Clinicopathological study of 6 cases of benign metastasizing leiomyoma / 临床与实验病理学杂志

Purpose To investigate the clinicopathological characteristics,diagnosis and differential diagnosis of benign metastasizing leiomyoma (BML).Methods The clinicopathological data in 6 patients with BML were collected.All cases of BLM were investigated by HE and immunohistochemistry of EnVision method.Results All cases were female,with age of 33 -65 years,and had undergone myomectomy.5 cases had lung metastasis,including abdominal wall metastasis and spinal metastasis in each of the 1 cases,and another case had inguinal metastasis.Morphology showed that the tumor cells were spindle without obvious atypia,nuclear mitoses and necrosis,some cases were cellular.Immunohistochemical staining showed that the tumor cells were positive for SMA,SM-MHC,desmin,ER,PR,vimentin,while negative for S-100,CD117,CD34.Ki-67 label index were less than 5％.3 patients were alive with tumor and 3 patients were alive without tumor in the follow up of 18,28,40,31,36,80 months.Conclusion BML often occurs in female patients that undergone uterine myomectomy.The lung is the most common site of metastasis,often accompanied by other sites.The disease progresses slowly,and most patients have a longer survival time.

MicroRNA expression based tumor origin classification / 临床检验杂志

Approximately 3 to 5％ of newly diagnosed metastatic cancers are of unknown primary tissue origin due to difficulties identifying a primary tumor using standard diagnostic approaches.MicroRNAs (miRNAs) have recently been demonstrated to be able to assist pathologist with improved accuracy in diagnosing cancers of unknown primary origin (CUP).In this short commentary,we will highlight some of the recent advancements in miRNA based cancer diagnosis as well as some future directions for the field.

Identiifcation and validation of a novel gene expression signature for diagnosing tumor tissue origin / 中国癌症杂志

Background and purpose:Cancer of unknown primary (CUP) represents approximately 5%~10%of malignant neoplasms. For CUP patients, identiifcation of tumor origin allows for more speciifc therapeutic regimens and improves outcomes.Methods:By retrieving the gene expression data from ArrayExpress and Gene Expression Omnibus data repositories, we established a comprehensive gene expression database of 5 800 tumor samples encom-passing 22 main tumor types. The support vector machine-recursive feature elimination algorithm was used for feature selection and classiifcation modelling. We further optimized the RNA isolation and real-time quantitative polymerase chain reaction (RTQ-PCR) methods for candidate gene expression proifling and applied the RTQ-PCR assays to a set of formalin-fixed, paraffin-embedded tumor samples.Results:Based on the pan-cancer transcriptome database, we identiifed a list of 96-tumor speciifc genes, including common tumor markers, such as cadherin 1 (CDH1), kallikrein-re-lated peptidase 3 (KLK3), and epidermal growth factor receptor (EGFR). Furthermore, we successfully translated the microarray-based gene expression signature to the RTQ-PCR assays, which allowed an overall success rate of 88.4% (95%CI: 83.2%-92.4%) in classifying 22 different tumor types of 206 formalin-fixed, paraffin-embedded samples. Conclusion:The 96-gene RTQ-PCR assay represents a useful tool for accurately identifying tumor origins. The assay uses RTQ-PCR and routine formalin-ifxed, paraffn-embedded samples, making it suitable for rapid clinical adoption.