CRISPRs in the human genome are differentially expressed between malignant and normal adjacent to tumor tissue

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) have been identified in bacteria, archaea and mitochondria of plants, but not in eukaryotes. Here, we report the discovery of 12,572 putative CRISPRs randomly distributed across the human chromosomes, which we termed hCRISPRs. By using available transcriptome datasets, we demonstrate that hCRISPRs are distinctively expressed as small non-coding RNAs (sncRNAs) in cell lines and human tissues. Moreover, expression patterns thereof enabled us to distinguish normal from malignant tissues. In prostate cancer, we confirmed the differential hCRISPR expression between normal adjacent and malignant primary prostate tissue by RT-qPCR and demonstrate that the SHERLOCK and DETECTR dipstick tools are suitable to detect these sncRNAs. We anticipate that the discovery of CRISPRs in the human genome can be further exploited for diagnostic purposes in cancer and other medical conditions, which certainly will lead to the development of point-of-care tests based on the differential expression of the hCRISPRs.

CRISPR elements in the human genome are expressed in both healthy tissues and tumors but with distinct patterns, representing a potential biomarker for cancer.

Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data

BACKGROUND

Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non-poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints.

RESULTS

We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA-minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG-positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq.

CONCLUSION

By using the full potential of non-poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.

Proteins in stool as biomarkers for non-invasive detection of colorectal adenomas with high risk of progression

Screening to detect colorectal cancer (CRC) in an early or premalignant state is an effective method to reduce CRC mortality rates. Current stool-based screening tests, e.g. fecal immunochemical test (FIT), have a suboptimal sensitivity for colorectal adenomas and difficulty distinguishing adenomas at high risk of progressing to cancer from those at lower risk. We aimed to identify stool protein biomarker panels that can be used for the early detection of high-risk adenomas and CRC. Proteomics data (LC-MS/MS) were collected on stool samples from adenoma (n = 71) and CRC patients (n = 81) as well as controls (n = 129). Colorectal adenoma tissue samples were characterized by low-coverage whole-genome sequencing to determine their risk of progression based on specific DNA copy number changes. Proteomics data were used for logistic regression modeling to establish protein biomarker panels. In total, 15 of the adenomas (15.8%) were defined as high risk of progressing to cancer. A protein panel, consisting of haptoglobin (Hp), LAMP1, SYNE2, and ANXA6, was identified for the detection of high-risk adenomas (sensitivity of 53% at specificity of 95%). Two panels, one consisting of Hp and LRG1 and one of Hp, LRG1, RBP4, and FN1, were identified for high-risk adenomas and CRCs detection (sensitivity of 66% and 62%, respectively, at specificity of 95%). Validation of Hp as a biomarker for high-risk adenomas and CRCs was performed using an antibody-based assay in FIT samples from a subset of individuals from the discovery series (n = 158) and an independent validation series (n = 795). Hp protein was significantly more abundant in high-risk adenoma FIT samples compared to controls in the discovery (p = 0.036) and the validation series (p = 9e-5). We conclude that Hp, LAMP1, SYNE2, LRG1, RBP4, FN1, and ANXA6 may be of value as stool biomarkers for early detection of high-risk adenomas and CRCs. © 2019 Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Molecular characterization of colorectal adenomas reveals POFUT1 as a candidate driver of tumor progression

Removal of colorectal adenomas is an effective strategy to reduce colorectal cancer (CRC) mortality rates. However, as only a minority of adenomas progress to cancer, such strategies may lead to overtreatment. The present study aimed to characterize adenomas by in‐depth molecular profiling, to obtain insights into altered biology associated with the colorectal adenoma‐to‐carcinoma progression. We obtained low‐coverage whole genome sequencing, RNA sequencing and tandem mass spectrometry data for 30 CRCs, 30 adenomas and 18 normal adjacent colon samples. These data were used for DNA copy number aberrations profiling, differential expression, gene set enrichment and gene‐dosage effect analysis. Protein expression was independently validated by immunohistochemistry on tissue microarrays and in patient‐derived colorectal adenoma organoids. Stroma percentage was determined by digital image analysis of tissue sections. Twenty‐four out of 30 adenomas could be unambiguously classified as high risk (n = 9) or low risk (n = 15) of progressing to cancer, based on DNA copy number profiles. Biological processes more prevalent in high‐risk than low‐risk adenomas were related to proliferation, tumor microenvironment and Notch, Wnt, PI3K/AKT/mTOR and Hedgehog signaling, while metabolic processes and protein secretion were enriched in low‐risk adenomas. DNA copy number driven gene‐dosage effect in high‐risk adenomas and cancers was observed for POFUT1, RPRD1B and EIF6. Increased POFUT1 expression in high‐risk adenomas was validated in tissue samples and organoids. High POFUT1 expression was also associated with Notch signaling enrichment and with decreased goblet cells differentiation. In‐depth molecular characterization of colorectal adenomas revealed POFUT1 and Notch signaling as potential drivers of tumor progression.

