Technologies capable of characterizing the full breadth of cellular systems need to be able to measure millions of proteins, isoforms, and complexes simultaneously. We describe an approach that fulfils this criterion: Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT). ADAPT employs an enriched library of single-stranded oligodeoxynucleotides (ssODNs) to profile complex biological samples, thus achieving an unprecedented coverage of system-wide, native biomolecules. We used ADAPT as a highly specific profiling tool that distinguishes women with or without breast cancer based on circulating exosomes in their blood. To develop ADAPT, we enriched a library of ~1011 ssODNs for those associating with exosomes from breast cancer patients or controls. The resulting 106 enriched ssODNs were then profiled against plasma from independent groups of healthy and breast cancer-positive women. ssODN-mediated affinity purification and mass spectrometry identified low-abundance exosome-associated proteins and protein complexes, some with known significance in both normal homeostasis and disease. Sequencing of the recovered ssODNs provided quantitative measures that were used to build highly accurate multi-analyte signatures for patient classification. Probing plasma from 500 subjects with a smaller subset of 2000 resynthesized ssODNs stratified healthy, breast biopsy-negative, and -positive women. An AUC of 0.73 was obtained when comparing healthy donors with biopsy-positive patients.
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.
Disease biomarkers play an essential role in disease-diagnostics and in monitoring their responses to therapies. Identification of low to medium abundance biomarkers is one of the biggest challenges in the field. We have developed Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT), a method in which libraries of single-stranded oligodeoxynucleotides (ssODNs) are enriched for sequences that bind to targets existing in samples in various amounts. Pull-downs with enriched libraries followed by LC-MS/MS allows for the enrichment and identification of low abundance biomarkers that cannot be identified by conventional proteomics. A highly diverse library of 1011 ssODNs was subjected to multiple rounds of positive selection against formalin-fixed paraffin-embedded (FFPE) colorectal cancer tissue with negative selection against adjacent non-cancer tissue of the same specimen. An enriched library of ~3x106 ssODNs that bound preferentially to cancer tissue was obtained and used in combination with LC-MS/MS to identify biomarkers related to colorectal cancer. Using this approach, a total of 14 proteins were identified in cancer but not in non-cancer tissue lysates. Their identification was only possible due to their enrichment by binding of the immobilized ssODN library to the cancer sample since the same proteins were undetectable by conventional proteomics. Immunohistochemical staining (IHC) of multiple colorectal cancer cases verified that several of the identified target proteins, including nucleophosmin (NPM1) and synaptotagmin-like protein 2 (SYTL2), showed higher expression in cancer tissue compared to adjacent non-cancer tissue. Our data indicate the potential of the ADAPT platform to profile small differences between cancer affected and unaffected tissue and provide a novel approach for cancer biomarker discovery. Citation Format: Tassilo Hornung, Jelena Zarkovic, Michelle Kassner, Matthew Rosenow, Mark R. Miglarese, Günter Mayer, Michael Famulok, David B. Spetzler. Discovery of low abundance colorectal cancer related biomarkers by the ADAPT Biotargeting System [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3136.
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