MS-based Quantitative Proteomics Research Articles

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy

In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients’ tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets.

Comparative proteomic analysis of edible bird’s nest from different origins

Edible bird’s nest (EBN) mainly made of saliva that secreted by a variety of swiftlets is a kind of precious traditional Chinese medicine. EBNs from different biological and geographical origins exhibit varieties in morphology, material composition, nutritive value and commercial value. Here, we collected four different EBN samples from Huaiji, China (Grass EBN), Nha Trang, Vietnam (Imperial EBN) and East Kalimantan, Indonesia (White EBN and Feather EBN) respectively, and applied label-free quantitative MS-based proteomics technique to identify its protein composition. First, phylogenetic analysis was performed based on cytb gene to identify its biological origin. Second, a total of 37 proteins of EBNs were identified, among which there were six common proteins that detected in all samples and exhibited relatively higher content. Gene ontology analysis revealed the possible function of EBN proteins, and principal component analysis and hierarchical clustering analysis based on 37 proteins were performed to compare the difference of various EBNs. In summary, our study deciphered the common and characteristic protein components of EBNs of different origins and described their possible functions by GO enrichment analysis, which helps to establish an objective and reliable quality evaluation system.

A novel strategy to characterize the pattern of β-lactam antibiotic-induced drug resistance in Acinetobacter baumannii

Carbapenem-resistant Acinetobacter baumannii (CRAb) is an urgent public health threat, according to the CDC. This pathogen has few treatment options and causes severe nosocomial infections with > 50% fatality rate. Although previous studies have examined the proteome of CRAb, there have been no focused analyses of dynamic changes to β-lactamase expression that may occur due to drug exposure. Here, we present our initial proteomic study of variation in β-lactamase expression that occurs in CRAb with different β-lactam antibiotics. Briefly, drug resistance to Ab (ATCC 19606) was induced by the administration of various classes of β-lactam antibiotics, and the cell-free supernatant was isolated, concentrated, separated by SDS-PAGE, digested with trypsin, and identified by label-free LC–MS-based quantitative proteomics. Thirteen proteins were identified and evaluated using a 1789 sequence database of Ab β-lactamases from UniProt, the majority of which were Class C β-lactamases (≥ 80%). Importantly, different antibiotics, even those of the same class (e.g. penicillin and amoxicillin), induced non-equivalent responses comprising various isoforms of Class C and D serine-β-lactamases, resulting in unique resistomes. These results open the door to a new approach of analyzing and studying the problem of multi-drug resistance in bacteria that rely strongly on β-lactamase expression.

Deciphering the underlying mechanisms of the oxidative perturbations and impaired meat quality in Wooden breast myopathy by label-free quantitative MS-based proteomics

The study aimed to investigate biochemical mechanisms occurred in Wooden breast (WB) chicken meat, with attention to the impact on meat quality. Commercial chicken breasts were classified as Normal (N, n = 12), WB-M (moderate degree; focal hardness on cranial region, n = 12) and WB-S (severe degree; extreme and diffused hardness over the entire surface, n = 12). Samples were analyzed for physico-chemical properties, oxidative damage to lipids and proteins, and discriminating sarcoplasmic proteins by using a Q-Exactive mass spectrometer. WB meat presented impaired composition and functionality and higher levels of lipid and protein oxidation markers than N meat. The proteomic profile of WB-S presents a dynamic regulation of the relevant proteins involved in redox homeostasis, carbohydrate, protein and lipid metabolisms. Proteomics results demonstrate that the physiological and metabolic processes of muscles affected by WB myopathy are involved in combating the inflammatory process and in repairing the damaged tissue by oxidative stress.

An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples

BackgroundClinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers.ResultsWe have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC–MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1–5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies.ConclusionsOverall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Quantitative proteomics I.: Concept, design, and planning of quantitative proteomics experiments.

Quantitative proteomics I.: Concept, design, and planning of quantitative proteomics experiments.

A multi-omics study to characterize the transdifferentiation of human dermal fibroblasts to osteoblast-like cells.

