Ovarian cancer remains one of the most lethal gynecologic malignancies, largely because of late-stage diagnosis, extensive intratumoral heterogeneity, and the dynamic complexity of the tumor microenvironment (TME). Emerging evidence highlights the TME as a central orchestrator of immune evasion, angiogenic remodeling, and therapeutic resistance, which are three mechanistic pillars that critically shape disease progression and treatment outcomes. This narrative review synthesizes current mechanistic insights into how stromal, immune, and vascular components interact to promote tumor survival and metastasis. We examine the roles of immunosuppressive cell populations, cytokine networks, and checkpoint pathways in facilitating immune escape; delineate angiogenic drivers and endothelial-tumor crosstalk that sustain aberrant vascularization; and explore TME-mediated mechanisms that underlie chemoresistance, targeted therapy failure, and limited immunotherapy responsiveness. Furthermore, we evaluate recent advances in biomarker discovery, including the identification of circulating ncRNAs, exosomal signatures, spatial immune profiles, and TME-derived molecular indicators, which hold promise for improving early detection, prognostication, and therapeutic stratification. By integrating mechanistic biology with translational biomarker innovation, this review outlines a forward-looking framework for leveraging TME-informed diagnostics and therapeutics to enhance precision oncology in ovarian cancer.

Background: Ethylmalonic encephalopathy 1 (ETHE1), a persulfide dioxygenase, is abnormally expressed in various malignancies, but its mechanism and therapeutic potential in lung cancer remain unclear. This study aimed to elucidate the molecular mechanisms through which ETHE1 promotes lung cancer progression via coordination of the PI3K/AKT signaling pathway and tumor metabolism. The feasibility of using ETHE1 as a therapeutic target was also explored. Methods: Bioinformatics analysis was used to assess ETHE1 expression levels in lung cancer tissues and its relationship with patient prognosis. ETHE1-overexpressing and ETHE1-silenced lung cancer cell models were constructed. CCK-8, BrdU, and Transwell assays were used to detect cell proliferation, migration, and invasion capabilities. Nude mouse lung metastasis models were established to validate the functions of ETHE1 in vivo. Western blotting was used to analyze the activation status of the PI3K/AKT signaling pathway. Coexpression analysis and functional enrichment analysis were performed to explore the mechanisms underlying the effects of ETHE1. Molecular docking and cellular experiments were employed to screen potential ETHE1 inhibitors and evaluate their antitumor effects. Results: ETHE1 was significantly overexpressed in human lung cancer tissues and closely associated with poor patient prognosis. Functional enrichment analysis revealed that genes coexpressed with ETHE1 were involved mainly in cellular metabolism and signal transduction processes. In vitro and in vivo experiments confirmed that ETHE1 overexpression significantly promoted lung cancer cell proliferation, migration, invasion, and lung metastasis. Mechanistic studies revealed that ETHE1 exerted oncogenic effects by activating the PI3K/AKT signaling pathway. ETHE1 forms a regulatory axis with the key metabolic enzyme hexokinase 2 (HK2), further amplifying its oncogenic effects. ETHE1 silencing significantly enhanced lung cancer cell sensitivity to chemotherapy drugs such as cisplatin and partially reversed drug resistance. Drug screening identified neobavaisoflavone (NBIF) as an effective ETHE1 inhibitor. NBIF treatment suppressed ETHE1 expression and enhanced chemotherapy sensitivity. Conclusion: ETHE1 plays a crucial role in lung cancer progression by activating the PI3K/AKT signaling pathway and regulating HK2-mediated metabolism. ETHE1 silencing or NBIF inhibition significantly suppressed malignant tumor behaviors and enhanced chemotherapy sensitivity. These findings establish ETHE1 as a promising therapeutic target for lung cancer treatment.

