Integrated analysis identifies TfR1 as a prognostic biomarker which correlates with immune infiltration in breast cancer

Abstract

Breast cancer (BC) is the most common malignancy with high morbidity and mortality in females worldwide. Emerging evidence indicates that transferrin receptor 1 (TfR1) plays vital roles in regulating cellular iron import. However, the distinct role of TfR1 in BC remains elusive. TfR1 expression was investigated using the TCGA, GEO, TIMER, UALCAN and Oncomine databases. The prognostic potential of TfR1 was evaluated by Kaplan-Meier (KM) plotter and univariate and multivariate Cox regression analyses. Moreover, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore the molecular mechanism of TfR1. The potential link between TfR1 expression and infiltrating abundances of immune cells was examined through the TIMER and CIBERSORT algorithm. The expression of TfR1 was dramatically upregulated in BC tissues. Increased TfR1 expression and decreased methylation levels of TfR1 were strongly correlated with multiple clinicopathological parameters. Elevated TfR1 expression was associated with a poor survival rate in BC patients. The nomogram model further confirmed that TfR1 could act as an independent prognostic biomarker in BC. The results of GO, KEGG and GSEA revealed that TfR1 was closely correlated with multiple signaling pathways and immune responses. Additionally, TfR1 was positively associated with the infiltration abundances of six major immune cells, including CD4+ T cells, CD8+ T cells, B cells, neutrophils, macrophages, and dendritic cells in BC. Interestingly, TfR1 influenced prognosis partially through immune infiltration. These comprehensive bioinformatics analyses suggest that TfR1 is a new independent prognostic biomarker and a potential target for immunotherapy in BC.

PODNL1 Methylation Serves as a Prognostic Biomarker and Associates with Immune Cell Infiltration and Immune Checkpoint Blockade Response in Lower-Grade Glioma

“…al, 2020) [40]. Increased immune cell infiltration levels are linked to heightened tumor aggressiveness in a range of cancers including breast cancer, kidney renal clear cell carcinoma, uveal melanoma, pancreatic cancer, and osteosarcoma [41][42][43][44][45][46][47][48]. In gliomas, including LGG, increased immune cell infiltration levels showed poor prognosis and more aggressive phenotypes [21,22,[49][50][51][52][53][54][55][56][57].…”

Decreased TMPRSS2 expression by SARS-CoV-2 predicts the poor prognosis of lung cancer patients through metabolic pathways and immune infiltration

“…In terms of nodal metastasis status, TMPRSS2 expression was also greatly decreased in N0, N1, N2 and N3 in both LUSC and LUAD (Figure 2C). TMPRSS2 expression was lower in tumors from patients in different age groups (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59)(60), 61-80 and 81-100 years) than in normal lung tissues (Supplementary Figure 2A). Moreover, TMPRSS2 expression in Asian, African-American and Caucasian was significantly decreased in LUSC patients (Supplementary Figure 2B).…”

“…The Oncomine database (http://www.oncomine.org) was used to determine TMPRSS2 expression in lung cancer tissues and adjacent corresponding normal tissues [44][45][46][47][48]. The investigation was carried out based on the following criteria: P value, <0.01; fold change, < −2.5; and gene ranking, all.…”

“…We used GEPIA2 (http://gepia2.cancer-pku.cn/#index) to examine the mRNA expression level of TMPRSS2 in lung cancer and validate the correlation between TMPRSS2 and the expression levels of candidate genes [44][45][46][47][48].…”

“…The correlations between TMPRSS2 expression and the abundance of immune cell infiltrates in lung cancer datasets were analyzed using the TIMER database (https://cistrome.shinyapps.io/timer/) [44][45][46][47][48]. Correlations between TMPRSS2 expression and various gene marker sets of tumor-infiltrating immune cells were determined through a correlation module.…”