Tumor microenvironment remodeling plus immunotherapy could be used in mesenchymal-like tumor with high tumor residual and drug resistant rate.

Epithelial-mesenchymal transition (EMT) is a common process during tumor progression and is always related to residual tumor, drug resistance and immune suppression. However, considering the heterogeneity in EMT process, there is still a need to establish robust EMT classification system with reasonable molecular, biological and clinical implications to investigate whether these unfavorable survival factors are common or unique in different individuals. In our work, we classify tumors with four EMT status, that is, EMTlow, EMTmid, EMThigh-NOS (Not Otherwise Specified), and EMThigh-AKT (AKT pathway overactivation) subtypes. We find that EMThigh-NOS subtype is driven by intrinsic somatic alterations. While, EMThigh-AKT subtype is maintained by extrinsic cellular interplay between tumor cells and macrophages in an AKT-dependent manner. EMThigh-AKT subtype is both unresectable and drug resistant while EMThigh-NOS subtype can be treated with cell cycle related drugs. Importantly, AKT activation in EMThigh-AKT not only enhances EMT process, but also contributes to the immunosuppressive microenvironment. By remodeling tumor immune-microenvironment by AKT inhibition, EMThigh-AKT can be treated by immune checkpoint blockade therapies. Meanwhile, we develop TumorMT website ( http://tumormt.neuroscience.org.cn/ ) to apply this EMT classification and provide reasonable therapeutic guidance.

Single-cell RNA sequencing and multiple bioinformatics methods to identify the immunity and ferroptosis-related biomarkers of SARS-CoV-2 infections to ischemic stroke.

BACKGROUND: Since December 2019, Coronavirus disease 2019 (COVID-19) induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in significant morbidity and mortality worldwide. There is an increased risk of ischemic stroke (IS) associated with COVID-19. However, few studies have been reported to explain the potential correlation between COVID-19 and IS. METHODS: We investigated the relationship and relevant mechanisms between COVID-19 and IS using single-cell RNA sequencing and multiple bioinformatics approaches. RESULTS: By intersecting differentially expressed genes and WGCNA critical module genes, we obtained 73 COVID-19-related IS genes. According to the KEGG pathway analysis, the COVID-19-related IS disease genes were significantly enriched in the hematopoietic cell lineage pathway, ribosome pathway, COVID-19 pathway and primary immunodeficiency pathway. Finally, three genes associated with immunity (B4GALT5, CRISPLD2, F5) and two genes associated with ferroptosis (ACSL1, CREB5) were identified up-regulated in COVID-19-related IS. Significantly, it was found that all five genes were highly expressed in monocytes by single cell RNA sequencing. CONCLUSION: We believe these genes (B4GALT5, CRISPLD2, F5, ACSL1, CREB5) may regulate the immune response and ferroptosis of multiple immune cells, mainly including monocytes, which may contribute to the development of COVID-19-related IS. In addition, these genes may be potential targets for the treatment of COVID-19-related IS.

Chemerin enhances mesenchymal features of glioblastoma by establishing autocrine and paracrine networks in a CMKLR1-dependent manner.

Glioblastoma multiforme (GBM) with mesenchymal features exhibits enhanced chemotherapeutic resistance and results in reduced overall survival. Recent studies have suggested that there is a positive correlation between the GBM mesenchymal status and immune cell infiltration. However, the mechanisms by which GBM acquires its mesenchymal features in a tumor immune microenvironment-dependent manner remains unknown. Here, we uncovered a chemerin-mediated autocrine and paracrine network by which the mesenchymal phenotype of GBM cells is strengthened. We identified chemerin as a prognostic secretory protein mediating the mesenchymal phenotype-promoting network between tumor-associated macrophages (TAMs) and tumor cells in GBM. Mechanistically, chemerin promoted the mesenchymal features of GBM by suppressing the ubiquitin-proteasomal degradation of CMKLR1, a chemerin receptor predominantly expressed on TAMs and partially expressed on GBM cells, thereby enhancing NF-κB pathway activation. Moreover, chemerin was found to be involved in the recruitment of TAMs in the GBM tumor microenvironment. We revealed that chemerin also enhances the mesenchymal phenotype-promoting ability of TAMs and promotes their M2 polarization via a CMKLR1/NF-κB axis, which further exacerbates the mesenchymal features of GBM. Blocking the chemerin/CMKLR1 axis with 2-(α-naphthoyl) ethyltrimethylammonium iodide disrupted the mesenchymal network and suppressed tumor growth in GBM. These results suggest the therapeutic potential of targeting the chemerin/CMKLR1 axis to block the mesenchymal network in GBM.

