Higher Expression Of Immune Checkpoints Research Articles

A cuproptosis-related prognostic signature for guiding clinical diagnosis and treatment in uveal melanoma patients

BackgroundCuproptosis, one of the most recently discovered forms of cell death, is induced by the disruption of copper binding to the mitochondrial respiratory acylation components. However, the mechanism underlying cuproptosis in uveal melanoma (UM) has not yet been adequately studied. MethodsRNA and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed cuproptosis-related genes were identified by R software. A prognostic signature was constructed by applying LASSO regression and Cox regression models. The associations between the signature and the immune microenvironment, overall survival, and drug sensitivity were studied. In addition, qPCR and Western blotting were performed on UM cells and RPE cell lines to verify the expression levels of the genes encoding dihydrolipoamide dehydrogenase (DLD) and dihydrolipoamide S-succinyltransferase (DLST) in UM cases. ResultsUsing a cuproptosis-related prognostic signature, UM samples were classified into high- and low-risk groups. A significant difference in overall survival between the two risk groups was evident. Receiver operating characteristic curves demonstrated that the signature is a reliable predictor of prognosis. Immune cell infiltration, drug sensitivity, and immune checkpoint expression were analysed. Significant immune difference between the two high-risk groups was found, and the high expression of immune checkpoints in high-risk groups suggests significant immunotherapy potential. In addition, drug sensitivity analysis experiments suggest that erlotinib may be a potential treatment for high-risk patients. The results of in vitro experiments confirmed that DLD and DLST had higher expression levels in UM cell lines. ConclusionsThe prognostic signature developed in this study is a reliable biomarker for predicting the prognosis of UM and may serve as a tool for personalised treatment of patients with UM.

Stratifying osteosarcoma patients using an epigenetic modification-related prognostic signature: implications for immunotherapy and chemotherapy selection.

Osteosarcoma (OS) poses significant challenges in treatment and lacks reliable prognostic markers. Epigenetic alterations play a crucial role in disease progression. This study aimed to develop an accurate prognostic signature for OS using epigenetic modification genes (EMGs). The Therapeutically Applicable Research to Generate Effective Treatments (TARGET)-OS cohort was analyzed. Univariate Cox analysis identified survival-associated EMGs. Based on least absolute shrinkage and selection operator (LASSO) regression and multivariate analysis, a 6-gene prognostic signature termed the epigenetic modification-related prognostic signature (EMRPS) was derived in the testing cohort. Kaplan-Meier and receiver operating characteristic (ROC) curve analysis confirmed predictive accuracy through internal and external validation (GEO accession GSE21257). A prognostic nomogram incorporating EMRPS and clinical features was constructed. Transcriptomic analysis including differential gene expression, Gene Ontology (GO), gene set enrichment analysis (GSEA), and immune infiltration analysis was conducted to explore mechanisms linking EMRPS to OS prognosis. Additionally, EMRPS impact on drug sensitivity was predicted. A 6-gene EMRPS comprising DDX24, DNAJC1, HDAC4, SIRT7, SP140 and UHRF2 was successfully developed. The high-risk group showed significantly shorter survival, consistently observed in both internal and external validation. EMRPS demonstrated high predictive efficacy for 1-, 3-, and 5-year overall survival, with area under curve (AUC) >0.85 in training and ~0.7 in testing. The nomogram integrating age, gender, metastasis status, and EMRPS exhibited high predictive performance based on concordance index analysis. Mechanistic analysis indicated the low-risk group had increased immune infiltration and activity with higher immune checkpoint expression, reflecting an immune-activated tumor microenvironment (TME) suitable for immunotherapy. Drug sensitivity analysis revealed the low-risk group had increased sensitivity to cisplatin, a first-line OS chemotherapy. Our study successfully established an efficient EMRPS and nomogram, highlighting their potential as novel prognostic markers and indicators for selecting appropriate immunotherapy and chemotherapy candidates in OS treatment.

Immune infiltrate analysis to reveal distinct immune classes for leiomyosarcomas.

