The mutagenic forces shaping the genomic landscape of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) accounts for up to 25% of all lung cancers and has been associated with exposure to secondhand tobacco smoke and air pollution in observational studies. Here, we evaluate the mutagenic exposures in LCINS by examining deep whole-genome sequencing data from a large international cohort of 871 treatment-naïve LCINS recruited from 28 geographical locations within the Sherlock-Lung study. KRAS mutations were 3.8-fold more common in adenocarcinomas of never smokers from North America and Europe, while a 1.6-fold higher prevalence of EGFR and TP53 mutations was observed in adenocarcinomas from East Asia. Signature SBS40a, with unknown cause, was found in most samples and accounted for the largest proportion of single base substitutions in adenocarcinomas, being enriched in EGFR-mutated cases. Conversely, the aristolochic acid signature SBS22a was almost exclusively observed in patients from Taipei. Even though LCINS exposed to secondhand smoke had an 8.3% higher mutational burden and 5.4% shorter telomeres, passive smoking was not associated with driver mutations in cancer driver genes or the activities of individual mutational signatures. In contrast, patients from regions with high levels of air pollution were more likely to have TP53 mutations while exhibiting shorter telomeres and an increase in most types of somatic mutations, including a 3.9-fold elevation of signature SBS4 (q-value=3.1 × 10-5), previously linked mainly to tobacco smoking, and a 76% increase of clock-like signature SBS5 (q-value=5.0 × 10-5). A positive dose-response effect was observed with air pollution levels, which correlated with both a decrease in telomere length and an elevation in somatic mutations, notably attributed to signatures SBS4 and SBS5. Our results elucidate the diversity of mutational processes shaping the genomic landscape of lung cancer in never smokers.

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers.

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Serum sex hormones correlate with pathological features of papillary thyroid cancer.

PURPOSE: Sex hormones are thought to be responsible for the unique gender differences in papillary thyroid cancer(PTC). Most previous studies on these have focused on the expression of estrogen receptors, or have been limited to animal studies. The aim of our study was to explore the relationship between serum sex hormones and the pathological features of PTC in the clinical setting, as further evidence of the role of sex hormones in PTC. METHODS: Retrospective data analysis of patients who underwent thyroid surgery at the Department of Thyroid Surgery, Nanjing Drum Tower Hospital from January 2022 to September 2022 Correlation between serum sex hormone and pathological features was analyzed in male patients and in menopausal female patients. Serum sex hormones include luteinizing hormone(LH), follicle stimulating hormone(FSH), estradiol(E2), total testosterone(TT), progesterone(P), and prolactin(PRL). Tumor pathological characteristics include the number and size of tumor, presence of extrathyroidal extension(ETE), presence of lymph node metastasis(LNM). RESULTS: Preoperative serum E2 in male patients was positively correlated with tumor size in PTC, LH was negatively correlated with LNM, while TT and P were negatively correlated with ETE. Similar findings were not observed in menopausal female patients. CONCLUSION: We observed that serum sex hormones correlate with the pathological features of PTC in male patients, for the first time in a clinical study. High serum estrogens may be a risk factor for PTC, while androgens are the opposite. This somewhat corroborates previous research and provides new variables for future PTC prediction models.

The association between poor oral health and risk of breast cancer in the UK Biobank.

PURPOSE: Specific oral health conditions may be risk factors for breast cancer. This study aimed to investigate the associations of oral health conditions with breast cancer risk. METHODS: A total of 234,363 women from the UK Biobank prospective cohort were included in this study. We examined the association of self-reported painful/bleeding gums, loose teeth, mouth ulcers, toothache, and use of dentures with the risk of breast cancer. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the associations were calculated with adjustment for multiple confounders. RESULTS: No associations of self-reported painful/bleeding gums (HR = 1.04, 95% CI 0.98-1.10), loose teeth (HR = 0.92, 95% CI 0.82-1.02), mouth ulcers (HR = 0.99, 95% CI 0.93-1.06), toothache (HR = 1.03, 95% CI 0.92-1.14), or denture use (HR = 0.96, 95% CI 0.91-1.02) with breast cancer risk were found. No statistical heterogeneity was observed in analyses stratified by baseline smoking and menopausal status. CONCLUSION: We observed no association between self-reported oral health conditions with the risk of breast cancer. Additional research with clinical examinations or oral health biomarkers in diverse populations is warranted.

