tumor immune microenvironment

Identifying the tumor immune microenvironment-associated prognostic genes for prostate cancer

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Abstract

Purpose

This study aimed to explore novel tumor immune microenvironment (TIME)-associated biomarkers in prostate adenocarcinoma (PRAD).

Methods

PRAD RNA-sequencing data were obtained from UCSC Xena database as the training dataset. The ESTIMATE package was used to evaluate stromal, immune, and tumor purity scores. Differentially expressed genes (DEGs) related to TIME were screened using the immune and stromal scores. Gene functions were analyzed using DAVID. The LASSO method was performed to screen prognostic TIME-related genes. Kaplan–Meier curves were used to evaluate the prognosis of samples. The correlation between the screened genes and immune cell infiltration was explored using Tumor IMmune Estimation Resource. The GSE70768 dataset from the Gene Expression Omnibus was used to validate the expression of the screened genes.

Results

The ESTIMATE results revealed that high immune, stromal, and ESTIMATE scores and low tumor purity had better prognoses. Function analysis indicated that DEGs are involved in the cytokine–cytokine receptor interaction signaling pathway. In TIME-related DEGs, METTL7B, HOXB8, and TREM1 were closely related to the prognosis. Samples with low expression levels of METTL7B, HOXB8, and TREM1 had better survival times. Similarly, both the validation dataset and qRT-PCR suggested that METTL7B, HOXB8, and TREM1 were significantly decreased. The three genes showed a positive correlation with immune infiltration.

Conclusions

This study identified three TIME-related genes, namely, METTL7B, HOXB8, and TREM1, which correlated with the prognosis of patients with PRAD. Targeting the TIME-related genes might have important clinical implications when making decisions for immunotherapy in PRAD.

1 Introduction

Prostate adenocarcinoma (PRAD) remains the leading cause of cancer related mortality among men in the United States [1]. Despite advances in clinical care, mortality rates remain high, indicating a need for better understanding of the factors influencing PRAD prognosis and treatment response [2, 3].

Recent evidence suggests that PRAD prognosis is heavily dependent on the tumor microenvironment [4]. The tumor immune microenvironment (TIME), comprised of extracellular matrix, stromal cells, and other tumor associated cells, can modulate the tumor’s response to therapy and can influence the progression of the tumor [5]. TIME has been reported to profoundly influence the growth and metastasis of cancer. It affects prognosis, tumor growth, and treatment response through a variety of mechanisms [6]. The composition of the tumor microenvironment can affect prognosis by influencing the proliferation, metastasis, and drug resistance of cancer cells [7]. Factors like the abundance of immune cells, angiogenesis (new blood vessel formation), and cytokines (types of proteins) released by the environment can either inhibit or promote the growth of cancer cells [8]. These signals can also have a large impact on how a patient responds to treatment; for example, certain treatments may be targeted more directly at immunoprivileged environments, and certain drugs tested in preclinical trials may not reach the tumor due to an immunosuppressive microenvironment [9]. In terms of tumor growth, TIME affect the rate of metastasis, and provide signals for cell growth, movement, and survival [10]. TIME could also be a source of genetic mutations, which can lead to the selection of drug resistant tumor cells [11]. Additionally, the presence of certain immune cells can influence the growth and progression of tumors [12]. Finally, the microenvironment can also influence response to treatments. Factors like hypoxia (low oxygen) or the immune cell composition can affect the effectiveness of certain therapies [13]. Additionally, certain signaling pathways in the microenvironment can be targeted by drugs to suppress tumor growth and improve outcomes [14]. Overall, the tumor microenvironment is an essential component of tumor biology and can affect the prognosis, growth, and response to treatments of cancer.

In this study, we downloaded the PRAD RNA-sequencing (RNA-seq) data from the UCSC Xena database. Then, the ESTIMATE method was employed to analyze the immune and stromal scores and tumor purity of PRAD samples. In addition, we analyzed the correlation between TIME and clinical information, from which we obtained the novel TIME-related prognostic genes for PRAD.

Discussion

Multiple factors, stages, and genes are involved in the occurrence and development of PRAD, where TIME is an important factor. Recently, immunotherapy was the novel treatment for PRAD tumors, whereas the clinical outcome was related to the characteristics of malignant tumors, such as hormone dependence, low tumor mutation load, and immunosuppressive microenvironment. Besides, previous studies have found that TIME correlated with the prognosis of patients with PRAD [27]. Thus, further exploration of TIME in PRAD was significant to help doctors make decisions about the treatment method and predict the prognosis for PRAD.