Ovarian cancer remains one of the most lethal gynecologic malignancies due to its asymptomatic onset and the lack of reliable early stage diagnostic tools. Immunosensor technologies have emerged as powerful platforms capable of detecting ovarian cancer-associated biomarkers with high sensitivity, specificity, and rapid turnaround times. Recent advances in nanomaterials, microfluidic integration, and signal amplification strategies have significantly enhanced the analytical performance of electrochemical, optical, and piezoelectric immunosensors. These innovations enable ultrasensitive quantification of key biomarkers such as CA 125, HE4, mesothelin, and emerging multi marker panels, supporting earlier detection and improved disease monitoring. Furthermore, the development of portable and point of care immunosensing devices offers promising avenues for decentralized screening and personalized clinical decision making. This review highlights the latest technological breakthroughs, design principles, and translational challenges in immunosensor based ovarian cancer diagnostics, emphasizing their potential to transform early detection and patient outcomes.

Lactylation, a recently identified histone modification derived from lactate metabolism, has emerged as a critical regulator of epigenetic reprogramming, tumor proliferation, and immune evasion. In ovarian cancer, lactate dehydrogenase A (LDHA) and other metabolic enzymes contribute to lactate accumulation, which supports chemotherapy resistance and disease progression. Although lactylation is increasingly linked to therapy failure, its precise molecular connection with ovarian cancer, as well as its therapeutic potential are unclear. Traditional analytical approaches often fail to integrate the complexity of multi-omics, limiting the discovery of actionable lactylation-associated vulnerabilities. This research aims to develop an AI-driven multi-omics framework to identify lactylation-related genes, stratify patient drug responses, and establish prognostic signatures in ovarian cancer. Transcriptomic, epigenomic, pharmacogenomic, mutation, and clinical outcome data were collected from The Cancer Genome Atlas (TCGA), the Genomics of Drug Sensitivity in Cancer (GDSC), and independent ovarian cancer cohorts. Deep learning models, including variational autoencoders (VAEs), Long Short-Term Memory (LSTM) networks, and Multitask Multilayer Perceptrons (MLPs) (LSTM-MLP), were applied for molecular subtyping, survival analysis, and IC50 prediction. Findings were validated through pathway enrichment, mutation mapping, immune infiltration profiling, and structure-guided drug repurposing, the proposed method achieved precision of (0.955). Key lactylation-related genes, including LDHA and SLC16A3, were associated with immune exhaustion and cisplatin resistance. The Gln-TEx score and lactylation risk signature robustly predicted patient survival and drug response across TCGA and validation cohorts. Perturbation sensitivity and repurposing analyses revealed novel therapeutic vulnerabilities. This study establishes a precision oncology framework that integrates lactylation biology with AI-driven analytics to uncover druggable targets, enhance patient stratification, and inform the design of multi-target therapies in ovarian cancer.

The identification of biomarkers correlated with colorectal cancer (CRC) prognosis holds substantial importance from both clinical and scientific perspectives. Zinc finger protein 26 (ZNF26) has not been previously investigated or documented in solid tumors; thus, further research is necessary to ascertain its prognostic value in CRC. Gene expression profiles and clinicopathological data were acquired from The Cancer Genome Atlas (TCGA) database. Subsequently, expression correlation was assessed utilizing the TCGA CRC cohort. The prognostic value of ZNF26 was evaluated through Kaplan-Meier (KM) and ROC curve analyses. Following this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to perform enrichment analysis between high- and low-ZNF26 expression groups. The association between immune cells, immune checkpoint genes, and ZNF26 expression levels was examined. Lastly, the research findings were further validated using CRC tissue samples. The results revealed that, in comparison to healthy controls, CRC significantly reduced ZNF26 expression. Elevated ZNF26 expression was associated with poorer overall survival in CRC patients. Additionally, high ZNF26 expression exhibited an inverse relationship with the immunological score and immune checkpoint gene expression in CRC patients. The findings from the TCGA data analysis were corroborated by the PCR results obtained from CRC tissue samples. ZNF26 is markedly upregulated in colorectal cancer tissues, potentially serving as a biomarker for CRC.

