TCGA Database Research Articles

SEH1L siliencing induces ferroptosis and suppresses hepatocellular carcinoma progression via ATF3/HMOX1/GPX4 axis

SEH1 like nucleoporin (SEH1L) is an important component of nuclear pore complex (NPC), which is crucial in the regulation of cell division. However, the interrelation between SEH1L expression and tumor progression is less studied. In this research, we performed a systematic bioinformatic analysis about SEH1L using TCGA, Timer 2.0, Cbioportal, UCLAN and CellMiner™ databases in pan-cancer. Besides, we further validated the bioinformatic results through in vitro and in vivo experiments in HCC, including transcriptome sequencing, real-time quantitative PCR (RT-qPCR), western blotting (WB), immunohistochemistry (IHC), cell proliferation assays, clone formation, EdU, transwell, flow cytometry and subcutaneous tumor model. Our results suggested that SEH1L was significantly up-regulated and related to poor prognosis in most cancers, and may serve as a potential biomarker. SEH1L could promote HCC progression in vitro and in vivo. Besides, the next generation sequencing suggested that 684 genes was significantly up-regulated and 678 genes was down-regulated after the knock down of SEH1L. SEH1L siliencing could activate ATF3/HMOX1/GPX4 axis, decrease mitochondrial membrane potential and GSH, but increase ROS and MDA, and these effects could be reversed by the knock down of ATF3. This study indicated that SEH1L siliencing could induce ferroptosis and suppresses hepatocellular carcinoma (HCC) progression via ATF3/HMOX1/GPX4 axis.

The immunotherapy mechanism of Hedyotis Diffusae Herba in treating liver cancer: a study based on network pharmacology, bioinformatics, and experimental validation.

Liver cancer is a malignant tumor that develops on or inside the liver. Hedyotis diffusa Willd (HDW) plays a significant role in anti-tumor activities; however, its mechanism against liver cancer remains unclear. This study aims to evaluate the immunotherapeutic mechanism of HDW in treating liver cancer through network pharmacology, bioinformatics analysis, and experimental validation. Network pharmacology was utilized to identify the active components and potential targets of HDW from the TCMSP database. A potential target protein-protein interaction (PPI) network was constructed using the STRING database, followed by function and pathway enrichment analysis of the targets using GO and KEGG methods. In addition, the key targets for HDW against liver cancer were identified using five different algorithms in Cytoscape. The TCGA and HPA databases were used to assess the mRNA and protein expression of core target genes in normal liver and liver cancer tissues and their relationship with overall survival in liver cancer, as well as their role in immune infiltration. Molecular docking between the core components of HDW and the core targets was performed using PyMOL software. The effects of HDW on the proliferation and apoptosis of liver cancer cells were examined using MTT and flow cytometry. The regulatory effects of the core component quercetin on core targets were validated using RT-qPCR and Western blot. A total of 163 potential targets were identified by searching for intersections among 7 types of active components and all potential and liver cancer targets. PPI network analysis revealed the core targets IL6 and TNF. GO enrichment analysis involved 2089 biological processes, 76 cellular components, and 196 molecular functions. KEGG enrichment analysis suggested that the anti-cancer effects of HDW might be mediated by the AGE-RAGE signaling pathway, IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, and NF-κB signaling pathway. Database validation of key targets showed that mRNA and protein expression results for the IL6 gene were contradictory, while those for the TNF gene were consistent, both being underexpressed in liver cancer. Importantly, the expression of IL6 and TNF was related to the infiltration of 24 types of immune cells, with the highest correlation with macrophages. Molecular docking showed that IL6 and TNF had high binding stability with quercetin, with binding energies of - 7.4 and - 6.0kJ∙mol-1, respectively. Experimental validation showed that quercetin inhibited liver cancer cell proliferation and promoted apoptosis in a dose-dependent manner, with protein results indicating that quercetin downregulated the mRNA and protein expression of IL6 and TNF, and upregulated key proteins in the AGE-RAGE signaling pathway, AGEs, and RAGE. This study comprehensively elucidates the activity, potential targets, and molecular mechanisms of HDW against liver cancer, providing a promising strategy for the scientific basis and treatment mechanism of traditional Chinese medicine in treating liver cancer.

The Biological Function of POLA2 in Hepatocellular Carcinoma.

