High-resolution proteomics and metabolomics in thyroid cancer: Deciphering novel biomarkers

The influence of cancer on the reprogramming of lipid metabolism in healthy thyroid tissues of patients with papillary thyroid carcinoma

BACKGROUND AND OBJECTIVES

Over the years we observed changes in the metabolism of glucose, amino acids, fatty acids (FA) and nucleotides in cancer cells in order to maintain their viability and proliferate. Moreover, as the latest data show, cancer also forces a complete change in the behavior of other tissues. For instance, fat-filled adipocytes are often found in the vicinity of invasive solid human tumors. We investigated the effects of papillary thyroid carcinoma (PTC) on the lipid metabolism of healthy tissue distant from the tumor.

METHOD

Thyroid tissue was collected from female patients immediately after surgical removal of the entire thyroid gland. Blood samples were collected from PTC patients and healthy volunteers. Real-time PCR assays were performed to analyze the expression of lipogenic genes and a broad panel of FA was determined using the gas chromatography-mass spectrometry method.

RESULTS

The concentration of lipids was higher in paratumor tissue than in healthy thyroid tissue (p = 0.005). The lipogenic genes tested were significantly increased in paratumor tissue compared to healthy tissue, especially enzymes related to the synthesis of very long-chain saturated and polyunsaturated FAs (VLCSFAs and PUFAs, respectively) (p < 0.001). The FA profile also showed increased levels of C22-C26, VLCSFAs and almost all PUFAs in paratumor tissue (p < 0.05).

CONCLUSION

Our study suggests that a restructuring of lipid metabolism occurs in the adjacent healthy thyroid gland and that the metabolism of VLCSFAs and PUFAs is higher in the paratumor tissue than in the distant tissue of the healthy thyroid gland.

Assessment of circulating proteins in thyroid cancer: Proteome-wide Mendelian randomization and colocalization analysis

The causality between circulating proteins and thyroid cancer (TC) remains unclear. We employed five large-scale circulating proteomic genome-wide association studies (GWASs) with up to 100,000 participants and a TC meta-GWAS (nCase = 3,418, nControl = 292,703) to conduct proteome-wide Mendelian randomization (MR) and Bayesian colocalization analysis. Protein and gene expressions were validated in thyroid tissue. Through MR analysis, we identified 26 circulating proteins with a putative causal relationship with TCs, among which NANS protein passed multiple corrections (P BH = 3.28e-5, 0.05/1,525). These proteins were involved in amino acids and organic acid synthesis pathways. Colocalization analysis further identified six proteins associated with TCs (VCAM1, LGMN, NPTX1, PLEKHA7, TNFAIP3, and BMP1). Tissue validation confirmed BMP1, LGMN, and PLEKHA7's differential expression between normal and TC tissues. We found limited evidence for linking circulating proteins and the risk of TCs. Our study highlighted the contribution of proteins, particularly those involved in amino acid metabolism, to TCs.

Homogentisic acid metabolism inhibits papillary thyroid carcinoma proliferation through ROS and p21-induced cell cycle arrest

Thyroid cancer is one of the most common primary endocrine malignancies worldwide, and papillary thyroid carcinoma (PTC) is the predominant histological type observed therein. Although PTC has been studied extensively, our understanding of the altered metabolism and metabolic profile of PTC tumors is limited. We identified that the content of metabolite homogentisic acid (HGA) in PTC tissues was lower than that in adjacent non-cancerous tissues. We evaluated the potential of HGA as a novel molecular marker in the diagnosis of PTC tumors, as well as its ability to indicate the degree of malignancy. Studies have further shown that HGA contributes to reactive oxygen species (ROS) associated oxidative stress, leading to toxicity and inhibition of proliferation. In addition, HGA caused an increase in p21 expression levels in PTC cells and induced G1 arrest. Moreover, we found that the low HGA content in PTC tumors was due to the low expression levels of tyrosine aminotransferase (TAT) and p-hydroxyphenylpyruvate hydroxylase (HPD), which catalyze the conversion of tyrosine to HGA. The low expression levels of TAT and HPD are strongly associated with a higher probability of PTC tumor invasion and metastasis. Our study demonstrates that HGA could be used to diagnose PTC and provides mechanisms linking altered HGA levels to the biological behavior of PTC tumors.

