IMvigor210 Cohort Research Articles

Identification of immune-related gene signature model for predicting lung cancer survival and response to immunotherapy.

Studies have shown that immune-related genes play a crucial role in tumor development and treatment. However, the specific roles and potential value of these genes in lung cancer patients are still not fully understood. Therefore, this study aims to establish a novel risk model based on immune-related genes for evaluating the prognostic risk and response to immune therapy in lung cancer patients. Gene expression and clinical data of lung cancer patients were retrieved from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, while immune-related genes were obtained from the ImmPort database. A risk signature model was developed using univariate Cox analysis and LASSO regression analysis. The prognostic value of the model and its response to immunotherapy were analyzed by survival analysis, immune infiltration analysis and immunotherapy response analysis. We have developed a risk signature model based on eight key immune-related genes, which can classify patients into high-risk and low-risk groups. The prognosis of the high-risk group was significantly lower than that of the low-risk group and was validated in multiple GEO datasets. The mutation frequency was lower in the low-risk group compared to the high-risk group (TP53: 55% vs 65%; TTN: 52% vs 60%; CSMD3: 34% vs 45%). Futhermore, CD274 expression was lower in the low-risk patients, and the high-risk patients in the IMvigor210 cohort had lower survival. Immune infiltration analyses showed that the high-risk group was negatively correlated with the infiltration level of B cells, CD4+ T cells, and NK cells. Importantly, patients in the low-risk group exhibit significantly lower TIDE scores, suggesting that they are more responsive to immunotherapy. Our study has established a novel and robust immune-related gene risk model that can assist in evaluating the prognostic risk and immune therapy response of lung cancer patients.

The prognostic value and immunological role of calcium/calmodulin dependent protein kinase kinase 2 (CAMKK2) in pan-cancer study.

A thorough assessment of calcium/calmodulin dependent protein kinase kinase 2 (CAMKK2) in pan-cancer studies is currently absent. We integrate multi-omics and clinical data to conduct a molecular landscape of CAMKK2. Gene variation results revealed abnormal high frequency mutations of CAMKK2 in uterine corpus endometrial carcinoma, while expression level analysis demonstrated relatively high expression of CAMKK2 in prostate adenocarcinoma. The aberrant expression of CAMKK2 was found to be predictive of survival outcomes in several cancer types. Additionally, we identified potential regulators of CAMKK2 expression, including miRNAs such as miR.129.1.3p, as well as small-molecule drugs such as EPZ004777, which significantly correlated with CAMKK2 expression. Single-cell transcriptome analysis of kidney renal clear cell carcinoma further revealed a significantly higher expression of CAMKK2 in and monocyte and macrophage M1. Furthermore, in the kidney renal clear cell carcinoma IMvigor210 cohort, patients ongoing immunotherapy with higher CAMKK2 expression experienced a significantly longer median overall survival, but it was observed that in bladder urothelial carcinoma GSE176307 and skin cutaneous melanoma GSE78220 cohorts, CAMKK2 might significantly prolong overall survival. Briefly, CAMKK2 emerges as a promising molecular biomarker that holds potential implications for prognostic evaluation and predicting the effectiveness of immunotherapy across cancers.

Machine learning-based integration of CD8 T cell-related gene signatures for comprehensive prognostic assessment in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) stands as the most prevalent histological subtype of lung cancer, exhibiting heterogeneity in outcomes and diverse responses to therapy. CD8 T cells are consistently present throughout all stages of tumor development and play a pivotal role within the tumor microenvironment (TME). Our objective was to investigate the expression profiles of CD8 T cell marker genes, establish a prognostic risk model based on these genes in LUAD, and explore its relationship with immunotherapy response. By leveraging the expression data and clinical records from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, we identified 23 consensus prognostic genes. Employing ten machine-learning algorithms, we generated 101 combinations, ultimately selecting the optimal algorithm to construct an artificial intelligence-derived prognostic signature named riskScore. This selection was based on the average concordance index (C-index) across three testing cohorts. RiskScore emerged as an independent risk factor for overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS) in LUAD. Notably, riskScore exhibited notably superior predictive accuracy compared to traditional clinical variables. Furthermore, we observed a positive correlation between the high-risk riskScore group and tumor-promoting biological functions, lower tumor mutational burden (TMB), lower neoantigen (NEO) load, and lower microsatellite instability (MSI) scores, as well as reduced immune cell infiltration and an increased probability of immune evasion within the TME. Of significance, the immunophenoscore (IPS) score displayed significant differences among risk subgroups, and riskScore effectively stratified patients in the IMvigor210 and GSE135222 immunotherapy cohort based on their survival outcomes. Additionally, we identified potential drugs that could target specific risk subgroups. In summary, riskScore demonstrates its potential as a robust and promising tool for guiding clinical management and tailoring individualized treatments for LUAD patients.

