Effective Immunotherapy Strategies Research Articles

Cyclodextrin-Functionalized Gold Nanorods Loaded with Meclofenamic Acid for Improving N6-Methyladenosine-Mediated Second Near-Infrared Photothermal Immunotherapy.

Cancer immunotherapy has achieved considerable clinical progress in recent years on account of its potential to treat metastatic tumors and inhibit recurrence. However, low patient response rates and dose-limiting toxicity are the major limitations of immunotherapy. Nanoparticle-based photothermal immunotherapy can amplify antitumor immune responses, although poor tumor penetration depth of near-infrared radiation (NIR) and the immunosuppressive tumor microenvironment significantly dampen its effects. We designed a nanoplatform based on gold nanorods for NIR-II-mediated photothermal therapy (PTT) combined with N6-methyladenosine (m6A) demethylase inhibition to achieve enhanced photothermal immunotherapy against prostate cancer. The GNRs were assembled layer by layer with polystyrenesulfonate as the interconnecting layer and then coated with a cationic polymer of γ-cyclodextrin (CD)-cross-linked low-molecular-weight polyethylenimine that was conjugated to an 8-mer peptide targeting the prostate tumor-specific gastrin-releasing peptide receptor. The m6A RNA demethylase inhibitor meclofenamic acid (MA) was then loaded into the CD cavity through hydrophobic interactions. GNR-CDP8MA specifically targeted the prostate tumor cells and selectively accumulated at the tumor site in vivo. In addition, GNR-CDP8MA almost completely ablated prostate cancer cell-derived tumors upon 1208 nm laser irradiation. Mechanistically, NIR-II triggered the release of MA from GNR-CDP8MA, which increased global mRNA m6A methylation and decreased the stability of PDL1 transcripts. Furthermore, GNR-CDP8MA-mediated PTT-induced immunogenic cell death in the primary tumor and consequently enhanced antitumor immunity by activating the antigen-presenting dendritic cells and tumor-specific effector T cells in the metastatic tumors. This study offers insights into synergistic m6A RNA methylation and PTT as an effective strategy for cancer immunotherapy.

Prognostic alternative splicing events related splicing factors define the tumor microenvironment and pharmacogenomic landscape in lung adenocarcinoma.

Background: Recent studies identified correlations between splicing factors (SFs) and tumor progression and therapy. However, the potential roles of SFs in immune regulation and the tumor microenvironment (TME) remain unknown.Methods: We used UpSet plots to screen for prognostic-related alternative splicing (AS) events. We evaluated SF patterns in specific immune landscapes. Single sample gene set enrichment analysis (ssGSEA) algorithms were used to quantify relative infiltration levels in immune cell subsets. Principal component analysis (PCA) algorithm-based SFscore were used to evaluate SF patterns in individual tumors with an immune response.Results: From prognosis-related AS events, 16 prognosis-related SFs were selected to construct three SF patterns. Further TME analyses showed these patterns were highly consistent with immune-inflamed, immune-excluded, and immune-desert landscapes. Based on SFscore constructed using differentially expressed genes (DEGs) between SF patterns, patients were classified into two immune-subtypes associated with differential pharmacogenomic landscapes and cell features. A low SFscore was associated with high immune cell infiltration, high tumor mutation burden (TMB), and elevated expression of immune check points (ICPs), indicating a better immune response.Conclusions: SFs are significantly associated with TME remodeling. Evaluating different SF patterns enhances our understanding of the TME and improves effective immunotherapy strategies.

M6A Regulator-Based Exosomal Gene Methylation Modification Patterns Identify Distinct Microenvironment Characterization and Predict Immunotherapeutic Responses in Colon Cancer.

Recent studies have highlighted the biological significance of exosomes and m6A modifications in immunity. Nonetheless, it remains unclear whether the m6A modification gene in exosomes of body fluid has potential roles in the tumor microenvironment (TME). Herein, we identified three different m6A-related exosomal gene modification patterns based on 59 m6A-related exosomal genes, which instructed distinguishing characteristics of TME in colon cancer (CC). We demonstrated that these patterns could predict the stage of tumor inflammation, subtypes, genetic variation, and patient prognosis. Furthermore, we developed a scoring mode—m6A-related exosomal gene score (MREGS)—by detecting the level of m6A modification in exosomes to classify immune phenotypes. Low MREGS, characterized by prominent survival and immune activation, was linked to a better response to anti-PDL1 immunotherapy. In contrast, the higher MREGS group displayed remarkable stromal activation, high activity of innate immunocytes, and a lower survival rate. Hence, this work provides a novel approach for evaluating TME cell infiltration in colon cancer and guiding more effective immunotherapy strategies.

