A Qualitative Transcriptional Signature To Reclassify HER2 Status Of Breast Cancer Patients

Purpose:Among females,breast cancer is with the highest morbidity.About15-20%of breast cancer patients are of HER2-positive,with high degree of malignancy and poor prognosis.HER2-positive breast cancer patients can benefit from the treatment of anti-HER2 monoclonal antibodies,such as trastuzumab and pertuzumab.HER2-negative patients can not benefit from therapy with anti-HER2monoclonal antibodies and they should be treated with chemotherapy.During clinicopathological examination,immuno-histochemistry and fluorescence in situ hybridization are adopted to test the HER2 status of breast cancer samples.However,the results of HER2 status testing are inconsistent between different laboratories or between different detection methods to a certain.Currently,studies have used gene expression profiles to identify classification signatures for determining HER2 status of breast cancer,but most of these signatures were extracted based on summarizing a classification threshold from the quantitative expression values of a group of genes.It has been reported that the quantitative gene expression values are sensitive to factors,such as sample quality and batch effect.These signatures are lack of reproducibility for independent datasets and with limitation of application to clinical practice.Therefore,it is of great importance to accurately evaluate the HER2 status.Method:In order to identify the HER2 status of breast cancer patients accurately,based on within-sample relative expression orderings（REO）,we developed a qualitative transcriptional signature that can classify the HER2 status of breast cancer patients.Firstly,for datasets measured by the microarray platform and the next-generation sequencing platform,we identified reversal-stable gene pairs in which gene pairs were stable in HER2 negative breast cancer samples but reversed in HER2positive breast cancer samples.And we extracted the reversal-stable gene pairs with concordantly reversal REO pattern in both microarray and next-generation sequencing.Then,considering that the HER2 status is associated with prognosis of breast cancer,we used the univariate Cox regression model to identify the prognostic-associated reversal-stable gene pairs.Furthermore,a forward selection procedure was applied to search the set of gene pairs with highest H-score as the classification signature for HER2 status.Finally,we compared the concordance between the reclassified label and their pathological labels,and evaluated the accuracy of reclassified samples by the treatment benefit and survival rate.Result:In this study,a total of 7 datasets from the microarray platform and the next-generation sequencing platform were used to developed a classification signature that can reclassify breast cancer HER2 status,consisting of 12 gene pairs（12-GPS）.we reclassified 303 samples of microarray platform and 90%of the samples were reclassified to HER2 status consistent with pathological labels.For 3151 samples from the next-generation sequencing platform,94%of the samples were consistent with pathological labels.For samples receiving trastuzumab,the reclassified HER2-negative samples from pathological HER2-positive samples had marginally significant higher recurrence-free ratio than that of HER2-positive patients（HR=0.18,95%CI0.02-1.42,log-rank P=0.0658）.For the three datasets with samples receiving surgery only,survival rate of reclassified HER2-positive samples was significantly lower than that of reclassified HER2-negative samples in GSE4922＿so,while the prognosis of reclassified samples in the other two datasets were with marginally significant difference.However,for the three datasets with samples receiving endocrine therapy,all of the three datasets were with significant prognosis differences(HR:3.09,3.16,and 1.98;95%CI:1.12-8.56,1.94-5.15,and 1.24-3.16;log-rank P:0.022,1.07×10^-6and 3.96×10^-3;respectively).In the ER-positive samples,the survival rate of reclassified HER2-positive samples was significantly lower than that of the reclassified HER2-negative samples.Conclusion:In summary,based on qualitative transcriptional reclassification signature,12-GPS,could accurately identify the HER2 status for individual breast cancer patient,which can assist in the decision-making of clinical therapy.