A dual program for translation regulation in cellular proliferation and differentiation.

A dichotomous choice for metazoan cells is between proliferation and differentiation. Measuring tRNA pools in various cell types, we found two distinct subsets, one that is induced in proliferating cells, and repressed otherwise, and another with the opposite signature. Correspondingly, we found that genes serving cell-autonomous functions and genes involved in multicellularity obey distinct codon usage. Proliferation-induced and differentiation-induced tRNAs often carry anticodons that correspond to the codons enriched among the cell-autonomous and the multicellularity genes, respectively. Because mRNAs of cell-autonomous genes are induced in proliferation and cancer in particular, the concomitant induction of their codon-enriched tRNAs suggests coordination between transcription and translation. Histone modifications indeed change similarly in the vicinity of cell-autonomous genes and their corresponding tRNAs, and in multicellularity genes and their tRNAs, suggesting the existence of transcriptional programs coordinating tRNA supply and demand. Hence, we describe the existence of two distinct translation programs that operate during proliferation and differentiation.

Beyond basics: Key mutation selection features for successful tumor-informed ctDNA detection.

Tumor-informed mutation-based approaches are frequently used for detection of circulating tumor DNA (ctDNA). Not all mutations make equally effective ctDNA markers. The objective was to explore if prioritizing mutations using mutational features-such as cancer cell fraction (CCF), multiplicity, and error rate-would improve the success rate of tumor-informed ctDNA analysis. Additionally, we aimed to develop a practical and easily implementable analysis pipeline for identifying and prioritizing candidate mutations from whole-exome sequencing (WES) data. We analyzed WES and ctDNA data from three tumor-informed ctDNA studies, one on bladder cancer (Cohort A) and two on colorectal cancer (Cohorts I and N). The studies included 390 patients. For each patient, a unique set of mutations (median mutations/patient: 6, interquartile 13, range: 1-46, total n = 4023) were used as markers of ctDNA. The tool PureCN was used to assess the CCF and multiplicity of each mutation. High-CCF mutations were detected more frequently than low-CCF mutations (Cohort A: odds ratio [OR] 20.6, 95% confidence interval [CI] 5.72-173, p = 1.73e-12; Cohort I: OR 2.24, 95% CI 1.44-3.52, p = 1.66e-04; and Cohort N: OR 1.78, 95% CI 1.14-2.79, p = 7.86e-03). The detection-likelihood was additionally improved by selecting mutations with multiplicity of two or above (Cohort A: OR 1.55, 95% CI 1. 14-2.11, p = 3.85e-03; Cohort I: OR 1.78, 95% CI 1.23-2.56, p = 1.34e-03; and Cohort N: OR 1.94, 95% CI 1.63-2.31, p = 2.83e-14). Furthermore, selecting the mutations for which the ctDNA detection method had the lowest error rates, additionally improved the detection-likelihood, particularly evident when plasma cell-free DNA tumor fractions were below 0.1% (p = 2.1e-07). Selecting mutational markers with high CCF, high multiplicity, and low error rate significantly improve ctDNA detection likelihood. We provide free access to the analysis pipeline enabling others to perform qualified prioritization of mutations for tumor-informed ctDNA analysis.

Error Characterization and Statistical Modeling Improves Circulating Tumor DNA Detection by Droplet Digital PCR.

