Hederagenol improves multiple sclerosis by modulating Th17 cell differentiation.

Multiple sclerosis (MS) is a common autoimmune illness that is difficult to treat. The upregulation of Th17 cells is critical in the pathological process of MS. Hederagenol (Hed) has been shown to lower IL-17 levels, although its role in MS pathophysiology is uncertain. In this study, we explore whether Hed could ameliorate MS by modulating Th17 cell differentiation, with the goal of identifying new treatment targets for MS. The experimental autoimmune encephalomyelitis (EAE) mouse model was conducted and Hed was intraperitoneally injected into mice. The weight was recorded and the clinical symptom grade was assessed. Hematoxylin-eosin staining was carried out to determine the extent of inflammation in the spinal cord and liver. The luxol Fast Blue staining was performed to detect the pathological changes in the myelin sheath. Nerve damage was detected using NeuN immunofluorescence staining and terminal deoxynucleotidyl transferase dUTP nick-end labeling staining. Immunohistology approaches were used to study alterations in immune cells in the spinal cord. The proportions of T cell subsets in the spleens were analyzed by flow cytometry. RORγt levels were measured using quantitative real-time PCR or Western blot. The activity of the RORγt promoter was analyzed by Chromatin immunoprecipitation. Hed administration reduced the clinical symptom grade of EAE mice, as well as the inflammatory infiltration, demyelination, and cell disorder of the spinal cord, while having no discernible effect on the mouse weight. In addition, Hed treatment significantly reduced the number of T cells, particularly Th17 cells in the spinal cord and spleen-isolated CD4+ T cells. Hed lowered the RORγt levels in spleens and CD4+ T cells and overexpression of RORγt reversed the inhibitory effect of Hed on Th17 differentiation. Hed decreased nerve injury by modulating Th17 differentiation through the RORγt promoter. Hed regulates Th17 differentiation by reducing RORγt promoter activity, which reduces nerve injury and alleviates EAE.

Design and synthesis of cantharidin derivative DCZ5418 as a TRIP13 inhibitor with anti-multiple myeloma activity in vitro and in vivo.

Natural product cantharidin can inhibit multiple myeloma cell growth in vitro, while serious adverse effects limited its clinical application. Therefore, the structural modification of cantharidin is needed. Herein, inspired by the structural similarity of the aliphatic endocyclic moiety in cantharidin and TRIP13 inhibitor DCZ0415, we designed and synthesized DCZ5418 and its nineteen derivatives. The molecular docking study indicated that DCZ5418 had a similar binding mode to TRIP13 protein as DCZ0415 while with a stronger docking score. Moreover, the bioassay studies of the MM-cells viability inhibition, TRIP13 protein binding affinity and enzyme inhibiting activity showed that DCZ5418 had good anti-MM activity in vitro and definite interaction with TRIP13 protein. The acute toxicity test of DCZ5418 showed less toxicity in vivo than cantharidin. Furthermore, DCZ5418 showed good anti-MM effects in vivo with a lower dose administration than DCZ0415 (15 mg/kg vs 25 mg/kg) on the tumor xenograft models. Thus, we obtained a new TRIP13 inhibitor DCZ5418 with improved safety and good activity in vivo, which provides a new example of lead optimization by using the structural fragments of natural products.

"One pot" synthesis of quinazolinone-[2,3]-fused polycyclic scaffolds in a three-step reaction sequence.

Diverse quinazolinone-[2,3]-fused polycyclic skeletons occupy a prominent position in drug discovery. Even with currently available methods there still remain unmet needs for flexible access to such structures. Herein, we have explored a mild "one pot" procedure for the construction of various quinazolinone-[2,3]-fused polycycles. The procedure involves Pd-catalyzed carbonylation of N-(2-iodophenyl)acetamides, release of the masked terminal amine, and two sequential and spontaneous cyclizations. This generally applicable approach features easy assembly of precursors from readily available starting materials, mild reaction conditions, non-cumbersome operation, and polycyclic diversity.

Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study.

