1 Introduction

Renal cell carcinoma (RCC) is the most prevalent type of kidney cancer, accounting for around 90% of kidney malignancies. The most common subtype, clear-cell renal cell carcinoma (ccRCC), comprises 70-80% of all RCC cases. Historically, RCC has been regarded as resistant to conventional therapies such as chemotherapy and radiotherapy, which led to the exploration of alternative treatments like targeted therapy and immunotherapy. The introduction of immune checkpoint inhibitors (ICIs) targeting PD-1, PD-L1, and CTLA-4 has revolutionized the treatment landscape for metastatic RCC, offering patients new hope with durable responses and improved survival rates (Xu et al., 2020). However, the efficacy of these treatments is limited by intrinsic and acquired resistance mechanisms, necessitating further research to improve patient outcomes. This study will provide a detailed exploration of the mechanisms underlying resistance to immune checkpoint blockade, the therapeutic efficacy of ICIs in RCC, and emerging strategies to overcome these barriers (Chatwal et al., 2023). The development of ICI therapies has provided a foundation for understanding how the immune system can be harnessed to target cancer cells. Yet, the dynamic interplay between tumor cells and the immune system can limit the long-term effectiveness of these therapies. Understanding the immune microenvironment of RCC, identifying biomarkers predictive of response to ICIs, and overcoming resistance are essential components of advancing treatment for patients with advanced disease (Diaz-Montero et al., 2020).

Renal cell carcinoma (RCC) develops from the renal epithelium, with clear-cell RCC (ccRCC) being the most common histological subtype. This form of cancer is often associated with mutations in the von Hippel-Lindau (VHL) gene, which leads to an upregulation of hypoxia-inducible factors (HIFs) and promotes angiogenesis through increased production of vascular endothelial growth factor (VEGF) (Diaz-Montero et al., 2020). The VHL-HIF-VEGF axis is central to the biology of RCC, resulting in a highly vascularized tumor microenvironment (TME) that facilitates tumor growth and metastasis. This explains why anti-angiogenic therapies, such as tyrosine kinase inhibitors (TKIs), have historically been effective in treating advanced RCC (Xu et al., 2020). Additionally, RCC is characterized by an immunosuppressive TME, which is rich in regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs). These immune cells contribute to the suppression of cytotoxic T cell activity, allowing the tumor to evade immune surveillance (Diaz-Montero et al., 2020). Tumor cells in RCC also upregulate immune checkpoint molecules like PD-L1, which further inhibit the activation of T cells and promote immune escape (Chatwal et al., 2023). Despite its immunogenic nature, RCC often does not respond robustly to immunotherapy alone due to these complex interactions within the TME.

Immune checkpoint blockade (ICB) represents a significant advancement in cancer immunotherapy, particularly for metastatic renal cell carcinoma (mRCC). The concept behind ICB revolves around inhibiting the regulatory pathways that suppress T-cell activity, which are often hijacked by tumors to evade immune responses. In RCC, immune checkpoint inhibitors (ICIs) target molecules such as programmed cell death protein 1 (PD-1), its ligand (PD-L1), and cytotoxic T lymphocyte-associated protein 4 (CTLA-4). These molecules play critical roles in maintaining immune homeostasis by preventing overactivation of T cells, but tumors exploit these pathways to suppress anti-tumor immunity. By blocking these checkpoints, ICIs reinvigorate T-cell function, enabling the immune system to mount a more effective attack against cancer cells (Luyo et al., 2019). The development of ICIs like nivolumab (anti-PD-1) and ipilimumab (anti-CTLA-4) has transformed the treatment landscape for advanced RCC (Budka et al., 2019). Clinical trials, such as the CheckMate 214 trial, demonstrated that combination therapy with nivolumab and ipilimumab significantly improves overall survival in patients with intermediate- to poor-risk mRCC compared to standard therapies like sunitinib. These findings led to the approval of the combination as a first-line treatment for advanced RCC (Xu et al., 2020). However, despite these advancements, a substantial number of patients either do not respond to ICIs or develop resistance over time, underscoring the need for continued research into optimizing these therapies and understanding the mechanisms of resistance (Chatwal et al., 2023).

The primary objective of this study is to provide an in-depth analysis of the therapeutic efficacy of immune checkpoint blockade in renal cell carcinoma, with a particular focus on metastatic disease. The study will explore both the mechanisms that contribute to the success of these therapies as well as the factors that lead to primary and acquired resistance. In doing so, it aims to bridge the knowledge gap between current clinical outcomes and future therapeutic potential. Understanding these mechanisms is critical for developing more effective treatment strategies and improving patient outcomes. The significance of this study lies in the ongoing challenge of resistance to immune checkpoint blockade. Although immune checkpoint inhibitors have demonstrated impressive efficacy in certain patients, a significant proportion either do not respond initially or develop resistance after a period of response. This resistance can arise from various tumor-intrinsic factors, such as mutations that affect antigen presentation, or from changes within the tumor microenvironment that inhibit effective T-cell function. Identifying predictive biomarkers and novel therapeutic targets will be crucial for overcoming these obstacles and enhancing the effectiveness of immunotherapy in RCC. This study will also highlight emerging combination therapies that could potentially overcome resistance, including the use of ICIs in conjunction with other immunomodulatory agents or targeted therapies.

