Cell Infiltration In Tumor Microenvironment Research Articles

Identification of prognostic m6A modification patterns and score system in melanoma patients.

N6-methyladenosine (m6A) is the most common modification on RNAs and LncRNAs. It plays an important role in cancer stem cell differentiation, T cell differentiation, and immune homeostasis. In this study, we explored the potential roles of m6A modification of RNA in melanoma and investigated the immune cell infiltration in tumor microenvironment in diverse m6Aclusters and different m6Ascore groups. A consensus clustering algorithm determined m6A modification patterns based on 14 m6A regulators, and further explored the biological functions and the connection with TME. An m6A-related gene signature (m6Ascore) was constructed based on m6A-related genes using principal component analysis. Three m6A modification patterns were identified based on 14 m6A regulators, named as m6Aclusters A-C. The prognosis of m6Acluster A was more favorable than m6Aclusters B and C, and it was more closely associated with immune regulation. To quantify the m6A modification patterns of individual tumor, an m6Ascore was constructed, and patients were classified into high and low m6Ascore groups. The low m6Ascore group, which had a favorable prognosis, was more relevant to immunology. The expression of PD-L1 was higher and the immunophenoscore (IPS) revealed stronger response to immunotherapy in the low m6Ascore group. This study identified 3 m6A modification patterns with different immune characteristics and constructed an m6Ascore system to predict prognosis and immunogenicity of patients, which is conducive to clinical prognosis judgment and individual treatment.

Abstract LB077: CSF-1R inhibition with Pimicotinib (ABSK021) enhanced anti-tumor efficacy of KRASG12C inhibitors in preclinical non-small cell lung cancer mouse models

Abstract Background: KRAS mutations are highly prevalent oncogenic drivers in human cancers and KRASG12C is the most frequent mutations found in KRAS-mutant non-small lung cancer (NSCLC). It is reported that tumor associated macrophages (TAMs) are enriched in KRAS-driven transgenic lung cancer models. Depletion of macrophage results in a significant decrease in tumor burden and increased survival. Sotorasib (AMG510), the first KRASG12C inhibitor approved by FDA, has been found to modulate tumor immunity, impacting the recruitment of macrophages. CSF-1R signaling is critical for macrophage proliferation and survival. CSF-1R inhibition depletes TAMs and reprograms tumor microenvironment (TME), resulting in enhancement of anti-tumor immunity. Therefore, the combination of KRASG12C and CSF-1R inhibitors may synergize to enhance anti-tumor efficacy. Pimicotinib (ABSK021) is a potential best-in-class small molecule inhibitor of CSF-1R in clinical development of multiple indications. Here, we conducted in vivo experiments to explore the combined effects of KRASG12C and CSF-1R inhibitors. Methods: In vivo efficacy studies were performed to evaluate the combined treatment of KRASG12C inhibitors (AMG510 and ABSK071, a next-generation inhibitor targeting KRASG12C with better inhibitory activity) and CSF-1R inhibitor (ABSK021) in NCI-H2122 PBMC humanized mice and LLC syngeneic mice. RNA sequencing was employed to investigate the mechanism of action underlying the synergistic anti-tumor effect. Immunohistochemistry (IHC) was utilized to examine the changes of immune cell populations in TME. Results: The combinatory regimen of ABSK021 and KRASG12C inhibitors showed improved anti-tumor effects than each single agent alone in both mouse NSCLC models. Bioinformatics and follow-up analysis revealed a reduction in immune suppressive TAMs in tumors treated with ABSK021 alone or in combination with KRASG12C inhibitors. Furthermore, modulation of TME related to anti-tumor immunity, such as activated CD4 T, CD8 T and NK cells, was increased, and pro-tumor immunity, such as MDSC, regulatory T cells, was decreased in combination group. IHC results confirmed that ABSK021 addition led to macrophage depletion and more CD8 T cell infiltration in TME. Conclusions: For the first time, we demonstrate that the combined inhibition of KRASG12C and CSF-1R leads to superior therapeutic efficacy in preclinical NSCLC mouse models. This results suggests a potential novel therapeutic regimen that could yield improved clinical benefit to patients. Citation Format: Nannan Zhang, Bin Shen, Shenyan Liu, Cheng Dai, Haiyan Ying, Fushen Guo, Zhixuan Zhu, Wan Shi, Min Tu, Jie Wang, Jie Zhang, Manqi Liu, Qi Zhang, Zhui Chen. CSF-1R inhibition with Pimicotinib (ABSK021) enhanced anti-tumor efficacy of KRASG12C inhibitors in preclinical non-small cell lung cancer mouse models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB077.

A Novel Gene Signature Based on Immune Cell Infiltration Landscape Predicts Prognosis in Lung Adenocarcinoma Patients.