11546 Background: Leiomyosarcomas (LMS) are aggressive malignancies of smooth-muscle origin. Few targeted molecular options exist and immunotherapy (IO) agents against T cells have been disappointing. In this study, we examine the immune infiltrate of LMS tumors by immunohistochemistry (IHC) and gene expression. Our objective was to identify actionable targets for immunotherapy in patients with LMS. Methods: Tumor samples from a series of LMS patients were prospectively collected and banked for DNA and RNA sequencing as part of the MD Anderson Patient Mosaic. Associated clinical data for the patients were collected and maintained. IHC was performed on available separate tissue microarrays. Differential gene expression (DGE) analysis was done using the DESeq2 package for R and the Benjamini-Hochberg procedure used to control for false discovery rate. Immune cell fractions were estimated using the MCPcounter package. All gene expression analyses were repeated on The Cancer Genome Atlas (TCGA) dataset as an independent dataset. Results: A total of 104 TCGA samples and 72 samples from Mosaic from 53 patients with uterine or soft tissue LMS were included in the analysis. Tumors in the TCGA group were treatment naive. Of the samples in the Mosaic group, 61 (85%) had been previously treated with chemotherapy, 8 (11%) had been radiated, and 5 (7.5%) had been previously treated with immunotherapy. Thirty-one (43%) tumors were metastatic. Fifty-one (70%) were soft tissue LMS and 21 (30%) were uterine LMS. Four distinct immune classes were seen in both the TGCA and Mosaic: a predominantly B-cell group, a monocyte/macrophage group, a mixed infiltrate group and a group with a neutrophil signature. DGE performed between the subgroups revealed a unique gene expression pattern for tumors in the B cell and monocyte/macrophage subgroups. Interrogation of specific immune-associated genes revealed low levels of expression in the neutrophil group, suggesting this may be the most immunologically “cold” subset. Some of these results were reproduced by IHC using a TMA: the presence of a cluster of samples with B-cells and higher expression of immune checkpoints, a macrophage driven cluster, and an immunologically cold cluster. Conclusions: Analyses of LMS samples across two large datasets demonstrate the existence of 4 distinct immune classes of tumors that persist despite variation in clinical and treatment conditions: B cell, monocytic/macrophage, mixed-infiltrate and neutrophil rich. The B cell and monocytic groups have increased expression of immune markers which may be amenable to targeted therapies.

Identification of the CD8 + T-cell Related Signature for Predicting the Prognosis of Gastric Cancer Based on Integrated Analysis of Bulk and Single-cell RNA Sequencing Data.

The infiltration of CD8 + T cells in the tumor microenvironment is associated with better survival and immunotherapy response. However, their roles in gastric cancer have not been explored so far. In here, the profiles of GC gene expression were collected from The Cancer Genome Atlas database. Single-cell transcriptomic data originated from GSE134520. Cell clustering, annotation, and CD8 + T-cell differential genes were from the TISCH database. We determined 896 CD8 + T-cell differential genes by scRNA-seq analysis. After integrating immune-related genes, 174 overlapping genes were obtained and a novel risk model was subsequently built. The performance of CD8 + T-cell-associated gene signature was assessed in the training and external validation sets. The gene signature showed independent risk factors of overall survival for GC. A quantitative nomogram was built to enhance the clinical efficacy of this signature. Furthermore, low-risk individuals showed higher mutation status, higher immune checkpoint expression, low Tumour Immune Dysfunction and Exclusion (TIDE) scores, and higher IPS-PD-1 combined IPS-CTLA4 scores, indicating a greater response to immunotherapy. In addition, analysis of IMvigor210 immunotherapy cohort demonstrated that low-risk individuals had a favorable response to prognosis and immunotherapy. In conclusion, we generated a CD8 + T-cell-related signature that can serve as a promising tool for personalized prognosis prediction and guiding decisions regarding immunotherapy in GC patients.

Abstract PO1-14-06: Integrated analysis reveals the impact of obesity on triple-negative breast cancer

