Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

BACKGROUND

Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy.

METHODS

An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms.

RESULTS

We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments.

CONCLUSIONS

The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

Para-toluenesulfonamide, a novel potent carbonic anhydrase inhibitor, improves hypoxia-induced metastatic breast cancer cell viability and prevents resistance to αPD-1 therapy in triple-negative breast cancer

Overexpression of the hypoxia-induced transmembrane enzyme carbonic anhydrase IX (CA9) has been associated with poor prognosis and chemoresistance in aggressive breast cancer. This study aimed to investigate the involvement of CA9 in the anti-tumor activity of para-toluenesulfonamide (PTS) and elucidate its mechanism of action against breast cancer both in vitro and in vivo. MCF-7 and MDA-MB-231 breast cancer cells were treated with PTS or subjected to hypoxic conditions using cobalt chloride (CoCl2), with acetazolamide serving as a positive control. Additionally, 4T1 breast cancer cell allograft mice were co-treated with PTS and α-programmed cell death 1 (αPD-1) monoclonal antibody for one month. The results demonstrated that PTS effectively reduced cell viability and reversed migration ability in MCF-7 and MDA-MB-231 cells under CoCl2-induced hypoxia. Furthermore, PTS upregulated the expression of apoptosis-related proteins and downregulated CA9, hypoxia-inducible factor-1α (HIF-1α), and vascular endothelial growth factor (VEGF) proteins, possibly through modulation of p38 MAPK and ERK1/2 phosphorylated proteins. In the animal model, PTS100 inhibited tumor growth and lung metastasis in mammary tumor allograft mice, exhibiting synergistic effects when combined with αPD-1 therapy. Collectively, our findings suggest that PTS inhibits breast cancer growth and metastasis through the p38 MAPK/ERK1/2 pathway. Moreover, PTS may have the potential to prevent the development of resistance to αPD-1 therapy in breast cancer.

Selenium metabolism heterogeneity in pan-cancer: insights from bulk and single-cell RNA sequencing

BACKGROUND

Selenium, a natural microelement with both nutritional and toxicological properties, is intertwined with tumorigenesis and progression. However, it is not fully understood how selenium metabolism affects immune response and cancer biology.

METHODS

We estimated selenium metabolism by Gene Set Enrichment Analysis (GSEA) to delineate the selenium metabolism landscape using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and a integrated pan-cancer single-cell dataset. We systematically explored the prognostic implications of selenium metabolism and selenium-related regulatory patterns. The therapeutic value of selenium metabolism was explored through machine learning and examined in several immunotherapy cohorts. The heterogeneity and underlying mechanism of selenium metabolism were investigated by cell‒cell communication analysis at the single-cell level.

RESULTS

A GSEA analysis based on 86 genes was used to evaluate the selenium metabolism landscape. The selenium metabolism score exhibited prognostic value in predicting the lower risk of mortality, possibly due to its correlation with multiple cancer hallmarks, including a positive correlation with complement (R = 0.761, P < 0.001), inflammatory response (R = 0.663, P < 0.001), apoptosis (R = 0.626, P < 0.001), hypoxia (R = 0.587, P < 0.001), reactive oxygen species (ROS) (R = 0.558, P < 0.001), and interferon gamma response (R = 0.539, P < 0.001). We also observed heterogeneity in the relationship between selenium metabolism and immunity across different cancers. Based on selenium-related genes, we constructed a machine learning model with area under the ROC curve (AUC) of 0.82 in predicting immune checkpoint inhibitor (ICI)-based immunotherapy response. Single-cell selenium metabolism quantification revealed that adjacent and tumor tissues had higher selenium metabolism compared with normal tissues, especially in epithelial cells, fibroblasts and macrophages. The communication between high-selenium epithelium and high-selenium fibroblast was significantly higher than other cells, especially in cytokines, chemokines, collagen, Wnt, VEGF, IGF and FGF pathways.

CONCLUSION

Our study provides a comprehensive landscape of selenium metabolism levels and diverse regulatory patterns in different cancers, deepening the understanding of selenium's roles in tumorigenesis and immunity.

Unveiling the link between inflammasomes and skin cutaneous melanoma: Insights into expression patterns and immunotherapy response prediction

Skin cutaneous melanoma (SKCM) is one of the most malignant forms of skin cancer, characterized by its high metastatic potential and low cure rate in advanced stages. Despite advancements in clinical therapies, the overall cure rate for SKCM remains low due to its resistance to conventional treatments. Inflammation is associated with the activation and regulation of inflammatory responses and plays a crucial role in the immune system. It has been implicated in various physiological and pathological processes, including cancer. However, the mechanisms of inflammasome activation in SKCM remain largely unexplored. In this study, we quantified the expression level of six inflammasome-related gene sets using transcriptomic data from SKCM patients. As a result, we found that inflammasome features were closely associated with various clinical characteristics and served as a favorable prognostic factor for patients. A functional enrichment analysis revealed the oncogenic role of inflammasome features in SKCM. Unsupervised clustering was applied to identify immune clusters and inflammatory subtypes, revealing a significant overlap between immune cluster 4 and SKCM subtype 2. The CASP1, GSDMD, NLRP3, IL1B, and IL18 features could predict immune checkpoint blockade therapy response in various SKCM cohorts. In conclusion, our study highlighted the significant association between the inflammasome and cancer treatment. Understanding the role of inflammasome signaling in SKCM pathology can help identify potential therapeutic targets and improve patient prognosis.

Selective control of transposable element expression during T cell exhaustion and anti-PD-1 treatment

In chronic infections and cancer, T cells are exposed to prolonged antigen stimulation, resulting in loss of function (or exhaustion) and impairment of effective immunological protection. Exhausted T cells are heterogeneous and include early progenitors (Tpex) and terminally exhausted cells (Tex). Here, we used bulk and single-cell transcriptomics to analyze expression of transposable elements (TEs) in subpopulations of mouse and human CD8+ tumor-infiltrating T lymphocytes (TILs). We show that in mice, members of the virus-like murine VL30 TE family (mostly intact, evolutionary young ERV1s) are strongly repressed in terminally exhausted CD8+ T cells in both tumor and viral models of exhaustion. Tpex expression of these VL30s, which are mainly intergenic and transcribed independently of their closest gene neighbors, was driven by Fli1, a transcription factor involved in progression from Tpex to Tex. Immune checkpoint blockade (ICB) in both mice and patients with cancer increased TE expression (including VL30 in mice), demonstrating that TEs may be applicable as ICB response biomarkers. We conclude that expression of TEs is tightly regulated in TILs during establishment of exhaustion and reprogramming by ICB. Analyses of TE expression on single cells and bulk populations open opportunities for understanding immune cell identity and heterogeneity, as well as for defining cellular gene expression signatures and disease biomarkers.

Tumor-repopulating cell-derived microparticles elicit cascade amplification of chemotherapy-induced antitumor immunity to boost anti-PD-1 therapy

Immune checkpoint blockade (ICB) therapy, particularly antibodies targeting the programmed death receptor 1 (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment. However, its efficacy as a standalone therapy remains limited. Although ICB therapy in combination with chemotherapy shows promising therapeutic responses, the challenge lies in amplifying chemotherapy-induced antitumor immunity effectively. This relies on efficient drug delivery to tumor cells and robust antigen presentation by dendritic cells (DCs). Here, we developed tumor-repopulating cell (TRC)-derived microparticles with exceptional tumor targeting to deliver doxorubicin (DOX@3D-MPs) for improve anti-PD-1 therapy. DOX@3D-MPs effectively elicit immunogenic tumor cell death to release sufficient tumor antigens. Heat shock protein 70 (HSP70) overexpressed in DOX@3D-MPs contributes to capturing tumor antigens, promoting their phagocytosis by DCs, and facilitating DCs maturation, leading to the activation of CD8+ T cells. DOX@3D-MPs significantly enhance the curative response of anti-PD-1 treatment in large subcutaneous H22 hepatoma, orthotopic 4T1 breast tumor and Panc02 pancreatic tumor models. These results demonstrate that DOX@3D-MPs hold promise as agents to improve the response rate to ICB therapy and generate long-lasting immune memory to prevent tumor relapse.

An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma

Senescent tumor cells (STCs) can induce immunosuppression, promoting tumor progression and therapy resistance. However, the specific characteristics of immunosuppressive STC have not been thoroughly investigated. This study aimed to characterize and elucidate the immunosuppressive phenotype of STC in lung adenocarcinoma by employing single-cell and bulk transcriptomics, as well as serum proteomics profiling. We identified senescence-related genes specific to tumors and identified Cluster10 of STC as the immunomodulatory subtype. Cluster10 exhibited a distinct secretome dominated by cytokines such as CXCL1, CXCL2, and CXCL8 and showed activation of transcription factors associated with cytokine secretion, including NFKB1, RELA, and STAT3. Notably, Cluster10 demonstrated the highest degree of intercellular communication among all cell types, with interactions as LGALS9-TIM3 and MIF-CD74. Furthermore, Cluster10 showed significant associations with poor prognosis and diminished response to immunotherapy. Analysis of serum proteomics data from our in-house cohort identified CXCL8 as a potential marker for predicting immunotherapeutic outcomes.

