Quantitative mass spectrometry analysis using PAcIFIC for the identification of plasma diagnostic biomarkers for abdominal aortic aneurysm

Background

Abdominal aortic aneurysm (AAA) is characterized by increased aortic vessel wall diameter (>1.5 times normal) and loss of parallelism. This disease is responsible for 1–4% mortality occurring on rupture in males older than 65 years. Due to its asymptomatic nature, proteomic techniques were used to search for diagnostic biomarkers that might allow surgical intervention under nonlife threatening conditions.

Methodology/Principal Findings

Pooled human plasma samples of 17 AAA and 17 control patients were depleted of the most abundant proteins and compared using a data-independent shotgun proteomic strategy, Precursor Acquisition Independent From Ion Count (PAcIFIC), combined with spectral counting and isobaric tandem mass tags. Both quantitative methods collectively identified 80 proteins as statistically differentially abundant between AAA and control patients. Among differentially abundant proteins, a subgroup of 19 was selected according to Gene Ontology classification and implication in AAA for verification by Western blot (WB) in the same 34 individual plasma samples that comprised the pools. From the 19 proteins, 12 were detected by WB. Five of them were verified to be differentially up-regulated in individual plasma of AAA patients: adiponectin, extracellular superoxide dismutase, protein AMBP, kallistatin and carboxypeptidase B2.

Conclusions/Significance

Plasma depletion of high abundance proteins combined with quantitative PAcIFIC analysis offered an efficient and sensitive tool for the screening of new potential biomarkers of AAA. However, WB analysis to verify the 19 PAcIFIC identified proteins of interest proved inconclusive save for five proteins. We discuss these five in terms of their potential relevance as biological markers for use in AAA screening of population at risk.     

Quest for novel cardiovascular biomarkers by proteomic analysis

Atherosclerosis, and the resulting coronary heart disease and stroke, is the most common cause of death in developed countries. Atherosclerosis is an inflammatory process that results in the development of complex lesions or plaques that protrude into the arterial lumen. Plaque rupture and thrombosis result in the acute clinical complications of myocardial infarction (MI) and stroke. Although certain risk factors (dyslipidemias, diabetes, hypertension) and humoral markers of plaque vulnerability (C-reactive protein, interleukin-6, 10 and 18, CD40L) have been identified, a highly sensitive and specific biomarker or protein profile, which could provide information on the stability/vulnerability of atherosclerotic lesions, remains to be identified. In this review, we report several proteomic approaches which have been applied to circulating or resident cells, atherosclerotic plaques or plasma, in the search for new proteins that could be used as cardiovascular biomarkers. First, an example using a differential proteomic approach (2-DE and MS) comparing the secretome from control mammary arteries and atherosclerotic plaques is displayed. Among the different proteins identified, we showed that low levels of HSP-27 could be a potential marker of atherosclerosis. Second, we have revised several studies performed in cells involved in the pathogenesis of atherosclerosis (foam cells and smooth muscle cells). Another approach consists of performing proteomic analysis on circulating cells or plasma, which will provide a global view of the whole body response to atherosclerotic aggression. Circulating cells can bear information reflecting directly an inflammatory or pro-coagulant state related to the pathology. As an illustration, we report that circulating monocytes and plasma in patients with acute coronary syndromes has disclosed that mature Cathepsin D is increased both in the plasma and monocytes of these patients. Finally, the problems of applying proteomic approach directly to plasma will be discussed. The purpose of this review is to provide the reader with an overview of different proteomic approaches that can be used to identify new biomarkers in vascular diseases.     

Proteomic identification of plasma biomarkers in uterine leiomyoma

Recent progresses in quantitative proteomics have offered opportunities to discover plasma proteins as biomarkers for tracking the progression and for understanding the molecular mechanisms of uterine leiomyomas. In the present study, plasma samples were analyzed by fluorescence two-dimensional differential gel electrophoresis (2D-DIGE) and differentially expressed proteins were identified by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In total, 20 proteins have been firmly identified representing 13 unique gene products. These proteins mainly functioned in transportation (such as apolipoprotein A-I) and coagulation (such as fibrinogen gamma chain). Additionally, our quantitative proteomic approach has identified numerous previous reported plasma markers of uterine leiomyomas such as alpha-1-antitrypsin. On the contrary, we have presented several putative uterine leiomyomas biomarkers including afamin, apolipoprotein A-I, carbonic anhydrase 1, fibrinogen beta chain, fibrinogen gamma chain, gelsolin, hemopexin, leucine-rich alpha-2-glycoprotein, serotransferrin and vitamin D-binding protein which have not been reported and may be associated with the progression and development of the disease. In summary, we report a comprehensive patient-based proteomic approach for the identification of potential plasma biomarkers for uterine leiomyomas. The potential of utilizing these markers for screening and treating uterine leiomyomas warrants further investigations.     