BACKGROUND: Droplet digital PCR (ddPCR) is a widely used and sensitive application for circulating tumor DNA (ctDNA) detection. As ctDNA is often found in low abundance, methods to separate low-signal readouts from noise are necessary. We aimed to characterize the ddPCR-generated noise and, informed by this, create a sensitive and specific ctDNA caller. METHODS: We built 2 novel complimentary ctDNA calling methods: dynamic limit of blank and concentration and assay-specific tumor load estimator (CASTLE). Both methods are informed by empirically established assay-specific noise profiles. Here, we characterized noise for 70 mutation-detecting ddPCR assays by applying each assay to 95 nonmutated samples. Using these profiles, the performance of the 2 new methods was assessed in a total of 9447 negative/positive reference samples and in 1311 real-life plasma samples from colorectal cancer patients. Lastly, performances were compared to 7 literature-established calling methods. RESULTS: For many assays, noise increased proportionally with the DNA input amount. Assays targeting transition base changes were more error-prone than transversion-targeting assays. Both our calling methods successfully accounted for the additional noise in transition assays and showed consistently high performance regardless of DNA input amount. Calling methods that were not noise-informed performed less well than noise-informed methods. CASTLE was the only calling method providing a statistical estimate of the noise-corrected mutation level and call certainty. CONCLUSIONS: Accurate error modeling is necessary for sensitive and specific ctDNA detection by ddPCR. Accounting for DNA input amounts ensures specific detection regardless of the sample-specific DNA concentration. Our results demonstrate CASTLE as a powerful tool for ctDNA calling using ddPCR.

Enhanced Performance of DNA Methylation Markers by Simultaneous Measurement of Sense and Antisense DNA Strands after Cytosine Conversion.

BACKGROUND: Most existing DNA methylation-based methods for detection of circulating tumor DNA (ctDNA) are based on conversion of unmethylated cytosines to uracil. After conversion, the 2 DNA strands are no longer complementary; therefore, targeting only 1 DNA strand merely utilizes half of the available input DNA. We investigated whether the sensitivity of methylation-based ctDNA detection strategies could be increased by targeting both DNA strands after bisulfite conversion. METHODS: Dual-strand digital PCR assays were designed for the 3 colorectal cancer (CRC)-specific methylation markers KCNQ5, C9orf50, and CLIP4 and compared with previously reported single-strand assays. Performance was tested in tumor and leukocyte DNA, and the ability to detect ctDNA was investigated in plasma from 43 patients with CRC stages I to IV and 42 colonoscopy-confirmed healthy controls. RESULTS: Dual-strand assays quantified close to 100% of methylated control DNA input, whereas single-strand assays quantified approximately 50%. Furthermore, dual-strand assays showed a 2-fold increase in the number of methylated DNA copies detected when applied to DNA purified from tumor tissue and plasma from CRC patients. When the results of the 3 DNA methylation markers were combined into a ctDNA detection test and applied to plasma, the dual-strand assay format detected 86% of the cancers compared with 74% for the single-strand assay format. The specificity was 100% for both the dual- and single-strand test formats. CONCLUSION: Dual-strand assays enabled more sensitive detection of methylated ctDNA than single-strand assays.

Putative cis-regulatory drivers in colorectal cancer.

The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.

Gel-Based Proteomics of Clinical Samples Identifies Potential Serological Biomarkers for Early Detection of Colorectal Cancer.

The burden of colorectal cancer (CRC) is considerable-approximately 1.8 million people are diagnosed each year with CRC and of these about half will succumb to the disease. In the case of CRC, there is strong evidence that an early diagnosis leads to a better prognosis, with metastatic CRC having a 5-year survival that is only slightly greater than 10% compared with up to 90% for stage I CRC. Clearly, biomarkers for the early detection of CRC would have a major clinical impact. We implemented a coherent gel-based proteomics biomarker discovery platform for the identification of clinically useful biomarkers for the early detection of CRC. Potential protein biomarkers were identified by a 2D gel-based analysis of a cohort composed of 128 CRC and site-matched normal tissue biopsies. Potential biomarkers were prioritized and assays to quantitatively measure plasma expression of the candidate biomarkers were developed. Those biomarkers that fulfilled the preset criteria for technical validity were validated in a case-control set of plasma samples, including 70 patients with CRC, adenomas, or non-cancer diseases and healthy individuals in each group. We identified 63 consistently upregulated polypeptides (factor of four-fold or more) in our proteomics analysis. We selected 10 out of these 63 upregulated polypeptides, and established assays to measure the concentration of each one of the ten biomarkers in plasma samples. Biomarker levels were analyzed in plasma samples from healthy individuals, individuals with adenomas, CRC patients, and patients with non-cancer diseases and we identified one protein, tropomyosin 3 (Tpm3) that could discriminate CRC at a significant level (p = 0.0146). Our results suggest that at least one of the identified proteins, Tpm3, could be used as a biomarker in the early detection of CRC, and further studies should provide unequivocal evidence for the real-life clinical validity and usefulness of Tpm3.