Abstract Background: Obesity and overweight status, which has been growing rapidly over the past few decades, is considered as a risk factor for many types of cancers including breast cancer. Despite the multi-omics profile of triple-negative breast cancer (TNBC) has been comprehensively characterized, the impact of obesity on molecular features of TNBC is not fully appreciated. Methods: We applied an integrative analysis on clinicopathological data and molecular data (including genomic, transcriptomic, proteomic and metabolomic profiling) using the multi-omics database of TNBC (N = 465) from Fudan University Shanghai Cancer Center (FUSCC) for associations with patient body mass index (BMI). Patients were categorized into overweight/obese (OW/OB, BMI ≥ 24 kg/m2) and normal (NL, BMI < 24 kg/m2) group according to the Chinese criteria of BMI. The clinical and molecular differences between OW/OB and NL patients were systematically explored. We also constructed high-fat diet (HFD)-induced obese mouse tumor models and used single-cell RNA sequencing to investigate the impact of obesity on the tumor microenvironment. Furthermore, we analyzed the efficacy of anti-PD-1 immunotherapy on TNBC tumors in both obese and normal mice. Results: OW/OB patients exhibited higher proportion of metabolic syndrome, more adipose tissue in the breast and worse survival than NL patients. Among most frequently mutated genes, OBSCN showed statistically significantly less mutated in the OW/OB group (3.2% vs 9.6%), while TP53 (68.3% vs 76.9%) and PIK3CA (21.4% vs 14.1%) had tendency to be different. In terms of copy number alterations, we found OW/OB patients had a higher amplified or gained frequency of 13q14.11 (FOXO1) and a lower frequency of deletion or loss of chromosomal region 7p22.1 (FOXK1). We further dissect the expression profile of TNBC. Differentially expressed gene analysis and pathway enrichment analysis demonstrated that immune and metabolic pathways were the major distinction between OW/OB and NL tumors. OW/OB tumors were characterized with elevated inflammation of tumor microenvironment, as well as higher expression of immune checkpoints. Moreover, analyses focusing on metabolic heterogeneity using transcriptomic, proteomic and metabolomic data revealed upregulation of lipid metabolism and reactive oxygen species pathway in OW/OB group. In addition, our in vivo experiments demonstrated that TNBC in the obese mice displayed faster growth rates. Flow cytometry analysis and single-cell RNA sequencing showed that higher proportion of immunosuppressive myeloid cells and exhausted CD8+ T cells and upregulation of lipid metabolism in HFD group. Applying anti-PD-1 immunotherapy in both obese and normal mice displayed that tumors in the obese mice showed more sensitive to anti-PD-1 immunotherapy. Conclusion: Our study systematically revealed that obesity might play a significant role in the molecular heterogeneity of TNBC and showed distinct sensitivities to immunotherapy, which should be taken in account in the field of precision medicine. Keywords: triple-negative breast cancer, obesity, immune, tumor microenvironment, metabolism Citation Format: Yue Gong, Peng Ji, Huai-liang Wu, Li-Hua He, Ming-Liang Jin, Xin Hu, Yi-Zhou Jiang, Zhiming Shao. Integrated analysis reveals the impact of obesity on triple-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-14-06.

Comprehensive Molecular Analyses of an M2-Like Tumor-Associated Macrophage for Predicting the Prognosis and Immunotherapy in Breast Cancer.

The involvement of M2-like tumor-associated macrophages (TAMs) in the advancement and treatment of cancer has been widely documented. This study aimed to develop a new signature associated with M2-like TAMs to predict the prognosis and treatment response in individuals diagnosed with breast cancer (BC). Weighted gene co-expression network analysis (WGCNA) was used to identity for M2-like TAM-related modular genes. The M2-like TAM-related modular subtype was identified using unsupervised clustering. WGCNA identified 722 M2-like TAM genes, 204 of which were associated with recurrence-free survival (RFS). Patients in cluster 1 exhibited upregulated cancer-related pathways, a higher proportion of triple-negative breast cancer (TNBC) subtypes, lower expression of immune checkpoints, and worse prognosis. Cluster 2 was characterized by upregulated immune-related pathways, a higher proportion of luminal A subtypes, and higher expression of immune checkpoints. A prognostic signature was created and confirmed using an independent dataset. A well-built nomogram can accurately forecast the survival outcomes for every individual. Furthermore, patients classified as low-risk exhibited a more favorable outlook, elevated tumor microenvironment (TME) score, and superior reaction to immunotherapy. In conclusion, we discovered 2 different types of M2-like TAMs and developed a prognostic signature revealing the diversity of M2-like TAMs in BC and their correlation with immune status and prognosis. This feature can predict the prognosis and immunotherapeutic effects of BC and offer novel concepts and approaches for tailoring BC treatment.

