CCL21 and CLDN11 Are Key Driving Factors of Lymph Node Metastasis in Gastric Cancer.

BACKGROUND: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide. Understanding the molecular mechanisms of GC metastasis is crucial for improving patient survival outcomes. METHODS: RNA sequencing and analysis were performed on tissue samples from primary and lymph node metastatic lesions of gastric cancer. Differential gene analysis and functional pathway analysis were conducted. Immune infiltrating environment and protein expression levels were evaluated using immunohistochemistry. Cell experiments were conducted to investigate the role of CCL21 in GC metastasis. RESULTS: ACTG2, CNN1, DES, MUC6, and PGC were significantly upregulated in primary tumor cells, while CCL21, MS4A1, CR2, CLDN11, and FDCSP were significantly upregulated in metastatic tumor cells. Functional pathway analysis revealed enrichment in pathways related to immune response. CLDN11 and CCL21 were found to play important roles in promoting gastric cancer metastasis. Cell experiments confirmed the role of CCL21 in promoting GC cell growth and metastasis. CCL21 is highly expressed in GC tissues and binds to CCR7, leading to upregulation of CLDN11. This results in GC-lymph node metastasis and abnormal activation of immune cells (B cells and CD4+ T cells). CONCLUSION: Inhibition of CCL21 and CLDN11 proteins may be a promising strategy for treating GC and preventing lymph node metastasis. These findings provide specific molecular markers for early lymph node metastases of GC, which can aid in developing treatment strategies and predicting patient prognosis.

Metagenomic association analysis of cognitive impairment in community-dwelling older adults.

The gut microbiota is reportedly involved in neurodegenerative disorders, and exploration of differences in the gut microbiota in different cognitive status could provide clues for early detection and intervention in cognitive impairment. Here, we used data from the Taizhou Imaging Study (N = 516), a community-based cohort, to compare the overall structure of the gut microbiota at the species level through metagenomic sequencing, and to explore associations with cognition. Interestingly, bacteria capable of producing short-chain fatty acids (SCFAs), such as Bacteroides massiliensis, Bifidobacterium pseudocatenulatum, Fusicatenibacter saccharivorans and Eggerthella lenta, that can biotransform polyphenols, were positively associated with better cognitive performance (p < 0.05). Although Diallister invisus and Streptococcus gordonii were not obviously related to cognition, the former was dominant in individuals with mild cognitive impairment (MCI), while the later was more abundant in cognitively normal (CN) than MCI groups, and positively associated with cognitive performance (p < 0.05). Functional analysis further supported a potential role of SCFAs and lactic acid in the association between the gut microbiota and cognition. The significant associations persisted after accounting for dietary patterns. Collectively, our results demonstrate an association between the gut microbiota and cognition in the general population, indicating a potential role in cognitive impairment. The findings provide clues for microbiome biomarkers of dementia, and insight for the prevention and treatment of dementia.

High-dimensional analysis reveals an immune atlas and novel neutrophil clusters in the lungs of model animals with Actinobacillus pleuropneumoniae-induced pneumonia.

Due to the increase in bacterial resistance, improving the anti-infectious immunity of the host is rapidly becoming a new strategy for the prevention and treatment of bacterial pneumonia. However, the specific lung immune responses and key immune cell subsets involved in bacterial infection are obscure. Actinobacillus pleuropneumoniae (APP) can cause porcine pleuropneumonia, a highly contagious respiratory disease that has caused severe economic losses in the swine industry. Here, using high-dimensional mass cytometry, the major immune cell repertoire in the lungs of mice with APP infection was profiled. Various phenotypically distinct neutrophil subsets and Ly-6C+ inflammatory monocytes/macrophages accumulated post-infection. Moreover, a linear differentiation trajectory from inactivated to activated to apoptotic neutrophils corresponded with the stages of uninfected, onset, and recovery of APP infection. CD14+ neutrophils, which mainly increased in number during the recovery stage of infection, were revealed to have a stronger ability to produce cytokines, especially IL-10 and IL-21, than their CD14- counterparts. Importantly, MHC-II+ neutrophils with antigen-presenting cell features were identified, and their numbers increased in the lung after APP infection. Similar results were further confirmed in the lungs of piglets infected with APP and Klebsiella pneumoniae infection by using a single-cell RNA-seq technique. Additionally, a correlation analysis between cluster composition and the infection process yielded a dynamic and temporally associated immune landscape where key immune clusters, including previously unrecognized ones, marked various stages of infection. Thus, these results reveal the characteristics of key neutrophil clusters and provide a detailed understanding of the immune response to bacterial pneumonia.

