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Low expression of SerpinB2 is associated with reduced survival in lung adenocarcinomas.

ABSTRACT: Lung cancer is a leading cause of cancer deaths worldwide and new biomarkers are of utmost importance. Studies have indicated that the anti-plasminogen activators SerpinB2 and Neuroserpin, and the adhesion molecule L1CAM, have a coordinated impact on development of metastasis. Here, we examined whether expression of these markers was associated with clinico-pathologic characteristics and prognosis in resected non-small cell lung cancer (NSCLC). Surgical specimens from 438 NSCLC patients treated at Haukeland University Hospital, Bergen, Norway (1993-2010) were included (median age 68 years; 213 adenocarcinomas, 135 squamous cell carcinomas, 90 others). Representative tumor sections were stained for SerpinB2, Neuroserpin, and L1CAM. Low expression of SerpinB2 was associated with reduced lung cancer specific survival (LCSS) in adenocarcinomas (p = 0.017), also in stage I (p = 0.031). In contrast, high SerpinB2 was associated with reduced LCSS in stage I squamous cell carcinomas (p = 0.022). Although Neuroserpin and L1CAM showed some associations with clinico-pathologic phenotype, there were no associations with survival. In multivariate survival analysis of adenocarcinomas, low SerpinB2 demonstrated independent prognostic value (HR 1.8, p = 0.008). In summary, low expression of SerpinB2 in lung adenocarcinomas was an independent prognostic factor. In contrast to findings by others, we found no impact of L1CAM on survival.

SUBMITTER: Ramnefjell M

PROVIDER: S-EPMC5710879 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Low expression of SerpinB2 is associated with reduced survival in lung adenocarcinomas.

Ramnefjell Maria M Aamelfot Christina C Helgeland Lars L Akslen Lars A LA

Oncotarget 20171003 53

Lung cancer is a leading cause of cancer deaths worldwide and new biomarkers are of utmost importance. Studies have indicated that the anti-plasminogen activators SerpinB2 and Neuroserpin, and the adhesion molecule L1CAM, have a coordinated impact on development of metastasis. Here, we examined whether expression of these markers was associated with clinico-pathologic characteristics and prognosis in resected non-small cell lung cancer (NSCLC). Surgical specimens from 438 NSCLC patients treated ...[more]

PMID: 29207598

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Project description:AimThis study is aimed at building a risk model based on the genes that significantly altered the proliferation of lung adenocarcinoma cells and exploring the underlying mechanisms.MethodsThe data of 60 lung adenocarcinoma cell lines in the Cancer Dependency Map (Depmap) were used to identify the genes whose knockout led to dramatical acceleration or deacceleration of cell proliferation. Then, univariate Cox regression was performed using the survival data of 497 patients with lung adenocarcinoma in The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) model was used to construct a risk prediction score model. Patients with lung adenocarcinoma from TCGA were classified into high- or low-risk groups based on the scores. The differences in clinicopathologic, genomic, and immune characteristics between the two groups were analyzed. The prognosis of the genes in the model was verified with immunohistochemical staining in 100 samples from the Department of Thoracic Surgery, Zhongshan Hospital, and the alteration in the proliferation rate was checked after these genes were knocked down in lung adenocarcinoma cells (A549 and H358).ResultsA total of 55 genes were found to be significantly related to survival by combined methods, which were crucial to tumor progression in functional enrichment analysis. A six-gene-based risk prediction score, including the proteasome subunit beta type-6 (PSMB6), the heat shock protein family A member 9 (HSPA9), the deoxyuridine triphosphatase (DUT), the cyclin-dependent kinase 7 (CDK7), the polo-like kinases 1 (PLK1), and the folate receptor beta 2 (FOLR2), was built using the LASSO method. The high-risk group classified with the score model was characterized by poor overall survival (OS), immune infiltration, and relatively higher mutation load. A total of 9864 differentially expressed genes and 138 differentially expressed miRNAs were found between the two groups. Also, a nomogram comparing score model, age, and the stage was built to predict OS for patients with lung adenocarcinoma. Using immunohistochemistry, the expression levels of PSMB6, HSPA9, DUT, CDK7, and PLK1 were found to be higher in lung adenocarcinoma tissues of patients, while the expression of FOLR2 was low, which was consistent with survival prediction. The knockdown of PSMB6 and HSPA9 by siRNA significantly downregulated the proliferation of A549 and H358 cells.ConclusionThe proposed score model may function as a promising risk prediction tool for patients with lung adenocarcinoma and provide insights into the molecular regulation mechanism of lung adenocarcinoma.

Project description:Although the most predominant subtype of invasive lung adenocarcinoma has been reported to have clinical significance, a major limitation of this concept is that most tumors are mixed-subtype. Therefore, we aimed to determine the individual prognostic significance of each subtype and also attempted to establish a pathologic index that reflects the pathologic subtypes and overall heterogeneity of lung adenocarcinomas and evaluated its prognostic significance. The individual prognostic impact of each subtype was assessed from the development cohort using the disease-free survival (DFS) curve of a previous large-scale study. Hazard ratios (HRs) from the development cohort were 1, 1.025, 1.059, 1.495, and 1.160 for the lepidic, acinar, papillary, micropapillary, and solid pattern subtype, respectively. Based on the calculated HR of each subtype, four indices representing pathologic heterogeneity were developed. The first and second indices were defined as the sum of the proportions of each subtype multiplied by their HRs, with the addition of either entropy or Gini coefficient, respectively. The third index was calculated as the sum of all subtype percentages multiplied by their HRs. To emphasize heterogeneity, the fourth index was defined as the simple arithmetic sum of the scores of the subtypes multiplied by their HRs. Each subtype was assigned a score of 0 if the subtype was absent and a score of 1 if the subtype was present in a binary fashion. We applied these four pathologic indices to a validation group of 148 patients with comprehensive histologic subtyping for completely resected lung adenocarcinomas. DFS curves were plotted and predictive ability of each pathologic index was evaluated. Among the four pathologic indices, only pathologic index 3 enabled significant patient stratification in the validation cohort according to DFS (P = 0.004) and showed the highest Harrell's C index of 0.691 of all four pathologic indices. In conclusion, we estimated the HR of each subtype and generated four pathologic indices that reflect heterogeneity. One of these, index 3, the pathologic heterogeneity index based on the sum of all subtype percentages multiplied by their HR, possesses good prognostic ability for predicting survival in patients with lung adenocarcinoma.

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Low expression of SerpinB2 is associated with reduced survival in lung adenocarcinomas.

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Low expression of SerpinB2 is associated with reduced survival in lung adenocarcinomas.

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