Atlas Dataset Research Articles

Abstract B028: The Role of cDC1 Gene Signatures in gastric cancer prognosis and immune microenvironment modulation

Abstract Background and Aim: Gastric cancer (GC) continues to be a major global health burden, with a growing body of evidence highlighting the critical role of conventional type 1 dendritic cells (cDC1s) within the tumor microenvironment. This study aims to elucidate the prognostic significance of cDC1-associated genes—CD141, XCR1, CLEC9A, CADM1, and BTLA—in gastric cancer, as well as to explore the biological mechanisms that underpin their effects on patient outcomes. Materials and Methods: We conducted a comprehensive analysis of RNA- seq data from The Cancer Genome Atlas (TCGA-STAD) and Gene Expression Omnibus (GEO) datasets, focusing on the expression profiles of five cDC1-related genes. Patients were stratified into high and low expression groups based on a defined cDC1 gene signature. To assess the impact of these signatures, we utilized gene set variation analysis (GSVA) to examine relevant oncogenic pathways and performed Kaplan-Meier survival analysis along with Cox proportional hazards modeling to evaluate their prognostic value. Results: Our findings demonstrate that patients exhibiting a high cDC1-related gene signature had significantly worse overall and disease-free survival within the TCGA-STAD cohort. Further analysis revealed marked differences in CD8+ T cell infiltration and cytotoxic activity between the high and low cDC1 signature groups. Additionally, the high cDC1 signature group was strongly associated with upregulated expression of immune checkpoint proteins and the activation of oncogenic pathways, indicating a highly immunosuppressive tumor microenvironment. Conclusions: This study suggests that the cDC1-related gene signature may serve as a potent prognostic biomarker in gastric cancer, offering new insights into the complex interactions between the tumor and immune microenvironment. These results could pave the way for innovative therapeutic strategies that target the immune landscape in gastric cancer, potentially improving patient outcomes. Citation Format: Song-hee han. The Role of cDC1 Gene Signatures in gastric cancer prognosis and immune microenvironment modulation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B028.

Senescence cell signature associated with poor prognosis, epithelial-mesenchymal transition, solid histology, and spread through air spaces in lung adenocarcinoma.

Cellular senescence is involved in critical processes in tumor progression. Despite this potential relationship, the relationship between tumor cell senescence, prognostic significance, spread through air spaces (STAS), and tumor histology has not been investigated in lung adenocarcinoma (LUAD). We used the LUAD PanCancer Atlas dataset to assess senescence cell signature (SCS) based on the SenMayo gene set. We examined the relationship between SCS, prognostic significance, STAS, and tumor histology. This relationship was confirmed in independent LUAD datasets by validation using immunohistochemical senescence markers. In the LUAD PanCancer Atlas dataset, patients with high SCS expression had a higher prevalence of solid histology and STAS patterns than those with low SCS expression. In the independent LUAD datasets, high p21 expression and low HMGB1 expression were correlated with solid histology or STAS patterns. SCS level was also independent prognostic factor in four different LUAD datasets. The HMGB1 expression was an independent prognostic factor in the independent LUAD dataset in multivariate analysis. The expression of p21 and the presence of solid histology were linked to the epithelial-mesenchymal transition (EMT) phenotype. In LUAD cell lines, inducing senescence with a DNA-damaging agent led to an increase in EMT marker expression. Our findings suggest a strong link between senescence, EMT, and solid histology, offering valuable insight into how cancer cell senescence may promote tumor progression through particular pathways.

Overexpression of CDCA8 predicts poor prognosis and drug insensitivity in lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) accounts for the highest proportion of lung cancers; however, specific biomarkers are lacking for diagnosis, treatment, and prognostic assessment. Cell division cycle-associated 8 (CDCA8) is a cell cycle regulator with elevated expression in various cancers. However, the association between CDCA8 expression and LUAD prognosis remains unclear.MethodsThe association between CDCA8 and LUAD prognosis was evaluated based on the The Cancer Genome Atlas (TCGA) dataset, and CDCA8 related functions were determined using gene enrichment and gene ontology analyses. We also analyzed the association between CDCA8 expression and immune cell infiltration. Immunohistochemistry was used to determine the differential expression of CDCA8 in tumors and controls. Finally, we evaluated the differences in the sensitivity of different levels of CDCA8 to different anticancer drugs in LUAD.ResultsCDCA8 expression was significantly higher in primary LUAD tumors than in normal tissues (P < 0.001). Moreover, Kaplan–Meier survival analysis demonstrated that high CDCA8 expression predicted poor survival in patients with LUAD (P = 0.006). The receiver operating characteristic (ROC) curves indicated that CDCA8 was an effective guide for the diagnosis of LUAD. Functional annotation indicated that CDCA8 might be involved in functions such as p53 stabilization, nucleotide metabolism, RNA-mediated gene silencing, and the G2/M phase checkpoint. Immune infiltration results suggested that CDCA8 was positively correlated with Th2 cells and Tgd and negatively correlated with Eosinophils and Mast cells (P < 0.01). In addition, elevated expression of CDCA8 may increase the sensitivity of patients to certain anticancer drugs.ConclusionsCDCA8 upregulation is significantly associated with poor survival and immune infiltration in patients with LUAD. Our study suggests that CDCA8 can be used as a biomarker for LUAD prognosis and a reference for personalized medication.Graphical