Proteomics analysis of kojic acid treated A375 human malignant melanoma cells

Although the toxicogenomics of kojic acid treated A375 human malignant melanoma cells has been elucidated, the proteomics of cellular response is still poorly understood. We performed proteomic analysis to investigate the anticancer effect of kojic acid on protein expression profile in A375 cells. A375 cells were treated with kojic acid at 8 microg/mL for 24, 48, and 72 h. With the use of 2-D PAGE and MALDI-Q-TOF MS and MS/MS analyses, proteomic profiles of A375 cells between control and kojic acid treatment were compared, and 30 differentially expressed proteins, containing 2 up-regulated proteins and 28 down-regulated proteins, were identified. Among these proteins, 17 isoforms of 5 identical proteins were observed and 11 chaperone proteins showed the high proportion of protein spots with 36.7% of total proteins. Bioinformatic tools were used to search for protein function and prediction of protein interaction. Sixteen differentially expressed proteins exhibited interaction network linked to the downstream regulations of p53 tumor suppressor and cell apoptosis, which may lead to suppress the melanogenesis and tumorigenesis of kojic acid treated A375 cells. In addition, GRP75, VIME and 2AAA were validated by Western blot analysis, whereas GRP75, 2AAA, HS90B, ENPL and KPYM were validated by RT-PCR. Therefore, these proteins play the important roles in cancer progression and may be potential biomarkers that are useful for diagnostic and therapeutic applications of malignant melanoma cancer.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.     

Plasma protein changes in horse after prolonged physical exercise: a proteomic study

Physical exercise induces various stress responses and metabolic adaptations that have not yet been completely elucidated. Novel biomarkers are needed in sport veterinary medicine to monitor training levels and to detect subclinical conditions that can develop into exercise-related diseases. In this study, protein modifications in horse plasma induced by prolonged, aerobic physical exercise were investigated by using a proteomic approach based on 2-DE and combined mass spectrometry procedures. Thirty-eight protein spots, associated with expression products of 13 genes, showed significant quantitative changes; spots identified as membrane Cu amine oxidase, α-1 antitrypsin, α-1 antitrypsin-related protein, caeruloplasmin, α-2 macroglobulin and complement factor C4 were augmented in relative abundance after the race, while haptoglobin β chain, apolipoprotein A-I, transthyretin, retinol binding protein 4, fibrinogen γ chain, complement factor B and albumin fragments were reduced. These results indicate that prolonged physical exercise affects plasma proteins involved in pathways related to inflammation, coagulation, immune modulation, oxidant/antioxidant activity and cellular and vascular damage, with consequent effects on whole horse metabolism.     

Proteomic analysis of human pleural effusion

Pleural effusion, an accumulation of pleural fluid, contains proteins originating from plasma filtrate and, especially when tissues are damaged, parenchymal interstitial spaces of lungs and/or other organs. This report presents data of the first global proteomic analysis of human pleural effusion. A composite sample was prepared by pooling pleural effusions from seven lung adenocarcinoma patients. Two-dimensional gel electrophoresis analysis of the composite sample revealed 472 silver-stained spots. 242 selected gel spots were subjected to protein identification by in-gel digestion, liquid chromatography-tandem mass spectrometry, and sequence database search. 44 proteins were identified with higher confidence levels (at least two unique peptide sequences matched), while 161 other proteins were identified at the minimal confidence level (only one unique peptide sequence matched). The data provide fundamental information on the composition of protein contents in human pleural effusion. Among these 44 proteins that were identified with higher confidence levels, 7 proteins, retinoblastoma binding protein 7, synaptic vesicle membrane protein, corticosteroid binding globulin precursor, PR-domain containing protein 11, envelope glycoprotein, MSIP043 protein, and titin have not been reported in plasma and may represent proteins specifically present in pleural effusion. These proteins could have originated from parenchymal interstitial spaces and represent potential candidates of useful biomarkers that could not be readily detected in plasma but in pleural effusion. Retinoblastoma binding protein 7 is of special interest since it may play a role in the regulation of cell proliferation and differentiation.     