BACKGROUND: Predictive modeling based on multi-omics data, which incorporates several types of omics data for the same patients, has shown potential to outperform single-omics predictive modeling. Most research in this domain focuses on incorporating numerous data types, despite the complexity and cost of acquiring them. The prevailing assumption is that increasing the number of data types necessarily improves predictive performance. However, the integration of less informative or redundant data types could potentially hinder this performance. Therefore, identifying the most effective combinations of omics data types that enhance predictive performance is critical for cost-effective and accurate predictions. METHODS: In this study, we systematically evaluated the predictive performance of all 31 possible combinations including at least one of five genomic data types (mRNA, miRNA, methylation, DNAseq, and copy number variation) using 14 cancer datasets with right-censored survival outcomes, publicly available from the TCGA database. We employed various prediction methods and up-weighted clinical data in every model to leverage their predictive importance. Harrell's C-index and the integrated Brier Score were used as performance measures. To assess the robustness of our findings, we performed a bootstrap analysis at the level of the included datasets. Statistical testing was conducted for key results, limiting the number of tests to ensure a low risk of false positives. RESULTS: Contrary to expectations, we found that using only mRNA data or a combination of mRNA and miRNA data was sufficient for most cancer types. For some cancer types, the additional inclusion of methylation data led to improved prediction results. Far from enhancing performance, the introduction of more data types most often resulted in a decline in performance, which varied between the two performance measures. CONCLUSIONS: Our findings challenge the prevailing notion that combining multiple omics data types in multi-omics survival prediction improves predictive performance. Thus, the widespread approach in multi-omics prediction of incorporating as many data types as possible should be reconsidered to avoid suboptimal prediction results and unnecessary expenditure.

Up-regulation of thioesterase superfamily member 2 in skeletal muscle promotes hepatic steatosis and insulin resistance in mice.

BACKGROUND AND AIMS: Thioesterase superfamily member 2 (Them2) is highly expressed in liver and oxidative tissues, where it hydrolyzes long-chain fatty acyl-CoA esters to free fatty acids and CoA. Although mice globally lacking Them2 (Them2-/- ) are protected against diet-induced obesity, hepatic steatosis (HS), and insulin resistance (IR), liver-specific Them2-/- mice remain susceptible. The aim of this study was to test whether Them2 activity in extrahepatic oxidative tissues is a primary determinant of HS and IR. APPROACH AND RESULTS: Upon observing IR and up-regulation of Them2 in skeletal, but not cardiac, muscle of high-fat-diet (HFD)-fed wild-type compared to Them2-/- mice, we created mice with Them2 specifically deleted in skeletal (S-Them2-/- ) and cardiac muscle (C-Them2-/- ), as well as in adipose tissue (A-Them2-/- ). When fed an HFD, S-Them2-/- , but not C-Them2-/- or A-Them2-/- , mice exhibited reduced weight gain and improved glucose homeostasis and insulin sensitivity. Reconstitution of Them2 expression in skeletal muscle of global Them2-/- mice, using adeno-associated virus, was sufficient to restore excess weight gain. Increased rates of fatty acid oxidation in skeletal muscle of S-Them2-/- mice contributed to protection from HFD-induced HS by increasing VLDL triglyceride secretion rates in response to greater demand. Increases in insulin sensitivity were further attributable to alterations in production of skeletal muscle metabolites, including short-chain fatty acids, branched-chain amino acids, and pentose phosphate pathway intermediates, as well as in expression of myokines that modulate insulin responsiveness. CONCLUSIONS: These results reveal a key role for skeletal muscle Them2 in the pathogenesis of HS and IR and implicate it as a target in the management of NAFLD.

Design, synthesis of auristatins-glucuronide conjugates targeting the ß-glucuronidase in tumor microenvironment.

Auristatins-glucuronide conjugates designed targeting the ß-Glucuronidase in tumor microenvironment were synthesized and evaluated on stabilities, the release of auristatins and the antitumor activities in this study. Conjugates 20 and 21 showed remarkable stabilities in phosphate buffer and bovine serum solution, and excellent selectivity between the in vitro antiproliferative activities against ß-glucuronidase pretreated and untreated cancer cells (IC50 = 5.7 nM âˆ¼ 9.7 nM, IC50 (-Enz) > 1 µM). Furthermore, conjugate 20 showed potent antitumor efficacy in HCT-116 xenograft mouse model without inducing side effects.

Synthesis, evaluation and molecular dynamics study of human toll-like receptor 2/6 specific monoacyl lipopeptides as candidate immunostimulants.

