Identification of prognostic genes in adrenocortical carcinoma microenvironment based on bioinformatic methods

Abstract

Background:To identify prognostic genes which were associated with adrenocortical carcinoma (ACC) tumor microenvironment (TME). Methods and materials: Transcriptome profiles and clinical data of ACC samples were collected from The Cancer Genome Atlas (TCGA) database. We use ESTIMATE (estimation of stromal and Immune cells in malignant tumor tissues using expression data) algorithm to calculate immune scores, stromal scores and estimate scores.Heatmap and volcano plots were applied for differential analysis. Venn plots were used for intersect genes selection. We used protein-protein interaction (PPI) networks and functional analysis to explore underlying pathways. After performing stepwise regression method and multivariate Cox analysis, we finally screened hub genes associated with ACC TME. We calculated risk scores (RS) for ACC cases based on multivariate Cox results and evaluated the prognostic value of RS shown by receiver operating characteristic curve (ROC). We investigated the association between hub genes with immune infiltrates supported by algorithm from online TIMER database. Results: Gene expression profiles and clinical data were downloaded from TCGA.Lower immune scores were observed in disease with distant metastasis (DM) and locoregional recurrence (LR) than other cases (P = .0204). Kaplan-Meier analysis revealed that lower immune scores were significantly associated with poor overall survival (OS) (P = .0495). We screened 1649 differentially expressed genes (DEGs) and 1521 DEGs based on immune scores and stromal scores, respectively. Venn plots helped us find 1122 intersect genes. After analysing by cytoHubba from Cytoscape software, 18 hub genes were found. We calculated RS and ROC showed significantly predictive accuracy (area under curve (AUC) = 0.887). ACC patients with higher 1162 | LI et aL.

Transcriptional characterization of conjunctival melanoma identifies the cellular tumor microenvironment and prognostic gene signatures

“…Taken together, our results suggest that the enriched immune cells might play a crucial role in the development of CM and thus may represent potential therapeutic targets for a specific anti-tumor immune response. Additionally, the present study revealed that CM with systemic metastases had significantly lower immune scores than non-metastatic tumors, a finding that has previously been reported for different cancer types 27,28 . In a study of Mlecnik et al 27 , a low immune score was associated with an increased risk of systematic metastases in patients with colorectal cancer.…”

Adjuvant Therapy in Adrenocortical Carcinoma: Reflections and Future Directions

“…Initial data have been in favor of its use [71][72][73]; however, this tool is not prospectively validated, which limits its use in clinical practice. Based on the data we have regarding genetic markers in patients with ACC [41][42][43]74], using genetic profiling to predict recurrence risk is another important tool. It has been used successfully as a prognostic marker in other malignancies, including breast cancer [75]; however, studies are needed to prospectively validate its use for ACC.…”

Comparative performances of nomograms and conditional survival after resection of adrenocortical cancer

“…To provide more precise prediction of individualized outcomes, future survival estimates have to be based on a better understanding of the biology of ACC. Pangenomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) can provide discriminant prognostic models for localized ACC 31 , 32 , and genes associated with prognosis in the ACC tumour microenvironment are also valuable 33 . Such techniques are unlikely to become part of routine clinical practice soon and, until the results of such genomic tests can be integrated in this way, risk stratification based on easily accessible parameters remains paramount.…”