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Claus Lindbjerg Andersen

Publications and source records attributed to Claus Lindbjerg Andersen.

5 recordsLinked to original sources

An alignment-free strategy for circulating tumor DNA detection and tumor fraction estimation from whole-genome sequencing data.

Circulating tumor DNA (ctDNA) is emerging as a promising biomarker for postoperative monitoring of cancer patients. Precise estimation of circulating tumor fraction is crucial for evaluating treatment effects and timely detection of disease recurrence. All current ctDNA detection methods that utilize whole-genome sequencing (WGS) data rely on the reference genome alignment of sequencing reads and often apply separate tools for detecting different variant types. However, various bioinformatic analysis confounders and the application of external variant calling tools could be avoided by analyzing k-mers from unaligned sequencing reads. While k-mer-based methods have successfully been applied for somatic variant validation and detection, the potential of k-mer-based ctDNA detection is unexplored. We have developed a tumor-informed alignment-free ctDNA detection tool called ctDNAmer that detects tumor-specific somatic variation directly from unaligned sequencing data by identifying k-mers unique to the tumor DNA. ctDNAmer detects variant information across the genome by comparing the primary tumor and germline WGS data and accounts for sample-specific germline variability and technical noise in the same framework. We tested the utility of ctDNAmer for tumor fraction estimation on postoperative plasma cfDNA WGS data (mean sequencing depth ~ 28x) from 90 stage III colorectal cancer patients with three years of follow-up. The tumor fraction (TF) estimates agreed with the available clinical information and ctDNA was detected in 77% (17/22) of recurring patients with a median lead time of 8 months compared to radiological imaging. We further validated ctDNAmer's tumor fraction estimates based on a comparison with the mean cfDNA allele frequencies of somatic clonal SNVs identified from aligned primary tumor sequencing data. The TF estimates showed a strong Pearson correlation of 0.897 with the mean allele frequencies and improved ctDNA detection results across samples with an AUC of 0.79 compared to 0.75 if the mean allele frequency of clonal mutations is used.

Circulating Tumor DNA↗

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson&#x2019;s r&#x2009;>&#x2009;0.93, p&#x2009;<&#x2009;2.2&#x2009;&#xd7;&#x2009;10&#x2212; 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

Humans↗

Frequent occurrence of uniparental disomy in colorectal cancer.

We used SNP arrays to identify and characterize genomic alterations associated with colorectal cancer (CRC). Laser microdissected cancer cells from 15 adenocarinomas were investigated by Affymetrix Mapping 10K SNP arrays. Analysis of the data extracted from the SNP arrays revealed multiple regions with copy number alterations and loss of heterozygosity (LOH). Novel LOH areas were identified at chromosomes 13, 14 and 15. Combined analysis of the LOH and copy number data revealed genomic structures that could not have been identified analyzing either data type alone. Half of the identified LOH regions showed no evidence of a reduced copy number, indicating the presence of uniparental structures. The distribution of these structures was non-random, primarily involving 8q, 13q and 20q. This finding was supported by analysis of an independent set of array-based transcriptional profiles, consisting of 17 normal mucosa and 66 adenocarcinoma samples. The transcriptional analysis revealed an unchanged expression level in areas with intact copy number, including regions with uniparental disomy, and a reduced expression level in the LOH regions representing factual losses (including 5q, 8p and 17p). The analysis also showed that genes in regions with increased copy number (including 7p and 20q) were predominantly upregulated. Further analyses of the SNP data revealed a subset of the identified alterations to be specifically associated with TP53 inactivation (including 8q gain and 17p loss) and lymph node metastasis status (gain of 7q and 13q). Another subset of the identified alterations was shown to represent intratumor heterogeneity. In conclusion, we demonstrate that uniparental disomy is frequent in CRC, and identify genomic alterations associated with TP53 inactivation and lymph node status.

Adenocarcinoma↗

Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.

Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.

Biomarkers, Tumor↗

A narrow deletion of 7q is common to HCL, and SMZL, but not CLL.

To further characterise the genetic background of the two closely related B-lymphocytic malignancies hairy cell leukaemia (HCL), and splenic marginal zone lymphoma (SMZL) we have identified characteristic copy number imbalances by comparative genomic hybridisation (CGH). Based on these findings, areas of special interest were fine mapped, and relevant probes constructed for use in interphase-fluorescence in situ hybridisation (FISH) investigations. Thus, using the CGH data from 52 HCL and 61 SMZL patients, we identified the characteristic profiles of copy number imbalances for both diseases. These were a gain of 5q13-31 (19%) and loss of 7q22-q35 (6%) for HCL, and gain of 3q25 (28%), loss of 7q31 (16%), and gain of 12q15 (16%) for SMZL. A partial loss of 7q unusual for low-malignant B-cell diseases was found to be common to the two diseases. This loss was therefore fine mapped with BAC/PAC clones. Fine mapping revealed that in SMZL the minimal lost region covers 11.4 Mb spanning from 7q31.33 to 7q33 located between sequence tagged site (STS)-markers SHGC-3275 and D7S725. This area was distinct from the commonly deleted 7q region of myelodysplastic syndrome/acute myeloid leukaemia (MDS/AML). A FISH probe specific for the 7q region was constructed. Using this probe in an interphase-FISH investigation we showed the minimal lost 7q-region of HCL and SMZL to be one and the same. In one HCL case, this investigation furthermore showed the extent of the deleted region to be below the detection limit of CGH, whereas interphase-FISH screening of 36 chronic lymphocytic leukaemia (CLL) cases showed no deletion of the 7q area. In conclusion, we have identified characteristic profiles of copy number imbalances in HCL and SMZL and fine mapped the minimal extent of a commonly lost 7q area of special interest. We hypothesise that this region may contain (a) gene(s) important for the pathology of HCL and SMZL.

Biopsy↗