Masaru Ushijima

ATP Citrate Lyase: Activation and Therapeutic Implications in Non–Small Cell Lung Cancer

Enhanced glucose and lipid metabolism is one of the most common properties of malignant cells. ATP citrate lyase (ACLY) is a key enzyme of de novo fatty acid synthesis responsible for generating cytosolic acetyl-CoA and oxaloacetate. To evaluate its role in lung cancer progression, we here analyzed ACLY expression in a subset of human lung adenocarcinoma cell lines and showed a relationship with the phosphatidyl-inositol-3 kinase-Akt pathway. The introduction of constitutively active Akt into cells enhanced the phosphorylation of ACLY, whereas dominant-negative Akt caused attenuation. In human lung adenocarcinoma samples, ACLY activity was found to be significantly higher than in normal lung tissue. Immunohistochemical analysis further showed phosphorylated ACLY overexpression in 162 tumors, well-correlating with stage, differentiation grade, and a poorer prognosis. Finally, to show the therapeutic potential and mechanism of ACLY inhibition for lung cancer treatment, we assessed the effect of RNA interference targeting ACLY on lipogenesis and cell proliferation in A549 cells. ACLY inhibition resulted in growth arrest in vitro and in vivo. Interestingly, increased intracellular lipids were found in ACLY knockdown cells, whereas de novo lipogenesis was inhibited. Supplementation of insulin could rescue the proliferative arrest elicited by ACLY inhibition; however, in contrast, fatty acid palmitate induced cell death. Taken together, these findings suggest that ACLY is involved in lung cancer pathogenesis associated with metabolic abnormality and might offer a novel therapeutic target.

Long noncoding RNA HOTAIR is relevant to cellular proliferation, invasiveness, and clinical relapse in small‐cell lung cancer

Small‐cell lung cancer (SCLC) is a subtype of lung cancer with poor prognosis. To identify accurate predictive biomarkers and effective therapeutic modalities, we focus on a long noncoding RNA, Hox transcript antisense intergenic RNA (HOTAIR), and investigated its expression, cellular functions, and clinical relevance in SCLC. In this study, HOTAIR expression was assessed in 35 surgical SCLC samples and 10 SCLC cell lines. The efficacy of knockdown of HOTAIR by siRNA transfection was evaluated in SBC‐3 cells in vitro, and the gene expression was analyzed using microarray. HOTAIR was expressed highly in pure, rather than combined, SCLC (P = 0.012), that the subgroup with high expression had significantly more pure SCLC (P = 0.04), more lymphatic invasion (P = 0.03) and more relapse (P = 0.04) than the low‐expression subgroup. The knockdown of HOTAIR in SBC‐3 cells led to decreased proliferation activity and decreased invasiveness in vitro. Gene expression analysis indicated that depletion of HOTAIR resulted in upregulation of cell adhesion‐related genes such as ASTN1, PCDHA1, and mucin production‐related genes such as MUC5AC, and downregulation of genes involved in neuronal growth and signal transduction including NTM and PTK2B. Our results suggest that HOTAIR has an oncogenic role in SCLC and could be a prognostic biomarker and therapeutic target.

Identification of a predictive gene expression signature of cervical lymph node metastasis in oral squamous cell carcinoma

An accurate assessment of the cervical lymph node metastasis status in oral cavity cancer not only helps predict the prognosis of patients, but also helps surgeons to perform the appropriate treatment. We investigated the utilization of microarray technology focusing on the differences in gene expression profiles between primary tumors of oral squamous cell carcinoma that had metastasized to cervical lymph nodes and those that had not metastasized in the hope of finding new biomarkers to serve for diagnosis and treatment of oral cavity cancer. To design this experiment, we prepared two groups: the learning case group with 30 patients and the test case group with 13 patients. All tissue samples were performed using laser captured microdissection to yield cancer cells, and RNA was isolated from purified cancer cells. To identify a predictive gene expression signature, the different gene expressions between the two groups with and without metastasis in the learning case (n = 30) were analyzed, and the 85 genes expressed differentially were selected. Subsequently, to construct a more accurate prediction model, we further selected the genes with a high power for prediction from the 85 genes using the AdaBoost algorithm. The eight candidate genes, DCTD, IL‐15, THBD, GSDML, SH3GL3, PTHLH, RP5‐1022P6 and C9orf46, were selected to achieve the minimum error rate. Quantitative reverse transcription–polymerase chain reaction was carried out to validate the selected genes. From these statistical methods, the prediction model was constructed including the eight genes and this model was evaluated by using the test case group. The results in 12 of 13 cases (∼92.3%) were predicted correctly. (Cancer Sci 2007; 98: 740–746)

Prognostic factors and the therapeutic strategy for patients with bone metastasis from differentiated thyroid carcinoma.

