Literature DB >> 24270684

Biologic frontiers in multiple myeloma: from biomarker identification to clinical practice.

Ola Landgren1, Gareth J Morgan.   

Abstract

Since the mid-1990s, the multiple myeloma treatment landscape has evolved considerably, which has led to improved patient outcomes and prolonged survival. In addition to discovering new, targeted agents or treatment regimens, the identification and validation of biomarkers has the potential to further improve patient outcomes. The International Staging System relies on a number of biochemical parameters to stratify patients into risk categories. Other biologically relevant markers that are indicative of inherited genetic variation (e.g., single-nucleotide polymorphisms) or tumor-acquired genetic events (e.g., chromosomal translocations or mutations) have been studied for their prognostic potential. In patients with high-risk cytogenetics, plasma cells (PC) undergo genetic shifts over time, which may partially explain why high-risk patients relapse and are so difficult to treat. Although novel agents have improved treatment outcomes, identification of markers that will enable clinicians to determine which treatment is most appropriate for high-risk patients following initial diagnosis represents an exciting frontier in the clinical management of multiple myeloma. Biomarkers based on quantitating PCs or factors that are secreted from them (e.g., serum free light chain) may also help to risk-stratify patients with asymptomatic multiple myeloma. Eventually, identification of novel biomarkers may lead to the creation of personalized treatment regimens that are optimized to target clonal PCs that express a specific oncogenomic profile. Although the future is exciting, validation will be necessary before these biologic and molecular beacons can inform decision-making processes in a routine clinical setting. ©2013 AACR

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Year:  2013        PMID: 24270684      PMCID: PMC5576179          DOI: 10.1158/1078-0432.CCR-13-2159

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  80 in total

1.  t(11;14) and t(4;14) translocations correlated with mature lymphoplasmacytoid and immature morphology, respectively, in multiple myeloma.

Authors:  R Garand; H Avet-Loiseau; F Accard; P Moreau; J L Harousseau; R Bataille
Journal:  Leukemia       Date:  2003-10       Impact factor: 11.528

2.  A gene expression signature for high-risk multiple myeloma.

Authors:  R Kuiper; A Broyl; Y de Knegt; M H van Vliet; E H van Beers; B van der Holt; L el Jarari; G Mulligan; W Gregory; G Morgan; H Goldschmidt; H M Lokhorst; M van Duin; P Sonneveld
Journal:  Leukemia       Date:  2012-05-08       Impact factor: 11.528

3.  A TC classification-based predictor for multiple myeloma using multiplexed real-time quantitative PCR.

Authors:  M F Kaiser; B A Walker; S L Hockley; D B Begum; C P Wardell; D Gonzalez; F M Ross; F E Davies; G J Morgan
Journal:  Leukemia       Date:  2013-01-15       Impact factor: 11.528

Review 4.  Role of microRNAs from monoclonal gammopathy of undetermined significance to multiple myeloma.

Authors:  Katherine R Calvo; Ola Landgren; Aldo M Roccaro; Irene M Ghobrial
Journal:  Semin Hematol       Date:  2011-01       Impact factor: 3.851

5.  Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides.

Authors:  Jan B Egan; Chang-Xin Shi; Waibhav Tembe; Alexis Christoforides; Ahmet Kurdoglu; Shripad Sinari; Sumit Middha; Yan Asmann; Jessica Schmidt; Esteban Braggio; Jonathan J Keats; Rafael Fonseca; P Leif Bergsagel; David W Craig; John D Carpten; A Keith Stewart
Journal:  Blood       Date:  2012-04-23       Impact factor: 22.113

6.  Combining fluorescent in situ hybridization data with ISS staging improves risk assessment in myeloma: an International Myeloma Working Group collaborative project.

Authors:  H Avet-Loiseau; B G M Durie; M Cavo; M Attal; N Gutierrez; J Haessler; H Goldschmidt; R Hajek; J H Lee; O Sezer; B Barlogie; J Crowley; R Fonseca; N Testoni; F Ross; S V Rajkumar; P Sonneveld; J Lahuerta; P Moreau; G Morgan
Journal:  Leukemia       Date:  2012-10-03       Impact factor: 11.528

7.  Inherited variation in the androgen pathway is associated with the efficacy of androgen-deprivation therapy in men with prostate cancer.

Authors:  Robert W Ross; William K Oh; Wanling Xie; Mark Pomerantz; Mari Nakabayashi; Oliver Sartor; Mary-Ellen Taplin; Meredith M Regan; Philip W Kantoff; Matthew Freedman
Journal:  J Clin Oncol       Date:  2008-02-20       Impact factor: 44.544

8.  Criteria for the classification of monoclonal gammopathies, multiple myeloma and related disorders: a report of the International Myeloma Working Group.

Authors: 
Journal:  Br J Haematol       Date:  2003-06       Impact factor: 6.998

9.  A new staging system for multiple myeloma based on the number of S-phase plasma cells.

Authors:  J F San Miguel; R García-Sanz; M González; M J Moro; J M Hernández; F Ortega; D Borrego; M Carnero; F Casanova; R Jiménez
Journal:  Blood       Date:  1995-01-15       Impact factor: 22.113

10.  Frequent engagement of the classical and alternative NF-kappaB pathways by diverse genetic abnormalities in multiple myeloma.

