Defining and using immune archetypes to classify and treat cancer

Interferon-stimulated gene subtypes as key indicators of immune landscape and survival outcomes in ovarian cancer

PURPOSE

Ovarian cancer (OV) remains the most lethal gynecological malignancy, underscoring the critical need for robust prognostic biomarkers to enhance patient outcomes. In this study, we classified OV patients by their interferon-stimulated gene (ISG) expression profiles and investigated the associations between these subtypes, the immune microenvironment, and survival outcomes.

METHODS

We employed consensus clustering in the TCGA-OV cohort (n = 376) to classify patients into ISG-related subgroups. Survival analysis, differential gene expression (DESeq), KEGG and GSEA pathway enrichment analyses, genomic variation assessments, immune cell profiling using the CIBERSORT algorithm, and TIDE analysis were conducted in the TCGA-OV cohort. In addition, immune checkpoint marker expressions were assessed using data from the TCGA-OV cohort and multiplex immunofluorescence (mIF) staining on an independent cohort (n = 80).

RESULTS

Two distinct ISG subtypes were identified: ISG Cluster A and ISG Cluster B. Patients in ISG Cluster B exhibited significantly improved overall survival (OS) (p = 0.0442). A total of 328 dysregulated genes were identified, with Cluster B showing overexpression of immune-related genes and enhanced involvement in immune signaling pathways. ISG Cluster B also presented higher tumor mutation burden (TMB) and an enriched immune profile, including M1 macrophages and CD8 + T cells. TIDE analysis indicated a more favorable response to immune checkpoint inhibitors in this cluster, corroborated by high expressions of PD-L1 and ISG15, which were associated with prolonged OS.

CONCLUSIONS

Our findings demonstrate that ISG-related subtypes are significantly associated with the immune microenvironment and survival outcomes in OV. The biomarkers identified in this study have the potential to inform precision therapy development, thereby enhancing treatment efficacy and personalized care for OV patients.

Enhancing immuno-oncology investigations through multidimensional decoding of tumor microenvironment with IOBR 2.0

The use of large transcriptome datasets has greatly improved our understanding of the tumor microenvironment (TME) and helped develop precise immunotherapies. The growing application of multi-omics, single-cell RNA sequencing (scRNA-seq), and spatial transcriptome sequencing has led to many new insights, yet these findings still require clinical validation in large cohorts. To advance multi-omics integration in TME research, we have upgraded the Immuno-Oncology Biological Research (IOBR) package to IOBR 2.0, restructuring and standardizing its analytical workflow. IOBR 2.0 offers six modules for TME analysis based on multi-omics data, including data preprocessing, TME estimation, TME infiltration pattern identification, cellular interaction analysis, genome and TME interaction, and feature visualization, as well as modeling. Additionally, IOBR 2.0 enables constructing gene signatures and reference matrices from scRNA-seq data for TME deconvolution. The user-friendly pipeline provides comprehensive insights into tumor-immune interactions, and a detailed GitBook(https://iobr.github.io/book/) offers a complete manual and analysis guide for each module.

B cells spatial organization defines their phenotype and function in cancer "Tell me with whom you consort, and I will tell you who you are" - Goethe

The presence of B cells and their subtypes in the tumor environment has been recognized a for very long time. Immunoglobulins specific for more than thousands of tumor-associated antigens were detected in the sera of patients with cancer; however, antibody-mediated cancer cell killing is usually impaired. The role of humoral immune response remained elusive until recently, with new discoveries regarding their contribution in regulating antitumor immunity, particularly during immunotherapy. Humoral immunity has been described to promote or attenuate tumorigenesis and can have opposing effects on therapeutic outcome in different tumor entities. The antagonism effect of B cells depends on their subtypes and immunoglobulin isotypes and is regulated by their spatial distribution and localization. In this short review, we will focus on how the spatial organization of B cells within the tumor microenvironment, tumor-associated lymph nodes, and tertiary lymphoid structures define their fate and function and contribute to the regulation of antitumor immunity.