Analysis of circulating tumour DNA to monitor disease burden following colorectal cancer surgery.

OBJECTIVE: To develop an affordable and robust pipeline for selection of patient-specific somatic structural variants (SSVs) being informative about radicality of the primary resection, response to adjuvant therapy, incipient recurrence and response to treatment performed in relation to diagnosis of recurrence. DESIGN: We have established efficient procedures for identification of SSVs by next-generation sequencing and subsequent quantification of 3-6 SSVs in plasma. The consequence of intratumour heterogeneity on our approach was assessed. The level of circulating tumour DNA (ctDNA) was quantified in 151 serial plasma samples from six relapsing and five non-relapsing colorectal cancer (CRC) patients by droplet digital PCR, and correlated to clinical findings. RESULTS: Up to six personalised assays were designed for each patient. Our approach enabled efficient temporal assessment of disease status, response to surgical and oncological intervention, and early detection of incipient recurrence. Our approach provided 2-15 (mean 10) months' lead time on detection of metastatic recurrence compared to conventional follow-up. The sensitivity and specificity of the SSVs in terms of detecting postsurgery relapse were 100%. CONCLUSIONS: We show that assessment of ctDNA is a non-invasive, exquisitely specific and highly sensitive approach for monitoring disease load, which has the potential to provide clinically relevant lead times compared with conventional methods. Furthermore, we provide a low-coverage protocol optimised for identifying SSVs with excellent correlation between SSVs identified in tumours and matched metastases. Application of ctDNA analysis has the potential to change clinical practice in the management of CRC.

Performance of the colorectal cancer screening marker Sept9 is influenced by age, diabetes and arthritis: a nested case-control study.

BACKGROUND: Annually, colorectal cancer (CRC) is diagnosed in >1.4 million subjects worldwide and incidence is increasing. Much effort has therefore been focused on screening, which has proven to reduce cancer-related mortality. The Sept9 DNA-methylation assay is among the most well studied blood-based screening markers. However, earlier reported performances may be misleading: the Sept9 test was recently examined in two screening based cohorts and yielded performances lower than expected. We hypothesize that comorbidities and/or demographic characteristics affect the results of the Sept9 test. METHODS: Using a retrospective nested case-control study design, we studied plasma from 150 cancer and 150 controls selected from a well-characterized cohort of 4698 subjects referred for diagnostic colonoscopy due to CRC-related symptoms. The cases and controls were matched on age and gender, and moreover cases were stratified on tumor-site and tumor-stage. The selected cohort included a wide range of comorbidities. Plasma Sept9 levels were assessed using a commercially available PCR based assay (Epi-proColon). RESULTS: Clinical sensitivity for CRC stages I-IV was 37 %, 91 %, 77 %, and 89 %, and the overall sensitivity 73 % (95 % CI, 64-80 %) and specificity 82 % (95 % CI, 75-88 %), respectively. Age >65 was associated with both increased false positive and false negative results (p < 0.05). Arthritis was associated with a higher false negative rate (p = 0.005) whereas Arteriosclerosis was associated with a higher false positive rate (p = 0.007). Diabetes was associated with Sept9 positivity with an OR of 5.2 (95 % CI 1.4-19.1). When the performance of Sept9 was adjusted for these parameters in a final multivariate regression model, the OR for a positive Sept9 test to be associated with CRC increased from 8.25 (95 % CI 4.83-14.09) to 29.46 (95 % CI 12.58-69.02). CONCLUSIONS: The results indicate that the performance of the Sept9 assay is negatively affected by several factors commonly associated with CRC screening populations: early-stage disease, age > 65 years, diabetes, arthritis, and arteriosclerosis. This should be taken into account if the Sept9 assay is used as a single marker for CRC screening, but may also have a wider impact, as it is likely that such factors may affect other blood based DNA markers as well.