Synergistic antitumor activity of METTL3 peptide degrader and immune checkpoint inhibitor in advanced urothelial cancer.

e14623 Background: In patients afflicted with advanced urothelial carcinoma (aUC), the durable response rate to immune checkpoint inhibitor (ICI) is approximately 20%. Recent study showed the pivotal role of N6-methyladenosine (m6A) methyltransferase-like 3 (METTL3) in immune escape and the progression of aUC. This study aimed to develop a novel METTL3 peptide degrader RKL and investigate its synergistic effects and underlying mechanisms in combination with ICI for aUC. Methods: Methyltransferase expression profiles were scrutinized using The Cancer Genome Atlas database; while the prognostic implications of METTL3 expression in response to ICI were analyzed in the IMvigor210 cohort study. Single-cell RNA sequencing (scRNA-seq) was employed to elucidate the mechanistic insights. The METTL3 peptide degrader RKL was synthesized using Fmoc solid-phase peptide synthesis and purified with high-performance liquid chromatography. In vivo and in vitro experiments were conducted to assess the impact of RKL, ICI, and their combination on aUC inhibition. Results: In aUC, METTL3 exhibited the most significant up-regulation among m6A methyltransferases, while METTL14 and WTAP showed down-regulated expression. In the IMvigor210 cohort study, aUC patients with elevated METTL3 expression and treated with ICI demonstrated a poorer prognosis. scRNA-seq revealed that METTL3 upregulation promoted the expression of genes regulating cancer-associated fibroblast proliferation, contributing to enhanced tumor resistance to immunotherapy. RKL demonstrated high toxicity to urothelial carcinoma cell lines, inhibiting their proliferative, migratory, and invasive capacities in vitro. The combined treatment of RKL and ICI significantly reduced tumor volume (P<0.001), with a complete response achieved in 87.5% (7/8) of mice in the combination group, 12.5% (1/8) in the RKL group, and 25.0% (2/8) in the ICI group. Conclusions: METTL3 overexpression in aUC is associated with immune escape and resistance to ICI therapy. The METTL3 peptide degrader RKL, when combined with ICI, demonstrates synergistic antitumor effects in aUC, warranting further exploration in clinical research.

RAD51 Expression as a Biomarker to Predict Efficacy of Platinum-Based Chemotherapy and PD-L1 Blockade for Muscle-Invasive Bladder Cancer.

RAD51, a key recombinase that catalyzes homologous recombination (HR), is commonly overexpressed in multiple cancers. It is curial for DNA damage repair (DDR) to maintain genomic integrity which could further determine the therapeutic response. Herein, we attempt to explore the clinical value of RAD51 in therapeutic guidance in muscle-invasive bladder cancer (MIBC). In this retrospective study, a total of 823 patients with MIBC were included. Zhongshan hospital (ZSHS) cohort (n=134) and The Cancer Genome Atlas-Bladder Cancer (TCGA-BLCA) cohort (n=391) were included for the investigation of chemotherapeutic response. The IMvigor210 cohort (n=298) was utilized to interrogate the predictive efficacy of RAD51 status to programmed cell death ligand-1 (PD-L1) blockade. In addition, the association of RAD51 with genomic instability and tumor immune contexture was investigated. Patients with RAD51 overexpression were more likely to benefit from both platinum-based chemotherapy and immunotherapy rather than RAD51-low patients. The TMBhighPD-L1highRAD51high subgroup possessed the best clinical benefits from PD-L1 blockade. RAD51-high tumors featured by genomic instability were correlated to highly inflamed and immunogenic contexture with activated immunotherapeutic pathway in MIBC. RAD51 could serve as a prognosticator for treatment response to platinum-based chemotherapy and PD-L1 inhibitor in MIBC patients. Besides, it could also improve the predictive efficacy of TMB and PD-L1.

Discovery of a T cell proliferation-associated regulator signature correlates with prognosis risk and immunotherapy response in bladder cancer.

