Functional genomic landscape of cancer-intrinsic evasion of killing by T cells

SOCS1 Protects Acute Myeloid Leukemia against Allogeneic T Cell-Mediated Cytotoxicity

SIGNIFICANCE

Our investigation of the SOCS1 pathway in AML and T-cell interactions provides insights into potential mechanisms of resistance of AML to allogeneic hematopoietic stem cell transplantation and demonstrates the potential of targeting SOCS1 and its downstream mediators to enhance antileukemic T-cell activity. See related commentary by Fry, p. 157.

Identify key genes and biological processes participated in obesity-related cancer based on studying 12 cancers

Obesity significantly increases the risk of various diseases, particularly cancers, which present a serious threat to public health. Therefore, identifying cancers related to obesity and exploring their pathological pathways and key genes are highly significant for the prevention and treatment of these cancers. In this study, we propose the obesity and cancer edge connectivity based on expanded modular disease genes and expanded modular networks (OCEC_eDMN) algorithm, which based on the disease-related genes, Biological Process (BP) genes, and Protein-Potein Interaction (PPI) network. The algorithm utilizes Random Walk with Restart (RWR) to expand BP genes and disease genes to generate the expanded modular networks (eMNs) and disease genes (eMDs). Finally, this algorithm calculates the average interaction number between eMDs on eMNs. We utilize OCEC_eDMN to predict the ranking of 12 cancers related to obesity/morbid obesity and obtain an AUC of 0.93/0.84. Additionally, OCEC_eDMN reveals the significant BPs associated with obesity-cancer connections. For instance, "gluconeogenesis" plays a critical role in the connections between obesity and cancers. Through key driver analysis (KDA) on eMDs, we identify the key connectors in obesity-cancer connections. Genes such as GRB2 are instrumental in linking morbid obesity to colorectal cancer in the eMNs of "response to molecule of bacterial origin". The significant eMNs and key genes provide valuable references for the prevention and treatment of obesity-related cancers and carry important theoretical implications.

AGO2 mediates immunotherapy failure via suppressing tumor IFN-gamma response-dependent CD8+ T cell immunity

Interferon-gamma (IFN-γ), a cytokine essential for activating cellular immune responses, plays a crucial role in cancer immunosurveillance and the clinical success of immune checkpoint blockade therapy. In this study, we show that Argonaute 2 (AGO2), a key mediator in small RNA-guided gene regulation, inversely correlates with tumor responsiveness to IFN-γ and the efficacy of immunotherapy. Mechanistically, IFN-γ upregulates miR-1246 expression in tumor cells, enhancing its interaction with AGO2. This miR-1246-AGO2 complex disrupts IFN-γ-mediated signal transducer and activator of transcription 1 (STAT1) phosphorylation by stabilizing protein tyrosine phosphatase non-receptor 6 (PTPN6) mRNA, thereby suppressing the expression of downstream C-X-C motif chemokine ligands (CXCLs), IFN-stimulated genes (ISGs), and human leukocyte antigen (HLA) molecules, which collectively contribute to tumor immune evasion. In preclinical cancer models, inhibiting AGO2 with BCI-137 or targeting miR-1246 with its antagomir re-sensitizes tumor cells to IFN-γ, leading to the enhanced recruitment, activation, and cytotoxicity of CD8+ T cells and ultimately improving immunotherapy efficacy.

Immunocytes in the tumor microenvironment: recent updates and interconnections

The tumor microenvironment (TME) is a complex, dynamic ecosystem where tumor cells interact with diverse immune and stromal cell types. This review provides an overview of the TME's evolving composition, emphasizing its transition from an early pro-inflammatory, immune-promoting state to a later immunosuppressive milieu characterized by metabolic reprogramming and hypoxia. It highlights the dual roles of key immunocytes-including T lymphocytes, natural killer cells, macrophages, dendritic cells, and myeloid-derived suppressor cells-which can either inhibit or support tumor progression based on their phenotypic polarization and local metabolic conditions. The article further elucidates mechanisms of immune cell plasticity, such as the M1/M2 macrophage switch and the balance between effector T cells and regulatory T cells, underscoring their impact on tumor growth and metastasis. Additionally, emerging therapeutic strategies, including checkpoint inhibitors and chimeric antigen receptor (CAR) T and NK cell therapies, as well as approaches targeting metabolic pathways, are discussed as promising avenues to reinvigorate antitumor immunity. By integrating recent molecular insights and clinical advancements, the review underscores the importance of deciphering the interplay between immunocytes and the TME to develop more effective cancer immunotherapies.

Leveraging genetics to understand ADAR1-mediated RNA editing in health and disease

Endogenous, long double-stranded RNA (dsRNA) can resemble viral dsRNA and be recognized by cytosolic dsRNA sensors, triggering autoimmunity. Genetic studies of rare, inherited human diseases and experiments using mouse models have established the importance of adenosine-to-inosine RNA editing by the enzyme adenosine deaminase acting on RNA 1 (ADAR1) as a critical safeguard against autoinflammatory responses to cellular dsRNA. More recently, human genetic studies have revealed that dsRNA editing and sensing mechanisms are involved in common inflammatory diseases, emphasizing the broader role of dsRNA in modulating immune responses and disease pathogenesis. These findings have highlighted the therapeutic potential of targeting dsRNA editing and sensing, as exemplified by the emergence of ADAR1 inhibition in cancer therapy.

Prognostic implications of the interaction between intratumoral microbiome and immune response in gastric cancer

Gastric cancer (GC) prognosis is significantly influenced by intratumoral microbiomes, which modulate host-immune interactions. This study analyzed data from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify immune genes associated with GC prognosis and conducted prognostic immune subtypes. GC patients were classified into two distinct prognostic immune phenotypes C1 and C2 based on the non-negative matrix factorization consensus clusters. Phenotype C2 exhibited a better prognosis and distinct immune characteristics, including enhanced presence of Th2 and Th17 cells and improved response to chemotherapy. In contrast, phenotype C1 showed higher expression levels of PDCD1LG2 and TLR9, which were critical immune factors involved in immune regulation. Both phenotypes were linked to immune genes influencing intratumoral microbiomes and GC immunotherapy responses. A prediction risk model was constructed using the LASSO regression analysis and showed great prognostic value for GC patients. The key genes were correlated with immune cells and suppressed the function of the host immune system. The intratumoral microbiomes were strongly associated with the hosts' immune infiltration and significantly interacted with host immune genes to influence GC outcomes. Candidatus Nitrosotenuis plays a significant role in predicting the prognosis of GC patients. This research underscores the pivotal role of intratumoral microbiomes in GC prognosis and supports the development of future personalized therapeutic approaches.IMPORTANCEIncreasing evidence confirms the presence of intratumoral microbiomes. However, the role of the intratumoral microbiomes in the progression of gastric cancer and their relationship with the immune microenvironment remain unclear. Our study classified gastric cancer patients into two immune prognostic subtypes, C1 and C2, using non-negative matrix factorization consensus clusters. The C2 subtype exhibited a better prognosis and more pronounced immune characteristics. Microbiome analyses revealed associations between both subtypes and immune genes that affect intratumoral microbiomes and their responses to immunotherapy. The intratumoral microbiomes were closely linked with host immune infiltration and significantly interacted with immune genes, which influence the prognosis of gastric cancer. Notably, Candidatus Nitrosotenuis showed a significant prognostic value in gastric cancer patients. Our findings highlight the critical role of the intratumoral microbiomes in affecting gastric cancer prognosis and its interaction with the immune microenvironment, supporting future personalized therapeutic approaches.

The mRNA export pathway licenses viral mimicry response and antitumor immunity by actively exporting nuclear retroelement transcripts

Nuclear retroelement transcripts (RTs), which can be elicited both transcriptionally and posttranscriptionally, form double-stranded RNA (dsRNA) in cytosol to trigger the viral mimicry response (VMR) and antitumor immunity. However, the strength of the induced VMR varies tremendously across tumor types, and the underlying mechanisms remain poorly understood. Here, we demonstrate that the mRNA export pathway modulates the VMR through actively exporting nuclear RTs for cytosolic dsRNA formation after their induction. Tumor cells hijack this process for immune evasion through aberrant coactivator-associated arginine methyltransferase 1 (CARM1) expression. Mechanistically, we show that the cytoplasmic transportation of RTs by the mRNA export pathway is counteracted by the RNA exosome, which cleaves multiple transcripts within this pathway, including those encoding the essential DExD-box helicase 39A (DDX39A) and the adaptor protein ALYREF. CARM1 enhances the RNA exosome activity to attenuate the nuclear export of RTs by the mRNA export pathway through two synergistic mechanisms: (i) transcriptionally activating several RNA exosome components and (ii) posttranslationally methylating arginine 6 of the RNA exosome subunit EXOSC1, which protects it from proteasome-mediated degradation. Collectively, our study highlights the critical active regulatory role of the mRNA export pathway in transporting nuclear RTs into the cytosol for triggering the VMR and tumor immunity. Furthermore, we propose that enhancing the mRNA export pathway activity, either through CARM1 inhibition or RNA exosome modulation, could reinforce the therapeutic agent-induced VMR, thus holding the promise for overcoming tumor immune evasion and immunotherapy resistance.