TLR2 agonists typified by the S-[2,3-bis(palmitoyloxy)-(2RS)-propyl]-R-cysteinyl-S-serine (Pam2CS) motif have exhibited powerful immunostimulatory activities. Based on simplified monoacyl lipopeptide (Carbamate-linked N-Ac PamCS), we describe interesting SAR investigations where modifications are done to alter the size of substituents on the cysteine amine, introduce ionizable groups to the terminal and insert aromatic substitutions to the aliphatic chain. Our structural modifications have led to a highly specific human TLR2/6 agonist 14a (EC50 = 0.424 nM), which behaves like Pam2CSK4 by inducing NF-κB activation to trigger downstream signaling pathways, such as subsequent phosphorylation of related proteins (p65, p38) and production of key inflammatory cytokines (IL-6, IL-1ß, TNF-α). Importantly, the ability to stimulate enhanced T cell response compared to Carbamate-linked N-Ac PamCS makes compound 14a a further potential candidate immunostimulant.

5-HMF attenuates inflammation and demyelination in experimental autoimmune encephalomyelitis mice by inhibiting the MIF-CD74 interaction.

The neuroprotective role of 5-hydroxymethyl-2-furfural (5-HMF) has been demonstrated in a variety of neurological diseases. The aim of this study is to investigate the effect of 5-HMF on multiple sclerosis (MS). IFN-γ-stimulated murine microglia (BV2 cells) are considered a cell model of MS. With 5-HMF treatment, microglial M1/2 polarization and cytokine levels are detected. The interaction of 5-HMF with migration inhibitory factor (MIF) is predicted using online databases. The experimental autoimmune encephalomyelitis (EAE) mouse model is established, followed by a 5-HMF injection. The results show that 5-HMF facilitates IFN-γ-stimulated microglial M2 polarization and attenuates the inflammatory response. According to the network pharmacology and molecular docking results, 5-HMF has a binding site for MIF. Further results show that blocking MIF activity or silencing CD74 enhances microglial M2 polarization, reduces inflammatory activity, and prevents ERK1/2 phosphorylation. 5-HMF inhibits the MIF-CD74 interaction by binding to MIF, thereby inhibiting microglial M1 polarization and enhancing the anti-inflammatory response. 5-HMF ameliorates EAE, inflammation, and demyelination in vivo. In conclusion, our research indicates that 5-HMF promotes microglial M2 polarization by inhibiting the MIF-CD74 interaction, thereby attenuating inflammation and demyelination in EAE mice.

An improved nonnegative matrix factorization with the imputation method model for pollution source apportionment during rainstorm events.

Data scarcity caused by extreme conditions during storms adds difficulties in performing pollution source apportionment. This study integrated nonnegative matrix factorization with the imputation method (NMF-IM) to fill in missing data (NAs) and conduct source apportionment. A total of 367 river samples and 35 runoff samples were taken from the Banqiao and Nanfei River basins located in Hefei, China, during four rainfall events from June to August 2020. Sixteen indicators were quantified and used for source diagnostics using NMF-IM. The results showed that total phosphorus (TP) had higher concentrations and more violent fluctuations than total nitrogen (TN) in river samples taken from rain. NMF-IM was shown to recover the value distribution of NAs approximately. The source profiles and contribution rates calculated by NMF-IM with NAs were close to the original results calculated by NMF without NAs, with root mean square error of less than 2.3% and differences less than 9.5%. Multiple forms of nitrogen and phosphorus indicators benefit reaching reasonable source diagnostics results. At least four indicators were needed to reach the same contribution rates as 16 indicator diagnostics. The two good indicator combination groups are nitrate (NO3-N), nitrite (NO2-N), ammonia nitrogen (NH3-N), and total suspended solids (TSS) and NO3-N, NO2-N, phosphorus (PO4-P), and TSS. The pollution source contributions changed with the Antecedent dry period (ADPs) of rain events. Treated tailwater and untreated sewage were major sources, contributing more than 80% of the total pollution of the rainstorm events with short ADPs. Dust wash became the dominant contributor after 60 min and contributed 36% of the total pollution of rainstorm events with long ADPs. The average source contribution rates for rainfall events in the Banqiao River were treated tailwater (41%) > untreated sewage (27%) > dust wash (19%) > other sources (16%). The pollution source diagnostics results were verified to be reasonable by simulation using tested run-off data and literature results.

An in-depth investigation of the influence of sample size on PCA-MLR, PMF, and FA-NNC source apportionment results.