The role and prognostic value of POLA2 in liver cancer were comprehensively analyzed through TCGA, GEO, and ICGC databases, and the role of POLA2 in liver cancer cells and the regulatory mechanism involved were further verified through cell experiments. Hepatocellular carcinoma (HCC) is the most prevalent malignancy with high morbidity and mortality. Consequently, it is critical to identify robust and reliable predictive biomarkers and therapeutic targets for HCC patients. POLA2 is involved in the regulation of various tumors, but the specific role of POLA2 in HCC has not been reported. The regulatory role and prognostic value of POLA2 in HCC were determined by bioinformatics techniques and cell experiments. The specific role and prognostic value of POLA2 in HCC were comprehensively analyzed by combining the expression data of POLA2 in TCGA, GEO, and ICGC databases and clinical data. In clinical samples, the expression of POLA2 in liver cancer was verified by QPCR. Further, the regulatory role of POLA2 in HCC was explored through cell experiments such as CCK-8, clonal formation experiment, EDU cell proliferation experiment, and flow cytometry. In terms of mechanism exploration, western blot was used to verify the specific regulatory mechanism that POLA2 participated in. Finally, the relationship between POLA2 and immune invasion of HCC was analyzed by using the TIMER database. A POLA2 expression and prognosis analysis of HCC patients was conducted using the TCGA, GEO, and ICGC databases. We hypothesized that POLA2 might be one of the key factors contributing to the HCC progression. According to a combined analysis of TCGA, ICGC, and GEO databases, POLA2 was highly expressed in HCC. This was further confirmed in clinical samples using the qPCR. POLA2 knockdown was also performed in vitro on HCC cell lines to study the changes in their biological behavior. We confirmed that POLA2 was associated with HCC proliferation by CCK-8, Colony Formation, and EDU assay. We verified the POLA2's involvement in cell cycle regulation using flow techniques. The relationship between POLA2 and PI3K/AKT/mTOR pathway was explored using Western Blotting experiments regarding its mechanism. Further analysis revealed that the POLA2 expression was significantly associated with HCC immune infiltration. Our study demonstrated POLA2's importance in HCC development and progression and its potential role as a biomarker for disease progression on multiple levels. POLA2 has an important role in regulating the cell cycle and cell proliferation. By interfering with the cell cycle and proliferation, HCC cell growth is inhibited. Furthermore, POLA2 expression was significantly associated with immune infiltration. POLA2 may play a role in HCC immunotherapy based on its correlation with several immune cell types' genetic markers. The findings of this study are expected to lead to new anticancer strategies for HCC.

Development of a disulfidptosis-related lncRNA prognostic signature for enhanced prognostic assessment and therapeutic strategies in lung squamous cell carcinoma

Limited treatment options and poor prognosis present significant challenges in the treatment of lung squamous cell carcinoma (LUSC). Disulfidptosis impacts cancer progression and prognosis. We developed a prognostic signature using disulfidptosis-related long non-coding RNAs (lncRNAs) to predict the prognosis of LUSC patients. Gene expression matrices and clinical information for LUSC were downloaded from the TCGA database. Co-expression analysis identified 209 disulfidptosis-related lncRNAs. LASSO-Cox regression analysis identified nine key lncRNAs, forming the basis for establishing a prognostic model. The model’s validity was confirmed by Kaplan–Meier and ROC curves. Cox regression analysis identified the risk score (RS) as an independent prognostic factor inversely correlated with overall survival. A nomogram based on the RS demonstrated good predictive performance for LUSC patient prognosis. The relationship between RS and immune function was explored using ESTIMATE, CIBERSORT, and ssGSEA algorithms. According to the TIDE database, a negative correlation was found between RS and immune therapy responsiveness. The GDSC database revealed that 49 drugs were beneficial for the low-risk group and 25 drugs for the high-risk group. Silencing C10orf55 expression in SW900 cells reduced invasiveness and migration potential. In summary, this lncRNA model based on TCGA-LUSC data effectively predicts prognosis and assists clinical decision-making.

The role of RRS1 in breast cancer cells metastasis and AEG-1/AKT/c-Myc signaling pathway.