Comprehensive bioinformatics analysis identified HMGB3 as a promising immunotherapy target for glioblastoma multiforme

OBJECTIVE

Glioblastoma multiforme (GBM) presents significant therapeutic challenges due to its heterogeneous tumorigenicity, drug resistance, and immunosuppression. Although several molecular markers have been developed, there still lack of sensitive molecular for accurately detection. Studying the mechanisms underlying the development of GBM and finding relevant prognostic biomarkers remains crucial.

METHODS

Single-cell RNA sequencing, bulk RNA-seq, and cancer immune cycle activities of GBM were used to assess the expression of different molecular related to GBM. Bioinformatics analyses were carried to evaluate the functional of the high mobility group protein B3 (HMGB3) in GBM.

RESULTS

HMGB3 was highly expressed in GBM tissues and influenced the interpatient and intratumoral transcriptomic heterogeneity as well as immunosuppression in GBM. HMGB3 also contributes to a no inflamed tumor microenvironment (TME) and has an inhibitory effect on tumor-associated immune cell infiltration. Besides, HMGB3 participated GBM chemotherapeutic sensitivity and negative correlation with 140 medicines.

CONCLUSION

HMGB3 as a heterogeneous and immunosuppressive molecule in the GBM TME, making it a potential target for precision therapy for GBM.

iMLGAM: Integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis for pan-cancer immunotherapy response prediction

To address the substantial variability in immune checkpoint blockade (ICB) therapy effectiveness, we developed an innovative R package called integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis (iMLGAM), which establishes a comprehensive scoring system for predicting treatment outcomes through advanced multi-omics data integration. Our research demonstrates that iMLGAM scores exhibit superior predictive performance across independent cohorts, with lower scores correlating significantly with enhanced therapeutic responses and outperforming existing clinical biomarkers. Detailed analysis revealed that tumors with low iMLGAM scores display distinctive immune microenvironment characteristics, including increased immune cell infiltration and amplified antitumor immune responses. Critically, through clustered regularly interspaced short palindromic repeats screening, we identified Centrosomal Protein 55 (CEP55) as a key molecule modulating tumor immune evasion, mechanistically confirming its role in regulating T cell-mediated antitumor immune responses. These findings not only validate iMLGAM as a powerful prognostic tool but also propose CEP55 as a promising therapeutic target, offering novel strategies to enhance ICB treatment efficacy. The iMLGAM package is freely available on GitHub (https://github.com/Yelab1994/iMLGAM), providing researchers with an innovative approach to personalized cancer immunotherapy prediction.

Integrated Bioinformatic Analyses Constructed a Novel Immune Escape-Related Signature and Classifier to Predict Tuberculosis

Despite its high preventability and curability, tuberculosis (TB) remains a leading cause of morbidity and mortality worldwide. One factor that contributes to the susceptibility and progression of various diseases is immune escape. Therefore, the primary aim of our study was to explore the involvement of immune escape-related genes in the pathogenesis of TB. Two TB datasets retrieved from the gene expression omnibus database were used to identify differentially expressed genes (DEGs). Machine learning was used to identify the hub immune escape-related genes (HIERGs). Weighted gene co-expression network analysis supported and further validated these findings. Subsequently, we scrutinised two distinct subgroups that were determined through the identification of hub immune escape-related genes, and evaluated the distinct function of the subgroups. Our study identified a total of 11 genes related to immune escape in TB. Additionally, six HIERGs were identified through the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Diagnostic models constructed using HIERGs exhibited high accuracy. Two immune escape-related subclusters were identified in TB samples, which delineated differences in immune infiltration cells with the distinct TB subgroups. The heightened expression of six HIERGs serves as a significant risk factor for TB. The six HIERGs also contribute towards the development of TB-related diseases. Our findings demonstrate a significant enrichment of immune escape-related gene expression in individuals with TB, suggesting a close relationship between immune escape activity and immune cell abundance. These results underscore the putative role of immune escape in the advancement of TB by disrupting or perturbing the immune response.

VDAC2 loss elicits tumour destruction and inflammation for cancer therapy

Tumour cells often evade immune pressure exerted by CD8+ T cells or immunotherapies through mechanisms that are largely unclear1,2. Here, using complementary in vivo and in vitro CRISPR-Cas9 genetic screens to target metabolic factors, we established voltage-dependent anion channel 2 (VDAC2) as an immune signal-dependent checkpoint that curtails interferon-γ (IFNγ)-mediated tumour destruction and inflammatory reprogramming of the tumour microenvironment. Targeting VDAC2 in tumour cells enabled IFNγ-induced cell death and cGAS-STING activation, and markedly improved anti-tumour effects and immunotherapeutic responses. Using a genome-scale genetic interaction screen, we identified BAK as the mediator of VDAC2-deficiency-induced effects. Mechanistically, IFNγ stimulation increased BIM, BID and BAK expression, with VDAC2 deficiency eliciting uncontrolled IFNγ-induced BAK activation and mitochondrial damage. Consequently, mitochondrial DNA was aberrantly released into the cytosol and triggered robust activation of cGAS-STING signalling and type I IFN response. Importantly, co-deletion of STING signalling components dampened the therapeutic effects of VDAC2 depletion in tumour cells, suggesting that targeting VDAC2 integrates CD8+ T cell- and IFNγ-mediated adaptive immunity with a tumour-intrinsic innate immune-like response. Together, our findings reveal VDAC2 as a dual-action target to overcome tumour immune evasion and establish the importance of coordinately destructing and inflaming tumours to enable efficacious cancer immunotherapy.

The NF1 tumor suppressor regulates PD-L1 and immune evasion in melanoma

Hotspot BRAF, hotspot NRAS, and NF1 loss-of-function mutations are found in approximately 50%, 25%, and 15% of cutaneous melanomas, respectively. Compared to mutant BRAF and NRAS, the role of NF1 loss in melanoma remains understudied. NF1 has a RAS GTPase-activating protein (GAP) function; however, studies also support NF1 RAS-independent tumor-suppressor functions. Recent reports indicate that patients with NF1 mutant melanoma have high response rates to anti-PD-1 immune checkpoint inhibitors (ICIs) for reasons that are not entirely clear. Here, we present data demonstrating that NF1 interacts with PD-L1. Furthermore, NF1 loss in melanoma lines increases PD-L1 cell surface expression through a RAS-GAP-independent mechanism. Co-culture experiments demonstrate that NF1 depletion in melanoma increases resistance to T cell killing, which can be abrogated with anti-PD-1/PD-L1 ICIs. These results support a model whereby NF1 loss leads to immune evasion through the PD-L1/PD-1 axis, providing support for the examination of anti-PD-1 therapies in other NF1 mutant cancers.

Integrated analysis reveals an immune evasion prognostic signature for predicting the overall survival in patients with hepatocellular carcinoma

BACKGROUND

The development of immunotherapy has enriched the treatment of hepatocellular carcinoma (HCC), but the efficacy is not as expected, which may be due to immune evasion. Immune evasion is related to the immune microenvironment of HCC, but there is little research on it.

METHODS

We employed unsupervised clustering analysis to categorize patients from TCGA based on 182 immune evasion-related genes (IEGs). We utilized single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT to calculate differences in immune cell infiltration between clusters. The differences in immune cells and immune-related pathways were assessed using GSEA. We constructed an immune escape prognosis signature (IEPS) using univariate Cox and LASSO Cox algorithms and evaluated the predictive performance of IEPS with receiver operating characteristic (ROC) curves and survival curves. Additionally, we established a nomogram for clinical application based on IEPS. IHC validated the expression of Carbamoyl phosphate synthetase 2, Aspartate transcarbamylase, and Dihydroorotase (CAD) and Phosphatidylinositol Glycan Anchor Biosynthesis Class U (PIGU) in HCC. We transfected liver cancer cell lines with siRNA and overexpression plasmids, and confirmed the relationship between CAD, PIGU, and the potential downstream TGF-β1 in HCC using qRT-PCR and Western blot. Finally, we validated the tumor response of CAD overexpression using an animal model.