The efficacy of immunotherapy is heavily influenced by T cell activity. This study aimed to examine how T cell proliferation regulators can predict the prognosis and response to immunotherapy in patients with bladder cancer (BCa). T cell proliferation-related subtypes were determined by employing the non-negative matrix factorization (NMF) algorithm that analyzed the expression patterns of T cell proliferation regulators. Subtypes were assessed for variations in prognosis, immune infiltration, and functional behaviors. Subsequently, a risk model related to T cell proliferation was created through Cox and Lasso regression analyses in the TCGA cohort and then confirmed in two GEO cohorts and an immunotherapy cohort. BCa patients were categorized into two subtypes (C1 and C2) according to the expression profiles of 31T cell proliferation-related genes (TRGs) with distinct prognoses and immune landscapes. The C2 subtype had a shorter overall survival (OS), with higher levels of M2 macrophage infiltration, and the activation of cancer-related pathways than the C1 subtype. Following this, thirteen prognosis-related genes that were involved in T cell proliferation were utilized to create the prognostic signature. The model's predictive accuracy was confirmed by analyzing both internal and external datasets. Individuals in the high-risk category experienced a poorer prognosis, increased immunosuppressive factors in the tumor microenvironment, and diminished responses to immunotherapy. Additionally, the immunotherapeutic prediction efficacy of the model was further confirmed by an immunotherapy cohort (anti-PD-L1 in the IMvigor210 cohort). Our study characterized two subtypes linked to T cell proliferation in BCa patients with distinct prognoses and tumor microenvironment (TME) patterns, providing new insights into the heterogeneity of T cell proliferation in BCa and its connection to the immune landscape. The signature has prospective clinical implications for predicting outcomes and may help physicians to select prospective responders who prioritize current immunotherapy.

Increased co-expression of 4-1BB with PD-1 on CD8+ tumor-infiltrating lymphocytes is associated with improved prognosis and immunotherapy response in cervical cancer.

The combination of agonistic antibodies with immune checkpoint inhibitors presents a promising avenue for cancer immunotherapy. Our objective is to explore the co-expression of 4-1BB, ICOS, CD28, with PD-1 on CD8+ T cells in the peripheral blood and tumor tissue of cervical cancer(CC) patients, with a specific focus on the association between the co-expression levels of 4-1BB with PD-1 and clinical features, prognosis as well as immunotherapy response. The goal is to offer valuable insights into cervical cancer immunotherapy. In this study, 50 treatment-naive patients diagnosed with CC were enrolled. Flow cytometry was used to detect PD-1/4-1BB, PD-1/ICOS and PD-1/CD28 co-expression on CD8+ T cells. Subsequent analysis aimed to investigate the differential co-expression between peripheral blood and cancer tissue, and also the correlation between co-expression and clinical features in these patients. Gene Expression Omnibus (GEO) datasets, The Cancer Genome Atlas (TCGA) cohort, The IMvigor210 cohort, The BMS038cohort and Immunophenoscores were utilized to investigate the correlation between PD-1/4-1BB and the immune microenvironment, prognosis, immunotherapy, and drug sensitivity in cervical cancer. The co-expression levels of PD-1/4-1BB, PD-1/ICOS, and PD-1/CD28 on CD8+ tumor-infiltrating lymphocytes (TILs) were significantly higher in cervical cancer patients compared to those in peripheral blood. Clinical feature analysis reveals that on CD8+ TILs, the co-expression of PD-1/4-1BB is more closely correlated with clinical characteristics compared to PD-1/ICOS, PD-1/CD28, PD-1, and 4-1BB. Pseudo-time analysis and cell communication profiling reveal close associations between the subgroups harboring 4-1BB and PD-1. The prognosis, tumor mutation burden, immune landscape, and immunotherapy response exhibit statistically significant variations between the high and low co-expression groups of PD-1/4-1BB. The high co-expression group of PD-1/4-1BB is more likely to benefit from immunotherapy. PD-1/4-1BB, PD-1/ICOS, and PD-1/CD28 exhibit elevated co-expression on CD8+TILs of cervical cancer, while demonstrating lower expression in circulating T cells. The co-expression patterns of PD-1/4-1BB significantly contributed to the prediction of immune cell infiltration characteristics, prognosis, and tailored immunotherapy tactics. PD-1/4-1BB exhibits potential as a target for combination immunotherapy in cervical cancer.