Background: Various skeletal disorders display defects in osteoblast development and function. An in vitro model can help to understand underlying disease mechanisms. Currently, access to appropriate starting material for in vitro osteoblastic studies is limited. Native osteoblasts and their progenitors, the bone marrow mesenchymal stem cells, (MSCs) are problematic to isolate from affected patients and challenging to expand in vitro. Human dermal fibroblasts in vitro are a promising substitute source of cells. Method: We developed an in vitro culturing technique to transdifferentiate fibroblasts into osteoblast-like cells. We obtained human fibroblasts from forearm skin biopsy and differentiated them into osteoblast-like cells with ß-glycerophosphate, ascorbic acid, and dexamethasone treatment. Osteoblastic phenotype was confirmed by staining for alkaline phosphatase (ALP), calcium and phosphate deposits (Alizarin Red, Von Kossa) and by a multi-omics approach (transcriptomic, proteomic, and phosphoproteomic analyses). Result: After 14days of treatment, both fibroblasts and MSCs (reference cells) stained positive for ALP together with a significant increase in bone specific ALP (p = 0.04 and 0.004, respectively) compared to untreated cells. At a later time point, both cell types deposited minerals, indicating mineralization. In addition, fibroblasts and MSCs showed elevated expression of several osteogenic genes (e.g. ALPL, RUNX2, BMPs and SMADs), and decreased expression of SOX9. Ingenuity Pathways Analysis of RNA sequencing data from fibroblasts and MSCs showed that the osteoarthritis pathway was activated in both cell types (p_adj. = 0.003 and 0.004, respectively). Discussion: These data indicate that our in vitro treatment induces osteoblast-like differentiation in fibroblasts and MSCs, producing an in vitro osteoblastic cell system. This culturing system provides an alternative tool for bone biology research and skeletal tissue engineering.

ETMR-02. Overexpression of Lin28A in neural progenitor cells in vivo does not lead to brain tumor formation but results in reduced spine density

The RNA binding protein LIN28A is a stem- and progenitor marker and one of the factors necessary to induce pluripotent stem cells. An overexpression of LIN28A has been identified in malignant brain tumors called embryonal tumors with multilayered rosettes (ETMR) but its specific role during brain development remains largely unknown. Radial glia cells of the ventricular zone (VZ) are proposed as a cell of origin for ETMR. We asked whether an overexpression of LIN28A in such cells might affect brain development or result in the formation of brain tumors. Constitutive overexpression of LIN28A in hGFAP-cre::lsl-Lin28A (GL) mice led to a transient increase of proliferation in the cortical VZ at embryonic stages but no postnatal brain tumor formation. Postnatally, GL mice displayed a pyramidal cell layer dispersion of the hippocampus and altered spine and dendrite morphology, including reduced dendritic spine densities in the hippocampus and cortex. GL mice displayed hyperkinetic activity and differential quantitative MS-based proteomics revealed altered time dependent molecular functions regarding mRNA processing and spine morphogenesis. Phosphoproteomic analyses indicated a downregulation of mTOR pathway modulated proteins such as Map1b being involved in microtubule dynamics within a crosstalk of Gsk3b/Rho-Rac/Map1b signaling. In conclusion, we show that Lin28A overexpression transiently increases proliferation of neural precursor cells but it is not sufficient to drive brain tumors in vivo. In contrast, Lin28A impacts on protein abundancy patterns related to spine morphogenesis and phosphorylation levels of proteins involved in microtubule dynamics, resulting in decreased spine densities of neurons in the hippocampus and cortex as well as in altered behavior. Our work provides new insights into the role of LIN28A for neuronal morphogenesis and development and may reveal future targets for treatment of ETMR patients.

Hyperthermia enhances the efficacy of chemotherapeutic drugs in heat-sensitive cells through interfering with DNA damage repair.