LINC01764 promotes colorectal cancer cells proliferation, metastasis, and 5-fluorouracil resistance by regulating glucose and glutamine metabolism via promoting c-MYC translation.

Few biomarkers are available for predicting chemotherapeutic response and prognosis in colorectal cancer (CRC). Long-noncoding RNAs (lncRNAs) are essential for CRC development and growth. Therefore, studying lncRNAs may reveal potential predictors of chemotherapy response and prognosis in CRC. LINC01764 was analyzed using datasets from Fudan University Shanghai Cancer Center's advanced CRC patients' RNA-seq and The Cancer Genome Atlas datasets. Gene set enrichment analysis was employed to detect related pathways. Cotransfection experiments, RNA pulldown assays, RNA-binding protein immunoprecipitation, protein synthesis activity, and dual-luciferase reporter assays were performed to determine interactions among LINC01764, hnRNPK, and c-MYC. High LINC01764 expression correlates with metastasis, a poor response to FOLFOX/XELOX chemotherapy, and a poor prognosis in CRC. LINC01764 enhance glycolysis and glutamine metabolism to promote CRC cells proliferation, metastasis, and 5-fluorouracil (5-FU) resistance. LINC01764 specifically binds to hnRNPK, facilitating its interaction with c-MYC mRNA and promoting internal ribosome entry site (IRES)-dependent translation of c-MYC, thereby exerting oncogenic effects. LINC01764 induced 5-FU chemoresistance by upregulating the c-MYC, glucose, and glutamine metabolism pathways, which downregulated UPP1, crucial for activating 5-FU. Conclusively, LINC01764 promotes CRC progression and 5-FU resistance through hnRNPK-mediated-c-MYC IRES-dependent translational regulation, which suggests its potential as a predictor of CRC chemotherapy response and prognosis.

Low-grade endometrial cancer histology at diagnosis does not improve survival in the TP53 molecular subtype regardless of stage: A large, retrospective cohort validated by the Cancer Genome Atlas dataset

Low-grade endometrial cancer histology at diagnosis does not improve survival in the TP53 molecular subtype regardless of stage: A large, retrospective cohort validated by the Cancer Genome Atlas dataset

Identification and validation of a prognostic model based on immune-related genes in ovarian carcinoma.

A novel valuable prognostic model has been developed on the basis of immune-related genes (IRGs), which could be used to estimate overall survival (OS) in ovarian cancer (OC) patients in The Cancer Genome Atlas (TCGA) dataset and the International Cancer Genome Consortium (ICGC) dataset. This prognostic model was engineered by employing LASSO regression in training cohort (TCGA dataset). The corresponding growth predictive values of this model for individualized survival was evaluated using survival analysis, receiver operating characteristic curve (ROC curve), and risk curve analysis. Combined with clinical characteristics, a model risk score nomogram for OS was well built. Thereafter, depended on the model risk score, patients were divided into high and low risk subgroups. The survival difference between these subgroups was measured using Kaplan-Meier survival method. In addition, correlations containing pathway enrichment, treatment, immune cell infiltration and the prognostic model were also analyzed. We established the ovarian cancer cell line W038 for this study and identified the performances of GBP1P1 knockdown on a series of activities including cellular proliferation, apoptosis, migration, and invasion of W038 cells in vitro. We constructed a 25-genes prognostic model (TNFAIP8L3, PI3, TMEM181, GBP1P1 (LOC400759), STX18, KIF26B, MRPS11, CACNA1C, PACSIN3, GMPR, MANF, PYGB, SNRPA1, ST7L, ZBP1, BMPR1B-DT, STAC2, LINC02585, LYPD6, NSG1, ACOT13, FAM120B, LEFTY1, SULT1A2, FZD3). The areas under the curves (AUC) of 1, 2 and 3 years were 0.806, 0.773 and 0.762, in the TCGA cohort, respectively. Besides, the effectiveness of the model was verified using ICGC testing data. Univariate and multivariate Cox regression analysis exposes the risk score as an independent prognosis predictor for OS both in the TCGA and ICGC cohort. In summary, we utilized comprehensive bioinformatics analysis to build an effective prognostic gene model for OC patients. These bioinformatic results suggested that GBP1P1 could act as a novel biomarker for OC. GBP1P1 knockdown substantially inhibited the proliferation, migration, and invasion of W038 cells in vitro, and increased the percentage of apoptotic W038 cells. The analyses of genetic status of patients with 25-genes model might improve the ability to predict the prognosis of patients with OC and help to select patients suit able to therapies. Immune-related gene GBP1P1 might serve as prognostic biomarker for OC.

