ACAT1-mediated METTL3 acetylation inhibits cell migration and invasion in triple negative breast cancer.

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive disease with poor prognosis. Acetylation modifications affect a great number of biological processes of malignant tumors. The current study aims at revealing the role of acetylation-related mechanism in TNBC progression. Methyltransferase like-3 (METTL3) was found to be downregulated in TNBC cells via quantitative polymerase chain reaction (qPCR) and western blot analyses. Co-Immunoprecipitation (Co-IP) and GST pulldown assays revealed the interaction between acetyl-CoA acetyltransferase 1 (ACAT1) and METTL3. Through further immunoprecipitation (IP) assay, we determined that ACAT1 stabilizes METTL3 protein via inhibiting the degradation of ubiquitin-proteasome. Functionally, ACAT1 inhibits TNBC cell migration and invasion. Moreover, nuclear receptor subfamily 2 group F member 6 (NR2F6) regulates ACAT1 expression at transcriptional level. Finally, we demonstrated that NR2F6/ACAT/METTL3 axis suppresses the migration and invasion of TNBC cells via METTL3. In conclusion, NR2F6 transcriptionally activates ACAT1 and promotes the suppressive effects of ACAT1-mediated METTL3 acetylation on TNBC cell migration and invasion.

Role of GSDM family members in airway epithelial cells of lung diseases: a systematic and comprehensive transcriptomic analysis.

Gasdermin (GSDM) family, the key executioners of pyroptosis, play crucial roles in anti-pathogen and anti-tumor immunities, although little is known about the expression of GSDM in lung diseases at single-cell resolution, especially in lung epithelial cells. We comprehensively investigated the transcriptomic profiles of GSDM members in various lung tissues from healthy subjects or patients with different lung diseases at single cell level, e.g., chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), lung adenocarcinoma (LUAD), or systemic sclerosis (SSC). The expression of GSDM members varied among pulmonary cell types (immune cells, structural cells, and especially epithelial cells) and even across lung diseases. Regarding disease-associated specificities, we found that GSDMC or GSDMD altered significantly in ciliated epithelia of COPD or LUAD, GSDMD in mucous, club, and basal cells of LUAD and GSDMC in mucous epithelia of para-tumor tissue, as compared with the corresponding epithelia of other diseases. The phenomic specificity of GSDM in lung cancer subtypes was noticed by comparing with 15 non-pulmonary cancers and para-cancer samples. GSDM family gene expression changes were also observed in different lung epithelial cell lines (e.g., HBE, A549, H1299, SPC-1, or H460) in responses to external challenges, including lipopolysaccharide (LPS), lysophosphatidylcholine (lysoPC), cigarette smoking extract (CSE), cholesterol, and AR2 inhibitor at various doses or durations. GSDMA is rarely expressed in those cell lines, while GSDMB and GSDMC are significantly upregulated in human lung epithelia. Our data indicated that the heterogeneity of GSDM member expression exists at different cells, pathologic conditions, challenges, probably dependent upon cell biological phenomes, functions, and behaviors, upon cellular responses to external changes, and the nature and severity of lung disease. Thus, the deep exploration of GSDM phenomes may provide new insights into understanding the single-cell roles in the tissue, regulatory roles of the GSDM family in the pathogenesis, and potential values of biomarker identification and development.

The methodology study of three-dimensional (3D) genome research.

Multiple dimensions of genome organization play critical roles in the regulation of non-coding regions in gene expression in cell/organ development and pathogenesis. Precise measurements of multi-dimensional genome structure ensure data quality and fully depend upon the study design. We here overview the number of methodologies used in the detection and analysis of genome structure and compare advantages and disadvantages of 3C-based, PCR amplification-based, and sequencing-based measurements. We discuss about the optimization of various techniques according to targeted genomic sites, the required resolution, and possible technique biases. Comparison of different analysis tools and computational system-based automatic analysis is evaluated to define more opportunities and challenges of data analysis in 3D genome research. The genome structure is visualized in levels of single genome organized by enhancer-promoter interactions, TAD, and intra-chromosomal and inter-chromosomal interactions between TADs. Thus, methodologies of genome organization multi-dimensions are not only critical in studies on 3D genome-regulated transcriptions, but also in the discovery of disease-specific biomarkers and targets for diagnosis and therapies.

