Prognostic value of nuclear area index in combination with the World Health Organization grading system for patients with renal cell carcinoma

Suppressive effects of RASAL2 on renal cell carcinoma via SOX2/ERK/p38 MAPK pathway

Metastatic renal cell carcinoma (RCC) is associated with poor prognosis. Ras protein activator like 2 (RASAL2) protein has been previously demonstrated to serves as a tumor suppressor in a variety of malignancies. Therefore, the aim of the present study was to investigate the role of RASAL2 in RCC. Reverse transcription-quantitative PCR, western blot analysis and immunohistochemistry were performed to measure mRNA and protein expression in RCC tissues, whilst immunofluorescence and western blotting were performed to evaluate protein expression in RCC cells. A Cell Counting Kit-8 and 5-bromo-2'-deoxyuridine staining were applied to determine cell viability, and Transwell assays were conducted to measure RCC cell invasion and migration. RASAL2 expression was identified to be downregulated in RCC tissues, which associate negatively with RCC pathological grade. Sox2 expression, in addition to ERK1/2 and p38 MAPK phosphorylation, were demonstrated to be increased in RCC tissues. In RCC cells, RASAL2 overexpression decreased the expression of Sox2 and the activation of ERK1/2 and p38 MAPK. Physiologically, RASAL2 overexpression decreased RCC cell viability, invasion and migration. The expression of metalloproteinase-2/9 and tissue inhibitor of metalloproteinase 1 were also identified to be decreased and increased by RASAL2 overexpression, respectively. By contrast, RASAL2 knockdown exerted opposite effects on RCC cells compared with those observed following RASAL2 overexpression. RASAL2 expression decreased RCC cell viability, migration and invasion, which was demonstrated to be associated with the inactivation of SOX2/ERK1/2/p38 MAPK signaling. These results suggest that RASAL2 may potentially serve as a potential target for the development of novel therapeutic intervention strategies against RCC.

Integrative Analysis of Pathological Images and Multi-Dimensional Genomic Data for Early-Stage Cancer Prognosis

The integrative analysis of histopathological images and genomic data has received increasing attention for studying the complex mechanisms of driving cancers. However, most image-genomic studies have been restricted to combining histopathological images with the single modality of genomic data (e.g., mRNA transcription or genetic mutation), and thus neglect the fact that the molecular architecture of cancer is manifested at multiple levels, including genetic, epigenetic, transcriptional, and post-transcriptional events. To address this issue, we propose a novel ordinal multi-modal feature selection (OMMFS) framework that can simultaneously identify important features from both pathological images and multi-modal genomic data (i.e., mRNA transcription, copy number variation, and DNA methylation data) for the prognosis of cancer patients. Our model is based on a generalized sparse canonical correlation analysis framework, by which we also take advantage of the ordinal survival information among different patients for survival outcome prediction. We evaluate our method on three early-stage cancer datasets derived from The Cancer Genome Atlas (TCGA) project, and the experimental results demonstrated that both the selected image and multi-modal genomic markers are strongly correlated with survival enabling effective stratification of patients with distinct survival than the comparing methods, which is often difficult for early-stage cancer patients.

Prognostic value of nuclear area index in patients with bladder cancer

BACKGROUND

To assess the prognostic usefulness of the nuclear area index (NAI), a new nuclear morphometric parameter expressed as the mean nuclear area (MNA) ratio of cancer to normal transitional cells in patients with bladder cancer, who have undergone radical cystectomy.

METHODS

Measurements of the nuclear areas of cancer and normal transitional cells were carried out on the histological slides of 73 patients with bladder cancer. The clinical usefulness of MNA, NAI, grade, and TNM categories for the prediction of the cause-specific survival of the patients was examined.

RESULTS

The median values of MNA and NAI in the 73 patients were 39 micro m2 and 1.2, respectively. Cause-specific survival rates of the patients were calculated according to stage (T1-2 vs T3-4), grade (grade 2 vs grade 3), MNA (<39 micro m2 vs>/=39 micro m2) and NAI value (<1.2 vs>/=1.2). Using univariate analysis, all these parameters were statistically significant prognostic factors. However, by multivariate analysis, NAI was the only independent variable for the survival of the patients (P < 0.01). Cause-specific survival rates of patients with NAI values of less than 1.2 were significantly higher than those with NAI values of 1.2 or more, in both grade 2 and grade 3 tumors.

CONCLUSIONS

These results suggest that NAI could provide improved prognostic information for patients with bladder cancer.