Platelet factor 4-induced TH1-Treg polarization suppresses antitumor immunity

The tumor microenvironment (TME) contains a number of immune-suppressive cells such as T helper 1-polarized regulatory T cells (TH1-Treg cells). However, little is known about the mechanism behind the abundant presence of TH1-Treg cells in the TME. We demonstrate that selective depletion of arginase I (Arg1)-expressing tumor-associated macrophages (Arg1+ TAMs) inhibits tumor growth and concurrently reduces the ratio of TH1-Treg cells in the TME. Arg1+ TAMs secrete the chemokine platelet factor 4 (PF4), which reinforces interferon-γ (IFN-γ)-induced Treg cell polarization into TH1-Treg cells in a manner dependent on CXCR3 and the IFN-γ receptor. Both genetic PF4 inactivation and PF4 neutralization hinder TH1-Treg cell accumulation in the TME and reduce tumor growth. Collectively, our study highlights the importance of Arg1+ TAM-produced PF4 for high TH1-Treg cell levels in the TME to suppress antitumor immunity.

Tumor microenvironment RNA test to predict immunotherapy outcomes in advanced gastric cancer: The TIMES001 trial

BACKGROUND

Clinical trials support the efficacy of immune checkpoint blockades (ICBs) plus chemotherapy in a subset of patients with metastatic gastric cancer (mGC). To identify the determinants of response, we developed a TMEscore model to assess tumor microenvironment (TME), which was previously proven to be a biomarker for ICBs.

METHODS

A reference database of TMEscore assays was established using PCR assay kits containing 30 TME genes. This multi-center prospective clinical trial (NCT#04850716) included patients with mGC who were administered ICB combined with chemotherapy as a first-line regimen. Eighty-six tumor samples extracted from five medical centers before treatment were used to estimate the TMEscore, PD-L1 (CPS), and mismatch repair deficiency.

FINDINGS

The objective response rate (ORR) and median PFS of the cohort were 31.4% and six months. Enhanced ORR was observed in TMEscore-high mGC patients (ORR = 59%). The survival analysis demonstrated that high TMEscore was significantly associated with a more favorable PFS and OS. Moreover, TMEscore was found to be a predictive biomarker that surpassed MSI and CPS (AUC = 0.873, 0.511, and 0.524, respectively). By integrating the TMEscore and clinical variables, the fused model further enhances the predictive efficiency and translational application in a clinical setting.

CONCLUSIONS

This prospective clinical study indicates that the TMEscore assay is a robust biomarker for screening patients with mGC who may derive survival benefits from ICB plus chemotherapy.

FUNDING

Guangdong Basic and Applied Basic Research Foundation (2023A1515011214), Science and Technology Program of Guangzhou (202206080011), and Guangzhou Science and Technology Project (2023A03J0722 and 2023A04J2357).

DKN-01 in Combination With Tislelizumab and Chemotherapy as First-Line Therapy in Advanced Gastric or Gastroesophageal Junction Adenocarcinoma: DisTinGuish

PURPOSE

The outcomes of anti-PD-1 agents plus fluoropyrimidine/platinum in frontline advanced gastroesophageal adenocarcinomas (aGEAs) remain poor. We investigated the safety, tolerability, and activity of fluoropyrimidine/oxaliplatin and tislelizumab with the DKK1-neutralizing antibody DKN-01 in aGEAs in a phase IIa open-label study.

PATIENTS AND METHODS

Patients had untreated human epidermal growth factor receptor 2-negative aGEAs, RECIST v1.1 measurable disease, Eastern Cooperative Oncology Group (ECOG) performance status 0-1, and adequate organ function. Patients received intravenous DKN-01 300 mg once every 2 weeks, tislelizumab 200 mg once every 3 weeks, oxaliplatin 130 mg/m2 once every 3 weeks, and capecitabine 1,000 mg/m2 twice daily on days 1-15 of each 21-day cycle. The primary end point was safety and tolerability. Key secondary end points included objective response rate (ORR) by RECISTv1.1, progression-free survival (PFS), and overall survival (OS).

