MOESM2 of Residual tissue repositories as a resource for population-based cancer proteomic studies

Additional file 2: Table S2.  TMT labeling scheme for phosphoproteomics

MOESM1 of Residual tissue repositories as a resource for population-based cancer proteomic studies

Additional file 1: Table S1.  TMT labeling scheme for expression proteomics

MOESM4 of Residual tissue repositories as a resource for population-based cancer proteomic studies

Additional file 4: Table S4.  Table of specimen age and RTR

MOESM6 of Residual tissue repositories as a resource for population-based cancer proteomic studies

Additional file 6.  Supplementary figures

MOESM7 of Residual tissue repositories as a resource for population-based cancer proteomic studies

Additional file 7: Table S6. Significantly affected GO terms

MOESM5 of Residual tissue repositories as a resource for population-based cancer proteomic studies

Additional file 5: Table S5.  Identified peptides, proteins, and phosphopeptides

Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis

<div><p>Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the <i>PTEN</i> tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (<i>AR</i>) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an <i>in silico</i> down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.</p></div

Genomic instability and CNVs in mCRPC patient CTCs.

<p>(A) Box-whisker plot of LST scores for patient CTCs. High LST scores were observed in 5/7 (71%) patients. (B) Dot plot of log2 normalized DNA copy number in <i>AR</i>. Amplification of the <i>AR</i> gene was observed in 5/7 (71%) patients. (C) Dot plot of AR N-Terminal protein expression status in each single CTC as detected by IF, 5/7 (71%) patients had amplified AR protein, where AR amplification is observed in both CK positive and CK negative CTCs. (D) Box-whisker plot of AR N-Terminal protein expression in AR copy number gain and copy number neutral CTCs. Higher AR protein expression was observed in the <i>AR</i> copy number gain group, <i>p =</i> 0.0025 by Student’s t-test. (E) Dot plot of log2 normalized DNA copy number in <i>PTEN</i>. Loss of <i>PTEN</i> was observed in 5/7 (71%) patients. In each figure, one dot represents a single CTC.</p

Prostate cancer cell line single cell CNV profiles, genomic instability scores and AR, PTEN copy number status.

<p>Whole genome copy number plots from prostate cancer cell lines (A) LNCaP, (B) PC3, and (C) VCaP, and (D) WBC controls. (E) Absolute Pearson correlation values (0–100%) were calculated across samples and viewed using Circos Table Viewer (<a href="http://circos.ca/presentations/articles/vis_tables1/" target="_blank">http://circos.ca/presentations/articles/vis_tables1/</a>). For visualization purposes, the top 25% highest correlations are displayed. Each color-coded segment represents a cell line replicate. Correlations between replicates are denoted by links or ribbons, the width of which is proportional to the degree of correlation. Much higher correlations were observed in intra-cell line comparisons than inter-cell line comparisons, indicating that the assay has good reproducibility regardless of cell line used. (F) Box-whisker plot of LST scores for prostate cancer cell lines and WBCs. All 3 cell lines had high LST scores compared to the WBCs, with PC3 and VCaP having the highest scores. (G) Box-whisker plot of log2 normalized DNA copy number in <i>AR</i>. Amplification of the <i>AR</i> gene was observed in the VCaP single cells reproducibly (5/5, 100%). This amplification was not observed in PC3 (0/7), LNCaP (0/8), or WBC controls (0/3). (H) Box-whisker plot of log2 normalized DNA copy number in <i>PTEN</i>. The VCaP cell line has non-deleted <i>PTEN</i> (0/5, 0%), while <i>PTEN</i> loss was detected in PC3 (6/7, 86%), LNCaP (1/8, 13%), and 1/3 WBC controls (1/3, 33%).</p

Epic Sciences single cell NGS-based CNV analysis pipeline.

<p>FASTQ files were aligned to hg38 human reference genome from UCSC using BWA. BAM files with a MAPQ quality score greater than 30 were kept for further analysis with two separate pipelines: analysis pipeline 1 for genomic instabilities estimation using 1M bp window; analysis pipeline 2 for determining copy number alterations of individual genes.</p