Environmental risk factors and genetic markers of Kaposi's sarcoma-associated herpesvirus infection among Uygur population in Xinjiang, China.

Kaposi sarcoma-associated herpesvirus (KSHV) is endemic in Xinjiang, China. Determinants of KSHV seropositivity among high-risk groups are not well understood. We seek to identify genetic and environmental predisposing factors for KSHV infection among Uygurs in this endemic region. A cross-sectional study was performed among the Uygur population in Xinjiang, China. KSHV-antibodies were detected using immunofluorescence assay (IFA) and human leukocyte antigen (HLA) alleles were genotyped. Univariate and multivariate logistic regression analyses were applied to explore the environmental and genetic risk factors of KSHV seropositivity. Finally, a total of 721 participants were included. The seroprevalence of KSHV was 24.1% among this population. Sweet-food preference (odds ratio [OR] 1.85, 95% confidence interval [CI] 1.03-3.34), and coronary heart disease (OR 1.91, 95%CI 1.24-2.94) were statistically correlated with KSHV infection. HLA-DQB1*06:09 were found to significantly increase the risk of KSHV infection under all 3 models (ORAllelic = 4.06; ORDominant = 3.27; and ORRecessive = 8.06). Six SNPs (SNP0260, SNP0361, SNP0797, SNP0852, SNP1159, and SNP1375) in the DQB1 and DRB1 region and haploid type GTCTAACTAATC in block 17 were statistically associated with KSHV infection. We demonstrated that genetic variations in HLA-DQB1/DRB1 and environmental risk factors were strongly associated with KSHV infection among this population.

Functional consequences of a rare missense BARD1 c.403G>A germline mutation identified in a triple-negative breast cancer patient.

We identified a rare missense germline mutation in BARD1 (c.403G>A or p.Asp135Asn) as pathogenic using integrated genomics and transcriptomics profiling of germline and tumor samples from an early-onset triple-negative breast cancer patient who later was administrated with a PARP inhibitor for 2 months. We demonstrated in cell and mouse models that, compared to the wild-type, (1) c.403G>A mutant cell lines were more sensitive to irradiation, a DNA damage agent, and a PARP inhibitor; (2) c.403G>A mutation inhibited interaction between BARD1 and RAD51 (but not BRCA1); and (3) c.403G>A mutant mice were hypersensitive to ionizing radiation. Our study shed lights on the clinical interpretation of rare germline mutations of BARD1.

The gut microbiome in subclinical atherosclerosis: a population-based multiphenotype analysis.

OBJECTIVES: An altered microbiota, which can be described quantitatively, has been identified as playing a pivotal role in host vascular physiology, and it may contribute to various diseases. The aim of this study was to better understand the role of the gut microbiota in vascular physiology in a subclinical elderly population, and to investigate how lifestyle affects the composition of host gut microbiota to further impact the pathogenesis of vascular diseases. METHODS: We performed a population-based faecal metagenomic study over 569 elderly asymptomatic subclinical individuals in rural China. An association network was built based on clinical measurements and detailed epidemiologic questionnaires, including blood chemistry, arterial stiffness, carotid ultrasonography, and metagenomic datasets. RESULTS: By analyzing the breadth, depth and impact of each node of the association network, we found carotid arterial atherosclerosis indices, including intima-media thickness (IMT), were essential in the network, and were significantly associated with living habits, socio-economic status, and diet. Using mediation analysis, we found that higher frequency of eating fresh fruits and vegetables, and more exercise significantly reduced carotid atherosclerosis in terms of IMT, peak systolic velocity and end-diastolic velocity values through the mediation of Alistepes, Oligella and Prevotella. Gut microbes explained 16.5% of the mediation effect of lifestyle on the pathogenesis of carotid atherosclerosis. After adjustment, Faecalicatena [odds ratio (OR) = 0.12 ∼0.65] was shown to be protective against the formation of carotid atherosclerosis, independently, while Libanicoccus (OR = 1.46 ∼4.20 ) was associated with increased carotid arterial IMT. KEGG/KO Kyoto Encyclopedia of Genes and Genomes/ KEGG Orthology (KEGG/KO) analyses revealed a loss of anti-inflammation function in IMT subjects. CONCLUSION: Our study revealed a Chinese population-wide phenotype-metagenomic association network and a mediation effect of gut microbiota on carotid artery atherosclerosis, hinting at potential therapeutic and preventive uses for microbiota in vascular diseases.