Drug resistance in ALK-positiveNon-small cell lungcancer patients.

Patients are diagnosed as anaplastic lymphoma kinase (ALK) positive, i.e. exhibiting the ALK rearrangement, and comprise 3-7% of non-small-cell lung cancer (NSCLC) cases. Three generations of ALK inhibitors have been developed and used in targeted therapy, although there are still improving spaces of drug resistance at the initiation of each treatment. The current review discusses the pathophysiology of ALK-positive NSCLC and the role of three generations of ALK target inhibitors including crizotinib, ceritinib, alectinib and lorlatinib, as well as the mechanisms of the secondary resistance. We mainly focused on the point mutations that are the most important resistance-producing mechanism and most common form caused by each inhibitor. In addition, we examine the three-dimensional structure of ALK to understand the functional impact of these mutations and analyse the underlying molecular mechanisms of the resistance to each generation of ALK inhibitor to benefit the selection decision of the most rational therapy and improve therapeutic effects to the disease.

Detection of single cell heterogeneity in cancer.

Single cell heterogeneity has already been highlighted in cancer classification, diagnosis, and treatment. Recent advanced technologies have gained more ability to reveal the heterogeneity on single cell level. In this review, we listed various detection targets applied in single cell study, including tumor tissue cells, circulating tumor cells (CTCs), disseminated tumor cells (DTCs), circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), and cancer stem cells (CSCs). We further discussed and compared detection methods using these detection targets in different fields to reveal single cell heterogeneity in cancer. We focused not only on the methods that have already been established and validated, but also on newly developed methods. In morphology and phenotype, the methods mainly included cell imaging and immune-staining. In genomics and proteomics, the main methods were single cell sequencing and single cell western blotting. Collectively, from using these methods, we can have a better understanding of the single cell variation, as well as what kind of variation it is and how the variation works. Our observations imply that study on single cell heterogeneity in cancer is an important step to precision medicine. The development of technologies in detection of single cell heterogeneity will be sure to improve the diagnosis and treatment in cancer.

Roles of tumor heterogeneity in the development of drug resistance: A call for precision therapy.

The drug resistance limits the optimal efficacy of drugs during target therapies for lung cancer and requires the development of precision medicine to identify and develop new highly selective drugs and more precise tailoring of medicine to the target population. Lung cancer heterogeneity as a potential cause of drug resistance to targeted therapy may foster tumor evolution and adaptation and fade personalized-medicine strategies. The present review elucidates the influence of tumor heterogeneity on drug efficacy and resistance, and discusses potential strategies to combat heterogeneity for cancer treatment. There is an urgent need to discover and develop disease- and biology-specific biomarkers for monitoring the existence and occurrence of lung cancer heterogeneity, testing targeted drugs in clinical trials, and implementing precision medicine for patients. Better understanding of lung cancer heterogeneity will strengthen therapeutic strategies and apply precision medicine to cure the disease.

Detection and Application of RNA Editing in Cancer.

RNA editing is the process which happened in the post-transcriptional stage that the genetic information contained in an RNA molecule will be changed. RNA editing has been found to be related with many cancers, so through identifying RNA editing sites, we can find useful information on the process of carcinogenesis. In this review, we will discuss the main types of RNA editing and their role in cancers, as well as the current detection methods of RNA editing and the challenges we should overcome.

Approach, Application, and Bioethics of mtDNA Sequencing in Cancer.