Progress of depression mechanism based on Omics method

Depression is a very common disabling mental disorder, which is typically characterized by high rates of disability and mortality. Although research into the various mechanisms of depression was still underway, its physiopathology remains uncertain. The rapid developments in new technologies and the combined use of a variety of techniques will help to understand the pathogenesis of depression and explore effective treatment methods. In this review, we focus on the combination of proteomic and metabolomic approaches to analyze metabolites and proteins in animal models of depression induced by different modeling approaches, with the aim of broadening the understanding of the physiopathological mechanisms of depression using complementary "omics" strategy.

Integrated proteomic and metabolomic analysis of plasma reveals regulatory pathways and key elements in thyroid cancer

Thyroid cancer (TC) is the most common endocrine malignancy with increasing incidence in recent years. Fine-needle aspiration biopsy (FNAB), as a gold standard for the initial evaluation of thyroid nodules, fails to cover all the cytopathologic conditions resulting in overdiagnosis. There is an urgent need for a better classification of thyroid cancer from benign thyroid nodules (BTNs). Here, data independent acquisition (DIA)-based proteomics and untargeted metabolomics in plasma samples of 10 patients with TC and 15 patients with BTNs were performed. Key proteins and metabolites were identified specific to TC, and an independent cohort was used to validate the potential biomarkers using enzyme-linked immunosorbent assay (ELISA). In total, 1429 proteins and 1172 metabolites were identified. Principal component analysis showed a strong overlap at the proteomic level and a significant discrimination at the metabolomic level between the two groups, indicating a more drastic disturbance in the metabolome of thyroid cancer. Integrated analysis of proteomics and metabolomics shows glycerophospholipid metabolism and arachidonic acid metabolism as key regulatory pathways. Furthermore, a multi-omics biomarker panel was developed consisting of LCAT, GPX3 and leukotriene B4. Based on the AUC value for the discovery set, the classification performance was 0.960. The AUC value of the external validation set was 0.930. Altogether, our results will contribute to the clinical application of potential biomarkers in the diagnosis of thyroid cancer.

Hyperbranched polyamidoamine-RGD peptide/si-circICA1 in the treatment of invasive thyroid cancer through targeting of the miR-486-3p/SERPINA1 axis

Aim: This study aimed to identify molecular markers associated with papillary thyroid cancer (PTC) and investigate the therapeutic potential of targeted nanoscale drugs. Materials & methods: We analyzed the effects of circICA1 and miR-486-3p on B-CPAP cells' proliferation, apoptosis, migration and invasion. The regulation of the miR-486-3p/SERPINA1 axis was explored using quantitative real-time reverse transcription PCR and western blot analyses for metastasis. In vivo, we evaluated the effects of hyperbranched polyamidoamine-RGD peptide/si-circICA1 on PTC growth and metastasis. Results: Enhanced miR-486-3p expression inhibits B-CPAP cells' proliferation and invasion. si-circICA1 delivered via hyperbranched polyamidoamine-RGD peptide nanoparticles shows potential for treating metastasis in PTC. Conclusion: This study identifies key molecular mechanisms underlying PTC invasiveness and suggests a promising therapeutic strategy for PTC using targeted nanoscale drugs.

Progress in understanding primary glomerular disease: insights from urinary proteomics and in-depth analyses of potential biomarkers based on bioinformatics

Chronic kidney disease (CKD) has become a global public health challenge. While primary glomerular disease (PGD) is one of the leading causes of CKD, the specific pathogenesis of PGD is still unclear. Accurate diagnosis relies largely on invasive renal biopsy, which carries risks of bleeding, pain, infection and kidney vein thrombosis. Problems with the biopsy procedure include lack of glomeruli in the tissue obtained, and the sampling site not being reflective of the overall lesion in the kidney. Repeated renal biopsies to monitor disease progression cannot be performed because of the significant risks of bleeding and kidney vein thrombosis. On the other hand, urine collection, a noninvasive method, can be performed repeatedly, and urinary proteins can reflect pathological changes in the urinary system. Advancements in proteomics technologies, especially mass spectrometry, have facilitated the identification of candidate biomarkers in different pathological types of PGD. Such biomarkers not only provide insights into the pathogenesis of PGD but also are important for diagnosis, monitoring treatment, and prognosis. In this review, we summarize the findings from studies that have used urinary proteomics, among other omics screens, to identify potential biomarkers for different types of PGD. Moreover, we performed an in-depth bioinformatic analysis to gain a deeper understanding of the biological processes and protein-protein interaction networks in which these candidate biomarkers may participate. This review, including a description of an integrated analysis method, is intended to provide insights into the pathogenesis, noninvasive diagnosis, and personalized treatment efforts of PGD and other associated diseases.

