Abstract Background The tumor microenvironment plays a crucial role in determining the prognosis of tumors. Fc gamma receptor IIa (FcγRIIa), one of the three subtypes of FcγRII, is expressed on platelets and immunocytes such as macrophages and neutrophils. These cellular elements collectively contribute to the tumor microenvironment. Previous research has indicated that FcγRIIa activates platelets and inflammatory cells, thus participating in tumor growth and metastasis. Nonetheless, limited information is available regarding FcγRIIa levels in most cancer types. This study aimed to detect serum FcγRIIa in 333 patients with non-small cell lung cancer (NSCLC) and 100 healthy individuals, and to explore the relationship between serum FcγRIIa levels and clinical outcomes in patients with NSCLC. Methods Serum samples from 333 patients with stage I–IV NSCLC and 100 healthy volunteers were analyzed using ELISA. The clinical and laboratory data underwent statistical analysis. Results Circulating FcγRIIa levels were markedly increased in patients with NSCLC, especially in advanced pathologic stages.ROC curve analysis yielded an AUC of 0.7713 (95% CI: 0.7132–0.8264), with an optimal cutoff value of 2115.88 pg/mL based on the Youden index (sensitivity: 60.06%, specificity: 86.00%). Notably, 13% of healthy controls showed FcγRIIa levels above the cutoff, suggesting that elevated FcγRIIa may partially reflect systemic inflammatory status. Survival analysis in 333 patients with NSCLC showed markedly shorter overall survival in FcγRIIa-positive cases. Serum FcγRIIa levels were further identified to be significantly associated with metastatic status. Conclusion This study demonstrated that circulating FcγRIIa levels rise along with tumor progression and may serve as a potential complementary prognostic indicator in metastatic NSCLC, though these findings require validation in prospective cohorts with comprehensive adjustment for inflammatory markers and treatment regimens.

Abstract High-grade serous ovarian carcinoma (HGSOC) is an aggressive malignancy marked by high recurrence rates, poor prognosis, and limited response to immune checkpoint inhibitors, primarily attributable to its immunologically “cold” tumor microenvironment (TME). To profile the immunological landscape of HGSOC, we conducted single-cell RNA sequencing (scRNA-seq) on 84,065 cells from tumor tissues of eight treatment-naïve patients and one normal ovarian tissue, identifying six major cell clusters and revealing substantial immune cell infiltration. Further analysis of CD8⁺ T cells identified two key subpopulations—precursor and terminally exhausted T cells—and delineated their developmental trajectories. The accumulation of exhausted CD8⁺ T cells (Tex) suggested an immunosuppressive TME. Integrated trajectory inference and high-dimensional weighted gene co-expression network analysis (hdWGCNA) identified CCL3 as a novel hub gene specifically expressed in Tex cells. Communication analysis suggested that Tex cells may interact with M2 macrophages via the CCL3–CCR1 ligand–receptor axis. Functional validation confirmed that: (1) secretomes from Tex cells—but not effector T cells—significantly promoted M2 polarization in both THP-1 and bone marrow-derived macrophages (CD206⁺ THP-1: 83.8% vs. 51.4%, p < 0.001; CD206⁺ BMDM: 72.4% vs. 41.5%, p < 0.001); and (2) recombinant CCL3 acted synergistically with IL-4/IL-10 to further enhance M2 polarization (59.2% vs. 37.7%, p = 0.008). Collectively, our findings unveil a previously unrecognized immunoregulatory axis whereby exhausted CD8⁺ T cells drive immunosuppression via CCL3–CCR1–mediated communication with M2 macrophages, presenting a promising therapeutic target to reverse the immune-cold TME in HGSOC.

