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2. Detection of circulating tumor DNA by tumor-informed whole-genome sequencing enables prediction of recurrence in stage III colorectal cancer patients

Author

Frydendahl, Amanda, Nors, Jesper, Rasmussen, Mads H., Henriksen, Tenna V., Nesic, Marijana, Reinert, Thomas, Afterman, Danielle, Lauterman, Tomer, Kuzman, Maja, Gonzalez, Santiago, Glavas, Dunja, Smadback, James, Maloney, Dillon, Levativ, Jurica, Yahalom, Michael, Ptashkin, Ryan, Tavassoly, Iman, Donenhirsh, Zohar, White, Eric, Kandasamy, Ravi, Alon, Ury, Nordentoft, Iver, Lindskrog, Sia V., Dyrskjøt, Lars, Jaensch, Claudia, Løve, Uffe S., Andersen, Per V., Thorlacius-Ussing, Ole, Iversen, Lene H., Gotschalck, Kåre A., Zviran, Asaf, Oklander, Boris, and Andersen, Claus L.

Published
2024
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9. Publisher Correction: MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer

Author

Mattesen, Trine B., Rasmussen, Mads H., Sandoval, Juan, Ongen, Halit, Árnadóttir, Sigrid S., Gladov, Josephine, Martinez-Cardus, Anna, de Moura, Manuel Castro, Madsen, Anders H., Laurberg, Søren, Dermitzakis, Emmanouil T., Esteller, Manel, Andersen, Claus L., and Bramsen, Jesper B.

Published
2020
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11. Table S1-6 from Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer

Author

Schøler, Lone V., primary, Reinert, Thomas, primary, Ørntoft, Mai-Britt W., primary, Kassentoft, Christine G., primary, Árnadóttir, Sigrid S., primary, Vang, Søren, primary, Nordentoft, Iver, primary, Knudsen, Michael, primary, Lamy, Philippe, primary, Andreasen, Ditte, primary, Mortensen, Frank V., primary, Knudsen, Anders R., primary, Stribolt, Katrine, primary, Sivesgaard, Kim, primary, Mouritzen, Peter, primary, Nielsen, Hans J., primary, Laurberg, Søren, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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13. Figure S4 from Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer

Author

Schøler, Lone V., primary, Reinert, Thomas, primary, Ørntoft, Mai-Britt W., primary, Kassentoft, Christine G., primary, Árnadóttir, Sigrid S., primary, Vang, Søren, primary, Nordentoft, Iver, primary, Knudsen, Michael, primary, Lamy, Philippe, primary, Andreasen, Ditte, primary, Mortensen, Frank V., primary, Knudsen, Anders R., primary, Stribolt, Katrine, primary, Sivesgaard, Kim, primary, Mouritzen, Peter, primary, Nielsen, Hans J., primary, Laurberg, Søren, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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14. Supplementary Figure legends from Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer

Author

Schøler, Lone V., primary, Reinert, Thomas, primary, Ørntoft, Mai-Britt W., primary, Kassentoft, Christine G., primary, Árnadóttir, Sigrid S., primary, Vang, Søren, primary, Nordentoft, Iver, primary, Knudsen, Michael, primary, Lamy, Philippe, primary, Andreasen, Ditte, primary, Mortensen, Frank V., primary, Knudsen, Anders R., primary, Stribolt, Katrine, primary, Sivesgaard, Kim, primary, Mouritzen, Peter, primary, Nielsen, Hans J., primary, Laurberg, Søren, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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15. List of Supplementary Tables from Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer

Author

Schøler, Lone V., primary, Reinert, Thomas, primary, Ørntoft, Mai-Britt W., primary, Kassentoft, Christine G., primary, Árnadóttir, Sigrid S., primary, Vang, Søren, primary, Nordentoft, Iver, primary, Knudsen, Michael, primary, Lamy, Philippe, primary, Andreasen, Ditte, primary, Mortensen, Frank V., primary, Knudsen, Anders R., primary, Stribolt, Katrine, primary, Sivesgaard, Kim, primary, Mouritzen, Peter, primary, Nielsen, Hans J., primary, Laurberg, Søren, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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16. Supplementary Figures 1-3 from Diagnostic and Prognostic MicroRNAs in Stage II Colon Cancer

Author

Schepeler, Troels, primary, Reinert, Jørgen T., primary, Ostenfeld, Marie S., primary, Christensen, Lise L., primary, Silahtaroglu, Asli N., primary, Dyrskjøt, Lars, primary, Wiuf, Carsten, primary, Sørensen, Frank J., primary, Kruhøffer, Mogens, primary, Laurberg, Søren, primary, Kauppinen, Sakari, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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17. Supplementary Table 4 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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19. Supplementary Figure 1 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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21. Supplementary Table 2 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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22. Supplementary Table 3 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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23. Supplementary Table 6 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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24. Supplementary Table 1 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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25. Data from Diagnostic and Prognostic MicroRNAs in Stage II Colon Cancer

