DNA and Tissue Microarrays

2008 ◽  
pp. 98-108
Author(s):  
Maysa M. Abu-Khalaf ◽  
Lyndsay N. Harris ◽  
Gina G. Chung
Keyword(s):  
Tissue Microarrays

scholarly journals Mismatch repair deficiency is associated with specific morphologic features and frequent loss of ARID1A expression in ovarian clear cell carcinoma

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Huijuan Ge ◽  
Yaoxin Xiao ◽  
Guangqi Qin ◽  
Yanzi Gu ◽  
Xu Cai ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Tumor Infiltrating Lymphocytes ◽  
Tissue Microarrays ◽  
Ovarian Clear Cell Carcinoma ◽  
Repair Deficiency ◽  
Ovarian Epithelial Carcinoma ◽  
Histological Characteristics ◽  
Infiltrating Lymphocytes

Abstract Background Ovarian clear cell carcinoma (OCCC) is the second subtype of ovarian epithelial carcinoma reported to be closely related to Lynch syndrome (LS). ARID1A mutation is an important pathogenetic mechanism in OCCC that leads to loss of ARID1A expression in approximately half of OCCCs. However, the correlation of MMR status and ARID1A deficiency is unclear. The current study aimed to identify the clinical and histopathological characteristics of OCCC associated with dMMR and to further explore the association between dMMR and ARID1A deficiency. Methods A cohort of 176 primary OCCC patients was enrolled and review included histological characteristics (nuclear atypia, necrosis, mitosis, stromal hyalinization, and background precursors) and host inflammatory response (tumor-infiltrating lymphocytes, peritumoral lymphocytes, intratumoral stromal inflammation and plasma cell infiltration). Immunohistochemical staining of MLH1, PMS2, MSH2, MSH6 and ARID1A was performed using tissue microarrays. Results dMMR was detected in 10/176 tumors (6 %), followed by MSH2/MSH6 (6/176), MLH1/PMS2 (3/176), and MSH6 (1/176). The average age of patients with dMMR was younger than that of patients with intact MMR (46 y vs. 53 y). Tumors with diffuse intratumoral stromal inflammation remained significantly associated after multivariate analysis. ARID1A expression was absent in 8 patients with dMMR (8/10), which is a significantly higher frequency than that observed in patients with intact MMR (80 % vs. 43.2 %). Conclusions Our study indicates that diffuse intratumoral stromal inflammation of OCCCs is associated with dMMR, with loss of MSH2/MSH6 expression being most frequent. dMMR is strongly associated with the loss of ARID1A expression in OCCC.

scholarly journals Multi-institutional TSA-amplified Multiplexed Immunofluorescence Reproducibility Evaluation (MITRE) Study

2021 ◽  
Vol 9 (7) ◽  
pp. e002197
Author(s):  
Janis M Taube ◽  
Kristin Roman ◽  
Elizabeth L Engle ◽  
Chichung Wang ◽  
Carmen Ballesteros-Merino ◽  
...  
Keyword(s):  
Breast Carcinoma ◽  
Multispectral Imaging ◽  
Immune Cell ◽  
Clinical Laboratory ◽  
Predictive Biomarkers ◽  
Spatial Arrangement ◽  
Tissue Microarrays ◽  
Fluorescent Detection ◽  
Nsclc Tissue ◽  
Tissue Sections

BackgroundEmerging data suggest predictive biomarkers based on the spatial arrangement of cells or coexpression patterns in tissue sections will play an important role in precision immuno-oncology. Multiplexed immunofluorescence (mIF) is ideally suited to such assessments. Standardization and validation of an end-to-end workflow that supports multisite trials and clinical laboratory processes are vital. Six institutions collaborated to: (1) optimize an automated six-plex assay focused on the PD-1/PD-L1 axis, (2) assess intersite and intrasite reproducibility of staining using a locked down image analysis algorithm to measure tumor cell and immune cell (IC) subset densities, %PD-L1 expression on tumor cells (TCs) and ICs, and PD-1/PD-L1 proximity assessments.MethodsA six-plex mIF panel (PD-L1, PD-1, CD8, CD68, FOXP3, and CK) was rigorously optimized as determined by quantitative equivalence to immunohistochemistry (IHC) chromogenic assays. Serial sections from tonsil and breast carcinoma and non-small cell lung cancer (NSCLC) tissue microarrays (TMAs), TSA-Opal fluorescent detection reagents, and antibodies were distributed to the six sites equipped with a Leica Bond Rx autostainer and a Vectra Polaris multispectral imaging platform. Tissue sections were stained and imaged at each site and delivered to a single site for analysis. Intersite and intrasite reproducibility were assessed by linear fits to plots of cell densities, including %PDL1 expression by TCs and ICs in the breast and NSCLC TMAs.ResultsComparison of the percent positive cells for each marker between mIF and IHC revealed that enhanced amplification in the mIF assay was required to detect low-level expression of PD-1, PD-L1, FoxP3 and CD68. Following optimization, an average equivalence of 90% was achieved between mIF and IHC across all six assay markers. Intersite and intrasite cell density assessments showed an average concordance of R2=0.75 (slope=0.92) and R2=0.88 (slope=0.93) for breast carcinoma, respectively, and an average concordance of R2=0.72 (slope=0.86) and R2=0.81 (slope=0.68) for NSCLC. Intersite concordance for %PD-L1+ICs had an average R2 value of 0.88 and slope of 0.92. Assessments of PD-1/PD-L1 proximity also showed strong concordance (R2=0.82; slope=0.75).ConclusionsAssay optimization yielded highly sensitive, reproducible mIF characterization of the PD-1/PD-L1 axis across multiple sites. High concordance was observed across sites for measures of density of specific IC subsets, measures of coexpression and proximity with single-cell resolution.

