Overexpression of syndecan-1, MUC-1, and putative stem cell markers in breast cancer leptomeningeal metastasis: a cerebrospinal fluid flow cytometry study.

BACKGROUND: Cancer is a mosaic of tumor cell subpopulations, where only a minority is responsible for disease recurrence and cancer invasiveness. We focused on one of the most aggressive circulating tumor cells (CTCs) which, from the primitive tumor, spreads to the central nervous system (CNS), evaluating the expression of prognostic and putative cancer stem cell markers in breast cancer (BC) leptomeningeal metastasis (LM). METHODS: Flow cytometry immunophenotypic analysis of cerebrospinal fluid (CSF) samples (4.5 ml) was performed in 13 consecutive cases of BCLM. Syndecan-1 (CD138), MUC-1 (CD227) CD45, CD34, and the putative cancer stem cell markers CD15, CD24, CD44, and CD133 surface expression were evaluated on CSF floating tumor cells. The tumor-associated leukocyte population was also characterized. RESULTS: Despite a low absolute cell number (8 cell/µl, range 1-86), the flow cytometry characterization was successfully conducted in all the samples. Syndecan-1 and MUC-1 overexpression was documented on BC cells in all the samples analyzed; CD44, CD24, CD15, and CD133 in 77%, 75%, 70%, and 45% of cases, respectively. A strong syndecan-1 and MUC-1 expression was also documented by immunohistochemistry on primary breast cancer tissues, performed in four patients. The CSF tumor population was flanked by T lymphocytes, with a different immunophenotype between the CSF and peripheral blood samples (P ≤ 0.02). CONCLUSIONS: Flow cytometry can be successfully employed for solid tumor LM characterization even in CSF samples with low cell count. This in vivo study documents that CSF floating BC cells overexpress prognostic and putative cancer stem cell biomarkers related to tumor invasiveness, potentially representing a molecular target for circulating tumor cell detection and LM treatment monitoring, as well as a primary target for innovative treatment strategies. The T lymphocyte infiltration, documented in all CSF samples, suggests a possible involvement of the CNS lymphatic system in both lymphoid and cancer cell migration into and out of the meninges, supporting the extension of a new form of cellular immunotherapy to LM. Due to the small number of cases, validation on large cohorts of patients are warranted to confirm these findings and to evaluate the impact and value of these results for diagnosis and management of LM.

MicroRNA profiles discriminate among colon cancer metastasis.

MicroRNAs are being exploited for diagnosis, prognosis and monitoring of cancer and other diseases. Their high tissue specificity and critical role in oncogenesis provide new biomarkers for the diagnosis and classification of cancer as well as predicting patients' outcomes. MicroRNAs signatures have been identified for many human tumors, including colorectal cancer (CRC). In most cases, metastatic disease is difficult to predict and to prevent with adequate therapies. The aim of our study was to identify a microRNA signature for metastatic CRC that could predict and differentiate metastatic target organ localization. Normal and cancer tissues of three different groups of CRC patients were analyzed. RNA microarray and TaqMan Array analysis were performed on 66 Italian patients with or without lymph nodes and/or liver recurrences. Data obtained with the two assays were analyzed separately and then intersected to identify a primary CRC metastatic signature. Five differentially expressed microRNAs (hsa-miR-21, -103, -93, -31 and -566) were validated by qRT-PCR on a second group of 16 American metastatic patients. In situ hybridization was performed on the 16 American patients as well as on three distinct commercial tissues microarray (TMA) containing normal adjacent colon, the primary adenocarcinoma, normal and metastatic lymph nodes and liver. Hsa-miRNA-21, -93, and -103 upregulation together with hsa-miR-566 downregulation defined the CRC metastatic signature, while in situ hybridization data identified a lymphonodal invasion profile. We provided the first microRNAs signature that could discriminate between colorectal recurrences to lymph nodes and liver and between colorectal liver metastasis and primary hepatic tumor.