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Lars Egevad

Bio: Lars Egevad is an academic researcher from Karolinska Institutet. The author has contributed to research in topics: Prostate cancer & Prostate. The author has an hindex of 69, co-authored 381 publications receiving 22188 citations. Previous affiliations of Lars Egevad include University of Erlangen-Nuremberg & Uppsala University.


Papers
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Journal ArticleDOI
TL;DR: The basis for a new grading system was proposed in 2013 by one of the authors and accepted by the World Health Organization for the 2016 edition of Pathology and Genetics: Tumours of the Urinary System and Male Genital Organs.
Abstract: In November, 2014, 65 prostate cancer pathology experts, along with 17 clinicians including urologists, radiation oncologists, and medical oncologists from 19 different countries gathered in a consensus conference to update the grading of prostate cancer, last revised in 2005. The major conclusions were: (1) Cribriform glands should be assigned a Gleason pattern 4, regardless of morphology; (2) Glomeruloid glands should be assigned a Gleason pattern 4, regardless of morphology; (3) Grading of mucinous carcinoma of the prostate should be based on its underlying growth pattern rather than grading them all as pattern 4; and (4) Intraductal carcinoma of the prostate without invasive carcinoma should not be assigned a Gleason grade and a comment as to its invariable association with aggressive prostate cancer should be made. Regarding morphologies of Gleason patterns, there was clear consensus on: (1) Gleason pattern 4 includes cribriform, fused, and poorly formed glands; (2) The term hypernephromatoid cancer should not be used; (3) For a diagnosis of Gleason pattern 4, it needs to be seen at 10x lens magnification; (4) Occasional/seemingly poorly formed or fused glands between well-formed glands is insufficient for a diagnosis of pattern 4; (5) In cases with borderline morphology between Gleason pattern 3 and pattern 4 and crush artifacts, the lower grade should be favored; (6) Branched glands are allowed in Gleason pattern 3; (7) Small solid cylinders represent Gleason pattern 5; (8) Solid medium to large nests with rosette-like spaces should be considered to represent Gleason pattern 5; and (9) Presence of unequivocal comedonecrosis, even if focal is indicative of Gleason pattern 5. It was recognized by both pathologists and clinicians that despite the above changes, there were deficiencies with the Gleason system. The Gleason grading system ranges from 2 to 10, yet 6 is the lowest score currently assigned. When patients are told that they have a Gleason score 6 out of 10, it implies that their prognosis is intermediate and contributes to their fear of having a more aggressive cancer. Also, in the literature and for therapeutic purposes, various scores have been incorrectly grouped together with the assumption that they have a similar prognosis. For example, many classification systems consider Gleason score 7 as a single score without distinguishing 3+4 versus 4+3, despite studies showing significantly worse prognosis for the latter. The basis for a new grading system was proposed in 2013 by one of the authors (J.I.E.) based on data from Johns Hopkins Hospital resulting in 5 prognostically distinct Grade Groups. This new system was validated in a multi-institutional study of over 20,000 radical prostatectomy specimens, over 16,000 needle biopsy specimens, and over 5,000 biopsies followed by radiation therapy. There was broad (90%) consensus for the adoption of this new prostate cancer Grading system in the 2014 consensus conference based on: (1) the new classification provided more accurate stratification of tumors than the current system; (2) the classification simplified the number of grading categories from Gleason scores 2 to 10, with even more permutations based on different pattern combinations, to Grade Groups 1 to 5; (3) the lowest grade is 1 not 6 as in Gleason, with the potential to reduce overtreatment of indolent cancer; and (4) the current modified Gleason grading, which forms the basis for the new grade groups, bears little resemblance to the original Gleason system. The new grades would, for the foreseeable future, be used in conjunction with the Gleason system [ie. Gleason score 3+3=6 (Grade Group 1)]. The new grading system and the terminology Grade Groups 1-5 have also been accepted by the World Health Organization for the 2016 edition of Pathology and Genetics: Tumours of the Urinary System and Male Genital Organs.

