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Abstract Background The Stanford Tissue Microarray Database (TMAD) is a repository of data serving a consortium of pathologists and biomedical researchers. The tissue samples in TMAD are annotated with multiple free-text fields, specifying the pathological diagnoses for each sample. These text annotations are not structured according to any ontology, making future integration of this resource with other biological and clinical data difficult. Results We developed methods to map these annotations to the NCI thesaurus. Using the NCI-T we can effectively represent annotations for about 86% of the samples. We demonstrate how this mapping enables ontology driven integration and querying of tissue microarray data. We have deployed the mapping and ontology driven querying tools at the TMAD site for general use. Conclusion We have demonstrated that we can effectively map the diagnosis-related terms describing a sample in TMAD to the NCI-T. The NCI thesaurus terms have a wide coverage and provide terms for about 86% of the samples. In our opinion the NCI thesaurus can facilitate integration of this resource with other biological data.

Background: MicroRNAs (miRNA) are 20~25 nucleotide non-coding RNAs that inhibit the translation of targeted mRNA, and they have been implicated in the development of human malignancies. High grade serous ovarian carcinomas, the most common and lethal subtype of ovarian cancer, can occur sporadically or in the setting of BRCA1/2 syndromes. Little is known regarding the miRNA expression profiles of high grade serous carcinoma in relation to BRCA1/2 status, and compared to normal tubal epithelium, the putative tissue of origin for high grade serous carcinomas. Methodology/Principal Findings: Global miRNA expression profiling was performed on a series of 33 high grade serous carcinomas, characterized with respect to BRCA1/2 status (mutation, epigenetic silencing with loss of expression or normal), and with clinical follow-up, together with 2 low grade serous carcinomas, 2 serous borderline tumors, and 3 normal fallopian tube samples, using miRNA microarrays (328 human miRNA). Unsupervised hierarchical clustering based on miRNA expression profiles showed no clear separation between the groups of carcinomas with different BRCA1/2 status. There were relatively few miRNAs that were differentially expressed between the genotypic subgroups. Comparison of 33 high grade serous carcinomas to 3 normal fallopian tube samples identified several dysregulated miRNAs (false discovery rate <5%), including miR-422b and miR-34c. Quantitative RT-PCR analysis performed on selected miRNAs confirmed the pattern of differential expression shown by microarray analysis. Prognostically, lower level miR-422b and miR-34c in high grade serous carcinomas were both associated with decreased disease-specific survival by Kaplan-Meier analysis (p<0.05). Conclusions/Significance: High grade serous ovarian carcinomas with and without BRCA1/2 abnormalities demonstrate very similar miRNA expression profiles. High grade serous carcinomas as a group exhibit significant miRNA dysregulation in comparison to tubal epithelium and the levels of miR-34c and miR-422b appear to be prognostically important. [ABSTRACT FROM AUTHOR]

Background: The Stanford Tissue Microarray Database (TMAD) is a repository of data serving a consortium of pathologists and biomedical researchers. The tissue samples in TMAD are annotated with multiple free-text fields, specifying the pathological diagnoses for each sample. These text annotations are not structured according to any ontology, making future integration of this resource with other biological and clinical data difficult. Results: We developed methods to map these annotations to the NCI thesaurus. Using the NCIT we can effectively represent annotations for about 86% of the samples. We demonstrate how this mapping enables ontology driven integration and querying of tissue microarray data. We have deployed the mapping and ontology driven querying tools at the TMAD site for general use. Conclusion: We have demonstrated that we can effectively map the diagnosis-related terms describing a sample in TMAD to the NCI-T. The NCI thesaurus terms have a wide coverage and provide terms for about 86% of the samples. In our opinion the NCI thesaurus can facilitate integration of this resource with other biological data. [ABSTRACT FROM AUTHOR]