Ablation of ERO1A induces lethal endoplasmic reticulum stress responses and immunogenic cell death to activate anti-tumor immunity

Immunophenotyping of the tumor microenvironment (TME) is essential for enhancing immunotherapy efficacy. However, strategies for characterizing the TME exhibit significant heterogeneity. Here, we show that endoplasmic reticular oxidoreductase-1α (ERO1A) mediates an immune-suppressive TME and attenuates the response to PD-1 blockade. Ablation of ERO1A in tumor cells substantially incites anti-tumor T cell immunity and promotes the efficacy of aPD-1 in therapeutic models. Single-cell RNA-sequencing analyses confirm that ERO1A correlates with immunosuppression and dysfunction of CD8+ T cells along anti-PD-1 treatment. In human lung cancer, high ERO1A expression is associated with a higher risk of recurrence following neoadjuvant immunotherapy. Mechanistically, ERO1A ablation impairs the balance between IRE1α and PERK signaling activities and induces lethal unfolded protein responses in tumor cells undergoing endoplasmic reticulum stress, thereby enhancing anti-tumor immunity via immunogenic cell death. These findings reveal how tumor ERO1A induces immunosuppression, highlighting its potential as a therapeutic target for cancer immunotherapy.

Pan-cancer spatially resolved single-cell analysis reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment

Cancer-associated fibroblasts (CAFs) are a heterogeneous cell population that plays a crucial role in remodeling the tumor microenvironment (TME). Here, through the integrated analysis of spatial and single-cell transcriptomics data across six common cancer types, we identified four distinct functional subgroups of CAFs and described their spatial distribution characteristics. Additionally, the analysis of single-cell RNA sequencing (scRNA-seq) data from three additional common cancer types and two newly generated scRNA-seq datasets of rare cancer types, namely epithelial-myoepithelial carcinoma (EMC) and mucoepidermoid carcinoma (MEC), expanded our understanding of CAF heterogeneity. Cell-cell interaction analysis conducted within the spatial context highlighted the pivotal roles of matrix CAFs (mCAFs) in tumor angiogenesis and inflammatory CAFs (iCAFs) in shaping the immunosuppressive microenvironment. In patients with breast cancer (BRCA) undergoing anti-PD-1 immunotherapy, iCAFs demonstrated heightened capacity in facilitating cancer cell proliferation, promoting epithelial-mesenchymal transition (EMT), and contributing to the establishment of an immunosuppressive microenvironment. Furthermore, a scoring system based on iCAFs showed a significant correlation with immune therapy response in melanoma patients. Lastly, we provided a web interface ( https://chenxisd.shinyapps.io/pancaf/ ) for the research community to investigate CAFs in the context of pan-cancer.

Radiotherapy remodels the tumor microenvironment for enhancing immunotherapeutic sensitivity

Cancer immunotherapy has transformed traditional treatments, with immune checkpoint blockade being particularly prominent. However, immunotherapy has minimal benefit for patients in most types of cancer and is largely ineffective in some cancers (such as pancreatic cancer and glioma). A synergistic anti-tumor response may be produced through the combined application with traditional tumor treatment methods. Radiotherapy (RT) not only kills tumor cells but also triggers the pro-inflammatory molecules' release and immune cell infiltration, which remodel the tumor microenvironment (TME). Therefore, the combination of RT and immunotherapy is expected to achieve improved efficacy. In this review, we summarize the effects of RT on cellular components of the TME, including T cell receptor repertoires, different T cell subsets, metabolism, tumor-associated macrophages and other myeloid cells (dendritic cells, myeloid-derived suppressor cells, neutrophils and eosinophils). Meanwhile, non-cellular components such as lactate and extracellular vesicles are also elaborated. In addition, we discuss the impact of different RT modalities on tumor immunity and issues related to the clinical practice of combination therapy.

Hormone Receptor Signaling and Breast Cancer Resistance to Anti-Tumor Immunity

Breast cancers regroup many heterogeneous diseases unevenly responding to currently available therapies. Approximately 70-80% of breast cancers express hormone (estrogen or progesterone) receptors. Patients with these hormone-dependent breast malignancies benefit from therapies targeting endocrine pathways. Nevertheless, metastatic disease remains a major challenge despite available treatments, and relapses frequently ensue. By improving patient survival and quality of life, cancer immunotherapies have sparked considerable enthusiasm and hope in the last decade but have led to only limited success in breast cancers. In addition, only patients with hormone-independent breast cancers seem to benefit from these immune-based approaches. The present review examines and discusses the current literature related to the role of hormone receptor signaling (specifically, an estrogen receptor) and the impact of its modulation on the sensitivity of breast cancer cells to the effector mechanisms of anti-tumor immune responses and on the capability of breast cancers to escape from protective anti-cancer immunity. Future research prospects related to the possibility of promoting the efficacy of immune-based interventions using hormone therapy agents are considered.

Lag-3 expression and clinical outcomes in metastatic melanoma patients treated with combination anti-lag-3 + anti-PD-1-based immunotherapies

Lymphocyte-activation gene-3 (LAG-3), an immune checkpoint receptor, negatively regulates T-cell function and facilitates immune escape of tumors. Dual inhibition of LAG-3 and programmed cell death receptor-1 (PD-1) significantly improved progression-free survival (PFS) in metastatic melanoma patients compared to anti-PD-1 therapy alone. Investigating the utility of LAG-3 expression as a biomarker of response to anti-LAG-3 + anti-PD-1 immunotherapy is of great clinical relevance. This study sought to evaluate the association between baseline LAG-3 expression and clinical outcomes following anti-LAG-3 and anti-PD-1-based immunotherapy in metastatic melanoma. LAG-3 immunohistochemistry (clone D2G4O) was performed on pre-treatment formalin-fixed, paraffin-embedded metastatic melanoma specimens from 53 patients treated with combination anti-LAG-3 + anti-PD-1-based therapies. Eleven patients had received prior anti-PD-1-based treatment. Patients were categorized as responders (complete/partial response; n = 36) or non-responders (stable/progressive disease; n = 17) based on the Response Evaluation Criteria in Solid Tumours (RECIST). Tumor-infiltrating lymphocytes (TILs) were scored on hematoxylin and eosin-stained sections. LAG-3 expression was observed in 81% of patients, with staining in TILs and dendritic cells. Responders displayed significantly higher proportions of LAG-3+ cells compared to non-responders (P = .0210). LAG-3 expression positively correlated with TIL score (P < .01). There were no significant differences in LAG-3 expression between different sites of metastases (P > .05). Patients with ≥ 1% LAG-3+ cells in their tumors had significantly longer PFS compared to patients with < 1% LAG-3 expression (P = .0037). No significant difference was observed in overall survival between the two groups (P = .1417). Therefore, the assessment of LAG-3 expression via IHC warrants further evaluation to determine its role as a predictive marker of response and survival in metastatic melanoma.

Pan-cancer analysis of NFE2L2 mutations identifies a subset of lung cancers with distinct genomic and improved immunotherapy outcomes

BACKGROUND

Mutations in the KEAP1-NFE2L2 signaling pathway were linked to increased tumorigenesis and aggressiveness. Interestingly, not all hotspot mutations on NFE2L2 were damaging; some even were activating. However, there was conflicting evidence about the association between NFE2L2 mutation and Nrf2-activating mutation and responsiveness to immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and other multiple cancers.

METHODS

The study with the largest sample size (n = 49,533) explored the landscape of NFE2L2 mutations and their impact response/resistance to ICIs using public cohorts. In addition, the in-house WXPH cohort was used to validate the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC.

RESULTS

In two pan-cancer cohorts, Nrf2-activating mutation was associated with higher TMB value compared to wild-type. We identified a significant association between Nrf2-activating mutation and shorter overall survival in pan-cancer patients and NSCLC patients but not in those undergoing ICIs treatment. Similar findings were obtained in cancer patients carrying the NFE2L2 mutation. Furthermore, in NSCLC and other cancer cohorts, patients with NFE2L2 mutation demonstrated more objective responses to ICIs than patients with wild type. Our in-house WXPH cohort further confirmed the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. Lastly, decreased inflammatory signaling pathways and immune-depleted immunological microenvironments were enriched in Nrf2-activating mutation patients with NSCLC.

CONCLUSIONS

Our study found that patients with Nrf2-activating mutation had improved immunotherapy outcomes than patients with wild type in NSCLC and other tumor cohorts, implying that Nrf2-activating mutation defined a distinct subset of pan-cancers and might have implications as a biomarker for guiding ICI treatment, especially NSCLC.