RESULTS

Unsupervised clustering analysis based on IEGs divided HCC patients from TCGA into two groups. There were significant differences in prognosis and immune characteristics between the two groups of patients. Scoring of TCGA patients using IEPS revealed that higher scores were associated with poorer overall survival (OS). Validation was performed using the ICGC database. TIME analysis indicated that patients in the high-IEPS group were in an immunosuppressive state, possibly due to a significant increase in Treg infiltration. Compared to normal liver cells, HCC cells expressed higher levels of CAD and PIGU. Cellular experimental results showed a positive correlation between CAD, PIGU and the potential downstream TGF-β1 expression. Animal experiments demonstrated that CAD significantly promoted tumor progression, with an increase in Treg infiltration.

CONCLUSION

IEPS has strong prognostic value for HCC patients, and CAD and PIGU provide perspectives on new biomarkers and therapeutic targets for HCC.

Pharmacological rescue of mutant p53 triggers spontaneous tumor regression via immune responses

Tumor suppressor p53 is the most frequently mutated protein in cancer, possessing untapped immune-modulating capabilities in anticancer treatment. Here, we investigate the efficacy and underlying mechanisms of pharmacological reactivation of mutant p53 in treating spontaneous tumors in mice. In the p53 R279W (equivalent to the human hotspot R282W) mouse model developing spontaneous tumors, arsenic trioxide (ATO) treatment through drinking water significantly prolongs the survival of mice, dependent on p53-R279W reactivation. Transient regressions of spontaneous T-lymphomas are observed in 70% of the ATO-treated mice, accompanied by interferon (IFN) response. In allograft models, the tumor-suppressive effect of reactivated p53-R279W is detectably reduced in both immunodeficient Rag1-/- and CD8+ T cell-depleted mice. ATO also activates the IFN pathway in human cancer cells harboring various p53 mutations, as well as in primary samples derived from the p53-mutant patient treated with ATO. Together, p53 could serve as an alternative therapeutic target for the development of immunotherapies.

Sensitive detection of synthetic response to cancer immunotherapy driven by gene paralog pairs

Immunotherapies, including checkpoint blockade and chimeric antigen receptor T cell (CAR-T) therapy, have revolutionized cancer treatment; however, many patients remain unresponsive to these treatments or relapse following treatment. CRISPR screenings have been used to identify novel single gene targets that can enhance immunotherapy effectiveness, but the identification of combinational targets remains a challenge. Here, we introduce a computational approach that uses sgRNA set enrichment analysis to identify cancer-intrinsic paralog pairs for enhancing immunotherapy using genome-wide screens. We have further developed an ensemble learning model that uses an XGBoost classifier and incorporates features to predict paralog gene pairs that influence immunotherapy efficacy. We experimentally validated the functional significance of these predicted paralog pairs using CRISPR double knockout (DKO). These data and analyses collectively provide a sensitive approach to identifying previously undetected paralog gene pairs that can significantly affect cancer immunotherapy response, even when individual genes within the pair have limited effect.

HDAC1 Mediates Immunosuppression of the Tumor Microenvironment in Non-Small Cell Lung Cancer

Background

Studies have demonstrated that histone deacetylase 1 (HDAC1) enables cancer cells to evade killing mediated by cytotoxic T lymphocytes. However, there are no studies on the immunological aspects of HDAC1 in non-small cell lung cancer (NSCLC).

Methods

In this research, we used the Cancer Genome Atlas (TCGA) public database combined with tissue microarray (TMA) to investigate HDAC1 expression and prognosis in NSCLC. According to the median value of HDAC1 expression in the TCGA dataset, samples of patients with NSCLC were classified into high- and low-expression cohorts. Subsequently, the biological characteristics of HDAC1 in high- and low-expression cohorts in terms of signaling pathways, immune cell infiltration, immune cell function, and genomic stability were investigated to better understand the effect of HDAC1 in the tumor microenvironment (TME) of NSCLC. Additionally, we selected tissue samples with HDAC1 overexpression in TMA2 and performed immunohistochemical staining of CD8+ T cells to observe the distribution of CD8+ T cells in the tumor.

Results

The findings revealed that overexpression of HDAC1 in NSCLC was associated with poor prognosis. Analysis of signaling pathway enrichment indicated that HDAC1 downregulated immune-related signaling pathways in NSCLC. Immune cell infiltration, immune cell function, and genomic stability analyses suggested that the TME alteration mediated by HDAC1 in the high-expression cohort was consistent with the "immune desert" phenotype. Furthermore, CD8+ T immunohistochemical staining experiments of tissue samples with HDAC1 overexpression in NSCLC revealed few CD8+ T cells distributed in the tumor parenchyma and interstitium.

Conclusion

Conclusively, our findings from several biological analyses revealed that HDAC1 is overexpressed in NSCLC and induces TME immunosuppression.

Finding a needle in a haystack: functional screening for novel targets in cancer immunology and immunotherapies

Genome-wide functional genetic screening has been widely used in the biomedicine field, which makes it possible to find a needle in a haystack at the genetic level. In cancer research, gene mutations are closely related to tumor development, metastasis, and recurrence, and the use of state-of-the-art powerful screening technologies, such as clustered regularly interspaced short palindromic repeat (CRISPR), to search for the most critical genes or coding products provides us with a new possibility to further refine the cancer mapping and provide new possibilities for the treatment of cancer patients. The use of CRISPR screening for the most critical genes or coding products has further refined the cancer atlas and provided new possibilities for the treatment of cancer patients. Immunotherapy, as a highly promising cancer treatment method, has been widely validated in the clinic, but it could only meet the needs of a small proportion of cancer patients. Finding new immunotherapy targets is the key to the future of tumor immunotherapy. Here, we revisit the application of functional screening in cancer immunology from different perspectives, from the selection of diverse in vitro and in vivo screening models to the screening of potential immune checkpoints and potentiating genes for CAR-T cells. The data will offer fresh therapeutic clues for cancer patients.

PCBP2 promotes immune evasion via cGAS-STING pathway in biochemical recurrence of prostate cancer

Immunotherapy resistance is a significant obstacle in the treatment of prostate cancer (PCa), primarily due to immune evasion mechanisms. This study aims to explore cancer-intrinsic immune evasion-related genes (CIERGs) in PCa and develop a predictive signature for biochemical recurrence (BCR). Bulk RNA-seq data and single-cell RNA-sequencing (scRNA-seq) were obtained from TCGA and Gene Expression Omnibus database. The scRNA-seq data analysis revealed higher immune evasion scores in tumor cells compared to normal cells. Differentially expressed genes from TCGA-PRAD and GSE70769 cohorts were intersected with 182 core immune evasion genes, followed by univariate Cox regression, identifying 48 CIERGs significantly associated with BCR. Nonnegative matrix factorization (NMF) clustering revealed two immune evasion-related PCa subtypes. A risk signature based on CIERGs was developed using LASSO regression, and a nomogram was created to predict BCR-free survival. Among the 48 identified CIERGs, poly(C)-binding protein 2 (PCBP2) emerged as a key risk factor associated with poor prognosis in PCa, and its function was validated in vitro. NMF clustering identified two subtypes, with the C1 subtype having a poorer prognosis. Gene Set Variation Analysis highlighted enrichment in cell cycle, extracellular matrix receptor interaction, and transforming growth factor-beta signaling pathways in the C1 subtype. A CIERGs-based risk signature, including six key genes, was developed and validated, with the nomogram showing high predictive accuracy. In vitro experiments showed PCBP2 promotes PCa cell proliferation, migration, and invasion by inhibiting the cyclic GMP-AMP synthase-STING pathway. The CIERGs signature provides a precise prediction of BCR, with PCBP2 emerging as a potential therapeutic target due to its inhibition of the cGAS-STING pathway in PCa.

Investigating the Tumor-Suppressive, Antioxidant Effects and Molecular Binding Affinity of Quercetin-Loaded Selenium Nanoparticles in Breast Cancer Cells

In 2023, breast cancer is expected to have nearly 2 million new cases, making it the second most common cancer overall and the most prevalent among women. Multidrug resistance limits the effectiveness of chemotherapy; however, quercetin, a natural flavonoid, helps combat this issue. The goal of the current investigation is to determine the impact of a novel composite of quercetin and selenium nanoparticles (SeNPs) on the breast cancer cell lines MDA-MB-231 and MCF-7 in order to enhance quercetin’s tumor-suppressive action and decrease selenium (Se) toxicity. Particle size, zeta potential, FTIR, SEM, UV–VIS spectroscopy, and EDX were used to characterize quercetin-selenium nanoparticles (Que-SeNPs), in addition to evaluation of the antioxidant, apoptotic, and anticancer properties. Moreover, autophagy (Atg-13) protein receptors and PD-1/PD-L1 checkpoint were targeted using molecular docking modeling and molecular dynamics (MD) simulations to assess the interaction stability between Que-SeNPs and three targets: PDL-1, PD-1, and Atg-13HORMA domain. Que-SeNPs, synthesized with quercetin, were stable, semi-spherical (80–117 nm), and had a zeta potential of − 37.8 mV. They enhanced cytotoxicity, antioxidant activity, and apoptosis compared to quercetin alone in MCF-7 and MDA-MB-231 cells. Docking simulations showed strong binding to the PD-1/PD-L1 checkpoint and Atg-13HORMA protein receptors. Moreover, the molecular dynamics simulation revealed that the behavior of the PD-L1 intriguing insights into its structural dynamics, therefore, suggesting a stable phase where the complex is adjusting to the simulation environment. The present data confirmed that the stable formula of Que-SeNPs is cytotoxic, antioxidant, and has a potential activity to increase apoptosis in breast cancer cells, with the potential to inhibit PD-1/PD-L1 and Atg-13 proteins.

