Clinical validation of chemotherapy predictors developed on global microRNA expression in the NCI60 cell line panel tested in ovarian cancer

Prahm, Kira Philipsen; Høgdall, Claus; Karlsen, Mona Aarenstrup; Christensen, Ib Jarle; Novotny, Guy Wayne; Knudsen, Steen; Hansen, Anker; Jensen, Peter Buhl; Jensen, Thomas E.; Mirza, Mansoor Raza; Ekmann-Gade, Anne Weng; Nedergaard, Lotte; Høgdall, Estrid

doi:10.1371/journal.pone.0174300

Cited by 11 publications

(14 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All samples were hybridized to the Affymetrix GeneChip miRNA 2.0 Array, which returns expression data of 1105 human mature miRNAs and 911 precursor miRNAs (miRBase v. 15). We have used the Affymetrix platform in several published studies [ 29 – 33 ]. Expression data was normalized using the robust multi-array average (justRMA) method where the raw intensity values are background-corrected, log2-transformed and then quartile-normalized [ 34 ].…”

Section: Methodsmentioning

confidence: 99%

A 4-miRNA signature to predict survival in glioblastomas

et al. 2017

Self Cite

View full text Add to dashboard Cite

Glioblastomas are among the most lethal cancers; however, recent advances in survival have increased the need for better prognostic markers. microRNAs (miRNAs) hold great prognostic potential being deregulated in glioblastomas and highly stable in stored tissue specimens. Moreover, miRNAs control multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included retrospectively; patients were comparable on all clinical aspects except overall survival enabling patients to be categorized as short-term or long-term survivors based on median survival. A miRNome screening was employed, and a prognostic profile was developed using leave-one-out cross-validation. We found that expression patterns of miRNAs; particularly the four miRNAs: hsa-miR-107_st, hsa-miR-548x_st, hsa-miR-3125_st and hsa-miR-331-3p_st could determine short- and long-term survival with a predicted accuracy of 78%. Heatmap dendrograms dichotomized glioblastomas into prognostic subgroups with a significant association to survival in univariate (HR 8.50; 95% CI 3.06–23.62; p<0.001) and multivariate analysis (HR 9.84; 95% CI 2.93–33.06; p<0.001). Similar tendency was seen in The Cancer Genome Atlas (TCGA) using a 2-miRNA signature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available in TCGA. In TCGA, patients with O6-methylguanine-DNA-methyltransferase (MGMT) unmethylated tumors and low miR sum score had the shortest survival. Adjusting for age and MGMT status, low miR sum score was associated with a poorer prognosis (HR 0.66; 95% CI 0.45–0.97; p = 0.033). A Kyoto Encyclopedia of Genes and Genomes analysis predicted the identified miRNAs to regulate genes involved in cell cycle regulation and survival. In conclusion, the biology of miRNAs is complex, but the identified 4-miRNA expression pattern could comprise promising biomarkers in glioblastoma stratifying patients into short- and long-term survivors.

show abstract

Section: Methodsmentioning

confidence: 99%

A 4-miRNA signature to predict survival in glioblastomas

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…The study is expected to generate a vast amount of results and we plan to publish 10–15 papers in relation to it. The first promising results, regarding miRNAs and prediction of resistance to platinum-based drugs, has already been published in the paper “Clinical validation of chemotherapy predictors developed on global microRNA expression in the NCI60 cell line panel tested in ovarian cancer” [28] .…”

Section: Resultsmentioning

confidence: 99%

“…In order to identify new predictive miRNA markers, a correlation between miRNA expression and chemotherapy resistance was investigated in a retrospective study. The results of this study part have been published elsewhere [28] . A total of 198 patients were included ( Fig.…”

Section: Methods and Designmentioning

confidence: 99%

Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project

Hentze

Høgdall

Kjær

et al. 2017

Contemporary Clinical Trials Communications

Self Cite

View full text Add to dashboard Cite

Ovarian cancer is a silent killer and, due to late diagnosis, the primary cause of death amongst gynecological cancers, killing approximately 376 women annually in Denmark. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, but also treatment, by predicting which patients will benefit from specific treatment strategies. The Mermaid III project is consisting of 3 parts including “Early detection, screening and long-term survival,” “Biomarkers and/or prognostic markers” and “The infection theory.” The present paper gives an overview of the part regarding biomarkers and/or prognostic markers, with a focus on rationale and design.The study described has 3 major branches: microRNAs, epigenetics and Next Generation Sequencing. Tissue and blood from ovarian cancer patients, already enrolled in the prospective ongoing pelvic mass cohort, will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient, in order to identify possible biomarkers.A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

show abstract

“…With promising results from ovarian cancer we also tested a microRNA predictor of cisplatin on the RH-cohort [ 44 ], however this did not result in any relevant prediction in the current study.…”

Section: Discussionmentioning

confidence: 99%

Molecular prediction of adjuvant cisplatin efficacy in Non-Small Cell Lung Cancer (NSCLC)—validation in two independent cohorts

et al. 2018

Self Cite

View full text Add to dashboard Cite

IntroductionEffective predictive biomarkers for selection of patients benefiting from adjuvant platinum-based chemotherapy in non-small cell lung cancer (NSCLC) are needed. Based on a previously validated methodology, molecular profiles of predicted sensitivity in two patient cohorts are presented.MethodsThe profiles are correlations between in vitro sensitivity to cisplatin and vinorelbine and baseline mRNA expression of the 60 cell lines in the National Cancer Institute panel. An applied clinical samples filter focused the profiles to clinically relevant genes. The profiles were tested on 1) snap-frozen tumors from 133 patients with completely resected stage 1B-2 NSCLC randomized to adjuvant cisplatin and vinorelbine (ACV, n = 71) or no adjuvant treatment (OBS, n = 62) and 2) formalin-fixed paraffin-embedded (FFPE) tumors from 95 patients with completely resected stage 1A-3B NSCLC receiving adjuvant cisplatin and vinorelbine.ResultsThe combined cisplatin and vinorelbine profiles showed: 1) univariate Hazard Ratio (HR) for sensitive versus resistant of 0.265 (95% CI:0.079–0.889, p = 0.032) in the ACV cohort and a HR of 0.28 in a multivariate model (95% CI:0.08–1.04, p = 0.0573); 2) significant prediction at 3 year survival from surgery in univariate (HR = 0.138 (95% CI:0.035–0.537), p = 0.004) and multivariate analysis (HR = 0.14 (95% CI:0.030–0.6), p = 0.0081). No discrimination was found in the OBS cohort (HR = 1.328, p = 0.60). The cisplatin predictor alone had similar figures with 1) univariate HR of 0.37 (95% CI:0.12–1.15, p = 0.09) in the ACV cohort and 2) univariate HR of 0.14 (95% CI:0.03–0.59, p = 0.0076) to three years. Functional analysis on the cisplatin profile revealed a group of upregulated genes related to RNA splicing as a part of DNA damage repair and apoptosis.ConclusionsProfiles derived from snap-frozen and FFPE NSCLC tissue were prognostic and predictive in the patients that received cisplatin and vinorelbine but not in the cohort that did not receive adjuvant treatment.

show abstract

Clinical validation of chemotherapy predictors developed on global microRNA expression in the NCI60 cell line panel tested in ovarian cancer

Cited by 11 publications

References 43 publications

A 4-miRNA signature to predict survival in glioblastomas

A 4-miRNA signature to predict survival in glioblastomas

Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project

Molecular prediction of adjuvant cisplatin efficacy in Non-Small Cell Lung Cancer (NSCLC)—validation in two independent cohorts

Contact Info

Product

Resources

About