Establishment of tumor inflammasome clusters with distinct immunogenomic landscape aids immunotherapy.

Inflammasome signaling is a reaction cascade that influences immune response and cell death. Although the inflammasomes participate in tumorigenesis, their role as an oncogenic booster or a tumor suppresser is still controversial. Therefore, it is important to comprehensively investigate the inflammasome signaling status across various cancers to clarify its clinical and therapeutic significance. Methods: A total of 9881 patients across 33 tumor types from The Cancer Genome Atlas database were included in this study. Five gene sets were identified to step-wisely profile inflammasome signaling. Unsupervised clustering was used for sample classification based on gene set enrichment. Machine learning and in vitro and in vivo experiments were used to confirm the implications of inflammasome classification. Results: A hundred and forty-one inflammasome-signaling-related genes were identified to construct five gene sets representing the sensing, activation, and termination steps of the inflammasome signaling. Six inflammasome clusters were robustly established with distinct molecular, biological, clinical, and therapeutic features. Importantly, clusters with inflammasome signaling activation were found to be immunosuppressive and resistant to ICB treatment. Inflammasome inhibition reverted the therapeutic failure of ICB in inflammasome-activated tumors. Moreover, based on the proposed classification and therapeutic implications, an open website was established to provide tumor patients with comprehensive information on inflammasome signaling. Conclusions: Our study conducted a systematical investigation on inflammasome signaling in various tumor types. These findings highlight the importance of inflammasome evaluation in tumor classification and provide a foundation for improving relevant therapeutic regimens.

Development of a T-cell activation-related module with predictive value for the prognosis and immune checkpoint blockade therapy response in glioblastoma.

BACKGROUND: Despite the rise in the use of immune checkpoint blockade drugs (ICBs) in recent years, there are no ICB drugs that are currently approved or under large-scale clinical trials for glioblastoma (GBM). T-cells, which mainly mediate adaptive immunity, are an important part of the tumor immune microenvironment. The activation of T-cells in tumors plays a key role in evaluating the sensitivity of patients to immunotherapy. Therefore, we applied bioinformatics approaches to construct a T-cell activation related risk score to study the effect of the activation of T-cells on the prognosis and ICB response of patients with GBM. MATERIALS AND METHODS: This study collected TCGA, CGGA, and GSE16011 glioma cohorts, as well as the IMvigor210 immunotherapy dataset, with complete mRNA expression profiles and clinical information. GraphPad Prism 8 and R 3.6.3 were used for bioinformatics analysis and plotting. RESULTS: The activation of T-cells in patients with GBM is characterized by obvious heterogeneity. We established a T-cell activation-related risk score based on five univariate Cox regression prognostic genes (CD276, IL15, SLC11A1, TNFSF4, and TREML2) in GBM. The risk score was an independent risk factor for poor prognosis. The overall survival time of patients in the high-risk group was significantly lower than in the low-risk group. Moreover, the high-risk score was accompanied by a stronger immune response and a more complex tumor immune microenvironment. "Hot tumors" were mainly enriched in the high-risk group, and high-risk group patients highly expressed inhibitory immune checkpoints (PD1, PD-L1, TIM3 etc.). By combining the risk and priming scores we obtained the immunotherapy score, which was shown to be a good evaluation index for sensitivity to GBM immunotherapy. CONCLUSIONS: As an independent risk factor for poor prognosis, the T-cell activation-related risk score, combined with other clinical characteristics, could efficiently evaluate the survival of patients with GBM. The immunotherapy score obtained by combining the risk and priming scores could evaluate the ICB response of patients with GBM, providing treatment opportunities.

Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma.

BACKGROUND: Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated. METHODS: Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed. RESULTS: According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma. CONCLUSIONS: We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

Long non-coding RNA, HOTAIRM1, promotes glioma malignancy by forming a ceRNA network.

