Collagen type I alters the proteomic signature of macrophages in a collagen morphology-dependent manner

Idiopathic pulmonary fibrosis is a progressive lung disease that causes scarring and loss of lung function. Macrophages play a key role in fibrosis, but their responses to altered morphological and mechanical properties of the extracellular matrix in fibrosis is relatively unexplored. Our previous work showed functional changes in murine fetal liver-derived alveolar macrophages on fibrous or globular collagen morphologies. In this study, we applied differential proteomics to further investigate molecular mechanisms underlying the observed functional changes. Macrophages cultured on uncoated, fibrous, or globular collagen-coated plastic were analyzed by liquid chromatography-mass spectrometry. The presence of collagen affected expression of 77 proteins, while 142 were differentially expressed between macrophages grown on fibrous or globular collagen. Biological process and pathway enrichment analysis revealed that culturing on any type of collagen induced higher expression of enzymes involved in glycolysis. However, this did not lead to a higher rate of glycolysis, probably because of a concomitant decrease in activity of these enzymes. Our data suggest that macrophages sense collagen morphologies and can respond with changes in expression and activity of metabolism-related proteins. These findings suggest intimate interactions between macrophages and their surroundings that may be important in repair or fibrosis of lung tissue.

BluePrint breast cancer molecular subtyping recognizes single and dual subtype tumors with implications for therapeutic guidance

Purpose

BluePrint (BP) is an 80-gene molecular subtyping test that classifies early-stage breast cancer (EBC) into Basal, Luminal, and HER2 subtypes. In most cases, breast tumors have one dominant subtype, representative of a single activated pathway. However, some tumors show a statistically equal representation of more than one subtype, referred to as dual subtype. This study aims to identify and examine dual subtype tumors by BP to understand their biology and possible implications for treatment guidance.

Methods

The BP scores of over 15,000 tumor samples from EBC patients were analyzed, and the differences between the highest and the lowest scoring subtypes were calculated. Based upon the distribution of the differences between BP scores, a threshold was determined for each subtype to identify dual versus single subtypes.

Results

Approximately 97% of samples had one single activated BluePrint molecular subtype, whereas ~ 3% of samples were classified as BP dual subtype. The most frequently occurring dual subtypes were the Luminal-Basal-type and Luminal-HER2-type. Luminal-Basal-type displays a distinct biology from the Luminal single type and Basal single type. Burstein’s classification of the single and dual Basal samples showed that the Luminal-Basal-type is mostly classified as ‘luminal androgen receptor’ and ‘mesenchymal’ subtypes, supporting molecular evidence of AR activation in the Luminal-Basal-type tumors. Tumors classified as Luminal-HER2-type resemble features of both Luminal-single-type and HER2-single-type. However, patients with dual Luminal-HER2-type have a lower pathological complete response after receiving HER2-targeted therapies in addition to chemotherapy in comparison with patients with a HER2-single-type.

Conclusion

This study demonstrates that BP identifies tumors with two active functional pathways (dual subtype) with specific transcriptional characteristics and highlights the added value of distinguishing BP dual from single subtypes as evidenced by distinct treatment response rates.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-022-06698-x.

The ImPrint immune signature to identify patients with high-risk early breast cancer who may benefit from PD1 checkpoint inhibition in I-SPY2