Endoscopic mucosal resection-precutting vs conventional endoscopic mucosal resection for sessile colorectal polyps sized 10-20 mm.

BACKGROUND: The optimal method to remove sessile colorectal lesions sized 10-20 mm remains uncertain. Piecemeal and incomplete resection are major limitations in current practice, such as endoscopic mucosal resection (EMR) and cold or hot snare polypectomy. Recently, EMR with circumferential precutting (EMR-P) has emerged as an effective technique, but the quality of current evidence in comparative studies of conventional EMR (CEMR) and EMR-P is limited. AIM: To investigate whether EMR-P is superior to CEMR in removing sessile colorectal polyps. METHODS: This multicenter randomized controlled trial involved seven medical institutions in China. Patients with colorectal polyps sized 10-20 mm were enrolled and randomly assigned to undergo EMR-P or CEMR. EMR-P was performed following submucosal injection, and a circumferential mucosa incision (precutting) was conducted using a snare tip. Primary outcomes included a comparison of the rates of en bloc and R0 resection, defined as one-piece resection and one-piece resection with histologically assessed clear margins, respectively. RESULTS: A total of 110 patients in the EMR-P group and 110 patients in the CEMR group were finally evaluated. In the per-protocol analysis, the proportion of en bloc resections was 94.3% [95% confidence interval (CI): 88.2%-97.4%] in the EMR-P group and 86% (95%CI: 78.2%-91.3%) in the CEMR group (P = 0.041), while subgroup analysis showed that for lesions > 15 mm, EMR-P also resulted in a higher en bloc resection rate (92.0% vs 58.8% P = 0.029). The proportion of R0 resections was 81.1% (95%CI: 72.6%-87.4%) in the EMR-P group and 76.6% (95%CI: 68.8%-84.4%) in the CEMR group (P = 0.521). The EMR-P group showed a longer median procedure time (6.4 vs 3.0 min; P < 0.001). No significant difference was found in the proportion of patients with adverse events (EMR-P: 9.1%; CEMR: 6.4%; P = 0.449). CONCLUSION: In this study, EMR-P served as an alternative to CEMR for removing nonpedunculated colorectal polyps sized 10-20 mm, particularly polyps > 15 mm in diameter, with higher R0 and en bloc resection rates and without increasing adverse events. However, EMR-P required a relatively longer procedure time than CEMR. Considering its potential benefits for en bloc and R0 resection, EMR-P may be a promising technique in colorectal polyp resection.

Effect of Lactobacillus rhamnosus hsryfm 1301 Fermented Milk on Lipid Metabolism Disorders in High-Fat-Diet Rats.

To further explore and improve the mechanism of probiotics to alleviate the disorder of lipid metabolism, transcriptomic and metabolomic with bioinformatic analysis were combined. In the present study, we successfully established a rat model of lipid metabolism disorder using a high-fat diet. Intervention with Lactobacillus rhamnosus hsryfm 1301 fermented milk resulted in a significant reduction in body weight, serum free fatty acid and blood lipid levels (p < 0.05), which predicted that the lipid metabolism disorder was alleviated in rats. Metabolomics and transcriptomics identified a total of 33 significantly different metabolites and 183 significantly different genes screened in the intervention group compared to the model group. Comparative analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations identified a total of 61 pathways in which differential metabolites and genes were jointly involved, with linoleic acid metabolism, glycine, serine and threonine metabolism and glutamatergic synapse in both transcriptome and metabolome being found to be significantly altered (p < 0.05). Lactobacillus rhamnosus hsryfm 1301 fermented milk was able to directly regulate lipid metabolism disorders by regulating the metabolic pathways of linoleic acid metabolism, glycerophospholipid metabolism, fatty acid biosynthesis, alpha-linolenic acid metabolism, fatty acid degradation, glycerolipid metabolism and arachidonic acid metabolism. In addition, we found that Lactobacillus rhamnosus hsryfm 1301 fermented milk indirectly regulates lipid metabolism through regulating amino acid metabolism, the nervous system, the endocrine system and other pathways. Lactobacillus rhamnosus hsryfm 1301 fermented milk could alleviate the disorders of lipid metabolism caused by high-fat diet through multi-target synergy.

ezQTL: A Web Platform for Interactive Visualization and Colocalization of QTLs and GWAS Loci.