Negative correlation between endoglin levels and coronary atherosclerosis.

BACKGROUND: Coronary artery disease (CAD) is a common cardiovascular disease, and abnormal blood lipid metabolism is an important risk factor. Transforming growth factor-ß (TGF-ß) and its receptor (TGF-ßR) can inhibit the release of inflammatory factors through the SMAD pathway-mediated immune response, thereby suppressing the progression of CAD. Endoglin (TGF-ßRIII), a TGF-ßR family homologous receptor protein, is directly involved in the immunoregulatory process, but the exact mechanism is unclear. This study aimed to clarify the pathophysiological effects of endoglin on the development of atherosclerosis and to explore the mechanism of the signalling pathway. METHODS: We downloaded the GEO dataset to perform a functional analysis of SMAD family activity and TGF-ß receptor protein expression in the monocyte expression profiles of patients with familial hyperlipidaemia (FH). The effect of endoglin on endothelial cell proliferation, migration, and apoptosis was examined by disrupting the endoglin gene in human umbilical vein endothelial cells (HUVECs) and validated by western blotting. The related genes and pathways regulated by endoglin were obtained by analysing the sequencing data. RESULTS: Research has shown that interference with endoglin can promote the proliferation and migration and significantly inhibit the apoptosis of vascular endothelial cells. Interference with endoglin particularly encourages the expression of VEGFB in vascular endothelial cells. CONCLUSION: The endoglin gene in vascular endothelial cells regulates the PI3K-Akt, Wnt, TNF, and cellular metabolism pathways by activating the SMAD pathway. RAB26, MR1, CCL2, SLC29A4, IBTK, VEGFB, and GOLGA8B play critical roles. Endoglin interacts closely with 11 proteins such as CCL2 and SEPRINE1, which participate in the vital pathway of plaque formation. Interference with endoglin can alter the course of coronary atherosclerosis.

Lifestyle, multi-omics features, and preclinical dementia among Chinese: The Taizhou Imaging Study.

China has the largest number of patients with dementia in the world. However, dementia in the Chinese population is still poorly understood and under-researched. Given the differences in genetic, demographic, sociocultural, lifestyle, and health profiles among Chinese and other ethnic/racial groups, it is crucial to build appropriate infrastructure for long-term longitudinal studies to advance Chinese cognitive aging and dementia research. We initiated a community-based prospective cohort-the Taizhou Imaging Study (TIS)-to accelerate the understanding of dementia and cerebrovascular diseases in Chinese. This article presents the rationale, aims, study design, and organization of TIS. In addition, we described some examples of the types of studies such a resource might support. The TIS provides a new framework for facilitating Chinese dementia research, encompassing invaluable resources including detailed epidemiological, sociocultural, neuroimaging, and omics data.

The progress of gut microbiome research related to brain disorders.