The lncRNA AFAP1-AS1 is upregulated in metastatic triple-negative breast tumors and controls hypoxia-activated vasculogenic mimicry and angiogenesis

BackgroundVasculogenic mimicry (VM) is an alternative intratumoral microcirculation system that depends on the capacity of tumor cells to reorganize and grow in three-dimensional (3D) channel architectures like the capillaries formed by endothelial cells. Both VM and angiogenesis may coordinately function to feed cancer cells, allowing tumor growth. Long noncoding RNAs (lncRNAs) regulate critical cellular functions in cancer cells, including cell proliferation, apoptosis, angiogenesis, invasion, and metastasis. The lncRNA, known as actin filament-associated protein 1-antisense RNA 1 (AFAP1-AS1), has been described as an oncogene in diverse types of cancers. However, its role in VM and metastasis in triple-negative breast cancer (TNBC) is unknown.MethodsReverse transcription and quantitative polymerase chain reaction (RT‒qPCR) experiments were performed to evaluate the expression of 10 selected lncRNAs from literature in metastatic and nonmetastatic biopsies from TNBC patients. The expression of AFAP1-AS1 was analyzed in Genotype-Tissue Expression Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets. The AFAP1-AS1 expression was knocked in TNBC Hs578T cells by transfection of specific siRNAs. Channel-like formation assays were performed using 3D cultures over Matrigel in hypoxia-treated Hs578T cancer cells with diminished expression of AFAP1-AS1. The angiogenesis tests were conducted using human umbilical vein endothelial cells (HUVECs) and AFAP1-AS1- silenced Hs578T cells on 3D cell cultures. The presence of VM (CD31-/PAS+) in tumor tissues from TNBC patients with and without metastasis was assessed through immunohistochemistry using endothelial marker CD31 antibodies and periodic acid-Schiff (PAS) staining.ResultsCompared with normal mammary tissues, AFAP1-AS1 expression was higher in breast cancer tissues. Moreover, AFAP1-AS1 expression was upregulated in the TNBC subtype compared to receptor-positive breast tumors. In addition, the expression of AFAP1-AS1 was correlated with the expression of the thirteen genes characteristic of a previously reported hypoxia signature. Interestingly, AFAP1-AS1 was upregulated in primary TNBC tumors from patients who developed metastasis compared with the nonmetastatic group. Functional analysis revealed that the knockdown of AFAP1-AS1 in Hs578T cells significantly impaired the hypoxia-induced VM, accompanied by a decrease in the development of 3D channel networks. Similarly, AFAP1-AS1 knockdown counteracts the angiogenic potential of cancer cells, as indicated by a reduction in the number of polygons, sprouting cells, and nodes in HUVEC cells. Remarkably, an increase in CD31-/PAS + staining of 3D channel networks in primary breast tumors from metastatic patients was found compared with the nonmetastatic group. Finally, we found that the number of blood vessels increased in the nonmetastatic group more than in the metastatic cohort.ConclusionsOur data suggested that AFAP1-AS1 controls both VM and angiogenesis in Hs578T breast cancer cells and that increased metastasis is associated with VM in TNBC patients.