2 Resistance Mechanisms to Immune Checkpoint Blockade

Immune checkpoint blockade (ICB) therapies, such as those targeting PD-1/PD-L1 and CTLA-4, have transformed the treatment of metastatic renal cell carcinoma (mRCC). However, despite their success, a substantial number of patients either fail to respond initially (primary resistance) or develop resistance after an initial response (acquired resistance). Understanding these resistance mechanisms is crucial for optimizing therapy and improving patient outcomes. These resistance mechanisms involve complex molecular and cellular interactions within the tumor and its microenvironment, including alterations in antigen presentation, immune cell dynamics, and signaling pathways (Xu et al., 2020).

2.1 Molecular basis of primary resistance

Primary resistance to immune checkpoint blockade occurs when the tumor exhibits inherent mechanisms that prevent an effective immune response, even before the treatment is initiated. This resistance can result from tumor-intrinsic factors that impair immune recognition and attack. One such factor is the loss of function in the PBRM1 gene, which plays a role in chromatin remodeling and has been implicated in reduced responses to PD-1 blockade in RCC. Mutations in PBRM1 lead to altered immune signaling and hinder the recruitment of cytotoxic T cells, limiting their capacity to mount an anti-tumor response (Miao et al., 2018). Other intrinsic resistance mechanisms include defects in the antigen-presentation machinery, such as the loss of beta-2 microglobulin (B2M), which is crucial for MHC class I-mediated antigen presentation. Without proper antigen presentation, the immune system cannot effectively recognize and eliminate cancer cells (Lee et al., 2021).

Additionally, tumors can upregulate alternative immune checkpoints, such as TIM-3, LAG-3, and VISTA, which provide redundant inhibitory signals that bypass the blockade of PD-1 or CTLA-4 (Barrueto et al., 2020). These alternative checkpoints suppress immune activation and allow the tumor to escape immune surveillance. The tumor microenvironment (TME) itself can also contribute to primary resistance by promoting an immunosuppressive environment that favors tumor growth. For instance, increased infiltration of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) can inhibit the function of effector T cells, preventing a robust anti-tumor immune response. Overall, primary resistance reflects the tumor's inherent ability to evade immune detection and attack, necessitating the development of combination therapies that target multiple immune pathways simultaneously (Feng et al., 2019).

2.2 Molecular mechanisms of acquired resistance

Acquired resistance develops in patients who initially respond to immune checkpoint blockade but later experience disease progression. This form of resistance is typically driven by tumor evolution and changes in the tumor microenvironment that occur in response to immune pressure. One key mechanism of acquired resistance is immune escape, where tumors lose the neoantigens that were initially recognized by the immune system. This loss of neoantigens can occur through genetic mutations or deletions, reducing the immune system’s ability to recognize and target cancer cells effectively. Studies have shown that up to 60% of neoantigens present in primary tumors are no longer detectable in metastatic or resistant tumors, suggesting that immune editing plays a significant role in acquired resistance (Álvarez Ballesteros et al., 2021).

Another major contributor to acquired resistance is the remodeling of the immunosuppressive microenvironment. Over time, tumors can recruit higher numbers of immunosuppressive cells, such as Tregs, MDSCs, and tumor-associated macrophages (TAMs), which inhibit the activity of cytotoxic T cells and natural killer (NK) cells. These immunosuppressive cells create a hostile environment that protects the tumor from immune attack. Additionally, tumor cells can upregulate immune checkpoint molecules like PD-L1 in response to interferon signaling, further dampening the immune response (Bi et al., 2021). Acquired resistance can also involve mutations in key immune pathways, such as the JAK/STAT signaling pathway, which regulates immune cell infiltration and activation. Tumors with mutations in JAK2, for example, exhibit reduced sensitivity to immune checkpoint inhibitors, leading to treatment failure.

These insights into acquired resistance underscore the dynamic nature of the tumor-immune interaction and highlight the need for adaptive therapeutic strategies. By targeting both tumor-intrinsic mechanisms, such as mutations in antigen presentation pathways, and the immunosuppressive microenvironment, it may be possible to overcome acquired resistance and restore the effectiveness of immune checkpoint blockade (Luyo et al., 2019).

2.3 Identification of biomarkers for resistance to immune checkpoint blockade therapy

The identification of reliable biomarkers is essential for predicting which patients will respond to immune checkpoint blockade and for understanding resistance mechanisms. PD-L1 expression has been widely studied as a potential biomarker for response to PD-1/PD-L1 inhibitors, but its predictive value remains limited and inconsistent. Many patients with high PD-L1 expression still fail to respond, while some with low or no PD-L1 expression do benefit from treatment. Therefore, more robust biomarkers are needed to guide clinical decisions. Tumor mutational burden (TMB) is one emerging biomarker, as higher TMB has been associated with better responses to immune checkpoint inhibitors in various cancers, including RCC (Chatwal et al., 2023). High TMB increases the likelihood of neoantigen formation, which enhances immune recognition and response.

Other promising biomarkers include genetic alterations in immune-related genes, such as PBRM1 mutations, which have been linked to resistance in RCC (Miao et al., 2018). Additionally, gene expression signatures that reflect the immune context of the tumor, such as the presence of CD8+ T cells or specific interferon-stimulated genes, can provide insights into the likelihood of response. Immune cell infiltration patterns within the tumor microenvironment, particularly the ratio of cytotoxic T cells to immunosuppressive cells like Tregs and MDSCs, are also valuable indicators of treatment outcomes (Bi et al., 2021).

Efforts to identify predictive biomarkers extend beyond the tumor itself to include systemic factors, such as serum cytokine levels and the composition of the gut microbiome. These factors can influence immune responses and may serve as non-invasive biomarkers for predicting resistance to ICB therapy. Overall, the integration of tumor-specific and systemic biomarkers holds promise for improving patient selection and optimizing treatment strategies.