Identification of a cisplatin resistant-based prognostic immune related gene signature in MIBC

Cisplatin resistance plays a significant role in the dismal prognosis and progression of muscle-invasive bladder cancer (MIBC). However, the strategies to predict prognosis and cisplatin resistance are inefficient, and it remains unclear whether cisplatin resistance is associated with tumor immunity. In this study, we integrated the transcriptional data from cisplatin-resistant cell lines and a TCGA-MIBC cohort to establish cisplatin-resistance-related cluster classification and a cisplatin-resistance-related gene risk score (CRRGRS). Kaplan–Meier survival curves showed that compared with those in low CRRGRS group, MIBC patients belonging to high CRRGRS group had worse prognosis in TCGA-MIBC cohort and external GEO cohorts. Meanwhile, CRRGRS was able to help forecast chemotherapy and immunotherapy response of MIBC patients in the TGCA cohort and IMvigor210 cohort. Moreover, compared with the low CRRGRS group, the high CRRGS group possessed a relatively immunosuppressive “cold tumor” phenotype with a higher tumor immune dysfunction and exclusion (TIDE) score, ESTIMATE score, stromal score and immune score and a lower immunophenoscore (IPS) score. The upregulated expression levels of immune checkpoint genes, including PD-1, PD-L1 and CTLA4, in the high CRRGRS group also further indicated that a relative immunosuppressive tumor microenvironment may exist in MIBC patients belonging to high CRRGRS group. In addition, we integrated CRRGRS and clinical characteristics with prognostic value to develop a nomogram, which could help forecast overall survival of MIBC patients. Furthermore, DIAPH3 was identified as a regulator of proliferation and cisplatin resistance in MIBC. The expression of DIAPH3 was increased in cisplatin-resistant cell lines and chemotherapy-unsensitive people. Further mechanism exploration revealed that DIAPH3 facilitated tumor proliferation and cisplatin resistance by regulating the NF-kB and epithelial-mesenchymal transition (EMT) pathways. In conclusion, the comprehensive investigations of CRRGRS increased the understanding of cisplatin resistance and provided promising insights to restrain tumor growth and overcome chemoresistance by targeting DIAPH3.

LRP1 induces anti-PD-1 resistance by modulating the DLL4-NOTCH2-CCL2 axis and redirecting M2-like macrophage polarisation in bladder cancer

The tumour microenvironment (TME) drives bladder cancer (BLCA) progression. Targeting the TME has emerged as a promising strategy for BLCA treatment in recent years. Furthermore, checkpoint blockade therapies are only beneficial for a minority of patients with BLCA, and drug resistance is a barrier to achieving significant clinical effects of anti-programmed cell death protein-1 (PD-1)/programmed death protein ligand-1 (PD-L1) therapy. In this study, higher low-density lipoprotein receptor-related protein 1 (LRP1) levels were related to a poorer prognosis for patients with various cancers, including those with higher grades and later stages of BLCA. Enrichment analysis demonstrated that LRP1 plays a role in the epithelial–mesenchymal transition (EMT), NOTCH signalling pathway, and ubiquitination. LRP1 knockdown in BLCA cells delayed BLCA progression both in vivo and in vitro. Furthermore, LRP1 knockdown suppressed EMT, reduced DLL4-NOTCH2 signalling activity, and downregulated M2-like macrophage polarisation. Patients with BLCA and higher LRP1 levels responded weakly to anti-PD-1 therapy in the IMvigor210 cohort. Moreover, LRP1 knockdown enhanced the therapeutic effects of anti-PD-1 in mice. Taken together, our findings suggest that LRP1 is a potential target for improving the efficacy of anti-PD-1/PD-L1 therapy by preventing EMT and M2-like macrophage polarisation by blocking the DLL4-NOTCH2 axis.

Identification of VRK1 as a Novel Potential Biomarker for Prognosis and Immunotherapy in Hepatocellular Carcinoma.

