479 results on '"Lingjærde, Ole Christian"'
Search Results
2. Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease
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Stålberg, Stina Margrethe, Silwal-Pandit, Laxmi, Bastani, Nasser Ezzatkhah, Nebdal, Daniel Johan Hammer, Lingjærde, Ole Christian, Skålhegg, Bjørn Steen, and Kure, Elin Hegland
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- 2024
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3. Deep learning for automated scoring of immunohistochemically stained tumour tissue sections – Validation across tumour types based on patient outcomes
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Bathen, Tone F., Borgen, Elin, Børresen-Dale, Anne-Lise, Engebråten, Olav, Fritzman, Britt, Hartman-Johnsen, Olaf Johan, Garred, Øystein, Geisler, Jürgen, Geitvik, Gry Aarum, Hofvind, Solveig, Kåresen, Rolf, Langerød, Anita, Lingjærde, Ole Christian, Mælandsmo, Gunhild M., Naume, Bjørn, Russnes, Hege G., Sahlberg, Kristine Kleivi, Sauer, Torill, Skjerven, Helle Kristine, Schlichting, Ellen, Sørlie, Therese, Kildal, Wanja, Cyll, Karolina, Kalsnes, Joakim, Islam, Rakibul, Julbø, Frida M., Pradhan, Manohar, Ersvær, Elin, Shepherd, Neil, Vlatkovic, Ljiljana, Tekpli, Xavier, Kristensen, Gunnar B., Askautrud, Hanne A., Hveem, Tarjei S., and Danielsen, Håvard E.
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- 2024
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4. Transcriptomic subtyping of malignant peripheral nerve sheath tumours highlights immune signatures, genomic profiles, patient survival and therapeutic targets
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Høland, Maren, Berg, Kaja C.G., Eilertsen, Ina A., Bjerkehagen, Bodil, Kolberg, Matthias, Boye, Kjetil, Lingjærde, Ole Christian, Guren, Tormod K., Mandahl, Nils, van den Berg, Eva, Palmerini, Emanuela, Smeland, Sigbjørn, Picci, Piero, Mertens, Fredrik, Sveen, Anita, and Lothe, Ragnhild A.
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- 2023
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5. Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk
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Bathen, Tone F, Borgen, Elin, Fritzman, Britt, Garred, Øystein, Geitvik, Gry Aarum, Hofvind, Solveig, Langerød, Anita, Lingjærde, Ole Christian, Mælandsmo, Gunhild Mari, Russnes, Hege G, Skjerven, Helle Kristine, and Sørlie, Therese
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Genetics ,Prevention ,Breast Cancer ,Aging ,Clinical Research ,Cancer ,Aetiology ,Detection ,screening and diagnosis ,2.1 Biological and endogenous factors ,4.1 Discovery and preclinical testing of markers and technologies ,Breast Neoplasms ,Female ,Genetic Predisposition to Disease ,Genotyping Techniques ,Germ-Line Mutation ,Homeodomain Proteins ,Humans ,Middle Aged ,Risk Factors ,NBCS Collaborators ,ABCTB Investigators - Abstract
In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.