The splicing factor SRSF6 is amplified and is an oncoprotein in lung and colon cancers.

An increasing body of evidence connects alterations in the process of alternative splicing with cancer development and progression. However, a direct role of splicing factors as drivers of cancer development is mostly unknown. We analysed the gene copy number of several splicing factors in colon and lung tumours, and found that the gene encoding for the splicing factor SRSF6 is amplified and over-expressed in these cancers. Moreover, over-expression of SRSF6 in immortal lung epithelial cells enhanced proliferation, protected them from chemotherapy-induced cell death and converted them to be tumourigenic in mice. In contrast, knock-down of SRSF6 in lung and colon cancer cell lines inhibited their tumourigenic abilities. SRSF6 up- or down-regulation altered the splicing of several tumour suppressors and oncogenes to generate the oncogenic isoforms and reduce the tumour-suppressive isoforms. Our data suggest that the splicing factor SRSF6 is an oncoprotein that regulates the proliferation and survival of lung and colon cancer cells.

Exploring the biology of ctDNA release in colorectal cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a promising tool for early cancer detection and minimal residual disease monitoring. However, the biology underlying ctDNA release and its variation across cancer types and histologies remains poorly understood. This study investigated the biology behind ctDNA shedding in colorectal cancer. METHODS: The study included a local cohort of 747 stage I-III colorectal cancer patients. All patients had ctDNA measurement prior to treatment and extensive clinical data. Primary tumor RNA sequencing and whole exome sequencing was performed in 95 and 652 patients respectively. Additionally, the study evaluated 89 non-small cell lung cancer patients from the TRACERx cohort, comprising primary tumor RNA sequencing and ctDNA measurement. RESULTS: We found tumor size and proliferative capacity to be key factors associated with ctDNA shedding in colorectal cancer. Furthermore, we found that the secretory and CMS3 colorectal cancer subtypes exhibited lower ctDNA shedding, while microsatellite instability (MSI) tumors had higher levels of ctDNA. Mutational analysis did not reveal any genes or pathways associated with ctDNA shedding in colorectal cancer. A comparison of transcriptomic profiles across multiple cancer types demonstrated that colorectal cancer and lung squamous cell carcinoma tumors shared a high-proliferative ctDNA shedding phenotype, while lung adenocarcinoma tumors displayed a distinct low-proliferative subgroup. Additionally, proliferation levels correlated with ctDNA detection sensitivity across multiple cancer types. CONCLUSION: These findings suggest that tumor size and proliferative capacity are drivers of ctDNA release in colorectal cancer and provide insights into the biology of ctDNA shedding on a pan-cancer level.

Non-CpG island promoter hypomethylation and miR-149 regulate the expression of SRPX2 in colorectal cancer.

Gene silencing by DNA hypermethylation of CpG islands is a well-characterized phenomenon in cancer. The effect of hypomethylation in particular of non-CpG island genes is much less well described. By genome-wide screening, we identified 105 genes in microsatellite stable (MSS) colorectal adenocarcinomas with an inverse correlation (Spearman's ρ ≤ -0.40) between methylation and expression. Of these, 35 (33%) were hypomethylated non-CpG island genes and two of them, APOLD1 (Spearman's ρ = -0.82) and SRPX2 (Spearman's ρ = -0.80) were selected for further analyses. Hypomethylation of both genes were localized events not shared by adjacent genes. A set of 662 FFPE DNA samples not only confirmed that APOLD1 and SRPX2 are hypomethylated in CRC but also revealed hypomethylation to be significantly (p < 0.01) associated with tumors being localized in the left side, CpG island methylator phenotype negative, MSS, BRAF wt, undifferentiated and of adenocarcinoma histosubtype. Demethylation experiments supported SRPX2 being epigenetically regulated via DNA methylation, whereas other mechanisms in addition to DNA methylation seem to be involved in the regulation of APOLD1. We further identified miR-149 as a potential novel post-transcriptional regulator of SRPX2. In carcinoma tissue, miR-149 was downregulated and inversely correlated to SRPX2 (ρ = -0.77). Furthermore, ectopic expression of miR-149 significantly reduced SRPX2 transcript levels. Our study highlights that in colorectal tumors, hypomethylation of non-CpG island-associated promoters deregulate gene expression nearly as frequent as do CpG-island hypermethylation. The hypomethylation of SRPX2 is focal and not part of a large block. Furthermore, it often translates to an increased expression level, which may be modulated by miR-149.