Proteomic analysis of gingival crevicular fluid for discovery of novel periodontal disease markers

The protein composition of gingival crevicular fluid (GCF) may reflect the pathophysiology of periodontal diseases. A standard GCF proteomic pattern of healthy individuals would serve as a reference to identify biomarkers of periodontal diseases by proteome analyses. However, protein profiles of GCF obtained from apparently healthy individuals have not been well explored. As a step toward detection of proteomic biomarkers for periodontal diseases, we applied both gel-based and gel-free methods to analyze GCF obtained from healthy subjects as compared with supragingival saliva. To ensure optimized protein extraction from GCF, a novel protocol was developed. The proteins in GCF were extracted with high yield by urea buffer combined with ultrafiltration and the intensity of spots with supragingival saliva and GCF was compared using agarose two-dimensional electrophoresis. Eight protein spots were found to be significantly more intense in GCF. They included superoxide dismutase 1 (SOD1), apolipoprotein A-I (ApoA-I), and dermcidin (DCD). Moreover, GCF proteins from healthy subjects were broken down into small peptide fragments and then analyzed directly by LC-MS/MS analysis. A total of 327 proteins including ApoA-I, SOD1, and DCD were identified in GCF. These results may serve as reference for future proteomic studies searching for GCF biomarkers of periodontal diseases.     

Proteomic Analysis of the Aqueous Humor in Age-related Macular Degeneration (AMD) Patients

Age-related macular degeneration (AMD) can lead to irreversible central vision loss in the elderly. Although large number of growth factor pathways, including the vascular endothelial growth factor (VEGF), has been implicated in the pathogenesis of AMD, no study has directly assessed the whole proteomic composition in the aqueous humor (AH) among AMD patients. The AH contains proteins secreted from the anterior segment tissue, and these proteins may play an important role in the pathogenesis of AMD. Thus, comparisons between the AH proteomic profiles of AMD patients and non-AMD controls may lead to the verification of novel pathogenic proteins useful as potential clinical biomarkers. In this study, we used discovery-based proteomics and Multiple Reaction Monitoring Mass Spectrometry (MRM-MS) to analyze AH from AMD patients and AH from controls who underwent cataract surgery. A total of 154 proteins with at least two unique peptides were identified in the AH. Of these 154 proteins identified by discovery-based proteomics, 10 AH proteins were novel identifications. The protein composition in the AH was different between AMD patients and non-AMD controls. Subsequently, a systematic MRM-MS assay was performed in seven highly abundant differentially expressed proteins from these groups. Differential expression of three proteins was observed in the AH of AMD patients compared with that of cataract controls (p < 0.0312). Elucidation of the aqueous proteome will establish a foundation for protein function analysis and identify differentially expressed markers associated with AMD. This study demonstrates that integrated proteomic technologies can yield novel biomarkers to detect exudative AMD.     

Plasma and cerebrospinal fluid-based protein biomarkers for motor neuron disease

Motor neuron diseases (MNDs) and, in particular, amyotrophic lateral sclerosis (ALS), are a heterogeneous group of neurologic disorders characterized by the progressive loss of motor function. In ALS, a selective and relentless degeneration of both upper and lower motor neurons occurs, culminating in mortality typically within 5 years of symptom onset. However, survival rates vary among individual patients and can be from a few months to >10 years from diagnosis. Inadequacies in disease detection and treatment, along with a lack of diagnostic and prognostic tools, have prompted many to turn to proteomics-based biomarker discovery efforts. Proteomics refers to the study of the proteins expressed by a genome at a particular time, and the proteome can respond to and reflect the status of an organism, including health and disease states. Although an emerging field, proteomic applications promise to uncover biomarkers critical for differentiating patients with ALS and other MNDs from healthy individuals and from patients affected by other diseases. Ideally, these studies will also provide mechanistic information to facilitate identification of new drug targets for subsequent therapeutic development. In addition to proper experimental design, standard operating procedures for sample acquisition, preprocessing, and storage must be developed. Biological samples typically analyzed in proteomic studies of neurologic diseases include both plasma and cerebrospinal fluid (CSF). Recent studies have identified individual proteins and/or protein panels from blood plasma and CSF that represent putative biomarkers for ALS, although many of these proteins are not unique to this disease. Continued investigations are required to validate these initial findings and to further pursue the role of these proteins as diagnostic biomarkers or surrogate markers of disease progression. Protein biomarkers specific to ALS will additionally function to evaluate drug efficacy in clinical trials and to identify novel targets for drug design. It is hoped that proteomic technologies will soon integrate the basic biology of ALS with mechanistic disease information to achieve success in the clinical setting.     

