Evolving utility of exosomes in pancreatic cancer management

Table 1 Circulating biomarkers in pancreatic cancer

Biomarker	Type	Role in pancreatic cancer
CA19-9	Protein	Widely used biomarkers to aid in the diagnosis[4]
		Poor screening tool in asymptomatic patients
		Elevated in many benign gastrointestinal conditions as well as other malignancies, including pancreatitis, cirrhosis, cholangitis, and colorectal cancer[5]
		5%-10% of the caucasian population possesses a Lewis a-/b- genotype and thus does not express CA19-9
CEA	Glycoprotein	Elevated across several cancers[6]
		Non specific
		Inferior sensitivity of CEA compared to ca19-9[7]
CA125	Glycoprotein	Associated with ovarian cancer, CRC and cholangiocarcinoma[8]
		Superiority to CA19-9 in predicting resectability of PC, along with correlating with metastasis-associated disease burden
Anti-MUC1 antibody	Antibody	Anti-MUC1 antibody assays showed a sensitivity and specificity of 77% and 95%, respectively, in discriminating pancreatic cancer from pancreatitis[9]
CTCs	Tumour cells	CTCs had moderate diagnostic value in PC[10]
		Several studies have demonstrated isolation of CTCs regardless of stage among localized, locally advanced, or metastatic patients
		Conflicting evidence on CTC positivity is correlated with survivability
		In ombination with CA19-9, it was reported to have a superior sensitivity and specificity of 97.8% and 83.3% respectively, compared to when used in isolation[11]
		The presence of CTCs in 54/72 patients with confirmed PDAC (sensitivity = 75.0%, specificity = 96.4%, AUROC = 0.867, 95%CI: 0.798-0.935, and P < 0.001)[12]
		A cut-off of ≥ 3 CTCs in 4 mL blood could differentiate between local/regional and metastatic disease (AUROC: 0.885; 95%CI: 0.800-0.969; and P < 0.001)
cfDNA	DNA	Plasma ctDNA quantification of hot-spot mutations in KRAS and GNAS are useful in predicting tumor burden in patients diagnosed with PC[13]
		Digital PCR provided accurate tumor-derived mutant KRAS detection in plasma in resectable PC and improved post-resection recurrence prediction compared to CA19-9[14]
		Detection of plasma cfDNA mutations and copy number alterations may be helpful in pancreatic cancer prognosis and diagnosis
		Its sensitivity and specificity in identification of clinically relevant KRAS mutations was 87% and 99% respectively[15]
Cell-free RNA	RNA	Higher expression of lncRNA MALAT1 has been shown to correlate with poorer PDAC survival[16]
		Several microRNAs have also been associated with PDAC (i.e., miR-21 and miR-155), and correlate with tumor stage or prognosis[17]
EVs	Exosomes	KRAS G12D mutations were identified in 7.4% of control patients, 67% of localized PDAC, 80% of locally advanced PDAC, and 85% of metastatic PDAC patients[18]
		GPC1 EVs could be detected in both pancreatic precursor lesions and pancreatic cancer, and could distinguish between any evidence of malignancy and healthy patients with an AUC of 1 (100% sensitivity, 100% specificity)[19]
		miRNA isolated from EVs revealed a cocktail of miRNAs (miR-1246, 4644, 3976, 4306) upregulated in 83% of pancreatic cancer derived EV
		Glypican-1 exosomes are a potential biomarker for PC

CA: Carbohydrate antigen; PDAC: Pancreatic ductal adenocarcinoma; PC: Pancreatic cancer; CEA: Carcinoembryonic antigen; CTCs: Circulating tumour cells; cfDNA: Cell-free DNA; EVs: Extracellular vesicles; AUROC: Area under the curve.

Table 2 Comparison of usefulness of various liquid biopsies in pancreatic cancer

Item	CTC[20-22]	Ct DNA[21,23,24]	Exosomes[20,25-28]	CA 19-9[20,21,28-30]
Origin	Viable tumor cells	cfDNA, viable tumor cells, CTCs	DNA, proteins, lipids, RNAs metabolites, and tumor cells	Ductal cells in the pancreas, biliary system, and epithelial cells in the stomach, colon, uterus, and salivary glands
Samples used	Plasma	Frozen plasma, urine and other biofluids	Frozen plasma, urine and other biofluids	Plasma
Methods	CellSearch, MACS, Dynabeads, microfluidic, SE-iFISH, CD45/CEP8/DAPI staining-FISH, anti-EpCAM Portal-vein blood	Real-time quantitative PCR, digital PCR, droplet digital PCR, next-generation sequencing; commercial liquid biopsy platforms: GuardantTM (breast, colon, and lung cancers and multi-cancer detection) FoundationOne® (multi-cancer detection); signateraTM (colorectal cancer), Galleri (multi-cancer detection), CancerSEEK (multi-cancer detection), TempusTM (multi-cancer detection), Caris (bioinformatics testing of both circulating DNA and RNA)	Ultracentrifugation, ExoChip, precipitation, size-based isolation immunoaffinity-based isolation microfluidics-based isolation	Radio immuno assay
Mutation analysis	Yes	Yes	Yes	No
Drug delivery vehicle	No	No	Yes	No
Sensitivity	76.0%	65.0%	50.0%-85.0%	78.2%
Specificity	68.0%	75.0%	90.0%	82.8%
Usage in clinics	Diagnosis of PDAC, prognosis/prediction of PDAC	Diagnosis of PDAC; monitoring treatment efficacy; monitoring of disease progression	Diagnosis and prognosis of PDAC; prognosis/prediction of PDAC	Combining ct DNA with CA 19-9 levels could improve diagnostic sensitivity to 98%, and specificity to 97%; monitoring treatment efficacy; monitoring of disease progression