Author

Schepeler, Troels, primary, Reinert, Jørgen T., primary, Ostenfeld, Marie S., primary, Christensen, Lise L., primary, Silahtaroglu, Asli N., primary, Dyrskjøt, Lars, primary, Wiuf, Carsten, primary, Sørensen, Frank J., primary, Kruhøffer, Mogens, primary, Laurberg, Søren, primary, Kauppinen, Sakari, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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26. Supplementary Figure 2 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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28. Supplementary Tables 1-4 from Diagnostic and Prognostic MicroRNAs in Stage II Colon Cancer

Author

Schepeler, Troels, primary, Reinert, Jørgen T., primary, Ostenfeld, Marie S., primary, Christensen, Lise L., primary, Silahtaroglu, Asli N., primary, Dyrskjøt, Lars, primary, Wiuf, Carsten, primary, Sørensen, Frank J., primary, Kruhøffer, Mogens, primary, Laurberg, Søren, primary, Kauppinen, Sakari, primary, Ørntoft, Torben F., primary, and Andersen, Claus L., primary

Published
2023
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30. Supplementary Table 5 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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31. Supplementary Figure 3 from Genomic Profiling of MicroRNAs in Bladder Cancer: miR-129 Is Associated with Poor Outcome and Promotes Cell Death In vitro

Author

Dyrskjøt, Lars, primary, Ostenfeld, Marie S., primary, Bramsen, Jesper B., primary, Silahtaroglu, Asli N., primary, Lamy, Philippe, primary, Ramanathan, Ramshanker, primary, Fristrup, Niels, primary, Jensen, Jens L., primary, Andersen, Claus L., primary, Zieger, Karsten, primary, Kauppinen, Sakari, primary, Ulhøi, Benedicte P., primary, Kjems, Jørgen, primary, Borre, Michael, primary, and Ørntoft, Torben F., primary

Published
2023
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32. Additional file 1 of DREAMS: deep read-level error model for sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

Author

Christensen, Mikkel H., Drue, Simon O., Rasmussen, Mads H., Frydendahl, Amanda, Lyskjær, Iben, Demuth, Christina, Nors, Jesper, Gotschalck, Kåre A., Iversen, Lene H., Andersen, Claus L., and Pedersen, Jakob Skou

Abstract

Additional file 1. Supplementary material, Supplementary methods, tables, and figures [12, 16, 24, 33, 35–43].

Published
2023
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34. ctDNA-guided adjuvant chemotherapy for colorectal cancer—ready for prime time?

Author

Andersen, Claus L and Heitzer, Ellen

Subjects
Cancer Research, Neoplasm Recurrence, Local/drug therapy, Circulating Tumor DNA/genetics, Oncology, Chemotherapy, Adjuvant, Humans, Colorectal Neoplasms/drug therapy, Prospective Studies, Neoplasm Staging
Abstract

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.

Published
2022

35. DREAMS: Deep Read-level Error Model for Sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

Author

Christensen, Mikkel H., primary, Drue, Simon, additional, Rasmussen, Mads H., additional, Frydendahl, Amanda, additional, Lyskjær, Iben, additional, Demuth, Christina, additional, Nors, Jesper, additional, Gotschalck, Kåre A., additional, Iversen, Lene H., additional, Andersen, Claus L., additional, and Pedersen, Jakob Skou, additional

Published
2022
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36. A genetically inducible porcine model of intestinal cancer

Author

Callesen, Morten M., Árnadóttir, Sigrid S., Lyskjær, Iben, Ørntoft, Mai‐Britt W., Høyer, Søren, Dagnæs‐Hansen, Frederik, Liu, Ying, Li, Rong, Callesen, Henrik, Rasmussen, Mads H., Berthelsen, Martin F., Thomsen, Martin K., Schweiger, Pawel J., Jensen, Kim B., Laurberg, Søren, Ørntoft, Torben F., Elverløv‐Jakobsen, Jannik E., and Andersen, Claus L.

