• Asian Pacific Journal of Cancer Prevention
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• 제15권3호
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• pp.1197-1203
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• 2014

Background: Adenocarcinoma (ADC) is the most common histological type of lung cancer and its proportion is rising, especially in Asian non-smoking women. Recent studies suggest miR-25 may have diverse effects on the pathogenesis of different types of cancer. However, the role of miR-25 in lung cancer is still unknown. The aim of this study was to investigate the potential clinical value of miR-25 in non-smoking women with lung ADC. Patients and Methods: Quantitative RT-PCR was performed to evaluate the expression of miR-25 in 100 lung ADC tumor tissues and matched plasma samples and Pearson correlation tests were used to analyze the relationship between values. Associations of miR-25 expression with clinicopathological features were determined using the Student's t-test. To determine prognostic value, overall survival (OS) was evaluated using the Kaplan-Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazard model. Results: Expression of miR-25 in tissue was found to be associated with lymph node metastasis (P=0.021) and disease stage (P=0.012). Moreover, high miR-25 expression was also associated with poorer overall survival of women with lung ADC (P=0.008). Conclusion: Tissue miR-25 expression may be associated with tumor progression and have prognostic implications in female lung ADC patients.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.779-782
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• 2021

Survival time analysis is one of the main methods used by the pathologist to prognosis for cancer patients. In this paper, we strive to estimate the individual survival time of Adenocarcinoma (ADC) lung cancer patients from pathological images by adopting the convolutional neural network called the SurvPatchV1 model. First, we extracted tissue patches from the whole-slide images (WSI) to deal with extremely large dimensions of WSI. Then the survival time of each patch is estimated through the SurvPatchV1 model. Finally, the individual survival time of each patient is computed. The proposed method is trained and tested on the subset of the NLST dataset for ADC lung cancer. The result demonstrates that our model can obtain all tissue information in lieu of only tumor information in a whole pathological image to estimate the individual survival time.

• Asian Pacific Journal of Cancer Prevention
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• 제16권17호
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• pp.7529-7534
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• 2015

Background: The epidermal growth factor (EGF) plays important roles in non-small cell lung cancer (NSCLC) susceptibility and functional polymorphism in the EGF (+61A/G) gene has been linked to increased risk of NSCLC. This study aimed to evaluate the role of the EGF +61A/G polymorphism in risk of NSCLC adenocarcinoma (ADC) occurrence and survival in an Indian population. Materials and Methods: This casecontrol study included 100 histopathologically confirmed NSCLC (ADC) patients and 100 healthy controls. EGF (A61G) was genotyped by AS-PCR to elucidate putative associations with clinical outcomes. The association of the polymorphism with the survival of NSCLC patients was estimated by Kaplan-Meier curves. Results: It was found that EGF 61AG heterozygous and GG homozygous genotype is significantly associated with increased risk of NSCLC (ADC) occurrence compared to AA genotype, [OR 2.61 (1.31-5.18) and 3.25 (1.31-8.06), RR 1.51(1.15-2.0) and 1.72 (1.08-2.73) and RD 23.2 (6.90-39.5) and 28.53(7.0-50.1) for heterozygous AG (p=0.005) and homozygous GG (p=0.009)]. Patients homozygous for the G allele exhibited a significantly poor overall survival. The median survival time for patients with EGF 61 AA, AG, and GG genotypes was 10.5, 7.4, and 7.1 months (p=0.02), respectively. NSCLC (ADC) patients with GG + AG exhibited 7.3 months median survival compared to the AA genotype (p=0.009). Conclusions: The present study revealed that the EGF A61G genotype may be a novel independent prognostic marker to identify patients at higher risk of occurrence and an unfavourable clinical outcome.

