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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. [ABSTRACT FROM AUTHOR]

The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis (1,2). 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., The non-coding genome has so far been overlooked in the search for drivers in cancer, except for some isolated examples (1,2). The genome contains regulatory non-coding germline variation affecting gene [...]

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. [ABSTRACT FROM AUTHOR]

Abstract Background Approximately half of all human genes use alternative transcription start sites (TSSs) to control mRNA levels and broaden the transcriptional output in healthy tissues. Aberrant expression patterns promoting carcinogenesis, however, may arise from alternative promoter usage. Results By profiling 108 colorectal samples using exon arrays, we identified nine genes (TCF12, OSBPL1A, TRAK1, ANK3, CHEK1, UGP2, LMO7, ACSL5, and SCIN) showing tumor-specific alternative TSS usage in both adenoma and cancer samples relative to normal mucosa. Analysis of independent exon array data sets corroborated these findings. Additionally, we confirmed the observed patterns for selected mRNAs using quantitative real-time reverse-transcription PCR. Interestingly, for some of the genes, the tumor-specific TSS usage was not restricted to colorectal cancer. A comprehensive survey of the nine genes in lung, bladder, liver, prostate, gastric, and brain cancer revealed significantly altered mRNA isoform ratios for CHEK1, OSBPL1A, and TCF12 in a subset of these cancer types. To identify the mechanism responsible for the shift in alternative TSS usage, we antagonized the Wnt-signaling pathway in DLD1 and Ls174T colorectal cancer cell lines, which remarkably led to a shift in the preferred TSS for both OSBPL1A and TRAK1. This indicated a regulatory role of the Wnt pathway in selecting TSS, possibly also involving TP53 and SOX9, as their transcription binding sites were enriched in the promoters of the tumor preferred isoforms together with their mRNA levels being increased in tumor samples. Finally, to evaluate the prognostic impact of the altered TSS usage, immunohistochemistry was used to show deregulation of the total protein levels of both TCF12 and OSBPL1A, corresponding to the mRNA levels observed. Furthermore, the level of nuclear TCF12 had a significant correlation to progression free survival in a cohort of 248 stage II colorectal cancer samples. Conclusions Alternative TSS usage in colorectal adenoma and cancer samples has been shown for nine genes, and OSBPL1A and TRAK1 were found to be regulated in vitro by Wnt signaling. TCF12 protein expression was upregulated in cancer samples and correlated with progression free survival.

Abstract 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.

Abstract 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.

Abstract Background Mutations in the mismatch repair genes hMLH1 and hMSH2 predispose to hereditary non-polyposis colorectal cancer (HNPCC). Genetic screening of more than 350 Danish patients with colorectal cancer (CRC) has led to the identification of several new genetic variants (e.g. missense, silent and non-coding) in hMLH1 and hMSH2. The aim of the present study was to investigate the frequency of these variants in hMLH1 and hMSH2 in Danish patients with sporadic colorectal cancer and in the healthy background population. The purpose was to reveal if any of the common variants lead to increased susceptibility to colorectal cancer. Methods Associations between genetic variants in hMLH1 and hMSH2 and sporadic colorectal cancer were evaluated using a case-cohort design. The genotyping was performed on DNA isolated from blood from the 380 cases with sporadic colorectal cancer and a sub-cohort of 770 individuals. The DNA samples were analyzed using Single Base Extension (SBE) Tag-arrays. A Bonferroni corrected Fisher exact test was used to test for association between the genotypes of each variant and colorectal cancer. Linkage disequilibrium (LD) was investigated using HaploView (v3.31). Results Heterozygous and homozygous changes were detected in 13 of 35 analyzed variants. Two variants showed a borderline association with colorectal cancer, whereas the remaining variants demonstrated no association. Furthermore, the genomic regions covering hMLH1 and hMSH2 displayed high linkage disequilibrium in the Danish population. Twenty-two variants were neither detected in the cases with sporadic colorectal cancer nor in the sub-cohort. Some of these rare variants have been classified either as pathogenic mutations or as neutral variants in other populations and some are unclassified Danish variants. Conclusion None of the variants in hMLH1 and hMSH2 analyzed in the present study were highly associated with colorectal cancer in the Danish population. High linkage disequilibrium in the genomic regions covering hMLH1 and hMSH2, indicate that common genetic variants in the two genes in general are not involved in the development of sporadic colorectal cancer. Nevertheless, some of the rare unclassified variants in hMLH1 and hMSH2 might be involved in the development of colorectal cancer in the families where they were originally identified.