The potential value of LC-MS non-targeted metabonomics in the diagnosis of follicular thyroid carcinoma

Background

To explore the metabolic differences of follicular thyroid carcinoma (FTC) by metabonomics, to find potential biomarkers for the diagnosis of FTC, and to explore the pathogenesis and diagnosis and treatment strategies of FTC.

Method

The metabonomics of 15 patients with FTC and 15 patients with follicular thyroid nodules(FTN) treated in Henan Cancer Hospital were analyzed by liquid chromatography-mass spectrometry (LC-MS).

Results

The analysis showed that the metabolite profiles of FTC tissues could be well distinguished from those of control tissues, and 6 kinds of lipids were identified respectively, including lysophosphatidic acid(LysoPA) [LysoPA(0:0/18:0),LysoPA(0:0/18:2(9Z,12Z)],LysoPA[20:4(8Z,11Z,14Z,17Z)/0:0)]; phosphatidic acid(PA) [PA(20:3(8Z,11Z,14Z)/0:0),PA(20:4(5Z,8Z,11Z,14Z)/0:0),PA(20:5(5Z,8Z,11Z,14Z,17Z)/0:0)]; lysophosphatidylcholine(LPC) [LPC(18:1),LPC(16:0),LPC[16:1(9Z)/0:0],LPC(17:0),LPC[22:4(7Z,10Z,13Z,16Z),LPC(20:2(11Z,14Z); phosphatidylcholine(PC)(PC(14:0/0:0),PC(16:0/0:0); sphingomyelin(SM) (d18:0/12:0); fatty acid(FA)(18:1(OH3)]. There are 2 kinds of amino acids, including L-glutamate,L-glutamine.There are 3 other metabolites, including retinol,flavin adenine dinucleotide,androsterone glucuronide.Lipid metabolites are the main metabolites in these metabolites.The metabolic pathways related to FTC were analyzed by KEGG and HMDB, and 9 metabolic pathways were found, including 4 amino acid related metabolic pathways, 1 lipid metabolic pathways and 4 other related pathways.

Conclusion

There are significant differences in many metabonomic characteristics between FTC and FTN, suggesting that these metabolites can be used as potential biomarkers. Further study found that LysoPA and its analogues can be used as biomarkers in the early diagnosis of FTC.It may be related to the abnormal metabolism of phospholipase D (PLD), the key enzyme of LysoPA synthesis caused by RAS pathway. At the same time, it was found that the metabolic pathway of amino acids and lipids was the main metabolic pathway of FTC. The abnormality of LysoPA may be the cause of follicular tumor carcinogenesis caused by lipid metabolic pathway.

Comprehensive analysis of tissue proteomics in patients with papillary thyroid microcarcinoma uncovers the underlying mechanism of lymph node metastasis and its significant sex disparities

Background

Lymph node metastasis (LNM) in papillary thyroid microcarcinoma (PTMC) is associated with an increased risk of recurrence and poor prognosis. Sex has been regarded as a critical risk factor for LNM. The present study aimed to investigate the molecular mechanisms underlying LNM and its significant sex disparities in PTMC development.

Methods

A direct data-independent acquisition (DIA) proteomics approach was used to identify differentially expressed proteins (DEPs) in PTMC tumorous tissues with or without LNM and from male and female patients with LNM. The functional annotation of DEPs was performed using bioinformatics methods. Furthermore, The Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) dataset and immunohistochemistry (IHC) were used to validate selected DEPs.