Digital spatial proteomic profiling reveals immune checkpoints as biomarkers in lymphoid aggregates and tumor microenvironment of desmoplastic melanoma

BackgroundDesmoplastic melanoma (DM) is a rare melanoma subtype characterized by dense fibrous stroma, a propensity for local recurrence, and a high response rate to programmed cell death protein 1 (PD-1)...

Ubiquitination, SUMOylation, and NEDDylation related genes serve as prognostic and therapeutic biomarkers for oral squamous cell carcinoma.

Ubiquitination, small ubiquitin-related modifiers, and NEDDylation are now found to function in cancer biology; however, its role in the oral cancer patients remains unclear. A set of bioinformatic tools was integrated to analyze the expression and prognostic significance of ubiquitin and ubiquitin-like (UB/UBL) genes. A UB/UBL-related risk score was developed via correlation analyses, univariate Cox regression, and multivariate Cox regression. Nomogram analysis evaluates the model's prediction performance. The drug sensitivity analysis, immune profiles of UB/UBL-classified oral squamous cell carcinoma (OSCC) patients, and their related function pathway were investigated, and the role of UB/UBL-related genes in drug therapy was analyzed. A total of six prognostic UB/UBL-related genes were obtained. PSMD3, PCGF2, and H2BC10 were significantly downregulated in OSCC tissue and associated with longer survival time. OSCC patients in the high-risk group showed a significantly lower overall survival and enriched in cancer-related pathways. The prognostic potential of genes associated with UB/UBL was discovered, and patients with high-risk scores showed an increase of protumor immune infiltrates and a high expression of immune checkpoints. Moreover, the area under the curve of the annual survival rate was 0.616, 0.671, and 0.673, respectively. Besides, patients in the high-risk group are more sensitive to docetaxel, doxorubicin, and methotrexate therapy. We construct a prognosis model for OSCC patients with UB/UBL-related genes and try to find a new approach to treating oral cancer patients. The UB/UBL-related signature is helpful in developing new tumor markers, prognostic prediction, and in guiding treatment for OSCC patients.

Construction of a 12-gene prognostic model for colorectal cancer based on heat shock protein-related genes

Some heat shock proteins (HSPs) have been shown to influence tumor prognosis, but their prognostic significance in colorectal cancer (CRC) remains unclear. This study explored the prognostic significance of HSP-related genes in CRC. Transcriptional data and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) database, and a literature search was conducted to identify HSP-related genes. Using Least Absolute Selection and Shrinkage Operator (LASSO) regression and univariate/multivariate Cox regression analyses, 12 HSP-related genes demonstrating significant associations with CRC survival were successfully identified and employed to formulate a predictive risk score model. The efficacy and precision of this model were validated utilizing TCGA and Gene Expression Omnibus (GEO) datasets, demonstrating its reliability in CRC prognosis prediction. gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed significant disparities between high- and low-risk groups in chromatin remodeling biological functions and neutrophil extracellular trap formation pathways. Single sample gene set enrichment analysis (ssGSEA) further revealed differences in immune cell types and immune functional status between the two risk groups. Differential analysis showed higher expression of immune checkpoints within the low-risk group, while the high-risk group exhibited notably higher Tumor Immune Dysfunction and Exclusion (TIDE) scores. Additionally, we predicted the sensitivity of different prognosis risk patients to various drugs, providing potential drug choices for tailored treatment. Combined, our study successfully crafted a novel CRC prognostic model that can effectively predict patient survival, immune landscape, and treatment response, providing important support and guidance for CRC patient prognosis.

ARID1A deficiency promotes progression and potentiates therapeutic antitumour immunity in hepatitis B virus-related hepatocellular carcinoma.