Graphical Abstract

Role of Que-SeNPs on breast cancer cells in vitro against two breast cancer cell lines MDA-MB-231 and MCF-7.

Massively parallel in vivo Perturb-seq screening

Advances in genomics have identified thousands of risk genes impacting human health and diseases, but the functions of these genes and their mechanistic contribution to disease are often unclear. Moving beyond identification to actionable biological pathways requires dissecting risk gene function and cell type-specific action in intact tissues. This gap can in part be addressed by in vivo Perturb-seq, a method that combines state-of-the-art gene editing tools for programmable perturbation of genes with high-content, high-resolution single-cell genomic assays as phenotypic readouts. Here we describe a detailed protocol to perform massively parallel in vivo Perturb-seq using several versatile adeno-associated virus (AAV) vectors and provide guidance for conducting successful downstream analyses. Expertise in mouse work, AAV production and single-cell genomics is required. We discuss key parameters for designing in vivo Perturb-seq experiments across diverse biological questions and contexts. We further detail the step-by-step procedure, from designing a perturbation library to producing and administering AAV, highlighting where quality control checks can offer critical go-no-go points for this time- and cost-expensive method. Finally, we discuss data analysis options and available software. In vivo Perturb-seq has the potential to greatly accelerate functional genomics studies in mammalian systems, and this protocol will help others adopt it to answer a broad array of biological questions. From guide RNA design to tissue collection and data collection, this protocol is expected to take 9-15 weeks to complete, followed by data analysis.

Development of a novel prognostic signature based on cytotoxic T lymphocyte-evasion genes for hepatocellular carcinoma patient management

OBJECTIVES

Cytotoxic T lymphocytes (CTLs) are major actors in innate and adaptive antitumor response. We attempted to apply cancer cell-intrinsic CTL evasion genes (CCGs) to identify and verify a risk stratification signature in hepatocellular carcinoma (HCC) patients to assess the prognosis and benefits of immunotherapy, sorafenib treatment and transcatheter arterial chemoembolization (TACE) treatment.

METHODS

We developed a novel prognostic signature including six CCGs was developed by LASSO Cox regression. CIBERSORT, quanTIseq, and ssGSEA algorithms were used to investigated the correlation between the CCG signature and immune cell infiltration. We also assessed the performance of the CCG signature predicting immunotherapy, sorafenib treatment and TACE treatment with independent clinical mRNA sequencing data.

RESULTS

The area under the curve (AUC) of the CCG signature for predicting 1-, 3-, and 5-year OS was 0.77, 0.70 and 0.70 in the learning cohort, respectively. In the external verification cohort, the AUCs of the CCG signature were 0.71, 0.74 and 0.75. The CCG signature was significantly positively related to both TMB and MSI. In addition, responders had a significantly higher risk score than nonresponders when the signature was applied in urothelial cancer patients with immunotherapy, and the AUC of the CCG signature for predicting the response was 0.65. We further found that responders had a significantly lower risk score than nonresponders in the sorafenib and TACE treatment cohorts, and the AUCs of the CCG signature for predicting the response were 0.87 and 0.76, respectively. Finally, we identified four small molecule compounds negatively related to differentially expressed genes (DEGs) between the two categories of HCC patients, including monensin, etiocholanolone, naringenin, and Prestwick-1103.

CONCLUSIONS

The CCG signature has some clinical significance that may enhance HCC patient outcomes and even help develop novel strategies for HCC patient management.

TBK1 Targeting Is Identified as a Therapeutic Strategy to Enhance CAR T-Cell Efficacy Using Patient-Derived Organotypic Tumor Spheroids

Novel therapeutic strategies are needed to improve the efficacy of chimeric antigen receptor (CAR) T cells as a treatment of solid tumors. Multiple tumor microenvironmental factors are thought to contribute to resistance to CAR T-cell therapy in solid tumors, and appropriate model systems to identify and examine these factors using clinically relevant biospecimens are limited. In this study, we examined the activity of B7-H3-directed CAR T cells (B7-H3.CAR-T) using 3D microfluidic cultures of patient-derived organotypic tumor spheroids (PDOTS) and then confirmed the activity of B7-H3.CAR T cells in PDOTS. Although B7-H3 expression in PDOTS was associated with B7-H3.CAR-T sensitivity, mechanistic studies revealed dynamic upregulation of co-inhibitory receptors on CAR T-cells following target cell encounter that led to CAR T-cell dysfunction and limited efficacy against B7-H3-expressing tumors. PD-1 blockade restored CAR T-cell activity in monotypic and organotypic tumor spheroids with improved tumor control and upregulation of effector cytokines. Given the emerging role of TANK-binding kinase 1 (TBK1) as an immune evasion gene, we examined the effect of TBK1 inhibition on CAR T-cell efficacy. Similar to PD-1 blockade, TBK1 inhibition restored CAR T-cell activity in monotypic and organotypic tumor spheroids, prevented CAR T-cell dysfunction, and enhanced CAR T-cell proliferation. Inhibition or deletion of TBK1 also enhanced the sensitivity of cancer cells to immune-mediated killing. Taken together, our results demonstrate the feasibility and utility of ex vivo profiling of CAR T cells using PDOTS and suggest that targeting TBK1 could be used to enhance CAR T-cell efficacy by overcoming tumor-intrinsic and -extrinsic resistance mechanisms.

A Distinguished Roadmap of Fibroblast Senescence in Predicting Immunotherapy Response and Prognosis Across Human Cancers

The resistance of tumors to immune checkpoint inhibitors (ICI) may be intricately linked to cellular senescence, although definitive clinical validation remains elusive. In this study, comprehensive pan-cancer scRNA-seq analyses identify fibroblasts as exhibiting the most pronounced levels of cellular senescence among tumor-associated cell populations. To elucidate this phenomenon, a fibroblast senescence-associated transcriptomic signature (FSS), which correlated strongly with protumorigenic signaling pathways and immune dysregulation that fosters tumor progression, is developed. Leveraging the FSS, the machine learning (ML) framework demonstrates exceptional accuracy in predicting ICI response and survival outcomes, achieving superior area under curve (AUC) values across validation, testing, and in-house cohorts. Strikingly, FSS consistently outperforms established signatures in predictive robustness across diverse cancer subtypes. From an integrative analysis of 17 CRISPR/Cas9 libraries, CDC6 emerges as a pivotal biomarker for pan-cancer ICI response and prognostic stratification. Mechanistically, experimental evidence reveals that CDC6 in tumor cells orchestrates fibroblast senescence via TGF-β1 secretion and oxidative stress, subsequently reprogramming the tumor microenvironment and modulating ICI response. These findings underscore the translational potential of targeting fibroblast senescence as a novel therapeutic strategy to mitigate immune resistance and enhance antitumor efficacy.

ADARp110 promotes hepatocellular carcinoma progression via stabilization of CD24 mRNA

ADAR is highly expressed and correlated with poor prognosis in hepatocellular carcinoma (HCC), yet the role of its constitutive isoform ADARp110 in tumorigenesis remains elusive. We investigated the role of ADARp110 in HCC and underlying mechanisms using clinical samples, a hepatocyte-specific Adarp110 knock-in mouse model, and engineered cell lines. ADARp110 is overexpressed and associated with poor survival in both human and mouse HCC. It creates an immunosuppressive microenvironment by inhibiting total immune cells, particularly cytotoxic GZMB+CD8+ T cells infiltration, while augmenting Treg cells, MDSCs, and exhausted CD8+ T cells ratios. Mechanistically, ADARp110 interacts with SNRPD3 and RNPS1 to stabilize CD24 mRNA by inhibiting STAU1-mediated mRNA decay. CD24 protects HCC cells from two indispensable mechanisms: macrophage phagocytosis and oxidative stress. Genetic knockdown or monoclonal antibody treatment of CD24 inhibits ADARp110-overexpressing tumor growth. Our findings unveil different mechanisms for ADARp110 modulation of tumor immune microenvironment and identify CD24 as a promising therapeutic target for HCCs.