RESULTS

Between September 18, 2020, and April 8, 2021, 25 patients were enrolled. All patients who received at least one dose of DKN-01 were included in the safety analysis. Most patients had gastroesophageal junction tumors, median age was 61 years, 76% were male, and 55% were ECOG of 0. All patients reported at least one treatment-emergent adverse event. The ORR was 73% (95% CI, 49.8 to 89.3), with a disease control rate of 95%. The ORR was 90% (95% CI, 55.5 to 99.7) in the DKK1-high tumor patients and 67% (95% CI, 29.9 to 92.5) in the DKK1-low tumor patients. The median PFS was 11.3 months (95% CI, 5.8 to 12.0) and the 12-month PFS rate was 33%. The median OS was 19.5 months (95% CI, 15.2 to 24.4) with a 12-month OS rate of 76% and an 18-month OS rate of 55%.

CONCLUSION

DKN-01 can be safely combined with frontline fluoropyrimidine/oxaliplatin and tislelizumab and demonstrates encouraging activity independent of PD-L1 expression levels. A randomized phase II trial is ongoing (ClinicalTrials.gov identifier: NCT04363801).

Mannosylated Fluoropolypeptide Nanovaccines Remodeling Tumor Immunosuppressive Microenvironment to Achieve Highly Potent Cancer Immunotherapy

It is challenging for nanovaccines (NVs) to effectively deliver antigens/neoantigens to prime specifically potent immunities and remodel immunosuppressive tumor microenvironment (TME) for combating immune "cold" cancers. Herein, a novel kind of mannosylated fluoropolypeptide NVs of MFPCOFG (i.e., mannosylated fluoropoly(D,L-cysteine) ovalbumin-loaded Fe2+-gallic acid) is designed that synergistically integrates triple antigen-metal-thermoimmunity to remodel immunosuppressive TME and achieve highly potent immunities. MFPCOFG plus near-infrared irradiation (NIR) effectively facilitated antigen uptake and escape, induced the maturation and antigen cross-presentations of dendritic cells and macrophages, polarized anti-inflammatory macrophage phenotype M2 into tumoricial M1, primed potent CD4+/CD8+T cells responses, proinflammatory cytokines secretion and immune memory effects, showcasing triple antigen-metal-thermoimmunity outperforming combo/mono-immunity. Importantly, both MFPCOFG + NIR and personalized NVs can remarkably enhance the tumor infiltration of CD4+/CD8+T and NK cells to boost potent immunities and long-lasting memory effects, reduce regulatory T (Tregs) and M2 to remodel immunosuppressive TME in B16-OVA and 4T1 models, achieving superior tumor prevention, ablation, and tumor relapse and metastasis inhibition, as further orchestrated with anti-PD-1. Consequently, this work opens up a new avenue to design biocompatible polypeptide nanovaccines with potent immune-priming and TME-remodeling capabilities, holding great potentials to combat immune "cold" cancers with clinic-used anti-PD-1 for cancer immunotherapy and personalized immunotherapy.

Pan-cancer profiling of tumor-infiltrating natural killer cells through transcriptional reference mapping

The functional diversity of natural killer (NK) cell repertoires stems from differentiation, homeostatic, receptor-ligand interactions and adaptive-like responses to viral infections. In the present study, we generated a single-cell transcriptional reference map of healthy human blood- and tissue-derived NK cells, with temporal resolution and fate-specific expression of gene-regulatory networks defining NK cell differentiation. Transfer learning facilitated incorporation of tumor-infiltrating NK cell transcriptomes (39 datasets, 7 solid tumors, 427 patients) into the reference map to analyze tumor microenvironment (TME)-induced perturbations. Of the six functionally distinct NK cell states identified, a dysfunctional stressed CD56bright state susceptible to TME-induced immunosuppression and a cytotoxic TME-resistant effector CD56dim state were commonly enriched across tumor types, the ratio of which was predictive of patient outcome in malignant melanoma and osteosarcoma. This resource may inform the design of new NK cell therapies and can be extended through transfer learning to interrogate new datasets from experimental perturbations or disease conditions.