Lactate score predicts survival, immune cell infiltration and response to immunotherapy in breast cancer.

Background: Tumor-derived lactate can modulate the function of infiltrating immune cells to establish an immunosuppressive microenvironment that favors tumor progression. However, possible effects of lactate-related genes (LRGs) on the tumor microenvironment (TME) of breast cancer (BRCA) are still unknown. Methods: LRGs were comprehensively screened from lactate metabolism-related pathways. We correlated the expression of these LRGs with immune cell infiltrating characteristics in the TME and clinicopathological features of patients. We also established a lactate score for quantifying lactate metabolism patterns of cancers and to predict of recurrence-free survival (RFS). Results: We successfully constructed a lactate score that was an independent prognostic factor in BRCA. A low lactate score, which was associated with immune activation with increased CD8+ T cells infiltration levels, indicated an inflamed TME. Consistently, higher expression levels of inhibitory immune checkpoints, including PD-L1, LAG3, CTLA4, and TIM3, as observed from high lactate score subgroup, suggested an immune-desert phenotype as well as poor prognosis. Moreover, a low lactate score predicted the increased chemotherapeutic drug sensitivity and enhanced anti-PD-1 immunotherapy responses. Conclusion: The present study analyzed the potential roles of LRGs in the TME diversity and prognosis. These results will help to improve our understanding of the characteristics of TME immune cell infiltration and guide the development of more effective immunotherapy strategies.

Identification of metabolic genes for the prediction of prognosis and tumor microenvironment infiltration in early-stage non-small cell lung cancer.

Early-stage non-small cell lung cancer (NSCLC) patients are at substantial risk of poor prognosis. We attempted to develop a reliable metabolic gene-set-based signature that can predict prognosis accurately for early-stage patients. Least absolute shrinkage and selection operator method Cox regression models were performed to filter the most useful prognostic genes, and a metabolic gene-set-based signature was constructed. Forty-two metabolism-related genes were finally identified, and with specific risk score formula, patients were classified into high-risk and low-risk groups. Overall survival was significantly different between the two groups in discovery (HR: 5.050, 95% CI: 3.368–7.574, P < 0.001), internal validation series (HR: 6.044, 95% CI: 3.918–9.322, P < 0.001), GSE30219 (HR: 2.059, 95% CI: 1.510–2.808, P < 0.001), and GSE68456 (HR: 2.448, 95% CI: 1.723–3.477, P < 0.001). Survival receiver operating characteristic curve at the 5 years suggested that the metabolic signature (area under the curve [AUC] = 0.805) had better prognostic accuracy than any other clinicopathological factors. Further analysis revealed the distinct differences in immune cell infiltration and tumor purity reflected by an immune and stromal score between high- and low-risk patients. In conclusion, the novel metabolic signature developed in our study shows robust prognostic accuracy in predicting prognosis for early-stage NSCLC patients and may function as a reliable marker for guiding more effective immunotherapy strategies.

Identification of necroptosis-related gene signature and characterization of tumour microenvironment infiltration in non-small-cell lung cancer.

Necroptosis is a programmed necrosis in a caspase‐independent fashion. The role of necroptosis‐related genes (NRGs) in lung cancer remains unknow. Herein, we classified TCGA‐LUAD cohort into two necroptosis‐related subtypes (C1 and C2) by consensus clustering analysis. The result showed that subtype C1 had a favourable prognosis and higher infiltration levels of immune cells. Moreover, subtype C1 was more activated in immune‐associated pathways. Then, we established an NRG prognosis model (NRG score) composed of six NRGs (RIPK3, MLKL, TLR2, TLR4, TNFRSF1A, NDRG2) and divided the cohort into low‐ and high‐risk group. We found that the NRG score was associated with prognosis, tumour immune microenvironment and tumour mutation burden. We also constructed an accurate nomogram model to improve the clinical applicability of NRG score. The result indicated that NRG score may be an independent prognostic marker for lung cancer patients. Taken together, we established a prognosis model that may deepen the understanding of NRGs in lung cancer and provide a basis for developing more effective immunotherapy strategies.