• Asian Pacific Journal of Cancer Prevention
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• 제15권11호
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• pp.4629-4635
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• 2014

Background: Diffusion-weighted imaging (DWI) makes it possible to detect malignant tumors based on the diffusion of water molecules. However, it is uncertain whether DWI has advantages over FDG-PET for distinguishing malignant from benign pulmonary nodules and masses. Materials and Methods: One hundred-forty-three lung cancers, 17 metastatic lung tumors, and 29 benign pulmonary nodules and masses were assessed in this study. DWI and FDG-PET were performed. Results: The apparent diffusion coefficient (ADC) value ($1.27{\pm}0.35{\times}10^{-3}mm^2/sec$) of malignant pulmonary nodules and masses was significantly lower than that ($1.66{\pm}0.58{\times}10^{-3}mm^2/sec$) of benign pulmonary nodules and masses. The maximum standardized uptake value (SUVmax: $7.47{\pm}6.10$) of malignant pulmonary nodules and masses were also significantly higher than that ($3.89{\pm}4.04$) of benign nodules and masses. By using optimal cutoff values for ADC ($1.44{\times}10^{-3}mm^2/sec$) and for SUVmax (3.43), which were determined with receiver operating characteristics curves (ROC curves), the sensitivity (80.0%) of DWI was significantly higher than that (70.0%) of FDG-PET. The specificity (65.5%) of DWI was equal to that (65.5%) of FDG-PET. The accuracy (77.8%) of DWI was not significantly higher than that (69.3%) of FDG-PET for pulmonary nodules and masses. As the percentage of bronchioloalveolar carcinoma (BAC) component in adenocarcinoma increased, the sensitivity of FDG-PET decreased. DWI could not help in the diagnosis of mucinous adenocarcinomas as malignant, and FDG-PET could help in the correct diagnosis of 5 out of 6 mucinous adenocarcinomas as malignant. Conclusions: DWI has higher potential than PET in assessing pulmonary nodules and masses. Both diagnostic approaches have their specific strengths and weaknesses which are determined by the underlying pathology of pulmonary nodules and masses.

• Asian Pacific Journal of Cancer Prevention
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• 제16권5호
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• pp.1881-1895
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• 2015

Background: The vascular endothelial growth factor family has been implicated in tumorigenesis and metastasis. The prognostic value of each vascular endothelial growth factor family member, particular VEGF/VEGFR co-expression, in patients with non-small lung cancer remains controversial. Materials and Methods: Relevant literature was identified by searching PubMed, EMBASE and Web of Science. Studies evaluating expression of VEGFs and/or VEGFRs by immunohistochemistry or ELISA in lung cancer tissue were eligible for inclusion. Hazard ratios (HRs) and 95% confidence intervals (CIs) from individual study were pooled by using a fixed- or random-effect model, heterogeneity and publication bias analyses were also performed. Results: 74 studies covering 7,631 patients were included in the meta-analysis. Regarding pro-angiogenesis factors, the expression of VEGFA (HR=1.633, 95%CI: 1.490-1.791) and VEGFR1 (HR=1.924, 95%CI: 1.220-3.034) was associated separately with poor survival. Especially, VEGFA over-expression was an independent prognostic factor in adenocarcinoma (ADC) (HR=1.775, 95%CI: 1.384-2.275) and SCC (HR=2.919, 95%CI: 2.060-4.137). Co-expression of VEGFA/VEGFR2 (HR=2.011, 95%CI: 1.405-2.876) was also significantly associated with worse survival. For lymphangiogenesis factors, the expression of VEGFC (HR=1.611, 95%CI: 1.407-1.844) predicted a poor prognosis. Co-expression of VEGFC/VEGFR3 (HR=2.436, 95%CI: 1.468-4.043) emerged as a preferable prognostic marker. Conclusions: The expression of VEGFA (particularly in SCC and early stage NSCLC), VEGFC, VEGFR1 indicates separately an unfavorable prognosis in patients with NSCLC. Co-expression VEGFA/VEGFR2 is comparable with VEGFC/VEGFR3, both featuring sufficient discrimination value as preferable as prognostic biologic markers.