Cancer cells that transit from primary tumours into the circulatory system are known as circulating tumour cells (CTCs). These cancer cells have unique phenotypic and genotypic characteristics which allow them to survive within the circulation, subsequently extravasate and metastasise. CTCs have emerged as a useful diagnostic tool using “liquid biopsies” to report on the metastatic potential of cancers. However, CTCs by their nature interact with components of the blood circulatory system on a constant basis, influencing both their physical and morphological characteristics as well as metastatic capabilities. These properties and the associated molecular profile may provide critical diagnostic and prognostic capabilities in the clinic. Platelets interact with CTCs within minutes of their dissemination and are crucial in the formation of the initial metastatic niche. Platelets and coagulation proteins also alter the fate of a CTC by influencing EMT, promoting pro-survival signalling and aiding in evading immune cell destruction. CTCs have the capacity to directly hijack immune cells and utilise them to aid in CTC metastatic seeding processes. The disruption of CTC clusters may also offer a strategy for the treatment of advance staged cancers. Therapeutic disruption of these heterotypical interactions as well as direct CTC targeting hold great promise, especially with the advent of new immunotherapies and personalised medicines. Understanding the molecular role that platelets, immune cells and the coagulation cascade play in CTC biology will allow us to identify and characterise the most clinically relevant CTCs from patients. This will subsequently advance the clinical utility of CTCs in cancer diagnosis/prognosis.
Pancreatic ductal adenocarcinoma (PDAC) has a 5-year survival rate below 5%. CA19-9 is the most commonly used blood-based biomarker for PDAC in current clinical practice, despite having been shown repeatedly to be inaccurate and have poor diagnostic performance. This review aims to assess the reported diagnostic accuracy of all blood-based biomarkers investigated to date in PDAC, by directly comparing individual biomarkers and multi-biomarker panels, both containing CA19-9 and not (novel). A systematic review was conducted in accordance with PRISMA standards in July 2020. Individualised search strategies for three academic databases identified 5,885 studies between the years 1973-2020. After two rounds of screening, 250 studies were included. Data were extracted and assessed for bias. A multivariate three-level meta-analysis with subgroup moderators was run in R using AUC values as effect size. Based on this model, the pooled AUC value for all multi-biomarker panels (AUC=0.898, 95% CI:0.88-0.91) was significantly higher than all single biomarkers (AUC=0.803, 95% CI:0.78-0.83)(p<0.0001). The pooled AUC value for CA19-9 alone was significantly lower compared to the multi-biomarker panels containing CA19-9 (p<0.0001). For the novel biomarkers, the pooled AUC for single biomarkers was also significantly lower compared to multi-biomarker panels (p<0.0001). Novel biomarkers that have been repeatedly examined across the literature, such as TIMP-1, CEA and CA125, are highlighted as promising. These results suggest that CA19-9 may be best used as an addition to a panel of biomarkers rather than alone, and that multi-biomarker panels generate the most robust results in blood-based PDAC diagnosis.
Pancreatic cancer (PC) is among the most aggressive types of cancer, having caused over 495,000 deaths worldwide in 2020, with increasing annual incidence. Pancreatic cystic lesions (PCLs) are protrusions found within or on the surface of the pancreas, and in many cases have the potential to become malignant. Current methods of characterising PCLs are imperfect and there is a profound need for improved diagnostic algorithms. This review highlights the importance of biological markers in the context of PCLs and PC, with a focus on ‘omics’-related work. Successful integration of different ‘omics’ data could aid in the identification of a novel integrated biomarker profile for the risk stratification of patients with PCLs and PC.
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