scholarly journals Increasing expression of serine protease matriptase in ovarian tumors: tissue microarray analysis of immunostaining score with clinicopathological parameters

2006 ◽  
Vol 19 (3) ◽  
pp. 447-452 ◽  
Author(s):  
Jong-Shiaw Jin ◽  
Dar-Shih Hsieh ◽  
Shih-Hurng Loh ◽  
Ann Chen ◽  
Chen-Wen Yao ◽  
...  
Keyword(s):  
Serine Protease ◽  
Tissue Microarray ◽  
Microarray Analysis ◽  
Ovarian Tumors ◽  
Clinicopathological Parameters ◽  
Immunostaining Score ◽  
Tissue Microarray Analysis

Tissue microarray analysis of EGFR and erbB2 copy number changes in ovarian tumors

2006 ◽  
Vol 16 (1) ◽  
pp. 145-151 ◽  
Author(s):  
I. DIMOVA ◽  
B. ZAHARIEVA ◽  
S. RAITCHEVA ◽  
R. DIMITROV ◽  
N. DOGANOV ◽  
...  
Keyword(s):  
Tissue Microarray ◽  
Microarray Analysis ◽  
Copy Number ◽  
Ovarian Tumors ◽  
Copy Number Changes ◽  
Tissue Microarray Analysis

777: Tissue Microarray Analysis of pAkt, PTEN and L-Plastin in Urinary Bladder Cancer

2005 ◽  
Vol 173 (4S) ◽  
pp. 211-211
Author(s):  
Loleta D. Harris ◽  
Tomasz Tuziak ◽  
Jorge De Lo Cerda ◽  
Anita L. Sabichi ◽  
Ying Yang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Urinary Bladder ◽  
Tissue Microarray ◽  
Microarray Analysis ◽  
Urinary Bladder Cancer ◽  
Tissue Microarray Analysis

scholarly journals High-Throughput Tissue Microarray Analysis to Evaluate Genes Uncovered by cDNA Microarray Screening in Renal Cell Carcinoma

1999 ◽  
Vol 154 (4) ◽  
pp. 981-986 ◽  
Author(s):  
Holger Moch ◽  
Peter Schraml ◽  
Lukas Bubendorf ◽  
Martina Mirlacher ◽  
Juha Kononen ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Tissue Microarray ◽  
Microarray Analysis ◽  
Cdna Microarray ◽  
High Throughput ◽  
Renal Cell ◽  
Microarray Screening ◽  
Tissue Microarray Analysis

Frequent Alterations of Smad Signaling in Human Head and Neck Squamous Cell Carcinomas: A Tissue Microarray Analysis

2003 ◽  
Vol 14 (2) ◽  
pp. 61-73 ◽  
Author(s):  
Wen Xie ◽  
Savita Bharathy ◽  
David Kim ◽  
Bruce G. Haffty ◽  
David L. Rimm ◽  
...  
Keyword(s):  
Head And Neck ◽  
Tissue Microarray ◽  
Microarray Analysis ◽  
Squamous Cell ◽  
Human Head ◽  
Squamous Cell Carcinomas ◽  
Smad Signaling ◽  
Tissue Microarray Analysis

Novel Relational Database for Tissue Microarray Analysis

2003 ◽  
Vol 127 (4) ◽  
pp. 492-494 ◽  
Author(s):  
Rita Shaknovich ◽  
Ashlyn Celestine ◽  
Lin Yang ◽  
Giorgio Cattoretti
Keyword(s):  
Tissue Microarray ◽  
Microarray Analysis ◽  
Relational Database ◽  
Tissue Microarray Analysis

scholarly journals Identification of a molecular signature of prognostic subtypes in diffuse-type gastric cancer

2019 ◽  
Vol 23 (3) ◽  
pp. 473-482 ◽  
Author(s):  
Seon-Kyu Kim ◽  
Hee-Jin Kim ◽  
Jong-Lyul Park ◽  
Haejeong Heo ◽  
Seon-Young Kim ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Tissue Microarray ◽  
Microarray Analysis ◽  
Cox Regression ◽  
Molecular Signature ◽  
Diffuse Type ◽  
Rna Seq ◽  
Tissue Samples ◽  
Diffuse Type Gastric Cancer ◽  
Tissue Microarray Analysis

Abstract Background Although recent advances in high-throughput technology have provided many insights into gastric cancer (GC), few reliable biomarkers for diffuse-type GC have been identified. Here, we aim to identify a prognostic and predictive signature of diffuse-type GC heterogeneity. Methods We analyzed RNA-seq-based transcriptome data to identify a molecular signature in 150 gastric tissue samples including 107 diffuse-type GCs. The predictive value of the signature was verified using other diffuse-type GC samples in three independent cohorts (n = 466). Log-rank and Cox regression analyses were used to estimate the association between the signature and prognosis. The signature was also characterized by somatic variant analyses and tissue microarray analysis between diffuse-type GC subtypes. Results Transcriptomic profiling of RNA-seq data identified a signature which revealed distinct subtypes of diffuse-type GC: the intestinal-like (INT) and core diffuse-type (COD) subtypes. The signature showed high predictability and independent clinical utility in diffuse-type GC prognosis in other patient cohorts (HR 2.058, 95% CI 1.53–2.77, P = 1.76 × 10–6). Integrative mutational and gene expression analyses demonstrated that the COD subtype was responsive to chemotherapy, whereas the INT subtype was responsive to immunotherapy with an immune checkpoint inhibitor (ICI). Tissue microarray analysis showed the practical utility of IGF1 and NXPE2 for predicting diffuse-type GC heterogeneity. Conclusions We present a molecular signature that can identify diffuse-type GC patients who display different clinical behaviors as well as responses to chemotherapy or ICI treatment.

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