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Associations of MTA1 expression with CT features, pathology and prognosis of elderly patients with non-small cell lung cancer.

ABSTRACT: Associations of metastasis-associated protein 1 (MTA1) expression with computed tomography (CT) features, pathology and prognosis of elderly patients with non-small cell lung cancer (NSCLC), and its clinical significance were explored. A total of 98 elderly patients with NSCLC were selected and underwent CT examination. The expression of MTA1 in carcinoma tissues and para-carcinoma normal tissues was detected via immunohistochemistry, and its associations with CT features, pathology and prognosis were analyzed. The results manifested that the expression of MTA1 in carcinoma tissues was significantly higher than that in para-carcinoma normal tissues, and it was associated with the degree of differentiation, stage and lymph node metastasis (P<0.05). Besides, the high expression of MTA1 was also related to the spicule sign, pleural indentation and lymph node metastasis (P<0.05) as well as the CT perfusion parameter capillary permeability (PMB) (P<0.05), but not to blood volume (BV), blood flow (BF) or time to peak (TTP). Moreover, the patients with high expression of MTA1 had significantly shorter survival time and a remarkably lower 5-year survival rate than those with low expression of MTA1 (P<0.05). In conclusion, MTA1 plays a certain role in the occurrence and development of NSCLC in elderly patients and has an association with their prognosis, which can provide references for the treatment and prognosis of NSCLC, with important clinical significance.

SUBMITTER: Yang N

PROVIDER: S-EPMC7471726 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Associations of MTA1 expression with CT features, pathology and prognosis of elderly patients with non-small cell lung cancer.

Yang Ning N Li Chuanming C Han Xiao X Feng Zhihua Z Qiu Feng F Han Junqing J

Oncology letters 20200828 5

Associations of metastasis-associated protein 1 (MTA1) expression with computed tomography (CT) features, pathology and prognosis of elderly patients with non-small cell lung cancer (NSCLC), and its clinical significance were explored. A total of 98 elderly patients with NSCLC were selected and underwent CT examination. The expression of MTA1 in carcinoma tissues and para-carcinoma normal tissues was detected via immunohistochemistry, and its associations with CT features, pathology and prognosi ...[more]

PMID: 32934739

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Project description:BackgroundThe rapid aging of the population in Japan has been accompanied by an increased rate of surgery for lung cancer among elderly patients. It is thus an urgent priority to map out a treatment strategy for elderly patients with primary lung cancer. Although surgical resection remains standard treatment for early stage non-small-cell lung cancer (NSCLC), it is now essential to confirm the status of epidermal growth factor receptor (EGFR) gene mutations when planning treatment strategies. Furthermore, several studies have reported that EGFR mutations are an independent prognostic marker in NSCLC. However, the relations between age group and the molecular and pathological characteristics of NSCLC remain unclear. We studied the status of EGFR mutations in elderly patients with NSCLC and examined the relations of EGFR mutations to clinicopathological factors and outcomes according to age group.MethodsA total of 388 consecutive patients with NSCLC who underwent complete tumor resection in our hospital from 2006 through 2008 were studied retrospectively. Formalin-fixed, paraffin-embedded tissue sections were used to isolate DNA from carcinoma lesions. Mutational analyses of EGFR gene exons 19, 20, and 21 and KRAS gene exons 12 and 13 were performed by loop-hybrid mobility shift assay, a highly sensitive polymerase chain reaction-based method.ResultsEGFR mutations were detected in 185 (47.7%) and KRAS mutations were detected in 33 (8.5%) of the 388 patients. EGFR mutations were found in a significantly higher proportion of patients younger than 80 years (younger group; 178/359, 49.6%) than in patients 80 years or older (older group; 7/29, 24.1%) (P = 0.008). In contrast, KRAS mutations were more common in the older group (6/29, 20.7%) than in the younger group (27/359, 7.5%) (P = 0.014). The older group showed a trend toward a higher rate of 5-year overall survival among elderly patients with EGFR mutations (100%) than among those with wild-type EGFR (66.2%), but the difference was not significant.ConclusionsOur results suggest that the EGFR status of patients with NSCLC differs between patients 80 years or older and those younger than 80 years. EGFR mutation status might be a prognostic marker in elderly patients with completely resected NSCLC.

Project description:BackgroundThe prognosis of SCLC is poor and difficult to predict. The aim of this study was to explore whether a model based on radiomics and clinical features could predict the prognosis of patients with limited-stage small cell lung cancer (LS-SCLC).MethodsSimulated positioning CT images and clinical features were retrospectively collected from 200 patients with histological diagnosis of LS-SCLC admitted between 2013 and 2021, which were randomly divided into the training (n = 140) and testing (n = 60) groups. Radiomics features were extracted from simulated positioning CT images, and the t-test and the least absolute shrinkage and selection operator (LASSO) were used to screen radiomics features. We then constructed radiomic score (RadScore) based on the filtered radiomics features. Clinical factors were analyzed using the Kaplan-Meier method. The Cox proportional hazards model was used for further analyses of possible prognostic features and clinical factors to build three models including a radiomic model, a clinical model, and a combined model including clinical factors and RadScore. When a model has prognostic predictive value (AUC > 0.7) in both train and test groups, a nomogram will be created. The performance of three models was evaluated using area under the receiver operating characteristic curve (AUC) and Kaplan-Meier analysis.ResultsA total of 1037 features were extracted from simulated positioning CT images which were contrast enhanced CT of the chest. The combined model showed the best prediction, with very poor AUC for the radiomic model and the clinical model. The combined model of OS included 4 clinical features and RadScore, with AUCs of 0.71 and 0.70 in the training and test groups. The combined model of PFS included 4 clinical features and RadScore, with AUCs of 0.72 and 0.71 in the training and test groups. T stages, ProGRP and smoke status were the independent variables for OS in the combined model, whereas T stages, ProGRP and prophylactic cranial irradiation (PCI) were the independent factors for PFS. There was a statistically significant difference between the low- and high-risk groups in the combined model of OS (training group, p < 0.0001; testing group, p = 0.0269) and PFS (training group, p < 0.0001; testing group, p < 0.0001).ConclusionCombined models involved RadScore and clinical factors can predict prognosis in LS-SCLC and show better performance than individual radiomics and clinical models.

Dataset Information

Associations of MTA1 expression with CT features, pathology and prognosis of elderly patients with non-small cell lung cancer.

Publications

Associations of MTA1 expression with CT features, pathology and prognosis of elderly patients with non-small cell lung cancer.

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