Inflammatory Risk Factors for Early Recurrence of Non‐Small Cell Lung Cancer Within One Year Following Curative Resection

Kobayashi, Satoru; Karube, Yoko; Matsumura, Yuichi; Nishihira, Morimichi; Inoue, Takashi; Araki, Osamu; Maeda, Shin; Chida, Masayuki

doi:10.1007/s00268-020-05612-0

Cited by 12 publications

(10 citation statements)

References 41 publications

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“…31 Early postoperative recurrence in individuals with NSCLC has been linked to a poor prognosis in several studies. 32 In our study, we reached the same conclusion, with the median OS for the ER and NER groups being 20.6 and 83.1 months, respectively. Therefore, it is critical to identify risk factors for early recurrence and this may improve the survival rate of patients with stage pIIIA-N2 NSCLC.…”

Section: Discussionsupporting

confidence: 81%

Predictive Risk Factors for Early Recurrence of Stage pIIIA-N2 Non-Small Cell Lung Cancer

Yu¹,

Du²,

Fang³

et al. 2021

CMAR

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Section: Discussionsupporting

confidence: 81%

Predictive Risk Factors for Early Recurrence of Stage pIIIA-N2 Non-Small Cell Lung Cancer

Yu¹,

Du²,

Fang³

et al. 2021

CMAR

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“…In recent years, inflammation has been demonstrated to be a vital factor in tumor growth, invasion, and metastasis, and the association of inflammation with several malignancies has been revealed (17)(18)(19)(20). Many studies have investigated SII in various cancers, including esophageal squamous cell carcinoma, non-small cell lung cancer, hepatocellular carcinoma, and germ-cell tumors (7,(21)(22)(23).…”

Section: Discussionmentioning

confidence: 99%

Systemic Immune-Inflammation Index Is a Prognostic Factor for Breast Cancer Patients After Curative Resection

Deng

et al. 2021

Front. Oncol.

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BackgroundThe preoperative systemic immune-inflammation index (SII) is correlated with prognosis in several malignancies. The aim of this study was to investigate the prognosis value of SII in patients with resected breast cancer.Materials and MethodsA total of 784 breast cancer patients who underwent surgical resection were consecutively investigated. The optimal cutoff value of SII was evaluated using the receiver operating characteristic (ROC) curve. The collection of SII with clinicopathological characteristic and prognosis was further evaluated.ResultsThe optimal cutoff value for SII in the prediction of survival was 514 according to ROC curve analysis. A high SII was significantly correlated with younger age (P = 0.037), PR status (P < 0.001), and HER2 status (P = 0.035). Univariate analysis revealed that SII (P < 0.001), T-stage (P < 0.001), lymph node involvement post-surgery (P = 0.024), and histological grade (P < 0.001) were significantly related to DFS, and SII (P < 0.001), T-stage (P = 0.003), lymph node involvement post-surgery (P = 0.006), and histological grade (P < 0.001) were significantly associated with OS. In multivariate analysis, a high SII was an independent worse prognostic factor for DFS (HR, 4.530; 95% CI, 3.279-6.258; P < 0.001) and OS (HR, 3.825; 95% CI, 2.594-5.640; P < 0.001) in all the enrolled patients. Furthermore, subgroup analysis of molecular subtype revealed that SII was significantly associated with prognosis in all subtypes.ConclusionPreoperative SII is a simple and useful prognostic factor for predicting long-term outcomes for breast cancer patients undergoing surgery.

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“…To promote the clinical application of the model, we also developed a nomogram only combing ERSS and TNM stages. Previous studies have reported risk models for LUAD ( 22 – 26 ). The following differences distinguish our study from other prediction models.…”

Section: Discussionmentioning

confidence: 99%

“…First, external validation is one of the most important parts of model destruction. Some studies used one or two external cohorts ( 25 , 26 ), while some only used internal validation ( 22 – 24 ). We used three independent external cohorts, and the model performed well in all cohorts.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a prognosis prediction model based on 18 endoplasmic reticulum stress-related genes for patients with lung adenocarcinoma

2022

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BackgroundEndoplasmic reticulum (ER) stress had a crucial impact on cell survival, proliferation, and metastasis in various cancers. However, the role of ER stress in lung adenocarcinoma remains unclear.MethodGene expression and clinical data of lung adenocarcinoma (LUAD) samples were extracted from The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets. ER stress score (ERSS) was constructed based on hub genes selected from 799 ER stress-related genes by least absolute shrinkage and selection operator (LASSO) regression. A Cox regression model, integrating ERSS and the TNM stage, was developed to predict overall survival (OS) in TCGA cohort and was validated in GEO cohorts. Gene set enrichment analysis (GSEA), single-sample GSEA (ssGSEA), and gene mutation analyses were performed to further understand the molecular features of ERSS. The tumor immune infiltration was evaluated by ESTIMATE, CIBERSORT, and xCell algorithms. The receiver operating characteristic (ROC) curves were used to evaluate the predictive value of the risk model. p< 0.05 was considered statistically significant.ResultsOne hundred fifty-seven differentially expressed genes (DEGs) were identified between tumor and para-carcinoma tissues, and 45 of them significantly correlated with OS. Next, we identified 18 hub genes and constructed ERSS by LASSO regression. Multivariate analysis demonstrated that higher ERSS (p< 0.0001, hazard ratio (HR) = 3.8, 95%CI: 2.8–5.2) and TNM stage (p< 0.0001, HR = 1.55, 95%CI: 1.34–1.8) were independent predictors for worse OS. The prediction model integrating ERSS and TNM stage performed well in TCGA cohort (area under the curve (AUC) at five years = 0.748) and three GEO cohorts (AUC at 5 years = 0.658, 0.717, and 0.739). Pathway enrichment analysis showed that ERSS significantly correlated with unfolded protein response. Meanwhile, pathways associated with the cell cycle, growth, and metabolism were significantly enriched in the high ERSS group. Patients with SMARCA4, TP53, and EGFR mutations showed significantly higher ERSS (p = 4e−04, 0.0027, and 0.035, respectively). Tissues with high ERSS exhibited significantly higher infiltration of M1 macrophages, activated dendritic cells, and lower infiltration of CD8+ T cells and B cells, which indicate an activated tumor antigen-presenting but suppressive immune response status.ConclusionWe developed and validated an ER stress-related risk model that exhibited great predictive value for OS in patients with LUAD. Our work also expanded the understanding of the role of ER stress in LUAD.

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Inflammatory Risk Factors for Early Recurrence of Non‐Small Cell Lung Cancer Within One Year Following Curative Resection

Cited by 12 publications

References 41 publications

Predictive Risk Factors for Early Recurrence of Stage pIIIA-N2 Non-Small Cell Lung Cancer

Predictive Risk Factors for Early Recurrence of Stage pIIIA-N2 Non-Small Cell Lung Cancer

Systemic Immune-Inflammation Index Is a Prognostic Factor for Breast Cancer Patients After Curative Resection

Development and validation of a prognosis prediction model based on 18 endoplasmic reticulum stress-related genes for patients with lung adenocarcinoma

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