The results of this study revealed that the PRAD samples with high immune and stromal scores had a better prognosis, and those with high tumor purity had a worse prognosis. In addition, we collected the OS, RFS, and DFS of samples to examine the correlation in immune and stromal scores and survival time using KM curves. The results obtained were similar to the ESTIMATE results. These observations were consistent with the results of previous studies. For example, Chen et al. [28] suggested that stromal, immune, and ESTIMATE scores closely correlated with the OS of patients with PRAD. In addition, similar results were obtained in multiple cancer types, such as breast cancer, bladder cancer, and lung adenocarcinoma, indicating that the stromal, immune, and ESTIMATE scores and tumor purity in TIME played a significant role in immunotherapy [29,30,31]. Xiang et al. [32] indicated that the stromal, immune, and ESTIMATE scores and tumor purity in the microenvironment were associated with TIME. Thus, our study screened TIME-related DEGs by comparing stromal scores and immune scores. Subsequently, 1229 TIME-related DEGs were screened using the limma package. GO BP results indicated the involvement of DEGs in the immune response. Immune response regulated the development of PRAD tumors, which played an important role when making decisions for immunotherapy [33, 34]. The DEGs might be novel biomarkers for treating PRAD. In addition, KEGG results indicated that the DEGs were related to the cytokine–cytokine receptor interaction pathway. Previous studies have found that this pathway always involved some immune-related genes that are involved in different cancers, such as renal cell carcinoma and hepatocellular carcinoma [35, 36]. This pathway might be an important factor in the immunotherapy for PRAD. Further experiments must be performed to understand the mechanism of immunotherapy in PRAD.

Previous studies have indicated that the TIME was related to the prognosis of patients with PRAD. In this study, three prognostic DEGs, namely, METTL7B, HOXB8, and TREM1, were identified. The KM curves were used to evaluate the correlation between the three DEGs and patient prognosis, suggesting that patients with low expression levels of METTL7B, HOXB8, and TREM1 had good OS, RFS, and DFS. The results were validated using the external cohort, which obtained the same results as TCGA dataset. Our results were similar with the previous studies that have used external cohorts to validated the prognostic value of the biomarkers in PRAD [37,38,39]. The method further confirmed the results in this study. This novel TIME hub genes-related risk score model provides a new theoretical basis for the prognosis assessment of PRAD patients, which is expected to be further applied in the future clinical management. A prospective study of clinical cohorts recruiting PRAD patients in different stage will help validating this risk score model. The expression of METTL7B, HOXB8, and TREM1 was examined each month. Then, the follow-up was performed to observe the prognosis of PRAD patients. The KM curves and survival analysis will be carried out to the correlation between risk score model and prognosis. This study is expected to be conducted for 5 years or even longer to obtain good persuasiveness.

Meanwhile, significant differences in METTL7B, HOXB8, and TREM1 were found between the controls and tumor samples in both mRNA levels. The three genes might be novel TIME-related biomarkers for PRAD. METTL7B, an alkyl thiol methyltransferase, could metabolize hydrogen sulfide (H2S) [40]. H2S was found to participate in the epithelial–mesenchymal transition and tumor migration and invasion [41]. A recent study found that the expression of METTL7B positively correlated with immunosuppressive cells suggesting that it might play a significant role in modulating TIME [42]. Meanwhile, METTL7B expression was positively associated with CD4 + T cells and dendritic cells. All the results indicated that METTL7B could be used to predict the TIME in PRAD. Moreover, Redecke et al. [43] reported that HOXB8 transfected in mouse bone marrow cells with unlimited proliferative capacity that could enable investigations of immune cell differentiation and function. This study found that HOXB8 is closely correlated with CD4 + T cells. Besides, Zhao et al. [44] pointed out that high expression levels of TREM1 had improved the infiltration of regulatory T cells and reduced the infiltration of CD8 + T cells. Similarly, this study found that the expression of TREM1 could regulate the TIME, including neutrophils and dendritic cells. Previous studies have suggested that CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells are associated with the impairment of proliferation, cytokine production, and migratory capacities of effector T cells [45]. Besides, Meng et al. [46] firstly pointed out the infiltration of immunocytes among PRAD via the CIBERSORT algorithm. This study indicated that M2 macrophages was related to gene markers, whick could predict the prognosis of PRAD patients. These results were consistent with our study that we found that METTL7B, HOXB8, and TREM1 were positively correlated with M2 macrophages. Regulating the expression levels of METTL7B, HOXB8, and TREM1 may have remarkable clinical applications in enhancing immunotherapy. Immunotherapy has shown good prospects in treating cancer. We will continue to focus on the genes related to tumor microenvironment of PRAD in the future. Further exploration on genes related to tumor microenvironment will help treating patients with PRAD using immunotherapy as soon. Thus, more experiments such as mice experiments, molecular biology research and clinical test need be performed to validate these results in this study.