The tumor microenvironment (TME) is created by the tumor and dominated by tumor-induced interactions. Long-term survival of lung adenocarcinoma (LUAD) patients is strongly influenced by immune cell infiltration in TME. The current article intends to construct a gene signature from LUAD ICI for predicting patient outcomes. For the initial phase of the study, the TCGA-LUAD dataset was chosen as the training group for dataset selection. We found two datasets named GSE72094 and GSE68465 in the Gene Expression Omnibus (GEO) database for model validation. Unsupervised clustering was performed on the training cohort patients using the ICI profiles. We employed Kaplan-Meier estimators and univariate Cox proportional-hazard models to identify prognostic differentially expressed genes in immune cell infiltration (ICI) clusters. These prognostic genes are then used to develop a LASSO Cox model that generates a prognostic gene signature. Validation was performed using Kaplan-Meier estimation, Cox, and ROC analysis. Our signature and vital immune-relevant signatures were analyzed. Finally, we performed gene set enrichment analysis (GSEA) and immune infiltration analysis on our finding gene signature to further examine the functional mechanisms and immune cellular interactions. Our study found a sixteen-gene signature (EREG, HPGDS, TSPAN32, ACSM5, SFTPD, SCN7A, CCR2, S100P, KLK12, MS4A1, INHA, HOXB9, CYP4B1, SPOCK1, STAP1, and ACAP1) to be prognostic based on data from the training cohort. This prognostic signature was certified by Kaplan-Meier, Cox proportional-hazards, and ROC curves. 11/15 immune-relevant signatures were related to our signature. The GSEA results indicated our gene signature strongly correlates with immune-related pathways. Based on the immune infiltration analysis findings, it can be deduced that a significant portion of the prognostic significance of the signature can be attributed to resting mast cells. We used bioinformatics to determine a new, robust sixteen-gene signature. We also found that this signature's prognostic ability was closely related to the resting mast cell infiltration of LUAD patients.

Gasdermin C sensitizes tumor cells to PARP inhibitor therapy in cancer models.

Several poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) are approved by FDA to treat cancer with BRCA mutations. BRCA mutations are considered to fuel a PARPi killing effect by inducing apoptosis. However, resistance to PARPi is frequently observed in the clinic due to an incomplete understanding on the molecular basis of PARPi function and a lack of good markers, beyond BRCA mutations, to predict response. Here, we show that gasdermin C (GSDMC) sensitized tumor cells to PARPi in vitro and in immunocompetent mice and caused durable tumor regression in an immune-dependent manner. A high expression level of GSDMC predicted better response to PARPi treatment in patients with triple-negative breast cancer (TNBC). PARPi treatment triggered GSDMC/caspase-8-mediated cancer cell pyroptosis (CCP) that enhanced PARPi killing of tumor cells. GSDMC-mediated CCP increased memory CD8+ T cell population in lymph node (LN), spleen, and tumor and, thus, promoted cytotoxic CD8+ T cell infiltration in the tumor microenvironment. T cell-derived granzyme B (GZMB) activated caspase-6, which subsequently cleaved GSDMC to induce pyroptosis. Interestingly, IFN-γ induced GSDMC expression, which, in turn, enhanced the cytotoxicity of PARPi and T cells. Importantly, GSDMC promoted tumor clearance independent of BRCA deficiency in multiple cancer types with PARPi treatment. This study identifies a general marker and target for PARPi therapy and offers insights into the mechanism of PARPi function.

Pan-cancer analysis and experimental validation identify ndc1 as a potential immunological, prognostic and therapeutic biomarker in pancreatic cancer.

NDC1 is a transmembrane nucleoporin that participates in cell mitosis. In the field of oncology, NDC1 has shown its potential as a prognostic marker for multiple tumors. However, pan-cancer analysis of NDC1 to fully explore its role in tumors has not been performed and little is reported on its role in pancreatic cancers. In the present study, a pan-cancer analysis of NDC1 was performed using a bioinformatic approach. Survival analysis was performed by univariate Cox regression analysis and Kaplan-Meier survival analysis. Subsequently, the relationship between NDC1 and immune cell infiltration, TMB/MSI and drug sensitivity was analyzed. Moreover, the mechanism of NDC1 in pancreatic cancer were further analyzed by GSEA, GSVA. Finally, we conducted in vitro experiments including MTT, scratch, EdU, and apoptosis assays to explore the function of NDC1 in pancreatic cancer cells. High expression of NDC1 was demonstrated in 28 cancer types. Univariate Cox regression analysis revealed that NDC1 expression was closely associated with the survival outcome of 15 cancer types, and further Kaplan-Meier survival analysis showed negative associations with the progression-free survival in 14 cancers. In addition, a significant association between the NDC1 expression and immune cell infiltration in tumor microenvironment, immune-related genes, common tumor-regulatory and drug sensitivity was observed. Furthermore, NDC1 is abnormally expressed in pancreatic cancer, and is closely related to the prognosis of pancreatic cancer patients and chemosensitivity. The study reveals that NDC1 could be used as a potential immunological, prognostic and therapeutic target for pancreatic cancer.

Development of an Immune Prognostic Model for Clear Cell Renal Cell Carcinoma Based on Tumor Microenvironment.

