription factors and miR-30a-5p, miR-184, miR-195-5p may target SLC7A5 mRNA. SLC7A5 high-expression indicated poor prognosis and was an independent prognostic factor. mTORC1, cell cycle, DNA damage repair, response to reactive oxygen, angiogenesis, epithelial-mesenchymal transition (EMT) and various growth factors signaling pathways were activated in SLC7A5 high-expression group. Interestingly, SLC7A5 high-expression group had less immune-related genes expression and immune cells infiltration. Single-cell sequencing data also suggested SLC7A5 was downregulated in various T cells, especially effector T cells. Moreover, high SLC7A5 expression indicated poor immunotherapy efficacy and higher sensitivity to inhibitors of mTORC1 pathway, cell cycle and angiogenesis. SLC7A5 deficiency abrogated proliferation, migration and mTORC1 pathway activity. Conclusions: In summary, as a LUAD-specific prognostic AAT, SLC7A5 is involved in activation of multiple oncogenic pathways and indicates poor prognosis. Moreover, SLC7A5 may participate in forming immunosuppressive TME and is associated with low response of immunotherapy. SLC7A5 is promising to be a new diagnostic and prognostic biomarker and therapeutic target in LUAD.

Prognostic model of AU-rich genes predicting the prognosis of lung adenocarcinoma.

BACKGROUND: AU-rich elements (ARE) are vital cis-acting short sequences in the 3'UTR affecting mRNA stability and translation. The deregulation of ARE-mediated pathways can contribute to tumorigenesis and development. Consequently, ARE-genes are promising to predict prognosis of lung adenocarcinoma (LUAD) patients. METHODS: Differentially expressed ARE-genes between LUAD and adjacent tissues in TCGA were investigated by Wilcoxon test. LASSO and Cox regression analyses were performed to identify a prognostic genetic signature. The genetic signature was combined with clinicopathological features to establish a prognostic model. LUAD patients were divided into high- and low-risk groups by the model. Kaplan-Meier curve, Harrell's concordance index (C-index), calibration curves and decision curve analyses (DCA) were used to assess the model. Function enrichment analysis, immunity and tumor mutation analyses were performed to further explore the underlying molecular mechanisms. GEO data were used for external validation. RESULTS: Twelve prognostic genes were identified. The gene riskScore, age and stage were independent prognostic factors. The high-risk group had worse overall survival and was less sensitive to chemotherapy and radiotherapy (P < 0.01). C-index and calibration curves showed good performance on survival prediction in both TCGA (1, 3, 5-year ROC: 0.788, 0.776, 0.766) and the GSE13213 validation cohort (1, 3, 5-year ROC: 0.781, 0.811, 0.734). DCA showed the model had notable clinical net benefit. Furthermore, the high-risk group were enriched in cell cycle, DNA damage response, multiple oncological pathways and associated with higher PD-L1 expression, M1 macrophage infiltration. There was no significant difference in tumor mutation burden (TMB) between high- and low-risk groups. CONCLUSION: ARE-genes can reliably predict prognosis of LUAD and may become new therapeutic targets for LUAD.

Long non-coding RNA C5orf64 is a potential indicator for tumor microenvironment and mutation pattern remodeling in lung adenocarcinoma.

Understanding the synergistic and antagonistic effects of tumor microenvironment (TME) and tumor mutation pattern on lung adenocarcinoma (LUAD) is urgently needed. Herein, we applied ESTIMATE and CIBERSORT methods to calculate the ratio of immune and stromal components and TIICs proportion of LUAD samples from TCGA database. Immune-related genes were analyzed by Lasso regression analysis and used for ceRNA network construction. A 14-lncRNA immune-related signature was developed, among which C5orf64 was found to be positively correlated with abundances of M2 macrophages, monocytes, eosinophils and neutrophils, but negatively correlated with Tregs and plasma cells. PD-1, PD-L1 and CTLA-4 were demonstrated to be high expressed in high-level C5orf64 groups. However, C5orf64 had a negative correlation with TP53 mutation frequency. A novel model was built based on age, tumor stage and immune-related lncRNA signature. To conclude, lncRNA C5orf64 had potential to be an indicator for TME modulation and tumor mutation pattern remodeling in LUAD.

Comprehensive analyses of the heterogeneity and prognostic significance of tumor-infiltrating immune cells in non-small-cell lung cancer: Development and validation of an individualized prognostic model.

