Expression of Genomic Instability-Related Molecules: Cyclin F, RRM2 and SPDL1 and Their Prognostic Significance in Pancreatic Adenocarcinoma

Abstract

In the present study, we aimed to assess the selected components of cell cycle machinery, checkpoint, DNA repair, and synthesis, namely RRM2, cyclin F, and SPDL1 in pancreatic adenocarcinomas (PAC) by in-house immunohistochemistry (IHC) and bioinformatic analysis of public datasets, in terms of expression, correlation with clinicopathological parameters, and patient survival. Sixty eight patients with pancreatic ductal adenocarcinoma (PDAC) were included in our cohort study, and IHC was performed on tissue macroarrays. RNA-Seq-based transcriptome data for 177 PACs were retrieved from the Cancer Genome Atlas (TCGA). We found cyclin F, RRM2, and SPDL1 to be overexpressed at both protein and mRNA levels in tumor tissues compared to respective controls. Based on TCGA dataset, we have demonstrated that CCNF, RRM2, and SPDL1 are potent independent prognostic markers for poor overall survival, both by themselves and even more in combination with each other. Furthermore, high CCNF mRNA expression was associated with features of cancer progression. By contrast, overexpression of cyclin F or SPDL1 proteins denoted a good prognosis in PDAC patients; however, in the case of the former protein, the results did not reach statistical significance. Specifically, high levels of SPDL1 protein emerged as the most powerful independent prognostic factor associated with a better outcome. If validated, the CCNF/RRM2/SPDL1 three-gene panel developed in this study, as well as SPDL1 protein, may provide significant clinical implications for the prognosis prediction of PAC patients.

Prognostic Significance of KIF11 and KIF14 Expression in Pancreatic Adenocarcinoma

“…Variables of interest included gender, age, pathological T stage (pT), pathological N stage (pN), grading, staging, tumor location, vascular invasion (VI), perineural invasion (PNI), Ki-67 index, and MSH6 status. The primary source of Ki-67 values and MSH6 expression was our previous report [ 9 ]. The outcome of interest was overall survival (OS), which was defined as the time from diagnosis to last follow-up or death.…”

“…Postsurgical survival data were available for 62 patients. The same cohorts of patients and tissue samples have been included in our previous article [ 9 ]; however, the final follow-up was extended to 30 April 2020. The median follow-up time was 1298 days, whereby 52 (83.87%) patients died during follow-up.…”

“…Immunohistochemical staining was done on tissue macroarrays (TMA) constructed from a tumor-rich representative area of the paraffin blocks and the tumor-adjacent histologically normal tissue, as described previously [ 9 ]. Three- to four-micrometer-thin sections of the tissue arrays were dewaxed in xylene, rehydrated through graded alcohol concentrations, and antigen retrieved in either Ventana high-pH CC1 buffer (64 min for KIF11; Roche Diagnostics/Ventana Medical Systems, Tucson, AZ, USA) or Dako high-pH buffer (20 min for KIF14; Dako; Agilent Technologies, Inc., Santa Clara, CA, USA) in the automated PT Link system (Dako; Agilent Technologies).…”

“…Tissue arrays were incubated with a primary rabbit polyclonal anti-KIF11 antibody (1:150, 32 min; PA5-82394, ThermoFisher Scientific, Waltham, MA, USA) or primary rabbit polyclonal anti-KIF14 antibody (1:500, 30 min; HPA038061, Sigma Aldrich, St. Louis, MO, USA). Ki-67 and MSH6 IHC data generated on the same TMA were available from a previous study, and IHC was performed as previously published [ 9 ]. Primary antibodies were visualized using either the UltraView Universal DAB Detection Kit (Roche Diagnostics/Ventana) or the Envision Flex Kit (Dako, Agilent Technologies) followed by color development using 3,3-diaminobenzidine.…”

Identification of a Somatic Mutation-Derived Long Non-Coding RNA Signatures of Genomic Instability in Renal Cell Carcinoma

“…For example, structural changes in proto-oncogenes and tumor suppressor genes may lead to abnormalities in cell functions, including cell growth, cell cycle, cell senescence and apoptosis, cell invasion and metastasis (15)(16)(17)(18). The genomic instabilities of cancer mainly include gene mutation, chromosome rearrangement and aneuploidy (19). Genomic instability has been identified as a key prognostic factor, and it is of great importance to explore its clinical significance.…”