We aimed to investigate the role of large tumor suppressor kinase 2 (LATS2) in cisplatin (DDP) sensitivity in ovarian cancer. Bioinformatic analysis explored LATS2 expression, pathways, and regulators. Quantitative reverse transcription-PCR measured LATS2 and KLF4 mRNA levels. Dual-luciferase and chromatin immunoprecipitation assays confirmed their binding relationship. Cell viability, half maximal inhibitory concentration (IC50) values, cell cycle, and DNA damage were assessed using CCK-8, flow cytometry, and comet assays. Western blot analyzed protein expression. The effect of LATS2 on the sensitivity of ovarian cancer to DDP was verified in vivo. LATS2 and KLF4 were downregulated in ovarian cancer, with LATS2 enriched in cell cycle, DNA replication, and mismatch repair pathways. KLF4, an upstream regulator of LATS2, bound to its promoter. Overexpressing LATS2 increased G1-phase cells, reduced cell viability and IC50 values, and induced DNA damage. Silencing KLF4 alone showed the opposite effect on LATS2 overexpression. Knocking out LATS2 reversed the effects of KLF4 overexpression on cell viability, cell cycle, IC50 values, and DNA damage in ovarian cancer cells. Inhibiting LATS2 inactivated the Hippo-YAP signaling pathway. In vivo experiments showed that overexpression of LATS2 enhanced the sensitivity of ovarian cancer to DDP. KLF4 activates LATS2 via DNA damage to enhance DDP sensitivity in ovarian cancer, providing a potential target for improving treatment outcomes.

Chemoresistance, the primary cause of mortality among ovarian cancer (OC) patients, is a multifaceted process encompassing numerous biological phenomena. As sequencing technology continues to advance, single-cell sequencing has surfaced as a potent strategy to elucidate the pathogenesis of OC. We examined single-cell sequencing data derived from five OC samples (three resistant and two sensitive) and identified an epithelial subcluster associated with chemotherapy resistance and poor prognosis. Using GSVA and cell communication analysis, we explored the unique biological functions and communication characteristics of this resistant subcluster. We performed high dimensional weighted gene co-expression network analysis and differential expression analysis to identify the hub genes of c3. Lastly, we investigated the correlation between the hub gene, CLIC3, and chemotherapy drug sensitivity. We also validated their involvement in specific pathways using TCGA data. The effects and primary mechanism to chemoresistance of CLIC3 was explored. We identified a cell subcluster, denoted as c3, strongly linked to chemoresistance and poor prognosis in OC. This subcluster demonstrated a correlation with both extracellular matrix (ECM) formation and angiogenesis signature, with CLIC3 identified as its key marker. The expression levels of CLIC3 exhibit a significant association with the sensitivity to various chemotherapeutic drugs in OC. Mechanistically, CLIC3 increases OC resistance to cisplatin by promoting integrin β1 redistribution and PI3K-AKT pathway. This study offers a novel insight into the progression and chemoresistance of OC. Additionally, we identified a specific cell cluster highly associated with chemoresistance. The marker for this cluster, CLIC3, increases OC resistance to cisplatin by promoting integrin β1 redistribution and PI3K-AKT pathway and holds significant potential as a new therapeutic target for OC.

Tumor-associated macrophages (TAMs) play a pivotal role in immune suppression, tumor progression, and metastasis within the tumor microenvironment (TME) of ovarian cancer. While TAMs are known to promote T-cell dysfunction, the precise molecular mechanisms governing this process remain poorly understood. Here, we performed an integrated analysis of six high-grade serous ovarian cancer (HGSOC) single-cell sequencing datasets to investigate the molecular and functional diversity of TAMs in HGSOC. We identified an SPP1+ TAM subpopulation enriched in HGSOC and strongly associated with poor prognosis. These macrophages promoted T-cell exhaustion via the SPP1-CD44 axis, which emerged as the principal mediator of immune suppression. Functional assays demonstrated that SPP1 secreted by TAMs drove T-cell exhaustion, weakening anti-tumor immunity. Blocking either SPP1 or CD44 effectively reversed T-cell exhaustion, restored CD8+ T-cell functionality, and suppressed tumor growth in vivo. Furthermore, molecular docking and dynamics simulations identified nilotinib as a potential SPP1 inhibitor, exhibiting strong binding affinity and stability. In vitro assays confirmed that nilotinib reduced PD-1 expression in Jurkat cells induced by M2-type macrophages, underscoring its therapeutic potential in reversing T-cell exhaustion in ovarian cancer. The research demonstrates that SPP1+ TAMs drive immune suppression and T-cell exhaustion in ovarian cancer via the SPP1-CD44 axis, highlighting this pathway as a promising therapeutic target for reprogramming the immune microenvironment and improving patient outcomes.

