Enzyme-Instructed Photoactivatable Supramolecular Antigens on Cancer Cell Membranes for Precision-Controlled T-Cell-Based Cancer Immunotherapy.

Cancer immunotherapies based on cytotoxic CD8+ T lymphocytes (CTLs) are highly promising for cancer treatment. The specific interaction between T-cell receptors and peptide-MHC-I complexes (pMHC-I) on cancer cell membranes critically determines their therapeutic outcomes. However, the lack of appropriate endogenous antigens for MHC-I presentation disables tumor recognition by CTLs. By devising three antigen-loaded self-assembling peptides of pY-K(Ag)-ERGD, pY-K(Ag)-E, and Y-K(Ag)-ERGD to noncovalently generate light-activatable supramolecular antigens at tumor sites in different manners, we report pY-K(Ag)-ERGD as a promising candidate to endow tumor cells with pMHC-I targets on demand. Specifically, pY-K(Ag)-ERGD first generates low-antigenic supramolecular antigens on cancer cell membranes, and a successive light pulse allows antigen payloads to efficiently release from the supramolecular scaffold, directly producing antigenic pMHC-I. Intravenous administration of pY-K(Ag)-ERGD enables light-controlled tumor inhibition when combined with adoptively transferred antigen-specific CTLs. Our strategy is feasible for broadening tumor antigen repertoires for T-cell immunotherapies and advancing precision-controlled T-cell immunotherapies.

Inhibition of Hsp110-STAT3 interaction in endothelial cells alleviates vascular remodeling in hypoxic pulmonary arterial Hypertension model.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a progressive and devastating disease characterized by pulmonary vascular remodeling which is associated with the malignant phenotypes of pulmonary vascular cells. Recently, the effects of heat shock protein 110 (Hsp110) in human arterial smooth muscle cells were reported. However, the underlying roles and mechanisms of Hsp110 in human pulmonary arterial endothelial cells (HPAECs) that was disordered firstly at the early stage of PAH remain unknown. METHODS: In this research, the expression of Hsp110 in PAH human patients and rat models was investigated, and the Hsp110 localization was determined both in vivo and in vitro. The roles and mechanism of elevated Hsp110 in excessive cell proliferation and migration of HPAECs were assessed respectively exposed to hypoxia. Small molecule inhibitors targeting Hsp110-STAT3 interaction were screened via fluorescence polarization, anti-aggregation and western blot assays. Moreover, the effects of compound 6 on HPAECs abnormal phenotypes in vitro and pulmonary vascular remodeling of hypoxia-indued PAH rats in vivo by interrupting Hsp110-STAT3 interaction were evaluated. RESULTS: Our studies demonstrated that Hsp110 expression was increased in the serum of patients with PAH, as well as in the lungs and pulmonary arteries of PAH rats, when compared to their respective healthy subjects. Moreover, Hsp110 levels were significantly elevated in HPAECs under hypoxia and mediated its aberrant phenotypes. Furthermore, boosted Hsp110-STAT3 interaction resulted in abnormal proliferation and migration via elevating p-STAT3 and c-Myc in HPAECs. Notably, we successfully identified compound 6 as potent Hsp110-STAT3 interaction inhibitor, which effectively inhibited HPAECs proliferation and migration, and significantly ameliorated right heart hypertrophy and vascular remodeling of rats with PAH. CONCLUSIONS: Our studies suggest that elevated Hsp110 plays a vital role in HPAECs and inhibition of the Hsp110-STAT3 interaction is a novel strategy for improving vascular remodeling. In addition, compound 6 could serve as a promising lead compound for developing first-in-class drugs against PAH.

Clinical M2 macrophages-related genes to aid therapy in pancreatic ductal adenocarcinoma.