Biomarkers of systemic lupus erythematosus identified using mass spectrometry‐based proteomics: a systematic review

Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry‐based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta‐analyses guidelines. Twenty‐five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice.     

Establishment of a 2-D human urinary proteomic map in IgA nephropathy

Immunoglobulin A nephropathy (IgAN) is the most common form of immune complex-mediated glomerulonephritis worldwide. Although chronic renal failure develops in considerable numbers of IgAN patients, the exact etiology has not yet been clearly elucidated. To establish the urinary protein map of IgAN, we performed a urinary proteomic analysis. Thirteen patients with IgAN and 12 normal controls were recruited. Morning midstream spot urine samples were used with Centriprep ultrafiltration for concentration and desalting. 2-DE was performed and compared between IgAN and normal control, and urinary proteins were identified by MALDI-TOF MS. A large number of protein spots were identified in IgAN and normal control samples, with means of 311 spots and 174 spots, respectively. Approximately 216 protein spots were detected as differentially expressed in IgAN. Among these, 82 spots were over-expressed, and 134 spots were under-expressed compared to normal controls. A total of 84 differentially expressed spots, representing 59 different proteins, were finally identified in IgAN. We have established a urinary proteomic map of IgAN and this result helps in the identification. Further study is needed to determine the potential pathogenic role of these proteins.     

In-silico selection of cancer blood plasma proteins by integrating genomic and proteomic databases

Blood protein markers have been studied for the clinical management of cancer. Due to the large number of the proteins existing in blood, it is often necessary to pre-select potential protein markers before experimental studies. However, to date there is a lack of automated method for in-silico selection of cancer blood proteins that integrates the information from both genetic and proteomic studies in a cancer-specific manner. In this work, we synthesized both genomic and proteomic information from several open access databases and established a bioinformatic pipeline for in-silico selection of blood plasma proteins overexpressed in specific type of cancer. We demonstrated the workflow of this pipeline with an example of breast cancer, while the methodology was applicable for other cancer types. With this pipeline we obtained 10 candidate biomarkers for breast cancer. The proposed pipeline provides a useful and convenient tool for in-silico selection of candidate blood protein biomarkers for a variety of cancer research.     

Identification of differentially expressed proteins in blood plasma of control and cigarette smoke-exposed mice by 2-D DIGE/MS

Cigarette smoke exposure is known to induce obstructive lung disease and several cardiovascular disease states in humans and also in animal models. Smoking leads to oxidative stress and inflammation that are important in triggering pulmonary and cardiovascular disease. The objective of the current study was to quantify differences in expression levels of plasma proteins of cigarette smoke -exposed and control mice, at the time of disease onset, and identify these proteins for use as potential biomarkers of the onset of smoking-induced disease. We utilized 2-D DIGE/MS to characterize these proteomic changes. 2-D DIGE of plasma samples identified 11 differentially expressed proteins in cigarette smoke -exposed mice. From these 11 proteins, 9 were downregulated and 2 were upregulated. The proteins identified are involved in vascular function, coagulation, metabolism and immune function. Among these, the alterations in fibrinogen (2.2-fold decrease), α-1-antitrypsin (1.8-fold increase) and arginase (4.5-fold decrease) are of particular interest since these have been directly linked to cardiovascular and lung pathology. Differences in expression levels of these proteins were also confirmed by immunoblotting. Thus, we observe that chronic cigarette smoke exposure in mice leads to prominent changes in the protein expression profile of blood plasma and these changes in turn can potentially serve as markers predictive of the onset and progression of cardiovascular and pulmonary disease.     

Proteomic profiling of cerebrospinal fluid identifies prostaglandin D2 synthase as a putative biomarker for pediatric medulloblastoma: A pediatric brain tumor consortium study

The aims of this study were to demonstrate the feasibility of centrally collecting and processing high-quality cerebrospinal fluid (CSF) samples for proteomic studies within a multi-center consortium and to identify putative biomarkers for medulloblastoma in CSF. We used 2-DE to investigate the CSF proteome from 33 children with medulloblastoma and compared it against the CSF proteome from 25 age-matched controls. Protein spots were subsequently identified by a combination of in-gel tryptic digestion and MALDI-TOF TOF MS analysis. On average, 160 protein spots were detected by 2-DE and 76 protein spots corresponding to 25 unique proteins were identified using MALDI-TOF. Levels of prostaglandin D2 synthase (PGD2S) were found to be six-fold decreased in the tumor samples versus control samples (p<0.00001). These data were further validated using ELISA. Close examination of PGD2S spots revealed the presence of complex sialylated carbohydrates at residues Asn(78) and Asn(87) . Total PGD2S levels are reduced six-fold in the CSF of children with medulloblastoma most likely representing a host response to the presence of the tumor. In addition, our results demonstrate the feasibility of performing proteomic studies on CSF samples collected from patients at multiple institutions within the consortium setting.     

