Literature DB >> 27179111

Changes in Expression of Genes Representing Key Biologic Processes after Neoadjuvant Chemotherapy in Breast Cancer, and Prognostic Implications in Residual Disease.

Marie Klintman1, Richard Buus2, Maggie Chon U Cheang3, Amna Sheri4, Ian E Smith4, Mitch Dowsett5.   

Abstract

PURPOSE: The primary aim was to derive evidence for or against the clinical importance of several biologic processes in patients treated with neoadjuvant chemotherapy (NAC) by assessing expression of selected genes with prior implications in prognosis or treatment resistance. The secondary aim was to determine the prognostic impact in residual disease of the genes' expression. EXPERIMENTAL
DESIGN: Expression levels of 24 genes were quantified by NanoString nCounter on formalin-fixed paraffin-embedded residual tumors from 126 patients treated with NAC and 56 paired presurgical biopsies. The paired t test was used for testing changes in gene expression, and Cox regression and penalized elastic-net Cox Regression for estimating HRs.
RESULTS: After NAC, 12 genes were significantly up- and 8 downregulated. Fourteen genes were significantly associated with time to recurrence in univariable analysis in residual disease. In a multivariable model, ACACB, CD3D, MKI67, and TOP2A added prognostic value independent of clinical ER(-), PgR(-), and HER2(-) status. In ER(+)/HER2(-) patients, ACACB, PAWR, and ERBB2 predicted outcome, whereas CD3D and PAWR were prognostic in ER(-)/HER2(-) patients. By use of elastic-net analysis, a 6-gene signature (ACACB, CD3D, DECORIN, ESR1, MKI67, PLAU) was identified adding prognostic value independent of ER, PgR, and HER2.
CONCLUSIONS: Most of the tested genes were significantly enriched or depleted in response to NAC. Expression levels of genes representing proliferation, stromal activation, metabolism, apoptosis, stemcellness, immunologic response, and Ras-ERK activation predicted outcome in residual disease. The multivariable gene models identified could, if validated, be used to identify patients needing additional post-neoadjuvant treatment to improve prognosis. Clin Cancer Res; 22(10); 2405-16. ©2016 AACR. ©2016 American Association for Cancer Research.

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Year:  2016        PMID: 27179111     DOI: 10.1158/1078-0432.CCR-15-1488

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  16 in total

1.  Identification of differentially expressed protein-coding genes in lung adenocarcinomas.

Authors:  Luyao Wang; Shicheng Li; Yuanyong Wang; Zhenxue Tang; Chaolong Liu; Wenjie Jiao; Jia Liu
Journal:  Exp Ther Med       Date:  2019-12-06       Impact factor: 2.447

2.  Identification of tumor biomarkers for pathological complete response to neoadjuvant treatment in locally advanced breast cancer.

Authors:  Prarthana Gopinath; Sridevi Veluswami; Gopal Gopisetty; Shirley Sundersingh; Swaminathan Rajaraman; Rajkumar Thangarajan
Journal:  Breast Cancer Res Treat       Date:  2022-05-21       Impact factor: 4.872

3.  DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival.

Authors:  Christine Aaserød Pedersen; Maria Dung Cao; Thomas Fleischer; Morten B Rye; Stian Knappskog; Hans Petter Eikesdal; Per Eystein Lønning; Jörg Tost; Vessela N Kristensen; May-Britt Tessem; Guro F Giskeødegård; Tone F Bathen
Journal:  Breast Cancer Res       Date:  2022-06-24       Impact factor: 8.408

4.  Integrated analysis and identification of nine-gene signature associated to oral squamous cell carcinoma pathogenesis.

Authors:  Monika Yadav; Dibyabhaba Pradhan; Rana P Singh
Journal:  3 Biotech       Date:  2021-04-14       Impact factor: 2.406

5.  Neoadjuvant chemotherapy affects molecular classification of colorectal tumors.

Authors:  K Trumpi; I Ubink; A Trinh; M Djafarihamedani; J M Jongen; K M Govaert; S G Elias; S R van Hooff; J P Medema; M M Lacle; L Vermeulen; I H M Borel Rinkes; O Kranenburg
Journal:  Oncogenesis       Date:  2017-07-10       Impact factor: 7.485

6.  Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes.

Authors:  Juan Chen; Juan Xu; Yongsheng Li; Jinwen Zhang; Hong Chen; Jianping Lu; Zishan Wang; Xueying Zhao; Kang Xu; Yixue Li; Xia Li; Yan Zhang
Journal:  Oncotarget       Date:  2017-02-07

Review 7.  Chemoresistance and targeted therapies in ovarian and endometrial cancers.

Authors:  Kevin Brasseur; Nicolas Gévry; Eric Asselin
Journal:  Oncotarget       Date:  2017-01-17

8.  Identification of a prognostic 28-gene expression signature for gastric cancer with lymphatic metastasis.

Authors:  Chao Zhang; Li-Wei Jing; Zhi-Ting Li; Zi-Wei Chang; Hui Liu; Qiu-Meng Zhang; Qing-Yu Zhang
Journal:  Biosci Rep       Date:  2019-05-02       Impact factor: 3.840

Review 9.  Combination Therapy, a Promising Approach to Enhance the Efficacy of Radionuclide and Targeted Radionuclide Therapy of Prostate and Breast Cancer.

Authors:  Tyrillshall S T Damiana; Simone U Dalm
Journal:  Pharmaceutics       Date:  2021-05-07       Impact factor: 6.321

10.  Prediction of Target Genes and Pathways Associated With Cetuximab Insensitivity in Colorectal Cancer.

Authors:  Chaoran Yu; Hiju Hong; Jiaoyang Lu; Xuan Zhao; Wenjun Hu; Sen Zhang; Yaping Zong; Zhihai Mao; Jianwen Li; Mingliang Wang; Bo Feng; Jing Sun; Minhua Zheng
Journal:  Technol Cancer Res Treat       Date:  2018-01-01
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