Identification of mRNA vaccines and conserved ferroptosis related immune landscape for individual precision treatment in bladder cancer

BackgroundThe aim of this study was to identify the ferroptosis induced tumor microenvironment (FeME) landscape in bladder cancer (BCa) for mRNA vaccine development and selecting suitable patients for precision treatment.MethodsGene expression profiles and clinical information of 1216 BCa patients were extracted from TCGA-BLCA, three GEO databases and IMvigor210 cohort. We comprehensively established the FeME landscape of 1216 BCa samples based on 290 ferroptosis related genes (FRGs), and systematically correlated these regulation patterns with TME cell-infiltrating characteristics. Besides, we identified the patients’ ferroptosis risk index (FRI) to predict the prognosis of BCa for precise treatment.ResultsSix over-expressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in BCa. Furthermore, we demonstrated the evaluation of FeME within individual tumors could predict stages of tumor inflammation, subtypes, genetic variation, and patient prognosis. Then, 5-lncRNA signature was mined to produce the FRI. Low FRI was also linked to increased mutation load, better prognosis and enhanced response to anti-PD-L1 immunotherapy. Besides, an immunotherapy cohort confirmed patients with lower FRI demonstrated significant therapeutic advantages and clinical benefits.ConclusionsTFRC, SCD, G6PD, FADS2, SQLE, and SLC3A2 are potent antigens for developing anti-BCa mRNA vaccine. Establishment of FRI will contribute to enhancing our cognition of TME infiltration characterization and guiding more effective immunotherapy strategies and selecting appropriate patients for tumor vaccine therapy.

Molecular Subtyping Based on Cuproptosis-Related Genes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma.

The incidence of kidney renal clear cell carcinoma (KIRC) is rising worldwide, and the prognosis is poor. Cuproptosis is a new form of cell death that is dependent on and regulated by copper ions. The relationship between cuproptosis and KIRC remains unclear. In the current study, changes in cuproptosis-related genes (CRGs) in TCGA-KIRC transcriptional datasets were characterized, and the expression patterns of these genes were analyzed. We identified three main molecular subtypes and discovered that multilayer CRG changes were associated with patient clinicopathological traits, prognosis, elesclomol sensitivity, and tumor microenvironment (TME) cell infiltration characteristics. Then, a CRG score was created to predict overall survival (OS). The CRG score was found to be strongly linked to the TME. These findings may help elucidate the roles of CRGs in KIRC, potentially enhancing understanding of cuproptosis and supporting the development of more effective immunotherapy strategies.

M6A Regulator-Based Methylation Modification Patterns Characterized by Distinct Tumor Microenvironment Immune Profiles in Rectal Cancer.

BackgroundPrevious studies reported the related role of RNA n6-methyladenosine (m6A) modification in tumorigenesis and development. However, it is not clear whether m6A modification also plays a potential role in the immune regulation of rectal cancer (RC) and the formation of tumor microenvironment.MethodsIn this study, we screened 23 m6A regulatory factors from 369 rectal cancer specimens, further determined the modification patterns of m6A in RC, and systematically linked these modification patterns with the characteristics of TME cell infiltration. The principal component analysis (PCA) algorithm was used to evaluate the m6A modification pattern of a single tumor related to immune response.ResultsThree different m6A modification patterns were found in the measurement results, which are related to different clinical results and biological pathways. TME identification results show that the identified m6A pattern is closely related to immune characteristics. According to the m6Ascore extracted from m6A-related signature genes, RC patients were divided into high and low score subgroups combined with tumor mutation burden. Patients with high tumor mutation burden and higher m6Ascore have a significant survival advantage and enhanced immune infiltration. Further analysis showed that patients with higher m6Ascore had higher PD-L1 expression levels and showed better immune response and lasting clinical benefits.ConclusionsM6A modification plays a crucial role in the formation of TME diversity and complexity. The evaluation of the m6A modification mode will help us to enhance our understanding of the characteristics of TME infiltration and provide new insights for more effective immunotherapy strategies.

