Standards-Free Absolute Quantitation of Oxidizable Glycopeptides by Coulometric Mass Spectrometry.

Currently, glycopeptide quantitation is mainly based on relative quantitation due to absolute quantitation requiring isotope-labeled or standard glycopeptides which may not be commercially available or are very costly and time consuming to synthesize. To address this grand challenge, coulometric mass spectrometry (CMS), based on the combination of electrochemistry (EC) and mass spectrometry (MS), was utilized to quantify electrochemically active glycopeptides without the need of using standard materials. In this study, we studied tyrosine-containing glycopeptides, NYIVGQPSS(ß-GlcNAc)TGNL-OH and NYSVPSS(ß-GlcNAc)TGNL-OH, and successfully quantified them directly with CMS with a discrepancy of less than 5% between the CMS measured amount and the theoretical amount. Taking one step further, we applied this approach to quantify glycopeptides generated from the digestion of NIST mAb, a monoclonal antibody reference material. Through HILIC column separation, five N297 glycopeptides resulting from NIST mAb tryptic digestion were successfully separated and quantified by CMS for an absolute amount without the use of any standard materials. This study indicates the potential utility of CMS for quantitative proteomics research.

Mobile Affinity Selection Chromatography Analysis of Therapeutic Monoclonal Antibodies.

Federal regulatory agencies require continuous verification of recombinant therapeutic monoclonal antibody (mAb) quality that is commonly achieved in a two-step process. First, the host-cell proteome and metabolome are removed from the production medium by protein A affinity chromatography. Second, following recovery from the affinity column with an acidic wash, mAb quality is assessed in multiple ways by liquid chromatography-mass spectrometry (LC-MS). However, lengthy sample preparation and the lack of higher-order structure analyses are limitations of this approach. To address these issues, this report presents an integrated approach for the analysis of two critical quality attributes of mAbs, namely titer and relative aggregate content. Integration of sample preparation and molecular-recognition-based analyses were achieved in a single step utilizing an isocratically eluted mobile affinity selection chromatography (MASC) column. MASC circumvents the protein A step, simplifying sample preparation. Within 10 min, (i) mAbs are fluorescently coded for specific detection, (ii) monomers and aggregates are resolved, (iii) the mAb titer is quantified, (iv) relative aggregate content is determined, (v) analytes are detected, and (vi) the column is ready for the next sample. It is suggested herein that this mode of rapid quality assessment will be of value at all stages of discovery (screening, clone selection, characterization), process R&D, and manufacturing. Rapid monitoring of variant formation is a critical element of quality evaluation.

Diagnostic utility of N-terminal TMPP labels for unambiguous identification of clipped sites in therapeutic proteins.

Protein therapeutics are susceptible to clipping via enzymatic and nonenzymatic mechanisms that create neo-N-termini. Typically, neo-N-termini are identified by chemical derivatization of the N-terminal amine with (N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP) followed by proteolysis and mass spectrometric analysis. Detection of the TMPP-labeled peptide is achieved by mapping the peptide sequence to the product ion spectrum derived from collisional activation. The site-specific localization of the TMPP tag enables unambiguous determination of the true N-terminus or neo-N-termini. In addition to backbone product ions, TMPP reporter ions at m/z 573, formed via collision-induced dissociation, can be diagnostic for the presence of a processed N-termini. However, reporter ions generated by collision-induced dissociation may be uninformative because of their low abundance. We demonstrate a novel high-throughput LC-MS method for the facile generation of the TMPP reporter ion at m/z 533 and, in some instances m/z 590, upon electron transfer dissociation. We further demonstrate the diagnostic utility of TMPP labeled peptides derived from a total cell lysate shows high degree of specificity towards selective N-terminal labeling over labeling of lysine and tyrosine and highly-diagnostic Receiver Operating Characteristic's (ROC) of TMPP reporter ions of m/z 533 and m/z 590. The abundant generation of these reporters enables subsequent MS/MS by intensity and m/z-dependent triggering of complementary ion activation modes such as collision-induced dissociation, high-energy collision dissociation, or ultraviolet photo dissociation for subsequent peptide sequencing.

"Lab of the Future"─Today: Fully Automated System for High-Throughput Mass Spectrometry Analysis of Biotherapeutics.