PROTAC’ING CENTROSOME AMPLIfiCATION PROTEINS: TARGETED PROTEIN DEGRADATION AS A NOVEL THERAPEUTIC STRATEGY IN GLIOBLASTOMA

Abstract AIMS Glioblastomas (GBMs) are the most common and aggressive brain tumours, notoriously difficult to treat with universal treatment resistance. A key feature of cancer cells is centrosome amplification (CA), leading to chromosomal instability and worse patient outcomes, including metastasis development and treatment resistance. In this work, I identified CA proteins overexpressed in GBM and aimed to investigate how the targeted degradation of proteins associated with centrosome amplification can influence the growth and survival of GBM cells. METHOD Based on well-established literature data concerning CA-related genes, I evaluated the expression level of these targets in different types of samples from the Tumour Cancer Genome Atlas dataset of GBM patient samples. Following the identification of CA targets differentially overexpressed, to test the hypothesis that CA proteins could be involved in the survival of GBM cells and be potential therapeutic targets, I used a novel drug modality, named Proteolysis Targeting Chimeras (PROTACs) to degrade two CA proteins. PROTACs can quickly destroy specific proteins, potentially overcoming resistance to treatment. Target degradation was confirmed via immunoblotting and cell viability and cell cycle analysis were performed to evaluate the impact on GBM cells. RESULTS Both primary and recurrent GBM samples display high levels of CA gene signature when compared to noncancerous samples, and some CA genes are particularly upregulated in recurrent samples. The PROTACs were effective in degrading both CA targets in GBM cells, leading to a significant decrease in cell viability and G2 cell cycle arrest. CONCLUSION This study presents initial evidence that CA protein degradation could be a promising avenue for GBM research and therapy. Further research is needed to fully assess the translational potential of PROTACs in GBM treatment.

FBXO family genes promotes hepatocellular carcinoma via ubiquitination of p53

FBXO protein family plays an essential role in the ubiquitination process acting as E3 ligases, which may contribute to the progression of cancers. However, the molecular functions of FBXOs in hepatocellular carcinoma (HCC) remain incompletely understood. Here, we investigated the overlapping genes between the FBXOs and differentially expressed genes (DEGs) of HCC identified by utilizing The Cancer Genome Atlas (TCGA) dataset, then, a prognostic model with effective predictive capacity was constructed based on the uni-cox and LASSO regression analyses. To elucidate the underlying mechanism of the FBXO model genes, KEGG analysis was carried out. Drug metabolism-cytochrome P450 and retinol metabolism were revealed as the potential pathway, which Increased the credibility of subsequent drug prediction research. Meanwhile, patients divided by the prognostic model showed a different immune infiltrating status and we also found FBXO model genes may ubiquitinate P53, inducing TP53 more prone to mutations, thereby promoting the occurrence and development of tumors. Consistent with these findings, the result of immunohistochemistry (IHC) validated an elevated expression of these model genes in HCC tissues than in the adjacent tissues. The primary aim of this investigation is to formulate a prognostic model while exploring the underlying mechanisms associated with FBXO genes in HCC. These findings offer initial research perspectives on the involvement of FBXO genes in HCC and contribute to the discovery of dependable biomarkers for the management, prognostication, and early detection of HCC in patients.

Analyzing the Mutational Landscape of Prostate Cancer Susceptibility Genes through Next-Generation Sequencing (NGS) Analysis

Prostate cancer, a significant public health concern, exhibits a complex genetic landscape influenced by a variety of susceptibility genes. This study deciphers the intricate genetic makeup of prostate cancer by examining mutations in 14 prostate cancer susceptibility genes. The Next-Generation Sequencing (NGS) approach was employed on a cohort of 45 prostate cancer patients to detect mutations. The gnomAD database was used to analyze mutational frequencies in the Asian population suffering from prostate cancer. The cBioPortal database was employed to check the presence of observed mutations in The Cancer Genome Atlas (TCGA) dataset. In addition, this study employed RT-qPCR and Immunohistochemistry (IHC) techniques were utilized to check the functional consequences of the observed pathogenic mutations. Finally, Metascape and DrugBank resources were used for gene enrichment and drug prediction analyses. Results of the NGS analysis revealed a total of 29 mutations (pathogenic and benign) within the examined prostate cancer cohort, distributed across four key genes (BRCA1/2, TP53, and PMS2) out of the total analyzed 14 genes. Pathogenic mutations in BRCA1/2 and TP53 genes are of particular interest due to their fundamental roles in DNA repair, cell cycle regulation, and tumor suppression. Functional consequence analyses (RT-qPCR and IHC) demonstrated the down-regulation of BRCA1/2 and TP53 genes in prostate cancer samples with pathogenic mutations, reinforcing the disruption of their tumor suppressor roles. Lastly, drug prediction analysis uncovered promising therapeutic options by identifying drugs capable of enhancing the mRNA expression of these genes. This opens new avenues for tailored treatment strategies aimed at restoring normal cellular functions of the BRCA1/2 and TP53 genes. In conclusion, this study provides a comprehensive view of genetic mutations in prostate cancer susceptibility genes, ranging from benign to pathogenic. It emphasizes the genetic complexity of prostate cancer and offers insights into potential mechanisms driving this malignancy. These findings lay the groundwork for further research, personalized treatment approaches, and enhanced clinical management of prostate cancer.