Published
2017
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38. Tumour-agnostic circulating tumour DNA analysis for improved recurrence surveillance after resection of colorectal liver metastases: A prospective cohort study

Author

Øgaard, Nadia, primary, Reinert, Thomas, additional, Henriksen, Tenna V., additional, Frydendahl, Amanda, additional, Aagaard, Emilie, additional, Ørntoft, Mai-Britt W., additional, Larsen, Marie Ø., additional, Knudsen, Anders R., additional, Mortensen, Frank V., additional, and Andersen, Claus L., additional

Published
2022
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40. Correction: Corrigendum: A DERL3-associated defect in the degradation of SLC2A1 mediates the Warburg effect

Author

Lopez-Serra, Paula, Marcilla, Miguel, Villanueva, Alberto, Ramos-Fernandez, Antonio, Palau, Anna, Leal, Lucía, Wahi, Jessica E., Setien-Baranda, Fernando, Szczesna, Karolina, Moutinho, Catia, Martinez-Cardus, Anna, Heyn, Holger, Sandoval, Juan, Puertas, Sara, Vidal, August, Sanjuan, Xavier, Martinez-Balibrea, Eva, Viñals, Francesc, Perales, Jose C., Bramsem, Jesper B., Ørntoft, Torben F., Andersen, Claus L., Tabernero, Josep, McDermott, Ultan, Boxer, Matthew B., Vander Heiden, Matthew G., Albar, Juan Pablo, and Esteller, Manel

Published
2016
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41. Putative cis-regulatory drivers in colorectal cancer

Author

Ongen, Halit, Andersen, Claus L., Bramsen, Jesper B., Oster, Bodil, Rasmussen, Mads H., Ferreira, Pedro G., Sandoval, Juan, Vidal, Enrique, Whiffin, Nicola, Planchon, Alexandra, Padioleau, Ismael, Bielser, Deborah, Romano, Luciana, Tomlinson, Ian, Houlston, Richard S., Esteller, Manel, Orntoft, Torben F., and Dermitzakis, Emmanouil T.

Subjects
Oncology, Experimental, Gene expression -- Research, Genetic research, Quantitative trait loci -- Identification and classification, Colorectal cancer -- Development and progression -- Genetic aspects, Cancer -- Research, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

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 [...]

Published
2014

43. Abstract 2853: Transposon-activatedPOU5F1Bpromotes colorectal cancer growth and metastasis

Author

Simó-Riudalbas, Laia, primary, Planet, Evarist, additional, Offner, Sandra, additional, Duc, Julien, additional, Abrami, Laurence, additional, Dind, Sagane, additional, Coudray, Alexandre, additional, Coto-Llerena, Mairene, additional, Piscuoglio, Salvatore, additional, Andersen, Claus L., additional, Bramsen, Jesper Bertram, additional, and Trono, Didier, additional

Published
2021
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44. Establishment and characterization of models of chemotherapy resistance in colorectal cancer: Towards a predictive signature of chemoresistance

Author

Jensen, Niels F., Stenvang, Jan, Beck, Mette K., Hanáková, Barbora, Belling, Kirstine C., Do, Khoa N., Viuff, Birgitte, Nygård, Sune B., Gupta, Ramneek, Rasmussen, Mads H., Tarpgaard, Line S., Hansen, Tine P., Budinská, Eva, Pfeiffer, Per, Bosman, Fred, Tejpar, Sabine, Roth, Arnaud, Delorenzi, Mauro, Andersen, Claus L., Rmer, Maria U., Brünner, Nils, and Moreira, José M.A.

Published
2015
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45. Additional file 6 of MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

Author

Mattesen, Trine B., Andersen, Claus L., and Bramsen, Jesper B.

Abstract

Additional file 6: Figure S2. Molecular subtyping with MethCORR inferred RNA expression. a) Scatterplot with correlation between AUC values from a tumor vs normal analysis performed with RNA expression (x-axis) or iRNA expression (y-axis). b) Scatterplot with the first principal component (PC1; X-axis) and the second principal component (PC2; Y-axis) from a PCA performed with (left) RNA expression from TCGA BRCA samples, (middle) iRNA expression calculated in an independent fresh-frozen (GSE84207) cohort, and (right) iRNA expression calculated in an independent FFPE (GSE117439) cohort. Samples are colored according to their estrogen receptor (ER) status. c) Cluster dendrograms from hierarchical boostrap clustering (1000 repetitions) performed with BRCA RNA expression, BRCA iRNA expression, and iRNA expression from the fresh-frozen GSE84207 cohort, and the FFPE GSE117439 cohort. Samples with a “long id name” are ER negative samples. Approximately unbiased p-values (AU) values are given for each cluster node and clusters with AU>0.9 are highlighted by pink rectangles. d+e) Caleydo StratomeX [40] plots showing the concordance between TCGA BRCA microarray based PAM50 subtypes and RNA (d) or iRNA (e) expression based PAM50 subtypes (confidence=1). f) Scatterplot with regression model performance R2 (in independent validation samples) for the 50 genes that constitutes the PAM50 subtype classifier. Top three genes with the highest centroid value is marked for each PAM50 subtype. g) Kaplan–Meier plot showing the overall survival of AJCC stage I-IV patients from the TCGA BRCA cohort stratified according to microarray-based PAM50 subtypes (left panel), RNA-based PAM50 subtypes with confidence call=1 (middle panel), and iRNA-based PAM subtypes with confidence call=1 (right panel). Significance was evaluated by the log-rank test. In parenthesis is provided the Bonferroni-adjusted P values (two comparisons, i.e., LumA vs. HER2 and LumA vs. Basal). h) Consensus cumulative distribution function (CDF) plots for ConsensusClusterPlus analysis performed with (left) iRNA expression and (right) RNA expression for 497 TCGA PRAD tumor samples. The number of clusters, k, is determined where the CDF first approaches maximum [41, 48]. Here, a large increase is seen between k=2 and k=3 and further increases in k does not improve consensus substantially, i.e., k=3 for both iRNA expression and RNA expression. i) Scatterplot with the first principal component (PC1; X-axis) and the third principal component (PC3; Y-axis) from a PCA performed with TCGA PRAD RNA expression, TCGA PRAD iRNA expression, and iRNA expression calculated in an independent prostate cancer FFPE cohort (GSE73549). Samples are colored according to their predicted subtype.

