Dysregulation of the Kynurenine Pathway, Cytokine Expression Pattern, and Proteomics Profile Link to Symptomology in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).

Dysregulation of the kynurenine pathway (KP) is believed to play a significant role in neurodegenerative and cognitive disorders. While some evidence links the KP to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), further studies are needed to clarify the overall picture of how inflammation-driven KP disturbances may contribute to symptomology in ME/CFS. Here, we report that plasma levels of most bioactive KP metabolites differed significantly between ME/CFS patients and healthy controls in a manner consistent with their known contribution to symptomology in other neurological disorders. Importantly, we found that enhanced production of the first KP metabolite, kynurenine (KYN), correlated with symptom severity, highlighting the relationship between inflammation, KP dysregulation, and ME/CFS symptomology. Other significant changes in the KP included lower levels of the downstream KP metabolites 3-HK, 3-HAA, QUIN, and PIC that could negatively impact cellular energetics. We also rationalized KP dysregulation to changes in the expression of inflammatory cytokines and, for the first time, assessed levels of the iron (Fe)-regulating hormone hepcidin that is also inflammation-responsive. Levels of hepcidin in ME/CFS decreased nearly by half, which might reflect systemic low Fe levels or possibly ongoing hypoxia. We next performed a proteomics screen to survey for other significant differences in protein expression in ME/CFS. Interestingly, out of the seven most significantly modulated proteins in ME/CFS patient plasma, 5 proteins have roles in maintaining gut health, which considering the new appreciation of how gut microbiome and health modulates systemic KP could highlight a new explanation of symptomology in ME/CFS patients and potential new prognostic biomarker/s and/or treatment avenues.

Involvement of the kynurenine pathway in breast cancer: updates on clinical research and trials.

Breast cancer (BrCa) is the leading cause of cancer incidence and mortality in women worldwide. While BrCa treatment has been shown to be highly successful if detected at an early stage, there are few effective strategies to treat metastatic tumours. Hence, metastasis remains the main cause in most of BrCa deaths, highlighting the need for new approaches in this group of patients. Immunotherapy has been gaining attention as a new treatment for BrCa metastasis and the kynurenine pathway (KP) has been suggested as one of the potential targets. The KP is the major biochemical pathway in tryptophan (TRP) metabolism, catabolising TRP to nicotinamide adenine dinucleotide (NAD+). The KP has been reported to be elevated under inflammatory conditions such as cancers and that its activity suppresses immune surveillance. Dysregulation of the KP has previously been reported implicated in BrCa. This review aims to discuss and provide an update on the current mechanisms involved in KP-mediated immune suppression and cancer growth. Furthermore, we also provide a summary on 58 studies about the involvement of the KP and BrCa and five clinical trials targeting KP enzymes and their outcome.

Deciphering the Kidney Matrisome: Identification and Quantification of Renal Extracellular Matrix Proteins in Healthy Mice.

Precise characterization of a tissue's extracellular matrix (ECM) protein composition (matrisome) is essential for biomedicine. However, ECM protein extraction that requires organ-specific optimization is still a major limiting factor in matrisome studies. In particular, the matrisome of mouse kidneys is still understudied, despite mouse models being crucial for renal research. Here, we comprehensively characterized the matrisome of kidneys in healthy C57BL/6 mice using two ECM extraction methods in combination with liquid chromatography tandem mass spectrometry (LC-MS/MS), protein identification, and label-free quantification (LFQ) using MaxQuant. We identified 113 matrisome proteins, including 22 proteins that have not been previously listed in the Matrisome Database. Depending on the extraction approach, the core matrisome (structural proteins) comprised 45% or 73% of kidney ECM proteins, and was dominated by glycoproteins, followed by collagens and proteoglycans. Among matrisome-associated proteins, ECM regulators had the highest LFQ intensities, followed by ECM-affiliated proteins and secreted factors. The identified kidney ECM proteins were primarily involved in cellular, developmental and metabolic processes, as well as in molecular binding and regulation of catalytic and structural molecules' activity. We also performed in silico comparative analysis of the kidney matrisome composition in humans and mice based on publicly available data. These results contribute to the first reference database for the mouse renal matrisome.

Involvement of Kynurenine Pathway in Hepatocellular Carcinoma.

