Materials

Iron (III) chloride hexahydrate ACS, sodium acetate (anhydrous ACS), ethylene glycol, ammonium hydroxide 28–30%, ammonium persulfate (APS) (≥98%, Pro-Pure, Proteomics Grade), ethanol (reagent alcohol ACS), and methanol (≥99.8% ACS) were purchased from VWR. N,N′-Methylenebisacrylamide (99%) was purchased from EMD Millipore. Trisodium citrate dihydrate (ACS reagent, ≥99.0%), tetraethyl orthosilicate (TEOS) (reagent grade, 98%), 3-(trimethoxysilyl)propyl methacrylate (MPS) (98%), and poly(ethylene glycol) methyl ether methacrylate (OEGMA, average Mn 500, contains 100 ppm MEHQ as inhibitor, 200 ppm BHT as inhibitor) were purchased from Sigma–Aldrich. 4,4′-Azobis(4-cyanovaleric acid) (ACVA, 98%, cont. ca 18% water) and divinylbenzene (DVB, 80%, mixture of isomers) were purchased from Alfa Aesar and purified by passing a short silica column to remove the inhibitor. N-(3-Dimethylaminopropyl)methacrylamide (DMAPMA) was purchased from TCI and also purified by passing a short silica column to remove the inhibitor. The ELISA kit to measure human C-reactive protein (CRP) was purchased from R&D Systems (Minneapolis, MN). Human CRP protein purified from human serum was from Sigma–Aldrich.

Synthesis of NP SP-003, SP-007, and SP-011

The iron oxide core was synthesized following the published method via solvothermal reaction (Supplementary Fig. 3A)54,55. Typically, 26.4 g of iron (III) chloride hexahydrate was dissolved in 220 mL of ethylene glycol at 160 °C for ~10 min under mixing. Then 8.5 g of trisodium citrate dihydrate and 29.6 g sodium acetate anhydrous were added and fully dissolved by mixing for an additional 15 min at 160 °C. The solution was then sealed in a Teflon-lined stainless-steel autoclave (300 mL capacity) and heated to 200 °C for 12 h. After cooling to room temperature (RT), the black paramagnetic product was isolated by a magnet and washed with DI water 3–5 times. The final product was freeze-dried to a black powder for further use.

The silica-coated iron oxide NPs (SP-003) were prepared through a modified Stöber process as reported before (Supplementary Fig. 3B)56,57. Typically, 1 g of the SPIONs were homogeneously dispersed in a mixture of ethanol (400 mL), DI water (10 mL), and concentrated ammonia aqueous solution (10 mL, 28–30 wt%), followed by the addition of TEOS (2 mL). After stirring at 70 °C for 6 h, amorphous silica-coated SPIONs (denoted Fe3O4@SiO2) were washed three times with methanol, three times with water, and the final product was freeze-dried to a powder.

To prepare SP-007 (PDMAPMA-modified SPION) and SP-011 (PEG-modified SPION), vinyl group–functionalized SPIONs (denoted Fe3O4@MPS) were first prepared through a modified Stöber process as previously reported (Supplementary Fig. 3C)41. Briefly, 1 g of the SPIONs was homogeneously dispersed under the aid of vortexing (or sonication) in a mixture of ethanol (400 mL), DI water (10 mL), and concentrated ammonia aqueous solution (10 mL, 28–30 wt%), followed by the addition of TEOS (2 mL). After stirring at 70 °C for 6 h, 2 mL of 3-(trimethoxysilyl)propyl methacrylate was added into the reaction mixture and stirred at 70 °C overnight. Vinyl-functionalized SPIONs were obtained and washed three times with methanol, three times with water, and the final product freeze-dried to a powder. Next, for synthesis of poly(dimethylaminopropyl methacrylamide) (PDMAPMA)-coated SPIONs (denoted Fe3O4@PDMAPMA, SP-007 in Supplementary Fig. 3D), 100 mg of Fe3O4@MPS was homogeneously dispersed in 125 mL of DI water. After bubbling with N2 for 30 min, 2 g of N-[3-(dimethylamino)propyl] methacrylamide (DMAPMA) and 0.2 g of divinylbenzene (DVB) were added into the Fe3O4@MPS suspension under N2 protection. After the resulting mixture was heated to 75 °C, 40 mg of ammonium persulfate (APS) in 5 mL DI water was added and stirred at 75 °C overnight. After cooling, Fe3O4@PDMAPMA were isolated with a magnet and washed 3–5 times with water. The final product was freeze-dried to a dark brown powder. For synthesis of poly(ethylene glycol) (PEG)-coated SPIONs (denoted as Fe3O4@PEGOMA, SP-011 in Supplementary Fig. 3E), 100 mg of Fe3O4@MPS was homogeneously dispersed in 125 mL of DI water. After bubbling with N2 for 30 min, 2 g of poly(ethylene glycol) methyl ether methacrylate (OEGMA, average Mn 500) and 50 mg of N,N′-Methylenebisacrylamide (MBA) were added into the Fe3O4@MPS suspension under N2 protection. After the resulting mixture was heated to 75 °C, 50 mg of 4,4’-azobis(4-cyanovaleric acid) (ACVA) in 5 mL ethanol was added and stirred at 75 °C overnight. After cooling, Fe3O4@POEGMA were isolated with a magnet and washed 3–5 times with water. The final product was freeze-dried to a dark brown powder.

