Malignant peritoneal mesothelioma.

Malignant peritoneal mesothelioma (MPM) is a rare, life-threatening malignant tumor. We present a report of a rare case of a 67-year-old male patient with MPM and severe abdominal pain, bloating, and bloody ascites as manifestations. The diagnosis was confirmed by cytology of ascites aspiration fluid and further verified by laparoscopic exploratory biopsy. The characteristics of signs and clinical manifestations in this case are less common. As everyone knows, asbestos exposure is usually associated with pleural mesothelioma, but only 6%-10% of malignant mesothelioma cases originate from the peritoneum, which is far less than pleural mesothelioma. Generally, its non-specificity provides a huge challenge to medical professionals in its diagnosis, and this is also the main reason for delayed diagnosis. Patients should be vigilant, even though no clear risk factor is observed.

Integrative analyses of prognosis, tumor immunity, and ceRNA network of the ferroptosis-associated gene FANCD2 in hepatocellular carcinoma.

Extensive evidence has revealed that ferroptosis plays a vital role in HCC development and progression. Fanconi anemia complementation group D2 (FANCD2) has been reported to serve as a ferroptosis-associated gene and has a close relationship with tumorigenesis and drug resistance. However, the impact of the FANCD2-related immune response and its mechanisms in HCC remains incompletely understood. In the current research, we evaluated the prognostic significance and immune-associated mechanism of FANCD2 based on multiple bioinformatics methods and databases. The results demonstrated that FANCD2 was commonly upregulated in 15/33 tumors, and only the high expression of FANCD2 in HCC was closely correlated with worse clinical outcomes by OS and DFS analyses. Moreover, ncRNAs, including two major types, miRNAs and lncRNAs, were closely involved in mediating FANCD2 upregulation in HCC and were established in a ceRNA network by performing various in silico analyses. The DUXAP8-miR-29c-FANCD2 and LINC00511-miR-29c-FANCD2 axes were identified as the most likely ncRNA-associated upstream regulatory axis of FANCD2 in HCC. Finally, FANCD2 expression was confirmed to be positively related to HCC immune cell infiltration, immune checkpoints, and IPS analysis, and GSEA results also revealed that this ferroptosis-associated gene was primarily involved in cancer-associated pathways in HCC. In conclusion, our investigations indicate that ncRNA-related modulatory overexpression of FANCD2 might act as a promising prognostic and immunotherapeutic target against HCC.

Nonparametric single-cell multiomic characterization of trio relationships between transcription factors, target genes, and cis-regulatory regions.

The epigenetic control of gene expression is highly cell-type and context specific. Yet, despite its complexity, gene regulatory logic can be broken down into modular components consisting of a transcription factor (TF) activating or repressing the target gene expression through its binding to a cis-regulatory region. We propose a nonparametric approach, TRIPOD, to detect and characterize the three-way relationships between a TF, its target gene, and the accessibility of the TF's binding site using single-cell RNA and ATAC multiomic data. We apply TRIPOD to interrogate the cell-type-specific regulatory logic in peripheral blood mononuclear cells and contrast our results to detections from enhancer databases, cis-eQTL studies, ChIP-seq experiments, and TF knockdown/knockout studies. We then apply TRIPOD to mouse embryonic brain data and identify regulatory relationships, validated by ChIP-seq and PLAC-seq. Finally, we demonstrate TRIPOD on the SHARE-seq data of differentiating mouse hair follicle cells and identify lineage-specific regulation supported by histone marks and super-enhancer annotations. A record of this paper's transparent peer review process is included in the supplemental information.

Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer.

