Quantitative Risk Stratification of Oral Leukoplakia with Exfoliative Cytology

Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma (OSCC). Test outcome is reported as “negative”, “atypical” (defined as abnormal epithelial changes of uncertain diagnostic significance), and “positive” (defined as definitive cellular evidence of epithelial dysplasia or carcinoma). The major challenge is how to properly manage the “atypical” patients in order to diagnose OSCC early and prevent OSCC. In this study, we collected exfoliative cytology data, histopathology data, and clinical data of normal subjects (n=102), oral leukoplakia (OLK) patients (n=82), and OSCC patients (n=93), and developed a data analysis procedure for quantitative risk stratification of OLK patients. This procedure involving a step called expert-guided data transformation and reconstruction (EdTAR) which allows automatic data processing and reconstruction and reveals informative signals for subsequent risk stratification. Modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Among the several models tested using resampling methods for parameter pruning and performance evaluation, Support Vector Machine (SVM) was found to be optimal with a high sensitivity (median>0.98) and specificity (median>0.99). With the SVM model, we constructed an oral cancer risk index (OCRI) which may potentially guide clinical follow-up of OLK patients. One OLK patient with an initial OCRI of 0.88 developed OSCC after 40 months of follow-up. In conclusion, we have developed a statistical method for qualitative risk stratification of OLK patients. This method may potentially improve cost-effectiveness of clinical follow-up of OLK patients, and help design clinical chemoprevention trial for high-risk populations.     

Expressions of CXCR7/ligands may be involved in oral carcinogenesis

Oral carcinogenesis is a multistep process and requires accumulation and interplay of a series of molecular events. Chemokines and their receptors have been suggested to play important roles in the initiation or progression of cancers. Until now, no report focuses on their alterations in premalignant stage of oral squamous cell carcinoma (OSCC). Compared with normal tissues, mRNA levels of 9 chemokines and 3 chemokine receptors including CXCR7 in oral leukoplakia (OLK) were increased more than two folds by microarray analysis. Then, CXCR7 was selected for further confirmation and immunohistochemistry examination during multistage oral carcinogenesis. CXCR7 was expressed in 85% of OLK and 86% of OSCC. However, only 8% (1 of 13 cases) of normal tissue displayed CXCR7 immunostaining. The positive ratios of CXCR7, CXCL12 and CXCL11 in OLK and OSCC tissues respectively, were significantly higher than that in normal epithelia (P < 0.05), although no significant difference was found between OLK and OSCC. Meanwhile, CXCR7 always concomitantly expressed with it ligands in OLK and OSCC tissues. Our results indicated that CXCR7-CXCL12/CXCL11 axis might play important roles in oral carcinogenesis.     

Chromosome-specific segment size alterations are determinants of prognosis in prostate cancer

Currently, risk stratification is the most difficult problem in prostate cancer (PCa) management. Gleason grading cannot adequately predict cancer progression. This study aimed to identify chromosome-specific segment size alterations that could aid risk stratification and predict metastasis using a retrospective cohort-study strategy. A binary logistic regression model was generated using 16 chromosome-specific segments with size alterations (deletions and amplifications) that showed associations with disease stage (primary versus metastatic). The regression model was trained with the MSKCC PIK3R1 PCa cohort (n = 1417), and validated with the TCGA Firehose Legacy (n = 500), MSKCC Prostate Oncogenome Project (n = 218), and the SU2C/PCF Dream Team (n = 150) PCa cohorts. Furthermore, the capacity of the model to predict metastasis between primary tumours with metastasis (n = 54) and primary tumours without metastasis (n = 54) was tested. The accuracy, sensitivity, and specificity of the model at disease stage stratification ranged from 69.02% to 88.55%, 72.8% to 86.00% and 66.30% to 89.50%, respectively. The model also showed good performance at metastasis prediction with accuracy, sensitivity, and specificity of 57.41%, 62.96% and 51.85%, respectively. The study conclusion was that chromosome-specific segment size alterations can aid risk stratification and metastasis prediction. The significance of the study findings is that in combinations with clinical, biochemical, and histopathological variables, chromosome-specific alterations could improve current risk stratification and prediction models for PCa.     