Mitochondrial DNA (mtDNA) is more vulnerable to mutations and associated with many solid tumors. Through mtDNA sequencing, we can find useful information on the mutations implicated in diseases and can better define the impact of mitochondrial dysfunction on the process of carcinogenesis. In current article, we will discuss the current approaches of mtDNA sequencing and the challenges we should overcome, their applications in various cancers, and the potential bioethics problems we should face in the application of mtDNA sequencing in clinical diagnosis and treatment.

Comparison of Chromosome 4 gene expression profile between lung telocytes and other local cell types.

Telocytes (TCs) are new cellular entities of mesenchymal origin described almost ubiquitously in human and mammalian organs (www.telocytes.com). Different subtypes of TCs were described, all forming networks in the interstitial space by homo- and heterocellular junctions. Previous studies analysed the gene expression profiles of chromosomes 1, 2, 3, 17 and 18 of murine pulmonary TCs. In this study, we analysed by bioinformatics tools the gene expression profiles of chromosome 4 for murine pulmonary TCs and compared it with mesenchymal stem cells (MSCs), fibroblasts (Fbs), alveolar type II cells (ATII), airway basal cells, proximal airway cells, CD8(+) T cells from bronchial lymph nodes (T-BL) and CD8(+) T cells from lungs (T-L). Key functional genes were identified with the aid of the reference library of the National Center for Biotechnology Information Gene Expression Omnibus database. Seventeen genes were up-regulated and 56 genes were down-regulated in chromosome 4 of TCs compared with other cells. Four genes (Akap2, Gpr153, Sdc3 and Tbc1d2) were up-regulated between one and fourfold and one gene, Svep1, was overexpressed over fourfold. The main functional networks were identified and analysed, pointing out to a TCs involvement in cellular signalling, regulation of tissue inflammation and cell expansion and movement.

A new method for classifying different phenotypes of kidney transplantation.

For end-stage renal diseases, kidney transplantation is the most efficient treatment. However, the unexpected rejection caused by inflammation usually leads to allograft failure. Thus, a systems-level characterization of inflammation factors can provide potentially diagnostic biomarkers for predicting renal allograft rejection. Serum of kidney transplant patients with different immune status were collected and classified as transplant patients with stable renal function (ST), impaired renal function with negative biopsy pathology (UNST), acute rejection (AR), and chronic rejection (CR). The expression profiles of 40 inflammatory proteins were measured by quantitative protein microarrays and reduced to a lower dimensional space by the partial least squares (PLS) model. The determined principal components (PCs) were then trained by the support vector machines (SVMs) algorithm for classifying different phenotypes of kidney transplantation. There were 30, 16, and 13 inflammation proteins that showed statistically significant differences between CR and ST, CR and AR, and CR and UNST patients. Further analysis revealed a protein-protein interaction (PPI) network among 33 inflammatory proteins and proposed a potential role of intracellular adhesion molecule-1 (ICAM-1) in CR. Based on the network analysis and protein expression information, two PCs were determined as the major contributors and trained by the PLS-SVMs method, with a promising accuracy of 77.5 % for classification of chronic rejection after kidney transplantation. For convenience, we also developed software packages of GPS-CKT (Classification phenotype of Kidney Transplantation Predictor) for classifying phenotypes. By confirming a strong correlation between inflammation and kidney transplantation, our results suggested that the network biomarker but not single factors can potentially classify different phenotypes in kidney transplantation.

Adrenaline stimulates the proliferation and migration of mesenchymal stem cells towards the LPS-induced lung injury.