2.4 Therapeutic strategies to address resistance mechanisms

Overcoming resistance to immune checkpoint blockade requires innovative therapeutic strategies that target both tumor-intrinsic and extrinsic resistance mechanisms. One promising approach is the combination of immune checkpoint inhibitors with other immunomodulatory agents. For example, combining PD-1 blockade with inhibitors of alternative immune checkpoints, such as TIM-3 or LAG-3, can counteract the redundancy of immune-suppressive pathways and enhance anti-tumor responses (Barrueto et al., 2020). These combination therapies aim to simultaneously block multiple immune checkpoints, thereby preventing tumors from evading immune surveillance.

In addition to targeting immune checkpoints, therapies that modify the tumor microenvironment are gaining attention. Anti-angiogenic agents, such as tyrosine kinase inhibitors (TKIs), can disrupt the tumor's blood supply and reduce the recruitment of immunosuppressive cells, thereby enhancing the efficacy of immune checkpoint blockade (Álvarez Ballesteros et al., 2021). Another promising strategy is targeting metabolic pathways that contribute to immune suppression. For instance, blocking the kynurenine pathway, which is upregulated in many tumors and promotes immune tolerance, has shown potential in preclinical studies for enhancing responses to immunotherapy (Li et al., 2019). Personalized therapy based on biomarkers of resistance is also a key strategy for addressing resistance. By identifying specific genetic or molecular alterations that drive resistance, clinicians can tailor treatments to individual patients. For example, tumors with mutations in the JAK/STAT pathway may benefit from JAK inhibitors combined with immune checkpoint blockade. Additionally, ongoing research into the use of adoptive cell therapies, such as CAR-T cells or tumor-infiltrating lymphocytes (TILs), offers another avenue for overcoming resistance, particularly in patients with highly immunosuppressive tumors. These therapies involve engineering immune cells to specifically target and destroy tumor cells, potentially bypassing resistance mechanisms (Li et al., 2021).

In conclusion, addressing resistance to immune checkpoint blockade will require a multifaceted approach that includes combination therapies, biomarker-guided treatment, and novel immunotherapeutic strategies. By targeting both the tumor and its microenvironment, it is possible to enhance the durability and effectiveness of immune checkpoint blockade in RCC.

3 Relationship Between the Immune Microenvironment and Efficacy

The immune microenvironment, also known as the tumor microenvironment (TME), plays a crucial role in determining the efficacy of immune checkpoint blockade (ICB) therapy in renal cell carcinoma (RCC). A better understanding of the TME's components and their interactions can lead to improved therapeutic strategies and identification of biomarkers that predict treatment response.

3.1 Composition of immune cells in the tumor microenvironment

The TME of RCC is characterized by the presence of a variety of immune cells, including cytotoxic T cells (CD8+), regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), and dendritic cells. RCC has been shown to be one of the most immune-infiltrated tumors across different cancers, with tumor-infiltrating lymphocytes (TILs) being a common feature (Diaz-Montero et al., 2020). However, despite the presence of these immune cells, many fail to mount an effective anti-tumor response due to the immunosuppressive signals present within the TME (Chen, 2024).

Tregs and MDSCs, which inhibit cytotoxic T cell activity, are frequently found in RCC tumors and contribute to the suppression of the immune response. TAMs, particularly those with an M2 phenotype, also play an immunosuppressive role, promoting tumor growth and survival by inhibiting the activity of effector T cells. Conversely, CD8+ T cells, which are responsible for killing tumor cells, often exhibit exhaustion markers like PD-1, rendering them ineffective against the tumor (Rappold et al., 2021). This complex interplay of immune cell populations within the TME is a significant determinant of how well a patient responds to ICB therapy.

3.2 Correlation between PD-L1 expression and the efficacy of immune checkpoint blockade

PD-L1 (programmed death-ligand 1) expression in tumor cells has been widely studied as a potential biomarker for predicting the efficacy of PD-1/PD-L1 blockade therapies in RCC. PD-L1, when expressed on the surface of tumor cells or immune cells within the TME, binds to the PD-1 receptor on T cells, leading to their exhaustion and reduced anti-tumor activity. Therefore, high PD-L1 expression has been hypothesized to indicate a greater likelihood of response to PD-1/PD-L1 inhibitors, such as nivolumab.

However, the relationship between PD-L1 expression and treatment outcomes is complex. While several studies have demonstrated that high PD-L1 expression correlates with better responses to PD-1 blockade, there are also cases where patients with low or no PD-L1 expression still respond to treatment (Vuong et al., 2019). This inconsistency suggests that PD-L1 expression alone may not be a sufficient predictor of response and that other factors, such as the composition of the immune infiltrate and the overall immune landscape of the TME, play crucial roles in determining the efficacy of ICB therapy (Xu et al., 2020).

3.3 Other biomarkers potentially affecting efficacy

Beyond PD-L1 expression, several other biomarkers are being investigated for their potential to predict response to immune checkpoint blockade in RCC. Tumor mutational burden (TMB) refers to the total number of mutations present within a tumor's genome. High TMB has been associated with better responses to ICB in several cancer types, including RCC, as tumors with more mutations are thought to produce more neoantigens, which can be recognized by the immune system (Rappold et al., 2021).