There is increasing evidence showing that the dynamic changes in the gut microbiota can alter brain physiology and behavior. Cognition was originally thought to be regulated only by the central nervous system. However, it is now becoming clear that many non-nervous system factors, including the gut-resident bacteria of the gastrointestinal tract, regulate and influence cognitive dysfunction as well as the process of neurodegeneration and cerebrovascular diseases. Extrinsic and intrinsic factors including dietary habits can regulate the composition of the microbiota. Microbes release metabolites and microbiota-derived molecules to further trigger host-derived cytokines and inflammation in the central nervous system, which contribute greatly to the pathogenesis of host brain disorders such as pain, depression, anxiety, autism, Alzheimer's diseases, Parkinson's disease, and stroke. Change of blood-brain barrier permeability, brain vascular physiology, and brain structure are among the most critical causes of the development of downstream neurological dysfunction. In this review, we will discuss the following parts: Overview of technical approaches used in gut microbiome studiesMicrobiota and immunityGut microbiota and metabolitesMicrobiota-induced blood-brain barrier dysfunctionNeuropsychiatric diseases ■ Stress and depression■ Pain and migraine■ Autism spectrum disordersNeurodegenerative diseases ■ Parkinson's disease■ Alzheimer's disease■ Amyotrophic lateral sclerosis■ Multiple sclerosisCerebrovascular disease ■ Atherosclerosis■ Stroke■ Arteriovenous malformationConclusions and perspectives.

Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis.

BACKGROUND: Surgical resection is the major way to cure pancreatic ductal adenocarcinoma (PDAC). However, this operation is complex, and the peri-operative risk is high, making patients more likely to be admitted to the intensive care unit (ICU). Therefore, establishing a risk model that predicts admission to ICU is meaningful in preventing patients from post-operation deterioration and potentially reducing socio-economic burden. METHODS: We retrospectively collected 120 clinical features from 1242 PDAC patients, including demographic data, pre-operative and intra-operative blood tests, in-hospital duration, and ICU status. Machine learning pipelines, including Supporting Vector Machine (SVM), Logistic Regression, and Lasso Regression, were employed to choose an optimal model in predicting ICU admission. Ordinary least-squares regression (OLS) and Lasso Regression were adopted in the correlation analysis of post-operative bleeding, total in-hospital duration, and discharge costs. RESULTS: SVM model achieved higher performance than the other two models, resulted in an AU-ROC of 0.80. The features, such as age, duration of operation, monocyte count, and intra-operative partial arterial pressure of oxygen (PaO2), are risk factors in the ICU admission. The protective factors include RBC count, analgesic pump dexmedetomidine (DEX), and intra-operative maintenance of DEX. Basophil percentage, duration of the operation, and total infusion volume were risk variables for staying in ICU. The bilirubin, CA125, and pre-operative albumin were associated with the post-operative bleeding volume. The operation duration was the most important factor for discharge costs, while pre-lymphocyte percentage and the absolute count are responsible for less cost. CONCLUSIONS: We observed that several new indicators such as DEX, monocyte count, basophil percentage, and intra-operative PaO2 showed a good predictive effect on the possibility of admission to ICU and duration of stay in ICU. This work provided an essential reference for indication in advance to PDAC operation.

Changes in plasma bile acids are associated with gallbladder stones and polyps.

BACKGROUND: The development of gallbladder disease (GBD) is related to bile acid (BA) metabolism, and the rate of BA circulation increases the risk of biliary cancer. However, it is unclear whether patterns of circulating bile acids (BAs) change in patients with benign GBDs such as gallbladder stones and polyps. Herein, we compared and characterised plasma BA profiles in patients with cholecystolithiasis and non-neoplastic polyps with healthy controls, and explored relationships between plasma BA profiles, demographics, and laboratory test indices. METHODS: A total of 330 subjects (13 healthy controls, 292 cholecystolithiasis and 25 non-neoplastic polyps) were recruited and plasma BA profiles including 14 metabolites from patients with pathologically confirmed cholecystolithiasis and non-neoplastic polyps were compared with controls. BAs were quantitated by liquid chromatography and mass spectrometry, and statistical and regression analyses of demographics and laboratory test indices were performed. RESULTS: Females displayed a higher burden of GBD than males (63.36% cholecystolithiasis, 60% non-neoplastic polyps). Cholecystolithiasis and non-neoplastic polyps were associated with increased plasma total secondary BAs, while levels of primary BAs were lower than in healthy controls. Plasma ursodeoxycholic acid (UDCA), tauroursodeoxycholic acid (TUDCA), glycyurdeoxycholic acid (GUDCA), taurochenodeoxycholic acid (TCDCA) and glycochenodeoxycholic acid (GCDCA) were decreased significantly in GBDs, and ursodeoxycholic acid (UDCA) was negatively correlated with white blood cell count and neutrophil percentage. CONCLUSIONS: Secondary BA levels were higher in patients with cholecystolithiasis and non-neoplastic polyps. White blood cell count and percentage of neutrophil in peripheral blood were negatively correlated with UDCA, indicating an anti-inflammation effect of UDCA.