Abstract Background Affymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look at the genomic content of cancer cells and to investigate the underlying events leading to cancer. Genomic copy-numbers are today routinely derived from SNP array data, but the proposed algorithms for this task most often disregard the genotype information available from germline cells in paired germline-tumour samples. Including this information may deepen our understanding of the "true" biological situation e.g. by enabling analysis of allele specific copy-numbers. Here we rely on matched germline-tumour samples and have developed a Hidden Markov Model (HMM) to estimate allelic copy-number changes in tumour cells. Further with this approach we are able to estimate the proportion of normal cells in the tumour (mixture proportion). Results We show that our method is able to recover the underlying copy-number changes in simulated data sets with high accuracy (above 97.71%). Moreover, although the known copy-numbers could be well recovered in simulated cancer samples with more than 70% cancer cells (and less than 30% normal cells), we demonstrate that including the mixture proportion in the HMM increases the accuracy of the method. Finally, the method is tested on HapMap samples and on bladder and prostate cancer samples. Conclusion The HMM method developed here uses the genotype calls of germline DNA and the allelic SNP intensities from the tumour DNA to estimate allelic copy-numbers (including changes) in the tumour. It differentiates between different events like uniparental disomy and allelic imbalances. Moreover, the HMM can estimate the mixture proportion, and thus inform about the purity of the tumour sample.

Detection of circulating tumor DNA (ctDNA) post‐treatment is an emerging marker of residual disease. ctDNA constitutes only a minor fraction of the cell‐free DNA (cfDNA) circulating in cancer patients, complicating ctDNA detection. This is exacerbated by trauma‐induced cfDNA. To guide optimal blood sample timing, we investigated the duration and magnitude of surgical trauma‐induced cfDNA in patients with colorectal or bladder cancer. DNA levels were quantified in paired plasma samples collected before and up to 6 weeks after surgery from 436 patients with colorectal cancer and 47 patients with muscle‐invasive bladder cancer. To assess whether trauma‐induced cfDNA fragments are longer than ordinary cfDNA fragments, the concentration of short (< 1 kb) and long (> 1 kb) fragments was determined for 91 patients. Previously reported ctDNA data from 91 patients with colorectal cancer and 47 patients with bladder cancer were used to assess how trauma‐induced DNA affects ctDNA detection. The total cfDNA level increased postoperatively—both in patients with colorectal cancer (mean threefold) and bladder cancer (mean eightfold). The DNA levels were significantly increased up to 4 weeks after surgery in both patient cohorts (P = 0.0005 and P ≤ 0.0001). The concentration of short, but not long, cfDNA fragments increased postoperatively. Of 25 patients with radiological relapse, eight were ctDNA‐positive and 17 were ctDNA‐negative in the period with trauma‐induced DNA. Analysis of longitudinal samples revealed that five of the negative patients became positive shortly after the release of trauma‐induced cfDNA had ceased. In conclusion, surgery was associated with elevated cfDNA levels, persisting up to 4 weeks, which may have masked ctDNA in relapse patients. Trauma‐induced cfDNA was of similar size to ordinary cfDNA. To mitigate the impact of trauma‐induced cfDNA on ctDNA detection, it is recommended that a second blood sample collected after week 4 is analyzed for patients initially ctDNA negative. [ABSTRACT FROM AUTHOR]

