Literature DB >> 30814109

Plasma miRNA Levels for Predicting Therapeutic Response to Neoadjuvant Treatment in HER2-positive Breast Cancer: Results from the NeoALTTO Trial.

Serena Di Cosimo1, Valentina Appierto1, Sara Pizzamiglio2, Paola Tiberio1, Marilena V Iorio3, Florentine Hilbers4, Evandro de Azambuja5, Lorena de la Peña6, Miguel Izquierdo7, Jens Huober8, José Baselga9, Martine Piccart5, Filippo G de Braud10, Giovanni Apolone11, Paolo Verderio2, Maria Grazia Daidone12.   

Abstract

PURPOSE: To investigate the potential of circulating-miRNAs (ct-miRNA) as noninvasive biomarkers to predict the efficacy of single/dual HER2-targeted therapy in the NeoALTTO study. EXPERIMENTAL
DESIGN: Patients with plasma samples at baseline (T0) and/or after 2 weeks (T1) of treatment were randomized into training (n = 183) and testing (n = 246) sets. RT-PCR-based high-throughput miRNA profiling was employed in the training set. After normalization, ct-miRNAs associated with pathologic complete response (pCR) were identified by univariate analysis. Multivariate logistic regression models were implemented to generate treatment-specific signatures at T0 and T1, which were evaluated by RT-PCR in the testing set. Event-free survival (EFS) according to ct-miRNA signatures was estimated by Kaplan-Meier method and Cox regression model.
RESULTS: In the training set, starting from 51 ct-miRNAs associated with pCR, six signatures with statistically significant predictive capability in terms of area under the ROC curve (AUC) were identified. Four signatures were confirmed in the testing set: lapatinib at T0 and T1 [AUC 0.86; 95% confidence interval (CI), 0.73-0.98 and 0.71 (0.55-0.86)], respectively; trastuzumab at T1 (0.81; 0.70-0.92); lapatinib + trastuzumab at T1 (0.67; 0.51-0.83). These signatures were confirmed predictive after adjusting for known variables, including estrogen receptor status. ct-miRNA signatures failed to correlate with EFS. However, the levels of ct-miR-140-5p, included in the trastuzumab signature, were associated with EFS (HR 0.43; 95% CI, 0.22-0.84).
CONCLUSIONS: ct-miRNAs discriminate patients with and without pCR after neoadjuvant lapatinib- and/or trastuzumab-based therapy. ct-miRNAs at week two could be valuable to identify patients responsive to trastuzumab, to avoid unnecessary combination with other anti-HER2 agents, and finally to assist deescalating treatment strategies. ©2019 American Association for Cancer Research.

Entities:  

Year:  2019        PMID: 30814109     DOI: 10.1158/1078-0432.CCR-18-2507

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


  15 in total

1.  A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer.

Authors:  Chang Gong; Ziliang Cheng; Yaping Yang; Jun Shen; Yingying Zhu; Li Ling; Wanyi Lin; Zhigang Yu; Zhihua Li; Weige Tan; Chushan Zheng; Wenbo Zheng; Jiajie Zhong; Xiang Zhang; Yunjie Zeng; Qiang Liu; R Stephanie Huang; Andrzej L Komorowski; Eddy S Yang; François Bertucci; Francesco Ricci; Armando Orlandi; Gianluca Franceschini; Kazuaki Takabe; Suzanne Klimberg; Naohiro Ishii; Angela Toss; Mona P Tan; Mathew A Cherian; Erwei Song
Journal:  Sci China Life Sci       Date:  2022-05-13       Impact factor: 6.038

Review 2.  Panels of circulating microRNAs as potential diagnostic biomarkers for breast cancer: a systematic review and meta-analysis.

Authors:  Thu H N Nguyen; Thanh T N Nguyen; Tran T M Nguyen; Le H M Nguyen; Luan H Huynh; Hoang N Phan; Hue T Nguyen
Journal:  Breast Cancer Res Treat       Date:  2022-09-09       Impact factor: 4.624

Review 3.  Emergence of Circulating MicroRNAs in Breast Cancer as Diagnostic and Therapeutic Efficacy Biomarkers.