Immune infiltration remains at a high level in clear cell renal cell carcinoma (ccRCC). It has been confirmed that immune cell infiltration in tumor microenvironment (TME) is intimately bound up with the progression and the clinical outcome of ccRCC. The prognostic model, developed based on different immune subtypes of ccRCC, has a predictive value in patients' prognosis. RNA sequencing data, somatic mutation data of ccRCC and clinical information were acquired from the cancer genome atlas (TCGA) database. The key immune-related genes (IRGs) were selected and by univariate Cox, LASSO, and multivariate Cox regression analyses. Then the ccRCC prognostic model was developed. The applicability of this model was verified in the independent dataset GSE29609. Thirteen IRGs including CCL7, ATP6V1C2, ATP2B3, ELAVL2, SLC22A8, DPP6, EREG, SERPINA7, PAGE2B, ADCYAP1, ZNF560, MUC20, and ANKRD30A were finally selected and a 13-IRGs prognostic model was developed. Survival analysis demonstrated that when compared with the low-risk group, patients in the high-risk group had a lower overall survival (p<0.05). AUC values based on the 13-IRGs prognostic model used to predict 3- and 5-year survival of ccRCC patients were greater than 0.70. And risk score was an independent prognostic factor (p<0.001). In addition, nomogram could accurately predict ccRCC patient's prognosis. This 13-IRGs model can effectively evaluate the prognosis of ccRCC patients, and also provide guidance for the treatment and prognosis of ccRCC patients.

Cuproptosis combines immune landscape providing prognostic biomarker in head and neck squamous carcinoma

Head and neck squamous carcinomas (HNSC) are the seventh most common cancer around the world. Treatment options available today have considerable limitations in terms of efficacy. Identifying novel therapeutic targets for HNSC is, therefore, urgently needed. As a novel determined regulated cell death (RCD), Cuproptosis is correlated with the development, treatment response, and prognosis of various cancer. However, the potential role of Cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of HNSC remains unclear. To figure out whether TME cells and Cuproptosis could better predict prognosis, in this study, we analyzed the expression, mutation status, and other clinical information of 502 HNSC patients by dividing them into four clusters based on their CRGs and TME cell expression. Utilizing the LASSO-Cox method and bootstrap, we established Prognostic Cuproptosis and TME classifier, which were significantly associated with prognosis, pathways, clinical features, and immune cell infiltration in TME of HNSC. To go further, the subgroup Cup low/TMEhigh displayed a better prognosis than any others. Two GEO datasets demonstrated the proposed risk model's clinical applicability. Our GO enrichment analyses proved the conjoint effect of Cuproptosis and TME on tumor angiogenesis, proliferation, and so on. Single-cell analysis and Immunotherapy profile then provided a foundation for determining the molecular mechanisms. It revealed the prognostic risk score positively correlated with T cell activation and natural killer (NK) recruiting. As far as we know, this study is the first time to explore the involvement of CRGs regulation in the TME of HNSC. In a word, it is vital to use these findings to develop new therapeutic strategies.

Abstract 6778: Spatial analysis of genomic signatures on colorectal cancer pathogenesis using the GeoMx® Digital Spatial Profiler

Abstract Background: The development of colorectal cancer (CRC) is a complex process, involving multiple sequential molecular aberrations that contribute to disease progression. Understanding the immunopathogenesis of CRC particularly within the spatial context of tumor microenvironment (TME) may elucidate the genomic and biological changes to improve patient prognosis for adjuvant therapies and identifying potential drug targets. However, this can be challenging, as genomic signatures from sub-cellular populations and varying levels of immune cell infiltration in TME may be lost in bulk sequencing. In this study, we used the NanoString GeoMx® Digital Spatial Profiler (DSP) to spatially select epithelial, proximal stromal and distal stromal regions of TMEs on a total of 10 FFPE samples (5 colon cancer patients and 5 healthy donor samples) and profiled up to 1,800 genes included in the Cancer Transcriptome Atlas (CTA) panel. Methods: Selection of regions of interest (ROI) were guided by pathology assessment of H&amp;E images and fluorescent markers (CD45, PanCK, Syto13). Tumor and stroma (proximal and distal) regions were profiled through geometric ROI selection in PanCK+ (epithelial) and CD45+ (stromal/immune) enriched areas respectively, followed by collection of indexed oligonucleotides and sequencing on NextSeq 550 Illumina instrument. Differential expression and pathways enrichment analyses was performed using R BioConductor package DESeq2 and DSP GeoMx analysis suite. A subset of samples were tested for bulk RNA expression using PanCancer IO360 panel on NanoString nCounter Flex system and data analyzed using nSolver software 3.0 and TIS algorithm App. Results: The CTA panel is designed to profile the global immune response and all aspects of tumor microenvironment biology. From differential gene expression analysis of epithelial and distal/proximal stromal ROIs, we have identified biomarkers such as SOX9, IRAK2 and NLRP3 that are specifically upregulated in CRC samples compared to the healthy cohort. Comprehensive pathways analysis revealed an over activation of NF-kB signaling, extracellular matrix organization and interferon signaling pathways in the CRC cohort. Suppression of the NF-kB signaling pathway is a potential therapeutic approach in the treatment of colon cancer. Conclusion: With this spatial study using GeoMx CTA panel, we have highlighted key genes and pathways involved in CRC in order to provide a much-needed understanding of the underlying mechanisms as well as immune signatures in the development of colon cancer. Citation Format: Xiang Li, Qinqin Zha, Brigitte Lovell, Jane Reed, Anna Juncker-Jensen, Tricia Peters, Lakshmi Chandramohan. Spatial analysis of genomic signatures on colorectal cancer pathogenesis using the GeoMx® Digital Spatial Profiler. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6778.

