Project description:METTL16 has recently been identified as an RNA methyltransferase that installs m6A marks on a few transcripts. But its function in cytosol remains unclear. Puromycin-labelling and renilla luciferase assay revealed that METTL16 can promote translation efficiency in an m6A-independent manner. To explore the mechanism, we performed co-immunoprecipitation using METTL16 antibody and mass spectroscopy to identify its interaction proteins. Moreover, we find that METTL16 is essential for tumorigenesis of non-small cell lung cancer.
Project description:The health state of an individual is closely linked to the glycosylation patterns of their blood plasma proteins. However, obtaining this information requires cost- and time-efficient analytical methods. We put forward infrared spectroscopy, which allows label-free analysis of protein glycosylation, but so far has only been applied to analyses of individual proteins. Although spectral information does not directly provide the molecular structure of the glycans, it is sensitive to changes therein and covers all types of glycosidic linkages. Combining single-step ion exchange chromatography with infrared spectroscopy, we developed a workflow that enables separation and analysis of major protein classes in blood plasma. Our results demonstrate that infrared spectroscopy can identify different patterns and global levels of glycosylation of intact plasma proteins. To showcase the strengths and limitations of the proposed approach, we compare the glycoforms of human and bovine alpha-1-acid glycoproteins, which exhibit highly variable global levels of glycosylation. To further independently evaluate our conclusions, the glycan moieties of human alpha-1-acid glycoprotein were further analyzed using established glycomics workflow. Importantly, the chromatographic separation of blood plasma improves the detection of aberrant glycoforms of a given protein, as compared to infrared spectroscopy of bulk plasma. The presented approach allows time-efficient comparison of glycosylation patterns of multiple plasma proteins, opening new avenues for biomedical probing.
Project description:Early detection and treatment of gastric premalignant lesion and early gastric cancer (EGC) have been proposed to improve outcomes of gastric cancer. Gastric dysplasia is a premalignant lesion and the penultimate stage in gastric carcinogenesis. On white light endoscopy (WLE), it is difficult to distinguish gastric dysplasia and EGC from benign pathology such as gastric intestinal metaplasia (GIM). Image enhanced endoscopy such as narrow-band imaging (NBI) is recommended to improve characterization of suspicious gastric lesions detected on WLE. Magnified-endoscopy with NBI (ME-NBI) have been shown to be superior to HD-WLE for diagnosis of GIM and EGC. Data on gastric dysplasia is less robust. Ultimately, biopsy is required to confirm diagnosis of gastric dysplasia/EGC. Gastric dysplasia can be classified into low-grade dysplasia (LGD) or high-grade dysplasia (HGD). Biopsy sampling may not be representative of the final histopathological grade of resected specimens and may under-stage dysplasia. Thus, endoscopic resection (ER) is recommended for gastric dysplasia and EGC on biopsy for diagnostic and therapeutic purpose. The current gap is to improve concordance of endoscopic and histologic findings of gastric dysplasia and early gastric cancer. Raman spectroscopy based artificial intelligence system (SPECTRA IMDx) was developed to provide an objective method to identify patients with gastric premalignant lesions and EGC. SPECTRA IMDx interrogate tissues at the cellular level and utilizes molecular information to provide actionable information to endoscopist during gastroscopy. Studies on diagnostic performance using Raman spectroscopy analysis devices have shown high sensitivity and specificity in detection of gastric cancer and precancerous lesions compared to WLE. However, these studies included few GIM, gastric dysplasia and gastric carcinoma. It is still unclear if Raman spectroscopy outperforms WLE in diagnosis of gastric HGD and EGC. In addition, the Raman spectroscopy algorithm is only able to characterize lesions into high risk (HGD/EGC) versus low risk (GIM/LGD/Gastritis/Normal). It is also uncertain if this technology is able to differentiate GIM and LGD. We plan to conduct a prospective trial to validate the diagnostic accuracy of SPECTRA for prediction of gastric HGD and EGC prior to gastric ER. Hypothesis: SPECTRA IMDx is able to differentiate higher risk lesions (HGD/EGC) from lower risk tissue/lesion (GIM/LGD/Gastritis/Normal)
Project description:Inflammatory bowel diseases (IBD) are chronic inflammatory disorders that can be categorized as ulcerative colitis (UC), Crohn’s disease (CD) and indeterminate colitis (IC). Deep remission has been shown to improve disease outcome. There may be a lack of concordance between endoscopic and histologic remission. IBD patients with long standing colitis are at risk of developing dysplasia and colorectal cancer (CRC). However, it can be challenging to diagnose dysplasia in IBD patients during colonoscopy, as dysplasia frequently manifests as non-pedunculated lesions that present with only subtle visible changes or are even invisible due to the surrounding inflammation, scarring, pseudopolyps, or hyperplasia. Although white light endoscopy and chromoendoscopy are the current standard modality of imaging, there is still a gap to be bridged, in terms of improving endoscopic diagnosis of dysplasia and improving concordance of endoscopic and histologic remission. Raman spectroscopy is an inelastic light scattering technique provide specific fingerprints of molecular compositions and structures of biological tissues. It may be able to provide additional diagnostic information over standard endoscopy. A second-generation Raman endoscope system for improving in vivo tissue characterization and diagnosis during colonoscopy has been developed (SPECTRA IMDx system). Preliminary data suggested its utility in the diagnosis of colorectal neoplasia during colonoscopy. There is currently a lack of data concerning the application of this novel technology in the context of IBD. Specifically, whether the spectral signals generated can be used to better classify disease remission, and thus achieve higher concordance with histology when compared to standard endoscopy. It is also unclear whether this technology can be used to differentiate dysplastic mucosa from non-dysplastic mucosal in IBD patients.
