Differences in survival according to the pTERT mutation subtypes (-124C > T, -146C > T, and tandem -138_139CC > TT) have been observed. The present study aimed to describe the clinical as the histopathological and molecular cutaneous melanoma features according to the presence of the three most prevalent pTERT mutation subtypes (-124C > T, -146C > T, and tandem -138_139CC > TT). A retrospective cross-sectional study including 684 patients was designed, and a Partial Least-Squares Discriminant Analysis (PLS-DA) was performed. After the PSL-DA, it was observed that the tandem -138_139CC > TT subtype differs from the other subtypes. The model demonstrated that the -124C > T and the -138_139 CC > TT subtypes were associated with fast-growing melanomas (OR 0.5, CI 0.29-0.86, p = .012) and with Breslow >2 mm (OR 0.6, CI 0.37-0.97, p = .037), compared to the -146C > T mutation. Finally, the -124C > T appeared to be more associated with the presence of TILs (non-brisk) than the -146C > T (OR 0.6, CI 0.40-1.01, p = .05). These findings confirmed that the -124C > T and the tandem -138_139 CC > TT subtypes are both highly associated with the presence of features of aggressiveness; however, only the -124C > T was highly associated with TILs. This difference could explain the worse survival rate associated with the tandem -138_139CC > TT mutations.
- MeSH
- Humans MeSH
- Melanoma * genetics pathology mortality MeSH
- Mutation MeSH
- Skin Neoplasms genetics pathology mortality MeSH
- Promoter Regions, Genetic * genetics MeSH
- Cross-Sectional Studies MeSH
- Retrospective Studies MeSH
- Telomerase * genetics MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Although the identification of animal species and muscles have been reported previously, no studies have been found on the use of NIR spectroscopy to identify individual animals from the analysis of commercial meat cuts. The aim of this study was to evaluate the use of a portable near infrared (NIR) instrument combined with classical chemometrics methods [principal component analysis (PCA) and partial least squares discriminant analysis PLS-DA)] to identify the origin of individual goat animals using the spectral signature of their commercial cut. Samples were collected from several carcasses (6 commercial cuts x 24 animals) sourced from a commercial abattoir in Queensland (Australia). The NIR spectra of the samples were collected using a portable NIR instrument in the wavelength range between 950 and 1600 nm. Overall, the PLS-DA models correctly classify 82% and 79% of the individual goat samples using either the goat rack or loin cut samples, respectively. The study demonstrated that NIR spectroscopy was able to identify individual goat animals based on the spectra properties of some of the commercial cut samples analysed (e.g. loin and rack). These results showed the potential of this technique to identify individual animals as an alternative to other laboratory methods and techniques commonly used in meat traceability.
- Publication type
- Journal Article MeSH
PURPOSE: The field cancerization concept indicates the presence of pre-cancerous changes in clinically normal tissue surrounding the tumor. In squamous cell carcinoma of the oral tongue (SCCOT) which is infrequently linked to human papillomavirus infection, we have previously reported that clinically normal tongue contralateral to tumor (NTCT) is molecularly abnormal. Here, combining our transcriptomic and genomic data, we aimed to investigate the contribution of molecular changes in NTCT to cancer development. METHODS: Microarray gene expression data of 14 healthy controls, 23 NTCT and 29 SCCOT samples were investigated to characterize transcriptional profiles in NTCT. Whole exome sequencing and RNA-sequencing data of paired NTCT and tumor samples from 15 SCCOT patients were used to study correlation between copy number variation and differential gene expression. RESULTS: Using supervised multivariate partial least squares discriminant analysis, a total of 61 mRNAs that distinguish NTCT from healthy tongue were selected. Functional enrichment analysis of the 22 upregulated genes showed increased "positive regulation of nitrogen compound metabolic process" in NTCT. All 12 genes involved in this process have roles in apoptosis (anti- and/or pro-apoptotic). Compared to healthy controls, Zinc Finger Protein 395 (ZNF395), a pro-apoptotic tumor suppressor located on chromosome 8p, was the only gene showing increased mRNA level in NTCT whereas decreased in SCCOT. Given the frequent loss of chromosome 8p in SCCOT, the impact of ZNF395 copy number variation on gene expression was further examined, revealing a positive correlation between copy number and mRNA level (correlation coefficient = 0.572, p < 0.001). CONCLUSION: NTCT is susceptible to malignant transformation, where tissue homeostasis is maintained at least partly through regulation of apoptosis. Loss of the pro-apoptotic gene ZNF395 could thus initiate cancer development.
