构建 PANoptosis 相关 lncRNA 预后模型及肺腺癌免疫治疗敏感性分析

Lung cancer is the cancer with the highest mortality rate worldwide. PANoptosis is characterized by inflammatory lytic cell death facilitated by caspases and RIPKs. We determined the construction of PANoptosis-related lncRNA, constructed a prognosis-related model, and further screened potential therapeutic drugs.

The TCGA database was used to obtain the RNA-seq-based transcriptome profiling data, clinical information, and mutation data. We used multivariable Cox regression analysis to obtain PANoptosis-related lncRNAs. We then used the training group to build the prognostic model and used the testing group to verify the accuracy of the model. Calibration curves showed the difference between the predicted and observed outcomes. PCA analysis was used to explore the distribution of LUAD patients with high- and low-risk groups. The GO and GSEA enrichment analyses were performed. Immune cell infiltration and TMB analysis were performed using CIBERSORT and maftools algorithm. The TIDE algorithm was used to predict immunotherapy sensitivity and further predicted anti-tumor immune drugs. qPCR was used for experimental verification.

We identified 163 PANoptosis-related lncRNAs and identified 6 lncRNAs as independent prognostic factors. The PFS and OS of the low-risk group were significantly higher than those of the high-risk group. The risk signature is a prognostic factor, independent of other factors. Different stages (stages I-II and III-IV) could well predict the survival rate of LUAD patients and these lncRNAs can reliably stratify patient prognosis. GSEA analysis showed that chromosome segregation and activation of immune response were significantly enriched in the high- and low-risk groups. The high-risk group showed a lower fraction of T cells CD4 memory resting and a higher proportion of NK cells resting. The OS of the low TMB group was significantly lower than the high TMB group. Furthermore, the drug sensitivity of the high-risk group is significantly higher than the low-risk group. And the high-risk lncRNAs may serve as therapeutic targets.

In summary, the 6 PANoptosis-related lncRNAs can well predict the prognosis of LUAD patients, which may provide new insight for survival prediction and clinical immunotherapy of LUAD patients.