Genome-wide association studies (GWAS) have identified thousands of genomic loci associated with complex diseases and traits, including cancer. The vast majority of common trait-associated variants identified via GWAS fall in non-coding regions of the genome, posing a challenge in elucidating the causal variants, genes, and mechanisms involved. Expression quantitative trait locus (eQTL) and other molecular QTL studies have been valuable resources in identifying candidate causal genes from GWAS loci through statistical colocalization methods. While QTL colocalization is becoming a standard analysis in post-GWAS investigation, an easy web tool for users to perform formal colocalization analyses with either user-provided or public GWAS and eQTL datasets has been lacking. Here, we present ezQTL, a web-based bioinformatic application to interactively visualize and analyze genetic association data such as GWAS loci and molecular QTLs under different linkage disequilibrium (LD) patterns (1000 Genomes Project, UK Biobank, or user-provided data). This application allows users to perform data quality control for variants matched between different datasets, LD visualization, and two-trait colocalization analyses using two state-of-the-art methodologies (eCAVIAR and HyPrColoc), including batch processing. ezQTL is a free and publicly available cross-platform web tool, which can be accessed online at https://analysistools.cancer.gov/ezqtl.

Rare germline deleterious variants increase susceptibility for lung cancer.

Although multiple common susceptibility loci for lung cancer (LC) have been identified by genome-wide association studies, they can explain only a small portion of heritability. The etiological contribution of rare deleterious variants (RDVs) to LC risk is not fully characterized and may account for part of the missing heritability. Here, we sequenced the whole exomes of 2777 participants from the Environment and Genetics in Lung cancer Etiology study, a homogenous population including 1461 LC cases and 1316 controls. In single-variant analyses, we identified a new RDV, rs77187983 [EHBP1, odds ratio (OR) = 3.13, 95% confidence interval (CI) = 1.34-7.30, P = 0.008] and replicated two previously reported RDVs, rs11571833 (BRCA2, OR = 2.18; 95% CI = 1.25-3.81, P = 0.006) and rs752672077 (MPZL2, OR = 3.70, 95% CI = 1.04-13.15, P = 0.044). In gene-based analyses, we confirmed BRCA2 (P = 0.007) and ATM (P = 0.014) associations with LC risk and identified TRIB3 (P = 0.009), involved in maintaining genome stability and DNA repair, as a new candidate susceptibility gene. Furthermore, cases were enriched with RDVs in homologous recombination repair [carrier frequency (CF) = 22.9% versus 19.5%, P = 0.017] and Fanconi anemia (CF = 12.5% versus 10.2%, P = 0.036) pathways. Our results were not significant after multiple testing corrections but were enriched in cases versus controls from large scale public biobank resources, including The Cancer Genome Atlas, FinnGen and UK Biobank. Our study identifies novel candidate genes and highlights the importance of RDVs in DNA repair-related genes for LC susceptibility. These findings improve our understanding of LC heritability and may contribute to the development of risk stratification and prevention strategies.

Gene Expression Nebulas (GEN): a comprehensive data portal integrating transcriptomic profiles across multiple species at both bulk and single-cell levels.