Purpose: Leiomyosarcoma is a malignant neoplasm with smooth muscle differentiation. Little is known about its molecular heterogeneity and no targeted therapy currently exists for leiomyosarcoma. Recognition of different molecular subtypes is necessary to evaluate novel therapeutic options. In a previous study on 51 leiomyosarcomas, we identified three molecular subtypes in leiomyosarcoma. The current study was performed to determine whether the existence of these subtypes could be confirmed in independent cohorts., Experimental Design: Ninety-nine cases of leiomyosarcoma were expression profiled with 3'end RNA-Sequencing (3SEQ). Consensus clustering was conducted to determine the optimal number of subtypes., Results: We identified 3 leiomyosarcoma molecular subtypes and confirmed this finding by analyzing publically available data on 82 leiomyosarcoma from The Cancer Genome Atlas (TCGA). We identified two new formalin-fixed, paraffin-embedded tissue-compatible diagnostic immunohistochemical markers; LMOD1 for subtype I leiomyosarcoma and ARL4C for subtype II leiomyosarcoma. A leiomyosarcoma tissue microarray with known clinical outcome was used to show that subtype I leiomyosarcoma is associated with good outcome in extrauterine leiomyosarcoma while subtype II leiomyosarcoma is associated with poor prognosis in both uterine and extrauterine leiomyosarcoma. The leiomyosarcoma subtypes showed significant differences in expression levels for genes for which novel targeted therapies are being developed, suggesting that leiomyosarcoma subtypes may respond differentially to these targeted therapies., Conclusions: We confirm the existence of 3 molecular subtypes in leiomyosarcoma using two independent datasets and show that the different molecular subtypes are associated with distinct clinical outcomes. The findings offer an opportunity for treating leiomyosarcoma in a subtype-specific targeted approach., (©2015 American Association for Cancer Research.)

Background: MicroRNAs (miRNA) are 20 approximately 25 nucleotide non-coding RNAs that inhibit the translation of targeted mRNA, and they have been implicated in the development of human malignancies. High grade serous ovarian carcinomas, the most common and lethal subtype of ovarian cancer, can occur sporadically or in the setting of BRCA1/2 syndromes. Little is known regarding the miRNA expression profiles of high grade serous carcinoma in relation to BRCA1/2 status, and compared to normal tubal epithelium, the putative tissue of origin for high grade serous carcinomas., Methodology/principal Findings: Global miRNA expression profiling was performed on a series of 33 high grade serous carcinomas, characterized with respect to BRCA1/2 status (mutation, epigenetic silencing with loss of expression or normal), and with clinical follow-up, together with 2 low grade serous carcinomas, 2 serous borderline tumors, and 3 normal fallopian tube samples, using miRNA microarrays (328 human miRNA). Unsupervised hierarchical clustering based on miRNA expression profiles showed no clear separation between the groups of carcinomas with different BRCA1/2 status. There were relatively few miRNAs that were differentially expressed between the genotypic subgroups. Comparison of 33 high grade serous carcinomas to 3 normal fallopian tube samples identified several dysregulated miRNAs (false discovery rate <5%), including miR-422b and miR-34c. Quantitative RT-PCR analysis performed on selected miRNAs confirmed the pattern of differential expression shown by microarray analysis. Prognostically, lower level miR-422b and miR-34c in high grade serous carcinomas were both associated with decreased disease-specific survival by Kaplan-Meier analysis (p<0.05)., Conclusions/significance: High grade serous ovarian carcinomas with and without BRCA1/2 abnormalities demonstrate very similar miRNA expression profiles. High grade serous carcinomas as a group exhibit significant miRNA dysregulation in comparison to tubal epithelium and the levels of miR-34c and miR-422b appear to be prognostically important.

