Literature DB >> 33420139

Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning.

Kalifa Manjang1, Shailesh Tripathi1, Olli Yli-Harja2,3,4, Matthias Dehmer5,6,7, Galina Glazko4, Frank Emmert-Streib8,9.   

Abstract

The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.

Entities:  

Year:  2021        PMID: 33420139      PMCID: PMC7794581          DOI: 10.1038/s41598-020-79375-y

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  28 in total

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Review 2.  Gene-expression-based prognostic assays for breast cancer.

Authors:  Chungyeul Kim; Soonmyung Paik
Journal:  Nat Rev Clin Oncol       Date:  2010-05-04       Impact factor: 66.675

Review 3.  Reproducibility in science: improving the standard for basic and preclinical research.

Authors:  C Glenn Begley; John P A Ioannidis
Journal:  Circ Res       Date:  2015-01-02       Impact factor: 17.367

4.  Comparison of variable selection methods for high-dimensional survival data with competing events.

Authors:  Julia Gilhodes; Christophe Zemmour; Soufiane Ajana; Alejandra Martinez; Jean-Pierre Delord; Eve Leconte; Jean-Marie Boher; Thomas Filleron
Journal:  Comput Biol Med       Date:  2017-10-20       Impact factor: 4.589

Review 5.  Using high-throughput transcriptomic data for prognosis: a critical overview and perspectives.

Authors:  Eytan Domany
Journal:  Cancer Res       Date:  2014-09-01       Impact factor: 12.701

6.  Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity.

Authors:  Lao H Saal; Peter Johansson; Karolina Holm; Sofia K Gruvberger-Saal; Qing-Bai She; Matthew Maurer; Susan Koujak; Adolfo A Ferrando; Per Malmström; Lorenzo Memeo; Jorma Isola; Pär-Ola Bendahl; Neal Rosen; Hanina Hibshoosh; Markus Ringnér; Ake Borg; Ramon Parsons
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-23       Impact factor: 11.205

7.  A gene-expression signature as a predictor of survival in breast cancer.

Authors:  Marc J van de Vijver; Yudong D He; Laura J van't Veer; Hongyue Dai; Augustinus A M Hart; Dorien W Voskuil; George J Schreiber; Johannes L Peterse; Chris Roberts; Matthew J Marton; Mark Parrish; Douwe Atsma; Anke Witteveen; Annuska Glas; Leonie Delahaye; Tony van der Velde; Harry Bartelink; Sjoerd Rodenhuis; Emiel T Rutgers; Stephen H Friend; René Bernards
Journal:  N Engl J Med       Date:  2002-12-19       Impact factor: 91.245

8.  Molecular definition of breast tumor heterogeneity.

Authors:  Michail Shipitsin; Lauren L Campbell; Pedram Argani; Stanislawa Weremowicz; Noga Bloushtain-Qimron; Jun Yao; Tatiana Nikolskaya; Tatiana Serebryiskaya; Rameen Beroukhim; Min Hu; Marc K Halushka; Saraswati Sukumar; Leroy M Parker; Karen S Anderson; Lyndsay N Harris; Judy E Garber; Andrea L Richardson; Stuart J Schnitt; Yuri Nikolsky; Rebecca S Gelman; Kornelia Polyak
Journal:  Cancer Cell       Date:  2007-03       Impact factor: 31.743

9.  Gene expression programs in response to hypoxia: cell type specificity and prognostic significance in human cancers.

Authors:  Jen-Tsan Chi; Zhen Wang; Dimitry S A Nuyten; Edwin H Rodriguez; Marci E Schaner; Ali Salim; Yun Wang; Gunnar B Kristensen; Aslaug Helland; Anne-Lise Børresen-Dale; Amato Giaccia; Michael T Longaker; Trevor Hastie; George P Yang; Marc J van de Vijver; Patrick O Brown
Journal:  PLoS Med       Date:  2006-03       Impact factor: 11.069

10.  Effects of sample size on robustness and prediction accuracy of a prognostic gene signature.

Authors:  Seon-Young Kim
Journal:  BMC Bioinformatics       Date:  2009-05-16       Impact factor: 3.169

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  5 in total

1.  Prognostic modeling of predictive maintenance with survival analysis for mobile work equipment.

Authors:  Zhen Yang; Juho Kanniainen; Tomi Krogerus; Frank Emmert-Streib
Journal:  Sci Rep       Date:  2022-05-20       Impact factor: 4.996

2.  ZNF92, an unexplored transcription factor with remarkably distinct breast cancer over-expression associated with prognosis and cell-of-origin.

Authors:  Mohammad Kamran; Udayan Bhattacharya; Mohamed Omar; Luigi Marchionni; Tan A Ince
Journal:  NPJ Breast Cancer       Date:  2022-08-29

3.  Deep View of HCC Gene Expression Signatures and Their Comparison with Other Cancers.

Authors:  Yuquan Qian; Timo Itzel; Matthias Ebert; Andreas Teufel
Journal:  Cancers (Basel)       Date:  2022-09-03       Impact factor: 6.575

4.  Identification of therapeutically potential targets and their ligands for the treatment of OSCC.

Authors:  Pratima Kumari; Sugandh Kumar; Madhusmita Sethy; Shyamlal Bhue; Bineet Kumar Mohanta; Anshuman Dixit
Journal:  Front Oncol       Date:  2022-09-20       Impact factor: 5.738

5.  Prognostic Biomarker-Based Identification of Drugs for Managing the Treatment of Endometrial Cancer.

Authors:  Dilraj Kaur; Chakit Arora; Gajendra Pal Singh Raghava
Journal:  Mol Diagn Ther       Date:  2021-06-22       Impact factor: 4.074

  5 in total

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