A bile-based microRNA signature for differentiating malignant from benign pancreaticobiliary disease.

Differentiating between pancreatic ductal adenocarcinoma (PDAC) and cholangiocarcinoma (CCA) is crucial for the appropriate course of treatment, especially with advancements in the role of neoadjuvant chemotherapies for PDAC, compared to CCA. Furthermore, benign pancreaticobiliary diseases can mimic malignant disease, and indeterminate lesions may require repeated investigations to achieve a diagnosis. As bile flows in close proximity to these lesions, we aimed to establish a bile-based microRNA (miRNA) signature to discriminate between malignant and benign pancreaticobiliary diseases. We performed miRNA discovery by global profiling of 800 miRNAs using the NanoString nCounter platform in prospectively collected bile samples from malignant (n = 43) and benign (n = 14) pancreaticobiliary disease. Differentially expressed miRNAs were validated by RT-qPCR and further assessed in an independent validation cohort of bile from malignant (n = 37) and benign (n = 38) pancreaticobiliary disease. MiR-148a-3p was identified as a discriminatory marker that effectively distinguished malignant from benign pancreaticobiliary disease in the discovery cohort (AUC = 0.797 [95% CI 0.68-0.92]), the validation cohort (AUC = 0.772 [95% CI 0.66-0.88]), and in the combined cohorts (AUC = 0.752 [95% CI 0.67-0.84]). We also established a two-miRNA signature (miR-125b-5p and miR-194-5p) that distinguished PDAC from CCA (validation: AUC = 0.815 [95% CI 0.67-0.96]; and combined cohorts: AUC = 0.814 [95% CI 0.70-0.93]). Our research stands as the largest, multicentric, global profiling study of miRNAs in the bile from patients with pancreaticobiliary disease. We demonstrated their potential as clinically useful diagnostic tools for the detection and differentiation of malignant pancreaticobiliary disease. These bile miRNA biomarkers could be developed to complement current approaches for diagnosing pancreaticobiliary cancers.

Circulating MicroRNAs in Small-bowel Neuroendocrine Tumors: A Potential Tool for Diagnosis and Assessment of Effectiveness of Surgical Resection.

OBJECTIVE: To discover serum-based microRNA (miRNA) biomarkers for small-bowel neuroendocrine tumors (SBNET) to help guide clinical decisions. BACKGROUND: MiRNAs are small noncoding RNA molecules implicated in the initiation and progression of many cancers. MiRNAs are remarkably stable in bodily fluids, and can potentially be translated into clinically useful biomarkers. Novel biomarkers are needed in SBNET to determine disease aggressiveness, select patients for treatment, detect early recurrence, and monitor response. METHODS: This study was performed in 3 stages (discovery, validation, and a prospective, longitudinal assessment). Discovery comprised of global profiling of 376 miRNA in sera from SBNET patients (n = 11) versus healthy controls (HCs; n = 3). Up-regulated miRNAs were subsequently validated in additional SBNET (n = 33) and HC sera (n = 14); and then longitudinally after SBNET resection (n = 12), with serial serum sampling (preoperatively day 0; postoperatively at 1 week, 1 month, and 12 months). RESULTS: Four serum miRNAs (miR-125b-5p, -362-5p, -425-5p and -500a-5p) were significantly up-regulated in SBNET (P < 0.05; fold-change >2) based on multiple normalization strategies, and were validated by RT-qPCR. This combination was able to differentiate SBNET from HC with an area under the curve of 0.951. Longitudinal assessment revealed that miR-125b-5p returned towards HC levels at 1 month postoperatively in patients without disease, whereas remaining up-regulated in those with residual disease (RSD). This was also true at 12 months postoperatively. In addition, miR-362-5p appeared up-regulated at 12 months in RSD and recurrent disease (RCD). CONCLUSIONS: Our study represents the largest global profiling of serum miRNAs in SBNET patients, and the first to evaluate ongoing serum miRNA expression changes after surgical resection. Serum miR-125b-5p and miR-362-5p have potential to be used to detect RSD/RCD.

Acquired resistance to oxaliplatin is not directly associated with increased resistance to DNA damage in SK-N-ASrOXALI4000, a newly established oxaliplatin-resistant sub-line of the neuroblastoma cell line SK-N-AS.

The formation of acquired drug resistance is a major reason for the failure of anti-cancer therapies after initial response. Here, we introduce a novel model of acquired oxaliplatin resistance, a sub-line of the non-MYCN-amplified neuroblastoma cell line SK-N-AS that was adapted to growth in the presence of 4000 ng/mL oxaliplatin (SK-N-ASrOXALI4000). SK-N-ASrOXALI4000 cells displayed enhanced chromosomal aberrations compared to SK-N-AS, as indicated by 24-chromosome fluorescence in situ hybridisation. Moreover, SK-N-ASrOXALI4000 cells were resistant not only to oxaliplatin but also to the two other commonly used anti-cancer platinum agents cisplatin and carboplatin. SK-N-ASrOXALI4000 cells exhibited a stable resistance phenotype that was not affected by culturing the cells for 10 weeks in the absence of oxaliplatin. Interestingly, SK-N-ASrOXALI4000 cells showed no cross resistance to gemcitabine and increased sensitivity to doxorubicin and UVC radiation, alternative treatments that like platinum drugs target DNA integrity. Notably, UVC-induced DNA damage is thought to be predominantly repaired by nucleotide excision repair and nucleotide excision repair has been described as the main oxaliplatin-induced DNA damage repair system. SK-N-ASrOXALI4000 cells were also more sensitive to lysis by influenza A virus, a candidate for oncolytic therapy, than SK-N-AS cells. In conclusion, we introduce a novel oxaliplatin resistance model. The oxaliplatin resistance mechanisms in SK-N-ASrOXALI4000 cells appear to be complex and not to directly depend on enhanced DNA repair capacity. Models of oxaliplatin resistance are of particular relevance since research on platinum drugs has so far predominantly focused on cisplatin and carboplatin.

