Immune Cell Infiltration and Causal Relationships with Prostate Cancer: A Transcriptomic and Mendelian Randomization Study

Prostate cancer (PCa) is one of the most prevalent malignancies affecting men worldwide and represents a significant global health burden^[1]. According to the Global Cancer Statistics 2020, PCa is the second most frequently diagnosed cancer and the fifth leading cause of cancer-related deaths among men, with an estimated 1.4 million new cases and 375,000 deaths annually^[2]. The incidence of PCa shows considerable geographic variation, with the highest rates observed in North America, Northern and Western Europe, Australia, and New Zealand^[3,4]. These differences are attributed to variations in genetic predisposition, environmental factors, lifestyle, and the availability and utilization of screening programs such as prostate-specific antigen testing^[5,6]. The etiology of PCa is multifactorial, involving genetic, hormonal, and environmental influences^[7]. Age is the most significant risk factor, with the majority of cases diagnosed in men over 65 years of age^[8]. Family history and genetic mutations, such as those in BRCA1 and BRCA2 genes, also contribute to an increased risk^[9,10]. In addition, lifestyle factors, including diet, physical activity, and exposure to certain environmental toxins, have been implicated in the development of PCa^[11]. Despite extensive research, the precise mechanisms underlying prostate carcinogenesis remain incompletely understood, necessitating further investigation.

PCa typically progresses slowly, with many men remaining asymptomatic for years^[12]. However, the disease can be aggressive in some cases, leading to metastasis and significantly impacting the quality of life and survival of patients^[13]. The clinical management of PCa includes a range of options such as active surveillance, surgery, radiation therapy, hormone therapy, and chemotherapy^[14,15]. The choice of treatment depends on the stage of the disease, patient comorbidities, and preferences. Despite advances in diagnostic and therapeutic strategies, PCa remains a major public health challenge, emphasizing the need for improved understanding of its pathophysiology and the development of novel interventions. Recent research has increasingly focused on the tumor microenvironment, particularly the role of immune cells in cancer progression and response to therapy^[16,17,18]. The immune landscape of PCa is complex, involving various immune cell types such as macrophages, neutrophils, T cells, and B cells, which can exert both protumorigenic and antitumorigenic effects^[19,20,21]. Tumor-associated macrophages and neutrophils, for instance, have been shown to promote tumor growth, angiogenesis, and metastasis, whereas certain subsets of T cells can mediate antitumor immune responses^[22]. The dynamic interplay between immune cells and tumor cells is crucial in shaping the tumor microenvironment and influencing disease outcomes. Understanding the patterns of immune cell infiltration in PCa and their causal relationships with the disease is essential for identifying potential biomarkers and therapeutic targets. Immunotherapy, which harnesses the body's immune system to fight cancer, has emerged as a promising treatment modality for various cancers, including melanoma, lung cancer, and renal cell carcinoma^[23,24,25]. However, its efficacy in PCa has been limited, highlighting the need for a deeper understanding of the immune context in PCa.

In this study, we aim to elucidate the differences in immune cell infiltration between prostate tumor tissues and healthy controls using transcriptomic data and investigate the causal relationships between immune phenotypes and PCa through Mendelian randomization (MR). Our findings provide valuable insights into the immune mechanisms underlying PCa and may inform the development of novel immunotherapeutic strategies.

Our study focused on the immune cell infiltration in prostate tumor tissues compared to healthy tissues and explored the causal relationships between various immune phenotypes and PCa using MR. By employing robust analytical methods, including CIBERSORT, ssGSEA, and xCell, we identified significant differences in the infiltration levels of specific immune cell types. Our findings highlight that macrophages, Tregs, and several other immune cells are more prevalent in tumor tissues, whereas neutrophils and mast cells are more common in healthy tissues. Moreover, through MR analysis, we discovered that certain immune phenotypes, particularly CD4 on HLA DR+ CD4+ T cells, have a significant inverse causal association with PCa, suggesting their potential protective role. These results underscore the complexity of the immune landscape in PCa and provide valuable insights that could inform the development of novel immunotherapeutic strategies aimed at modulating the immune microenvironment to improve patient outcomes. The robustness of our findings was confirmed through extensive sensitivity analyses, ensuring the reliability and accuracy of the causal inferences drawn from this study.