Understanding the role of tumor-infiltrating immune cells (TIICs) in non-small cell lung cancer (NSCLC) is critical to finding new prognostic biomarkers and improving prognostic evaluation. Herein, we aimed to comprehensively analyze tumor-infiltrating pattern of TIICs in NSCLC and build a TIICs-associated, risk-stratification prognostic model for clinical practice. We applied CIBERSORT and ESTIMATE computational methods to analyze RNA-seq samples of 852 NSCLC patients from The Cancer Genome Atlas (TCGA). Prognotic factors were identified by univariate and multivariate Cox regression analyses for overall survival (OS). A novel model was developed to predict the 1-, 3- and 5-year OS of NSCLC based on the TCGA cohort, validated by external validation cohorts (GSE31210, GSE37745), and then evaluated by C-indexes and calibration plots. Significant heterogeneity in the infiltrating patterns of TIICs was shown among various pathological subtypes of NSCLC and between different genders. Further analyses showed that abundances of naive B cells (NBCs), T cells and mast cells (MCs) were positively correlated with prognosis. Tumor samples with high T cells abundances tended to have higher expression levels of immune checkpoint genes (PD-1, PD-L1, CTLA-4). A new immune-gene related index (IGRI) was built by five immune-related differentially expressed genes (DEGs) including BTK, CCR2, CLEC10A, NCR3 and PRKCB, which were closely correlated with TIICs abundances and prognosis. Tumor stage, IGRI, abundances of NBCs, T cells, MCs and NK cells were significant independent prognostic factors and were included in the nomogram as predictors. The internal and external calibration plots of the nomogram were in excellent agreement. This study reveals that TIICs are significantly correlated with clinicopathological features and prognosis in NSCLC and thus can be potential prognostic biomarker or therapeutic target. The remarkable heterogeneity of TIICs suggests that specific infiltrating patterns of TIICs should also be taken into consideration when determining individualized immunotherapy strategies for NSCLC patients.

Development and validation of a prognostic model of resectable small-cell lung cancer: a large population-based cohort study and external validation.

BACKGROUND: Survival outcomes of patients with resected SCLC differ widely. The aim of our study was to build a model for individualized risk assessment and accurate prediction of overall survival (OS) in resectable SCLC patients. METHODS: We collected 1052 patients with resected SCLC from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were selected by COX regression analyses, based on which a nomogram was constructed by R code. External validation were performed in 114 patients from Shandong Provincial Hospital. We conducted comparison between the new model and the AJCC staging system. Kaplan-Meier survival analyses were applied to test the application of the risk stratification system. RESULTS: Sex, age, T stage, N stage, LNR, surgery and chemotherapy were identified to be independent predictors of OS, according which a nomogram was built. Concordance index (C-index) of the training cohort were 0.721, 0.708, 0.726 for 1-, 3- and 5-year OS, respectively. And that in the validation cohort were 0.819, 0.656, 0.708, respectively. Calibration curves also showed great prediction accuracy. In comparison with 8th AJCC staging system, improved net benefits in decision curve analyses (DCA) and evaluated integrated discrimination improvement (IDI) were obtained. The risk stratification system can significantly distinguish the ones with different survival risk. We implemented the nomogram in a user-friendly webserver. CONCLUSIONS: We built a novel nomogram and risk stratification system integrating clinicopathological characteristics and surgical procedure for resectable SCLC. The model showed superior prediction ability for resectable SCLC.

Cezanne contributes to cancer progression by playing a key role in the deubiquitination of IGF-1R.