Selective Mitochondrial Respiratory Complex I Subunit Deficiency Causes Tumor Immunogenicity

Targeting of specific metabolic pathways in tumor cells has the potential to sensitize them to immune-mediated attack. Here we provide evidence for a specific means of mitochondrial respiratory Complex I (CI) inhibition that improves tumor immunogenicity and sensitivity to immune checkpoint blockade (ICB). Targeted genetic deletion of the CI subunits Ndufs4 and Ndufs6 , but not other subunits, induces an immune-dependent tumor growth attenuation in mouse melanoma models. We show that deletion of Ndufs4 induces expression of the transcription factor Nlrc5 and genes in the MHC class I antigen presentation and processing pathway. This induction of MHC-related genes is driven by an accumulation of pyruvate dehydrogenase-dependent mitochondrial acetyl-CoA downstream of CI subunit deletion. This work provides a novel functional modality by which selective CI inhibition restricts tumor growth, suggesting that specific targeting of Ndufs4 , or related CI subunits, increases T-cell mediated immunity and sensitivity to ICB.

GBP2 is a prognostic biomarker and associated with immunotherapeutic responses in gastric cancer

BACKGROUND

The interferon-induced protein known as guanylate-binding protein 2 (GBP2) has been linked to multiple different cancer types as an oncogenic gene. Although the role of GBP2 in cancer has been preliminarily explored, it is unclear how this protein interacts with tumor immunity in gastric cancer.

METHODS

The expression, prognostic value, immune-correlations of GBP2 in gastric cancer was explored in multiple public and in-house cohorts. In addition, the pan-cancer analysis was performed to investigate the immunological role of GBP2 based on The Cancer Genome Atlas (TCGA) dataset, and the predictive value of GBP2 for immunotherapy was also examined in multiple public cohorts.

RESULTS

GBP2 was highly expressed in tumor tissues and associated with poor prognosis in gastric cancer. In addition, GBP2 was associated with the immune-hot phenotype. To be more specific, GBP2 was positively related to immuno-modulators, tumor-infiltrating immune cells (TIICs), immunotherapy biomarkers, and even well immunotherapeutic response. In addition to gastric cancer, GBP2 was expected to be an indicator of high immunogenicity in most cancer types. Importantly, GBP2 could predict the immunotherapeutic responses in at least four different cancer types, including melanoma, urothelial carcinoma, non-small cell lung cancer, and breast cancer.

CONCLUSIONS

To sum up, GBP2 expression is a promising pan-cancer biomarker for estimating the immunological characteristics of tumors and may be utilized to detect immuno-hot tumors in gastric cancer.

Synthetic viability induces resistance to immune checkpoint inhibitors in cancer cells

BACKGROUND

Immune checkpoint inhibitors (ICI) have revolutionized the treatment for multiple cancers. However, most of patients encounter resistance. Synthetic viability (SV) between genes could induce resistance. In this study, we established SV signature to predict the efficacy of ICI treatment for melanoma.

METHODS

We collected features and predicted SV gene pairs by random forest classifier. This work prioritized SV gene pairs based on CRISPR/Cas9 screens. SV gene pairs signature were constructed to predict the response to ICI for melanoma patients.

RESULTS

This study predicted robust SV gene pairs based on 14 features. Filtered by CRISPR/Cas9 screens, we identified 1,861 SV gene pairs, which were also related with prognosis across multiple cancer types. Next, we constructed the six SV pairs signature to predict resistance to ICI for melanoma patients. This study applied the six SV pairs signature to divide melanoma patients into high-risk and low-risk. High-risk melanoma patients were associated with worse response after ICI treatment. Immune landscape analysis revealed that high-risk melanoma patients had lower natural killer cells and CD8+ T cells infiltration.

CONCLUSIONS

In summary, the 14 features classifier accurately predicted robust SV gene pairs for cancer. The six SV pairs signature could predict resistance to ICI.

Detailed characterization of PD-1/PD-L1 and CTLA4 expression and tumor-infiltrating lymphocytes in yolk sac tumors

BACKGROUND

Immune checkpoint blockade (ICB) is considered as a promising approach for cancer treatment. However, the potency of ICB therapy in yolk sac tumors (YSTs) has not been confirmed, and the comprehensive analysis of tumor immune microenvironment and the expression of PD-1/PD-L1 and CTLA4 were also not thoroughly evaluated.

METHODS

Immunohistochemistry was performed in formalin-fixed, paraffin-embedded tumor specimens from 23 YSTs patients to detect the density and distribution of tumor-infiltrating T cells, tertiary lymphoid structures (TLSs), as well as the expression of PD-1/PD-L1 and CTLA4.

RESULTS

Overall, more than half (61 %) of all patients exhibited an immune-desert phenotype based on CD3+ T cells. PD-1 expression was identified in five tumor samples (21.7 %), and PD-L1 expression exhibited a different positive rate in tumor cells (TCs) and tumor-infiltrating lymphocytes (TILs) (39.1 % and 17.4 %). Noteworthily, the rate of positive CTLA4 expression in both TCs and TILs was markedly higher (69.6 % and 56.5 %) than those of PD-1 and PD-L1 expression. Furthermore, TLSs were observed in 21.74 % of all tissues, and samples with TLSs exhibited significantly higher densities of TILs and higher expression of immune checkpoint molecules, particularly PD-1/PD-L1. In addition, tumors located in testes also exhibited a higher density of TILs and higher expression of immune checkpoint molecules.

CONCLUSION

Generally a high frequency of CTLA4 expression was found, PD-1/PD-L1 expression, the immune-inflamed phenotype, and TLSs were low frequency in YSTs, however, YSTs in testes showed a higher density of TILs and higher expression of immune checkpoint molecules.

Classification of the tumor immune microenvironment and associations with outcomes in patients with metastatic melanoma treated with immunotherapies

BACKGROUND

Tumor microenvironment (TME) characteristics are potential biomarkers of response to immune checkpoint inhibitors in metastatic melanoma. This study developed a method to perform unsupervised classification of TME of metastatic melanoma.

METHODS

We used multiplex immunohistochemical and quantitative pathology-derived assessment of immune cell compositions of intratumoral and peritumoral regions of metastatic melanoma baseline biopsies to classify TME in relation to response to anti-programmed cell death protein 1 (PD-1) monotherapy or in combination with anti-cytotoxic T-cell lymphocyte-4 (ipilimumab (IPI)+PD-1).

RESULTS

Spatial profiling of CD8+T cells, macrophages, and melanoma cells, as well as phenotypic PD-1 receptor ligand (PD-L1) and CD16 proportions, were used to identify and classify patients into one of three mutually exclusive TME classes: immune-scarce, immune-intermediate, and immune-rich tumors. Patients with immune-rich tumors were characterized by a lower proportion of melanoma cells and higher proportions of immune cells, including higher PD-L1 expression. These patients had higher response rates and longer progression-free survival (PFS) than those with immune-intermediate and immune-scarce tumors. At a median follow-up of 18 months (95% CI: 6.7 to 49 months), the 1-year PFS was 76% (95% CI: 64% to 90%) for patients with an immune-rich tumor, 56% (95% CI: 44% to 72%) for those with an immune-intermediate tumor, and 33% (95% CI: 23% to 47%) for patients with an immune-scarce tumor. A higher response rate was observed in patients with an immune-scarce or immune-intermediate tumor when treated with IPI+PD-1 compared with those treated with PD-1 alone.

CONCLUSIONS

Our study provides an automatic TME classification method that may predict the clinical efficacy of immunotherapy for patients with metastatic melanoma.

The role of IFN-γ-signalling in response to immune checkpoint blockade therapy

Treatment with immune checkpoint inhibitors, widely known as immune checkpoint blockade therapy (ICBT), is now the fourth pillar in cancer treatment, offering the chance of durable remission for patients with advanced disease. However, ICBT fails to induce objective responses in most cancer patients with still others progressing after an initial response. It is necessary, therefore, to elucidate the primary and acquired resistance mechanisms to ICBT to improve its efficacy. Here, we highlight the paradoxical role of the cytokine interferon-γ (IFN-γ) in ICBT response: on the one hand induction of IFN-γ signalling in the tumour microenvironment correlates with good ICBT response as it drives the cellular immune responses required for tumour destruction; nonetheless, IFN-γ signalling is implicated in ICBT acquired resistance. We address the negative feedback and immunoregulatory effects of IFN-γ signalling that promote immune evasion and resistance to ICBT and discuss how these can be targeted pharmacologically to restore sensitivity or circumvent resistance.

Identifying immune checkpoint-related lncRNA biomarkers for immunotherapy response and prognosis in cancers

Long non-coding RNAs (lncRNAs) could modulate expression of immune checkpoints (ICPs) in tumor-immune. However, precise functions in immunity and potential for predicting ICP inhibitors (ICI) response have been described for only a few lncRNAs. Here, a multiple-step pipeline was developed to identify cancer- and immune-context ICP and lncRNA cooperative regulation pairs (ICPaLncCRPs) across cancers. Immune-related ICPs and lncRNAs were extracted follow immune cell lines and immunologic constant of rejection groups. ICPaLncCRP networks were constructed, which likely to modulate tumor-immune by specific patterns. Common and specific hub ICPaLncs such as MIR155HG, TRG-AS1 and PCED1B-AS1 maybe play central roles in prognosis and circulating. Moreover, these hub ICPaLncs were significantly correlated with immune cell infiltration based on bulk and single-cell RNA sequencing data. Some ICPaLncCRPs such as IDO1-MIR155HG could predict three- and five-year prognosis of melanoma in two independent datasets. We also validated that some ICPaLncCRPs could effectively predict ICI-response follow six independent datasets. Collectively, this study will enhance our understanding of lncRNA functions and accelerate discovery of lncRNA-based biomarkers in ICI treatment.

