Archetypes of checkpoint-responsive immunity

The war between the immune system and the tumor - using immune biomarkers as tracers

Nowadays, immunotherapy is one of the most promising anti-tumor therapeutic strategy. Specifically, immune-related targets can be used to predict the efficacy and side effects of immunotherapy and monitor the tumor immune response. In the past few decades, increasing numbers of novel immune biomarkers have been found to participate in certain links of the tumor immunity to contribute to the formation of immunosuppression and have entered clinical trials. Here, we systematically reviewed the oncogenesis and progression of cancer in the view of anti-tumor immunity, particularly in terms of tumor antigen expression (related to tumor immunogenicity) and tumor innate immunity to complement the cancer-immune cycle. From the perspective of integrated management of chronic cancer, we also appraised emerging factors affecting tumor immunity (including metabolic, microbial, and exercise-related markers). We finally summarized the clinical studies and applications based on immune biomarkers. Overall, immune biomarkers participate in promoting the development of more precise and individualized immunotherapy by predicting, monitoring, and regulating tumor immune response. Therefore, targeting immune biomarkers may lead to the development of innovative clinical applications.

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.

Bridging the Gap between Innate and Adaptive Immunity in the Lung: Summary of the Aspen Lung Conference 2022

Although significant strides have been made in the understanding of pulmonary immunology, much work remains to be done to comprehensively explain coordinated immune responses in the lung. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic only served to highlight the inadequacy of current models of host-pathogen interactions and reinforced the need for current and future generations of immunologists to unravel complex biological questions. As part of that effort, the 64th Annual Thomas L. Petty Aspen Lung Conference was themed "Bridging the Gap between Innate and Adaptive Immunity in the Lung" and featured exciting work from renowned immunologists. This report summarizes the proceedings of the 2022 Aspen Lung Conference, which was convened to discuss the roles played by innate and adaptive immunity in disease pathogenesis, evaluate the interface between the innate and adaptive immune responses, assess the role of adaptive immunity in the development of autoimmunity and autoimmune lung disease, discuss lessons learned from immunologic cancer treatments and approaches, and define new paradigms to harness the immune system to prevent and treat lung diseases.

Identification of stromal cell proportion-related genes in the breast cancer tumor microenvironment using CorDelSFS feature selection: implications for tumor progression and prognosis

Background: The tumor microenvironment (TME) of breast cancer (BRCA) is a complex and dynamic micro-ecosystem that influences BRCA occurrence, progression, and prognosis through its cellular and molecular components. However, as the tumor progresses, the dynamic changes of stromal and immune cells in TME become unclear. Objective: The aim of this study was to identify differentially co-expressed genes (DCGs) associated with the proportion of stromal cells in TME of BRCA, to explore the patterns of cell proportion changes, and ultimately, their impact on prognosis. Methods: A new heuristic feature selection strategy (CorDelSFS) was combined with differential co-expression analysis to identify TME-key DCGs. The expression pattern and co-expression network of TME-key DCGs were analyzed across different TMEs. A prognostic model was constructed using six TME-key DCGs, and the correlation between the risk score and the proportion of stromal cells and immune cells in TME was evaluated. Results: TME-key DCGs mimicked the dynamic trend of BRCA TME and formed cell type-specific subnetworks. The IG gene-related subnetwork, plasmablast-specific expression, played a vital role in the BRCA TME through its adaptive immune function and tumor progression inhibition. The prognostic model showed that the risk score was significantly correlated with the proportion of stromal cells and immune cells in TME, and low-risk patients had stronger adaptive immune function. IGKV1D-39 was identified as a novel BRCA prognostic marker specifically expressed in plasmablasts and involved in adaptive immune responses. Conclusions: This study explores the role of proportionate-related genes in the tumor microenvironment using a machine learning approach and provides new insights for discovering the key biological processes in tumor progression and clinical prognosis.

Defining and using immune archetypes to classify and treat cancer

Tumours are surrounded by a host immune system that can suppress or promote tumour growth. The tumour microenvironment (TME) has often been framed as a singular entity, suggesting a single type of immune state that is defective and in need of therapeutic intervention. By contrast, the past few years have highlighted a plurality of immune states that can surround tumours. In this Perspective, we suggest that different TMEs have 'archetypal' qualities across all cancers - characteristic and repeating collections of cells and gene-expression profiles at the level of the bulk tumour. We discuss many studies that together support a view that tumours typically draw from a finite number (around 12) of 'dominant' immune archetypes. In considering the likely evolutionary origin and roles of these archetypes, their associated TMEs can be predicted to have specific vulnerabilities that can be leveraged as targets for cancer treatment with expected and addressable adverse effects for patients.

Identification of Ferroptosis-related molecular model and immune subtypes of hepatocellular carcinoma for individual therapy

BACKGROUND

Excessive iron accumulation and lipid peroxidation are primary characteristics of ferroptosis in hepatocellular carcinoma (HCC). Ferroptosis inducer combined with immunotherapy has become a new hope for HCC patients. Therefore, the construction and validation of subtype-specific sensitivity to ferroptosis inducer will be helpful for hierarchical management and precise individual therapy.

METHODS

RNA-seq transcriptome and clinical data of HCC patients were extracted from International Cancer Genome Consortium (ICGC) dataset and The Cancer Genome Atlas (TCGA) dataset. Consistency matrix and data clustering of the both cohorts were constructed by 'ConsensusClusterPlus' package. Single-sample gene set enrichment analysis (ssGSEA) analysis was performed to evaluate immune infiltration. Cox analysis was utilized to construct a ferroptosis phenotype-related prognostic model (FRPM) in HCC. The predictive efficiency of the constructed FRPM was evaluated through Kaplan Meier (K-M) survival analyses and Receiver Operating Characteristic (ROC) curves. The expression levels of candidate genes were detected and validated by Real-Time PCR between liver cancer tissues and adjacent non-tumor liver tissues.

RESULTS

45 differentially expressed ferroptosis-related genes (FRGs) were identified between HCC tissues and non-tumor liver tissues. Furthermore, four ferroptosis-associated clusters (FACs) of HCC were established via consensus clustering. Subsequently, we established a FRPM, consisting of four prognostic genes (SLC7A11, SLC1A5, GCLM and SAT1), to evaluate the survival of HCC patients, based on which, patients were divided into high-risk group and low-risk group. The high-risk group exhibited worse survival compared to low-risk group (p < 0.0001 both in TCGA and ICGC cohorts). Patients belong to different FACs or different risk scores showed distinct clinical characteristics. Moreover, in the validation experiment, the transcriptional expression levels of the four prognostic genes were consistent with the results drew from datasets.

CONCLUSION

We revealed a novel FRGs signature, which may provide the molecular characteristic data for effectively prognostic evaluation and potential personalized therapy for HCC patients.