BackgroundHyperthermic intraperitoneal chemotherapy (HIPEC) has been shown to be clinically effective, but the mechanisms by which hyperthermia enhances the sensitivity of cells to chemotherapeutic drugs has not yet been elucidated.MethodsTo identify the key molecules involved in thermochemotherapy, this study used mass spectrometry (MS)-based quantitative proteomics technology to analyze the effects of thermochemotherapy on the heat-sensitive ovarian cancer cell line A2780. We divided the A2780 cell line into four groups, one group served as blank control, and the other three groups were stimulated by oxaliplatin, stimulated by hyperthermia at 42 ℃, and stimulated by hyperthermia combined with oxaliplatin. Samples were then collected for tandem mass tag (TMT) labeling, high-performance liquid chromatography fractionation, and MS-based quantitative proteomics for analysis The differentially expressed proteins were quantitatively compared and identified, and Gene Ontology (GO) assessment and cluster analyses were performed. Finally, the above MS results were verified again by Western blotting experiments.ResultsA total of 349 differentially expressed proteins were identified between cells treated with chemotherapy alone (group B) and cells treated with a combination of chemotherapy and hyperthermia (group D). There were 145 upregulated proteins and 204 downregulated proteins. Among the top 20 proteins with significantly different expression levels, nearly two-thirds were involved in DNA damage repair. These proteins were subsequently verified by Western blot analysis. Indeed, consistent with MS data, the expression of the RBL1 protein was significantly upregulated in cells treated with thermochemotherapy (group D) compared to cells treated with chemotherapy alone (group B).ConclusionsIn heat-sensitive ovarian cancer cells, the damage repair of tumor cell DNA is disturbed by hyperthermia, making it unable to fully repair when damaged by chemotherapeutic drugs. As a result, hyperthermia enhances the efficacy of chemotherapeutic drugs. RBL1, as a tumor suppressor gene, may be associated with the repair of DNA damage, and thus it may be a key target for hyperthermia to enhance the sensitivity of thermosensitive cells to chemotherapeutic drugs.

Quantitative Mass Spectrometry by SILAC in Haloferax volcanii.

The development of mass spectrometry (MS)-based proteomics methods has been critical in providing new insight about cellular processes and adaptations in all domains of life. While traditional MS-based methods are not inherently quantitative, technologies are now available to overcome this limitation. Of note, stable isotope labeling of amino acids in cell culture (SILAC) is reported as a reliable tool to label proteomes for quantitative MS-based proteomics that is accurate and flexible for multiplexing. The isotopically labeled lysine and arginine are easily incorporated into the proteome of cells auxotrophic for these amino acids. Microorganisms of the domain Archaea provide a fascinating alternative to understanding cellular adaptations and responses to environmental stresses. However, the availability of preferred SILAC-based quantitative analyses is limited. This protocol describes the use of SILAC to quantitatively analyze the proteome of Haloferax volcanii, a mesophilic halophilic archaeon that is easy to grow and requires no special equipment to maintain.

Overexpression of Lin28A in neural progenitor cells in vivo does not lead to brain tumor formation but results in reduced spine density

LIN28A overexpression has been identified in malignant brain tumors called embryonal tumors with multilayered rosettes (ETMR) but its specific role during brain development remains largely unknown. Radial glia cells of the ventricular zone (VZ) are proposed as a cell of origin for ETMR. We asked whether an overexpression of LIN28A in such cells might affect brain development or result in the formation of brain tumors.Constitutive overexpression of LIN28A in hGFAP-cre::lsl-Lin28A (GL) mice led to a transient increase of proliferation in the cortical VZ at embryonic stages but no postnatal brain tumor formation. Postnatally, GL mice displayed a pyramidal cell layer dispersion of the hippocampus and altered spine and dendrite morphology, including reduced dendritic spine densities in the hippocampus and cortex. GL mice displayed hyperkinetic activity and differential quantitative MS-based proteomics revealed altered time dependent molecular functions regarding mRNA processing and spine morphogenesis. Phosphoproteomic analyses indicated a downregulation of mTOR pathway modulated proteins such as Map1b being involved in microtubule dynamics.In conclusion, we show that Lin28A overexpression transiently increases proliferation of neural precursor cells but it is not sufficient to drive brain tumors in vivo. In contrast, Lin28A impacts on protein abundancy patterns related to spine morphogenesis and phosphorylation levels of proteins involved in microtubule dynamics, resulting in decreased spine densities of neurons in the hippocampus and cortex as well as in altered behavior. Our work provides new insights into the role of LIN28A for neuronal morphogenesis and development and may reveal future targets for treatment of ETMR patients.