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- 2020
6. A Systemic Protein Deviation Score Linked to PD-1+ CD8+ T Cell Expansion That Predicts Overall Survival in Diffuse Large B Cell Lymphoma
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Ask, Eivind Heggernes, Tschan-Plessl, Astrid, Gjerdingen, Thea Johanne, Sætersmoen, Michelle Lu, Hoel, Hanna Julie, Wiiger, Merete Thune, Olweus, Johanna, Wahlin, Björn E., Lingjærde, Ole Christian, Horowitz, Amir, Cashen, Amanda F., Watkins, Marcus, Fehniger, Todd A., Holte, Harald, Kolstad, Arne, and Malmberg, Karl-Johan
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- 2021
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7. Ipilimumab and nivolumab combined with anthracycline-based chemotherapy in metastatic hormone receptor-positive breast cancer: A randomized phase 2b trial
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Andresen, Nikolai Kragøe, Røssevold, Andreas Hagen, Quaghebeur, Claire, Gilje, Bjørnar, Boge, Beate, Gombos, Andrea, Falk, Ragnhild Sørum, Mathiesen, Randi Ruud, Julsrud, Lars, Garred, Oystein, Russnes, Hege Giercksky, Lereim, Ragnhild Reehorst, Chauhan, Sudhir Kumar, Lingjærde, Ole Christian, Dunn, Claire, Naume, Bjorn, Kyte, Jon Amund, Andresen, Nikolai Kragøe, Røssevold, Andreas Hagen, Quaghebeur, Claire, Gilje, Bjørnar, Boge, Beate, Gombos, Andrea, Falk, Ragnhild Sørum, Mathiesen, Randi Ruud, Julsrud, Lars, Garred, Oystein, Russnes, Hege Giercksky, Lereim, Ragnhild Reehorst, Chauhan, Sudhir Kumar, Lingjærde, Ole Christian, Dunn, Claire, Naume, Bjorn, and Kyte, Jon Amund
- Abstract
Background Immune checkpoint inhibitors have shown minimal clinical activity in hormone receptor-positive metastatic breast cancer (HR + mBC). Doxorubicin and low-dose cyclophosphamide are reported to induce immune responses and counter regulatory T cells (Tregs). Here, we report the efficacy and safety of combined programmed cell death protein-1/cytotoxic T-lymphocyte-associated protein 4 blockade concomitant with or after immunomodulatory chemotherapy for HR + mBC. Methods Patients with HR + mBC starting first-/second- line chemotherapy (chemo) were randomized 2:3 to chemotherapy (pegylated liposomal doxorubicin 20 mg/m 2 every second week plus cyclophosphamide 50 mg by mouth/day in every other 2-week cycle) with or without concomitant ipilimumab (ipi; 1 mg/kg every sixth week) and nivolumab (nivo; 240 mg every second week). Patients in the chemo-only arm were offered cross-over to ipi/nivo without chemotherapy. Co-primary endpoints were safety in all patients starting therapy and progression-free survival (PFS) in the per-protocol (PP) population, defined as all patients evaluated for response and receiving at least two treatment cycles. Secondary endpoints included objective response rate, clinical benefit rate, Treg changes during therapy and assessment of programmed death-ligand 1 (PD-L1), mutational burden and immune gene signatures as biomarkers. Results Eighty-two patients were randomized and received immune-chemo (N=49) or chemo-only (N=33), 16 patients continued to the ipi/nivo-only cross-over arm. Median follow-up was 41.4 months. Serious adverse events occurred in 63% in the immune-chemo arm, 39% in the chemo-only arm and 31% in the cross-over-arm. In the PP population (N=78) median PFS in the immune-chemo arm was 5.1 months, compared with 3.6 months in the chemo-only arm, with HR 0.94 (95% CI 0.59 to 1.51). Clinical benefit rates were 55% (26/47) and 48% (15/31) in the immune-chemo and chemo-only arms, respectively. In the cross-over-arm (ipi/nivo-only, SCOPUS: ar.j, info:eu-repo/semantics/published
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- 2024
8. Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypes.
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Sharma, Abhibhav, Debik, Julia, Naume, Bjørn, Ohnstad, Hege Oma, Oslo Breast Cancer Consortium (OSBREAC), Sahlber, Kristine Kleivi, Borgen, Elin, Børresen-Dale, Anne-Lise, Engebråten, Olav, Fritzman, Britt, Garred, Øystein, Geisler, Jürgen, Geitvik, Gry Aarum, Hofvind, Solveig, Kristensen, Vessela N, Kåresen, Rolf, Langerød, Anita, Lingjærde, Ole Christian, Mælandsmo, Gunhild Mari, and Russnes, Hege G
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- 2024
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9. Mutational dynamics and immune evasion in diffuse large B-cell lymphoma explored in a relapse-enriched patient series
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Wise, Jillian F., Nakken, Sigve, Steen, Chloé B., Vodák, Daniel, Trøen, Gunhild, Johannessen, Bjarne, Lingjærde, Ole Christian, Hilden, Vera, Blaker, Yngvild Nuvin, Bai, Baoyan, Aasheim, Lars Birger, Pasanen, Annika, Lorenz, Susanne, Sveen, Anita, Lothe, Ragnhild A., Myklebost, Ola, Leppä, Sirpa, Meza-Zepeda, Leonardo A., Beiske, Klaus, Lawrence, Michael S., Hovig, Eivind, Myklebust, June Helen, Smeland, Erlend B., and Holte, Harald
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- 2020
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10. Ipilimumab and nivolumab combined with anthracycline-based chemotherapy in metastatic hormone receptor-positive breast cancer: a randomized phase 2b trial
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Andresen, Nikolai Kragøe, primary, Røssevold, Andreas Hagen, additional, Quaghebeur, Claire, additional, Gilje, Bjørnar, additional, Boge, Beate, additional, Gombos, Andrea, additional, Falk, Ragnhild Sørum, additional, Mathiesen, Randi R., additional, Julsrud, Lars, additional, Garred, Øystein, additional, Russnes, Hege G., additional, Lereim, Ragnhild Reehorst, additional, Chauhan, Sudhir Kumar, additional, Lingjærde, Ole Christian, additional, Dunn, Claire, additional, Naume, Bjørn, additional, and Kyte, Jon Amund, additional
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- 2024
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11. Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors
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Bjaanæs, Maria Moksnes, Nilsen, Gro, Halvorsen, Ann Rita, Russnes, Hege G., Solberg, Steinar, Jørgensen, Lars, Brustugun, Odd Terje, Lingjærde, Ole Christian, and Helland, Åslaug
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- 2021
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12. REPLY TO PARK ET AL.