What's new?

Removal of colorectal adenomas is an effective strategy to reduce colorectal cancer (CRC) mortality rates. However, as only a minority of adenomas progress to cancer, such strategies may lead to overtreatment. While high‐risk adenomas, defined by specific DNA copy number aberrations, have an increased risk of progression, the mechanisms underlying colorectal adenoma‐to‐carcinoma progression remain unclear. This molecular characterization of colorectal adenomas, CRCs, and normal adjacent colon samples demonstrates that biological processes inherent to CRC are already more active in high‐risk adenomas compared to low‐risk adenomas. Moreover, the findings highlight POFUT1 and Notch signaling as potential drivers of colorectal tumor development.

Abstract 1738: Characterization of structural variants within MACROD2 in the pathogenesis of colorectal cancer

Background: Cancer is caused by somatic DNA alterations, which comprise small nucleotide variants (SNVs), chromosome somatic copy number alterations (SCNAs) and chromosomal breakpoint structural variants (SVs). Previously, we investigated SCNA-associated SVs in colorectal cancer (CRC) and demonstrated that SVs within the MACROD2 gene are highly prevalent. This raises the question whether SVs in MACROD2 may already be present in CRC precursor lesions, i.e. in colorectal adenomas. We have also demonstrated that loss of MACROD2 protein expression is associated with poor response to treatment with 5-fluorouracil-based adjuvant chemotherapy, indicating that MACROD2 function is clinically relevant. The aim of this study is to characterize SVs within MACROD2 in more detail in the pathogenesis of colorectal cancer.

Methods: The frequencies of SCNA-associated SVs in 466 CRCs were compared to those in 118 colorectal adenomas, using array-comparative genomic hybridization. Targeted PacBio long-read sequencing was applied to detect and characterize SVs at nucleotide resolution within MACROD2, in tens of primary CRCs. Illumina whole genome sequencing data of > 450 CRC metastatic lesions, generated by the Hartwig Medical Foundation (HMF; www.hartwigmedicalfoundation.nl), were used for validation purposes.

Results: MACROD2 SCNA-associated SVs were rarely detected among 118 colorectal adenomas (<2%) while being highly prevalent among 466 CRCs (40%). SVs in MACROD2 are currently being characterized at nucleotide resolution by analysis of targeted PacBio long-read sequencing data, the results of which will be presented during the AACR annual meeting. Preliminary analysis of HMF whole genome sequencing data confirms that at least 40% of CRC metastatic lesions are affected by SVs within the MACROD2 gene, most commonly by focal deletions.

Discussion: The current observation that SVs in MACROD2 are nearly absent in adenomas while being highly prevalent in CRCs indicates that MACROD2 is affected at a late stage of colorectal adenoma-to-carcinoma progression. A recent publication by Sakthianandeswaren et al (Cancer Discovery 2018) indicated that loss of MACROD2 promotes chromosomal instability. Taken together, these data support a model in which adenoma-to-carcinoma progression is driven, at least in part, by genomic instability caused by loss of function of the MACROD2 tumor suppressor gene.

Citation Format: Remond J A Fijneman, Nienke Mekkes, Evert van den Broek, Bas Stringer, Roel A. Glas, Malgorzata A. Komor, Christian Rausch, Stef van Lieshout, Edwin Cuppen, Melissa L. Smith, Robert P. Sebra, William J. Rowell, Meredith Ashby, Beatriz Carvalho, Jaap Heringa, Gerrit A. Meijer, Sanne Abeln. Characterization of structural variants within MACROD2 in the pathogenesis of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1738.