Labeling and label-free quantitative proteomics in plant biology

Proteins not only construct cellular structures but also play regulatory functions in plant development and growth. Accurate quantification of protein dynamics, turnover rates, and post-translational modifications provide crucial insights into the molecular mechanisms of biological systems. While early studies only consisted of listing proteins identified in given organs or under specific conditions. There is growing need to apply quantitative proteomic techniques to be biased or unbiased studies of plant protein dynamic changes. With rapid improvements in mass spectrometry (MS) technologies, various proteomic quantification methods have been developed and widely used in biological research. In the meantime, MS-based quantitative proteomics has emerged as a powerful approach for gaining insights into functional aspects of proteins in biological systems. MS is not inherently quantitative; thus, several strategies have been developed to assist MS for protein quantification. These strategies can be distinguished not only by the method of quantification, such as labeled or label-free method, but also by the quantitative goal, such as relative or absolute quantification. They can be also distinguished by the scopes of the experiments performed, such as unbiased or targeted studies. Even within these different research goals, numerous options exist, since each strategy has advantages and disadvantages. For example, labeling methods can tag proteins/peptides with chemical, metabolic, or enzymatic reagents, whereas label-free quantitation methods use spectra ion counting, or peak intensity-based analysis. In comparison with labeling strategies, label-free methods are widely used because of the dynamic quantitative range, costing less, and without labeling steps. However, label-free methods are limited in the sample multiplex capacity and quantitative accuracy. For labeling-based quantitation, materials or samples are labeled by different isotope reagents, the paired MS spectra ions are extracted for relative or absolute quantification. In combination with high accuracy MS instruments, various labeling strategies can be used in quantitative proteome analysis, these methods can be distinguished by quantification ions, such as precursor ion-based, reporter ion-based, peptide-coupled reporter ion-based, and fragment ion-based quantitation. For stable isotope labeled methods, proteins or peptides labeled with different stable isotopes are combined into one vial for LC-MS analysis. These strategies have gained popularity due to the diversity and flexibility of stable isotope reactions, the power to analyze multiple samples simultaneously, and the high quantification accuracy. In this review, we discuss the most widely used label-free and stable isotope-labeling-based proteomic strategies for relative and absolute quantitative proteomics in plants. We compare their strengths and weaknesses in terms of quantitation accuracy, proteome coverage and robustness. We summarize the most promising recent developments and their applications for solving plant biological complexities.

The C-Mannosylome of Human Induced Pluripotent Stem Cells Implies a Role for ADAMTS16 C-Mannosylation in Eye Development

C-mannosylation is a modification of tryptophan residues with a single mannose and can affect protein folding, secretion, and/or function. To date, only a few proteins have been demonstrated to be C-mannosylated, and studies that globally assess protein C-mannosylation are scarce. To interrogate the C-mannosylome of human induced pluripotent stem cells, we compared the secretomes of CRISPR–Cas9 mutants lacking either the C-mannosyltransferase DPY19L1 or DPY19L3 to WT human induced pluripotent stem cells using MS-based quantitative proteomics. The secretion of numerous proteins was reduced in these mutants, including that of A Disintegrin And Metalloproteinase with ThromboSpondin Motifs 16 (ADAMTS16), an extracellular protease that was previously reported to be essential for optic fissure fusion in zebrafish eye development. To test the functional relevance of this observation, we targeted dpy19l1 or dpy19l3 in embryos of the Japanese rice fish medaka (Oryzias latipes) by CRISPR–Cas9. We observed that targeting of dpy19l3 partially caused defects in optic fissure fusion, called coloboma. We further showed in a cellular model that DPY19L1 and DPY19L3 mediate C-mannosylation of a recombinantly expressed thrombospondin type 1 repeat of ADAMTS16 and thereby support its secretion. Taken together, our findings imply that DPY19L3-mediated C-mannosylation is involved in eye development by assisting secretion of the extracellular protease ADAMTS16.

Quantitative proteomics revealed the putative biomarker for detection of early-stage intra-mammary gland infection in cow

Mastitis is defined as inflammation of the mammary gland and one of the most serious concerns with regard to milk production and animal health in the dairy industry. Indeed, mastitis has marked influence on the milk constituents, quality and yield. We performed a comparative proteome analysis of the bovine milk obtained from healthy, sub-clinical and clinical mastitis from Indian indigenous cattle Karan Fries. The collected milk was categorized for stage of mastitis using somatic cell count (SCC), California Mastitis Test (CMT). Whey tryptic peptides were labeled with isobaric tags (iTRAQ), followed by fractionation and desalting and subjected to nano-LC coupled MS (ESI-q-TOF). Using high-resolution MS-based quantitative proteomics, we identified a total of 851 proteins with unique peptide ≥ 2, out of which 231 proteins were differentially expressed having 197 up-regulated and 34 down-regulated proteins having fold change threshold ≥ 2 to ≤ 0.5, respectively. Gene ontology and protein–protein interaction enabled us to correlate the association of DEPs with potential pathways enriched during mammary gland infection. The current study reports potential protein targets which may have potential as biomarkers for identification of mammary gland infection at early stage.