BACKGROUND: Increasing evidence supports that infiltration M2 Macrophages act as pivotal player in tumor progression of pancreatic ductal adenocarcinoma (PDAC). Nonetheless, comprehensive analysis of M2 Macrophage infiltration and biological roles of hub genes (FAM53B) in clinical outcome and immunotherapy was lack. METHOD: The multiomic data of PDAC samples were downloaded from distinct datasets. CIBERSORT algorithm was performed to uncover the landscape of TIME. Weighted gene co-expression network analysis (WGCNA) was performed to identify candidate module and significant genes associated with M2 Macrophages. Kaplan-Meier curve and receiver operating characteristic (ROC) curves were applied for prognosis value validation. Mutation data was analyzed by using "maftools" R package. Gene set variation analysis (GSVA) was employed to assign pathway activity estimates to individual sample. Immunophenoscore (IPS) was implemented to estimate immunotherapeutic significance of risk score. The half-maximal inhibitory concentration (IC50) of chemotherapeutic drugs was predicted by using the pRRophetic algorithm. Finally, quantitative real-time polymerase chain reaction was used to determine FAM53B mRNA expression and TIMER database was utilized to uncover its possible role in immune infiltration of PDAC. RESULTS: Herein, 17,932 genes in 234 samples (214 tumor and 20 normal) were extracted from three platforms. Taking advantage of WGCNA, significant module (royalblue) and 135 candidate genes were considered as M2 Macrophages-related genes. Subsequently, risk signature including 5 hub genes was developed by multiple analysis, which exhibited excellent prognostic performance. Besides, comprehensive prognostic nomogram was constructed to quantitatively estimate risk. Then, intrinsic link between risk score with tumor mutation burden (TMB) was explored. Additionally, risk score significantly correlated with diversity of tumor immune microenvironment (TIME). PDAC samples within different risk presented diverse signaling pathways activity and experienced significantly distinct sensitivity to administering chemotherapeutic or immunotherapeutic agents. Finally, the biological roles of FAM53B were revealed in PDAC. CONCLUSIONS: Taken together, comprehensive analyses of M2 Macrophages profiling will facilitate prognostic prediction, delineating complexity of TIME, and contribute insight into precision therapy for PDAC.

Comparison of combined anterior-posterior approach versus posterior-only approach in neuromuscular scoliosis: a systematic review and meta-analysis.

PURPOSE: Neuromuscular scoliosis (NS) is a complicated spinal disorder, and it could be treated through posterior-only approach (POA) or combined anterior-posterior approach (APA), which one is better and how to choose the surgical tactic is still in controversy. So comparing POA with APA parameters in the treatment of NS is meaningful. METHODS: Database of PubMed, Embase and Cochrane Library was systematically searched, and the studies, which focus on the comparisons of POA and APA in the treatment of NS, were included. The meta-analysis was performed by RevMan 5.3. RESULTS: Seven retrospective studies with 602 patients were included in meta-analysis. In previous analysis, statistically significant differences were observed in the major parameters between APA and POA. However, the results of subgroup meta-analysis, which focused on the correction angle and loss angle to eliminate the influence of different preoperative angles, were tend to no difference between two groups, except loss angle of scoliosis (MD, 6.4; 95% CI - 0.19 to 13) and correction angle of pelvic obliquity (MD, - 3.44; 95% CI - 6.71 to - 0.17). CONCLUSIONS: Our meta-analysis suggested that POA was similar to APA in the correction of scoliosis in coronal and sagittal planes. However, APA had advantages in the correction of pelvic obliquity and decreasing the loss of angle between postoperation and follow-up in main scoliosis, whereas POA had advantages in operative time, blood loss, duration of hospital stay and complications. LEVEL OF EVIDENCE: Level II. These slides can be retrieved under Electronic Supplementary Material.

[Progress in the regulation of bone remodeling at the cellular level].

Bone remodeling requires an intimate cross-talk between osteoclasts and osteoblasts and is tightly coordinated with regulatory proteins that interact through complex autocrine/paracrine processes. Osteocytes, bone lining cells, osteomacs and vascular endothelial cells also regulate bone remodeling in the basic multicellular unit (BMU) via cell signaling networks of ligand-receptor complexes. In addition, through secreted and membrane-bound factors in the bone microenvironment, T and B lymphocytes mediate bone homeostasis for osteoimmunology. Osteoporosis and other bone diseases occur because multicellular communication within the BMU is disrupted. This review focuses on the roles of the cells in the BMU and the interaction between these cells and the factors involved in regulating bone remodeling at the cellular level. Understanding the process of bone remodeling and related genes could help us to lay the foundation for drug development against bone diseases.

Empirical analysis of spatial heterogeneity in the development of China's National Fitness Plan.