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Background: The remarkable increase of novel Immuno-Oncology drugs in many malignancies has led to the need for biomarkers to identify who would benefit. Various predictive biomarkers have been developed (PD-1/PD-L1 expression, mutations in mismatch repair genes and microsatellite instability, tumor mutational burden and immune infiltration), none have consistently predicted efficacy. The I-SPY2 consortium qualified several expression-based immune biology related signatures that predict response to PD1 checkpoint inhibition. Here we assessed whole transcriptome data of high-risk early-breast cancer (EBC) patients who received Pembrolizumab within the neoadjuvant biomarker-rich I-SPY2 trial (NCT01042379), aiming to migrate the I-SPY2 research findings to a robust clinical grade platform signature to predict sensitivity to PD1 checkpoint inhibition. Methods: Whole transcriptome microarray data were available from pre-treatment biopsies of 69 HER2- patients enrolled in the Pembrolizumab (4 cycles) arm of the I-SPY2 trial. All patients had a High-Risk 70-gene MammaPrint profile. Pathologic complete response (pCR) was defined as no residual invasive cancer in breast or nodes at the time of surgery. Of the 69 patients, 31 had a pCR (12 HR (hormonal receptor)+HER2-, 19 Triple Negative (TN)), while 38 (28 HR+HER2-, 10 TN) had residual disease (RD). To identify the most predictive genes associated with pCR, gene selection was performed comparing pCR and RD groups by iteratively splitting the dataset in training and test, balancing for HR status. Due to limited sample size, leave one out cross validation was used for performance assessment. Genes with effect size > 0.45 were considered significant. Results: A signature of 53 genes, named ImPrint, was identified with overall sensitivity and specificity > 90% and > 80% for predicting pCR to pembrolizumab in all patients. Sensitivity and specificity in TN were > 95% and ≥70%, and in HR+HER2- > 80% and > 85%, respectively. The Positive Predictive Value (PPV) is 77% for the HR+HER2- subgroup. Biological annotation of the 53 genes showed that over 90% of the genes have known immune system related functions, of which 63% were previously known to be involved in immune response (including genes coding PD-L1 and PD-1, as well as those identified in I-SPY2). Conclusions: In the signature development phase, ImPrint predicts pCR to Pembrolizumab in a set of 69 high risk EBC with high sensitivity and specificity. The signature features genes with immune-related functions known to be involved in immune response indicating that it might aid identifying patients with an immune-active phenotype. Importantly, ImPrint appears effective in identifying a subset of HR+HER2- patients who could benefit from immunotherapy. External validation in independent dataset(s) is ongoing and will be presented at the time of the meeting.

Reference intervals for Sysmex XN hematological parameters as assessed in the Dutch Lifelines cohort

OBJECTIVES

Our aim was to derive reference intervals for all Sysmex XN hematology analyzer parameters. The rationale behind the study was the lack of reference intervals for the XN analyzer cell population data (CPD) and functional parameters.

METHODS

Fresh fasting blood samples from 18,484 participants in the Dutch Lifelines study were analyzed using two automated XN analyzers. Structured health questionnaire data were used to select a subgroup of 15,803 apparently healthy individuals for inclusion in the reference population. The Latent Abnormal Values Exclusion (LAVE) approach was used to reduce the influence of latent diseases in the reference population on the resulting reference intervals. We applied analysis of variance to judge the need for partitioning of the reference intervals by sex or age.

RESULTS

We report reference intervals for 105 XN analyzer hematological parameters with and without applying LAVE. Sex-related partitioning was required for red blood cells, (RBC, RBC-O), hemoglobin (HGB, HGB-O), hematocrit (HCT), mean corpuscular hemoglobin concentration (MCHC), reticulocyte production index (RPI), and side scattered light intensity of the red blood cell population in the RET channel (RBC-Z). Partitioning for age was not warranted. Body mass index (BMI) and smoking had moderate influence on a minority of the parameters.

CONCLUSIONS

We provide reference intervals for all Sysmex XN analyzer routine, CPD and functional parameters, using a direct approach in a large cohort in the Netherlands.

Combined Metabolic and Chemical (CoMetChem) Labeling Using Stable Isotopes-a Strategy to Reveal Site-Specific Histone Acetylation and Deacetylation Rates by LC-MS

Histone acetylation is an important, reversible post-translational protein modification and a hallmark of epigenetic regulation. However, little is known about the dynamics of this process, due to the lack of analytical methods that can capture site-specific acetylation and deacetylation reactions. We present a new approach that combines metabolic and chemical labeling (CoMetChem) using uniformly 13C-labeled glucose and stable isotope-labeled acetic anhydride. Thereby, chemically equivalent, fully acetylated histone species are generated, enabling accurate relative quantification of site-specific lysine acetylation dynamics in tryptic peptides using high-resolution mass spectrometry. We show that CoMetChem enables site-specific quantification of the incorporation or loss of lysine acetylation over time, allowing the determination of reaction rates for acetylation and deacetylation. Thus, the CoMetChem methodology provides a comprehensive description of site-specific acetylation dynamics.