The novel cereblon modulator CC-885 inhibits mitophagy via selective degradation of BNIP3L.

Mitophagy is a degradative pathway that mediates the degradation of the entire mitochondria, and defects in this process are implicated in many diseases including cancer. In mammals, mitophagy is mediated by BNIP3L (also known as NIX) that is a dual regulator of mitochondrial turnover and programmed cell death pathways. Acute myeloid leukemia (AML) cells with deficiency of BNIP3L are more sensitive to mitochondria-targeting drugs. But small molecular inhibitors for BNIP3L are currently not available. Some immunomodulatory drugs (IMiDs) have been proved by FDA for hematologic malignancies, however, the underlining molecular mechanisms are still elusive, which hindered the applications of BNIP3L inhibition for AML treatment. In this study we carried out MS-based quantitative proteomics analysis to identify the potential neosubstrates of a novel thalidomide derivative CC-885 in A549 cells. In total, we quantified 5029 proteins with 36 downregulated in CRBN+/+ cell after CC-885 administration. Bioinformatic analysis showed that macromitophagy pathway was enriched in the negative pathway after CC-885 treatment. We further found that CC-885 caused both dose- and time-dependent degradation of BNIP3L in CRBN+/+, but not CRBN−/− cell. Thus, our data uncover a novel role of CC-885 in the regulation of mitophagy by targeting BNIP3L for CRL4CRBN E3 ligase-dependent ubiquitination and degradation, suggesting that CC-885 could be used as a selective BNIP3L degradator for the further investigation. Furthermore, we demonstrated that CC-885 could enhance AML cell sensitivity to the mitochondria-targeting drug rotenone, suggesting that combining CC-885 and mitochondria-targeting drugs may be a therapeutic strategy for AML patients.

Quantitative MS-Based Proteomics: Comparing the MCF-7 Cellular Response to Hypoxia and a 2-Oxoglutarate Analogue.

The hypoxia‐inducible factors (HIFs) are key transcription factors in determining cellular responses involving alterations in protein levels in response to limited oxygen availability in animal cells. 2‐Oxoglutarate‐dependent oxygenases play key roles in regulating levels of HIF and its transcriptional activity. We describe MS‐based proteomics studies in which we compared the results of subjecting human breast cancer MCF‐7 cells to hypoxia or treating them with a cell‐penetrating derivative (dimethyl N‐oxalylglycine; DMOG) of the stable 2OG analogue N‐oxalylglycine. The proteomic results are consistent with reported transcriptomic analyses and support the proposed key roles of 2OG‐dependent HIF prolyl‐ and asparaginyl‐hydroxylases in the hypoxic response. Differences between the data sets for hypoxia and DMOG might reflect context‐dependent effects or HIF‐independent effects of DMOG.

Quantitative Mass Spectrometric Analysis of Autoantibodies as a Paradigm Shift in Autoimmune Serology.