The mechanism by which parameters influence the source apportionment results of receptor models is not well understood. Three mature receptor models, namely, principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF) and factor analysis with nonnegative constraints (FA-NNC), were comparatively employed for source apportionment of 16 polycyclic aromatic hydrocarbons in 30 street dust samples. The results indicated that the FA-NNC and PMF models produced results with a higher degree of similarity than the results obtained with the PCA-MLR model. Moreover, when the sample size was gradually decreased, similar source profiles were extracted that were consistent with results obtained from all samples. However, the overall contribution rates were not as stable as the source profiles. The PCA-MLR results remained the most stable in both aspects. FA-NNC and PMF performed better in regards to the stability of contribution rates and source profiles, respectively. Improvements in the goodness of fit of overall and individual pollutants were always accompanied by a decrease in the relevance among the variables, indicating that while the model simulation effect was improved, the credibility of the results decreased. Thus, finding an appropriate number of sample size is more appropriate than simply involving too many samples in source apportionment models.

Benchmark study of feature selection strategies for multi-omics data.

BACKGROUND: In the last few years, multi-omics data, that is, datasets containing different types of high-dimensional molecular variables for the same samples, have become increasingly available. To date, several comparison studies focused on feature selection methods for omics data, but to our knowledge, none compared these methods for the special case of multi-omics data. Given that these data have specific structures that differentiate them from single-omics data, it is unclear whether different feature selection strategies may be optimal for such data. In this paper, using 15 cancer multi-omics datasets we compared four filter methods, two embedded methods, and two wrapper methods with respect to their performance in the prediction of a binary outcome in several situations that may affect the prediction results. As classifiers, we used support vector machines and random forests. The methods were compared using repeated fivefold cross-validation. The accuracy, the AUC, and the Brier score served as performance metrics. RESULTS: The results suggested that, first, the chosen number of selected features affects the predictive performance for many feature selection methods but not all. Second, whether the features were selected by data type or from all data types concurrently did not considerably affect the predictive performance, but for some methods, concurrent selection took more time. Third, regardless of which performance measure was considered, the feature selection methods mRMR, the permutation importance of random forests, and the Lasso tended to outperform the other considered methods. Here, mRMR and the permutation importance of random forests already delivered strong predictive performance when considering only a few selected features. Finally, the wrapper methods were computationally much more expensive than the filter and embedded methods. CONCLUSIONS: We recommend the permutation importance of random forests and the filter method mRMR for feature selection using multi-omics data, where, however, mRMR is considerably more computationally costly.

Discovery of 4'-O-methylscutellarein as a potent SARS-CoV-2 main protease inhibitor.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in millions of deaths and seriously threatened public health and safety. Despite COVID-19 vaccines being readily popularized worldwide, targeted therapeutic agents for the treatment of this disease remain very limited. Here, we studied the inhibitory activity of the scutellarein and its methylated derivatives against SARS-CoV-2 main protease (Mpro) by the fluorescence resonance energy transfer (FRET) assay. Among all the methylated derivatives we studied, 4'-O-methylscutellarein exhibited the most promising enzyme inhibitory activity in vitro, with the half-maximal inhibitory concentration value (IC50) of 0.40 ± 0.03 µM. Additionally, the mechanism of action of the hits was further characterized through enzyme kinetic studies and molecular docking. Overall, our results implied that 4'-O-methylscutellarein could be a primary lead compound with clinical potential for the development of inhibitors against the SARS-CoV-2 Mpro.

Discovery of novel benzimidazole derivatives as potent p300 bromodomain inhibitors with anti-proliferative activity in multiple cancer cells.

Adenovirus E1A-associated 300-kD protein (p300) bromodomain, which regulates gene expression by recognizing acetylated lysine (KAc) of histone, is a promising target for the treatment of cancer. Herein, a series of potent p300 bromodomain inhibitors with novel CBP30-based scaffolds was discovered through bioisosterism and conformational restriction strategies. The most promising compound 1u showed more potent inhibitory activity (IC50 = 49 nM) against p300 bromodomain and anti-proliferative activity in various cancer cell lines compared to CBP30. Moreover, 1u suppressed the expression of c-Myc and induced G1/G0 phase arrest and apoptosis in OPM-2 cells more potently than CBP30. This study provides new lead compounds for further research on the biological functions of p300.