BACKGROUND:This study aims to investigate centrosomal protein 70 (CEP70) in prostate cancer and its effects on angiogenesis and tumour metastasis and elucidate its molecular mechanisms. METHODS:We evaluated CEP70 and Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) in tissue samples from patients with prostate cancer by immunohistochemistry. In vitro experiments included overexpressing CEP70 through transfection and assessing its impact on human umbilical vein endothelial cells (HUVECs). Intervention experiments with an NF-κB pathway inhibitor were conducted to verify the mechanism. Finally, the effects of CEP70 on tumour growth, angiogenesis and metastasis were examined in a nude mouse model. RESULTS:CEP70 was significantly overexpressed in prostate cancer tissues compared with that in adjacent normal tissues (p < 0.001). In vitro experiments demonstrated that CEP70 overexpression promoted HUVEC migration (p < 0.001), invasion (p < 0.001) and tube formation (p < 0.05). CEP70 significantly upregulated VEGFA expression in prostate cancer cells at messenger RNA (mRNA) (p < 0.001) and protein levels (p < 0.05). VEGFA knockdown experiments confirmed CEP70 as an essential cytokine for CEP70-induced angiogenesis (p < 0.01). Mechanistically, CEP70 promoted VEGFA expression by activating the NF-κB signalling pathway, as evidenced by the reversal of CEP70-induced effects upon treatment with the NF-κB inhibitor BAY11-7082 (p < 0.01). CONCLUSIONS:CEP70 promotes tumour angiogenesis and metastasis by upregulating VEGFA through NF-κB pathway activation.

Background: Treating glioma with triptolide (TP) produces unsatisfactory outcomes. Previous studies showed that TP combined with succinic acid could sustain antitumor activity during cancer treatment. However, this activity of TP linked with succinic acid has been less investigated during the treatment of glioma. In this study, triptolide-succinic acid ester was synthesized, and its antitumor activity in glioma cells in vitro was determined.Methods: TP was coupled with succinic anhydride (SA) to obtain triptolide-succinic acid ester (TP-SAE). Cell counting kit-8 (CCK-8), transwell, wound healing assays, and flow cytometry analysis of apoptosis were used to evaluate the antitumor activity of TP-SAE in vitro.Results: Results from the cell counting kit-8 assay revealed that TP-SAE rapidly reduced proliferation of glioma cells compared with TP and TP + SA. Transwell and wound healing assays revealed that TP-SAE significantly decreased the invasion and migration of glioma cells compared with TP and TP + SA. The flow cytometry apoptosis assay indicated that apoptosis in glioma cells treated with TP-SAE was significantly higher than in those treated with TP and TP + SA. Conclusions: Triptolide-succinic acid ester could inhibit the proliferation, invasion, and migration activity of glioma cells and promote apoptosis of glioma cells in vitro.

