The Potential Role of ER-Associated Degradation Protein DERL3 in Multiple Myeloma

From the Washington University Office of Undergraduate Research Digest (WUURD), Vol. 12, 05-01-2017. Published by the Office of Undergraduate Research. Joy Zalis Kiefer, Director of Undergraduate Research and Associate Dean in the College of Arts & Sciences; Lindsey Paunovich, Editor; Helen Human, Programs Manager and Assistant Dean in the College of Arts and Sciences Mentor: Michael Tomasso

Regional gene repression by DNA double-strand breaks in G1 phase cells

DNA damage responses (DDR) to double-strand breaks (DSBs) alter cellular transcription programs at the genome-wide level. Through processes that are less well understood, DSBs also alter transcriptional responses locally, which may be important for efficient DSB repair. Here, we developed an approach to elucidate th

Supplementary Figure S1 from Progressive Spreading of DNA Methylation in the <i>GSTP1</i> Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer

Supplementary Figure S1 shows the phased methylation by allele of the GSTP1 promoter region classified by density of methylation.</p

Supplementary Figure S3 from Progressive Spreading of DNA Methylation in the <i>GSTP1</i> Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer

Supplementary Figure S3 shows the GSTP1 promoter methylation and its corresponding GSTP1 immunohistochemistry expression for PIA and PIN lesions within an individual patient, and notably the heterogeneity of the PIA lesions.</p

Supplementary Table S2 from Progressive Spreading of DNA Methylation in the <i>GSTP1</i> Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer

Supplementary Table S2 shows the phased methylation of the GSTP1 promoter region across 102 lesions classified by density of methylation.</p

Supplementary Table S3 from Progressive Spreading of DNA Methylation in the <i>GSTP1</i> Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer

Supplementary Table S3 shows the phased methylation of the GSTP1 promoter region across 908 alleles, or clones, classified by density of methylation.</p

Supplementary Table S1 from Progressive Spreading of DNA Methylation in the <i>GSTP1</i> Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer

Supplementary Table S1 shows patient and tumor characteristics from the patients who underwent radical prostatectomies for this study.</p

Supplementary Figure S2 from Progressive Spreading of DNA Methylation in the <i>GSTP1</i> Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer

Supplementary Figure S2 shows the methylation rate by allele of the GSTP1 promoter region for partially methylated PIN alleles and demonstrates a hotspot of methylation around transcription factor binding sites and the transcription start site.</p

A multiple myeloma-specific capture sequencing platform discovers novel translocations and frequent, risk-associated point mutations in IGLL5

Abstract Multiple myeloma (MM) is a disease of copy number variants (CNVs), chromosomal translocations, and single-nucleotide variants (SNVs). To enable integrative studies across these diverse mutation types, we developed a capture-based sequencing platform to detect their occurrence in 465 genes altered in MM and used it to sequence 95 primary tumor-normal pairs to a mean depth of 104×. We detected cases of hyperdiploidy (23%), deletions of 1p (8%), 6q (21%), 8p (17%), 14q (16%), 16q (22%), and 17p (4%), and amplification of 1q (19%). We also detected IGH and MYC translocations near expected frequencies and non-silent SNVs in NRAS (24%), KRAS (21%), FAM46C (17%), TP53 (9%), DIS3 (9%), and BRAF (3%). We discovered frequent mutations in IGLL5 (18%) that were mutually exclusive of RAS mutations and associated with increased risk of disease progression (p = 0.03), suggesting that IGLL5 may be a stratifying biomarker. We identified novel IGLL5/IGH translocations in two samples. We subjected 15 of the pairs to ultra-deep sequencing (1259×) and found that although depth correlated with number of mutations detected (p = 0.001), depth past ~300× added little. The platform provides cost-effective genomic analysis for research and may be useful in individualizing treatment decisions in clinical settings