December 4, 2022

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Heterogeneity of the tumor immune microenvironment

Heterogeneity of the tumor immune microenvironment



 

Heterogeneity of the tumor immune microenvironment.

During tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous.

Thus, tumors may be infiltrated by multiple immune-related components, including the cytokine/chemokine milieu, cytotoxic activity, or immunosuppressive factors.

This immune heterogeneity is prevalent in nearly all solid tumors and varies spatially or temporally with tumor progression and therapeutic intervention.

The heterogeneity of antitumor immunity is closely related to disease progression and responsiveness to treatment, especially in the field of immunotherapy.

 

Therefore, an accurate understanding of tumor immune heterogeneity is crucial for the development of effective treatments.

With the help of multiregional and omics sequencing, single-cell sequencing, and longitudinal liquid biopsy approaches, recent studies have shown the complexity of studying tumor immune heterogeneity and its potential for clinical relevance in immunotherapy.

Exploring the mechanisms underlying the heterogeneity of the tumor immune microenvironment can aid our clinical assessment of tumor heterogeneity, thereby facilitating the development of more effective personalized treatments.

 

 


The origin of heterogeneity in the tumor immune microenvironment

Heterogeneity of the tumor immune microenvironment

 

 

Genetic instability

High-throughput sequencing approaches have long been used to characterize the mutational spectrum and evolutionary trajectories of tumor cells, and these studies have delineated a wide range of genetic tumor heterogeneity in spatiotemporal dimensions, including heterogeneous single-nucleotide mutations, insertions, deletions and copy number mutations.

During tumor progression, genetic instability causes these changes to occur randomly.

 

In primary tumors, mutations in the driver genes often confer a survival advantage; thus, these cells are more likely to occupy positions of growth advantage and develop into a dominant clonal population.

In contrast, passenger mutations do not confer significant growth advantages during tumor evolution, and they are considered a major source of subclonal tumor cells.

Thus, genetic instability originating from clonal and subclonal tumor cells underlies tumor evolution and spatiotemporal heterogeneity.

At the same time, this genetic heterogeneity shapes the antigenic profile of tumors and ultimately contributes to the heterogeneity of the tumor immune microenvironment.

 

Epigenetic modification

Growing evidence suggests that epigenetic remodeling of tumor cells is also involved in the formation of a heterogeneous tumor immune microenvironment.

This regulatory mechanism is mainly attributed to alterations in DNA modifications, alterations in chromatin accessibility, or regulation of gene expression at the post-transcriptional level, such as noncoding RNA interference.

These epigenetic modifications promote the malignant progression of tumor cells and contribute to the formation of the tumor immune microenvironment.

 

In addition to methylation, various chromatin and epigenetic remodeling mechanisms confer advantages to tumor cells in adapting to their surrounding environment.

Typically, epigenetic modifications are conditionally reversible.

In tumor cells, these modifications can be inherited by their progeny, and as a result, these cells exhibit marked heterogeneity in both spatial and longitudinal dimensions.

 

Microenvironmental Disturbance Fitness

Tumor cells are continuously exposed to perturbations of the extracellular microenvironment.

There is increasing evidence that intracellular adaptations can be induced by external stresses, including DNA damage responses, unfolded protein responses, and mitochondrial stress signaling.

Tumors exhibit marked heterogeneity in histology and vascular architecture.

 

Regions proximal or distal to blood vessels within the tumor may be exposed to different oxygen supplies.

Thus, immune components are able to adapt to external stimuli based on oxygen tension, glucose availability, or oxidative pathways in a spatiotemporally heterogeneous manner.

Regardless of whether immune components are well-adapted to hypoxic conditions, almost all hypoxic responses are closely related to reprogramming of the tumor immune microenvironment, which is mainly characterized by a local switch in cellular glycolytic metabolism, increased glucose consumption, pyruvate and increased lactic acid production, and acidification.

 

Response to antitumor therapy

During treatment, tumor cells and all immune components in the microenvironment are either hit ( as in radiotherapy ) or continuously exposed to antitumor drugs.

In response to these stressors, adaptive mechanisms of tumor and immune cells are activated to establish a new homeostasis.