Research has indicated that VRK1 is essential for the tumor cell cycle. However, its prognostic and immunotherapeutic predictive significance has not been documented in hepatocellular carcinoma (HCC). The TCGA, ICGC, and GSE14520 datasets were used to investigate VRK1 expression and its predictive significance of survival outcomes. The qRT-PCR and immunohistochemistry (IHC) were used to confirm the findings. The immunotherapeutic response of VRK1 was anticipated by the IMvigor210 cohort. Lastly, the association between immune infiltration, m6A modification, and functional enrichment of differentially expressed genes (DEGs) was investigated in connection to VRK1 expression. VRK1 expression was markedly elevated on both the mRNA and protein levels in HCC. In HCC patients, a high expression of VRK1 was linked to a poor prognosis. Furthermore, there was a substantial positive correlation seen between increased VRK1 expression and the response rate to anti-PD-L1 immunotherapy. Relationships between VRK1 and m6A-related genes as well as different immune cells were shown by correlation studies. Lastly, enrichment analysis revealed a tight relationship between VRK1 and important biological functions, including DNA replication, cell cycle control, and fatty acid metabolism. Our research reveals the potential of VRK1 as a novel biomarker for prognosis and immunotherapy response in HCC patients.

Integration of CD4+ T cells and molecular subtype predicts benefit from PD-L1 blockade in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) is a disease characterized by molecular and clinical heterogeneity, posing challenges in selecting the most appropriate treatment in clinical settings. Considering the significant role of CD4+ T cells, there is an emerging need to integrate CD4+ T cells with molecular subtypes to refine classification. We conducted a comprehensive study involving 895 MIBC patients from four independent cohorts. The Zhongshan Hospital (ZSHS) and The Cancer Genome Atlas (TCGA) cohorts were included to investigate chemotherapeutic response. The IMvigor210 cohort was included to assess the immunotherapeutic response. NCT03179943 was used to evaluate the clinical response to a combination of immune checkpoint blockade (ICB) and chemotherapy. Additionally, we evaluated genomic characteristics and the immune microenvironment to gain deeper insights into the distinctive features of each subtype. We unveiled four immune-molecular subtypes, each exhibiting distinct clinical outcomes and molecular characteristics. These subtypes include luminal CD4+ Thigh, which demonstrated benefits from both immunotherapy and chemotherapy; luminal CD4+ Tlow, characterized by the highest level of fibroblast growth factor receptor 3 (FGFR3) mutation, thus indicating potential responsiveness to FGFR inhibitors; basal CD4+ Thigh, which could benefit from a combination of ICB and chemotherapy; and basal CD4+ Tlow, characterized by an immune suppression microenvironment and likely to benefit from transforming growth factor-β (TGF-β) inhibition. This immune-molecular classification offers new possibilities for optimizing therapeutic interventions in MIBC.

Graphene therapy-related lncRNAs as prognostic and immune microenvironmental biomarkers in hepatocellular carcinoma

BackgroundGraphene materials have the capacity to influence the tumor microenvironment and intracellular signaling responsiveness. However, the process of graphene-assisted liver cancer treatment still lacks specific biomarkers for assessing its efficacy. MethodsWe identified graphene therapy-related lncRNAs (GTLncRNAs) through gene analysis and correlation tests. Multivariate COX and LASSO regression analyses yielded significant lncRNAs for a risk score model. We evaluated clinicopathological factors and tumor microenvironment using ssGSEA. We scrutinized the pathways of immune function, the evasion of tumor immunity, and the potential for immunotherapy. GTLncRNAs with differential expression were subjected to GO/KEGG analysis, and prospective chemotherapy drugs were discerned utilizing the pRRophetic algorithm. The prognostic model was authenticated through the examination of the Imvigor210 cohort, and an analysis of mRNA stemness was executed. ResultsThe researchers constructed a prognostic model based on 22 graphene therapy-related lncRNAs. Protective lncRNAs (AC010280.2, AL365361.1, and LINC01549) and negative lncRNAs (AC026412.3, AL031985.3, ELFN1-AS1, SNHG4, and EB2-AS1) were identified. Higher risk scores correlated with shorter survival. Low-risk immune pathways included Type_II_IFN_Reponse and cytolytic_activity. Subgroups differed significantly in TMB, TIDE, MDSC, exclusion, and dysfunction. Low TMB values correlated with longer survival. The high-risk subgroup showed increased sensitivity to screened compounds, and mRNAsi was higher in cancer tissue. ConclusionsOur GTLncRNAs-based model accurately predicted survival of HCC patients and underscored the influence of graphene therapy-related genes on the tumor microenvironment. Potential treatment compounds were identified, and the mRNAsi index demonstrated prognostic value.