Comparison and development of machine learning tools in the prediction of chronic kidney disease progression.

BACKGROUND: Urinary protein quantification is critical for assessing the severity of chronic kidney disease (CKD). However, the current procedure for determining the severity of CKD is completed through evaluating 24-h urinary protein, which is inconvenient during follow-up. OBJECTIVE: To quickly predict the severity of CKD using more easily available demographic and blood biochemical features during follow-up, we developed and compared several predictive models using statistical, machine learning and neural network approaches. METHODS: The clinical and blood biochemical results from 551 patients with proteinuria were collected. Thirteen blood-derived tests and 5 demographic features were used as non-urinary clinical variables to predict the 24-h urinary protein outcome response. Nine predictive models were established and compared, including logistic regression, Elastic Net, lasso regression, ridge regression, support vector machine, random forest, XGBoost, neural network and k-nearest neighbor. The AU-ROC, sensitivity (recall), specificity, accuracy, log-loss and precision of each of the models were evaluated. The effect sizes of each variable were analysed and ranked. RESULTS: The linear models including Elastic Net, lasso regression, ridge regression and logistic regression showed the highest overall predictive power, with an average AUC and a precision above 0.87 and 0.8, respectively. Logistic regression ranked first, reaching an AUC of 0.873, with a sensitivity and specificity of 0.83 and 0.82, respectively. The model with the highest sensitivity was Elastic Net (0.85), while XGBoost showed the highest specificity (0.83). In the effect size analyses, we identified that ALB, Scr, TG, LDL and EGFR had important impacts on the predictability of the models, while other predictors such as CRP, HDL and SNA were less important. CONCLUSIONS: Blood-derived tests could be applied as non-urinary predictors during outpatient follow-up. Features in routine blood tests, including ALB, Scr, TG, LDL and EGFR levels, showed predictive ability for CKD severity. The developed online tool can facilitate the prediction of proteinuria progress during follow-up in clinical practice.

Comparative analysis of bone turnover markers in bone marrow and peripheral blood: implications for osteoporosis.

INTRODUCTION: This study examines bone turnover marker (BTM) variations between bone marrow and peripheral blood in osteoporotic and non-osteoporotic patients. BTMs offer insights into bone remodeling, crucial for understanding osteoporosis. METHODS: A total of 133 patients were categorized into osteoporotic and non-osteoporotic cohorts. BTMs-C-telopeptide cross-linked type 1 collagen (ß-CTX), serum osteocalcin (OC), Procollagen type I N-propeptide (P1NP), 25(OH)D-were measured in bone marrow and peripheral blood. Lumbar spine bone mineral density (BMD) was assessed. RESULTS: Osteoporotic patients exhibited elevated ß-CTX and OC levels in peripheral blood, indicating heightened bone resorption and turnover. ß-CTX levels in osteoporotic bone marrow were significantly higher. Negative correlations were found between peripheral blood ß-CTX and OC levels and lumbar spine BMD, suggesting their potential as osteoporosis severity indicators. No such correlations were observed with bone marrow markers. When analyzing postmenopausal women separately, we obtained consistent results. CONCLUSIONS: Elevated ß-CTX and OC levels in osteoporotic peripheral blood highlight their diagnostic significance. Negative ß-CTX and OC-BMD correlations underscore their potential for assessing osteoporosis severity. Discrepancies between peripheral blood and bone marrow markers emphasize the need for further exploration. This research advances our understanding of BTM clinical applications in osteoporosis diagnosis and treatment.