Comparison of different predictive biomarker testing assays for PD-1/PD-L1 checkpoint inhibitors response: a systematic review and network meta-analysis

Background

Accurate prediction of efficacy of programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) checkpoint inhibitors is of critical importance. To address this issue, a network meta-analysis (NMA) comparing existing common measurements for curative effect of PD-1/PD-L1 monotherapy was conducted.

Methods

We searched PubMed, Embase, the Cochrane Library database, and relevant clinical trials to find out studies published before Feb 22, 2023 that use PD-L1 immunohistochemistry (IHC), tumor mutational burden (TMB), gene expression profiling (GEP), microsatellite instability (MSI), multiplex IHC/immunofluorescence (mIHC/IF), other immunohistochemistry and hematoxylin-eosin staining (other IHC&HE) and combined assays to determine objective response rates to anti-PD-1/PD-L1 monotherapy. Study-level data were extracted from the published studies. The primary goal of this study was to evaluate the predictive efficacy and rank these assays mainly by NMA, and the second objective was to compare them in subgroup analyses. Heterogeneity, quality assessment, and result validation were also conducted by meta-analysis.

Findings

144 diagnostic index tests in 49 studies covering 5322 patients were eligible for inclusion. mIHC/IF exhibited highest sensitivity (0.76, 95% CI: 0.57-0.89), the second diagnostic odds ratio (DOR) (5.09, 95% CI: 1.35-13.90), and the second superiority index (2.86). MSI had highest specificity (0.90, 95% CI: 0.85-0.94), and DOR (6.79, 95% CI: 3.48-11.91), especially in gastrointestinal tumors. Subgroup analyses by tumor types found that mIHC/IF, and other IHC&HE demonstrated high predictive efficacy for non-small cell lung cancer (NSCLC), while PD-L1 IHC and MSI were highly efficacious in predicting the effectiveness in gastrointestinal tumors. When PD-L1 IHC was combined with TMB, the sensitivity (0.89, 95% CI: 0.82-0.94) was noticeably improved revealed by meta-analysis in all studies.

Interpretation

Considering statistical results of NMA and clinical applicability, mIHC/IF appeared to have superior performance in predicting response to anti PD-1/PD-L1 therapy. Combined assays could further improve the predictive efficacy. Prospective clinical trials involving a wider range of tumor types are needed to establish a definitive gold standard in future.

Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade

Immune checkpoint blockade (ICB) is a promising cancer therapy; however, resistance often develops. To learn more about ICB resistance mechanisms, we developed IRIS (Immunotherapy Resistance cell-cell Interaction Scanner), a machine learning model aimed at identifying candidate ligand-receptor interactions (LRI) that are likely to mediate ICB resistance in the tumor microenvironment (TME). We developed and applied IRIS to identify resistance-mediating cell-type-specific ligand-receptor interactions by analyzing deconvolved transcriptomics data of the five largest melanoma ICB therapy cohorts. This analysis identifies a set of specific ligand-receptor pairs that are deactivated as tumors develop resistance, which we refer to as resistance deactivated interactions (RDI). Quite strikingly, the activity of these RDIs in pre-treatment samples offers a markedly stronger predictive signal for ICB therapy response compared to those that are activated as tumors develop resistance. Their predictive accuracy surpasses the state-of-the-art published transcriptomics biomarker signatures across an array of melanoma ICB datasets. Many of these RDIs are involved in chemokine signaling. Indeed, we further validate on an independent large melanoma patient cohort that their activity is associated with CD8+ T cell infiltration and enriched in hot/brisk tumors. Taken together, this study presents a new strongly predictive ICB response biomarker signature, showing that following ICB treatment resistant tumors turn inhibit lymphocyte infiltration by deactivating specific key ligand-receptor interactions.

Targeting nucleic acid sensors in tumor cells to reprogram biogenesis and RNA cargo of extracellular vesicles for T cell-mediated cancer immunotherapy

Tumor-derived extracellular vesicles (EVs) have been associated with immune evasion and tumor progression. We show that the RNA-sensing receptor RIG-I within tumor cells governs biogenesis and immunomodulatory function of EVs. Cancer-intrinsic RIG-I activation releases EVs, which mediate dendritic cell maturation and T cell antitumor immunity, synergizing with immune checkpoint blockade. Intact RIG-I, autocrine interferon signaling, and the GTPase Rab27a in tumor cells are required for biogenesis of immunostimulatory EVs. Active intrinsic RIG-I signaling governs composition of the tumor EV RNA cargo including small non-coding stimulatory RNAs. High transcriptional activity of EV pathway genes and RIG-I in melanoma samples associate with prolonged patient survival and beneficial response to immunotherapy. EVs generated from human melanoma after RIG-I stimulation induce potent antigen-specific T cell responses. We thus define a molecular pathway that can be targeted in tumors to favorably alter EV immunomodulatory function. We propose "reprogramming" of tumor EVs as a personalized strategy for T cell-mediated cancer immunotherapy.

Construction of PANoptosis signature: Novel target discovery for prostate cancer immunotherapy

PANoptosis pathway gene sets encompassing pyroptosis, apoptosis, and necroptosis were identified from the MSigDB database. We analyzed the perturbations and crosstalk in the PANoptosis pathway in prostate adenocarcinoma (PRAD), including gene mutation, transcription, methylation, and clinical features. By constructing a PANoptosis signature, we accurately predicted the prognosis and immunotherapeutic response of PRAD patients. We further explored the molecular features and immunological roles of the signature, dividing patients into high- and low-score groups. Notably, the high-score group correlated with better survival outcomes and immunotherapeutic responses, as well as a higher mutation frequency and enrichment score in the PANoptosis and HALLMARK pathways. The PANoptosis signature also enhanced overall antitumor immunity, promoted immune cell infiltration, upregulated immune checkpoint regulators, and revealed the cold tumor characteristics of PRAD. We also identified potential drug targets based on the PANoptosis signature. These findings lead the way in identifying novel prognostic markers and therapeutic targets for patients with PRAD.

Tumor aerobic glycolysis confers immune evasion through modulating sensitivity to T cell-mediated bystander killing via TNF-α

Metabolic reprogramming toward glycolysis is a hallmark of cancer malignancy. The molecular mechanisms by which the tumor glycolysis pathway promotes immune evasion remain to be elucidated. Here, by performing genome-wide CRISPR screens in murine tumor cells co-cultured with cytotoxic T cells (CTLs), we identified that deficiency of two important glycolysis enzymes, Glut1 (glucose transporter 1) and Gpi1 (glucose-6-phosphate isomerase 1), resulted in enhanced killing of tumor cells by CTLs. Mechanistically, Glut1 inactivation causes metabolic rewiring toward oxidative phosphorylation, which generates an excessive amount of reactive oxygen species (ROS). Accumulated ROS potentiate tumor cell death mediated by tumor necrosis factor alpha (TNF-α) in a caspase-8- and Fadd-dependent manner. Genetic and pharmacological inactivation of Glut1 sensitizes tumors to anti-tumor immunity and synergizes with anti-PD-1 therapy through the TNF-α pathway. The mechanistic interplay between tumor-intrinsic glycolysis and TNF-α-induced killing provides new therapeutic strategies to enhance anti-tumor immunity.

Multi-omics Characterization of Response to PD-1 Inhibitors in Advanced Melanoma

Immunotherapy improves the survival of patients with advanced melanoma, 40% of whom become long-term responders. However, not all patients respond to immunotherapy. Further knowledge of the processes involved in the response and resistance to immunotherapy is still needed. In this study, clinical paraffin samples from fifty-two advanced melanoma patients treated with anti-PD-1 inhibitors were assessed via high-throughput proteomics and RNA-seq. The obtained proteomics and transcriptomics data were analyzed using multi-omics network analyses based on probabilistic graphical models to identify those biological processes involved in the response to immunotherapy. Additionally, proteins related to overall survival were studied. The activity of the node formed by the proteins involved in protein processing in the endoplasmic reticulum and antigen presentation machinery was higher in responders compared to non-responders; the activity of the immune and inflammatory response node was also higher in those with complete or partial responses. A predictor for overall survival based on two proteins (AMBP and PDSM5) was defined. In summary, the response to anti-PD-1 therapy in advanced melanoma is related to protein processing in the endoplasmic reticulum, and also to genes involved in the immune and inflammatory responses. Finally, a two-protein predictor can define survival in advanced disease. The molecular characterization of the mechanisms involved in the response and resistance to immunotherapy in melanoma leads the way to establishing therapeutic alternatives for patients who will not respond to this treatment.