Background: Degradation of insulin-like growth factor 1 receptor (IGF-1R) is mediated by internalization and endocytosis, for which ubiquitin-proteasome pathways play as a regulatory system. Cezanne expression is positively associated with IGF-1R expression. High Cezanne expression correlates with poor patient survival in NSCLC, yet the underlying mechanisms are not well defined. Methods: Co-Immunoprecipitation assay was performed to investigate the interactions between Cezanne and IGF-1R. A xenograft model was established to assess the efficacy of Cezanne on cancer progression in vivo. Cezanne overexpressing and Cezanne knockdown NSCLC cell lines were generated using lentiviral vectors. The effects of Cezanne and IGF-1R on cell proliferation of non-small-cell lung cancer were evaluated via Sulforhodamine B assay and colony formation assays. Results: Here, through co-Immunoprecipitation assay, we find Cezanne interacts with IGF-1R in tumor cells. Depletion of Cezanne promotes the ubiquitination and degradation of IGF-1R. Congruently, Cezanne regulates the protein level of IGF-1R and downstream AKT signaling pathway. Cezanne promotes proliferation of tumor cells in vitro and in vivo. In line with the change of IGF-1R downstream signaling pathway, IGF-1-induced growth signals recover cell proliferation of tumor cells with Cezanne knockdown. Conclusion: Mechanistically, Cezanne directly targets IGF-1R by deubiquitination and stabilization. This leads to AKT activation, which bolsters tumor cell growth in vitro and in vivo. These findings reveal Cezanne as a regulator of tumor cell proliferation via IGF-1R signaling pathway and a potential target for NSCLC therapy.

The role of surgery for atypical bronchopulmonary carcinoid tumor: Development and validation of a model based on Surveillance, Epidemiology, and End Results (SEER) database.

OBJECTIVES: The rarity of atypical carcinoid (AC) of lung and the lack of prospective clinical trials lead to limited knowledge of its biology, treatment information and prognosis. The current study analyzed AC patients from the Surveillance, Epidemiology, and End Results (SEER) database to better understand the clinical characteristics of this disease and build a prognostic nomogram for clinical practice. MATERIALS AND METHODS: A total of 507 AC patients with pathological confirmation from SEER database were performed with univariate Cox regression analyses for both overall survival (OS) and lung cancer specific survival (LCSS) analyses. Of the 507 observations, 464 were used in the multivariable Cox proportional hazards model as training cohort of new nomogram. A new nomogram was constructed based on the training cohort and validated by an external validation cohort to predict the 3-, 5- and 10-year OS of ACs. The accuracy and clinical practicability were separately tested by Harrell's C-indexes, calibration plots and decision curve analyses (DCA). RESULTS: Lobectomy and segmental resection were found to be protective factors for AC patients. Age, primary tumor size, N stage, M stage, surgery and regional lymph nodes examination were shown as significant prognostic factors in Cox regression analyses and included in the nomogram as predictors. The C-index in the training cohort for 3-, 5-, and 10-year OS were 0.722, 0.737 and 0.712, respectively. The internal and external calibration plots for predictions of the 3-, 5-, and 10-year OS were in excellent agreement. An online webserver was built based on the proposed nomogram for convenient clinical use. CONCLUSION: AC patients with lobectomy or segmental resection tended to have better OS and LCSS. A nomogram was constructed and validated to predict the OS for AC patients and to provide accurate and individualized survival predictions.

Survival nomogram for patients with initially diagnosed metastatic non-small-cell lung cancer: a SEER-based study.

Aim: Prognosis of patients with metastatic non-small-cell lung cancer differ widely. Methods: All patients were randomly divided into training or validation cohort. Cox-regression analyses were conducted to select independent predictors. We built a nomogram by R code and evaluated the accuracy and the reliability of the model using C-index, calibration curves and decision curve analyses. We made a risk classification system based on the nomogram. Results: In the validation cohort, C-index was 0.729 and 0.738 for 1- and 2-year overall survival. Calibration plots and decision curve analyses presented great prognostic accuracy and clinical applicability. Its prognostic accuracy preceded the American Joint Committee on Cancer staging with evaluated integrated discrimination improvement. Conclusion: The model can be a practical tool in treatment decision and individual counseling.

High PKD2 predicts poor prognosis in lung adenocarcinoma via promoting Epithelial-mesenchymal Transition.

Protein kinase D2 (PKD2) has been reported to be related with progression and invasion in various cancers. However, its prognostic value and the underlying mechanism in lung cancer remains unclear. Herein we evaluated the expression of PKD2 in lung adenocarcinoma and investigated its relationship with EMT. GSEA, TCGA and K-M plotter database were applied and revealed that high PKD2 expression predicted poor outcome and related with lymph nodes metastasis in lung cancer. IHC and qRT-PCR were performed and found PKD2 was elevated in lung adenocarcinoma and negatively related with OS (p = 0.015), PFS (p = 0.006) and the level of E-cadherin (p = 0.021). Experiment in lung adenocarcinoma cell lines demonstrated up-regulation of PKD2 led to high expression of mesenchymal markers (N-cadherin, vim, mmp9 et al.) and EMT transcription factors(zeb1, twist, snail), and the results were reversed when PKD2 was knocked down. Further investigation showed that abrogation of PKD2 inhibited A549 cell migration, invasion, proliferation and induced cell arrest in G2/M phase. We concluded that high expression of PKD2 was associated with poor prognosis and cancer progression in lung adenocarcinoma patients by promoting EMT.

