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Kim, Seungchan

https://orcid.org/0000-0003-4183-4338

Mayo Clinic

Translational Genomics Research Institute

Citations 12

Adrenocortical carcinoma survival rates correlated to genomic copy number variants
Stephan, Elizabeth, Chung, Tae‐Hoon , Grant, Clive S., Kim, Seungchan , Hoff, Daniel D. Von , Trent, Jeffrey M. , Demeure, Michael J. , Chung, Tae-Hoon

Molecular Cancer Therapeutics | February 15, 2008 | Volume: 7 | Issue: 2 | Pages: 425-431

10.1158/1535-7163.mct-07-0267 Get It

Abstract Adrenocortical carcinoma (ACC) is a rare endocrine malignancy accounting for between 0.02% and 0.2% of all cancer deaths. Surgical removal offers the only current potential for cure. Unfortunately, ACC has undergone metastatic spread in 40% to 70% of patients at the time of diagnosis. Standard chemotherapy with mitotane is often ineffective with intolerable side effects. The modern molecular technology of comparative genomic hybridization allows the examination of DNA for chromosomal alterations, which can lend biological insight into cancer processes. Genomes of 25 ACC clinical samples were queried on the Agilent 44K Human Genome comparative genomic hybridization array detecting regions of chromosomal gain and loss within the tumor population. Commonly shared amplifications appearing in ≥50% of tumors at P ≤ 10−4 include regions within chromosomes 5, 7, 12, 16q, and 20. Deleted genomic regions within ACC include portions of chromosomes 1, 3p, 10q, 11, 14q, 15q, 17, and 22q. Genomic aberrations in regions associated with differential survival (P ≤ 0.05) and presence in ≥20% of tumors include amplifications of 6q, 7q, 12q, and 19p. Deletions within stratified survival groups include localized regions within 3, 8, 10p, 16q, 17q, and 19q. Statistical analysis of this genetic landscape reveals a set of chromosomal aberrations strongly associated with survival in an accumulation-dependent fashion. These regions may hold prognostic indicators and offer therapeutic targets that can be used to develop novel treatments for aggressive tumors. [Mol Cancer Ther 2008;7(2):425–31]
Molecular Dissection of Hyperdiploid Multiple Myeloma by Gene Expression Profiling
Kumar, Shaji , VanWier, Scott, Ahmann, Greg, Price-Troska, Tammy, Henderson, Kim, Chung, Tae‐Hoon , Kim, Seungchan , Bryant, Barbara M. , Carpten, John D. , Rajkumar, S. Vincent , Lacy, Martha Q. , Dispenzieri, Angela , Kyle, Robert A. , Greipp, Philip R., Bergsagel, P. Leif , Fonseca, Rafaël , Bergsagel, P. Leif , Chng, Wee Joo , Henderson, Kimberly J., Mulligan, George , Gertz, Morie A. , Rajkumar, S Vincent , Dispenzieri, Angela , Chung, Tae-Hoon , Fonseca, Rafael

Cancer Research | April 4, 2007 | Volume: 67 | Issue: 7 | Pages: 2982-2989

10.1158/0008-5472.can-06-4046 Get It

Abstract Hyperdiploid multiple myeloma (H-MM) is the most common form of myeloma. In this gene expression profiling study, we show that H-MM is defined by a protein biosynthesis signature that is primarily driven by a gene dosage mechanism as a result of trisomic chromosomes. Within H-MM, four independently validated patient clusters overexpressing nonoverlapping sets of genes that form cognate pathways/networks that have potential biological importance in multiple myeloma were identified. One prominent cluster, cluster 1, is characterized by high expression of cancer testis antigen and proliferation-associated genes. Tumors from these patients were more proliferative than tumors in other clusters (median plasma cell labeling index, 3.8; P < 0.05). Another cluster, cluster 3, is characterized by genes involved in tumor necrosis factor/nuclear factor-κB signaling and antiapoptosis. These patients have better response to bortezomib as compared with patients within other clusters (70% versus 29%; P = 0.02). Furthermore, for a group of patients generally thought to have better prognosis, a cluster of patients with short survival (cluster 1; median survival, 27 months) could be identified. This analysis illustrates the heterogeneity within H-MM and the importance of defining specific cytogenetic prognostic factors. Furthermore, the signatures that defined these clusters may provide a basis for tailoring treatment to individual patients. [Cancer Res 2007;67(7):2982–9]