MiRNA-362-3p induces cell cycle arrest through targeting of E2F1, USF2 and PTPN1 and is associated with recurrence of colorectal cancer.

Colorectal cancer (CRC) is one of the leading causes of cancer deaths in Western countries. A significant number of CRC patients undergoing curatively intended surgery subsequently develop recurrence and die from the disease. MicroRNAs (miRNAs) are aberrantly expressed in cancers and appear to have both diagnostic and prognostic significance. In this study, we identified novel miRNAs associated with recurrence of CRC, and their possible mechanism of action. TaqMan(®) Human MicroRNA Array Set v2.0 was used to profile the expression of 667 miRNAs in 14 normal colon mucosas and 46 microsatellite stable CRC tumors. Four miRNAs (miR-362-3p, miR-570, miR-148 a* and miR-944) were expressed at a higher level in tumors from patients with no recurrence (p<0.015), compared with tumors from patients with recurrence. A significant association with increased disease free survival was confirmed for miR-362-3p in a second independent cohort of 43 CRC patients, using single TaqMan(®) microRNA assays. In vitro functional analysis showed that over-expression of miR-362-3p in colon cancer cell lines reduced cell viability, and proliferation mainly due to cell cycle arrest. E2F1, USF2 and PTPN1 were identified as potential miR-362-3p targets by mRNA profiling of HCT116 cells over-expressing miR-362-3p. Subsequently, these genes were confirmed as direct targets by Luciferase reporter assays and their knockdown in vitro phenocopied the effects of miR-362-3p over-expression. We conclude that miR-362-3p may be a novel prognostic marker in CRC, and hypothesize that the positive effects of augmented miR-362-3p expression may in part be mediated through the targets E2F1, USF2 and PTPN1.

Alternative splicing of SLC39A14 in colorectal cancer is regulated by the Wnt pathway.

Alternative splicing is a crucial step in the generation of protein diversity and its misregulation is observed in many human cancer types. By analyzing 143 colorectal samples using exon arrays, SLC39A14, a divalent cation transporter, was identified as being aberrantly spliced in tumor samples. SLC39A14 contains two mutually exclusive exons 4A and 4B and the exon 4A/4B ratio was significantly altered in adenomas (p = 3.6 × 10(-10)) and cancers (p = 9.4 × 10(-11)), independent of microsatellite stability status. The findings were validated in independent exon array data sets and by quantitative real-time reverse-transcription PCR (qRT-PCR). Aberrant Wnt signaling is a hallmark of colorectal tumorigenesis and is characterized by nuclear ß-catenin. Experimental inactivation of Wnt signaling in DLD1 and Ls174T cells by knockdown of ß-catenin or overexpression of dominant negative TCFs (TCF1 and TCF4) altered the 4A/4B ratio, indicating that SLC39A14 splicing is regulated by the Wnt pathway. An altered 4A/4B ratio was also observed in gastric and lung cancer where Wnt signaling is also known to be aberrantly activated. The splicing factor SRSF1 and its regulator, the kinase SRPK1, were found to be deregulated upon Wnt inactivation in colorectal carcinoma cells. SRPK1 was also found up-regulated in both adenoma samples (p = 1.5 × 10(-5)) and cancer samples (p = 5 × 10(-4)). In silico splicing factor binding analysis predicted SRSF1 to bind predominantly to the cancer associated exon 4B, hence, it was hypothesized that SRPK1 activates SRSF1 through phosphorylation, followed by SRSF1 binding to exon 4B and regulation of SLC39A14 splicing. Indeed, siRNA-mediated knockdown of SRPK1 and SRSF1 in DLD1 and SW480 colorectal cancer cells led to a change in the 4A/4B isoform ratio, supporting a role of these factors in the regulation of SLC39A14 splicing. In conclusion, alternative splicing of SLC39A14 was identified in colorectal tumors and found to be regulated by the Wnt pathway, most likely through regulation of SRPK1 and SRSF1.