Exploring predictive biomarkers and therapeutic strategies of ICBs has become an urgent need in clinical practice. Increasing evidence has shown that ARID1A deficiency might play a critical role in sculpting tumor environments in various tumors and might be used as pan-cancer biomarkers for immunotherapy outcomes. The current study aims to explored the immune-modulating role of ARID1A deficiency in Hepatitis B virus (HBV) related hepatocellular carcinoma (HBV-HCC) and its potential immunotherapeutic implications. In the current study, we performed a comprehensive analysis using bioinformatics approaches and pre-clinical experiments to evaluate the ARID1A regulatory role on the biological behavior, and immune landscape of Hepatitis B virus (HBV) related hepatocellular carcinoma (HBV-HCC). A total of 425 HBV-related hepatocellular carcinoma patients from TCGA-LIHC, AMC and CHCC-HBV cohort were enrolled in bioinformatics analysis.Immunohistochemical staining of HBV-HCC specimens and ARID1A deficiency cellular models were used to validate the results of the analysis. Our results have shown that ARID1A deficiency promoted tumor proliferation and metastasis. More importantly, ARID1A deficiency in HBV-HCC was associated with the higher TMB, elevated immune activity, and up-regulated expression of immune checkpoint proteins, especially TIM-3 in HBV-HCC. Further, the expression of Galectin-9, which is the ligand of TIM-3, was elevated in the ARID1A knockout HBV positive cell line. To conclude, we have shown that the ARID1A deficiency was correlated with more active immune signatures and higher expression of immune checkpoints in HBV-HCC. Additionally, the present study provides insights to explore the possibility of the predictive role of ARID1A in HBV-HCC patients responsive to immunotherapy.

A pyroptosis-related signature in colorectal cancer: exploring its prognostic value and immunological characteristics.

The heterogeneity of colorectal cancer (CRC) is the main cause of the disparity of drug sensitivity and the variability of prognosis. Pyroptosis is closely associated with the development and prognosis of various tumors, including CRC. Dividing CRC into distinct subgroups based on pyroptosis is a worthwhile topic for improving the precision treatment and prognosis prediction of CRC. We classified patients into two clusters using the consensus clustering based on the pyroptosis-related genes (PRGs). Next, the prognostic signature was developed with LASSO regression analysis using the screened genes from differentially expressed genes (DEGs) by univariate and multivariate Cox analyses. According to the pyroptosis-related score (PR score) calculated with the signature, patients belonged to two groups with distinct prognosis. Moreover, we assessed the immune profile to explore the relationship between the signature and immunological characteristics. Two single cell sequencing databases were adopted for further exploration of tumor immune microenvironment (TME). In addition, we applied our own cohort and Drugbank to explore the correlation of the signature and clinical therapies. We also studied the expression of key genes by immunohistochemistry. The signature performed well in predicting the prognosis of CRC as the high area under curve (AUC) value demonstrated. Patients with a higher PR score had poorer prognosis and higher expression of immune checkpoints but more abundant infiltration of immune cells. Combining with the indicator of therapeutic analysis, they might benefit more from immune checkpoint blockade (ICB) and neo-adjuvant chemoradiotherapy (nCRT). In conclusion, our study is based on genomics and transcriptomics to investigate the role of PRGs in CRC. We have established a prognostic signature and integrated single-cell data to study the relationship between the signature with the TME in CRC. Its clinical application in reliable prediction of prognosis and personalized treatment was validated by public and own sequencing cohort. It provided a new insight for the personalized treatment of CRC.

Tumour microenvironment influences response to treatment in oesophageal adenocarcinoma.

The poor treatment response of oesophageal adenocarcinoma (OAC) leads to low survival rates. Its increasing incidence makes finding more effective treatment a priority. Recent treatment improvements can be attributed to the inclusion of the tumour microenvironment (TME) and immune infiltrates in treatment decisions. OAC TME is largely immunosuppressed and reflects treatment resistance as patients with inflamed TME have better outcomes. Priming the tumour with the appropriate neoadjuvant chemoradiotherapy treatment could lead to higher immune infiltrations and higher expression of immune checkpoints, such as PD-1/PDL-1, CTLA4 or emerging new targets: LAG-3, TIM-3, TIGIT or ICOS. Multiple trials support the addition of immune checkpoint inhibitors to the current standard of care. However, results vary, supporting the need for better response biomarkers based on TME composition. This review explores what is known about OAC TME, the clinical significance of the various cell populations infiltrating it and the emerging therapeutical combination with a focus on immune checkpoints inhibitors.