Objective Autophagy is the catabolic process where the components of eukaryotes experience damage, and the affected or superfluous components undergo self-degradation. However autophagy can promote cancer cell apoptosis or facilitate cell growth. This work aimed to investigat the significance of autophagy-related genes (ARGs) in predicting the prognosis of breast cancer (BC) intervened with Cremastra. Methods Active ingredients and action targets were obtained using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction. Then, the BC transcriptome and clinical data were downloaded in The Cancer Genome Atlas (TCGA), whereas ARGs were collected in the Human Autophagy Database (HADb). Meanwhile, Perl and R software were used for data processing and analysis. Firstly, the transcriptome data of BC were mapped to ARGs to screen the BC-ARGs. Secondly, the above genes were mapped to the action targets of Cremastra, ARGs of Cremastra-intervened BC were then screened out. Moreover, an enrichment analysis of biological function was carried out. Univariate Cox regression was carried out on ARGs of BC for preliminarily selecting the independent prognostic genes and constructing the autophagy prognosis model. These genes were mapped to ARGs involved in Cremastra-intervened BC. Finally, those mapped genes were optimized by multi-factor Cox regression, and the key ARGs and potential compounds were obtained. Finally, all cases were classified as low- or high-risk group based on the median risk score. Receiver operating characteristic (ROC) curve, Kaplan-Meier (K-M) survival, independent prognosis and clinical correlation analyses were conducted for model evaluation and identification of factors to independently predict prognosis. Results Altogether, 66 active components and 38 targets of the Cremastra-intervened autophagy of BC were screened and the autophagy prognosis model demonstrate good predictive performance. As suggested by the survival curve, low-risk patients had a markedly increased survival rate compared with high-risk patients (P < .01). Besides, the gene expression levels of the high-risk group increased with the increases in patients' risk scores. Upon univariate regression, 34 differentially expressed ARGs related to BC treatment were screened. Multivariate regression identified 4 key ARGs, which were mainly derived from glycosides, lignans, flavonoids, and dibenzyl compounds. Thereafter, key genes were subjected to correlation analysis between clinicopathological features and prognosis, among which BCL2 and TP63, showed independent prognostic value. Conclusions In this study, an autophagy prognosis model was established, and BCL2 and TP63 were predicted for the Cremastra intervention of BC by Bioinformatics, which will be applied to further work.

Objective:The efficacy of different external treatment methods of traditional Chinese medicine in the treatment of cancer-related fatigue was analyzed by using network meta-analysis.Methods:Searches were conducted on PubMed, China Journal Full-text Database, Embase platform and so on. Filter according to the inclusion and exclusion criteria, and obtain the network relationship diagram through stata15.0 analysis.Results:This study included 31 articles and 6 kinds of external treatment of traditional Chinese medicine. The results showed that the Piper's fatigue scale(PFS) score improvement was ranked as follows: transcutaneous electrical acupoint stimulation+ conventional treatment > auricular point sticking+ conventional treatment > acupuncture+ moxibustion+ conventional treatment > acupuncture+ conventional treatment > acupoint application+ conventional treatment > moxibustion+ conventional treatment > conventional treatment. Significant differences were also observed between traditional Chinese medicine external treatment combined with conventional treatment and conventional treatment ( P<0.05). The results showed that the Karnofsky performance status(KPS) score improvement was ranked as follows: acupuncture+ moxibustion+ conventional treatment > acupuncture+ conventional treatment > moxibustion+ conventional treatment > acupoint application+ conventional treatment > auricular point sticking+ conventional treatment > conventional treatment. Among them, the top three intervention measures had statistically significant differences compared with conventional treatment ( P<0.05). Conclusion:External treatment of traditional Chinese medicine has a significant effect on improving cancer-related fatigue symptoms. However, due to the small sample size of this study, the results obtained in PFS and KPS scores are inconsistent, and the conclusion needs further confirmation.

Objective:To analyze and explore the possible mechanism of anti-tumor metastasis of Notoginseng Radix et Rhizoma using Internet pharmacology. Methods:The active components and targets of Notoginseng Radix et Rhizoma were screened by retrieving Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). GeneCards database was used to screen the anti-tumor metastasis-related targets, and compounds and disease targets were under mapping analysis. Key targets of Notoginseng Radix et Rhizoma for anti-tumor metastasis were screened through Venn map. With the help of Cytoscape 3.7.2 software, a compound-disease network diagram was constructed. String platform was used to build a PPI network. Bioconductor was used to enrich the target genes for KEGG signaling pathway and GO biological process analysis. Results:Totally 119 active components were selected from Notoginseng Radix et Rhizoma. There were 8 eligible active components, corresponding to 162 related targets, 121 targets related to anti-tumor metastasis, and 30 key targets screened by PPI network, including AKT1, MAPK1, JUN, RELA, IL6, etc. GO enrichment analysis mainly involved biological processes such as cytokine receptor binding, heme binding, RNA polymerase Ⅱ transcription factor binding, ubiquitin protein ligase binding, and steroid hormone receptor activity. 149 signal pathways related to Notoginseng Radix et Rhizoma anti-tumor metastasis were obtained by KEGG enrichment analysis, mainly involving multiple signal pathways, such as AGE-RAGE and PI3K-Akt, and hepatitis B, Kaposi's sarcoma-associated herpes virus infection, human cytomegalovirus infection and other viral infections and various tumors. Conclusion:Notoginseng Radix et Rhizoma can pass multiple active components, such as ginsenoside f2, ginsenoside rh2 β-, sitosterol, stigmasterol and quercetin, and multiple targets, such as AKT1, MAPK1, JUN, RELA and IL6, acting on multiple pathways such as PI3K-Akt, thereby playing the role of anti-tumor metastasis.

