JP-2026076269-A - Compositions, methods, and systems for protein corona analysis, and their uses

Abstract

[Problem] To provide compositions, methods, and systems for protein corona analysis, as well as their uses. [Solution] Compositions, methods, and systems for analyzing protein coronas are described herein, along with their applications to the discovery of therapeutic targets as well as advanced diagnostic tools. The present invention provides a panel of nanoparticles for the detection of a wide range of diseases and disorders in a subject and for the determination of disease conditions. While the creation and characterization of protein coronas have been carried out in the art, the majority of experiments have been performed using non-magnetic particles, such as liposomes and polymer nanoparticles, or other particle types that can be used for targeted drug delivery. [Selection Diagram] None

Inventors

• ホンウェイ シア
• マーウィン コ
• クレイグ ストラルチク
• セオドア プラット
• リンダル ヘスターバーグ
• マイケル フィガ
• シャオヤン ジャオ
• グレゴリー トロイアーノ
• ウィリアム マニング
• ジョン ブルーム
• オミッド ファロクザド
• マシュー マクリーン

Assignees

• シアー， インコーポレイテッド

Dates

Publication Date

20260511

Application Date

20260123

Priority Date

20181107

Claims (1)

1. The invention described in the specification.

Description

Cross-reference of Related Applications This application claims priority to and benefits from U.S. Provisional Patent Application No. 62/756,960 filed on 7 November 2018, U.S. Provisional Patent Application No. 62/824,278 filed on 26 March 2019, and U.S. Provisional Patent Application No. 62/874,862 filed on 16 July 2019, the entire contents of each of these applications incorporated herein by reference. The widespread implementation of proteomic information into science and medicine largely lags behind genomics due to the inherent complexity of protein molecules themselves, which requires complex workflows that limit the scalability of such analyses. Compositions and methods for the rapid processing of proteomic data and the identification of critical biomarkers related to disease are disclosed herein. Figure 1 shows an example of the surface chemical structure of magnetic particles (MPs). In some cases, magnetic particles may be magnetic core nanoparticles (MNPs). Figure 2A shows the formation of protein coronas on particles. The protein corona profile depends on protein-particle, protein-protein, and protein concentration factors. Figure 2B shows the formation of protein coronas on three different particles. In some cases, the particles can be nanoparticles. The properties of these particles result in different protein corona profiles. Figure 3 shows some examples of particle types and some examples of methods that can functionalize the particle surface. In some cases, the particles may be nanoparticles. Figure 4 shows the preparation of superparamagnetic iron oxide nanoparticles (SPION) from the residual solution. As shown in the left photograph, SPION disperses in the solution before or immediately upon contact with a magnet on the side of the vial, appearing as a dark, opaque solution in the glass vial. Within 30 seconds of contact with the magnet on the side of the vial, SPION separates from the solution, as illustrated by the accumulation of dark particles next to the magnet and the increased transparency of the solution in the right photograph. Shaking the separated solution, as shown in the right image, returns the particles to the dispersed state shown in the left image within 5 seconds. SPION exhibits a rapid response. Figure 5 provides an example of the process for generating proteome data and the process for panel selection. Figure 6 shows some examples of different properties of particles and methods for characterizing them. Figure 7 shows an example of the size distribution of nanoparticles characterized by dynamic light scattering. Figure 7 shows dynamic light scattering overlays for two particle types: SP-002 (phenol-formaldehyde coated particles) and SP-010 (carboxylate, PAA coated particles), both having an iron oxide core. Dynamic light scattering can also be used to measure the size distribution of larger particles, including microparticles. Figures 8A and 8B show the characterization of nanoparticles with different functionalizations before corona formation. Figure 8A shows a transmission electron microscope (TEM) observation of SP-002 (phenol-formaldehyde coated particles). Figure 8B shows a TEM of SP-339 (polystyrene carboxyl particles). TEM can also be used to characterize larger particles, including microparticles. Figure 9 shows Fe 2p/3 spectra from various nanoparticles, including SP-333 (carboxylate), SP-339 (polystyrene carboxylate), SP-356 (silica amino), SP-374 (silica silanol), HX-20 (SP-003) (silica coated), HX-42 (SP-006) (silica coated, amine), and HX-74 (SP-007) (PDMPAPMA coated (dimethylamine)). The spectra were obtained from XPS (X-ray photoelectron spectroscopy), which provides a chemical fingerprint of the particle surface (measuring the percentage of various elements on the surface). XPS can also be used to measure the spectra of larger particles, including microparticles. Figure 10 shows an example of the process of this disclosure for proteomic analysis. The process shown is optimized for high throughput and automation, and can be performed simultaneously across multiple samples within a few hours. The process includes particle-matrix association, particle washing (x3), protein corona formation, in-plate digestion, and mass spectrometry. Using this process, it may take only 4–6 hours per batch of 96 samples. Typically, one particle type is incubated with the sample at a time. Figure 11 shows protein counts (number of proteins identified from corona analysis) for panel sizes ranging from 1-particle to 12-particle. Each particle within the panel may have unique underlying material, surface functionalization, and/or physical properties (e.g., size or shape). A single pool of plasma representative of a pool of healthy subjects was used. Counts are the number of unique proteins observed across a 12-particle panel in approximately two hours of mass spectrometry (MS) run. 1318 proteins were identified using the 12-particle panel size. As used herein, “features” identifi