Investigating miRNA-mRNA regulatory networks using crosslinking immunoprecipitation methods for biomarker and target discovery in cancer.

INTRODUCTION: MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the post-transcriptional level. Recently, different experimental approaches, such as RNA Sequencing, crosslinking immunoprecipitation (CLIP) methods and its variations, together with computational approaches have been developed to elucidate the miRNA-mRNA targetome. Areas covered: This report focuses on comparing the different experimental and computational approaches, describing their advantages and disadvantages and providing several examples of preclinical (in vitro and in vivo) and clinical studies that have identified miRNA target genes in various tumour types, including breast, ovary, colorectal and pancreas. Expert commentary: The combination of CLIP methods with bioinformatic analyses is essential to better predict miRNA-mRNA interactions and associate their specific pathways within the extensive regulatory network. Nevertheless, further studies are needed to overcome the difficulties these methods have, in order to find a gold standard method that identifies, without any bias, the regulatory association between miRNAs and their target mRNAs.

Gene of the month: HGF.

Hepatocyte growth factor (HGF) is a multifunctional cytokine with important roles in cell proliferation, survival, motility and morphogenesis. Secreted by cells of mesenchymal origin, HGF is the specific ligand for the tyrosine-kinase receptor c-MET (cellular mesenchymal-epithelial transition), also called MET, which is expressed in different types of epithelial, endothelial and haematopoietic progenitor cells. The HGF/MET axis is involved in several biological processes, such as embryogenesis, organogenesis, adult tissue regeneration (including wound healing and liver regeneration) and carcinogenesis, for both solid and haematological malignancies.(1 2) HGF and its particular interaction with the MET receptor have been extensively investigated in the last decades and remain the focus of numerous clinical trials.(3-8) This short review focuses on HGF structure and function, as well as its roles in liver regeneration and different types of tumours.

Bioinformatic analysis reveals pancreatic cancer molecular subtypes specific to the tumor and the microenvironment.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a dense desmoplastic reaction surrounding malignant epithelial cells. Interaction between the epithelial and stromal compartments is suggested to enhance its aggressive nature. Indeed, therapies targeting the stroma, as well as the tumor cells, may improve survival outcomes for patients. The evaluated study by Moffitt et al. used bioinformatic techniques to separate gene expression patterns of normal tissues from PDAC and stroma in a large cohort of samples. The researchers identified two different subtypes of PDAC ('classical' and 'basal-like') and surrounding stroma ('normal' and 'activated'). The basal-like subtype was associated with worse prognosis and a trend towards better response to adjuvant therapy. Hopefully, the molecular stratification of PDAC will potentially allow more personalized treatment strategies and guide clinical decision making.

Single-cell sequencing in cancer research.

Genome-wide single-cell sequencing investigations have the potential to classify individual cells within a tumor mass. In recent years, various single-cell DNA and RNA quantification techniques have facilitated significant advances in our ability to classify subpopulations of cells within a heterogeneous population. These approaches provide the possibility of unraveling the complex variability in genetic, epigenetic and transcriptional interactions that occur within identical cells in a tumor. This should enhance our knowledge of the underlying biological phenotypes and could have a huge impact in designing more precise anticancer treatments in order to improve outcomes and avoid tumor resistance. In addition, single-cell sequencing analysis has the potential to allow the development of better diagnostic and prognostic biomarkers, and thus aid the delivery of more personalized targeted cancer therapy. Nevertheless, further research is still required to overcome technical, biological and computational problems before clinical application.

microRNAs with prognostic significance in pancreatic ductal adenocarcinoma: A meta-analysis.

BACKGROUND: Reports have described the prognostic relevance of microRNAs (miRNAs) in patients treated for pancreatic ductal adenocarcinoma (PDAC). However, many of these include small numbers of patients. To increase statistical power and improve translation, we performed a systematic review and meta-analysis to determine a pooled conclusion. We examined the impact of miRNAs on overall survival (OS) and disease-free survival (DFS) in PDAC. METHODS: Eligible studies were identified and quality assessed using multiple search strategies (last search December 2014). Data were collected from studies correlating clinical outcomes with dysregulated tumoural or blood miRNAs. Studies were pooled, and combined hazard ratios (HRs) with 95% confidence intervals (CIs) were used to estimate strength of the associations. RESULTS: Twenty studies involving 1525 patients treated for PDAC were included. After correcting for publication bias, OS was significantly shortened in patients with high tumoural miR-21 (adjusted HR = 2.48; 1.96-3.14). This result persisted when only studies adjusting for adjuvant chemotherapy were combined (adjusted HR = 2.72; 1.91-3.89). High miR-21 also predicted reduced DFS (adjusted HR = 3.08; 1.78-5.33). Similarly, we found significant adjusted HRs for poor OS for high miR-155, high miR-203, and low miR-34a; and unadjusted HRs for high miR-222 and high miR-10b. The small number of studies, limited number of miRNAs and paucity of multivariate analyses are the limitations of our study. CONCLUSIONS: This is the first rigorous pooled analysis assessing miRNAs as prognostic biomarkers in PDAC. Tumoural miR-21 overexpression emerged as an important predictor of poor prognosis after PDAC resection independent of other clinicopathologic factors, including adjuvant chemotherapy use.