Published
2021
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46. Additional file 7 of MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

Author

Mattesen, Trine B., Andersen, Claus L., and Bramsen, Jesper B.

Subjects
animal structures, endocrine system diseases, skin and connective tissue diseases, female genital diseases and pregnancy complications
Abstract

Additional file 7. Figure S3. Subtype characterization with MethCORR inferred RNA expression. a) Scatterplots showing correlations between normalized enrichment sores (NESs) from a gene set enrichment analysis (GSEA) of the TCGA BRCA HER2-enriched subtype vs. all other BRCA samples, the TCGA BRCA Luminal A subtype vs. all other BRCA samples, the TCGA BRCA Luminal B subtype vs. all other BRCA samples, and the TCGA BRCA Normal-like subtype vs all other BRCA samples performed with RNA expression (x-axis) and iRNA expression (y-axis). b) Scatterplots showing correlations between NESs from a GSEA of the HER2-enriched subtype vs. all other samples, the Luminal A subtype vs. all other samples, the Luminal B subtype vs. all other samples, and the Normal-like subtype vs all other samples performed with iRNA expression in the TCGA BRCA cohort (x-axis) and iRNA expression in the independent breast cancer FFPE cohort (GSE117439; y-axis). c) Kaplan–Meier plots showing the overall survival of all AJCC stage I-IV patients from the TCGA BRCA cohort stratified according to high or low CD8A expression (median cut-off) using either RNA (left panel) or iRNA (right panel). Significance was evaluated by the log-rank test.

Published
2021
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47. Additional file 5 of MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

Author

Mattesen, Trine B., Andersen, Claus L., and Bramsen, Jesper B.

Abstract

Additional file 5: Figure S1. MethCORR inferred RNA expression in ten cancer types. a) Graph showing the inter-sample RNA expression-iRNA expression squared correlations (R2) for BRCA, PRAD, and LUAD validation samples. Genes are ranked according to increasing RNA expression standard deviation in discovery samples. b) Scatterplots with correlations between RNA expression in matched fresh-frozen tissue and FFPE tissue for a representative validation sample from the TCGA BRCA, PRAD, and LUAD cohorts. c) Boxplot with MethCORR and TOBMI [16] validation set 3 inter-sample RNA expression-iRNA expression squared correlations (R2) for overlapping genes between the two methods. Data for all ten cancers are shown. * Wilcoxon rank-sum p

Published
2021
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49. Oncogene-induced senescence is part of the tumorigenesis barrier imposed by DNA damage checkpoints

Author

Bartkova, Jirina, Rezaei, Nousin, Liontos, Michalis, Karakaidos, Panagiotis, Kletsas, Dimitris, Issaeva, Natalia, Vassiliou, Leandros-Vassilios F., Kolettas, Evangelos, Niforou, Katerina, Zoumpourlis, Vassilis C., Takaoka, Munenori, Nakagawa, Hiroshi, Tort, Frederic, Fugger, Kasper, Johansson, Fredrik, Sehested, Maxwell, Andersen, Claus L., Dyrskjot, Lars, Ørntoft, Torben, Lukas, Jiri, Kittas, Christos, Helleday, Thomas, Halazonetis, Thanos D., Bartek, Jiri, and Gorgoulis, Vassilis G.

Published
2006
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50. Enhanced Performance of DNA Methylation Markers by Simultaneous Measurement of Sense and Antisense DNA Strands after Cytosine Conversion

Author

Jensen, Sarah, Øgaard, Nadia, Nielsen, Hans Jørgen, Bramsen, Jesper B., Andersen, Claus L., Jensen, Sarah, Øgaard, Nadia, Nielsen, Hans Jørgen, Bramsen, Jesper B., and Andersen, Claus L.

Abstract

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.

Published
2020

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