Genomic Grade Index (GGI): Feasibility in Routine Practice and Impact on Treatment Decisions in Early Breast Cancer

Metzger‐Filho, Otto; Catteau, Aurélie; Michiels, Stefan; Buyse, Marc; Ignatiadis, Michail; Saini, Kamal S.; Azambuja, Evandro de; Fasolo, Virginie; Naji, Sihem; Canon, Jean Luc; Delrée, P.; Coibion, Michel; Cusumano, P.; Jossa, Véronique; Kains, Jean Pierre; Larsimont, Denis; Richard, Vincent; Faverly, D.; Cornez, Nathalie; Vuylsteke, Peter; Vanderschueren, Brigitte; Peyro‐Saint‐Paul, Hélène; Piccart, Martine; Sotiriou, Christos

doi:10.1371/journal.pone.0066848

Cited by 23 publications

(11 citation statements)

References 20 publications

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“…Fresh frozen material is used to perform the analysis. [ 23 , 24 ] Oncotype Dx Recurrence Score RS 21 gene-based expression profile score using qRT-PCR (16 cancer genes, 5 housekeeping genes). FFPE blocks used to extract RNA.…”

Section: Molecular Scoresmentioning

confidence: 99%

“…The Genomic Grade Index (Ipsogen, now known as Qiagen Marseille, Marseille, France) is a 97 gene-based assay including mostly proliferation genes and was developed to refine the commonly used histological grade assessment (low, intermediate, and high). The assay classifies women into low- or high-grade groups and has been shown to better define tumor grade, patient prognosis, and breast cancer subtypes [ 23 , 24 ]. Again, this assay has been validated in many different patient subgroups, and the prediction of (distant) recurrence was limited to 5 years after diagnosis.…”

Section: Current Genetic Tests For the Prediction Of Recurrencementioning

confidence: 99%

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Markers for the identification of late breast cancer recurrence

Šestak

Cuzick

2015

Breast Cancer Res

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Postmenopausal women with early breast cancer are at an ongoing risk of relapse, even after successful surgery and treatment of the primary tumor. The treatment of breast cancer has changed in the past few years because of the discovery of prognostic and predictive biomarkers that allow individualized breast cancer treatment. However, it is still not clear how to identify women that are at high risk of a late recurrence. Clinical parameters are good prognostic markers for early recurrence, but only nodal status and, to a lesser extent, tumor size have proven to be strong prognostic markers for late recurrence. Multi-gene signatures have become widely used for the prediction of overall recurrence risk and tailoring administration of adjuvant chemotherapy, but only a few have been shown to be prognostic for late (distant) relapse. There is a need to accurately identify women who may benefit from extended endocrine therapy but also those who may be spared any additional treatment. Recent results from large clinical trials have shown that the research is going in the right direction, and these results might help to optimize extended endocrine therapy for patients with early breast cancer. However, further research is needed to select individual biomarkers or multi-gene signatures that offer identification of late recurrence specifically and thus justify routine use of these tests in the clinical setting.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-015-0516-0) contains supplementary material, which is available to authorized users.

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Section: Molecular Scoresmentioning

confidence: 99%

Section: Current Genetic Tests For the Prediction Of Recurrencementioning

confidence: 99%

Markers for the identification of late breast cancer recurrence

Šestak

Cuzick

2015

Breast Cancer Res

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“…The GGI was investigated alongside other signatures in a large cohort of 2833 patients, highlighting the importance of proliferation-associated genes in breast cancer prognostication [29]. Subsequent evaluation in various clinical cohorts demonstrated the utility of this signature, relative to other measures of a tumours proliferative capacity (Ki67 staining, histological grade, mitotic activity) for predicting disease free survival [42][43][44][45][46][47].…”

