Since the identification of the first RNA demethylase and the establishment of methylated RNA immunoprecipitationsequencing methodology 6 to 7 years ago, RNA methylation has emerged as a widespread phenomenon and a critical regulator of transcript expression. This new layer of regulation is termed "epitranscriptomics." The most prevalent RNA methylation, N 6-methyladenosine (m 6 A), occurs in approximately 25% of transcripts at the genome-wide level and is enriched around stop codons, in 5 0-and 3 0-untranslated regions, and within long internal exons. RNA m 6 A modification regulates RNA splicing, translocation, stability, and translation into protein. m 6 A is catalyzed by the RNA methyltransferases METTL3, METTL14, and METTL16 (writers), is removed by the demethylases FTO and ALKBH5 (erasers), and interacts with m 6 A-binding proteins, such as YTHDF1 and IGF2BP1 (readers). RNA methyltransferases, demethylases, and m 6 Abinding proteins are frequently upregulated in human cancer tissues from a variety of organ origins, increasing oncotranscript and oncoprotein expression, cancer cell proliferation, survival, tumor initiation, progression, and metastasis. Although RNA methyltransferase inhibitors are not available yet, FTO inhibitors have shown promising anticancer effects in vitro and in animal models of cancer. Further screening for selective and potent RNA methyltransferase, demethylase, or m 6 A-binding protein inhibitors may lead to compounds suitable for future clinical trials in cancer patients.

The oncofetal mRNA-binding protein IGF2BP1 and the transcriptional regulator SRF modulate gene expression in cancer. In cancer cells, we demonstrate that IGF2BP1 promotes the expression of SRF in a conserved and N6-methyladenosine (m6A)-dependent manner by impairing the miRNA-directed decay of the SRF mRNA. This results in enhanced SRF-dependent transcriptional activity and promotes tumor cell growth and invasion. At the post-transcriptional level, IGF2BP1 sustains the expression of various SRF-target genes. The majority of these SRF/IGF2BP1-enhanced genes, including PDLIM7 and FOXK1, show conserved upregulation with SRF and IGF2BP1 synthesis in cancer. PDLIM7 and FOXK1 promote tumor cell growth and were reported to enhance cell invasion. Consistently, 35 SRF/IGF2BP1-dependent genes showing conserved association with SRF and IGF2BP1 expression indicate a poor overall survival probability in ovarian, liver and lung cancer. In conclusion, these findings identify the SRF/IGF2BP1-, miRNome- and m6A-dependent control of gene expression as a conserved oncogenic driver network in cancer.

The IGF2 mRNA-binding protein 1 (IGF2BP1) is a non-catalytic post-transcriptional enhancer of tumor growth upregulated and associated with adverse prognosis in solid cancers. However, conserved effector pathway(s) and the feasibility of targeting IGF2BP1 in cancer remained elusive. We reveal that IGF2BP1 is a post-transcriptional enhancer of the E2F-driven hallmark in solid cancers. IGF2BP1 promotes G1/S cell cycle transition by stabilizing mRNAs encoding positive regulators of this checkpoint like E2F1. This IGF2BP1-driven shortening of the G1 cell cycle phase relies on 3′UTR-, miRNA- and m6A-dependent regulation and suggests enhancement of cell cycle progression by m6A-modifications across cancers. In addition to E2F transcription factors, IGF2BP1 also stabilizes E2F-driven transcripts directly indicating post-transcriptional ‘super’-enhancer role of the protein in E2F-driven gene expression in cancer. The small molecule BTYNB disrupts this enhancer function by impairing IGF2BP1-RNA association. Consistently, BTYNB interferes with E2F-driven gene expression and tumor growth in experimental mouse tumor models.

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimized miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses were calibrated with Mettl3 knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.

Circular RNAs (circRNAs) encompass a widespread and conserved class of RNAs, which are generated by back-splicing of downstream 5′ to upstream 3′ splice sites. CircRNAs are tissue-specific and have been implicated in diseases including cancer. They can function as sponges for microRNAs (miRNAs) or RNA binding proteins (RBPs), for example. Moreover, some contain open reading frames (ORFs) and might be translated. The functional relevance of such peptides, however, remains largely elusive. Here, we report that the ORF of circZNF609 is efficiently translated when expressed from a circZNF609 overexpression construct. However, endogenous proteins could not be detected. Moreover, initiation of circZNF609 translation is independent of m6A-generating enzyme METTL3 or RNA sequence elements such as internal ribosome entry sites (IRESs). Surprisingly, a comprehensive mutational analysis revealed that deletion constructs, which are deficient in producing circZNF609, still generate the observed protein products. This suggests that the apparent circZNF609 translation originates from trans-splicing by-products of the overexpression plasmids and underline that circRNA overexpression constructs need to be evaluated carefully, particularly when functional studies are performed.