Polycystic ovary syndrome (PCOS) is one of the most complicated chronic inflammatory diseases in women of reproductive age and is one of the primary factors responsible for infertility. There is substantial dispute relating to the pathophysiology of PCOS. Consequently, there is a critical need for further research to identify the factors underlying the pathophysiology of PCOS. Three transcriptome profiles of granulosa cells from patients with PCOS and normal controls were obtained from the gene expression integration database. We also obtained relevant microarrays of granulocytes prepared from PCOS patients and normal controls from the gene expression integration database. Then, we used the R package to perform correlations and identify differences between PCOS and normal controls with regard to immune infiltrating cells and functionality. Subsequently, intersecting genes were identified and risk models were constructed. Finally, the results were validated by enzyme linked immunosorbent assay and real-time PCR. We identified 8 genes related to cuproptosis (SLC31A1, PDHB, PDHA1, DLST, DLD, DLAT, DBT, and ATP7A) and 5 genes related to m7G (SNUPN, NUDT16, GEMIN5, DCPS, and EIF4E3) that were associated with immune infiltration. Furthermore, the expression levels of DLAT (P = .049) and NUDT16 (P = .024) differed significantly between the PCOS patients and normal controls, as revealed by multifactorial analysis. Both DLAT and NUDT16 were negatively correlated with immune cell expression and function and expression levels were significantly lower in the PCOS group. Finally, real-time PCR and enzyme linked immunosorbent assay demonstrated that the expression levels of DLAT and NUDT16 were significantly reduced in the granulosa cells of PCOS patients. In conclusion, our findings shed fresh light on the roles of immune infiltration, cuproptosis, and m7G alternations in PCOS. We also provide a reliable biomarker for the pathological classification of PCOS patients.