Nanomaterial-enabled metabolic reprogramming strategies for boosting antitumor immunity

Immunotherapy has become a crucial strategy in cancer treatment, but its effectiveness is often constrained. Most cancer immunotherapies focus on stimulating T-cell-mediated immunity by driving the cancer-immunity cycle, which includes tumor antigen release, antigen presentation, T cell activation, infiltration, and tumor cell killing. However, metabolism reprogramming in the tumor microenvironment (TME) supports the viability of cancer cells and inhibits the function of immune cells within this cycle, presenting clinical challenges. The distinct metabolic needs of tumor cells and immune cells require precise and selective metabolic interventions to maximize therapeutic outcomes while minimizing adverse effects. Recent advances in nanotherapeutics offer a promising approach to target tumor metabolism reprogramming and enhance the cancer-immunity cycle through tailored metabolic modulation. In this review, we explore cutting-edge nanomaterial strategies for modulating tumor metabolism to improve therapeutic outcomes. We review the design principles of nanoplatforms for immunometabolic modulation, key metabolic pathways and their regulation, recent advances in targeting these pathways for the cancer-immunity cycle enhancement, and future prospects for next-generation metabolic nanomodulators in cancer immunotherapy. We expect that emerging immunometabolic modulatory nanotechnology will establish a new frontier in cancer immunotherapy in the near future.

Evolutionary trajectories of immune escape across cancers

Immune escape is a critical hallmark of cancer progression and underlies resistance to multiple immunotherapies. However, it remains unclear when the genetic events associated with immune escape occur during cancer development. Here, we integrate functional genomics studies of immunomodulatory genes with a tumor evolution reconstruction approach to infer the evolution of immune escape across 38 cancer types from the Pan-Cancer Analysis of Whole Genomes dataset. Different cancers favor mutations in different immunomodulatory pathways. For example, the antigen presentation machinery is highly mutated in colorectal adenocarcinoma, lung squamous cell carcinoma, and chromophobe renal cell carcinoma, and the protein methylation pathway is highly mutated in bladder transitional cell carcinoma and lung adenocarcinoma. We also observe different timing patterns in multiple immunomodulatory pathways. For instance, mutations impacting genes involved in cellular amino acid metabolism were more likely to happen late in pancreatic adenocarcinoma. Mutations in the glucocorticoid receptor regulatory network pathway tended to occur early, while mutations in the TNF pathways were more likely to occur late in B-cell non-Hodgkin lymphoma. Mutations in the NOD1/2 signaling pathway and DNA binding transcription factor activity tended to happen late in breast adenocarcinoma and ovarian adenocarcinoma. Together, these results delineate the evolutionary trajectories of immune escape in different cancer types and highlight opportunities for improved immunotherapy of cancer.

Multiplexed inhibition of immunosuppressive genes with Cas13d for combinatorial cancer immunotherapy

The complex nature of the immunosuppressive tumor microenvironment (TME) requires multi-agent combinations for optimal immunotherapy. Here we describe multiplex universal combinatorial immunotherapy via gene silencing (MUCIG), which uses CRISPR-Cas13d to silence multiple endogenous immunosuppressive genes in the TME, promoting TME remodeling and enhancing antitumor immunity. MUCIG vectors targeting four genes delivered by adeno-associated virus (AAV) (Cd274/Pdl1, Lgals9/Galectin9, Lgals3/Galectin3 and Cd47; AAV-Cas13d-PGGC) demonstrate significant antitumor efficacy across multiple syngeneic tumor models, remodeling the TME by increasing CD8+ T-cell infiltration while reducing neutrophils. Whole transcriptome profiling validates the on-target knockdown of the four target genes and shows limited potential off-target or downstream gene alterations. AAV-Cas13d-PGGC outperforms corresponding shRNA treatments and individual gene knockdown. We further optimize MUCIG by employing high-fidelity Cas13d (hfCas13d), which similarly showed potent gene silencing and in vivo antitumor efficacy, without weight loss or liver toxicity. MUCIG represents a universal method to silence multiple immune genes in vivo in a programmable manner, offering broad efficacy across multiple tumor types.

Molecular subtype of gastric cancer based on apoptosis-related genes reveals differential immune microenvironment and intratumoral microorganisms distribution

BACKGROUND

Gastric cancer (GC) is known for its high heterogeneity, presenting challenges in current clinical treatment strategies. Accurate subtyping and in-depth analysis of the molecular heterogeneity of GC at the molecular level are still not fully understood.

METHODS

This study categorized GC into two subtypes based on apoptosis-related genes (ARGs) and investigated differences in tumor immune microenvironment, intratumoral microorganisms distribution, gene expression, and signaling pathways. Key prognostic genes related to apoptosis in GC were identified through random survival forest analysis, and their specific signaling mechanisms were explored. Expression levels of key genes were validated through PCR in paired GC tissues and cancer cell lines. Moreover, biological functions of these key genes were verified in vitro experiments.

RESULTS

A consistent clustering of GC was conducted using 161 apoptosis-related genes (ARGs), resulting in the identification of two subtypes, C1 and C2. Subsequently, significant differences were found in the tumor immune microenvironment, intratumoral microorganisms, gene expression, signaling pathways, and protein interaction networks between the two subtypes. GPX3, PLAT, and CAV1 were identified as key prognostic genes related to apoptosis in GC, with a focus on their impact on disease progression-related pathways. Furthermore, PCR assays validated that these three key genes exhibited significantly low expression levels in both GC cell lines and tissues. Finally, knocking down key genes expression significantly promoted cell proliferation, colony formation and invasion of GC.

CONCLUSIONS

Our study conducted a comprehensive analysis of the molecular characteristics of ARGs in GC, revealed their association with the tumor immune microenvironment and intratumoral microorganisms. These findings provide new ideas for the molecular classification of GC.

Remodelling of the immune landscape by IFNγ counteracts IFNγ-dependent tumour escape in mouse tumour models

Loss of IFNγ-sensitivity by tumours is thought to be a mechanism enabling evasion, but recent studies suggest that IFNγ-resistant tumours can be sensitised for immunotherapy, yet the underlying mechanism remains unclear. Here, we show that IFNγ receptor-deficient B16-F10 mouse melanoma tumours are controlled as efficiently as WT tumours despite their lower MHC class I expression. Mechanistically, IFNγ receptor deletion in B16-F10 tumours increases IFNγ availability, triggering a remodelling of the immune landscape characterised by inflammatory monocyte infiltration and the generation of 'mono-macs'. This altered myeloid compartment synergises with an increase in antigen-specific CD8+ T cells to promote anti-tumour immunity against IFNγ receptor-deficient tumours, with such an immune crosstalk observed around blood vessels. Importantly, analysis of transcriptomic datasets suggests that similar immune remodelling occurs in human tumours carrying mutations in the IFNγ pathway. Our work thus serves mechanistic insight for the crosstalk between tumour IFNγ resistance and anti-tumour immunity, and implicates this regulation for future cancer therapy.

Network Medicine-Based Strategy Identifies Maprotiline as a Repurposable Drug by Inhibiting PD-L1 Expression via Targeting SPOP in Cancer

Immune checkpoint inhibitors (ICIs) are drugs that inhibit immune checkpoint (ICP) molecules to restore the antitumor activity of immune cells and eliminate tumor cells. Due to the limitations and certain side effects of current ICIs, such as programmed death protein-1, programmed cell death-ligand 1, and cytotoxic T lymphocyte-associated antigen 4 (CTLA4) antibodies, there is an urgent need to find new drugs with ICP inhibitory effects. In this study, a network-based computational framework called multi-network algorithm-driven drug repositioning targeting ICP (Mnet-DRI) is developed to accurately repurpose novel ICIs from ≈3000 Food and Drug Administration-approved or investigational drugs. By applying Mnet-DRI to PD-L1, maprotiline (MAP), an antidepressant drug is repurposed, as a potential PD-L1 modifier for colorectal and lung cancers. Experimental validation revealed that MAP reduced PD-L1 expression by targeting E3 ubiquitin ligase speckle-type zinc finger structural protein (SPOP), and the combination of MAP and anti-CTLA4 in vivo significantly enhanced the antitumor effect, providing a new alternative for the clinical treatment of colorectal and lung cancer.