Affecting ~7–9% of individuals worldwide (1), autoimmunity is a relatively common condition that can cause substantial morbidity and mortality (2). However, there are considerable challenges in finding robust and accurate biomarkers for this heterogeneous group of diseases. Serum autoantibodies have served as archetypal diagnostic biomarkers for autoimmune diseases over decades (3). As pathologic species, they can be used to monitor disease activity and treatment responses (4). Most diagnostic laboratory tests for autoantibodies utilize conventional assays such as the solid-phase enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), or radioimmunoassay (RIA). All of these assays quantitate amounts of autoantibodies in the bodily fluid but fail to delineate their molecular composition. Multiplex assays have emerged for autoantibody high-throughput screening that enable rapid identification of subsets of patients to facilitate diagnostic and predictive medicine (5). This is particularly important since multiple autoantibodies are often responsible for autoimmune disease (6). However, such conventional assays cannot unravel clonal evolution and dynamic autoimmune responses. Frustratingly, prediction of disease onset and flares with these biomarkers remains suboptimal. Mass spectrometry (MS) is an analytical technique which can identify proteins by determining the amino acid sequence of peptides derived from each protein. MS can also measure changes in relative abundance of specific proteins as a consequence of treatment, and with appropriate standards, quantify absolute abundance. MS has been used previously to analyze specific antibodies or the repertoire of antibodies in order to better understand the dynamics of humoral immune responses in vaccinated animals (7). This technology has been used to characterize autoantibodies in diseases such as systemic lupus erythematosus (SLE) and Sjogren's syndrome (SS) by identifying their immunoglobulin variable region (IgV) subfamily usage and mutational profiles at a molecular level (8). Despite conventional immunoassays determining stability in autoantibody profiles, MS-based quantitative proteomics has been used to uncover the dynamic changes in molecular signatures and levels of autoantibodies as the disease progresses (9). Subtle nuances in the molecular profile of patient autoantibodies can be identified, paving the way for new diagnostic biomarkers that can anticipate the onset or severity of disease before conventional biomarkers or immunoassays (10). This exciting technology hence offers a unique opportunity to identify pathogenic “rogue” and/or protective clonotypes that characterize autoimmune diseases. By deconstructing these clonotypes by quantitative proteomics and establishing a database of clonotypes with their corresponding pathogenicity, this would possibly facilitate identification of at-risk patients for deterioration, or predict response to targeted therapy.

Abstract 4898: Clinical application of quantitative multiplex mass spectrometry-based proteomics in predicting clinical outcomes in locally advanced rectal cancer

Abstract Background: Neoadjuvant chemoradiotherapy (CRT) using 5-fluorouracil (5-FU) is a standard treatment for locally advanced rectal cancer (LARC) to improve clinical outcomes. The pathologic responses after neoadjuvant CRT is a major prognostic factor, thus identification of good or poor responder in advance is important. This study is to find candidate predictive biomarkers for CRT and prognosis in LARC patients using quantitative mass spectrometry (MS). Materials and methods: 86 patients with stage II/III LARC, received neoadjuvant CRT consisting of 5-FU/leucovorin followed by surgery were included. 14 proteins potentially associated with 5-FU activity or prognosis were evaluated in archived formalin-fixed, paraffin-embedded pre- and post-CRT tumor tissues using MS: DHFR, DPYD, EGFR, hENT1, Her2, MET, OPRT, p16, TK1, TYMP, TYMS, UCK1, UCK2, UPP1. Tumor regression grade (TRG) after CRT was assessed by Dworak criteria: 0, no regression; 1, dominant tumor mass with obvious fibrosis; 2, dominant fibrotic changes with few tumor cells; 3, very few tumor cells; 4, no tumor cells. Results: TGR was 0 in 2 (2.3%), 1 in 30 (34.9%), 2 in 23 (26.7%), 3 in 20 (23.3%), and 4 in 11(12.8%) patients. Major regression (TRG 2/3/4) was associated with high TK1 (P = 0.040), low TYMS (P = 0.037), p16 (P = 0.055), and UPP1 (P = 0.028) levels. Among the pre-CRT parameters, low CEA level (<5ng/mL, P = 0.013), clinical stage II (P<0.001), tumor differentiation (good, P = 0.052), low EGFR level (<200amol/ug, P=0.006), undetectable TYMS level (P = 0.070) were associated with longer recurrence-free survival (RFS). Among the post-CRT parameters, major pathologic response (P = 0.001), and the absence of lymphatic (P<0.001)/ vascular (P= 0.025)/ perineural invasion (P = 0.001) was associated with longer RFS. For 71 patients with available paired pre- and post-CRT tissues, the changes of protein expression were calculated. The pre-CRT/post-CRT ratio of DHFR (>1.1), Her2 (<1.25), MET (≥0.8), p16 (<2), TK1 (≥0.9) showed trend toward long RFS. Multivariate analysis showed that the presence of lymphatic invasion (HR=3.07; 95% CI, 1.35-7.01; P = 0.008) and pre-CRT high EGFR level (≥200amol/ug; HR=2.23; 95% CI, 1.03-4.83; P = 0.042) were significantly associated with shorter RFS. The presence of lymphatic invasion (P=0.005), positive pre-CRT TYMS level (P = 0.008), and high CEA level (P = 0.015) were significantly related to short survival. Conclusions: Quantitative MS-based proteomics can facilitate the identification of predictive biomarkers of CRT responses and prognosis in LARC patients. Citation Format: Ho Jung An, Ji-Han Jung, Byoung Yong Shim, Hyung Soon Park, Hyeon-Min Cho, Hyung-Jin Kim, Ri Na Yoo, Sung Hwan Kim, Jonghoon Lee, Kang-Moon Lee, Dae Bum Kim, Ji Min Lee. Clinical application of quantitative multiplex mass spectrometry-based proteomics in predicting clinical outcomes in locally advanced rectal cancer [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 4898.

