STEAP1–4 (Six-Transmembrane Epithelial Antigen of the Prostate 1–4) and Their Clinical Implications for Prostate Cancer

Xu, Michael; Evans, Latese; Bizzaro, Candice L.; Quaglia, Fabio; Verrillo, Cecilia E.; Li, Li; Stieglmaier, Julia; Schiewer, Matthew J.; Languino, Lucia R.; Kelly, William Kevin

doi:10.3390/cancers14164034

Cited by 23 publications

(20 citation statements)

References 77 publications

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“…For instance, STEAP1 is all-called six-transmembrane epithelial antigen of the prostate 1, which belongs to a family of metalloproteinases involved in iron and copper homeostasis and other cellular processes 37 . STEAP1 is overexpressed on the plasma membrane of PCa cells and is associated with PCa invasiveness and metastasis 50 . The possible mechanism of STEAP1 promoting tumor proliferation and metastasis is by acting as a channel for small molecules that are involved in intercellular communication 50 , 51 .…”

Section: Discussionmentioning

confidence: 99%

“…STEAP1 is overexpressed on the plasma membrane of PCa cells and is associated with PCa invasiveness and metastasis 50 . The possible mechanism of STEAP1 promoting tumor proliferation and metastasis is by acting as a channel for small molecules that are involved in intercellular communication 50 , 51 . Similarly,OR51E2 is a kind of olfactory receptor, which is also called prostate specific G-protein receptor 2, and is highly expressed in PCa 52 .…”

Section: Discussionmentioning

confidence: 99%

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Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Qian

Wang

Wei

et al. 2023

Sci Rep

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Current evidence indicate that cancer-associated fibroblasts (CAFs) play an important role in prostate cancer (PCa) development and progression. In this study, we identified CAF-related molecular subtypes and prognostic index for PCa patients undergoing radical prostatectomy through integrating single-cell and bulk RNA sequencing data. We completed analyses using software R 3.6.3 and its suitable packages. Through single-cell and bulk RNA sequencing analysis, NDRG2, TSPAN1, PTN, APOE, OR51E2, P4HB, STEAP1 and ABCC4 were used to construct molecular subtypes and CAF-related gene prognostic index (CRGPI). These genes could clearly divide the PCa patients into two subtypes in TCGA database and the BCR risk of subtype 1 was 13.27 times higher than that of subtype 2 with statistical significance. Similar results were observed in MSKCC2010 and GSE46602 cohorts. In addtion, the molucular subtypes were the independent risk factor of PCa patients. We orchestrated CRGPI based on the above genes and divided 430 PCa patients in TCGA database into high- and low- risk groups according to the median value of this score. We found that high-risk group had significant higher risk of BCR than low-risk group (HR: 5.45). For functional analysis, protein secretion was highly enriched in subtype 2 while snare interactions in vesicular transport was highly enriched in subtype 1. In terms of tumor heterogeneity and stemness, subtype 1 showd higher levels of TMB than subtype 2. In addition, subtype 1 had significant higher activated dendritic cell score than subtype 2. Based on eight CAF-related genes, we developed two prognostic subtypes and constructed a gene prognostic index, which could predict the prognosis of PCa patients very well.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Qian

Wang

Wei

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…STEAP1 is a member of metalloproteinases family that may participate in iron and copper homeostasis and other cellular processes such as cell proliferation and apoptosis ( Xu et al, 2022 ). The C-terminal domain of STEAP1 is homologous to the Saccharomyces cerevisiae ferric reductase.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatic analysis and machine learning to identify the diagnostic biomarkers and immune infiltration in adenomyosis