Microsatellite instability (MSI) is another biomarker that has been linked to better responses to ICB. MSI occurs when the DNA mismatch repair system is deficient, leading to a high mutation rate. While MSI is less common in RCC compared to other cancers such as colorectal cancer, its presence could still indicate a higher likelihood of response to ICB therapy. Other emerging biomarkers include gene expression signatures related to immune activation, such as interferon-gamma signatures, and specific genetic alterations like mutations in the PBRM1 gene, which have been associated with enhanced responses to PD-1 blockade in RCC (Bi et al., 2021). The identification and validation of these biomarkers are critical for developing personalized approaches to ICB therapy, ensuring that the right patients receive the most effective treatments.

4 Application of Immune Checkpoint Blockade Therapy in Renal Cell Carcinoma

Immune checkpoint blockade (ICB) therapy has transformed the treatment landscape for metastatic renal cell carcinoma (mRCC). These therapies target key immune regulatory pathways that tumors exploit to evade immune detection and destruction.

4.1 Mechanisms of major immune checkpoints (PD-1, PD-L1, CTLA-4)

Immune checkpoints act as critical regulators of the immune response, preventing excessive immune activation. Tumors hijack these pathways to avoid immune destruction, which makes them valuable therapeutic targets. The PD-1 (programmed death-1) receptor is an inhibitory checkpoint found on activated T cells. When PD-1 binds to its ligands, PD-L1 or PD-L2, the T cells become functionally exhausted, limiting their ability to attack cancer cells. Tumors often overexpress PD-L1 to evade immune detection. By blocking PD-1 or PD-L1, ICB therapies re-engage T cells and restore their ability to fight tumors (Rappold et al., 2021).

CTLA-4 (cytotoxic T-lymphocyte antigen 4) is another inhibitory checkpoint found on T cells. It competes with CD28, a stimulatory molecule, for binding to B7 molecules on antigen-presenting cells. When CTLA-4 binds B7, it inhibits T-cell activation. Blocking CTLA-4 enhances T-cell activation, amplifying the immune response against tumors. This mechanism is crucial in early immune responses and has been targeted in renal cell carcinoma to boost anti-tumor immunity (Flippot et al., 2018).

4.2 Approved immune checkpoint inhibitors and their clinical trial results

Several immune checkpoint inhibitors have been approved for mRCC, showing significant improvements in overall survival and progression-free survival compared to traditional therapies. Nivolumab, a PD-1 inhibitor, was one of the first immune checkpoint inhibitors to show efficacy in renal cell carcinoma. The CheckMate 025 trial demonstrated that nivolumab improved overall survival compared to everolimus in patients with previously treated mRCC (Flippot et al., 2018). This marked a pivotal shift in the management of advanced renal cell carcinoma.

Pembrolizumab, another PD-1 inhibitor, has also shown success in combination with the tyrosine kinase inhibitor (TKI) axitinib. The KEYNOTE-426 trial demonstrated that this combination significantly improved both progression-free survival and overall survival in treatment-naive patients with advanced RCC (Bedke et al., 2020). Additionally, the combination of ipilimumab, an anti-CTLA-4 antibody, and nivolumab has proven to be particularly effective in intermediate- and poor-risk patients, as shown in the CheckMate 214 trial. This combination has resulted in significant improvements in overall survival and objective response rates, making it a first-line treatment for certain RCC patients (Flippot et al., 2018).

4.3 Combination therapy strategies: with targeted therapy, radiotherapy, and chemotherapy

Combining immune checkpoint blockade with other therapeutic modalities has emerged as a strategy to enhance treatment efficacy. The combination of ICB with tyrosine kinase inhibitors (TKIs) has shown particularly promising results. The CheckMate 9ER trial demonstrated that nivolumab combined with cabozantinib significantly improved progression-free survival and overall survival compared to sunitinib monotherapy in patients with advanced RCC (Massari et al., 2021). These combinations leverage the anti-angiogenic effects of TKIs, which help modulate the tumor microenvironment, making it more susceptible to immune attack (Martínez-Sabadell et al., 2022).

Radiotherapy is another modality being explored in combination with immune checkpoint inhibitors. Radiotherapy can induce immunogenic cell death, releasing tumor antigens that enhance the immune response. Clinical trials are ongoing to determine the synergistic effects of radiotherapy with ICB in RCC, though early results suggest potential benefits in enhancing anti-tumor immunity (Bedke et al., 2020).

Chemotherapy, traditionally thought to suppress immune responses, has also been shown to synergize with ICB in certain contexts. Preclinical studies have demonstrated that chemotherapy can sensitize tumors to immune checkpoint blockade by enhancing antigen presentation and reducing the immunosuppressive tumor microenvironment. For example, combining 5-fluorouracil (5-FU) with anti-PD-L1 antibodies increased survival and tumor infiltration of cytotoxic T cells in RCC mouse models (Figure 1) (Cui et al., 2017).

Figure 2 IFN-γ response is required for efficient killing by redirected lymphocytes (Adopted from Martínez-Sabadell et al., 2022) Image caption: The response of target cells to HER2-TCB and HER2-CAR T cells in the presence or blockade of IFN-γ. Blocking IFN-γ significantly reduced the killing efficacy of these immunotherapies, indicating that IFN-γ is crucial for eliciting maximum T-cell anti-tumor activity. This further confirms that IFN-γ is indispensable for effective immunotherapy (Adapted from Martínez-Sabadell et al., 2022).

4.4 Clinical efficacy evaluation: overall survival, progression-free survival, objective response rate

The efficacy of immune checkpoint blockade therapies in renal cell carcinoma is typically evaluated using clinical endpoints such as overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). In clinical trials, OS represents the gold standard for determining the effectiveness of a treatment. For example, in the CheckMate 214 trial, the combination of nivolumab and ipilimumab demonstrated a significant improvement in OS compared to sunitinib, with a median survival benefit extending beyond 30 months in intermediate- and poor-risk patients (Bedke et al., 2020).

