Clonal competition with alternating dominance in multiple myeloma.

By J. Keats, M. Chesi, J. Egan, Victoria M Garbitt, Stephen E. Palmer, E. Braggio, S. V. Van Wier, P. Blackburn, A. Baker, A. Dispenzieri and 7 more. Blood, 2012

648 citations recorded by the source corpus.

Subfields: Hematology, Molecular Biology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/ce1de388daf88cf4333cbf34b9f1351940381383

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Hematology

1. S. Rajkumar

In Molecular Biology

1. Nicholas McGranahan
2. Charles Swanton
3. Elaine R. Mardis
4. S. Nik-Zainal
5. Richard K. Wilson
6. D. Hoon
7. Kevin J. Dawson
8. P. van Loo

In Radiology, Nuclear Medicine and Imaging

1. Charles Swanton
2. Nicholas McGranahan

Citations in the corpus

• Analytical and Clinical Validation of a Digital Sequencing Panel for Quantitative, Highly Accurate Evaluation of Cell-Free Circulating Tumor DNA (2015, background): “that the initial biopsy genomics did not reveal the tumor subclone that ultimately drove mortality (secondary plasma cell leukemia) [63].”
• Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy (2014, neutral): “…(e.g., cytogenetics, FISH, and array CGH) have pointed to the existence of clonal heterogeneity in MM, and recent studies using exome sequencing and copy number analyses in a small number of samples similarly documented clonal diversity (Egan et al., 2012; Keats et al., 2012; Walker et al., 2012).”
• SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution (2014, background): “For example, the alternate ‘‘waxing’’ and ‘‘waning’’ of subclonal CNAs has been observed in multiple myeloma [17,33].”
• Intratumor heterogeneity: evolution through space and time. (2012, neutral): “in cytogenetically high-risk multiple myeloma (24).”
• Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. (2015, background): “Interestingly, in a series of 28 patients with MM, those with the highest cytogenetically defined clinical risk harbored disease that was most dynamic during the course of treatment (Keats et al., 2012).”
• Heterogeneity of genomic evolution and mutational profiles in multiple myeloma (2014, positive): “…single nucleotide polymorphism (SNP) arrays on serial samples showed that molecular events necessary for MM progression are not attained in a linear fashion but rather through branching, nonlinear pathways 9,10 , a pattern typical of a complex ecosystem of clones competing for evolution.”
• Cancer heterogeneity: implications for targeted therapeutics (2013, background): “There are intriguing clinical examples of variation in temporal patterns of tumour genomic architectures within multiple myeloma patients, and in some patients a distinct pattern of complex clonal competition was observed (Keats et al, 2012).”