Metabolite profiling of blood plasma of patients with prostate cancer

Prostate cancer is one of the most common types of cancer in men. It is though extremely important to search for specific markers including metabolites, which concentration in blood could be a diagnostic measure. In this regard, the metabolite profiling of blood plasma was performed with two groups of people: healthy volunteers (n = 30) and patients with prostate cancer, second stage (n = 40). The profiling protocol included proteins removal from blood plasma with methanol and direct analysis of metabolite fractions by mass spectrometry. Identification of the most abundant metabolites in samples was performed using an accurate mass tag and an isotope pattern methods. Cancer-specific metabolites were revealed by statistical analysis of metabolite intensities in the mass spectra. Six different metabolites were found to be cancer-specific. Two metabolites, acylcarnitine and arachidonoyl amine, have the AUC 0.97 and 0.86, respectively, which are higher than those from PSA test, 0.59.     

口腔白斑抑癌基因DAPK和TIG1高甲基化表达研究

摘要 目的：探讨抑癌基因DAPK、TIG1高甲基化在口腔白斑中表达状态及其对口腔癌发生发展中的作用。方法：取77例口腔白斑、32例口腔鳞癌、32份正常口腔黏膜组织,用实时定量甲基化特异性PCR技术检测组织中DAPK、TIG1高甲基化表达并进行统计学分析。结果：DAPK在口腔鳞癌组织中高甲基化表达率为46.9%,表达量为（0.0728±0.1617）,明显高于其在口腔白斑组织（19.5%,0.0070±0.0172）和口腔正常组织（18.8%,0.0021±0.0050）中的表达,差异有统计学意义（P<0.05）。DAPK高甲基化表达与口腔白斑组织上皮异常增生程度相关,上皮增生高风险组相对于低风险组DAPK高甲基化表达风险增加（OR,1.013;95% CI,1.004-1.023;P=0.004）。TIG1高甲基化在正常组织中未表达,在口腔鳞癌组织和口腔白斑组织表达为（28.1%,0.0174±0.0440）和（27.3%,0.0035±0.0076）,与正常组织相比具有统计学意义（P<0.05）。结论：抑癌基因 DAPK、TIG1高甲基化有望成为口腔黏膜癌变早期标志物。     

MicroRNA-206 has a bright application prospect in the diagnosis of cases with oral cancer

Previous studies have shown that microRNA-206 (miR-206) exhibits anti-tumour properties in various tumours. Nevertheless, diagnostic significance of miR-206 in oral cancer is still poorly known. Our research was carried out to explore the performance of miR-206 in the diagnosis of oral cancer. Quantitative real-time polymerase chain reaction (qRT-PCR) method was adopted to measure the level of miR-206 in serum specimens from oral cancer cases and control individuals. Chi-square test was performed to analyse the correlation between miR-206 level and clinicopathological parameters of the cases. Receiver operating characteristic (ROC) curve was constituted to assess diagnostic accuracy of miR-206 in oral cancer. Serum miR-206 level in oral cancer patients was significantly lower than that in control individuals (P < .001). miR-206 expression was obviously related to T classification (P = .033), TNM stage (P = .008) and lymph node metastasis (P = .028). The area under the curve (AUC) of the ROC curve was 0.846 (95% CI = 0.797-0.896, P < .001) with a specificity of 72.7% and a sensitivity of 81.2%. It revealed that miR-206 might be a non-invasive indicator in differentiating oral cancer cases from control individuals. Down-regulation of miR-206 is related to the development of oral cancer. Serum miR-206 might be an effective indicator for early detection of oral cancer.     