PDAC: Pancreatic ductal adenocarcinoma; CTC: Circulating tumour cells; CA: Carbohydrate antigen; ctDNA: Circulating tumor DNA.

Table 3 Different isolation methods for exosome

Method	Sample volume	Time	Ref.
Ultracentrifugation	Low	Approximately 5 h	[48,49]
Density-gradient	Low	Approximately 5 h	[50]
Nanopillar	30 μL	Approximately 10 min	[51]
Acoustic-based	0.4-0.7 μL/min	< 30 min	[52]
Inertial lift force-based	70 μL/min	> 4 h	[53]
Surface-modified	4-16 μL/min	< 1 h	[53-55]
Nanoshearing	Not mentioned	< 3 h	[56]

Table 4 Different quantifying methods for exosome

Method	Size range	Specificity	Time	Ref.
Nanoparticle tracking analysis	10 nm-2 μm	Immunoaffinity	< 1 h	[48]
Dynamic light scattering	10 nm-8 μm	Size	< 1 h	[57]
Electron microscopy	10 nm	Size	< 1 h	[58,59]
Nanopore	> 10 nm	Size	< 1 h	[60,61]
Magnetic resonance	Wide range	Immunoaffinity	< 10 min	[62]
Electrochemical and plasmonic	Depends on binding	Immunoaffinity	< 10 min	[63,64]

Table 5 Comparison of various isolation methods for exosomes

Conventional isolation of exosomes
Methods	Advantages	Disadvantages	Clinical use	Ref.
Ultracentrifugation	Widely used; high purity; protein and RNA components are not affected	Highly labour intensive; time-consuming; yields are typically low extensive training of personnel needed; expensive; inappropriate for the extraction of exosomes from a small amount of serum samples	Functional study of exosomes	[65,66]
Ultrafiltration	High yield; simple; less time-consuming; do not require the use of special equipment	Low purity, clogging of pores	Study of sample concentration; used in combination with other methods	[67]
Precipitation	Widely used; economical	Co-isolation of non-EV particles	For studies with very low purity requirements that do not require omics studies	[68]
Size exclusion chromatography, OR, and gel filtration	Fast, reliable, and inexpensive; maintain the biological activity and integrity of exosomes; high purity	Nanoscale contaminants like lipoproteins; extensive laboratory equipment requirements	Suitable for exosome research in those requiring high purity, omics, and large volume samples	[69]
Immunoaffinity capture	Convenient; not affected by exosome size; no need for expensive instruments	Expensive; low capacity; low yields	Suitable for the Separation of specific exosome subgroups	[70]
Emerging isolation methods
Stirred ultrafltration	Do not rely on equipment; less time consuming; reduces the destruction of exosomes during the process	Moderate purity of isolated exosomes; loss of exosomes during the process	Isolating exosomes from culture supernatant of bone marrow mesenchymal stem cells	[71]
ExoTIC (exosome total isolation chip)	Simple, easy-to-use, modular, and facilitates high-yield and high-purity EV isolation from biofluids	Special equipment requirements; lack of tests on clinical samples	Efficiently isolate EVs from small sample volumes; EV-based clinical testing from fingerprick quantities (10-100 μL) of blood	[72,73]
3D ZnO Nanoarrays	Multifunction; high sensitivity; downstream analysis is possible; enhance the capture of exosomes at a high flow rate	Relatively expensive	Widely used in biosensing and analysis aspects, powerful tools for effective purification and molecular analysis of exosome	[74,75]
Nano plasmon-enhanced scattering	Rapid, high-throughput, sensitive, and specifc method for the detection of exosomes from trace samples depending on the amount of scatter area, based on calculation of the proportion of the area that contains scattered light	High reagent cost; complex statistical tools; low capacity	Uses antibodies against the cellular markers CD81, CD63, and CD9, which are enriched on most exosome membranes	[76]

SEC: Size exclusion chromatography; EV: Extracellular vesicle.