RAB11FIP1: An Indicator for Tumor Immune Microenvironment and Prognosis of Lung Adenocarcinoma from a Comprehensive Analysis of Bioinformatics

Dipeptidase‑2 is a prognostic marker in lung adenocarcinoma that is correlated with its sensitivity to cisplatin

Lung cancer accounts for the highest percentage of cancer morbidity and mortality worldwide, and lung adenocarcinoma (LUAD) is the most prevalent subtype. Although numerous therapies have been developed for lung cancer, patient prognosis is limited by tumor metastasis and more effective treatment targets are urgently required. In the present study, gene expression profiles were extracted from the Gene Expression Omnibus database and mRNA expression data were downloaded from The Cancer Genome Atlas database. In addition, TIMER 2.0 database was used to analyze the expression of genes in normal and multiple tumor tissues. Protein expression was confirmed using the Human Protein Atlas database and LUAD cell lines, sphere formation assay, western blotting, and a xenograft mouse model were used to confirm the bioinformatics analysis. Dipeptidase‑2 (DPEP2) expression was significantly decreased in LUAD and was negatively associated with prognosis. DPEP2 overexpression substantially inhibited epithelial‑mesenchymal transition (EMT) as well as LUAD cell metastasis, and limited the expression of the cancer stem cell transformation markers, CD44 and CD133. In addition, DPEP2 improved LUAD sensitivity to cisplatin by inhibiting EMT; this was verified in vitro and in vivo. These data indicated that DPEP2 upregulates E‑cadherin, thereby regulating cell migration, cancer stem cell transformation, and cisplatin resistance, ultimately affecting the survival of patients with LUAD. Overall, the findings of the present suggest that DPEP2 is important in the development of LUAD and can be used both as a prognostic marker and a target for future therapeutic research.

The Prognostic Signature of Head and Neck Squamous Cell Carcinoma Constructed by Immune-Related RNA-Binding Proteins

Purpose

This study aimed to construct a prognostic signature consisting of immune-related RNA-binding proteins (RBPs) to predict the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) effectively.

Methods

The transcriptome and clinical data of HNSCC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. First, we ascertained the immunological differences in HNSCC, through single-sample gene set enrichment analysis, stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE), and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) deconvolution algorithm. Then we used univariate proportional hazards (Cox) regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to screen immune-related RBPs and acquire the risk score of each sample. Subsequently, we further investigated the difference in prognosis, immune status, and tumor mutation burden in high- and low-risk groups. Finally, the efficacy of immunotherapy was measured by the tumor immune dysfunction and exclusion (TIDE) score.

Results

We derived 15 immune-related RBPs, including FRMD4A, ASNS, RAB11FIP1, FAM120C, CFLAR, CTTN, PLEKHO1, SELENBP1, CHCHD2, NPM3, ATP2A3, CFDP1, IGF2BP2, NQO1, and DENND2D. There were significant differences in the prognoses of patients in the high- and low-risk groups in the training set (p < 0.001) and the validation set (p < 0.01). Furthermore, there were statistical differences between the high-risk group and low-risk group in immune cell infiltration and pathway and tumor mutation load (p < 0.001). In the end, we found that patients in the low-risk group were more sensitive to immunotherapy (p < 0.001), and then we screened 14 small-molecule chemotherapeutics with higher sensitivity to the high-risk group (p < 0.001).

Conclusion

The study constructed a prognostic signature of HNSCC, which might guide clinical immunotherapy in the future.