Overcoming Resistance Mechanisms to Melanoma Immunotherapy

The advent of immune checkpoint inhibition has revolutionized treatment of advanced melanoma. While most patients derive survival benefit from established immunotherapies, notably monoclonal antibodies blocking cytotoxic T-lymphocyte antigen 4 and programmed cell death protein 1, a subset does not optimally respond due to the manifestation of innate or acquired resistance to these therapies. Combination regimens have proven efficacious relative to single-agent blockade, but also yield high-grade treatment toxicities that are often dose-limiting for patients. In this review, we discuss the significant strides made in the past half-decade toward expanding the melanoma immunotherapy treatment paradigm. These include newly approved therapies, adoption of neoadjuvant immunotherapy, and studies in the clinical trials pipeline targeting alternative immune checkpoints and key immunoregulatory molecules. We then review how developments in molecular and functional diagnostics have furthered our understanding of the tumor-intrinsic and -extrinsic mechanisms driving immunotherapy resistance, as well as highlight novel biomarkers for predicting treatment response. Throughout, we discuss potential approaches for targeting these resistance mechanisms in rational combination with established immunotherapies to improve outcomes for patients with melanoma.

Prognostic assessment value of immune escape-related genes in patients with acute myeloid leukemia

This study explores the prognostic value of immune escape-related genes in acute myeloid leukemia (AML) patients. Using TARGET_AML and GSE37642 datasets, we identified CEP55, DNAJC13, and EMC2 as significant prognostic indicators, with high transcript abundance correlating with poor outcomes. Consensus clustering divided patients into two groups, with Cluster 1 showing worse prognosis. A prognostic signature based on these genes stratified patients into high- and low-risk groups, with the high-risk group experiencing worse outcomes. The risk score was an independent prognostic factor. Functional analysis revealed that high-risk genes could promote cell cycle progression. The selected genes were strongly associated with immune cells, particularly mast cells and CD8+ T cells. This study enriches the prognostic evaluation system for AML and suggests a new therapeutic direction.

Cytokine-armed pyroptosis induces antitumor immunity against diverse types of tumors

Inflammasomes are defense complexes that utilize cytokines and immunogenic cell death (ICD) to stimulate the immune system against pathogens. Inspired by their dual action, we present cytokine-armed pyroptosis as a strategy for boosting immune response against diverse types of tumors. To induce pyroptosis, we utilize designed tightly regulated gasdermin D variants comprising different pore-forming capabilities and diverse modes of activation, representing a toolbox of ICD inducers. We demonstrate that the electrogenic transfer of ICD effector-encoding plasmids into mouse melanoma tumors when combined with intratumoral expression of cytokines IL-1β, IL-12, or IL-18, enhanced anti-tumor immune responses. Careful selection of immunostimulatory molecules is, however, imperative as a combination of IL-1β and IL-18 antagonized the protective effect of pyroptosis by IFNγ-mediated upregulation of several immunosuppressive pathways. Additionally, we show that the intratumoral introduction of armed pyroptosis provides protection against distant tumors and proves effective across various tumor types without inducing systemic inflammation. Deconstructed inflammasomes thus serve as a powerful, tunable, and tumor-agnostic strategy to enhance antitumor response, even against the most resilient types of tumors.

Prognostic significance of immune evasion-related genes in clear cell renal cell carcinoma immunotherapy

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignancy of the urinary system. Despite the integration of immune checkpoint inhibitors (ICIs) into the treatment paradigm for advanced RCC, resistance to immunotherapy has emerged as a pivotal determinant impacting the clinical outlook of ccRCC. Accumulating evidence underscores the pivotal role of immune evasion-related genes and pathways in enabling tumor escape from host immune surveillance, consequently influencing patients' responsiveness to immunotherapy. Nonetheless, the clinical relevance of immune evasion-related genes in ccRCC patients undergoing immunotherapy remains inadequately understood. In this study, we aggregated RNA sequencing and clinical data from ccRCC patients across three cohorts: the Cancer Genome Atlas (TCGA), CheckMate cohorts, and the JAVELIN Renal 101 trial. Leveraging a curated immune evasion-related gene set from Lawson et al., we employed the LASSO algorithm and Cox regression analysis to identify eight genes (LPAR6, RGS5, NFYC, PCDH17, CENPW, CNOT8, FOXO3, SNRPB) significantly associated with immune therapy prognosis (HR, 3.57; 95 % CI, 2.38-5.35; P<0.001). A predictive algorithm developed utilizing these genes exhibited notable accuracy in forecasting patients' progression-free survival in the training set (AUC, 0.835). Furthermore, stratification of patients by risk score revealed discernible differences in immunotherapy response and tumor microenvironment. In summary, we present a prognostic model intricately linked with immune status and treatment response. For ccRCC patients undergoing immunotherapy, this approach holds promise in aiding clinical decision-making by providing more precise and tailored treatment recommendations.

Leveraging CRISPR gene editing technology to optimize the efficacy, safety and accessibility of CAR T-cell therapy

Chimeric Antigen Receptor (CAR)-T-cell therapy has revolutionized cancer immune therapy. However, challenges remain including increasing efficacy, reducing adverse events and increasing accessibility. Use of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology can effectively perform various functions such as precise integration, multi-gene editing, and genome-wide functional regulation. Additionally, CRISPR screening using large-scale guide RNA (gRNA) genetic perturbation provides an unbiased approach to understanding mechanisms underlying anti-cancer efficacy of CAR T-cells. Several emerging CRISPR tools with high specificity, controllability and efficiency are useful to modify CAR T-cells and identify new targets. In this review we summarize potential uses of the CRISPR system to improve results of CAR T-cells therapy including optimizing efficacy and safety and, developing universal CAR T-cells. We discuss challenges facing CRISPR gene editing and propose solutions highlighting future research directions in CAR T-cell therapy.

Intracellular zinc protects tumours from T cell-mediated cytotoxicity

Tumour immune evasion presents a significant challenge to the effectiveness of cancer immunotherapies. Recent advances in high-throughput screening techniques have uncovered that loss of antigen presentation and cytokine signalling pathways are central mechanisms by which tumours evade T cell immunity. To uncover additional vulnerabilities in tumour cells beyond the well-recognized antigen presentation pathway, we conducted a genome-wide CRISPR/Cas9 screen to identify genes that mediate resistance to chimeric-antigen receptor (CAR)-T cells, which function independently of classical antigen presentation. Our study revealed that loss of core-binding factor subunit beta (CBFβ) enhances tumour cell resistance to T cell killing, mediated through T cell-derived TNF. Mechanistically, RNA-sequencing and elemental analyses revealed that deletion of CBFβ disrupts numerous pathways including those involved in zinc homoeostasis. Moreover, we demonstrated that modulation of cellular zinc, achieved by supplementation or chelation, significantly altered tumour cell susceptibility to TNF by regulating the levels of inhibitor of apoptosis proteins. Consistent with this, treatment of tumour cells with a membrane-permeable zinc chelator had no impact on tumour cell viability alone, but significantly increased tumour cell lysis by CD8+ T cells in a TNF-dependent but perforin-independent manner. These results underscore the crucial role of intracellular zinc in regulating tumour cell susceptibility to T cell-mediated killing, revealing a novel vulnerability in tumour cells that might be exploited for the development of future cancer immunotherapeutics.

Functional profiling of murine glioma models highlights targetable immune evasion phenotypes

Cancer-intrinsic immune evasion mechanisms and pleiotropy are a barrier to cancer immunotherapy. This is apparent in certain highly fatal cancers, including high-grade gliomas and glioblastomas (GBM). In this study, we evaluated two murine syngeneic glioma models (GL261 and CT2A) as preclinical models for human GBM using functional genetic screens, single-cell transcriptomics and machine learning approaches. Through CRISPR genome-wide co-culture killing screens with various immune cells (cytotoxic T cells, natural killer cells, and macrophages), we identified three key cancer-intrinsic evasion mechanisms: NFκB signaling, autophagy/endosome machinery, and chromatin remodeling. Additional fitness screens identified dependencies in murine gliomas that partially recapitulated those seen in human GBM (e.g., UFMylation). Our single-cell analyses showed that different glioma models exhibited distinct immune infiltration patterns and recapitulated key immune gene programs observed in human GBM, including hypoxia, interferon, and TNF signaling. Moreover, in vivo orthotopic tumor engraftment was associated with phenotypic shifts and changes in proliferative capacity, with murine tumors recapitulating the intratumoral heterogeneity observed in human GBM, exhibiting propensities for developmental- and mesenchymal-like phenotypes. Notably, we observed common transcription factors and cofactors shared with human GBM, including developmental (Nfia and Tcf4), mesenchymal (Prrx1 and Wwtr1), as well as cycling-associated genes (Bub3, Cenpa, Bard1, Brca1, and Mis18bp1). Perturbation of these genes led to reciprocal phenotypic shifts suggesting intrinsic feedback mechanisms that balance in vivo cellular states. Finally, we used a machine-learning approach to identify two distinct immune evasion gene programs, one of which represents a clinically-relevant phenotype and delineates a subpopulation of stem-like glioma cells that predict response to immune checkpoint inhibition in human patients. This comprehensive characterization helps bridge the gap between murine glioma models and human GBM, providing valuable insights for future therapeutic development.