Long non-coding RNAs play critical roles in tumorigenesis and the immune process. In this study, RNA sequencing data for 946 glioma samples from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas databases were analyzed to evaluate the prognostic value and function of homeobox A transcript antisense RNA myeloid-specific (HOTAIRM)1. HOTAIRM1 expression was associated with clinical and molecular features of glioma: patients with high HOTAIRM1 expression were more likely to be classified as malignant cases, and elevated HOTAIRM1 level was associated with shorter survival time in subgroups stratified by clinical and molecular features. A multivariate Cox regression analysis showed that HOTAIRM1 was an independent prognostic factor for patient outcome. In vitro experiments revealed that HOTAIRM1 knockdown suppressed the malignant behavior of glioma and increased tumor sensitivity to temozolomide. The results of an in silico analysis indicated that HOTAIRM1 promotes the malignancy of glioma by acting as a sponge for microRNA (miR)-129-5p and miR-495-3p. HOTAIRM1 overexpression was also associated with immune activation characterized by enhanced T cell-mediated immune and inflammatory responses. These results suggest that HOTAIRM1 is a prognostic biomarker and potential therapeutic target in glioma.

Bioinformatics profiling utilized a nine immune-related long noncoding RNA signature as a prognostic target for pancreatic cancer.

PURPOSE: To identify an immune-related long noncoding RNA (lncRNA) signature with potential prognostic value for patients with pancreatic cancer. METHODS: Pancreatic cancer samples with available clinical information and whole genomic mRNA expression data obtained from The Cancer Genome Atlas (TCGA) were enrolled in our research. The immune score of each sample was calculated according to the expression level of immune-related genes and used to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high- and low-risk groups were separated on the basis of the median risk score. The prediction reliability was further evaluated in the validation set and combination set. Both gene set enrichment analysis (GSEA) and principal component analysis (PCA) were performed for functional annotation, and the microenvironment cell population record was applied to evaluate the immune composition and purity of the tumor. RESULTS: A cohort of 176 samples was included in this study. A total of 163 immune-related lncRNAs were collected according to Pearson correlation analyses between immune score and lncRNA expression |R| > 0.5, P < 0.01). Nine immune-related lncRNAs (AL138966.2, AL133520.1, AC142472.1, AC127024.5, AC116913.1, AC083880.1, AC124016.1, AC008443.5, and AC092171.5) with the most significant prognostic values (P < 0.01) were identified. In the training set, it was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group (P < 0.001); meanwhile, similar results were found in the validation set, combination set and various stratified sets (P < 0.05, P < 0.001, P < 0.05, respectively). Moreover, the signature was identified as an independent prognostic factor and significantly associated with the OS of pancreatic cancer. The area under curve (AUC) of the receiver operating characteristic curve (ROC curve) for the nine lncRNA signature in predicting the 2-year survival rate was 0.703. In addition, the low-risk and high-risk groups displayed different distributed patterns in PCA and different immune statuses in the GSEA. The signature indicated decreased purity of the tumor by implying a lower proportion of cancer cells along with an increasing enrichment of fibroblasts, myeloid dendritic cells, and monocytic lineage cells. CONCLUSIONS: Our research suggests that the immune-related lncRNA signature possesses latent prognostic value for patients with pancreatic cancer and may provide new information for immunological research and treatment in pancreatic cancer.

DRAM1 regulates the migration and invasion of hepatoblastoma cells via autophagy-EMT pathway.

DNA-damage regulated autophagy modulator 1 (DRAM1) is known as a target of TP53-mediated autophagy, and has been reported to promote the migration and invasion abilities of glioblastoma stem cells. However, the precise contribution of DRAM1 to cancer cell invasion and migration, and the underlying mechanisms remain unclear. In the present study, small interfering (si)RNA or short hairpin RNA mediated knockdown of DRAM1 was performed in hepatoblastoma cells and the migration and invasion abilities were detected in vitro and in vivo. To investigate the underlying mechanisms, western blotting and immunofluorescence were used to detect the expression of autophagy-associated proteins and epithelial-mesenchymal-transition (EMT)-associated markers. The results showed that DRAM1 knockdown by specific siRNA abrogated cell autophagy, as well as inhibited the migration and invasion of HepG2 cells in Transwell assays, which may be reversed by rapamycin treatment. In addition, DRAM1 knockdown increased the expression of E-Cadherin while decreased the expression of vimentin in HepG2 cells, which was also be reversed by rapamycin treatment. Taken together, these results suggest that DRAM1 is involved in the regulation of the migration and invasion of HepG2 cells via autophagy-EMT pathway.