Here we describe a state-of-the-art, integrated, multi-instrument automated system designed to execute methods involved in mass spectrometry characterization of biotherapeutics. The system includes liquid and microplate handling robotics and utilities, integrated LC-MS, along with data analysis software, to perform sample purification, preparation, and analysis as a seamless integrated unit. The automated process begins with tip-based purification of target proteins from expression cell-line supernatants, which is initiated once the samples are loaded onto the automated system and the metadata are retrieved from our corporate data aggregation system. Subsequently, the purified protein samples are prepared for MS, including deglycosylation and reduction steps for intact and reduced mass analysis, and proteolytic digestions, desalting, and buffer exchange via centrifugation for peptide map analysis. The prepared samples are then loaded into the LC-MS instrumentation for data acquisition. The acquired raw data are initially stored on a local area network storage system that is monitored by watcher scripts that then upload the raw MS data to a network of cloud-based servers. The raw MS data are processed with the appropriately configured analysis workflows such as database search for peptide mapping or charge deconvolution for undigested proteins. The results are verified and formatted for expert curation directly in the cloud. Finally, the curated results are appended to sample metadata in the corporate data aggregation system to accompany the biotherapeutic cell lines in subsequent processes.

"Stapling" scFv for multispecific biotherapeutics of superior properties.

Single-chain fragment variable (scFv) domains play an important role in antibody-based therapeutic modalities, such as bispecifics, multispecifics and chimeric antigen receptor T cells or natural killer cells. However, scFv domains exhibit lower stability and increased risk of aggregation due to transient dissociation ("breathing") and inter-molecular reassociation of the two domains (VL and VH). We designed a novel strategy, referred to as stapling, that introduces two disulfide bonds between the scFv linker and the two variable domains to minimize scFv breathing. We named the resulting molecules stapled scFv (spFv). Stapling increased thermal stability (Tm) by an average of 10°C. In multiple scFv/spFv multispecifics, the spFv molecules display significantly improved stability, minimal aggregation and superior product quality. These spFv multispecifics retain binding affinity and functionality. Our stapling design was compatible with all antibody variable regions we evaluated and may be widely applicable to stabilize scFv molecules for designing biotherapeutics with superior biophysical properties.

Rapid Characterization of Antibodies via Automated Flow Injection Coupled with Online Microdroplet Reactions and Native-pH Mass Spectrometry.

Microdroplet reactions have aroused much interest due to significant reaction acceleration (e.g., ultrafast protein digestion in microdroplets could occur in less than 1 ms). This study integrated a microdroplet protein digestion technique with automated sample flow injection and online mass spectrometry (MS) analysis, to develop a rapid and robust method for structural characterization of monoclonal antibodies (mAbs) that is essential to assess the antibody drug's safety and quality. Automated sequential aspiration and mixing of an antibody and an enzyme (IdeS or IgdE) enabled rapid analysis with high reproducibility (total analysis time: 2 min per sample; reproducibility: ∼2% coefficient of variation). Spraying the sample in ammonium acetate buffer (pH 7) using a jet stream source allowed efficient digestion of antibodies and efficient ionization of resulting antibody subunits under native-pH conditions. Importantly, it also provided a platform to directly study specific binding of an antibody and an antigen (e.g., detecting the complexes mAb/RSFV antigen and F(ab')2/RSVF in this study). Furthermore, subsequent tandem MS analysis of a resulting subunit from microdroplet digestion enabled localizing post-translational modifications on particular domains of a mAb in a rapid fashion. In combination with IdeS digestion of an antibody, additional tris(2-carboxyethyl)phosphine (TCEP) reduction and N-glycosidase F (PNGase F) deglycosylation reactions that facilitate antibody analysis could be realized in "one-pot" spraying. Interestingly, increased deglycosylation yield in microdroplets was found, simply by raising the sample temperature. We expect that our method would have a high impact for rapid characterization of monoclonal antibodies.

Standard-Free Absolute Quantitation of Antibody Deamidation Degradation and Host Cell Proteins by Coulometric Mass Spectrometry.