Multi-cohort validation of Ascore: an anoikis-based prognostic signature for predicting disease progression and immunotherapy response in bladder cancer

Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown promise in clinical therapy in both operable and advanced bladder cancer, identifying patients who will respond is challenging. Anoikis, a specialized form of cell death that occurs when cells detach from the extracellular matrix, is closely linked to tumor progression. Here, we aimed to explore the anoikis-based biomarkers for bladder cancer prognosis and immunotherapeutic decisions. Through consensus clustering, we categorized patients from the TCGA-BLCA cohort into two clusters based on anoikis-related genes (ARGs). Significant differences in survival outcome, clinical features, tumor immune environment (TIME), and potential ICIs response were observed between clusters. We then formulated a four-gene signature, termed "Ascore", to encapsulate this gene expression pattern. The Ascore was found to be closely associated with survival outcome and served as an independent prognosticator in both the TCGA-BLCA cohort and the IMvigor210 cohort. It also demonstrated superior predictive capacity (AUC = 0.717) for bladder cancer immunotherapy response compared to biomarkers like TMB and PD-L1. Finally, we evaluated Ascore’s independent prognostic performance as a non-invasive biomarker in our clinical cohort (Gulou-Cohort1) using circulating tumor cells detection, achieving an AUC of 0.803. Another clinical cohort (Gulou-Cohort2) consisted of 40 patients undergoing neoadjuvant anti-PD-1 treatment was also examined. Immunohistochemistry of Ascore in these patients revealed its correlation with the pathological response to bladder cancer immunotherapy (P = 0.004). Impressively, Ascore (AUC = 0.913) surpassed PD-L1 (AUC = 0.662) in forecasting immunotherapy response and indicated better net benefit. In conclusion, our study introduces Ascore as a novel, robust prognostic biomarker for bladder cancer, offering a new tool for enhancing immunotherapy decisions and contributing to the tailored treatment approaches in this field.

Disulfidptosis-related genes of prognostic signature and immune infiltration features in hepatocellular carcinoma supported by bulk and single-cell RNA sequencing data.

Disulfidptosis is a new type of cellular death triggered in response to disulfide stress and is strongly linked to the progression of malignancies. Hepatocellular carcinoma (HCC) is a very common malignancy. Some reports have suggested a link between disulfidptosis-related genes (DRGs) and cancer; however, further research needs to be conducted. In this study, HCC data from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma and Gene Expression Omnibus data sets were collected and analyzed. A univariate Cox regression analysis, least absolute shrinkage and selection operator, and multivariate Cox regression analysis were conducted to identify the hub DRGs signature for prognosis. The HCC patients were allocated to high- and low-risk groups based on their disulfidptosis risk scores. The model was validated with a high degree of precision using both internal and external validation data sets. "ESTIMATE" and "CIBERSORT" packages were employed to assess the immunological landscapes and immune cell infiltration. The IMvigor210 cohort was chosen to validate the immunotherapy results. A drug sensitivity analysis was conducted to identify targeted medications. The expression of the hub DRGs in the HCC cells was confirmed using cytological techniques. The bioinformatic analysis revealed that 16 genes showed differential expression. A prognostic model was developed based on four genes: RPN1, SLC2A1, SLC2A4, and SLC7A11. A notable difference in prognosis was observed between the two risk groups. Based on the results of the immune microenvironment, tumor mutation burden, immunotherapy, and drug screening analyses, the DRGs signature can be employed in HCC immunotherapy decision making. Further, the expression levels of the hub DRGs were significantly upregulated in the HCC cells. Our four-DRGs signature could be used to predict HCC prognosis. Further, this study showed that the hub DRGs could serve as biomarkers for immunotherapy prediction and could potentially guide targeted therapies.

POLQ identifies a better response subset to immunotherapy in muscle-invasive bladder cancer with high PD-L1.

Though programmed cell death-ligand 1 (PD-L1) has been used in predicting the efficacy of immune checkpoint blockade (ICB), it is insufficient as a single biomarker. As a key effector of an intrinsically mutagenic microhomology-mediated end joining (MMEJ) pathway, DNA polymerase theta (POLQ) was overexpressed in various malignancies, whose expression might have an influence on genomic stability, therefore altering the sensitivity to chemotherapy and immunotherapy. A total of 1304 patients with muscle-invasive bladder cancer (MIBC) from six independent cohorts were included in this study. The Zhongshan Hospital (ZSHS) cohort (n = 134), The Cancer Genome Atlas (TCGA) cohort (n = 391), and the Neo-cohort (n = 148) were included for the investigation of chemotherapeutic response. The IMvigor210 cohort (n = 234) and the UNC-108 cohort (n = 89) were used for the assessment of immunotherapeutic response. In addition, the relationship between POLQ and the immune microenvironment was assessed, and GSE32894 (n = 308) was used only for the evaluation of the immune microenvironment. We identified POLQhigh PD-L1high patients could benefit more from immunotherapy and platinum-based chemotherapy. Further analysis revealed that high POLQ expression was linked to chromosome instability and higher tumor mutational burden (TMB), which might elicit the production of neoantigens. Further, high POLQ expression was associated with an active tumor immune microenvironment with abundant infiltration of immune effector cells and molecules. The study demonstrated that high POLQ expression was correlated with chromosome instability and antitumor immune microenvironment in MIBC, and the combination of POLQ and PD-L1 could be used as a superior companion biomarker for predicting the efficacy of immunotherapy.