Purpose: Platinum-based chemotherapy is effective but limited by resistance in high-grade serous ovarian cancer (HGSOC). Single-cell RNA sequencing (scRNA-seq) can reveal tumour cell heterogeneity and subclonal differentiation. We aimed to analyze resistance mechanisms and potential targets in HGSOC using scRNA-seq. Methods: We performed 10× genomics scRNA-seq sequencing on tumour tissues from 3 platinum-sensitive and 3 platinum-resistant HGSOC patients. We analyzed cell subcluster communication networks and spatial distribution using cellchat. We performed RNA-seq analysis on TACSTD2, a representative resistance gene in the E0 subcluster, to explore its molecular mechanism. Results: Epithelial cells, characterized by distinct chemotherapy resistance traits and highest gene copy number variations, revealed a specific cisplatin-resistant cluster (E0) associated with poor prognosis. E0 exhibited malignant features related to resistance, fostering growth through communication with fibroblasts and endothelial cells. Spatially, E0 promoted fibroblasts to protect tumour cells and impede immune cells infiltration. Furthermore, TACSTD2 was identified as a representative gene of the E0 subcluster, elucidating its role in platinum resistance through the Rap1/PI3K/AKT pathway. Conclusions: Our study reveals a platinum-resistant epithelial cell subcluster E0 and its association with TACSTD2 in HGSOC, uncovers new insights and evidence for the platinum resistance mechanism, and provides new ideas and targets for the development of therapeutic strategies against TACSTD2+ epithelial cancer cells.

Evidence concerning PM1 exposure, maternal blood pressure (BP), and hypertensive disorders of pregnancy (HDP) is sparse. We evaluated the associations using 105,063 participants from a nationwide cohort. PM1 concentrations were evaluated using generalized additive model. BP was measured according to the American Heart Association recommendations. Generalized linear mixed models were used to assess the PM1-BP/HDP associations. Each 10 μg/m3 higher first-trimester PM1 was significantly associated with 1.696 mmHg and 1.056 mmHg higher first-trimester SBP and DBP, and with 11.4% higher odds for HDP, respectively. The above associations were stronger among older participants (> 35 years) or those educated longer than 17 years or those with higher household annual income (> 400,000 CNY). To conclude, first-trimester PM1 were positively associated with BP/HDP, which may be modified by maternal age, education level, and household annual income. Further research is warranted to provide more information for both health management of HDP and environmental policies enactment.

Abstract Background Metastasis, the leading cause of cancer-related death in patients diagnosed with ovarian cancer (OC), is a complex process that involves multiple biological effects. With the continuous development of sequencing technology, single-cell sequence has emerged as a promising strategy to understand the pathogenesis of ovarian cancer. Methods Through integrating 10 × single-cell data from 12 samples, we developed a single-cell map of primary and metastatic OC. By copy-number variations analysis, pseudotime analysis, enrichment analysis, and cell–cell communication analysis, we explored the heterogeneity among OC cells. We performed differential expression analysis and high dimensional weighted gene co-expression network analysis to identify the hub genes of C4. The effects of RAB13 on OC cell lines were validated in vitro. Results We discovered a cell subcluster, referred to as C4, that is closely associated with metastasis and poor prognosis in OC. This subcluster correlated with an epithelial–mesenchymal transition (EMT) and angiogenesis signature and RAB13 was identified as the key marker of it. Downregulation of RAB13 resulted in a reduction of OC cells migration and invasion. Additionally, we predicted several potential drugs that might inhibit RAB13. Conclusions Our study has identified a cell subcluster that is closely linked to metastasis in OC, and we have also identified RAB13 as its hub gene that has great potential to become a new therapeutic target for OC.

