The early-stage triple-negative breast cancer landscape derives a novel prognostic signature and therapeutic target

• Published in: Breast cancer research and treatment 2022-06, Vol.193 (2), p.319-330
• Main Authors: Yang, Yun-Song, Ren, Yi-Xing, Liu, Cheng-Lin, Hao, Shuang, Xu, Xiao-En, Jin, Xi, Jiang, Yi-Zhou, Shao, Zhi-Ming
• Format: Article
• Language: English
• Subjects: Analysis; Breast cancer; Cancer research; Cell migration; Cell proliferation; Decision making; Diseases; Health aspects; Homologous recombination; Medicine; Medicine & Public Health; Oncology; Preclinical Study; Prognosis; Relapse; RNA; Therapeutic applications; Therapeutic targets; Transcriptomes; Tumors
• ISSN: 0167-6806; 1573-7217
• DOI: 10.1007/s10549-022-06537-z

Purpose Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Patients with early-stage TNBCs have distinct likelihood of distant recurrence. This study aimed to develop a prognostic signature of early-stage TNBC patients to improve risk stratification. Methods Using RNA-sequencing data, we analyzed 189 pathologically confirmed pT1-2N0M0 TNBC patients and identified 21 mRNAs that were highly expressed in tumor and related to relapse-free survival. All-subset regression program was used for constructing a 7-mRNA signature in the training set ( n  = 159); the accuracy and prognostic value were then validated using an independent validation set ( n  = 158). Results Here, we profiled the transcriptome data from 189 early-stage TNBC patients along with 50 paired normal tissues. Early-stage TNBCs mainly consisted of basal-like immune-suppressed subtype and had higher homologous recombination deficiency scores. We developed a prognostic signature including seven mRNAs (ACAN, KRT5, TMEM101, LCA5, RPP40, LAGE3, CDKL2). In both the training ( n  = 159) and validation set ( n  = 158), this signature could identify patients with relatively high recurrence risks and served as an independent prognostic factor. Time-dependent receiver operating curve showed that the signature had better prognostic value than traditional clinicopathological features in both sets. Functionally, we showed that TMEM101 promoted cell proliferation and migration in vitro, which represented a potential therapeutic target. Conclusions Our 7-mRNA signature could accurately predict recurrence risks of early-stage TNBCs. This model may facilitate personalized therapy decision-making for early-stage TNBCs individuals.