BackgroundPancreatic ductal adenocarcinoma (PDAC) is considered as one of the most aggressive cancers lacking efficient early detection biomarkers. Circulating miRNAs are now being considered to have potency to be used as diagnostic and prognostic biomarkers in different diseases as well as cancers. In case of cancer, a fraction of the circulating miRNAs is actually derived from the tumour tissue. This fraction would function as stable biomarker for the disease and also would contribute to the understanding of the disease development. There are not many studies exploring this aspect in pancreatic cancer and even there is not much overlap of results between existing studies.MethodsIn order to address that gap, we performed a miRNA microarray analysis to identify differentially expressed circulating miRNAs between PDAC patients and normal healthy individuals and also found two more similar datasets to perform a meta-analysis using a total of 182 PDAC patients and 170 normal, identifying a set of miRNAs significantly altered in patient serum. Next, we found five datasets studying miRNA expression profile in tumour tissues of PDAC patients as compared to normal pancreas and performed a second meta-analysis using data from a total of 183 pancreatic tumour and 47 normal pancreas to detect significantly deregulated miRNAs in pancreatic carcinoma. Comparison of these two lists and subsequent search for their target genes which were also deregulated in PDAC in inverse direction to miRNAs was done followed by investigation of their role in disease development.ResultsWe identified 21 miRNAs altered in both pancreatic tumour tissue and serum. While deciphering the functions of their target genes, we characterized key miR-Gene interactions perturbing the biological pathways. We identified important cancer related pathways, pancreas specific pathways, AGE-RAGE signaling, prolactin signaling and insulin resistance signaling pathways among the most affected ones. We also reported the possible involvement of crucial transcription factors in the process.ConclusionsOur study identified a unique meta-signature of 21 miRNAs capable of explaining pancreatic carcinogenesis and possibly holding the potential to act as biomarker for the disease detection which could be explored further.
Background Most often, the patients with pancreatic diseases are presented with a mass in pancreatic head region and existing methods of diagnosis fail to confirm whether the head mass is malignant or benign. As subsequent management of the disease hugely depends on the correct diagnosis, we wanted to explore possible biomarkers which could distinguish benign and malignant pancreatic head masses. Methods In order to address that gap, we performed a case–control study to identify genome-wide differentially expressed coding and noncoding genes between pancreatic tissues collected from benign and malignant head masses. These genes were next shortlisted using stringent criteria followed by selection of top malignancy specific genes. They subsequently got validated by quantitative RT-PCR and also in other patient cohorts. Survival analysis and ROC analysis were also performed. Results We identified 55 coding and 13 noncoding genes specific for malignant pancreatic head masses. Further shortlisting and validation, however, resulted in 5 coding genes as part of malignancy specific multi-gene signature, which was validated in three independent patient cohorts of 145 normal and 153 PDAC patients. We also found that overexpression of these genes resulted in survival disadvantage in the patients and ROC analysis identified that combination of 5 coding genes had the AUROC of 0.94, making them potential biomarker. Conclusions Our study identified a multi-gene signature comprising of 5 coding genes (CDCA7, DLGAP5, FOXM1, TPX2 and OSBPL3) to distinguish malignant head masses from benign ones.
Background. Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions of pancreatic ductal adenocarcinoma (PDAC). IPMNs are generally associated with high risk of developing malignancy and therefore need to be diagnosed and assessed accurately, once detected. Existing diagnostic methods are inadequate, and identification of efficient biomarker capable of detecting high-risk IPMNs is necessitated. Moreover, the mechanism of development of malignancy in IPMNs is also elusive. Methods. Gene expression meta-analysis conducted using 12 low-risk IPMN and 23 high-risk IPMN tissue samples. We have also listed all the altered miRNAs and long noncoding RNAs (lncRNAs), identified their target genes, and performed pathway analysis. We further enlisted cyst fluid proteins detected to be altered in high-risk or malignant IPMNs and compared them with fraction of differentially expressed genes secreted into cyst fluid. Results. Our meta-analysis identified 270 upregulated and 161 downregulated genes characteristically altered in high-risk IPMNs. We further identified 61 miRNAs and 14 lncRNAs and their target genes and key pathways contributing towards understanding of the gene regulation during the progression of the disease. Most importantly, we have detected 12 genes altered significantly both in cystic lesions and cyst fluid. Conclusion. Our study reports, for the first time, a meta-analysis identifying key changes in gene expression between low-risk and high-risk IPMNs and also explains the regulatory aspect through construction of a miRNA-lncRNA-mRNA interaction network. The 12-gene-signature could function as potential biomarker in cyst fluid for detection of IPMN with a high risk of developing malignancy.
Author contribution: Bishnupriya Chhatriya generated data, did formal analysis, and drafted the manuscript, reviewed and edited. Piyali Sarkar helped in data generation and data analysis. Srikanta Goswami conceptualized, designed the study, analyzed data, and wrote the manuscript. Sukanta Ray, Debashis Nath, and Kshaunish Das helped in finalizing the study design and drafting the manuscript apart from executing the clinical components of the study. Saroj K Mohapatra contributed to analytic tools, supervised data analysis and provided critical inputs to the manuscript. All authors read and approved the final manuscript, conception, and design or acquisition of data or analysis and interpretation of data. They have also been involved in drafting the manuscript or revising it critically for important intellectual content.
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