Abstract
PURPOSE: This study aimed to investigate the molecular characteristics associated with better prognosis in breast cancer. METHODS: We performed targeted sequencing of 962 genes in 56 samples, categorizing them into long-term and short-term survival groups as well as chemotherapy-sensitive and chemotherapy-resistant groups for further analyses. RESULTS: The results indicated that the tumor mutational burden values were significantly higher in the short-term survival and chemotherapy-resistant groups (p = 0.008 and p = 0.003, respectively). Somatic mutation analysis revealed that the mutation frequencies of BCL9L and WHSC1 were significantly lower in the long-term survival group than those in the short-term survival group (p = 0.029 and p = 0.024, respectively). CREB-regulated transcription coactivator 1 (CRTC1) mutations occurred significantly more frequently in the chemotherapy-resistant group (p = 0.027) and were associated with shorter progression-free survival (p = 0.036). Signature weighting analysis showed a significant increase in Signature.3, which is associated with homologous recombination repair deficiency in the chemotherapy-sensitive group (p = 0.045). Conversely, signatures related to effective DNA repair mechanisms, Signature.1 and Signature.15, were significantly reduced (p = 0.002 and p < 0.001, respectively). Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that gene mutations were significantly enriched in the JAK-STAT signaling pathway. CONCLUSION: This study, through intergroup comparative analysis, found that immunotherapy (using programmed death 1/programmed death-ligand 1 inhibitors) may improve the prognosis of patients with short survival and chemotherapy resistance. Additionally, the study revealed that mutations in BCL9L and WHSC1 could serve as biomarkers for breast cancer prognosis, while CRTC1 mutations and Signature.3 could predict chemotherapy response. The study also found that the JAK-STAT pathway might be a potential therapeutic target for chemotherapy resistance. Therefore, this study identifies molecular characteristics that influence the prognosis of breast cancer patients, providing important theoretical insights for the development of personalized treatment strategies.