CAV1 Impacts the Tumor Immune Microenvironment and Has Potential Value of Predicting Response to Immunotherapy in Esophageal Cancer

Caveolin-1 (CAV1) is one of the members of the caveolae, and the role of CAV1 in esophageal cancer (ESCA) is not completely clear. In this study, we found that expression of CAV1 was downregulated in ESCA in The Cancer Genome Atlas and the Genotype-Tissue Expression (GTEx) database and we also use immunohistochemistry of tissue microarray for verification. Then, we used bioinformatics methods to investigate the prognostic value of CAV1, influence on immune cell infiltration in tumor microenvironment (TME) and responding to immunotherapy in ESCA. Our result indicated that CAV1 designs an inflamed TME in ESCA based on the evidence that CAV1 positively correlated with immunomodulators, immune score, stomal score, cancer immunity cycles, tumor-infiltrating immune cells, T cell inflamed score, and immune checkpoints. Immunophenoscore, Tumor Immune Dysfunction and Exclusion algorithms, and the mutation analysis show that the downregulated CAV1 expression indicated higher tumor mutation burden and higher rate of response to immune checkpoint inhibitors (ICIs) in the low-expression group. In a word, our study demonstrated the impact of CAV1 to the TME in ESCA and it may be a new target for ESCA immunotherapy. In addition, the expression of CAV1 can predict the clinical response to ICIs, which may provide clinical treatment guidance.

Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma.

The m7G modification has been proven to play an important role in RNA post-transcriptional modification and protein translation. However, the potential role of m7G modification patterns in assessing the prognosis of Skin cutaneous melanoma (SKCM) and tumor microenvironment (TME) has not been well studied. In this study, we investigated and finally identified 21 available m7G-related genes. We used hierarchical clustering (K-means) to classify 743 SKCM patients into three m7G-modified subtypes named m7G/gene cluster-A, B, C. We found that both m7G cluster B and gene cluster B exhibited higher prognosis and higher immune cell infiltration in TME compared to other subtypes. EIF4E3 and IFIT5, two m7G related genes, were both markedly elevated in Cluster B. Then, we constructed an m7G score system utilizing principal component analysis (PCA) in order to evaluate the patients' prognosis. High m7G score subtype was associated with better survival prognosis and active immune response. Overall, this article revealed that m7G modification patterns were involved in the development of the tumor microenvironment. Evaluating patients' m7G modification patterns will enhance our understanding of TME characteristics and help to guide personal treatment in clinics in the future.

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer.

Cuproptosis is a novel identified regulated cell death (RCD), which is correlated with the development, treatment response and prognosis of cancer. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of gastric cancer (GC) remains unknown. Transcriptome profiling, somatic mutation, somatic copy number alteration and clinical data of GC samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database to describe the alterations of CRGs from genetic and transcriptional fields. Differential, survival and univariate cox regression analyses of CRGs were carried out to investigate the role of CRGs in GC. Cuproptosis molecular subtypes were identified by using consensus unsupervised clustering analysis based on the expression profiles of CRGs, and further analyzed by GO and KEGG gene set variation analyses (GSVA). Genes in distinct molecular subtypes were also analyzed by GO and KEGG gene enrichment analyses (GSEA). Differentially expressed genes (DEGs) were screened out from distinct molecular subtypes and further analyzed by GO enrichment analysis and univariate cox regression analysis. Consensus clustering analysis of prognostic DEGs was performed to identify genomic subtypes. Next, patients were randomly categorized into the training and testing group at a ratio of 1:1. CRG Risk scoring system was constructed through logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis, univariate and multivariate cox analyses in the training group and validated in the testing and combined groups. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to evaluate the expression of key Risk scoring genes. Sensitivity and specificity of Risk scoring system were examined by using receiver operating characteristic (ROC) curves. pRRophetic package in R was used to investigate the therapeutic effects of drugs in high- and low- risk score group. Finally, the nomogram scoring system was developed to predict patients' survival through incorporating the clinicopathological features and CRG Risk score. Most CRGs were up-regulated in tumor tissues and showed a relatively high mutation frequency. Survival and univariate cox regression analysis revealed that LIAS and FDX1 were significantly associated with GC patients' survival. After consensus unsupervised clustering analysis, GC patients were classified into two cuproptosis molecular subtypes, which were significantly associated with clinical features (gender, age, grade and TNM stage), prognosis, metabolic related pathways and immune cell infiltration in TME of GC. GO enrichment analyses of 84 DEGs, obtained from distinct molecular subtypes, revealed that DEGs primarily enriched in the regulation of metabolism and intracellular/extracellular structure in GC. Univariate cox regression analysis of 84 DEGs further screened out 32 prognostic DEGs. According to the expression profiles of 32 prognostic DEGs, patients were re-classified into two gene subtypes, which were significantly associated with patients' age, grade, T and N stage, and survival of patients. Nest, the Risk score system was constructed with moderate sensitivity and specificity. A high CRG Risk score, characterized by decreased microsatellite instability-high (MSI-H), tumor mutation burden (TMB) and cancer stem cell (CSC) index, and high stromal and immune score in TME, indicated poor survival. Four of five key Risk scoring genes expression were dysregulated in tumor compared with normal samples. Moreover, CRG Risk score was greatly related with sensitivity of multiple drugs. Finally, we established a highly accurate nomogram for promoting the clinical applicability of the CRG Risk scoring system. Our comprehensive analysis of CRGs in GC demonstrated their potential roles in TME, clinicopathological features, and prognosis. These findings may improve our understanding of CRGs in GC and provide new perceptions for doctors to predict prognosis and develop more effective and personalized therapy strategies.