Objective: The mortality rate of ovarian cancer (OC) is the highest among all gynecologic cancers. To predict the prognosis and the efficacy of immunotherapy, we identified new biomarkers. Methods: The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used to extract ovarian cancer transcriptomes. By performing the co-expression analysis, we identified necroptosis-associated long noncoding RNAs (lncRNAs). We used the least absolute shrinkage and selection operator (LASSO) to build the risk model. The qRT-PCR assay was conducted to confirm the differential expression of lncRNAs in the ovarian cancer cell line SK-OV-3. Gene Set Enrichment Analysis, Kaplan-Meier analysis, and the nomogram were used to determine the lncRNAs model. Additionally, the risk model was estimated to evaluate the efficacy of immunotherapy and chemotherapy. We classified necroptosis-associated IncRNAs into two clusters to distinguish between cold and hot tumors. Results: The model was constructed using six necroptosis-associated lncRNAs. The calibration plots from the model showed good consistency with the prognostic predictions. The overall survival of one, three, and five-year areas under the ROC curve (AUC) was 0.691, 0.678, and 0.691, respectively. There were significant differences in the IC50 between the risk groups, which could serve as a guide to systemic treatment. The results of the qRT-PCR assay showed that AL928654.1, AL133371.2, AC007991.4, and LINC00996 were significantly higher in the SK-OV-3 cell line than in the Iose-80 cell line (P < 0.05). The clusters could be applied to differentiate between cold and hot tumors more accurately and assist in accurate mediation. Cluster 2 was more vulnerable to immunotherapies and was identified as the hot tumor. Conclusion: Necroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors.

Evaluating the utility of an immune checkpoint-related lncRNA signature for identifying the prognosis and immunotherapy response of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer globally. However, the survival rate of lung adenocarcinoma patients remains low. Immune checkpoints and long noncoding RNAs are emerging as vital tools for predicting the immunotherapeutic response and outcomes of patients with lung adenocarcinoma. It is critical to identify lncRNAs associated with immune checkpoints in lung adenocarcinoma patients. In this study, immune checkpoint-related lncRNAs (IClncRNAs) were analysed and identified by coexpression. Based on the immune checkpoint-related lncRNAs, we divided patients with lung adenocarcinoma into two clusters and constructed a risk model. Kaplan-Meier analysis, Gene Set Enrichment Analysis, and nomogram analysis of the 2 clusters and the risk model were performed. Finally, the potential immunotherapeutic prediction value of this model was discussed. The risk model consisting of 6 immune checkpoint-related lncRNAs was an independent predictor of survival. Through regrouping the patients with this model, we can distinguish between them more effectively in terms of their immunotherapeutic response, tumour microenvironment, and chemotherapy response. This risk model based on immune checkpoint-based lncRNAs may have an excellent clinical value for predicting the immunotherapeutic response and outcomes of patients with LUAD.

Single-cell chromatin profiling of the primitive gut tube reveals regulatory dynamics underlying lineage fate decisions.

Development of the gastrointestinal system occurs after gut tube closure, guided by spatial and temporal control of gene expression. However, it remains unclear what forces regulate these spatiotemporal gene expression patterns. Here we perform single-cell chromatin profiling of the primitive gut tube to reveal organ-specific chromatin patterns that reflect the anatomical patterns of distinct organs. We generate a comprehensive map of epigenomic changes throughout gut development, demonstrating that dynamic chromatin accessibility patterns associate with lineage-specific transcription factor binding events to regulate organ-specific gene expression. Additionally, we show that loss of Sox2 and Cdx2, foregut and hindgut lineage-specific transcription factors, respectively, leads to fate shifts in epigenomic patterns, linking transcription factor binding, chromatin accessibility, and lineage fate decisions in gut development. Notably, abnormal expression of Sox2 in the pancreas and intestine impairs lineage fate decisions in both development and adult homeostasis. Together, our findings define the chromatin and transcriptional mechanisms of organ identity and lineage plasticity in development and adult homeostasis.

Immune checkpoints related-LncRNAs can identify different subtypes of lung cancer and predict immunotherapy and prognosis.