Consensus molecular subtype classification of colorectal adenomas

Consensus molecular subtyping is an RNA expression‐based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction‐based methodology. DNA copy number was assessed by low‐coverage DNA sequencing (n = 30) or array‐comparative genomic hybridisation (n = 32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n = 556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 ‘metabolic subtype’, which was least common among CRCs, was most prevalent among adenomas (n = 45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the ‘MSI immune’ subtype. Eight adenomas (13%) were classified as the ‘canonical’ CMS2. No adenomas were classified as the ‘mesenchymal’ CMS4, consistent with the fact that adenomas lack invasion‐associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high‐risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Abstract 3676: CMS classification of colorectal adenomas

Background Consensus molecular subtyping (CMS) is an RNA-expression-based classification of colorectal cancers (CRC). Genomic alterations, resulting in specific RNA-expression patterns, accumulate during CRC pathogenesis, including the premalignant adenoma stage.

Aim This study aimed to investigate whether differentiation of colorectal neoplasia into CMS classes can already be recognized at the adenoma stage, and whether specific CMS classes could be associated with DNA copy number aberrations that mark adenomas at high-risk of progressing to CRC.

Materials and Methods RNA-sequencing was performed on 62 advanced adenomas and 59 CRCs. DNA copy number analysis in adenomas was performed by low-coverage DNA-sequencing (n=30) or array-Comparative Genomic Hybridization (n=32). Microsatellite instability (MSI) status was determined by PCR methods. Adenomas and CRCs were classified into CMS subtypes together with CRCs (n=556) from The Cancer Genome Atlas, using the Random Forest CMS classifier.

Results The majority of the adenomas were classified as CMS3 (n=45; 72%), the 'metabolic subtype', recognized as least common among CRCs. No adenomas were classified as the 'mesenchymal' CMS4 subtype. One adenoma was classified as the 'MSI immune' CMS1 (2%), and 8 adenomas as the 'canonical' CMS2 (13%) type. The remaining 8 (13%) could not be classified. The CMS3 class was enriched with adenomas at low-risk of progression.

Conclusion Most adenomas were successfully classified. The lack of CMS4 adenomas is consistent with the fact that adenomas lack invasion-associated stroma. Adenomas showing cancer-associated chromosomal instability (CIN) or MSI (24%) were mostly classified as CMS2 and CMS1, respectively. The CMS3 subtype appeared to be the predominant adenoma signature.

Citation Format: Malgorzata A. Komor, Linda J. Bosch, Gergana Bounova, Anne S. Bolijn, Pien Delis-van Diemen, Christian Rausch, Youri Hoogstrate, Andrew Stubbs, Mark de Jong, Guido Jenster, Nicole C. an Grieken, Beatriz Carvalho, Lodewyk Wessels, Connie R. Jimenez, Remond J. Fijneman, Gerrit A. Meijer, NGS-ProToCol Consortium. CMS classification of colorectal adenomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3676.

Identification of Differentially Expressed Splice Variants by the Proteogenomic Pipeline Splicify

Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which can detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated downmodulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared with their controls. Splice variants identified included RAC1, OSBPL3, MKI67, and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 downmodulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers.

Abstract 1559: Proteogenomic analysis of alternative splicing in colorectal adenoma-to-carcinoma progression

Background

Early diagnosis of colorectal cancer (CRC) and identification of its precursor lesions (adenomas) is crucial in reducing CRC mortality rates. The fecal immunochemical test (FIT) is a non-invasive CRC screening test that detects human protein hemoglobin. Although FIT is beneficial in its current form with a sensitivity of ~65% for detection of CRC and ~27% for adenomas, its performance is still suboptimal and needs to be further improved. Adenoma-to-carcinoma progression is accompanied by alternative splicing, which results in expression of tumor-specific protein variants. These may yield novel biomarkers suitable for improving detection of progressive adenomas and CRCs.

Aim

We aim to identify novel biomarkers to improve early detection of CRC.

Materials and methods

RNA was isolated from 3D organoid cultures derived from 5 adenomas and 4 CRC tissues. RNA and proteins were isolated from 18 healthy human colon tissues, 30 adenomas and 30 CRCs. Samples were analyzed by RNA sequencing (Illumina) and in-depth tandem mass spectrometry proteomics (QExactive). For both organoid- and tissue-datasets differential splicing analysis was performed on RNA level to enrich the sequence database, against which mass spectra were searched, with predicted protein isoforms.