Predicting prognosis and clinical features of the tumor microenvironment based on ferroptosis score in patients with breast cancer

Ferroptosis genes have recently been reported to be involved in regulating the development of cancer, but their potential role in breast cancer (BRCA) is not fully understood. The purpose of this study is to systematically study the mechanism of ferroptosis in BRCA and its relationship with this cancer’s prognosis, cell infiltration, gene mutation, and other clinical features. In this study, The Cancer Genome Atlas breast cancer (TCGA-BRCA) database (UCSC Xena) was used to mine the ferroptosis genes related to BRCA patients, and the genes with prognostic value were screened by Cox regression analysis, which were then used to construct a prognostic model for scoring prognostic molecular risk. The relationships between ferroptosis score and prognosis, molecular typing, and clinical characteristics of BRCA were also analyzed. A total of 176 ferroptosis genes related to BRCA were retrieved from the database, 22 of which were found to be significantly related to BRCA prognosis after screening by single-factor Cox regression analysis (p < 0.01). Unsupervised clustering of samples was performed using factoextra, and two subgroups (ferroptosis cluster A and ferroptosis cluster B) with significant differences in prognosis were identified. Subsequently, single-factor Cox regression analysis and random forest dimensionality reduction were used to screen characteristic genes to construct a ferroptosis score model, which included a high ferroptosis score group and a low ferroptosis score group. The results showed that there were significant differences in ferroptosis scores between the ferroptosis cluster A and B groups. The prognosis of patients with low ferroptosis scores was poor, and the overall survival (OS) rate of patients with high ferroptosis scores was significantly higher, indicating that the prognosis of the sample can be well characterized based on calculated ferroptosis scores. Ferroptosis scores differed significantly according to patient age, TP53 and PIK3CA gene mutations, different PAM50 molecular types, and clinical stages. Ferroptosis activation plays a non-negligible role in tumor occurrence and development. Evaluating the ferroptosis score within BRCA will help advance our understanding of the infiltrating properties of cells in the tumor microenvironment and may guide more effective immunotherapy strategies.

A Novel PD-L1-Containing MSLN Targeting Vaccine for Lung Cancer Immunotherapy.

Therapeutic tumor vaccines have become an important breakthrough in the treatment of various solid tumors including lung cancer. Dendritic cells (DCs)-based tumor vaccines targeting tumor-associated antigens (TAAs) play a key role in immunotherapy and immunoprevention. However, the weak immunogenicity of TAAs and low immune response rates are a major challenge faced in the application of therapeutic tumor vaccines. Here, we tested whether targeting an attractive target Mesothelin (MSLN) and PD-L1 immune checkpoint molecule to DCs in vivo would elicit therapeutic antitumor cytotoxic T lymphocyte (CTL) response. We generated specific MSLN fragment combined with PD-L1 and GM-CSF peptide immunogen (MSLN-PDL1-GMCSF) based on the novel anti-PD-L1 vaccination strategy we recently developed for the cancer treatment and prevention. We found that DCs loaded with MSLN-PDL1-GMCSF vaccine elicited much stronger endogenous anti-PD-L1 antibody and T cell responses in immunized mice and that antigen specific CTLs had cytolytic activities against tumor cells expressing both MSLN and PD-L1. We demonstrated that vaccination with MSLN-PDL1-GMCSF potently inhibited the tumor growth of MSLN+ and PD-L1+ lung cancer cells, exhibiting a significant therapeutic anti-tumor potential. Furthermore, PD-1 blockade further improved the synergistic antitumor therapeutic efficacy of MSLN-PDL1-GMCSF vaccine in immunized mice. In summary, our data demonstrated for the first time that this PD-L1-containing MSLN therapeutic vaccine can induce persistent anti-PD-L1 antibody and CTL responses, providing an effective immunotherapeutic strategy for lung cancer immunotherapy by combining MSLN-PDL1-GMCSF vaccine and PD-1 blockade.