Characterization of NP physicochemical properties

Dynamic light scattering (DLS) and zeta potential were measured on a Zetasizer Nano ZS (Malvern Instruments, Worcestershire, UK). NPs were suspended at 10 mg/mL in water with 10 min of bath sonication prior to testing. Samples were then diluted to ~0.02 wt% for both DLS and zeta potential measurements in respective buffers. DLS was performed in water at 25 °C in disposable polystyrene semi-micro cuvettes (VWR, Randor, PA, USA) with a 1 min temperature equilibration time and the average taken from three runs of 1 min, with a 633 nm laser in 173° backscatter mode. DLS results were analyzed using the cumulants method. Zeta potential was measured in 5% pH 7.4 PBS (Gibco, PN 10010-023, USA) in disposable folded capillary cells (Malvern Instruments, PN DTS1070) at 25 °C with a 1 min equilibration time. Three measurements were performed with automatic measurement duration with a minimum of 10 runs, a maximum of 100 runs, and a 1 min hold between measurements. The Smoluchowski model was used to determine the zeta potential from the electrophoretic mobility.

Scanning electron microscopy (SEM) was performed using a FEI Helios 600 Dual-Beam FIB-SEM. Aqueous dispersions of NPs were prepared to a concentration of 10 mg/mL from weighted NP powders re-dispersed in DI water by 10 min sonication. Then the samples were 4× diluted by methanol (Fisher) to make a dispersion in water/methanol that was directly used for electron microscopy. SEM substrates were prepared by drop-casting 6 µL of NP samples on the Si wafer from Ted Pella, and the droplet was completely dried in a vacuum desiccator for about 24 h prior to measurements.

A Titan 80–300 transmission electron microscope (TEM) with an accelerating voltage of 300 kV was used for both low- and high-resolution TEM measurements. The TEM grids were prepared by drop-casting 2 µL of the NP dispersion in a water-methanol mixture (25–75 v/v%) with a final concentration of 0.25 mg/mL and dried in a vacuum desiccator for about 24 h prior to TEM analysis. All measurements were performed on the lacey holey TEM grids from Ted Pella.

X-Ray Photoelectron Spectroscopy (XPS) was performed using a PHI VersaProbe and a Thermo Scientific ESCALAB 250e III. XPS analysis was performed on the NP fine powders kept sealed and stored under desiccation prior to measurement. Materials were mounted on carbon tape to achieve a uniform surface for analysis. A monochromatic Al K-alpha X-ray source (50 W and 15 kV) was used over a 200 µm2 scan area with a pass energy of 140 eV, and all binding energies were referenced to the C–C peak at 284.8 eV. Both survey scans and high-resolution scans were performed to assess in detail the elements of interest. The atomic concentration of each element was determined from integrated intensity of elemental photoemission features corrected by relative atomic sensitivity factors by averaging the results from two different locations on the sample. In some cases, four or more locations were averaged to assess uniformity.

Protein corona preparation and proteomic analysis

Plasma and serum samples (BioIVT, Hicksville NY) were diluted 1:5 in a dilution buffer composed of TE buffer (10 mM Tris, 1 mM disodium EDTA, 150 mM KCl) with 0.05% CHAPS. NP powder was reconstituted by sonicating for 10 min in DI water followed by vortexing for 2–3 sec. To form the protein corona, 100 µL of NP suspension (SP-003, 5 mg/ml; SP-007, 2.5 mg/ml; SP-011, 10 mg/ml) was mixed with 100 µL of diluted biological samples in microtiter plates. The plates were sealed and incubated at 37 °C for 1 h with shaking at 300 rpm. After incubation, the plate was placed on top of a magnetic collection device for 5 min to draw down the NPs. Unbound proteins in supernatant were pipetted out. The protein corona was further washed with 200 µL of dilution buffer three times with magnetic separation.