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Dean, Katharine R., Krauer, Fabienne, Walløe, Lars, Lingjærde, Ole Christian, Bramanti, Barbara, Stenseth, Nils C., and Schmid, Boris V.
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- 2018
13. Human ectoparasites and the spread of plague in Europe during the Second Pandemic
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Dean, Katharine R., Krauer, Fabienne, Walløe, Lars, Lingjærde, Ole Christian, Bramanti, Barbara, Stenseth, Nils Chr., and Schmid, Boris V.
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- 2018
14. Protein Signature Predicts Response to Neoadjuvant Treatment With Chemotherapy and Bevacizumab in HER2-Negative Breast Cancers
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Haugen, Mads H., Lingjærde, Ole Christian, Hedenfalk, Ingrid, Garred, Øystein, Borgen, Elin, Loman, Niklas, Hatschek, Thomas, Børresen-Dale, Anne-Lise, Naume, Bjørn, Mills, Gordon B., Mælandsmo, Gunhild M., and Engebraaten, Olav
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- 2021
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15. Breast Cancer Molecular Stratification: From Intrinsic Subtypes to Integrative Clusters
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Russnes, Hege G., Lingjærde, Ole Christian, Børresen-Dale, Anne-Lise, and Caldas, Carlos
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- 2017
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16. Implementing precision cancer medicine in the public health services of Norway: the diagnostic infrastructure and a cost estimate
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Ree, Anne Hansen, Russnes, Hege G., Heinrich, Daniel, Dueland, Svein, Boye, Kjetil, Nygaard, Vigdis, Silwal-Pandit, Laxmi, Østrup, Olga, Hovig, Eivind, Nygaard, Vegard, Rødland, Einar A., Nakken, Sigve, Øien, Janne T., Johansen, Christin, Bergheim, Inger R., Skarpeteig, Veronica, Sathermugathevan, Menaka, Sauer, Torill, Lund-Iversen, Marius, Beiske, Klaus, Nasser, Salah, Julsrud, Lars, Reisse, Claudius H., Ruud, Espen A., Flørenes, ViviAnn, Hagene, Kirsten T., Aas, Eline, Lurås, Hilde, Johnsen-Soriano, Siv, Geitvik, Gry A., Lingjærde, Ole Christian, Børresen-Dale, Anne-Lise, Mælandsmo, Gunhild M., and Flatmark, Kjersti
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- 2017
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17. Author Correction: Pan-cancer analysis of homozygous deletions in primary tumours uncovers rare tumour suppressors
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Cheng, Jiqiu, Demeulemeester, Jonas, Wedge, David C., Vollan, Hans Kristian M., Pitt, Jason J., Russnes, Hege G., Pandey, Bina P., Nilsen, Gro, Nord, Silje, Bignell, Graham R., White, Kevin P., Børresen-Dale, Anne-Lise, Campbell, Peter J., Kristensen, Vessela N., Stratton, Michael R., Lingjærde, Ole Christian, Moreau, Yves, and Van Loo, Peter
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- 2019
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18. Gene expression and copy number profiling of follicular lymphoma biopsies from patients treated with first-line rituximab without chemotherapy.