As the second and third leading cancer-related death in men and the world, respectively, primary liver cancer remains a major concern to human health. Despite advances in diagnostic technology, patients with primary liver cancer are often diagnosed at an advanced stage. Treatment options for patients with advanced hepatocarcinoma (HCC) are limited to systemic treatment with multikinase inhibitors and immunotherapy. Furthermore, the 5-year survival rate for these late-stage HCC patients is approximately 12% worldwide. There is an unmet need to identify novel treatment options and/or sensitive blood-based biomarker(s) to detect this cancer at an early stage. Given that the liver harbours the largest proportion of immune cells in the human body, understanding the tumour-immune microenvironment has gained increasing attention as a potential target to treat cancer. The kynurenine pathway (KP) has been proposed to be one of the key mechanisms used by the tumour cells to escape immune surveillance for proliferation and metastasis. In an inflammatory environment such as cancer, the KP is elevated, suppressing local immune cell populations and enhancing tumour growth. In this review, we collectively describe the roles of the KP in cancer and provide information on the latest research into the KP in primary liver cancer.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Mass spectrometry-based protein identification in proteomics-a review.

Statistically, accurate protein identification is a fundamental cornerstone of proteomics and underpins the understanding and application of this technology across all elements of medicine and biology. Proteomics, as a branch of biochemistry, has in recent years played a pivotal role in extending and developing the science of accurately identifying the biology and interactions of groups of proteins or proteomes. Proteomics has primarily used mass spectrometry (MS)-based techniques for identifying proteins, although other techniques including affinity-based identifications still play significant roles. Here, we outline the basics of MS to understand how data are generated and parameters used to inform computational tools used in protein identification. We then outline a comprehensive analysis of the bioinformatics and computational methodologies used in protein identification in proteomics including discussing the most current communally acceptable metrics to validate any identification.

A high-stringency blueprint of the human proteome.

The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP's tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.

Improved sensitivity in cell surface protein detection by combining chemical labeling with mechanical lysis in a colorectal cancer cell model.

OBJECTIVE: To develop a new technique for improved cell surface protein detection and analysis by combining chemical labeling with mild cell lysis using model HCT 116 colorectal cancer cells. RESULTS: We found that Dounce homogenization by hand, rather than the typical sonication or syringe lysis method, recovered surface/membrane proteins more consistently and effectively. This was indicated by marker membrane proteins such as claudin-4 and EGFR (epidermal growth factor receptor) that span the typical 20-200 kD range. As monitored by Western blotting (WB), the Dounce lysis method combined with cell surface biotinylation showed consistent recovery of the marker proteins claudin-4 and EGFR. This lysis method was combined with a cell surface biotinylation strategy to enrich cell surface/membrane proteins using affinity bead-based purification with four-fold less cells compared to prior work. Subsequent LC/MS/MS analysis identified 49 additional surface/membrane proteins for the first time from HCT 116 cells. CONCLUSION: This combination of methodologies may fit into an advanced workflow for identifying new and elusive cell surface proteins. It can increase the protein coverage for biomarker discovery for colorectal cancer or other cancers. This new detection/analysis approach may also promote new applications in surface display systems as well as cell screening, selection, and binding processes.

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel.

BACKGROUND: One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). METHODS: A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. RESULTS: Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. CONCLUSION: MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

Proteomics Reveals Cell-Surface Urokinase Plasminogen Activator Receptor Expression Impacts Most Hallmarks of Cancer.

While metastasis is the primary cause of colorectal cancer (CRC) mortality, the molecular mechanisms underpinning it remains elusive. Metastasis is propagated through driver oncogene/suppressor gene mutations, accompanied by passenger mutations and underlying genomic instability. To understand cancer biology, a unifying framework called the "hallmarks of cancer" (HoCs) has been developed, which organizes cell biological alterations under ten key hallmarks. Underlying these HoCs, genome instability generates mutational diversity that is amplified by inflammation. Recognizing how critical cancer cell-surface proteins influence, these HoCs have been proposed to accelerate precision medicine therapeutic development. A moderate decrease (43%↓) in HCT116 cell surface urokinase plasminogen activator receptor (uPAR) expression mitigates against many HoCs driven by these cell's KRAS and PIK3CA mutational signature. Comprehensive proteomics (whole cell lysis with two membrane protein enrichments) coupled with ingenuity pathway analysis (IPA) demonstrates that uPAR negates essential pathways across the HoC spectrum, particularly those associated with metastasis, resisting cell death, and sustaining proliferation, and parallels Cancer Hallmarks Analytics Tool analysis. Decreasing uPAR predominantly alters metastasis-related and uPAR-interactome protein expression (e.g., EGFR, caveolin, vitronectin, integrin ß4). Collectively, it is demonstrated that uPAR is a lynchpin protein capable of regulating several HoC pathways in a classical CRC mutational background.