For the 10-NP screen, the five additional assay conditions evaluated were identical to those described above, with one of the following exceptions. First, a low concentration of NPs was evaluated that was 50% the original concentration (ranging from 2.5–15 mg/ml for each NP, depending on expected peptide yield). For the second and third assay variations, both low and high NP concentrations were run using an undiluted, neat plasma rather than diluting the plasma in buffer. For the fourth and fifth assay variations, both low and high NP concentrations were run using a pH 5 citrate buffer for both dilution and rinse.

To digest the proteins bound onto NPs, a trypsin digestion kit (iST 96×, PreOmics, Germany) was used according to protocols provided. Briefly, 50 µL of Lyse buffer was added to each well and heated at 95 °C for 10 min with agitation. After cooling the plates to room temperature, trypsin digestion buffer was added, and the plate incubated at 37 °C for 3 h with shaking. The digestion process was stopped with a stop buffer. The supernatant was separated from the NPs by a magnetic collector and further cleaned up by a peptide cleanup cartridge included in the kit. The peptide was eluted with 75 µL of elution buffer twice and combined. Peptide concentration was measured by a quantitative colorimetric peptide assay kit from Thermo Fisher Scientific (Waltham, MA).

NSCLC sample processing

As part of an ongoing, IRB-approved observational sample collection protocol, 24 sites were used to collect subject samples grouped into NSCLC (all stages, with 1, 2, and 3 referred to herein as early, and stage 4 defined as late), or healthy and pulmonary comorbid control arms. Subjects with pathology-confirmed NSCLC were enrolled post-diagnosis (typically achieved via a CT-guided fine-needle aspirant biopsy) but pretreatment. The protocol for obtaining blood samples from patients (Supplementary Note 1) was approved by the collections sites’ respective IRB’s (Supplementary Data 7), and all subjects gave written informed consent. Subjects were not necessarily fasted at the time of collection. Subjects for the pulmonary comorbidity control and healthy control groups were enrolled based on patient call-backs from participating study sites. In this context, healthy means the subjects did not have a current diagnosis of any form of cancer or any of the targeted pulmonary comorbidities including COPD, emphysema, etc. Sample types collected included EDTA plasma tubes, serum tubes, PAXgene RNA tubes, and Streck Blood Cell Collection tubes. For the purposes of this study, EDTA plasma was prepared as follows: After collection into the EDTA plasma tube per vendor instructions, the samples were centrifuged within 1 h of collection and the plasma fraction was aspirated and frozen within one hour of centrifugation prior to initial storage at −70 °C and subsequent shipment on dry ice. Study plasma samples were thawed at 4 °C, realiquoted, and refrozen once prior to NP processing. A randomly selected subcohort of 141 age- and gender-matched subjects from the healthy and early-stage NSCLC groups was selected for analysis from the collected samples with no significant differences between the groups based on Wilcoxon or Fisher tests, respectively. For NP analysis, the 141 plasma samples were randomized across sets of 96-well plates, one set for each NP. In addition to NP-plasma interrogation, a depleted plasma sample was prepared using the MARS-14 column (Agilent) per the manufacturer’s instructions. The NP-isolated peptides, as well as the peptides from equivalently digested depleted plasma, were evaluated by data-independent-acquisition mass spectrometry (DIA-MS) on Sciex Triple TOF 6600+ instruments coupled to an EKSPERT nano-LC 425 LC system running a 33 min sample-to-sample gradient. MS data acquisition took 2 weeks for all 141 samples.