PURPOSE: The National Fitness Plan (NFP) is a vital initiative aimed at realizing Healthy China 2030. This study assessed spatial heterogeneity in the NFP development and the socioeconomic factors contributing to this inequality. METHODS: Data from 31 administrative regions in 2021 were analyzed using four NFP development metrics. Spatial autocorrelation was evaluated using global Moran's I, followed by global and local regression models for non-random spatial patterns. RESULTS: National physical fitness exhibited significant clustering (z = 5.403), notably a high-high cluster in East China. The global regression model identified three socioeconomic factors in the geographically weighted regression model: per capita disposable income and the number of public buses positively affected national physical fitness, while general public budget expenditure had a negative impact. CONCLUSIONS: Persistent unequal NFP development is projected due to income disparities in economically backward regions. To promote the NFP effectively, a cost-efficient strategy includes creating 15-minute fitness circles, especially by establishing public sports facilities in Western China communities. These findings inform policy priorities for advancing the NFP towards Healthy China 2030.

Allosteric site identification, virtual screening and discovery of a sulfonamide Hsp110-STAT3 interaction inhibitor for the treatment of hypoxic pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is a severe pulmonary vascular disorder marked by vascular remodeling, which is linked to the malignant phenotypes of pulmonary vascular cells. The prevailing therapeutic approaches for PAH tend to neglect the potential role of vascular remodeling, leading to the clinical prognosis remains poor. Previously, we first demonstrated that heat shock protein (Hsp110) was significantly activated to boost Hsp110-STAT3 interaction, which resulted in abnormal proliferation and migration of human pulmonary arterial endothelial cells (HPAECs) under hypoxia. In the present study, we initially postulated the allosteric site of Hsp110, performed a virtual screening and biological evaluation studies to discover novel Hsp110-STAT3 interaction inhibitors. Here, we identified compound 29 (AN-329/43448068) as the effective inhibitor of HPAECs proliferation and the Hsp110-STAT3 association with good druggability. In vitro, 29 significantly impeded the chaperone function of Hsp110 and the malignant phenotypes of HPAECs. In vivo, 29 remarkably attenuated pulmonary vascular remodeling and right ventricular hypertrophy in hypoxia-induced PAH rats (i.g). Altogether, our data support the conclusion that it not only provides a novel lead compound but also presents a promising approach for subsequent inhibitor development targeting Hsp110-STAT3 interaction.

Utilizing machine learning to integrate single-cell and bulk RNA sequencing data for constructing and validating a novel cell adhesion molecules related prognostic model in gastric cancer.

BACKGROUND: Cell adhesion molecules (CAMs) play a vital role in cell-cell interactions, immune response modulation, and tumor cell migration. However, the unique role of CAMs in gastric cancer (GC) remains largely unexplored. METHODS: This study characterized the genetic alterations and mRNA expression of CAMs. The role of CD34, a representative molecule, was validated in 375 GC tissues. The activity of the CAM pathway was further tested using single-cell and bulk characterization. Next, data from 839 patients with GC from three cohorts was analyzed using univariate Cox and random survival forest methods to develop and validate a CAM-related prognostic model. RESULTS: Most CAM-related genes exhibited multi-omics alterations and were associated with clinical outcomes. There was a strong correlation between increased CD34 expression and advanced clinical staging (P = 0.026), extensive vascular infiltration (P = 0.003), and unfavorable prognosis (Log-rank P = 0.022). CD34 expression was also found to be associated with postoperative chemotherapy and tumor immunotherapy response. Furthermore, the CAM pathway was significantly activated and mediated poor prognosis. Additionally, eight prognostic signature genes (PSGs) were identified in the training cohort. There was a substantial upregulation of the expression of immune checkpoints and a pronounced infiltration of immune cells in GC tissues with high PSG score, which is consistent with the prediction of increased sensitivity to immunotherapy. Moreover, 9 compounds from the CTRPv2 database and 13 from the Profiling Relative Inhibition Simultaneously in Mixture (PRISM) database were identified as potential therapeutic drugs for patients with GC with high PSG score. CONCLUSION: Thorough understanding of CAM pathways regulation and the innovative PSG score model hold significant implications for medical diagnosis, potentially enhancing personalized treatment strategies and improving patient outcomes in GC management.

Discovery and Optimization of Hsp110 and sGC Dual-Target Regulators for the Treatment of Pulmonary Arterial Hypertension.