IL-2Rα-biased agonist enhances antitumor immunity by invigorating tumor-infiltrating CD25+CD8+ T cells

To avoid regulatory T cell promotion and vascular toxicity, the interleukin-2 receptor-β/interleukin-2 receptor-γ (IL-2Rβγ)-biased approach is used by most IL-2 analogs in immuno-oncology. However, recent clinical disappointments in these IL-2 agonists have questioned this strategy. Here we show that both wild-type (IL-2wt) and IL-2Rβγ-attenuated (IL-2α-bias) agonists that preserve IL-2Rα (CD25) activities can effectively expand tumor-specific CD8+ T cells (TSTs) and exhibit better antitumor efficacy and safety than the 'non-α' counterpart (IL-2nα). Mechanistically, TSTs coexpress elevated CD25 and PD-1 and are more susceptible to stimulation by IL-2Rα-proficient agonists. Moreover, the antitumor efficacy of anti-PD-1 depends on activation of PD-1+CD25+ TSTs through autocrine IL-2-CD25 signaling. In individuals with cancer, a low IL-2 signature correlates with non-responsiveness to anti-PD-1 treatment. In mouse models, IL-2α-bias, but not IL-2nα, restores the IL-2 signature and synergizes with anti-PD-1 to eradicate large established tumors. These findings underscore the indispensable function of CD25 in IL-2-based immunotherapy and provide rationales for evaluating IL-2Rα-biased agonists in individuals with cancer.

Chromatin accessibility dynamics in colorectal cancer liver metastasis: Uncovering the liver tropism at single cell resolution

Tumor metastasis causes over 90% of cancer related death and no currently available therapies target it. However, there is limited understanding regarding the epigenetic regulation of genes during this complex process. Here by integrating single-cell ATAC-seq (scATAC-seq), single-cell RNA-seq (scRNA-seq), microarray, bulk RNA-seq, immunohistochemistry (IHC) staining, as well as proteomics datasets from paired primary and liver metastatic colorectal cancer (CRC) patient-derived xenograft (PDX) model and patients, we discovered that liver metastatic CRC cells lose their colon-specific chromatin accessible sites yet gain liver-specific ones. Importantly, we observed elevated accessibility of HNF4A, a liver-specific transcription factor, in liver metastatic CRC cells. Subsequently, we performed clustering analysis of liver metastatic CRC cells together with cells involved in liver development, revealing significant heterogeneity among the liver metastatic CRC cells. Over 50% of the liver metastatic CRC cells exhibited characteristics similar to those of erythroid progenitors and hepatocytes, showing increased expression of genes involved in oxidative phosphorylation and glycolysis. Moreover, our discovery further revealed that the MHC and IFN response genes in these cells exhibit moderate epigenetic activity, which is significantly associated with the low objective response rates in checkpoint blockade immunotherapy. Our findings uncovered the critical roles of HNF4A and the cell populations within liver metastatic CRC cells might serve as crucial therapeutic targets for addressing liver metastasis and improving the immunotherapy response in patients with CRC.

Interleukin 17 signaling supports clinical benefit of dual CTLA-4 and PD-1 checkpoint inhibition in melanoma

Recent studies suggest that BRAFV600-mutated melanomas in particular respond to dual anti-programmed cell death protein 1 (PD-1) and anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) immune checkpoint inhibition (ICI). Here we identified an over-representation of interleukin (IL)-17-type 17 helper T (TH17) gene expression signatures (GES) in BRAFV600-mutated tumors. Moreover, high baseline IL-17 GES consistently predicted clinical responses in dual-ICI-treated patient cohorts but not in mono anti-CTLA-4 or anti-PD-1 ICI cohorts. High IL-17 GES corresponded to tumor infiltration with T cells and neutrophils. Accordingly, high neutrophil infiltration correlated with clinical response specifically to dual ICI, and tumor-associated neutrophils also showed strong IL-17-TH17 pathway activity and T cell activation capacity. Both the blockade of IL-17A and the depletion of neutrophils impaired dual-ICI response and decreased T cell activation. Finally, high IL-17A levels in the blood of patients with melanoma indicated a higher global TH17 cytokine profile preceding clinical response to dual ICI but not to anti-PD-1 monotherapy, suggesting a future role as a biomarker for patient stratification.

Photodynamic therapy improves the outcome of immune checkpoint inhibitors via remodelling anti-tumour immunity in patients with gastric cancer

BACKGROUND

Photodynamic therapy (PDT) plays an immunoregulatory role in tumours. Here, we conducted a retrospective patient analysis to evaluate the effectiveness of PDT plus immune checkpoint inhibitors (ICIs) in gastric cancer. Further, we performed a dynamic analysis of gastric cancer patients receiving PDT to clarify its effects on anti-tumour immunity.

METHODS

Forty ICI-treated patients that received PDT or not were retrospectively analysed. Five patients with gastric adenocarcinoma were enrolled for sample collection before and after PDT. Single-cell RNA/T cell receptor (TCR) sequencing, flow cytometry and histological exanimation were used to analyse the collected specimens.

RESULTS

Patients in PDT group had a significantly better OS after ICI treatment than those in No PDT group. Single-cell analysis identified ten cell types in gastric cancer tissues and four sub-populations of T cells. Immune cell infiltration increased in the tumours after PDT and the circular immune cells showed consistent alterations. TCR analysis revealed a specific clonal expansion after PDT in cytotoxic T lymphocytes (CTL), but a constriction in Tregs. The B2M gene is upregulated in tumour cells after PDT and is associated with immune cell infiltration. Several pathways involving the positive regulation of immunity were enriched in tumour cells in the post-PDT group. The interactions following PDT were increased between tumour cells and effector cells but decreased between Tregs and other immune cells. Some co-stimulatory signaling emerged, whereas co-inhibitory signaling disappeared in intercellular communication after PDT.

CONCLUSIONS

PDT elicits an anti-tumour response through various mechanisms and is promising as an adjuvant to enhance ICI benefit.

Predictive biomarkers of immunotherapy response with pharmacological applications in solid tumors

Immune-checkpoint inhibitors show promising effects in the treatment of multiple tumor types. Biomarkers are biological indicators used to select patients for a systemic anticancer treatment, but there are only a few clinically useful biomarkers such as PD-L1 expression and tumor mutational burden, which can be used to predict immunotherapy response. In this study, we established a database consisting of both gene expression and clinical data to identify biomarkers of response to anti-PD-1, anti-PD-L1, and anti-CTLA-4 immunotherapies. A GEO screening was executed to identify datasets with simultaneously available clinical response and transcriptomic data regardless of cancer type. The screening was restricted to the studies involving administration of anti-PD-1 (nivolumab, pembrolizumab), anti-PD-L1 (atezolizumab, durvalumab) or anti-CTLA-4 (ipilimumab) agents. Receiver operating characteristic (ROC) analysis and Mann-Whitney test were executed across all genes to identify features related to therapy response. The database consisted of 1434 tumor tissue samples from 19 datasets with esophageal, gastric, head and neck, lung, and urothelial cancers, plus melanoma. The strongest druggable gene candidates linked to anti-PD-1 resistance were SPIN1 (AUC = 0.682, P = 9.1E-12), SRC (AUC = 0.667, P = 5.9E-10), SETD7 (AUC = 0.663, P = 1.0E-09), FGFR3 (AUC = 0.657, P = 3.7E-09), YAP1 (AUC = 0.655, P = 6.0E-09), TEAD3 (AUC = 0.649, P = 4.1E-08) and BCL2 (AUC = 0.634, P = 9.7E-08). In the anti-CTLA-4 treatment cohort, BLCAP (AUC = 0.735, P = 2.1E-06) was the most promising gene candidate. No therapeutically relevant target was found to be predictive in the anti-PD-L1 cohort. In the anti-PD-1 group, we were able to confirm the significant correlation with survival for the mismatch-repair genes MLH1 and MSH6. A web platform for further analysis and validation of new biomarker candidates was set up and available at https://www.rocplot.com/immune . In summary, a database and a web platform were established to investigate biomarkers of immunotherapy response in a large cohort of solid tumor samples. Our results could help to identify new patient cohorts eligible for immunotherapy.

A tumor-associated endothelial signature score model in immunotherapy and prognosis across pan-cancers

Background: The tumor-associated endothelial cell (TAE) component plays a vital role in tumor immunity. However, systematic tumor-associated endothelial-related gene assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers have not been explored. Herein, we investigated a TAE gene risk model to predict CIT responses and patient survival in a pan-cancer analysis. Methods: We analyzed publicly available datasets of tumor samples with gene expression and clinical information, including gastric cancer, metastatic urothelial cancer, metastatic melanoma, non-small cell lung cancer, primary bladder cancer, and renal cell carcinoma. We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm. Results: The model demonstrated a high predictive accuracy in both training and validation cohorts. The response rate of the high score group to immunotherapy in the training cohort was significantly higher than that of the low score group, with CIT response rates of 51% and 27%, respectively. The survival analysis showed that the prognosis of the high score group was significantly better than that of the low score group (all p < 0·001). Tumor-associated endothelial gene signature scores positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may benefit patients in the high score group. The analysis of TAE scores across 33 human cancers revealed that the TAE model could reflect immune cell infiltration and predict the survival of cancer patients. Conclusion: The TAE signature model could represent a CIT response prediction model with a prognostic value in multiple cancer types.

