Pan-cancer adaptive immune resistance as defined by the Tumor Inflammation Signature (TIS): results from The Cancer Genome Atlas (TCGA)

Aberrant PLAC8 expression characterizes glioblastoma with temozolomide resistance and an immunosuppressive microenvironment

Glioblastoma (GBM), Isocitrate Dehydrogenase-wildtype (IDH-WT) represents the most prevalent and clinically aggressive subtype of adult diffuse gliomas, typically associated with poor prognosis. Temozolomide (TMZ) remains the first-line chemotherapeutic agent for GBM; however, the emergence of TMZ resistance represents a major therapeutic obstacle in clinical practice. This study identifies placenta-specific 8 (PLAC8) as a novel mediator of TMZ resistance in IDH-WT GBM. Elevated PLAC8 expression was strongly correlated with poorer survival rates, higher tumor grades in glioma, establishing it as an independent prognostic factor. Notably, consistent upregulation of PLAC8 was observed in both TMZ-resistant GBM cells and TMZ-treated patients, suggesting its potential as a biomarker for TMZ resistance. Mechanistic studies revealed that PLAC8 regulates TMZ sensitivity in GBM cells through the AKT-mTOR signaling pathway. Additionally, integrated bioinformatics and clinical analyses demonstrated that PLAC8 expression positively correlates with immune cell infiltration while promoting an immunosuppressive tumor microenvironment and modulating immunotherapy-related biomarkers, suggesting its potential as a predictive biomarker for immunotherapy response. In conclusion, PLAC8 represents a promising biomarker and therapeutic target for overcoming TMZ resistance and guiding immunotherapy in GBM. This study provides valuable insights for the development of personalized treatment strategies aimed at improving patient outcomes.

Identification of novel biomarkers and prognostic model for neuroblastoma using Mendelian randomization and transcriptomic analysis

BACKGROUND

Neuroblastoma (NB) is the most common extracranial malignant tumor in children, presenting significant challenges in prognosis and treatment stratification. This study aims to identify novel biomarkers for NB and develop a prognostic model using comprehensive analytical methods, including Mendelian randomization (MR) analysis.

METHODS

Utilizing bioinformatics and Mendelian randomization methods, we explored biomarkers associated with neuroblastoma at the mRNA level. We used chip expression data from the GEO database to screen for differentially expressed genes (DEGs) and conducted two-sample MR analysis using expression quantitative trait loci (eQTL) and neuroblastoma data from the IEU database to identify co-expressed genes through colocalization. A relevant prognostic model was constructed using lasso regression based on the co-expressed genes. Furthermore, we confirmed the correlation between high-risk and low-risk groups with the tumor microenvironment and immune cell infiltration. Subsequently, we evaluated the relationship between risk scores and sensitivity to immunotherapy and anti-tumor drugs.

RESULTS

Differential analysis identified 485 downregulated and 349 upregulated genes that play important roles in NB. MR analysis identified 4 significant co-expressed genes associated with NB: CAV2, CTSK, LXN, and NDRG2. GO and KEGG enrichment analyses revealed that these genes are involved in crucial biological processes and pathways. A prognostic model based on these four genes was constructed, and its independence as a prognostic factor was confirmed. NB patients were divided into two different risk score groups, with survival analysis indicating that the high-risk group had poorer overall survival, lower immune infiltration, and poorer immune therapy response. In contrast, the low-risk group showed potential efficacy in immunotherapy and higher sensitivity to anti-tumor drugs.

CONCLUSION

Our findings provide new insights into the molecular basis of NB, identifying four novel biomarkers and developing a risk scoring model based on four co-expressed genes. This model has the potential to become an effective tool for predicting prognosis and guiding treatment in NB patients.

PKCδ Germline Variants and Genetic Deletion in Mice Augment Antitumor Immunity through Regulation of Myeloid Cells

Based on the notion that hypomorphic germline genetic variants are linked to autoimmune diseases, we reasoned that novel targets for cancer immunotherapy might be identified through germline variants associated with greater T-cell infiltration into tumors. Here, we report that while investigating germline polymorphisms associated with a tumor immune gene signature, we identified protein kinase C delta (PKCδ) as a candidate. Genetic deletion of Prkcd in mice resulted in improved endogenous antitumor immunity and increased efficacy of anti-PD-L1. Single-cell RNA sequencing revealed myeloid cell expression of Prkcd, and PKCδ deletion caused a shift in macrophage gene expression from an M2-like to an M1-like phenotype. Conditional deletion of Prkcd in myeloid cells recapitulated improved tumor control that was augmented further with anti-PD-L1. Analysis of clinical samples confirmed an association between PRKCD variants and M1/M2 phenotype, as well as between a PKCδ knockout-like gene signature and clinical benefit from anti-PD-1. Our results identify PKCδ as a candidate therapeutic target that modulates myeloid cell states.

Pan-cancer analysis shapes the understanding of cancer biology and medicine

Advances in multi-omics datasets and analytical methods have revolutionized cancer research, offering a comprehensive, pan-cancer perspective. Pan-cancer studies identify shared mechanisms and unique traits across different cancer types, which are reshaping diagnostic and treatment strategies. However, continued innovation is required to refine these approaches and deepen our understanding of cancer biology and medicine. This review summarized key findings from pan-cancer research and  explored their potential to drive future advancements in oncology.

Mechanosensitive ion channel-related genes in hepatocellular carcinoma: Unraveling prognostic genes and their roles in drug resistance and immune modulation

Background and aims

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, and its etiology involves a complex interplay of genetic and environmental factors. Despite advancements in our understanding of HCC biology and the development of novel therapeutic strategies, the molecular mechanisms underlying its onset, progression, and resistance to therapy remain largely vague. This study aimed to investigate the role of mechanosensitive ion channel-related genes (MICRGs) in HCC, focusing on their potential as prognostic biomarkers and their involvement in immune modulation and drug resistance.

Methods

A comprehensive analysis was conducted using The Cancer Genome Atlas database to identify MICRGs that are upregulated in HCC. Gene expression profiling, bioinformatics tools, and functional experiments were employed to elucidate the role of these channels. In addition, protein-protein interaction (PPI) network analyses and enrichment analyses were performed to explore the biological significance of these genes. An immune cell infiltration analysis was also conducted to understand MICRG-related immune landscape. Single-cell RNA sequencing (scRNA-seq) data were utilized to identify MICRGs in different cell types within the HCC tissue. Deep-learning neural network analysis across patient cohorts was conducted to identify genes associated with sorafenib resistance. Knockdown experiments, cell viability assays, and apoptosis assays on HCC cell lines were performed to examine the role of Piezo-type mechanosensitive ion channel component 1 (PIEZO1) in sorafenib resistance.

Results

The analysis identified a subset of MICRGs, including PIEZO1, that were significantly upregulated in HCC and associated with poor prognosis. The PPI network analysis revealed complex interactions among these genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses proposed the involvement of these genes in calcium signaling pathways. Immune cell infiltration analysis demonstrated distinct associations between MICRGs and various immune subpopulations, highlighting their potential roles in immune modulation. scRNA-seq data indicated the upregulation of MICRGs in various cell types in HCC tissues, particularly in endothelial cells and tumor-associated macrophages. Deep-learning neural network analysis across different patient cohorts identified PIEZO1 as a crucial regulator of sorafenib resistance in HCC, which was further validated by functional assays on HCC cell lines.

Conclusions

This study provides evidence that MICRGs, particularly PIEZO1, take on crucial roles in HCC progression and drug resistance. The upregulation of PIEZO1 in HCC cells is associated with poor prognosis and resistance to sorafenib. These findings indicate that PIEZO1 could serve as a potential therapeutic target for overcoming drug resistance and a prognostic biomarker in HCC. Future studies should focus on validating these findings in larger patient cohorts and exploring the functional implications of targeting PIEZO1 in preclinical models.

Next-Generation Sequencing-Based MSI Scoring Predicts Benefit in Mismatch Repair-Deficient Tumors Treated with Nivolumab: Follow-up on NCI-MATCH Arm Z1D

PURPOSE

Mismatch repair-deficient (dMMR) tumors have demonstrated favorable responses to immune checkpoint inhibition targeting PD-1. However, more in-depth identification of predictors of response could further refine patient selection for immunotherapy treatment.

PATIENTS AND METHODS

We undertook integrated evaluation performed on samples collected from 28 of 42 patients enrolled on the NCI-Molecular Analysis for Therapy Choice arm Z1D trial that evaluated PD-1 inhibition treatment with nivolumab in patients with noncolorectal dMMR tumors. Genomic analyses were performed using next-generation sequencing (NGS), whole-exome sequencing, and RNA sequencing and supplemented by multiplex immunofluorescence performed on tissue samples.

RESULTS

In this dMMR population, more extensive alterations of microsatellites as assessed by measures of NGS were associated with clinical benefit and tumor mutational burden. RNA sequencing further revealed associations between clinical benefit and immune infiltration index. Gene sets enriched in patients with clinical benefit included IFN signaling, antigen processing, and PI3K-AKT-mTOR signaling, whereas hedgehog signaling was found to be enriched in subjects lacking clinical benefit.

CONCLUSIONS

These genomic data highlight the importance of immune infiltration and antigen presentation in dMMR tumors that respond to immune checkpoint blockade. In addition, they suggest that, even within a dMMR population, NGS-based measures of microsatellite instability could serve as biomarkers of immunotherapy response.

Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma

BACKGROUND

Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. While the dysregulation of ERV transcription has been linked to immune cell infiltration in various cancers, its relationship with immune checkpoint inhibitor (ICI) response in solid tumors, particularly metastatic clear-cell renal cell carcinoma (ccRCC), remains inadequately explored.

METHODS

This study analyzed patients with metastatic ccRCC from two prospective clinical trials, encompassing 181 patients receiving nivolumab in the CheckMate trials (-009 to -010 and -025) and 48 patients treated with the ipilimumab-nivolumab combination in the BIONIKK trial. ERV expression was quantified using the ERVmap algorithm from RNA sequencing data. Our primary objective was to correlate ERV expression with progression-free survival, with overall survival and time-to-second-treatment survival as secondary endpoints. We used bootstrap methods with univariate Cox regression on 666 substantially expressed ERVs to evaluate their prognostic significance and stability.

RESULTS

Our analysis centered on two ERVs, E4421_chr17 and E1659_chr4, which consistently exhibited opposing prognostic impacts across both cohorts. We developed a stratification system based on their median expression levels, categorizing patients into four ERV subgroups. These subgroups were further consolidated into a three-tier risk model that significantly correlated with ICI treatment outcomes. The most responsive ERV risk category showed enhanced endothelial cell infiltration, whereas the resistant category was characterized by higher levels of myeloid dendritic cells, regulatory T cells, myeloid-derived suppressor cells, and markers of T-cell exhaustion. Notably, this ERV-based classification outperformed traditional transcriptomic signatures in predicting ICI efficacy and showed further improvement when combined with epigenetic DNA methylation markers.

CONCLUSIONS

Our findings introduce a dual ERV-based stratification system that effectively categorizes patient risk and predicts clinical outcomes for ccRCC patients undergoing ICI therapy. Beyond enhancing the predictive precision of existing transcriptomic models, this system paves the way for more targeted and individualized approaches in the realm of precision oncology.

Multiomics characterization of breast angiosarcoma from an Asian cohort reveals enrichment for angiogenesis signaling pathway and tumor-infiltrating macrophages

Introduction

Recent epidemiological data suggests a rising incidence of breast angiosarcoma (AS-B) in the Western population, with over two-thirds related to irradiation or chronic lymphedema. However, unlike head and neck angiosarcoma (AS-HN), AS-B disease characteristics in Asia remain unclear.

Methods

We examined clinical patterns of angiosarcoma patients (n = 176) seen in an Asiantertiary cancer center from 1999 to 2021, and specifically investigated the molecular and immune features of AS-B in comparison to AS-HN. Data from whole genome sequencing (WGS), NanoString gene expression profiling and 10x Genomics Visium spatial transcriptomics were analyzed.

Results

Majority of cases were AS-HN (n = 104; 59.1%), while AS-B (n = 16, all females) accounted for 9.1% of the cases. The median age at diagnosis was 43 years (range, 26 to 74). Based on WGS, 4 of the 7 AS-B had non-synonymous somatic variants in 47 genes (range, 2 to 28 per case). These genes were functionally annotated and were enriched in cancer-related pathways such as regulation of cell differentiation, VEGFR and receptor tyrosine kinases signaling pathways. By NanoString gene expression profiling, ASB, compared to AS-HN, were enriched for angiogenesis, notch signaling and metastasis-associated matrix remodeling pathways. Additionally, AS-B were enriched for macrophages and CD8+ T cells expression signatures. Similarly, Visium spatial transcriptomics showed that AS-B were enriched for macrophages and T-cells.

Discussion

In conclusion, in our AS-B cases, we observed a convergence of both mutational and expression signatures on angiogenic-related pathways. Thus, anti-angiogenic therapy could be an option to treat AS-B.

The role of CD95 in modulating CAR T-cell therapy: Challenges and therapeutic opportunities in oncology

CAR T cell therapy has revolutionized how we deliver cancer treatment, most notably for hematologic cancers, by compelling T cells to recognize and kill tumor cells. Nevertheless, current obstacles to utilizing this therapy in solid tumors and overcoming cancer resistance include radicalization. This review discusses how CD95 modulation can boost CAR T cell efficacy. Traditionally, CD95 was known to execute apoptosis induction, but it plays a dual role in induced cell death or in supporting cancer cell survival. Recent data have demonstrated that cancer cells escape CD95-mediated apoptosis via the downregulation of CD95, caspase 8 mutation, or the expression of the inhibition protein cFLIP. Additionally, the immunosuppressive tumor microenvironment, containing CD95L expressing immune cells, explains CAR T cell therapy resistance. Furthermore, we characterize the therapeutic potential of CD95 targeted approaches, including CD95L inhibition (APG101) and alterations in CAR T cell manufacturing (tyrosine kinase inhibitors to mitigate fratricide). In this review, we highlight the importance of multi-path way strategies combining CD95 modulation with CAR T cell engineering to overcome resistance, specifically to target tumor cells better and sustain CAR T cell persistence to enhance treatment efficacy in solid tumors.

Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma

Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness and suitability for immunotherapy has the potential to improve clinical management and outcomes. Here, we present a radiogenomic analysis of pLGGs, integrating MRI and RNA sequencing data. We identify three immunologically distinct clusters, with one group characterized by increased immune activity and poorer prognosis, indicating potential benefit from immunotherapies. We develop a radiomic signature that predicts these immune profiles with over 80% accuracy. Furthermore, our clinicoradiomic model predicts progression-free survival and correlates with treatment response. We also identify genetic variants and transcriptomic pathways associated with progression risk, highlighting links to tumor growth and immune response. This radiogenomic study in pLGGs provides a framework for the identification of high-risk patients who may benefit from targeted therapies.

Evaluating the Prognostic Role of the PAM50 Signature and Selected Immune-Related Signatures for Recurrence in Patients With T1abN0 Breast Cancer

BACKGROUND

De-escalation of adjuvant treatment in patients with T1abN0 breast cancer is discussed internationally. Identification of new prognostic factors in these patients may assist this de-escalation. The PAM50 signature and tumor inflammation signature (TIS), Programmed Cell Death Protein 1 (PD-1) and Programmed Cell Death Ligand 1 (PD-L1) signatures are possible prognostic factors for recurrence.

MATERIALS AND METHODS

Danish patients with T1abN0 breast cancer diagnosed between 2007-2016 were identified, the NanoString Breast Cancer 360 Panel was performed on tissue samples from cases with recurrence matched 1:1 with controls without recurrence (n = 234). The association between gene signatures and recurrence was analyzed with conditional logistic regression.

RESULTS

Patients with the basal-like subtype had higher values of TIS, PD-1 and PD-L1 scores compared with other subtypes. Patients with higher PD-L1 score had significantly lower odds of recurrence (odds ratio [OR] 0.61, P = .01). Likewise, an increased TIS score was associated to lower, but nonsignificant odds of recurrence (OR 0.76, P = .07). Patients with human epidermal growth factor receptor 2 (HER2)-enriched subtype had significantly higher odds of recurrence compared with patients with luminal A subtype (OR 4.8, P = .03).

DISCUSSION

PAM50 and immune-related signatures provide important prognostic information in patients with T1abN0 breast cancer, which may refine the risk assessment in these patients.

Amino acid metabolism-related genes as potential biomarkers and the role of MATN3 in stomach adenocarcinoma: A bioinformatics, mendelian randomization and experimental validation study

BACKGROUND

Stomach adenocarcinoma (STAD) is a major contributor to cancer-related mortality worldwide. Alterations in amino acid metabolism, which is integral to protein synthesis, have been observed across various tumor types. However, the prognostic significance of amino acid metabolism-related genes in STAD remains underexplored.

METHODS

Transcriptomic gene expression and clinical data for STAD patients were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Amino acid metabolism-related gene sets were sourced from the Gene Set Enrichment Analysis (GSEA) database. A prognostic model was built using LASSO Cox regression based on the TCGA cohort and validated with GEO datasets (GSE84433, GSE84437, GSE84426). Kaplan-Meier analysis compared overall survival (OS) between high- and low-risk groups, and ROC curves assessed model accuracy. A nomogram predicted 1-, 3-, and 5-year survival. Copy number variations (CNVs) in model genes were visualized using data from the Xena platform, and mutation profiles were analyzed with "maftools" to create a waterfall plot. KEGG and GO enrichment analyses were performed to explore biological mechanisms. Immune infiltration and related functions were evaluated via ssGSEA, and Spearman correlation analyzed associations between risk scores and immune components. The TIDE database predicted immunotherapy efficacy, while FDA-approved drug sensitivity was assessed through CellMiner database. The role of MATN3 in STAD was further examined in vitro and in vivo, including amino acid-targeted metabolomic sequencing to assess its impact on metabolism. Finally, Mendelian randomization (MR) analysis evaluated the causal relationship between the model genes and gastric cancer.