Comprehensive molecular analysis identifies RET alterations association with response of ICIs in multi-immunotherapy cohorts

BackgroundThe RET gene, which is frequently mutated across many types of cancer, has been proven to be critically involved in tumorigenesis and tumour development; however, its prediction of the therapeutic efficacy of immune checkpoint inhibitor (ICI) therapy remains to be elucidated. The present research aims to investigate the association between RET mutations and the efficiency of ICI therapy. MethodWe analysed the role of RET mutations in predicting the prognosis of patients receiving ICIs therapy in the discovery cohort and validated it in the validation cohort. Then, multi-omics data from TCGA pan-cancer cohort was employed to propose the association between RET mutations and tumour inflamed anti-tumour immune response and tumour antigenicity. ResultsOur study revealed that among 606 cases and across five types of cancer, RET mutation was associated with better clinical outcomes for ICIs therapy, including elevated response rate, longer progression-free survival PFS, and longer overall survival OS. Multivariate analysis showed that RET mutation could independently predict the prognosis of patients treated with ICIs, after adjusting cancer types. The predictive value of RET status for the OS of patients treated with ICIs immunotherapy was further validated in the validation cohort (n = 1,409). Subgroup analysis suggested that only the monotherapy group showed significant differences in OS(P < 0.05) and PFS(P < 0.05) between RET-wildtype tumours and RET-mutant tumours. Multi-omics data analysis revealed potential anti-tumour immunity mechanisms of RET mutations, suggesting that RET-mutant tumours have enhanced immunogenicity, higher expression of immune checkpoints and chemokines, and higher immune cell infiltration than those observed in RET-wildtype tumours; thus, potentially indicating a more favourable response to immunotherapy. ConclusionsRET mutation may be a predictive biomarker of enhanced response to ICIs therapy. Extensive investigation of the underlying molecular mechanisms and prospective studies are needed in the future.

Identification and validation of palmitoylation metabolism-related signature for liver hepatocellular carcinoma

BackgroundProtein S-palmitoylation is a reversible posttranslational modification widely involved in tumor progression. Nevertheless, the function of palmitoylation metabolism in prognosis and tumor microenvironment characteristics in liver hepatocellular carcinoma (LIHC) patients is not fully understood. MethodsmRNA and clinical data of LIHC patients were obtained from the TCGA and ICGC databases. Consensus clustering was used to construct palmitoylation metabolism-related clusters. Univariate Cox and Lasso regression analyses were employed to establish a palmitoylation metabolism-related signature (PMS). ssGSEA was applied to evaluate the immune cell score in each LIHC sample. Functional enrichments were accessed through GO, KEGG and GSVA. Drug sensitivity data were downloaded from the GDSC database. ResultsThree palmitoylation metabolism-related clusters with different prognostic and immune infiltration characteristics were constructed in LIHC. We identified PMS with distinct survival, clinical, and tumor immune microenvironment characteristics. The high PMS group had a poorer prognosis, higher infiltration of immunosuppressive cells and higher expression of immune checkpoints. ZDHHC20 exerted a tumor-promoting role in LIHC and was significantly associated with immunosuppressive cells and immunosuppressive checkpoints. Additionally, in HepG-2 and SMCC-7721 cells, si-ZDHHC20 boosted apoptosis but decreased proliferation and migration when compared to si-NC. ConclusionOur research revealed that PMS may accurately predict the prognosis and immune characteristics of LIHC patients. ZDHHC20 has significant clinical and immune relevance in LIHC and may contribute to the formulation of new targets for LIHC immunotherapy.

Multi-omics analysis reveals CLIC1 as a therapeutic vulnerability of gliomas.

Introduction: Despite advances in comprehending cancer biology, malignant gliomas remain incurable. The present work conducted a multi-omics analysis for investigating the significance of chloride intracellular channel 1 (CLIC1) in gliomas. Methods: Multi-omics data of glioma covering transcriptomics, genomics, DNA methylation and single-cell transcriptomics from multiple public cohorts were enrolled for analyzing CLIC1. In vitro experiments were conducted to measure apoptosis and cell mobility in U251 and U373 glioma cells following transfection of CLIC1 siRNAs. Results: Elevated CLIC1 expression was proven to stably and independently estimate worse survival outcomes. CLIC1 expression was higher in more advanced stage, wild-type IDH and unmethylated MGMT samples. Tumorigenic and anticancer immunity pathways were remarkably enriched in CLIC1-up-regulated tumors. Additionally, CLIC1 was positively linked with cancer-immunity cycle, stromal activation, DNA damage repair and cell cycle. Suppressing CLIC1 resulted in apoptosis and attenuated cell motility of glioma cells. More frequent genomic alterations were found in CLIC1-up-regulated tumors. CLIC1 expression presented a remarkably negative connection to DNA methylation. High CLIC1 expression samples were more sensitive to camptothecin, cisplatin, doxorubicin, erlotinib, paclitaxel, rapamycin, clofarabine, tanespimycin, methotrexate, everolimus, TAK-733, trametinib and AZD8330. Tumors with upregulated CLIC1 presented abundant immune cell infiltration, higher expression of immune-checkpoints and -modulators and similar transcriptome profiling, indicative of well response to immune-checkpoint blockade (ICB). Nevertheless, due to elevated TIDE score, tumors with CLIC1 upregulation appeared to be resistant to ICB. Single-cell analysis unveiled that CLIC1 was expressed ubiquitously in tumor cells and tumor microenvironment. Conclusions: Overall, CLIC1 was a promising treatment vulnerability in glioma.

