1.The preliminary study of structure variation related to keloid based on the whole-gene resequencing technique.
Chang LIU ; Guodong TENG ; Minliang CHEN ; Kui MA ; Tongtong YAN
Chinese Journal of Plastic Surgery 2014;30(4):279-282
OBJECTIVETo investigate the genome structure variation (SV) related with keloid using the whole-gene resequencing technology.
METHODSWe studied a keloid pedigree containing 4 generation of 27 people. 5 people (4 cases of keloid patients, and 1 case of normal) were selected to extract the genomic DNA. Then the whole-gene resequencing technique was used to check the variations.
RESULTSThrough database comparison and variation annotation analysis, we obtained 2 SVs associated with keloid formation. We used DAVID software to do the gene ontology and pathway analysis. We found a 168 bp inversion in gene tetraspanin 8 (TSPAN8) in all keloid patients, which contained the forth exon of TSPAN8.
CONCLUSIONSThere was no report about SVs related to keloid. In this study, we found 2 SVs associated with keloid, especially TSPAN8. The tumor cells express the TSPAN8 can up-regulate the vascular endothelial growth factor and its receptors, promote the adjacent fibroblasts secrete matrix metalloproteinases and uridylyl phosphate adenosine. So we hypothesis that the inversion of the forth exon in TSPAN8 may lead to the signal transduction disorder in the keloid patients. This study was a preliminary research. It needs a further study containing large sample to confirm.
Base Sequence ; Female ; Humans ; Keloid ; genetics ; Male ; Molecular Sequence Data ; Pedigree ; Sequence Analysis ; methods ; Tetraspanins ; genetics
2.Characterization of candidate factors associated with the metastasis and progression of high-grade serous ovarian cancer.
Huiping LIU ; Ling ZHOU ; Hongyan CHENG ; Shang WANG ; Wenqing LUAN ; E CAI ; Xue YE ; Honglan ZHU ; Heng CUI ; Yi LI ; Xiaohong CHANG
Chinese Medical Journal 2023;136(24):2974-2982
BACKGROUND:
High-grade serous ovarian cancer (HGSOC) is the biggest cause of gynecological cancer-related mortality because of its extremely metastatic nature. This study aimed to explore and evaluate the characteristics of candidate factors associated with the metastasis and progression of HGSOC.
METHODS:
Transcriptomic data of HGSOC patients' samples collected from primary tumors and matched omental metastatic tumors were obtained from three independent studies in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were selected to evaluate the effects on the prognosis and progression of ovarian cancer using data from The Cancer Genome Atlas (TCGA) database. Hub genes' immune landscapes were estimated by the Tumor Immune Estimation Resource (TIMER) database. Finally, using 25 HGSOC patients' cancer tissues and 10 normal fallopian tube tissues, immunohistochemistry (IHC) was performed to quantify the expression levels of hub genes associated with International Federation of Gynecology and Obstetrics (FIGO) stages.
RESULTS:
Fourteen DEGs, ADIPOQ , ALPK2 , BARX1 , CD37 , CNR2 , COL5A3 , FABP4 , FAP , GPR68 , ITGBL1 , MOXD1 , PODNL1 , SFRP2 , and TRAF3IP3 , were upregulated in metastatic tumors in every database while CADPS , GATA4 , STAR , and TSPAN8 were downregulated. ALPK2 , FAP , SFRP2 , GATA4 , STAR , and TSPAN8 were selected as hub genes significantly associated with survival and recurrence. All hub genes were correlated with tumor microenvironment infiltration, especially cancer-associated fibroblasts and natural killer (NK) cells. Furthermore, the expression of FAP and SFRP2 was positively correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, and their increased protein expression levels in metastatic samples compared with primary tumor samples and normal tissues were confirmed by IHC ( P = 0.0002 and P = 0.0001, respectively).
CONCLUSIONS
This study describes screening for DEGs in HGSOC primary tumors and matched metastasis tumors using integrated bioinformatics analyses. We identified six hub genes that were correlated with the progression of HGSOC, particularly FAP and SFRP2 , which might provide effective targets to predict prognosis and provide novel insights into individual therapeutic strategies for HGSOC.
Humans
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Female
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Ovarian Neoplasms/pathology*
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Prognosis
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Gene Expression Profiling
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Transcriptome
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Tumor Microenvironment
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Receptors, G-Protein-Coupled/therapeutic use*
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Tetraspanins/genetics*
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Protein Kinases
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Integrin beta1/therapeutic use*
3.Urinary Nucleic Acid TSPAN13-to-S100A9 Ratio as a Diagnostic Marker in Prostate Cancer.
Chunri YAN ; Ye Hwan KIM ; Ho Won KANG ; Sung Phil SEO ; Pildu JEONG ; Il Seok LEE ; Dongho KIM ; Jung Min KIM ; Yung Hyun CHOI ; Sung Kwon MOON ; Seok Joong YUN ; Wun Jae KIM
Journal of Korean Medical Science 2015;30(12):1784-1792
The potential use of urinary nucleic acids as diagnostic markers in prostate cancer (PCa) was evaluated. Ninety-five urine samples and 234 prostate tissue samples from patients with PCa and benign prostatic hyperplasia (BPH) were analyzed. Micro-array analysis was used to identify candidate genes, which were verified by the two-gene expression ratio and validated in tissue mRNA and urinary nucleic acid cohorts. Real-time quantitative polymerase chain reaction (qPCR) was used to measure urinary nucleic acid levels and tissue mRNA expression. The TSPAN13-to-S100A9 ratio was selected to determine the diagnostic value of urinary nucleic acids in PCa (P = 0.037) and shown to be significantly higher in PCa than in BPH in the mRNA and nucleic acid cohort analyses (P < 0.001 and P = 0.013, respectively). Receiver operating characteristic (ROC) analysis showed that the area under the ROC curve was 0.898 and 0.676 in tissue mRNA cohort and urinary nucleic acid cohort, respectively. The TSPAN13-to-S100A9 ratio showed a strong potential as a diagnostic marker for PCa. The present results suggest that the analysis of urine supernatant can be used as a simple diagnostic method for PCa that can be adapted to the clinical setting in the future.
Aged
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Aged, 80 and over
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Biomarkers, Tumor/*genetics/*urine
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Calgranulin B/*genetics
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Cohort Studies
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Humans
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Male
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Middle Aged
;
Nucleic Acids/*genetics/*urine
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Oligonucleotide Array Sequence Analysis
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Prostate/metabolism
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Prostatic Hyperplasia/diagnosis/genetics/urine
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Prostatic Neoplasms/diagnosis/*genetics/*urine
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RNA, Messenger/genetics/metabolism
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RNA, Neoplasm/genetics/metabolism
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ROC Curve
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Real-Time Polymerase Chain Reaction
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Tetraspanins/*genetics