Progression-free survival (PFS), which measures the time during and after treatment that a patient lives without disease progression, is another key endpoint. In the KEYNOTE-426 trial, pembrolizumab and axitinib significantly prolonged PFS compared to sunitinib in treatment-naive patients, with benefits observed across all subgroups (Massari et al., 2021).

Objective response rate (ORR) refers to the proportion of patients whose tumors shrink or disappear following treatment. Combination therapies involving immune checkpoint inhibitors have been shown to improve ORRs in patients with mRCC. For instance, the ORR in patients receiving the combination of nivolumab and cabozantinib was significantly higher than those receiving monotherapy, with more patients achieving partial or complete responses (Flippot et al., 2018).

5 Safety and Adverse Effects

Immune checkpoint blockade (ICB) therapies, such as those targeting PD-1, PD-L1, and CTLA-4, have shown remarkable efficacy in treating renal cell carcinoma (RCC). However, these therapies are also associated with a range of immune-related adverse events (irAEs).

5.1 Common adverse effects and their management

ICB therapies can induce irAEs, which result from the immune system becoming overactive and attacking healthy tissues. These irAEs can affect various organ systems, including the skin, gastrointestinal tract, liver, endocrine glands, and kidneys. Common irAEs include colitis, hepatitis, pneumonitis, nephritis, hypothyroidism, and rash. Severe cases of irAEs may lead to life-threatening complications, such as autoimmune encephalitis or severe interstitial nephritis (Murakami et al., 2016; Mysler et al., 2023).

Management of irAEs generally involves immunosuppressive treatments such as corticosteroids, which can mitigate inflammation. In cases where corticosteroids are insufficient, additional immunosuppressants like infliximab or mycophenolate mofetil may be required. Early recognition and treatment of irAEs are critical to preventing severe outcomes. For example, patients experiencing immune-related nephritis often respond well to high-dose corticosteroids if the condition is identified early (Dougan, 2017). Regular monitoring and patient education are essential components of managing irAEs effectively, especially as the incidence and severity of irAEs are expected to rise with the increasing use of combination therapies.

5.2 Long-term safety evaluation of immune checkpoint blockade therapy

Long-term safety of ICB therapy is an evolving area of research, particularly as more patients are treated with these agents for extended durations. Current evidence suggests that while many irAEs are manageable and reversible, some adverse events may persist or recur after discontinuation of ICB therapy. For instance, immune-related endocrinopathies, such as hypothyroidism or adrenal insufficiency, may require lifelong hormone replacement (Byun et al., 2017). Studies also indicate that patients who experience severe irAEs and are subsequently retreated with ICIs may have a higher risk of recurrent irAEs, although most of these recurrences are low grade and manageable with appropriate interventions (Abou Alaiwi et al., 2020).

Additionally, long-term immune surveillance is necessary for patients receiving ICB therapy, as late-onset irAEs may occur months or even years after treatment initiation. For example, autoimmune encephalitis and nephritis have been reported long after the initial course of ICB therapy. The long-term effects of ICBs on organ function, particularly in vulnerable organs like the kidneys and liver, remain under investigation (Dougan, 2017).

5.3 Safety considerations in special patient populations

The safety profile of ICB therapy in special patient populations, such as the elderly and those with pre-existing autoimmune diseases, is an important consideration for clinicians. Elderly patients, who are often excluded from clinical trials, may experience a different spectrum of irAEs due to age-related changes in immune function. However, studies have shown that elderly patients (over 70 years old) receiving ICBs for metastatic RCC have similar efficacy outcomes and adverse event rates compared to younger patients. Although elderly patients may have higher rates of gastrointestinal irAEs, overall, ICBs appear to be well-tolerated in this population, and age alone should not be a contraindication for ICB therapy.

Patients with pre-existing autoimmune diseases pose a unique challenge, as ICBs can exacerbate underlying autoimmune conditions. For example, patients with rheumatoid arthritis or inflammatory bowel disease may experience flare-ups during ICB treatment. Despite this risk, studies have shown that some patients with autoimmune diseases can safely receive ICBs with close monitoring and appropriate management of irAEs. Special care should be taken when considering ICB therapy in these populations, and a multidisciplinary approach involving rheumatologists or other specialists is often necessary to balance the benefits of cancer treatment against the risks of exacerbating autoimmune disease (Henau et al., 2016).

6 Future Directions and Clinical Challenges

As immune checkpoint blockade (ICB) therapy continues to transform the treatment of renal cell carcinoma (RCC), new challenges and opportunities arise. Overcoming immune resistance, advancing novel immunotherapeutic strategies, and incorporating personalized immunotherapy are crucial areas of focus for improving patient outcomes.

6.1 Overcoming immune resistance

Resistance to immune checkpoint inhibitors (ICIs), whether primary or acquired, remains a significant hurdle in treating RCC. Immune resistance can arise from a variety of factors, including tumor-intrinsic mechanisms, such as mutations in genes involved in antigen presentation or immune evasion, as well as tumor-extrinsic factors, such as the suppressive nature of the tumor microenvironment (TME). For example, tumors often recruit immunosuppressive cells like regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), which inhibit effective anti-tumor immune responses (Álvarez Ballesteros et al., 2021).