A Single-Cell Atlas of Tumor-Infiltrating Immune Cells in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with limited treatment options. To guide the design of more effective immunotherapy strategies, mass cytometry was employed to characterize the cellular composition of the PDAC-infiltrating immune cells. The expression of 33 protein markers was examined at the single-cell level in more than two million immune cells from four types of clinical samples, including PDAC tumors, normal pancreatic tissues, chronic pancreatitis tissues, and peripheral blood. Based on the analyses, we identified 23 distinct T-cell phenotypes, with some cell clusters exhibiting aberrant frequencies in the tumors. Programmed cell death protein 1 (PD-1) was extensively expressed in CD4+ and CD8+ T cells and coexpressed with both stimulatory and inhibitory immune markers. In addition, we observed elevated levels of functional markers, such as CD137L and CD69, in PDAC-infiltrating immune cells. Moreover, the combination of PD-1 and CD8 was used to stratify PDAC tumors from The Cancer Genome Atlas database into three immune subtypes, with S1 (PD-1+CD8+) exhibiting the best prognosis. Further analysis suggested distinct molecular mechanisms for immune exclusion in different subtypes. Taken together, the single-cell protein expression data depicted a detailed cell atlas of the PDAC-infiltrating immune cells and revealed clinically relevant information regarding useful cell phenotypes and targets for immunotherapy development.

PD-1 Cellular Nanovesicles Carrying Gemcitabine to Inhibit the Proliferation of Triple Negative Breast Cancer Cell.

PD-1 inhibitor Keytruda combined with chemotherapy for Triple-negative breast cancer (TNBC) has been approved for FDA, successfully representing the combination therapy of immunotherapy and chemotherapy for the first time in 2020. However, PD-L1 inhibitor Tecentriq combined with albumin paclitaxel using the similar strategy failed to achieve the expected effect. Therefore, it is still necessary to explore new effective immunotherapy and chemotherapy-based combined strategies. We developed a cell membrane-derived programmed death-ligand 1(PD-1) nanovesicle to encapsulate low-dose gemcitabine (PD-1&GEM NVs) to study the effect on breast cancer in vitro and in vivo. We found that engineered PD-1&GEM NVs could synergistically inhibit the proliferation of triple-negative breast cancer, which interacted with PD-L1 in triple-negative breast cancer to disrupt the PD-L1/PD-1 immune inhibitory axis and promoted cancer cell apoptosis. Moreover, PD-1&GEM NVs had better tumor targeting ability for PD-L1 highly-expressed TNBC cells, contributing to increasing the drug effectiveness and reducing toxicity. Importantly, gemcitabine-encapsulated PD-1 NVs exerted stronger effects on promoting apoptosis of tumor cells, increasing infiltrated CD8+ T cell activation, delaying the tumor growth and prolonging the survival of tumor-bearing mice than PD-1 NVs or gemcitabine alone. Thus, our study highlighted the power of combined low-dose gemcitabine and PD-1 in the nanovesicles as treatment to treat triple-negative breast cancer.

M6A-Regulator Expression Signatures Identify a Subset of Follicular Lymphoma Harboring an Exhausted Tumor Microenvironment.

The role of N6-methyladenosine (m6A) modification in tumor microenvironment has rarely been explored in follicular lymphoma (FL). To examine the role of m6A modification in biological behavior, especially the immune landscape of FL, we utilized the Gene Expression Omnibus database to determine the expression signatures of m6A-regulators by unsupervised clustering, and then condense into a risk score, which was validated in an external cohort from the Tianjin Medical University Cancer Institute and Hospital. Finally, 16 m6A-regulators in 351 FL patients were evaluated and two m6A clusters were identified, characterized by differences in prognosis and biological behaviors. The m6A score was further developed based on 20-genes to quantify the m6A-regulator expression signature in each patient with FL. The low m6A score was associated with inferior prognosis of patients, with a median survival time of 8.84 (95% confidence interval [CI]: 7.251-10.429) years, which was remarkably shorter than that of patients with high m6A scores (15.73 years, 95% CI: 11.729-19.731; p<0.0001). Genes like TNFRSF14, CREBBP, and CARD11 were shown to be more often mutated in the low m6A group. This group was enriched with immune/inflammatory response but along with the abundant infiltration of exhausted T cells and the upregulated PD-1 and PD-L1 expression. Finally, we verified the m6A score could predict the response to anti-PD-L1 antibodies in an immunotherapy cohort. To conclude, the m6A score recognizes a section of FL patients harboring an exhausted tumor microenvironment and may help guide more effective immunotherapy strategies for patients with FL.