Results

The proteomics profile in PTMC with LNM differed from that of PTMC without LNM. The metastasis-related DEPs were primarily enriched in categories associated with mitochondrial dysfunction and may promote tumor progression by activating oxidative phosphorylation and PI3K/AKT signaling pathways. Comparative analyses of these DEPs revealed downregulated expression of specific proteins with well-established links to tumor metastasis, such as SLC25A15, DIRAS2, PLA2R1, and MTARC1. Additionally, the proteomics profiles of male and female PTMC patients with LNM were dramatically distinguishable. An elevated level of ECM-associated proteins might be related to more LNM in male PTMC than in female PTMC patients. The upregulated expression levels of MMRN2 and NID2 correlated with sex disparities and showed a positive relationship with unfavorable variables, such as LNMs and poor prognosis.

Conclusions

The proteomics profiles of PTMC show significant differences associated with LNM and its sex disparities, which further expands our understanding of the functional networks and signaling pathways related to PTMC with LNM.

Nomograms Based on Serum N-glycome for Diagnosis of Papillary Thyroid Microcarcinoma and Prediction of Lymph Node Metastasis

Non-invasive biomarkers for the diagnosis and prognosis of papillary thyroid microcarcinoma (PTMC) are still urgently needed. We aimed to characterize the N-glycome of PTMC, and establish nomograms for the diagnosis of PTMC and the prediction of lymph node metastasis (LNM). N-glycome of PTMC (LNM vs. non-LNM, capsular invasion (CI) vs. non-CI (NCI)) and matched healthy controls (HC) were quantitatively analyzed based on mass spectrometry. N-glycan traits associated with PTMC/LNM were used to create binomial logistic regression models and were visualized as nomograms. We found serum N-glycome differed between PTMC and HC in high-mannose, complexity, fucosylation, and bisection, of which, four N-glycan traits (TM, CA1, CA4, and A2Fa) were significantly associated with PTMC. The nomogram based on four traits achieved good performance for the identification of PTMC. Two N-glycan traits (CA4 and A2F0S0G) showed strong associations with LNM. The nomogram based on two traits showed relatively good performance in predicting LNM. We also found differences between CI and NCI in several N-glycan traits, which were not the same as that associated with LNM. This study reported serum N-glycosylation signatures of PTMC for the first time. Nomograms constructed from aberrant glycans could be useful tools for PTMC diagnosis and stratification.

Metabolic Profile Characterization of Different Thyroid Nodules Using FTIR Spectroscopy: A Review

Thyroid cancer's incidence has increased in the last decades, and its diagnosis can be a challenge. Further and complementary testing based in biochemical alterations may be important to correctly identify thyroid cancer and prevent unnecessary surgery. Fourier-transform infrared (FTIR) spectroscopy is a metabolomic technique that has already shown promising results in cancer metabolome analysis of neoplastic thyroid tissue, in the identification and classification of prostate tumor tissues and of breast carcinoma, among others. This work aims to gather and discuss published information on the ability of FTIR spectroscopy to be used in metabolomic studies of the thyroid, including discriminating between benign and malignant thyroid samples and grading and classifying different types of thyroid tumors.

Analysis of the Diagnostic Effect of EUS-RTE on Giant Cystic Tumours of the Oesophagus Based on Cluster Analysis

This paper presents an in-depth analysis and study of the diagnostic effectiveness of EUS-RTE in giant cystic tumours of the oesophagus utilizing cluster analysis. A new form of interval data expression was designed based on the cluster analysis algorithm, as well as a new way of updating the cluster radius and cluster centre. Feature triads are defined, eliminating the need to access all historical data at the time of update. It also prevents the case of overfusion of clusters and outputting only one cluster. If there exist a very low number of clusters, the newly merged clusters are reclustered according to the density clustering method for the internal data objects based on the cluster segmentation so that the data objects in the same cluster have a high similarity as possible. All accumulated electronic files of oesophageal cancer cases were collected and comprehensively organized, and all clinical data of 129 eligible cases with a total of 356 consultations were screened in strict accordance with inclusion and exclusion criteria. A database of oesophageal cancer cases was established using Visual FoxPro software, and frequency distribution, cluster analysis, association rule, and chi-square test were used to focus on mining the association between symptoms, disease mechanisms, prescriptions, and medications. The results were analysed and summarized. Overall, the therapeutic efficacy and safety of the three groups of treatment modalities for gastric mesenchymal tumours were positive, and the preoperative endoscopic treatment modalities should be selected based on the EUS-RTE characteristics of the tumour, the site, and the operator's skill level in a comprehensive manner.

