Libraries of single-stranded oligodeoxynucleotides (ssODNs) can be enriched for sequences that specifically bind molecules on naïve complex biological samples like cells or tissues. Depending on the enrichment strategy, the ssODNs can identify molecules specifically associated with a defined biological condition, for example a pathological phenotype, and thus are potentially useful for biomarker discovery. We performed ADAPT, a variant of SELEX, on exosomes secreted by VCaP prostate cancer cells. A library of ∼1011 ssODNs was enriched for those that bind to VCaP exosomes and discriminate them from exosomes derived from LNCaP prostate cancer cells. Next-generation sequencing (NGS) identified the best discriminating ssODNs, nine of which were resynthesized and their discriminatory ability confirmed by qPCR. Affinity purification with one of the sequences (Sequence 7) combined with LC–MS/MS identified its molecular target complex, whereof most proteins are part of or associated with the multiprotein ESCRT complex participating in exosome biogenesis. Within this complex, YBX1 was identified as the directly-bound target protein. ADAPT thus is able to differentiate exosomes from cancer cell subtypes from the same lineage. The composition of ESCRT complexes in exosomes from VCaP versus LNCaP cells might constitute a discriminatory element between these prostate cancer subtypes.
In the recent years it was demonstrated that a multitude of body fluids contains substantial amounts of exosomes, extracellular vesicles with sizes ranging between 40 and 100 nm. Those vesicles have protein profiles characteristic of their cells of origin. It was shown that exosomes play a role in cell-to-cell communication making them attractive targets to identify early disease stage biomarkers. Cancer heterogeneity is known for a long time to be an important clinical determinant of patient outcome. We developed the highly multiplexed ADAPT platform to capture systems-based biological signatures that may reflect the molecular heterogeneity of various cancer types and help to improve diagnosis of the disease. Exosomes from two prostate cancer cell lines, VCaP and LNCaP, were used to train ssDNA libraries to discriminate them. A highly diverse library of 1012 oligonucleotides (ODNs) was subjected to five rounds of positive and negative selection against exosomes from VCaP and LNCaP prostate cancer cell lines. Individual ODNs that bound preferably to exosomes from VCaP cells were identified by NGS, resynthesized and binding of co-precipitated ODNs to VCaP exosomes was verified by qPCR. LC-MS/MS was used to identify binding partners of ODNs bound to VCaP exosomes. Several of those binding partners (CHMP1b/2a/4b, VPS28, Syntenin-1) were found to be part of the ESCRT machinery, which participates in exosomes biogenesis. It was found that those proteins are overexpressed in human cancers. In addition, we identified the chemokine I-TAC, which is overexpressed in blood and tissue of men with advanced prostate adenocarcinomas. Finally, we found hnRNP-1, a cancer associated splicing factor, and the cold shock proteins RNPL and A18 hnRNP. Knock-down of these cold shock proteins has been shown to enhance chemotherapeutic cell killing of prostate cells. ADAPT is an unbiased profiling platform that identifies cancer associated proteins expressed on exosomes. This platform can be deployed against multiple cancer types and offers broad potential applications in biomarker discovery. Citation Format: Tassilo Hornung, Stephen Logie, Aniket S. Bondre, Varun Maher, Melissa N. Richards, Jelena Zarkovic, Teresa T. Tinder, Heather A. O'Neill, Mark R. Miglarese, David B. Spetzler. Adaptive dynamic artificial polyligand targeting (ADAPT): a method to identify exosomal proteins from a prostate cancer cell line [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2214. doi:10.1158/1538-7445.AM2017-2214
Identification of novel biomarkers and drug targets for colorectal cancer remains a critically unmet medical need. Target identification has historically been driven by preclinical models which poorly recapitulate the complex biology of human cancers. We describe a unique approach to drug target identification and comprehensive profiling directly in clinical specimens. Using the Adaptive Dynamic Artificial Polyligand Targeting (ADAPT) system, we aimed to identify such disease specific drug targets using a highly complex library of single-stranded oligodeoxynucleotides (ODNs). To generate the library, the ODNs were enriched using FFPE tissue specimens from pathologically determined colorectal cancer (CRC) and counter-selected against normal adjacent tissue (NAT) regions. Once the specificity of the library was verified via differential binding on independent CRC cases, it was used to affinity purify cognate biding partners from 393 CRC FFPE lysates with appropriate representation of cases with either KRAS, NRAS or BRAF mutations. Greater than 700 proteins were identified by mass spectrometry exclusively in the CRC FFPE tissue lysates and not in the NAT FFPE tissue lysates for all 393 CRC cases. Classification of these proteins into the druggable protein classes revealed G-protein coupled receptors, transporters, voltage-gated ion channels, proteases, and protein kinases. In addition, subsequent verification studies confirmed novel candidate cell surface protein targets appropriate for targeting by antibody-drug conjugates (ADC) or other biologic modalities. mRNA expression corresponding to the 700 potential targets was analyzed in over 1600 CRC FFPE tumor samples and >9000 other cancer types as well as in a broad panel of normal tissues by Whole Transcriptome Sequencing (WTS) and immunohistochemistry (IHC). We conclude that the unbiased ADAPT platform provides a robust and novel approach to drug target discovery with highly selective expression profiles directly from FFPE clinical specimens. Citation Format: Stephanie Williams, Chao Sima, Tassilo Hornung, Matthew Rosenow, Teresa Tinder, Varun Maher, Michelle Kassner, Gerri Ortiz, Perrin Mok, Nicholas Helle, Stephen Logie, Heather ONeill, Mark Miglarese, David Spetzler. Novel approach to colorectal cancer drug target discovery in human FFPE tissue using the Adaptive Dynamic Artificial Polyligand Targeting System [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5165.
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