Numerous types of cancer exhibit increased lipogenesis and expression of lipogenic enzymes and transcription factors, including sterol regulatory element-binding protein-1. Lipogenic gene expression is upregulated at the mRNA level, in concert with metabolic pathways associated with changes in expression and/or activity of lipogenic transcription factors. However, this expression pattern in human gastric carcinoma has not been elucidated. In this study, lipogenic gene expression in cancer tissues was investigated using quantitative PCR. In patients with gastric cancer, carnitine O-palmitoyltransferase type I mRNA and miR-33b were significantly downregulated, suggesting that miR-33b downregulation is mediated by conditions that also affect the expression and/or activity of transcription factors involved in lipogenic gene expression. Consequently, the association between miR-33b and gastric cancer may provide a novel strategy for the genetic diagnosis of gastric cancer. However, additional studies including a larger number of samples are required to confirm these results.

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Breast cancer subtypes have been classified based on the gene expression profiles, and the specifically effective treatments for each subtype have been developed and applied in clinical situations. However, there is no effective treatment for metaplastic breast carcinomas, which are pathological tissue types with poor prognosis. Metaplastic breast carcinomas are almost resistant to existing chemotherapy because it has not been identified the specific therapeutic target molecules. Recently, Lehmann et al. reported that breast cancers with chondroid metaplasia are categorized in Mesenchymal (M) type, which is one subtype out of six triple negative breast cancer (TNBC) subtypes based on drug susceptibility. From the knowledge on this report, we hypothesized that integrative analyses using the gene expression profile data sets obtained from various types of breast cancers with or without cartilage formation may enable us to identify the therapeutic target genes for metaplastic breast carcinomas, especially for breast cancers with chondroid metaplasia. Bioinformatics analyses were performed using the gene expression profile data sets of TNBC, which are registered in Gene Expression Omnibus (GEO). When compared with metaplastic breast carcinomas (28 data sets), 200 genes were specifically fluctuated over 2-fold in breast cancer with chondroid metaplasia (8 data sets). On the other hand, M type (11 data sets) specific 578 genes were identified over 56 TNBC data sets. In addition, 57 genes were overlapped between chondoroid metaplastic 200 genes and M type 578 genes. Therefore, these 57 overlapped genes might be considered as possible poor prognostic factors in breast cancer with chondroid metaplasia. As a result of Gene Ontology analysis on these 57 genes, skeletal system development and extracellular matrix structural constituent were significantly enriched in Biological process and Molecular function, respectively. Also, SCRG1, SOX8 and SOX10, which are genes related to cartilage differentiation, were included. Next, we focused 14 genes because these genes could serve as therapeutic targets. Then, we validated the expression levels of these 14 genes using tissues obtained from surgically resected human breast cancer with chondroid metaplasia dividing into three parts, the invasive ductal carcinoma, the chondroid metaplasia and normal mammary gland. As a result, SCRG1, CD86, HCLS1, EPSTI1, LYZ, and SLA were significantly increased in chondroid metaplasia part, suggesting that these validated genes were identified as possible therapeutic targets for breast cancer with chondroid metaplasia. Further study will help us to investigate a novel and effective therapeutic strategy for metaplastic breast carcinomas. Citation Format: Yamashita M, Kamei Y, Kusakabe E, Yamasawa H, Aoki R, Taguchi K, Nishiyama K, Murakami A, Sawada Y, Takada Y, Imai Y. Exploring novel therapeutic target molecules for metaplastic breast carcinoma using comprehensive genome-wide gene expression analyses [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-07.