Plasma circulating tumor DNA in pancreatic adenocarcinoma for screening, diagnosis, prognosis, treatment and follow-up: A systematic review

Integrating a microRNA signature as a liquid biopsy-based tool for the early diagnosis and prediction of potential therapeutic targets in pancreatic cancer

INTRODUCTION

Pancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies.

MATERIALS AND METHODS

The analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved.

RESULTS

Our multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients.

CONCLUSION

A panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

Pancreatic cancer evolution and heterogeneity: integrating omics and clinical data

Pancreatic ductal adenocarcinoma (PDAC), already among the deadliest epithelial malignancies, is rising in both incidence and contribution to overall cancer deaths. Decades of research have improved our understanding of PDAC carcinogenesis, including characterizing germline predisposition, the cell of origin, precursor lesions, the sequence of genetic alterations, including simple and structural alterations, transcriptional changes and subtypes, tumour heterogeneity, metastatic progression and the tumour microenvironment. These fundamental advances inform contemporary translational efforts in primary prevention, screening and early detection, multidisciplinary management and survivorship, as prospective clinical trials begin to adopt molecular-based selection criteria to guide targeted therapies. Genomic and transcriptomic data on PDAC were also included in the international pan-cancer analysis of approximately 2,600 cancers, a milestone in cancer research that allows further insight through comparison with other tumour types. Thus, this is an ideal time to review our current knowledge of PDAC evolution and heterogeneity, gained from the study of preclinical models and patient biospecimens, and to propose a model of PDAC evolution that takes into consideration findings from varied sources, with a particular focus on the genomics of human PDAC.

A systematic review and meta-analysis of the association between circulating tumor DNA (ctDNA) and prognosis in pancreatic cancer

Pancreatic cancer is a deadly disease with limited therapeutic options. Several strategies are being investigated to improve disease management, including the early diagnosis of recurrences and treatment tailoring by better prognosis estimation. Circulating tumor DNA (ctDNA) could be a promising tool in this regard, although the data is limited. Therefore, we conducted a systemical review and meta-analysis of the published studies on the association of ctDNA and survival outcomes in pancreatic cancer. In the pooled analysis, positive preoperative or postoperative ctDNA was associated with lower RFS/PFS (HR: 2.27, 95 % CI: 1.59-3.24, p < 0.001) and OS (HR: 2.04, 95 % CI: 1.29-3.21, p = 0.002) in localized pancreatic cancer. Similarly, positive baseline ctDNA was associated with lower RFS/PFS (HR: 2.61, 95 % CI: 1.94-3.51, p < 0.001) and OS (HR: 2.41, 95 % CI: 1.74-3.34, p < 0.001) in advanced pancreatic cancer. In conclusion, ctDNA could be a promising tool to individualize treatment planning and to improve outcomes in pancreatic cancer.

Neoadjuvant Treatment for Pancreatic Adenocarcinoma: A False Promise or an Opportunity to Improve Outcome?

Simple Summary

Pancreatic cancer usually presents late when it has spread to distant sites. In a small proportion of patients, the cancer can be removed by surgery. Surgery is usually followed by chemotherapy, as studies have shown that this improves survival. However, due to complications after surgery and a decline in fitness, some patients do not start their chemotherapy and many do not complete the planned course. The cancer returns in the majority of patients. Chemotherapy or a combination of chemotherapy and radiotherapy before surgery are being investigated to improve survival. The best treatment regime and patient selection for different treatment strategies remains to be defined and is discussed here.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) has an aggressive tumor biology and is associated with poor survival outcomes. Most patients present with metastatic or locally advanced disease. In the 10–20% of patients with upfront resectable disease, surgery offers the only chance of cure, with the addition of adjuvant chemotherapy representing an established standard of care for improving outcomes. Despite resection followed by adjuvant chemotherapy, at best, 3-year survival reaches 63.4%. Post-operative complications and poor performance mean that around 50% of the patients do not commence adjuvant chemotherapy, and a significant proportion do not complete the intended treatment course. These factors, along with the advantages of early treatment of micrometastatic disease, the ability to downstage tumors, and the increase in R0 resection rates, have increased interest in neo-adjuvant treatment strategies. Here we review biomarkers for early diagnosis of PDAC and patient selection for a neo-adjuvant approach. We also review the current evidence for different chemotherapy regimens in this setting, as well as the role of chemoradiotherapy and immunotherapy, and we discuss ongoing trials.

Pancreatic cancer intrinsic PI3Kα activity accelerates metastasis and rewires macrophage component

Pancreatic ductal adenocarcinoma (PDAC) patients frequently suffer from undetected micro-metastatic disease. This clinical situation would greatly benefit from additional investigation. Therefore, we set out to identify key signalling events that drive metastatic evolution from the pancreas. We searched for a gene signature that discriminate localised PDAC from confirmed metastatic PDAC and devised a preclinical protocol using circulating cell-free DNA (cfDNA) as an early biomarker of micro-metastatic disease to validate the identification of key signalling events. An unbiased approach identified, amongst actionable markers of disease progression, the PI3K pathway and a distinctive PI3Kα activation signature as predictive of PDAC aggressiveness and prognosis. Pharmacological or tumour-restricted genetic PI3Kα-selective inhibition prevented macro-metastatic evolution by hindering tumoural cell migratory behaviour independently of genetic alterations. We found that PI3Kα inhibition altered the quantity and the species composition of the produced lipid second messenger PIP3 , with a selective decrease of C36:2 PI-3,4,5-P3 . Tumoural PI3Kα inactivation prevented the accumulation of pro-tumoural CD206-positive macrophages in the tumour-adjacent tissue. Tumour cell-intrinsic PI3Kα promotes pro-metastatic features that could be pharmacologically targeted to delay macro-metastatic evolution.