Prediction of lymph node metastasis using the combined criteria of helical CT and mRNA expression profiling for non-small cell lung cancer.

To improve the diagnostic accuracy of nodal metastasis, we suggest new criteria for the prediction of nodal metastasis with combining CT and mRNA expression profiling. Gene signatures related to nodal metastasis were selected from a microarray using extracted mRNA of 112 patients who underwent surgical resection for non-small cell lung cancer. Included patients were randomized into two groups; the training set (n=79) and the test set (n=33). On the basis of the gene signatures, the chest CTs of the training set of patients were re-analyzed and we set up hypothetical criteria for nodal diagnosis. Thirty-one genes were selected from the mRNA expression profiling to separate the LN-metastasis prediction (+) and LN-metastasis prediction (-) groups. On the basis of these signatures, the criteria of lymph node was adjusted (1) in cases of 'LN-metastasis prediction (+)', mediastinal nodes greater than a 5mm in short axis diameter and detectable hilar nodes were considered as metastatic, and (2) in cases of 'LN-metastasis prediction (-), the conventional size criterion was applied for both mediastinal and hilar lymphadenopathies, except for enlarged nodes along with obstructive pneumonia. The sensitivity and accuracy for the nodal diagnosis were improved from 31% to 85% and 58% to 86%, respectively (p<0.05) by using the combined criteria of CT and the microarray results in the test set as compared to those of CT alone. Prediction of lymph node metastasis using combination of gene signatures and chest CT is superior to the CT-only diagnosis.

Identification of differentially expressed genes in microsatellite stable HNPCC and sporadic colon cancer.

BACKGROUND: Some sporadic colon cancers and hereditary nonpolyposis colorectal cancer (HNPCC) have been known by a constitutional defect in mismatch gene repair (MMR) and dysfunction in of this MMR system, which lead to an aberrant phenotype that can cause microsatellite instability. However, the clinicopathologic features of still existing microsatellite stable (MSS) colon cancer remain to be investigated. METHOD: We compared the gene expression patterns of nine tumor tissues of HNPCC and nine tumor tissues of sporadic colon cancer with their adjacent pathologically normal, MSS tissues by modified differential display-polymerase chain reaction, selected four potential marker genes, and confirmed their reproducibility by reverse transcriptase-polymerase chain reaction. RESULTS: Reg I, MLCK, and MYH11 in tumors of MSS HNPCC showed significant differences in gene expression pattern compared with the adjacent pathologically normal tissues (P = 0.028, P = 0.002, and P = 0.001, respectively). Similar differences in expression patterns for the same set of genes were seen between the sporadic colon cancer group and their adjacent pathologically normal tissues (P = 0.012, P = 0.003, and P = 0.002, respectively). CONCLUSION: We suggest that the three cancer-associated differentially expressed genes in MSS sporadic colon cancer or MSS HNPCC might be potential tumor markers.

The signature from messenger RNA expression profiling can predict lymph node metastasis with high accuracy for non-small cell lung cancer.

BACKGROUND: The extent of regional lymph node (LN) metastasis is the most important factor in the evaluation of resectability and prognosis of non-small cell lung cancer (NSCLC) to increase the chance of complete cure. The authors attempted to deduce a group of genes from the analysis of mRNA expression profiles of the tumor tissues of NSCLC patients with or without LN metastasis, and make a classification model for better prediction of LN metastasis. METHODS: The authors analyzed mRNA expression profiles of 79 NSCLC patients with or without LN metastasis, and deduced the gene signature for the predictive model of LN metastasis in lung cancer. The authors evaluated the predictive accuracy of each of four algorithms by applying them to another set of 33 NSCLC patients. Each algorithm's accuracy was calculated by 10-fold cross-validation, and a combined model showed a level of accuracy that was higher than any one of the better three component algorithms (i.e., ANN, DT, or NB). Avadis, SAS, ArrayXPath, and R-package were the statistical analysis software packages used. RESULTS: The authors selected 949 genes using a classical permutation t test (p < 0.01) and finally obtained a gene signature consisting of 31 genes by adjustment of multiple-hypothesis testing. The LN metastasis prediction model derived from the signature (31 genes) and their characteristic interactions provided a predictive accuracy of 84.85% when applied to a test set of 33 patients. CONCLUSIONS: The authors have demonstrated that their gene signature developed by the expression profiling of mRNAs from the primary tissue could predict the LN metastasis status of NSCLC.

RASSF1A is not appropriate as an early detection marker or a prognostic marker for non-small cell lung cancer.

Aberrant methylation of several tumor suppressor genes often occurs during the pathogenesis of lung cancer. RASSF1A is one of the tumor suppressor genes, and it is frequently inactivated by hypermethylation of its promoter region in a variety of human cancers, including lung cancer. It has recently been suggested that RASSF1A methylation was frequently observed in poorly differentiated tumors, and that it was correlated with adverse survival in lung adenocarcinoma (Tomizawa Y, et al., Clin Cancer Res 2002;8:2362-8). In this study, we investigated the pathogenetic and clinicopathologic significance of RASSF1A methylation for the development and/or progression of non small cell lung cancer (NSCLC). We examined 116 cases of NSCLC for the methylation status of RASSF1A. Methylation-specific analysis demonstrated that 40.5% (47 of 116) of the cases were methylated at the CpG sites in the promoter. Methylation of RASSF1A was associated with cellular differentiation (p = 0.0244) and it was related to survival (p = 0.0276). However, there was no association between RASSF1A methylation and the individual clinicopathologic features: TNM stage (p > 0.1), recurrence (p > 0.1), lymphatic permeation (p > 0.1) and smoking duration time (p > 0.1). Furthermore, we analyzed RASSF1A's probability as a prognostic marker by using stepwise Cox proportional hazard regression testing. As a result, the stage proved to be the most important factor (p = 0.0089), more than any other factors such as age, gender, cell type, methylation status, differentiation, smoking duration time, tumor size and lymph node permeation. There was no other significant factor other than stage and age. These results show that epigenetic inactivation of RASSF1A cannot be a prognostic marker of NSCLC.

The tumour suppressor RASSF1A regulates mitosis by inhibiting the APC-Cdc20 complex.

The tumour suppressor gene RASSF1A is frequently silenced in lung cancer and other sporadic tumours as a result of hypermethylation of a CpG island in its promoter. However, the precise mechanism by which RASSF1A functions in cell cycle regulation and tumour suppression has remained unknown. Here we show that RASSF1A regulates the stability of mitotic cyclins and the timing of mitotic progression. RASSF1A localizes to microtubules during interphase and to centrosomes and the spindle during mitosis. The overexpression of RASSF1A induced stabilization of mitotic cyclins and mitotic arrest at prometaphase. RASSF1A interacts with Cdc20, an activator of the anaphase-promoting complex (APC), resulting in the inhibition of APC activity. Although RASSF1A does not contribute to either the Mad2-dependent spindle assembly checkpoint or the function of Emi1 (ref. 1), depletion of RASSF1A by RNA interference accelerated the mitotic cyclin degradation and mitotic progression as a result of premature APC activation. It also caused a cell division defect characterized by centrosome abnormalities and multipolar spindles. These findings implicate RASSF1A in the regulation of both APC-Cdc20 activity and mitotic progression.