Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer.

BACKGROUND: This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients. METHODS: A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre­therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines. RESULTS: Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels. CONCLUSION: Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

Different risk and prognostic factors for liver metastasis of breast cancer patients with de novo and relapsed distant metastasis in a Chinese population.

Purpose: The present study aimed to identify clinicopathological characteristics of breast cancer liver metastasis (BCLM) as well as to characterize the risk and prognostic factors for the liver metastasis (LM) of breast cancer patients with de novo and relapsed distant metastasis in a Chinese population. Materials and methods: Patients with metastatic breast cancer (MBC) who were hospitalized in the Breast Cancer Center at Chongqing University between January 2011 and December 2019 were included in the present study. Logistic regression analyses were conducted to identify risk factors for the presence of BCLM. Cox proportional hazard regression models were performed to determine the prognostic factors for the survival of BCLM patients. The correlation between LM and overall survival was assessed by the Kaplan-Meier method. Results: In total, 1,228 eligible MBC patients, including 325 cases (26.5%) with de novo metastasis (cohort A) and 903 cases (73.5%) with relapsed metastasis (cohort B), were enrolled in the present study. In cohort A and cohort B, 81 (24.9%) and 226 (25.0%) patients had BCLM, respectively. Patients in these two cohorts had different clinicopathological features. Logistic regression analysis identified that the human epidermal growth factor receptor 2 (HER2) status in cohort A as well as the HER2 status and invasive ductal carcinoma histology in cohort B were risk factors for BCLM. The median OS of patients with LM was inferior to that of non-LM patients (17.1 vs. 37.7 months, P = 0.0004 and 47.6 vs. 84.0 months, P < 0.0001, respectively). Cox analysis identified that the primary T stage, Ki67 level, and breast surgery history were independent prognostic factors for cohorts A and B, respectively. Conclusions: De novo and relapsed MBC patients have different risk and prognostic factors for LM. Patients with BCLM have an unfavorable prognosis.

Neutrophil-to-lymphocyte ratio is a negative prognostic biomarker for luminal A breast cancer.

Background: Inflammation plays an important role in the occurrence, development, and metastasis of tumors. However, the prognostic role of the neutrophil-to-lymphocyte ratio (NLR) in patients with luminal A breast cancer has rarely been reported in the literature. The purpose of this study was to investigate the relationship between preoperative peripheral blood NLR and the survival rate of patients with luminal A breast cancer. Methods: Data from 226 eligible patients with luminal A breast cancer at the Chongqing University Cancer Hospital between 2011 and 2016 were obtained. The cut-off value for NLR for predicting overall survival (OS) rate was obtained from the receiver operating characteristic (ROC) curve. The baseline characteristics of 2 groups were compared using the Chi-square test or Fisher's exact test, and OS was estimated using the Kaplan-Meier method. Cox analysis was performed to determine the correlation between clinicopathological parameters and prognosis. Results: ROC curve analysis showed that the cutoff value for NLR to predict OS was 2.0. Kaplan-Meier analysis revealed that the OS of patients with a NLR <2.0 was significantly longer than that of patients with a higher NLR >2 (P<0.0001). The area under the curve (AUC) for NLR to predict OS was 0.781 [95% confidence interval (CI): 0.712-0.851], sensitivity was 54.17%, and specificity was 97.06%. In univariate Cox regression analysis, NLR, tumor (T) stage (T3-T4 vs. T1-T2), and histological grade (II-III vs. I) were all significantly associated with OS. In multivariate Cox regression analysis, NLR and histology grade (II-III vs. I) were independent prognostic factors for OS. Conclusions: The results suggested that higher preoperative NLR was associated with worse prognosis in luminal A breast cancer.