The results of our immune infiltration analysis reveal significant differences in the composition of various immune cell types between prostate tumor tissues and healthy control tissues, as determined by CIBERSORT, ssGSEA, and xCell methodologies. The CIBERSORT analysis identified a significant increase in the infiltration of macrophages M0, Tregs, and macrophages M1 in tumor tissues. This suggests that these immune cells may contribute to the immunosuppressive tumor microenvironment, which can promote tumor growth and evade immune surveillance^[39]. The increased presence of Tregs, known for their immunosuppressive functions, further supports this notion^[40]. Conversely, decrease in neutrophils, activated dendritic cells, monocytes, and resting mast cells in tumor tissues indicates reduced presence of immune cells typically associated with antitumor immune responses, potentially facilitating tumor progression^[41,42]. The ssGSEA analysis corroborated the CIBERSORT findings by showing an increase in Th2 cells, Tregs, and Th17 cells in tumor tissues. Th2 cells are associated with anti-inflammatory responses, which may aid in creating a favorable environment for tumor growth^[43,44]. The presence of Th17 cells, despite their known proinflammatory role, could be indicative of a complex interplay, where they might be contributing to tumor-promoting inflammation^[45]. However, significant reduction in neutrophils, Tgd cells, Th1 cells, NK cells, and resting mast cells in tumor tissues suggests a diminished antitumor immune response, as these cells are crucial for orchestrating effective antitumor immunity. The xCell analysis provided further insights, showing increased infiltration of macrophages, plasma cells, CD4+ Tem cells, Pro-B cells, basophils, Th1 cells, class-switched memory B cells, and CD4+ Tcm cells in tumor tissues. The elevated levels of these cells, particularly macrophages and Th1 cells, suggest a complex tumor microenvironment where both protumorigenic and antitumorigenic forces are at play^[46]. The increase in memory B cells and plasma cells might reflect an ongoing humoral immune response, though its efficacy in controlling tumor growth remains uncertain^[47]. Decreases in astrocytes, mesangial cells, keratinocytes, smooth muscle cells, and fibroblasts in tumor tissues are notable, as these nonimmune cells also contribute to the tumor microenvironment's structural and functional integrity. These differential infiltration patterns underscore the complexity of the immune landscape in PCa. The increased presence of immunosuppressive cells and decreased levels of antitumor immune cells suggest a tumor-promoting environment that facilitates cancer progression and immune evasion. These insights emphasize the potential of targeting specific immune cell types and pathways to modulate the tumor microenvironment for therapeutic benefit. Moreover, understanding these immune dynamics can inform the development of novel immunotherapies. For instance, strategies aimed at reducing Treg and M2 macrophage populations or enhancing the activity of Th1 cells and NK cells could potentially shift the balance toward a more effective antitumor immune response. The findings also highlight the importance of personalized approaches, as the immune landscape can vary significantly between patients.

The MR analysis identified 42 immune phenotypes with a potential causal relationship with PCa before FDR correction, highlighting the complex interplay between the immune system and tumor development. Among these immune phenotypes, various subtypes of T cells (CD4+ T cells, CD8+ T cells, Tregs), B cells (including IgD+ and IgD− subsets), monocytes (CD14+ and CD16+ subtypes), natural killer T cells, and myeloid-derived suppressor cells featured prominently. The involvement of these immune cell types in PCa suggests that the immune landscape is crucial in the disease's etiology and progression. Specific surface markers and activation states, such as HLA-DR, CD27, CD28, CD39, CD62L, and CX3CR1, further emphasize the nuanced roles of these immune cells, as these markers are often involved in cell activation, differentiation, and signaling pathways. After FDR correction, the finding that CD4 on HLA DR+ CD4+ T cells exhibited a significant inverse association with PCa risk (OR [95% CI] = 0.54 (0.43–0.71), P = 3.86E-06) is particularly noteworthy. This result suggests that higher levels of these specific T cells may confer a protective effect against PCa development. The inverse association indicates that these cells might be crucial in mounting an effective immune response to prevent or control tumor growth. This protective role could be due to the enhanced antigen-presenting capabilities of HLA DR+ CD4+ T cells, which can activate other immune cells and orchestrate a more robust antitumor response^[48,49]. The implications of these findings are profound as they not only provide insights into the immune mechanisms underlying PCa but also suggest potential therapeutic targets. Enhancing the population or activity of CD4 on HLA DR+ CD4+ T cells could be explored as a strategy to bolster antitumor immunity^[50]. Immunotherapies designed to increase the presence or function of these cells might improve patient outcomes, especially in individuals with low levels of these protective T cells. The findings also underscore the importance of considering the immune microenvironment in PCa research and treatment. The diverse array of immune cell types and their functional states play distinct roles in either promoting or inhibiting tumor growth. Understanding these roles can guide the development of more effective immunotherapies. For instance, strategies to deplete immunosuppressive cells, such as Tregs and myeloid-derived suppressor cells, or to enhance the function of antitumor immune cells, like CD8+ T cells and natural killer cells, could be promising avenues for treatment.

Several limitations should be acknowledged. Firstly, the study relies on transcriptomic data from TCGA and GWAS data from publicly available databases, which may introduce selection bias due to the specific populations included in these datasets. The majority of the data used in this analysis are derived from European populations, potentially limiting the generalizability of the findings to other ethnic groups. Secondly, the immune cell infiltration profiles were determined using computational methods (CIBERSORT, ssGSEA, and xCell) based on RNA sequencing data. While these methods provide a detailed view of immune cell composition, they are inherently limited by their reliance on predefined gene expression signatures and may not fully capture the complexity of the tumor microenvironment. Thirdly, the MR analysis, while robust, is dependent on the selection of appropriate IVs. Although stringent criteria were used for IV selection, residual confounding or pleiotropy cannot be entirely ruled out. In addition, the number of SNPs used as IVs for certain immune phenotypes was relatively small, which could impact the power and accuracy of the causal estimates. Moreover, the cross-sectional nature of the data limits the ability to infer temporal relationships between immune cell infiltration and PCa progression. Longitudinal studies would be necessary to elucidate the dynamic changes in immune cell populations over the course of the disease. Lastly, while sensitivity analyses indicated no evidence of heterogeneity or pleiotropy, the potential for unmeasured confounding factors remains. Further validation using independent cohorts and experimental models would be essential to corroborate these findings and fully understand the mechanistic pathways involved.