Ki Yeol Kim

Tumor‐stromal crosstalk in invasion of oral squamous cell carcinoma: a pivotal role of CCL7

Recent studies have shown that stromal fibroblasts have a more profound influence on the initiation and progression of carcinoma than was previously appreciated. This study aimed at investigating the reciprocal relationship between cancer cells and their associated fibroblasts at both the molecular and cellular level in oral squamous cell carcinoma (OSCC). To identify key molecular regulators expressed by carcinoma‐associated fibroblasts (CAF) that promote cancer cell invasion, microarrays were performed by comparing cocultured OSCC cells and CAF with monoculture controls. Microarray and real‐time PCR analysis identified marked upregulation of the chemokine (C‐C motif) ligand 7 (CCL7) in cocultured CAF. ELISA showed an elevated level of CCL7 secretion from CAF stimulated by coculture with OSCC cells. CCL7 promoted the invasion and migration of OSCC cells, and the invasiveness was inhibited by treatment with CCL7 neutralizing antibody. OSCC cells were shown to express CCR1, CCR2 and CCR3, receptors for CCL7, by RT‐PCR. In addition, treatment with anti‐CCR1 or anti‐CCR3 antibody inhibited CCL7‐induced OSCC cell migration, implicating that CCL7 promotes cancer cell migration through CCR1 and CCR3 on OSCC cells. Cytokine antibody array analysis of the supernatant from OSCC cell culture revealed that interleukin‐1α was an inducer of CCL7 secretion by CAF. This study confirms the reciprocal relationship of the molecular crosstalk regulating the invasion of OSCC and describes new potential targets for future therapy.

Significance of molecular markers in survival prediction of oral squamous cell carcinoma

An accurate system for predicting the survival of patients with oral squamous cell carcinoma (OSCC) will be useful for deciding appropriate therapies. The prediction accuracy of prediction models can be improved by using molecular biomarkers. We constructed a nomogram for predicting the survival of patients with OSCC using clinical variables and molecular markers.

Insulin-like growth factor II mRNA-binding protein 3: a novel prognostic biomarker for oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is caused by multiple factors, including carcinogen exposure. Insulin‐like growth factor II mRNA‐binding protein 3 (IMP3) is highly expressed in various cancer cells but is rarely expressed in normal cells. We investigated whether IMP3 can be used as a prognostic biomarker for OSCC.

Estimating the adjuvant chemotherapy effect in elderly stage II and III colon cancer patients in an observational study.

Adjuvant chemotherapy has been known as a standard treatment for patients with resected colon cancer. However, in elderly colon cancer patients, the characteristics of patients are heterogeneous with regard to life expectancy and comorbidities. Thus, with regard to the effectiveness of adjuvant chemotherapy for colon cancer, it is difficult to extrapolate data of clinical trials from the younger into the older general population.

Risk stratification of oral cancer patients using a combined prognostic factor including lymph node density and biomarker

PurposeIn this study, we aimed to validate the lymph node density (LND) as an independent prognostic factor of oral squamous cell carcinoma (OSCC) and identify a combined prognostic factor including LND, predicting better performance in risk stratification.MethodsWe reviewed the clinical, pathological variables and biomarker of 95 OSCC patients who underwent surgery. LND was calculated as the ratio of positive lymph nodes to total lymph nodes removed. Principle component analysis was performed to identify a combined predictor.ResultsMultivariate analysis showed that variables independently prognostic overall survival were IMP3 (hazard ratio [HR]xa0=xa03.01, 95% confidence interval [95% CI]xa0=xa01.17–7.75, Pxa0=xa00.022) in a model without LND and were IMP3 (HRxa0=xa03.64, 95% CIxa0=xa01.38–9.58, Pxa0=xa00.008) and LND (HRxa0=xa00.57, 95% CIxa0=xa00.57–1.75, Pxa0=xa00.322; HRxa0=xa02.45, 95% CIxa0=xa01.20–4.97, Pxa0=xa00.013) in a model with LND. The risk stratification using the combined prognostic factor was more significant (Pxa0=xa00.00117) than the conventional staging system and biomarker.ConclusionsThe LND was shown to be an independent prognostic factor in OSCC, and a combined factor including LND may be used for risk stratification of OSCC patients, which displayed the best performance.

Risk prediction for malignant conversion of oral epithelial dysplasia by hypoxia related protein expression

Aims: Increased aerobic glycolysis is a unique finding in cancers and hypoxia-related proteins are associated with aerobic glycolysis. Therefore, we aimed to investigate whether hypoxia-related proteins can be predictive markers for malignant conversion of oral premalignant lesions with epithelial dysplasia (OED). Methods: Expression of HIF-1&agr;, Glut-1 and CA9 were detected in clinical samples of eight normal oral mucosa, 85 transitional areas of oral squamous cell carcinoma (OSCC) and 28 OED with or without malignant conversion using immunohistochemistry and were also comparatively detected in immortalised human oral keratinocyte (IHOK) and OSCC cell lines under hypoxia using immunoblotting. Results: Sequential expression of HIF-1&agr;, Glut-1 and CA9 was found both in transitional areas of OSCC and cell lines of IHOK and OSCC under hypoxia, supporting hypoxia-aerobic glycolysis-acidosis axis. Expression of all proteins showed significant association with malignant conversion of OED and CA9 was an independent risk factor of malignant transformation of OED. But the predictability of malignant transformation was improved when all three proteins were applied together. Conclusion: High expression of CA9 was an independent predictive marker of malignant conversion. Moreover, the combined application of these three proteins may be useful to assess the risk of malignant conversion of OED.