Feature Pyramid Network Based Spatial Attention and Cross‐Level Semantic Similarity for Diseases Segmentation From Capsule Endoscopy Images

ABSTRACTAs an emerging technology that uses a pill‐sized camera to visualize images of the digestive tract. Wireless capsule endoscopy (WCE) presents several advantages, since it is far less invasive, does not need sedation and has less possible complications compared to standard endoscopy. Hence, it might be exploited as alternative to the standard procedure. WCE is used to diagnosis a variety of gastro‐intestinal diseases such as polyps, ulcers, crohns disease, and hemorrhages. Nevertheless, WCE videos produced after a test may consist of thousands of frames per patient that must be viewed by medical specialists, besides, the capsule free mobility and technological limits cause production of a low quality images. Hence, development of an automatic tool based on artificial intelligence might be very helpful. Moreover, most state‐of‐the‐art works aim at images classification (normal/abnormal) while ignoring diseases segmentation. Therefore, in this work a novel method based on Feature Pyramid Network model is presented. This approach aims at diseases segmentation from WCE images. In this model, modules to optimize and combine features were employed. Specifically, semantic and spatial features were mutually compensated by spatial attention and cross‐level global feature fusion modules. The proposed method testing F1‐score and mean intersection over union are 94.149% and 89.414%, respectively, in the MICCAI 2017 dataset. In the KID Atlas dataset, the method achieved a testing F1‐score and mean intersection over union of 94.557% and 90.416%, respectively. Through the performance analysis, the mean intersection over union in the MICCAI 2017 dataset is 20.414%, 18.484%, 11.444%, 8.794% more than existing approaches. Moreover, the proposed scheme surpassed the methods used for comparison by 29.986% and 9.416% in terms of mean intersection over union in KID Atlas dataset. These results indicate that the proposed approach is promising in diseases segmentation from WCE images.

Graph-based diffusion model for fast shower generation in calorimeters with irregular geometry

Denoising diffusion models have gained prominence in various generative tasks, prompting their exploration for the generation of calorimeter responses. Given the computational challenges posed by detector simulations in high-energy physics experiments, the necessity to explore new machine-learning-based approaches is evident. This study introduces a novel graph-based diffusion model designed specifically for rapid calorimeter simulations. The methodology is particularly well-suited for low-granularity detectors featuring irregular geometries. We apply this model to the ATLAS dataset published in the context of the Fast Calorimeter Simulation Challenge 2022, marking the first application of a graph diffusion model in the field of particle physics. Published by the American Physical Society 2024

Development of a disulfidptosis-related prognostic model for endometrial cancer with potential therapeutic target

Prognosis biomarkers for endometrial cancer (EC) are in need. Recent evidence demonstrated the critical role of disulfidptosis, a novel cell death modality, in cancer. However, limited studies have developed a disulfidptosis-related gene model for EC. Disulfidptosis prognosis score of EC (disulfidptosis-PSEC) were constructed using disulfidptosis-related differently expression genes with the RNA data of 544 EC patients from The Cancer Genome Atlas (TCGA) dataset. Model was evaluated using time-dependent receiver operating characteristic curve analysis for overall survival (OS) and disease-free survival (DFS), along with the hazard ratio (HR) between risk groups. Then, the cellular and molecular profile for different risk groups were performed, along with drug target inference. Disulfidptosis-PSEC demonstrated outstanding prognostic value for OS and DFS, with 5-year area under curve of 0.71 (95% CI, 0.58–0.75) and 0.69 (95% CI, 0.62–0.76), respectively. Low risk group demonstrated better survival with an HR of 0.38 (95% CI, 0.24–0.59) and 0.46 (95% CI, 0.32–0.66) for OS and DFS, respectively. The model was independent of TCGA subtype. Low risk group were featured with more immune cell infiltration and less gene mutation. Serval drug targets, and the therapeutic value of serotonin receptor among copy number (CN)-low subpopulation, were identified. Disulfidptosis-PSEC was a potential prognosis biomarker for EC with targetable biological process.

