Genes identified in prostate tissue. In the association analysis between prostate cancer individuals who developed proctitis (cases) and who didn’t develop proctitis (controls), we found a total of 62 differentially expressed genes to be significantly associated. Based on z-score direction, 28 genes were downregulated, and 34 genes were upregulated in the prostate tissue (Table S1). We mapped the genes to tissue-specific protein-protein interaction (PPI) network to understand combined functional relationship of differentially expressed genes. Integrating PPI information with identified genes, we found an additional 22 genes which interact with 20 genes associated with proctitis based on genetically regulated expression of prostate tissue. Analyzing all the genes in the network for enriched gene ontology of biological processes, molecular functions and cellular components (Fig 1) highlighted protein deubiquitination (ARRB2, TP53, SHMT2, BRCA1, ESR1, NEDD8, MYC), wnt signaling (MOV10, ARRB2, LRRK2, TNIK, ESR1, APP, CUL3) , regulation of apoptosis signaling (ARRB2, TP53, LRRK2, BRCA1, YWHAZ, PTTG1IP), response to radiation (CIRBP, TP53, BRCA1, APP, MYC) and mitochondrial organization & apoptotic mitochondrial changes (ARRB2, TP53, LRRK2, YWHAZ) (Table S2). Specifically, gene ontology categories that included genes identified via SNP-based gene expression were ‘response to radiation’ and ‘regulation of apoptotic signaling pathway’.
Genes identified in whole blood tissue. We found a total of 98 genes to be associated with proctitis in whole blood tissue. 49 genes were upregulated, and 49 genes were downregulated (Table S3). Integrating PPI network information with the significant genes, found an additional 51 intermediate genes that interact with identified genes based on genetically regulated gene expression from whole blood. Investigating all the genes in the network for over-represented biological processes, highlighted DNA repair processes (Fig 2) such as DNA replication (TERF2, EGFR, CDC7, BRCA1, ATRIP, RBBP8, SLX4, ORC1, ORC6, RAD50, CDK2, MCM2, DTL, RPA1, RPA2, RPA3), DNA integrity checkpoint (FBXO6, BRCA1, CDC5L, ATRIP, MDM2, ORC1, FZR1, CDK2, TP53, DTL, RPA2), nucleotide excision repair (COPS6, RBBP8, DDB1, UBC, SLX4, TP53, RPA1, RPA2, RPA3), recombinational repair (CDC7, BRCA1, RBBP8, SLX4, RAD50, RPA1, RPA2, RPA3), detection of DNA damage and response (DDB1,UBC,DTL,RPA1,RPA2,RPA3) and telomeric maintenance (TERF2, CCT5, SLX4, RAD50, TELO2, RPA1, RPA2, RPA3) (Table S4). Thus, integrating PPI information allows for the inference of gene-network as the gene expression changes attributed to genetic variants is limited in identifying all gene members of DNA damage and its related networks.
Replication dataset for transcriptomic findings. In order to replicate our genetically-regulated gene expression genes associated with radiation toxicity-proctitis, we identified the study of van Oorschot et. al, whose data were deposited in gene expression omnibus (GEO). Their study isolated and cultured lymphocytes from individuals who received radiation treatment for their prostate cancer and were assessed for radiotoxicity for a period of 2 years. In their study design they irradiated lymphocytes (collected prior to radiation treatment) with untreated and 2Gy of gamma ray, followed by microarray analysis. We analyzed differential expression of genes between the two irradiated groups. A total of 27 genes overlapped between significant genes identified in replication cohort and significant genes in whole blood tissue (overlapping p-value: 0.00028), and 5 genes overlapped with significant genes in prostate tissue. We further investigated the 27 genes that significantly overlapped with the external cohort for direction of gene expression. We found 14 genes to have concordant direction of expression between both results whereas the remaining 13 genes were discordant. The GSEA analysis of these 14 genes was enriched for Cilium Assembly, DNA repair, Organelle biogenesis and maintenance, CHEK2 PCC Network, Response to Ionizing radiation, TP53 Targets and Damaged DNA binding (Fig 3; Supplementary file – Table S5).
CNV association and GSEA of mapped genes. We found 7 CNV regions associated with proctitis on chromosomes 1, 3, 4, 11, 12 and 15 (Fig 4; Table S6). We identified genes within CNV regions using the UCSC browser (hg19) (Table S7). Interestingly, out of the two regions on chromosome 11 that were significant, we observed a high number of TRIM family genes (chr11:89487937-89909274 bps). The mapped genes from copy number regions were investigated for gene interactions using biobase knowledge of Ingenuity Pathway Analysis®. The pathway with the highest number of query genes (Fig 5) was further analyzed for enriched disease and functional categories (Table S8). Cell-to-cell signaling interaction processes for renal and urological system, connective tissue development and function, and organismal injury were significantly associated processes, and their functional categorization included synthesis, proliferation, apoptosis and transmembrane transport. It is interesting to note, that most of these processes were dominated by TRH and TRIM-family genes. Furthermore, we also observed that the ALG1L2 gene, which was one of the significantly downregulated genes in whole-blood tissue, was also mapped to significant CNV region on chr3:129690192-129896364 bps which observes both gain and loss of copy, referred to as mixed regions.