Breast cancer is the most common malignant tumor in women. Recurrence, metastasis, and chemotherapy resistance are the main causes of death in breast cancer patients. The inhibition of breast cancer metastasis is of great significance for prolonging its survival. Ribosome biogenesis regulatory protein homolog (RRS1) is overexpressed in breast cancer tissues and is involved in regulating the carcinogenic process of breast cancer cells. However, the exact signaling pathway and molecular mechanism of RRS1 promoting breast cancer metastasis are not fully understood. Hence, the primary objective of our study is to investigate the correlation between RRS1 and breast cancer metastasis. Bioinformatic analysis was used to identify the expression levels and prognostic significance of RRS1 in breast cancer. Lenti-sh RRS1 lentivirus was constructed and employed to downregulate the RRS1 expression in MDA-MB-231 and BT549 cells, which had a high-level expression of RRS1. Subsequently, we assessed the impact of RRS1 downregulation on the proliferation, migration, and invasion of breast cancer cells using CCK-8, apoptosis, and cell cycle by flow cytometry, wound healing test, Transwell migration, and invasion experiments. Moreover, we utilized an in vivo imaging system to examine the metastatic potential of breast cancer cells after RRS1 knockdown. Picrate staining and hematoxylin-eosin staining were employed to evaluate the presence of metastatic lesions. To gain a deeper understanding of the molecular mechanism, we conducted co-immunoprecipitation and western blot. The significant overexpression of RRS1 in breast cancer indicates a worse prognosis, as determined through TCGA databases (p<0.01). Additionally, RRS1 exhibits upregulation in breast cancer (p<0.001), which is tightly linked to the occurrence of lymph node metastasis (p<0.001). Clinical breast cancer tissues and breast cancer cell lines also demonstrated a noteworthy upregulation of RRS1 (p<0.05). Loss-of-function experiment illustrated that the inhibiting of RRS1 expression reduced the rapid proliferation capacity of MDA-MB-231 and BT549 cells and hindered their migration and invasion capabilities (p<0.05). Importantly, the suppression of RRS1 significantly diminished lung metastasis in Balb/c nude mice that were injected with MDA-MB-231 cells (p<0.01). Mechanistically, RRS1 may interact with the AEG-1 to modulate the phosphorylation of AKT at T308 and S473, consequently impeding the activity of c-Myc (p<0.05). To conclude, RRS1 functions as a potential oncogene in breast cancer by leveraging the AEG-1/AKT/c-Myc signaling.

Exploring the relationship between anal fistula and colorectal cancer based on Mendelian randomization and bioinformatics.

The association between anal fistula patients and colorectal cancer, as well as the potential pathophysiological mechanisms, remains unclear. To explore the relationship between anal fistula and colorectal cancer and its potential mechanisms. Analysis of GEO and TCGA databases. Disease-related genes were also referenced from Coremine Medical, GeneCard and OMIM. Core hub genes were identified through protein-protein interaction analysis by intersecting differentially expressed genes from the datasets with disease data. On one hand, a prognostic model was developed using genes and its prognostic role was validated. On the other hand, the optimal diagnostic genes were selected through machine learning. Mendelian randomization (MR) analysis was conducted to explore the potential causal link between anal fistula and colorectal cancer. Thirteen core genes were identified (TMEM121B, PDGFRA, MID2, WNT10B, HOXD13, BARX1, SIX2, MMP1, SNAL1, CDKN2A, ITGB3, TIMP1, CALB2). Functional enrichment analysis revealed that the intersecting genes between anal fistula and colorectal cancer were associated with extracellular matrix components, signalling pathways, cell growth, protein modification, as well as important roles in cellular activities, tissue and organ development, and biological function maintenance. These genes were also involved in pathways related to Wnt signalling and colorectal cancer development. Prognostic analysis and immune infiltration analysis indicated a close relationship between core hub genes and the prognosis and immune infiltration in colorectal cancer. Machine learning showed that core genes played an essential role in the diagnostic differentiation of colorectal cancer. MR results suggested no causal relationship between anal fistula and colorectal cancer. This study identified shared core genes between anal fistula and colorectal cancer, involved in various pathways related to tumour development. These genes play crucial roles in prognosis and diagnosis.

Knockdown of CDX2 Induces microRNA-221 Up-regulation in Human Colon Cancer Cells.

