Bronchoalveolar Lavage Proteomics in Patients with Suspected Lung Cancer

All experiments including MS analysis were supported by Fundacao para a Ciencia e Tecnologia project EXPL/DTP-PIC/0616/2013. RM is supported by FCT investigator program 2012 (IF/01002/2012). ASC is supported by grant SFRH/BPD/85569/2012 funded by Fundacao para a Ciencia e Tecnologia.Lung cancer configures as one of the deadliest types of cancer. The future implementation of early screening methods such as exhaled breath condensate analysis and low dose computed tomography (CT) as an alternative to current chest imaging based screening will lead to an increased burden on bronchoscopy units. New approaches for improvement of diagnosis in bronchoscopy units, regarding patient management, are likely to have clinical impact in the future. Diagnostic approaches to address mortality of lung cancer include improved early detection and stratification of the cancers according to its prognosis and further response to drug treatment. In this study, we performed a detailed mass spectrometry based proteome analysis of acellular bronchoalveolar lavage (BAL) fluid samples on an observational prospective cohort consisting of 90 suspected lung cancer cases which were followed during two years. The thirteen new lung cancer cases diagnosed during the follow up time period clustered, based on liquid chromatography-mass spectrometry (LC-MS) data, with lung cancer cases at the time of BAL collection. Hundred and thirty-tree potential biomarkers were identified showing significantly differential expression when comparing lung cancer versus non-lung cancer. The regulated biomarkers showed a large overlap with biomarkers detected in tissue samples.publishersversionpublishe

Immunopeptidomics and autoantigens of interstitial lung diseases

We investigate Sarcoidosis and Idiopathic Pulmonary Fibrosis, IPF, to find markers for early fibrosis development. The aetiologies for both diseases are unknown and there is no specific treatment, moreover, there is a lack of diagnostic biomarkers for both diagnose and disease activity. Overall, the diseases have a considerable effect on patients’ physical health and quality of life. To identify patients at risk of rapid development of fibrosis, it is vital to improve patient care. We hypothesize that identification of specific antigens can help in the exposition of the pathogenesis of sarcoidosis as well as of IPF, and in the long perspective this could lead to identification of therapeutic targets. In project I we investigated the presence of proteins in BAL and serum from sarcoidosis patients and controls to discover disease associated proteins. In total eight proteins had increased levels in sarcoidosis patients, two were the most prominent (Fibronectin 1, FN1 and C-C motif chemokine 2, CCL2) that displayed the greatest differences between cohorts. Furthermore, the protein cadherin 5 (CDH5) had a positive association to lymphocyte count in BAL, interesting since T-lymphocytes are the major cell type in sarcoidosis. Potentially this could provide a way of monitoring lymphocyte presence in the lung through blood sample. In project II the large source of antigens from the Human Protein Atlas Project, a large library of protein fragments and antibodies that represent virtually all proteins in the body, was used to screen the immunoglobulin G specificity towards 3072 selected antigens in serum and BAL samples from patients with either of the sarcoidosis subcategories (Löfgren's syndrome (LS), non-Löfgren's sarcoidosis (nLS)), and asthma as well as healthy controls. A selected set of antigens went on to be analyzed in mSBA analysis. Sarcoidosis patients demonstrated an elevated reactivity frequencies toward Zinc finger protein 688 (ZNF688) and mitochondrial ribosomal protein L43 (MRPL43), particularly MRLP43 displayed a higher frequency in patients with non-Löfgren syndrome. Even though the protein fragment representing adenosine diphosphate-ribosylation factor GTPase activating protein 1 (ARFGAP1) showed high reactivity frequency in all sample groups, it was still significantly elevated in patients with sarcoidosis compared to the other cohorts. In project III we used a mass spectrometry-based method to analyze and characterize the Fc regions of human IgGs in paired serum and BAL fluid. Antibodies were isolated using a fast and reliable approach via MelonGel extraction. The isolated IgGs were digested by trypsin and separated by nLC (nano liquid chromatography) as in conventional proteomics, but peptide fragmentation was performed by both high resolution HCD MS/MS (Higher-energy C-trap dissociation) and high-resolution ETD MS/MS (Electron-transfer dissociation). We identified a candidate marker IgG4, which corresponded well to inflammatory activity in chronic lung diseases while also correlating between BAL and serum (R2=0.95), thus being readily available for sample collection. The IgG galactosylation marker could prove to be useful in clinical settings by monitoring chronic pulmonary inflammation status. Based on the results of project II we concluded that the Fc galactosylation status of IgG4 could potentially be used as a serum marker for severity in pulmonary inflammation. In project IV project, we used the mSBA approach for both sarcoidosis and IPF samples in order to evaluate similarities and differences between fibrosis associated diseases. Autoantigens were found in a majority of patient samples, including healthy controls, although that cohort displayed a lower frequency of autoreactivity and also comparatively lower titers. Altogether, autoreactivity was higher in IPF and in nLS patients compared to all other groups; both groups included a higher fibrosis rate than the other diseases potentially linking a general presence of autoreactive antibodies to fibrosis development. Reactivity toward collagen 5A1 (COL5A1) was discovered with a statistical significant higher frequency in patients with IPF compared to all other groups apart from the nLS group. The protein epitope of COL5A1 is proposed as an autoimmune target and/or marker of fibrosis, and is of interest for further investigation. In this thesis we have profiled the repertoire of proteins and autoantibodies in serum and BAL from patients with sarcoidosis, in addition we also investigated and compared the presence of autoreactive antibodies in patients with sarcoidosis and IPF, as well as control subjects and various comparable diseases. We have also proposed the ratio between agalactosylated and galactosylated forms of the Fc region in IgG4 as a marker for severe chronic lung disease. These discoveries open up for more studies to characterize, and test functionality, of these autoantibodies and proteins in the setting of sarcoidosis, IPF, or inflammatory and/or pulmonary diseases