Transcriptomic profiling is critical to uncovering functional elements from transcriptional and post-transcriptional aspects. Here, we present Gene Expression Nebulas (GEN, https://ngdc.cncb.ac.cn/gen/), an open-access data portal integrating transcriptomic profiles under various biological contexts. GEN features a curated collection of high-quality bulk and single-cell RNA sequencing datasets by using standardized data processing pipelines and a structured curation model. Currently, GEN houses a large number of gene expression profiles from 323 datasets (157 bulk and 166 single-cell), covering 50 500 samples and 15 540 169 cells across 30 species, which are further categorized into six biological contexts. Moreover, GEN integrates a full range of transcriptomic profiles on expression, RNA editing and alternative splicing for 10 bulk datasets, providing opportunities for users to conduct integrative analysis at both transcriptional and post-transcriptional levels. In addition, GEN provides abundant gene annotations based on value-added curation of transcriptomic profiles and delivers online services for data analysis and visualization. Collectively, GEN presents a comprehensive collection of transcriptomic profiles across multiple species, thus serving as a fundamental resource for better understanding genetic regulatory architecture and functional mechanisms from tissues to cells.

Genomic and evolutionary classification of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) is a common cause of cancer mortality but its genomic landscape is poorly characterized. Here high-coverage whole-genome sequencing of 232 LCINS showed 3 subtypes defined by copy number aberrations. The dominant subtype (piano), which is rare in lung cancer in smokers, features somatic UBA1 mutations, germline AR variants and stem cell-like properties, including low mutational burden, high intratumor heterogeneity, long telomeres, frequent KRAS mutations and slow growth, as suggested by the occurrence of cancer drivers' progenitor cells many years before tumor diagnosis. The other subtypes are characterized by specific amplifications and EGFR mutations (mezzo-forte) and whole-genome doubling (forte). No strong tobacco smoking signatures were detected, even in cases with exposure to secondhand tobacco smoke. Genes within the receptor tyrosine kinase-Ras pathway had distinct impacts on survival; five genomic alterations independently doubled mortality. These findings create avenues for personalized treatment in LCINS.

Genome Warehouse: A Public Repository Housing Genome-scale Data.

The Genome Warehouse (GWH) is a public repository housing genome assembly data for a wide range of species and delivering a series of web services for genome data submission, storage, release, and sharing. As one of the core resources in the National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB; https://ngdc.cncb.ac.cn), GWH accepts both full and partial (chloroplast, mitochondrion, and plasmid) genome sequences with different assembly levels, as well as an update of existing genome assemblies. For each assembly, GWH collects detailed genome-related metadata of biological project, biological sample, and genome assembly, in addition to genome sequence and annotation. To archive high-quality genome sequences and annotations, GWH is equipped with a uniform and standardized procedure for quality control. Besides basic browse and search functionalities, all released genome sequences and annotations can be visualized with JBrowse. By May 21, 2021, GWH has received 19,124 direct submissions covering a diversity of 1108 species and has released 8772 of them. Collectively, GWH serves as an important resource for genome-scale data management and provides free and publicly accessible data to support research activities throughout the world. GWH is publicly accessible at https://ngdc.cncb.ac.cn/gwh.

Tracing Lung Cancer Risk Factors Through Mutational Signatures in Never-Smokers.

Epidemiologic studies often rely on questionnaire data, exposure measurement tools, and/or biomarkers to identify risk factors and the underlying carcinogenic processes. An emerging and promising complementary approach to investigate cancer etiology is the study of somatic "mutational signatures" that endogenous and exogenous processes imprint on the cellular genome. These signatures can be identified from a complex web of somatic mutations thanks to advances in DNA sequencing technology and analytical algorithms. This approach is at the core of the Sherlock-Lung study (2018-ongoing), a retrospective case-only study of over 2,000 lung cancers in never-smokers (LCINS), using different patterns of mutations observed within LCINS tumors to trace back possible exposures or endogenous processes. Whole genome and transcriptome sequencing, genome-wide methylation, microbiome, and other analyses are integrated with data from histological and radiological imaging, lifestyle, demographic characteristics, environmental and occupational exposures, and medical records to classify LCINS into subtypes that could reveal distinct risk factors. To date, we have received samples and data from 1,370 LCINS cases from 17 study sites worldwide and whole-genome sequencing has been completed on 1,257 samples. Here, we present the Sherlock-Lung study design and analytical strategy, also illustrating some empirical challenges and the potential for this approach in future epidemiologic studies.

IC4R-2.0: Rice Genome Reannotation Using Massive RNA-seq Data.

