Putatively cancer-specific exon–exon junctions are shared across patients and present in developmental and other non-cancer cells

David, Julianne K.; Maden, Sean K.; Weeder, Benjamin R.; Thompson, Reid F.; Nellore, Abhinav

doi:10.1093/narcan/zcaa001

Cited by 14 publications

(15 citation statements)

References 44 publications

(52 reference statements)

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“…David et al (2020) extended the analysis of exon-exon junctions to 10,549 tumor samples across 33 TCGA cancer types and observed that more than 50% of new junctions were not shared among cancer samples. Importantly, in cervical cancer they identified a total of 14,086,434 exon-exon junctions of which 2,263,326 were specific to cervical cancer (David et al, 2020).…”

Section: Deregulation Of the Splicing Machinery In Cancermentioning

confidence: 99%

The Role of RNA Splicing Factors in Cancer: Regulation of Viral and Human Gene Expression in Human Papillomavirus-Related Cervical Cancer

Cerasuolo

Buonaguro

Tornesello

2020

Front. Cell Dev. Biol.

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The spliceosomal complex components, together with the heterogeneous nuclear ribonucleoproteins (hnRNPs) and serine/arginine-rich (SR) proteins, regulate the process of constitutive and alternative splicing, the latter leading to the production of mRNA isoforms coding multiple proteins from a single pre-mRNA molecule. The expression of splicing factors is frequently deregulated in different cancer types causing the generation of oncogenic proteins involved in cancer hallmarks. Cervical cancer is caused by persistent infection with oncogenic human papillomaviruses (HPVs) and constitutive expression of viral oncogenes. The aberrant activity of hnRNPs and SR proteins in cervical neoplasia has been shown to trigger the production of oncoproteins through the processing of pre-mRNA transcripts either derived from human genes or HPV genomes. Indeed, hnRNP and SR splicing factors have been shown to regulate the production of viral oncoprotein isoforms necessary for the completion of viral life cycle and for cell transformation. Target-therapy strategies against hnRNPs and SR proteins, causing simultaneous reduction of oncogenic factors and inhibition of HPV replication, are under development. In this review, we describe the current knowledge of the functional link between RNA splicing factors and deregulated cellular as well as viral RNA maturation in cervical cancer and the opportunity of new therapeutic strategies.

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Section: Deregulation Of the Splicing Machinery In Cancermentioning

confidence: 99%

The Role of RNA Splicing Factors in Cancer: Regulation of Viral and Human Gene Expression in Human Papillomavirus-Related Cervical Cancer

Cerasuolo

Buonaguro

Tornesello

2020

Front. Cell Dev. Biol.

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“…We benchmarked SICILIAN using three different types of data: matched bulk and scRNA-seq data from five human lung adenocarcinoma cell lines 17 , simulated data with known grown truth 9,18 , and real scRNA-seq data, where we ran SICILIAN on 36,583 lung cells from two individuals from the human lung cell atlas (HLCA) 16 and 16,755 lung cells from two individuals from the mouse lemur cell atlas (MLCA) studies, all sequenced using the 10x platform. We compared SICILIAN to commonly used filtering criteria in the field: all junction calls based on STAR 13 raw alignments, the junctions supported only by uniquely mapping reads 19 , and calling junctions based on read counts 20,21 .…”

mentioning

confidence: 99%

Specific splice junction detection in single cells with SICILIAN

Dehghannasiri

Olivieri

Salzman

2020

Preprint

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Precise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology.Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN's precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, increases agreement between biological replicates, and reliably detects un-annotated splicing in single cells, enabling the discovery of novel splicing regulation. Main text:Alternative splicing is essential for the specialized functions of eukaryotic cells, necessary for development 1 , and a greater contributor to genetic disease burden than mutations 2 . Despite the importance of splicing and massive RNA-seq data generated on single cells, the extent to which the diversity of RNA splicing in single cells is regulated and functional versus transcriptional noise remains contentious 3 .Given the resolution and massive number of available single-cell RNA-seq (scRNA-seq) datasets, precise quantification of splicing in single cells has great promise for discovering regulatory and functional splicing biology. While there are a number of methods developed for isoform quantification at the single-cell level 4,5 , a problem that has not been addressed is the precise discovery of splice junctions. There is a great need for precise junction detection: spliced aligners are designed for bulk RNA-seq and, in addition, generate many artifacts 6-10 , which will be referred to in this paper as "false positives". The problem is exacerbated in scRNA-seq analysis due to the high-level and single-cell-specific biochemical noise and multiple testing errors arising from the analysis of thousands of cells. This problem is typically addressed through the use of simple filters on junction calls, which remove many true positives, especially when the data is sparse such as scRNA-seq. Because of these challenges, there is debate

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“…The importance of the latter was highlighted by David et al, [ 55 ] through analyses of splicing events in cancer and non-cancer RNA-seq data from The Cancer Genome Atlas, the Genotype-Tissue Expression Project, and the Sequence Read Archive. The result of this analysis demonstrated that simply comparing cancer samples to the matched normal tissue from which cancer derives, in that absence of considering other tissue types and developmental time points, results in erroneously identified cancer-specific neojunctions.…”

Section: T Cell-mediated Immunitymentioning

confidence: 99%

Implications of Antigen Selection on T Cell-Based Immunotherapy

Camp

Slansky

2021

Pharmaceuticals

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Many immunotherapies rely on CD8+ effector T cells to recognize and kill cognate tumor cells. These T cell-based immunotherapies include adoptive cell therapy, such as CAR T cells or transgenic TCR T cells, and anti-cancer vaccines which expand endogenous T cell populations. Tumor mutation burden and the choice of antigen are among the most important aspects of T cell-based immunotherapies. Here, we highlight various classes of cancer antigens, including self, neojunction-derived, human endogenous retrovirus (HERV)-derived, and somatic nucleotide variant (SNV)-derived antigens, and consider their utility in T cell-based immunotherapies. We further discuss the respective anti-tumor/anti-self-properties that influence both the degree of immunotolerance and potential off-target effects associated with each antigen class.

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Putatively cancer-specific exon–exon junctions are shared across patients and present in developmental and other non-cancer cells

Cited by 14 publications

References 44 publications

The Role of RNA Splicing Factors in Cancer: Regulation of Viral and Human Gene Expression in Human Papillomavirus-Related Cervical Cancer

The Role of RNA Splicing Factors in Cancer: Regulation of Viral and Human Gene Expression in Human Papillomavirus-Related Cervical Cancer

Specific splice junction detection in single cells with SICILIAN

Implications of Antigen Selection on T Cell-Based Immunotherapy

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