Global analysis of RNA-binding proteins identifies a positive feedback loop between LARP1 and MYC that promotes tumorigenesis.

In addition to genomic alterations, aberrant changes in post-transcriptional regulation can modify gene function and drive cancer development. RNA-binding proteins (RBPs) are a large class of post-transcriptional regulators that have been increasingly implicated in carcinogenesis. By integrating multi-omics data, we identify LARP1 as one of the most upregulated RBPs in colorectal cancer (CRC) and demonstrate its oncogenic properties. We perform LARP1:RNA interactome profiling and unveil a previously unexplored role for LARP1 in targeting the 3'UTR of oncogenes in CRC. Notably, we identify the proto-oncogenic transcription factor MYC as a key LARP1-regulated target. Our data show that LARP1 positively modulates MYC expression by associating with its 3'UTR. In addition, antisense oligonucleotide-mediated blocking of the interaction between LARP1 and the MYC 3'UTR reduces MYC expression and in vitro CRC growth. Furthermore, a systematic analysis of LARP1:protein interactions reveals IGF2BP3 and YBX1 as LARP1-interacting proteins that also regulate MYC expression and CRC development. Finally, we demonstrate that MYC reciprocally modulates LARP1 expression by targeting its enhancer. In summary, our data reveal a critical, previously uncharacterized role of LARP1 in promoting CRC tumorigenesis, validate its direct regulation of the proto-oncogene MYC and delineate a model of the positive feedback loop between MYC and LARP1 that promotes CRC growth and development.

An isoform-resolution transcriptomic atlas of colorectal cancer from long-read single-cell sequencing.

Colorectal cancer (CRC) ranks as the second leading cause of cancer deaths globally. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor heterogeneities. However, these studies only enable gene-level quantification but neglect alterations in transcript structures arising from alternative end processing or splicing. In this study, we integrated short- and long-read scRNA-seq of CRC samples to build an isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of splicing events. Second, we characterized genes and isoforms associated with epithelial lineages and subpopulations exhibiting distinct prognoses. Among 31,935 isoforms with novel junctions, 330 were supported by The Cancer Genome Atlas RNA-seq and mass spectrometry data. Finally, we built an algorithm that integrated novel peptides derived from open reading frames of recurrent tumor-specific transcripts with mass spectrometry data and identified recurring neoepitopes that may aid the development of cancer vaccines.

MiR-138 is a potent regulator of the heterogenous MYC transcript population in cancers.

3'UTR shortening in cancer has been shown to activate oncogenes, partly through the loss of microRNA-mediated repression. This suggests that many reported microRNA-oncogene target interactions may not be present in cancer cells. One of the most well-studied oncogenes is the transcription factor MYC, which is overexpressed in more than half of all cancers. MYC overexpression is not always accompanied by underlying genetic aberrations. In this study, we demonstrate that the MYC 3'UTR is shortened in colorectal cancer (CRC). Using unbiased computational and experimental approaches, we identify and validate microRNAs that target the MYC coding region. In particular, we show that miR-138 inhibits MYC expression and suppresses tumor growth of CRC and hepatocellular carcinoma (HCC) cell lines. Critically, the intravenous administration of miR-138 significantly impedes MYC-driven tumor growth in vivo. Taken together, our results highlight the previously uncharacterized shortening of the MYC 3'UTR in cancer, and identify miR-138 as a potent regulator of the heterogenous MYC transcript population.

Automated Hypothesis Generation to Identify Signals Relevant in the Development of Mammalian Cell and Tissue Bioprocesses, With Validation in a Retinal Culture System.

We have developed an accessible software tool (receptoR) to predict potentially active signaling pathways in one or more cell type(s) of interest from publicly available transcriptome data. As proof-of-concept, we applied it to mouse photoreceptors, yielding the previously untested hypothesis that activin signaling pathways are active in these cells. Expression of the type 2 activin receptor (Acvr2a) was experimentally confirmed by both RT-qPCR and immunochemistry, and activation of this signaling pathway with recombinant activin A significantly enhanced the survival of magnetically sorted photoreceptors in culture. Taken together, we demonstrate that our approach can be easily used to mine publicly available transcriptome data and generate hypotheses around receptor expression that can be used to identify novel signaling pathways in specific cell types of interest. We anticipate that receptoR (available at https://www.ucalgary.ca/ungrinlab/receptoR) will enable more efficient use of limited research resources.