A comprehensive framework for analysis of microRNA sequencing data in metastatic colorectal cancer

ABSTRACT Although microRNAs (miRNAs) contribute to all hallmarks of cancer, miRNA dysregulation in metastasis remains poorly understood. The aim of this work was to reliably identify miRNAs associated with metastatic progression of colorectal cancer (CRC) using novel and previously published next-generation sequencing (NGS) datasets generated from 268 samples of primary (pCRC) and metastatic CRC (mCRC; liver, lung and peritoneal metastases) and tumor adjacent tissues. Differential expression analysis was performed using a meticulous bioinformatics pipeline, including only bona fide miRNAs, and utilizing miRNA-tailored quality control and processing. Five miRNAs were identified as up-regulated at multiple metastatic sites Mir-210_3p, Mir-191_5p, Mir-8-P1b_3p [mir-141–3p], Mir-1307_5p and Mir-155_5p. Several have previously been implicated in metastasis through involvement in epithelial-to-mesenchymal transition and hypoxia, while other identified miRNAs represent novel findings. The use of a publicly available pipeline facilitates reproducibility and allows new datasets to be added as they become available. The set of miRNAs identified here provides a reliable starting-point for further research into the role of miRNAs in metastatic progression.

High-grade ovarian cancer associated H/ACA snoRNAs promote cancer cell proliferation and survival

ABSTRACT Small nucleolar RNAs (snoRNAs) are an omnipresent class of non-coding RNAs involved in the modification and processing of ribosomal RNA (rRNA). As snoRNAs are required for ribosome production, the increase of which is a hallmark of cancer development, their expression would be expected to increase in proliferating cancer cells. However, assessing the nature and extent of snoRNAs’ contribution to cancer biology has been largely limited by difficulties in detecting highly structured RNA. In this study, we used a dedicated midsize non-coding RNA (mncRNA) sensitive sequencing technique to accurately survey the snoRNA abundance in independently verified high-grade serous ovarian carcinoma (HGSC) and serous borderline tumour (SBT) tissues. The results identified SNORA81, SNORA19 and SNORA56 as an H/ACA snoRNA signature capable of discriminating between independent sets of HGSC, SBT and normal tissues. The expression of the signature SNORA81 correlates with the level of ribosomal RNA (rRNA) modification and its knockdown inhibits 28S rRNA pseudouridylation and accumulation leading to reduced cell proliferation and migration. Together our data indicate that specific subsets of H/ACA snoRNAs may promote tumour aggressiveness by inducing rRNA modification and synthesis.

Comprehensive profiling of mRNA splicing indicates that GC content signals altered cassette exon inclusion in Ewing sarcoma

ABSTRACT Ewing sarcoma (EwS) is a small round blue cell tumor and is the second most frequent pediatric bone cancer. 85% of EwS tumors express the fusion oncoprotein EWS-FLI1, the product of a t(11;22) reciprocal translocation. Prior work has indicated that transcription regulation alone does not fully describe the oncogenic capacity of EWS-FLI1, nor does it provide an effective means to stratify patient tumors. Research using EwS cell lines and patient samples has suggested that EWS-FLI1 also disrupts mRNA biogenesis. In this work we both describe the underlying characteristics of mRNA that are aberrantly spliced in EwS tumor samples as well as catalogue mRNA splicing events across other pediatric tumor types. Here, we also use short- and long-read sequencing to identify cis-factors that contribute to splicing profiles we observe in Ewing sarcoma. Our analysis suggests that GC content upstream of cassette exons is a defining factor of mRNA splicing in EwS. We also describe specific splicing events that discriminate EwS tumor samples from the assumed cell of origin, human mesenchymal stem cells derived from bone marrow (hMSC-BM). Finally, we identify specific splicing factors PCBP2, RBMX, and SRSF9 by motif enrichment and confirm findings from tumor samples in EwS cell lines.

Quantification of radiation-induced DNA double strand break repair foci to evaluate and predict biological responses to ionizing radiation

Radiation-induced foci (RIF) are nuclear puncta visualized by immunostaining of proteins that regulate DNA double-strand break (DSB) repair after exposure to ionizing radiation. RIF are a standard metric for measuring DSB formation and repair in clinical, environmental and space radiobiology. The time course and dose dependence of their formation has great potential to predict in vivo responses to ionizing radiation, predisposition to cancer and probability of adverse reactions to radiotherapy. However, increasing complexity of experimentally and therapeutically setups (charged particle, FLASH …) is associated with several confounding factors that must be taken into account when interpreting RIF values. In this review, we discuss the spatiotemporal characteristics of RIF development after irradiation, addressing the common confounding factors, including cell proliferation and foci merging. We also describe the relevant endpoints and mathematical models that enable accurate biological interpretation of RIF formation and resolution. Finally, we discuss the use of RIF as a biomarker for quantification and prediction of in vivo radiation responses, including important caveats relating to the choice of the biological endpoint and the detection method. This review intends to help scientific community design radiobiology experiments using RIF as a key metric and to provide suggestions for their biological interpretation.

