Fig. 1: Integrative comprehensive multi region genomic profiling of primary prostate cancer with synchronous lymph node (LN) metastasis.
We used two targeted DNAseq panels to identify key somatic mutations and copy number alterations (CNA) across 10 patients who passed our custom quality control filtering criteria. For CNA analysis, only the top 445 genes (no. of amplicons per gene > 4 & log10 false discovery rate <0.01 & absolute log2CNvalue > 0.3) with losses and gains are displayed in the heatmap. Unsupervised hierarchical clustering of all tumor regions within each patient was performed to interrogate primary tumor regions that cluster with their respective synchronous LN metastasis regions using log2 normalized data. Genes were ordered by the chromosome number along with their start and end positions within each chromosome. CNA for the known prostate cancer-relevant genes are annotated. ETS gene fusion status was derived from targeted RNAseq data using an in-house fusion quantification pipeline. Relevant clinicopathologic variables such as grade, stage, extraprostatic extension (EPE), seminal vesicle invasion (SVI), lymphovascular invasion (LVI), cribriform pattern, solid pattern, single cells and derived commercially available prognostic scores (mxCCP (derived Cell Cycle Progression score or ProlarisTM), mxGPS (derived Genomic Prostate Score or OncotypeTM), and mxGC (derived Genomic Classifier or DecipherTM) for each sample are annotated on the heatmap. Prognostic scores were categorized into low, mid, and high groups based on their Q1 and Q3 values for comparison among samples with the same patient as well as comparison across different scores within each sample. We observed intra- and inter-patient heterogeneity in histologic grade, genomic alterations, and derived prognostic gene signatures. Source data are provided as a Source Data file.