Bone marrow-derived mesenchymal stem cells (BMSCs) could modulate inflammation in experimental lung injury. On the other hand, adrenergic receptor agonists could increase DNA synthesis of stem cells. Therefore, we investigated the therapeutic role of adrenaline-stimulated BMSCs on lipopolysaccharide (LPS)-induced lung injury. BMSCs were cultured with adrenergic receptor agonists or antagonists. Suspensions of lung cells or sliced lung tissue from animals with or without LPS-induced injury were co-cultured with BMSCs. LPS-stimulated alveolar macrophages were co-cultured with BMSCs (with adrenaline stimulation or not) in Transwell for 6 hrs. A preliminary animal experiment was conducted to validate the findings in ex vivo study. We found that adrenaline at 10 µM enhanced proliferation of BMSCs through both α- and ß-adrenergic receptors. Adrenaline promoted the migration of BMSCs towards LPS-injured lung cells or lung tissue. Adrenaline-stimulated BMSCs decreased the inflammation of LPS-stimulated macrophages, probably through the expression and secretion of several paracrine factors. Adrenaline reduced the extent of injury in LPS-injured rats. Our data indicate that adrenaline-stimulated BMSCs might contribute to the prevention from acute lung injury through the activation of adrenergic receptors, promotion of proliferation and migration towards injured lung, and modulation of inflammation.

Differences in the expression of chromosome 1 genes between lung telocytes and other cells: mesenchymal stem cells, fibroblasts, alveolar type II cells, airway epithelial cells and lymphocytes.

Telocytes (TCs) are a unique type of interstitial cells with specific, extremely long prolongations named telopodes (Tps). Our previous study showed that TCs are distinct from fibroblasts (Fbs) and mesenchymal stem cells (MSCs) as concerns gene expression and proteomics. The present study explores patterns of mouse TC-specific gene profiles on chromosome 1. We investigated the network of main genes and the potential functional correlations. We compared gene expression profiles of mouse pulmonary TCs, MSCs, Fbs, alveolar type II cells (ATII), airway basal cells (ABCs), proximal airway cells (PACs), CD8(+) T cells from bronchial lymph nodes (T-BL) and CD8(+) T cells from lungs (T-LL). The functional and feature networks were identified and compared by bioinformatics tools. Our data showed that on TC chromosome 1, there are about 25% up-regulated and 70% down-regulated genes (more than onefold) as compared with the other cells respectively. Capn2, Fhl2 and Qsox1 were over-expressed in TCs compared to the other cells, indicating that biological functions of TCs are mainly associated with morphogenesis and local tissue homoeostasis. TCs seem to have important roles in the prevention of tissue inflammation and fibrogenesis development in lung inflammatory diseases and as modulators of immune cell response. In conclusion, TCs are distinct from the other cell types.

Variations of chromosomes 2 and 3 gene expression profiles among pulmonary telocytes, pneumocytes, airway cells, mesenchymal stem cells and lymphocytes.

Telocytes (TCs) were identified as a distinct cellular type of the interstitial tissue and defined as cells with extremely long telopodes (Tps). Our previous data demonstrated patterns of mouse TC-specific gene profiles on chromosome 1. The present study focuses on the identification of characters and patterns of TC-specific or TC-dominated gene expression profiles in chromosome 2 and 3, the network of principle genes and potential functional association. We compared gene expression profiles of pulmonary TCs, mesenchymal stem cells, fibroblasts, alveolar type II cells, airway basal cells, proximal airway cells, CD8(+) T cells from bronchial lymph nodes (T-BL), and CD8(+) T cells from lungs (T-LL). We identified that 26 or 80 genes of TCs in chromosome 2 and 13 or 59 genes of TCs up- or down-regulated in chromosome 3, as compared with other cells respectively. Obvious overexpression of Myl9 in chromosome 2 of TCs different from other cells, indicates that biological functions of TCs are mainly associated with tissue/organ injury and ageing, while down-expression of Pltp implies that TCs may be associated with inhibition or reduction of inflammation in the lung. Dominant overexpression of Sh3glb1, Tm4sf1 or Csf1 in chromosome 3 of TCs is mainly associated with tumour promotion in lung cancer, while most down-expression of Pde5 may be involved in the development of pulmonary fibrosis and other acute and chronic interstitial lung disease.

Network analysis reveals roles of inflammatory factors in different phenotypes of kidney transplant patients.