Silencing circRNA protein kinase C iota (circ-PRKCI) suppresses cell progression and glycolysis of human papillary thyroid cancer through circ-PRKCI/miR-335/E2F3 ceRNA axis

The circular RNA PRKCI (circ-PRKCI; ID: hsa_circ_0122683) is highly expressed in human papillary thyroid cancer (PTC) tumors according to GSE93522 dataset. However, its role in PTC tumorigenesis remains to be documented. Here, quantitative real-time PCR showed that expression of circ-PRKCI was abnormally upregulated in human PTC patients' tumors and cells, and higher circ-PRKCI might predict lymph node metastasis and recurrence. Functionally, cell behaviors were measured by 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide assay, colony formation assay, fluorescence-activated cell sorting method, scratch wound assay, transwell assay, western blotting, and assay kits for glucose and lactate. As a result, circ-PRKCI knockdown could suppress cell cycle progression of PTC cells and restrain the abilities of cell proliferation, colony formation, wound closure, invasion, glucose consumption and lactate production, accompanied with decreased levels of matrix metalloproteinase-2 (MMP2), MMP9 and Snail. Moreover, above-mentioned inhibition could be imitated by overexpressing microRNA-335-5p (miR-335). Molecularly, circ-PRKCI functioned as a sponge for miR-335 and miR-335 could further targeted E2F transcription factor-3 (E2F3), according to dual-luciferase reporter assay and RNA immunoprecipitation. However, downregulating miR-335 diminished the effects of circ-PRKCI role on cell growth, metastasis and glycolysis in PTC cells; besides, there was a counteractive effect between miR-335 upregulation and E2F3 upregulation in PTC cells as well. Furthermore, xenograft experiment revealed that silencing circ-PRKCI could retard tumor growth of PTC cells in vivo. Collectively, circ-PRKCI exerted oncogenic role in PTC by antagonizing cell progression and glycolysis via regulating miR-335/E2F3 axis, suggesting circ-PRKCI was a potential biomarker and target for PTC.

Clinical implications of TPO and AOX1 in pediatric papillary thyroid carcinoma

BACKGROUND

Thyroid carcinoma is a common pediatric head and neck cancer, of which papillary thyroid cancer (PTC) is the most common type. Previously, we found that thyroid peroxidase (TPO) and aldehyde oxidase 1 (AOX1) were differentially expressed in PTC. This study explored the clinical importance of TPO and AOX1 in the diagnosis and prognosis of PTC in children.

METHODS

Both TPO and AOX1 expression in PTC were analyzed using datasets from Gene Expression Omnibus (GEO). TPO and AOX1 protein levels in plasma from patients with PTC and non-tumor controls were detected via enzyme-linked immunosorbent assay (ELISA). The diagnostic accuracy of TPO and AOX1 was assessed using receiver operating characteristic (ROC) curve analysis. The association between gene expression levels and patient survival was explored using the Kaplan-Meier plotter online database.

RESULTS

The results revealed that TPO and AOX1 expression was significantly downregulated in four independent datasets (GSE33630, GSE27155, GSE3678, and GSE3467). TPO and AOX1 protein levels in blood plasma were significantly decreased in patients with PTC. Quantitative analysis demonstrated that TPO and AOX1 levels in plasma had satisfactory predictive performance and the ability to discriminate PTC from healthy samples. Prognostic analysis demonstrated that low levels of TPO and AOX1 were markedly associated with poor survival in patients with PTC.

CONCLUSIONS

In summary, these results implied that TPO and AOX1 could serve as novel biomarkers for the diagnosis and prognosis of pediatric PTC.