Background Ovarian cancer (OC) is one of the commonest and deadliest diseases that threaten the health of women worldwide. It is essential to find out its pathogenic mechanisms and therapeutic targets for OC patients. Although NUF2 (Ndc80 kinetochore complex component) has been suggested to play an important role in the development of many cancers, but little is known about its function and the roles of proteins that regulate NUF2 in OC. This study aimed to investigate the effect of NUF2 on the tumorigenicity of OC and the activities of proteins that interact with NUF2. Methods Oncomine database and immunohistochemical (IHC) staining were used to evaluate the expression of NUF2 in OC tissues and normal tissues respectively. Normal ovarian epithelial cell lines (HOSEpiC) and OC cell lines (OVCAR3、HEY、SKOV3) were cultured. Western blot was applied to analyze the expression of NUF2 in these cell lines. Small interfering RNA (siRNA) was used to silence the expression of NUF2 in OC cell lines, SKOV3 and HEY. Gene Set Variation Analysis (GSVA), Gene Set Enrichment Analysis (GSEA), the CCK-8 method, colony formation assay and flow cytometry were conducted to analyze the biological functions of NUF2 in vitro. OC subcutaneous xenograft tumor models were used for in vivo tests. Immunoprecipitation and mass spectrometry (IP/MS) were performed to verify the molecular mechanisms of NUF2 in OC. IP, immunofluorescence, IHC staining, and Gene Expression Profiling Interactive Analysis platform (GEPIA) were used to analyze the relationship between HNRNPA2B1 and NUF2 in OC cells. SiRNA was used to silence the expression of HNRNPA2B1 in SKOV3 cells, reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay and western blot were used to detect the effect of HNRNPA2B1 on NUF2. GEPIA, The Cancer Genome Atlas (TCGA) database, GSEA and western blot were used to detect the potential signaling pathways related to the roles of HNRNPA2B1 and NUF2 in OC cells. Results Our results showed high NUF2 expression in OC tissues and OC cell lines, which was associated with shorter overall survival and progression-free survival in patients. NUF2 depletion by siRNA suppressed the proliferation abilities and induced cell apoptosis of OC cells in vitro, and impeded OC growth in vivo. Mechanistically, NUF2 interacted with HNRNPA2B1 and activated the PI3K/AKT/mTOR signaling pathway in OC cells. Conclusion NUF2 could serve as a prognostic biomarker, and regulated the carcinogenesis and progression of OC. Moreover, NUF2 may interact with HNRNPA2B1 by activating the PI3K/AKT/mTOR signaling pathway to promote the development of OC cells. Our present study supported the key role of NUF2 in OC and suggested its potential as a novel therapeutic target.

ObjectiveCongenital heart disease (CHD) is complex in its etiology. Its genetic causes have been investigated, whereas the non-genetic factor related studies are still limited. We aimed to identify dominant parental predictors and develop a predictive model and nomogram for the risk of offspring CHD.MethodsThis was a retrospective study from November 2017 to December 2021 covering 44,578 participants, of which those from 4 hospitals in eastern China were assigned to the development cohort and those from 5 hospitals in central and western China were used as the external validation cohort. Univariable and multivariable analyses were used to select the dominant predictors of CHD among demographic characteristics, lifestyle behaviors, environmental pollution, maternal disease history, and the current pregnancy information. Multivariable logistic regression analysis was used to construct the model and nomogram using the selected predictors. The predictive model and the nomogram were both validated internally and externally. A web-based nomogram was developed to predict patient-specific probability for CHD.ResultsDominant risk factors for offspring CHD included increased maternal age [odds ratio (OR): 1.14, 95% CI: 1.10–1.19], increased paternal age (1.05, 95% CI: 1.02–1.09), maternal secondhand smoke exposure (2.89, 95% CI: 2.22–3.76), paternal drinking (1.41, 95% CI: 1.08–1.84), maternal pre-pregnancy diabetes (3.39, 95% CI: 1.95–5.87), maternal fever (3.35, 95% CI: 2.49–4.50), assisted reproductive technology (2.89, 95% CI: 2.13–3.94), and environmental pollution (1.61, 95% CI: 1.18–2.20). A higher household annual income (100,000–400,000 CNY: 0.47, 95% CI: 0.34–0.63; > 400,000 CNY: 0.23, 95% CI: 0.15–0.36), higher maternal education level (13–16 years: 0.68, 95% CI: 0.50–0.93; ≥ 17 years: 0.87, 95% CI: 0.55–1.37), maternal folic acid (0.21, 95% CI: 0.16–0.27), and multivitamin supplementation (0.33, 95% CI: 0.26–0.42) were protective factors. The nomogram showed good discrimination in both internal [area under the receiver-operating-characteristic curve (AUC): 0.843] and external validations (development cohort AUC: 0.849, external validation cohort AUC: 0.837). The calibration curves showed good agreement between the nomogram-predicted probability and actual presence of CHD.ConclusionWe revealed dominant parental predictors and presented a web-based nomogram for the risk of offspring CHD, which could be utilized as an effective tool for quantifying the individual risk of CHD and promptly identifying high-risk population.