Data-dependent acquisition (DDA)

LC-MS/MS: Next, the peptide eluates were lyophilized and reconstituted in 0.1% TFA. A 2 µg aliquot from each sample was analyzed by nano-LC-MS/MS with either a Waters NanoAcquity HPLC system or a Thermo Scientific UltiMate 3000 RSLCnano system interfaced to an Orbitrap Fusion Lumos Tribrid Mass Spectrometer from Thermo Scientific. Peptides were loaded on a trapping column and eluted over a 75 µm analytic column at either 350 nL/min (NanoAcquity HPLC) or 250 nL/min (UltiMate 3000 RSLCnano system) using a gradient of 2–35% acetonitrile over 44 min, for a total time between injections of 64 (UltiMate 3000 RSLCnano system) or 66 min (NanoAcquity HPLC). The mass spectrometer was operated in data-dependent mode, with MS and MS/MS performed in the Orbitrap at 60,000 FWHM resolution and 15,000 FWHM resolution, respectively.

DDA Data Processing (all data excluding the NSCLC study): The MS data at the protein group level were acquired as follows. MS raw files were processed with MaxQuant/Andromeda (v. 1.6.7)21,22, searching MS/MS spectra against the UniProtKB human FASTA database (UP000005640, 74,349 forward entries; version from August 2019) employing standard settings. Enzyme digestion specificity was set to trypsin, allowing cleavage N-terminal to proline and up to 2 miscleavages. Minimum peptide length was set to seven amino acids and maximum peptide mass to 4600 Da. Methionine oxidation and protein N-terminus acetylation were configured as a variable modification, and carbamidomethylation of cysteines was set as a fixed modification. MaxQuant improves precursor ion mass accuracy by time-dependent recalibration algorithms and defines individual mass tolerances for each peptide. As initial maximum precursor mass tolerances, we allowed 20 ppm during the first search and 4.5 ppm in the main search. The MS/MS mass tolerance was set to 20 ppm. For analysis, we applied a false discovery rate (FDR) cutoff of 1% at both the peptide and protein level (protein groups are reported with their corresponding q-value). “Match between runs” was disabled. Identifications were quantified based on protein intensities (only proteins with q-value < 1%) requiring at least one razor peptide (Supplementary Data 3, 4). MaxLFQ58 normalized protein intensities (requiring at least one peptide ratio count) are reported in the raw output and were used only for the CV precision analysis. Proteins that could not be discriminated based on unique peptides were assembled in protein groups. Furthermore, proteins were filtered for a list of common contaminants included in MaxQuant. Proteins identified only by site modification were strictly excluded from analysis.

Annotation-diversity analysis

To determine which annotations are predominantly enriched in the 10-NP panel (Fig. 4), we performed an annotation enrichment analysis using a Fisher’s exact test comparing proteins identified throughout the 10 NPs (requiring three out of three identifications across replicates) in a pooled plasma sample. Uniprot IDs (MaxQuant: Majority protein IDs) were matched to a list of 5304 published plasma proteins5 if any of the Uniprot IDs in the MaxQuant output matched the reported Uniprot ID. Next, annotations from five different spaces, GO Cellular Compartment (GOCC), GO Biological Process (GOBP), Uniprot Keywords, Protein families (Pfam), and Kyoto Encyclopedia of Genes and Genomes (KEGG), were matched to the protein groups based on Uniprot identifiers. Using Fisher’s exact test, we determined enriched annotations comparing the population of proteins identified by the 10 NPs within the reference database against the proteins that did not map into the 10-NP panel. Enrichment scores (Log2 Odds ratios) where calculated and plotted against the p-values (Fig. 4d). Annotations significantly enriched with a Benjamini–Hochberg FDR < 1% are indicated in blue. If log2 Odds were infinite, the maximum/ minimum log2 Odds where used for drawing.

We used continuous enrichment analysis (e.g., 1D annotation enrichment) to compare individual NPs at the annotation level, which has the advantage of using quantitative comparison, as a more powerful evaluation tool then requiring a binary input (e.g., presence/absence, threshold counting, etc.)64. We used this method to interrogate annotations enriched in the protein coronas by computing the 1D enrichment scores for each NP in the panel. In summary, log10-transformed MaxQuant intensities for each protein group in each sample were normalized by median subtraction. Protein groups that were not quantified in three out of three replicates used in the analysis on at least one NP were removed. A difference score was calculated for each protein group between the medians on one NP versus the average for that group across all of the other NPs. Annotations from five different spaces, GO Cellular Compartment (GOCC), GO Biological Process (GOBP), Uniprot Keywords, Protein families (Pfam), and Kyoto Encyclopedia of Genes and Genomes (KEGG), were matched to the protein groups based on the Uniprot identifiers reported in the MaxQuant output for each group as Majority Protein IDs. To match identifier format in the annotation reference, the isoform extensions were removed. The annotation references were retrieved from Uniprot on November 25, 2019 using the Perseus/MaxQuant framework73. The 1D annotation enrichment was calculated using R scripts adapted from the reported literature64. The results were filtered requiring (1) an annotation group size (i.e., number of protein groups with that annotation) greater than 10, and (2) a Benjamini–Hochberg-adjusted p-value (FDR) less than 2% for enrichment or depletion for at least one NP. The 1D enrichment score was visualized as a heatmap after hierarchical clustering as shown in Fig. 4e Gene Ontology Cellular Component (GOCC), B) Gene Ontology Biological Process (GOBP), C) Uniprot Keywords, D) Protein families (Pfam), E) Kyoto Encyclopedia of Genes and Genomes (KEGG). Hierarchical clustering is based on “complete linkage”.