Authors:  Christina M Annunziata; R Eric Davis; Yulia Demchenko; William Bellamy; Ana Gabrea; Fenghuang Zhan; Georg Lenz; Ichiro Hanamura; George Wright; Wenming Xiao; Sandeep Dave; Elaine M Hurt; Bruce Tan; Hong Zhao; Owen Stephens; Madhumita Santra; David R Williams; Lenny Dang; Bart Barlogie; John D Shaughnessy; W Michael Kuehl; Louis M Staudt
Journal:  Cancer Cell       Date:  2007-08       Impact factor: 31.743

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  14 in total

1.  TPL2 kinase regulates the inflammatory milieu of the myeloma niche.

Authors:  Chelsea Hope; Samuel J Ollar; Erika Heninger; Ellen Hebron; Jeffrey L Jensen; Jaehyup Kim; Ioanna Maroulakou; Shigeki Miyamoto; Catherine Leith; David T Yang; Natalie Callander; Peiman Hematti; Marta Chesi; P Leif Bergsagel; Fotis Asimakopoulos
Journal:  Blood       Date:  2014-04-10       Impact factor: 22.113

2.  Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models.

Authors:  Emily A Lanzel; M Paula Gomez Hernandez; Amber M Bates; Christopher N Treinen; Emily E Starman; Carol L Fischer; Deepak Parashar; Janet M Guthmiller; Georgia K Johnson; Taher Abbasi; Shireen Vali; Kim A Brogden
Journal:  Cancer Immunol Immunother       Date:  2016-09-29       Impact factor: 6.968

3.  Long-term survival in multiple myeloma.

Authors:  Cristina João; Carlos Costa; Inês Coelho; Maria João Vergueiro; Mafalda Ferreira; Maria Gomes da Silva
Journal:  Clin Case Rep       Date:  2014-05-28

Review 4.  Utilization of translational bioinformatics to identify novel biomarkers of bortezomib resistance in multiple myeloma.

Authors:  Deanna J Fall; Holly Stessman; Sagar S Patel; Zohar Sachs; Brian G Van Ness; Linda B Baughn; Michael A Linden
Journal:  J Cancer       Date:  2014-09-21       Impact factor: 4.207

5.  Clinicopathological significance of the p16 hypermethylation in multiple myeloma, a systematic review and meta-analysis.

Authors:  Huiqing Yu; Liejun Yang; Yunfeng Fu; Meng Gao; Ling Tian
Journal:  Oncotarget       Date:  2017-06-27

6.  PGC1β regulates multiple myeloma tumor growth through LDHA-mediated glycolytic metabolism.

Authors:  Hongyu Zhang; Ling Li; Qi Chen; Min Li; Jia Feng; Ying Sun; Rong Zhao; Yin Zhu; Yang Lv; Zhigang Zhu; Xiaodong Huang; Weiguo Xie; Wei Xiang; Paul Yao
Journal:  Mol Oncol       Date:  2018-08-14       Impact factor: 6.603

7.  Prognostic or predictive value of circulating cytokines and angiogenic factors for initial treatment of multiple myeloma in the GIMEMA MM0305 randomized controlled trial.

Authors:  Ilaria Saltarella; Fortunato Morabito; Nicola Giuliani; Carolina Terragna; Paola Omedè; Antonio Palumbo; Sara Bringhen; Lorenzo De Paoli; Enrica Martino; Alessandra Larocca; Massimo Offidani; Francesca Patriarca; Chiara Nozzoli; Tommasina Guglielmelli; Giulia Benevolo; Vincenzo Callea; Luca Baldini; Mariella Grasso; Giovanna Leonardi; Manuela Rizzo; Antonietta Pia Falcone; Daniela Gottardi; Vittorio Montefusco; Pellegrino Musto; Maria Teresa Petrucci; Franco Dammacco; Mario Boccadoro; Angelo Vacca; Roberto Ria
Journal:  J Hematol Oncol       Date:  2019-01-09       Impact factor: 17.388

8.  PTTG1 expression is associated with hyperproliferative disease and poor prognosis in multiple myeloma.

Authors:  Jacqueline E Noll; Kate Vandyke; Duncan R Hewett; Krzysztof M Mrozik; Rachel J Bala; Sharon A Williams; Chung H Kok; Andrew Cw Zannettino
Journal:  J Hematol Oncol       Date:  2015-10-06       Impact factor: 17.388

9.  Combined use of free light chain and heavy/light chain ratios allow diagnosis and monitoring of patients with monoclonal gammopathies: Experience of a single institute, with three exemplar case reports.

Authors:  Alfredo Gagliardi; Claudio Carbone; Angela Russo; Rosanna Cuccurullo; Anna Lucania; Paola Della Cioppa; Gabriella Misso; Michele Caraglia; Catello Tommasino; Lucia Mastrullo
Journal:  Oncol Lett       Date:  2016-08-05       Impact factor: 2.967

Review 10.  Potential Clinical Application of Genomics in Multiple Myeloma.

Authors:  Cinnie Yentia Soekojo; Sanjay de Mel; Melissa Ooi; Benedict Yan; Wee Joo Chng
Journal:  Int J Mol Sci       Date:  2018-06-10       Impact factor: 5.923

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