Literature DB >> 25874688

Gene expression-based prognostic and predictive tools in breast cancer.

Gyöngyi Munkácsy1, Marcell A Szász, Otilia Menyhárt.   

Abstract

Genomic assays measuring the expression of multiple genes have made their way into clinical practice and their utilization is now recommended by major international guidelines. A basic property of these tests is their capability to sub-divide patients into high- and low-risk cohorts thereby providing prognostic, and in certain settings, predictive decision support. Here, we summarize commercially available assays for breast cancer including RT-PCR and gene chip-based tests. Given the relative uncertainty in cancer treatment, multigene tests have the potential for a significant cost reduction as they can pinpoint those patients for whom chemotherapy proves to be unnecessary. However, concordance of risk assessment for an individual patient is still far from optimal. Additionally, emerging multigene approaches focus on predicting therapy response, which is a black spot of current tests. Promising techniques include the homologous recombination deficiency score, utilization of massive parallel sequencing to identify driver genes, employment of internet-based meta-analysis tools and investigation of miRNA expression signatures. Combination of multiple simultaneous analyses at diagnosis, including classical histopathological diagnostics, monogenic markers, genomic signatures and clinical parameters will most likely bring maximal benefit for patients. As the main driving force behind such genomic tests is the power to achieve cost reduction due to avoiding unnecessary systemic treatment, the future is most likely to hold a further proliferation of such assays.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25874688     DOI: 10.1007/s12282-015-0594-y

Source DB:  PubMed          Journal:  Breast Cancer        ISSN: 1340-6868            Impact factor:   4.239


  5 in total

Review 1.  Progress in the clinical detection of heterogeneity in breast cancer.

Authors:  Jun-Long Song; Chuang Chen; Jing-Ping Yuan; Sheng-Rong Sun
Journal:  Cancer Med       Date:  2016-10-24       Impact factor: 4.452

2.  The potential of RNA as a target for national screening of pre-cancer.

Authors:  Frank Karlsen; Margaret Muturi; Cosmas Muyabwa; Lars E Roseng; Serge Bigabwa; Byamungu Chihongola; Lucy Muchiri
Journal:  J Public Health Afr       Date:  2018-12-21

3.  Independent validation of induced overexpression efficiency across 242 experiments shows a success rate of 39.

Authors:  Gyöngyi Munkácsy; Péter Herman; Balázs Győrffy
Journal:  Sci Rep       Date:  2019-01-23       Impact factor: 4.379

4.  Practical consensus recommendations regarding the management of hormone receptor positive early breast cancer in elderly women.

Authors:  Govind Babu; A Goel; S Agarwal; S Gupta; P Kumar; B K Smruti; V Goel; R Sarangi; M Gairola; S Aggarwal; Purvish M Parikh
Journal:  South Asian J Cancer       Date:  2018 Apr-Jun

5.  A six-gene-based signature for breast cancer radiotherapy sensitivity estimation.

Authors:  Xing Chen; Junjie Zheng; Min Ling Zhuo; Ailong Zhang; Zhenhui You
Journal:  Biosci Rep       Date:  2020-12-23       Impact factor: 3.840

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.