PAX5 Haploinsufficiency Induces Low T Cell Infiltration in the Cancer Microenvironment via Reduced Chemokines.

To investigate the effects of PAXT mutations on tumor immunity. Loss of function of PAX5 plays a key role in the PAX5 mutation tumor. PAX5 haploinsufficiency promoting tumorigenesis is related to immune escape, but there was no report about mechanisms of PAX5 mutation inducing tumor immunological escape. We constructed the PAX5 haplodeletion A20 cell lines using gene-editing technology, built allografted A20 tumor models and evaluated the effect of PAX5 haplodeletion on T cells and chemokines in the tumor microenvironment (TME). Our results from different methods indicated percentages of CD3+ CD4+ T cells and CD3+ CD8+ T cells in TME of PAX5 haplodeletion clones decreased significantly compared with that of PAX5 wild type control. Several chemokines, such as Ccl2, Ccl4, Cxcl9 and Cxcl10, in TME of PAX5. Our study showed that PAX5 haploinsufficiency induced low T cell infiltration in TME using decreased chemokines.

Cuproptosis-related modification patterns depict the tumor microenvironment, precision immunotherapy, and prognosis of kidney renal clear cell carcinoma.

BackgroundDue to the different infiltration abundance of immune cells in tumor, the efficacy of immunotherapy varies widely among individuals. Recently, growing evidence suggested that cuproptosis has impact on cancer immunity profoundly. However, the comprehensive roles of cuproptosis-related genes in tumor microenvironment (TME) and in response to immunotherapy are still unclear.MethodsBased on 43 cuproptosis-related genes, we employed unsupervised clustering to identify cuproptosis-related patterns and single-sample gene set enrichment analysis algorithm to build a cuproptosis signature for individual patient’s immune cell infiltration and efficacy of immune checkpoint blockade (ICB) evaluation. Then, the cuproptosis-related genes were narrowed down using univariate Cox regression model and least absolute shrinkage and selection operator algorithm. Finally, a cuproptosis risk score was built by random survival forest based on these narrowed-down genes.ResultsTwo distinct cuproptosis-related patterns were developed, with cuproptosis cluster 1 showing better prognosis and higher enrichment of immune-related pathways and infiltration of immune cells. For individual evaluation, the cuproptosis signature that we built could be used not only for predicting immune cell infiltration in TME but also for evaluating an individual’s sensitivity to ICBs. Patients with higher cuproptosis signature scores exhibited more activated cancer immune processes, higher immune cell infiltration, and better curative efficacy of ICBs. Furthermore, a robust cuproptosis risk score indicated that patients with higher risk scores showed worse survival outcomes, which could be validated in internal and external validation cohorts. Ultimately, a nomogram which combined the risk score with the prognostic clinical factors was developed, and it showed excellent prediction accuracy for survival outcomes.ConclusionDistinct cuproptosis-related patterns have significant differences on prognosis and immune cell infiltration in kidney renal clear cell carcinoma (KIRC). Cuproptosis signature and risk score are able to provide guidance for precision therapy and accurate prognosis prediction for patients with KIRC.

Prognostic Signature, Immune Features, and Therapeutic Responses of a Novel Ubiquitination-Related Gene Signature in Lung Adenocarcinoma.

Growing studies have implicated the association of ubiquitination-related genes (UbRGs) with the cancer progression and the long-term survival of patients. However, the prognostic values of UbRGs in lung adenocarcinoma (LUAD) have not been investigated. Our study aimed to establish a ubiquitination-related model for prognosis prediction and internal mechanism investigation. The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from TCGA and GEO datasets. Differentially expressed genes (DEGs) were screened between LUAD specimens and nontumor specimens. Kaplan–Meier analysis and univariate assays were carried out on DEGs to preliminarily screen survival-related UbRGs. Then, the LASSO Cox regression model was applied to develop a multigene signature, which was then demonstrated in two GEO datasets by the use of Kaplan-Meier, ROC, and Cox analyses. We estimated the immune cell infiltration in tumor microenvironment via CIBERSORT and immunotherapy response through the TIDE algorithm. In this study, a total of 71 ubiquitination-related DEGs were identified. Nine UbRGs, including TUBA4A, TRIM2, PLK1, ARRB1, TRIM58, PLK1, ARRB1, CCNB1, TRIM6, PTTG1, and CCT2, were included to establish a risk model, which was validated in TCGA and GEO datasets. The multivariate assays demonstrated that the 9-UbRGs signature was a robust independent prognostic factor in the overall survival of LUAD patients. The abundance of CD8 T cells, activated CD4 T memory cells, resting NK cells and macrophages was higher in the high-risk group, and the TMB of high-risk group was statistically higher than the low-risk group. Multiple drugs approved by FAD, targeting UbRGs, were available for the treatment of LUAD. Overall, we identified a nine ubiquitination-related gene signature, and the signature may be applied to be a potential biomarker for CD8 T cells response and clinical responses to immune checkpoint inhibitors for LUAD.

Computational construction of TME-related lncRNAs signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.

