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Following the concept of RNA dependence and exploiting its application in the R-DeeP screening approach, we have identified RNA-dependent proteins in A549 lung adenocarcinoma cells. RNA-dependent proteins are defined as proteins whose interactome depends on RNA and thus entails RNA-binding proteins (RBPs) as well as proteins in ribonucleoprotein complexes (RNPs) without direct RNA interaction. With this proteome-wide technique based on sucrose density gradient ultracentrifugation and fractionation followed by quantitative mass spectrometry and bioinformatic analysis, we have identified 1189 RNA-dependent proteins including 170 proteins which had never been linked to RNA before. R-DeeP provides quantitative information on the fraction of a protein being RNA-dependent as well as it allows the reconstruction of protein complexes based on co-segregation. The RNA dependence of three newly identified RNA-dependent proteins, DOCK5, ELMO2, also known as CED12A, and ABRAXAS1, also known as CCDC98, was validated using western blot analysis, and the direct RNA interaction was verified by iCLIP2 for the migration-related protein DOCK5 and the mitosis-related protein ABRAXAS1. The R-DeeP 2.0 database provides proteome-wide and cell line-specific information from A549 and HeLa S3 cells on proteins and their RNA dependence to contribute to understanding the functional role of RNA and RNA-binding proteins in cancer cells.

Circular RNAs (circRNAs) play critical roles in a broad spectrum of physiological and pathological processes, including cancer. Here, we provide a comprehensive database&mdash, circ2GO&mdash, systematically linking circRNAs to the functions and processes of their linear counterparts. circ2GO contains 148,811 circular human RNAs originating from 12,251 genes, which we derived from deep transcriptomics after rRNA depletion in a panel of 60 lung cancer and non-transformed cell lines. The broad circRNA expression dataset is mapped to all isoforms of the respective gene. The data are visualized in transcript maps and in heatmaps, to intuitively display a comprehensive portrait for the abundance of circRNAs across transcripts and cell lines. By integrating gene ontology (GO) information for all genes in our dataset, circ2GO builds a connection between circRNAs and their host genes&rsquo, biological functions and molecular mechanisms. Additionally, circ2GO offers target predictions for circRNA&mdash, microRNA (miRNA) pairs for 25,166 highly abundant circRNAs from 6578 genes and 897 high-confidence human miRNAs. Visualization, user-friendliness, intuitive and advanced forward and reverse search options, batch processing and download options make circ2GO a comprehensive source for circRNA information to build hypotheses on their function, processes, and miRNA targets.

The ability of cancer cells to adopt various migration modes (the plasticity of cancer cell invasiveness) is a substantive obstacle in the treatment of metastasis, yet still an incompletely understood process. We performed a comparison of publicly available transcriptomic datasets from various cell types undergoing a switch between the mesenchymal and amoeboid migration modes. Strikingly, lncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) was one of three genes that were found upregulated in all amoeboid cells analyzed. Accordingly, downregulation of MALAT1 in predominantly amoeboid cell lines A375m2 and A2058 resulted in decrease of active RhoA (Ras homolog family member A) and was accompanied by the amoeboid-mesenchymal transition in A375m2 cells. Moreover, MALAT1 downregulation in amoeboid cells led to increased cell proliferation. Our work is the first to address the role of MALAT1 in MAT/AMT (mesenchymal to amoeboid transition/amoeboid to mesenchymal transition) and suggests that increased MALAT1 expression is a common feature of amoeboid cells.

The class of circular RNA (circRNA) is characterized by head-to-tail bonds between exons formed by backsplicing. Here, we provide a resource of circRNA expression in a comprehensive panel of 60 lung cancer and non-transformed cell lines (FL3C dataset). RNA sequencing after depletion of ribosomal RNA quantified the expression of circRNA and linear RNA. We detected 148,811 circular RNAs quantified by 2.8 million backsplicing reads originating from 12,251 genes. The number of identified circRNAs was markedly higher using rRNA depletion compared to public polyA-enriched RNA-seq datasets. CircRNAs almost never started in the first exon nor ended in the last exon and started more frequently in earlier exons. Most circRNAs showed high cell line specificity and correlated positively with their linear RNA counterpart. Known cancer genes produced more circRNAs than non-cancer genes. Subsets of circRNAs correlated with cell proliferation, histological subtype or genotype. CircTNFRSF21 was translated crossing the backsplice site in two different reading frames. Overexpression of circPVT1, circERBB2, circHIPK3, circCCNB1, circSMAD2, circTNFRSF21 and circKIF5B significantly increased colony formation. In conclusion, our data provide a comprehensive map of circRNA expression in lung cancer cells and global patterns of circRNA production as a useful resource for future research into lung cancer circRNAs.