It is well established that lncRNAs are aberrantly expressed in cancer where they have been shown to act as oncogenes or tumor suppressors. RNA profiling of 314 colorectal adenomas/adenocarcinomas and 292 adjacent normal colon mucosa samples using RNA-sequencing demonstrated that the snoRNA host gene 16 (SNHG16) is significantly up-regulated in adenomas and all stages of CRC. SNHG16 expression was positively correlated to the expression of Wnt-regulated transcription factors, including ASCL2, ETS2, and c-Myc. In vitro abrogation of Wnt signaling in CRC cells reduced the expression of SNHG16 indicating that SNHG16 is regulated by the Wnt pathway. Silencing of SNHG16 resulted in reduced viability, increased apoptotic cell death and impaired cell migration. The SNHG16 silencing particularly affected expression of genes involved in lipid metabolism. A connection between SNHG16 and genes involved in lipid metabolism was also observed in clinical tumors. Argonaute CrossLinking and ImmunoPrecipitation (AGO-CLIP) demonstrated that SNHG16 heavily binds AGO and has 27 AGO/miRNA target sites along its length, indicating that SNHG16 may act as a competing endogenous RNA (ceRNA) “sponging” miRNAs off their cognate targets. Most interestingly, half of the miRNA families with high confidence targets on SNHG16 also target the 3′UTR of Stearoyl-CoA Desaturase (SCD). SCD is involved in lipid metabolism and is down-regulated upon SNHG16 silencing. In conclusion, up-regulation of SNHG16 is a frequent event in CRC, likely caused by deregulated Wnt signaling. In vitro analyses demonstrate that SNHG16 may play an oncogenic role in CRC and that it affects genes involved in lipid metabolism, possible through ceRNA related mechanisms. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: The kinase Mnk2 is a substrate of the MAPK pathway and phosphorylates the translation initiation factor eIF4E. In humans, MKNK2, the gene encoding for Mnk2, is alternatively spliced yielding two splicing isoforms with differing last exons: Mnk2a, which contains a MAPK-binding domain, and Mnk2b, which lacks it. We found that the Mnk2a isoform is downregulated in breast, lung, and colon tumors and is tumor suppressive. Mnk2a directly interacts with, phosphorylates, activates, and translocates p38α-MAPK into the nucleus, leading to activation of its target genes, increasing cell death and suppression of Ras-induced transformation. Alternatively, Mnk2b is pro-oncogenic and does not activate p38-MAPK, while still enhancing eIF4E phosphorylation. We further show that Mnk2a colocalization with p38α-MAPK in the nucleus is both required and sufficient for its tumor-suppressive activity. Thus, Mnk2a downregulation by alternative splicing is a tumor suppressor mechanism that is lost in some breast, lung, and colon tumors. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