Section: Commercially Available Mrna-based Diagnostic Testsmentioning

confidence: 99%

Molecular signatures in breast cancer

Lal

Reed

Luca

et al. 2017

Methods

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The use of molecular signatures to add value to standard clinical and pathological parameters has impacted clinical practice in many cancer types, but perhaps most notably in the breast cancer field. This is, in part, due to the considerable complexity of the disease at the clinical, morphological and molecular levels. The adoption of molecular profiling of DNA, RNA and protein continues to reveal important differences in the intrinsic biology between molecular subtypes and has begun to impact the way patients are managed. Several bioinformatic tools have been developed using DNA or RNA-based signatures to stratify the disease into biologically and/or clinically meaningful subgroups. Here, we review the approaches that have been used to develop gene expression signatures into currently available diagnostic assays (e.g. OncotypeDX® and Mammaprint®), plus we describe the latest work on genome sequencing, the methodologies used in the discovery process of mutational signatures, and the potential of these signatures to impact the clinic.

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“…Some signatures had been developed to re-classify the HG status of BC samples, for example, during the development of GGI, samples with ≥100 ng and a RIN ≥ 7 were considered as qualified, and the quantitative threshold has been adopted during the re-classification process which might be affected by constituent ratios of samples [41], which results lacking of reproducibility for datasets generated by different labs or platforms and limitation of individual application. Meanwhile, the qualitative signature 10-GPS is with wider application to Fig.…”

Section: Discussionmentioning

confidence: 99%

“…For each of the four validation datasets, we obtained relapse risk by using existing signatures such as Gene expression Grade Index (GGI) [41], PAM50 [42] and Oncotype DX [43]. Chi-square test were conducted, revealing that there were significant differences in relapse risks generated by almost all the three existing signatures between HG1 and HG3 cohorts (Fig.…”

Section: Comparison Of 10-gps Prognostic Significance With Ggi Oncotmentioning

confidence: 99%

A qualitative transcriptional signature to reclassify histological grade of ER-positive breast cancer patients

Jiang

Liang

et al. 2020

BMC Genomics

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Background: Histological grade (HG) is commonly adopted as a prognostic factor for ER-positive breast cancer patients. However, HG evaluation methods, such as the pathological Nottingham grading system, are highly subjective with only 50-85% inter-observer agreements. Specifically, the subjectivity in the pathological assignment of the intermediate grade (HG2) breast cancers, comprising of about half of breast cancer cases, results in uncertain disease outcomes prediction. Here, we developed a qualitative transcriptional signature, based on within-sample relative expression orderings (REOs) of gene pairs, to define HG1 and HG3 and reclassify pathologically-determined HG2 (denoted as pHG2) breast cancer patients. Results: From the gene pairs with significantly stable REOs in pathologically-determined HG1 (denoted as pHG1) samples and reversely stable REOs in pathologically-determined HG3 (denoted as pHG3) samples, concordantly identified from seven datasets, we extracted a signature which could determine the HG state of samples through evaluating whether the within-sample REOs match with the patterns of the pHG1 REOs or pHG3 REOs. A sample was classified into the HG3 group if at least a half of the REOs of the 10 gene pairs signature within this sample voted for HG3; otherwise, HG1. Using four datasets including samples of early stage (I-II) ER-positive breast cancer patients who accepted surgery only, we validated that this signature was able to reclassify pHG2 patients into HG1 and HG3 groups with significantly different survival time. For the original pHG1 and pHG3 patients, the signature could also more accurately and objectively stratify them into distinct prognostic groups. And the up-regulated and down down-regulated genes in HG1 compared with HG3 involved in cell proliferation and extracellular signal transduction pathways respectively. By comparing with existing signatures, 10-GPS was with prognostic significance and was more aligned with survival of patients especially for pHG2 samples. Conclusions: The transcriptional qualitative signature can provide an objective assessment of HG states of ER-positive breast cancer patients, especially for reclassifying patients with pHG2, to assist decision making on clinical therapy.

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Genomic Grade Index (GGI): Feasibility in Routine Practice and Impact on Treatment Decisions in Early Breast Cancer

Cited by 23 publications

References 20 publications

Markers for the identification of late breast cancer recurrence

Markers for the identification of late breast cancer recurrence

Molecular signatures in breast cancer

A qualitative transcriptional signature to reclassify histological grade of ER-positive breast cancer patients

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