Targeting the TME, particularly through inhibiting pathways like PI3Kγ in myeloid cells, has shown promise in reversing resistance and enhancing the efficacy of ICIs. Additionally, combination therapies that pair ICIs with agents targeting angiogenesis, such as VEGF inhibitors, or novel immunomodulatory agents are being explored to overcome immune resistance and extend patient survival (Moreira et al., 2020). Future strategies will likely focus on a precision medicine approach, tailoring treatments based on the specific mechanisms driving resistance in individual patients.

6.2 Novel immunotherapeutic strategies

In addition to checkpoint inhibitors, novel immunotherapeutic strategies, such as bispecific antibodies and chimeric antigen receptor T (CAR-T) cell therapy, are emerging as promising treatments for RCC. Bispecific antibodies (BsAbs), such as bispecific T-cell engagers (BiTEs), are designed to engage both T cells and tumor cells by simultaneously binding to a tumor antigen and a T-cell receptor, thereby directing the immune system to target cancer cells more effectively. While BsAbs have shown significant efficacy in hematologic malignancies, their success in solid tumors like RCC has been limited, largely due to the immunosuppressive TME (Goebeler and Bargou, 2020). Research is ongoing to improve their effectiveness by combining BsAbs with other immunotherapies or modifying their structure to enhance their function in solid tumors (Zhou, 2024).

CAR-T cell therapy, which involves engineering a patient’s T cells to express receptors specific to tumor antigens, has been revolutionary in treating certain blood cancers. However, its application in solid tumors, including RCC, has faced challenges related to the TME and the difficulty of targeting appropriate antigens. Efforts are being made to modify CAR-T cells to enhance their persistence and efficacy in the hostile environment of solid tumors. For instance, using CAR-T cells that secrete pro-inflammatory cytokines or combining them with checkpoint inhibitors may improve outcomes in RCC patients (Martínez-Sabadell et al., 2022). As research advances, these therapies hold potential for transforming the treatment landscape for RCC.

6.3 Prospects for personalized immunotherapy

The future of cancer treatment is increasingly moving toward personalized immunotherapy, where treatment is tailored to the unique characteristics of each patient’s tumor and immune profile. Advances in genomic sequencing, immunoprofiling, and liquid biopsies have enabled the identification of predictive biomarkers, such as tumor mutational burden (TMB), microsatellite instability (MSI), and specific genetic mutations (e.g., in PBRM1 or JAK2), which can help predict a patient's response to immunotherapy (Meng et al., 2023). This allows clinicians to select the most effective therapies for each patient, minimizing unnecessary treatments and improving outcomes.

Moreover, the development of novel immunotherapies, such as personalized cancer vaccines, oncolytic viruses, and adoptive T-cell therapies, offers the potential for more precise targeting of tumors based on their immunogenic characteristics. For example, therapeutic cancer vaccines aim to stimulate the patient’s immune system to recognize and attack tumor-specific antigens, while oncolytic viruses can selectively infect and kill cancer cells while boosting immune responses. By integrating these novel approaches with existing ICB therapies, personalized immunotherapy could significantly improve survival rates and quality of life for RCC patients (Moreira et al., 2020).

As the field of immuno-oncology evolves, the goal is to develop more individualized treatment plans that take into account not only the genetic makeup of the tumor but also the patient's overall immune health and response to therapy. This approach is expected to enhance the effectiveness of immunotherapies and reduce treatment-related toxicities, leading to better patient outcomes in the future.

7 Concluding Remarks

Immune checkpoint blockade (ICB) therapy has significantly transformed the treatment landscape for renal cell carcinoma (RCC). However, numerous challenges remain, particularly regarding resistance to therapy and optimizing treatment regimens. This concluding section will summarize the efficacy of ICB in RCC and discuss the implications for future research and clinical practice. ICB therapies, particularly those targeting PD-1, PD-L1, and CTLA-4, have demonstrated significant clinical benefits in RCC patients, especially in the metastatic setting. Agents such as nivolumab and pembrolizumab have shown improved survival outcomes, including longer progression-free survival (PFS) and overall survival (OS) compared to traditional therapies. In particular, combination therapies like nivolumab and ipilimumab or pembrolizumab with tyrosine kinase inhibitors (TKIs) have resulted in higher response rates and longer-lasting remissions for many patients. Clinical trials like CheckMate 214 and KEYNOTE-426 have established these combination regimens as standard treatments in metastatic RCC, with evidence showing improved OS and objective response rates (ORR) compared to sunitinib monotherapy. However, while these treatments have provided new hope, only a subset of patients experience durable responses, and resistance to therapy remains a key challenge.

Looking forward, overcoming immune resistance is one of the most critical challenges in ICB therapy for RCC. Future research must focus on better understanding the mechanisms driving both primary and acquired resistance, including the role of the tumor microenvironment and immune evasion tactics employed by cancer cells. Targeting myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), and exploring epigenetic modulators like HDAC inhibitors could offer new avenues to improve ICB efficacy. Another area ripe for exploration is the development of novel immunotherapies such as bispecific antibodies and CAR-T cells, which could enhance the targeting of cancer cells in patients who do not respond to traditional ICBs. Moreover, personalized immunotherapy—tailored to individual patient profiles based on biomarkers such as tumor mutational burden (TMB) and HLA diversity—holds promise for optimizing treatment outcomes and minimizing adverse effects.

Finally, further studies are needed to establish reliable predictive biomarkers for patient selection, which will help clinicians personalize therapy based on individual tumor characteristics and immune profiles. Advances in genetic and molecular profiling are expected to pave the way for more precise and effective use of immunotherapies in RCC, ultimately leading to improved patient outcomes and longer-lasting responses to treatment.