Survival Outcomes for Patients with Surgical and Non-Surgical Treatments in Stages I-III Small-Cell Lung Cancer.

Objectives: Chemotherapy and radiation therapy are the standard treatments for patients with small-cell lung cancer (SCLC). However, recent studies suggest that patients with limited stage (I-III) SCLC may benefit from surgical treatment. This study was performed to evaluate the survival outcomes of surgery for stage I-III SCLC. Methods: This analysis used data from the Surveillance, Epidemiology, and End Results (SEER) database. All stage I-III (excluding N3 and Nx) SCLC patients received a diagnosis between 2004 and 2014. Overall survival (OS) and lung cancer-specific survival (LCSS) were determined by Kaplan-Meier analysis and compared using the log-rank test. A Cox proportional hazard model identified relevant survival variables. Results: A total of 4,780 histologically confirmed patients were identified from the SEER database, comprising 1,018 patients (21.3%) with stage I disease; 295 (6.2%) with stage II; and 3,467 (72.5%) with stage III disease. Among all of the patients, 520 had been treated with surgery, the majority (n = 344; 66.2%) of whom had stage I disease. The hazard ratio (HR) for OS and LCSS, in patients who underwent surgery, according to stage were as follows: OS, 0.369 and LCSS, 0.335 in stage I; OS, 0.549 and LCSS, 0.506 in stage II; and OS, 0.477 and LCSS, 0.456 in stage III (all p < 0.001). Patients who underwent surgery had significantly better OS, and lobectomy was associated with the best outcome. Conclusions: Surgical resection was associated with significantly improved OS outcomes and should be considered in the management of stage I-III SCLC.

Optimal managements of stage IIIA (N2) non-small cell lung cancer patients: a population-based survival analysis.

BACKGROUND: This study aimed to investigate the optimal management of stage IIIA (cN2) non-small cell lung cancer (NSCLC) patients and determine potential predictive factors. METHODS: We extracted patients diagnosed as NSCLC stage IIIA (cN2) between 2004 and 2011 from Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) and lung cancer-specific survival (LCSS) were compared among patients given different clinical managements by Kaplan-Meier method. Other variables such as age, sex and tumor size were analyzed to explore the factors associated with outcomes. RESULTS: A total of 98,700 IIIA-cN2 NSCLC patients were identified from SEER database. Survival of patients treated with surgery was better than that of patients treated by radiotherapy alone (P<0.001). Radiation prior to surgery significantly improved the survival in comparison with surgery alone (P<0.001). In the subgroups of OS analysis, age >65 (P=0.902), adenocarcinoma (P=0.279), tumor size ≤3 cm (P=0.170), well differentiated (P=0.360) patients, preoperative radiotherapy improved survival insignificantly compared with surgery alone. CONCLUSIONS: Preoperative radiation with surgery had the most encouraging survival outcomes in stage IIIA-cN2 NSCLC patients compared with radiation or surgery alone. No significant outcome improvement was shown between postoperative radiotherapy (PORT) and surgery alone.

Subcellular localization of ß-arrestin1 and its prognostic value in lung adenocarcinoma.

ß-Arrestins play important roles in cancer progression, and the subcellular localization of ß-arrestin1 has been receiving increasingly more attention. Intriguingly, several studies, including some of our previous work, showed that the effects of ß-arrestin1 on outcomes of cancer patients were controversial.Specimens were obtained from 133 patients with lung adenocarcinoma. Immunohistochemistry was used to detect the expression of ß-arrestin1 and p300 in the collected tissues. The Kaplan-Meier analysis and Cox proportional hazards regression were used to examine the relationship between ß-arrestin1 and patient survival.We found no significant association between ß-arrestin1 and clinicopathological variables. The Kaplan-Meier plot showed that patients with high expression of ß-arrestin1 (especially in the nucleus) had a poorer overall survival (OS) and shorter disease-free survival (DFS) (P = .026, P = .015). Additionally, high p300 expression also resulted in worse OS (P = .039). Following the univariate analysis, high expressions of nuclear ß-arrestin1 and p300 were classed as poor prognostic factors for both OS (P = .016) and DFS (P = .025).The expression of ß-arrestin1 in the nucleus is associated with increased malignant tendency of lung adenocarcinoma, and the predictive value of ß-arrestin1 may be optimized by combining information about the expression of p300 acetyltransferase.