Background Spontaneous abortion is one of the prevalent adverse reproductive outcomes, which seriously threatens maternal health around the world. Objective The current study is aimed to evaluate the association between maternal age and risk for spontaneous abortion among pregnant women in China. Methods This was a case-control study based on the China Birth Cohort, we compared 338 cases ending in spontaneous abortion with 1,352 controls resulting in normal live births. The main exposure indicator and outcome indicator were maternal age and spontaneous abortion, respectively. We used both a generalized additive model and a two-piece-wise linear model to determine the association. We further performed stratified analyses to test the robustness of the association between maternal age and spontaneous abortion in different subgroups. Results We observed a J-shaped relationship between maternal age and spontaneous abortion risk, after adjusting for multiple covariates. Further, we found that the optimal threshold age was 29.68 years old. The adjusted odds ratio (95% confidence interval) of spontaneous abortion per 1 year increase in maternal age were 0.97 (0.90–1.06) on the left side of the turning point and 1.25 (1.28–1.31) on the right side. Additionally, none of the covariates studied modified the association between maternal age and spontaneous abortion ( P > 0.05). Conclusions Advanced maternal age (>30 years old) was significantly associated with increased prevalence of spontaneous abortion, supporting a J-shaped association between maternal age and spontaneous abortion.

NUF2 is responsible for the attachment of kinetochore-microtubules and proper chromosome segregation during mitosis. NUF2 is highly expressed in hepatocellular carcinoma, pancreatic cancer, esophageal cancer, non-small cell lung cancer, breast cancer and other tumor tissues and cells, and can be used as prognostic markers. Further clarifying the relationship between NUF2 and tumor prognosis can provide help for the application of NUF2 in prognostic assessment of cancers.

Background Ovarian cancer (OC) is a fatal gynecological tumor with high mortality and poor prognosis. Yet, its molecular mechanism is still not fully explored, and early prognostic markers are still missing. In this study, we assessed carcinogenicity and clinical significance of family with sequence similarity 83 member D (FAM83D) in ovarian cancer by integrating single-cell RNA sequencing (scRNA-seq) and a prognostic model. Methods A 10x scRNA-seq analysis was performed on cells from normal ovary and high-grade serous ovarian cancer (HGSOC) tissue. The prognostic model was constructed by Lasso-Cox regression analysis. The biological function of FAM83D on cell growth, invasion, migration, and drug sensitivity was examined in vitro in OC cell lines. Luciferase reporter assay was performed for binding analysis between FAM83D and microRNA-138-5p (miR-138-5p). Results Our integrative analysis identified a subset of malignant epithelial cells (C1) with epithelial-mesenchymal transition (EMT) and potential hyperproliferation gene signature. A FAM83D+ malignant epithelial subcluster (FAM83D+ MEC) was associated with cell cycle regulation, apoptosis, DNA repair, and EMT activation. FAM83D resulted as a viable prognostic marker in a prognostic model that efficiently predict the overall survival of OC patients. FAM83D downregulation in SKOV3 and A2780 cells increased cisplatin sensitivity, reducing OC cell proliferation, migration, and invasion. MiR-138-5p was identified to regulate FAM83D’s carcinogenic effect in OC cells. Conclusions Our findings highlight the importance of miR-138 -5p/FAM83D/EMT signaling and may provide new insights into therapeutic strategies for OC.