In Silico Peptide Repertoire of Human Olfactory Receptor Proteomes on High-Stringency Mass Spectrometry.

Human olfactory receptors (ORs) are seven-pass transmembrane G-protein coupled receptors (GPCR) involved in smell perception and many other signaling pathways. They are primarily expressed in the olfactory epithelium and ectopically expressed in several other organs and tissues. neXtProt contains 4 PE1 (protein existence 1, evidenced at the protein level) ORs, determined on the basis of either protein interaction data (i.e., OR1D4 and OR2AG1) or convincing genetic, haplotype, or biochemical data (i.e., OR1D2 and OR2J3). Not a single OR currently qualifies for neXtProt PE1 status based on mass spectrometry (MS) evidence. Many reasons for this absence of MS-based identification have been proposed, including (i) confined or spatiotemporal or developmental expression, (ii) low copy number, (iii) OR repertoire gene silencing, and (iv) limited tissue availability. OR transmembrane domains (TMDs) inherently limit MS identification because the hydrophobic nature restricts the access of trypsin to potential cleavage sites. Equally, the extremely low frequency or lack of accessible arginine and lysine residues in TMDs renders trypsin cleavage ineffective. Here, we demonstrate an analytical approach specifically focused on the hydrophilic (trypsin-accessible) domains of ORs [i.e., with all transmembrane segments and anchored peptides excluded). We predicted the ability of OR soluble (hydrophilic) domains to yield 2 or more >9 amino acids (aa) length unique mapping (unique to a protein only), non-nested (peptides with varying length at the N or C terminal but containing the same core sequence), leucine/isoleucine (I/L) switch examined (I and L have same mass and cannot be distinguished by MS) tryptic peptides. Our analysis showed that ∼58% of the human OR proteome could potentially generate tryptic peptides that satisfy current the Human Proteome Project data interpretation guidelines (version 2.1) when no missed cleavages are allowed and increases to ∼78% when one missed cleavage is allowed. The utilization of current biological data (adjuvant genomics, expression profile, transcriptomics, epigenome silencing data, etc.) and the adoption of a non-conventional proteomics approach (e.g., Confetti multiprotease digestion, CNBr cleavage of TMDs, and more-extreme chromatographic and MS methods) could aid in the detection of the remaining ORs.

Evaluation of two high-throughput proteomic technologies for plasma biomarker discovery in immunotherapy-treated melanoma patients.

BACKGROUND: Selective kinase and immune checkpoint inhibitors, and their combinations, have significantly improved the survival of patients with advanced metastatic melanoma. Not all patients will respond to treatment however, and some patients will present with significant toxicities. Hence, the identification of biomarkers is critical for the selection and management of patients receiving treatment. Biomarker discovery often involves proteomic techniques that simultaneously profile multiple proteins but few studies have compared these platforms. METHODS: In this study, we used the multiplex bead-based Eve Technologies Discovery assay and the aptamer-based SomaLogic SOMAscan assay to identify circulating proteins predictive of response to immunotherapy in melanoma patients treated with combination immune checkpoint inhibitors. Expression of four plasma proteins were further validated using the bead-based Millipore Milliplex assay. RESULTS: Both the Discovery and the SOMAscan assays detected circulating plasma proteins in immunotherapy-treated melanoma patients. However, these widely used assays showed limited correlation in relative protein quantification, due to differences in specificity and the dynamic range of protein detection. Protein data derived from the Discovery and Milliplex bead-based assays were highly correlated. CONCLUSIONS: Our study highlights significant limitations imposed by inconsistent sensitivity and specificity due to differences in the detection antibodies or aptamers of these widespread biomarker discovery approaches. Our findings emphasize the need to improve these technologies for the accurate identification of biomarkers.