Cisplatin (DDP) based chemotherapy occurs a reduced therapeutic effect on the later treatment of ovarian cancer (OC) due to DDP resistance. Astragaloside II (ASII), a natural product extracted from Radix Astragali, has shown promising anticancer effects. However, the effects of ASII on OC have not been clarified. In this study, we found that ASII inhibited cell growth and promoted cell apoptosis of DDP-resistant OC cells in vitro and in vivo. Further study showed that ASII downregulated multidrug resistance-related protein MDR1 and cell cycle-related protein Cyclin D1 and PCNA, and also upregulated apoptosis-related protein leaved PRAP and cleaved caspase-3. In addition, ASII induced autophagy, characterized by upregulation of LC3II expression, downregulation of p62 expression, and elevation of LC3 punctuation, may be associated with inhibition of the AKT/mTOR signaling pathway. Moreover, the messenger RNA-sequencing was used to identify potential molecules regulated by ASII. In conclusion, these findings indicated that ASII increased sensitivity of DDP in the treatment of OC.

Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remain unclear. The MSigDB database collecting ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients. Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remains unclear. The MSigDB database collected ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients.

Purpose: To investigate the effect and regulatory mechanism of fucoxanthin (FX) on oral squamous cell carcinoma (OSCC). Methods: Human OSCC SCC9 and Cal27 cells were treated with different concentrations of FX (7.5, 15, and 30 μM) to determine cell viability, number of colonies, and apoptosis rate using methyl thiazolyl diphenyl-tetrazolium bromide (MTT) assay, crystal violet staining, and flow cytometry, respectively. In addition, the number of spheres of OSCC cells was determined by a cell sphere-forming assay. The stem cells and levels of pathway-related proteins were evaluated by western blotting. Results: Fucoxanthin decreased SCC9 and Cal27 cell viability and the number of colonies, but increased apoptosis in a dose-dependent manner. The expression levels of SOX2 and POU5F1 were down-regulated, while the number of spheres was reduced in SCC9 and Cal27 cells treated with 7.5 or 15 μM of FX (p < 0.05). Moreover, FX attenuated p-JAK/JAK and p-STAT3/STAT3 expression levels in a dose-dependent manner (p < 0.05). Conclusion: Fucoxanthin accelerates apoptosis and inhibits cell mobility and OSCC stem cell formation by suppressing JAK/STAT3 pathway in OSCC, thus providing an experimental basis for research on the anti-tumor effect of kelp extract and the development of new drugs from marine plants.

随着中医肿瘤诊疗领域理论和技术的发展,国家中医药管理部门鼓励各地开展探索新的中医肿瘤诊疗模式.通过梳理黑龙江省肿瘤诊疗的发展现状,分析传统运行模式存在的弊端,提出了新的"一体两翼"运行模式.在新模式下,中医肿瘤诊疗中心坚持中西医并重,实现宣教、诊治、康复于一体,为患者提供更加全面、科学的诊疗服务.同时,新模式促进医、教、研深度协同,注重加强多学科人才培养、团队建设,有助于推动中医药事业高质量发展.

