Comparative Gene-Expression Profiling of CD133
            <sup>+</sup>
            and CD133
            <sup>-</sup>
            D10 Melanoma Cells

Roudi, Raheleh; Ebrahimi, Marzieh; Sabet, Mehrdad Nasrollahzadeh; Najafi, Ali; Nourani, Mohamad Reza; Fomeshi, Motahareh Rajabi; Samadikuchaksaraei, Alí; Shariftabrizi, Ahmad; Madjd, Zahra

doi:10.2217/fon.15.174

Cited by 10 publications

(7 citation statements)

References 32 publications

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“…Roudi et al evaluated the genomic expression profile of D10 melanoma cells. In CD133 (+) D10 cells, many genes related to tumor aggressiveness were upregulated, including some of the genes in this study (Roudi et al, 2015). Our results suggest that CXCL10 may play a protective factor in lowering the risk of SKCM and trying to improve prognosis, while RXRG, SCG2 was affiliated with a poor prognosis in SKCM, a trying to find in line with previous reports of similar research, with resulting methods to be investigated further.…”

Section: Discussionsupporting

confidence: 89%

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Shen¹,

Shang²,

Han³

et al. 2023

Front. Genet.

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Skin cutaneous melanoma (SKCM) is the skin cancer that causes the highest number of deaths worldwide. There is growing evidence that the tumour immune microenvironment is associated with cancer prognosis, however, there is little research on the role of immune status in melanoma prognosis. In this study, data on patients with Skin cutaneous melanoma were downloaded from the GEO, TCGA, and GTEx databases. Genes associated with the immune pathway were screened from published papers and lncRNAs associated with them were identified. We performed immune microenvironment and functional enrichment analyses. The analysis was followed by applying univariate/multivariate Cox regression algorithms to finally identify three lncRNAs associated with the immune pathway for the construction of prognostic prediction models (CXCL10, RXRG, and SCG2). This stepwise downscaling method, which finally screens out prognostic factors and key genes and then uses them to build a risk model, has excellent predictive power. According to analyses of the model’s reliability, it was able to differentiate the prognostic value and continued existence of Skin cutaneous melanoma patient populations more effectively. This study is an analysis of the immune pathway that leads lncRNAs in Skin cutaneous melanoma in an effort to open up new treatment avenues for Skin cutaneous melanoma.

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Section: Discussionsupporting

confidence: 89%

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Shen¹,

Shang²,

Han³

et al. 2023

Front. Genet.

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“…It seems to be related to pathways of tumor progression and aggressiveness (epithelial-tomesenchymal transition, EMT; Wnt signaling pathway) [33] and, as such, it has been associated with CSCs in different tumors [34]. However, conflicting results have been reported regarding its role in defining the CSC population in melanoma tumors [21,35,36].…”

Section: Surface Markersmentioning

confidence: 99%

Cellular and molecular biology of cancer stem cells in melanoma: Possible therapeutic implications

Marzagalli

Raimondi

Fontana

et al. 2019

Seminars in Cancer Biology

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“…Among the surface markers commonly used to identify melanoma stem cells are CD133, CD271, ABCB5, and ALDH1A [ 151 ]. CD133 has been associated with CSCs in different tumors including melanoma [ 151 , 152 ]. A previous study indicated that CD133 + CSCs isolated from the metastatic melanoma cell line D10 significantly induced and accelerated initial angiogenesis compared to CD133 − cells [ 117 ].…”

Section: Characterization Of Oral Non-scc Cancer Stem Cellsmentioning

confidence: 99%

Oral Cancer Stem Cells: Therapeutic Implications and Challenges

Shahoumi

2021

Front. Oral. Health

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Head and neck squamous cell carcinoma (HNSCC) is currently one of the 10 most common malignancies worldwide, characterized by a biologically highly diverse group of tumors with non-specific biomarkers and poor prognosis. The incidence rate of HNSCC varies widely throughout the world, with an evident prevalence in developing countries such as those in Southeast Asia and Southern Africa. Tumor relapse and metastasis following traditional treatment remain major clinical problems in oral cancer management. Current evidence suggests that therapeutic resistance and metastasis of cancer are mainly driven by a unique subpopulation of tumor cells, termed cancer stem cells (CSCs), or cancer-initiating cells (CICs), which are characterized by their capacity for self-renewal, maintenance of stemness and increased tumorigenicity. Thus, more understanding of the molecular mechanisms of CSCs and their behavior may help in developing effective therapeutic interventions that inhibit tumor growth and progression. This review provides an overview of the main signaling cascades in CSCs that drive tumor repropagation and metastasis in oral cancer, with a focus on squamous cell carcinoma. Other oral non-SCC tumors, including melanoma and malignant salivary gland tumors, will also be considered. In addition, this review discusses some of the CSC-targeted therapeutic strategies that have been employed to combat disease progression, and the challenges of targeting CSCs, with the aim of improving the clinical outcomes for patients with oral malignancies. Targeting of CSCs in head and neck cancer (HNC) represents a promising approach to improve disease outcome. Some CSC-targeted therapies have already been proven to be successful in pre-clinical studies and they are now being tested in clinical trials, mainly in combination with conventional treatment regimens. However, some studies revealed that CSCs may not be the only players that control disease relapse and progression of HNC. Further, clinical research studying a combination of therapies targeted against head and neck CSCs may provide significant advances.

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Comparative Gene-Expression Profiling of CD133 ⁺ and CD133 ^- D10 Melanoma Cells

Abstract: We conclude that many genes involved in drug resistance and tumor aggressiveness are upregulated in CD133(+) D10 cells and targeting them might be an efficient strategy for treatment of melanoma.

Cited by 10 publications

References 32 publications

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Cellular and molecular biology of cancer stem cells in melanoma: Possible therapeutic implications

Oral Cancer Stem Cells: Therapeutic Implications and Challenges

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Comparative Gene-Expression Profiling of CD133 + and CD133 - D10 Melanoma Cells

Abstract: We conclude that many genes involved in drug resistance and tumor aggressiveness are upregulated in CD133(+) D10 cells and targeting them might be an efficient strategy for treatment of melanoma.

Cited by 10 publications

References 32 publications

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Cellular and molecular biology of cancer stem cells in melanoma: Possible therapeutic implications

Oral Cancer Stem Cells: Therapeutic Implications and Challenges

Contact Info

Product

Resources

About

Comparative Gene-Expression Profiling of CD133 ⁺ and CD133 ^- D10 Melanoma Cells