Human Prestin: A Candidate PE1 Protein Lacking Stringent Mass Spectrometric Evidence?

The evidence that any protein exists in the Human Proteome Project (HPP; protein evidence 1 or PE1) has revolved primarily (although not exclusively) around mass spectrometry (MS) (93% of PE1 proteins have MS evidence in the latest neXtProt release), with robust and stringent, well-curated metrics that have served the community well. This has led to a significant number of proteins still considered "missing" (i.e., PE2-4). Many PE2-4 proteins have MS evidence of unacceptable quality (small or not enough unitypic peptides and unacceptably high protein/peptide FDRs), transcriptomic, or antibody evidence. Here we use a Chromosome 7 PE2 example called Prestin to demonstrate that clear and robust criteria/metrics need to be developed for proteins that may not or cannot produce clear-cut MS evidence while possessing significant non-MS evidence, including disease-association data. Many of the PE2-4 proteins are inaccessible, spatiotemporally expressed in a limited way, or expressed at such a very low copy number as to be unable to be detected by current MS methodologies. We propose that the HPP community consider and lead a communal initiative to accelerate the discovery and characterization of these types of "missing" proteins.

A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes.

In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. We present here a simple and intuitive workflow for the research community to investigate and mine this data, not only to extract relevant data but also to segregate usable, quality data to develop hypotheses for investigation and validation. We apply an MS evidence workflow for verifying peptides of proteins from one's own data as well as publicly available databases. We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.

Adenosine monophosphate deaminase 3 activation shortens erythrocyte half-life and provides malaria resistance in mice.

The factors that determine red blood cell (RBC) lifespan and the rate of RBC aging have not been fully elucidated. In several genetic conditions, including sickle cell disease, thalassemia, and G6PD deficiency, erythrocyte lifespan is significantly shortened. Many of these diseases are also associated with protection from severe malaria, suggesting a role for accelerated RBC senescence and clearance in malaria resistance. Here, we report a novel, N-ethyl-N-nitrosourea-induced mutation that causes a gain of function in adenosine 5'-monophosphate deaminase (AMPD3). Mice carrying the mutation exhibit rapid RBC turnover, with increased erythropoiesis, dramatically shortened RBC lifespan, and signs of increased RBC senescence/eryptosis, suggesting a key role for AMPD3 in determining RBC half-life. Mice were also found to be resistant to infection with the rodent malaria Plasmodium chabaudi. We propose that resistance to P. chabaudi is mediated by increased RBC turnover and higher rates of erythropoiesis during infection.

A novel multiplexed immunoassay identifies CEA, IL-8 and prolactin as prospective markers for Dukes' stages A-D colorectal cancers.

BACKGROUND: Current methods widely deployed for colorectal cancers (CRC) screening lack the necessary sensitivity and specificity required for population-based early disease detection. Cancer-specific protein biomarkers are thought to be produced either by the tumor itself or other tissues in response to the presence of cancers or associated conditions. Equally, known examples of cancer protein biomarkers (e.g., PSA, CA125, CA19-9, CEA, AFP) are frequently found in plasma at very low concentration (pg/mL-ng/mL). New sensitive and specific assays are therefore urgently required to detect the disease at an early stage when prognosis is good following surgical resection. This study was designed to meet the longstanding unmet clinical need for earlier CRC detection by measuring plasma candidate biomarkers of cancer onset and progression in a clinical stage-specific manner. EDTA plasma samples (1 µL) obtained from 75 patients with Dukes' staged CRC or unaffected controls (age and sex matched with stringent inclusion/exclusion criteria) were assayed for expression of 92 human proteins employing the Proseek® Multiplex Oncology I proximity extension assay. An identical set of plasma samples were analyzed utilizing the Bio-Plex Pro™ human cytokine 27-plex immunoassay. RESULTS: Similar quantitative expression patterns for 13 plasma antigens common to both platforms endorsed the potential efficacy of Proseek as an immune-based multiplex assay for proteomic biomarker research. Proseek found that expression of Carcinoembryonic Antigen (CEA), IL-8 and prolactin are significantly correlated with CRC stage. CONCLUSIONS: CEA, IL-8 and prolactin expression were found to identify between control (unaffected), non-malignant (Dukes' A + B) and malignant (Dukes' C + D) stages.