Caudal-type homeobox transcription factor 2 (CDX2) is a master regulator of intestinal development and maintenance of the intestinal epithelium. We previously revealed that CDX2Low colorectal cancers (CRCs) were associated with poor survival and differential response to adjuvant chemotherapy. MicroRNAs (miRNAs), a class of non-coding RNAs typically composed of fewer than 25 nucleotides, are known to regulate gene expression and signaling pathways. This study aimed to identify oncogenic miRNAs induced by CDX2 in CRC. HCT116 cells were cultured and transfected with CDX2 siRNA. The expression levels of four oncogenic miRNAs (miR-9, miR-25, miR-106b and miR-221) were quantified by RT-qPCR. To understand whether CDX2 represented a key regulator of miR-221 expression in vivo, we analyzed the relationship between CDX2 and miR-221expression levels in the TCGA COAD database (n=454). The expression level of miR-221 was significantly up-regulated in CDX2 knockdown cells (n=2, p<0.05). In the TCGA database, we observed an inverse correlation between CDX2 and miR-221 expression levels, consistent with our in vitro data (r=-0.114, p=0.0149). Furthermore, the expression level of miR-221 was significantly elevated in patients with CDX2Low CRC (p<0.05). Knockdown of CDX2 induces microRNA-221 up-regulation in human CRC. Further research is warranted to elucidate the molecular mechanisms underlying miR-221 up-regulation in CDX2Low CRCs.

Multiomics Analysis of Disulfidptosis Patterns and Integrated Machine Learning to Predict Immunotherapy Response in Lung Adenocarcinoma.

Recent studies have unveiled disulfidptosis as a phenomenon intimately associated with cellular damage, heralding new avenues for exploring tumor cell dynamics. We aimed to explore the impact of disulfide cell death on the tumor immune microenvironment and immunotherapy in lung adenocarcinoma (LUAD). We initially utilized pan-cancer transcriptomics to explore the expression, prognosis, and mutation status of genes related to disulfidptosis. Using the LUAD multi- -omics cohorts in the TCGA database, we explore the molecular characteristics of subtypes related to disulfidptosis. Employing various machine learning algorithms, we construct a robust prognostic model to predict immune therapy responses and explore the model's impact on the tumor microenvironment through single-cell transcriptome data. Finally, the biological functions of genes related to the prognostic model are verified through laboratory experiments. Genes related to disulfidptosis exhibit high expression and significant prognostic value in various cancers, including LUAD. Two disulfidptosis subtypes with distinct prognoses and molecular characteristics have been identified, leading to the development of a robust DSRS prognostic model, where a lower risk score correlates with a higher response rate to immunotherapy and a better patient prognosis. NAPSA, a critical gene in the risk model, was found to inhibit the proliferation and migration of LUAD cells. Our research introduces an innovative prognostic risk model predicated upon disulfidptosis genes for patients afflicted with Lung Adenocarcinoma (LUAD). This model proficiently forecasts the survival rates and therapeutic outcomes for LUAD patients, thereby delineating the high-risk population with distinctive immune cell infiltration and a state of immunosuppression. Furthermore, NAPSA can inhibit the proliferation and invasion capabilities of LUAD cells, thereby identifying new molecules for clinical targeted therapy.

Hedgehog/Gli2 signaling triggers cell proliferation and metastasis via EMT and wnt/β-catenin pathways in oral squamous cell carcinoma

BackgroundOral squamous cell carcinoma (OSCC) is the most lethal oral malignant tumor, however, clinical outcomes remain unsatisfactory. The Hedgehog/Gli2 pathway plays a pivotal role in tumor progression, yet the regulatory mechanism governing its involvement in the malignant evolution process of OSCC remains elusive. MethodsOSCC animal tissue samples were used to detect the activation of the Hedgehog/Gli2 pathway in OSCC. Based on the clinical information of oral cancer patients in TCGA database, the role of this pathway in patients was analyzed, and the activation status of this pathway was verified in human OSCC cells. After activating or inhibiting the Hedgehog pathway, the effects of this pathway on the biological function of OSCC cells and its regulatory mechanism were examined. Interfering the expression of Gli2, a key transcription factor in this pathway, revealed the role of Hedgehog/Gli2 pathway in the malignant evolution of OSCC cells. ResultsThe Hedgehog pathway exhibits abnormal activation in animal models of OSCC. Clinical data from TCGA demonstrate a significant enrichment of the Hedgehog pathway in patients with OSCC, and Gli2, a key downstream factor of this pathway, is closely associated with the occurrence and progression of OSCC. Cellular studies have revealed aberrant activation of this pathway in human OSCC cells, which exerts its function by modulating the activation of epithelial-mesenchymal transition (EMT) and Wnt/β-catenin pathways. Subsequent investigations further confirm the pivotal involvement of Gli2 in the Hedgehog pathway activation, underscoring its potential as a therapeutic target for inhibiting malignant proliferation and metastasis of OSCC cells through modulation of EMT and Wnt/β-catenin pathways. ConclusionThe Hedgehog/Gli2 pathway induces EMT and activates Wnt/β-catenin pathway to trigger the malignant proliferation and metastasis of OSCC cells, and Gli2 plays a key role in this process, which suggests that targeting Gli2 may be a promising therapeutic strategy for inhibiting the proliferation and metastasis of OSCC.