Results

Comparative splicing analysis between CRC and adenoma organoids revealed ~90 differentially spliced genes, yielding candidate biomarkers from epithelial origin. In the tissues, differential splicing analysis between CRCs and controls and between CRCs and adenomas identified over 1000 of splice variants. These include known alternatively spliced genes involved in cancer such as CD44 and VEGFA and a number of candidates overlapping with the isoforms derived from the organoids. Proteomics analysis revealed that approximately 150 of the splice variants were expressed on protein level.

Conclusion and Discussion

We have confirmed that adenoma-to-carcinoma progression is accompanied by aberrant splicing. Analysis of the organoid cultures allowed us to identify gene isoforms from (neoplastic) epithelial origin. Tissue analysis yielded tumor-specific splice variants that represent novel protein candidate biomarkers for early detection of CRC. The diagnostic performance of these splice variant proteins will be validated in series of stool and FIT samples.

Citation Format: Malgorzata A. Komor, Thang V. Pham, Sander R. Piersma, Anne S. Bolijn, Tim Schelfhorst, Pien M. Delis-van Diemen, Marianne Tijssen, Annemieke C. Hiemstra, Meike de Wit, Beatriz Carvalho, Gerrit A. Meijer, Connie R. Jimenez, Remond J. Fijneman. Proteogenomic analysis of alternative splicing in colorectal adenoma-to-carcinoma progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1559. doi:10.1158/1538-7445.AM2017-1559

Abstract 848: Proteogenomic analysis of alternative splicing: the search for novel biomarkers for colorectal cancer

Introduction

Early detection of colorectal cancer (CRC) and its precursor lesions (adenomas) is crucial to reduce mortality rates. The fecal immunochemical test (FIT) is a non-invasive CRC screening test detecting blood-derived protein hemoglobin. However, FIT sensitivity is suboptimal especially in detection of CRC precursor lesions. As adenoma-to-carcinoma progression is accompanied by alternative splicing, tumor-specific proteins derived from alternatively spliced RNA transcripts might serve as candidate biomarkers for CRC detection.

Materials and methods

RNA and proteins were isolated from CRC cell line SW480 before and after siRNA-mediated down-modulation of the splicing machinery: SF3B1, U2AF1, and SRSF1. To identify splice variants, mRNA was sequenced (Illumina HiSeq) and analyzed. RNA-seq analysis included quality checks (FASTQ, RSeQC), reads mapping (STAR), differential gene expression (DESeq2) and differential expression of splicing isoforms between conditions (MATS). Results from the in silico analysis were validated by qRT-PCR. Proteins were analyzed by in-depth tandem mass spectrometry (QExactive). A proteogenomic data analysis pipeline was established to enrich the sequence database, against which the mass spectra are searched, with the predicted protein splice variants and identify protein isoforms. To further extend the splice-variant database, PacBio sequencing of full-length transcripts is being performed for the SW480 siSF3B1- and control-samples.

Results

Differential expression analysis on RNA and protein level proved that the knock-down experiments were performed successfully. The RNA-seq analysis revealed hundreds of mRNA splice variants, including positive controls described in literature. For example, down-modulation of SF3B1 resulted in quantitative mRNA changes of spliced isoforms of ADD3 both in RNA-seq and RT-PCR data. The proteomics experiment yielded over 6000 proteins per sample, among which a number of protein isoforms resulting from alternative splicing.

Conclusions and discussion

We established a proteogenomic pipeline for the analysis of alternative splicing and provided experimental proof of concept.

We expect, however, that the true complexity of RNA variant information remains highly underestimated. We therefore are performing PacBio long-read RNA-seq to validate our approach and to identify additional (novel) splicing events. In future studies we will apply the mRNA-seq based proteogenomic pipeline for detection of protein alterations to a series of adenomas at low- and high-risk of progression, and CRCs to validate the isoforms in a clinically relevant setting. Novel findings will be evaluated for their performance as screening markers for CRC.

This work was financially supported by KWF project nr: VU 2013-6025.

Citation Format: Malgorzata A. Komor, Annemieke C. Hiemstra, Thang V. Pham, Sander R. Piersma, Robert P. Sebra, Bo W. Han, Meredith Ashby, Beatriz Carvalho, Gerrit A. Meijer, Connie R. Jimenez, Remond JA Fijneman. Proteogenomic analysis of alternative splicing: the search for novel biomarkers for colorectal cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 848.