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Leich, E., Brodtkorb, Marianne, Schmidt, T., Altenbuchinger, M., Lingjærde, Ole Christian, Lockmer, S., Holte, H., Nedeva, T., Grieb, T., Sander, B., Sundström, C., Spang, R., Kimby, E., and Rosenwald, A.
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FOLLICULAR lymphoma ,RITUXIMAB ,GENE expression ,CANCER chemotherapy ,LOGISTIC regression analysis - Abstract
The Nordic Lymphoma Study Group has performed two randomized clinical trials with chemotherapy-free first-line treatment (rituximab +/- interferon) in follicular lymphoma (FL), with 73% of patients alive and 38% without any need of chemotherapy after 10.6 years median follow-up. In order to identify predictive markers, that may also serve as therapeutic targets, gene expression- and copy number profiles were obtained from 97 FL patients using whole genome microarrays. Copy number alterations (CNAs) were identified, e.g. by GISTIC. Cox Lasso Regression and Lasso logistic regression were used to determine molecular features predictive of time to next therapy (TTNT). A few molecular changes were associated with TTNT (e.g. increased expression of INPP5B, gains in 12q23/q24), but were not significant after adjusting for multiple testing. Our findings suggest that there are no strong determinants of patient outcome with respect to GE data and CNAs in FL patients treated with a chemotherapy-free regimen (i.e. rituximab +/– interferon). [ABSTRACT FROM AUTHOR]
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- 2023
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19. Table S1 from Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
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Silwal-Pandit, Laxmi, primary, Stålberg, Stina M., primary, Johansson, Henrik J., primary, Mermelekas, Georgios, primary, Lothe, Inger Marie B., primary, Skrede, Martina L., primary, Dalsgaard, Astrid Marie, primary, Nebdal, Daniel J. H., primary, Helland, Åslaug, primary, Lingjærde, Ole Christian, primary, Labori, Knut Jørgen, primary, Skålhegg, Bjørn S., primary, Lehtiö, Janne, primary, and Kure, Elin H., primary
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- 2023
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20. Abstract 5627: Spatial protein profiling by cyclic immunofluorescence to interpret and improve bulk tumor-based predictor of response to chemotherapy with bevacizumab in neoadjuvant breast cancer treatment
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Haugen, Mads Haugland, primary, Kilburn, David, additional, Ma, Hongli, additional, Watson, Cameron, additional, Creason, Allison, additional, Zhang, Dong, additional, Dahle, Maria Aa, additional, Lingjaerde, Ole Christian, additional, Smebye, Marianne L., additional, Garred, Oeystein, additional, Foersund, Mette S., additional, Nguyen, Mai T., additional, Maelandsmo, Gunhild M., additional, Mills, Gordon, additional, and Engebraaten, Olav, additional
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- 2023
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21. Data from Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
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Silwal-Pandit, Laxmi, primary, Stålberg, Stina M., primary, Johansson, Henrik J., primary, Mermelekas, Georgios, primary, Lothe, Inger Marie B., primary, Skrede, Martina L., primary, Dalsgaard, Astrid Marie, primary, Nebdal, Daniel J. H., primary, Helland, Åslaug, primary, Lingjærde, Ole Christian, primary, Labori, Knut Jørgen, primary, Skålhegg, Bjørn S., primary, Lehtiö, Janne, primary, and Kure, Elin H., primary
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- 2023
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22. Abstract 2170: Pre-treatment protein landscape in HER2-negative breast cancer treated with carboplatin in a neoadjuvant chemotherapy setting
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Dahle, Maria Aanesland, primary, Egeland, Eivind Valen, additional, Prasmickaite, Lina, additional, Lingjærde, Ole Christian, additional, Russnes, Hege, additional, Garred, Øystein, additional, Smebye, Marianne L., additional, Skjerven, Helle, additional, Schlichting, Ellen, additional, Naume, Bjørn, additional, Mælandsmo, Gunhild, additional, Engebraaten, Olav, additional, and Haugen, Mads H., additional
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- 2023
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23. Table S5-S9 from Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