Design, synthesis and biological evaluation of (R)-5-methylpyrrolidin-2-ones as p300 bromodomain inhibitors with Anti-Tumor activities in multiple tumor lines.

p300/CBP bromodomain plays an important role in transcriptional regulation, and its overexpression is closely related to various diseases such as cancers. Two inhibitors of this target are currently in clinical trials but only CCS1477 (A1) have been published with the chemical structure. Herein, we modified the structure of CCS1477 based on the principle of bioisosterism and reasonable scaffold hopping, and discovered a series of new p300 bromodomain inhibitors with improved potency. More tumor cell lines sensitive to p300/CBP bromodomain inhibition were also identified. Among our new inhibitors, (R)-5-methylpyrrolidin-2-one derivitive B4 was the most potent one which showed comparable inhibitory activity against p300 (IC50 = 0.060 µM) as lead A1 (IC50 = 0.064 µM) at molecular level, and performed more potent proliferation inhibitory activities on various tumor cells than A1. Further we found that compound B4 had the high cell permeability and overcame the defect of the high efflux rate of A1, which could also explain the possible reason why B4 showed more potent inhibitory activities on sensitive tumor cells than lead A1. Western blotting analysis proved the target effects that B4 could suppress the expression of c-Myc and reduce H3K27 acetylation significantly. Liver microsomal metabolic stability assay and hERG channel inhibition evaluation illustrate compound B4 is metabolic stabilizable in human liver microsomes and has no hERG risk, which further demonstrate the good drug-likeness of B4. Therefore, compound B4 is a promising compound for further optimization and development.

The influence of rainfall and catchment characteristics on runoff generation in urban catchments-a case study in Hebi City of China.

An in-depth understanding of the rainfall-runoff process is essential for effective stormwater management. However, the understanding of the hierarchy of rainfall characteristics in terms of their importance in influencing runoff generation is limited. This paper investigates the influence of rainfall characteristics and catchment characteristics on runoff generation in urban catchments. The outcomes showed that there are 4 dominant factors affecting runoff generation: total precipitation TP and maximum 60-min rainfall intensity MAX60 are the two top-ranked factors while average rainfall intensity RI and maximum 5-min rainfall intensity MAX5 are ranked second. Additionally, compared to the moderate rainfall regime (MR), the heavy rainfall regime (HR) tends to produce higher peak flow rates, higher total inflow per unit area, and lower runoff control effect. Note that the antecedent precipitation has a more significant effect on runoff generation and is even the dominant factor when rainstorm events with daily rainfall larger than 50 mm are not considered. The results of analyzing the influence of catchment characteristics suggest that only under HR regime conditions do the catchment characteristics have an impact on runoff generation and behave as smaller catchment areas, and higher proportions of green landscapes always lead lower peak flow rates, lower total inflows per unit area, and higher runoff control effects.

Discovery of oxyepiberberine as a novel tubulin polymerization inhibitor and an anti-colon cancer agent against LS-1034 cells.

Coptis chinensis Franch. has been extensively used in traditional Chinese medicine. The chemical structure of oxyepiberberine, as an alkaloid isolated from Coptis chinensis Franch., has been previously studied. However, anti-cancer effects and underlying mechanisms of oxyepiberberine need to be explored. This study aimed to investigate the anti-cancer effects and underlying mechanisms of oxyepiberberine on LS-1034 human colon cancer cells. The anti-proliferative effects of six derivatives of oxyepiberberine on colon cancer cells were assessed. Among six derivatives, oxyepiberberine showed the greatest anti-proliferative effect on LS-1034 cells with an IC50 value of 1.36 µM. Oxyepiberberine also induced apoptosis and inhibited migration of LS-1034 cells in a concentration-dependent manner. Importantly, oxyepiberberine was identified as a potent tubulin polymerization inhibitor. The tubulin polymerization inhibitory effects of oxyepiberberine in a concentration-dependent manner with an IC50 value of 1.26 µM were observed. A xenograft mouse model of colon cancer showed that oxyepiberberine could suppress tumor growth without an obvious toxicity. Conclusion Oxyepiberberine was found as a novel tubulin polymerization inhibitor, and it could be a promising agent to treat colon cancer.

Synthesis of the analogs of plocabulin and their preliminary structure-activity relationship study.