HYDIN mutation status as a potential predictor of immune checkpoint inhibitor efficacy in melanoma

BACKGROUND

The advent of immune checkpoint inhibitors (ICIs) has altered the outlook for cancer treatment. The estimation of predictive biomarkers could contribute to maximizing the benefits from ICIs treatment. Here, we explored the association between HYDIN mutations (HYDIN-MUT) in melanoma and ICIs efficacy.

METHODS

Clinical data and sequencing data from published studies were utilized to assess the association between HYDIN-MUT and the efficacy of ICIs treatment in melanoma patients.

RESULTS

Compared to other tumor types, HYDIN (36.14%) has the highest mutation rate in melanoma patients. In the anti-PD-1 treated cohort (n = 254), the HYDIN-MUT patients had a longer OS after ICIs treatment than the HYDIN wild-type (HYDIN-WT) patients (HR = 0.590 [95% CI, 0.410-0.847], P = 0.004); the objective response rate (ORR) and durable clinical benefit (DCB) were increased in patients with HYDIN-MUT (ORR = 46.25, DCB = 56.00%) compared to patients with HYDIN-WT (ORR = 30.99%, DCB = 42.76%) (ORR: P = 0.019; DCB: P = 0.060). In the anti-CTLA4 treated cohort (n = 174), HYDIN-MUT patients achieved significantly longer OS than HYDIN-WT patients (HR = 0.549 [95% CI, 0.366-0.823], P = 0.003); the proportion of ORR and DCB in HYDIN-MUT patients was significantly higher than that in HYDIN-WT patients (ORR 40.54% vs. 14.42%, P = 0.031; DCB 45.76% vs. 22.22%, P = 0.002). Further gene set enrichment analysis demonstrated that DNA repair and anti-tumor immunity were significantly enhanced in HYDIN-MUT patients.

CONCLUSIONS

HYDIN mutations are a potential predictive biomarker of ICIs efficacy in melanoma patients.

A Comprehensive Benchmark of Transcriptomic Biomarkers for Immune Checkpoint Blockades

Immune checkpoint blockades (ICBs) have revolutionized cancer therapy by inducing durable clinical responses, but only a small percentage of patients can benefit from ICB treatments. Many studies have established various biomarkers to predict ICB responses. However, different biomarkers were found with diverse performances in practice, and a timely and unbiased assessment has yet to be conducted due to the complexity of ICB-related studies and trials. In this study, we manually curated 29 published datasets with matched transcriptome and clinical data from more than 1400 patients, and uniformly preprocessed these datasets for further analyses. In addition, we collected 39 sets of transcriptomic biomarkers, and based on the nature of the corresponding computational methods, we categorized them into the gene-set-like group (with the self-contained design and the competitive design, respectively) and the deconvolution-like group. Next, we investigated the correlations and patterns of these biomarkers and utilized a standardized workflow to systematically evaluate their performance in predicting ICB responses and survival statuses across different datasets, cancer types, antibodies, biopsy times, and combinatory treatments. In our benchmark, most biomarkers showed poor performance in terms of stability and robustness across different datasets. Two scores (TIDE and CYT) had a competitive performance for ICB response prediction, and two others (PASS-ON and EIGS_ssGSEA) showed the best association with clinical outcome. Finally, we developed ICB-Portal to host the datasets, biomarkers, and benchmark results and to implement the computational methods for researchers to test their custom biomarkers. Our work provided valuable resources and a one-stop solution to facilitate ICB-related research.

Intermittent dietary methionine deprivation facilitates tumoral ferroptosis and synergizes with checkpoint blockade

Dietary methionine interventions are beneficial to apoptosis-inducing chemotherapy and radiotherapy for cancer, while their effects on ferroptosis-targeting therapy and immunotherapy are unknown. Here we show the length of time methionine deprivation affects tumoral ferroptosis differently. Prolonged methionine deprivation prevents glutathione (GSH) depletion from exceeding the death threshold by blocking cation transport regulator homolog 1 (CHAC1) protein synthesis. Whereas, short-term methionine starvation accelerates ferroptosis by stimulating CHAC1 transcription. In vivo, dietary methionine with intermittent but not sustained deprivation augments tumoral ferroptosis. Intermittent methionine deprivation also sensitizes tumor cells against CD8+ T cell-mediated cytotoxicity and synergize checkpoint blockade therapy by CHAC1 upregulation. Clinically, tumor CHAC1 correlates with clinical benefits and improved survival in cancer patients treated with checkpoint blockades. Lastly, the triple combination of methionine intermittent deprivation, system xc- inhibitor and PD-1 blockade shows superior antitumor efficacy. Thus, intermittent methionine deprivation is a promising regimen to target ferroptosis and augment cancer immunotherapy.

Subsets of IFN Signaling Predict Response to Immune Checkpoint Blockade in Patients with Melanoma

PURPOSE

IFN signaling in the tumor microenvironment is a critical determinant of both response and resistance of cancer to immune checkpoint inhibitors (ICI). We hypothesized that distinct patterns of IFN signaling in melanoma are associated with clinical response or resistance to ICIs.

EXPERIMENTAL DESIGN

Two tissue microarrays containing samples from 97 patients with metastatic melanoma who received nivolumab, pembrolizumab, or a combination of ipilimumab and nivolumab at Yale New Haven Hospital between 2011 and 2017 were randomized into discovery and validation cohorts. Samples were stained and visualized using multiplexed immunofluorescence microscopy for STAT1, STAT1 phosphorylated at Y701 (pSTAT1Y701), and PD-L1, and signals were quantified using the automated quantitative analysis method of quantitative immunofluorescence. Treatment response was assessed using RECIST, and overall survival was analyzed. For in vitro studies, human melanoma cell lines were stimulated with IFNγ and IFNβ, and Western blotting was performed.

RESULTS

Pretreatment STAT1 levels were higher in responders to ICIs [complete response/partial response/stable disease (SD) for > 6 months] than in nonresponders (SD < 6 months/progressive disease). Higher pretreatment STAT1 levels were associated with improved survival after ICIs in both the discovery and validation cohorts. Western blot analysis of human melanoma cell lines stimulated with IFN demonstrated distinct patterns of upregulation of STAT1 compared with pSTAT1Y701 and PD-L1. When combining STAT1 and PD-L1 markers, patients with STAT1highPD-L1low tumors had improved survival compared with those with STAT1lowPD-L1high tumors.

CONCLUSIONS

STAT1 may better predict melanoma response to ICIs than current strategies, and combined STAT1 and PD-L1 biomarkers may provide insight into IFN-responsive versus IFN-resistant states.

Identification of the relationship between single-cell N6-methyladenosine regulators and the infiltrating immune cells in esophageal carcinoma

Background

N6-methyladenosine (m⁶A) RNA methylation plays a crucial role in important genomic processes in a variety of malignancies. However, the characterization of m⁶A with infiltrating immune cells in the tumor microenvironment (TME) in esophageal squamous carcinoma (ESCC) remains unknown.

Methods

The single-cell transcriptome data from five ESCC patients in our hospital were analyzed, and TME clusters associated with prognosis and immune checkpoint genes were investigated. Cell isolation and qPCR were conducted to validate the gene characterization in different cells.

Results

According to distinct biological processes and marker genes, macrophages, T cells, and B cells clustered into three to four different subgroups. In addition, we demonstrated that m⁶A RNA methylation regulators were strongly related to the clinical and biological features of ESCC. Analysis of transcriptome data revealed that m⁶A-mediated TME cell subsets had high predictive value and showed a close relationship with immune checkpoint genes. The validation results from qPCR demonstrated the characteristics of essential genes. CellChat analysis revealed that RNA from TME cells m⁶A methylation-associated cell subtypes had substantial and diversified interactions with cancer cells. Further investigation revealed that MIF- (CD74+CXCR4) and MIF- (CD74⁺CD44) ligand-receptor pairings facilitated communication between m⁶A-associated subtypes of TME cells and cancer cells.

Conclusion

Overall, our study demonstrated for the first time the function of m⁶A methylation-mediated intercellular communication in the microenvironment of tumors in controlling tumor development and anti-tumor immune regulation in ESCC.