2,153 citations

Journal ArticleDOI
Thomas J. Hudson1, Thomas J. Hudson2, Warwick Anderson3, Axel Aretz4  +270 moreInstitutions (92)
15 Apr 2010
TL;DR: Systematic studies of more than 25,000 cancer genomes will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

2,041 citations

Journal ArticleDOI
TL;DR: It is suggested that prostate tumors can be usefully classified according to their gene expression patterns, and these tumor subtypes may provide a basis for improved prognostication and treatment stratification.
Abstract: Prostate cancer, a leading cause of cancer death, displays a broad range of clinical behavior from relatively indolent to aggressive metastatic disease. To explore potential molecular variation underlying this clinical heterogeneity, we profiled gene expression in 62 primary prostate tumors, as well as 41 normal prostate specimens and nine lymph node metastases, using cDNA microarrays containing ≈26,000 genes. Unsupervised hierarchical clustering readily distinguished tumors from normal samples, and further identified three subclasses of prostate tumors based on distinct patterns of gene expression. High-grade and advanced stage tumors, as well as tumors associated with recurrence, were disproportionately represented among two of the three subtypes, one of which also included most lymph node metastases. To further characterize the clinical relevance of tumor subtypes, we evaluated as surrogate markers two genes differentially expressed among tumor subgroups by using immunohistochemistry on tissue microarrays representing an independent set of 225 prostate tumors. Positive staining for MUC1, a gene highly expressed in the subgroups with “aggressive” clinicopathological features, was associated with an elevated risk of recurrence (P = 0.003), whereas strong staining for AZGP1, a gene highly expressed in the other subgroup, was associated with a decreased risk of recurrence (P = 0.0008). In multivariate analysis, MUC1 and AZGP1 staining were strong predictors of tumor recurrence independent of tumor grade, stage, and preoperative prostate-specific antigen levels. Our results suggest that prostate tumors can be usefully classified according to their gene expression patterns, and these tumor subtypes may provide a basis for improved prognostication and treatment stratification.

1,315 citations

Journal ArticleDOI
TL;DR: Looking at outcomes for prostate cancer treated with radical prostatectomy or radiation therapy and validated a new grading system with more accurate grade stratification than current systems, including a simplified grading system of five grades and the lowest grade is 1, as opposed to 6, with the potential to reduce overtreatment of PCa.