Proteome-wide analysis of protein abundance and turnover remodelling during oncogenic transformation of human breast epithelial cells

Background: Viral oncogenes and mutated proto-oncogenes are potent drivers of cancer malignancy. Downstream of the oncogenic trigger are alterations in protein properties that give rise to cellular transformation and the acquisition of malignant cellular phenotypes. Developments in mass spectrometry enable large-scale, multidimensional characterisation of proteomes. Such techniques could provide an unprecedented, unbiased view of how oncogene activation remodels a human cell proteome. Methods: Using quantitative MS-based proteomics and cellular assays, we analysed how transformation induced by activating v-Src kinase remodels the proteome and cellular phenotypes of breast epithelial (MCF10A) cells. SILAC MS was used to comprehensively characterise the MCF10A proteome and to measure v-Src-induced changes in protein abundance across seven time-points (1-72 hrs). We used pulse-SILAC MS ( Boisvert et al., 2012), to compare protein synthesis and turnover in control and transformed cells. Follow-on experiments employed a combination of cellular and functional assays to characterise the roles of selected Src-responsive proteins. Results: Src-induced transformation changed the expression and/or turnover levels of ~3% of proteins, affecting ~1.5% of the total protein molecules in the cell. Transformation increased the average rate of proteome turnover and disrupted protein homeostasis. We identify distinct classes of protein kinetics in response to Src activation. We demonstrate that members of the polycomb repressive complex 1 (PRC1) are important regulators of invasion and migration in MCF10A cells. Many Src-regulated proteins are present in low abundance and some are regulated post-transcriptionally. The signature of Src-responsive proteins is highly predictive of poor patient survival across multiple cancer types. Open access to search and interactively explore all these proteomic data is provided via the EPD database ( www.peptracker.com/epd). Conclusions: We present the first comprehensive analysis measuring how protein expression and protein turnover is affected by cell transformation, providing a detailed picture at the protein level of the consequences of activation of an oncogene.

Proteome-wide analysis of protein abundance and turnover remodelling during oncogenic transformation of human breast epithelial cells.

Background: Viral oncogenes and mutated proto-oncogenes are potent drivers of cancer malignancy. Downstream of the oncogenic trigger are alterations in protein properties that give rise to cellular transformation and the acquisition of malignant cellular phenotypes. Developments in mass spectrometry enable large-scale, multidimensional characterisation of proteomes. Such techniques could provide an unprecedented, unbiased view of how oncogene activation remodels a human cell proteome. Methods: Using quantitative MS-based proteomics and cellular assays, we analysed how transformation induced by activating v-Src kinase remodels the proteome and cellular phenotypes of breast epithelial (MCF10A) cells. SILAC MS was used to comprehensively characterise the MCF10A proteome and to measure v-Src-induced changes in protein abundance across seven time-points (1-72 hrs). We used pulse-SILAC MS ( Boisvert et al., 2012), to compare protein synthesis and turnover in control and transformed cells. Follow-on experiments employed a combination of cellular and functional assays to characterise the roles of selected Src-responsive proteins. Results: Src-induced transformation changed the expression and/or turnover levels of ~3% of proteins, affecting ~1.5% of the total protein molecules in the cell. Transformation increased the average rate of proteome turnover and disrupted protein homeostasis. We identify distinct classes of protein kinetics in response to Src activation. We demonstrate that members of the polycomb repressive complex 1 (PRC1) are important regulators of invasion and migration in MCF10A cells. Many Src-regulated proteins are present in low abundance and some are regulated post-transcriptionally. The signature of Src-responsive proteins is highly predictive of poor patient survival across multiple cancer types. Open access to search and interactively explore all these proteomic data is provided via the EPD database ( www.peptracker.com/epd). Conclusions: We present the first comprehensive analysis measuring how protein expression and protein turnover is affected by cell transformation, providing a detailed picture at the protein level of the consequences of activation of an oncogene.