Using bacterial biomarkers to identify early indicators of cystic fibrosis pulmonary exacerbation onset

Acute periods of pulmonary exacerbation are the single most important cause of morbidity in cystic fibrosis patients, and may be associated with a loss of lung function. Intervening prior to the onset of a substantially increased inflammatory response may limit the associated damage to the airways. While a number of biomarker assays based on inflammatory markers have been developed, providing useful and important measures of disease during these periods, such factors are typically only elevated once the process of exacerbation has been initiated. Identifying biomarkers that can predict the onset of pulmonary exacerbation at an early stage would provide an opportunity to intervene before the establishment of a substantial immune response, with major implications for the advancement of cystic fibrosis care. The precise triggers of pulmonary exacerbation remain to be determined; however, the majority of models relate to the activity of microbes present in the patient's lower airways of cystic fibrosis. Advances in diagnostic microbiology now allow for the examination of these complex systems at a level likely to identify factors on which biomarker assays can be based. In this article, we discuss key considerations in the design and testing of assays that could predict pulmonary exacerbations

Identification of Lung Carcinoma Biomarkers Associated with Tumour Development and Drug Resistance

Lung cancer is the most common cause of death from cancer worldwide, estimated to be responsible for nearly one in five (1.59 million deaths, 19.4% of the total). Lung cancer is acknowledged as a complex and heterogeneous disease, not only at the biochemical level (genes, proteins, metabolites) but also at the tissue, organism, and population level. In the past decade, with the advancements in high-throughput profiling technologies, a huge amount of work has been done to derive biomarkers to supplement clinical diagnosis. The levels of a variety of different biomarkers, such as proteins and metabolites, in biological fluid or tissue/cells could potentially detect cancer at an early stage, determine cancer subtype, or monitor the sensitivity/resistance to cancer treatment. The research in this thesis aims to discover new biomarkers, using proteomic techniques, with the potential to supplement current clinical criteria for the management of lung cancer patients. Label-free mass spectrometry of bronchoalveolar lavage fluid (BALF), blood (serum), tissue and cell lines was performed to identify candidate biomarkers and perturbed cellular pathways. Validation of significant results was performed using immunological methods and biochemical assays. These studies have yielded valuable information that has unravelled several key molecular events of lung cancer tumorigenesis, including proteomic signature of lung cancer in BALF, tissue and blood. BALF analysis identified a promising signature distinguish between adenocarcinoma of the lung and squamous cell carcinoma of the lung. Many proteins found to be significant changed in abundance in BALF also displayed similar trends in tissue specimens. Tumour heterogeneity was also evident when examining tumour specimens, reinforcing the need for panels of biomarkers and multiple sampling. At strong metabolic pattern was also evident during proteomics based investigations of clinical material, a result that was confirmed using metabolomics platforms to screen patient samples. Drug resistant protein patterns were also identified using label-free mass spectrometry on cell lines models demonstrating resistance to Apitolisib (GDC-0980), a dual phosphatidylinositol-3-kinase and mammalian target of rapamycin kinase inhibitor. Early in vitro data on resistant mechanisms associated with new lung cancer treatments is crucial to allow resistance to be detected in patients and to understand and potentially target resistant pathways. The molecular analysis of a variety of biospecimens has allowed the discovery of relevant candidate biomarkers and consequently the identification of novel proteins that may have a role in the development of lung cancer and establishment of drug resistance. There is a need for incorporating findings from multiple discovery platforms and multiple sample types into a lung cancer specific data framework that can improve our level of understanding of the disease process

A Mini Review of Trends towards Automated and Non-Invasive Techniques for Early Detection of Lung Cancer: From Radiomics through Proteogenomics to Breathomics

Carcinoma of the Lung is one of the most common cancers in the world and the leading cause of tumor-related deaths. Less than 15% of patients survive 5 years post diagnosis due to its relatively poor prognosis. This has been ascribed to lack of effective diagnostic methods for early detection. Different medical imaging techniques such as chest radiography, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are used in routine clinical practice for tumor detection. These techniques are medically unsatisfactory and inconvenient for patients due to poor diagnostic accuracy. Endobronchial biopsies are the gold standard for diagnosis but have the inherent risk of full or partial invasive procedures. Thus, diagnostic technology that uses data mining algorithms with medical image analysis, generally known as radiomics emerged. Radiomics extracts complex information from conventional radiographic images and quantitatively correlates image features with diagnostic and therapeutic outcomes. In spite of the benefits, radiomics is prone to high false positives and there is no established standard for acquisition of parameters. Further efforts towards outcome improvement led to the proteomic and genomic (proteogenomic) approach to lung cancer detection. Although proteogenomic has a diagnostic edge over traditional techniques, variations in bio-specimen and heterogeneity of lung cancer still possess a major challenge. Recent findings have established that changes normally occur in the gene or protein due to tumor growth in the lungs and this often leads to peroxidation of cell membrane that releases Volatile Organic Compounds (VOCs) through the breath of Lung Cancer patients. The comprehensive analysis of breath VOCs, which is tagged Breathomics in the literature,unveils opportunities for noninvasive biomarker discovery towards early detection. Breathomics has therefore become the current pace-setter in medical diagnostics research because of its non-invasiveness and cost effectiveness. This paper presents a mini survey of trends in early lung cancer detection from radiomics, through proteogenomic to breathomics