1,062 citations

Journal ArticleDOI
John R. Srigley1, Brett Delahunt2, John N. Eble3, Lars Egevad4, Jonathan I. Epstein5, David J. Grignon3, Ondrej Hes6, Holger Moch7, Rodolfo Montironi, Satish K. Tickoo5, Ming Zhou8, Pedram Argani9, Anila Abraham, Adebowale J. Adeniran, Khalid Ahmed, Hikmat Al Ahmadie, Ferran Algaba, Robert W. Allan, Mahul B. Amin, Ulrika Axcrona, Marc Barry, Dilek Ertoy Baydar, Louis R. Bégin, Daniel M. Berney, Peter Bethwaite, Athanase Billis, Ruth Birbe, Stephen M. Bonsib, David G. Bostwick, Fadi Brimo, Helen P. Cathro, Ying-Bei Chen, Liang Cheng, John C. Cheville, Yong Mee Cho, Ai Ying Chuang, Cynthia Cohen, Henry Crist, Warick Delprado, Fang Ming Deng, Andrew Evans, Oluwole Fadare, Daniel A. Fajardo, Sara M. Falzarano, Samson W. Fine, Stewart Fleming, Eddie Fridman, Bungo Furusato, Masoud Ganji, Masoumeh Ghayouri, Giovanna A. Giannico, Neriman Gokden, David J. Griffiths, Nilesh S. Gupta, Omar Hameed, Michelle S. Hirsch, Jiaoti Huang, Wei Huang, Christina Hulsbergen Van De Kaa, Peter A. Humphrey, Sundus Hussein, Kenneth A. Iczkowski, Rafael E. Jimenez, Edward C. Jones, Laura Irene Jufe, James G. Kench, Masatoshi Kida, Glen Kristiansen, Lakshmi P. Kunju, Zhaoli Lane, Mathieu Latour, Claudio Lewin, Kathrine Lie, Josep Lloreta, Barbara Loftus, Antonio Lopez-Beltran, Fiona Maclean, Cristina Magi-Galluzzi, Guido Martignoni, Teresa McHale, Jesse K. McKenney, Maria Merino, Rose Miller, Hiroshi Miyamoto, Hedwig Murphy, John N. Nacey, Tipu Nazeer, Gabriella Nesi, George J. Netto, Peter W. Nichols, Marie O'Donnell, Semra Olgac, Roberto Orozco, Adeboye O. Osunkoya, Aysim Ozagari, Chin Chen Pan, Anil V. Parwani, Joanna Perry-Keene, Constantina Petraki, Maria M. Picken, Maria Pyda-Karwicka, Victor E. Reuter, Katayoon Rezaei, Nathalie Rioux-Leclercq, Brian D. Robinson, Stephen Rohan, Ruben Ronchetti, Laurie Russell, Hemamali Samaratunga, Marina Scarpelli, Ahmed Shabaik, Rajal B. Shah, Jonathan H Shanks, Steven S. Shen, Maria Shevchuk, Mathilde Sibony, Bhuvana Srinivasan, Martin Susani, Sueli Suzigan, Joan Sweet, Hiroyuki Takahashi, Pheroze Tamboli, Puay Hoon Tan, Isabel Trias, Kiril Trpkov, Larry True, Toyonori Tsuzuki, Funda Vakar-Lopez, Theo H. van der Kwast, Cheng Wang, Anne Y. Warren, Jorge L. Yao, Asli Yilmaz, Jin Zhao, Debra L. Zynger 
TL;DR: The classification working group of the International Society of Urological Pathology consensus conference on renal neoplasia was in charge of making recommendations regarding additions and changes to the current World Health Organization Classification of Renal Tumors, with consensus that 5 entities should be recognized as new distinct epithelial tumors within the classification system.
Abstract: The classification working group of the International Society of Urological Pathology consensus conference on renal neoplasia was in charge of making recommendations regarding additions and changes to the current World Health Organization Classification of Renal Tumors (2004). Members of the group performed an exhaustive literature review, assessed the results of the preconference survey and participated in the consensus conference discussion and polling activities. On the basis of the above inputs, there was consensus that 5 entities should be recognized as new distinct epithelial tumors within the classification system: tubulocystic renal cell carcinoma (RCC), acquired cystic disease-associated RCC, clear cell (tubulo) papillary RCC, the MiT family translocation RCCs (in particular t(6;11) RCC), and hereditary leiomyomatosis RCC syndrome-associated RCC. In addition, there are 3 rare carcinomas that were considered as emerging or provisional new entities: thyroid-like follicular RCC; succinate dehydrogenase B deficiency-associated RCC; and ALK translocation RCC. Further reports of these entities are required to better understand the nature and behavior of these highly unusual tumors. There were a number of new concepts and suggested modifications to the existing World Health Organization 2004 categories. Within the clear cell RCC group, it was agreed upon that multicystic clear cell RCC is best considered as a neoplasm of low malignant potential. There was agreement that subtyping of papillary RCC is of value and that the oncocytic variant of papillary RCC should not be considered as a distinct entity. The hybrid oncocytic chromophobe tumor, which is an indolent tumor that occurs in 3 settings, namely Birt-Hogg-Dube Syndrome, renal oncocytosis, and as a sporadic neoplasm, was placed, for the time being, within the chromophobe RCC category. Recent advances related to collecting duct carcinoma, renal medullary carcinoma, and mucinous spindle cell and tubular RCC were elucidated. Outside of the epithelial category, advances in our understanding of angiomyolipoma, including the epithelioid and epithelial cystic variants, were considered. In addition, the apparent relationship between cystic nephroma and mixed epithelial and stromal tumor was discussed, with the consensus that these tumors form a spectrum of neoplasia. Finally, it was thought that the synovial sarcoma should be removed from the mixed epithelial and mesenchymal category and placed within the sarcoma group. The new classification is to be referred to as the International Society of Urological Pathology Vancouver Classification of Renal Neoplasia.

