Non-small cell lung cancer (NSCLC) patients face challenges such as recurrence or resistance to treatment. Multiple studies have demonstrated the importance of SLC7A11 and ferroptosis in NSCLC, but the specific mechanisms still require further investigation. Thus this study aimed to explore SLC7A11 and ferroptosis related prognostic genes and their mechanisms in NSCLC. Differentially expressed genes1 (DEGs1) between NSCLC and control groups, and DEGs2 based on high and low SLC7A11 expression groups were intersected with ferroptosis related genes (FRGs) to produce candidate genes. Prognostic genes were then finalized through multiple regression analyses. Subsequently, the prognostic model and nomogram model were constructed and evaluated, followed by functional enrichment, immune microenvironment and molecular regulatory network analyses. The relationships between key cells, prognostic genes, SLC7A11, and NSCLC were then analyzed at the single-cell level. Ultimately, prognostic genes’ expression was determined using reverse transcription quantitative PCR (RT-qPCR). Through regression analyses, 5 prognostic genes (SLC2A1, TRIB3, HNF4A, NOS2, and FLT3) were identified. The prognostic model was subsequently validated in the validation set: survival differences were observed to be significant between risk groups (p 0.6). The nomogram model was also evaluated and showed good disease prediction performance. mTORC1 signaling and glycolysis were found to be associated with NSCLC, and there were 14 different immune cells between 2 risk groups (p < 0.05). Additionally, macrophages were determined as key cells. The expression of SLC2A1, FLT3, and SLC7A11 was found to vary during macrophage differentiation. The RT-qPCR results confirmed that HNF4A and FLT3 was significantly downregulated in the NSCLC group, while SLC2A1 and TRIB3 were significantly upregulated, but there was no significant difference in NOS2. This study identified 5 prognostic genes (SLC2A1, TRIB3, HNF4A, NOS2, and FLT3) that might play significant roles in NSCLC, providing valuable insights for prognostic evaluation and mechanism exploration.
Diao et al. (Thu,) studied this question.