Single-cell transcriptomic sequencing analysis of mechanistic insights into the IFN-γ signaling pathway in different tumor cells.

This study aimed to investigate the relationship between the interferon-gamma (IFN-γ) pathway in different tumor microenvironments (TME) and patients' prognosis, as well as the regulatory mechanisms of this pathway in tumor cells. Using RNA-seq data from the TCGA database, we analyzed the predictive value of the IFN-γ pathway across various tumors. We employed a univariate Cox regression model to assess the prognostic significance of IFN-γ signaling in different tumor types. Additionally, we analyzed single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database to examine the distribution characteristics of the IFN-γ pathway and explore its regulatory mechanisms, highlighting how IFN-γ influenced cellular interactions within the TME. Our analysis revealed a significant association between the IFN-γ pathway and adverse prognosis in pan-cancer tissues (P < 0.001). Interestingly, this correlation varied regarding positive and negative regulation across different tumor types. Through a detailed examination of scRNA-seq data, we found that the IFN-γ pathway exerted substantial regulatory effects on stromal and immune cells. In contrast, its expression and regulatory patterns in tumor cells exhibited diversity and heterogeneity. Further analysis indicated that the IFN-γ pathway not only enhanced the immunogenicity of tumor cells but also inhibited their proliferation. Cell-cell interaction analysis confirmed the pivotal role of the IFN-γ pathway within the overall regulatory network. Moreover, we identified HMGB2 (high mobility group box 2) in T cells as a potential key regulator of tumor cell proliferation. The IFN-γ pathway exhibited a dual function by both suppressing tumor cell proliferation and enhancing their immunogenicity, positioning it as a pivotal target for refined cancer diagnosis and cancer strategies.

Prognostic Value of Fatty Acid Metabolism-related Genes in Patients with Bladder Cancer.

This study aimed to explore the expression profiles of fatty acid metabolism- related genes (FAMRGs) in patients with bladder cancer (BLCA). The corresponding clinicopathological features of BLCA patients and RNA sequencing data were downloaded from TCGA and GSE13507. Univariate Cox regression was used to determine the prognostic value of FRGS in BLCA patients. LASSO regression analysis was then performed to select potential risk genes and eliminate genes that might overfit the model. Based on the independent prognostication-related FRGs, the nomogram survival model was established using the root mean square value of the R packet to predict the 1-year, 3-year, and 5-year survival rates of BLCA patients. By determining the area under the curve (AUC) value, the time-dependent receiver operating characteristic curve (ROC) was used to evaluate the prognostic efficiency of our model. A total of 243 DEFRGs were identified. Twenty FRGs were found to be related to the prognosis of BLCA in the TCGA database. Survival curves showed that high-risk patients had significantly shorter OS than low-risk cases (p < 0.001). The AUC of risk was 0.784, which was superior to age, sex, and stage, suggesting that the risk score was more favorable in predicting OS than traditional pathologic prognostic factors. The AUC was 0.757 at 1 year, 0.732 at 3 years, and 0.733 at 5 year-OS. In this study, we demonstrated that a FAMRG prognosis biomarker is associated with the tumor immune microenvironment in patients with BLCA.