Data-independent acquisition (DIA), NSCLC study

LC-MS/MS: For DIA analyses using SWATH, peptides were reconstituted in a solution of 0.1% FA and 3% ACN spiked with 5fmol/uL PepCalMix from SCIEX (Framingham, MA). A constant mass of 5 ug of peptides per MS injection volume of 10 uL was targeted, but in some instances with lesser yield the maximum amount available was injected. Each sample was analyzed by an Eksigent nano-LC system coupled with a SCIEX Triple TOF 6600+ mass spectrometer equipped with OptiFlow source using a trap-and-elute method. First, the peptides were loaded on a trap column and then separated on an Eksigent ChromXP analytical column (150 mm × 15 cm, C18, 3 mm, 120 Å) at a flow rate of 5 uL/min using a gradient of 3–32% solvent B (0.1% FA, 100% ACN) over 20 min, resulting in a 33 min total run time. The mass spectrometer was operated in SWATH mode using 100 variable windows across the 400–1250 m/z range.

Library generation for NSCLC study: To build a peptide-spectral library, four plasma pools were created from the patients in the lung cancer. Each pool was analyzed by the Proteograph using the panel of 10 NPs. In addition, the four plasma pools were depleted using a MARS-14 column (Agilent, Santa Clara, CA) and the Agilent 1260 Infinity II HPLC system. The samples were analyzed in data-dependent mode on the UltiMate 3000 RSLCnano system coupled with Orbitrap Fusion Lumos using a gradient of 5–35% over 109 min, for a total run time of 125 min. The rest of the parameters were set as mentioned above.

To further expand the spectral library, a dataset from a separate experiment using a pooled plasma consisting of 157 healthy and lung cancer patients varying in age, gender, and disease stage was used in combination with the NSCLC-DDA data. In short, the pooled plasma was analyzed by the Proteograph assay using the panel of 10 NPs. Furthermore, the pooled plasma was depleted using the MARS-14 column and fractionated into nine concatenated fractions using a high-pH fractionation method (XBridge BEH C18 column, Waters). All samples were prepared in three replicates and analyzed in data-dependent mode using the same parameters as NSCLC-DDA analysis.

Plasma depletion: All depleted plasma samples were prepared using an Agilent 1260 Infinity II Bioinert HPLC system consisting of autosampler, pumps, column compartment, UV detector, and fraction collector. Plasma depletion was conducted by first diluting 25 μL of plasma to a final volume of 100 μL using Agilent Buffer A plasma depletion mobile-phase. Each diluted sample was filtered through an Agilent 0.22 μm cellulose acetate spin filter to remove any particulates and transferred to a 96-well plate. The plate was then placed in an autosampler and held at 4 °C for the entirety of the assay. Eighty microliters of the diluted plasma was then injected onto an Agilent 4.6 × 50 mm Human 14 Multiple Affinity Removal System (MARS-14) depletion column housed in the column compartment at a constant temperature of 20 °C. Mobile-phase conditions used during protein depletion consisted of 100% Buffer A mobile-phase flowing at a rate of 0.125 mL/min. Proteins eluting from the column were detected using the Agilent UV absorbance detector operated at 280 nm with a bandwidth of 4 nm. The early eluding peak for each injection, representing the depleted plasma proteins, was collected using a refrigerated fraction collector with peak-intensity based triggering (i.e., 200 mAu threshold with a maximum peak width of 3 min). After peak collection, the fractions were held at 4 °C for the duration of the analysis. The sample volume was then reduced to approximately 20 μL using an Amicon Centrifugal Concentrator (Amicon Ultra-0.5 mL, 3k MWCO) with a centrifuge operating at 4 °C and 14,000 × g. Five microliters of each depleted sample was then reduced, alkylated, digested, desalted, and analyzed according to the sample preparation and MS analysis protocols described. During each sample depletion cycle, the MARS-14 column was regenerated with the Agilent Buffer B mobile-phase for ~4 ½ min at a flow rate of 1 mL/min and equilibrated back to the original protein capture condition by flowing Buffer A at 1 mL/min for ~9 min.

