Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc

Abstract

The aims of this study were to explore the expression of hypoxia inducible factor-1α (HIF-1α) and c-myc protein in triple-negative breast cancer (TNBC) and its clinical prognostic significance, and to establish a prediction model for postoperative survival of TNBC based on nomogram.A total of 87 patients with TNBC at the Department of Breast Surgery, Beijing Chaoyang Hospital, Capital Medical University from January 2012 to December 2015 were enrolled in this study. Immunohistochemistry was performed to detect the expression of HIF-1α and c-myc protein in breast cancer tissues. Cox regression analyses were performed to explore the correlation between HIF-1α/c-myc expression and clinical pathological parameters as well as prognosis. Receiver-operating characteristic curve was generated for cox multivariate analysis. A nomogram was generated based on the cox multivariate analysis, and a calibration curve was prepared for the nomogram to evaluate the consistency between the predicted probability of the nomogram and the actual observed probability. The stability of nomogram model was validated with an external cohort including 39 TNBC patients.The positive expression rates of HIF-1α and c-myc protein in breast cancer tissues were 41.4% (36/87) and 55.2% (48/87), respectively. HIF-1α expression was significantly correlated with age, tumor diameter, histological grade, lymph node status, and tumor TNM stage; c-myc expression was significantly associated with tumor diameter, histological grade, lymph node status, and tumor TNM stage. Cox univariate and multivariate analyses showed that HIF-1α and c-myc protein expression, histological grade, lymph node status, and tumor TNM stage were the independent risk factors for postoperative survival in TNBC patients. The AUC of prediction model was 0.843 (0.809–0.887). The nomogram could predict the probability of 3-year disease-free survival according to each patient's condition. The calibration curve displayed good agreement of the predicted probability with the actual observed probability, indicating that the nomogram model had great value of prediction. The external validation indicated the prediction model had good stability.HIF-1α-positive expression, c-myc positive expression, histological grade III, lymph node positive, and TNM stage III tumors suggested that TNBC patients had a poor prognosis. This prediction model can be used to predict postoperative survival of TNBC.

Molecular Crosstalk Between MYC and HIF in Cancer

“…High MYC level was significantly associated with stabilized HIF1α expression in various cancers, such as prostate cancer, triple-negative breast cancer (TNBC) and animal model of CNS primitive neuroectodermal tumors (Malchenko et al, 2017;Boldrini et al, 2019;Cui and Jiang, 2019). Deregulated MYC cooperates with HIFs to regulate cancer cell adaptation to hypoxia, rewire metabolism, and promote angiogenesis.…”

“…Deregulated MYC cooperates with HIFs to regulate cancer cell adaptation to hypoxia, rewire metabolism, and promote angiogenesis. Also, high MYC and HIF expression is associated with poor outcome in various cancers such as prostate and breast cancers and clear cell renal cell carcinomas (Maroto et al, 2017;Boldrini et al, 2019;Cui and Jiang, 2019). Therefore, MYC and HIFs are potential biomarkers for targeting both pathways.…”

Targeting HIF-1α Function in Cancer through the Chaperone Action of NQO1

“…Although the complexities of cancer prognosis (the high variability of tumor mutations, histological types, grades and stages) makes it too simplistic to think that the levels of expression of a single gene such as HIF1A might have significant impact on prognosis, increased HIF-1α and HIF-2α protein levels in diagnostic tumor biopsies have been correlated with poor prognosis in other types of cancer also, such as brain, breast, colon, cervix, endometrium, head/neck, lung, ovary, pancreas, prostate, rectum and stomach (reviewed in [1]). More recently, high HIF-1α expression has been studied in triple-negative breast cancer (TNBC) [73]. TNBC are a heterogeneous group of poorly differentiated, highly aggressive and metastatic breast cancer type.…”

“…They lack specific molecular-targeted therapy and there is an urgent need to find effective biomarkers rather than relying of their lack of hormone receptors and Her2 expression to define this subgroup. These authors [73] found that HIF-1α and c-Myc expression detected by immunohistochemistry could add to the development of a prognostic nomogram including histological grade and stage of cancer (based on tumor size (T), lymph node involvement (N) and distant metastases (M), known as TNM status). In an effort to validate the proposed nomogram in our institution, we are currently evaluating the feasibility of including HIF-1α immunohistochemistry in the biomarker profile ( Figure 2).…”

A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer

“…To date, nomogram predictions for the survival of TNBCs merely considered conventional clinical and pathological risk factors [ 8 – 10 ]. While efforts have been made in adding novel prognostic factors such as the expression of HIF-1 α and c-myc to nomograms [ 11 ], imaging features have not yet been analyzed. Nowadays, the advent of deep-learning-based “radiomics” technology has allowed for the high-throughput extraction of quantitative imaging features from images, thus enhancing the accuracy of diagnosis and prognostic prediction, especially for malignancies [ 12 ].…”