Optimizing Levothyroxine Replacement: A Precision Dosage Model for Post-Thyroidectomy Patients.

Background: Thyroidectomy is commonly performed for benign or malignant thyroid tumors, often resulting in hypothyroidism. Levothyroxine (LT4) supplementation is crucial to maintain hormone levels within the normal range and suppress TSH for cancer control. However, determining the optimal dosage remains challenging, leading to uncertain outcomes and potential side effects. Methods: We analyzed clinical examination data from 510 total thyroidectomy patients, including demographic information, blood tests, and thyroid function. Using R, we applied data preprocessing techniques and identified 274 samples with 98 variables. Principal Component Analysis, correlation analysis, and regression analysis were conducted to identify factors associated with optimal LT4 dosage. Results: The analysis revealed that only eight variables significantly influenced the final satisfactory dosage of LT4 in tablets: Benign0/Malignant1 (benign or malignant), BQB (electrophoretic albumin ratio), TP (total protein), FDP (fibrin degradation products), TRAB_1 (thyroid-stimulating hormone receptor antibody), PT (prothrombin time), MONO# (monocyte count), and HCV0C (hepatitis C antibody). The resulting predictive model was: . Conclusion: Parameters such as benign/malignant status, TRAB_1, and BQB ratio during medication can serve as observational indicators for postoperative LT4 dosage. The calculated linear model can predict the LT4 dosage for patients after thyroidectomy, leading to improved treatment effectiveness and conserving medical resources.

Single-cell analysis defines LGALS1 + fibroblasts that promote proliferation and migration of intrahepatic cholangiocarcinoma.

The incidence rate of intrahepatic cholangiocarcinoma (ICC), which has a poor prognosis, is rapidly increasing. To investigate the intratumor heterogeneity of ICC, we analyzed single-cell RNA sequencing data from the primary tumor and adjacent normal tissues of 14 treatment-naïve patients. We identified ten major cell types, along with 45 subclusters of cells. Notably, we identified a fibroblast cluster, Fibroblast_LUM+, which was preferably enriched in tumor tissues and actively interacted with cholangiocytes. LGALS1 was verified as a marker gene of Fibroblast_LUM+, contributing to the malignant phenotype of ICC. The higher amount of LGALS1 + fibroblasts were associated with poorer overall survival in ICC patients. LGALS1 + fibroblasts activated the proliferation and migration of tumor cells by upregulating the expression levels of CCR2, ADAM15, and ß-integrin. Silencing LGALS1 in cancer-associated fibroblasts (CAFs) suppressed CAF-augmented tumor cell migration and invasion in vitro as well as tumor formation in vivo, suggesting that blockade of LGALS1 serves as a potential therapeutic approach for ICC. Taken together, our single-cell analysis provides insight into the interaction between malignant cells and specific subtypes of fibroblasts. Our work will further the understanding of the intratumor heterogeneity of ICC and provide novel strategies for the treatment of ICC by targeting fibroblasts in the tumor microenvironment.

The critical role of platelet in cancer progression and metastasis.

Platelets play a crucial role in cancer blood metastasis. Various cancer-related factors such as Toll-like receptors (TLRs), adenosine diphosphate (ADP) or extracellular matrix (ECM) can activate these small particles that function in hemostasis and thrombosis. Moreover, platelets induce Epithelial Mesenchymal Transition (EMT) to promote cancer progression and invasiveness. The activated platelets protect circulating tumor cells from immune surveillance and anoikis. They also mediate tumor cell arrest, extravasation and angiogenesis in distant organs through direct or indirect modulation, creating a metastatic microenvironment. This review summarizes the recent advances and progress of mechanisms in platelet activation and its interaction with cancer cells in metastasis.

The effects of altered DNA damage repair genes on mutational processes and immune cell infiltration in esophageal squamous cell carcinoma.