Novel biomarkers in Alzheimer's disease using high resolution proteomics and metabolomics: miRNAS, proteins and metabolites

Alzheimer's disease (AD) is the most common form of dementia. It affects approximately 6% of people over the age of 65 years. It is a clinicopathological, degenerative, chronical and progressive disease that exhibits a deterioration of memory, orientation, speech and other functions. Factors contributing to the pathogenesis of the disease are the presence of extracellular amyloid deposits, called neuritic senile plaques, and fibrillary protein deposits inside neurons, known as neurofibrillary bundles, that appear mainly in the frontal and temporal lobes. AD has a long preclinical latency and is difficult to diagnose and prevent at early stages. Despite the advent of novel high-throughput technologies, it is a great challenge to identify precise biomarkers to understand the progression of the disease and the development of new treatments. In this sense, important knowledge is emerging regarding novel molecular and biological candidates with diagnostic potential, including microRNAs that have a key role in gene repression. On the other hand, proteomic approaches offer a platform for the comprehensive analysis of the whole proteome in a certain physiological time. Proteomic technology investigates protein expression directly and reveals post-translational modifications known to be determinant for many human diseases. Clinically, there is growing evidence for the role of proteomic and metabolomic technologies in AD biomarker discovery. This review discusses the role of several miRNAs identified using genomic technologies, and the importance of novel proteomic and metabolomic approaches to identify new proteins and metabolites that may be useful as biomarkers for monitoring the progression and treatment of AD.

Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood

The incidence rate of thyroid carcinoma, especially papillary thyroid carcinoma (PTC), has increased significantly over time. As a primary pathway for metastasis, the lymphatic system is an important prognostic factor for PTC patients. Although the metabolic changes in PTC patients have been investigated in extensive studies, few studies focused on the whole blood metabolic profiling of PTC patients. In this study, we investigated the ¹H NMR-based metabolic profiles of whole blood samples that were obtained from healthy individuals and PTC patients, with or without lymph node metastasis. The estimation of the predictive potential of metabolites was evaluated using multivariate statistical analyses, which revealed that the whole blood carries information that is sufficient for distinguishing between PTC patients and healthy individuals. However, PTC patients were not well classified as positive or negative according to the lymph nodes. We did not find a metabolite that could discriminate the presence of lymph node metastasis. Further studies with larger sample sizes are needed to elucidate significant metabolites to indicate the presence of lymph node metastasis in patients with PTC.

Molecular Markers Guiding Thyroid Cancer Management

The incidence of thyroid cancer is rapidly increasing, mostly due to the overdiagnosis and overtreatment of differentiated thyroid cancer (TC). The increasing use of potent preclinical models, high throughput molecular technologies, and gene expression microarrays have provided a deeper understanding of molecular characteristics in cancer. Hence, molecular markers have become a potent tool also in TC management to distinguish benign from malignant lesions, predict aggressive biology, prognosis, recurrence, as well as for identification of novel therapeutic targets. In differentiated TC, molecular markers are mainly used as an adjunct to guide management of indeterminate nodules on fine needle aspiration biopsies. In contrast, in advanced thyroid cancer, molecular markers enable targeted treatments of affected signalling pathways. Identification of the driver mutation of targetable kinases in advanced TC can select treatment with mutation targeted tyrosine kinase inhibitors (TKI) to slow growth and reverse adverse effects of the mutations, when traditional treatments fail. This review will outline the molecular landscape and discuss the impact of molecular markers on diagnosis, surveillance and treatment of differentiated, poorly differentiated and anaplastic follicular TC.

Effect of simulated microgravity on metabolism of HGC-27 gastric cancer cells

The understanding into the pathogenesis and treatment of gastric cancer has improved in recent years; however, a number of limitations have delayed the development of effective treatment. Cancer cells can undergo glycolysis and inhibit oxidative phosphorylation in the presence of oxygen (Warburg effect). Previous studies have demonstrated that a rotary cell culture system (RCCS) can induce glycolytic metabolism. In addition, the potential of regulating cancer cells by targeting their metabolites has led to the rapid development of metabolomics. In the present study, human HGC-27 gastric cancer cells were cultured in a RCCS bioreactor, simulating weightlessness. Subsequently, liquid chromatography-mass spectrometry was used to examine the effects of simulated microgravity (SMG) on the metabolism of HGC-27 cells. A total of 67 differentially regulated metabolites were identified, including upregulated and downregulated metabolites. Compared with the normal gravity group, phosphatidyl ethanolamine, phosphatidyl choline, arachidonic acid and sphinganine were significantly upregulated in SMG conditions, whereas sphingomyelin, phosphatidyl serine, phosphatidic acid, L-proline, creatine, pantothenic acid, oxidized glutathione, adenosine diphosphate and adenosine triphosphate were significantly downregulated. The Human Metabolome Database compound analysis revealed that lipids and lipid-like metabolites were primarily affected in an SMG environment in the present study. Overall, the findings of the present study may aid our understanding of gastric cancer by identifying the underlying mechanisms of metabolism of the disease under SMG.