目的:基于分子对接技术探讨还涎方抑制溃疡性结肠炎(UC)癌前病变的作用机制.方法:选取60只BALB/C小鼠,随机分为空白组、模型组、还涎方组、美沙拉嗪组、康复新液组,每组12只.使用氧化偶氮甲烷和葡聚糖硫酸钠诱导建立UC癌前病变模型,采用保留灌肠法治疗UC.观察小鼠便隐血情况,计算疾病活动指数(DAI)评分、结肠炎症反应评分;利用系统药理学分子高通量技术筛选获得关键靶点,进行病理HE染色及Western blot验证,利用分子对接技术分析还涎方中主要成分与关键靶点的结合能力.结果:与模型组比较,还涎方可显著缓解UC癌前病变小鼠便隐血症状,降低DAI评分及结肠黏膜损伤(P＜0.01).高通量筛选得出关键靶点p53、cox-2、bcl-2;与空白组比较,模型组p53、cox-2和bcl-2蛋白表达水平显著升高(P＜0.01);与模型组比较,还涎方组p53、cox-2和bcl-2蛋白表达水平显著降低(P＜0.01).p53、cox-2和bcl-2与还涎方中主要成分进行分子对接,亲和力水平cox-2＞p53＞bcl-2.结论:还涎方可通过干预cox-2、p53、bcl-2靶点抑制UC癌前病变的发生.

目的 真武汤加地龙治疗肺癌并发恶性胸腔积液的疗效及对血清IL-18、TNF-α和肠道菌群的影响.方法 选取2019年6月-2020年6月收治的60例肺癌并发恶性胸腔积液患者临床资料进行分析,对照组(30例)给予静滴长春瑞滨和顺铂抗癌与对症治疗,研究组(30例)在对照组基础上配合真武汤加地龙治疗,比较2组疗效、中医证候积分、不良反应、生存质量和血清IL-18、TNF-α水平,16S rRAN测序检测肠道菌群多样性.结果 研究组治疗总有效率为63.33％,较对照组的40％显著增高(P<0.05);2组治疗后中医证候积分均低于治疗前,且以研究组指标下降更显著(P<0.05);研究组与对照组不良反应总发生率无显著差异(P>0.05);研究组认知功能等生存质量各项评分均高于对照组(P<0.05);2组治疗后血清IL-18和TNF-α水平均降低,且以研究组下降更显著(P<0.05);与对照组比较,研究组菌群多样性更丰富.结论 真武汤加地龙治疗肺癌并发恶性胸腔积液可显著改善临床症状,降低血清IL-18和TNF-α水平,改善菌群多样性,提升临床治疗效果.

Cervical cancer (CC) is the second most common malignancy among women. GEPIA demonstrated that MEF2C-AS1 and its nearby gene MEF2C present downregulation in CC tissues. We attempted to clarify molecular mechanism between MEF2C-AS1 and MEF2C underlying CC progression. RT-qPCR was used to measure expression levels and subcellular distribution of MEF2C-AS1 and MEF2C in CC cell lines. Gain-of-function assays were conducted to reveal roles of MEF2C-AS1 and MEF2C in CC cell behaviors. Bioinformatics, RNA pull down, and RIP assays were performed to assess association of MEF2C-AS1 or MEF2C with miR-20 b-5p in CC cells. Rescue assays were done to assess regulatory function of the MEF2C-AS1-miR-20 b-5p-MEF2C axis in CC cellular processes. MEF2C-AS1 and its nearby gene MEF2C showed downregulation and had a positive expression correlation in CC tissues. MEF2C-AS1 and MEF2C presented downregulation in CC cells, and they majorly distributed in CC cell cytoplasm. MEF2C-AS1 and MEF2C upregulation repressed CC cell proliferative, migratory, and angiogenic abilities. MEF2C-AS1 competitively bound with miR-20 b-5p to upregulate MEF2C in CC cells. The impacts of MEF2C-AS1 elevation on CC cell proliferative, migratory, and angiogenic capabilities were countervailed by miR-20 b-5p overexpression. The impacts of miR-20 b-5p inhibitor on CC cell proliferative, migratory and angiogenic capabilities were countervailed by MEF2C depletion. To sum up, MEF2C-AS1 and its nearby gene MEF2C present downregulation and serve as tumor suppressors in CC cells. MEF2C-AS1 suppresses CC cell malignancy in vitro through sponging miR-20 b-5p to upregulate MEF2C, which may provide a potential new direction for seeking therapeutic plans of CC.

