CTPC, a combined transcriptome data set of human prostate cancer cell lines

PCTA, a pan-cancer cell line transcriptome atlas

A substantial volume of RNA sequencing data have been generated from cancer cell lines. However, it requires specific bioinformatics skills to compare gene expression levels across cell lines. This has hindered non-bioinformaticians from fully utilizing these valuable datasets in their research. To bridge this gap, we established a curated Pan-cancer Cell Line Transcriptome Atlas (PCTA) dataset. This resource aims to provide a user-friendly platform, allowing researchers without extensive bioinformatics expertise to access and leverage the wealth of information within the dataset for their studies. The PCTA dataset encompasses the expression matrix of 24,965 genes, featuring data from 84,385 samples derived from 5677 studies. This comprehensive compilation spans 535 cell lines, representing a spectrum of 114 cancer types originating from 30 diverse tissue types. On UMAP plots, cell lines originating from the same type of tissue tend to cluster together, illustrating the dataset's ability to capture biological relationships. Additionally, an interactive and user-friendly web application (https://pcatools.shinyapps.io/PCTA_app/) was developed for researchers to explore the PCTA dataset. This platform allows users to examine the expression of their genes of interest across a diverse array of samples.

The expression of PKM1 and PKM2 in developing, benign, and cancerous prostatic tissues

Background

Neuroendocrine prostate cancer (NEPCa) is the most aggressive type of prostate cancer (PCa). However, energy metabolism, one of the hallmarks of cancer, in NEPCa has not been well studied. Pyruvate kinase M (PKM), which catalyzes the final step of glycolysis, has two main splicing isoforms, PKM1 and PKM2. The expression pattern of PKM1 and PKM2 in NEPCa remains unknown.

Methods

In this study, we used immunohistochemistry, immunofluorescence staining, and bioinformatics analysis to examine the expression of PKM1 and PKM2 in mouse and human prostatic tissues.

Results

We found that PKM2 was the predominant isoform expressed throughout prostate development and PCa progression, with slightly reduced expression in murine NEPCa. PKM1 was mostly expressed in stromal cells but low-level PKM1 was also detected in prostate basal epithelial cells. Its expression was absent in the majority of prostate adenocarcinoma (AdPCa) specimens but present in a subset of NEPCa. Additionally, we evaluated the mRNA levels of ten PKM isoforms that express exon 9 (PKM1-like) or exon 10 (PKM2-like). Some of these isoforms showed notable expression levels in PCa cell lines and human PCa specimens.

Discussion

Our study characterized the expression pattern of PKM1 and PKM2 in prostatic tissues including developing, benign, and cancerous prostate. These findings lay the groundwork for understanding the metabolic changes in different PCa subtypes.

PCTA, A PAN-CANCER CELL LINE TRANSCRIPTOME ATLAS

Background

A substantial volume of RNA sequencing data were generated from cancer cell lines. However, it requires specific bioinformatics skills to compare gene expression levels across cell lines. This has hindered non-bioinformaticians from fully utilizing these valuable datasets in their research. To bridge this gap, we established a curated Pan-cancer Cell Line Transcriptome Atlas (PCTA) dataset. This resource aims to provide a user-friendly platform, allowing researchers without extensive bioinformatics expertise to access and leverage the wealth of information within the dataset for their studies. Importantly, PCTA stands out by offering sufficient sample numbers per cell line in comparison to other pan-cancer datasets.

Methods

Cell lines' meta data and RNA sequencing data were retrieved from the Cancer Cell Line Encyclopedia (CCLE), SRA and ARCHS4 databases. Utilizing the programming language R, we conducted data retrieval, normalization, and visualization. Only expression data for protein-coding genes and long-non-coding RNAs (LncRNAs) were considered in this study, streamlining the focus to enhance the precision and relevance of the analysis.

Results

The resulting PCTA dataset encompasses the expression matrix of 24,965 genes, featuring data from 84,385 samples derived from 5,677 studies. This comprehensive compilation spans 535 cell lines, representing a spectrum of 114 cancer types originating from 30 diverse tissue types. On UMAP plots, cell lines originating from the same type of tissue tend to cluster together, illustrating the dataset's ability to capture biological relationships. To unravel molecular signatures, marker genes were identified for each cancer type. Additionally, an interactive and user-friendly web application (https://pcatools.shinyapps.io/PCTA_app/ ) was developed for researchers to explore the PCTA dataset. This platform allows users to examine the expression pattern of their genes of interest across a diverse array of samples. Data are visualized as violin-, box-, and point- plots, enhancing the interpretability of the findings.

Conclusion

The PCTA stands as a comprehensive resource, offering insights into gene expression patterns across diverse cancer cell lines and providing a valuable tool to explore molecular signatures and potential therapeutic targets in cancer research.

The expression of PKM1 and PKM2 in developing, benign, and cancerous prostatic tissues

Neuroendocrine prostate cancer (NEPCa) is the most aggressive type of prostate cancer. However, energy metabolism, one of the hallmarks of cancer, in NEPCa has not been well studied. Pyruvate kinase M (PKM), which catalyzes the final step of glycolysis, has two main splicing isoforms, PKM1 and PKM2. PKM2 is known to be upregulated in various cancers, including prostate adenocarcinoma (AdPCa). In this study, we used immunohistochemistry, immunofluorescence staining, and bioinformatic analysis to examine the expression of PKM1 and PKM2 in mouse and human prostatic tissues, including developing, benign and cancerous prostate. We found that PKM2 was the predominant isoform expressed throughout prostate development and PCa progression, with slightly reduced expression in some NEPCa samples. PKM1 was mostly expressed in stromal cells but low-level PKM1 was also detected in prostate basal epithelial cells. Its expression was absent in the majority of PCa specimens but present in a subset of NEPCa. Additionally, we evaluated the mRNA levels of ten PKM isoforms that express exon 9 (PKM1-like) or exon 10 (PKM2-like). Some of these isoforms showed notable expression levels in PCa cell lines and human PCa specimens. These findings lay the groundwork for understanding PKMs' role in PCa carcinogenesis and NEPCa progression. The distinct expression pattern of PKM isoforms in different PCa subtypes may offer insights into potential therapeutic strategies for treating PCa.