Prediction of response to promising first-line chemotherapy in ovarian cancer patients with residual peritoneal tumors: practical biomarkers and robust multiplex models.

IF 2.4 3区 医学 Q3 ONCOLOGY International Journal of Clinical Oncology Pub Date : 2024-09-01 Epub Date: 2024-05-20 DOI:10.1007/s10147-024-02552-w
Reika Kawabata-Iwakawa, Norihiro Iwasa, Kenichi Satoh, Jacques Colinge, Muneaki Shimada, Satoshi Takeuchi, Hiroyuki Fujiwara, Hidetaka Eguchi, Tetsuro Oishi, Toru Sugiyama, Mitsuaki Suzuki, Kosei Hasegawa, Keiichi Fujiwara, Masahiko Nishiyama
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Abstract

Background: Platinum/taxane (TC) chemotherapy with debulking surgery stays the mainstay of the treatment in ovarian cancer patients with peritoneal metastasis, and recently its novel modality, intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip), was shown to have greater therapeutic impact. Nevertheless, the response varies among patients and consequent recurrence, or relapse often occurs. Discovery of therapeutic response predictor to ddTCip and/or TC therapy is eagerly awaited to improve the treatment outcome.

Methods: Using datasets in 76 participants in our ddTCip study and published databases on patients received TC therapy, we first validated a total of 75 previously suggested markers, sought out more active biomarkers through the association analyses of genome-wide transcriptome and genotyping data with progression-free survival (PFS) and adverse events, and then developed multiplex statistical prediction models for PFS and toxicity by mainly using multiple regression analysis and the classification and regression tree (CART) algorithm.

Results: The association analyses revealed that SPINK1 could be a possible biomarker of ddTCip efficacy, while ABCB1 rs1045642 and ERCC1 rs11615 would be a predictor of hematologic toxicity and peripheral neuropathy, respectively. Multiple regression analyses and CART algorithm finally provided a potent efficacy prediction model using 5 gene expression data and robust multiplex toxicity prediction models-CART models using a total of 4 genotype combinations and multiple regression models using 15 polymorphisms on 12 genes.

Conclusion: Biomarkers and multiplex models composed here could work well in the response prediction of ddTCip and/or TC therapy, which might contribute to realize optimal selection of the key therapy.

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预测有腹膜残留肿瘤的卵巢癌患者对有希望的一线化疗的反应:实用的生物标记物和稳健的多重模型。
背景:铂类/他卡西酮(TC)化疗和剥离手术一直是腹膜转移卵巢癌患者的主要治疗方法,而最近的新疗法--腹腔注射卡铂和剂量密集型紫杉醇(ddTCip)--被证明具有更大的治疗效果。然而,不同患者的反应各不相同,因此经常会出现复发或复发。为了改善治疗效果,人们迫切希望发现ddTCip和/或TC疗法的治疗反应预测指标:利用我们的 ddTCip 研究中 76 名参与者的数据集和已发表的接受 TC 治疗患者的数据库,我们首先验证了之前提出的 75 个标记物,通过全基因组转录组和基因分型数据与无进展生存期(PFS)和不良事件的关联分析,寻找更多活跃的生物标记物,然后主要利用多元回归分析和分类回归树(CART)算法,建立了无进展生存期和毒性的多重统计预测模型:结果:关联分析表明,SPINK1可能是ddTCip疗效的生物标志物,而ABCB1 rs1045642和ERCC1 rs11615则分别是血液学毒性和周围神经病变的预测因子。多元回归分析和 CART 算法最终利用 5 个基因表达数据提供了一个有效的疗效预测模型和稳健的多重毒性预测模型--利用共 4 个基因型组合的 CART 模型和利用 12 个基因的 15 个多态性的多元回归模型:结论:本文提出的生物标志物和多重模型可以很好地预测 ddTCip 和/或 TC 治疗的反应,有助于实现关键疗法的优化选择。
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来源期刊
CiteScore
6.80
自引率
3.00%
发文量
175
审稿时长
2 months
期刊介绍: The International Journal of Clinical Oncology (IJCO) welcomes original research papers on all aspects of clinical oncology that report the results of novel and timely investigations. Reports on clinical trials are encouraged. Experimental studies will also be accepted if they have obvious relevance to clinical oncology. Membership in the Japan Society of Clinical Oncology is not a prerequisite for submission to the journal. Papers are received on the understanding that: their contents have not been published in whole or in part elsewhere; that they are subject to peer review by at least two referees and the Editors, and to editorial revision of the language and contents; and that the Editors are responsible for their acceptance, rejection, and order of publication.
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