Plocabulin, a marine natural polyketide isolated from the sponge Lithoplocamia lithistoides, is a novel and potent microtubule-destabilizing agent. Guided by the reported binding mode, several new analogs of plocabulin have been designed through removing the right aliphatic chain and further modifying on the carbamate group and the enamide unit. The preliminary results indicate that the right aliphatic chain in plocabulin is allowed to remove with a little loss of activity, the carbamate group plays a role in the activity, and particularly, the enamide unit has an important effect on the activity. This new finding will aid the design of novel potent tubulin-binding agents based on plocabulin.

Synthesis and biological evaluation of novel cabazitaxel analogues.

Cabazitaxel is one of the most recently FDA-approved taxane anticancer agent. In view of the advantages in preclinical and clinical data of cabazitaxel over former toxoids, the synthesis and biological evaluation of novel cabazitaxel analogues were conducted. First, a novel semi-synthesis of cabazitaxel was described. This strategy is concise and efficient, which needs five steps from the 10-deacetylbaccatin III (10-DAB) moiety and a commercially available C13 side chain precursor with a 32% overall yield. Besides, this strategy avoids using many hazardous reagents that involved in the previously reported processes. Then, a panel of cabazitaxel analogues were prepared basing on this strategy. The cytotoxicity evaluations showed that the majority of these cabazitaxel analogues are potent against both A549 and KB cells and their corresponding drug-resistant cell lines KB/VCR, and A549/T, respectively. Further in vivo antitumor efficacies assessment of 7,10-di-O-methylthiomethyl (MTM) modified cabazitaxel (compounds 16 and 19) on SCID mice A549 xenograft model showed they both had similar antitumor activity to the cabazitaxel. Since compound 19 was observed causing more body wight loss on the mice than 16, these preliminary studies suggest 16 might be a potent drug candidate for further preclinical evaluation.

Resilience process and its protective factors in long-term survivors after lung cancer surgery: a qualitative study.

BACKGROUND: Resilience was correlated with psychological outcomes and quality of life in lung cancer patients. But the resilience process and its protective factors remained uncertain. PURPOSE: To investigate and analyze resilience process and its protective factors in long-term survivors after lung cancer surgery. METHODS: This qualitative study included 19 patients who had survived at least 5 years after lung cancer surgery. Colaizzi's method of phenomenology was used for data analysis. RESULTS: Analysis of this study was divided into the resilience process and protective factors. The resilience process was summarized into three stages, including initial stress, adaptation to disease, and personal growth. Five themes were regarded contributing to their own resilience in this process, including excellent psychological qualities, good social support, regular lifestyle and exercise, participating in social activities, and Chinese medicine. CONCLUSION: This study showed the dynamic process of resilience and its protective factors in long-term survivors after lung cancer surgery. Future studies could identify average length of time of each stage and how patients transfer between stages during resilience process. Besides, interventions could be carried out to educate patients diagnosed with cancer about normal stages of change in body and resilience through time and strategies on adaptation and adjustment of lung cancer.

Potential role of chimeric genes in pathway-related gene co-expression modules.

BACKGROUND: Gene fusion has epigenetic modification functions. The novel proteins encoded by gene fusion products play a role in cancer development. Therefore, a better understanding of the novel protein products may provide insights into the pathogenesis of tumors. However, the characteristics of chimeric genes are rarely studied. Here, we used weighted co-expression network analysis to investigate the biological roles and underlying mechanisms of chimeric genes. METHODS: Download the pig transcriptome data, we screened chimeric genes and parental genes from 688 sequences and 153 samples, predict their domains, and analyze their associations. We constructed a co-expression network of chimeric genes in pigs and conducted Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis on the generated modules using DAVID to identify key networks and modules related to chimeric genes. RESULTS: Our findings showed that most of the protein domains of chimeric genes were derived from fused pre-genes. Chimeric genes were enriched in modules involved in the negative regulation of cell proliferation and protein localization to centrosomes. In addition, the chimeric genes were related to the growth factor-ß superfamily, which regulates cell growth and differentiation. Furthermore, in helper T cells, chimeric genes regulate the specific recognition of T cell receptors, implying that chimeric genes play a key role in the regulation pathway of T cells. Chimeric genes can produce new domains, and some chimeric genes are a key role involved in pathway-related function. CONCLUSIONS: Most chimeric genes show binding activity. Domains of chimeric genes are derived from several combinations of parent genes. Chimeric genes play a key role in the regulation of several cellular pathways. Our findings may provide new directions to explore the roles of chimeric genes in tumors.