Hypotheses
1. Raman spectroscopy based artificial intelligence system has the potential to be used to differentiate disease remission from active mucosal inflammation and hence improve concordance between endoscopic and histologic remission, with the potential to decrease the need for random biopsies real-time during colonoscopy.
2. Raman spectroscopy based artificial intelligence system has the potential to differentiate dysplastic mucosa in IBD patients (low grade and high grade dysplasia; colorectal cancer) from non-dysplastic mucosa. real-time during colonoscopy.
Project description:Primary outcome(s): The diagnostic agreement between diagnosis by endocytoscopy and pathological diagnosis by biopsy, endoscopic resection and operation.
Project description:Background and study aims
Bowel cancer is one of the commonest cancers worldwide. Earlier detection causes better outcomes for patients and longer survival. Symptoms of bowel cancer are non-specific and are shared by harmless bowel disorders. It is a challenge for doctors in general practice to diagnose bowel cancer and many symptomatic patients are sent to hospital for tests to rule it out. This is normally a colonoscopy, which is expensive, uncomfortable and can be harmful. The current approach to diagnosis causes great anxiety in patients waiting for these tests and is not a prudent approach to diagnosis. To allow earlier diagnosis by GPs we have studied whether a newly designed blood test taken in primary care is accurate and effective in patients with bowel symptoms that could be linked with cancer. This would benefit a large number of patients who are concerned about their bowel symptoms without the need for referral to hospital. It could also lead to diagnosis of bowel cancer at an earlier stage improving survival in the longer term. The aim of this study is to use a newly developed blood test for bowel cancer in primary care to achieve an earlier diagnosis. This would allow more timely appropriate treatment both for patients diagnosed with bowel cancer and those who are cancer free.
Who can participate?
Adults aged 50 years and older who have symptoms of bowel cancer.
What does the study involve?
Participants are randomly allocated to one of two groups. Those in the first group have their Raman spectroscopy blood test done immediately and those in the second grou have their sample tested after they’ve had a diagnosis. The amount of participants who are referred on the USC pathway from each group are assessed after 12 months.
Project description:Large-scale immune monitoring experiments (such as clinical trials) are a promising direction for biomarker discovery and responder stratification in immunotherapy. Mass cytometry is one of the tools in the immune monitoring arsenal. We propose a standardized workflow for the acquisition and analysis of large-scale mass cytometry experiments. The workflow includes two-tiered barcoding, a broad lyophilized panel, and the incorporation of a fully automated, cloud-based analysis platform. We applied the workflow to a large antibody staining screen using the LEGENDScreen kit, resulting in single-cell data for 350 antibodies over 71 profiling subsets. The screen recapitulates many known trends in the immune system and reveals potential markers for delineating MAIT cells. Additionally, we examine the effect of fixation on staining intensity and identify several markers where fixation leads to either gain or loss of signal. The standardized workflow can be seamlessly integrated into existing trials. Finally, the antibody staining data set is available as an online resource for researchers who are designing mass cytometry experiments in suspension and tissue.
Project description:Medulloblastoma (MB) is the most common malignant brain tumor occurring in childhood and rarely found in adult. Based on transcriptome profile MB are currently classified into four major molecular groups reflecting a considerable biological heterogeneity: WNT-activated, SHH-activated, group 3 and group 4. Recently, DNA methylation profiling allowed the identification of additional subgroups within the four major molecular groups associated with different clinic-pathological and molecular features. Isocitrate Dehydrogenase-1 (IDH1) mutations have been described in several tumours, including gliomas, while in MB are exceptionally reported and not routinely investigated. By mean of magnetic resonance spectroscopy (MRS) we unequivocally assessed the presence the oncometabolite D-2-Hydroxyglutarate (2HG), a marker of IDH1 and IDH2 mutation, in a case of adult MB. Immunophenotypical work-up and methylation profiling assigned the diagnosis of MB, subclass SHH-A, and molecular testing revealed the presence of the non-canonical somatic IDH1(p.R132C) mutation and an additional GNAS mutation, also exceptionally described in MB. To our knowledge this is the first reported case of MB harboring both mutations together. Of note, tumour exhibited a heterogeneous phenotype with a tumour component displaying glial differentiation, with robust GFAP expression, and a component with conventional MB features and selective presence of GNAS mutation, suggesting coexistence of two different major tumour clones. These findings draw attention to the need of a deeper genetic characterization of MB in order to get insights into their biology and improve stratification and clinical management of the patients. Moreover, reported data underling the importance of performing MRS for the identification of IDH mutations in non-glial tumours. The use of throughput molecular profiling analysis and advanced medical imaging technology will certainly increase the frequency with which rare tumour entities will be identified. Whether they have any particular therapeutic implications or prognostic relevance requires further investigations.