High copy number variations, particular transcription factors, and low immunity contribute to the stemness of prostate cancer cells

Abstract Background Tumor metastasis is the main cause of death of cancer patients, and cancer stem cells (CSCs) is the basis of tumor metastasis. However, systematic analysis of the stemness of prostate cancer cells is still not abundant. In this study, we explore the effective factors related to the stemness of prostate cancer cells by comprehensively mining the multi-omics data from TCGA database. Methods Based on the prostate cancer transcriptome data in TCGA, gene expression modules that strongly relate to the stemness of prostate cancer cells are obtained with WGCNA and stemness scores. Copy number variation of stemness genes of prostate cancer is calculated and the difference of transcription factors between prostate cancer and normal tissues is evaluated by using CNV (copy number variation) data and ATAC-seq data. The protein interaction network of stemness genes in prostate cancer is constructed using the STRING database. Meanwhile, the correlation between stemness genes of prostate cancer and immune cells is analyzed. Results Prostate cancer with higher Gleason grade possesses higher cell stemness. The gene set highly related to prostate cancer stemness has higher CNV in prostate cancer samples than that in normal samples. Although the transcription factors of stemness genes have similar expressions, they have different contributions between normal and prostate cancer tissues; and particular transcription factors enhance the stemness of prostate cancer, such as PUM1, CLOCK, SP1, TCF12, and so on. In addition, the lower tumor immune microenvironment is conducive to the stemness of prostate cancer. CD8 + T cells and M1 macrophages may play more important role in the stemness of prostate cancer than other immune cells in the tumor microenvironment. Finally, EZH2 is found to play a central role in stemness genes and is negatively correlated with resting mast cells and positively correlated with activated memory CD4 + T cells. Conclusions Based on the systematic and combined analysis of multi-omics data, we find that high copy number variation, specific transcription factors, and low immune microenvironment jointly contribute to the stemness of prostate cancer cells. These findings may provide us new clues and directions for the future research on stemness of prostate cancer.

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High copy number variations, particular transcription factors, and low immunity contribute to the stemness of prostate cancer cells.

10.21203/rs.3.rs-100256/v2 ◽

2021 ◽

Author(s):

Zao Dai ◽

Ping Liu

Keyword(s):

Prostate Cancer ◽

Transcription Factors ◽

Copy Number Variation ◽

Cancer Cells ◽

Immune Cells ◽

Copy Number ◽

Tumor Metastasis ◽

Prostate Cancer Cells ◽

Immune Microenvironment ◽

Number Variation

Abstract Background: Tumor metastasis is the main cause of death of cancer patients, and the existence of cancer stem cells is the basis of tumor metastasis. However, the systematic analysis of the stemness of prostate cancer cells is still not abundant. This article explores the effective factors that lead to the stemness of prostate cancer cells with multi-omics data mining.Methods: Gene expression modules that were strongly related to the stemness of prostate cancer cells were obtained with WGCNA and stemness scores, based on the prostate cancer transcriptome data in TCGA. Calculated the copy number variation of stemness genes of prostate cancer and evaluated the difference of transcription factors in prostate cancer and normal tissues, based on CNV (copy number variation) data and ATAC-seq data. The protein interaction network of stemness genes of prostate cancer was constructed with the STRING database. At the same time, the correlation between stemness genes of prostate cancer and immune cells was analyzed.Results: Prostate cancer with high Gleason grade was more stemness. The gene set highly related to prostate cancer stemness had higher CNV in prostate cancer samples than normal samples. The transcription factors of stemness genes had similar expressions but had different contributions in normal and prostate cancer tissues. And particular transcription factors enhanced the stemness of prostate cancer, such as PUM1, CLOCK, SP1, TCF12, and so on. The lower tumor immune microenvironment was conducive to the stemness of prostate cancer, and CD8+ T cells and M1 macrophages might play an important role than other immune cells in the tumor microenvironment. We also found that EZH2 played a central role in stemness genes and was negatively correlated with resting mast cells and positively correlated with activated memory CD4+ T cells.Conclusions: This study found that high copy number variation, specific transcription factors, and low immune microenvironment contributed to the stemness of prostate cancer cells through systematic multi-omics analysis. These findings would provide new clues and directions for future research of prostate cancer stem cells.

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Resveratrol Induces Growth Arrest and Apoptosis through Activation of FOXO Transcription Factors in Prostate Cancer Cells

PLoS ONE ◽

10.1371/journal.pone.0015288 ◽

2010 ◽

Vol 5 (12) ◽

pp. e15288 ◽

Cited By ~ 118

Author(s):

Qinghe Chen ◽

Suthakar Ganapathy ◽

Karan P. Singh ◽

Sharmila Shankar ◽

Rakesh K. Srivastava

Keyword(s):

Prostate Cancer ◽

Transcription Factors ◽

Cancer Cells ◽

Growth Arrest ◽

Prostate Cancer Cells ◽

Foxo Transcription Factors

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Germline copy number variation analysis in Finnish families with hereditary prostate cancer

The Prostate ◽

10.1002/pros.23123 ◽

2015 ◽

Vol 76 (3) ◽

pp. 316-324 ◽

Cited By ~ 9

Author(s):

Virpi H. Laitinen ◽

Oyediran Akinrinade ◽

Tommi Rantapero ◽

Teuvo L.J. Tammela ◽

Tiina Wahlfors ◽

...