RESULTS

In this study, we developed a prognostic risk model for STAD based on three amino acid metabolism-related genes (SERPINE1, NRP1, MATN3) using LASSO regression analysis. CNV amplification was common in SERPINE1 and NRP1, while CNV deletion frequently occurred in MATN3. STAD patients were classified into high- and low-risk groups based on the median risk score, with the high-risk group showing worse prognosis. A nomogram incorporating the risk score and clinical factors was created to estimate 1-, 3-, and 5-year survival rates. Distinct mutation profiles were observed between risk groups, with KEGG pathway analysis showing immune-related pathways enriched in the high-risk group. High-risk scores were significantly associated with the C6 (TGF-β dominant) subtype, while low-risk scores correlated with the C4 (lymphocyte-depleted) subtype. Higher risk scores also indicated increased immune infiltration, enhanced immune functions, lower tumor purity, and poorer immunotherapy response. Model genes were linked to anticancer drug sensitivity. Manipulating MATN3 expression showed that it promoted STAD cell proliferation and migration in vitro and tumor growth in vivo. Metabolomic sequencing revealed that MATN3 knockdown elevated levels of 30 amino acid metabolites, including alpha-aminobutyric acid, glycine, and aspartic acid, while reducing (S)-β-Aminoisobutyric acid and argininosuccinic acid. MR analysis found a significant causal effect of NRP1 on gastric cancer, but no causal relationship for MATN3 or SERPINE1.

CONCLUSION

In conclusion, the amino acid metabolism-related prognostic model shows promise as a valuable biomarker for predicting the clinical prognosis, selecting immunotherapy and drug treatment for STAD patients. Furthermore, our study has shed light on the potential value of the MATN3 as a promising strategy for combating the progression of STAD.

Future Directions for Gestational Trophoblastic Disease

Gestational trophoblastic disease encompasses a spectrum of premalignant and malignant conditions. While centralized care models significantly improve survival rates, many countries still lack such specialized centers, leading to preventable deaths. Current research focuses on refining diagnostic and treatment methods, aiming to better predict the risk of malignancy and reduce the need for aggressive therapies. Immunotherapy has emerged as a promising treatment modality, offering high cure rates with fewer side effects compared to traditional chemotherapy. Global efforts must continue to expand access to specialized care and integrate new therapies to improve outcomes and reduce treatment-related harm.

PD-1/PD-L1 immune checkpoint blockade in breast cancer: research insights and sensitization strategies

Immunotherapy targeting programmed cell death-1 (PD-1) and PD-L1 immune checkpoints has reshaped treatment paradigms across several cancers, including breast cancer. Combining PD-1/PD-L1 immune checkpoint blockade (ICB) with chemotherapy has shown promising efficacy in both early and metastatic triple-negative breast cancer, although only a subset of patients experiences durable responses. Identifying responders and optimizing immune drug selection are therefore critical. The effectiveness of PD-1/PD-L1 immunotherapy depends on both tumor-intrinsic factors and the extrinsic cell-cell interactions within the tumor microenvironment (TME). This review systematically summarizes the key findings from clinical trials of ICBs in breast cancer and examines the mechanisms underlying PD-L1 expression regulation. We also highlight recent advances in identifying potential biomarkers for PD-1/PD-L1 therapy and emerging evidence of TME alterations following treatment. Among these, the quantity, immunophenotype, and spatial distribution of tumor-infiltrating lymphocytes stand out as promising biomarkers. Additionally, we explore strategies to enhance the effectiveness of ICBs in breast cancer, aiming to support the development of personalized treatment approaches tailored to the unique characteristics of each patient's tumor.

Potential predictive biomarkers in antitumor immunotherapy: navigating the future of antitumor treatment and immune checkpoint inhibitor efficacy

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment modality, offering promising outcomes for various malignancies. However, the efficacy of ICIs varies among patients, highlighting the essential need of accurate predictive biomarkers. This review synthesizes the current understanding of biomarkers for ICI therapy, and discusses the clinical utility and limitations of these biomarkers in predicting treatment outcomes. It discusses three US Food and Drug Administration (FDA)-approved biomarkers, programmed cell death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), and microsatellite instability (MSI), and explores other potential biomarkers, including tumor immune microenvironment (TIME)-related signatures, human leukocyte antigen (HLA) diversity, non-invasive biomarkers such as circulating tumor DNA (ctDNA), and combination biomarker strategies. The review also addresses multivariable predictive models integrating multiple features of patients, tumors, and TIME, which could be a promising approach to enhance predictive accuracy. The existing challenges are also pointed out, such as the tumor heterogeneity, the inconstant nature of TIME, nonuniformed thresholds and standardization approaches. The review concludes by emphasizing the importance of biomarker research in realizing the potential of personalized immunotherapy, with the goal of improving patient selection, treatment strategies, and overall outcomes in cancer treatment.

Phase I dose escalation study of IO-108, an anti-LILRB2 antibody, in patients with advanced solid tumors

PURPOSE

In this first-in-human dose escalation study, the safety and efficacy of IO-108, a fully human monoclonal antibody targeting leukocyte immunoglobulin-like receptor B2 (LILRB2), was investigated in patients with advanced solid tumors as monotherapy and in combination with pembrolizumab, an anti-programmed cell death protein 1 (PD-1) antibody.

METHODS

The study included patients with histologically or cytologically confirmed advanced and relapsed solid tumors, with measurable disease by Response Evaluation Criteria In Solid Tumors (RECIST) V.1.1. Patients were treated with escalating doses of IO-108 every 3 weeks (Q3W) as monotherapy and in combination with pembrolizumab. Safety and tolerability were the primary objectives. Secondary and exploratory objectives included: pharmacokinetics, clinical efficacy, immunogenicity and biomarkers.

RESULTS

Of 25 patients enrolled, 12 were treated with IO-108 monotherapy and 13 received combination therapy. IO-108 was well-tolerated up to the maximally administered dose of 1,800 mg every 3 weeks (Q3W) as monotherapy and in combination with pembrolizumab. No dose-limiting toxicity was observed, and a maximum tolerated dose was not reached. Treatment-related adverse events (TRAEs) occurred in 6 (50.0%) patients treated with IO-108 monotherapy and 6 (46.2%) patients treated with IO-108+pembrolizumab. All TRAEs were mild or moderate (Grade 1 or 2), and no TRAEs led to treatment discontinuation or death. IO-108 exhibited a dose-proportional increase in exposure. Full receptor occupancy (RO) in peripheral blood was achieved at doses ≥600 mg. The overall response rate was 9% (1/11) in the monotherapy and 23% (3/13) in the combination therapy. A patient with treatment-refractory Merkel cell carcinoma treated with IO-108 monotherapy achieved a durable complete response (CR) for more than 2 years. Pharmacodynamic gene expression changes reflecting increased tumor infiltration of T cells were associated with clinical benefits in both monotherapy and combination therapy. Additionally, baseline tumor inflammation gene signature (TIS) scores correlated with clinical benefit.

CONCLUSION

IO-108 is well tolerated and has led to objective response as monotherapy and in combination with pembrolizumab. The complete response and the pharmacodynamic changes in the monotherapy cohort demonstrate single agent activity of IO-108 and provide proof of concept that targeting myeloid-suppressive pathways through LILRB2 inhibition may potentiate the clinical efficacy of anti-PD-1 immune checkpoint inhibitors.

TRIAL REGISTRATION NUMBER

NCT05054348.

Androgen Deprivation Therapy Drives a Distinct Immune Phenotype in Localized Prostate Cancer

PURPOSE

Androgen deprivation therapy (ADT) remains the backbone of prostate cancer treatment. Beyond the suppression of testosterone and tumor cell growth, emerging evidence suggests that ADT also modulates the immune tumor microenvironment. However, a more precise understanding of the timing and intricacies of these immunologic shifts is needed.

EXPERIMENTAL DESIGN

In this study, we analyzed 49 primary prostate cancers, comparing those surgically removed either without treatment or following treatment with degarelix at 4, 7, and 14 days before surgery. Utilizing next-generation DNA and RNA sequencing and multiplexed immunofluorescence, we examined alterations in immune phenotypes in the presence or absence of ADT.

RESULTS

Our findings reveal that ADT rapidly transforms the typically bland prostate tumor microenvironment into an inflamed environment within days. Notably, we observed an increase in activated CD8 T cells along with an increase in suppressive regulatory T cells (Treg). We also found an expansion of the myeloid compartment, particularly proinflammatory M1-like tumor-associated macrophages. Intriguingly, discernable changes which have not previously been described also occurred in tumor cells, including upregulation of antigen presentation by MHC classes I and II and, unexpectedly, a decrease in the "do not eat me" signal CD47.

CONCLUSIONS

These observations underscore the critical role of timing and disease context in order to optimize the therapeutic efficacy of immune modulators combined with androgen ablation, for which the presurgical neoadjuvant setting may be ideal. Our findings warrant future prospective validation, which is currently underway.