BACKGROUND: Systems-level characterization of inflammation in kidney transplantation remains incomplete. By stratifying kidney transplant patients based on phenotypes, the present study sought to identify the role of inflammatory proteins in disease progress and assess potential biomarkers for allograft monitoring. METHODS: Kidney transplant patients with different allograft status were enrolled in the study: stable renal function (ST), impaired renal function (UNST), acute rejection (AR), and chronic rejection (CR). We stratified the patients into 3 phenotype levels according to their symptoms and pathogenesis. Serum protein concentrations were measured by a quantitative protein array. All differentially expressed proteins were analyzed by protein-protein interaction networks (PPINs) to highlight protein interactions in patients with the above dysfunction levels. We identified level-related proteins and evaluated the classification efficiency of these biomarkers based on leave-one-out validation. The candidate proteins related to phenotype transforming were annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. RESULTS: Based on the hypothesis that common proteins and their up- or down-regulation promote disease progress, we obtained 12 common proteins and 11 level-specific proteins from the phenotype-related PPINs. The common proteins were annotated for KEGG enrichment: (1) cytokine-cytokine receptor interaction; (2) hematopoietic cell lineage; (3) Jak-STAT signaling pathway; (4) allograft rejection; and (5) T cell receptor signaling pathway. The level-specific proteins could be potential biomarkers with diagnostic value. The classification potency of the 11 level-specific proteins (IL-1R-1, IL-16, TIMP-1, G-CSF, MIG, IL-11, BLC, TNF-ß, Eotaxin-2, I-309 and IL-6 sR) was better than the performance using all 40 proteins. CONCLUSION: The study demonstrated the potential value of PPINs-based approach to understanding inflammation-derived mechanisms and developing diagnostic biomarkers. Independent evaluations are required to further estimate the clinical relevance of the new diagnostic biomarkers.

Genetic comparison of mouse lung telocytes with mesenchymal stem cells and fibroblasts.

Telocytes (TCs) are interstitial cells with telopodes - very long prolongations that establish intercellular contacts with various types of cells. Telocytes have been found in many organs and various species and have been characterized ultrastructurally, immunophenotypically and electrophysiologically (www.telocytes.com). Telocytes are distributed through organ stroma forming a three-dimensional network in close contacts with blood vessels, nerve bundles and cells of the local immune system. Moreover, it has been shown that TCs express a broad range of microRNAs, such as pro-angiogenic and stromal-specific miRs. In this study, the gene expression profile of murine lung TCs is compared with other differentiated interstitial cells (fibroblasts) and with stromal stem/progenitor cells. More than 2000 and 4000 genes were found up- or down-regulated, respectively, in TCs as compared with either MSCs or fibroblasts. Several components or regulators of the vascular basement membrane are highly expressed in TCs, such as Nidogen, Collagen type IV and Tissue Inhibitor of Metalloproteinase 3 (TIMP3). Given that TCs locate in close vicinity of small vessels and capillaries, the data suggest the implication of TCs in vascular branching. Telocytes express also matrix metalloproteases Mmp3 and Mmp10, and thus could regulate extracellular matrix during vascular branching and de novo vessel formation. In conclusion, our data show that TCs are not fibroblasts, as the ultrastructure, immunocytochemistry and microRNA assay previously indicated. Gene expression profile demonstrates that TCs are functionally distinct interstitial cells with specific roles in cell signalling, tissue remodelling and angiogenesis.

Risk factors of recurrent thyroid nodules after radiofrequency ablation.