Clinical relationships between the intratumoral microbiome and risk factors for head and neck cancer

A bioinformatic analysis is a promising approach to understand the relationship between the vast tumor microbiome and cancer development. In the present study, we studied the relationships between the intratumoral microbiome and classical clinical risk factors using bioinformatics analysis of the Cancer Genome Atlas (TCGA) and the Cancer Microbiome Atlas (TCMA) datasets involving HNSCC patients. We used TCMA database and investigated the abundance of microbes at the genus level in solid normal tissue (n=22) and the primary tumors of patients with head and neck squamous cell carcinoma (HNSCC) (n=154) and identified three major tumor microbiomes, Fusobacterium, Prevotella, and Streptococcus. The tissue level of Fusobacterium was higher in primary tumors than in solid normal tissue. However, univariate and multivariate analyses of these 3 microbes showed no significant effects on patient survival. We then extracted 43, 55, or 59 genes that were differentially expressed between the over and under the median groups for Fusobacterium, Prevotella, or Streptococcus using the criteria of >2.5, >1.5, or >2.0 fold and p<0.05 in the Mann-Whitney U-test. The results of a pathway analysis revealed the association of Fusobacterium- and Streptococcus-related genes with the IL-17 signaling pathway and Staphylococcus aureus infection, while Prevotella-associated pathways were not extracted. A protein-protein interaction analysis revealed a dense network in the order of Fusobacterium, Streptococcus, and Prevotella. An investigation of the relationships between the intratumoral microbiome and classical clinical risk factors showed that high levels of Fusobacterium were associated with a good prognosis in the absence of alcohol consumption and smoking, while high levels of Streptococcus were associated with a poor prognosis in the absence of alcohol consumption. In conclusion, intratumoral Fusobacterium and Streptococcus may affect the prognosis of patients with HNSCC, and their effects on HNSCC are modulated by the impact of drinking and smoking.

UCHL1 Overexpression Is Related to the Aggressive Phenotype of Non-small Cell Lung Cancer.

Ubiquitin C-terminal hydrolase L1 (UCHL1), which encodes thiol protease that hydrolyzes a peptide bond at the C-terminal glycine residue of ubiquitin, regulates cell differentiation, proliferation, transcriptional regulation, and numerous other biological processes and may be involved in lung cancer progression. UCHL1 is mainly expressed in the brain and plays a tumor-promoting role in a few cancer types; however, there are limited reports regarding its role in lung cancer. Single-cell RNA (scRNA) sequencing using 10X chromium v3 was performed on a paired normal-appearing and tumor tissue from surgical specimens of a patient who showed unusually rapid progression. To validate clinical implication of the identified biomarkers, immunohistochemical (IHC) analysis was performed on 48 non-small cell lung cancer (NSCLC) tissue specimens, and the correlation with clinical parameters was evaluated. We identified 500 genes overexpressed in tumor tissue compared to those in normal tissue. Among them, UCHL1, brain expressed X-linked 3 (BEX3), and midkine (MDK), which are associated with tumor growth and progression, exhibited a 1.5-fold increase in expression compared to that in normal tissue. IHC analysis of NSCLC tissues showed that only UCHL1 was specifically overexpressed. Additionally, in 48 NSCLC specimens, UCHL1 was specifically upregulated in the cytoplasm and nuclear membrane of tumor cells. Multivariable logistic analysis identified several factors, including smoking, tumor size, and high-grade dysplasia, to be typically associated with UCHL1 overexpression. Survival analyses using The Cancer Genome Atlas (TCGA) datasets revealed that UCHL1 overexpression is substantially associated with poor survival outcomes. Furthermore, a strong association was observed between UCHL1 expression and the clinicopathological features of patients with NSCLC. UCHL1 overexpression was associated with smoking, tumor size, and high-grade dysplasia, which are typically associated with a poor prognosis and survival outcome. These findings suggest that UCHL1 may serve as an effective biomarker of NSCLC.

Growth differentiation factor 7 alleviates the proliferation and metastasis of hepatocellular carcinoma