Invention and characterization of a systemically administered, attenuated and killed bacteria-based multiple immune receptor agonist for anti-tumor immunotherapy

Activation of immune receptors, such as Toll-like (TLR), NOD-like (NLR) and Stimulator of Interferon Genes (STING) is critical for efficient innate and adaptive immunity. Gram-negative bacteria (G-NB) contain multiple TLR, NOD and STING agonists. Potential utility of G-NB for cancer immunotherapy is supported by observations of tumor regression in the setting of infection and Coley's Toxins. Coley reported that intravenous (i.v.) administration was likely most effective but produced uncontrollable toxicity. The discovery of TLRs and their agonists, particularly the potent TLR4 agonist lipopolysaccharide (LPS)-endotoxin, comprising ~75% of the outer membrane of G-NB, suggests that LPS may be both a critical active ingredient and responsible for dose-limiting i.v. toxicity of G-NB. This communication reports the production of killed, stabilized, intact bacteria products from non-pathogenic G-NB with ~96% reduction of LPS-endotoxin activity. One resulting product candidate, Decoy10, was resistant to standard methods of cell disruption and contained TLR2,4,8,9, NOD2 and STING agonist activity. Decoy10 also exhibited reduced i.v. toxicity in mice and rabbits, and a largely uncompromised ability to induce cytokine and chemokine secretion by human immune cells in vitro, all relative to unprocessed, parental bacterial cells. Decoy10 and a closely related product, Decoy20, produced single agent anti-tumor activity or combination-mediated durable regression of established subcutaneous, metastatic or orthotopic colorectal, hepatocellular (HCC), pancreatic, and non-Hodgkin's lymphoma (NHL) tumors in mice, with induction of both innate and adaptive immunological memory (syngeneic and human tumor xenograft models). Decoy bacteria combination-mediated regressions were observed with a low-dose, oral non-steroidal anti-inflammatory drug (NSAID), anti-PD-1 checkpoint therapy, low-dose cyclophosphamide (LDC), and/or a targeted antibody (rituximab). Efficient tumor eradication was associated with plasma expression of 15-23 cytokines and chemokines, broad induction of cytokine, chemokine, innate and adaptive immune pathway genes in tumors, cold to hot tumor inflammation signature transition, and required NK, CD4+ and CD8+ T cells, collectively demonstrating a role for both innate and adaptive immune activation in the anti-tumor immune response.

Expression of PD-L1, PD-L2, and inflammatory gene expression profile in locally advanced head and neck squamous cell carcinoma

BACKGROUND

The tumor immune microenvironment in cancer treatment response and resistance is of increasing interest. This retrospective study characterized and investigated programmed death-ligand 1 (PD-L1), PD-L2, and the immune gene expression signature and their association with clinical outcomes in locoregionally advanced head and neck squamous cell carcinoma (LA HNSCC).

PATIENTS AND METHODS

PD-L1 and PD-L2 expression on tumor and immune-infiltrating cells (positivity defined as combined positive score or immunohistochemistry proportion score >1) and T-cell-inflamed gene expression profile (TcellinfGEP) were evaluated in patients with LA HNSCC treated in South Korea from 2000 to 2015. Correlations among the three biomarkers and their associations with overall survival and recurrence-free survival were assessed.

RESULTS

Among 366 patients, 38.8% had human papillomavirus-positive disease. PD-L1-positive, PD-L2-positive, and high TcellinfGEP (≤-0.162) status were observed in 83.6%, 85.4%, and 73.2% of patients, respectively; 4.1% were posttreatment samples. Correlation between PD-L1 and PD-L2 scores was moderate (rSpearman = 0.50), and each biomarker was slightly less correlated with TcellinfGEP (0.41-0.45). PD-L1 expression and high TcellinfGEP status were associated with human papillomavirus positivity. Higher levels of all biomarkers were observed in oral cavity and oropharyngeal cancers compared with other HNSCC sites. In a multivariable analysis that simultaneously adjusted for all three biomarkers, only high TcellinfGEP was significantly associated with longer overall survival (adjusted hazard ratio, 0.57; 95% confidence interval 0.33-0.98) and recurrence-free survival (adjusted hazard ratio, 0.41; 95% confidence interval 0.23-0.74).

CONCLUSION

High TcellinfGEP status, but not PD-L1 or PD-L2 expression, was independently associated with longer survival in patients with LA HNSCC. Results may have implications for evaluating therapies targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) in HNSCC.

Immunological facets of prostate cancer and the potential of immune checkpoint inhibition in disease management

Prostate cancer (PCa) is the most common non-cutaneous cancer in men and a major cause of cancer-related deaths. Whereas localized PCa can be cured by surgery and radiotherapy, metastatic disease can be treated, but is not curable. Inhibition of androgen signaling remains the main therapeutic intervention for treatment of metastatic PCa, in addition to chemotherapy, radionuclide therapy and emerging targeted therapies. Although initial responses are favorable, resistance to these therapies invariably arise with development of castration resistant PCa (CRPC) and lethal phenotypes. Recent findings have implicated the crosstalk between PCa cells and the tumor microenvironment (TME) as a key factor for disease progression and metastasis, and the immune system is becoming an increasingly attractive target for therapy. Given the striking success of immune checkpoint inhibitors (ICIs) in various cancer types, preclinical and clinical studies have begun to explore their potential in PCa. It has become clear that the PCa TME is largely immunosuppressive, and ICI therapy does not have efficacy for PCa. Intense effort is therefore being made in the field to understand the mechanisms of suppression and to turn the immunosuppressive TME into an immune active one that would enable ICI efficacy. Herein we examine this recent body of knowledge and how the mutational landscape of PCa integrates with an immunosuppressive TME to circumvent ICI-mediated T-cell activity and tumor killing. We then review the emerging potential success of combinatorial ICI approaches, utility of careful patient selection, and potential novel strategies to improve the efficacy of ICI for PCa therapy.

Dynamic reciprocal interactions between activated T cells and tumor associated macrophages drive macrophage reprogramming and proinflammatory T cell migration within prostate tumor models

Tumor-associated macrophages (TAMs) have been implicated as a tumor microenvironment (TME) cell population, which may be playing a vital role in the inhibition of effective T cell responses in the prostate TME. In this manuscript, we leverage a novel microscale cell culture platform, known as Stacks, to investigate mono-, co-, and tri-culture TME models comprised of prostate tumor cell lines, primary macrophages, and autologous T cells from patients with prostate cancer. Through multiplexed analysis of these multi-cellular prostate tumor models, we capture a dynamic interaction between primary TAMs and activated T cells that resulted in reciprocal proinflammatory activation of both cell populations upon interaction. These findings suggest that activated T cells are capable of reprogramming immunosuppressive TAMs in the context of prostate tumor models and that TAM reprogramming may play a key supportive role in restoring proinflammatory T cell tumor responses in the prostate TME.

Cabozantinib inhibits tumor growth in mice with ovarian cancer

Ovarian cancer is usually detected in the advanced stages. Existing treatments for high grade serous ovarian cancer (HGSOC) are not adequate and approximately fifty percent of patients succumb to this disease and die within five years after diagnosis. We conducted pre-clinical studies in a mouse model of ovarian cancer to evaluate disease outcome in response to treatment with the multi-kinase inhibitor cabozantinib. Cabozantinib is a receptor tyrosine kinase inhibitor with multiple targets including vascular endothelial growth factor receptor-2 (VEGFR-2), associated with immune suppression in ovarian cancer. Mice (C57BL/6) were injected with ID8-RFP ovarian tumor cells and treated with cabozantinib. Studies investigated ascites development, tumor burden and regulation of anti-tumor immunity with treatment. Mice treated with cabozantinib had significantly decreased solid tumor burden and decreased malignant ascites as compared to untreated controls. Improved outcome in cabozantinib treated mice was associated with a significantly higher percentage of CD69 early activated T cells, a higher percentage of granzyme B secreting CD8 T cells, the enhanced release of cytokines and chemokines known to recruit CD8 T cells and amplify T cell function, as well as reduced VEGFR-2. Findings suggest that cabozantinib is an important clinical agent capable of improving ovarian cancer in mice potentially in part by priming the autologous immune system to promote anti-tumor immunity.

YAP1 Status Defines Two Intrinsic Subtypes of LCNEC with Distinct Molecular Features and Therapeutic Vulnerabilities

PURPOSE

Large cell neuroendocrine carcinoma (LCNEC) is a high-grade neuroendocrine malignancy that, like small cell lung cancer (SCLC), is associated with the absence of druggable oncogenic drivers and dismal prognosis. In contrast to SCLC, however, there is little evidence to guide optimal treatment strategies, which are often adapted from SCLC and non-small cell lung cancer approaches.

EXPERIMENTAL DESIGN

To better define the biology of LCNEC, we analyzed cell line and patient genomic data and performed IHC and single-cell RNA sequencing of core needle biopsies from patients with LCNEC and preclinical models.

RESULTS

In this study, we demonstrate that the presence or absence of YAP1 distinguishes two subsets of LCNEC. The YAP1-high subset is mesenchymal and inflamed and is characterized, alongside TP53 mutations, by co-occurring alterations in CDKN2A/B and SMARCA4. Therapeutically, the YAP1-high subset demonstrates vulnerability to MEK- and AXL-targeting strategies, including a novel preclinical AXL chimeric antigen receptor-expressing T cell. Meanwhile, the YAP1-low subset is epithelial and immune-cold and more commonly features TP53 and RB1 co-mutations, similar to those observed in pure SCLC. Notably, the YAP1-low subset is also characterized by the expression of SCLC subtype-defining transcription factors, especially ASCL1 and NEUROD1, and as expected, given its transcriptional similarities to SCLC, exhibits putative vulnerabilities reminiscent of SCLC, including delta-like ligand 3 and CD56 targeting, as is with novel preclinical delta-like ligand 3 and CD56 chimeric antigen receptor-expressing T cells, and DNA damage repair inhibition.

CONCLUSIONS

YAP1 defines distinct subsets of LCNEC with unique biology. These findings highlight the potential for YAP1 to guide personalized treatment strategies for LCNEC.