DREAMS: deep read-level error model for sequencing data applied to low-frequency variant calling and circulating tumor DNA detection.

Circulating tumor DNA detection using next-generation sequencing (NGS) data of plasma DNA is promising for cancer identification and characterization. However, the tumor signal in the blood is often low and difficult to distinguish from errors. We present DREAMS (Deep Read-level Modelling of Sequencing-errors) for estimating error rates of individual read positions. Using DREAMS, we develop statistical methods for variant calling (DREAMS-vc) and cancer detection (DREAMS-cc). For evaluation, we generate deep targeted NGS data of matching tumor and plasma DNA from 85 colorectal cancer patients. The DREAMS approach performs better than state-of-the-art methods for variant calling and cancer detection.

Rseg--an R package to optimize segmentation of SNP array data.

UNLABELLED: The use of high-density SNP arrays for investigating copy number alterations in clinical tumor samples, with intra tumor heterogeneity and varying degrees of normal cell contamination, imposes several problems for commonly used segmentation algorithms. This calls for flexibility when setting thresholds for calling gains and losses. In addition, sample normalization can induce artifacts in the copy-number ratios for the non-changed genomic elements in the tumor samples. RESULTS: We present an open source R package, Rseg, which allows the user to define sample-specific thresholds to call gains and losses. It also allows the user to correct for normalization artifacts. AVAILABILITY: The R package, Rseg, is available at: http://www.cs.au.dk/~plamy/Rseg/ and runs on Linux and MS-Windows.

Oncogene-induced senescence is part of the tumorigenesis barrier imposed by DNA damage checkpoints.

Recent studies have indicated the existence of tumorigenesis barriers that slow or inhibit the progression of preneoplastic lesions to neoplasia. One such barrier involves DNA replication stress, which leads to activation of the DNA damage checkpoint and thereby to apoptosis or cell cycle arrest, whereas a second barrier is mediated by oncogene-induced senescence. The relationship between these two barriers, if any, has not been elucidated. Here we show that oncogene-induced senescence is associated with signs of DNA replication stress, including prematurely terminated DNA replication forks and DNA double-strand breaks. Inhibiting the DNA double-strand break response kinase ataxia telangiectasia mutated (ATM) suppressed the induction of senescence and in a mouse model led to increased tumour size and invasiveness. Analysis of human precancerous lesions further indicated that DNA damage and senescence markers cosegregate closely. Thus, senescence in human preneoplastic lesions is a manifestation of oncogene-induced DNA replication stress and, together with apoptosis, provides a barrier to malignant progression.

ctDNA-guided adjuvant chemotherapy for colorectal cancer-ready for prime time?

In stage II colorectal cancer, adjuvant chemotherapy is controversial, and overtreatment is substantial due to suboptimal risk stratification. In a recent New England Journal of Medicine article reporting from a prospective randomized phase II trial, Tie and colleagues demonstrate how ctDNA-guided risk-stratification reduces the use of adjuvant chemotherapy without compromising recurrence risk.

Tumour-agnostic circulating tumour DNA analysis for improved recurrence surveillance after resection of colorectal liver metastases: A prospective cohort study.