Acknowledgments

I would like to thank two anonymous peer reviewers for their suggestions on my manuscript.

Conflict of Interest Disclosure

The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Abou Alaiwi S., Xie W., Nassar A., Dudani S., Martini D., Bakouny Z., Steinharter J.A., Nuzzo P.V., Flippot R., Martinez-Chanza N., Wei X., McGregor B.A., Kaymakcalan M.D., Heng D.Y.C., Bilen M.A., Choueiri T.K., and Harshman L.C., 2020, Safety and efficacy of restarting immune checkpoint inhibitors after clinically significant immune-related adverse events in metastatic renal cell carcinoma, Journal for Immunotherapy of Cancer, 8(1): e000144.

https://doi.org/10.1136/jitc-2019-000144

PMID: 32066646 PMCID: PMC7057439

Álvarez Ballesteros P., Chamorro J., San Román-Gil M., Pozas J., Gómez Dos Santos V., Granados A., Grande E., Alonso-Gordoa T., and Molina-Cerrillo J., 2021, Molecular mechanisms of resistance to immunotherapy and antiangiogenic treatments in clear cell renal cell carcinoma, Cancers, 13(23): 5981.

https://doi.org/10.3390/cancers13235981

PMID: 34885091 PMCID: PMC8656474

Barrueto L., Caminero F., Cash L., Makris C., Lamichhane P., and Deshmukh R., 2020, Resistance to checkpoint inhibition in cancer immunotherapy, Translational Oncology, 13(3): 100738.

https://doi.org/10.1016/j.tranon.2019.12.010

PMID: 32114384 PMCID: PMC7047187

Bedke J., Albiges L., Capitanio U., Giles R., Hora M., Lam T., Ljungberg B., Marconi L., Klatte T., Volpe A., Abu-Ghanem Y., Dabestani S., Fernández Pello S., Hofmann F., Kuusk T., Tahbaz R., Powles T., and Bex A., 2020, Updated european association of urology guidelines on renal cell carcinoma: nivolumab plus cabozantinib joins immune checkpoint inhibition combination therapies, European Urology, 79(3): 339-342.

https://doi.org/10.1016/j.eururo.2020.12.005

PMID: 33357997

Bi K., He M.X., Bakouny Z., Kanodia A., Napolitano S., Wu J., Grimaldi G., Braun D., Cuoco M.S., Mayorga A., Dellostritto L., Bouchard G., Steinharter J., Tewari A.K., Vokes N., Shannon E., Sun M., Park J., Chang S.L., McGregor B., Haq R., Denize T., Signoretti S., Guerriero J.L., Vigneau S., Rozenblatt-Rosen O., Rotem A., Regev A., Choueiri T., and Van Allen E.V., 2021, Tumor and immune reprogramming during immunotherapy in advanced renal cell carcinoma, Cancer Cell, 39(5): 649-661.

https://doi.org/10.1016/j.ccell.2021.02.015

PMID: 33711272 PMCID: PMC8115394

Budka J.A., Damayanti N., and Pili R., 2019, HDAC inhibition improves immune checkpoint inhibitor efficacy in renal cell carcinoma, Immunology, 79 (13_Supplement): 2366.

https://doi.org/10.1158/1538-7445.SABCS18-2366

Byun D., Wolchok J., Rosenberg L., and Girotra M., 2017, Cancer immunotherapy - immune checkpoint blockade and associated endocrinopathies, Nature Reviews Endocrinology, 13(4): 195-207.

https://doi.org/10.1038/nrendo.2016.205

PMID: 28106152 PMCID: PMC5629093

Chatwal M., Chahoud J., and Spiess P.E., 2023, Revisiting mechanisms of resistance to immunotherapies in metastatic clear-cell renal-cell carcinoma, Cancer Drug Resistance, 6: 314-326.

https://doi.org/10.20517/cdr.2023.09

Chen T., 2024, Single-cell RNA sequencing reveals new insights into tumor heterogeneity, Cancer Genetics and Epigenetics, 12(1): 55-65.

https://doi.org/10.5376/cge.2024.12.0007

Cui S., 2017, Immunogenic chemotherapy sensitizes renal cancer to immune checkpoint blockade therapy in preclinical models, Medical Science Monitor, 23: 3360-3366.

https://doi.org/10.12659/MSM.902426

PMID: 28697172 PMCID: PMC5516681

Diaz-Montero C., Rini B., and Finke J., 2020, The immunology of renal cell carcinoma, Nature Reviews Nephrology, 16: 721-735.

https://doi.org/10.1038/s41581-020-0316-3

Dougan M., 2017, Checkpoint blockade toxicityand immune homeostasis in the gastrointestinal tract, Frontiers in Immunology, 8: 1547.

https://doi.org/10.3389/fimmu.2017.01547

PMID: 29230210 PMCID: PMC5715331

Feng M., Jiang W., Kim B., Zhang C., Fu Y., and Weissman I., 2019, Phagocytosis checkpoints as new targets for cancer immunotherapy, Nature Reviews Cancer, 19: 568-586.

https://doi.org/10.1038/s41568-019-0183-z

Flippot R., Escudier B., and Albiges L., 2018, Immune checkpoint inhibitors: toward new paradigms in renal cell carcinoma, Drugs, 78: 1443-1457.

https://doi.org/10.1007/s40265-018-0970-y

PMID: 30187355

Goebeler M., and Bargou R., 2020, T cell-engaging therapies - BiTEs and beyond, Nature Reviews Clinical Oncology, 17(7): 418-434.

