Database-assisted global metabolomics profiling of pleural effusion induced by tuberculosis and malignancy

Determination of dimethylated nucleosides in serum from colorectal cancer patients by hydrophilic interaction liquid chromatography-tandem mass spectrometry

RNA modifications play a crucial regulatory role in a variety of biological processes and are closely related to numerous diseases, including cancer. The diversity of metabolites in serum makes it a favored biofluid for biomarkers discovery. In this work, a robust and accurate hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS) approach was established for simultaneous determination of dimethylated nucleosides in human serum. Using the established method, we were able to accurately quantify the concentrations of N6-2'-O-dimethyladenosine (m6Am), N2,N2-dimethylguanosine (m2,2G), and 5,2'-O-dimethyluridine (m5Um) in serum samples from 53 healthy controls, 57 advanced colorectal adenoma patients, and 39 colorectal cancer (CRC) patients. The results showed that, compared with healthy controls and advanced colorectal adenoma patients, the concentrations of m6Am and m2,2G were increased in CRC patients, while the concentration of m5Um was decreased in CRC patients. These results indicate that these three dimethylated nucleosides could be potential biomarkers for early detection of colorectal cancer. Interestingly, the level of m5Um was gradually decreased from healthy controls to advanced colorectal adenoma patients to CRC patients, indicating m5Um could also be used to evaluate the level of malignancy of colorectal tumor. In addition, this study will contribute to the investigation on the regulatory mechanisms of RNA dimethylation in the onset and development of colorectal cancer.

Development and validation of an artificial neural network model for non-invasive gastric cancer screening and diagnosis

Non-invasive and cost-effective diagnosis of gastric cancer is essential to improve outcomes. Aim of the study was to establish a neural network model based on patient demographic data and serum biomarker panels to aid gastric cancer diagnosis. A total of 295 patients hospitalized in Nanjing Drum Tower hospital diagnosed with gastric cancer based on tissue biopsy, and 423 healthy volunteers were included in the study. Demographical information and tumor biomarkers were obtained from Hospital Information System (HIS) as original data. Pearson's correlation analysis was applied on 574 individuals' data (training set, 229 patients and 345 healthy volunteers) to analyze the relationship between each variable and the final diagnostic result. And independent sample t test was used to detect the differences of the variables. Finally, a neural network model based on 14 relevant variables was constructed. The model was tested on the validation set (144 individuals including 66 patients and 78 healthy volunteers). The predictive ability of the proposed model was compared with other common machine learning models including logistic regression and random forest. Tumor markers contributing significantly to gastric cancer screening included CA199, CA125, AFP, and CA242 were identified, which might be considered as important inspection items for gastric cancer screening. The accuracy of the model on validation set was 86.8% and the F1-score was 85.0%, which were better than the performance of other models under the same condition. A non-invasive and low-cost artificial neural network model was developed and proved to be a valuable tool to assist gastric cancer diagnosis.

Simultaneous Determination of Methylated Nucleosides by HILIC-MS/MS Revealed Their Alterations in Urine from Breast Cancer Patients

RNA methylation plays a vital role in the pathogenesis of a variety of diseases including cancer, and aberrant levels of modified nucleosides in RNA were revealed to be related to cancer. Urine is a favored source for biomarker discovery due to the non-invasion to patients. Herein, we developed a sensitive hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC–MS/MS) method combined with stable isotope dilution for accurate quantification of methylated nucleosides in human urine. With this method, we successfully quantified ten methylated nucleosides in urine samples collected from healthy controls and breast cancer patients. We found N⁶-methyladenosine (m⁶A), 2′-O-methyladenosine (A_m), N¹-methyladenosine (m¹A), N⁶,2′-O-dimethyladenosine (m⁶A_m), N¹-methylguanosine (m¹G), 2′-O-methylguanosine (G_m), 5-methylcytidine (m⁵C) and 2′-O-methylcytidine (C_m) were all decreased in early-stage breast cancer patients, and a nomogram prediction model was constructed. Locally advanced breast cancer patients exhibited elevated levels of urinary 2′-O-methylated nucleosides in comparison to early-stage breast cancer patients. Together, we developed a robust method for the simultaneous determination of methylated nucleosides in human urine, and the results revealed an association between the contents of urinary methylated nucleosides and the occurrence of breast cancer, which may stimulate future studies about the regulatory roles of these methylated nucleosides in the initiation and progression of breast cancer.

Determination of adenosine and its modifications in urine and plasma from breast cancer patients by hydrophilic interaction liquid chromatography-tandem mass spectrometry

RNA modifications have been revealed to be essential in many biological activities, and their disorders are associated with various human diseases, including cancers. 2'-O-methyladenosine (A_m), N¹-methyladenosine (m¹A), N⁶-methyladenosine (m⁶A), N⁶,2'-O-dimethyladenosine (m⁶A_m) and N⁶,N⁶-dimethyladenosine (m⁶₂A) are important adenosine (A) modifications. The noninvasive collection of urine samples and the diverse contents of metabolites in plasma make them favored biofluids for biomarkers discovery. In this work, we established a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS) method to quantify these six nucleosides in urine and plasma of healthy controls and breast cancer (BC) patients. The limit of detection (LOD) for A, A_m, m¹A, m⁶A, m⁶A_m, and m⁶₂A were 0.0025, 0.01, 0.05, 0.005, 0.005, and 0.005 nM. The results showed that the concentrations of A_m, m⁶A, and m⁶A_m were increased, whereas m¹A was decreased in the urine of BC patients compared with the healthy controls. We also found that the level ratios of m¹A/A, m⁶A/A, and m⁶A_m/A were all reduced in plasma from BC patients, compared with healthy controls. Interestingly, these ratios of methylated adenosine nucleosides to adenosine in plasma could better discriminate BC patients from healthy controls, compared to the levels of these nucleosides. The present study not only suggests these modified adenosines can act as noninvasive biomarkers of BC but also will contribute to investigating the impacts of RNA methylation on the occurrence and development of BC.

Metabolomics as a Tool to Investigate HIV/TB Co-Infection

The HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) and tuberculosis (TB) pandemics are perpetuated by a significant global burden of HIV/TB co-infection. The synergy between HIV and Mycobacterium tuberculosis (Mtb) during co-infection of a host is well established. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms thereof remain poorly understood. Metabolomics has been applied to study various aspects of HIV and Mtb infection separately, yielding insights into infection- and treatment-induced metabolic adaptations experienced by the host. Despite the contributions that metabolomics has made to the field, this approach has not yet been systematically applied to characterize the HIV/TB co-infected state. Considering that limited HIV/TB co-infection metabolomics studies have been published to date, this review briefly summarizes what is known regarding the HIV/TB co-infection synergism from a conventional and metabolomics perspective. It then explores metabolomics as a tool for the improved characterization of HIV/TB co-infection in the context of previously published human-related HIV infection and TB investigations, respectively as well as for addressing the gaps in existing knowledge based on the similarities and deviating trends reported in these HIV infection and TB studies.