Keyword(s):

Prostate Cancer ◽

Copy Number Variation ◽

Copy Number ◽

Variation Analysis ◽

Hereditary Prostate Cancer ◽

Copy Number Variation Analysis ◽

Number Variation

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Abstract 4588: Prognostic association of plasma cell free DNA (cfDNA) copy number variation based algorithmic score with survival in metastatic castration resistant prostate cancer (mCRPC)

10.1158/1538-7445.am2018-4588 ◽

2018 ◽

Author(s):

Manish Kohli ◽

Meijun Du ◽

Liang Wang ◽

Chiang-Ching Huang

Keyword(s):

Prostate Cancer ◽

Copy Number Variation ◽

Plasma Cell ◽

Copy Number ◽

Castration Resistant Prostate Cancer ◽

Cell Free Dna ◽

Castration Resistant ◽

Free Dna ◽

Number Variation ◽

Prognostic Association

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MP66-10 CHARACTERIZATION OF SUSCEPTIBILITY LOCI IN HEREDITARY PROSTATE CANCER FAMILIES USING COPY NUMBER VARIATION AND LINKAGE ANALYSIS

The Journal of Urology ◽

10.1016/j.juro.2015.02.2363 ◽

2015 ◽

Vol 193 (4S) ◽

Author(s):

Elisa Ledet ◽

Kirsten Wood ◽

Joan Bailey-Wilson ◽

Oliver Sartor ◽

Marilyn Li ◽

...

Keyword(s):

Prostate Cancer ◽

Linkage Analysis ◽

Copy Number Variation ◽

Copy Number ◽

Susceptibility Loci ◽

Hereditary Prostate Cancer ◽

Number Variation

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Copy Number Variation of GSTT1 and GSTM1 and the Risk of Prostate Cancer in a Caribbean Population of African Descent

PLoS ONE ◽

10.1371/journal.pone.0107275 ◽

2014 ◽

Vol 9 (9) ◽

pp. e107275 ◽

Cited By ~ 13

Author(s):

Elise Emeville ◽

Cédric Broquère ◽

Laurent Brureau ◽

Séverine Ferdinand ◽

Pascal Blanchet ◽

...

Keyword(s):

Prostate Cancer ◽

Copy Number Variation ◽

Copy Number ◽

African Descent ◽

Number Variation ◽

Caribbean Population

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Comprehensive Analysis of Metabolic Genes in Breast Cancer Based on Multi-Omics Data

Pathology & Oncology Research ◽

10.3389/pore.2021.1609789 ◽

2021 ◽

Vol 27 ◽

Author(s):

Yu Hua ◽

Lihong Gao ◽

Xiaobo Li

Keyword(s):

Breast Cancer ◽

Dna Methylation ◽

Arachidonic Acid ◽

Copy Number Variation ◽

Immune Cells ◽

Copy Number ◽

Clinical Parameters ◽

Omics Data ◽

Metabolic Genes ◽

Number Variation

Background: Reprogramming of cell metabolism is one of the most important hallmarks of breast cancer. This study aimed to comprehensively analyze metabolic genes in the initiation, progression, and prognosis of breast cancer.Materials and Methods: Data from The Cancer Genome Atlas (TCGA) in breast cancer were downloaded including RNA-seq, copy number variation, mutation, and DNA methylation. A gene co-expression network was constructed by the weighted correlation network analysis (WGCNA) package in R. Association of metabolic genes with tumor-related immune cells and clinical parameters were also investigated.Results: We summarized 3,620 metabolic genes and observed mutations in 2,964 genes, of which the most frequently mutated were PIK3CA (51%), TNN (26%), and KMT2C (15%). Four genes (AKT1, ERBB2, KMT2C, and USP34) were associated with survival of breast cancer. Significant association was detected in the tumor mutation burden (TMB) of metabolic genes with T stage (p = 0.045) and N stage (p = 0.004). Copy number variations were significantly associated with recurrence and prognosis of breast cancer. The co-expression network for differentially expressed metabolic genes by WGCNA suggested that the modules were associated with glycerophospholipid, arachidonic acid, carbon, glycolysis/gluconeogenesis, and pyrimidine/purine metabolism. Glycerophospholipid metabolism correlated with most of the immune cells, while arachidonic acid metabolism demonstrated a significant correlation with endothelial cells. Methylation and miRNA jointly regulated 14 metabolic genes while mutation and methylation jointly regulated PIK3R1.Conclusion: Based on multi-omics data of somatic mutation, copy number variation, mRNA expression, miRNA expression, and DNA methylation, we identified a series of differentially expressed metabolic genes. Metabolic genes are associated with tumor-related immune cells and clinical parameters, which might be therapy targets in future clinical application.

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