- MeSH
- Apoptosis * genetics MeSH
- Squamous Cell Carcinoma of Head and Neck * genetics pathology MeSH
- Adult MeSH
- Homeostasis genetics MeSH
- Middle Aged MeSH
- Humans MeSH
- Tongue Neoplasms * genetics pathology MeSH
- Gene Expression Regulation, Neoplastic MeSH
- Aged MeSH
- Carcinoma, Squamous Cell genetics pathology MeSH
- Transcriptome MeSH
- Up-Regulation * MeSH
- DNA Copy Number Variations MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Multiple myeloma (MM) is the second most prevalent hematological malignancy, characterized by infiltration of the bone marrow by malignant plasma cells. Extramedullary disease (EMD) represents a more aggressive condition involving the migration of a subclone of plasma cells to paraskeletal or extraskeletal sites. Liquid biopsies could improve and speed diagnosis, as they can better capture the disease heterogeneity while lowering patients' discomfort due to minimal invasiveness. Recent studies have confirmed alterations in the proteome across various malignancies, suggesting specific changes in protein classes. In this study, we show that MALDI-TOF mass spectrometry fingerprinting of peripheral blood can differentiate between MM and primary EMD patients. We constructed a predictive model using a supervised learning method, partial least squares-discriminant analysis (PLS-DA) and evaluated its generalization performance on a test dataset. The outcome of this analysis is a method that predicts specifically primary EMD with high sensitivity (86.4%), accuracy (78.4%), and specificity (72.4%). Given the simplicity of this approach and its minimally invasive character, this method provides rapid identification of primary EMD and could prove helpful in clinical practice.
- MeSH
- Middle Aged MeSH
- Humans MeSH
- Multiple Myeloma * blood diagnosis MeSH
- Biomarkers, Tumor blood MeSH
- Aged MeSH
- Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization methods MeSH
- Liquid Biopsy methods MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Nuclear magnetic resonance (NMR) metabolomics was used for identification of metabolic changes in pancreatic cancer (PC) blood plasma samples when compared to healthy controls or diabetes mellitus patients. An increased number of PC samples enabled a subdivision of the group according to individual PC stages and the construction of predictive models for finer classification of at-risk individuals recruited from patients with recently diagnosed diabetes mellitus. High-performance values of orthogonal partial least squares (OPLS) discriminant analysis were found for discrimination between individual PC stages and both control groups. The discrimination between early and metastatic stages was achieved with only 71.5% accuracy. A predictive model based on discriminant analyses between individual PC stages and the diabetes mellitus group identified 12 individuals out of 59 as at-risk of development of pathological changes in the pancreas, and four of them were classified as at moderate risk.
- MeSH
- Diabetes Mellitus * MeSH
- Discriminant Analysis MeSH
- Humans MeSH
- Magnetic Resonance Spectroscopy MeSH
- Metabolomics * MeSH
- Pancreas MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
For the understanding of pathological states of bone tissues in oral surgery, it would be desirable to have the possibility to simulate these processes on bone cell models in vitro. These cultures, similarly to bone tissues, contain numerous proteins entrapped in the insoluble matrix. The major goal of this study was to verify whether a method based on direct in-matrix protein digestion could be suitable for the discrimination between different induced pathological states of bone cell models cultivated in vitro. Using in-sample specific protein digestion with trypsin followed by liquid chromatography-tandem mass spectrometry analysis of released peptides, 446 proteins (in average per sample) were identified in a bone cell in vitro model with induced cancer, 440 proteins were found in a model with induced inflammation, 451 proteins were detected in control in vitro culture, and 491 proteins were distinguished in samples of vestibular laminas of maxillary bone tissues originating from six different patients. Subsequent partial least squares - discrimination analysis of obtained liquid chromatography-tandem mass spectrometry data was able to discriminate among in vitro cultures with induced cancer, with induced inflammation, and control cultivation. Thus, the direct in-sample protein digestion by trypsin followed by liquid chromatography-tandem mass spectrometry analysis of released specific peptide fragments from the insoluble matrix and mathematical analysis of the mass spectrometry data seems to be a promising tool for the routine proteomic characterization of in vitro human bone models with induced different pathological states.
- MeSH
- Chromatography, Liquid methods MeSH
- Humans MeSH
- Peptides analysis MeSH
- Proteins chemistry MeSH
- Proteolysis MeSH
- Proteomics methods MeSH
- Oral Surgical Procedures * MeSH
- Tandem Mass Spectrometry * methods MeSH
- Trypsin chemistry MeSH
- Inflammation MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
As early detection is crucial for improvement of cancer prognosis, we searched for biomarkers in plasma from individuals who later developed squamous cell carcinoma of the oral tongue (SCCOT) as well as in patients with an already established SCCOT. Levels of 261 proteins related to inflammation and/or tumor processes were measured using the proximity extension assay (PEA) in 179 plasma samples (42 collected before diagnosis of SCCOT with 81 matched controls; 28 collected at diagnosis of SCCOT with 28 matched controls). Statistical modeling tools principal component analysis (PCA) and orthogonal partial least square - discriminant analysis (OPLS-DA) were applied to provide insights into separations between groups. PCA models failed to achieve group separation of SCCOT patients from controls based on protein levels in samples taken prior to diagnosis or at the time of diagnosis. For pre-diagnostic samples and their controls, no significant OPLS-DA model was identified. Potentials for separating pre-diagnostic samples collected up to five years before diagnosis (n = 15) from matched controls (n = 28) were seen in four proteins. For diagnostic samples and controls, the OPLS-DA model indicated that 21 proteins were important for group separation. TNF receptor associated factor 2 (TRAF2), decreased in pre-diagnostic plasma (< 5 years) but increased at diagnosis, was the only protein showing altered levels before and at diagnosis of SCCOT (p-value < 0.05). Taken together, changes in plasma protein profiles at diagnosis were evident, but not reliably detectable in pre-diagnostic samples taken before clinical signs of tumor development. Variation in protein levels during cancer development poses a challenge for the identification of biomarkers that could predict SCCOT development.