Objective: To investigate the risk factors of thyroid nodule recurrence after radiofrequency ablation (RFA). METHODS The medical record information of 120 patients with thyroid nodules admitted to our hospital from June 2019 to April 2022 was retrospectively analysed. All participants received RFA treatment. According to the results of the postoperative thyroid ultrasound examination (USG), the patients were divided into the recurrence group (R, N=16) and the non-recurrence group (NR, N=104). Binary logistic regression analysis was performed to identify the independent risk factors of thyroid nodule recurrence after RFA. The receiver operating characteristic (ROC) curve was used to analyse the value of the forecast of each independent factor and combined model for thyroid nodule recurrence after RFA. Results: During the follow-up period, 16 patients recurred, and the recurrence rate was 13.33%. Univariate regression analysis showed that whether the nodules are solitary (WNS), nodule diameter (ND), the degree of risk of nodular location (DRN), recurrent laryngeal nerve (RLN) injury were associated with thyroid nodule recurrence after RFA (P<0.05). Binary logistic regression analysis showed that WNS, ND, DRN and RLN injury were independent risk factors for the recurrence of thyroid nodules after RFA (P<0.05). ROC analysis of independent factors and combined model showed that solitary nodules, nodule diameter and nodule location risk degree had diagnostic value, while RLN injury had no predictive value. The combined model is more predictive than the independent factors. Conclusions: The risk factors of recurrent thyroid nodules after radiofrequency ablation are related to WNS, ND, DRN and so on, which should be paid attention to and preventive measures should be taken.

Distinct immunoreactions after a primary tumor microwave ablation using different heating parameters in a VX2 tumor model.

BACKGROUND: Thermal ablation of solid tumors in situ can activate the immune system and produce a specific immune response against the tumor. Microwave ablation (MWA) with different parameters can ablate tumors with similar sizes and cause different local inflammatory effects. Our aim was to determine the immunological effects induced by different energy modes of MWA for a primary tumor. METHODS: Seventy rabbits with VX2 tumors that were implanted subcutaneously underneath the right second nipple were treated with high-power MWA (40 W for 1 min), low-power MWA (20 W for 2 min), or surgical resection or were left without treatment (control). Survival time was evaluated by log-rank test. On day 14 after ablation, immunohistochemistry and flow cytometry were used to evaluate the T-cell immune responses. In addition, the cytokine patterns were identified by enzyme-linked immunosorbent assay. RESULTS: Tumor eradication was achieved completely in the MWA groups, as proven by nicotinamide adenine dinucleotide diaphorase staining. Compared with the three treatment groups, the control group had a significantly higher number of pulmonary metastases and worse survival; however, no significant difference was observed among the three treatment groups. More intra-tumoral and systemic CD4+ and CD8+ T-cells were induced in the MWA groups than in the control group. Compared with operation, MWA induced more systemic CD4+ T-cells. More intra-tumoral CD4+ and CD8+ T-cells and systemic CD4+ T-cells were induced by high-power MWA than by low-power MWA. Moreover, MWA increased the interleukin 2 (IL2) and IL12 levels and decreased the IL4, IL6, and IL10 levels. Importantly, the serum IL12 level was significantly higher after high-power MWA than after low-power MWA. CONCLUSION: High-power MWA enhanced the type 1 T helper immune response and may be selected for the treatment of solid tumors. Future studies are needed to confirm our results.

Blood metagenomics next-generation sequencing has advantages in detecting difficult-to-cultivate pathogens, and mixed infections: results from a real-world cohort.

Background: Blood is a common sample source for metagenomics next-generation sequencing (mNGS) in clinical practice. In this study, we aimed to detect the diagnostic value of blood mNGS in a large real-world cohorts. Methods: Blood mNGS results of 1,046 cases were collected and analyzed along with other laboratory tests. The capabilities and accuracy of blood mNGS were compared with other conventional approaches. Results: Both the surgical department and the intensive care unit had a positive rate of over 80% in blood mNGS. The positive rate of mNGS was consistent with clinical manifestations. Among the 739 positive samples, 532 were detected as mixed infections. Compared to pathogen cultures, the negative predictive value of blood mNGS for bacteria and fungi detection was 98.9% [95%CI, 96.9%-100%], with an accuracy rate of 89.39%. When compared with polymer chain reaction, the consistency rates of blood mNGS for virus identification were remarkably high. Conclusions: Blood mNGS have significant advantages in detecting difficult-to-cultivate bacteria or fungi, viruses, and mixed infections, which benefits patients of surgery department the most. Samples other than blood are recommended for mNGS test if a specific infection is suspected. The reporting threshold and reporting criteria of blood mNGS need to be optimized.