Objective:To explore the mechanism of glycine dehydrogenase (GLDC) regulating the proliferation and apoptosis of ovarian cancer cells through PI3K/Akt/mTOR pathway.Methods:RNA interference method was used to silence the expression of GLDC in ovarian cancer cell lines HEY and SK-OV-3. The HEY and SK-OV-3 cells were divided into si-control group (transfected with siRNA-control), si-GLDC#1 group (trans-fected with siRNA-GLDC#1) and si-GLDC#2 group (transfected with siRNA-GLDC#2). The expression level of GLDC and the protein phosphorylation level of PI3K/Akt/mTOR were detected by Western blotting. Cell proli-feration, migration and apoptosis were detected by CCK-8 method, Transwell chamber test, cell scratch test and flow cytometry.Results:The relative expression levels of GLDC in the si-control group, si-GLDC#1 group amd si-GLDC#2 group of HEY cells were 1.00±0.01, 0.68±0.10, 0.80±0.08, and there was a statistically significant difference ( F=13.80, P=0.006). The relative expression levels of GLDC in the si-control group, si-GLDC#1 group and si-GLDC#2 group of SK-OV-3 cells were 1.02±0.01, 0.58±0.17, 0.60±0.25, and there was a statistically significant difference ( F=6.08, P=0.036). The absorbance ( A) values in the si-control group, si-GLDC#1 group and si-GLDC#2 group of HEY cells were 1.04±0.03, 0.91±0.02, 0.82±0.01 at 24 h after transfection, 1.53±0.13, 1.30±0.03, 1.29±0.07 at 48 h after transfection, 1.44±0.08, 1.25±0.01, 1.15±0.03 at 72 h after transfection, and there were statistically significant differences ( F=83.14, P<0.001; F=8.96, P=0.007; F=29.55, P<0.001). Further pairwise comparison showed that the proliferation abilities of the si-GLDC#1 and si-GLDC#2 group at 24, 48 and 72 h were significantly lower than those of the si-control group (all P<0.05). In HEY cells, the migration numbers of cells in the si-control group, si-GLDC#1 group and si-GLDC#2 group were 57.33±6.43, 27.67±5.13 and 30.67±2.31, and there was a statistically significantly difference ( F=32.88, P=0.001). The migration numbers of cells in the si-GLDC#1 group and si-GLDC#2 group were significantly lower than that in the si-control group ( P<0.001; P=0.001). Similar results were also observed in SK-OV-3 cells. In SK-OV-3 cells, the scratch healing rates in the si-control group, si-GLDC#1 group and si-GLDC#2 group were (51.27±1.59)%, (26.35±2.94)% and (26.34±7.69)%, and there was a statistically significant difference ( F=26.54, P=0.001). The scratch healing rates in the si-GLDC#1 group and si-GLDC#2 group were significantly lower than that in the si-control group (both P=0.001). In HEY cells, the apoptosis rates in the si-control group, si-GLDC#1 group and si-GLDC#2 group were (7.11±0.82)%, (10.44±1.50)%, (17.39±1.55)%, and there was a statistically significantly difference ( F=46.52, P<0.001). The apoptosis rates in the si-GLDC#1 group and si-GLDC#2 group were significantly higher than that in the si-control group ( P=0.022; P<0.001). Similar results were also observed in SK-OV-3 cells. In HEY cells, there was no significant difference in total PI3K protein in the si-control group, si-GLDC#1 group and si-GLDC#2 group ( F=0.54, P=0.631), but there were significant differences in pAkt/Akt and pmTOR/mTOR levels ( F=22.14, P=0.016; F=10.57, P=0.044). The pAkt/Akt and pmTOR/mTOR levels in the si-GLDC#1 group and si-GLDC#2 group were significantly lower than those in the si-control group ( P=0.015, P=0.008; P=0.039, P=0.023). Similar results were also observed in SK-OV-3 cells. Conclusion:In ovarian cancer cells, GLDC silencing can inhibit cell proliferation and promote apoptosis by inhibiting the PI3K/Akt/mTOR pathway.

As label-free biomarkers, electrical properties of single cells have been widely used for cell-type classification and cell-status evaluation. However, as intrinsic bioelectrical markers, previously reported membrane capacitance and cytoplasmic resistance (e.g., specific membrane capacitance Cspecific membrane and cytoplasmic conductivity σcytoplasm ) of tumor subtypes were derived from tens of single cells, lacking statistical significance due to low cell numbers. In this study, tumor subtypes were constructed based on phenotype (treatment with 4-methylumbelliferone) or genotype (knockdown of ROCK1) modifications and then aspirated through a constriction-channel based impedance flow cytometry to characterize single-cell Cspecific membrane and σcytoplasm . Thousands of single tumor cells with phenotype modifications were measured, resulting in significant differences in 1.64 ± 0.43 μF/cm2 vs. 1.55 ± 0.47 μF/cm2 of Cspecific membrane and 0.96 ± 0.37 S/m vs. 1.24 ± 0.47 S/m of σcytoplasm for 95C cells (792 cells of 95C-control vs. 1529 cells of 95C-pheno-mod); 2.56 ± 0.88 μF/cm2 vs. 2.33 ± 0.56 μF/cm2 of Cspecific membrane and 0.83 ± 0.18 S/m vs. 0.93 ± 0.25 S/m of σcytoplasm for H1299 cells (962 cells of H1299-control vs. 637 cells of H1299-pheno-mod). Furthermore, thousands of single tumor cells with genotype modifications were measured, resulting in significant differences in 3.82 ± 0.92 vs. 3.18 ± 0.47 μF/cm2 of Cspecific membrane and 0.47 ± 0.05 vs. 0.52 ± 0.05 S/m of σcytoplasm (1100 cells of A549-control vs. 1100 cells of A549-geno-mod). These results indicate that as intrinsic bioelectrical markers, specific membrane capacitance and cytoplasmic conductivity can be used to classify tumor subtypes.