Comparison of accuracy of ultrasonography, progesterone, and pregnancy-associated glycoprotein tests for pregnancy diagnosis in semidomesticated reindeer

The aim of the study was to compare transrectal ultrasound with progesterone (P4) and pregnancy-associated glycoproteins (PAGs) as pregnancy detection methods for semidomesticated reindeer (Rangifer tarandus tarandus) in field conditions. Female reindeer (n = 195) were scanned transrectally by a 7.5-MHz linear array transducer, and blood was sampled either in December 2005 (n = 33), December 2006 (n = 92), or January 2007 (n = 70) during early or mid gestation. Plasma levels of P4 and PAGs were assessed by radioimmunoassay (RIA). Based on calving records, the sensitivity, specificity, predictive values, and the overall accuracy of the three tests were calculated. The overall calving rate calculated from the calving records was 86.2%. The overall accuracy of transrectal ultrasound was 99.5%. The sensitivity and specificity of transrectal ultrasound were 99.4% and 100%, respectively. In the plasma P4 test, the threshold level of 5.0 nmol/L gave the highest overall accuracy (94.9%). The sensitivity of the P4 test decreased from 96.4% to 81.5%, when the threshold level increased from 5.0 nmol/L to 8.0 nmol/L, while the specificity remained at 85.2% over the range of these cutoff values. The overall accuracy of the plasma PAG test decreased from 96.4% to 64.1% when the plasma PAG threshold level increased from 0.5 ng/mL to 3.5 ng/mL, whereas sensitivity decreased from 99.4% to 58.3%. Specificity increased from 77.8% to 100% when the plasma PAG threshold level reached 3.0 ng/mL. Transrectal ultrasound showed higher diagnostic values than those of plasma P4-RIA and PAG-RIA in diagnosing pregnancy of reindeer, with the advantage that diagnoses can be made in real time in field conditions.     

The Rate of Decline in Small Fibre Function Assessed Using Axon Reflex-Mediated Neurogenic Vasodilatation and the Importance of Age Related Centile Values to Improve the Detection of Clinical Neuropathy

Background

The LDIflare technique (LDIflare) is a simple non-invasive test of small fibre function in dorsal foot skin involving skin heating and measuring the size of the resulting axon reflex-mediated vasodilator (flare) response using a laser Doppler imager (LDI). This study establishes age-related normative reference ranges for the test and determines the rate of decline in small fibre function per decade. Additionally, the potential value of using age related centiles rather than Receiver Operator Curves (ROC) was explored by comparison of the sensitivity and specificity of each analytic technique in identifying clinical neuropathy.

Methods

LDIflare areas were assessed in 94 healthy controls and 66 individuals with diabetes with (DN+, n = 31) and without clinical neuropathy (DN-, n = 35); neuropathy defined as a Neuropathy Disability Score ≥3. The age specific 5th centile values were used as the ‘cut-offs’ for the diagnosis of neuropathy from which sensitivity and specificity were calculated.

Results

There was a significant age dependant decrease in LDIflare size (r = −0.42, p<0.0001) with no significant gender differences. The LDIflare size reduced 0.56 cm² per decade which gives a percentage reduction of approximately 5.5% per decade. Using the normative 5th centiles as the cut-offs, the technique had a sensitivity of 77%, specificity of 90%, positive predictive value of 82% and negative predictive value of 87%.The ROC analysis gave a threshold of <3.66 cm² for the cut-off, resulting in a sensitivity of 75%, specificity of 85%, positive predictive value of 74% and negative predictive value of 86%.

Conclusions

There is an age dependent decrease in small fibre function in the foot of 5.5% per decade. Both analytic techniques demonstrate good sensitivity and specificity for detecting clinical neuropathy but the technique based on age centiles offers better diagnostic accuracy and is therefore proposed as the method of choice.     