911 citations


Cited by
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Journal ArticleDOI
TL;DR: The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
Abstract: The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.

11,912 citations

Journal ArticleDOI
TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

10,947 citations

Journal ArticleDOI
Ludmil B. Alexandrov1, Serena Nik-Zainal2, Serena Nik-Zainal3, David C. Wedge1, Samuel Aparicio4, Sam Behjati1, Sam Behjati5, Andrew V. Biankin, Graham R. Bignell1, Niccolo Bolli1, Niccolo Bolli5, Åke Borg2, Anne Lise Børresen-Dale6, Anne Lise Børresen-Dale7, Sandrine Boyault8, Birgit Burkhardt8, Adam Butler1, Carlos Caldas9, Helen Davies1, Christine Desmedt, Roland Eils5, Jorunn E. Eyfjord10, John A. Foekens11, Mel Greaves12, Fumie Hosoda13, Barbara Hutter5, Tomislav Ilicic1, Sandrine Imbeaud14, Sandrine Imbeaud15, Marcin Imielinsk15, Natalie Jäger5, David T. W. Jones16, David T. Jones1, Stian Knappskog11, Stian Knappskog17, Marcel Kool11, Sunil R. Lakhani18, Carlos López-Otín18, Sancha Martin1, Nikhil C. Munshi19, Nikhil C. Munshi20, Hiromi Nakamura13, Paul A. Northcott16, Marina Pajic21, Elli Papaemmanuil1, Angelo Paradiso22, John V. Pearson23, Xose S. Puente18, Keiran Raine1, Manasa Ramakrishna1, Andrea L. Richardson20, Andrea L. Richardson22, Julia Richter22, Philip Rosenstiel22, Matthias Schlesner5, Ton N. Schumacher24, Paul N. Span25, Jon W. Teague1, Yasushi Totoki13, Andrew Tutt24, Rafael Valdés-Mas18, Marit M. van Buuren25, Laura van ’t Veer26, Anne Vincent-Salomon27, Nicola Waddell23, Lucy R. Yates1, Icgc PedBrain24, Jessica Zucman-Rossi15, Jessica Zucman-Rossi14, P. Andrew Futreal1, Ultan McDermott1, Peter Lichter24, Matthew Meyerson20, Matthew Meyerson15, Sean M. Grimmond23, Reiner Siebert22, Elias Campo28, Tatsuhiro Shibata13, Stefan M. Pfister16, Stefan M. Pfister11, Peter J. Campbell29, Peter J. Campbell30, Peter J. Campbell3, Michael R. Stratton3, Michael R. Stratton31 
22 Aug 2013-Nature
TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Abstract: All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

7,904 citations

Journal ArticleDOI
TL;DR: The Perseus software platform was developed to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data and it is anticipated that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
Abstract: A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

5,165 citations

Journal ArticleDOI
TL;DR: This work has examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites, and over one-third of GENCODE protein-Coding genes aresupported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas.
Abstract: The GENCODE Consortium aims to identify all gene features in the human genome using a combination of computational analysis, manual annotation, and experimental validation. Since the first public release of this annotation data set, few new protein-coding loci have been added, yet the number of alternative splicing transcripts annotated has steadily increased. The GENCODE 7 release contains 20,687 protein-coding and 9640 long noncoding RNA loci and has 33,977 coding transcripts not represented in UCSC genes and RefSeq. It also has the most comprehensive annotation of long noncoding RNA (lncRNA) loci publicly available with the predominant transcript form consisting of two exons. We have examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites. Over one-third of GENCODE protein-coding genes are supported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas. New models derived from the Illumina Body Map 2.0 RNA-seq data identify 3689 new loci not currently in GENCODE, of which 3127 consist of two exon models indicating that they are possibly unannotated long noncoding loci. GENCODE 7 is publicly available from gencodegenes.org and via the Ensembl and UCSC Genome Browsers.

4,281 citations