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DNA methylation markers panel can improve prediction of response to neoadjuvant chemotherapy in luminal B breast cancer.

ABSTRACT: Despite the advantages of neoadjuvant chemotherapy (NACT), associated toxicity is a serious complication that renders monitoring of the patients' response to NACT highly important. Thus, prediction of tumor response to treatment is imperative to avoid exposure of potential non-responders to deleterious complications. We have performed genome-wide analysis of DNA methylation by XmaI-RRBS and selected CpG dinucleotides differential methylation of which discriminates luminal B breast cancer samples with different sensitivity to NACT. With this data, we have developed multiplex methylation sensitive restriction enzyme PCR (MSRE-PCR) protocol for determining the methylation status of 10 genes (SLC9A3, C1QL2, DPYS, IRF4, ADCY8, KCNQ2, TERT, SYNDIG1, SKOR2 and GRIK1) that distinguish BC samples with different NACT response. Analysis of these 10 markers by MSRE-PCR in biopsy samples allowed us to reveal three top informative combinations of markers, (1) IRF4 and C1QL2; (2) IRF4, C1QL2, and ADCY8; (3) IRF4, C1QL2, and DPYS, with the areas under ROC curves (AUCs) of 0.75, 0.78 and 0.74, respectively. A classifier based on IRF4 and C1QL2 better meets the diagnostic panel simplicity requirements, as it consists of only two markers. Diagnostic accuracy of the panel of these two markers is 0.75, with the sensitivity of 75% and specificity of 75%.

SUBMITTER: Sigin VO

PROVIDER: S-EPMC7280523 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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DNA methylation markers panel can improve prediction of response to neoadjuvant chemotherapy in luminal B breast cancer.

Sigin Vladimir O VO Kalinkin Alexey I AI Kuznetsova Ekaterina B EB Simonova Olga A OA Chesnokova Galina G GG Litviakov Nikolai V NV Slonimskaya Elena M EM Tsyganov Matvey M MM Ibragimova Marina K MK Volodin Ilya V IV Vinogradov Ilya I II Vinogradov Maksim I MI Vinogradov Igor Y IY Kutsev Sergey I SI Strelnikov Vladimir V VV Zaletaev Dmitry V DV Tanas Alexander S AS

Scientific reports 20200608 1

Despite the advantages of neoadjuvant chemotherapy (NACT), associated toxicity is a serious complication that renders monitoring of the patients' response to NACT highly important. Thus, prediction of tumor response to treatment is imperative to avoid exposure of potential non-responders to deleterious complications. We have performed genome-wide analysis of DNA methylation by XmaI-RRBS and selected CpG dinucleotides differential methylation of which discriminates luminal B breast cancer samples ...[more]

PMID: 32514046

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Project description:Background: Neoadjuvant chemotherapy is increasingly being used to preoperatively shrink breast tumours prior to surgery. This approach also provides the opportunity to study the molecular changes associated with treatment and evaluate whether on-treatment sequential samples can improve response and outcome predictions over diagnostic or excision samples alone. Methods: A total of 95 samples from a cohort of 50 neoadjuvant chemotherapy-treated primary breast cancer patients (aged 29-76, 48% ER+, 20% HER2+) enrolled in the NEO trial taken before, at 2 weeks on-treatment, mid-therapy and at resection were sequenced with Ion Ampliseq transcriptome yielding expression values for 12,635 genes. Differential expression analysis was performed across 16 responders and 34 non-responders defined by pathological complete response and over treatment time to identify significantly differentially expressed genes, pathways and markers indicative of response status. Prediction accuracy was compared with estimations of established gene signatures, for this dataset and validated using data from the I-SPY1 trial. Results: AAGAB was identified as a novel on-treatment biomarker for pathological complete response, with an accuracy of 100% in the NEO training dataset and 78% accuracy in the I-SPY1 Trial. AAGAB levels on treatment were also significantly predictive of term survival (p = 0.048, p = 0.031) in the two cohorts. This single gene on-treatment biomarker, had greater predictive accuracy than established prognostic tests, Mammaprint and Pam50 risk of recurrence score, although interesting both of these tests performed better in the on-treatment rather than the accepted pre-treatment setting (accuracy improving consistently by 2-8%). Conclusion: Changes in gene expression measured in sequential samples from breast cancer patients receiving neoadjuvant chemotherapy resulted in the identification of a novel on-treatment biomarker and suggest that established prognostic tests may have greater prediction accuracy on- than before treatment. These results support the potential use and further evaluation of on- treatment testing in breast cancer to improve the accuracy of tumour response prediction.