Genome reannotation aims for complete and accurate characterization of gene models and thus is of critical significance for in-depth exploration of gene function. Although the availability of massive RNA-seq data provides great opportunities for gene model refinement, few efforts have been made to adopt these precious data in rice genome reannotation. Here we reannotate the rice (Oryza sativa L. ssp. japonica) genome based on integration of large-scale RNA-seq data and release a new annotation system IC4R-2.0. In general, IC4R-2.0 significantly improves the completeness of gene structure, identifies a number of novel genes, and integrates a variety of functional annotations. Furthermore, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) are systematically characterized in the rice genome. Performance evaluation shows that compared to previous annotation systems, IC4R-2.0 achieves higher integrity and quality, primarily attributable to massive RNA-seq data applied in genome annotation. Consequently, we incorporate the improved annotations into the Information Commons for Rice (IC4R), a database integrating multiple omics data of rice, and accordingly update IC4R by providing more user-friendly web interfaces and implementing a series of practical online tools. Together, the updated IC4R, which is equipped with the improved annotations, bears great promise for comparative and functional genomic studies in rice and other monocotyledonous species. The IC4R-2.0 annotation system and related resources are freely accessible at http://ic4r.org/.

Impact of H2O on atmospheric CH4 measurement in near-infrared absorption spectroscopy.

A distributed-feedback (DFB) diode laser based near-infrared absorption spectrometer was used to study H2O broadening coefficients for methane (CH4) transitions at 1.653 µm, which contains well-characterized and relatively isolated transitions of appropriate line strengths for sensitive atmospheric CH4 detection. The influence of H2O broadening on R3 transitions of CH4 at 6046.9 cm-1 was experimentally investigated in detail. The results indicate that H2O broadening coefficients are approximately 1.3 times higher than the corresponding air-broadening parameters. Based on the measured H2O induced broadening coefficients, the influence of H2O on actual measurement of atmospheric CH4 in tunable diode laser absorption spectroscopy was theoretically and experimentally discussed and compared, and a good agreement was obtained. The experimental results proved that the difference between air- and H2O-broadenings cannot be neglected for high precision gas concentration measurement, especially in a highly humid environment.

The effect of Lactobacillus fermentum DALI02 in reducing the oxidative stress and inflammatory response induced by high-fat diet of rats.

A long-term high-fat diet (HFD) leads to significant oxidative stress in the body and induces inflammation. A preliminary evidence suggests a potential therapeutic utility of probiotics for this condition. To evaluate the potential effect of Lactobacillus fermentum DALI02 on the oxidative stress and inflammatory damage induced by HFD, we used a hyperlipidemic rat as a model fed with HFD. Results revealed that HFD induced a significant oxidative stress and inflammation. However, results reveal that L. fermentum DALI02, manifested a significant decrease in levels of malondialdehyde (MDA), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and resistin, while the catalase (CAT), total antioxidant capability (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and adiponectin (ADPN) levels significantly increased. And it was dose-dependent that the effect of high dose groups with high viable count was particularly notable. The results suggest that L. fermentum DALI02 could alleviate oxidative stress and inflammation as it appeared to reduce lipid peroxidation and improved the lipid metabolism in vivo.

EWAS Data Hub: a resource of DNA methylation array data and metadata.

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

Mesoscale Simulation to Study Constitutive Properties of TATB/F2314 PBX.

Material Point Method (MPM) mesoscale simulation was used to study the constitutive relation of a polymer bonded explosive (PBX) consisting of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) and a fluorine polymer binder F2314. The stress-strain variations of the PBX were calculated for different temperatures and different porosities, and the results were found to be consistent with experimental observations. The stress-strain relations at different temperatures were used to develop the constitutive equation of the PBX by using numerical data fitting. Stress-strain data for different porosities were used to establish the constitutive equation by fitting the simulation data to an improved Hashion-Shtrikman model. The equation can be used to predict the shear modulus and bulk modulus of the PBX at different densities of the sample. The constitutive equations developed for TATB/F2314 PBX by MPM mesoscale simulation are important equations for the numerical simulations of the PBX at macroscale. The method presented in this study provides an alternative approach for studying the constitutive relations of PBX.