https://doi.org/10.1038/s41571-020-0347-5

PMID: 32242094

Henau O.de., Rausch M., Winkler D., Liu C., Cymerman D.H., Budhu S., Ghosh A., Pink M., Tchaicha M., Douglas M., Tibbitts T., Sharma S., Proctor J., Kosmider N., White K.F., Stern H., Soglia J., Adams J., Palombella V., and McGovern K., 2016, Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells, Nature, 539: 443-447.

https://doi.org/10.1038/nature20554

PMID: 27828943 PMCID: PMC5634331

Lee C.H., Dinatale R., Chowell D., Krishna C., Makarov V., Valero C., Vuong L., Weiss K., Hoen D.R., Morris L., Kotecha R., and Chan T., 2021, High response rate and durability driven by HLA genetic diversity in patients with kidney cancer treated with lenvatinib and pembrolizumab, Molecular Cancer Research, 19: 1510-1521.

https://doi.org/10.1158/1541-7786.MCR-21-0053

PMID: 34039647 PMCID: PMC8419018

Li H., Bullock K., Gurjao C., Braun D., Shukla S., Bossé D., Lalani A., Gopal S., Jin C., Horak C., Wind-Rotolo M., Signoretti S., McDermott D., Freeman G., Van Allen E.V., Schreiber S., Hodi F.S., Sellers W., and Garraway L., 2019, Metabolomic adaptations and correlates of survival to immune checkpoint blockade, Nature Communications, 10(1): 4346.

https://doi.org/10.1038/s41467-019-12361-9

PMID: 31554815 PMCID: PMC6761178

Li J., Chen Y., Li Y., Liu N., and Ma J., 2021, Chemotherapeutic and targeted agents can modulate the tumor microenvironment and increase the efficacy of immune checkpoint blockades, Molecular Cancer, 20(1): 27.

https://doi.org/10.1186/s12943-021-01317-7

PMID: 33541368 PMCID: PMC7863268

Martínez-Sabadell A., Arenas E.J., Rius Ruiz I., Alonso M.R., Escorihuela M., Luque A., Fajardo C.A., Gros A., and Arribas J., 2022, Acquired cancer cell resistance to T cell bispecific antibodies and CAR T targeting HER2 through JAK2 down-modulation, Cancer Research, 82 (12_Supplement): 3970.

https://doi.org/10.1158/1538-7445.AM2022-3970

Massari F., Rizzo A., Mollica V., Rosellini M., Marchetti A., Ardizzoni A., and Santoni M., 2021, Immune-based combinations for the treatment of metastatic renal cell carcinoma: au meta-analysis of randomised clinical trials, European Journal of Cancer, 154: 120-127.

https://doi.org/10.1016/j.ejca.2021.06.015

PMID: 34265504

Meng L., Collier K.A., Wang P., Li Z., Monk P., Mortazavi A., Hu Z., Spakowicz D.J., Zheng L., and Yang Y., 2023, Emerging immunotherapy approaches for advanced clear cell renal cell carcinoma, Cells, 13(1): 34.

https://doi.org/10.3390/cells13010034

PMID: 38201238 PMCID: PMC10777977

Miao D., Margolis C., Gao W., Voss M., Li W., Martini D., Norton C.K., Bossé D., Wankowicz S.A.M., Cullen D., Horak C., Wind-Rotolo M., Tracy A., Giannakis M., Hodi F., Drake C., Ball M.W., Allaf M., Snyder A., Hellmann M.D., Ho T., Motzer R.J., Signoretti S., Kaelin W.J., Choueir T.K., and Van Allen E.V., 2018, Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma, Science, 359(6377): 801-806.

https://doi.org/10.1126/science.aan5951

PMID: 38201238

Moreira M., Pobel C., Epaillard N., Simonaggio A., Oudard S., and Vano Y., 2020, Resistance to cancer immunotherapy in metastatic renal cell carcinoma, Cancer Drug Resistance, 3(3): 454-471.

https://doi.org/10.20517/cdr.2020.16

PMID: 35582435 PMCID: PMC8992500

Murakami N., Borges T., Yamashita M., and Riella L., 2016, Severe acute interstitial nephritis after combination immune-checkpoint inhibitor therapy for metastatic melanoma, Clinical Kidney Journal, 9: 411-417.

https://doi.org/10.1093/ckj/sfw024

PMID: 27274826 PMCID: PMC4886917

Mysler S.J., Perazzo F., and Mandó P., 2023, Autoimmune encephalitis related to nivolumab followed by tumor regression, Medicina, 83(3): 479-483.

PMID: 37379548

Rappold P., Silagy A., Kotecha R., and Hakimi A., 2021, Immune checkpoint blockade in renal cell carcinoma, Journal of Surgical Oncology, 123: 739-750.

https://doi.org/10.1002/jso.26339

PMID: 33595892 PMCID: PMC8364550

Vuong L., Kotecha R., Voss M., and Hakimi A., 2019, Tumor microenvironment dynamics in clear-cell renal cell carcinoma, Cancer Discovery, 9(10): 1349-1357.

https://doi.org/10.1158/2159-8290.CD-19-0499

PMID: 31527133 PMCID: PMC6774890

Xu W., Atkins M., and McDermott D., 2020, Checkpoint inhibitor immunotherapy in kidney cancer, Nature Reviews Urology, 17: 137-150.

https://doi.org/10.1038/s41585-020-0282-3

PMID: 32020040

Zhou J.Y., 2024, The Application of genomics in personalized cancer therapy, Cancer Genetics and Epigenetics, 12(1): 66-74.

https://doi.org/10.5376/cge.2024.12.0009