Objective: Nucleoredoxin Like 1 (NXNL1) is a protein coding gene. Diseases associated with NXNL1 include Retinitis Pigmentosa. However, the roles of NXNL1 in cancer remain unknown. Methods: The expression of NXNL1 was interpreted by The Cancer Genome Atlas (TCGA) database and Genotype Tissue-Expression (GTEX) database. Analysis of NXNL1 genomic alterations and protein expression in human cancer tissues was analyzed by the cBioPortal database and human multiple organ tissue arrays. The correlations between NXNL1 expression and survival outcomes, clinical features, and immune-associated cell infiltration were analyzed using the TCGA, ESTIMATE algorithm, and TIMER databases. Gene Set Enrichment Analysis (GSEA) was applied to elucidate the biological function of NXNL1 in pan-cancer. We evaluated the influence of NXNL1 on survival of BC patients by survival module. Then, data sets of Breast Cancer were downloaded from TCGA. The correlations between clinical information and NXNL1 expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in TCGA patients using Cox regression. In addition, we explored the correlation between NXNL1 and cancer immune infiltrates using CIBERSORT and “Correlation” module of GEPIA. Results: The differential analysis showed that the level of NXNL1 mRNA expression was upregulated in 23 tumor types compared with normal tissues, which was consistent with its protein expression in most cancer types. The abnormal expression of NXNL1 could predict the survival outcome of patients with breast cancer (BC). The expression of NXNL1 was related to the infiltration levels of various immune-associated cells in breast cancer by TIMER database mining and ESTIMATE algorithm. wherein NXNL1 expression used as the categorical dependent variable, indicated that increased NXNL1 expression is significantly correlated with ER status, PR status, and HER2 status. Moreover, univariate and multivariate analysis revealed that the up-regulated NXNL1 expression is independent prognostic factors for good prognosis. Specifically, a positive correlation between increased NXNL1 expression and immune infiltrating level of the abundance of B cells, Neutrophils, Mast cells and NK cells was established using CIBERSORT analysis. Furthermore, we confirmed it in “correlation” module of GEPIA. Conclusion: Our results suggest that NXNL1 is a potential molecular biomarker for predicting patient prognosis, and immunoreaction in Breast Cancer.