A gene expression profile for detection of sufficient tumour cells in breast tumour tissue: microarray diagnosis eligibility

Roepman, Paul; Schuurman, Arenda; Delahaye, Leonie; Witteveen, Anke; Floore, Arno; Glas, Annuska M.

doi:10.1186/1755-8794-2-52

Cited by 11 publications

(5 citation statements)

References 10 publications

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“…Fresh tissue samples were placed [29,30]. TargetPrint microarrays (Agendia) contain multiple replicate probes for detection of mRNA levels of ER (ESR1; nine probes), PR (PGR; nine probes), and HER2 (ERBB2; six probes) and a large number of probes for normalization (465) and quality control (536) purposes.…”

Section: Tumor Samplesmentioning

confidence: 99%

An international study comparing conventional versus mRNA level testing (TargetPrint) for ER, PR, and HER2 status of breast cancer

et al. 2016

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To compare results from messenger RNA (mRNA)-based TargetPrint testing with those from immunohistochemistry (IHC) and in situ hybridization (ISH) conducted according to local standard procedures at hospitals worldwide. Tumor samples were prospectively obtained from 806 patients at 22 hospitals. The mRNA level of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) was assessed by TargetPrint quantitative gene expression readouts. IHC/ISH assessments were performed according to local standards at the participating hospitals. TargetPrint readout showed a high concordance with IHC/ISH of 95 % (kappa 0.81) for ER, 81 % (kappa 0.56) for PR, and 94 % (kappa 0.76) for HER2. The positive/negative agreement between TargetPrint and IHC for ER, PR, and HER2 was 96 %/87 %, 84 %/74 %, and 74 %/98 %, respectively. The concordance rate in IHC/ISH results between hospitals varied: 88-100 % for ER (kappa 0.50-1.00); 50-100 % for PR (kappa 0.20-1.00); and 90-100 % for HER2 (kappa 0.59-1.00). mRNA readout of ER, PR, and HER2 status by TargetPrint was largely comparable to local IHC/ISH analysis. However, there was substantial discordance in IHC/ISH results between different hospitals. When results are discordant, the use of TargetPrint would improve the reliability of hormone receptor and HER2 results by prompting retesting in a reference laboratory.

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Section: Tumor Samplesmentioning

confidence: 99%

An international study comparing conventional versus mRNA level testing (TargetPrint) for ER, PR, and HER2 status of breast cancer

et al. 2016

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“…The incorporation of GEP array information requires the extraction of good-quality DNA and RNA from tissues or blood, and often the need for fresh samples is a logistic challenge that is difficult to overcome in routine practice. Therefore, not surprisingly, FNC samples have been conveniently used for the GEP of different tumors [63,64], including lymphomas [65], exploiting the specific advantages of FNC - namely to harvest vital tumor cells avoiding stroma, fat and other nontumor components. GEP improves the current prognostic indexes based on clinical criteria, such as the International Prognostic Index (IPI) [60,66], because the corresponding GEP-based prognostic models are different in each pathological entity.…”

Section: High-throughput Technologies-based Arraysmentioning

confidence: 99%

Lymph Node Fine-Needle Cytology: Beyond Flow Cytometry

Peluso

Ieni²,

Mignogna³

et al. 2016

Acta Cytologica

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Lymph node (LN) fine-needle cytology (FNC) coupled with flow cytometry immunophenotyping provides relevant information for the diagnosis of non-Hodgkin lymphoma (NHL). Numerous studies have shown FNC samples to be suitable for different molecular procedures; in this review, some of the molecular procedures most commonly employed for NHL are briefly described and evaluated in this perspective. Fluorescence in situ hybridization and chromogenic in situ hybridization are briefly described. Polymerase chain reaction (PCR)-based assays are used to identify and quantify mutations and translocations, namely immunoglobulin (IGH) and T-cell receptor rearrangements by clonality testing and IGVH somatic hypermutations either by Sanger sequencing, single-strand conformational polymorphisms or RT-PCR strategies. High-throughput technologies (HTT) encompass numerous and different diagnostic tools that share the capacity of multiple molecular investigation and sample processing in a fast and reproducible manner. HTT includes gene expression profiling, comparative genomic hybridization, single-nucleotide polymorphism arrays and next-generation sequencing technologies. A brief description of these tools and their potential application to LN FNC is reported. The challenge for FNC will be to achieve new knowledge and apply new technologies to FNC, exploiting its own basic qualities.

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“…Disease classification models are typically determined using multivariate regression analysis ( 27 , 28 ), ROC curve ( 29 – 32 ) or prospective validation ( 33 ). ROC curve was used in the present study in order to evaluate the discriminant effect of the mathematical model and directly observe the accuracy of the present analysis method.…”

Section: Methodsmentioning

confidence: 99%

Establishment of a prediction model of changing trends in cardiac hypertrophy disease based on microarray data screening

Ying

Zhang

et al. 2016

Experimental and Therapeutic Medicine

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The aim of the present study was to construct a mathematical model to predict the changing trends of cardiac hypertrophy at gene level. Microarray data were downloaded from Gene Expression Omnibus database (accession, GSE21600), which included 35 samples harvested from the heart of Wistar rats on postoperative days 1 (D1 group), 6 (D6 group) and 42 (D42 group) following aorta ligation and sham operated Wistar rats, respectively. Each group contained six samples, with the exception of the samples harvested from the aorta ligated group after 6 days, where n=5. Differentially expressed genes (DEGs) were identified using a Limma package in R. Hierarchical clustering analysis was performed on common DEGs in order to construct a linear equation between the D1 and D42 groups, using linear discriminant analysis. Subsequent verification was performed using receiver operating characteristic (ROC) curve and the measurement data at day 42. A total of 319, 44 and 57 DEGs were detected in D1, D6 and D42 sample groups, respectively. AKIP1, ANKRD23, LTBP2, TGF-β2 and TNFRSF12A were identified as common DEGs in all groups. The predicted linear equation between D1 and D42 group was calculated to be y=1.526×-186.671. Assessment of the ROC curve demonstrated that the area under the curve was 0.831, with a specificity and sensitivity of 0.8. As compared with the predictive and measurement data at day 42, the consistency of the two sets of data was 76.5%. In conclusion, the present model may contribute to the early prediction of changing trends in cardiac hypertrophy disease at gene level.

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A gene expression profile for detection of sufficient tumour cells in breast tumour tissue: microarray diagnosis eligibility

Cited by 11 publications

References 10 publications

An international study comparing conventional versus mRNA level testing (TargetPrint) for ER, PR, and HER2 status of breast cancer

An international study comparing conventional versus mRNA level testing (TargetPrint) for ER, PR, and HER2 status of breast cancer

Lymph Node Fine-Needle Cytology: Beyond Flow Cytometry

Establishment of a prediction model of changing trends in cardiac hypertrophy disease based on microarray data screening

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