Identification and Functional Characterization of PI3K/Akt/mTOR Pathway-Related lncRNAs in Lung Adenocarcinoma: A Retrospective Study.

This paper aimed to investigate the PI3K/Akt/mTOR signal-pathway regulator factor-related lncRNA signatures (PAM-SRFLncSigs), associated with regulators of the indicated signaling pathway in patients with lung adenocarcinoma (LUAD) undergoing immunotherapy. In this retrospective study, we employed univariate Cox, multivariate Cox, and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostically relevant long non-coding RNAs (lncRNAs), construct prognostic models, and perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Subsequently, immunoassay and chemotherapy drug screening were conducted. Finally, the prognostic model was validated using the Imvigor210 cohort, and tumor stem cells were analyzed. We identified seven prognosis-related lncRNAs (AC084757.3, AC010999.2, LINC02802, AC026979.2, AC024896.1, LINC00941 and LINC01312). We also developed prognostic models to predict survival in patients with LUAD. KEGG enrichment analysis confirmed association of LUAD with the PI3K/Akt/mTOR signaling pathway. In the analysis of immune function pathways, we discovered three good prognostic pathways (Cytolytic_activity, Inflammation-promoting, T_cell_co-inhibition) in LUAD. Additionally, we screened 73 oncology chemotherapy drugs using the "pRRophetic" algorithm. Identification of seven lncRNAs linked to regulators of the PI3K/Akt/mTOR signaling pathway provided valuable insights into predicting the prognosis of LUAD, understanding the immune microenvironment and optimizing immunotherapy strategies.

Carcinogenic Role and Clinical Significance of Histone H3-H4 Chaperone Anti-silencing Function 1 B (ASF1B) in Lung Adenocarcinoma.

Histone H3-H4 chaperone anti-silencing function 1 (ASF1) plays an important role in the polymerization, transport, and modification of histones. However, the significance of ASF1B in lung adenocarcinoma (LUAD) is largely overlooked. We investigated the aberrant expression of ASF1B in LUAD and its potential link to patient survival using multiple databases. ASF1B-overexpressing and knockdown cell lines were constructed to explore its effects on the biological behavior of lung cancer cells. ssGSEA, TMB, TIDE and IMvigor210 cohort were used to explore and validate the association of ASF1B to tumor immunity. Our data suggested that ASF1B was overexpressed in LUAD, and was associated with poor prognosis. ASF1B promoted the proliferation, migration, and invasion of lung cancer cells by regulating the phosphorylation of AKT in vitro. ASF1B was associated with tumor immunity. In summary, ASF1B may promote malignant behavior of LUAD cells, and its overexpression correlates with worse prognosis and better immunotherapy effect.

Role of vascular endothelial growth factor D in lung adenocarcinoma immunotherapy response.