Morphogenesis and biological significance of spindle cell transformation in a spindle cell carcinoma.

Our study investigated the histogenesis and biological significance of spindle cell carcinoma (SpCC) by comparing with moderately-well-differentiated squamous cell carcinoma (SCC) cell lines. Snail mRNA expression was readily detectable in the SpCC cell line, while E-cadherin was undetectable. SpCC cells showed lower proliferative and invasive activities than two other SCC cell lines. Culturing under air-liquid interface conditions promoted squamous cell differentiation, whereas fibroblastic differentiation after submerged culture with collagen, suggesting that the microenvironment may be a regulating factor of spindle cell differentiation as well as Snail expression and spindle cell change may not always entail the invasive behavior.

Novel and simple transformation algorithm for combining microarray data sets

BackgroundWith microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Such systematic differences present a substantial obstacle to the analysis of microarray data, resulting in inconsistent and unreliable information. Therefore, one of the most pressing challenges in the field of microarray technology is how to integrate results from different microarray experiments or combine data sets prior to the specific analysis.ResultsTwo microarray data sets based on a 17k cDNA microarray system were used, consisting of 82 normal colon mucosa and 72 colorectal cancer tissues. Each data set was prepared from either total RNA or amplified mRNA, and the difference of RNA source between these two data sets was detected by ANOVA (Analysis of variance) model. A simple integration method was introduced which was based on the distributions of gene expression ratios among different microarray data sets. The method transformed gene expression ratios into the form of a reference data set on a gene by gene basis. Hierarchical clustering analysis, density and box plots, and mixture scores with correlation coefficients revealed that the two data sets were well intermingled, indicating that the proposed method minimized the experimental bias. In addition, any RNA source effect was not detected by the proposed transformation method. In the mixed data set, two previously identified subgroups of normal and tumor were well separated, and the efficiency of integration was more prominent in tumor groups than normal groups. The transformation method was slightly more effective when a data set with strong homogeneity in the same experimental group was used as a reference data set.ConclusionProposed method is simple but useful to combine several data sets from different experimental conditions. With this method, biologically useful information can be detectable by applying various analytic methods to the combined data set with increased sample size.

A weighted sample size for microarray datasets that considers the variability of variance and multiplicity.

Microarray experiments are often performed to detect differently expressed genes among different clinical phenotypes. The method used to calculate the appropriate sample size for this purpose differs from the sample size calculation used for general clinical experiments, because microarrays include tens of thousands of genes. We proposed a sample size calculation method that considers variance among an entire gene set and used the Bonferroni correction to address the multiplicity problem. Specifically, by adjusting for the multiplicity problem, the existing equation for sample size calculation was modified based on the Bonferroni correction. By k-means cluster analysis, the variances across all genes can be divided into several groups with similar values, and the sample sizes for each group were subsequently calculated and weight-averaged. The results of this study show that the sample size was related to the number of genes on a chip. The weighted sample size, calculated by the proposed method, preserved the Type I error for selection of significant genes within a microarray data set.

Angiogenic factor thymidine phosphorylase associates with angiogenesis and lymphangiogenesis in the intestinal-type gastric cancer

Summary As an angiogenic factor, thymidine phosphorylase (TP) expression in primary tumours has been thought to be a risk factor for lymph node (LN) and hepatic metastasis in patients with gastric adenocarcinoma. However, the molecular basis for the induction of metastasis by TP is largely unknown. We aim to elucidate the role of TP expression in gastric cancer neovascularisation and LN metastasis. The angiogenic and lymphangiogenic activity (CD31, D2-40, Ki-67, VEGFC, VEGFR3) and expression status of TP were detected in 103 resected human gastric carcinoma samples by immunohistochemistry. The influence of TP expression on neovascularisation and cancer cell invasion was further comparatively investigated in two groups of nude mice intraperitoneally injected with TP overexpressing MKN-45 cells (MKN-45/TP) and control cells (MKN-45/CV). In gastric cancer tissues, we found that high TP expression and various angiogenic and lymphangiogenic activities were significantly associated with poor prognostic outcomes. In addition, TP expression was also found to be associated with neovascularisation activity of gastric cancer tissues. In vivo, the MKN-45/TP group exhibited significantly increased infiltrating tumour nodules and neovascularisation activity compared to the MKN-45/CV group. TP could strongly influence gastric cancer progression via the dual activities of angiogenesis and lymphangiogenesis.