Appropriate surgical modalities for stages T2a and T2b in the eighth TNM classification of lung cancer.

Patients with tumors of 3 to 5 cm were divided into stages T2a (3 to 4 cm) and T2b (4 to 5 cm) based on the 8th tumor-node-metastasis staging system for lung cancer. The objective of our study was to explore appropriate surgical modalities for the new stages, T2a and T2b. We selected 6,996 node-negative non-small-cell lung cancer patients with tumor sizes of 3 to 5 cm, diagnosed between 2009 and 2013, from the Surveillance, Epidemiology, and End Results (SEER) program. The Pearson [Formula: see text]. statistic test and Kaplan-Meier curve were used to analyze patient data. The prognosis of patients with stage T2a was significantly better than that of patients with stage T2b, both in overall survival (p = 0.018) and lung cancer specific survival (p = 0.001). For patients with stage T2a, lobectomy had a significantly better outcome. For patients with stage T2b, surgical modalities including pneumonectomy, segmental resection and lobectomy, had similar outcomes in terms of survival. Consequently, lobectomy was the most appropriate surgical treatment modality for new stage T2a patients, whereas, for new T2b patients, treatment outcome did not vary significantly with the choice of surgical modality.

Down-regulation of long non-coding RNA MEG3 indicates an unfavorable prognosis in non-small cell lung cancer: Evidence from the GEO database.

Long non-coding RNA (lncRNA) MEG3 (maternally expressed gene 3) is an imprinted gene that suppresses cells growth in various tumors. However, the association between MEG3 expression and prognosis in non-small cell lung cancer (NSCLC) has not been fully investigated. Seven datasets with 1144 patients were obtained from Gene Expression Omnibus (GEO) database (Affymetrix U133 Plus 2.0 platform). Association between MEG3 and other variables was tested using the chi-squared test. Kaplan-Meier survival analysis was carried out to explore the association between MEG3 expression and overall survival (OS)/progression free survival (PFS). Results of univariate and multivariate Cox regression analysis were represented in HR and 95%CI form. Summarized results and publication bias were showed by forest plots and funnel plots respectively. Differential expression of MEG3 was related to stage (GSE31210OS and GSE31210PFS), histology (GSE29013OS and GSE29013PFS) and gender (GSE29013PFS). In summary, low MEG3 expression was associated with shorter long-term survival time in several datasets (GSE3141 (p=0.039), GSE30219 (p=0.008) for OS and GSE30219 (p=0.048) for PFS). We found that MEG3 was an independent prognostic factor in GSE30219 for PFS (HR 0.666, 95%CI 0.458-0.969, p=0.033). The summarized results suggested that low MEG3 expression was a poor prognostic factor in NSCLC (HR=0.77, 95%CI 0.63-0.95). Specifically, the association between low MEG3 expression and poor prognosis was markedly significant in younger patients (≤60years old) (HR0.602, 95%CI 0.417-0.867, p=0.007). These findings indicate that MEG3 could be a novel prognostic factor for NSCLC patients.

Expressions of insulin-like growth factor receptor-1 and cezanne-1 in lung adenocarcinoma.