Pipelines and Systems for Threshold-Avoiding Quantification of LC-MS/MS Data

The accurate processing of complex liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS) data from biological samples is a major challenge for metabolomics, proteomics, and related approaches. Here, we present the pipelines and systems for threshold-avoiding quantification (PASTAQ) LC–MS/MS preprocessing toolset, which allows highly accurate quantification of data-dependent acquisition LC–MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parameterization and automatic generation of quality control plots for data and preprocessing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender-related proteins.

Dynamic binning peak detection and assessment of various lipidomics liquid chromatography-mass spectrometry pre-processing platforms

Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics generates large datasets that need to be interpreted using high-performance data pre-processing tools such as XCMS, mzMine, and Progenesis. These pre-processing tools rely heavily on accurate peak detection, which depends on proper setting of the peak detection mass tolerance (PDMT). The PDMT is usually set with a fixed value in either ppm or Da units. However, this fixed value may result in duplicates or missed peak detection and inaccurate peak quantification. To improve the accuracy of peak detection, we developed the dynamic binning method, which considers peak broadening described by the physics of ion separation and sets the PDMT dynamically in function of m/z. In our method, the PDMT is proportional to (mz)² for Fourier-transform ion cyclotron resonance (FTICR), to (mz)^1.5 for Orbitrap and to m/z for Quadrupole time-of-flight (Q-TOF), and is a constant for Quadrupole mass analyzer. The dynamic binning method was implemented in XCMS [1,2], and the adopted source code is available in GitHub at https://github.com/xiaodfeng/DynamicXCMS. We have compared the performance of the XCMS implemented dynamic binning with different popular lipidomics pre-processing tools to find differential compounds. We generated set samples with 43 lipid internal standards that were differentially spiked to aliquots of one human plasma lipid sample using Orbitrap LC-MS/MS. The performance of various pipelines using matched parameter sets was quantified by a quality score system that reflects the ability of a pre-processing pipeline to detect differential peaks spiked at various concentrations. The quality score indicated that our dynamic binning method improves the quantification performance of XCMS (maximum p-value 9.8·10^-3 of two-sample Wilcoxon test) over its original implementation. We also showed that the XCMS with dynamic binning found differential spiked-in lipids better or with similar performance as mzMine and Progenesis do.

Determination of multiple mycotoxins in Qatari population serum samples by LC-MS/MS

Human exposure to mycotoxins is almost inevitable as mycotoxins are naturally occurring contaminants of large portion of food and feed. Depending on the type of mycotoxins, inter-individual mycotoxin adsorption, bioaccumulation, distribution, metabolism and excretion, can cause serious adverse health effects. Therefore, continuous biomonitoring studies of population exposure to mycotoxins are needed. Here we describe a multi-analyte approach for the detection and quantification of 20 mycotoxins in human serum using ultra-performance liquid chromatography-electrospray/tandem mass spectrometry operated in targeted multiple reaction monitoring mode. The validated method was used to assess occurrence of mycotoxins in serum samples of 46 residents of Qatar. Mycotoxins that were detected with high incidence were HT-2 toxin (13.0%), sterigmatocystin (10.9%) and 3-acetyldeoxynivalenol (6.5%). Also, co-exposure to several mycotoxins was noticed in the analysed samples. Our results show that strict food quality control is needed to remove mycotoxin contaminated food from the market in order to minimise human exposure to mycotoxins.

Dietary exposure of the Qatari population to food mycotoxins and reflections on the regulation limits

The article estimates the exposure of the population of Qatar to aflatoxins, fumonisins and ochratoxins, measured in food samples collected from the markets of Doha. The mycotoxin extractions were performed using the "Quick Easy Cheap Effective Rugged Safe" Method (QuEChERS) and the extract measured with LC-MS/MS. High contamination with aflatoxins was detected in Nuts and Spices (e.g. 534.15 ng/g and 371.6 ng/g respectively). The estimated daily intake (EDI) level was estimated using statistical data on average Qatari population. Additionally, the probability to exceed TDI was calculated for fumonisins and ochratoxins. The results indicate high exposure to aflatoxins (with alarming values of margin of exposure, i.e. MoE). The article points to the necessity of a regular assessment and reevaluation of the concentration limits allowed in food products accounting for statistics on the population (i.e. food consumption), economic growth of the country, and monitoring of mycotoxin contamination of food as much as technological, financial and human resources of a country allows.