Background and aimInflammatory factors play significant roles in the development and occurrence of hepatocellular carcinoma (HCC). However, the tumor-protective functions of growth differentiation factors (GDFs) in HCC are yet to be clarified. In this study, we aimed to evaluate the expression levels of 10 GDFs in tumor and paratumor tissues from patients with HCC and perform in vitro and in vivo experiments to elucidate the role of GDF7 in regulating the proliferation and metastasis of HCC. MethodsThe gene expression of 10 GDFs was compared between HCC and paratumors using The Cancer Genome Atlas dataset and patient-derived tissues. A tumor microarray containing 108 HCC tissue samples was used to explore the prognostic value of GDF7 expression. Loss-of-function experiments were also performed in vitro and in vivo to investigate the role of GDF7 in HCC. ResultsThe mRNA and protein levels of GDF7 were significantly lower in HCC tumors than in paratumors (P < 0.001). Kaplan–Meier analysis showed that decreased GDF7 expression in HCC was associated with worse overall survival (5-year rate: 61.8% vs. 27.5%, P < 0.001) and increased recurrence risk (P < 0.001). Multivariate Cox regression analysis demonstrated that low GDF7 expression, the presence of microvascular invasion, and elevated alpha-fetoprotein (AFP) levels were independent risk factors for tumor recurrence and poor survival. Downregulation of GDF7 also increased the tumor growth in HCC cells and in an HCC xenograft model. GDF7 knockdown promoted migration and invasion via epithelial–mesenchymal transition. Meanwhile, a negative correlation between JunB proto-oncogene (JUNB) and GDF7 was observed in HCC tissues. Modulating JUNB levels altered GDF7 protein expression. ConclusionGDF7 is a potential biomarker for predicting superior outcomes in patients with HCC. GDF7 amplification is a potential therapeutic option for HCC.

SRPK Inhibitors Reduce the Phosphorylation and Translocation of SR Protein Splicing Factors, thereby Correcting BIN1, MCL-1 and BCL2 Splicing Errors and Enabling Apoptosis of Cholangiocarcinoma Cells.

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium that is commonly found in the Thai population. CCA has poor prognosis and a low survival rate due to the lack of early diagnosis methods and the limited effectiveness of current treatments. A number of oncogenic spliced-transcripts resulting from mRNA splicing errors have been reported in CCA, and aberrant mRNA splicing is suspected to be a key driver of this cancer type. The hyperphosphorylation of serine/arginine rich-splicing factors (SRSFs) by serine/arginine protein kinases (SRPKs) causes them to translocate to the nucleus where they facilitate gene splicing errors that generate cancer-related mRNA/protein isoforms. The correlation between SRPK expression and the survival of CCA patients was analyzed using data from The Cancer Genome Atlas (TCGA) dataset. The effect of SRPK inhibitors (SRPIN340 and SPHINX31) on two CCA cell lines (KKU-213A and TFK-1) was also investigated. The induction of cell death was studied by Calcein-AM/PI staining, AnnexinV/7AAD staining, immunofluorescence (IF), and Western blotting (WB). The phosphorylation and nuclear translocation of SRSFs was tracked by WB and IF, and the repair of splicing errors was examined by Reverse Transcription-Polymerase Chain Reaction (RT-PCR). High levels of SRPK1 and SRPK2 transcripts, and in particular SRPK1, correlated with shorter survival in CCA patients. SRPIN340 and SPHINX31 increased the number of dead and apoptotic cells in a dose-dependent manner. CCA also showed diffuse expression of cytoplasmic cytochrome C and upregulation of cleaved caspase-3. Moreover, SRSFs showed low levels of phosphorylation, resulting in the accumulation of cytoplasmic SRSF1. To link these phenotypes with aberrant gene splicing, the apoptosis-associated genes Bridging Integrator 1 (BIN1), Myeloid cell leukemia factor 1 (MCL-1) and B-cell lymphoma 2 (BCL2) were selected for further investigation. Treatment with SRPIN340 and SPHINX31 decreased anti-apoptotic BIN1+12A and increased pro-apoptotic MCL-1S and BCL-xS. The SRPK inhibitors SRPIN340 and SPHINX31 can suppress the phosphorylation of SRSFs and their nuclear translocation, thereby producing BIN1, MCL-1 and BCL2 isoforms that favor apoptosis and facilitate CCA cell death.

CT45A1-mediated MLC2 (MYL9) phosphorylation promotes natural killer cell resistance and outer cell fate in a cell-in-cell structure, potentiating the progression of microsatellite instability-high colorectal cancer.

