Literature DB >> 23203637

SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B are markers of resistance to neoadjuvant chemotherapy in HER2-negative breast cancer.

Jorma J de Ronde1, Esther H Lips, Lennart Mulder, Andrew D Vincent, Jelle Wesseling, Marja Nieuwland, Ron Kerkhoven, Marie-Jeanne T F D Vrancken Peeters, Gabe S Sonke, Sjoerd Rodenhuis, Lodewyk F A Wessels.   

Abstract

Response rates to chemotherapy remain highly variable in breast cancer patients. We set out to identify genes associated with chemotherapy resistance. We analyzed what is currently the largest single-institute set of gene expression profiles derived from breast cancers prior to a single neoadjuvant chemotherapy regimen (dose-dense doxorubicin and cyclophosphamide). We collected, gene expression-profiled, and analyzed 178 HER2-negative breast tumor biopsies ("NKI dataset"). We employed a recently developed approach for detecting imbalanced differential signal (DIDS) to identify markers of resistance to treatment. In contrast to traditional methods, DIDS is able to identify markers that show aberrant expression in only a small subgroup of the non-responder samples. We found a number of markers of resistance to anthracycline-based chemotherapy. We validated our findings in three external datasets, totaling 456 HER2-negative samples. Since these external sets included patients who received differing treatment regimens, the validated markers represent markers of general chemotherapy resistance. There was a highly significant overlap in the markers identified in the NKI dataset and the other three datasets. Five resistance markers, SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B, were identified in three of the four datasets (p value overlap < 1 × 10(-6)). These five genes identified resistant tumors that could not have been identified by merely taking ER status or proliferation into account. The identification of these genes might lead to a better understanding of the mechanisms involved in (clinically) observed chemotherapy resistance and could possibly assist in the recognition of breast cancers in which chemotherapy does not contribute to response or survival.

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Year:  2012        PMID: 23203637     DOI: 10.1007/s10549-012-2340-x

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  22 in total

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Journal:  Breast Cancer Res Treat       Date:  2022-03-06       Impact factor: 4.872

4.  Development and validation of a novel lipid metabolism-related gene prognostic signature and candidate drugs for patients with bladder cancer.

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Journal:  Lipids Health Dis       Date:  2021-10-27       Impact factor: 3.876

5.  X-box binding protein 1 (XBP1): a potential role in chemotherapy response, clinical pathologic features, non-inflamed tumour microenvironment for breast cancer.

Authors:  Zhipeng Zhu; Hongliang Zhan; Anran Sun; Heqing Huang; Baisheng Chen; Fuxing Zhang
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Authors:  Tomas Blom; Shiqian Li; Andrea Dichlberger; Nils Bäck; Young Ah Kim; Ursula Loizides-Mangold; Howard Riezman; Robert Bittman; Elina Ikonen
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7.  Preliminary investigation of the function of hsa_circ_0006215 in pancreatic cancer.

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Review 8.  G-protein coupled receptors of the renin-angiotensin system: new targets against breast cancer?

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Authors:  Fabian R Reimold; Savithri Balasubramanian; David B Doroquez; Boris E Shmukler; Zsuzsanna K Zsengeller; David Saslowsky; Jay R Thiagarajah; Isaac E Stillman; Wayne I Lencer; Bai-Lin Wu; Salvador Villalpando-Carrion; Seth L Alper
Journal:  Front Physiol       Date:  2015-06-23       Impact factor: 4.566

10.  Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response.

Authors:  Esther H Lips; Magali Michaut; Marlous Hoogstraat; Lennart Mulder; Nicolle J M Besselink; Marco J Koudijs; Edwin Cuppen; Emile E Voest; Rene Bernards; Petra M Nederlof; Jelle Wesseling; Sjoerd Rodenhuis; Lodewyk F A Wessels
Journal:  Breast Cancer Res       Date:  2015-10-03       Impact factor: 6.466

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