The Modulatory Properties of Li-Ru-Kang Treatment on Hyperplasia of Mammary Glands Using an Integrated Approach

Background: Li-Ru-Kang (LRK) has been used in the treatment of hyperplasia of mammary glands (HMG) for several decades and can effectively improve clinical symptoms. This study aims to investigate the mechanism by which LRK intervenes in HMG based on an integrated approach that combines metabolomics and network pharmacology analyses.

Methods: The effects of LRK on HMG induced by estrogen-progesterone in rats were evaluated by analyzing the morphological and pathological characteristics of breast tissues. Moreover, UPLC-QTOF/MS was performed to explore specific metabolites potentially affecting the pathological process of HMG and the effects of LRK. Pathway analysis was conducted with a combination of metabolomics and network pharmacology analyses to illustrate the pathways and network of LRK-treated HMG.

Results: Li-Ru-Kang significantly improved the morphological and pathological characteristics of breast tissues. Metabolomics analyses showed that the therapeutic effect of LRK was mainly associated with the regulation of 10 metabolites, including prostaglandin E2, phosphatidylcholine, leukotriene B4, and phosphatidylserine. Pathway analysis indicated that the metabolites were related to arachidonic acid metabolism, glycerophospholipid metabolism and linoleic acid metabolism. Moreover, principal component analysis showed that the metabolites in the model group were clearly classified, whereas the metabolites in the LRK group were between those in the normal and model groups but closer to those in the normal group. This finding indicated that these metabolites may be responsible for the effects of LRK. The therapeutic effect of LRK on HMG was possibly related to the regulation of 10 specific metabolites. In addition, we further verified the expression of protein kinase C alpha (PKCα), a key target predicted by network pharmacology analysis, and showed that LRK could significantly improve the expression of PKCα.

Conclusion: Our study successfully explained the modulatory properties of LRK treatment on HMG using metabolomics and network pharmacology analyses. This systematic method can provide methodological support for further understanding the complex mechanism underlying HMG and possible traditional Chinese medicine (TCM) active ingredients for the treatment of HMG.

Integrative Proteomics-Metabolomics Strategy for Pathological Mechanism of Vascular Depression Mouse Model

Vascular depression (VD), a subtype of depression, is caused by vascular diseases or cerebrovascular risk factors. Recently, the proportion of VD patients has increased significantly, which severely affects their quality of life. However, the current pathogenesis of VD has not yet been fully understood, and the basic research is not adequate. In this study, on the basis of the combination of LC-MS-based proteomics and metabolomics, we aimed to establish a protein metabolism regulatory network in a murine VD model to elucidate a more comprehensive impact of VD on organisms. We detected 44 metabolites and 304 proteins with different levels in the hippocampus samples from VD mice using a combination of metabolomic and proteomics analyses with an isobaric tags for relative and absolute quantification (iTRAQ) method. We constructed a protein-to-metabolic regulatory network by correlating and integrating the differential metabolites and proteins using ingenuity pathway analysis. Then we quantitatively validated the levels of the bimolecules shown in the bioinformatics analysis using LC-MS/MS and Western blotting. Validation results suggested changes in the regulation of neuroplasticity, transport of neurotransmitters, neuronal cell proliferation and apoptosis, and disorders of amino acids, lipids and energy metabolism. These proteins and metabolites involved in these dis-regulated pathways will provide a more targeted and credible direction to study the mechanism of VD. Therefore, this paper presents an approach and strategy that was applied in integrative proteomics and metabolomics for research and screening potential targets and biomarkers of VD, which could be more precise and credible in a field lacking adequate basic research.