BackgroundThe tumor microenvironment (TME) is closely related to clear cell renal cell carcinoma (ccRCC) prognosis, and immunotherapy response. In current study, comprehensive bio‐informative analysis was adopted to construct a TME‐related lncRNA signature for immune checkpoint inhibitors (ICIs) and targeted drug responses in ccRCC patients.MethodsThe TME mRNAs were screened following the immune and stromal scores with the data from GSE15641, GSE29609, GSE36895, GSE46699, GSE53757, and The Cancer Genome Atlas (TCGA)‐kidney renal clear cell carcinoma (KIRC). And the TME‐related lncRNAs were recognized using correlation analysis. The TME‐related lncRNAs prognostic model was constructed using the training dataset. Kaplan–Meier analysis, principal‐component analysis, and time‐dependent receiver operating characteristic were used to evaluate the risk model. The immune cell infiltration in TME was evaluated using the single‐sample gene set enrichment analysis (ssGSEA), ESTIMATE, and microenvironment cell populations counter algorithm. The immunophenoscore (IPS) was used to assess the response to immunotherapy with the constructed model.ResultsIn the current study, 364 TME‐related lncRNAs were selected based on the integrated bioinformatical analysis. Six TME‐related lncRNAs (LINC00460, LINC01094, AC008870.2, AC068792.1, and AC007637.1) were identified as the prognostic signature in the training dataset and subsequently verified in the testing and entire datasets. Patients in the high‐risk group exhibited poor overall survival and disease‐free survival than those in the low‐risk group. The 1‐, 3‐, and 5‐year areas under the curves of the prognostic signature in the entire dataset were 0.704, 0.683, and 0.750, respectively. The risk score independently predicted ccRCC survival based on univariate and multivariate Cox regression. GSEA analysis suggested that the high‐risk group was concentrated on immune‐related pathways. The high‐risk group were characterized by high immune cell infiltration, high TMB and somatic mutation counters, high IPS‐PD‐1 + CTLA4 scores, and immune checkpoints expression upregulation, reflecting the higher ICIs response. The half inhibitory concentrations of sunitinib, temsirolimus, and rapamycin were low in the high‐risk group.ConclusionThe TME‐related lncRNAs signature constructed could reliably predict the prognosis and immunotherapy response and targeted ccRCC patients' therapy.

Differential OAT methylation correlates with cell infiltration in tumor microenvironment and overall survival postradiotherapy in oral squamous cell carcinoma patient.

Given that DNA methylation and tumor microenvironment (TME) are susceptible to radiotherapy, we aimed to figure out specific differential DNA methylation to reflect oral squamous cell carcinoma (OSCC) prognosis and associated effect on TME changes postradiotherapy, performing as an efficient biomarker. Differentially methylation analysis was performed using data from The Cancer Genome Atlas. Curves of Kaplan-Meier (K-M) survival, cumulative hazard and events, Cox proportional hazards, and linear regression model were conducted to screen and validate differential methylation genes, while multiple regression equation to analyze if ornithine aminotransferase (OAT) methylation correlates with radiotherapy. For correlation between OAT methylation and immune infiltrates, CIBERSORT and ESTIMATE algorithms were performed, following gene set enrichment analysis (GSEA) and ssGSEA analysis to evaluate biological process. Compared to normal tissues, only OAT in OSCC was differential significantly by K-M analysis (p=0.0364). OAT hypermethylation was associated with increased overall survival (hazard ratio: 0.65, p=0.0358). Radiotherapy correlated with OAT methylation (β=-0.01, p=0.0061); most patients with OAT hypermethylation were radiation-sensitive. Hypomethylated OAT correlated with higher cell infiltrations in TME. Neuroactive ligand-receptor interaction was most significantly related to OAT methylation (p=9.2e-10). Sulfur metabolism was the most significantly in OAT hypermethylation group (p=0.0041) and RIG-I-like receptor in OAT hypomethylation group (p=0.0094). OAT methylation can serve as a predictor of OSCC prognosis postradiotherapy with potential mechanism by changing cell infiltrations in TME, but further experimental study deserves to carry out confirming the role and mechanism of OAT methylation in OSCC.

The Emerging Role of MTHFD Family Genes in Regulating the Tumor Immunity of Oral Squamous Cell Carcinoma.

Objective To investigate the function and regulatory mechanisms of methylenetetrahydrofolate dehydrogenase (MTHFD) family genes in oral squamous cell carcinoma (OSCC), especially focus on their regulating role in tumor immunity. Methods The publicly available data from the TCGA database were used to investigate the expression pattern and regulatory role of MTHFD family genes in OSCC. More importantly, the involvement of MTHFD family genes in tumor immunity was investigated in terms of immune and stromal cell infiltration in tumor microenvironment, tumor-infiltrating immune cells, and immunomodulatory genes (e.g., immunoinhibitory genes and immunostimulatory genes). Statistical analysis was performed using R software packages and public web servers. Results MTHFD family genes were considerably upregulated in OSCC as compared with normal oral tissue. Patients with high MTHFD2 expression presented worse survival outcomes than those with low MTHFD2 expression. Functional enrichment analysis showed that the top 100 positively and negatively correlated genes of the MTHFD family genes were significantly enriched in several KEGG pathways, including cell cycle, spliceosome, DNA replication, and Th17 cell differentiation. As a result of tumor immunity analysis, MTHFD2L expression was found to be negatively related to the Estimate-Stromal-Immune score in OSCC; however, there was no statistical significance between the Estimate-Stromal-Immune score and MTHFD1, MTHFD1L, or MTHFD2 in OSCC. Additionally, MTHFD family genes were found to be significantly positively correlated with tumor-infiltrating immune cells, including Treg and Th17 cells. Moreover, MTHFD family genes were significantly correlated with several immune inhibitory genes such as CD274 and CTLA4 and several immune-stimulatory genes such as CXCL12, CXCR4, and TMIGD2. Conclusion Given the expression pattern, prognostic value, biological functions, and involvement in tumor immunity, MTHFD family genes could serve as potential therapeutic biomarkers in targeting tumor immunity in oral cancer.