Identification of Cuproptosis-Associated Prognostic Gene Expression Signatures from 20 Tumor Types

We investigated the mRNA expression of 124 cuproptosis-associated genes in 7489 biopsies from 20 different tumor types of The Cancer Genome Atlas (TCGA). The KM plotter algorithm has been used to calculate Kaplan-Meier statistics and false discovery rate (FDR) corrections. Interaction networks have been generated using Ingenuity Pathway Analysis (IPA). High mRNA expression of 63 out of 124 genes significantly correlated with shorter survival times of cancer patients across all 20 tumor types. IPA analyses revealed that their gene products were interconnected in canonical pathways (e.g., cancer, cell death, cell cycle, cell signaling). Four tumor entities showed a higher accumulation of genes than the other cancer types, i.e., renal clear cell carcinoma (n = 21), renal papillary carcinoma (n = 13), kidney hepatocellular carcinoma (n = 13), and lung adenocarcinoma (n = 9). These gene clusters may serve as prognostic signatures for patient survival. These signatures were also of prognostic value for tumors with high mutational rates and neoantigen loads. Cuproptosis is of prognostic significance for the survival of cancer patients. The identification of specific gene signatures deserves further exploration for their clinical utility in routine diagnostics.

Comprehensive analysis of bulk, single-cell RNA sequencing, and spatial transcriptomics revealed IER3 for predicting malignant progression and immunotherapy efficacy in glioma

BACKGROUND

As part of stress-triggered molecules, immediate early response 3 (IER3) dysregulation has been reported to sustain pro-oncogenic pathways and precede malignant transformation. However, the role of IER3 in glioma pathology is ill-defined.

METHODS

Immunohistochemistry (IHC) assay and publicly available glioma datasets were used to calculate the IER3 expression level in glioma. Wound healing, invasion and cell counting kit-8 (CCK8) assays were applied to measure the cell viability and capacities of migration and invasion of glioma cells in vitro. The immunofluorescence (IF) assay was used to assess the expression associations of IER3 with CCL2 and TGFBI. Cox regression analysis and Kaplan-Meier (K-M) curve were introduced to compute the prognosis-predicting value of IER3. Variations in copy number (CNVs), single nucleotide (SNVs), and methylation profiles were analyzed to illustrate the epigenetic modifications of IER3. Gliomas were divided into two subgroups using the restricted cubic spline (RCS) method. RESULTS IER3: was overexpressed and hypomethylated in gliomas and significantly associated with the dismal prognosis of glioma samples. Samples in the high IER3 subgroup were characterized by increased infiltration of tumor-associated monocytes/macrophages (TAMMs), as well as the elevated sensitivity to Dabrafenib, an inhibitor of BRAF. In addition, this subgroup demonstrated a low mutation rate of IDH, high gain rates of BRAF, ELTD1, and PDGFA. Gliomas with relatively low IER3 expression demonstrated a less invasive subtype and were featured by favorable prognosis, increased response to immunotherapy, and adjuvant chemotherapy plus radiotherapy. The IF assay revealed that IER3 was co-localized and co-expressed with TGFBI. The glioma cells with small interfering RNA (siRNA)-silenced IER3 displayed lower migration, invasion, proliferation, and cell viability than the control group.

CONCLUSIONS

In this study, we identified IER3 upregulation as an essential biomarker that could assist in adjuvant therapy and prognosis prediction for gliomas.

Signature stemmed from two transcription factor families determines histological fate and regulates immune infiltration in patients with lung cancer

Background

Earlier research has reported that transcription factors play a crucial role in the anti-tumorigenic immune response of lung cancer patients. The aim of this study is to determine the relationship between post-translational modifications of transcription factors and histological fate and patient prognosis.

Methods

Based on the information of 293 lung cancer patients in the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) related to the interferon regulatory factor (IRF) and signal transducer and activator of transcription (STAT) families between patients experiencing early death and those with long-term survival were identified and characterized. A survival prediction model was established by incorporating 7 STAT genes and 9 IRF genes into the least absolute shrinkage and selection operator (LASSO) algorithm. Gene Ontology (GO) enrichment analysis indicated that these two transcription factor families can govern lung cancer tissue differentiation and predict patient prognosis. Moreover, the Cox proportional hazards regression model was applied to select the genes with the highest predictive capability to construct a gene-based signature. Lastly, the data of 1,803 and 784 lung cancer patients from the Kaplan-Meier plotter (KMPLOT) and The Cancer Genome Atlas (TCGA) databases were used to evaluate the accuracy and sensitivity of the model.

Results

Based on the minimum criterion, TRIM28, IRF3, and STAT3 were employed to generate the prognostic model. The 1-, 3-, and 5-year area under the curve (AUC) values of the three-gene-based signature showed consistent results, signifying that the model had excellent accuracy and sensitivity in predicting overall survival (OS) for patients with lung cancer. Finally, the three-gene signature and tumor-node-metastasis (TNM) staging system were combined to construct a nomogram for evaluating the OS of lung cancer patients. TRIM28 may affect the stability of IRF3. Encouragingly, the predicted OS was highly consistent with the observed OS in multiple cohorts.

Conclusions

Taken together, these findings implied that the predictive model based on the three-gene signature showed robust discriminatory performance.

Transforming pancreaticobiliary cancer treatment: Exploring the frontiers of adoptive cell therapy and cancer vaccines

Pancreaticobiliary cancer, encompassing malignancies of both the pancreatic and biliary tract, presents a formidable clinical challenge marked by a uniformly bleak prognosis. The asymptomatic nature of its early stages often leads to delayed detection, contributing to an unfavorable 5-year overall survival rate. Conventional treatment modalities have shown limited efficacy, underscoring the urgent need for alternative therapeutic approaches. In recent years, immunotherapy has emerged as a promising avenue in the fight against pancreaticobiliary cancer. Strategies such as therapeutic vaccines and the use of tumor-infiltrating lymphocytes have garnered attention for their potential to elicit more robust and durable responses. This review seeks to illuminate the landscape of emerging immunotherapeutic interventions, offering insights from both clinical and research perspectives. By deepening our understanding of pancreaticobiliary cancer and exploring innovative treatment modalities, we aim to catalyze improvements in patient outcomes and quality of life.

A phase II clinical trial of toripalimab in advanced solid tumors with polymerase epsilon/polymerase delta (POLE/POLD1) mutation

Patients carrying mutations in polymerase epsilon/polymerase delta have shown positive responses to immune checkpoint inhibitors. Yet, prospective trials exploring the efficacy in those with polymerase epsilon/polymerase delta mutations are still lacking. A phase II clinical trial was initiated to evaluate the efficacy of toripalimab, a humanized IgG4K monoclonal antibody to human PD-1, in patients with advanced solid tumors with unselected polymerase epsilon/polymerase delta mutations but without microsatellite instability-high. A total of 15 patients were enrolled, 14 of whom were assessed for treatment efficacy. There was a 21.4% overall response rate, with a disease control rate of 57.1%. The median overall survival and median progression-free survival were 17.9 (95% CI 13.5-not reach) months and 2.5 (95% CI 1.4-not reach) months, respectively. For patients with exonuclease domain mutations, the objective response rate was 66.7% (2/3), with a disease control rate of 66.7% (2/3). For those with non-exonuclease domain mutations, the rates were 9.1% (1/11) and 54.5% (6/11), respectively. Notably, patients with PBRM1 gene mutations exhibited a high response rate to toripalimab at 75.0% (3/4). This study showed that neither the exonuclease domain mutations nor non-exonuclease domain mutations could fully predict the efficacy of immunotherapy, urging the need for more investigations to clarify potential immune sensitization differences within polymerase epsilon/polymerase delta mutation variants.

Age-Related Clusters and Favorable Immune Phenotypes in Young Breast Cancer Patients

Breast cancer (BC) patients aged <40 years at diagnosis experience aggressive disease and poorer survival compared with women diagnosed with BC at 40 to 49 years, but the age-related biology is described to little extent. Here, we explored transcriptional alterations in BC to gain better understanding of age-related tumor biology. We studied a subset of the Bergen in-house cohort (n = 127; age range, 26-49 years) and used the NanoString Breast Cancer 360 expression panel on formalin-fixed paraffin-embedded BC tissue, and publicly available global BC messenger RNA expression data (n = 204; age range, 22-49 years), to explore differentially expressed genes between the young (age <40 years) and older (age 40-49 years) patients. Unsupervised hierarchical clustering was applied to identify gene expression-based patient clusters. We applied established computational approaches to define the PAM50 subtypes, risk of recurrence scores (ROR), and risk groups and to infer the proportions of 22 immune cell types from bulk gene expression profiles of patients aged <50 years at BC diagnosis. Differentially expressed genes and gene sets were investigated using OncoEnrichR and g:Profiler to describe functional profiles and pathway enrichment. We identified 4 age-related patient clusters presenting distinct characteristics of PAM50 subtypes and ROR profiles, which demonstrated independent prognostic value when adjusted for traditional clinicopathologic variables and the known molecular subtypes. Our findings showed better survival than expected in the basal-enriched cluster 2 and in triple-negative and basal-like BC. Deconvolution analyses of immunophenotypes indicated higher levels of M0 and M1 macrophages than M2 macrophages in subsets of young BC. Our approach identifies age-based patient clusters with distinct clinicopathologic profiles, to a large extent overlapping with the PAM50 subtypes, although with independent prognostic values in multivariate survival analyses. The patient clusters provided new insight in the immune cell distribution across tumor subtypes, potentially contributing to survival differences between the clusters and the molecular subtypes and indicating age-related mechanisms improving outcome. Our study confirms the applicability of ROR as a valid prognosticator also in a young BC cohort.