Cyclin Y (CCNY) is a novel cyclin and highly conserved in metazoan species. Previous studies from our and other laboratory indicate that CCNY play a crucial role in tumor progression. There are two CCNY isoform which has different subcellular distributions, with cytoplasmic isoform (CCNYc) and membrane distribution isoform (CCNYm). However, the expression and function of CCNY isoforms is still unclear. We firstly found CCNYc was expressed in natural lung cancer tissue and cells through the subcellular distribution. Co-IP and immunofluorescence showed that both CCNYm and CCNYc could interact with PFTK1. Further studies illustrated that CCNYc but not CCNYm enhanced cell migration and invasion activity both in vivo and vitro. The function of CCNYc could be inhibited by suppression of PFTK1 expression. In addition, our data indicated that tropomyosin 4 (TPM4), a kind of actin-binding proteins, was down-regulated by suppression of CCNY. F-actin assembly could be controlled by CCNYc as well as PFTK1 and TPM4. As a result, CCNY was mainly expressed in lung cancer. CCNYc could promote cell motility and invasion. It indicated that CCNYc/PFTK1 complex could promote cell metastasis by regulating the formation of F-actin via TPM4.

BACKGROUND:Epithelial ovarian cancer (EOC), as a lethal malignancy in women, is often diagnosed as advanced stages. In contrast, intermediating between benign and malignant tumors, ovarian low malignant potential (LMP) tumors show a good prognosis. However, the differential diagnosis of the two diseases is not ideal, resulting in delays or unnecessary therapies. Therefore, unveiling the molecular differences between LMP and EOC may contribute to differential diagnosis and novel therapeutic and preventive policies development for EOC.METHODS:In this study, three microarray data (GSE9899, GSE57477 and GSE27651) were used to explore the differentially expressed genes (DEGs) between LMP and EOC samples. Then, 5 genes were screened by protein-protein interaction (PPI) network, receiver operating characteristic (ROC), survival and Pearson correlation analysis. Meanwhile, chemical-core gene network construction was performed to identify the potential drugs or risk factors for EOC based on 5 core genes. Finally, we also identified the potential function of the 5 genes for EOC through pathway analysis.RESULTS:Two hundred thirty-four DEGs were successfully screened, including 81 up-regulated genes and 153 down-regulated genes. Then, 5 core genes (CCNB1, KIF20A, ASPM, AURKA, and KIF23) were identified through PPI network analysis, ROC analysis, survival and Pearson correlation analysis, which show better diagnostic efficiency and higher prognostic value for EOC. Furthermore, NetworkAnalyst was used to identify top 15 chemicals that link with the 5 core genes. Among them, 11 chemicals were potential drugs and 4 chemicals were risk factors for EOC. Finally, we found that all 5 core genes mainly regulate EOC development via the cell cycle pathway by the bioinformatic analysis.CONCLUSION:Based on an integrated bioinformatic analysis, we identified potential biomarkers, risk factors and drugs for EOC, which may help to provide new ideas for EOC diagnosis, condition appraisal, prevention and treatment in future.