Previously, we showed that the presence of high numbers of macrophages correlates with poor prognosis in nongynecological leiomyosarcoma (LMS). In gynecological LMS, a similar trend was noted but did not reach statistical significance. Colony-stimulating factor-1 (CSF1) is a major chemoattractant for macrophages. Here we show that in a subset of LMS cases, CSF1 is expressed by the malignant cells. Previously, we found that CSF1 is translocated and highly expressed in tenosynovial giant cell tumors (TGCTs), and this observation allowed us to identify genes that showed a coordinate expression with CSF1. Here, we evaluated the expression of CSF1 and TGCT-associated proteins in 149 cases of LMS. The coordinate expression of CSF1 and three TGCT-associated proteins (CD163, FCGR3a, and CTSL1) identified cases with poor prognosis in both gynecological LMS (P = 0.00006) and nongynecological LMS (P = 0.03). In gynecological LMS, the coordinate expression of these four markers was the only independent prognosticator in multivariate analysis (hazard ratio, 4.2; 95% CI, 1.12 to 16; P = 0.03). Our findings indicate that CSF1 may play an important role in the clinical behavior of LMS that may open a window for new therapeutic reagents.

Purpose: Macrophages play an important role in breast carcinogenesis. The pathways that mediate the macrophage contribution to breast cancer and the heterogeneity that exists within macrophages are incompletely understood. Macrophage colony-stimulating factor 1 (CSF1) is the primary regulator of tissue macrophages. The purpose of this study was to define a novel CSF1 response signature and to evaluate its clinical and biological significance in breast cancer., Experimental Design: We defined the CSF1 response signature by identifying genes overexpressed in tenosynovial giant cell tumor and pigmented villonodular synovitis (tumors composed predominantly of macrophages recruited in response to the overexpression of CSF1) compared with desmoid-type fibromatosis and solitary fibrous tumor. To characterize the CSF1 response signature in breast cancer, we analyzed the expression of CSF1 response signature genes in eight published breast cancer gene expression data sets (n = 982) and did immunohistochemistry and in situ hybridization for CSF1 response genes on a breast cancer tissue microarray (n = 283)., Results: In both the gene microarray and tissue microarray analyses, a consistent subset (17-25%) of breast cancers shows the CSF1 response signature. The signature is associated with higher tumor grade, decreased expression of estrogen receptor, decreased expression of progesterone receptor, and increased TP53 mutations (P < 0.001)., Conclusions: Our data show that the CSF1 response signature is consistently seen in a subset of breast carcinomas and correlates with biological features of the tumor. Our findings provide insight into macrophage biology and may facilitate the development of personalized therapy for patients most likely to benefit from CSF1-targeted treatments.

Purpose: Macrophages are migratory cells that are frequently recruited to the site of tumors. Their presence is associated with poor clinical outcome in a variety of epithelial malignancies. The aim of this study is to examine the prognostic significance of tumor-associated macrophages in sarcomas., Experimental Design: Global gene expression profiling data of a series of soft tissue tumors were analyzed for macrophage-associated gene expression. Immunohistochemistry on tissue microarrays containing leiomyosarcoma cases with known clinical outcome was used to verify the presence of macrophages and to examine the relationship between tumor-associated macrophages and clinical outcome., Results: Gene expression profiling revealed high-level expression of several macrophage-associated genes such as CD163 and CD68 in a subset of leiomyosarcomas, indicating the presence of variable numbers of tumor-infiltrating macrophages. This was confirmed by CD68 and CD163 immunostaining of a tissue microarray containing 149 primary leiomyosarcomas. Kaplan-Meier survival analysis showed that high density of tumor-infiltrating macrophages as identified by CD163 or CD68 staining is associated with a significantly worse disease-specific survival in nongynecologic leiomyosarcomas, whereas leiomyosarcomas arising from the gynecologic tract showed no significant association between macrophage infiltration and survival. The presence of tumor necrosis did not correlate significantly with outcome., Conclusions: An increased density of CD163- or CD68-positive tumor-infiltrating macrophages is associated with poor outcome in nongynecologic leiomyosarcomas. This may help the clinical management of patients with leiomyosarcomas.