Metabolic signatures of esophageal cancer: NMR-based metabolomics and UHPLC-based focused metabolomics of blood serum

Focused metabolic profiling is a powerful tool for the determination of biomarkers. Here, a more global proton nuclear magnetic resonance (¹H NMR)-based metabolomic approach coupled with a relative simple ultra high performance liquid chromatography (UHPLC)-based focused metabolomic approach was developed and compared to characterize the systemic metabolic disturbances underlying esophageal cancer (EC) and identify possible early biomarkers for clinical prognosis. Serum metabolic profiling of patients with EC (n = 25) and healthy controls (n = 25) was performed by using both ¹H NMR and UHPLC, and metabolite identification was achieved by multivariate statistical analysis. Using orthogonal projection to least squares discriminant analysis (OPLS-DA), we could distinguish EC patients from healthy controls. The predictive power of the model derived from the UHPLC-based focused metabolomics performed better in both sensitivity and specificity than the results from the NMR-based metabolomics, suggesting that the focused metabolomic technique may be of advantage in the future for the determination of biomarkers. Moreover, focused metabolic profiling is highly simple, accurate and specific, and should prove equally valuable in metabolomic research applications. A total of nineteen significantly altered metabolites were identified as the potential disease associated biomarkers. Significant changes in lipid metabolism, amino acid metabolism, glycolysis, ketogenesis, tricarboxylic acid (TCA) cycle and energy metabolism were observed in EC patients compared with the healthy controls. These results demonstrated that metabolic profiling of serum could be useful as a screening tool for early EC diagnosis and prognosis, and might enhance our understanding of the mechanisms involved in the tumor progression.     

NT-ProBNP Levels in Saliva and Its Clinical Relevance to Heart Failure

Background

Current blood based diagnostic assays to detect heart failure (HF) have large intra-individual and inter-individual variations which have made it difficult to determine whether the changes in the analyte levels reflect an actual change in disease activity. Human saliva mirrors the body’s health and well being and ∼20% of proteins that are present in blood are also found in saliva. Saliva has numerous advantages over blood as a diagnostic fluid which allows for a non-invasive, simple, and safe sample collection. The aim of our study was to develop an immunoassay to detect NT-proBNP in saliva and to determine if there is a correlation with blood levels.

Methods

Saliva samples were collected from healthy volunteers (n = 40) who had no underlying heart conditions and HF patients (n = 45) at rest. Samples were stored at −80°C until analysis. A customised homogeneous sandwich AlphaLISA^(R) immunoassay was used to quantify NT-proBNP levels in saliva.

Results

Our NT-proBNP immunoassay was validated against a commercial Roche assay on plasma samples collected from HF patients (n = 37) and the correlation was r² = 0.78 (p<0.01, y = 1.705× +1910.8). The median salivary NT-proBNP levels in the healthy and HF participants were <16 pg/mL and 76.8 pg/mL, respectively. The salivary NT-proBNP immunoassay showed a clinical sensitivity of 82.2% and specificity of 100%, positive predictive value of 100% and negative predictive value of 83.3%, with an overall diagnostic accuracy of 90.6%.

Conclusion

We have firstly demonstrated that NT-proBNP can be detected in saliva and that the levels were higher in heart failure patients compared with healthy control subjects. Further studies will be needed to demonstrate the clinical relevance of salivary NT-proBNP in unselected, previously undiagnosed populations.     

Tumor markers (CEA, TPA and CA 19-9) in urine of bladder cancer patients

This study was carried out to evaluate the usefulness of determining urinary levels of carcinoembryogenic antigen (CEA), tissue-polypeptide antigen (TPA), and gastro-intestinal cancer antigen (Ca19-9) in addition to the usual diagnostic procedures for bladder cancer. Sixty-seven patients with transitional bladder cancer, 40 healthy controls and 20 patients with inflammatory diseases of the urinary tract were considered. All urine samples were obtained from patients with intact renal function and no urinary tract infection. TPA and Ca19-9 urinary levels in patients with G3 bladder tumors were significantly higher than in those with lower graded neoplasms. The sensitivity, specificity, and predictive value of a positive (PV+) or negative (PV-) test and the diagnostic accuracy were also evaluated. Ca19-9 was the best urinary marker for bladder cancer (sensitivity 71.6%, specificity 91.6%, PV+ 90.5%, PV- 74.3%, diagnostic accuracy 81%).     