Project description:BackgroundNeoadjuvant chemotherapy is increasingly given preoperatively to shrink breast tumours prior to surgery. This approach also provides the opportunity to study the molecular changes associated with treatment and evaluate whether on-treatment sequential samples can improve response and outcome predictions over diagnostic or excision samples alone.MethodsThis study included a total of 97 samples from a cohort of 50 women (aged 29-76, with 46% ER+ and 20% HER2+ tumours) with primary operable breast cancer who had been treated with neoadjuvant chemotherapy. Biopsies were taken at diagnosis, at 2 weeks on-treatment, mid-chemotherapy, and at resection. Fresh frozen samples were sequenced with Ion AmpliSeq Transcriptome yielding expression values for 12,635 genes. Differential expression analysis was performed across 16 patients with a complete pathological response (pCR) and 34 non-pCR patients, and over treatment time to identify significantly differentially expressed genes, pathways, and markers indicative of response status. Prediction accuracy was compared with estimations of established gene signatures, for this dataset and validated using data from the I-SPY 1 Trial.ResultsAlthough changes upon treatment are largely similar between the two cohorts, very few genes were found to be consistently different between responders and non-responders, making the prediction of response difficult. AAGAB was identified as a novel potential on-treatment biomarker for pathological complete response, with an accuracy of 100% in the NEO training dataset and 78% accuracy in the I-SPY 1 testing dataset. AAGAB levels on-treatment were also significantly predictive of outcome (p = 0.048, p = 0.0036) in both cohorts. This single gene on-treatment biomarker had greater predictive accuracy than established prognostic tests, Mammaprint and PAM50 risk of recurrence score, although interestingly, both of these latter tests performed better in the on-treatment rather than the accepted pre-treatment setting.ConclusionChanges in gene expression measured in sequential samples from breast cancer patients receiving neoadjuvant chemotherapy resulted in the identification of a potentially novel on-treatment biomarker and suggest that established prognostic tests may have greater prediction accuracy on than before treatment. These results support the potential use and further evaluation of on-treatment testing in breast cancer to improve the accuracy of tumour response prediction.

Project description:BackgroundLocally advanced breast cancer is a heterogeneous disease with respect to response to neoadjuvant chemotherapy (NACT) and survival. It is currently not possible to accurately predict who will benefit from the specific types of NACT. DNA methylation is an epigenetic mechanism known to play an important role in regulating gene expression and may serve as a biomarker for treatment response and survival. We investigated the potential role of DNA methylation as a prognostic marker for long-term survival (> 5 years) after NACT in breast cancer.MethodsDNA methylation profiles of pre-treatment (n = 55) and post-treatment (n = 75) biopsies from 83 women with locally advanced breast cancer were investigated using the Illumina HumanMethylation450 BeadChip. The patients received neoadjuvant treatment with epirubicin and/or paclitaxel. Linear mixed models were used to associate DNA methylation to treatment response and survival based on clinical response to NACT (partial response or stable disease) and 5-year survival, respectively. LASSO regression was performed to identify a risk score based on the statistically significant methylation sites and Kaplan-Meier curve analysis was used to estimate survival probabilities using ten years of survival follow-up data. The risk score developed in our discovery cohort was validated in an independent validation cohort consisting of paired pre-treatment and post-treatment biopsies from 85 women with locally advanced breast cancer. Patients included in the validation cohort were treated with either doxorubicin or 5-FU and mitomycin NACT.ResultsDNA methylation patterns changed from before to after NACT in 5-year survivors, while no significant changes were observed in non-survivors or related to treatment response. DNA methylation changes included an overall loss of methylation at CpG islands and gain of methylation in non-CpG islands, and these changes affected genes linked to transcription factor activity, cell adhesion and immune functions. A risk score was developed based on four methylation sites which successfully predicted long-term survival in our cohort (p = 0.0034) and in an independent validation cohort (p = 0.049).ConclusionOur results demonstrate that DNA methylation patterns in breast tumors change in response to NACT. These changes in DNA methylation show potential as prognostic biomarkers for breast cancer survival.

Dataset Information

DNA methylation markers panel can improve prediction of response to neoadjuvant chemotherapy in luminal B breast cancer.

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DNA methylation markers panel can improve prediction of response to neoadjuvant chemotherapy in luminal B breast cancer.

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