Objective:To perform gene set enrichment analysis (GSEA) and analysis of immune cell infiltration on non-small-cell lung cancer (NSCLC) expression profiling microarray data based on bioinformatics, construct TICS scoring model to distinguish prognosis time, screen key genes and cancer-related pathways for NSCLC treatment, explore differential genes in NSCLC patients, predict potential therapeutic targets for NSCLC, and provide new directions for the treatment of NSCLC. Methods:Transcriptome data of 81 NSCLC patients and the GEO database were used to download matching clinical data (access number: GSE120622). Form the expression of non-small cell lung cancer (NSCLC). TICS values were calculated and grouped according to TICS values, and we used mRNA expression profile data to perform GSEA in non-small-cell lung cancer patients. Biological process (GO) analysis and DAVID and KOBAS were used to undertake pathway enrichment (KEGG) analysis of differential genes. Use protein interaction (PPI) to analyze the database STRING, and construct a PPI network model of target interaction. Results:We obtained 6 significantly related immune cells including activated B cells through the above analysis (Figure 1(b), p < 0.001). Based on the TICS values of significantly correlated immune cells, 41 high-risk and 40 low-risk samples were obtained. TICS values and immune score values were subjected to Pearson correlation coefficient calculation, and TICS and IMS values were found to be significantly correlated (Cor = 0.7952). Based on non-small-cell lung cancer mRNA expression profile data, a substantial change in mRNA was found between both the high TICS group as well as the low TICS group (FDR 0.01, FC > 2). The researchers discovered 730 mRNAs that were considerably upregulated in the high TICS group and 121 mRNAs that were considerably downregulated in the low TICS group. High confidence edges (combined score >0.7) were selected using STRING data; then, 191 mRNAs were matched to the reciprocal edges; finally, an undirected network including 164 points and 777 edges was constructed. Important members of cellular chemokine-mediated signaling pathways, such as CCL19, affect patient survival time. Conclusion:(1) The longevity of patients with non-small-cell lung cancer was substantially connected with the presence of immature B cells, activated B cells, MDSC, effector memory CD4 T cells, eosinophils, and regulatory T cells. (2) Immune-related genes such as CX3CR1, CXCR4, CXCR5, and CCR7, which are associated with the survival of NSCLC, affect the prognosis of NSCLC patients by regulating the immune process.

减毒增效、改善患者生存质量是中医药治疗恶性肿瘤的特色和优势所在,运用中医药来减轻肿瘤患者放化疗毒副反应、提高患者对放化疗的耐受性、增强免疫力、延长患者生存时间的临床效果常让人满意.刘松江教授运用中药治疗恶性肿瘤已有30余年,临证经验丰富,其在运用芪桂消癥方治疗卵巢癌方面,也积累了宝贵的心得体会.笔者通过跟诊学习以及对门诊典型医案的收集、整理,初步总结、概括了刘松江教授运用芪桂消癥方治疗卵巢癌的学术经验.刘松江教授认为东北地区的卵巢癌患者普遍具有虚、毒、瘀的病理特点,而由桂枝茯苓丸加减化裁而来的芪桂消癥方的立论组方恰好契合该病理特点.该方剂在临证应用时,可以根据患者的不同证型来进行加减化裁或与其他方剂联合运用.本文总结了该方剂在卵巢癌常见5种证型治疗中的具体化裁、运用情况,并详细介绍运用芪桂消癥方加减治疗的卵巢癌术后患者1例,以期为临床工作者提供辨证施治经验与思路.