A Multivalent DNA Nanoparticle/Peptide Hybrid Molecular Modality for the Modulation of Protein-Protein Interactions in the Tumor Microenvironment

Despite success in the treatment of some blood cancers and melanoma, positive response to immunotherapies remains disappointingly low in the treatment of solid tumors. The context of the molecular crosstalk within the tumor microenvironment can result in dysfunctional immune cell activation, leading to tumor tolerance and progression. Although modulating these protein-protein interactions (PPIs) is vital for appropriate immune cell activation and recognition, targeting nonenzymatic PPIs has proven to be fraught with challenges. To address this, we introduce a synthetic, multivalent molecular modality comprised of small interfering peptides precisely hybridized to a semi-rigid DNA scaffold. Herein, we describe a prototype of this modality that targets the IL-33/ST2 signaling axis, which is associated with tumor tolerance and immunotherapy treatment failure. Using peptides that mimic the specific high energy "hotspot" residues with which the IL-33/ST2 co-receptor, IL-1RAcP, interacts with the initial binary complex, we show this platform to effectively bind IL-33/ST2 with aK D of 110 nM. Additionally, this molecule effectively abrogates signal transduction in cell models at high nanomolar concentrations and is exquisitely selective for this complex over structurally similar PPIs within the same cytokine superfamily.

Exploiting temporal aspects of cancer immunotherapy

Many mechanisms underlying an effective immunotherapy-induced antitumour response are transient and critically time dependent. This is equally true for several immunological events in the tumour microenvironment induced by other cancer treatments. Immune checkpoint therapy (ICT) has proven to be very effective in the treatment of some cancers, but unfortunately, with many cancer types, most patients do not experience a benefit. To improve outcomes, a multitude of clinical trials are testing combinations of ICT with various other treatment modalities. Ideally, those combination treatments should take time-dependent immunological events into account. Recent studies have started to map the dynamic cellular and molecular changes that occur during treatment with ICT, in the tumour and systemically. Here, we overlay the dynamic ICT response with the therapeutic response following surgery, radiotherapy, chemotherapy and targeted therapies. We propose that by combining treatments in a time-conscious manner, we may optimally exploit the interactions between the individual therapies.

HTR2B as a novel biomarker of chronic obstructive pulmonary disease with lung squamous cell carcinoma

Chronic obstructive pulmonary disease (COPD) is often associated with lung squamous cell carcinoma (LUSC), which has the same etiology (smoking, inflammation, oxidative stress, microenvironmental changes, and genetics). Smoking, inflammation, and airway remodeling are the most important and classical mechanisms of COPD comorbidity in LUSC patients. Cancer can occur during repeated airway damage and repair (airway remodeling). Changes in the inflammatory and immune microenvironments, which can cause malignant transformation of some cells, are currently being revealed in both LUSC and COPD patients. We obtained the GSE76925 dataset from the Gene Expression Omnibus database. Screening for possible COPD biomarkers was performed using the LASSO regression model and a random forest classifier. The compositional patterns of the immune cell fraction in COPD patients were determined using CIBERSORT. HTR2B expression was analyzed using validation datasets (GSE47460, GSE106986, and GSE1650). HTR2B expression in COPD cell models was determined via real-time quantitative PCR. Epithelial-mesenchymal transition (EMT) marker expression levels were determined after knocking down or overexpressing HTR2B. HTR2B function and mechanism in LUSC were analyzed with the Kaplan‒Meier plotter database. HTR2B expression was inhibited to detect changes in LUSC cell proliferation. A total of 1082 differentially expressed genes (DEGs) were identified in the GSE76925 dataset (371 genes were significantly upregulated, and 711 genes were significantly downregulated). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were mainly enriched in the p53 signaling and β-alanine metabolism pathways. Gene Ontology enrichment analysis indicated that the DEGs were largely related to transcription initiation from the RNA polymerase I promoter and to the regulation of mononuclear cell proliferation. The LASSO regression model and random forest classifier results revealed that HTR2B, DPYS, FRY, and CD19 were key COPD genes. Immune cell infiltration analysis indicated that these genes were closely associated with immune cells. Analysis of the validation sets suggested that HTR2B was upregulated in COPD patients. HTR2B was significantly upregulated in COPD cell models, and its upregulation was associated with increased EMT marker expression. Compared with that in bronchial epithelial cells, HTR2B expression was upregulated in LUSC cells, and inhibiting HTR2B expression led to the inhibition of LUSC cell proliferation. In conclusions, HTR2B might be a new biomarker and therapeutic target in COPD patients with LUSC.

Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression. Meanwhile, we constructed a multi-omics prognostic model that suggested the patients exhibiting downregulated expression of NETs may have an unfavorable outcome. We also confirmed TLR2 as a potent prognosis factor and patients with low TLR2 expression had more effective T cells and an overall survival extension for 6 months. Targeting TLR2 might be a promising strategy to reverse immunosuppression and control tumor progression for an improved prognosis.

Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in patients with cancer

The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.

Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer

Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches.

SIGNIFICANCE

The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.

HOXC9 characterizes a suppressive tumor immune microenvironment and integration with multiple immune biomarkers predicts response to PD-1 blockade plus chemotherapy in lung adenocarcinoma

BACKGROUND

The quest for dependable biomarkers to predict responses to immune checkpoint inhibitors (ICIs) combined with chemotherapy in advanced non-small cell lung cancer remains unfulfilled. HOXC9, known for its role in oncogenesis and creating a suppressive tumor microenvironment (TME), shows promise in enhancing predictive precision when included as a TME biomarker. This study explores the predictive significance of HOXC9 for ICI plus chemotherapy efficacy in lung adenocarcinoma (LUAD).

METHODS

Following the bioinformatic findings, assays were performed to ascertain the effects of Hoxc9 on oncogenesis and response to programmed death 1 (PD-1) blockade. Furthermore, a cohort of LUAD patients were prospectively enrolled to receive anti-PD-1 plus chemotherapy. Based on the expression levels, baseline characteristics, and clinical outcomes, the predictive potential of HOXC9, PD-L1, CD4, CD8, CD68, and FOXP3 was integrally analyzed. HOXC9 not only mediated oncogenesis, but also corelated with suppressive TME. CMT167 and LLC cell lines unveiled the impacts of Hoxc9 on proliferation, invasion, and migration. Subsequently, tumor-bearing murine models were established to validate the inverse relationship between Hoxc9 expression and effective CD8+ T cells.

RESULTS

Inhibition of Hoxc9 significantly curtailed tumor growth (P<0.05), independent of PD-1 blockade. In patient studies, while individual markers fell short in prognosticating survival, a notable elevation in CD8-positive expression was observed in responders (P=0.042). Yet, the amalgamation of HOXC9 with other markers provided a more distinct differentiation between responders and non-responders. Notably, patients displaying PD-L1+/HOXC9- and CD8+/HOXC9- phenotypes exhibited significantly prolonged progression-free survival.

CONCLUSIONS

The expression of HOXC9 may serve as a biomarker to amplifying predictive efficacy for ICIs plus chemotherapy, which is also a viable oncogene and therapeutic target for immunotherapy in LUAD.

Ceramide metabolism-related prognostic signature and immunosuppressive function of ST3GAL1 in osteosarcoma

