Abstract 4599: Sequential monitoring of single-cell copy number variation in metastatic prostate cancer.

Abstract Background The highly intra-tumoral heterogeneity and complex cell origination of prostate cancer greatly limits the utility of traditional bulk RNA sequencing in finding better biomarker for disease diagnosis and stratification. Tissue specimens based single-cell RNA sequencing holds great promise for identification of novel biomarkers. However, this technique has yet been used in the study of prostate cancer heterogeneity. Methods Cell types and the corresponding marker genes were identified by single-cell RNA sequencing. Malignant states of different clusters were evaluated by copy number variation analysis and differentially expressed genes of pseudo-bulks sequencing. Diagnosis and stratification of prostate cancer was estimated by receiver operating characteristic curves of marker genes. Expression characteristics of marker genes were verified by immunostaining. Results Fifteen cell groups including three luminal clusters with different expression profiles were identified in prostate cancer tissues. The luminal cluster with the highest copy number variation level and marker genes enriched in prostate cancer-related metabolic processes was considered the malignant cluster. This cluster contained a distinct subgroup with high expression level of prostate cancer biomarkers and a strong distinguishing ability of normal and cancerous prostates across different pathology grading. In addition, we identified another marker gene, Hepsin (HPN), with a 0.930 area under the curve score distinguishing normal tissue from prostate cancer lesion. This finding was further validated by immunostaining of HPN in prostate cancer tissue array. Conclusion Our findings provide a valuable resource for interpreting tumor heterogeneity in prostate cancer, and a novel candidate marker for prostate cancer management.

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

Journal of Translational Medicine ◽

10.1186/s12967-021-02870-x ◽

2021 ◽

Vol 19 (1) ◽

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 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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EPCO-28. SINGLE-CELL RNA SEQUENCING IDENTIFIES INTRATUMORAL HETEROGENEITY AND ACTIVATION OF PRO-INVASIVE PATHWAYS IN NON-FUNCTIONING PITUITARY ADENOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.027 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi8-vi8

Author(s):

Saket Jain ◽

Elaina Wang ◽

Husam Babikir ◽

Karin Shamardani ◽

Aaron Diaz ◽

...

Keyword(s):

Copy Number Variation ◽

Wnt Signaling ◽

Single Cell ◽

Rna Sequencing ◽

Pituitary Adenomas ◽

Copy Number ◽

Variation Analysis ◽

Copy Number Variation Analysis ◽

Single Cell Rna Sequencing ◽

Number Variation

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise 15% of brain neoplasms. Most PAs are histologically benign but can cause significant morbidity. The genetic profile of PAs is poorly understood. We used single-cell RNA sequencing using the 10X genomic platform to investigate cellular heterogeneity in twelve non-functioning pituitary adenoma samples from nine patients including site-specific (core vs edge) samples from three patients. Our analysis identified discrete clusters of cells associated with activation of specific functional pathways including lipid metabolism, angiogenic, and antigen presentation and processing pathways regardless of location within the tumor. MALT1, a lncRNA associated with increased proliferation and metastasis was ubiquitously expressed amongst these samples. Analysis of the core vs edge samples showed two specific clusters with activated invasion-promoting pathways including PI3k/AKT signaling, Wnt signaling (Wnt6 and FZD4), and epithelial-mesenchymal transition (TGFB1, SMAD1, ZEB1, and SNAI2) in the edge of the tumors. The activated Wnt signaling cascade drove a proinflammatory tumor microenvironment induced by the expression of IL-1, IL-17, and Toll-like receptors (TLR6 and TLR7/8) resulting in suppression of Tregs. Copy number variation analysis using the CONICS-CNV algorithm highlighted distinct chromosomal alterations within our samples that led to insight into clonal variations within each tumor with loss of chromosome 2 an early event in tumorigenesis and gain/loss of chromosome 19 as late events. Mapping the copy number variation analysis with the somatic variant analysis using the Vartrix algorithm identified novel driver mutations within these tumors. These findings help define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized for better management of these tumors.

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