Oncolytic virus expressing PD-1 inhibitors activates a collaborative intratumoral immune response to control tumor and synergizes with CTLA-4 or TIM-3 blockade

BackgroundOncolytic viruses (OVs) are capable to inflame the tumor microenvironment (TME) and elicit infiltrating tumor-specific T cell responses. However, OV treatment negatively alters the cancer-immune set point in tumors to...

Necroptosis is Related to Anti-PD-1 Treatment Response and Influences the Tumor Microenvironment in Head and Neck Squamous Cell Carcinoma.

The latest research suggesting that necroptosis plays a vital role in immune response. However, the influence of necroptosis on tumor microenvironment (TME) remodeling and immunotherapy is still unclear. We analyzed the variations in the expression of 26 necroptosis-related molecules in HNSCC and the influence of genome changes. We investigated HNSCC samples and determined that there are two necroptosis phenotypes in HNSCC cancer, and there are significant differences in cell infiltration characteristics and survival in different necroptosis phenotypes. We used the single‐sample gene set enrichment analysis to measure the level of necroptosis in patients with NecroticScore, we confirmed that the NecroticScore can predict the prognosis of HNSCC patients and the response to immunotherapy. Patients with a high NecroticScore are more sensitive to immunotherapy and have a better prognosis. Our study suggests a significant correlation between the expression imbalance of necroptosis-related molecules and suggests necroptosis plays an important role in modeling the TME. In addition, we construct a risk prediction model which could stratify patients with HNSCC and predict patient prognosis according to this necroptosis-related molecules. In conclusion, evaluating necroptosis modification patterns contributes to enhancing our understanding of TME and can guide more effective immunotherapy strategies.

Cancer germline antigen gene MAGEB2 promotes cell invasion and correlates with immune microenvironment and immunotherapeutic efficiency in laryngeal cancer

By multiple transcriptome datasets (TCGA, GSE59102, GSE25727, GSE27020 and GSE65858) and multi-omics (RNA-seq, SNP, CNV, DNA methylation) in-depth analysis, we found that cancer germline antigen (CGA) family/genes MAGEB2 is involved in the imitation, progression and prognosis in LC as well as correlated positively with lymphatic metastasis and negatively with DNA methylation. Then, in vitro experiment verified that MAGEB2 expression renders significant alteration in LC tissues and cells via immunohistochemical (IHC), qRT-PCR and western blot (WB), and up-regulation of MAGEB2 expression could facilitate the proliferation, migration and invasion of LC cells and vice versa. Subsequently, MAGEB2 knockdown suppressed tumor growth and lung metastasis in vivo animal experiment, while MAGEB2 overexpression promoted tumor growth and lung metastasis. Lastly, MAGEB2 is significantly associated with immune cell infiltration (CD8+ T cells particularly, IHC staining confirmed that as the protein expression of MAGEB2 increased, the protein level of CD8 (representing tumor-infiltrating CD8 + T cells) decreased in vitro), immunomodulators (knockdown or overexpression of MAGEB2 on LC cell lines can significantly affect the chemokine/cytokine secretion in vitro), and immunogenicity(TMB) in LC, which hints that MAGEB2 is tightly correlated with immune characteristics and might guide more effective immunotherapy strategies for LC patients.

Construction of immune-related LncRNAs classifier to predict prognosis and immunotherapy response in thymic epithelial tumors.

The primary objective of this study was to construct an immune-related long noncoding RNAs (IRLs) classifier to precisely predict the prognosis and immunotherapy response of patients with thymic epithelial tumors (TET). Based on univariable Cox regression analysis and Lasso regression, six prognosis-related IRLs (AC004466.3, AC138207.2, AC148477.2, AL450270.1, HOXB-AS1 and SNHG8) were selected to build an IRL classifier. Importantly, results of qRT-PCR validated that higher expression levels of AC138207.2, AC148477.2, AL450270.1 and SNHG8 as well as lower expression levels of AC004466.3, and HOXB-AS1 in TETs samples compared with normal controls. The IRL classifier could effectively classify patients into the low-risk and high-risk groups based on the different survival parameters. In terms of predictive ability and clinical utility, the IRL classifier was superior to Masaoka staging system. Additionally, IRL classifier is significantly associated with immune cells infiltration (dendritic cells, activated CD4 memory T cells and tumor-infiltrating lymphocyte (TIL), T cell subsets in particular), immune microenvironment (immune score and immune checkpoint inhibitors) and immunogenicity (TMB) in TETs, which hints that IRL classifier is tightly correlated with immune characteristics and might guide more effective immunotherapy strategies for TETs patients. Encouragingly, according to TIDE algorithm, there were more immunotherapy responders in the low-risk IRL subgroup and the IRL score was robustly negatively linked to the immunotherapeutic response. To sum up, the IRL classifier was established, which can be used to predict the prognosis, immune infiltration status, immunotherapy response in TETs patients, and may facilitate personalized counseling for immunotherapy.