Targeting SNORA38B attenuates tumorigenesis and sensitizes immune checkpoint blockade in non-small cell lung cancer by remodeling the tumor microenvironment via regulation of GAB2/AKT/mTOR signaling pathway.

BackgroundNon-coding RNAs (ncRNAs), including small nucleolar RNAs (snoRNAs), are widely involved in the physiological and pathological processes of human beings. While up to date, although considerable progress has been achieved in ncRNA-related pathogenesis of non-small cell lung cancer (NSCLC), the underlying mechanisms and biological significance of snoRNAs in NSCLC still need to be further clarified.MethodsQuantitative real-time polymerase chain reaction or RNAscope was performed to verify the expression of Small Nucleolar RNA, H/ACA Box 38B (SNORA38B) in NSCLC cell lines or clinical samples. BALB/c nude mice xenograft model or C57BL/6J mice syngeneic tumor model were estimated to detect the effects of SNORA38B in tumor growth or tumor immune microenvironment in vivo. Cytometry by time of flight, enzyme-linked immunosorbent assay and flow cytometry assay were conducted to clarify the effects and mechanisms of SNORA38B-mediated tumor immunosuppressive microenvironment. The binding activity between SNORA38B and E2F transcription factor 1(E2F1) was detected by RNA immunoprecipitation and RNA pull-down assays. Then, bioinformatics analysis and chromatin immunoprecipitation were utilized to demonstrate the regulation of GRB2-associated-binding protein 2 (GAB2) by E2F1. Moreover, the combinatorial treatment of SNORA38B locked nucleic acid (LNA) and immune checkpoint blockade (ICB) was used to treat murine Lewis lung carcinoma-derived tumor burden C57BL/6J mice to clarify the effectiveness of targeting SNORA38B in NSCLC immunotherapy.ResultsSNORA38B was found highly expressed in NSCLC tissues and cell lines, and associated with worse prognosis. Further results showed that SNORA38B functioned as an oncogene via facilitating cell proliferation, migration, invasion, and inhibiting cell apoptosis in vitro and promoting tumorigenesis of NSCLC cells in vivo. SNORA38B could also recruit the CD4+FOXP3+ regulatory T cells by triggering tumor cells to secrete interleukin 10, which in turn reduced the infiltration of CD3+CD8+ T cells in NSCLC tumor microenvironment (TME), favoring tumor progression and poorer immune efficacy. Mechanistically, SNORA38B mainly distributed in the nucleus, and promoted NSCLC progression by regulating GAB2 transcription to activate protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway through directly binding with E2F1. Moreover, we found that SNORA38B LNAs were able to ameliorate CD3+CD8+ T cell infiltration in TME, which sensitized NSCLC to the treatment of ICB.ConclusionsIn conclusion, our data demonstrated that SNORA38B functioned as an oncogene in NSCLC both in vitro and in vivo at least in part by regulating the GAB2/AKT/mTOR pathway via directly binding to E2F1. SNORA38B could also sensitize NSCLC to immunotherapy, which may be a critical therapeutic target for NSCLC.

PD46-10 SATURATED FATTY ACID PROMOTES PROSTATE CANCER DEVELOPMENT WITH TUMOR INFILTRATING REGULATORY T CELL ALTERATION IN A PTEN-DEFICIENT MOUSE MODEL

