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Pancreatic cancer prognosis is predicted by chromatin accessibility (Quantseq)

ABSTRACT: About 50% of resected pancreatic ductal adenocarcinoma (PDAC) recur within just one year following surgery. Prognostic molecular markers predicting rapid recurrence are currently unavailable. We hypothesized that epigenetic differences at the level of chromatin accessibility, potentially linked to distinct differentiation states, might distinguish rapidly recurrent from non-recurrent tumors. Therefore, we interrogated genome-wide chromatin accessibility using Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) on EpCAM+ PDAC malignant cells sorted from a cohort of 54 treatment-naïve resected tumors, in hopes of defining a tumor-intrinsic chromatin signature associated with recurrence. We discovered a signature of ~1000 loci that were differentially accessible between recurrent (disease free survival (DFS) < 1 year) and non-recurrent patients (DFS > 1 year). Through transcription factor (TF) binding motif analysis using supervised learning, we identified candidate TFs whose accessible motifs were differentially associated with recurrence. Nuclear localization of two such TFs as selected by top hits, ZKSCAN1 and HNF1b, were assessed by both immunohistochemistry and immunofluorescence on the tissue microarrays (TMA) of 40 out of 54 patients. Nuclear staining of HNF1b was strong in the non-recurrent and weak or absent in the recurrent patients but ZKSCAN1 was not significantly associated with recurrence. In an independent TMA of PDAC cohort (n=97) preselected for 52 long (OS 6 years)- and 45 short (OS 6 months)- term survivors, the number of nuclear positive cells for HNF1b was 52-fold higher in the long-term compared to the short-term survivors and that for ZKSCAN1 was 5.3-fold higher in the short-term compared to the long-term survivors. Altogether, these results provide novel prognostic molecular markers of early recurrence in PDAC and also suggest that the global epigenetic landscape is a prognostic feature in this disease.

ORGANISM(S): Homo sapiens

PROVIDER: GSE124230 | GEO | 2021/03/30

REPOSITORIES: GEO

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Project description:Purpose: The goals of this study are to delineate genes when comparing long-term (LT) and short-term (ST) PDAC survivors, and to exploit the merits of extensive integrative individual- and group-based transcriptome profiling. Method: Using a discovery cohort of 19 PDAC patients, we first performed differential gene expression (DGE) analysis comparing LT to ST PDAC groups. Second, we adopted unsupervised systems biology approaches to obtain meaningful gene modules showing associations to clinical features. Third, we created individual-level gene expression perturbation profiles and identified key regulators across the perturbed profiles of LT patients at the pathway and motif level. Furthermore, we applied two network context gene prioritization approaches for the depiction of PDAC specific regulatory genes. In particular, we used the random walk-based DADA method to develop PDAC disease modules considering the use of PDAC seed genes (via prior biological knowledge). As an alternative, we used NetICS to prioritize PDAC survival associated genes, by integrating information regarding group-based and individual-specific perturbed genes. Result: DGE analysis resulted in differences in the expression of genes involved in immune responses, cell cycle and metabolic pathways. Validation of a selection of DGEs in the molecular lab suggested a role of REG4 and TSPAN8 in PDAC survival. Detailed inspection of individual-specific omics changes across LT survivors revealed biological signatures associated with focal adhesion and extracellular matrix (ECM) receptors, commonly perturbed in at least 2 out of 9 LT survivors, implying a potential role in molecular-level heterogeneity of LT PDAC survivors. Network centric approaches such as NetICS (integrating group-based and individual-specific perturbed genes) and DADA (degree-aware disease gene prioritizing), identified various known oncogenes such as CUL1, SCF62, EGF, FOSL1, MMP9, and TGFB1. In addition, we identified TAC1, KCNH7, IRS4, DKK4, further warranting detailed follow-up investigations. Conclusion:Our proposed analytic workflow, combining clinical and omics data, and individual-level and group-level transcriptome profiling, highlighted transcriptome marks of PDAC long-term survival heterogeneity. The identified genes open up avenues towards better understanding the mechanisms underlying PDAC survival extension.

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Pancreatic cancer prognosis is predicted by chromatin accessibility (Quantseq)

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