Serum evaluation of soluble interferon-α/β receptor and high-sensitivity C-reactive protein for diagnosis of the patients with gastrointestinal and hepatobiliary-pancreatic cancer

Serum soluble interferon-α/β receptor (sIFN-α/βR) and high-sensitivity C-reactive protein (hs-CRP) levels were evaluated in the patients with gastrointestinal and hepatobiliary-pancreatic cancer. We compared the sensitivity and specificity of serum sIFN-α/βR with that of serum hs-CRP and evaluated the two diagnostic parameters in combination. Serum sIFN-α/βR levels were measured in 92 patients and 25 healthy individuals by enzyme-linked immunosorbent assay. The diagnoses were 37 cases of hepatocellular carcinoma, 17 cases of pancreatic cancer, 15 cases of colon cancer, 13 cases of biliary tract cancer, and 10 cases of gastric cancer. Serum levels of sIFN-α/βR and hs-CRP were significantly higher in the patients than in healthy individuals (p < 0.05). The optimal cut-off values of sIFN-α/βR and hs-CRP were 3600 pg/ml and 0.5 μg/ml, respectively. The sensitivity and specificity for these thresholds were 94.6% and 88.0%, whereas positive predictive and negative predictive values were 96.7% and 81.5%. These results suggest that a combination of serum sIFN-α/βR and hs-CRP thresholds may be more reliable diagnostic parameter for gastrointestinal and hepatobiliary-pancreatic cancer.     

Comparative Assessment of ELISAs Using Recombinant Saposin-Like Protein 2 and recombinant Cathepsin L-1 from Fasciola hepatica for the Serodiagnosis of Human Fasciolosis

Two recombinant Fasciola hepatica antigens, saposin-like protein-2 (recSAP2) and cathepsin L-1 (recCL1), were assessed individually and in combination in enzyme-linked immunosorbent assays (ELISA) for the specific serodiagnosis of human fasciolosis in areas of low endemicity as encountered in Central Europe. Antibody detection was conducted using ProteinA/ProteinG (PAG) conjugated to alkaline phosphatase. Test characteristics as well as agreement with results from an ELISA using excretory–secretory products (FhES) from adult stage liver flukes was assessed by receiver operator characteristic (ROC) analysis, specificity, sensitivity, Youdens J and overall accuracy. Cross-reactivity was assessed using three different groups of serum samples from healthy individuals (n = 20), patients with other parasitic infections (n = 87) and patients with malignancies (n = 121). The best combined diagnostic results for recombinant antigens were obtained using the recSAP2-ELISA (87% sensitivity, 99% specificity and 97% overall accuracy) employing the threshold (cut-off) to discriminate between positive and negative reactions that maximized Youdens J. The findings showed that recSAP2-ELISA can be used for the routine serodiagnosis of chronic fasciolosis in clinical laboratories; the use of the PAG-conjugate offers the opportunity to employ, for example, rabbit hyperimmune serum for the standardization of positive controls.     

Diagnosing Impaired Glucose Tolerance Using Direct Infusion Mass Spectrometry of Blood Plasma

The goal of this study was to evaluate the capacity for mass spectrometry of blood plasma to diagnose impaired glucose tolerance (IGT). For this study, blood plasma samples from control subjects (n = 30) and patients with IGT (n = 20) were treated with methanol and low molecular weight fraction were then analyzed by direct infusion mass spectrometry. A total of 51 metabolite ions strongly associated with IGT were detected. The area under a receiver operating characteristic (ROC) curve (AUC) for diagnosing IGT that was based on an analysis of all these metabolites was 0.93 (accuracy 90%, specificity 90%, and sensitivity 90%). The associated reproducibility was 85%. The metabolites identified were also consistent with risk factors previously associated with the development of diabetes. Thus, direct infusion mass spectrometry of blood plasma metabolites represents a rapid, single-step, and reproducible method for the analysis of metabolites. Moreover, this method has the potential to serve as a prototype for clinical analyses that could replace the currently used glucose tolerance test with a more patient-friendly assay.     