Authors:  Vaishali Aggarwal; Kumari Priyanka; Hardeep Singh Tuli
Journal:  Mol Diagn Ther       Date:  2020-04       Impact factor: 4.074

Review 4.  Circulating miRNAs in HER2-Positive and Triple Negative Breast Cancers: Potential Biomarkers and Therapeutic Targets.

Authors:  Ishita Gupta; Balsam Rizeq; Semir Vranic; Ala-Eddin Al Moustafa; Halema Al Farsi
Journal:  Int J Mol Sci       Date:  2020-09-15       Impact factor: 5.923

5.  What if the future of HER2-positive breast cancer patients was written in miRNAs? An exploratory analysis from NeoALTTO study.

Authors:  Sara Pizzamiglio; Giulia Cosentino; Chiara M Ciniselli; Loris De Cecco; Alessandra Cataldo; Ilaria Plantamura; Tiziana Triulzi; Sarra El-Abed; Yingbo Wang; Mohammed Bajji; Paolo Nuciforo; Jens Huober; Susan L Ellard; David L Rimm; Andrea Gombos; Maria Grazia Daidone; Paolo Verderio; Elda Tagliabue; Serena Di Cosimo; Marilena V Iorio
Journal:  Cancer Med       Date:  2021-12-17       Impact factor: 4.452

6.  The Essentials of Multiomics.

Authors:  John L Marshall; Beth N Peshkin; Takayuki Yoshino; Jakob Vowinckel; Håvard E Danielsen; Gerry Melino; Ioannis Tsamardinos; Christian Haudenschild; David J Kerr; Carlos Sampaio; Sun Young Rha; Kevin T FitzGerald; Eric C Holland; David Gallagher; Jesus Garcia-Foncillas; Hartmut Juhl
Journal:  Oncologist       Date:  2022-04-05

7.  MicroRNA-208a-3p promotes osteosarcoma progression via targeting PTEN.

Authors:  Yutuo Fu; Yan Wang; Ke Bi; Lei Yang; Yi Sun; Boyuan Li; Zhenzhong Liu; Fulin Zhang; Yuan Li; Chao Feng; Zhenggang Bi
Journal:  Exp Ther Med       Date:  2020-10-23       Impact factor: 2.447

8.  MiR-100 is a predictor of endocrine responsiveness and prognosis in patients with operable luminal breast cancer.

Authors:  Annalisa Petrelli; Sara Erika Bellomo; Ivana Sarotto; Franziska Kubatzki; Paola Sgandurra; Furio Maggiorotto; Maria Rosaria Di Virgilio; Riccardo Ponzone; Elena Geuna; Danilo Galizia; Anna Maria Nuzzo; Enzo Medico; Umberto Miglio; Enrico Berrino; Tiziana Venesio; Salvatore Ribisi; Paolo Provero; Anna Sapino; Silvia Giordano; Filippo Montemurro
Journal:  ESMO Open       Date:  2020-10

9.  Multi-omics analyses identify HSD17B4 methylation-silencing as a predictive and response marker of HER2-positive breast cancer to HER2-directed therapy.

Authors:  Satoshi Yamashita; Naoko Hattori; Satoshi Fujii; Takeshi Yamaguchi; Masato Takahashi; Yasuo Hozumi; Takahiro Kogawa; Omar El-Omar; Yu-Yu Liu; Nobuaki Arai; Akiko Mori; Hiroko Higashimoto; Toshikazu Ushijima; Hirofumi Mukai
Journal:  Sci Rep       Date:  2020-09-23       Impact factor: 4.379

10.  Prediction of Grade Reclassification of Prostate Cancer Patients on Active Surveillance through the Combination of a Three-miRNA Signature and Selected Clinical Variables.

Authors:  Paolo Gandellini; Chiara Maura Ciniselli; Tiziana Rancati; Cristina Marenghi; Valentina Doldi; Rihan El Bezawy; Mara Lecchi; Melanie Claps; Mario Catanzaro; Barbara Avuzzi; Elisa Campi; Maurizio Colecchia; Fabio Badenchini; Paolo Verderio; Riccardo Valdagni; Nadia Zaffaroni
Journal:  Cancers (Basel)       Date:  2021-05-18       Impact factor: 6.639

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