Tumor-Intrinsic Activity of Chromobox 2 Remodels the Tumor Microenvironment in High-grade Serous Carcinoma

Chromobox 2 (CBX2), an epigenetic reader and component of polycomb repressor complex 1, is highly expressed in >75% of high-grade serous carcinoma. Increased CBX2 expression is associated with poorer survival, whereas CBX2 knockdown leads to improved chemotherapy sensitivity. In a high-grade serous carcinoma immune-competent murine model, knockdown of CBX2 decreased tumor progression. We sought to explore the impact of modulation of CBX2 on the tumor immune microenvironment (TIME), understanding that the TIME plays a critical role in disease progression and development of therapy resistance. Exploration of existing datasets demonstrated that elevated CBX2 expression significantly correlated with specific immune cell types in the TIME. RNA sequencing and pathway analysis of differentially expressed genes demonstrated immune signature enrichment. Confocal microscopy and co-culture experiments found that modulation of CBX2 leads to increased recruitment and infiltration of macrophages. Flow cytometry of macrophages cultured with CBX2-overexpressing cells showed increased M2-like macrophages and decreased phagocytosis activity. Cbx2 knockdown in the Trp53-null, Brca2-null ID8 syngeneic murine model (ID8 Trp53-/-Brca2-/-) led to decreased tumor progression compared with the control. NanoString immuno-oncology panel analysis suggested that knockdown in Cbx2 shifts immune cell composition, with an increase in macrophages. Multispectral immunohistochemistry (mIHC) further confirmed an increase in macrophage infiltration. Increased CBX2 expression leads to recruitment and polarization of protumor macrophages, and targeting CBX2 may serve to modulate the TIME to enhance the efficacy of immune therapies.

SIGNIFICANCE

CBX2 expression correlates with the TIME. CBX2 modulation shifts the macrophage population, potentially leading to an immunosuppressive microenvironment, highlighting CBX2 as a target to improve efficacy of immunotherapy.

Head-to-head comparison of composite and individual biomarkers to predict clinical benefit to PD-1 blockade in non-small cell lung cancer

BACKGROUND

The efficacy of PD-1 blocking agents in advanced NSCLC has shown prolonged effectiveness, but only in a minority of patients. Multiple biomarkers have been explored to predict treatment benefit, yet their combined performance remains inadequately examined. In this study, we assessed the combined predictive performance of multiple biomarkers in NSCLC patients treated with nivolumab.

METHODS

Pretreatment samples from 135 patients receiving nivolumab were used to evaluate the predictive performance of CD8 tumor-infiltrating lymphocytes (TILs), intratumoral (IT) localization of CD8 TILs, PD-1 high expressing TILs (PD1T TILs), CD3 TILs, CD20 B-cells, tertiary lymphoid structures (TLS), PD-L1 tumor proportion score (TPS) and the Tumor Inflammation score (TIS). Patients were randomly assigned to a training (n = 55) and validation cohort (n = 80). The primary outcome measure was Disease Control at 6 months (DC 6m) and the secondary outcome measure was DC at 12 months (DC 12m).

RESULTS

In the validation cohort, the two best performing composite biomarkers (i.e. CD8+IT-CD8 and CD3+IT-CD8) demonstrated similar or lower sensitivity (64% and 83%) and NPV (76% and 85%) compared to individual biomarkers PD-1T TILs and TIS (sensitivity: 72% and 83%, NPV: 86% and 84%) for DC 6m, respectively. Additionally, at 12 months, both selected composite biomarkers (CD8+IT-CD8 and CD8+TIS) demonstrated inferior predictive performance compared to PD-1T TILs and TIS alone. PD-1T TILs and TIS showed high sensitivity (86% and 100%) and NPV (95% and 100%) for DC 12m. PD-1T TILs could more accurately discriminate patients with no long-term benefit, as specificity was substantially higher compared to TIS (74% versus 39%).

CONCLUSION

Composite biomarkers did not show improved predictive performance compared to PD-1T TILs and TIS alone for both the 6- and 12-month endpoints. PD-1T TILs and TIS identified patients with DC 12m with high sensitivity. Patients with no long-term benefit to PD-1 blockade were most accurately identified by PD-1T TILs.

A m6A regulators-related classifier for prognosis and tumor microenvironment characterization in hepatocellular carcinoma

Background

Increasing evidence have highlighted the biological significance of mRNA N6-methyladenosine (m6A) modification in regulating tumorigenicity and progression. However, the potential roles of m6A regulators in tumor microenvironment (TME) formation and immune cell infiltration in liver hepatocellular carcinoma (LIHC or HCC) requires further clarification.

Method

RNA sequencing data were obtained from TCGA-LIHC databases and ICGC-LIRI-JP databases. Consensus clustering algorithm was used to identify m6A regulators cluster subtypes. Weighted gene co-expression network analysis (WGCNA), LASSO regression, Random Forest (RF), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were applied to identify candidate biomarkers, and then a m6Arisk score model was constructed. The correlations of m6Arisk score with immunological characteristics (immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), and immune checkpoints) were systematically evaluated. The effective performance of nomogram was evaluated using concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic curve (ROC).

Results

Two distinct m6A modification patterns were identified based on 23 m6A regulators, which were correlated with different clinical outcomes and biological functions. Based on the constructed m6Arisk score model, HCC patients can be divided into two distinct risk score subgroups. Further analysis indicated that the m6Arisk score showed excellent prognostic performance. Patients with a high m6Arisk score was significantly associated with poorer clinical outcome, lower drug sensitivity, and higher immune infiltration. Moreover, we developed a nomogram model by incorporating the m6Arisk score and clinicopathological features. The application of the m6Arisk score for the prognostic stratification of HCC has good clinical applicability and clinical net benefit.

Conclusion

Our findings reveal the crucial role of m6A modification patterns for predicting HCC TME status and prognosis, and highlight the good clinical applicability and net benefit of m6Arisk score in terms of prognosis, immunophenotype, and drug therapy in HCC patients.

Immuno-oncologic profiling of pediatric brain tumors reveals major clinical significance of the tumor immune microenvironment

With the success of immunotherapy in cancer, understanding the tumor immune microenvironment (TIME) has become increasingly important; however in pediatric brain tumors this remains poorly characterized. Accordingly, we developed a clinical immune-oncology gene expression assay and used it to profile a diverse range of 1382 samples with detailed clinical and molecular annotation. In low-grade gliomas we identify distinct patterns of immune activation with prognostic significance in BRAF V600E-mutant tumors. In high-grade gliomas, we observe immune activation and T-cell infiltrates in tumors that have historically been considered immune cold, as well as genomic correlates of inflammation levels. In mismatch repair deficient high-grade gliomas, we find that high tumor inflammation signature is a significant predictor of response to immune checkpoint inhibition, and demonstrate the potential for multimodal biomarkers to improve treatment stratification. Importantly, while overall patterns of immune activation are observed for histologically and genetically defined tumor types, there is significant variability within each entity, indicating that the TIME must be evaluated as an independent feature from diagnosis. In sum, in addition to the histology and molecular profile, this work underscores the importance of reporting on the TIME as an essential axis of cancer diagnosis in the era of personalized medicine.

Characteristics of the immune environment in prostate cancer as an adjunct to immunotherapy

Background and Aims

The tumor microenvironment (TME) exerts an important role in carcinogenesis and progression. Several investigations have suggested that immune cell infiltration (ICI) is of high prognostic importance for tumor progression and patient survival in many tumors, particularly prostate cancer. The pattern of immune infiltration of PCa, on the other hand, has not been thoroughly understood.

Methods

The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets on PCa were obtained, and several datasets were merged into one data set using the "ComBat" algorithm. The ICI profiles of PCa patients were then to be uncovered by two computer techniques. The unsupervised clustering method was utilized to identify three ICI patterns in tumor samples, and Principal Component Analysis (PCA) was conducted to estimate the ICI score.

Results

Three different clusters of three ICIs were identified in 1341 PCa samples, which also correlated with different clinical features/characteristics and biological pathways. Patients with PCa are classified into high and low subtypes based on the ICI scores extracted from immune-associated signature genes. High ICI score subtypes are associated with a worse prognosis, which may intrigue the activation of cancer-related and immune-related pathways such as pathways involving Toll-like receptors, T-cell receptors, JAK-STAT, and natural killer cells. The ICI score was linked to tumor mutation load and immune/cancer-relevant signaling pathways, which explain prostate cancer's poor prognosis.

Conclusion

The findings of this study not only advanced our knowledge of the mechanism of immune response in the prostate tumor microenvironment but also provided a novel biomarker, that is, the ICI score, for disease prognosis and guiding precision immunotherapy.