Proteomic and cytokine plasma biomarkers for predicting progression from colorectal adenoma to carcinoma in human patients

In the present study, we screened proteomic and cytokine biomarkers between patients with adenomatous polyps and colorectal cancer (CRC) in order to improve our understanding of the molecular mechanisms behind turmorigenesis and tumor progression in CRC. To this end, we performed comparative proteomic analysis of plasma proteins using a combination of 2DE and MS as well as profiled differentially regulated cytokines and chemokines by multiplex bead analysis. Proteomic analysis identified 11 upregulated and 13 downregulated plasma proteins showing significantly different regulation patterns with diagnostic potential for predicting progression from adenoma to carcinoma. Some of these proteins have not previously been implicated in CRC, including upregulated leucine‐rich α‐2‐glycoprotein, hemoglobin subunit β, Ig α‐2 chain C region, and complement factor B as well as downregulated afamin, zinc‐α‐2‐glycoprotein, vitronectin, and α‐1‐antichymotrypsin. In addition, plasma levels of three cytokines/chemokines, including interleukin‐8, interferon gamma‐induced protein 10, and tumor necrosis factor α, were remarkably elevated in patients with CRC compared to those with adenomatous polyps. Although further clinical validation is required, these proteins and cytokines can be established as novel biomarkers for CRC and/or its progression from colon adenoma.     

Proteome Analysis of Cerebrospinal Fluid in Amyotrophic Lateral Sclerosis (ALS)

Cerebrospinal fluid (CSF) is a promising source of biomarkers in amyotrophic lateral sclerosis (ALS). Using the two-dimensional difference in gel electrophoresis (2-D-DIGE), we compared CSF samples from patients with ALS (n = 14) with those from normal controls (n = 14). Protein spots that showed significant differences between patients and controls were selected for further analysis by MALDI-TOF mass spectrometry. For validation of identified spots western blot analysis and ELISA was performed. We identified 2 proteins that were upregulated and 3 proteins that were down-regulated in CSF in ALS. Of these, two proteins (Zn-alpha-2-glycoprotein and ceruloplasmin precursor protein) have not been reported in CSF of patients with ALS so far. In contrast, several other proteins (transferrin, alpha-1-antitrypsin precursor and beta-2-microglobulin) seem to be unspecifically affected in different neurological diseases and may therefore be of limited value as disease-related biochemical markers in ALS. Further evaluation of the candidate proteins identified here is necessary.     

Pilot and feasibility study: comparative proteomic analysis by 2-DE MALDI TOF/TOF MS reveals 14-3-3 proteins as putative biomarkers of response to neoadjuvant chemotherapy in ER-positive breast cancer

Neoadjuvant chemotherapy is used to treat oestrogen receptor-positive breast cancer however chemo-resistance is a major obstacle in this molecular subtype. The ability to predict tumour response would allow chemotherapy administration to be directed towards patients who would most benefit, thus maximising treatment efficacy. We aimed to identify protein biomarkers associated with response to neoadjuvant chemotherapy, in a pilot study using comparative 2-DE MALDI TOF/TOF MS proteomic analysis of breast tumour samples. A total of 3 comparative proteomic experiments were performed, comparing protein expression between chemotherapy-sensitive and chemotherapy-resistant oestrogen receptor-positive invasive ductal carcinoma tissue samples. This identified a list of 132 unique proteins that were significantly differentially expressed (≥ 2 fold) in chemotherapy resistant samples, 57 of which were identified in at least two experiments. Ingenuity? Pathway Analysis was used to map the 57 DEPs onto canonical signalling pathways. We implicate several isoforms of 14-3-3 family proteins (theta/tau, gamma, epsilon, beta/alpha and zeta/delta), which have previously been associated with chemotherapy resistance in breast cancer. Extensive clinical validation is now required to fully assess the role of these proteins as putative markers of chemotherapy response in luminal breast cancer subtypes.