Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P04155 (pS2)
 1,234 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The development of distant metastases is the major cause of death from breast cancer. In order to predict and prevent tumour spreading, many attempts are being made to detect small numbers of tumour cells that have shed from the primary lesions and have moved to lymph nodes, blood or bone marrow. This article presents the advantages and the limitations of techniques used for disseminated tumour cells (DTC) detection. DTC markers are listed and the most currently used of them (KRT19, CEACAM5, TACSTD1, MUC1, EGFR, ERBB2, SCGB2A2, SCGB2A1, SCGB1D2, PIP, SBEM, TFF1, TFF3, ANKRD30A, SPDEF, ESR1, SERPINB5 and GABRP) are discussed, notably on the basis of recent data on breast tumour portraits (luminal epithelial-like, basal/myoepithelial-like and ERBB2). The significance of DTC for the prognosis and prediction of response to therapy is examined. DTC viability, the notion of cell dormancy and the concept of breast cancer stem cells are also discussed.
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PMID:Significance, detection and markers of disseminated breast cancer cells. 1715 53

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.
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PMID:Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma. 2967 33