D2–40 and calretinin—a tissue microarray analysis of 341 malignant mesotheliomas with emphasis on sarcomatoid differentiation

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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High throughput tissue microarray analysis of FHIT expression in diffuse large cell B-cell lymphoma from Saudi Arabia

Modern Pathology ◽

10.1038/modpathol.3800631 ◽

2006 ◽

Vol 19 (8) ◽

pp. 1124-1129 ◽

Cited By ~ 5

Author(s):

Khawla Al Kuraya ◽

Abdul Khalid Siraj ◽

Prashant Bavi ◽

Naif Al-Jomah ◽

Hassan El-Solh ◽

...

Keyword(s):

Saudi Arabia ◽

B Cell ◽

Tissue Microarray ◽

Microarray Analysis ◽

High Throughput ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Large Cell ◽

Tissue Microarray Analysis

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Detecting Activation of Ribosomal Protein S6 Kinase by Complementary DNA and Tissue Microarray Analysis

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/92.15.1252 ◽

2000 ◽

Vol 92 (15) ◽

pp. 1252-1259 ◽

Cited By ~ 188

Author(s):

M. Barlund ◽

F. Forozan ◽

J. Kononen ◽

L. Bubendorf ◽

Y. Chen ◽

...

Keyword(s):

Ribosomal Protein ◽

Tissue Microarray ◽

Microarray Analysis ◽

S6 Kinase ◽

Complementary Dna ◽

Ribosomal Protein S6 ◽

Tissue Microarray Analysis ◽

Ribosomal Protein S6 Kinase

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Immune Checkpoint Profiles in Luminal B Breast Cancer (Alliance)

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djz213 ◽

2019 ◽

Vol 112 (7) ◽

pp. 737-746 ◽

Cited By ~ 9

Author(s):

Meenakshi Anurag ◽

Mayanne Zhu ◽

Chen Huang ◽

Suhas Vasaikar ◽

Junkai Wang ◽

...

Keyword(s):

Breast Cancer ◽

Tissue Microarray ◽

Microarray Analysis ◽

Immune Tolerance ◽

Immune Checkpoint ◽

Mrna Levels ◽

Breast Cancers ◽

Er Positive ◽

Tissue Microarray Analysis ◽

Positive Breast Cancer

Abstract Background Unlike estrogen receptor (ER)-negative breast cancer, ER-positive breast cancer outcome is less influenced by lymphocyte content, indicating the presence of immune tolerance mechanisms that may be specific to this disease subset. Methods A supervised analysis of microarray data from the ACOSOG Z1031 (Alliance) neoadjuvant aromatase inhibitor (AI) trial identified upregulated genes in Luminal (Lum) B breast cancers that correlated with AI-resistant tumor proliferation (percentage of Ki67-positive cancer nuclei, Pearson r > 0.4) (33 cases Ki67 > 10% on AI) vs LumB breast cancers that were more AI sensitive (33 cases Ki67 < 10% on AI). Overrepresentation analysis was performed using WebGestalt. All statistical tests were two-sided. Results Thirty candidate genes positively correlated (r ≥ 0.4) with AI-resistant proliferation in LumB and were upregulated greater than twofold. Gene ontologies identified that the targetable immune checkpoint (IC) components IDO1, LAG3, and PD1 were overrepresented resistance candidates (P ≤ .001). High IDO1 mRNA was associated with poor prognosis in LumB disease (Molecular Taxonomy of Breast Cancer International Consortium, hazard ratio = 1.43, 95% confidence interval = 1.04 to 1.98, P = .03). IDO1 also statistically significantly correlated with STAT1 at protein level in LumB disease (Pearson r = 0.74). As a composite immune tolerance signature, expression of IFN-γ/STAT1 pathway components was associated with higher baseline Ki67, lower estrogen, and progesterone receptor mRNA levels and worse disease-specific survival (P = .002). In a tissue microarray analysis, IDO1 was observed in stromal cells and tumor-associated macrophages, with a higher incidence in LumB cases. Furthermore, IDO1 expression was associated with a macrophage mRNA signature (M1 by CIBERSORT Pearson r = 0.62 ) and by tissue microarray analysis. Conclusions Targetable IC components are upregulated in the majority of endocrine therapy–resistant LumB cases. Our findings provide rationale for IC inhibition in poor-outcome ER-positive breast cancer.

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