 

Tumor cell responsiveness to therapy varies markedly due to inherent heterogeneity in driver mutations or molecular signatures.

Cytotoxic conditions cause tumor and immune cells to undergo phenotypic changes, cellular senescence and even cell death.

Local tumor clones that do not survive treatment release large amounts of ATP through autophagy-mediated cell death. These ATPs can promote chemotaxis and generate inflammatory responses in tumors.

Conversely, in the presence of extracellular nucleotidases, ATPs can be rapidly converted to adenosine in the extracellular matrix, creating an inhibitory immune microenvironment.

 

For immune cells, the T cell phenotype changes dramatically in response to ICI, with distinct T cell subset composition and cytokine production.

The complex and dynamic interactions among therapeutic drugs, tumor cells, and immune cells significantly contribute to the formation of a spatiotemporally heterogeneous immune microenvironment.

 

 


Heterogeneity of the tumor immune microenvironment

 


Spatial heterogeneity

The characteristics of the tumor immune microenvironment are mainly determined by tumor and non-tumor components.

Their localization or abundance/activity differs spatially, including surface expression of inhibitory immune checkpoints such as PD-L1 , secretion of immunosuppressive or pro-inflammatory cytokines, infiltration of immunosuppressive or effector cells, vascular The state of the system, the spatial distance of marginal regions, and the distribution of metabolic nutrients. These spatial variations also have profound implications for clinical prognosis and treatment response.

 

Heterogeneity of the tumor immune microenvironment

 

 

The phenotype of intratumoral T cells exhibited marked heterogeneity.

T cells often have different clonality, proliferative potential, differentiation stage, functional polarization, cytokine secretion profile or metabolic environment.

Regarding the propensity of the T cell repertoire, expanding/proliferating T cell receptors ( TCRs ) can be further divided into common TCR clones ( detected in all regions within the tumor ) or regional clones ( heterogeneous distribution ).

The number of common and regional TCR clones positively correlated with the burden of common and regional non-synonymous mutations, indicating regional heterogeneity, antigen-driven T cell proliferation.

In addition, it is worth noting that regulatory T cells ( Tregs ) also showed significant intratumoral spatial heterogeneity and functional orientation.

 

In addition to T cell subsets, intratumoral heterogeneity of many other immune cells has also been found in various tumor types. In gastric cancer, macrophages with CD68+CD163+CD206+ phenotype were mainly located in the stroma, and CD68+IRF8+ macrophages were overexpressed in the core zone compared with the marginal zone.

In addition to immune cell populations, stromal cells, such as fibroblasts , also display a high degree of spatial orientation in tumors.

 

Metabolic profiles are important regulators of the immune microenvironment and may play a role by affecting the proliferative potential and adaptation of cancer cells to the environment. The heterogeneity of the metabolic signature appears to contribute to the heterogeneity of the tumor immune microenvironment.

Malignant cells with high glycolytic activity can not only switch their metabolic pathways to anabolic responses, but also produce large amounts of immunosuppressive mediators, such as lactate and adenosine, to attenuate immune surveillance by cytotoxic cells.

 

Temporal heterogeneity

Tumor and immune cells are easily perturbed by genetic or non-genetic environmental factors and thus determine disease progression and response to antitumor therapy, as well as the dynamic evolution of tumor cells themselves.

RNA-Seq in patients with pancreatic ductal adenocarcinoma revealed marked changes in the infiltrating component of immune cells during the progression of the disease from a non-invasive lesion to an aggressive phenotype.

Usually manifested as decreased infiltration of CD8+ T cells and dendritic cells, and abnormal aggregation or expansion of immunosuppressive cells, including Treg, MDSC, or CAF .

 

In addition, impaired cytolytic activity, limited cell pool expansion and clonality, and progressive exhaustion of T and B cells are also present during disease progression in multiple tumor types.

The appearance of immunologically disadvantaged regions or lesions in individual patients appears to be inversely related to disease control and survival prognosis, further reinforcing the importance of spatiotemporal heterogeneity for disease outcome.