2023

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Background: Adenomyosis is a hormone-dependent benign gynecological disease characterized by the invasion of the endometrium into the myometrium. Women with adenomyosis can suffer from abnormal uterine bleeding, severe pelvic pain, and subfertility or infertility, which can interfere with their quality of life. However, effective diagnostic biomarkers for adenomyosis are currently lacking. The aim of this study is to explore the mechanism of adenomyosis by identifying biomarkers and potential therapeutic targets for adenomyosis and analyzing their correlation with immune infiltration in adenomyosis.Methods: Two datasets, GSE78851 and GSE68870, were downloaded and merged for differential expression analysis and functional enrichment analysis using R software. Weighted gene co-expression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and support vector machine-recursive feature elimination (SVE-RFE) were combined to explore candidate genes. Quantitative reverse transcriptase PCR (qRT-PCR) was conducted to verify the biomarkers and receiver operating characteristic curve analysis was used to assess the diagnostic value of each biomarker. Single-sample Gene Set Enrichment Analysis (ssGSEA) and CIBERSORT were used to explore immune cell infiltration in adenomyosis and the correlation between diagnostic biomarkers and immune cells.Results: A total of 318 genes were differentially expressed. Through the analysis of differentially expressed genes and WGCNA, we obtained 189 adenomyosis-related genes. After utilizing the LASSO and SVM-RFE algorithms, four hub genes, namely, six-transmembrane epithelial antigen of the prostate-1 (STEAP1), translocase of outer mitochondrial membrane 20 (TOMM20), glycosyltransferase eight domain-containing 2 (GLT8D2), and NME/NM23 family member 5 (NME5) expressed in nucleoside-diphosphate kinase, were identified and verified by qRT-PCR. Immune infiltration analysis indicated that T helper 17 cells, CD56dim natural killer cells, monocytes, and memory B-cell may be associated with the occurrence of adenomyosis. There were significant correlations between the diagnostic biomarkers and immune cells.Conclusion: STEAP1, TOMM20, GLT8D2, and NME5 were identified as potential biomarkers and therapeutic targets for adenomyosis. Immune infiltration may contribute to the onset and progression of adenomyosis.

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“…STEAP1, together with STEAP2-4, is part of the six-transmembrane epithelial antigen of prostate (STEAP) family of proteins [115]. The STEAP1 protein is overexpressed in several human cancers, including prostate, bladder, colon ovary, breast, and cervical cancer [116].…”

Section: Steap1mentioning

confidence: 99%

Combined Therapies with Taxanes Based-Chemotherapeutic Drugs in Prostate Cancer: Novel Insights and Future Directions

Coelho¹,

Rocha²,

Maia³

2023

Preprint

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The oncologic disease is a big global health issue that causes thousands of deaths annually, and it has a significant impact in the life quality of patients. Prostate cancer (PCa) is the second most diagnosed cancer and the fourth leading cause of cancer-related death in men in the western world. Delineation of pathogenetic pathways and key driver molecular alterations involved in PCa development has provided a roadmap for the evaluation of biomarkers in predicting disease outcome and to identify potential therapeutic targets. Chemotherapeutic agents introduced from the 1990s include the taxanes (paclitaxel, docetaxel and cabazitaxel), which are the most anticancer drugs used for PCa treatment. This review presents the current knowledge about the onset and development of PCa, state-of-art on the use of taxane-based therapy, and their combination with targeting different transmembrane oncoproteins in PCa. The silencing of some transmembrane proteins can improve taxane sensitivity, and therefore, may be a mechanism to improve the ef-fectiveness of these drugs in PCa treatment. This combined therapy needs to be explored as po-tential therapeutic agent for reducing cell proliferation, migration, and invasiveness in PCa.

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STEAP1–4 (Six-Transmembrane Epithelial Antigen of the Prostate 1–4) and Their Clinical Implications for Prostate Cancer

Cited by 23 publications

References 77 publications

Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Bioinformatic analysis and machine learning to identify the diagnostic biomarkers and immune infiltration in adenomyosis

Combined Therapies with Taxanes Based-Chemotherapeutic Drugs in Prostate Cancer: Novel Insights and Future Directions

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