Tyrosine Kinase Inhibition Activates Intratumoral γδ T Cells in Gastrointestinal Stromal Tumor.

γδ T cells are a rare but potent subset of T cells with pleiotropic functions. They commonly reside within tumors but the response of γδ T cells to tyrosine kinase inhibition is unknown. To address this, we studied a genetically engineered mouse model of gastrointestinal stromal tumor (GIST) driven by oncogenic Kit signaling that responds to the Kit inhibitor imatinib. At baseline, γδ T cells were antitumoral, as blockade of either γδ T-cell receptor or IL17A increased tumor weight and decreased antitumor immunity. However, imatinib therapy further stimulated intratumoral γδ T cells, as determined by flow cytometry and single-cell RNA sequencing (scRNA-seq). Imatinib expanded a highly activated γδ T-cell subset with increased IL17A production and higher expression of immune checkpoints and cytolytic effector molecules. Consistent with the mouse model, γδ T cells produced IL17A in fresh human GIST specimens, and imatinib treatment increased γδ T-cell gene signatures, as measured by bulk tumor RNA-seq. Furthermore, tumor γδ T cells correlated with survival in patients with GIST. Our findings highlight the interplay between tumor cell oncogene signaling and antitumor immune responses and identify γδ T cells as targets for immunotherapy in GIST.

Developing a novel SARS-CoV-2 risk index to predict the prognostic and therapeutic effects in acute myeloid leukemia

There is growing evidence of a strong association between SARS-CoV-2 and cancer prognosis and treatment outcome. However, there are no reliable SARS-CoV-2 assessment models to accurately predict prognostic and therapeutic effects in acute myeloid leukemia (AML). Here, differentially expressed genes associated with SARS-CoV-2 were detected, and multiple Cox regression methods were used to construct a SARS-CoV-2 risk index (SC2RI). Then, RT-qPCR was used to validate the gene expression levels in the AML samples. Finally, we explored how the SC2RI affected prognosis, immune infiltration, immunotherapy, and drug sensitivity in AML. We found that CYB5R3 and CLIP4 had been confirmed as hub genes in AML and were used to generate the SC2RI. The datasets indicated that the SC2RI had a superior predictive impact on the prognosis of AML. In addition, high expression of immune checkpoints and numerous immunological infiltrations were substantially correlated with a high SC2RI. However, it responded poorly to immune checkpoint blockade, which may be related to T-cell dysfunction, lack of effective antigens, and deficiency of synaptic capacity. Moreover, a high SC2RI was less susceptible to mTOR-related pathway medications but more sensitive to cell cycle suppressors. Therefore, categorization based on SC2RI could enhance the prognostic prediction of AML and help identify novel therapeutic approaches.

Analysis of Nucleoporin 107 Overexpression and Its Association with Prognosis and Immune Infiltration in Lung Adenocarcinoma by Bioinformatics Methods.

