Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer

Abstract

BackgroundBreast cancer (BC) is the most common malignancy among women. Nicotinamide (NAM) metabolism regulates the development of multiple tumors. Herein, we sought to develop a NAM metabolism-related signature (NMRS) to make predictions of survival, tumor microenvironment (TME) and treatment efficacy in BC patients.MethodsTranscriptional profiles and clinical data from The Cancer Genome Atlas (TCGA) were analyzed. NAM metabolism-related genes (NMRGs) were retrieved from the Molecular Signatures Database. Consensus clustering was performed on the NMRGs and the differentially expressed genes between different clusters were identified. Univariate Cox, Lasso, and multivariate Cox regression analyses were sequentially conducted to develop the NAM metabolism-related signature (NMRS), which was then validated in the International Cancer Genome Consortium (ICGC) database and Gene Expression Omnibus (GEO) single-cell RNA-seq data. Further studies, such as gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, SubMap, and Immunophenoscore (IPS) algorithm, cancer-immunity cycle (CIC), tumor mutation burden (TMB), and drug sensitivity were performed to assess the TME and treatment response.ResultsWe identified a 6-gene NMRS that was significantly associated with BC prognosis as an independent indicator. We performed risk stratification according to the NMRS and the low-risk group showed preferable clinical outcomes (P < 0.001). A comprehensive nomogram was developed and showed excellent predictive value for prognosis. GSEA demonstrated that the low-risk group was predominantly enriched in immune-associated pathways, whereas the high-risk group was enriched in cancer-related pathways. The ESTIMATE and CIBERSORT algorithms revealed that the low-risk group had a higher abundance of anti-tumor immunocyte infiltration (P < 0.05). Results of Submap, IPS, CIC, TMB, and external immunotherapy cohort (iMvigor210) analyses showed that the low-risk group were indicative of better immunotherapy response (P < 0.05).ConclusionsThe novel signature offers a promising way to evaluate the prognosis and treatment efficacy in BC patients, which may facilitate clinical practice and management.

Construction and validation of a novel NAD+ metabolism‐related risk model for prognostic prediction in osteosarcoma

“…In our OS study, in contrast to the low‐risk group, the high‐risk one presented a notable long‐term survival disadvantage, and it had substantially lower stromal score, immune score, as well as ESTIMATE score, as well as greater responsiveness to a variety of chemotherapeutic agents. These findings were corroborated by previous studies focusing on breast cancer 19,25 . In terms of in vitro OS cell experiments, we demonstrated that by inhibiting the upstream target genes, the TGF‐β1/Smad2/3 pathway can be modulated to promote tumor cell migration, proliferation, as well as invasion, which is consistent with findings in thyroid, 28 gastric, 29 pancreatic, 30 and cervical cancers 31 .…”

“…These findings were corroborated by previous studies focusing on breast cancer. 19,25 In terms of in vitro OS cell experiments, we demonstrated that by inhibiting the upstream target genes, the TGF-β1/Smad2/3 pathway can be modulated to promote tumor cell migration, proliferation, as well as invasion, which is consistent with findings in thyroid, 28 gastric, 29 pancreatic, 30 and cervical cancers. 31 Besides, Zhang et al 32,33 found that glaucocalyxin A and oridonin, both of which can reverse epithelial-mesenchymal transition (EMT) as well as TGF-β3-induced EMT through suppressing TGF-β1/Smad2 in OS, which is an important discovery for innovative drugs of OS.…”

“…Consistently, previous studies somewhat support our findings. In terms of bioinformatics analysis, Cui et al 25 and Yang et al 19 have revealed that NAD + biosynthesis metabolism is strongly bound up with the TIME of breast cancer based on the mining and validation of NMRGs model and serves for predicting the survival outcome of breast cancer patients. In parallel, Jiang et al 26 constructed a prognostic signature of glioma patients based on NMRGs, and further confirmed that the signature could help to assess the TIME and prognosis, as well as guide the clinical treatment of glioma patients.…”

Identification of a PANoptosis-related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer

“…In addition, the ROC and calibration curves of the external validation cohort further confirmed the significant predictive value of our model (Figure 2G, H). Taken together, these results demonstrated the outstanding performance of our nomogram compared with previously established prognostic models [43][44][45].…”

“…Tian et al have built a prognostic model using basement membrane-related genes 43 . Cui et al have also established a nomogram based on nicotinamide metabolism-related signature 44 , while Li's model was constructed utilizing m6A-related genes 45 . However, none of these models perform better than our PANoptosis-based nomogram (assessed using AUC), further proving the vital value of our research.…”