Genome-aware annotation of CRISPR guides validates targets in variant cell lines and enhances discovery in screens

BACKGROUND

CRISPR-Cas9 technology has revolutionised genetic screens and can inform on gene essentiality and chemo-genetic interactions. It is easily deployed and widely supported with many pooled CRISPR libraries available commercially. However, discrepancies between the reference genomes used in the design of those CRISPR libraries and the cell line under investigation can lead to loss of signal or introduction of bias. The problem is particularly acute when dealing with variant cell lines such as cancer cell lines.

RESULTS

Here, we present an algorithm, EXOme-guided Re-annotation of nuCleotIde SEquences (Exorcise), which uses sequence search to detect and correct mis-annotations in CRISPR libraries. Exorcise verifies the presence of CRISPR targets in the target genome and applies corrections to CRISPR libraries using existing exome annotations. We applied Exorcise to re-annotate guides in pooled CRISPR libraries available on Addgene and found that libraries designed on a more permissive reference sequence had more mis-annotations. In simulated CRISPR screens, we modelled common mis-annotations and found that they adversely affect discovery of hits in the intermediate range. We then confirmed this by applying Exorcise on datasets from Dependency Map (DepMap) and the DNA Damage Response CRISPR Screen Viewer (DDRcs), where we found improved discovery power upon Exorcise while retaining the strongest hits.

CONCLUSIONS

Pooled CRISPR libraries map guide sequences to genes and these mappings might not be ready to use due to permissive library design or investigating a variant cell line. By re-annotating CRISPR guides, Exorcise focuses CRISPR experiments towards the genome of the cell line under investigation. Exorcise can be applied at the library design stage or the analysis stage and allows post hoc re-analysis of completed screens. It is available under a Creative Commons Zero v1.0 Universal licence at https://github.com/SimonLammmm/exorcise .

The hallmarks of cancer immune evasion

According to the widely accepted "three Es" model, the host immune system eliminates malignant cell precursors and contains microscopic neoplasms in a dynamic equilibrium, preventing cancer outgrowth until neoplastic cells acquire genetic or epigenetic alterations that enable immune escape. This immunoevasive phenotype originates from various mechanisms that can be classified under a novel "three Cs" conceptual framework: (1) camouflage, which hides cancer cells from immune recognition, (2) coercion, which directly or indirectly interferes with immune effector cells, and (3) cytoprotection, which shields malignant cells from immune cytotoxicity. Blocking the ability of neoplastic cells to evade the host immune system is crucial for increasing the efficacy of modern immunotherapy and conventional therapeutic strategies that ultimately activate anticancer immunosurveillance. Here, we review key hallmarks of cancer immune evasion under the "three Cs" framework and discuss promising strategies targeting such immunoevasive mechanisms.

TMED inhibition suppresses cell surface PD-1 expression and overcomes T cell dysfunction

BACKGROUND

Blockade of the programmed cell death protein 1 (PD-1) immune checkpoint (ICB) is revolutionizing cancer therapy, but little is known about the mechanisms governing its expression on CD8 T cells. Because PD-1 is induced during activation of T cells, we set out to uncover regulators whose inhibition suppresses PD-1 abundance without adversely impacting on T cell activation.

METHODS

To identify PD-1 regulators in an unbiased fashion, we performed a whole-genome, fluorescence-activated cell sorting (FACS)-based CRISPR-Cas9 screen in primary murine CD8 T cells. A dual-readout design using the activation marker CD137 allowed us to uncouple genes involved in PD-1 regulation from those governing general T cell activation.

RESULTS

We found that the inactivation of one of several members of the TMED/EMP24/GP25L/p24 family of transport proteins, most prominently TMED10, reduced PD-1 cell surface abundance, thereby augmenting T cell activity. Another client protein was cytotoxic T lymphocyte-associated protein 4 (CTLA-4), which was also suppressed by TMED inactivation. Treatment with TMED inhibitor AGN192403 led to lysosomal degradation of the TMED-PD-1 complex and reduced PD-1 abundance in tumor-infiltrating CD8 T cells (TIL) in mice, thus reversing T cell dysfunction. Clinically corroborating these findings, single-cell RNA analyses revealed a positive correlation between TMED expression in CD8 TIL, and both a T cell dysfunction signature and lack of ICB response. Similarly, patients receiving a TIL product with high TMED expression had a shorter overall survival.

CONCLUSION

Our results uncover a novel mechanism of PD-1 regulation, and identify a pharmacologically tractable target whose inhibition suppresses PD-1 abundance and T cell dysfunction.

Anti-Cancer Strategy Based on Changes in the Role of Autophagy Depending on the Survival Environment and Tumorigenesis Stages

Autophagy is a crucial mechanism for recycling intracellular materials, and under normal metabolic conditions, it is maintained at low levels in cells. However, when nutrients are deficient or under hypoxic conditions, the level of autophagy significantly increases. Particularly in cancer cells, which grow more rapidly than normal cells and tend to grow in a three-dimensional manner, cells inside the cell mass often face limited oxygen supply, leading to inherently higher levels of autophagy. Therefore, the initial development of anticancer drugs targeting autophagy was based on a strategy to suppress these high levels of autophagy. However, anticancer drugs that inhibit autophagy have not shown promising results in clinical trials, as it has been revealed that autophagy does not always play a role that favors cancer cell survival. Hence, this review aims to suggest anticancer strategies based on the changes in the role of autophagy according to survival conditions and tumorigenesis stage.

A multi-subunit autophagic capture complex facilitates degradation of ER stalled MHC-I in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDA) evades immune detection partly via autophagic capture and lysosomal degradation of major histocompatibility complex class I (MHC-I). Why MHC-I is susceptible to capture via autophagy remains unclear. By synchronizing exit of proteins from the endoplasmic reticulum (ER), we show that PDAC cells display prolonged retention of MHC-I in the ER and fail to efficiently route it to the plasma membrane. A capture-complex composed of NBR1 and the ER-phagy receptor TEX264 facilitates targeting of MHC-I for autophagic degradation, and suppression of either receptor is sufficient to increase total levels and re-route MHC-I to the plasma membrane. Binding of MHC-I to the capture complex is linked to antigen presentation efficiency, as inhibiting antigen loading via knockdown of TAP1 or beta 2-Microglobulin led to increased binding between MHC-I and the TEX264-NBR1 capture complex. Conversely, expression of ER directed high affinity antigenic peptides led to increased MHC-I at the cell surface and reduced lysosomal degradation. A genome-wide CRISPRi screen identified NFXL1, as an ER-resident E3 ligase that binds to MHC-I and mediates its autophagic capture. High levels of NFXL1 are negatively correlated with MHC-I protein expression and predicts poor patient prognosis. These data highlight an ER resident capture complex tasked with sequestration and degradation of non-conformational MHC-I in PDAC cells, and targeting this complex has the potential to increase PDAC immunogenicity.

Establishment and Verification of a Novel Gene Signature Connecting Hypoxia and Lactylation for Predicting Prognosis and Immunotherapy of Pancreatic Ductal Adenocarcinoma Patients by Integrating Multi-Machine Learning and Single-Cell Analysis

Pancreatic ductal adenocarcinoma (PDAC) has earned a notorious reputation as one of the most formidable and deadliest malignant tumors. Within the tumor microenvironment, cancer cells have acquired the capability to maintain incessant expansion and increased proliferation in response to hypoxia via metabolic reconfiguration, leading to elevated levels of lactate within the tumor surroundings. However, there have been limited studies specifically investigating the association between hypoxia and lactic acid metabolism-related lactylation in PDAC. In this study, multiple machine learning approaches, including LASSO regression analysis, XGBoost, and Random Forest, were employed to identify hub genes and construct a prognostic risk signature. The implementation of the CERES score and single-cell analysis was used to discern a prospective therapeutic target for the management of PDAC. CCK8 assay, colony formation assays, transwell, and wound-healing assays were used to explore both the proliferation and migration of PDAC cells affected by CENPA. In conclusion, we discovered two distinct subtypes characterized by their unique hypoxia and lactylation profiles and developed a risk score to evaluate prognosis, as well as response to immunotherapy and chemotherapy, in PDAC patients. Furthermore, we indicated that CENPA may serve as a promising therapeutic target for PDAC.