Pyroptosis-Related Patterns Predict Tumor Immune Landscape and Immunotherapy Response in Bladder Cancer.

Background: Bladder cancer (BC) is a leading cause of death from malignancy, with significant heterogeneity in the immunotherapeutic responsiveness of advanced status. Pyroptosis, a newly discovered inflammatory programmed cell death, is confirmed to play an indispensable role in tumorigenesis and anti-tumor activity. However, the effect of pyroptosis on the tumor-immune landscape remodeling and immunotherapy in BC remains elusive. Methods: We comprehensively evaluated the mRNA expression and genomic alterations of 33 pyroptosis-related genes (PRGs) in BC and evaluated the patterns of pyroptosis in publicly available BC datasets. An unsupervised clustering method was used to classify patients into distinct patterns. Then, we established a pyroptosis-related signature score (PS-score) model to quantify the pyroptosis-related patterns of individual BC patients using principal component analysis. Furthermore, we correlated the patterns with the immune landscape and response efficacy of immunotherapy. Results: Two pyroptosis-related patterns were identified in BC, and distinct patterns showed various immune characteristics. Patterns with a high expression level of PRGs exhibited a survival advantage and showed higher infiltration of cytotoxic lymphocytes. Tumors with a low PS-score were characterized by high tumor-infiltrating lymphocytes and considered “hot.” Further analysis revealed that the PS-score was an independent prognostic factor and could predict the response to immunotherapy for patients with advanced BC. We found a significant positive association between AHNAK2, AHNAK nucleoprotein 2, expression, and PS-score. Functional assays showed that AHNAK2 knockdown was correlated with attenuated invasive ability. Conclusion: This work comprehensively demonstrated the potential function of pyroptosis-related patterns in the bladder tumor-immune landscape and identified their therapeutic liability in immunotherapy. Our study enhanced our understanding of the immune landscape and provided a new approach toward more effective immunotherapy strategies.

A Novel Quantification System Combining iTRAQ Technology and Multi-Omics Assessment to Predict Prognosis and Immunotherapy Efficacy in Colon Cancer.

Background: Colon cancer is one of the most common cancer types, although it has certain unique genetic features. This study aimed to develop a unique score for assessing prognosis and immunotherapy efficacy using integrated multi-omics analysis. Methods: Isobaric tagging for relative and absolute quantification (iTRAQ) based proteomic analysis was used to screen differentially expressed proteins (DEP) between tumor and normal samples. DEP mRNA obtained from TCGA were clustered into different categories to show landscape-related prognosis and function. Following that, DEG was extracted from DEP mRNA, and the DEP-related score (DEPRS) was constructed to investigate the difference in immunotherapy prognosis and sensitivity. Finally, WCGNA, random forest, and artificial neural networks were used to screen for key genes. The prognostic value and protein level of these genes were validated. Results: A total of 243 DEPs were identified through iTRAQ analysis, and the corresponding DEP mRNA was clustered into three. Following a series of tests, 1,577 DEGs were identified from overlapped DEP mRNA clusters and were classified into three gene clusters. The two types of clusters described above shared comparable characteristics in terms of prognosis and function. Then, it was established that a high DEPRS indicated a poor prognosis and DEPRS had significant associations with TMB, MSI status, and immunotherapeutic response. Finally, the key genes HART3 and FBLN2 were identified and were found to be implicated in immunotherapy and prognosis. Conclusion: The development of a DEPRS based on multi-omics analysis will aid in improving our understanding of colon cancer and guiding a more effective immunotherapy strategy. DEPRS and key genes are used as biomarkers in the clinical evaluation of patients.