Proteomic absolute quantitation strategies mainly rely on the use of synthetic stable isotope-labeled peptides or proteins as internal standards, which are highly costly and time-consuming to synthesize. To circumvent this limitation, we recently developed a coulometric mass spectrometry (CMS) approach for absolute quantitation of proteins without the use of standards, based on the electrochemical oxidation of oxidizable surrogate peptides, followed by mass spectrometry measurement of the peptide oxidation yield. Previously, CMS was only applied for single-protein quantitation. In this study, first, we demonstrated absolute quantitation of multiple proteins in a mixture (e.g., ß-lactoglobulin B, α-lactalbumin, and carbonic anhydrase) by CMS in one run, without using any standards. The CMS quantitation result was validated with a traditional isotope dilution method. Second, CMS can be used for absolute quantitation of a low-level target protein in a mixture; for instance, 500 ppm of PLBL2, a problematic host cell protein (HCP), in the presence of a highly abundant monoclonal antibody (mAb) was successfully quantified by CMS with no use of standards. Third, taking one step further, this study demonstrated the unprecedented quantitative analysis of deamidated peptide products arising from the mAb heavy chain deamidation reaction. In particular, absolute quantitation of the deamidation succinimide intermediate which had not been performed before due to the lack of standard was conducted by CMS, for the first time. Overall, our data suggest that CMS has potential utilities for quantitative proteomics and biotherapeutic drug discovery.

Investigation of Tryptic Protein Digestion in Microdroplets and in Bulk Solution.

Recent studies have shown that ultrafast enzymatic digestion of proteins can be achieved in microdroplet within 250 µs. Further investigation of peptides resulting from microdroplet digestion (MD) would be necessary to evaluate it as an alternative to the conventional bulk digestion for bottom-up and biotherapeutic protein characterization. Herein we examined and compared protein tryptic digestion in both MD and bulk solution. In the case of MD of ß-lactoglobulin B, the preservation of long peptides was observed due to the short digestion time. In addition, MD is applicable to digest both high- and low-abundance proteins in mixture. In the case of digesting NIST 8671 mAb antibody containing a low level of commonly encountered host cell protein (HCP) PLBL2 (mAb:PLBL2 = 100:1 by weight), MD produced lower levels of digestion-induced chemical modifications of asparagine/glutamine deamidation, compared with overnight digestion. No significant difference between MD and bulk digestion was observed in terms of trypsin digestion specificity based on examination of semi- and unspecific-cleaved peptides. Our study suggests that MD, a fast digestion approach, could be adopted for bottom-up proteomics research and for peptide mapping of mAbs to characterize site-specific deamidation and glycosylation, for the purpose of development of biopharmaceuticals.

Microdroplet Ultrafast Reactions Speed Antibody Characterization.

Recently, microdroplet reactions have aroused much interest because the microdroplet provides a unique medium where organic reactions could be accelerated by a factor of 103 or more. However, microdroplet reactions of proteins have been rarely studied. We report the occurrence of multiple-step reactions of a large protein, specifically, the digestion, reduction, and deglycosylation of an intact antibody, which can take place in microseconds with high reaction yields in aqueous microdroplets at room temperature. As a result, fast structural characterization of a monoclonal antibody, essential for assessing its quality as a therapeutic drug, can be enabled. We found that the IgG1 antibody can be digested completely by the IdeS protease in aqueous microdroplets in 250 microseconds, a 7.5 million-fold improvement in speed in comparison to traditional digestion in bulk solution (>30 min). Strikingly, inclusion of the reductant tris(2-carboxyethyl)phosphine in the spray solution caused simultaneous antibody digestion and disulfide bond reduction. Digested and reduced antibody fragments were either collected or analyzed online by mass spectrometry. Further addition of PNGase F glycosylase into the spray solution led to antibody deglycosylation, thereby producing reduced and deglycosylated fragments of analytical importance. In addition, glycated fragments of IgG1 derived from glucose modification were identified rapidly with this ultrafast digestion/reduction technique. We suggest that microdroplets can serve as powerful microreactors for both exploring large-molecule reactions and speeding their structural analyses.

Desalting Paper Spay Mass Spectrometry (DPS-MS) for Rapid Detection of Glycans and Glycoconjugates.

The detection of glycans and glycoconjugates has gained increasing attention in biological fields. Traditional mass spectrometry (MS)-based methods for glycoconjugate analysis are challenged with poor intensity when dealing with complex biological samples. We developed a desalting paper spray mass spectrometry (DPS-MS) strategy to overcome the issue of signal suppression of carbohydrates in salted buffer. Glycans and glycoconjugates (i.e., glycopeptides, nucleotide sugars, etc.) in non-volatile buffer (e.g., Tris buffer) can be loaded on the paper substrate from which buffers can be removed by washing with ACN/H2O (90/10 v/v) solution. Glycans or glycoconjugates can then be eluted and spray ionized by adding ACN/H2O/formic acid (FA) (10/90/1 v/v/v) solvent and applying a high voltage (HV) to the paper substrate. This work also showed that DPS-MS is applicable for direct detection of intact glycopeptides and nucleotide sugars as well as determination of glycosylation profiling of antibody, such as NIST monoclonal antibody IgG (NISTmAb). NISTmAb was deglycosylated with PNGase F to release N-linked oligosaccharides. Twenty-six N-linked oligosaccharides were detected by DPS-MS within a 5-minute timeframe without the need for further enrichment or derivatization. This work demonstrates that DPS-MS allows fast and sensitive detection of glycans/oligosaccharides and glycosylated species in complex matrices and has great potential in bioanalysis.