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Silwal-Pandit, Laxmi, primary, Stålberg, Stina M., primary, Johansson, Henrik J., primary, Mermelekas, Georgios, primary, Lothe, Inger Marie B., primary, Skrede, Martina L., primary, Dalsgaard, Astrid Marie, primary, Nebdal, Daniel J. H., primary, Helland, Åslaug, primary, Lingjærde, Ole Christian, primary, Labori, Knut Jørgen, primary, Skålhegg, Bjørn S., primary, Lehtiö, Janne, primary, and Kure, Elin H., primary
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- 2023
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24. Table S10A and S10B from Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
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Silwal-Pandit, Laxmi, primary, Stålberg, Stina M., primary, Johansson, Henrik J., primary, Mermelekas, Georgios, primary, Lothe, Inger Marie B., primary, Skrede, Martina L., primary, Dalsgaard, Astrid Marie, primary, Nebdal, Daniel J. H., primary, Helland, Åslaug, primary, Lingjærde, Ole Christian, primary, Labori, Knut Jørgen, primary, Skålhegg, Bjørn S., primary, Lehtiö, Janne, primary, and Kure, Elin H., primary
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- 2023
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25. Figures FS1-FS15 from Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
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Silwal-Pandit, Laxmi, primary, Stålberg, Stina M., primary, Johansson, Henrik J., primary, Mermelekas, Georgios, primary, Lothe, Inger Marie B., primary, Skrede, Martina L., primary, Dalsgaard, Astrid Marie, primary, Nebdal, Daniel J. H., primary, Helland, Åslaug, primary, Lingjærde, Ole Christian, primary, Labori, Knut Jørgen, primary, Skålhegg, Bjørn S., primary, Lehtiö, Janne, primary, and Kure, Elin H., primary
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- 2023
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26. Supplementary Methods SM1 from Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
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Silwal-Pandit, Laxmi, primary, Stålberg, Stina M., primary, Johansson, Henrik J., primary, Mermelekas, Georgios, primary, Lothe, Inger Marie B., primary, Skrede, Martina L., primary, Dalsgaard, Astrid Marie, primary, Nebdal, Daniel J. H., primary, Helland, Åslaug, primary, Lingjærde, Ole Christian, primary, Labori, Knut Jørgen, primary, Skålhegg, Bjørn S., primary, Lehtiö, Janne, primary, and Kure, Elin H., primary
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- 2023
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27. Supplementary Figure S3. The figure shows CNA profile of three IPMN samples. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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28. Supplementary Figure S5. Frequency plot of the CNAs of periampullary adenocarcinomas based on site of origin. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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29. Supplementary Table S1: Frequencies of gains and losses for selected genes in both OUH and TCGA cohorts. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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30. Supplementary Figure S1. Heatmap shows the cytobands amplified and deleted in OUH and TCGA cohort. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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31. Supplementary Tables from The Longitudinal Transcriptional Response to Neoadjuvant Chemotherapy with and without Bevacizumab in Breast Cancer
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Silwal-Pandit, Laxmi, primary, Nord, Silje, primary, von der Lippe Gythfeldt, Hedda, primary, Møller, Elen K., primary, Fleischer, Thomas, primary, Rødland, Einar, primary, Krohn, Marit, primary, Borgen, Elin, primary, Garred, Øystein, primary, Olsen, Tone, primary, Vu, Phuong, primary, Skjerven, Helle, primary, Fangberget, Anne, primary, Holmen, Marit M., primary, Schlitchting, Ellen, primary, Wille, Elisabeth, primary, Nordberg Stokke, Mette, primary, Moen Vollan, Hans Kristian, primary, Kristensen, Vessela, primary, Langerød, Anita, primary, Lundgren, Steinar, primary, Wist, Erik, primary, Naume, Bjørn, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, and Engebraaten, Olav, primary
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- 2023