Peptide fractionation: A total of 100 μl of reconstituted peptides was loaded to a Waters XBridge column (2.1 × 250 mm, BEH C18, 3.5 mm, 300 Å) using the Agilent 1260 Infinity II HPLC system. The peptides were separated at the flow rate of 350 mL/min using a gradient of 3–30% in 30 min, with a total run time of 47 min, and the fractions were collected every 1.5 min. The fractions were then dried using a speed vac. Finally, the dried peptides were reconstituted in a solution of 0.1% FA and 3% ACN and concatenated to 9 fractions.

Data analysis for library generation: To generate a spectral library, all the DDA data were first searched against human Uniprot database using the Pulsar search engine in Spectronaut (Biognosys, Switzerland). Then the library was generated using Spectronaut with 1% FDR cutoff at peptide and protein level.

DIA raw data processing: The SWATH data were processed on Spectronaut. The default settings (version 13.8.190930.43655) were used for the analysis with the Q-value cutoff at precursor and protein level set to 0.01 (Supplementary Data 5).

For classification analysis (NSCLC study), primary MS data were prepared as follows. Statistical analysis was performed using the R platform as described above including the core ‘tidyverse‘ packages, the ‘caret‘ classification framework and the ‘ranger‘ random forest model package. Missing values for a given protein group within a subject were median imputed. No other normalization was applied to the data prior to classification. In order to construct between-group classifier models, log-transformed protein group data were evaluated in ten rounds of 10-fold cross validation. All protein group features were used for classification and the relative importance of those features in the cross-validations was reported. In order to detect possible overfitting, ten iterations of the cross-validation procedure were performed after randomization of the subjects’ class assignments. Initial classification results highlighted a significant signal from both the depleted plasma and NP panel data from proteins typically associated with stress and acute-phase response, likely a result of the sample acquisition strategy (e.g., post biopsy, diagnosis-aware). To eliminate this possibly confounding signal, all protein group data from the NP-derived dataset that was derived from any protein also observed in depleted plasma was removed from subsequent analysis.

Platelet Index (PI)

Protein groups identified in a sample by particle were matched to the platelet signature protein list from Geyer et al.67, and the sample platelet index (PI) was calculated as the median of the ln intensity of the signature proteins divided by the median of the ln intensity of the non-signature proteins. In order to summarize an overall PI for the sample from all particles and depleted plasma, the PIs for each particle were scaled and centered (default scale() R function) and the average was taken across the six values (five NPs and DP).

Spike recovery

Baseline concentration of CRP in a pooled healthy plasma sample was measured with the ELISA kit as described above (Materials) according to the manufacturer-suggested protocols. A stock solution and appropriate dilutions of CRP were prepared and spiked into the identical pooled plasma samples to make final concentrations 2×, 5×, 10×, and 100× baseline endogenous concentrations. The volume of additions to the pooled plasma was 10% of the total sample volume. A spike control was made by adding the same volume of buffer to the pooled plasma sample. Concentrations of spiked samples were measured again by ELISA to confirm the CRP levels in each spiking level. The samples were used to evaluate Proteograph NP corona measurement linearity as described in the Results above.

Background robustness test

Interference substances were obtained from Sun Diagnostics. Lipids: Triglyceride-rich lipoproteins derived from human. Hemolysate: Red blood cell hemolysate derived from human. A pooled plasma was spiked at different concentrations Lipid: High (1000 mg/dL), Low (100 mg/dL), and Control (buffer only). Hemolysate: High (1000 mg/dL), Low(100 mg/dL), and Control (buffer only).

Statistics and reproducibility

Statistical analysis and visualization were performed using R (v3.5.2) with appropriate packages74. Experiments were conducted in assay replicates (n = 3) unless noted differently. NSCLC data were acquired for biological replicates (see above). Mass spectrometry raw data and functional protein annotation references are available through PRIDE75 and Perseus76, respectively.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

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