Currently, bifunctional agents with vasodilation and ameliorated vascular remodeling effects provide more advantages for the treatment of pulmonary arterial hypertension (PAH). In this study, we first screened the hit 1 with heat shock protein 110 (Hsp110) inhibition effect from our in-house compound library with soluble guanylate cyclase (sGC) activity. Subsequently, a series of novel bisamide derivatives were designed and synthesized as Hsp110/sGC dual-target regulators based on hit 1. Among them, 17i exhibited optimal Hsp110 and sGC molecular activities as well as remarkable cell malignant phenotypes inhibitory and vasodilatory effects in vitro. Moreover, compared to riociguat, 17i showed superior efficacy in attenuating pulmonary vascular remodeling and right ventricular hypertrophy via Hsp110 suppression in hypoxia-induced PAH rat models (i.g.). Notably, our study successfully demonstrated that the simultaneous regulation of Hsp110 and sGC dual targets was a novel and feasible strategy for PAH therapy, providing a promising lead compound for anti-PAH drug discovery.

Retrospective study of influencing factors on the outcomes of luteal phase stimulation in patients with dual stimulation.

Background: Dual/double stimulation (DS) is an ovarian stimulation strategy that has emerged in recent years; it is characterized by two rounds of ovarian stimulation and oocyte retrieval in the same menstrual cycle. DS can greatly shorten the time required to obtain valid embryos in assisted reproduction. For fertility preservation, DS can speed up oocyte storage process. However, factors influencing luteal phase ovarian stimulation (LPS) outcomes in DS have not been elucidated. Methods: A total of 156 cycles from 78 cases were studied. Patients were grouped and analyzed according to their follicular phase ovarian stimulation (FPS) types. Female ages, ovarian stimulation protocols, number of oocytes retrieved, embryo quality were recorded. Comparisons of outcomes were conducted between different groups. Results: Our study found that LPS obtained similar outcomes to follicular phase stimulation (FPS), and that the choice of FPS protocol affected the efficiency of LPS, the antagonist protocol and progestin-primed ovarian stimulation (PPOS) protocol resulted in better embryo outcomes in LPS. In LPS of DS, sufficient stimulation duration was the guarantee of embryo quality (number of available embryos: ß = 0.145, 95% CI [0.078-0.211], P = 0.000; number of high-quality embryos: ß = 0.114, 95% CI [0.057-0.171], P = 0.000). Discussion: This study provided ideas for the precise use of DS. We suggest to further expand the sample size of DS in the future, conduct prospective controlled studies, unify the sample size of each subgroup, include the ovarian reserve of patients in the grouping basis, and exclude the influence of male factors. We hope that this study will help further refinement of DS so as to maximize patient benefits from it. Conclusion: When the DS strategy is considered in the follicular phase, the antagonist protocol and PPOS protocol are more recommended for better embryo outcomes in LPS. During LPS, adequate ovarian stimulation duration is the most important guarantee for LPS efficiency.

Clinical application of molecular residual disease detection by circulation tumor DNA in solid cancers and a comparison of technologies: review article.

Molecular residual disease (MRD), detected by circulating tumor DNA (ctDNA) can be involved in the entire process of solid tumor management, including recurrence prediction, efficacy evaluation, and risk stratification. Currently, the detection technologies are divided into two main categories, as follows: tumor-agnostic and tumor informed. Tumor-informed assay obtains mutation information by sequencing tumor tissue samples before blood MRD monitoring, followed by formulation of a personalized MRD panel. Tumor-agnostic assays are carried out using a fixed panel without the mutation information from primary tumor tissue. The choice of testing strategy may depend on the level of evidence from ongoing randomized clinical trials, investigator preference, cost-effectiveness, patient economics, and availability of tumor tissue. The review describes the difference between tumor informed and tumor agnostic detection. In addition, the clinical application of ctDNA MRD in solid tumors was introduced, with emphasis on lung cancer, colorectal cancer, Urinary system cancer, and breast cancer.

ASAP1 activates the IQGAP1/CDC42 pathway to promote tumor progression and chemotherapy resistance in gastric cancer.

