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NMR-Based Metabolomics Analysis Predicts Response to Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer

ABSTRACT: Triple-negative breast cancer (TNBC) is the most fatal type of breast cancer (BC). Due to the lack of relevant targeted drug therapy, in addition to surgery, chemotherapy is still the most common treatment option for TNBC. TNBC is heterogeneous, and different patients have an unusual sensitivity to chemotherapy. Only part of the patients will benefit from chemotherapy, so neoadjuvant chemotherapy (NAC) is controversial in the treatment of TNBC. Here, we performed an NMR spectroscopy–based metabolomics study to analyze the relationship between the patients’ metabolic phenotypes and chemotherapy sensitivity in the serum samples. Metabolic phenotypes from patients with pathological partial response, pathological complete response, and pathological stable disease (pPR, pCR, and pSD) could be distinguished. Furthermore, we conducted metabolic pathway analysis based on identified significant metabolites and revealed significantly disturbed metabolic pathways closely associated with three groups of TNBC patients. We evaluated the discriminative ability of metabolites related to significantly disturbed metabolic pathways by using the multi-receiver–operating characteristic (ROC) curve analysis. Three significantly disturbed metabolic pathways of glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, and alanine, aspartate, and glutamate metabolism could be used as potential predictive models to distinguish three types of TNBC patients. These results indicate that a metabolic phenotype could be used to predict whether a patient is suitable for NAC. Metabolomics research could provide data in support of metabolic phenotypes for personalized treatment of TNBC.

SUBMITTER: He X

PROVIDER: S-EPMC8592909 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Our goal was to determine the impact of pathologic response after neoadjuvant chemotherapy in triple negative breast cancer (TNBC) on the subsequent risk of locoregional recurrence (LRR) and disease-free survival (DFS) in the setting of adjuvant radiation therapy.This was an institutional review board-approved retrospective chart review of patients with clinical stage I-III breast cancer treated with neoadjuvant chemotherapy, local surgery (breast conservation or mastectomy), and adjuvant radiation therapy between 1997 and 2015. Medical records were reviewed for clinical stage, tumor grade and subtype, neoadjuvant chemotherapy regimen, type of surgery, pathologic stage, use of radiation therapy, date and location of recurrence, and date of death. Molecular subtypes were defined using immunohistochemistry and histologic grade. ypT0 and ypN0 were defined as no residual invasive disease in breast or nodes, respectively. LRR was defined as any failure within the breast, chest wall, or regional lymph nodes. Statistical analysis was performed; LRR and DFS rates over 30 months were determined from Kaplan-Meier plots.Ninety-four patients with TNBC were analyzed, of whom 72 received radiation therapy. This subgroup was isolated for further investigation. Median follow-up was 32.5 months in this group. The pathologic complete response (pCR) rate was 36%, and presence or absence of disease in breast and/or nodes was significantly predictive of LRR. In TNBC patients who received radiation therapy, 30-month LRR was 22% in 41 patients with ypT+ versus 0% in 31 patients with ypT0 (P = .003), 23% in 31 patients with ypN+ versus 5% in 41 patients with ypN0 (P = .016), and 20% in 46 patients with residual disease in breast or nodes versus 0% in 26 patients with pCR (P = .015). The difference in the rate of LRR between those who underwent lumpectomy versus mastectomy did not reach significance (8% vs 17%, respectively). Furthermore, patients with residual disease had a higher rate of DFS events (hazard ratio, 3.58; 95% confidence interval, 1.37-9.41; P = .006). The difference in DFS was not significantly associated with the type of surgery received.Patients with TNBC treated with neoadjuvant chemotherapy who have residual disease in the breast or lymph nodes at the time of surgery have significantly higher rates of locoregional failure and lower DFS compared with those with a pCR despite the use of adjuvant radiation therapy. Strategies to intensify therapy for patients with residual disease warrant further investigation.

Project description:BackgroundWhile the efficacy of neoadjuvant chemotherapy (NACT) in treating triple-negative breast cancer (TNBC) is generally accepted, not all patients derive benefit from this preoperative treatment. Presently, there are no validated biomarkers to predict the NACT response, and previous attempts to develop predictive classifiers based on gene expression data have not demonstrated clinical utility. However, predictive models incorporating biological constraints have shown increased robustness and improved performance compared to agnostic classifiers.MethodsWe used the preoperative transcriptomic profiles from 298 patients with TNBC to train and test a rank-based classifier, k-top scoring pairs, to predict whether the patient will have pathological complete response (pCR) or residual disease (RD) following NACT. To reduce overfitting and enhance the signature's interpretability, we constrained the training process to genes involved in the Notch signaling pathway. Subsequently, we evaluated the signature performance on two independent cohorts with 75 and 71 patients. Finally, we assessed the prognostic value of the signature by examining its association with relapse-free survival (RFS) using Kaplan‒Meier (KM) survival estimates and a multivariate Cox proportional hazards model.ResultsThe final signature consists of five gene pairs, whose relative ordering can be predictive of the NACT response. The signature has a robust performance at predicting pCR in TNBC patients with an area under the ROC curve (AUC) of 0.76 and 0.85 in the first and second testing cohorts, respectively, outperforming other gene signatures developed for the same purpose. Additionally, the signature was significantly associated with RFS in an independent TNBC patient cohort even after adjusting for T stage, patient age at the time of diagnosis, type of breast surgery, and menopausal status.ConclusionWe introduce a robust gene signature to predict pathological complete response (pCR) in patients with TNBC. This signature applies easily interpretable, rank-based decision rules to genes regulated by the Notch signaling pathway, a known determinant in breast cancer chemoresistance. The robust predictive and prognostic performance of the signature make it a strong candidate for clinical implementation, aiding in the stratification of TNBC patients undergoing NACT.

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NMR-Based Metabolomics Analysis Predicts Response to Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer

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