IGF1R (insulin-like growth factor receptor-1) was confirmed to play a significant role in the development of cancer. Cezanne-1 overexpression was considered to be associated with enhancement of EGFR signaling pathway and reduced degeneration of EGFR. There was a close relationship between EGFR and IGFR as previous study showed. Dynamic balance between receptor ubiquitination and deubiquitination was critical in the process of termination of IGF signaling pathway. So we conducted an IHC staining to initially prove the correlation. Cezanne-1 and IGF1R expressions were evaluated in 103 patients with lung adenocarcinoma using immunohistochemical (IHC) analysis. The relationship between expressions of cezanne-1 and IGF1R were analyzed by χ2 test. Kaplan-Meier method was used to generate the survival curve, and the statistical difference was calculated by log-rank test. We also used data in R2 system to verify the relationship between IGF1R and cezanne-1. R2 system showed there was a close correlation between IGF1R and cezanne-1. Positive expression of cezanne-1 was detected in 64.1% patients. A significant association was shown between cezanne-1 and IGF1R expression (p < 0.001). Multivariate analysis confirmed that both cezanne-1 and IGF1R expressions were independent prognostic factors for OS. (HR 2.96, 95% CI 1.090-8.060, p = 0.033; HR 2.273, 95% CI 1.016-5.085, p = 0.046, respectively). Our findings indicated both cezanne-1 and IGF1R expressions were negative independent predictive factors for the prognosis of lung adenocarcinoma, respectively. There was a close positive interrelationship between cezanne-1 and IGF1R expression.

Prognostic effects of preoperative obstructive pneumonitis or atelectasis and comparison with tumor size in non-small cell lung cancer.

BACKGROUND: In the eighth TNM staging system proposal, lung cancer with part or complete obstructive pneumonitis/atelectasis was classified to T2 category, and dividing lines of T category were changed. We conducted this study to search prognostic effect of preoperative obstructive pneumonitis/atelectasis and its comparison with tumor size. METHODS: We collected clinical characteristics, preoperative hematological indicators, follow-up information of 1,313 lung cancer patients. Chi-square test was used to search relationship between obstruction pneumonitis/atelectasis and other factors. Kaplan-Meier (K-M) curves and cox regression methods were used for survival analysis. RESULTS: Preoperative obstructive pneumonitis/atelectasis indicated shorter OS (HR: 1.308; 95% CI: 1.058-1.619) and RFS (HR: 1.276; 95% CI: 1.032-1.579) as an independent factor. In comparison with tumor size, we found patients with obstructive pneumonitis/atelectasis and T1 size tumor had similar prognosis to those with T2 size but without obstructive pneumonitis/atelectasis, and OS, RFS of patients with obstructive pneumonitis/atelectasis and T2 size were significantly shorter than those with T2 tumor size but without obstructive pneumonitis/atelectasis, while similar to patients with T3 tumor size but without obstructive pneumonitis/atelectasis according to division by the eighth edition. We also found obstructive pneumonitis/atelectasis was significantly related to higher neutrophil (P<0.001), platelet (P<0.001), monocyte (P<0.001), NLR (P<0.001), PLR (P=0.002), ESR (P<0.001) and lower LMR (P<0.001). CONCLUSIONS: Preoperative obstructive pneumonitis/atelectasis predicted poor survival independently in non-small cell lung cancer (NSCLC). And we suggested which T staging group the patients with obstructive pneumonitis/atelectasis would be divided to should depend on tumor size in the eighth TNM staging system.

Update of IGF-1 receptor inhibitor (ganitumab, dalotuzumab, cixutumumab, teprotumumab and figitumumab) effects on cancer therapy.

BACKGROUND: Prognostic studies of insulin-like growth factor-1 receptor(IGF-1R) inhibitors in cancer therapy had promising results in infratests, which exhibited that IGF-1R signalling was crucial in cancer cells growth. However, the conclusion of later clinical trials revealed a dim future for IGF-1R inhibitors to treat cancer. We conducted this analysis to figure out how IGF-1R inhibitors acted in clinical cancer therapy. MATERIAL AND METHODS: We searched up-to-date studies about the single agent of IGF-1R inhibitors or combination with other therapies in solid tumor. Five IGF-1R anti-agents were involved. The primary endpoint was progression-free survival (PFS). The secondary endpoint was overall survival (OS). RESULT: 17studies were enrolled. The results was not significant in overall survival (I2=37.1%, P=0.080, HR=1.08, 95% CI=0.97-1.21) and in progression-free survival (I2=0.0%, P=0.637, HR=1.05, 95% CI=0.98-1.12). OS for dalotuzumab, breast cancer, colorectal cancer, and PFS for prostate cancer even indicated harmful effects. CONCLUSION: So far, anti-IGF-1R mono-antibodies did not make significant differences in solid tumor prognosis. On the contrary, pessimistic effects were shown in the dalotuzumab, breast cancer, colorectal cancer and prostate cancer subgroups. Further studies of IGF-1R anti-agents were needed, but unwarranted in unselected patients by predictive biomarkers.