Ehmt2 inactivation in pancreatic epithelial cells shapes the transcriptional landscape and inflammation response of the whole pancreas

Introduction: The Euchromatic Histone Methyl Transferase Protein 2 (EHMT2), also known as G9a, deposits transcriptionally repressive chromatin marks that play pivotal roles in the maturation and homeostasis of multiple organs. Recently, we have shown that Ehmt2 inactivation in the mouse pancreas alters growth and immune gene expression networks, antagonizing Kras-mediated pancreatic cancer initiation and promotion. Here, we elucidate the essential role of Ehmt2 in maintaining a transcriptional landscape that protects organs from inflammation. Methods: Comparative RNA-seq studies between normal postnatal and young adult pancreatic tissue from Ehmt2 conditional knockout animals (Ehmt2 fl/fl ) targeted to the exocrine pancreatic epithelial cells (Pdx1-Cre and P48 Cre/+ ), reveal alterations in gene expression networks in the whole organ related to injury-inflammation-repair, suggesting an increased predisposition to damage. Thus, we induced an inflammation repair response in the Ehmt2 fl/fl pancreas and used a data science-based approach to integrate RNA-seq-derived pathways and networks, deconvolution digital cytology, and spatial transcriptomics. We also analyzed the tissue response to damage at the morphological, biochemical, and molecular pathology levels. Results and discussion: The Ehmt2 fl/fl pancreas displays an enhanced injury-inflammation-repair response, offering insights into fundamental molecular and cellular mechanisms involved in this process. More importantly, these data show that conditional Ehmt2 inactivation in exocrine cells reprograms the local environment to recruit mesenchymal and immunological cells needed to mount an increased inflammatory response. Mechanistically, this response is an enhanced injury-inflammation-repair reaction with a small contribution of specific Ehmt2-regulated transcripts. Thus, this new knowledge extends the mechanisms underlying the role of the Ehmt2-mediated pathway in suppressing pancreatic cancer initiation and modulating inflammatory pancreatic diseases.

An immunogenic cell death-related lncRNA signature correlates with prognosis and tumor immune microenvironment in bladder cancer

Immunogenic cell death (ICD) is a newly discovered form of cellular demise that triggers adaptive immune responses mediated by T cells. However, the immunogenic cell death-related lncRNAs (ICDRLs) involved in bladder cancer (BC) development and progression remain to be further elucidated. Molecular profiling data and clinicopathological information for BC patients were obtained from TCGA, and the ICDRGs list was obtained from published literature. For the identification of ICDRLs, Pearson co-expression analysis was performed, and a prognostic signature based on 13 ICDRLs was constructed by univariate assays and LASSO assays. Herein, an ICDRLSig consisting of 13 ICDRLs was constructed. KM curves and ROC curves demonstrated that the constructed signature in the TCGA training, testing, entire and external sets have good predictive performance. Multivariate assays illuminated that the signature is an independent predictor for BC patients' OS, exhibiting greater predictive power for the survival than traditional clinicopathological features. Additionally, patients in the high-ICDRLSig risk subgroup had more abundant immune infiltration, higher immune checkpoint gene expression, lower TMB and poorer response to immunotherapy. We have developed a novel ICDRLSig that can be exploited for survival prediction and provide a reference for further individualized treatment.

Immune profiling of dedifferentiated liposarcoma and identification of novel antigens for targeted immunotherapy

Dedifferentiated liposarcoma (DDLS) is an aggressive, recurring sarcoma with limited treatments. T-cell immunotherapies selectively target malignant cells, holding promise against DDLS. The development of successful immunotherapy for DDLS requires a thorough evaluation of the tumor immune microenvironment and the identification and characterization of targetable immunogenic tumor antigens. To assess the complexity of the human DDLS tumor immune microenvironment and to identify target antigens, we used the nCounter NanoString platform, analyzing gene expression profiles across 29 DDLS and 10 healthy adipose tissue samples. Hierarchical clustering of tumors based on expression of tumor inflammation signature genes revealed two distinct groups, consisting of 15 inflamed tumors and 14 non-inflamed tumors, demonstrating tumor heterogeneity within this sarcoma subtype. Among the identified antigens, PBK and TTK exhibited substantial upregulation in mRNA expression compared to healthy adipose tissue controls, further corroborated by positive protein expression by IHC. This data shows considerable inter-tumoral heterogeneity of inflammation, which should be taken into consideration when designing an immunotherapy for DDLS, and provides a novel targetable antigen in DDLS. The results of this study lay the groundwork for the development of a novel immunotherapy for this highly aggressive sarcoma.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Facts and Hopes in Using Omics to Advance Combined Immunotherapy Strategies

The field of oncology has been transformed by immune checkpoint inhibitors (ICI) and other immune-based agents; however, many patients do not receive a durable benefit. While biomarker assessments from pivotal ICI trials have uncovered certain mechanisms of resistance, results thus far have only scraped the surface. Mechanisms of resistance are as complex as the tumor microenvironment (TME) itself, and the development of effective therapeutic strategies will only be possible by building accurate models of the tumor-immune interface. With advancement of multi-omic technologies, high-resolution characterization of the TME is now possible. In addition to sequencing of bulk tumor, single-cell transcriptomic, proteomic, and epigenomic data as well as T-cell receptor profiling can now be simultaneously measured and compared between responders and nonresponders to ICI. Spatial sequencing and imaging platforms have further expanded the dimensionality of existing technologies. Rapid advancements in computation and data sharing strategies enable development of biologically interpretable machine learning models to integrate data from high-resolution, multi-omic platforms. These models catalyze the identification of resistance mechanisms and predictors of benefit in ICI-treated patients, providing scientific foundation for novel clinical trials. Moving forward, we propose a framework by which in silico screening, functional validation, and clinical trial biomarker assessment can be used for the advancement of combined immunotherapy strategies.

Discovery of a novel ROS-based signature for predicting prognosis and immunosuppressive tumor microenvironment in lung adenocarcinoma

The role of reactive oxygen species (ROS) is critical in the emergence and progression of lung adenocarcinoma (LUAD), affecting cell survival, proliferation, angiogenesis, and metastasis. Further investigations are needed to elucidate these effects' precise pathways and devise therapeutic approaches targeting ROS. Moreover, the expression pattern and clinical significance of the ROS-related genes in LUAD remain elusive. Through comprehensive analysis incorporating 1494 LUAD cases from The Cancer Genome Atlas, six Gene Expression Omnibus series, and a Chinese LUAD cohort, we identified a ROS-related signature with substantial predictive value in various LUAD patient cohorts. The ROS-related signature has demonstrated a significant negative relationship with antitumor immunity and dendritic cell maturation and activation. Moreover, The ROS-related signature showed predictive value on immunotherapy outcomes across multiple types of solid tumors, including LUAD. These findings reinforce the ROS-related signature as a predictive tool for LUAD and provide new insights into its link with antitumor immunity and immunotherapy efficacy. These results have implications for refining clinical assessments and tailoring immunotherapeutic strategies for patients with LUAD.

EHMT2 Inactivation in Pancreatic Epithelial Cells Shapes the Transcriptional Landscape and Inflammation Response of the Whole Pancreas

The Euchromatic Histone Methyl Transferase Protein 2 (EHMT2), also known as G9a, deposits transcriptionally repressive chromatin marks that play pivotal roles in the maturation and homeostasis of multiple organs. Recently, we have shown that EHMT2 inactivation alters growth and immune gene expression networks, antagonizing KRAS-mediated pancreatic cancer initiation and promotion. Here, we elucidate the essential role of EHMT2 in maintaining a transcriptional landscape that protects organs from inflammation. Comparative RNA-seq studies between normal postnatal and young adult pancreatic tissue from EHMT2 conditional knockout animals ( EHMT2 fl/fl ) targeted to the exocrine pancreatic epithelial cells ( Pdx1-Cre and P48 Cre/+ ), reveal alterations in gene expression networks in the whole organ related to injury-inflammation-repair, suggesting an increased predisposition to damage. Thus, we induced an inflammation repair response in the EHMT2 fl/fl pancreas and used a data science-based approach to integrate RNA-seq-derived pathways and networks, deconvolution digital cytology, and spatial transcriptomics. We also analyzed the tissue response to damage at the morphological, biochemical, and molecular pathology levels. The EHMT2 fl/fl pancreas displays an enhanced injury-inflammation-repair response, offering insights into fundamental molecular and cellular mechanisms involved in this process. More importantly, these data show that conditional EHMT2 inactivation in exocrine cells reprograms the local environment to recruit mesenchymal and immunological cells needed to mount an increased inflammatory response. Mechanistically, this response is an enhanced injury-inflammation-repair reaction with a small contribution of specific EHMT2-regulated transcripts. Thus, this new knowledge extends the mechanisms underlying the role of the EHMT2-mediated pathway in suppressing pancreatic cancer initiation and modulating inflammatory pancreatic diseases.

Moving from conventional to adaptive risk stratification for oropharyngeal cancer

Oropharyngeal cancer (OPC) poses a complex therapeutic dilemma for patients and oncologists alike, made worse by the epidemic increase in new cases associated with the oncogenic human papillomavirus (HPV). In a counterintuitive manner, the very thing which gives patients hope, the high response rate of HPV-associated OPC to conventional chemo-radiation strategies, has become one of the biggest challenges for the field as a whole. It has now become clear that for ~30-40% of patients, treatment intensity could be reduced without losing therapeutic efficacy, yet substantially diminishing the acute and lifelong morbidity resulting from conventional chemotherapy and radiation. At the same time, conventional approaches to de-escalation at a population (selected or unselected) level are hampered by a simple fact: we lack patient-specific information from individual tumors that can predict responsiveness. This results in a problematic tradeoff between the deleterious impact of de-escalation on patients with aggressive, treatment-refractory disease and the beneficial reduction in treatment-related morbidity for patients with treatment-responsive disease. True precision oncology approaches require a constant, iterative interrogation of solid tumors prior to and especially during cancer treatment in order to tailor treatment intensity to tumor biology. Whereas this approach can be deployed in hematologic diseases with some success, our ability to extend it to solid cancers with regional metastasis has been extremely limited in the curative intent setting. New developments in metabolic imaging and quantitative interrogation of circulating DNA, tumor exosomes and whole circulating tumor cells, however, provide renewed opportunities to adapt and individualize even conventional chemo-radiation strategies to diseases with highly variable biology such as OPC. In this review, we discuss opportunities to deploy developing technologies in the context of institutional and cooperative group clinical trials over the coming decade.