目的:研究沉默细胞分裂相关基因NUF2的表达对卵巢癌细胞侵袭及迁移的影响,并初步探讨其潜在的分子作用机制.方法:用基因表达谱数据动态分析(GEPIA)和实时荧光定量PCR(qRT-PCR)分别检测卵巢癌组织和细胞中NUF2的表达情况;将卵巢癌HEY、SKOV3细胞分为空白对照组、control siRNA(si-control)组和NUF2 siRNA(si-NUF2)组,用qRT-PCR检测各组细胞的NUF2 mRNA表达水平以验证转染效果;Transwell小室实验和细胞划痕实验检测沉默NUF2后各组细胞侵袭、迁移能力的改变;蛋白印迹法检测各组细胞中Notch通路相关蛋白Notch1、Hes1的表达水平.结果:NUF2在卵巢癌组织或细胞中均高表达,差异均有统计学意义(P<0.05);与空白对照组和si-control组相比,si-NUF2组细胞中NUF2 mRNA表达水平显著下降(P<0.05),侵袭、迁移细胞数明显减少(P<0.05),Notch1和Hes1蛋白表达降低.结论:沉默NUF2表达可抑制卵巢癌细胞侵袭、迁移能力,其分子作用机制与抑制Notch信号通路有关.

BACKGROUND:PFTK1, a novel cyclin-dependent kinase, plays pivotal roles in tumorigenesis. Cell motility and invasiveness could be enhanced by PFTK1 in various tumors. However, the function of PFTK1 in NSCLC metastasis remains unclear. In this study, the potential role of PFTK1 in NSCLC metastasis was determined.MATERIALS AND METHODS:In this study, the potential function of PFTK1 in lung cancer patients was analyzed with the Kaplan-Meier plotter database. RNA interference-mediated knockdown of PFTK1 was established in two NSCLC cell lines (H1299 and 95C) to explore the role of PFTK1 in NSCLC. The efficacy of downregulation of PFTK1 was examined by Western blot and immunofluorescence. The role of PFTK1 in cell migration and invasion ability was detected by wound healing and transwell assays. The protein levels in lung cancer cells were determined by Western blot. Immunofluorescence analysis was used to evaluate the structure of filamentous actin.RESULTS:Overexpression of PFTK1 was associated with the poor survival prognosis in NSCLC patients. PFTK1 knockdown cells were constructed successfully. Suppression of PFTK1 significantly inhibited the cell migration and invasion in H1299 and 95C cells. Notably, after PFTK1 downregulation, the epithelial-mesenchymal transition (EMT) markers vimentin, ZEB1 and β-catenin were obviously decreased. Additionally, immunofluorescence analysis indicated that PFTK1 downregulation remarkably induced filamentous actin depolymerization.CONCLUSION:In summary, PFTK1 could significantly promote lung cancer metastasis through changing EMT progress and modulating intracellular cytoskeleton F-actin expression. Taken together, our findings indicated that PFTK1 might serve as a novel therapeutic target for the inhibition of NSCLC progression.

Background: Laryngeal carcinoma is a common cancer among head and neck tumors, accounting for 0.5-1% new cancer cases or deaths of all tumors throughout the body. Despite improvements in diagnostic and therapy, the prognosis of laryngeal carcinoma patients still remains poor. Thus, it is very important to identify the biomarkers involved in the molecular pathogenesis of laryngeal carcinoma. Cyclin Y (CCNY) is a conserved cell cycle regulator that acts as a growth factor in many cancers. The clinical significance of CCNY in laryngeal carcinoma remains unknown. The function of CCNY in laryngocarcinoma was studied in this paper. Materials and Methods: CCNY knock-out cells were constructed by CRISPR/CAS9 technique. CCNY overexpression cells were also constructed based on CCNY knock-out cells. Cell growth ability was detected by MTS assay, high-content cell analysis, colony formation assays, and anchorage-independent growth assays. The protein levels in laryngocarcinoma cells were determined by Western blot. The role of CCNY in cell cycle progression was evaluated by flow cytometry. Results: CCNY knock-out cells and CCNY up-regulation cell models were obtained successfully. Suppression of CCNY expression inhibited Hep2 cell growth. Cell growth was enhanced by the up-regulation of CCNY. The percentage of cells in G1 phase was altered when CCNY expression was down-regulated or up-regulated. The phosphorylation level of MEK and ERK as well as cyclin E protein level was also regulated by the expression level of CCNY. Conclusion: In laryngocarcinoma cell line Hep2 cells, cell proliferation was controlled by CCNY. The expression of CCNY was involved in the cell cycle progress of Hep2 cells. It indicated that CCNY could promote cell growth by activating MEK/ERK/cyclin E signaling pathway.