In Situ Tumor Vaccine for Lymph Nodes Delivery and Cancer Therapy Based on Small Size Nanoadjuvant

Tumor vaccine is a promising cancer treatment modality, however, the convenient antigens loading in vivo and efficient delivery of vaccines to lymph nodes (LNs) still remain a formidable challenge. Herein, an in situ nanovaccine strategy targeting LNs to induce powerful antitumor immune responses by converting the primary tumor into whole-cell antigens and then delivering these antigens and nanoadjuvants simultaneously to LNs is proposed. The in situ nanovaccine is based on a hydrogel system, which loaded with doxorubicin (DOX) and nanoadjuvant CpG-P-ss-M. The gel system exhibits ROS-responsive release of DOX and CpG-P-ss-M, generating abundant in situ storage of whole-cell tumor antigens. CpG-P-ss-M adsorbs tumor antigens through the positive surface charge and achieves charge reversal, forming small-sized and negatively charged tumor vaccines in situ, which are then primed to LNs. Eventually, the tumor vaccine promotes antigens uptake by dendritic cells (DCs), maturation of DCs, and proliferation of T cells. Moreover, the vaccine combined with anti-CTLA4 antibody and losartan inhibits tumor growth by 50%, significantly increasing the percentage of splenic cytotoxic T cells (CTLs), and generating tumor-specific immune responses. Overall, the treatment effectively inhibits primary tumor growth and induces tumor-specific immune response. This study provides a scalable strategy for in situ tumor vaccination.

Aggrephagy-related patterns in tumor microenvironment, prognosis, and immunotherapy for acute myeloid leukemia: a comprehensive single-cell RNA sequencing analysis

Acute myeloid leukemia (AML) is a complex mixed entity composed of malignant tumor cells, immune cells and stromal cells, with intra-tumor and inter-tumor heterogeneity. Single-cell RNA sequencing enables a comprehensive study of the highly complex tumor microenvironment, which is conducive to exploring the evolutionary trajectory of tumor cells. Herein, we carried out comprehensive analyses of aggrephagy-related cell clusters based on single-cell sequencing for patients with acute myeloid leukemia. A total of 11 specific cell types (T, NK, CMP, Myeloid, GMP, MEP, Promono, Plasma, HSC, B, and Erythroid cells) using t-SNE dimension reduction analysis. Several aggrephagy-related genes were highly expressed in the 11 specific cell types. Using Monocle analysis and NMF clustering analysis, six aggrephagy-related CD8+ T clusters, six aggrephagy-related NK clusters, and six aggrephagy-related Mac clusters were identified. We also evaluated the ligand-receptor links and Cell-cell communication using CellChat package and CellChatDB database. Furthermore, the transcription factors (TFs) of aggrephagy-mediated cell clusters for AML were assessed through pySCENIC package. Prognostic analysis of the aggrephagy-related cell clusters based on R package revealed the differences in prognosis of aggrephagy-mediated cell clusters. Immunotherapy of the aggrephagy-related cell clusters was investigated using TIDE algorithm and public immunotherapy cohorts. Our study revealed the significance of aggrephagy-related patterns in tumor microenvironment, prognosis, and immunotherapy for AML.

Loss of PHF8 induces a viral mimicry response by activating endogenous retrotransposons

Immunotherapy has become established as major treatment modality for multiple types of solid tumors, including colorectal cancer. Identifying novel immunotherapeutic targets to enhance anti-tumor immunity and sensitize current immune checkpoint blockade (ICB) in colorectal cancer is needed. Here we report the histone demethylase PHD finger protein 8 (PHF8, KDM7B), a Jumonji C domain-containing protein that erases repressive histone methyl marks, as an essential mediator of immune escape. Ablation the function of PHF8 abrogates tumor growth, activates anti-tumor immune memory, and augments sensitivity to ICB therapy in mouse models of colorectal cancer. Strikingly, tumor PHF8 deletion stimulates a viral mimicry response in colorectal cancer cells, where the depletion of key components of endogenous nucleic acid sensing diminishes PHF8 loss-meditated antiviral immune responses and anti-tumor effects in vivo. Mechanistically, PHF8 inhibition elicits H3K9me3-dependent retrotransposon activation by promoting proteasomal degradation of the H3K9 methyltransferase SETDB1 in a demethylase-independent manner. Moreover, PHF8 expression is anti-correlated with canonical immune signatures and antiviral immune responses in human colorectal adenocarcinoma. Overall, our study establishes PHF8 as an epigenetic checkpoint, and targeting PHF8 is a promising viral mimicry-inducing approach to enhance intrinsic anti-tumor immunity or to conquer immune resistance.

Integrative analysis of multi-omics data for discovery of ferroptosis-related gene signature predicting immune activity in neuroblastoma

Immunotherapy for neuroblastoma remains unsatisfactory due to heterogeneity and weak immunogenicity. Exploring powerful signatures for the evaluation of immunotherapy outcomes remain the primary purpose. We constructed a ferroptosis-related gene (FRG) signature by least absolute shrinkage and selection operator and Cox regression, identified 10 independent prognostic FRGs in a training cohort (GSE62564), and then verified them in an external validation cohort (TCGA). Associated with clinical factors, the signature accurately predicts overall survival of 3, 5, and 10 years. An independent prognostic nomogram, which included FRG risk, age, stage of the International Neuroblastoma Staging System, and an MYCN status, was constructed. The area under the curves showed satisfactory prognostic predicting performance. Through bulk RNA-seq and proteomics data, we revealed the relationship between hub genes and the key onco-promoter MYCN gene and then validated the results in MYCN-amplified and MYCN-non-amplified cell lines with qRT-PCR. The FRG signature significantly divided patients into high- and low-risk groups, and the differentially expressed genes between the two groups were enriched in immune actions, autophagy, and carcinogenesis behaviors. The low-risk group embodied higher positive immune component infiltration and a higher expression of immune checkpoints with a more favorable immune cytolytic activity (CYT). We verified the predictive power of this signature with data from melanoma patients undergoing immunotherapy, and the predictive power was satisfactory. Gene mutations were closely related to the signature and prognosis. AURKA and PRKAA2 were revealed to be nodal hub FRGs in the signature, and both were shown to have significantly different expressions between the INSS stage IV and other stages after immunohistochemical validation. With single-cell RNA-seq analysis, we found that genes related to T cells were enriched in TNFA signaling and interferon-γ hallmark. In conclusion, we constructed a ferroptosis-related gene signature that can predict the outcomes and work in evaluating the effects of immunotherapy.

Deep learning identifies a T-cell exhaustion-dependent transcriptional signature for predicting clinical outcomes and response to immune checkpoint blockade

Immune checkpoint blockade (ICB) therapies have brought unprecedented advances in cancer treatment, but responses are limited to a fraction of patients. Therefore, sustained and substantial efforts are required to advance clinical and translational investigation on managing patients receiving ICB. In this study, we investigated the dynamic changes in molecular profiles of T-cell exhaustion (TEX) during ICB treatment using single-cell and bulk transcriptome analysis, and demonstrated distinct exhaustion molecular profiles associated with ICB response. By applying an ensemble deep-learning computational framework, we identified an ICB-associated transcriptional signature consisting of 16 TEX-related genes, termed ITGs. Incorporating 16 ITGs into a machine-learning model called MLTIP achieved reliable predictive power for clinical ICB response with an average AUC of 0.778, and overall survival (pooled HR = 0.093, 95% CI, 0.031-0.28, P < 0.001) across multiple ICB-treated cohorts. Furthermore, the MLTIP consistently demonstrated superior predictive performance compared to other well-established markers and signatures, with an average increase in AUC of 21.5%. In summary, our results highlight the potential of this TEX-dependent transcriptional signature as a tool for precise patient stratification and personalized immunotherapy, with clinical translation in precision medicine.

MYC Induces Immunotherapy and IFNγ Resistance Through Downregulation of JAK2

Immunotherapy has revolutionized the treatment of advanced melanoma. Because the pathways mediating resistance to immunotherapy are largely unknown, we conducted transcriptome profiling of preimmunotherapy tumor biopsies from patients with melanoma that received PD-1 blockade or adoptive cell therapy with tumor-infiltrating lymphocytes. We identified two melanoma-intrinsic, mutually exclusive gene programs, which were controlled by IFNγ and MYC, and the association with immunotherapy outcome. MYC-overexpressing melanoma cells exhibited lower IFNγ responsiveness, which was linked with JAK2 downregulation. Luciferase activity assays, under the control of JAK2 promoter, demonstrated reduced activity in MYC-overexpressing cells, which was partly reversible upon mutagenesis of a MYC E-box binding site in the JAK2 promoter. Moreover, silencing of MYC or its cofactor MAX with siRNA increased JAK2 expression and IFNγ responsiveness of melanomas, while concomitantly enhancing the effector functions of T cells coincubated with MYC-overexpressing cells. Thus, we propose that MYC plays a pivotal role in immunotherapy resistance through downregulation of JAK2.

Decoupling the correlation between cytotoxic and exhausted T lymphocyte transcriptomic signatures enhances melanoma immunotherapy response prediction from tumor expression

Background

Cytotoxic T lymphocytes (CTL) play a crucial role in anti-cancer immunity. Progression of CTL to terminal exhausted T lymphocytes (ETL) that overexpress inhibitory receptors can substantially decrease effector cytokines production and diminish cytolytic activity and terminal exhausted T cell cannot be reprogrammed by ICIs in tumor microenvironment (TME). However, while the activity levels of CTL and ETL are considered important determinants of immune checkpoint inhibitors (ICIs) response, it has been repeatedly observed that their predictive power of the latter is quite limited. Studying this conundrum on a large scale across the TCGA cohort, we find that ETL and CTL activity (estimated based on conventional gene signatures in the bulk tumor expression) is strongly positively correlated in most cancer types. We hypothesized that the limited predictive power of CTL activity might result from the high concordance of CTL and ETL activities, which mutually cancels out their individual antagonistic effects on ICI response.