scholarly journals PD-L1 Testing and Squamous Cell Carcinoma of the Head and Neck: A Multicenter Study on the Diagnostic Reproducibility of Different Protocols

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 292
Author(s):  
Simona Crosta ◽  
Renzo Boldorini ◽  
Francesca Bono ◽  
Virginia Brambilla ◽  
Emanuele Dainese ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Checkpoint Inhibitors ◽  
Interobserver Reliability ◽  
Tissue Microarrays ◽  
Observer Agreement ◽  
Alternative Methods ◽  
Observer Reliability

Immune checkpoint inhibitors for blocking the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis are now available for squamous cell carcinoma of the head and neck (HNSCC) in relapsing and/or metastatic settings. In this work, we compared the resulting combined positive score (CPS) of PD-L1 using alternative methods adopted in routine clinical practice and determined the level of diagnostic agreement and inter-observer reliability in this setting. The study applied 5 different protocols on 40 tissue microarrays from HNSCC. The error rate of the individual protocols ranged from a minimum of 7% to a maximum of 21%, the sensitivity from 79% to 96%, and the specificity from 50% to 100%. In the intermediate group (1 ≤ CPS < 20), the majority of errors consisted of an underestimation of PD-L1 expression. In strong expressors, 5 out of 14 samples (36%) were correctly evaluated by all the protocols, but no protocol was able to correctly identify all the “strong expressors”. The overall inter-observer agreement in PD-L1 CPS reached 87%. The inter-observer reliability was moderate, with an ICC of 0.774 (95% CI (0.651; 0.871)). In conclusion, our study showed moderate interobserver reliability among different protocols. In order to improve the performances, adequate specific training to evaluate PD-L1 by CPS in the HNSCC setting should be coordinated.

scholarly journals piNET–An Automated Proliferation Index Calculator Framework for Ki67 Breast Cancer Images

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 11
Author(s):  
Rokshana Stephny Geread ◽  
Abishika Sivanandarajah ◽  
Emily Rita Brouwer ◽  
Geoffrey A. Wood ◽  
Dimitrios Androutsos ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Tissue Microarrays ◽  
False Positives ◽  
Proliferation Index ◽  
Tumor Segmentation ◽  
Significant Activity ◽  
Hotspot Analysis ◽  
Weak Supervision ◽  
Wide Variability ◽  
Whole Slide Images

In this work, a novel proliferation index (PI) calculator for Ki67 images called piNET is proposed. It is successfully tested on four datasets, from three scanners comprised of patches, tissue microarrays (TMAs) and whole slide images (WSI), representing a diverse multi-centre dataset for evaluating Ki67 quantification. Compared to state-of-the-art methods, piNET consistently performs the best over all datasets with an average PI difference of 5.603%, PI accuracy rate of 86% and correlation coefficient R = 0.927. The success of the system can be attributed to several innovations. Firstly, this tool is built based on deep learning, which can adapt to wide variability of medical images—and it was posed as a detection problem to mimic pathologists’ workflow which improves accuracy and efficiency. Secondly, the system is trained purely on tumor cells, which reduces false positives from non-tumor cells without needing the usual pre-requisite tumor segmentation step for Ki67 quantification. Thirdly, the concept of learning background regions through weak supervision is introduced, by providing the system with ideal and non-ideal (artifact) patches that further reduces false positives. Lastly, a novel hotspot analysis is proposed to allow automated methods to score patches from WSI that contain “significant” activity.

Tissue microarrays for early target evaluation

2004 ◽  
Vol 1 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Ronald Simon ◽  
Martina Mirlacher ◽  
Guido Sauter
Keyword(s):  
Tissue Microarrays

scholarly journals Software Tools for High-Throughput Analysis and Archiving of Immunohistochemistry Staining Data Obtained with Tissue Microarrays

2002 ◽  
Vol 161 (5) ◽  
pp. 1557-1565 ◽  
Author(s):  
Chih Long Liu ◽  
Wijan Prapong ◽  
Yasodha Natkunam ◽  
Ash Alizadeh ◽  
Kelli Montgomery ◽  
...  
Keyword(s):  
High Throughput ◽  
Tissue Microarrays ◽  
Software Tools ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Immunohistochemistry Staining
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