Application of Displacement Chromatography to Online Two-Dimensional Liquid Chromatography Coupled to Tandem Mass Spectrometry Improves Peptide Separation Efficiency and Detectability for the Analysis of Complex Proteomes

The complexity of mammalian proteomes is a challenge in bottom-up proteomics. For a comprehensive proteome analysis, multidimensional separation strategies are necessary. Online two-dimensional liquid chromatography–tandem mass spectrometry (2D-LC-MS/MS) combining strong cation exchange (SCX) in the first dimension with reversed-phase (RP) chromatography in the second dimension provides a powerful approach to analyze complex proteomes. Although the combination of SCX with RP chromatography provides a good orthogonality, only a moderate separation is achieved in the first dimension for peptides with two (+2) or three (+3) positive charges. The aim of this study was to improve the performance of online SCX-RP-MS/MS by applying displacement chromatography to the first separation dimension. Compared to gradient chromatography mode (GCM), displacement chromatography mode (DCM) was expected to improve the separation of +2-peptides and +3-peptides, thus reducing complexity and increasing ionization and detectability. The results show that DCM provided a separation of +2-peptides and +3-peptides in remarkably sharp zones with a low degree of coelution, thus providing fractions with significantly higher purities compared to GCM. In particular, +2-peptides were separated over several fractions, which was not possible to achieve in GCM. The better separation in DCM resulted in a higher reproducibility and significantly higher identification rates for both peptides and proteins including a 2.6-fold increase for +2-peptides. The higher number of identified peptides in DCM resulted in significantly higher protein sequence coverages and a considerably higher number of unique peptides per protein. Compared to conventionally used salt-based GCM, DCM increased the performance of online SCX-RP-MS/MS and enabled comprehensive proteome profiling in the low microgram range.

Use of Bayesian Statistics for Pairwise Comparison of Megavariate Data Sets: Extracting Meaningful Differences between GCxGC-MS Chromatograms Using Jensen-Shannon Divergence

A new method for comparison of GCxGC-MS is proposed. The method is aimed at spotting the differences between two GCxGC-MS injections, in order to highlight the differences between two samples, in order to flag differences in composition, or to spot compounds only present in one of the samples. The method is based on application of the Jensen-Shannon divergence (JS) analysis combined with Bayesian hypothesis testing. In order to make the method robust against misalignment in both time dimensions, a moving-window approach is proposed. Using a Bayesian framework, we provide a probabilistic visual map (i.e., log likelihood ratio map) of the significant differences between two data sets consequently excluding the deterministic (i.e., "yes" or "no") decision. We proved this approach to be a versatile tool in GCxGC-MS data analysis, especially when the differences are embedded inside a complex matrix. We tested the approach to spot contamination of diesel samples.

Post-polymerization photografting on methacrylate-based monoliths for separation of intact proteins and protein digests with comprehensive two-dimensional liquid chromatography hyphenated with high-resolution mass spectrometry

Post-polymerization photografting is a versatile tool to alter the surface chemistry of organic-based monoliths so as to obtain desired stationary phase properties. In this study, 2-acrylamido-2-methyl-1-propanesulfonic acid was grafted to a hydrophobic poly(butyl methacrylate-co-ethylene glycol dimethacrylate) monolith to create a strong cation exchange stationary phase. Both single-step and two-step photografting were addressed, and the effects of grafting conditions were assessed. An experimental design has been applied in an attempt to optimize three of the key parameters of the two-step photografting chemistry, i.e. the grafting time of the initiator, the monomer concentration and the monomer irradiation time. The photografted columns were implemented in a comprehensive two-dimensional column liquid chromatography (^tLC × ^tLC) workflow and applied for the separation of intact proteins and peptides. A baseline separation of 11 intact proteins was obtained within 20 min by implementing a gradient across a limited RP composition window in the second dimension. ^tLC × ^tLC with UV detection was used for the separation of cytochrome c digest, bovine serum insulin digest and a digest of a complex protein mixture. A semi-quantitative estimation of the occupation of separation space, the orthogonality, of the ^tLC × ^tLC system yielded 75 %. The ^tLC × ^tLC setup was hyphenated to a high-resolution Fourier transform ion cyclotron resonance mass spectrometer instrument to identify the bovine serum insulin tryptic peptides and to demonstrate the compatibility with MS analysis.