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32. Supplementary table S1 from T Cells Expressing Checkpoint Receptor TIGIT Are Enriched in Follicular Lymphoma Tumors and Characterized by Reversible Suppression of T-cell Receptor Signaling
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Josefsson, Sarah E., primary, Huse, Kanutte, primary, Kolstad, Arne, primary, Beiske, Klaus, primary, Pende, Daniela, primary, Steen, Chloé B., primary, Inderberg, Else Marit, primary, Lingjærde, Ole Christian, primary, Østenstad, Bjørn, primary, Smeland, Erlend B., primary, Levy, Ronald, primary, Irish, Jonathan M., primary, and Myklebust, June H., primary
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- 2023
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33. Supplementary methods and references, Supplementary Figures 1-9 from T Cells Expressing Checkpoint Receptor TIGIT Are Enriched in Follicular Lymphoma Tumors and Characterized by Reversible Suppression of T-cell Receptor Signaling
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Josefsson, Sarah E., primary, Huse, Kanutte, primary, Kolstad, Arne, primary, Beiske, Klaus, primary, Pende, Daniela, primary, Steen, Chloé B., primary, Inderberg, Else Marit, primary, Lingjærde, Ole Christian, primary, Østenstad, Bjørn, primary, Smeland, Erlend B., primary, Levy, Ronald, primary, Irish, Jonathan M., primary, and Myklebust, June H., primary
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- 2023
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34. Supplementary Figure S2. CNA profile of the two xenografts cell lines and their original tumors. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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35. Data from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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36. Supplementary Table S3: Table shows the pathway deregulated in OUH and TCGA cohort. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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37. Supplementary Figure S4. Correlation between genome instability index (GII) and ploidy. from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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- 2023
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38. Supplementary figures 1-9 from T Cells Expressing Checkpoint Receptor TIGIT Are Enriched in Follicular Lymphoma Tumors and Characterized by Reversible Suppression of T-cell Receptor Signaling
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Josefsson, Sarah E., primary, Huse, Kanutte, primary, Kolstad, Arne, primary, Beiske, Klaus, primary, Pende, Daniela, primary, Steen, Chloé B., primary, Inderberg, Else Marit, primary, Lingjærde, Ole Christian, primary, Østenstad, Bjørn, primary, Smeland, Erlend B., primary, Levy, Ronald, primary, Irish, Jonathan M., primary, and Myklebust, June H., primary
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39. Supplementary file: Legends of supplementary material from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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40. Supplementary Table S2: Table shows the correlation score (r) between allele frequency and gene expression from The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma
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Sandhu, Vandana, primary, Wedge, David C., primary, Bowitz Lothe, Inger Marie, primary, Labori, Knut Jørgen, primary, Dentro, Stefan C., primary, Buanes, Trond, primary, Skrede, Martina L., primary, Dalsgaard, Astrid M., primary, Munthe, Else, primary, Myklebost, Ola, primary, Lingjærde, Ole Christian, primary, Børresen-Dale, Anne-Lise, primary, Ikdahl, Tone, primary, Van Loo, Peter, primary, Nord, Silje, primary, and Kure, Elin H., primary
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41. PathTracer: High-sensitivity detection of differential pathway activity in tumours
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Nygård, Ståle, Lingjærde, Ole Christian, Caldas, Carlos, Hovig, Eivind, Børresen-Dale, Anne-Lise, Helland, Åslaug, and Haakensen, Vilde D.
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- 2019
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42. Breast cancer quantitative proteome and proteogenomic landscape