Non-computer-assisted liquid-based cytology for diagnosis of oral squamous cell carcinoma

Abstract

The development of oral squamous cell carcinoma (OSCC) occasionally follows the neoplastic progression of other premalignant lesions. Although biopsy is the definitive diagnostic method, liquid-based cytology is an adequate method for screening suspicious lesions. We compared liquid-based cytology to histology for diagnosis of OSCC in patients with oral lesions that raised clinical suspicion of malignancy. Our sample consisted of 48 patients. Cytological samples were obtained by scraping the lesion superficially using Cytobrush^®. We conducted cytological and histopathological evaluation of all preparations. We estimated sensitivity and specificity levels as well as positive and negative predictive values. The degree of inter-observer agreement for both methods was assessed using the kappa index. Twenty-eight (58.3%) of the cases finally were diagnosed with OSCC and 20 (41.7%) were determined to be premalignant lesions. We observed eight false negatives and no false positives; OSCC prevalence was 56.5%. The values for diagnostic indices were: sensitivity, 69% (CI 95%, prevalence 51.87); specificity, 100%; positive predictive value, 100%; negative predictive value, 71% (CI 95% 54.82). A kappa index of 0.622 (CI 95% 0.93, 0.39) was observed.     

A novel serum metabolomics-based diagnostic approach for colorectal cancer

Background

To improve the quality of life of colorectal cancer patients, it is important to establish new screening methods for early diagnosis of colorectal cancer.

Methodology/Principal Findings

We performed serum metabolome analysis using gas-chromatography/mass-spectrometry (GC/MS). First, the accuracy of our GC/MS-based serum metabolomic analytical method was evaluated by calculating the RSD% values of serum levels of various metabolites. Second, the intra-day (morning, daytime, and night) and inter-day (among 3 days) variances of serum metabolite levels were examined. Then, serum metabolite levels were compared between colorectal cancer patients (N = 60; N = 12 for each stage from 0 to 4) and age- and sex-matched healthy volunteers (N = 60) as a training set. The metabolites whose levels displayed significant changes were subjected to multiple logistic regression analysis using the stepwise variable selection method, and a colorectal cancer prediction model was established. The prediction model was composed of 2-hydroxybutyrate, aspartic acid, kynurenine, and cystamine, and its AUC, sensitivity, specificity, and accuracy were 0.9097, 85.0%, 85.0%, and 85.0%, respectively, according to the training set data. In contrast, the sensitivity, specificity, and accuracy of CEA were 35.0%, 96.7%, and 65.8%, respectively, and those of CA19-9 were 16.7%, 100%, and 58.3%, respectively. The validity of the prediction model was confirmed using colorectal cancer patients (N = 59) and healthy volunteers (N = 63) as a validation set. At the validation set, the sensitivity, specificity, and accuracy of the prediction model were 83.1%, 81.0%, and 82.0%, respectively, and these values were almost the same as those obtained with the training set. In addition, the model displayed high sensitivity for detecting stage 0–2 colorectal cancer (82.8%).

Conclusions/Significance

Our prediction model established via GC/MS-based serum metabolomic analysis is valuable for early detection of colorectal cancer and has the potential to become a novel screening test for colorectal cancer.     