Patients with microsatellite instability-high (MSI-H) colorectal cancer (CRC) have high tumor mutation burden and tumor immunogenicity, exhibiting a higher response rate to immunotherapy and better survival. However, a portion of MSI-H CRC patients still experience adverse disease outcomes. We aimed to identify the tumor-autonomous regulators determining these heterogeneous clinical outcomes. The Cancer Genome Atlas (TCGA) dataset was used to identify regulators in MSI-H CRC patients with unfavorable outcomes. Stable CRC tumor clones expressing targeted regulators were established to evaluate migratory and stemness properties, immune cell vulnerability, and cell-in-cell (CIC) structure formation. RNA-sequencing (RNA-seq) was used to identify enriched biological pathways in stable CRC tumor clones. Clinicopathological characterization of formalin-fixed paraffin-embedded (FFPE) MSI-H CRC specimens was performed to explore the underlying mechanisms involved. We showed that cancer/testis antigen family 45 member A1 (CT45A1) expression was upregulated in MSI-H CRC patients with poor survival outcomes. CT45A1-expressing microsatellite stable (MSS) CRC cells showed enhanced migratory ability. However, CT45A1-expressing MSI-H CRC cells, but not MSS CRC cells, showed higher resistance to natural killer (NK) cell cytotoxicity and served as outer cells in homotypic CIC structures, preventing exogenous or therapeutic antibody access to inner CRCcells. Inactivating RHO-ROCK/MLCK-MLC2 signaling with small-molecule inhibitors or short-hairpin RNAs (shRNAs) targeting myosin light chain kinase (MYLK) abolished NK cell resistance and reduced the outer cell fate of CT45A1-expressing MSI-H CRC cells. In MSI-H CRC patients, CT45A1-positive tumors exhibited increased MLC2 phosphorylation, increased outer cell fate, and decreased survival. We demonstrated that CT45A1 potentiates the advanced progression of MSI-H CRC, and targeting MLC2 phosphorylation may enhance immunotherapy efficacy in CT45A1-positive MSI-H CRC patients.

Global RNA Interaction and Transcriptome Profiles Demonstrate the Potential Anti-Oncogenic Targets and Pathways of RBM6 in HeLa Cells

Background: The fate and functions of RNAs are coordinately regulated by RNA-binding proteins (RBPs), which are often dysregulated in various cancers. Known as a splicing regulator, RNA-binding motif protein 6 (RBM6) harbors tumor-suppressor activity in many cancers; however, there is a lack of research on the molecular targets and regulatory mechanisms of RBM6. Methods: In this study, we constructed an RBM6 knock-down (shRBM6) model in the HeLa cell line to investigate its functions and molecular targets. Then we applied improved RNA immunoprecipitation coupled with sequencing (iRIP-seq) and whole transcriptome sequencing approaches to investigate the potential role and RNA targets of RBM6. Results: Using The Cancer Genome Atlas dataset, we found that higher expression of RBM6 is associated with a better prognosis in many cancer types. In addition, we found that RBM6 knockdown promoted cell proliferation and inhibited apoptosis, demonstrating that RBM6 may act as an anti-oncogenic protein in cancer cells. RBM6 can regulate the alternative splicing (AS) of genes involved in DNA damage response, proliferation, and apoptosis-associated pathways. Meanwhile, RBM6 knockdown activated type I interferon signaling pathways and inhibited the expression of genes involved in the cell cycle, cellular responses to DNA damage, and DNA repair pathways. The differentially expressed genes (DEGs) by shRBM6 and their involved pathways were likely regulated by the transcription factors undergoing aberrant AS by RBM6 knockdown. For iRIP-seq analysis, we found that RBM6 could interact with a large number of mRNAs, with a tendency for binding motifs GGCGAUG and CUCU. RBM6 bound to the mRNA of cell proliferation- and apoptosis-associated genes with dysregulated AS after RBM6 knockdown. Conclusions: In summary, our study highlights the important role of RBM6, as well as the downstream targets and regulated pathways, suggesting the potential regulatory mechanisms of RBM6 in the development of cancer.

Epigenetic Characteristics in Primary and Recurrent Glioblastoma-Influence on the Clinical Course.

Epigenetic tumor characteristics are in focus for glioblastoma prognosis. This raises the question if these characteristics present with stable expression during the progression of the disease, and if potential temporal instability might influence their prognostic value. A total of 44 patients suffering from glioblastoma who were treated for their primary and relapse tumors were included in the study. Tumor specimens from the initial and recurrent tumor resection were subjected to evaluation of MGMT, p15, and p16 methylation statuses. MiRNA-21, -24, -26a, and -181d expression was evaluated as well. The stability of these epigenetic markers during the progression of the disease was correlated with further clinical data. A Cancer Genome Atlas (TCGA) dataset of 224 glioblastoma patients was used as an independent cohort to validate the results. Instability was observed in all examined epigenetic markers. MGMT methylation changed in 30% of patients, p15 methylation changed in 35%, and p16 methylation changed in 37.5% of cases. MiRNA expression in corresponding initial and relapse tumor specimens varied considerably in general, individual cases presented with a stable expression. Patients with a decreased expression of miRNA-21 in their recurrence tumor showed significantly longer overall survival. These results are supported by the data from TCGA indicating similar results. Epigenetic characteristics may change during the course of glioblastoma disease. This may influence the prognostic value of derived molecular markers.