Epithelial and stromal cell urokinase plasminogen activator receptor expression differentially correlates with survival in rectal cancer stages B and C patients.

Urokinase plasminogen activator receptor (uPAR) has been proposed as a potential prognostic factor for colorectal cancer (CRC) patient survival. However, CRC uPAR expression remains controversial, especially regarding cell types where uPAR is overexpressed (e.g., epithelium (uPARE) or stroma-associated cells (uPARS)) and associated prognostic relevance. In this study, two epitope-specific anti-uPAR monoclonal antibodies (MAbs) could discriminate expression of uPARE from uPARS and were used to examine this association with survival of stages B and C rectal cancer (RC) patients. Using immunohistochemistry, MAbs #3937 and R4 were used to discriminate uPARE from uPARS respectively in the central and invasive frontal regions of 170 stage B and 179 stage C RC specimens. Kaplan-Meier and Cox regression analyses were used to determine association with survival. uPAR expression occurred in both epithelial and stromal compartments with differential expression observed in many cases, indicating uPARE and uPARS have different cellular roles. In the central and invasive frontal regions, uPARE was adversely associated with overall stage B survival (HR = 1.9; p = 0.014 and HR = 1.5; p = 0.031, respectively) reproducing results from previous studies. uPARS at the invasive front was associated with longer stage C survival (HR = 0.6; p = 0.007), reflecting studies demonstrating that macrophage peritumoural accumulation is associated with longer survival. This study demonstrates that different uPAR epitopes should be considered as being expressed on different cell types during tumour progression and at different stages in RC. Understanding how uPARE and uPARS expression affects survival is anticipated to be a useful clinical prognostic marker of stages B and C RC.

Characterization of the interaction between heterodimeric αvß6 integrin and urokinase plasminogen activator receptor (uPAR) using functional proteomics.

Urokinase plasminogen activator receptor (uPAR) and the epithelial integrin αvß6 are thought to individually play critical roles in cancer metastasis. These observations have been highlighted by the recent discovery (by proteomics) of an interaction between these two molecules, which are also both implicated in the epithelial-mesenchymal transition (EMT) that facilitates escape of cells from tissue barriers and is a common signature of cancer metastases. In this study, orthogonal in cellulo and in vitro functional proteomic approaches were used to better characterize the uPAR·αvß6 interaction. Proximity ligation assays (PLA) confirmed the uPAR·αvß6 interaction on OVCA429 (ovarian cancer line) and four different colon cancer cell lines including positive controls in cells with de novo ß6 subunit expression. PLA studies were then validated using peptide arrays, which also identified potential physical sites of uPAR interaction with αvß6, as well as verifying interactions with other known uPAR ligands (e.g., uPA, vitronectin) and individual integrin subunits (i.e., αv, ß1, ß3, and ß6 alone). Our data suggest that interaction with uPAR requires expression of the complete αß heterodimer (e.g., αvß6), not individual subunits (i.e., αv, ß1, ß3, or ß6). Finally, using in silico structural analyses in concert with these functional proteomics studies, we propose and demonstrate that the most likely unique sites of interaction between αvß6 and uPAR are located in uPAR domains II and III.

Correlations between integrin ανß6 expression and clinico-pathological features in stage B and stage C rectal cancer.

Integrin ανß6 is highly expressed in a range of human cancers and frequently correlates with patient survival. This study examines correlations between ανß6 expression and patient clinico-pathological features in Stage B and Stage C rectal cancer, including overall survival. Expression of ανß6 was measured in 362 Stage B or C rectal cancer tissue samples at the tumour central region, invasive tumour front and adjacent non-neoplastic mucosa using immunohistochemistry. Distribution of ανß6 was found to be significantly higher at the invasive front compared to central regions of the tumour (p<0.001) or adjacent non-neoplastic mucosa (p<0.001) suggesting ανß6 plays a role in tumour cell invasion. However, integrin ανß6 expression was not associated with clinico-pathological features or overall survival indicating it is not an independent prognostic marker differentiating Stage B or C rectal cancer. Previous ανß6 studies have suggested the expression of ανß6 is involved in the earlier stages (i.e. Stages A/B) of tumour progression rather than the later stages (i.e. Stages C/D). However, our study has revealed that in rectal cancer ανß6 expression does not increase between Stages B and C, but may occur earlier, namely before or during Stage B cancer.