Construction and validation of a SASP-related prognostic signature in patients with acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is a common and highly aggressive haematological malignancy in adults. Senescence-associated secretory phenotype (SASP) plays important roles in tumorigenesis and progression of tumour. However, the prognostic value of SASP in patients with AML has not been clarified. The present study aims to explore the prognostic value of SASP and develop a prognostic risk signature for AML. The RNA-sequencing data was collected from the TCGA, GTEx and TARGET databases. Subsequently, differentially expressed gene analysis, univariate Cox regression and LASSO regression were applied to identified prognostic SASP-related genes and construct a prognostic risk-scoring model. The risk score of each patient were calculated and patients were divided into high- or low-risk groups by the median risk score. This novel prognostic signature included 11 genes: G6PD, CDK4, RPS6KA1, UBC, H2BC12, KIR2DL4, HSF1, IFIT3, PIM1, RUNX3 and TRIM21. The patients with AML in the high-risk group had shorter OS, demonstrating that the risk score acted as a prognostic predictor, which was validated in the TAGET-AML dataset. Univariate and multivariate analysis revealed the risk score was an independent prognostic factor in patients with AML. Furthermore, the present study revealed that the risk score was associated with immune landscape, immune checkpoint gene expression and chemotherapeutic efficacy. In the present study, we constructed and validated a unique SASP-related prognostic model to assess therapeutic effect and prognosis in patients with AML, which might contribute to understanding the role of SASP in AML and guiding the treatment for AML.

Building endoplasmic reticulum stress-related LncRNAs signatures of lung adenocarcinoma.

Endoplasmic reticulum stress (ERS) could be a strategy for treating malignant tumors. Moreover, long noncoding RNAs (lncRNAs) can promote tumorigenesis and progression, and forecast the prognosis of cancers. Nevertheless, the prognostic value of ERS-related lncRNAs has not been reported in lung adenocarcinoma (LUAD). The messenger RNA (mRNA), microRNA (miRNA) and lncRNA expression data related to LUAD were obtained in public databases (TCGA and GEO databases). Prognostic ERS-related differentially expressed lncRNAs (ERS-DELs) were obtained and used to build an ERS-related model by Cox regression analysis. Moreover, we further screened independent prognostic elements and built a nomogram. Furthermore, enrichment analysis of genes was conducted to investigate the functions. A lncRNA-miRNA-mRNA network was built to explore mechanism of lncRNAs. Finally, qRT-PCR was utilized to examine the expression levels of lncRNAs. 30 ERS-DELs were identified, and an ERS-related signature was built based on AF131215.2, LINC00472, LINC01352, RP1-78O14.1, RP11-253E3.3, RP11-98D18.9, and SNHG12. Gene set enrichment analysis indicated that genes in the high-risk group were chiefly focused on the regulation of mRNA binding, and genes in the low-risk group were significantly focused on protein localization to cilia. A lncRNA-miRNA-mRNA network, containing 7 signature lncRNAs, 23 miRNAs, and 128 mRNAs, was also established. Eventually, quantitative real-time polymerase chain reaction was used to confirm that seven prognostic lncRNAs had a consistent expression with the analysis. An ERS-related signature containing seven prognostic lncRNAs was built, which offered new thinking concerning the role of ERS-related lncRNAs in LUAD.

Identification and validation of basement membrane-associated gene AGRN as prognostic and immune-associated biomarkers in colorectal cancer patients.

Colorectal cancer (COCA) has a poor prognosis, with growing evidence implicating basement membranes (BMs) in cancer progression. Our goal was to investigate the role and predictive significance of BMs in COCA patients. We obtained BMs-related genes from cutting-edge research and used TCGA and GTEx databases for mRNA expression and patient information. Cox regression and LASSO regression were used for prognostic gene selection and risk model construction. We compared prognosis using Kaplan-Meier analysis and examined drug sensitivity differences. The CMAP dataset identified potential small molecule drugs. Invitro tests involved suppressing a crucial gene to observe its impact on tumour metastasis. We developed a 12 BMs-based approach, finding it to be an independent prognostic factor. Functional analysis showed BMs concentrated in cancer-associated pathways, correlating with immune cell infiltration and immune checkpoint activation. High-risk individuals exhibited increased drug sensitivity. AGRN levels were linked to decreased progression-free survival (p < 0.001). AGRN knockdown suppressed tumour growth and metastasis. Our study offers new perspectives on BMs in COCA, concluding that AGRN is a dependable biomarker for patient survival and prognosis.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and invitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through invitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration invitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Exploring Novel Genome Instability-associated lncRNAs and their Potential Function in Pan-Renal Cell Carcinoma.