 

 

 


The clinical significance of the heterogeneity of the tumor immune microenvironment

 

Immune prognostic or predictive biomarkers for nearly all cancer patients have been established based on the analysis of a single biopsy sample.

However, heterogeneity is a significant barrier to study reproducibility and diminishes its clinical utility.

In addition, substantial evidence suggests that the heterogeneity of the tumor microenvironment, whether genetic or immune, affects the outcome of immunotherapy in patients with solid tumors.

 

Heterogeneity of PD-L1 expression

Since the first evidence supporting a correlation between PD-L1 protein expression and the efficacy of anti-PD-1 checkpoint blockade therapy, PD-L1 levels have been used as a companion diagnostic to predict the clinical response of various solid tumor types to ICI immunotherapy. 

However, there was marked heterogeneity of PD-L1 expression at both the intratumoral or intertumoral scales, as well as in the spatial and temporal dimensions.

 

After evaluating PD-L1 expression in primary and brain metastases from NSCLC patients, significant differences in PD-L1 expression between the two lesions could be observed.

PD-L1 expression is strongly induced by the IFN-γ signaling pathway, which is heterogeneously regulated in subclones containing dysfunctional JAK1/2 mutations.

Furthermore, antigen processing and presentation-deficient subclones in patients treated with ICI are associated with poor clinical outcomes in melanoma, lung and colorectal cancer.

This potential heterogeneity may explain why a subset of patients with PD-L1-positive tumors do not respond, while some patients with PD-L1-negative tumors respond well to ICI immunotherapy.

 

Heterogeneous responses in TMB hyperresponders

Mutational burden, a reasonable approximate surrogate for neoantigen burden, has been used to identify favorable responders to ICI immunotherapy in various solid tumor types.

However, the response of patients with high TMB to ICB treatment is highly heterogeneous, and a substantial proportion of patients with low TMB levels can also benefit from ICI immunotherapy, and vice versa.

In high-risk patients with TMB who do not respond well to ICI therapy, defective/dysregulated antigen presentation mechanisms are considered to be the main mechanisms of immunotherapy resistance, especially haplotype and regional expression of HLA, and expression of B2M molecules.

In addition, phylogenetic analysis found that clonal heterogeneity, whether measured by the number of clones constituting a tumor or by clonal differentiation, had a profound impact on survival outcomes from ICI treatment.

 

Heterogeneous responses in patients with MMR deficiency

Patients lacking MMR are extremely sensitive to ICI therapy, which is largely attributable to elevated predicted neoantigens and an improved immunogenic tumor microenvironment.

In patients with advanced dMMR across numerous solid tumor types, pembrolizumab has gained unprecedented recognition as the optimal treatment for patients with MSI-H tumors.

However, only a minority of patients respond well to ICI therapy.

 

Both the tumor cell intrinsic genotype and the extrinsic immune environment of dMMR tumors can influence their efficacy, and the degree of genomic instability of infiltrating immune cells appears to be largely heterogeneous in dMMR tumors, leading to limited immunogenicity discrete niches and insufficient immune-mediated tumor control, which may lead to drug resistance.

In addition, other variables that affect the response of MSI-H tumors to ICI include that, during development, they tend to perform robust immune editing and transition to a glycolytic profile, which largely contributes to immune escape.

 

 

 


Strategies to overcome the heterogeneity of the tumor immune microenvironment

 

Heterogeneity of the tumor immune microenvironment

 


Against public antigens

The existence of spatially distinct immunogenicity is the underlying reason for the heterogeneous response to immunotherapy.

Rational strategies to overcome this obstacle include the development of shared neoantigens or uniformly expressed tumor-associated antigens ( TAAs ) that can target the entire tumor niche .

 

In contrast to individualized neoantigens, common or shared neoantigens are derived from driver mutations in oncogenes or other hotspot mutations in the genome.

They are characterized by immunogenic epitopes present in subsets of patients with specific cancer subtypes.

Thus, the discovery of public neoantigens relies on the analysis of individualized neoantigens from sizable patient repertoires.

An example of a public neoantigen is the mutation of G12D on KRAS, which is common in pancreatic, colon adenocarcinoma, non-small cell lung, and colorectal cancers.