5 Conclusions

This study explored the expression levels of three TIME-related genes including METTL7B, HOXB8, and TREM1, which correlated with the prognosis of patients with PRAD. Moreover, targeting the TIME-related genes might have important clinical implications when making decisions for immunotherapy in PRAD.

Exploring the frontiers: tumor immune microenvironment and immunotherapy in head and neck squamous cell carcinoma

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Abstract

The global prevalence of head and neck malignancies positions them as the sixth most common form of cancer, with the head and neck squamous cell carcinoma (HNSCC) representing the predominant histological subtype. Despite advancements in multidisciplinary approaches and molecular targeted therapies, the therapeutic outcomes for HNSCC have only marginally improved, particularly in cases of recurrent or metastatic HNSCC (R/MHNSCC). This situation underscores the critical necessity for the development of innovative therapeutic strategies. Such strategies are essential not only to enhance the efficacy of HNSCC treatment but also to minimize the incidence of associated complications, thus improving overall patient prognosis. Cancer immunotherapy represents a cutting-edge cancer treatment that leverages the immune system for targeting and destroying cancer cells. It’s applied to multiple cancers, including melanoma and lung cancer, offering precision, adaptability, and the potential for long-lasting remission through immune memory. It is observed that while HNSCC patients responsive to immunotherapy often experience prolonged therapeutic benefits, only a limited subset demonstrates such responsiveness. Additionally, significant clinical challenges remain, including the development of resistance to immunotherapy. The biological characteristics, dynamic inhibitory changes, and heterogeneity of the tumor microenvironment (TME) in HNSCC play critical roles in its pathogenesis, immune evasion, and therapeutic resistance. This review aims to elucidate the functions and mechanisms of anti-tumor immune cells and extracellular components within the HNSCC TME. It also introduces several immunosuppressive agents commonly utilized in HNSCC immunotherapy, examines factors influencing the effectiveness of these treatments, and provides a comprehensive summary of immunotherapeutic strategies relevant to HNSCC.

1 Introduction

HNSCC represents the predominant malignancy in the head and neck region, accounting for approximately 90% of all head and neck cancers and 16–40% of systemic malignancies [1]. Annually, it contributes to 600,000 new cases globally [1]. The incidence and mortality rates of HNSCC have been increasing steadily over the years. Notably, HNSCC is characterized by its heterogeneity, with over 60% of patients presenting with advanced or metastatic disease at diagnosis. Despite the employment of aggressive treatment modalities, including surgery, chemoradiotherapy, or a combination of these approaches, the 5 year overall survival rate for HNSCC, particularly those associated with carcinogens, remains limited to only 40–50% [2, 3]. In addition, conventional therapies may lead to complications. Patients may suffer from functional disabilities or cosmetic defects after surgery, and recurrence remains a huge challenge after incomplete surgical resection. Chemoradiotherapy has systemic toxicity which can damage other organs and also has a risk of pharyngeal dysfunction [4]. Consequently, in cases of R/MHNSCC, the therapeutic options are limited, and the prognosis is generally poor.