In our study, whole-genome methylation arrays were applied to identify novel genes with tumor specific DNA methylation of promoter CpG islands in pre-malignant and malignant colorectal lesions. Using a combination of Illumina HumanMethylation27 beadchips, Methylation-Sensitive High Resolution Melting (MS-HRM) analysis, and Exon arrays (Affymetrix) the DNA methylation pattern of ∼14,000 genes and their transcript levels were investigated in six normal mucosas, six adenomas and 30 MSI and MSS carcinomas. Sixty eight genes with tumor-specific hypermethylation were identified ( p < 0.005). Identified hypermethylated sites were validated in an independent sample set of eight normal mucosas, 12 adenomas, 40 MSS and nine MSI cancer samples. The methylation patterns of 15 selected genes, hypermethylated in adenomas and carcinomas ( FLI1, ST6GALNAC5, TWIST1, ADHFE1, JAM2, IRF4, CNRIP1, NRG1 and EYA4), in carcinomas only ( ABHD9, AOX1 and RERG), or in MSI but not MSS carcinomas ( RAMP2, DSC3 and MLH1) were validated using MS-HRM. Four of these genes ( MLH1, AOX1, EYA4 and TWIST1) had previously been reported to be hypermethylated in CRC. Eleven genes, not previously known to be affected by CRC specific hypermethylation, were identified and validated. Inverse correlation to gene expression was observed for six of the 15 genes with Spearman correlation coefficients ranging from −0.39 to −0.60. For six of these genes the altered methylation patterns had a profound transcriptional association, indicating that methylation of these genes may play a direct regulatory role. The hypermethylation changes often occurred already in adenomas, indicating that they may be used as biomarkers for early detection of CRC. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Mutations in the mismatch repair genes hMLH1 and hMSH2 predispose to hereditary non-polyposis colorectal cancer (HNPCC). Genetic screening of more than 350 Danish patients with colorectal cancer (CRC) has led to the identification of several new genetic variants (e.g. missense, silent and non-coding) in hMLH1 and hMSH2. The aim of the present study was to investigate the frequency of these variants in hMLH1 and hMSH2 in Danish patients with sporadic colorectal cancer and in the healthy background population. The purpose was to reveal if any of the common variants lead to increased susceptibility to colorectal cancer. Methods: Associations between genetic variants in hMLH1 and hMSH2 and sporadic colorectal cancer were evaluated using a case-cohort design. The genotyping was performed on DNA isolated from blood from the 380 cases with sporadic colorectal cancer and a sub-cohort of 770 individuals. The DNA samples were analyzed using Single Base Extension (SBE) Tag-arrays. A Bonferroni corrected Fisher exact test was used to test for association between the genotypes of each variant and colorectal cancer. Linkage disequilibrium (LD) was investigated using HaploView (v3.31). Results: Heterozygous and homozygous changes were detected in 13 of 35 analyzed variants. Two variants showed a borderline association with colorectal cancer, whereas the remaining variants demonstrated no association. Furthermore, the genomic regions covering hMLH1 and hMSH2 displayed high linkage disequilibrium in the Danish population. Twenty-two variants were neither detected in the cases with sporadic colorectal cancer nor in the sub-cohort. Some of these rare variants have been classified either as pathogenic mutations or as neutral variants in other populations and some are unclassified Danish variants. Conclusion: None of the variants in hMLH1 and hMSH2 analyzed in the present study were highly associated with colorectal cancer in the Danish population. High linkage disequilibrium in the genomic regions covering hMLH1 and hMSH2, indicate that common genetic variants in the two genes in general are not involved in the development of sporadic colorectal cancer. Nevertheless, some of the rare unclassified variants in hMLH1 and hMSH2 might be involved in the development of colorectal cancer in the families where they were originally identified. [ABSTRACT FROM AUTHOR]

Background: Affymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look at the genomic content of cancer cells and to investigate the underlying events leading to cancer. Genomic copy-numbers are today routinely derived from SNP array data, but the proposed algorithms for this task most often disregard the genotype information available from germline cells in paired germline-tumour samples. Including this information may deepen our understanding of the "true" biological situation e.g. by enabling analysis of allele specific copynumbers. Here we rely on matched germline-tumour samples and have developed a Hidden Markov Model (HMM) to estimate allelic copy-number changes in tumour cells. Further with this approach we are able to estimate the proportion of normal cells in the tumour (mixture proportion). Results: We show that our method is able to recover the underlying copy-number changes in simulated data sets with high accuracy (above 97.71%). Moreover, although the known copynumbers could be well recovered in simulated cancer samples with more than 70% cancer cells (and less than 30% normal cells), we demonstrate that including the mixture proportion in the HMM increases the accuracy of the method. Finally, the method is tested on HapMap samples and on bladder and prostate cancer samples. Conclusion: The HMM method developed here uses the genotype calls of germline DNA and the allelic SNP intensities from the tumour DNA to estimate allelic copy-numbers (including changes) in the tumour. It differentiates between different events like uniparental disomy and allelic imbalances. Moreover, the HMM can estimate the mixture proportion, and thus inform about the purity of the tumour sample. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. 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'. 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). 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. • Recurrence rates after colorectal cancer liver metastases (CRLM) resection are high. • Postoperative circulating tumour DNA(ctDNA) status is a strong recurrence predictor. • ctDNA analysis at the time of inconclusive surveillance scans predicts recurrence. • Serial analysis detects ctDNA up to 10 months ahead of radiologic recurrence. • ctDNA growth rate as proxy of tumour growth is associated with disease outcome. [ABSTRACT FROM AUTHOR]