Osteosarcoma is the most common primary malignant bone tumor with elevated disability and mortality rates in children and adolescents and the therapeutic effect for osteosarcoma has remained stagnant in the past 30 years. Emerging evidence has shown ceramide metabolism plays a vital role in tumor progression, but its mechanisms in osteosarcoma progression remain unknown. Through consensus clustering and LASSO regression analysis based on the osteosarcoma cohorts from TARGET database, we constructed a ceramide metabolism-related prognostic signature including ten genes for osteosarcoma, with ST3GAL1 exhibiting the highest hazard ratio. Biological signatures analysis demonstrated that ceramide metabolism was associated with immune-related pathways, immune cell infiltration and the expression of immune checkpoint genes. Single-cell profiling revealed that ceramide metabolism was enriched in myeloid, osteoblast and mesenchymal cells. The interaction between TAMs and CD8+ T cells played an essential role in osteosarcoma. ST3GAL1 regulated the SPP1-CD44 interaction between TAMs and CD8+ T cells and IL-10 secretion in TAMs through α2,3 sialic acid receptors, which inhibited CD8+ T cell function. IHC analysis showed that ST3GAL1 expression correlated with the prognosis of osteosarcoma patients. Co-culture assay revealed that upregulation of ST3GAL1 in tumor cells regulated the differentiation of TAMs and cytokine secretion. Collectively, our findings demonstrated that ceramide metabolism was associated with clinical outcome in osteosarcoma. ST3GAL1 facilitated tumor progression through regulating tumor immune microenvironment, providing a feasible therapeutic approach for patients with osteosarcoma.

Enhancing personalized immune checkpoint therapy by immune archetyping and pharmacological targeting

Immune checkpoint inhibitors (ICIs) are an expanding class of immunotherapeutic agents with the potential to cure cancer. Despite the outstanding clinical response in patient subsets, most individuals become refractory or develop resistance. Patient stratification and personalized immunotherapies are limited by the absence of predictive response markers. Recent findings show that dominant patterns of immune cell composition, T-cell status and heterogeneity, and spatiotemporal distribution of immune cells within the tumor microenvironment (TME) are becoming essential determinants of prognosis and therapeutic response. In this context, ICIs also function as investigational tools and proof of concept, allowing the validation of the identified mechanisms. After reviewing the current state of ICIs, this article will explore new comprehensive predictive markers for ICIs based on recent discoveries. We will discuss the recent establishment of a classification of TMEs into immune archetypes as a tool for personalized immune profiling, allowing patient stratification before ICI treatment. We will discuss the developing comprehension of T-cell diversity and its role in shaping the immune profile of patients. We describe the potential of strategies that score the mutual spatiotemporal modulation between T-cells and other cellular components of the TME. Additionally, we will provide an overview of a range of synthetic and naturally occurring or derived small molecules. We will compare compounds that were recently identified by in silico prediction to wet lab-validated drug candidates with the potential to function as ICIs and/or modulators of the cellular components of the TME.

CD40 agonism improves anti-tumor T cell priming induced by the combination of radiation therapy plus CTLA4 inhibition and enhances tumor response

Radiation therapy (RT) combined with CTLA4 blockers converts immunosuppressed (cold) mouse triple negative breast cancers (TNBCs) into immune infiltrated (hot) lesions. We have recently shown that targeting the myeloid compartment to improve dendritic cell activation is required for most TNBC-bearing mice to achieve superior therapeutic responses to RT plus CTLA4 inhibitors.

A tumor microenvironment-based classification of gastric cancer for more effective diagnosis and treatment

With approximately one million diagnosed cases and over 700,000 deaths recorded annually, gastric cancer (GC) is the third most common cause of cancer-related deaths worldwide. GC is a heterogeneous tumor. Thus, optimal management requires biomarkers of prognosis, treatment selection, and treatment response. The Cancer Genome Atlas program sub-classified GC into molecular subtypes, providing a framework for treatment personalization using traditional chemotherapies or biologics. Here, we report a comprehensive study of GC vascular and immune tumor microenvironment (TME)-based on stage and molecular subtypes of the disease and their correlation with outcomes. Using tissues and blood circulating biomarkers and a molecular classification, we identified cancer cell and tumor archetypes, which show that the TME evolves with the disease stage and is a major determinant of prognosis. Moreover, our TME-based subtyping strategy allowed the identification of archetype-specific prognostic biomarkers such as CDH1-mutant GC and circulating IL-6 that provided information beyond and independent of TMN staging, MSI status, and consensus molecular subtyping. The results show that integrating molecular subtyping with TME-specific biomarkers could contribute to improved patient prognostication and may provide a basis for treatment stratification, including for contemporary anti-angiogenesis and immunotherapy approaches.