BACKGROUND: Non-small cell lung cancer is the most common subtype of lung cancer in the world. However, the survival rate of non-small cell lung cancer patients remains low currently. Immune checkpoint and long non-coding RNAs are emerging as critical roles in prognostic significance and the immunotherapeutic response of non-small cell lung cancer. It is critical to discern LncRNAs related with immune checkpoints in patients with Non-small cell lung cancer. METHODS: In this study, immune checkpoint-linked LncRNAs were determined and achieved by the co-expression analysis. Immune checkpoint-linked LncRNAs with noteworthy prognostic value (P < 0.05) gained were next utilized to separate into two cluster by non-negative matrix factorization (NMF). Univariate and a least absolute shrinkage and selection operator were applied to construct an immune checkpoint-linked LncRNAs model. Kaplan-Meier analysis, Gene Set Enrichment Analysis, and the nomogram were utilized to investigate the LncRNAs model. Lastly, the capability immunotherapy and chemotherapy prediction value of this risk model were also estimated. RESULTS: The model consisting of ten immune checkpoint-related LncRNAs was acknowledged to be a self-determining predictor of prognosis. Through regrouping the NSCLC patients by this model, difference between them more efficiently on immunotherapeutic response, tumor microenvironment and chemotherapy response could be discovered. This risk model related to the immune checkpoint-based LncRNAs may have an excellent clinical prediction for prognosis and the immunotherapeutic response in patients with NSCLC. CONCLUSIONS: We performed an integrative analysis of LncRNAs linked with immune checkpoints and emphasized the significance of NSCLC subtypes classification, immune checkpoints related LncRNAs in estimating the tumor microenvironment score, immune cell infiltration of the tumor, immunotherapy, and chemotherapy response.

NcRNA-regulated CAPZA1 associated with prognostic and immunological effects across lung adenocarcinoma.

Recent discoveries have suggested that the F-actin capping protein α1 subunit (CAPZA1) in various human tumors could play a significantly important role in regulating cell proliferation, metastasis, and epithelial-mesenchymal transition. However, the immune-regulating role of CAPZA1 in the initiation and development of lung adenocarcinoma (LUAD) remains unclear. In our research, we first found that CAPZA1 serves as an oncogene in pan-cancers from the TCGA data and higher CAPZA1 expression process unfavorably prognostic value in LUAD based on starBase database, PrognoScan, and LOGpc database. Then, in our analyses, lncRNAs AC026356.1 in LUAD acted as a competitive endogenous RNA (ceRNA) of miR-30d-5p, which might be the possible regulatory miRNA of CAPZA1 based on the starBase database. Finally, we confirmed that CAPZA1 expression had a tightly positive correlation with immune infiltration cells, immune infiltration markers, TMB, MSI, immune score, stromal score, and immune checkpoints, indicating that CAPZA1 was a markedly reliable therapeutic target for immunological antitumor strategies. In conclusion, our investigations revealed that CAPZA1 might function as an immune-associated biomarker in the development and treatment of LUAD, thereby acting as a promising prognostic and therapeutic target against LUAD.

The TP53-Related Signature Predicts Immune Cell Infiltration, Therapeutic Response, and Prognosis in Patients With Esophageal Carcinoma.

TP53 mutation (TP53MUT) is one of the most common gene mutations and frequently occurs in many cancers, especially esophageal carcinoma (ESCA), and it correlates with clinical prognostic outcomes. Nevertheless, the mechanisms by which TP53MUT regulates the correlation between ESCA and prognosis have not been sufficiently studied. Here, in the current research, we constructed a TP53MUT-related signature to predict the prognosis of patients with esophageal cancer and successfully verified this model in patients in the TP53 mutant group, esophageal squamous cell carcinoma group, and adenocarcinoma group. The risk scores proved to be better independent prognostic factors than clinical features, and prognostic features were combined with other clinical features to establish a convincing nomogram to predict overall survival from 1 to 3 years. In addition, we further predicted the tumor immune cell infiltration, chemical drugs, and immunotherapy responses between the high-risk group and low risk group. Finally, the gene expression of the seven-gene signature (AP002478.1, BHLHA15, FFAR2, IGFBP1, KCTD8, PHYHD1, and SLC26A9) can provide personalized prognosis prediction and insights into new treatments.

An Extracellular Matrix-Based Signature Associated With Immune Microenvironment Predicts the Prognosis and Therapeutic Responses of Patients With Oesophageal Squamous Cell Carcinoma.