T cell-based immunotherapies, including immune checkpoint inhibitors (ICIs), have demonstrated efficacy in increasing the overall survival (OS) rate in patients with R/MHNSCC. ICIs function by reactivating cytotoxic T lymphocytes (CTLs) and are dependent on their ability to target and eliminate tumor cells [4, 5]. While these therapies yield a high rate of sustained response, only a small percentage of HNSCC patients exhibit a favorable response, and challenges such as resistance to immunotherapy remain prevalent. TME plays a crucial role in the pathogenesis, progression, metastasis, diagnosis, and treatment of HNSCC [6]. The TME undergoes dynamic changes that collectively weaken the immune response against cancer. This includes the generation of immunosuppressive factors by tumor and stromal cells, an increase in immune-suppressive cells like Tregs and MDSCs, and the remodeling of the extracellular matrix creating physical barriers. Additionally, metabolic competition and hypoxic conditions further impair immune cell function, while the expression of immune checkpoint molecules like PD-L1 by tumor cells actively inhibits immune attacks. These complex interactions in the TME challenge the effectiveness of the body’s natural immune response, underscoring the importance of targeted cancer therapies [5, 6]. Thus, investigating the roles and mechanisms of both anti-tumor and pro-tumor immune cells, as well as extracellular components within the TME of HNSCC, and exploring the significance of tumor immunotherapy in its treatment, can offer new strategies for personalized precision immunotherapy in HNSCC.

Outlook

Immunotherapy has demonstrated positive therapeutic effects in some patients with HNSCC. However, in many cases, TME can induce drug resistance through compensatory feedback mechanisms and dynamic evolution, which may impede the effectiveness of immunotherapy and potentially lead to tumor hyperprogression. Given the dynamic and inhibitory nature of the TME, further research is needed to explore immunotherapeutic targets involving molecules or signaling pathways within the TME. The main factors limiting the efficacy of immunotherapy in HNSCC include a low response of the host immune system to TAAs, poor immune cell infiltration in the tumor, and the development of an immunosuppressive TME. Considering these challenges, there is a need for identifying predictive biomarkers sensitive to various immunotherapies. Unlike prognostic biomarkers, the field of predictive biomarkers is less developed. Effective predictive biomarkers could forecast the success of specific immunotherapies, leading to substantial improvements in treatment outcomes and enhancing our understanding of the interactions between tumor cells and the TME. Investigating the potential of combining ICIs with other therapeutic strategies is crucial. Optimizing combinations, such as integrating traditional cancer treatments like radiotherapy or chemotherapy with immunotherapy, or combining multiple immunotherapies, could significantly enhance the overall effectiveness in eradicating tumor cells. Additionally, novel immune activation strategies like oncolytic viruses could modify the local immune state of the TME, promoting an inflammatory immune microenvironment conducive to antitumor activity.

Analyzing the immune microenvironment around Hodgkin lymphoma tumors

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The most detailed study of Hodgkin lymphoma, a type of blood cancer, has offered considerable insight into what tumor cells must do to sustain. The Wellcome Sanger Institute discovered that cancer cells utilize signals to attract specific types of immune cells and direct them not to attack.

Hodgkin lymphoma

The study, which was published in Blood, also discovered that high concentrations of these cell clusters in existing sample data predicted chemotherapy failure. This understanding could be used to speed up the transition to precision medicine and identify patients who just might profit from newer immune-based therapies, which are more efficient when conventional therapies fail.

Hodgkin lymphoma is a cancer of the lymphatic system, a vital component of the human immune system that aids in the fight against infections and the destruction of abnormal cells. Hodgkin lymphoma is distinguished by the presence of Hodgkin/Reed-Sternberg cells, which are cancerous white blood cells known as B lymphocytes. B lymphocytes normally produce antibodies to aid in the fight against infections.

Hodgkin lymphoma affects approximately 2,100 people in the UK each year. Though most patients respond well to chemotherapy, radiotherapy, or a combination of the two, these treatments do not work for everyone. The good news is that these patients frequently respond favorably to new treatments such as “immune checkpoint inhibitors,” particularly PD-1 blockers.

In this recent study, investigators used a variety of methods to examine the immune microenvironment surrounding Hodgkin lymphoma tumors in extraordinary depth.

The Wellcome Sanger Institute produced single-cell sequencing and spatial transcriptomic data from Hodgkin lymphoma and healthy lymph node tissue to pinpoint the genes expressed by each cell and their position in relation to their neighbors. This was coupled with microscope imaging data from Newcastle University Hodgkin lymphoma biopsies.