BACKGROUND: Defects in DNA damage repair (DDR) pathways lead to genomic instability and oncogenesis. DDR deficiency is prevalent in esophageal squamous cell carcinoma (ESCC), but the effects of DDR alterations on mutational processes and tumor immune microenvironment in ECSS remain unclear. METHODS: Whole-exome and transcriptome sequencing data of 45 ESCC samples from Taizhou, China, were used to identify genomic variations, gene expression modulation in DDR pathways, and the abundance of tumor-infiltrating immune cells. Ninety-six ESCC cases from The Cancer Genome Atlas (TCGA) project were used for validation. RESULTS: A total of 57.8% (26/45) of the cases in the Taizhou data and 70.8% (68/96) of the cases in the TCGA data carried at least one functional impact DDR mutation. Mutations in the DDR pathways were associated with a high tumor mutation burden. Several DDR deficiency-related mutational signatures were discovered and were associated with immune cell infiltration, including T cells, monocytes, dendritic cells, and mast cells. The expression levels of two DDR genes, HFM1 and NEIL1, were downregulated in ESCC tumor tissues and had an independent effect on the infiltration of mast cells. In the Taizhou data, increased expression of HFM1 was associated with a poor prognosis, and the increased expression of NEIL1 was associated with a good outcome, but no reproducible correlation was observed in the TCGA data. CONCLUSION: This research demonstrated that DDR alterations could impact mutational processes and immune cell infiltration in ESCC. The suppression of HFM1 and NEIL1 could play a crucial role in ESCC progression and may also serve as prognostic markers.

Identification of RAC1 in promoting brain metastasis of lung adenocarcinoma using single-cell transcriptome sequencing.

This study aims to give a new perspective to the biomarkers in the lung adenocarcinoma (LUAD) brain metastasis, pathways involved and potential therapeutics. We performed a comprehensive single-cell level transcriptomic analysis on one LUAD patient with circulating tumor cells (CTCs), primary tumor tissue and metastatic tumor tissue using scRNA-seq approach to identify metastasis related biomarkers. Further scRNA-seq were performed on 7 patients to validate the cancer metastatic hallmark. with single cells collected from either metastatic or primary LUAD tissues. Pathological and functional studies were also performed to evidence the critical role of RAC1 in the LUAD metastasis. Hallmark gene was verified based on immunohistochemistry staining, cytological experiment, survival information from The Cancer Genome Atlas (TCGA), and staining results from Human Protein Atlas (HPA) databases. PCA analysis revealed that CTCs were in the intermediate place between the metastatic group and primary group. In the unsupervised clustering analysis CTCs were closer to one of the metastatic tumor cells, implying heterogeneity of the metastatic tumor and origin of the CTCs were from metastatic site. Transitional phase related gene analysis identified RAC1 was enriched in metastatic tumor tissue (MTT) preferred gene set functioning as regulated cell death and apoptosis as well as promoted macromolecule organization. Compared with normal tissue, expression levels of RAC1 increased significantly in LUAD tissue based on HPA database. High expression of RAC1 predicts worse prognosis and higher-risk. EMT analysis identified the propensity of mesenchymal state in primary cells while epithelial signals were higher in the metastatic site. Functional clustering and pathway analyses suggested genes in RAC1 highly expressed cells played critical roles in adhesion, ECM and VEGF signaling pathways. Inhibition of RAC1 attenuates the proliferation, invasiveness and migration ability of lung cancer cells. Besides, through MRI T2WI results, we proved that RAC1 can promote brain metastasis in the RAC1-overexpressed H1975 cell burden nude mouse model. RAC1 and its mechanisms might promote drug design against LUAD brain metastasis.

Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling.

Certified RNA reference materials are indispensable for assessing the reliability of RNA sequencing to detect intrinsically small biological differences in clinical settings, such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multi-omics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two samples, providing cross-platform and cross-laboratory 'ground truth'. Investigation of the intrinsically subtle biological differences among the Quartet samples enables sensitive assessment of cross-batch integration of transcriptomic measurements at the ratio level. The Quartet RNA reference materials, combined with the ratio-based reference datasets, can serve as unique resources for assessing and improving the quality of transcriptomic data in clinical and biological settings.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials.

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.