Genomic instability can drive clonal evolution, continuous modification of tumor genomes, and tumor genomic heterogeneity. The molecular mechanism of genomic instability still needs further investigation. This study aims to identify novel genome instabilityassociated lncRNAs (GI-lncRNAs) and investigate the role of genome instability in pan-Renal cell carcinoma (RCC). A mutator hypothesis was employed, combining the TCGA database of somatic mutation (SM) information, to identify GI-lncRNAs. Subsequently, a training cohort (n = 442) and a testing cohort (n = 439) were formed by randomly dividing all RCC patients. Based on the training cohort dataset, a multivariate Cox regression analysis lncRNAs risk model was created. Further validations were performed in the testing cohort, TCGA cohort, and different RCC subtypes. To confirm the relative expression levels of lncRNAs in HK-2, 786-O, and 769-P cells, qPCR was carried out. Functional pathway enrichment analyses were performed for further investigation. A total of 170 novel GI-lncRNAs were identified. The lncRNA prognostic risk model was constructed based on LINC00460, AC073218.1, AC010789.1, and COLCA1. This risk model successfully differentiated patients into distinct risk groups with significantly different clinical outcomes. The model was further validated in multiple independent patient cohorts. Additionally, functional and pathway enrichment analyses revealed that GI-lncRNAs play a crucial role in GI. Furthermore, the assessments of immune response, drug sensitivity, and cancer stemness revealed a significant relationship between GI-lncRNAs and tumor microenvironment infiltration, mutational burden, microsatellite instability, and drug resistance. In this study, we discovered four novel GI-lncRNAs and developed a novel signature that effectively predicted clinical outcomes in pan-RCC. The findings provide valuable insights for pan-RCC immunotherapy and shed light on potential underlying mechanisms.

Knockdown of long noncoding RNA AL161431.1 inhibits malignant progression of cholangiocarcinoma.

Cholangiocarcinoma (CCA) is one of the most deadly cancers in the world. It usually has a bad prognosis and is challenging to identify in its early stages. Long noncoding RNAs (lncRNAs) have been shown in an increasing number of studies to be important in the control of signaling pathways, cell behaviors, and epigenetic modification that contribute to the growth of tumors. The purpose of this work was to examine the relationship between CCA and lncRNA AL161431.1. Using TCGA clinical survival data, we evaluated the association between AL161431.1 expression and patient prognosis. Using the program cluster Profiler R, enrichment analysis was performed. Additionally, the association between immune cell infiltration and AL161431.1 expression was evaluated by a review of the TCGA database. Next, to ascertain if AL161431.1 influences tumor growth, migration, and invasion in CCA, functional in vitro assays were conducted. Quantitative real-time polymerase chain reaction (qPCR) was employed to gauge AL161431.1 expression levels in CCA cells. Western blot was used to measure protein levels. In CCA, AL161431.1 was extremely expressed. The patients in the high-risk group had a significantly poorer overall survival (OS) than the patients in the low-risk group. A more thorough look at the TCGA data showed a relationship between high expression levels of AL161431.1 and increased infiltration of T cells, T helper cells, and NK CD56dim cells. Furthermore, AL161431.1 knockdown in CCA cells impeded invasion, migration, and proliferation and also lowered the expression of phosphorylated Smad2/Smad3 to restrain the TGFβ/SMAD signaling pathway. Our results indicate that the lncRNA AL161431.1 activates the TGFβ/SMAD signaling pathway to enhance CCA development and metastasis. AL161431.1 could be a novel target for cholangiocarcinoma treatment or a diagnostic marker.

Significance and Possible Biological Mechanism for CLDN8 Downregulation in Kidney Renal Clear Cell Carcinoma Tissues.