Similarly, TP53 is a well-known tumor suppressor gene that is widely mutated in a large number of cancers, has a broad spectrum of hotspot mutations, and is shared by multiple cancers.

 

Multiple antigen targeting

Overcoming immunogenicity heterogeneity by targeting multiple antigens simultaneously is another plausible approach.

This strategy minimizes the potential for immune escape in solid tumors upon antigen loss due to heterogeneous immunogenicity.

 

Currently, a variety of dual-targeting strategies have been applied to CAR-T cell therapy, two CAR-T cells targeting different epitopes respectively, or a single CAR-T cell targeting multiple epitopes simultaneously.

For example, anti-CD38/BCMA CAR-T cells have been tested in patients with multiple myeloma, and anti-CD19/CD22 bispecific CAR-T cells have been tested in patients with B-NHL.

 

Promotes immunogenic cell death and epitope spreading

In cancer immunotherapy, tumor vaccines are a promising therapeutic strategy not only because of their ability to trigger an inflammatory environment by delivering highly immunogenic antigens, but also because they broaden and diversify the antigenic spectrum by promoting epitope spreading.

 

With breakthroughs in the functional identification of individual neoantigens, robust neoantigen-specific T cell responses have been consistently detected in patients treated with synthetic neoantigens over a long clinical course.

With the persistence of neoantigen-specific T-cell clones, a diverse T-cell repertoire with a wider specification was also observed after vaccination, offering a greater possibility to fully cover the tumor mass with heteroantigenicity.

In addition to the direct delivery of synthetic peptides, RNA vaccines encoding personalized neoantigens or dendritic cell-loaded neoantigen vaccines have also successfully mobilized potent and sustained antitumor immunity with broad T cell specificity.

 

Another strategy to overcome the heterogeneity of the immune microenvironment is to use oncolytic viruses to directly kill malignant cells, which strongly promote immunity by releasing a large number of immunologically active components, including cryptic tumor-associated antigens, danger signals, cytokines, and chemokines. primary cell death.

This concomitant paracrine effect is critical for activating non-selective T cell toxicity at sites surrounding the intratumoral space, especially for sites with relatively low immunogenicity.

In addition to oncolytic viruses, various approaches can be introduced to stimulate the inflammatory immune microenvironment through mechanisms mediated by soluble components, such as novel drugs, tyrosine kinase inhibitors, cationic amphoteric peptides, microwaves, and radiotherapy.

All of this highlights a key issue, namely that a robust therapeutic response often involves the remodeling of the entire immune microenvironment into an immunocompetent, homogeneous environment.

 

 

 

 


Summary

 

Oncogenesis is an integrated and cumulative dysregulation of a series of genetic and non-genetic processes.

Due to the inherent genetic instability of tumor genomes, most tumorigenic events inevitably occur in a random manner during disease progression.

These stochastic events create the necessary conditions for the development of a heterogeneous immune microenvironment in the spatial or temporal dimension.

In addition, competition for metabolites and nutrients, therapeutic pressure, or the evolution of key oncogenes continually reshape the immune microenvironment.

This ultimately creates an opportunity for malignant cells to evade immune surveillance, ultimately leading to disease progression and metastasis.

 

This immune heterogeneity also accounts for the poor performance of predictive biomarkers based on a single biopsy and the development of resistance to immunotherapy.

Therefore, given the unending development of tumor genome instability and heterogeneity, it is necessary to focus on lessons learned from heterogeneous tumor models.

A complex, controlled model allows us to precisely understand the mechanisms that regulate the antitumor immune response to heterogeneity.

Treatment approaches should consider not only oncogenic targets or representative immune checkpoints, but also the heterogeneity and reactivity of the immune microenvironment.

Tracking the spatiotemporal interactions between tumor and immune cells is critical for guiding effective and durable responses to immunotherapy.

 

 

 

 

 

 

 

references:

1.Heterogeneity of the tumor immunemicroenvironment and its clinical relevance. Exp Hematol Oncol. 2022;11:24.

Heterogeneity of the tumor immune microenvironment

(source:internet, reference only)


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