Methods

Consequently, we have set out to identify a set of genes whose expression identifies a subset of patients where the CTL and ETL correlation is diminished, such that the association between these CD8+ T cell states and ICIs response is enhanced.

Results

Analyzing TCGA melanoma bulk gene expression, we identified a set of genes whose over-expression markedly diminishes the CTL and ETL correlation, termed a decoupling signature (DS). Reassuringly, we first find that the correlation between ETL and CTL activities is indeed markedly lower across high scoring DS patients than that observed across low scoring DS patients in numerous independent melanoma ICIs cohorts. Second, indeed, this successful decoupling increases the power of CTL activity in predicting ICIs response in high DS scoring patients. We show that the resulting prediction accuracy is superior to other state-of-art ICI predictive transcriptomic signatures.

Conclusion

The new decoupling score boosts the power of CTL activity in predicting ICIs response in melanoma from the tumor bulk expression. Its use enables a two-step stratification approach, where the response of high scoring DS patient can be predicted more accurately that with extant transcriptomic signatures.

Tumor-secreted IFI35 promotes proliferation and cytotoxic activity of CD8+ T cells through PI3K/AKT/mTOR signaling pathway in colorectal cancer

BACKGROUND

A large proportion of the patients with cancer do not respond to immunotherapies. Recent studies suggested an important role for tumor-infiltrating cytotoxic T lymphocytes (CTL) in enhancing response to immunotherapy. Here, we aim to identify gene that induce proliferative and cytotoxic states of CD8⁺ T cells, and to investigate its effect on CAR-T cells against colorectal cancer.

METHODS

Correlation between the expression of IFI35 with the activation and cytotoxicity of CD8⁺ T cells was assessed with TCGA and proteomic databases. Then we constructed murine colon cancer cells over-expressing IFI35 and tested their effect on anti-tumor immunity in both immunodeficient and immunocompetent mouse models. Flow cytometry and immunohistochemistry were performed to assess the immune microenvironment. Western blot analysis was used to identify the potential down-stream signaling pathway regulated by IFI35. We further investigated the efficacy of the rhIFI35 protein in combination with immunotherapeutic treatment.

RESULTS

The transcriptional and proteomic analysis of the activation and cytotoxicity of CD8⁺ T cells in human cancer samples demonstrated that IFI35 expression is correlated with increased CD8⁺ T cell infiltration and predicted a better outcome in colorectal cancer. The number and cytotoxicity of CD8⁺ T cells were significantly increased in IFI35-overexpressing tumors. Mechanistically, we identified that the IFNγ-STAT1-IRF7 axis stimulated IFI35 expression, and that IFI35-mediated regulation of CD8⁺ T cell proliferation and cytotoxicity was dependent on PI3K/AKT/mTOR signaling pathway in vitro. Furthermore, IFI35 protein enhanced the efficacy of CAR-T cells against colorectal cancer cells.

CONCLUSION

Our findings identify IFI35 as a new biomarker that can enhance the proliferation and function of CD8⁺ T cells, as well as increase the efficacy of CAR-T cells against colorectal cancer cells.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Deciphering the role of NETosis-related signatures in the prognosis and immunotherapy of soft-tissue sarcoma using machine learning

Background: Soft-tissue sarcomas (STSs) are a rare type of cancer, accounting for about 1% of all adult cancers. Treatments for STSs can be difficult to implement because of their diverse histological and molecular features, which lead to variations in tumor behavior and response to therapy. Despite the growing importance of NETosis in cancer diagnosis and treatment, researches on its role in STSs remain limited compared to other cancer types. Methods: The study thoroughly investigated NETosis-related genes (NRGs) in STSs using large cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and Support Vector Machine Recursive Feature Elimination (SVM-RFE) were employed for screening NRGs. Utilizing single-cell RNA-seq (scRNA-seq) dataset, we elucidated the expression profiles of NRGs within distinct cellular subpopulations. Several NRGs were validated by quantitative PCR (qPCR) and our proprietary sequencing data. To ascertain the impact of NRGs on the sarcoma phenotype, we conducted a series of in vitro experimental investigations. Employing unsupervised consensus clustering analysis, we established the NETosis clusters and respective NETosis subtypes. By analyzing DEGs between NETosis clusters, an NETosis scoring system was developed. Results: By comparing the outcomes obtained from LASSO regression analysis and SVM-RFE, 17 common NRGs were identified. The expression levels of the majority of NRGs exhibited notable dissimilarities between STS and normal tissues. The correlation with immune cell infiltration were demonstrated by the network comprising 17 NRGs. Patients within various NETosis clusters and subtypes exhibited different clinical and biological features. The prognostic and immune cell infiltration predictive capabilities of the scoring system were deemed efficient. Furthermore, the scoring system demonstrated potential for predicting immunotherapy response. Conclusion: The current study presents a systematic analysis of NETosis-related gene patterns in STS. The results of our study highlight the critical role NRGs play in tumor biology and the potential for personalized therapeutic approaches through the application of the NETosis score model in STS patients.

Immunogenetic polymorphisms predict therapeutic efficacy and survival outcomes in tumor patients receiving PD-1/PD-L1 blockade

BACKGROUND

While immune checkpoint inhibitors (ICIs) demonstrate remarkable clinical responses, only a small subset of patients obtains benefits. Genes linked to the tumor immune system are confirmed to be critical for the treatment of ICIs, and their polymorphisms can contribute to ICI efficacy. Here, we examined the potential of immunogenetic variations to predict the efficacy and survival of the PD-1/PD-L1 blockade.

METHODS

Cancerous patients receiving PD-1/PD-L1 blockade were recruited and followed up. Pivotal genes related to tumor-immunity were filtered through a protein-protein interaction network and the degree algorithm in Cytoscape. Finally, 39 genetic variants were genotyped through multiplex genotyping assays. Association analyses between variants and ICI efficacy and progression-free survival (PFS) were performed.

RESULTS

Overall, 318 patients were ultimately enrolled. Hence, three immunogenetic variants were identified as predictors of PD-1/PD-L1 blockade response. Mutant alleles from ATG7 rs7625881, CD274 rs2297136, and TLR4 rs1927911 were all at increased risk of tumor progression following ICI therapy (OR: 1.475, 1.641, 1.462, respectively; P value: 0.028, 0.017, 0.027, respectively). Significant immunogenetic variants also attained similar trends in the PD-1 blockade, lung cancer, or lung cancer using PD-1 blockade subgroups. Furthermore, the mutant genotypes of CD274 rs2297136 (GG as the reference: HR: 0.50 (95%CI: 0.29-0.88), P value: 0.015) and TLR4 rs1927911 (AA as the reference: HR: 0.65 (95%CI: 0.47-0.91), P value: 0.012) indicated poorer PFS and were both independent prognostic factors.

CONCLUSION

Immunogenetic polymorphisms, including ATG7 rs7625881, CD274 rs2297136, and TLR4 rs1927911, were first identified as potential predictors of response to PD-1/PD-L1 blockade in tumor patients.

Pan-cancer analysis of Homeobox B9 as a predictor for prognosis and immunotherapy in human tumors

BACKGROUND

Although several animal and cell studies have described the association between HOXB9 and cancers, there is no pan-cancer investigation of HOXB9. In this article, we explored the expression levels and prognosis of HOXB9 in pan-cancer. We evaluated the correlation of HOXB9 expression level with the efficacy of immunotherapy.

METHODS

We conducted a survival analysis of HOXB9 in various types of cancer using publicly available databases. We also examined the relationship between HOXB9 expression levels and several factors including prognosis, immune infiltration, immune checkpoint genes, tumor mutational burden, microsatellite instability, mismatch repair, and DNA methylation. TIMER2.0 tool was conducted to explore the immune cell infiltrations related to HOXB9 in this analysis.

RESULTS

It was discovered through a comprehensive analysis of multiple public datasets that HOXB9 expression was highly expressed in most tumor tissues and cancer cell lines and that distinct associations exist between HOXB9 expression and tumor patient prognosis. Besides, HOXB9 expression was closely associated with immune cell infiltration and checkpoint genes in many cancers. Further, HOXB9 was associated with immune cell infiltration, TMB, MSI, MMR, and DNA methylation. It was also confirmed that HOXB9 was highly expressed in clinical GBM tissues. Experiments further revealed that knockdown of HOXB9 expression could suppress proliferation, migration, and invasion of glioma cells.

CONCLUSIONS

The results revealed that HOXB9, a robust tumor biomarker, has a significant prognostic value. HOXB9 may act as a new predictor to assess cancer prognosis and therapeutic efficacy of the immune in various cancers.