Characterization of the consensus mucosal microbiome of colorectal cancer

Dysbioisis is an imbalance of an organ's microbiome and plays a role in colorectal cancer pathogenesis. Characterizing the bacteria in the microenvironment of a cancer through genome sequencing has advantages compared to culture-based profiling. However, there are notable technical and analytical challenges in characterizing universal features of tumor microbiomes. Colorectal tumors demonstrate microbiome variation among different studies and across individual patients. To address these issues, we conducted a computational study to determine a consensus microbiome for colorectal cancer, analyzing 924 tumors from eight independent RNA-Seq data sets. A standardized meta-transcriptomic analysis pipeline was established with quality control metrics. Microbiome profiles across different cohorts were compared and recurrently altered microbial shifts specific to colorectal cancer were determined. We identified cancer-specific set of 114 microbial species associated with tumors that were found among all investigated studies. Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were among the four most abundant phyla for the colorectal cancer microbiome. Member species of Clostridia were depleted and Fusobacterium nucleatum was one of the most enriched bacterial species in tumors. Associations between the consensus species and specific immune cell types were noted. Our results are available as a web data resource for other researchers to explore (https://crc-microbiome.stanford.edu).

Misregulation of the expression and activity of DNA methyltransferases in cancer

In mammals, DNA methyltransferases DNMT1 and DNMT3’s (A, B and L) deposit and maintain DNA methylation in dividing and nondividing cells. Although these enzymes have an unremarkable DNA sequence specificity (CpG), their regional specificity is regulated by interactions with various protein factors, chromatin modifiers, and post-translational modifications of histones. Changes in the DNMT expression or interacting partners affect DNA methylation patterns. Consequently, the acquired gene expression may increase the proliferative potential of cells, often concomitant with loss of cell identity as found in cancer. Aberrant DNA methylation, including hypermethylation and hypomethylation at various genomic regions, therefore, is a hallmark of most cancers. Additionally, somatic mutations in DNMTs that affect catalytic activity were mapped in Acute Myeloid Leukemia cancer cells. Despite being very effective in some cancers, the clinically approved DNMT inhibitors lack specificity, which could result in a wide range of deleterious effects. Elucidating distinct molecular mechanisms of DNMTs will facilitate the discovery of alternative cancer therapeutic targets. This review is focused on: (i) the structure and characteristics of DNMTs, (ii) the prevalence of mutations and abnormal expression of DNMTs in cancer, (iii) factors that mediate their abnormal expression and (iv) the effect of anomalous DNMT-complexes in cancer.

Polycomb group proteins in cancer: multifaceted functions and strategies for modulation

Polycomb repressive complexes (PRCs) are a heterogenous collection of dozens, if not hundreds, of protein complexes composed of various combinations of subunits. PRCs are transcriptional repressors important for cell-type specificity during development, and as such, are commonly mis-regulated in cancer. PRCs are broadly characterized as PRC1 with histone ubiquitin ligase activity, or PRC2 with histone methyltransferase activity; however, the mechanism by which individual PRCs, particularly the highly diverse set of PRC1s, alter gene expression has not always been clear. Here we review the current understanding of how PRCs act, both individually and together, to establish and maintain gene repression, the biochemical contribution of individual PRC subunits, the mis-regulation of PRC function in different cancers, and the current strategies for modulating PRC activity. Increased mechanistic understanding of PRC function, as well as cancer-specific roles for individual PRC subunits, will uncover better targets and strategies for cancer therapies.

NAD+ bioavailability mediates PARG inhibition-induced replication arrest, intra S-phase checkpoint and apoptosis in glioma stem cells

Elevated expression of the DNA damage response proteins PARP1 and poly(ADP-ribose) glycohydrolase (PARG) in glioma stem cells (GSCs) suggests that glioma may be a unique target for PARG inhibitors (PARGi). While PARGi-induced cell death is achieved when combined with ionizing radiation, as a single agent PARG inhibitors appear to be mostly cytostatic. Supplementation with the NAD+ precursor dihydronicotinamide riboside (NRH) rapidly increased NAD+ levels in GSCs and glioma cells, inducing PARP1 activation and mild suppression of replication fork progression. Administration of NRH+PARGi triggers hyperaccumulation of poly(ADP-ribose) (PAR), intra S-phase arrest and apoptosis in GSCs but minimal PAR induction or cytotoxicity in normal astrocytes. PAR accumulation is regulated by select PARP1- and PAR-interacting proteins. The involvement of XRCC1 highlights the base excision repair pathway in responding to replication stress while enhanced interaction of PARP1 with PCNA, RPA and ORC2 upon PAR accumulation implicates replication associated PARP1 activation and assembly with pre-replication complex proteins upon initiation of replication arrest, the intra S-phase checkpoint and the onset of apoptosis.

UNMASC: tumor-only variant calling with unmatched normal controls

Despite years of progress, mutation detection in cancer samples continues to require significant manual review as a final step. Expert review is particularly challenging in cases where tumors are sequenced without matched normal control DNA. Attempts have been made to call somatic point mutations without a matched normal sample by removing well-known germline variants, utilizing unmatched normal controls, and constructing decision rules to classify sequencing errors and private germline variants. With budgetary constraints related to computational and sequencing costs, finding the appropriate number of controls is a crucial step to identifying somatic variants. Our approach utilizes public databases for canonical somatic variants as well as germline variants and leverages information gathered about nearby positions in the normal controls. Drawing from our cohort of targeted capture panel sequencing of tumor and normal samples with varying tumortypes and demographics, these served as a benchmark for our tumor-only variant calling pipeline to observe the relationship between our ability to correctly classify variants against a number of unmatched normals. With our benchmarked samples, approximately ten normal controls were needed to maintain 94% sensitivity, 99% specificity and 76% positive predictive value, far outperforming comparable methods. Our approach, called UNMASC, also serves as a supplement to traditional tumor with matched normal variant calling workflows and can potentially extend to other concerns arising from analyzing next generation sequencing data.