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Johansson, Henrik J., Socciarelli, Fabio, Vacanti, Nathaniel M., Haugen, Mads H., Zhu, Yafeng, Siavelis, Ioannis, Fernandez-Woodbridge, Alejandro, Aure, Miriam R., Sennblad, Bengt, Vesterlund, Mattias, Branca, Rui M., Orre, Lukas M., Huss, Mikael, Fredlund, Erik, Beraki, Elsa, Garred, Øystein, Boekel, Jorrit, Sauer, Torill, Zhao, Wei, Nord, Silje, Höglander, Elen K., Jans, Daniel C., Brismar, Hjalmar, Haukaas, Tonje H., Bathen, Tone F., Schlichting, Ellen, Naume, Bjørn, Consortia Oslo Breast Cancer Research Consortium (OSBREAC), Luders, Torben, Borgen, Elin, Kristensen, Vessela N., Russnes, Hege G., Lingjærde, Ole Christian, Mills, Gordon B., Sahlberg, Kristine K., Børresen-Dale, Anne-Lise, and Lehtiö, Janne
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- 2019
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43. Author Correction: Pan-cancer analysis of homozygous deletions in primary tumours uncovers rare tumour suppressors
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Cheng, Jiqiu, Demeulemeester, Jonas, Wedge, David C., Vollan, Hans Kristian M., Pitt, Jason J., Russnes, Hege G., Pandey, Bina P., Nilsen, Gro, Nord, Silje, Bignell, Graham R., White, Kevin P., Børresen-Dale, Anne-Lise, Campbell, Peter J., Kristensen, Vessela N., Stratton, Michael R., Lingjærde, Ole Christian, Moreau, Yves, and Van Loo, Peter
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- 2018
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44. Time series analysis of neoadjuvant chemotherapy and bevacizumab-treated breast carcinomas reveals a systemic shift in genomic aberrations
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Höglander, Elen Kristine, Nord, Silje, Wedge, David C., Lingjærde, Ole Christian, Silwal-Pandit, Laxmi, Gythfeldt, Hedda vdL, Vollan, Hans Kristian Moen, Fleischer, Thomas, Krohn, Marit, Schlitchting, Ellen, Borgen, Elin, Garred, Øystein, Holmen, Marit M., Wist, Erik, Naume, Bjørn, Van Loo, Peter, Børresen-Dale, Anne-Lise, Engebraaten, Olav, and Kristensen, Vessela
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- 2018
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45. A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns
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Jiao, Wei, Atwal, Gurnit, Polak, Paz, Karlic, Rosa, Cuppen, Edwin, Al-Shahrour, Fatima, Bailey, Peter J, Biankin, Andrew V, Boutros, Paul C, Campbell, Peter J, Chang, David K, Cooke, Susanna L, Deshpande, Vikram, Faltas, Bishoy M, Faquin, William C, Garraway, Levi, Getz, Gad, Grimmond, Sean M, Haider, Syed, Hoadley, Katherine A, Kaiser, Vera B, Kato, Mamoru, Kübler, Kirsten, Lazar, Alexander J, Li, Constance H, Louis, David N, Margolin, Adam, Martin, Sancha, Nahal-Bose, Hardeep K, Nielsen, G Petur, Nik-Zainal, Serena, Omberg, Larsson, P’ng, Christine, Perry, Marc D, Rheinbay, Esther, Rubin, Mark A, Semple, Colin A, Sgroi, Dennis C, Shibata, Tatsuhiro, Siebert, Reiner, Smith, Jaclyn, Stein, Lincoln D, Stobbe, Miranda D, Sun, Ren X, Thai, Kevin, Wright, Derek W, Wu, Chin-Lee, Yuan, Ke, Zhang, Junjun, Danyi, Alexandra, de Ridder, Jeroen, van Herpen, Carla, Lolkema, Martijn P, Steeghs, Neeltje, Morris, Quaid D, Aaltonen, Lauri A, Abascal, Federico, Abeshouse, Adam, Aburatani, Hiroyuki, Adams, David J, Agrawal, Nishant, Ahn, Keun Soo, Ahn, Sung-Min, Aikata, Hiroshi, Akbani, Rehan, Akdemir, Kadir C, Al-Ahmadie, Hikmat, Al-Sedairy, Sultan T, Alawi, Malik, Albert, Monique, Aldape, Kenneth, Alexandrov, Ludmil B, Ally, Adrian, Alsop, Kathryn, Alvarez, Eva G, Amary, Fernanda, Amin, Samirkumar B, Aminou, Brice, Ammerpohl, Ole, Anderson, Matthew J, Ang, Yeng, Antonello, Davide, Anur, Pavana, Aparicio, Samuel, Appelbaum, Elizabeth L, Arai, Yasuhito, Aretz, Axel, Arihiro, Koji, Ariizumi, Shun-ichi, Armenia, Joshua, Arnould, Laurent, Asa, Sylvia, Assenov, Yassen, Aukema, Sietse, Auman, J Todd, Aure, Miriam RR, Awadalla, Philip, Aymerich, Marta, Bader, Gary D, Baez-Ortega, Adrian, Bailey, Matthew H, Balasundaram, Miruna, Balu, Saianand, Bandopadhayay, Pratiti, Banks, Rosamonde E, Barbi, Stefano, Barbour, Andrew P, Barenboim, Jonathan, Barnholtz-Sloan, Jill, Barr, Hugh, Barrera, Elisabet, Bartlett, John, Bartolome, Javier, Bassi, Claudio, Bathe, Oliver F, Baumhoer, Daniel, Bavi, 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Broaddus, Russell R, Brock, Jane E, Brock, Malcolm, Broeks, Annegien, Brooks, Angela N, Brooks, Denise, Brors, Benedikt, Brunak, Søren, Bruxner, Timothy JC, Bruzos, Alicia L, Buchanan, Alex, Buchhalter, Ivo, Buchholz, Christiane, Bullman, Susan, Burke, Hazel, Burkhardt, Birgit, Burns, Kathleen H, Busanovich, John, Bustamante, Carlos