- Publication type
- Journal Article MeSH
At present, Alzheimer's disease is detected mainly using psychological tests, which can only confirm the disease in its more advanced phases. Therefore, bioanalytical possibilities for detecting this disease earlier are being investigated. To date, the results of analyses, which focus mainly on the study of lipids and proteins either in cerebrospinal fluid or much less often in blood plasma, do not provide satisfactory results. In addition, cerebrospinal fluid sampling is uncomfortable for the patients and involves many health risks. In this work, we deal with proteomic analysis using Matrix-Assisted Laser Desorption/Ionisation-Time of Flight and Liquid Chromatography coupled to tandem Mass Spectrometry of blood plasma with a focus on various ways of preanalytical sample treatments. This should lead to results improvement and facilitate the subsequent evaluation using principal component analysis and partial least squares discriminant analysis. The obtained results indicate the direction of further research, namely the study of interactions between proteins and lipids contained in blood plasma. These substances may be regarded as potential biomarkers allowing for the diagnosis of Alzheimer ́s disease even in its early stages.
- MeSH
- Alzheimer Disease * blood diagnosis MeSH
- Biomarkers blood MeSH
- Chromatography, Liquid methods MeSH
- Plasma chemistry MeSH
- Blood Proteins analysis MeSH
- Middle Aged MeSH
- Humans MeSH
- Lipids blood MeSH
- Lipid Metabolism MeSH
- Proteomics methods MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization methods MeSH
- Tandem Mass Spectrometry methods MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Hepatitis B virus (HBV) infection is more likely to develop into chronic and persistent infection in China, which is the main cause of chronic liver disease. We examined the cytokine profiles of chronic hepatitis B (CHB) and CHB-caused liver cirrhosis (LC) to look for the predictor of progression from CHB to LC. Serum samples of 15 healthy controls (HC), 15 CHB patients and 15 LC patients were collected to detect the profiles of 48 cytokines by multiplex biometric ELISA-based immunoassay. Partial least squares discriminant analysis (PLS-DA) and random forest were used to analyse significant cytokines, which were further validated by ELISA using an independent cohort of 60 CHB patients, 60 LC patients and 35 HC samples. There were 18 differentially expressed cytokines of CHB and LC. Three cytokines were identified by PLS-DA and random forest, including interleukin (IL)-9, granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-2 receptor subunit α (IL-2Rα), which displayed significant changes in serum levels. Differentially expressed cytokine networks between HC, CHB and LC also indicated particular cytokine co-expression network patterns of CHB and LC. The receiver-operator characteristic (ROC) analysis demonstrated that IL-9, GM-CSF, IL-2Rα and their logistic regression panel are potential predictors that significantly differentiate CHB from LC (P < 0.001) and CHB from Child class A LC (P < 0.001). The three cytokines and the panel showed significant correlation with the Child-Pugh score. IL-9, GM-CSF, IL-2Rα and their logistic panel may be predictors for monitoring the progression of CHB to LC.
- MeSH
- Hepatitis B, Chronic * MeSH
- Cytokines MeSH
- Liver Cirrhosis MeSH
- Humans MeSH
- Hepatitis B virus MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- China MeSH
The lipidomic research is currently devoting considerable effort to the harmonization that should enable the generation of comparable and accurate quantitative lipidomic data across different laboratories and regardless of the mass spectrometry-based platform used. In the present study, we systematically investigate the effects of the experimental setup on quantitative lipidomics data obtained by two lipid class separation approaches, hydrophilic interaction liquid chromatography (HILIC) and ultrahigh-performance supercritical fluid chromatography (UHPSFC), coupled to two different quadrupole - time of flight (QTOF) mass spectrometers from the same vendor. This approach is applied for measurements of 268 human plasma samples of healthy volunteers and renal cell carcinoma patients resulting in four data sets. We investigate and visualize differences among these data sets by multivariate data analysis methods, such as principal component analysis (PCA), orthogonal partial least square discriminant analysis (OPLS-DA), box plots, and logarithmic correlations of molar concentrations of individual lipid species. The results indicate that even measurements in the same laboratory for the same samples using different analytical platforms may yield slight variations in the molar concentrations determined. The normalization to a reference sample with defined lipid concentrations can further diminish these small differences, resulting in highly homogenous molar concentrations of individual lipid species. This strategy indicates a potential approach towards the reporting of comparable quantitative results independent from the quantitative approach and mass spectrometer used, which is important for a wider acceptance of lipidomics data in various biomarker inter-laboratory studies and ring trials.