Selection of disease-specific biomarkers by integrating inflammatory mediators with clinical informatics in AECOPD patients: a preliminary study.

Systemic inflammation is a major factor influencing the outcome and quality of patient with chronic obstructive pulmonary disease (COPD) and acute exacerbations (AECOPD). Because of the inflammatory complexity, a great challenge is still confronted to optimize the identification and validation of disease-specific biomarkers. This study aimed at developing a new protocol of specific biomarker evaluation by integrating proteomic profiles of inflammatory mediators with clinical informatics in AECOPD patients, understand better their function and signal networks. Plasma samples were collected from healthy non-smokers or patients with stable COPD (sCOPD) or AECOPD on days 1 and 3 of the admission and discharging day (day 7-10). Forty chemokines were measured using a chemokine multiplex antibody array. Clinical informatics was achieved by a Digital Evaluation Score System (DESS) for assessing severity of patients. Chemokine data was compared among different groups and its correlation with DESS scores was performed by SPSS software. Of 40 chemokines, 30 showed significant difference between sCOPD patients and healthy controls, 16 between AECOPD patients and controls and 13 between AECOPD patients and both sCOPD and controls, including BTC, IL-9, IL-18Bpa, CCL22,CCL23, CCL25, CCL28, CTACK, LIGHT, MSPa, MCP-3, MCP-4 and OPN. Of them, some had significant correlation with DESS scores. There is a disease-specific profile of inflammatory mediators in COPD and AECOPD patients which may have a potential diagnostics together with clinical informatics of patients. Our preliminary study suggested that integration of proteomics with clinical informatics can be a new way to validate and optimize disease-special biomarkers.

[Expression of inflammation cytokines and network analysis in acute rejection of renal transplantation].

OBJECTIVE: To explore the changes of inflammation cytokines during acute renal transplantation rejection and decipher the functions of their protein-protein interaction network. METHODS: Serum samples were collected from renal transplantation patients with stable renal function or acute rejection (n = 6 each) to measure the expression level of 40 inflammatory factors by APIX protein array. The differentially expressed proteins were selected and their protein-protein interaction networks constructed. And biologic processes were analyzed by the online tools of String and Network Ontology Analysis. RESULTS: There were 8 differentially expressed cytokines in the AR group versus the stable group (M (Q(1)-Q(3)), CCL24: 700 (255 - 1157) vs 330 (100 - 610) ng/L, ICAM-1: 58 737 (8018 - 105 395) vs 22 660 (137 - 68 914) ng/L, IL-10: 120 (20 - 517) vs 298 (81 - 11 609) ng/L, IL-6sR: 11 328 (3357 - 21 251) vs 7665 (370 - 12 455) ng/L, CCL3: 1712(7002 - 32 634) vs 283 (54 - 1915) ng/L, CCL4: 554 (28 - 2355) vs 283(104 - 1915) ng/L, TIMP-1: 15 560 (13 343 - 42 481) vs 11 271 (1207 - 18 228) ng/L, CCL5: 44 547 (38 252 - 78 631) vs 27 765 (12 073 - 46 627) ng/L, all P < 0.05). The analyses of protein-protein association network showed that these proteins were correlated and involved in such biological processes as taxis, chemotaxis, inflammatory reactions, wound responses and leukocytic migration. CONCLUSIONS: Comparing the inter-group differences of inflammatory cytokines and further developing and analyzing the protein-protein interaction network may help us to explore the mechanisms of acute renal transplantation rejection. And the differential cytokines can be used as candidate diagnostic biomarkers and intervention targets.