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)

Ovarian/primary peritoneal carcinoma and breast carcinoma are the gynaecological cancers that most frequently involve the serosal cavities.With the objective of improving on the limited diagnostic panel currently available for the differential diagnosis of these two malignancies,as well as to define tumour-specific biological targets, we compared their global gene expression patterns. Gene expression profiles of 10 serous ovarian/peritoneal and eight ductal breast carcinoma effusions were analysed using the HumanRef-8 BeadChip from Illumina.Differentially expressed candidate genes were validated using quantitative real-time PCR and immunohistochemistry. Unsupervised hierarchical clustering using all 54,675 genes in the array separated ovarian from breast carcinoma samples. We identified 288 unique probes that were significantly differentially expressed in the two cancers by greater than 3.5-fold, of which 81 and 207 were overexpressed in breast and ovarian/peritoneal carcinoma, respectively. SAM analysis identified 1078 differentially expressed probes with false discovery rate less than 0.05. Genes overexpressed in breast carcinoma included TFF1, TFF3, FOXA1, CA12, GATA3, SDC1, PITX1, TH, EHFD1, EFEMP1, TOB1 and KLF2. Genes overexpressed in ovarian/peritoneal carcinoma included SPON1, RBP1, MFGE8, TM4SF12, MMP7, KLK5/6/7, FOLR1/3,PAX8, APOL2 and NRCAM. The differential expression of 14 genes was validated by quantitative real-time PCR, and differences in 5 gene products were confirmed by immunohistochemistry. Expression profiling distinguishes ovarian/peritoneal carcinoma from breast carcinoma and identifies genes that are differentially expressed in these two tumour types. The molecular signatures unique to these cancers may facilitate their differential diagnosis and may provide a molecular basis for therapeutic target discovery.
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PMID:Gene expression signatures differentiate ovarian/peritoneal serous carcinoma from breast carcinoma in effusions. 2013 13

Intrinsic and acquired resistance to the monoclonal antibody drug trastuzumab is a major problem in the treatment of HER2-positive breast cancer. A deeper understanding of the underlying mechanisms could help to develop new agents. Our intention was to detect genes and single nucleotide polymorphisms (SNPs) affecting trastuzumab efficiency in cell culture. Three HER2-positive breast cancer cell lines with different resistance phenotypes were analyzed. We chose BT474 as model of trastuzumab sensitivity, HCC1954 as model of intrinsic resistance, and BTR50, derived from BT474, as model of acquired resistance. Based on RNA-Seq data, we performed differential expression analyses on these cell lines with and without trastuzumab treatment. Differentially expressed genes between the resistant cell lines and BT474 are expected to contribute to resistance. Differentially expressed genes between untreated and trastuzumab treated BT474 are expected to contribute to drug efficacy. To exclude false positives from the candidate gene set, we removed genes that were also differentially expressed between untreated and trastuzumab treated BTR50. We further searched for SNPs in the untreated cell lines which could contribute to trastuzumab resistance. The analysis resulted in 54 differentially expressed candidate genes that might be connected to trastuzumab efficiency. 90% of 40 selected candidates were validated by RT-qPCR. ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line. GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed. Additionally, we inferred SNPs in HCC1954 for CAV1, PTGS2, IL8 and IGFBP3. The latter also had a variation in BTR50. 20% of the validated subset have already been mentioned in literature. For half of them we called and analyzed SNPs. These results contribute to a better understanding of trastuzumab action and resistance mechanisms.
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PMID:mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer. 2571 May 61