Abnormal expression and remodeling of cytoskeletal regulatory proteins are important mechanisms for tumor development and chemotherapy resistance. This study systematically analyzed the relationship between differential expression of cytoskeleton genes and prognosis in gastric cancer (GC). We found the Arf GTP-activating protein ASAP1 plays a key role in cytoskeletal remodeling and prognosis in GC patients. Here we analyzed the expression level of ASAP1 in tissue microarrays carrying 564 GC tissues by immunohistochemistry. The results showed that ASAP1 expression was upregulated in GC cells and can be served as a predictor of poor prognosis. Moreover, ASAP1 promoted the proliferation, migration, and invasion of GC cells both in vitro and in vivo. We also demonstrated that ASAP1 inhibited the ubiquitin-mediated degradation of IQGAP1 and thus enhanced the activity of CDC42. The activated CDC42 upregulated the EGFR-MAPK pathway, thereby promoting the resistance to chemotherapy in GC. Taken together, our results revealed a novel mechanism by which ASAP1 acts in the progression and chemotherapy resistance in GC. This may provide an additional treatment option for patients with GC.

Radiomics based on machine learning algorithms could predict prognosis and postoperative chemotherapy benefits of patients with gastric cancer: a retrospective cohort study.

Background: Traditional clinical characteristics have certain limitations in evaluating cancer prognosis. The radiomics features provide information on tumor morphology, tissue texture, and hemodynamics, which can accurately reflect personalized predictions. This study investigated the clinical value of radiomics features on contrast-enhanced computed tomography (CT) images in predicting prognosis and postoperative chemotherapy benefits for patients with gastric cancer (GC). Methods: For this study, 171 GC patients who underwent radical gastrectomy and pathology confirmation of the malignancy at the First Affiliated Hospital of Wenzhou Medical University were retrospectively enrolled. The general information, pathological characteristics, and postoperative chemotherapy information were collected. Patients were also monitored through telephone interviews or outpatient treatment. GC patients were randomly divided into the developing cohort (n=120) and validation cohort (n=51). The intra-tumor areas of interest inside the tumors were delineated, and 1,218 radiomics features were extracted. The optimal radiomics risk score (RRS) was constructed using 8 machine learning algorithms and 29 algorithm combinations. Furthermore, a radiomics nomogram that included clinicopathological characteristics was constructed and validated through univariate and multivariate Cox analyses. Results: Eleven prognosis-related features were selected, and an RRS was constructed. Kaplan-Meier curve analysis showed that the RRS had a high prognostic ability in the developing and validation cohorts (log-rank P<0.01). The RRS was higher in patients with a larger tumor size (≥3 cm), higher Charlson score (≥2), and higher clinical stage (Stages III and IV) (all P<0.001). Furthermore, GC patients with a higher RRS significantly benefited from postoperative chemotherapy. The results of univariate and multivariate Cox regression analyses demonstrated that the RRS was an independent risk factor for overall survival (OS) and disease-free survival (DFS) (P<0.001). A visual nomogram was established based on the significant factors in multivariate Cox analysis (P<0.05). The C-index was 0.835 (0.793-0.877) for OS and 0.733 (0.677-0.789) for DFS in the developing cohort. The calibration curve also showed that the nomogram had good agreement. Conclusions: A nomogram that combines the RRS and clinicopathological characteristics could serve as a novel noninvasive preoperative prediction model with the potential to accurately predict the prognosis and chemotherapy benefits of GC patients.

NSUN2 Promotes Tumor Progression and Regulates Immune Infiltration in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in the head and neck with a complex etiology, such as environmental factors, genetic factors, and Epstein-Barr virus infection. The NOP2/Sun domain family, member 2 (NSUN2) is a methyltransferase of m5C methylation modification that has been reported to be involved in the occurrence and progression of various tumors, but its role in NPC remains unclear. In this study, we found that NSUN2 was upregulated in NPC and predicted a poor prognosis for NPC patients in both GEO datasets and our tissue microarrays containing 125 NPC tissues. Next, we demonstrated that NSUN2 promoted the proliferation, migration, and invasion of NPC cells in vitro. Additionally, the differential expression genes between NSUN2-high and low expression patients were mainly enriched in multi-immune cell activation and proliferation. Furthermore, NSUN2 negatively regulates immune cell infiltration in the tumor microenvironment (TME) of NPC, which indicates that the NSUN2 level may be negatively correlated with the sensitivity of immunotherapy and chemotherapy. In conclusion, our findings highlight that NSUN2 might act as an important oncogene involved in NPC progression and serve as a potential biomarker to predict poor prognosis and drug sensitivity of NPC patients.

Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant progression, single-cell RNA sequencing (scRNA-seq) was employed. PCA and TSNE were used for dimensionality reduction analysis and cell clustering. Find All Markers function was used to calculate differential genes in each cluster, and Do Heatmap function was used to plot the distribution of differential genes in each cluster. GSVA was employed to assign pathway activity estimates to individual cells. Lineage trajectory progression was inferred by monocle. CNV status was inferred to compare the heterogeneity among patients and subtypes by infercnv. Ligand-receptor interactions were identified by CellPhoneDB, and regulons network of cells was analyzed by SCENIC. Through RNA-sequencing of 6236 individual cells from 5 liver metastatic PDAC lesions, 10 major cell clusters are identified by using unbiased clustering analysis of expression profiling and well-known cell markers. Cells with high CNV level were considered as malignant cells and pathway analyses were carried out to highlight intratumor heterogeneity in PDAC. Pseudotime trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. The complex cellular communication suggested potential immunotherapeutic targets in PDAC. Regulon network identified multiple candidates for promising cell-specific transcriptional factors. Finally, metastatic-related genes expression levels and signaling pathways were validated in bulk RNA Sequencing data. This study contributed a comprehensive single-cell transcriptome atlas and contributed into novel insight of intratumor heterogeneity and molecular mechanism in metastatic PDAC.

Landscape of Immune Microenvironment Under Immune Cell Infiltration Pattern in Breast Cancer.

Background: Increasing evdence supports the suggestion that the immune cell infiltration (ICI) patterns play a pivotal role in tumor progression in breast cancer (BRCA). Nonetheless, there has been no comprehensive analysis of the ICI patterns effects on the clinical outcomes and immunotherapy. Methods: Multiomic data for BRCA samples were downloaded from TCGA. ESTIMATE algorithm, ssGSEA method, and CIBERSORT analysis were used to uncover the landscape of the tumor immune microenvironment (TIME). BRCA subtypes based on the ICI pattern were identified by consensus clustering and principal-component analysis was performed to obtain the ICI scores to quantify the ICI patterns in individual tumors. Their prognostic value was validated by the Kaplan-Meier survival curves. Gene set enrichment analysis (GSEA) was applied for functional annotation. Immunophenoscore (IPS) was employed to explore the immunotherapeutic role of the ICI scores. Finally, the mutation data was analyzed by using the "maftools" R package. Results: Three different immune infiltration patterns with a distinct prognosis and biological signature were recognized among 1,198 BRCA samples. The characteristics of TIME under these three patterns were highly consistent with three known immune profiles: immune- excluded, immune-desert, and immune-inflamed phenotypes, respectively. The identification of the ICI patterns within individual tumors based on the ICI score, developed under the ICI-related signature genes, contributed into dissecting biological processes, clinical outcome, immune cells infiltration, immunotherapeutic effect, and genetic variation. High ICI score subtype, characterized with a suppression of immunity, suggested an immune-exhausted phenotype. Abundant effective immune cells were discovered in the low ICI score patients, which corresponded to an immune-activated phenotype and might present an immunotherapeutic advantage. Immunophenoscore was implemented as a surrogate of immunotherapeutic outcome, low-ICI scores samples obtained a significantly higher immunophenoscore. Enrichment of the JAK/STAT and VEGF signal pathways were activated in the ICI low-score subgroup. Finally, the synergistic effect between the ICI score and the tumor mutation burden (TMB) was confirmed. Conclusion: This work comprehensively elucidated that the ICI patterns served as an indispensable player in complexity and diversity of TIME. Quantitative identification of the ICI patterns in individual tumor will contribute into mapping the landscape of TIME further optimizing precision immunotherapy.

Prognostic Role of ceRNA Network in Immune Infiltration of Hepatocellular Carcinoma.