Evidence has suggested that the cancer-associated extracellular matrix (ECM) could be recognised as immune-related biomarkers that modulate tumour progression and expansion. However, the ECM-associated immune effect on esophageal squamous cell carcinoma (ESCC) prognosis and therapy has not been well characterised. In our study, we first constructed an ECM-related signature including four genes CST1, NELL2, ADAMTSL4, and ANGPTL7 by multivariate Cox regression analyses. This signature could serve as a marker to evaluate the prognosis of patients with ESCC and was successfully validated in testing and combined (training plus testing) cohorts. We also found that there were significant different therapeutic responses to chemotherapy and targeted drugs between the high-risk and low-risk groups of patients defined by the signature. Furthermore, the expression of four genes and immune function analysis suggested that this ECM-related signature gene might play important roles in the changes of the tumour microenvironment. In conclusion, our findings demonstrated that the ECM-related signature might serve as an independent prognostic factor and provide a potential biomarker for chemotherapy responses for patients with ESCC.

Identification of a PLCE1­regulated competing endogenous RNA regulatory network for esophageal squamous cell carcinoma.

Phospholipase C epsilon 1 (PLCE1) and the competing endogenous RNA (ceRNA) network are crucial for tumorigenesis and the progression of esophageal squamous cell carcinoma (ESCC). However, whether PLCE1 can regulate the ceRNA network in ESCC has not been clarified. In the present study, we aimed to identify the PLCE1­regulated ceRNA network and further elucidate the regulatory mechanisms by which ESCC is promoted. Microarray analysis was used to identify differentially expressed lncRNAs (DELs) and differentially expressed genes (DEGs) from three pairs of samples of PLCE­silenced Eca109 and control Eca109 cells. Next, the ceRNA regulatory network was established and visualized in Cytoscape, and functional enrichment analysis was performed to analyze DEGs from ceRNAs. Protein­protein interaction (PPI) networks among the DEGs were established by the STRING database to screen hub genes. Kaplan­Meier survival analysis was used to validate hub genes. Finally, PLCE1­related hub gene/lncRNA/miRNA axes were also constructed based on the ceRNA network. A total of 105 DELs and 346 DEGs were found to be dysregulated in the microarray data (|log2FC| >1.5, adjusted P<0.05). We constructed a PLCE1­regulated ceRNA network that incorporated 12 lncRNAs, 43 miRNAs, and 169 mRNAs. Functional enrichment analysis indicated that the DEGs might be associated with ESCC onset and development. A PPI network was established, and 9 hub genes [WD and tetratricopeptide repeats 1 (WDTC1), heat shock protein family A (Hsp70) member 5 (HSPA5), N­ethylmaleimide sensitive factor, vesicle fusing ATPase (NSF), fibroblast growth factor 2 (FGF2), cyclin dependent kinase inhibitor 1A (CDKN1A or P21), bone morphogenetic protein 2 (BMP2), complement C3 (C3), GM2 ganglioside activator (GM2A) and discs large MAGUK scaffold protein 4 (DLG4)] were determined from the network. Kaplan­Meier survival analysis validated four hub genes (BMP2, CDKN1A, GM2A, and DLG4) that were treated as prognostic factors. Ultimately, hub gene/lncRNA/miRNA subnetworks were obtained based on the 4 hub genes, 13 DEmiRNAs, and 10 DELs. In conclusion, the PLCE1­regulated ceRNA contributes to the onset and progression of ESCC and the underlying molecular mechanisms may provide insights into personalized prognosis and new therapies for ESCC patients.

CD155-Prognostic and Immunotherapeutic Implications Based on Multiple Analyses of Databases Across 33 Human Cancers.

Growing evidence has suggested that CD155 participates in the regulation of many biological processes ranging cell growth, invasion, and migration from regulation of immune responses in most malignances. However, the impact of prognostic value and CD115-related immune response on the survival in multiple cancers remains incompletely clear. In our study, we assessed the prognostic significance and immune-associated mechanism of CD155 based on data from multiple databases and methods, including UCSC Xena, Oncomine, PrognoScan. We identified that CD155 was commonly upregulated in most human cancers, and High expression of CD155 was closely correlated with unfavorable clinical outcomes in 10/33 of human cancers, while CD155 at low level was responsible for better survival in KICH and PAAD. More intriguingly, CD155 expression had a significant interaction with immune function in several tumors by analyzing Tumor mutational burden and microsatellite in stability, immune score and stromal score. The correlation between immune infiltration and CD155 expression also indicated that CD155 expression positively correlated with CD4+ T cells in Head and Neck squamous cell carcinoma, Lung adenocarcinoma and Colon adenocarcinoma, while had inversely interaction with CD8+ T in Kidney renal clear cell carcinoma and Head and Neck squamous cell carcinoma as well as Tregs in Skin Cutaneous Melanoma, Head and Neck squamous cell carcinoma and Bladder Urothelial Carcinoma. These findings indicate CD155 correlates with cancer immunotherapy function. In conclusions, our observations revealed CD155 might function as immune-associated system in the development of human cancers, and acted as a promising prognostic and therapeutic target against human cancers.