To identify key genes associated with tumor-associated macrophages (TAMs), tumor immunotherapy, in the prognosis of lung adenocarcinoma (LUAD). The mRNA expression profiles of LUAD samples were obtained from The Cancer Genome Atlas (TCGA) database. The "CIBERSORT" R package was employed to calculate the proportion of innate immune cell infiltration in both tumor and adjacent normal tissues. TAM-associated genes in LUAD were identified to construct a prognostic risk model using weighted gene correlation network analysis (WGCNA), Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses (COX). The IMvigor210 cohort was utilized to validate the roles of these genes as predictors of immunotherapy response. Tissue microarrays, immunofluorescence staining, and mRNA level detection methods were used to determine the correlation of risk factors in LUAD tissues. CIBERSORT analysis revealed significant differences in innate immune cells between tumor and adjacent tissues. Seventy-four differential genes linked to these cells were identified from WGCNA. Four hub genes (endothelin receptor type B, vascular endothelial growth factor D (VEGFD), latent transforming growth factor beta binding protein 4 (LTBP4), and fibroblast growth factor receptor 4 (FGFR4)) in the TAM prognostic model were identified as independent prognostic risk factors (P < 0.05). VEGFD expression was identified as a low-risk factor for LUAD prognosis prediction (P < 0.05). Moreover, low-risk patients exhibited higher sensitivity to anti-PD-L1 therapy compared to high-risk patients (P < 0.05). VEGFD levels were negatively correlated with programmed cell death 1 (PD-1) levels (r = -0.363; P < 0.05), suggesting that VEGFD may serve as a predictor for anti-PD-1 treatment. VEGFD is associated with innate immunity in LUAD, it can predict LUAD prognosis, and therefor may be a potential predictor for anti-PD-1 treatment in patients with LUAD.

IL4I1: a novel molecular biomarker represents an inflamed tumor microenvironment and precisely predicts the molecular subtype and immunotherapy response of bladder cancer.

Introduction: IL4I1, also known as Interleukin-4-induced gene 1, is an enzyme that can modulate the immune system by acting as a L-amino acid oxidase. Nevertheless, a precise understanding of the correlation of IL4I1 with immunological features and immunotherapy efficacy in bladder cancer (BLCA) remains incomplete. Methods: We analyzed RNA sequencing data from the Cancer Genome Atlas (TCGA) to investigate the immune function and prognostic importance of IL4I1 across different cancer types. We further examined the TCGA-BLCA cohort for correlations between IL4I1 and various immunological characteristics of tumor microenvironment (TME), such as cancer immune cycle, immune cell infiltration, immune checkpoint expression and T cell inflamed score. Validation was conducted using two independent cohort, GSE48075 and E-MTAB-4321. Finally, RNA sequencing data from the IMvigor210 cohort and immunohistochemistry assays were employed to validate the predictive value of IL4I1 for the TME and immunotherapy efficacy. Results: In our findings, a positive correlation was observed between IL4I1 expression and immunomodulators expression, immune cell infiltration, the cancer immune cycle, and T cell inflamed score in BLCA, suggesting a significant link to the inflamed TME. In addition, studies have shown that IL4I1 elevated levels of individuals tend to be more performance for basal subtype and exhibit enhanced response rates to diverse treatment modalities, specifically immunotherapy. Clinical data from the IMvigor 210 cohort confirmed a higher rate of response to immunotherapy and better survival benefits in patients with high IL4I1 expression. Discussion: To summarize, our research showed that elevated IL4I1 levels are indicative of an inflamed TME, the basal subtype, and a more favorable response to various treatment methods, especially immune checkpoint blockade therapy in BLCA.

Identification of a cancer associated fibroblasts-related index to predict prognosis and immune landscape in ovarian cancer

Cancer-associated fibroblasts (CAFs) play a role in ovarian cancer (OV) evolution, immunosuppression and promotion of drug resistance. Exploring the value of CAFs-related biomarker in OV is of great importance. In the present work, we developed a CAFs-related index (CAFRI) based on an integrated analysis of single-cell and bulk RNA-sequencing and highlighted the value of CAFRI in predicting clinical outcomes in individuals with OV, tumour immune microenvironment (TIME) and response to immune checkpoint inhibitors (ICIs). The GSE151214 cohort was used for cell subpopulation localization and analysis, the TCGA-OV patients as a training set. Moreover, the ICGC-OV, GSE26193, GSE26712 and GSE19829 cohorts were used for the validation of CAFRI. The TIMER 2.0, CIBERSORT and ssGSEA algorithms were used for analysis of TIME characteristics based on the CAFRI. The GSVA, GSEA, GO, KEGG and tumour mutation burden (TMB) analyses were used for mechanistic exploration. Additionally, the IMvigor210 cohort was conducted to validate the predictive value of CAFRI on the efficacy of ICIs. Finally, CAFRI-based antitumour drug sensitivity was analysed. The findings demonstrate that the CAFRI can served as an excellent predictor of prognosis for individuals with OV, as well as identifying patients with different TIME characteristics, differentiating between immune ‘hot’ and ‘cold’ tumour populations, and providing new insights into the selection of ICIs and personalised treatment regimens. CAFRI provides new perspectives for the development of novel prognostic and immunotherapy efficacy predictive biomarkers for OV.