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM.

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. Herein, we report on the use of high-resolution ion mobility spectrometry separations in structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 m SLIM IMS separation, the various drug-bound antibody species could be well resolved for both chains. We also show significantly higher resolution separations were possible for these large ions with SLIM IMS as compared to ones performed on a commercially available (1 m) drift tube IMS-MS platform. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

The effects of nonignorable missing data on label-free mass spectrometry proteomics experiments.

An idealized version of a label-free discovery mass spectrometry proteomics experiment would provide absolute abundance measurements for a whole proteome, across varying conditions. Unfortunately, this ideal is not realized. Measurements are made on peptides requiring an inferential step to obtain protein level estimates. The inference is complicated by experimental factors that necessitate relative abundance estimation and result in widespread non-ignorable missing data. Relative abundance on the log scale takes the form of parameter contrasts. In a complete-case analysis, contrast estimates may be biased by missing data and a substantial amount of useful information will often go unused. To avoid problems with missing data, many analysts have turned to single imputation solutions. Unfortunately, these methods often create further difficulties by hiding inestimable contrasts, preventing the recovery of interblock information and failing to account for imputation uncertainty. To mitigate many of the problems caused by missing values, we propose the use of a Bayesian selection model. Our model is tested on simulated data, real data with simulated missing values, and on a ground truth dilution experiment where all of the true relative changes are known. The analysis suggests that our model, compared with various imputation strategies and complete-case analyses, can increase accuracy and provide substantial improvements to interval coverage.

Rapid Screening of Ellagitannins in Natural Sources via Targeted Reporter Ion Triggered Tandem Mass Spectrometry.

Complex biomolecules present in their natural sources have been difficult to analyze using traditional analytical approaches. Ultrahigh-performance liquid chromatography (UHPLC-MS/MS) methods have the potential to enhance the discovery of a less well characterized and challenging class of biomolecules in plants, the ellagitannins. We present an approach that allows for the screening of ellagitannins by employing higher energy collision dissociation (HCD) to generate reporter ions for classification and collision-induced dissociation (CID) to generate unique fragmentation spectra for isomeric variants of previously unreported species. Ellagitannin anions efficiently form three characteristic reporter ions after HCD fragmentation that allows for the classification of unknown precursors that we call targeted reporter ion triggering (TRT). We demonstrate how a tandem HCD-CID experiment might be used to screen natural sources using UHPLC-MS/MS by application of 22 method conditions from which an optimized data-dependent acquisition (DDA) emerged. The method was verified not to yield false-positive results in complex plant matrices. We were able to identify 154 non-isomeric ellagitannins from strawberry leaves, which is 17 times higher than previously reported in the same matrix. The systematic inclusion of CID spectra for isomers of each species classified as an ellagitannin has never been possible before the development of this approach.

Micro-Data-Independent Acquisition for High-Throughput Proteomics and Sensitive Peptide Mass Spectrum Identification.

State-of-the-art strategies for proteomics are not able to rapidly interrogate complex peptide mixtures in an untargeted manner with sensitive peptide and protein identification rates. We describe a data-independent acquisition (DIA) approach, microDIA (µDIA), that applies a novel tandem mass spectrometry (MS/MS) mass spectral deconvolution method to increase the specificity of tandem mass spectra acquired during proteomics experiments. Using the µDIA approach with a 10 min liquid chromatography gradient allowed detection of 3.1-fold more HeLa proteins than the results obtained from data-dependent acquisition (DDA) of the same samples. Additionally, we found the µDIA MS/MS deconvolution procedure is critical for resolving modified peptides with relatively small precursor mass shifts that cause the same peptide sequence in modified and unmodified forms to theoretically cofragment in the same raw MS/MS spectra. The µDIA workflow is implemented in the PROTALIZER software tool which fully automates tandem mass spectral deconvolution, queries every peptide with a library-free search algorithm against a user-defined protein database, and confidently identifies multiple peptides in a single tandem mass spectrum. We also benchmarked µDIA against DDA using a 90 min gradient analysis of HeLa and Escherichia coli peptides that were mixed in predefined quantitative ratios, and our results showed µDIA provided 24% more true positives at the same false positive rate.