RAI14 Is a Prognostic Biomarker and Correlated With Immune Cell Infiltrates in Gastric Cancer.

OBJECTIVE: To analyze the expression and clinical significance of retinoic acid-induced protein 14 (RAI14) in gastric cancer and its relationship with immune cell infiltration by mining databases such as Oncomine, TIMER, UALCAN, and Kaplan Meier Plotter. METHODS: RAI14 expression in various cancer types was analyzed using the Oncomine and TIMER databases. We used the Kaplan-Meier Plotter and UALCAN databases to evaluate the impact of RAI14 on clinicopathological parameters in gastric cancer. The correlation between RAI14 expression and immune cell invasion was studied using TIMER. TIMER was also used to analyze the correlation between RAI14 expression and marker levels of tumor-infiltrating immune cells. RESULTS: High RAI14 expression in gastric cancer was significantly associated with poor overall survival (OS; hazard ratio [HR] = 1.82, 95% confidence interval [CI] = 1.53-2.15, P < 0.001) and poor progression-free survival (PFS; HR = 2.16, 95% CI = 1.77-2.65, P < 0.001). Furthermore, high RAI14 expression was significantly associated with poor prognosis of patients with stage 2-4 gastric cancer, but not with OS and PFS of stage 1 patients (OS P = 0.17; PFS P = 0.09), and patients with stage N0 PFS had nothing to do (PFS P = 0.238). RAI14 expression was positively correlated with the infiltration levels of monocytes, tumor-associated macrophages, macrophages, neutrophils, and Treg cells in gastric cancer. Besides, RAI14 expression was closely related to various marker genes in immune cells. CONCLUSION: RAI14 is highly expressed in gastric cancer, and its expression level is correlated with the prognosis of patients with gastric cancer. RAI14 plays also an important role in the recruitment and regulation of infiltrating immune cells and is, thus, expected to become a target for the optimal treatment of gastric cancer.

A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulation.

BACKGROUND: Cryo-electron tomography is an important and powerful technique to explore the structure, abundance, and location of ultrastructure in a near-native state. It contains detailed information of all macromolecular complexes in a sample cell. However, due to the compact and crowded status, the missing edge effect, and low signal to noise ratio (SNR), it is extremely challenging to recover such information with existing image processing methods. Cryo-electron tomogram simulation is an effective solution to test and optimize the performance of the above image processing methods. The simulated images could be regarded as the labeled data which covers a wide range of macromolecular complexes and ultrastructure. To approximate the crowded cellular environment, it is very important to pack these heterogeneous structures as tightly as possible. Besides, simulating non-deformable and deformable components under a unified framework also need to be achieved. RESULT: In this paper, we proposed a unified framework for simulating crowded cryo-electron tomogram images including non-deformable macromolecular complexes and deformable ultrastructures. A macromolecule was approximated using multiple balls with fixed relative positions to reduce the vacuum volume. A ultrastructure, such as membrane and filament, was approximated using multiple balls with flexible relative positions so that this structure could deform under force field. In the experiment, 400 macromolecules of 20 representative types were packed into simulated cytoplasm by our framework, and numerical verification proved that our method has a smaller volume and higher compression ratio than the baseline single-ball model. We also packed filaments, membranes and macromolecules together, to obtain a simulated cryo-electron tomogram image with deformable structures. The simulated results are closer to the real Cryo-ET, making the analysis more difficult. The DOG particle picking method and the image segmentation method are tested on our simulation data, and the experimental results show that these methods still have much room for improvement. CONCLUSION: The proposed multi-ball model can achieve more crowded packaging results and contains richer elements with different properties to obtain more realistic cryo-electron tomogram simulation. This enables users to simulate cryo-electron tomogram images with non-deformable macromolecular complexes and deformable ultrastructures under a unified framework. To illustrate the advantages of our framework in improving the compression ratio, we calculated the volume of simulated macromolecular under our multi-ball method and traditional single-ball method. We also performed the packing experiment of filaments and membranes to demonstrate the simulation ability of deformable structures. Our method can be used to do a benchmark by generating large labeled cryo-ET dataset and evaluating existing image processing methods. Since the content of the simulated cryo-ET is more complex and crowded compared with previous ones, it will pose a greater challenge to existing image processing methods.

Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1) Are Associated with Progression and Prognosis of Esophageal Cancer as Identified by Integrated Expression Profiles Analysis.

BACKGROUND Esophageal cancer is a malignant tumor with a complex pathogenesis and a poor 5-year survival rate, which encourages researchers to explore its molecular mechanisms deeper to improve the prognosis. MATERIAL AND METHODS DEGs were from 4 Gene Expression Omnibus (GEO) databases (GSE92396, GSE20347, GSE23400, and GSE45168) including 87 esophageal tumor samples and 84 normal samples. We performed Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Protein-Protein interaction (PPI) analysis, and GeneMANIA to identify the DEGs. Gene set enrichment analysis (GSEA) and Kaplan-Meier survival analyses were performed. RESULTS There was an overlapping subset consisting of 120 DEGs that was present in all esophageal tumor samples. The DEGs were enriched in extracellular matrix (ECM)-receptor interaction, as well as focal adhesion and transcriptional mis-regulation in cancer. The 2 most crucial regulatory pathways in esophageal cancer were the amebiasis pathway and the PI3K-Akt signaling pathway. Secreted phosphoprotein 1 (SPP1) and fibronectin 1 (FN1) were selected and verified in an independent cohort and samples using the TCGA and GTEx projects. Gene set enrichment analysis (GSEA) showed that proteasome and nucleotide excision repair were 2 most differentially enriched pathways in the SPP1 high-expression phenotype, and ECM-receptor interaction and focal adhesion in FN1 high-expression phenotype. Kaplan-Meier survival analysis showed that SPP1 and FN1 were significantly positively related to overall survival and had the potential to predict patient relapse. CONCLUSIONS Our analysis is the first to show that SPP1 and FN1 might work as biological markers of progression and prognosis in esophageal carcinoma (ESCA).

Immune signature of T follicular helper cells predicts clinical prognostic and therapeutic impact in lung squamous cell carcinoma.

Lung cancer is the leading reason of cancer-related death from cancer globally for both men and women. Recently, tumor immune heterogeneity has been implicated in cancer clinical outcome. However, this prognostic significance of immune cell types in lung squamous cell carcinoma (LUSC) is unclear and should be systematically investigated. Two microarray datasets (GSE67061 and GSE2088) from the Gene Expression Omnibus (GEO) database were downloaded and then integrated to estimate the fraction of 22 immune cell types by CIBERSORT algorithm. To validate the estimation for LUSC, the data of LUSC TCGA were also assessed in order to determine specific infiltrating immune cell type closely correlated with LUSC patients' survival determined by Cox regression analyses. Immunotherapeutic and chemotherapeutic response between the LUSC patients were also evaluated. T follicular helper cells were obtained by Cox regression analysis to develop the prognostic signature. According to this immune prognostic risk score, immune signature of T follicular helper cells is an independent and specific prognostic signature for predictions of LUSC patient overall survival. Moreover, high-risk group exhibited less expression of N6-methyladenosine (m6A) RNA methylation regulator including ALKBH5, METTL3, HNRNPC and KIAA1429 and was much more sensitive to immunotherapy and chemotherapy. This study suggests that this immune signature is important determinants of prognosis in LUSC and may provide potential prognostic biomarker or therapeutic target for immunotherapeutic and chemotherapeutic development.