Genomic instability as a driver and suppressor of anti-tumor immunity

Genomic instability is a driver and accelerator of tumorigenesis and influences disease outcomes across cancer types. Although genomic instability has been associated with immune evasion and worsened disease prognosis, emerging evidence shows that genomic instability instigates pro-inflammatory signaling and enhances the immunogenicity of tumor cells, making them more susceptible to immune recognition. While this paradoxical role of genomic instability in cancer is complex and likely context-dependent, understanding it is essential for improving the success rates of cancer immunotherapy. In this review, we provide an overview of the underlying mechanisms that link genomic instability to pro-inflammatory signaling and increased immune surveillance in the context of cancer, as well as discuss how genomically unstable tumors evade the immune system. A better understanding of the molecular crosstalk between genomic instability, inflammatory signaling, and immune surveillance could guide the exploitation of immunotherapeutic vulnerabilities in cancer.

Identification and validation of an m7G-related lncRNAs signature for predicting prognosis, immune response and therapy landscapes in ovarian cancer

Background

Ovarian cancer is the most mortality malignancy in gynecology. N7-methylguanosine (m7G) is one of the most prevalent RNA modifications in the development and progression of cancer. The aim of this study is to investigate the effect of m7G-related lncRNA on ovarian cancer in terms of instruction prognosis and immunotherapy.

Methods

After integrating and processing the RNA expression profiles with the clinical sample information in the TCGA database, we initially screened to the m7G-related lncRNAs by Spearman correlation analysis, and subsequently obtained a prognostic model constructed by five m7G-related lncRNAs with Univariate Cox analysis, LASSO regression analysis, and Multivariate Cox regression analysis, after which we further evaluated and validated the prognostic value of the model using Kaplan-Meier survival analysis, Principal component analysis, Nomogram, and ROC curve. In addition, based on this risk model, we explored the differentially enriched pathways and functions of the high and low risk groups, and characterized the immune cells, immune functions, gene mutations, and drug sensitivity between the two groups.

Results

After a series of rigorous filtering, we finally attained a prognostic risk model consisting of KRT7-AS, USP30-AS1, ZFHX4-AS1, ACAP2-IT1, and TWSG1-DT which is excellent in predicting the prognostic survival of ovarian cancer patients as well as existing as an independent prognostic factor. Moreover, the model has certain relevance in the immune cells and functions between high and low risk groups, and simultaneously, the signature has the role of guiding the option of immunotherapy and chemotherapeutic drugs.

Conclusion

Altogether, our study established a tight connection between m7G-associated lncRNAs and ovarian cancer, with potential that the prognostic patterns contribute to steering the prognosis of ovarian cancer patients, measuring the efficacy of immunotherapeutic approaches, and detecting effective chemotherapeutic agents.

Mapping spatial organization and genetic cell-state regulators to target immune evasion in ovarian cancer

The drivers of immune evasion are not entirely clear, limiting the success of cancer immunotherapies. Here we applied single-cell spatial and perturbational transcriptomics to delineate immune evasion in high-grade serous tubo-ovarian cancer. To this end, we first mapped the spatial organization of high-grade serous tubo-ovarian cancer by profiling more than 2.5 million cells in situ in 130 tumors from 94 patients. This revealed a malignant cell state that reflects tumor genetics and is predictive of T cell and natural killer cell infiltration levels and response to immune checkpoint blockade. We then performed Perturb-seq screens and identified genetic perturbations-including knockout of PTPN1 and ACTR8-that trigger this malignant cell state. Finally, we show that these perturbations, as well as a PTPN1/PTPN2 inhibitor, sensitize ovarian cancer cells to T cell and natural killer cell cytotoxicity, as predicted. This study thus identifies ways to study and target immune evasion by linking genetic variation, cell-state regulators and spatial biology.

Mechanism of TBK1 activation in cancer cells

TANK-binding kinase 1 (TBK1) is a serine/threonine kinase with well-established roles as a central player in innate immune signaling. Dysregulation of TBK1 activity has been implicated in a variety of pathophysiologic conditions, including cancer. Generally, TBK1 acts as an oncogene and increased TBK1 activity, indicated by increased phosphorylation at the Ser172 residue, can be observed in multiple human cancers. TBK1 can be activated either by autophosphorylation of Ser172 or transphosphorylation at this site by upstream kinases. Serving as a hub for integrating numerous extracellular and intracellular signals, TBK1 can be activated through multiple signaling pathways. However, the direct upstream kinase responsible for TBK1 activation remains elusive, which limits our comprehensive understanding of its activation mechanism and potential therapeutic application targeting TBK1-related signaling especially in cancer. In this review, we summarize the findings on mechanisms of TBK1 activation in cancer cells and recent discoveries that shed light on the direct upstream kinases promoting TBK1 activation.

The emerging role of fat-inducing transcript 2 in endoplasmic reticulum proteostasis and lipoprotein biogenesis

PURPOSE OF REVIEW

This review examines the evolving role of the fat-inducing transcript 2 (FIT2) protein in lipid droplet (LD) biology and its broader implications in cellular physiology and disease. With recent advancements in understanding FIT2 function across various model systems, this review provides a timely synthesis of its mechanisms and physiological significance.

RECENT FINDINGS

FIT2, an endoplasmic reticulum (ER)-resident protein, has been established as a critical regulator of LD formation in diverse organisms, from yeast to mammals. It facilitates LD biogenesis by sequestering diacylglycerol (DAG) and potentially influencing ER membrane dynamics. Beyond its role in lipid metabolism, FIT2 intersects with the ER-associated degradation (ERAD), is critical for protein homeostasis, and is linked to the unfolded protein response (UPR). Dysregulation of FIT2 has also been linked to metabolic disorders such as insulin resistance and lipodystrophy, highlighting its clinical relevance.

SUMMARY

Insights into FIT2 function underscore its pivotal role in LD formation and lipid homeostasis. Understanding its involvement in ER proteostasis and very low density lipoprotein biogenesis has broad implications for metabolic diseases and cancer. Therapeutic strategies targeting FIT2 may offer novel approaches to modulate lipid metabolism and mitigate associated pathologies. Further research is needed to elucidate the full spectrum of FIT2's interactions within cellular lipid and protein networks, potentially uncovering new therapeutic avenues for metabolic and ER stress-related disorders.

Advances in the prerequisite and consequence of STING downstream signalosomes

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway is an evolving DNA-sensing mechanism involved in innate immunity and pathogen defense that has been optimized while remaining conserved. Aside from recognizing pathogens through conserved motifs, these receptors also detect aberrant or misplaced self-molecules as possible signs of perturbed homeostasis. Upon binding external or self-derived DNA, a mobile secondary messenger 2'3'-cyclic GMP-AMP (cGAMP) is produced by cGAS and in turn activates its adapter STING in the endoplasmic reticulum (ER). Resting-state or activated STING protein is finely restricted by multiple degradation machineries. The post-translational changes of the STING protein, along with the regulatory machinery of the secret routes, limit the onset, strength and sustention of STING signal. STING experiences a conformational shift and relocates with TBK1 from the ER to perinuclear vesicles containing transcription factors, provoking the transcription activity of IRF3/IFN-I and NF-κB pathways, as well as to initiate a number of cellular processes that have been shown to alter the immune landscape in cancer, such as autophagy, NLRP3 inflammasome, ER stress, and cell death. STING signal thus serves as a potent activator for immune mobilization yet also triggers immune-mediated pathology in tissues. Recent advances have established the vital role of STING in immune surveillance as well as tumorigenic process. This review provides an overview of the disparate outcomes of cancer attributed to the actions of pleiotropic and coordinated STING downstream signalosomes, along with the underlying mechanisms of STING function in pathologies, providing therapeutic implications for new approaches in hunt for the next generation of cancer immunotherapy base on STING.

EPDR1 promotes PD-L1 expression and tumor immune evasion by inhibiting TRIM21-dependent ubiquitylation of IkappaB kinase-β

While immune checkpoint blockade (ICB) has shown promise for clinical cancer therapy, its efficacy has only been observed in a limited subset of patients and the underlying mechanisms regulating innate and acquired resistance to ICB of tumor cells remain poorly understood. Here, we identified ependymin-related protein 1 (EPDR1) as an important tumor-intrinsic regulator of PD-L1 expression and tumor immune evasion. Aberrant expression of EPDR1 in hepatocellular carcinoma is associated with immunosuppression. Mechanistically, EPDR1 binds to E3 ligase TRIM21 and disrupts its interaction with IkappaB kinase-b, suppressing its ubiquitylation and autophagosomal degradation and enhancing NF-κB-mediated transcriptional activation of PD-L1. Further, we validated through a mouse liver cancer model that EPDR1 mediates exhaustion of CD8+ T cells and promotes tumor progression. In addition, we observed a positive correlation between EPDR1 and PD-L1 expression in both human and mouse liver cancer samples. Collectively, our study reveals a previously unappreciated role of EPDR1 in orchestrating tumor immune evasion and cancer progression.