Lung adenocarcinoma (LUAD) has high morbidity and mortality. Current studies indicate nucleoporin 107 (NUP107) is involved in the construction of nuclear pore complex, and NUP107 overexpression contributes to the growth and development in most types of cancers, but its effect in LUAD has not been elucidated. Differences in NUP107 expression were investigated using the Cancer Genome Atlas (TCGA) and multiple Gene Expression Omnibus (GEO) data sets. Enrichment analysis were implemented to probe the NUP107 function. The association of NUP107 with the degree of immune cell infiltration was investigated by the TIMER database, single-sample gene set enrichment analysis (ssGSEA), and ESTIMATE. The association of NUP107 expression with tumor mutation burden (TMB), TP53, and immune checkpoint was analyzed. Single-cell RNA sequencing data were used to detect NUP107 expression in different cell clusters. Finally, we performed real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) to prove the difference of NUP107 expression. NUP107 was overexpressed in LUAD and mainly expressed in cancer stem cell (CSC). Overexpression of NUP107 in LUAD suggested a poorer prognosis. Functional enrichment analysis pointed out that NUP107 was mainly linked to the regulation of cell cycle. Both immune cell infiltration and TMB were found to be in connection with NUP107. Cases in the group with high NUP107 expression had poorer immune infiltration, but had higher expression of immune checkpoints, TMB, and proportion of TP53 mutations. NUP107 is a sensitive diagnostic and prognostic factor for LUAD and may be involved in tumor progression through its effects on cell cycle and immune infiltration.

Establishment of a new molecular subtyping and prognostic signature with m6A/m5C/m1A/m7G regulatory genes for hepatocellular carcinoma

BackgroundRNA modification, including m6A, m5C, m1A, and m7G, participated in tumor progress. Therefore, the purpose of the present study was to explore the role of m6A/m5C/m1A/m7G regulatory genes in the prognosis and tumor microenvironment (TME) for hepatocellular carcinoma (HCC). Methods71 m6A/m5C/m1A/m7G regulatory genes expression for HCC was detected, differentially expressed genes were screened, and molecular forms were classified by unsupervised consensus clustering. Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) analysis were applied to establish a prognostic signature. Time-dependent receiver operating characteristic (ROC) curves were evaluated for clinical effectiveness and accuracy of the prognostic hazard model. In cluster subtypes and risk models, the differences in prognosis, immune cell infiltration, immune checkpoint, immunotherapy, and drug sensitivity between different subtypes were evaluated. ResultsHCC patients were classified into two clusters (cluster 1 and cluster 2) according to the expression of 71 m6A/m5C/m1A/m7G regulatory genes. Cluster 1 had a poor prognosis and different immune cell infiltration. Cluster 1 had higher immune checkpoint expression and TIDE score than cluster 2. Subsequently, we construct a five-gene prognostic model of m6A/m5C/m1A/m7G regulatory genes (YTHDF2, YTHDF1,YBX1, TRMT61A, TRMT10C). The Kaplan-Meier and ROC curve analysis showed that the prognostic signature exhibited good predictability. The risk score was considered an independent poor prognostic index. The high-risk group had higher immune checkpoint expression and higher TIDE scores. 5-Fluorouracil, docetaxel, doxorubicin, etoposide, gemcitabine, paclitaxel, sorafenib, and vinblastine were more suitable for high-risk patients. ECM receptor interaction, cell cycle, and Leishmania infection were enriched in the high-risk group. ConclusionThe clustering subgroups and prognostic model of m6A/m5C/m1A/m7G regulatory genes were linked with bad prognosis and TME for HCC, and had the potential to be a novel tool to evaluate the outcomes of HCC patients.

A BRCA2 germline mutation and high expression of immune checkpoints in a TNBC patient

Triple-negative breast cancer (TNBC) is the most aggressive subtype of mammary carcinoma. Here, we describe a case of an 81-year-old female diagnosed with ductal triple negative breast cancer with a germline pathogenic variant in BReast CAncer gene2 (BRCA2). Genetic testing also revealed the presence of four somatic mutations in the ephrin type-A receptor 3 (EphA3), TP53, BRCA1-associated protein (BAP1), and MYB genes. The BRCA2, TP53, and BAP1 gene mutations are highly predictive of a defective homologous recombination repair system and subsequent chromosomal instability in this patient. Coherently, the patient displayed a strong homologous recombination deficiency signature and high tumor mutational burden status, which are generally associated with increased probability of immune neoantigens formation and presentation, and with tumor immunogenicity. Analysis of immune checkpoint revealed high expression of programmed cell death ligand 1 (PD-L1), programmed cell death ligand 2 (PD-L2), programmed death 1 (PD1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA 4), suggesting that the patient might likely benefit from immunotherapies. Altogether, these findings support an unveiled link between BRCA2 inactivation, HR deficiency and increased expression of immune checkpoints in TNBC. This clinical case highlights the importance of screening TNBC patients for genetic mutations and TMB biomarkers in order to predict the potential efficacy of immunotherapy.