PURPOSE: Nearly 50% of patients recur within two years after curatively intended resection of colorectal cancer liver metastasis (CRLM). The optimal surveillance strategy is unknown due to the lack of evidence. Here, we explored the potential for improving postoperative CRLM surveillance by performing serial circulating tumour DNA (ctDNA) assessments parallel to standard-of-care surveillance. EXPERIMENTAL DESIGN: 499 prospectively collected serial plasma samples from 96 patients undergoing CRLM resection were analysed using the tumour-agnostic methylation multiplex droplet-digital PCR test 'TriMeth'. RESULTS: Patients with ctDNA postoperatively or post adjuvant chemotherapy experienced a significant lower recurrence-free survival than patients without ctDNA (hazard ratio (HR) 4.5; P < 0.0001 and HR 8.4, P < 0.0001). ctDNA status was a stronger predictor of recurrence than standard clinical risk factors and carcinoembryonic antigen. Serial TriMeth analysis detected ctDNA before radiological recurrence in 55.6% of ctDNA-positive patients, with up to 10.6 months lead-time (median 3.1 months). During surveillance, 24% of patients had inconclusive CT scans, which was associated with a significant delay in recurrence diagnosis (median 3.5 months versus 1.0 month, P < 0.0001). Uniquely, ctDNA status at the time of inconclusive CT scans predicted recurrence with positive and negative predictive values of 100%, and 75% (P = 0.0003). Serial TriMeth analysis allowed ctDNA growth rate assessment and revealed that fast ctDNA growth was associated with poor overall survival (HR: 1.6, P = 0.0052). CONCLUSIONS: Serial postoperative ctDNA analysis has a strong prognostic value and is more sensitive for recurrence detection than standard-of-care CRLM surveillance tools. Altogether, TriMeth provides several opportunities for improving postoperative surveillance of CRLM patients.

A beta-mixture model for dimensionality reduction, sample classification and analysis.

BACKGROUND: Patterns of genome-wide methylation vary between tissue types. For example, cancer tissue shows markedly different patterns from those of normal tissue. In this paper we propose a beta-mixture model to describe genome-wide methylation patterns based on probe data from methylation microarrays. The model takes dependencies between neighbour probe pairs into account and assumes three broad categories of methylation, low, medium and high. The model is described by 37 parameters, which reduces the dimensionality of a typical methylation microarray significantly. We used methylation microarray data from 42 colon cancer samples to assess the model. RESULTS: Based on data from colon cancer samples we show that our model captures genome-wide characteristics of methylation patterns. We estimate the parameters of the model and show that they vary between different tissue types. Further, for each methylation probe the posterior probability of a methylation state (low, medium or high) is calculated and the probability that the state is correctly predicted is assessed. We demonstrate that the model can be applied to classify cancer tissue types accurately and that the model provides accessible and easily interpretable data summaries. CONCLUSIONS: We have developed a beta-mixture model for methylation microarray data. The model substantially reduces the dimensionality of the data. It can be used for further analysis, such as sample classification or to detect changes in methylation status between different samples and tissues.

Evaluation of two commercial global miRNA expression profiling platforms for detection of less abundant miRNAs.

BACKGROUND: microRNAs (miRNA) are short, endogenous transcripts that negatively regulate the expression of specific mRNA targets. miRNAs are found both in tissues and body fluids such as plasma. A major perspective for the use of miRNAs in the clinical setting is as diagnostic plasma markers for neoplasia. While miRNAs are abundant in tissues, they are often scarce in plasma. For quantification of miRNA in plasma it is therefore of importance to use a platform with high sensitivity and linear performance in the low concentration range. This motivated us to evaluate the performance of three commonly used commercial miRNA quantification platforms: GeneChip miRNA 2.0 Array, miRCURY Ready-to-Use PCR, Human panel I+II V1.M, and TaqMan Human MicroRNA Array v3.0. RESULTS: Using synthetic miRNA samples and plasma RNA samples spiked with different ratios of 174 synthetic miRNAs we assessed the performance characteristics reproducibility, recovery, specificity, sensitivity and linearity. It was found that while the qRT-PCR based platforms were sufficiently sensitive to reproducibly detect miRNAs at the abundance levels found in human plasma, the array based platform was not. At high miRNA levels both qRT-PCR based platforms performed well in terms of specificity, reproducibility and recovery. At low miRNA levels, as in plasma, the miRCURY platform showed better sensitivity and linearity than the TaqMan platform. CONCLUSION: For profiling clinical samples with low miRNA abundance, such as plasma samples, the miRCURY platform with its better sensitivity and linearity would probably be superior.