D, Butler, Adam P, Butte, Atul J, Byrne, Niall J, Børresen-Dale, Anne-Lise, Caesar-Johnson, Samantha J, Cafferkey, Andy, Cahill, Declan, Calabrese, Claudia, Caldas, Carlos, Calvo, Fabien, Camacho, Niedzica, Campo, Elias, Cantù, Cinzia, Cao, Shaolong, Carey, Thomas E, Carlevaro-Fita, Joana, Carlsen, Rebecca, Cataldo, Ivana, Cazzola, Mario, Cebon, Jonathan, Cerfolio, Robert, Chadwick, Dianne E, Chakravarty, Dimple, Chalmers, Don, Chan, Calvin Wing Yiu, Chan, Kin, Chan-Seng-Yue, Michelle, Chandan, Vishal S, Chanock, Stephen J, Chantrill, Lorraine A, Chateigner, Aurélien, Chatterjee, Nilanjan, Chayama, Kazuaki, Chen, Hsiao-Wei, Chen, Jieming, Chen, Ken, Chen, 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Deurzen, Carolien HM, van de Vijver, Marc J, Veer, L van’t, and von Mering, Christian
- Subjects
Human Biology & Physiology ,Ecology,Evolution & Ethology ,Tumour Biology ,Genetics & Genomics ,Structural Biology & Biophysics ,Computational & Systems Biology - Abstract
In cancer, the primary tumour’s organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA.
- Published
- 2023
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46. Combined burden and functional impact tests for cancer driver discovery using DriverPower
- Author
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- Subjects
Human Biology & Physiology ,Ecology,Evolution & Ethology ,Tumour Biology ,Genetics & Genomics ,Structural Biology & Biophysics ,Computational & Systems Biology - Abstract
The discovery of driver mutations is one of the key motivations for cancer genome sequencing. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we describe DriverPower, a software package that uses mutational burden and functional impact evidence to identify driver mutations in coding and non-coding sites within cancer whole genomes. Using a total of 1373 genomic features derived from public sources, DriverPower’s background mutation model explains up to 93% of the regional variance in the mutation rate across multiple tumour types. By incorporating functional impact scores, we are able to further increase the accuracy of driver discovery. Testing across a collection of 2583 cancer genomes from the PCAWG project, DriverPower identifies 217 coding and 95 non-coding driver candidates. Comparing to six published methods used by the PCAWG Drivers and Functional Interpretation Working Group, DriverPower has the highest F1 score for both coding and non-coding driver discovery. This demonstrates that DriverPower is an effective framework for computational driver discovery.
- Published
- 2023
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47. Integrative pathway enrichment analysis of multivariate omics data
- Author
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Vijver, Marc J, and Veer, L van’t
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Human Biology & Physiology ,Ecology,Evolution & Ethology ,Tumour Biology ,Genetics & Genomics ,Structural Biology & Biophysics ,Computational & Systems Biology - Abstract
Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.
- Published
- 2023
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48. Pathway and network analysis of more than 2500 whole cancer genomes
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Human Biology & Physiology ,Ecology,Evolution & Ethology ,Tumour Biology ,Genetics & Genomics ,Structural Biology & Biophysics ,Computational & Systems Biology - Abstract
The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
- Published
- 2023
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49. Divergent mutational processes distinguish hypoxic and normoxic tumours
- Author
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Human Biology & Physiology ,Ecology,Evolution & Ethology ,Tumour Biology ,Genetics & Genomics ,Structural Biology & Biophysics ,Computational & Systems Biology - Abstract
Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer.
- Published
- 2023
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50. Genomic footprints of activated telomere maintenance mechanisms in cancer
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Christian
- Subjects
Human Biology & Physiology ,Ecology,Evolution & Ethology ,Tumour Biology ,Genetics & Genomics ,Structural Biology & Biophysics ,Computational & Systems Biology - Abstract
Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.
- Published
- 2023
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