Global Proteomic Changes Induced by the Epstein-Barr Virus Oncoproteins Latent Membrane Protein 1 and 2A.

The Epstein-Barr virus (EBV) oncoproteins latent membrane protein 1 (LMP1) and LMP2A constitutively activate multiple signaling pathways, and both have been shown to interact with cellular ubiquitin ligases and affect cellular ubiquitination. To detect the LMP1- and LMP2A-mediated effects on the global cellular proteome, epithelial cell lines expressing LMP1 or LMP2A were analyzed using label-free quantitative proteomics. To identify proteins whose ubiquitination is affected by the viral proteins, the cells were cultured in the presence and absence of deubiquitinase (DUB) and proteasome inhibitors. More than 7,700 proteins were identified with high confidence and considerably more proteins showed significant differences in expression in the presence of inhibitors. Few of the differentially expressed proteins with or without inhibitors were common between LMP1 and LMP2A, confirming that the viral proteins induce unique changes in cell expression and function. However, ingenuity pathway analysis (IPA) of the data indicated that LMP1 and LMP2A modulate many of the same cellular regulatory pathways, including cell death and survival, cell movement, and actin filament dynamics. In addition, various proteasome subunits, ubiquitin-specific peptidases and conjugating enzymes, vesicle trafficking proteins, and NF-κB and mitogen-activated protein kinase signaling proteins were affected by LMP1 or LMP2A. These findings suggest that LMP1 and LMP2A may commonly target critical cell pathways through effects on distinct genes, with many cellular proteins modified by ubiquitination and/or degradation.IMPORTANCE The Epstein-Barr virus proteins latent membrane protein 1 and 2 have potent effects on cell growth and signaling. Both proteins bind to specific ubiquitin ligases and likely modulate the cellular proteome through ubiquitin-mediated effects on stability and intracellular location. In this study, a comprehensive proteomic analysis of the effects of LMP1 and LMP2A revealed that both proteins affected proteasome subunits, ubiquitin-specific conjugases and peptidases, and vesical trafficking proteins. The data suggest that the effects of these proteins on the abundance and ubiquitination of cellular proteins are in part responsible for their effects on cell growth regulation.

Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer.

To discriminate the patient subpopulations with different clinical outcomes within each breast cancer (BC) subtype, we introduce a robust, clinical-practical, activity-based proteogenomic method that identifies, in their oncogenically active states, candidate biomarker genes bearing patient-specific transcriptomic/genomic alterations of prognostic value. First, we used the intronic splicing enhancer (ISE) probes to sort ISE-interacting trans-acting protein factors (trans-interactome) directly from a tumor tissue for subsequent mass spectrometry characterization. In the retrospective, proteogenomic analysis of patient datasets, we identified those ISE trans-factor-encoding genes showing interaction-correlated expression patterns (iCEPs) as new BC-subtypic genes. Further, patient-specific co-alterations in mRNA expression of select iCEP genes distinguished high-risk patient subsets/subpopulations from other patients within a single BC subtype. Function analysis further validated a tumor-phenotypic trans-interactome contained the drivers of oncogenic splicing switches, representing the predominant tumor cells in a tissue, from which novel personalized biomarkers were clinically characterized/validated for precise prognostic prediction and subsequent individualized alignment of optimal therapy.

Row versus column correlations: avoiding the ecological fallacy in RNA/protein expression studies.

Biomedical researchers are often interested in computing the correlation between RNA and protein abundance. However, correlations can be computed between rows of a data matrix or between columns, and the results are not the same. The belief that these two types of correlation are estimating the same phenomenon is a special case of a well-known logical error called the ecological fallacy. In this article, we review different uses of correlation found in the literature, explain the differences between row and column correlations and argue that one of them has an undesirable interpretation in most applications. Through simulation studies and theoretical derivations, we show that the commonly used Pearson's coefficient, computed from protein and transcript data from a single sample, is only loosely related to the biological correlation that most researchers will be interested in studying. Beyond our basic exploration of the ecological fallacy, we examine how correlations are affected by relative quantification proteomics data and common normalization procedures, finding that double normalization is capable of completely masking true correlative relationships. We conclude with guidelines for properly identifying and computing consistent correlation coefficients.

Proteogenomic integration reveals therapeutic targets in breast cancer xenografts.

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.