Chasing disease footprints in blood samples

An assay to efficiently capture tumor-derived extracellular vesicles.

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Feb 06, 2017
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Despite significant strides in cancer diagnosis and treatment over the past decades, some cancers are still primarily detected at advanced stages, when patient outcomes can be bleak. Pancreatic cancer, for example, seldom displays obvious symptoms in its early stages, yet can develop aggressively, and more than half of pancreatic cancer cases are diagnosed at later stages for which 1-year and 5-year survival rates are only 15% and 2%, respectively1. Early detection is essential, since the only accepted cure for pancreatic cancer is surgical removal of all tumor tissue, but only 9% of pancreatic cancer cases are currently diagnosed with local disease, which offers the best hope for successful tumor resection.

Numerous studies have therefore addressed the potential for early cancer detection with blood tests directed against circulating tumor cells (CTCs) or DNA (ctDNA)2, or tumor-derived proteins or extracellular vesicles (EVs)3. Most of these 'tumor footprints' are difficult to detect due to their low abundance (CTC and ctDNA) and/or stability and specificity (protein biomarkers), especially when assayed in individuals with early stage cancer. EVs, however, are abundantly secreted by most cells – including tumors cells, which generally secrete more EVs than normal cells – and have several properties that suggest their potential utility as cancer biomarkers.

EVs appear to play a vital role in the development and progression of certain cancers, including pancreatic cancer, as they are known to migrate to other tissues and modify their surroundings to create an environment favorable for tumor invasion and growth4. EVs have also been reported to regulate tumor chemoresistance by exporting anti-tumor drugs or through the transfer of micoRNAs or proteins that impact tumor cell growth4,5. Further, the EV factors that regulate these effects are either enclosed by or embedded within the EV membrane, reducing their exposure to serum hydrolase activities that can attenuate the detection of soluble tumor-derived proteins and nucleic acids.

Most current EV analyses methods, however, require time-consuming EV isolation and purification steps that are not feasible in a clinical setting, after which isolated EVs must then assayed for the tumor-specific factor(s) of interest. To streamline this process, our laboratory has worked to develop a procedure in which target membrane proteins of EVs captured directly from unprocessed serum and plasma samples are used to distinguish specific cancer-derived EVs from the total EV population.

Our current approach uses an antibody to a common EV membrane protein to immobilize serum EVs after which they are hybridized with gold nanorods (AuR) and nanospheres (AuS) that respectively bind a second EV membrane protein and a pancreatic cancer specific EV membrane protein. Only cancer-derived EVs bind both AuR and AuS, and the resulting AuR-EV-AuS complex produces a nanoplasmon that markedly shifts the spectrum and the intensity of light scattered by these EVs, readily distinguishing them from the AuR-EV complexes that form on normal EVs (Scheme 1). The current study uses a standard dark-field microscopy system to analyze EV assay samples; however, we are now developing a fully-automated system to reduce the cost and increase the throughput of the assay and to improve its potential for rapid clinical translation.

Scheme 1. Artistic representation of the nanoplasmon-enhanced scattering technique for the detection of tumor-derived extracellular vesicles.

This approach requires very little sample (≤1µL) and thus permits longitudinal analyses to be performed in mouse models of human disease, which have not been feasible with previous EV analysis methods. We applied this new ability to analyze a mouse model of pancreatic cancer, finding that EphA2-EVs plasma concentrations linearly increased with time after tumor initiation, and highly correlated with tumor volume. This new capacity for longitudinal disease-specific EV analysis should provide valuable insights into factors associated with cancer progression, metastasis and drug resistance in similar mouse cancer models.

Notably, our assay approach can be readily customized to detect other cancers and chronic diseases by substituting the EphA2 probe for a probe specific to an EV membrane protein linked to a given disease of interest. Our initial studies have shown promise adapting this approach to specifically detect lung cancer-derived EVs in blood and bacterial-derived EVs in urine, suggesting that such adaptations are feasible across a spectrum of sample and disease types.

Our paper: Liang, K. et al. Nanoplasmonic quantification of tumour-derived extracellular vesicles in plasma microsamples for diagnosis and treatment monitoring. Nat. Biomed. Eng. 1, 0021 (2017).

References:

1. American Cancer Society. Cancer Facts & Figures 2015. Atlanta: American Cancer Society; 2015.

2. Bidard FC, Weigelt B, Reis-Filho JS. Going with the flow: from circulating tumor cells to DNA. Sci Transl Med 2013; 5(207): 207ps14.

3. Soung YH, Ford S, Zhang V, Chung J. Exosomes in Cancer Diagnostics. Cancers (Basel) 2017; 9(1).

4. Azmi AS, Bao B, Sarkar FH. Exosomes in cancer development, metastasis, and drug resistance: a comprehensive review. Cancer Metastasis Rev 2013; 32(3-4): 623-42.

5. Shedden K, Xie XT, Chandaroy P, Chang YT, Rosania GR. Expulsion of small molecules in vesicles shed by cancer cells: association with gene expression and chemosensitivity profiles. Cancer Res 2003; 63(15): 4331-7.

Go to the profile of Kai Liang

Kai Liang

Assistant investigator / Postdoctoral researcher, Institute of biophysics, Chinese Academy of Sciences/Methodist Hospital Research Institute

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