BACKGROUND The treatment of bone metastasis in association with thyroid cancer represents a difficult challenge. Given the paucity of patients with bone metastasis and the difficulty of treating this disease, few studies have investigated the clinical features and prognostic factors of bone metastasis from differentiated thyroid cancer. METHODS During the 31-year-period from 1976 to 2006, a total of 1,398 patients underwent initial thyroidectomy at Cancer Institute Hospital for differentiated thyroid carcinomas, including standard papillary thyroid carcinoma, papillary microcarcinoma (primary tumor diameter < or =1.0 cm), and follicular thyroid carcinoma. Among these, 25 (2%) patients displayed bone metastasis at initial presentation (synchronous) and 27 patients showed bone metastasis during follow-up (metachronous). The records for these 52 patients were reviewed retrospectively to identify prognostic factors and analyze treatment strategies. RESULTS Univariate analysis for disease-specific survival indicated metachronous bone metastasis and the presence of distant metastasis at sites other than bone as indicators of significantly worse prognosis. The type of cancer (papillary thyroid carcinoma versus follicular thyroid carcinoma) was not a significant indicator of prognosis; however, patients with papillary microcarcinoma showed significantly worse survival than patients with standard papillary and follicular thyroid carcinoma. A significant survival advantage was observed among patients who underwent radioactive iodine therapy, and better prognosis seemed to be obtained with greater doses of radioactive iodine. Operative resection of metastatic bone lesions also seemed to be associated with better prognosis. A multivariate analysis for disease-specific survival identified the coexistence of distant metastasis at sites other than bone as the only independent variable indicative of poor prognosis. CONCLUSION In the absence of definitive, effective treatments for this disease, radioactive iodine therapy combined with resection of bone metastasis, wherever possible, seems to represent the most potent therapy available. Although bone metastasis is a strong sign of poor prognosis, early detection and administration of appropriate therapy using radioactive iodine seems likely to improve the survival rate and quality of life in patients with bone metastasis from differentiated thyroid carcinoma.

Molecular markers associated with lymph node metastasis in pancreatic ductal adenocarcinoma by genome-wide expression profiling.

Lymph node metastasis (LNM) is the most important prognostic factor in patients undergoing surgical resection of pancreatic ductal adenocarcinoma (PDAC). In this study, we aimed to identify molecular markers associated with LNM in PDAC using genome‐wide expression profiling. In this study, laser microdissection and genome‐wide transcriptional profiling were used to identify genes that were differentially expressed between PDAC cells with and without LNM obtained from 20 patients with PDAC. Immunohistochemical staining was used to confirm the clinical significance of these markers in an additional validation set of 43 patients. In the results, microarray profiling identified 46 genes that were differently expressed between PDAC with and without LNM with certain significance. Four of these biomarkers were validated by immunohistochemical staining for association with LNM in PDAC in an additional validation set of patients. In 63 patients with PDAC, significant LNM predictors in PDAC elucidated from multivariate analysis were low expression of activating enhancer binding protein 2 (AP2α) (P = 0.012) and high expression of mucin 17 (MUC17) (P = 0.0192). Furthermore, multivariate analysis revealed that AP2α‐low expression and MUC17‐high expression are independent prognostic factors for poor overall survival (P = 0.0012, 0.0001, respectively). In conclusion, AP2α and MUC17 were independent markers associated with LNM of PDAC. These two markers were also associated with survival in patients with resected PDAC. We demonstrate that AP2α and MUC17 may serve as potential prognostic molecular markers for LNM in patients with PDAC. (Cancer Sci 2009)

Genotyping of single nucleotide polymorphism using model-based clustering

MOTIVATION Single nucleotide polymorphisms have been investigated as biological markers and the representative high-throughput genotyping method is a combination of the Invader assay and a statistical clustering method. A typical statistical clustering method is the k-means method, but it often fails because of the lack of flexibility. An alternative fast and reliable method is therefore desirable. RESULTS This paper proposes a model-based clustering method using a normal mixture model and a well-conceived penalized likelihood. The proposed method can judge unclear genotypings to be re-examined and also work well even when the number of clusters is unknown. Some results are illustrated and then satisfactory genotypings are shown. Even when the conventional maximum likelihood method and the typical k-means clustering method failed, the proposed method succeeded.

ASCL1-coexpression profiling but not single gene expression profiling defines lung adenocarcinomas of neuroendocrine nature with poor prognosis