Crosstalk of cell death pathways unveils an autophagy-related gene AOC3 as a critical prognostic marker in colorectal cancer

The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Specifically, we identified a subtype (CDN4) endowed with high autophagy activity and the worst prognosis. Furthermore, AOC3 was identified as a potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and significant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC.

Biomarker-directed targeted therapy plus durvalumab in advanced non-small-cell lung cancer: a phase 2 umbrella trial

For patients with non-small-cell lung cancer (NSCLC) tumors without currently targetable molecular alterations, standard-of-care treatment is immunotherapy with anti-PD-(L)1 checkpoint inhibitors, alone or with platinum-doublet therapy. However, not all patients derive durable benefit and resistance to immune checkpoint blockade is common. Understanding mechanisms of resistance-which can include defects in DNA damage response and repair pathways, alterations or functional mutations in STK11/LKB1, alterations in antigen-presentation pathways, and immunosuppressive cellular subsets within the tumor microenvironment-and developing effective therapies to overcome them, remains an unmet need. Here the phase 2 umbrella HUDSON study evaluated rational combination regimens for advanced NSCLC following failure of anti-PD-(L)1-containing immunotherapy and platinum-doublet therapy. A total of 268 patients received durvalumab (anti-PD-L1 monoclonal antibody)-ceralasertib (ATR kinase inhibitor), durvalumab-olaparib (PARP inhibitor), durvalumab-danvatirsen (STAT3 antisense oligonucleotide) or durvalumab-oleclumab (anti-CD73 monoclonal antibody). Greatest clinical benefit was observed with durvalumab-ceralasertib; objective response rate (primary outcome) was 13.9% (11/79) versus 2.6% (5/189) with other regimens, pooled, median progression-free survival (secondary outcome) was 5.8 (80% confidence interval 4.6-7.4) versus 2.7 (1.8-2.8) months, and median overall survival (secondary outcome) was 17.4 (14.1-20.3) versus 9.4 (7.5-10.6) months. Benefit with durvalumab-ceralasertib was consistent across known immunotherapy-refractory subgroups. In ATM-altered patients hypothesized to harbor vulnerability to ATR inhibition, objective response rate was 26.1% (6/23) and median progression-free survival/median overall survival were 8.4/22.8 months. Durvalumab-ceralasertib safety/tolerability profile was manageable. Biomarker analyses suggested that anti-PD-L1/ATR inhibition induced immune changes that reinvigorated antitumor immunity. Durvalumab-ceralasertib is under further investigation in immunotherapy-refractory NSCLC.ClinicalTrials.gov identifier: NCT03334617.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

Translational research on drug development and biomarker discovery for hepatocellular carcinoma

Translational research plays a key role in drug development and biomarker discovery for hepatocellular carcinoma (HCC). However, unique challenges exist in this field because of the limited availability of human tumor samples from surgery, the lack of homogenous oncogenic driver mutations, and the paucity of adequate experimental models. In this review, we provide insights into these challenges and review recent advancements, with a particular focus on the two main agents currently used as mainstream therapies for HCC: anti-angiogenic agents and immunotherapy. First, we examine the pre-clinical and clinical studies to highlight the challenges of determining the optimal therapeutic combinations with biologically effective dosage for HCC. Second, we discuss biomarker studies focusing on anti-PD1/anti-PD-L1-based combination therapy. Finally, we discuss the progress made in our collective understanding of tumor immunology and in multi-omics analysis technology, which enhance our understanding of the mechanisms underlying immunotherapy, characterize different patient subgroups, and facilitate the development of novel combination approaches to improve treatment efficacy. In summary, this review provides a comprehensive overview of efforts in translational research aiming at advancing our understanding of and improving the treatment of HCC.

A Dysfunctional T-cell Gene Signature for Predicting Nonresponse to PD-1 Blockade in Non-small Cell Lung Cancer That Is Suitable for Routine Clinical Diagnostics

PURPOSE

Because PD-1 blockade is only effective in a minority of patients with advanced-stage non-small cell lung cancer (NSCLC), biomarkers are needed to guide treatment decisions. Tumor infiltration by PD-1T tumor-infiltrating lymphocytes (TIL), a dysfunctional TIL pool with tumor-reactive capacity, can be detected by digital quantitative IHC and has been established as a novel predictive biomarker in NSCLC. To facilitate translation of this biomarker to the clinic, we aimed to develop a robust RNA signature reflecting a tumor's PD-1T TIL status.

EXPERIMENTAL DESIGN

mRNA expression analysis using the NanoString nCounter platform was performed in baseline tumor samples from 41 patients with advanced-stage NSCLC treated with nivolumab that were selected on the basis of PD-1T TIL infiltration by IHC. Samples were included as a training cohort (n = 41) to develop a predictive gene signature. This signature was independently validated in a second cohort (n = 42). Primary outcome was disease control at 12 months (DC 12 m), and secondary outcome was progression-free and overall survival.

RESULTS

Regularized regression analysis yielded a signature using 12 out of 56 differentially expressed genes between PD-1T IHC-high tumors from patients with DC 12 m and PD-1T IHC-low tumors from patients with progressive disease (PD). In the validation cohort, 6/6 (100%) patients with DC 12 m and 23/36 (64%) with PD were correctly classified with a negative predictive value (NPV) of 100% and a positive predictive value of 32%.

CONCLUSIONS

The PD-1T mRNA signature showed a similar high sensitivity and high NPV as the digital IHC quantification of PD-1T TIL. This finding provides a straightforward approach allowing for easy implementation in a routine diagnostic clinical setting.

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

Combined Immunotherapy Improves Outcome for Replication-Repair-Deficient (RRD) High-Grade Glioma Failing Anti-PD-1 Monotherapy: A Report from the International RRD Consortium

Immune checkpoint inhibition (ICI) is effective for replication-repair-deficient, high-grade gliomas (RRD-HGG). The clinical/biological impact of immune-directed approaches after failing ICI monotherapy is unknown. We performed an international study on 75 patients treated with anti-PD-1; 20 are progression free (median follow-up, 3.7 years). After second progression/recurrence (n = 55), continuing ICI-based salvage prolonged survival to 11.6 months (n = 38; P < 0.001), particularly for those with extreme mutation burden (P = 0.03). Delayed, sustained responses were observed, associated with changes in mutational spectra and the immune microenvironment. Response to reirradiation was explained by an absence of deleterious postradiation indel signatures (ID8). CTLA4 expression increased over time, and subsequent CTLA4 inhibition resulted in response/stable disease in 75%. RAS-MAPK-pathway inhibition led to the reinvigoration of peripheral immune and radiologic responses. Local (flare) and systemic immune adverse events were frequent (biallelic mismatch-repair deficiency > Lynch syndrome). We provide a mechanistic rationale for the sustained benefit in RRD-HGG from immune-directed/synergistic salvage therapies. Future approaches need to be tailored to patient and tumor biology.

SIGNIFICANCE

Hypermutant RRD-HGG are susceptible to checkpoint inhibitors beyond initial progression, leading to improved survival when reirradiation and synergistic immune/targeted agents are added. This is driven by their unique biological and immune properties, which evolve over time. Future research should focus on combinatorial regimens that increase patient survival while limiting immune toxicity. This article is featured in Selected Articles from This Issue, p. 201.

The Identification of Gamma-Glutamyl Hydrolase in Uterine Corpus Endometrial Carcinoma: a Predictive Model and Machine Learning

BACKGROUND

Poor neoplastic differentiation contributes to the rapid progression of uterine corpus endometrial carcinoma (UCEC). Thus, it is essential to identify candidate genes, clarifying the carcinogenesis and progression of UCEC.

METHODS

We screened genes that affect differentiation and prognosis in UCEC. Least absolute selection and shrinkage operator (LASSO) regression, univariate Cox, and multivariate Cox proportional risk regression analyses were performed to screen out γ-glutamyl hydrolase (GGH) as the candidate gene. The clinical value of GGH on prognosis was evaluated. The relationship between GGH and immune infiltration was assessed by CIBERSORT, EPIC, ssGSEA, unsupervised clustering and immunohistochemistry (IHC). Additionally, we investigated the effect of GGH knockdown in vitro.

RESULTS

Among the GGH, CDKN2A, and SIX1 genes, the impact of GGH was predominant on immune infiltration in UCEC. A nomogram containing GGH and other clinical features showed good predictive performance via curve analysis (DCA). In the functional analysis, GGH affected differentiation, tumour proliferation, and immune regulation. The immunosuppressive components were enriched in the GGH-high group, with poor immunotherapy efficacy. The study suggests that GGH may influence the progression of UCEC by regulating the glycolytic process.

CONCLUSIONS

GGH is closely associated with various immune cell infiltrations. Our study demonstrates the prognostic role of GGH in carcinogenesis in UCEC.