Limonin enhances the radiosensitivity of nasopharyngeal carcinoma cells via attenuating Stat3-induced cell stemness.

The inhibitory effects of limonin have been disclosed in various tumors, however, its roles in nasopharyngeal carcinoma (NPC) progression are never been revealed. In the current work, we collected NPC cells with a higher stemness compared with bulk cells through isolating the side population (SP) cells. It was found that limonin exhibited a stronger inhibitory effect on SP cells than that in bulk cells, which was evident by a lower IC50 value. Additionally, limonin attenuated the stemness and migration ability of SP cells with the higher stemness, characterized as decreasing the spheroid formation ability, expression of stemness markers and migration ability. Moreover, the proportion of SP cells in G0 phase was remarkably higher than that in bulk cells. Notably, upon limonin treatment, the proportion of SP cells in G0 was decreased and S/G2/M increased. Furthermore, limonin enhanced the radiosensitivity of NPC cells. The mechanistic studies based on RNA-sequencing analysis revealed that limonin inhibited the gene transcription driven by Stat3 (signal transducer and activator of transcription 3) and an activator of Stat3 (Colivelin or IL-6) rescued the inhibitory effects of limonin. Therefore, these results demonstrate that limonin could reduce the stemness of NPC cells and thus the radiosensitivity through suppressing Stat3 transcriptional activity.

Proteomics study of the effect of high-fat diet on rat liver.

Excessive intake of high-energy diets is an important cause of most obesity. The intervention of rats with high-fat diet can replicate the ideal animal model for studying the occurrence of human nutritional obesity. Proteomics and bioinformatics analyses can help us to systematically and comprehensively study the effect of high-fat diet on rat liver. In the present study, 4056 proteins were identified in rat liver by using tandem mass tag. A total of 198 proteins were significantly changed, of which 103 were significantly up-regulated and ninety-five were significantly down-regulated. These significant differentially expressed proteins are primarily involved in lipid metabolism and glucose metabolism processes. The intake of a high-fat diet forces the body to maintain physiological balance by regulating these key protein spots to inhibit fatty acid synthesis, promote fatty acid oxidation and accelerate fatty acid degradation. The present study enriches our understanding of metabolic disorders induced by high-fat diets at the protein level.

Serum-plasma matched metabolomics for comprehensive characterization of benign thyroid nodule and papillary thyroid carcinoma.

Metabolomics offers a noninvasive methodology to identify metabolic markers for pathogenesis and diagnosis of diseases. This work aimed to characterize circulating metabolic signatures of benign thyroid nodule (BTN) and papillary thyroid carcinoma (PTC) via serum-plasma matched metabolomics. A cohort of 1,540 serum-plasma matched samples and 114 tissues were obtained from healthy volunteers, BTN and PTC patients enrolled from 6 independent centers. Untargeted metabolomics was determined by liquid chromatography-quadrupole time-of-flight mass spectrometric and multivariate statistical analyses. The use of serum-plasma matched samples afforded a broad-scope detection of 1,570 metabolic features. Metabolic phenotypes revealed significant pattern differences for healthy versus BTN and healthy versus PTC. Perturbed metabolic pathways related mainly to amino acid and lipid metabolism. It is worth noting that, BTN and PTC showed no significant differences but rather overlap in circulating metabolic signatures, and this observation was replicated in all study centers. For differential diagnosis of healthy versus thyroid nodules (BTN + PTC), a panel of 6 metabolic markers, namely myo-inositol, α-N-phenylacetyl-L-glutamine, proline betaine, L-glutamic acid, LysoPC(18:0) and LysoPC(18:1) provided area under the curve of 97.68% in the discovery phase and predictive accuracies of 84.78-98.18% in the 4 validation centers. Taken together, serum-plasma matched metabolomics showed significant differences in circulating metabolites for healthy versus nodules but not for BTN versus PTC. Our results highlight the true metabolic nature of thyroid nodules, and potentially decrease overtreatment that exposes patients to unnecessary risks.