Single-cell analysis showed that cancer cells were enveloped by immune cell clusters of macrophages, monocytes, and cDC2 dendritic cells. Data from imaging revealed that these cells expressed molecules that inhibited their anti-tumor abilities.

This study is a great example of how much information we can get out of one tissue sample. By combining single-cell, spatial transcriptome and histological data, we were able to learn how precisely Hodgkin lymphoma manages to evade immune response. You could think of this approach as a sort of roadmap for molecular pathology, which could be applied to other diseases as well.”

Dr Ben Stewart, Study First Author, Wellcome Sanger Institutute.

Researchers also discovered two distinct “microenvironments” around cancer cells, which indicated how effective conventional therapies would be. High concentrations of immune cell clusters around cancer cells predicted treatment failure, even though a high concentration of stromal cells in the microenvironment predicted treatment success.

Since stromal cells imply that tissue has been repaired earlier, it is possible that the immune system was already partially successful in combating the disease, with treatment offering a helping hand to completely eradicate cancer.

Understanding how Hodgkin lymphoma tumors bypass the body’s immune response opens up new possibilities to treat this disease. If we could identify which patients have higher concentrations of these immune cell clusters around the tumor, for example, we could tailor their treatments, limiting the effects of chemotherapy for patients in whom it is less likely to work and proceeding directly to immune-based therapies that stand a better chance.”

Dr Chris Carey, Study Senior Author, Newcastle University

A possible drug target is the cellular messaging used by cancer cells to manipulate immune cells. In theory, interrupting this signaling would enable the immune system to respond normally and attack the cancer cells.

Single-cell and spatial transcriptomic approaches are bringing a whole new level of detail for the study of human health and disease. When they are combined with other types of data, you can be incredibly specific about what is happening in the human body. This precision is key and I’m sure in time the data that we have generated in this study will have a positive impact on the treatment of Hodgkin lymphoma.”

Dr Sam Behjati, Study Senior Author, Wellcome Sanger Institute

Comprehensive analysis of pyroptosis regulation patterns and their influence on tumor immune microenvironment and patient prognosis in glioma

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Abstract

Background

Glioma is the most common intracranial malignancy with a poor prognosis. Although remarkable advances have been made in the study of diagnostic and prognostic biomarkers, the efficacy of current treatment strategies is still unsatisfactory. Therefore, developing novel and reliable targets is desperately needed for glioma patients. Pyroptosis reshapes tumor immune microenvironment (TME) and promotes the destruction of the tumor by the immune system. Moreover, pyroptosis levels correlate with prognosis and immunotherapy response in many cancer patients. This study performed a comprehensive analysis of pyroptosis in the glioma, unveiling its potential value in glioma prognosis prediction and therapy efficacy.

Methods

Firstly, the pyroptosis regulation patterns were comprehensively evaluated on 33 pyroptosis-related genes in 1716 glioma samples. The correlations were analyzed between pyroptosis regulation patterns and TME immune cell infiltration properties. Next, pyroptosis regulation patterns were measured by the PSscore model based on principal component analysis algorithms. The correlations were analyzed between PSscore and tumor mutational burden (TMB), immune checkpoint blockade (ICB) therapeutic advantages. Last, the findings were validated in an independently collected external clinical cohort.

Results

We determined two distinct pyroptosis regulation patterns. The cluster-A was high immune cell infiltration with a poor prognosis (p < 0.001), whereas the cluster-B was low immune cell infiltration with a better prognosis (p < 0.001). We developed the PSscore as a measure for pyroptosis regulation patterns. The high PSscore with an inflamed TME phenotype, a high TMB (p < 0.0001), increased innate immune response, and a poor prognosis (p < 0.001). It was in stark contrast to the low PSscore (p < 0.001). Analysis of PSscore with checkpoint therapy indicated high PSscore were correlated with enhanced response to anti-PD-1 immunotherapy (p = 0.0046). For validation, we utilized in vitro experiments on an external clinical cohort. The results demonstrated that GSDMD expression level in the high PSscore group was significantly upregulated compared to the low PSscore group (p < 0.001); the CD3+ T cells and the CD3+PD-1+ cells significantly increased in the high PSscore group compared to the low PSscore group (p < 0.01).

Conclusions

The PSscore of pyroptosis regulation pattern is a reliable biomarker, and it is valuable to predict prognosis, TME, and ICB therapeutic efficiency in glioma patients.