BACKGROUND Lung adenocarcinoma is heterogeneous regarding histology, etiology and prognosis. Although there have been several attempts to find a subgroup with poor prognosis, it is unclear whether or not adenocarcinoma with neuroendocrine (NE) nature has unfavorable prognosis. MATERIALS AND METHODS To elucidate whether a subtype of adenocarcinoma with NE nature has poor prognosis, we performed gene expression profiling by cDNA microarray for 262 Japanese lung cancer and 30 normal lung samples, including 171 adenocarcinomas, 56 squamous cell carcinomas and 35 NE tumors. A co-expression gene set with ASCL1, an NE master gene, was utilized to classify tumors by non-negative matrix factorization, followed by validation using an ASCL1 knock-down gene set in DMS79 cells as well as an independent cohort (n=139) derived from public microarray databases as a test set. RESULTS The co-expression gene set classified the adenocarcinomas into alveolar cell (AL), squamoid, and NE subtypes. The NE subtype, which clustered together almost all the NE tumors, had significantly poorer prognosis than the AL subtype that clustered with normal lung samples (p=0.0075). The knock-down gene set also classified the 171 adenocarcinomas into three subtypes and this NE subtype also had the poorest prognosis. The co-expression gene set classified the independent database-derived American cohort into two subtypes, with the NE subtype having poorer prognosis. None of the single NE gene expression was found to be linked to survival difference. CONCLUSION Co-expression gene set with ASCL1, rather than single NE gene expression, successfully identifies an NE subtype of lung adenocarcinoma with poor prognosis.

Functional in vivo optical imaging of tumor angiogenesis, growth, and metastasis prevented by administration of anti-human VEGF antibody in xenograft model of human fibrosarcoma HT1080 cells

Angiogenesis plays a crucial role in cancer progression and metastasis. Thus, blocking tumor angiogenesis is potentially a universal approach to prevent tumor establishment and metastasis. In this study, we used in vivo and ex vivo fluorescence imaging to show that an antihuman vascular endothelial growth factor (VEGF) antibody represses angiogenesis and the growth of primary tumors of human fibrosarcoma HT1080 cells in implanted nude mice. Interestingly, administering the antihuman VEGF antibody reduced the development of new blood vessels and normalized pre‐existing tumor vasculature in HT1080 cell tumors. In addition, antihuman VEGF antibody treatment decreased lung metastasis from the primary tumor, whereas it failed to block lung metastasis in a lung colonization experiment in which tumor cells were injected into the tail vein. These results suggest that VEGF produced by primary HT1080 cell tumors has a crucial effect on lung metastasis. The present study indicates that the in vivo fluorescent microscopy system will be useful to investigate the biology of angiogenesis and test the effectiveness of angiogenesis inhibitors. (Cancer Sci 2009)

Development of imaging mass spectrometry (IMS) dataset extractor software, IMS convolution

Imaging mass spectrometry (IMS) is a powerful tool for detecting and visualizing biomolecules in tissue sections. The technology has been applied to several fields, and many researchers have started to apply it to pathological samples. However, it is very difficult for inexperienced users to extract meaningful signals from enormous IMS datasets, and the procedure is time-consuming. We have developed software, called IMS Convolution with regions of interest (ROI), to automatically extract meaningful signals from IMS datasets. The processing is based on the detection of common peaks within the ordered area in the IMS dataset. In this study, the IMS dataset from a mouse eyeball section was acquired by a mass microscope that we recently developed, and the peaks extracted by manual and automatic procedures were compared. The manual procedure extracted 16 peaks with higher intensity in mass spectra averaged in whole measurement points. On the other hand, the automatic procedure using IMS Convolution easily and equally extracted peaks without any effort. Moreover, the use of ROIs with IMS Convolution enabled us to extract the peak on each ROI area, and all of the 16 ion images on mouse eyeball tissue were from phosphatidylcholine species. Therefore, we believe that IMS Convolution with ROIs could automatically extract the meaningful peaks from large-volume IMS datasets for inexperienced users as well as for researchers who have performed the analysis.

Incidence and prediction of invasive disease and nodal metastasis in preoperatively diagnosed ductal carcinoma in situ

For breast cancer patients with a preoperative diagnosis of ductal carcinoma in situ (DCIS), sentinel lymph node (SN) biopsy has been proposed as an axillary staging procedure in selected patients with a higher likelihood of having occult invasive lesions. With detailed histological examination of primary tumors and molecular whole‐node analysis of SNs, we aimed to validate whether this selective application accurately identifies patients with SN metastasis. The subjects were 336 patients with a preoperative needle‐biopsy diagnosis of DCIS who underwent SN biopsy using the one‐step nucleic acid amplification assay in the period 2009–2011. The incidence and preoperative predictors of upstaging to invasive disease on final pathology and SN metastasis, and their correlation, were investigated. Of the 336 patients, 113 (33.6%) had invasive disease, and 6 (1.8%) and 17 (5.0%) had macro‐ and micrometastasis in axillary nodes respectively. Of the 113 patients with invasive disease, 4 (3.5%) and 9 (8.0%) had macro‐ and micrometastasis. Predictors of invasive disease included palpability, mammographic mass, and calcifications (spread >20 mm), and intraductal solid structure, but no predictor was found for SN metastasis. Therefore, even though occult invasive disease was found at final pathology, most of the patients had no metastasis or only micrometastasis in axillary nodes. Predictors of invasive disease and SN metastasis were not completely consistent, so the selective SN biopsy for patients with a higher risk of invasive disease may not accurately identify those with SN metastasis. More accurate application of SN biopsy is required for patients with a preoperative diagnosis of DCIS.