The clinical role of claudin 8 (CLDN8) in kidney renal clear cell carcinoma (KIRC) remains unclarified. Herein, the expression level and potential molecular mechanisms of CLDN8 underlying KIRC were determined. High-throughput datasets of KIRC were collected from GEO, ArrayExpress, SRA, and TCGA databases to determine the mRNA expression level of the CLDN8. In-house tissue microarrays and immunochemistry were performed to examine CLDN8 protein expression. A summary receiver operating characteristic curve (SROC) and standardized mean difference (SMD) forest plot were generated using Stata v16.0. Single-cell analysis was conducted to further prove the expression level of CLDN8. A clustered regularly interspaced short palindromic repeats knockout screen analysis was executed to assess the growth impact of CLDN8. Functional enrichment analysis was conducted using the Metascape database. Additionally, single-sample gene set enrichment analysis was implied to explore immune cell infiltration in KIRC. A total of 17 mRNA datasets comprising 1,060 KIRC samples and 452 non-cancerous control samples were included in this study. Additionally, 105 KIRC and 16 non-KIRC tissues were analyzed using in-house immunohistochemistry. The combined SMD was -5.25 (95% confidence interval (CI): -6.13 to -4.37), and CLDN8 downregulation yielded an SROC area under the curve (AUC) close to 1.00 (95% CI: 0.99 - 1.00). CLDN8 downregulation was also confirmed at the single-cell level. Knocking out CLDN8 stimulated KIRC cell proliferation. Lower CLDN8 expression was correlated with worse overall survival of KIRC patients (hazard ratio of CLDN8 downregulation = 1.69, 95% CI: 1.2 - 2.4). Functional pathways associated with CLDN8 co-expressed genes were centered on carbon metabolism obstruction, with key hub genes ACADM, ACO2, NDUFS1, PDHB, SDHD, SUCLA2, SUCLG1, and SUCLG2. CLDN8 is downregulated in KIRC and is considered a potential tumor suppressor. CLDN8 deficiency may promote the initiation and progression of KIRC, potentially in conjunction with metabolic dysfunction.

Active Heme Metabolism Suppresses Macrophage Phagocytosis via the TLR4/Type I IFN Signaling/CD36 in Uterine Endometrial Cancer.

Uterine endometrial cancer (UEC) is a common gynecological estrogen-dependent carcinoma, usually accompanied by intermenstrual bleeding. Active heme metabolism frequently plays an increasingly important role in many diseases, especially in cancers. Tumor-associated macrophages (TAMs) are the major population in the immune microenvironment of UEC. However, the roles of heme metabolisms in the crosstalk between UEC cells (UECCs) and macrophages are unclear. In our study, by using TCGA database analysis, integration analysis of the protein-protein interaction (PPI) network and sample RNA transcriptome sequencing were done. The expression level of both heme-associated molecules and iron metabolism-related molecules were measured by quantitative real-time polymerase chain reaction. Heme level detection was done through dehydrohorseradish peroxidase assay. In addition to immunohistochemistry, phagocytosis assay of macrophages, immunofluorescence staining, intracellular ferrous iron staining, as well as enzyme-linked immune sorbent assay were performed. In the study, we verified that heme accumulation in UECCs is apparently higher than in endometrial epithelium cells. Low expression of succinate dehydrogenase B under the regulation of estrogen contributes to over-production of succinate and heme accumulation in UECC. More importantly, excessive heme in UECCs impaired macrophage phagocytosis by regulation of CD36. Mechanistically, this process is dependent on toll-like receptor (TLR4)/type I interferons alpha (IFN Iα) regulatory axis in macrophage. Collectively, these findings elucidate that active heme metabolism of UECCs directly decreases phagocytosis by controlling the secretion of TLR4-mediated IFN Iα and the expression of CD36, and further contributing to the immune escape of UEC.

Periplocin Inhibited Gliomas Migration by Targeting Migrasome Related Gene TSPAN6

Glioma is a life-threatening brain tumor characterized by rapid growth and resistance to treatment. Periplocin, the monomeric compound, exhibits anti-tumor activities. However, the action of periplocin in gliomas remain unclear. Migrasome, a vesicle-like structure derived from the tips or intersections of contractile filaments in migrating cells, was investigated in this study to explore the antitumor activity of periplocin in glioma and elucidate its mechanism. The proliferation, apoptosis, migration and MMP in periplocin-treated LN229 and KNS-89 cells were examined. In order to revealed the mechanism of Periplocin inhibition of migration. Additionally, we revealed the relation of Migrasome-related genes with glioma based on TCGA database analysis, and we found TSPAN6 may be the direct target in glioma, Periplocin could inhibited LN229 and KNS-89 cell proliferation and migration, and promoted their apoptosis. Moreover, targeting TSPAN6 resulted in reduced cell viability and migration, as well as increased apoptosis in glioma cells.