Learning to predict cancer-associated skeletal muscle wasting from 1H-NMR profiles of urinary metabolites

Cancer-associated muscle wasting is associated with reduction in functional status, in response to treatment and in life expectancy. Methods currently used to assess muscle loss involve diagnostic imaging techniques such as computed tomography (CT), which are costly, inconvenient, invasive, time consuming and have limited ability to detect early or slowly evolving wasting. We present a novel approach using single time-point urinary metabolite profiles to determine whether a patient is experiencing muscle wasting. We analyzed 93 random urine samples from patients with cancer using ¹H-NMR. Using two successive CT images we assessed their lumbar skeletal muscle area (cm²) to estimate the rate of muscle change (% loss or gain over time) for each patient. The average muscle change over time was −4.71%/100 days in the muscle-losing group and +3.91%/100 days in the comparator group. Bivariate statistics identified metabolites related with muscle loss, including constituents and metabolites of muscle (creatine, creatinine, 3-OH-isovalerate), amino acids (Leu, Ile, Val, Ala, Thr, Tyr, Gln, Ser) and intermediary metabolites. We also applied machine-learning techniques to identify patterns of urinary metabolites that identify which patients are likely to lose muscle mass. We evaluated the predictive performance of 8 machine-learning approaches using fivefold cross validation and permutation testing, and found that SVM provided the best generalization accuracy (82.2%). These results suggest that ¹H-NMR analysis of a single random urine sample may be a fast, cheap, safe and inexpensive tool to screen and monitor muscle loss, and that useful classifiers for predicting related metabolic conditions are possible with the methodology presented.     

Spermine and Citrate as Metabolic Biomarkers for Assessing Prostate Cancer Aggressiveness

Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients) with a high cancer content (mean: 61.8%) were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS) were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS). Multivariate analysis (PLS, PLS-DA) and absolute quantification (LCModel) were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30) and high grade (GS≥7, n = 81) cancer with normal adjacent tissue (n = 47). High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044) and citrate (p = 7.73·10⁻⁴), and an increase in the clinically applied (total choline+creatine+polyamines)/citrate (CCP/C) ratio (p = 2.17·10⁻⁴). The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71), and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS) within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.     

Sphingolipids signature in plasma and tissue as diagnostic and prognostic tools in oral squamous cell carcinoma

Enzymes related to sphingolipids metabolism has been suggested as altered in oral squamous cell carcinoma (OSCC). However, clinical relevance of diverse sphingolipids in OSCC is not fully known. Here, we evaluated sphingolipidomics in plasma and tumor tissues as a tool for diagnosis/prognosis in OSCC patients. Plasma was obtained from 58 controls and 56 OSCC patients, and paired tumor and surgical margin tissues (n = 42). The levels of 28 sphingolipids molecules were obtained by mass spectrometry. Furthermore, sphingolipids were analyzed with clinical and pathological characteristics to search the potential for diagnosis and prognosis. Lower levels of 17 sphingolipids was found in the plasma of OSCC patients compared to controls while four were elevated in tumor tissues. C18:0 dyhidroceramide and C24:0 lactosylceramide in plasma were associated with perineural invasion, while tissue levels of ceramide and dyhidroceramide were associated with advanced tumor stage and perineural invasion. High plasma levels of C24:0 ceramide (HR = 0.10, p = 0.0036) and C24:1 glucosylceramide (HR = 6.62, p = 0.0023), and tissue levels of C24:0 dyhidroceramide (HR = 3.95, p = 0.032) were identified as independent prognostic factors. Moreover, we identified signatures composed by i) sphinganine-1-phosphate and C16 ceramide-1-phosphate in plasma with significant diagnostic accuracy, while ii) C24:0 ceramide, C24:0 dyhidroceramide, and C24:1 glucosylceramide plasma levels, and iii) C24:0 dyhidrosphingomyelin and C24:0 ceramide tissue levels showed value to predict survival in patients aged 60 years or older. We proposed the sphingolipids signatures in plasma and tumor tissues as biomarkers candidates to diagnosis and prognosis in OSCC.