Background: Increasing evidence supports that competing endogenous RNAs (ceRNAs) and tumor immune infiltration act as pivotal players in tumor progression of hepatocellular carcinoma (HCC). Nonetheless, comprehensive analysis focusing on ceRNAs and immune infiltration in HCC is lacking. Methods: RNA and miRNA sequencing information, corresponding clinical annotation, and mutation data of HCC downloaded from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) project were employed to identify significant differentially expressed mRNAs (DEMs), miRNAs (DEMis), and lncRNAs (DELs) to establish a ceRNA regulatory network. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) enrichment pathways were analyzed to functionally annotate these DEMs. A multigene-based risk signature was developed utilizing least absolute shrinkage and selection operator method (LASSO) algorithm. Moreover, survival analysis and receiver operating characteristic (ROC) analysis were applied for prognostic value validation. Seven algorithms (TIMER, XCELL, MCPcounter, QUANTISEQ, CIBERSORT, EPIC, and CIBERSORT-ABS) were utilized to characterize tumor immune microenvironment (TIME). Finally, the mutation data were analyzed by employing "maftools" package. Results: In total, 136 DELs, 128 DEMis, and 2,028 DEMs were recognized in HCC. A specific lncRNA-miRNA-mRNA network consisting of 3 lncRNAs, 12 miRNAs, and 21 mRNAs was established. A ceRNA-based prognostic signature was established to classify samples into two risk subgroups, which presented excellent prognostic performance. In additional, prognostic risk-clinical nomogram was delineated to assess risk of individual sample quantitatively. Besides, risk score was significantly associated with contexture of TIME and immunotherapeutic targets. Finally, potential interaction between risk score with tumor mutation burden (TMB) was revealed. Conclusion: In this work, comprehensive analyses of ceRNAs coexpression network will facilitate prognostic prediction, delineate complexity of TIME, and contribute insight into precision therapy for HCC.

The diverse roles of circular RNAs in pancreatic cancer.

Pancreatic cancer is one of the malignant tumors with poor prognosis. The molecular mechanisms of pancreatic oncogenesis and malignant progression are not fully elucidated. Several key signaling pathways, such as Notch, Wnt and hedgehog pathways, are important to drive pancreatic carcinogenesis. Recently, noncoding RNAs, especially circular RNAs (circRNAs), have been characterized to participate into pancreatic cancer development. Therefore, in this review article, we describe the association between circRNAs and pancreatic cancer prognosis. Moreover, we discuss how circRNAs are involved in regulation of cellular processes in pancreatic cancer, including proliferation, apoptosis, cell cycle, migration, invasion, EMT, metastasis, angiogenesis, drug resistance and immune escape. Furthermore, we mention that several compounds could regulate the expression of circRNAs, indicating that targeting circRNAs by compounds might be helpful for treating pancreatic cancer patients.

Immunological Significance of Prognostic DNA Methylation Sites in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and high mortality worldwide. DNA methylation, one of the most common epigenetic changes, might serve a vital regulatory role in cancer. Methods: To identify categories based on DNA methylation data, consensus clustering was employed. The risk signature was yielded by systematic bioinformatics analyses based on the remarkably methylated CpG sites of cluster 1. Kaplan-Meier analysis, variable regression analysis, and ROC curve analysis were further conducted to validate the prognosis predictive ability of risk signature. Gene set enrichment analysis (GSEA) was performed for functional annotation. To uncover the context of tumor immune microenvironment (TIME) of HCC, we employed the ssGSEA algorithm and CIBERSORT method and performed TIMER database exploration and single-cell RNA sequencing analysis. Additionally, quantitative real-time polymerase chain reaction was employed to determine the LRRC41 expression and preliminarily explore the latent role of LRRC41 in prognostic prediction. Finally, mutation data were analyzed by employing the "maftools" package to delineate the tumor mutation burden (TMB). Results: HCC samples were assigned into seven subtypes with different overall survival and methylation levels based on 5'-cytosine-phosphate-guanine-3' (CpG) sites. The risk prognostic signature including two candidate genes (LRRC41 and KIAA1429) exhibited robust prognostic predictive accuracy, which was validated in the external testing cohort. Then, the risk score was significantly correlated with the TIME and immune checkpoint blockade (ICB)-related genes. Besides, a prognostic nomogram based on the risk score and clinical stage presented powerful prognostic ability. Additionally, LRRC41 with prognostic value was corroborated to be closely associated with TIME characterization in both expression and methylation levels. Subsequently, the correlation regulatory network uncovered the potential targets of LRRC41 and KIAA1429. Finally, the methylation level of KIAA1429 was correlated with gene mutation status. Conclusion: In summary, this is the first to identify HCC samples into distinct clusters according to DNA methylation and yield the CpG-based prognostic signature and quantitative nomogram to precisely predict prognosis. And the pivotal player of DNA methylation of genes in the TIME and TMB status was explored, contributing to clinical decision-making and personalized prognosis monitoring of HCC.