You have accessJournal of UrologyCME1 May 2022PD46-10 SATURATED FATTY ACID PROMOTES PROSTATE CANCER DEVELOPMENT WITH TUMOR INFILTRATING REGULATORY T CELL ALTERATION IN A PTEN-DEFICIENT MOUSE MODEL Hiromi Sato, Shintaro Narita, Yoshiko Takahashi, Masanori Ishida, Soki Kasima, Ryohei Yamamoto, Atsushi Koizumi, Taketoshi Nara, Mingguo Huang, Kazuyuki Numakura, Mitsuru Saito, Toshiaki Yoshioka, and Tomonori Habuchi Hiromi SatoHiromi Sato More articles by this author , Shintaro NaritaShintaro Narita More articles by this author , Yoshiko TakahashiYoshiko Takahashi More articles by this author , Masanori IshidaMasanori Ishida More articles by this author , Soki KasimaSoki Kasima More articles by this author , Ryohei YamamotoRyohei Yamamoto More articles by this author , Atsushi KoizumiAtsushi Koizumi More articles by this author , Taketoshi NaraTaketoshi Nara More articles by this author , Mingguo HuangMingguo Huang More articles by this author , Kazuyuki NumakuraKazuyuki Numakura More articles by this author , Mitsuru SaitoMitsuru Saito More articles by this author , Toshiaki YoshiokaToshiaki Yoshioka More articles by this author , and Tomonori HabuchiTomonori Habuchi More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002614.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Recent studies reported that gut microbiota plays an important role in systemic immune response and is involved in cancer development. Herein, using a Pten-deficient mouse model, we assessed the role of systematic and local inflammation, tumor immune microenvironment and gut microbiota profiles on specific-fat diet-induced PCa development. METHODS: Immunocompetent Pten-deficient mice were fed with isocaloric diets that differed in fat composition (lard or fish oil), and were sacrificed at 28 weeks. Using 16S rRNA gene amplicon sequencing, the gut microbiota was profiled for the phylum levels. We performed flow cytometry analyses and quantitative RT-PCR to evaluate the number of prostate infiltrating immune cells and expression of immune cell markers in the prostates of the mice. Antibiotic-treated mice were developed to assess the impact of gut microbiome on fat-diet induced PCa development. RESULTS: The lard diet (LD) -fed mice gained more weight and prostate volume than the fish-oil diet (FOD) -fed mice. We noticed invasive PCa in the LD group (3 of 10 mice) alone, and the Ki67 positivity in the prostates of the LD group was significantly higher than that of the FOD mice (p<0.01). The mean serum LPS level tended to be higher in the LD group (p=0.09), and significantly correlated with mouse weight (p<0.01, r=0.78). The two dietary groups showed markedly different gut microbiota profiles, and the proportion of the Proteobacteria phylum in the LD group was significantly higher than in the FOD group (p=0.02). The mean number of regulatory T cells in the prostates of the LD group was significantly higher than the FOD group (p=0.03). Larger growth of the prostate, higher mean serum LPS level and higher expression of Foxp3 in the prostates of the LD group than those of the FOD group were observed, whereas the microbiota ablation using antibiotics-treated mice abrogated the differences. CONCLUSIONS: LD accelerates PCa development through elevated serum LPS, alteration of gut microbiota and regulatory T cell infiltration in tumor microenvironment in an engineered mouse model of PCa. Immune cell modulation in tumor microenvironment on basis of diet and/or gut microbial changes may be a novel treatment strategy for PCa. Source of Funding: nothing © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e791 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hiromi Sato More articles by this author Shintaro Narita More articles by this author Yoshiko Takahashi More articles by this author Masanori Ishida More articles by this author Soki Kasima More articles by this author Ryohei Yamamoto More articles by this author Atsushi Koizumi More articles by this author Taketoshi Nara More articles by this author Mingguo Huang More articles by this author Kazuyuki Numakura More articles by this author Mitsuru Saito More articles by this author Toshiaki Yoshioka More articles by this author Tomonori Habuchi More articles by this author Expand All Advertisement PDF DownloadLoading ...

Pan-Cancer Analyses Confirmed the Ferroptosis-Related Gene SLC7A11 as a Prognostic Biomarker for Cancer.

PurposeFerroptosis is an iron-dependent and reactive oxygen species (ROS)-reliant form of cell death, exhibiting cellular, molecular, and gene-level characteristics distinct from those of necrosis, autophagy, apoptosis, and pyroptosis. Solute carrier family 7 member 11 (SLC7A11), which encodes a cystine/glutamate antiporter transmembrane protein, inhibits ferroptosis by importing cystine and promoting glutathione (GSH) biosynthesis and was found to be overexpressed in multiple human cancers. However, the specific role and underlying mechanism of SLC7A11 in cancers remains poorly characterized. This research aimed to identify the relationship between SLC7A11 expression and tumor microenvironment and visualize its prognostic value in pan-cancer.Patients and MethodsTranscriptomic data for 6313 tumors and normal samples across 20 cancer types were acquired from The Cancer Genome Atlas (TCGA) database. Besides, we presented a novel bioinformatics pipeline that uncovered the impacts of SLC7A11 on cancer prognosis, tumor mutational burden (TMB), immune cell infiltration in tumor microenvironment, and drug responses. The Genotype-Tissue Expression (GTEx), cBioportal, TCGA and Connectivity Map (CMap) databases were used to explore the expression, genetic alterations, immune microenvironment, and drug responses of SLC7A11. A series of deconvolution algorithms, including EPIC, CIBERSORT and GSEA, were utilized for multidimensional analyses of the cancer transcriptomic data.ResultsSLC7A11 was found to be highly expressed in the 20 types of cancer, especially in solid tumors. Survival analysis uncovered that most cancer patients with up-regulated expression of SLC7A11 showed poor prognosis, suggesting that SLC7A11 is a potential oncogene in most cancer types. Furthermore, the expression level of SLC7A11 was confirmed to be associated with immune cell infiltration in tumor microenvironment, TMB, and drug responses. Gene set enrichment analysis (GESA) revealed that dysregulation of SLC7A11 was associated with metabolic and immunity-related signaling pathways in the cancers.ConclusionThe comprehensive pan-cancer analyses identified SLC7A11 as an attractive biomarker for immune infiltration and poor prognosis in cancers, shedding new light on the therapeutics of cancers.