Overcoming Immunotherapy Resistance: Novel Checkpoints, Biomarkers, and Emerging Therapeutic Strategies

Introduction: The Growing Challenge of Immunotherapy Resistance in Oncology

Immunotherapy has transformed the landscape of cancer treatment, offering durable responses and long-term survival benefits in a subset of patients across multiple tumor types. By harnessing the body’s immune system particularly through immune checkpoint inhibitors targeting PD-1, PD-L1, and CTLA-4 - oncology has entered an era where advanced cancers can be managed more effectively than ever before. However, the initial enthusiasm has been tempered by a significant clinical challenge: not all patients respond, and many who initially benefit eventually develop resistance.

This resistance, whether primary (present from the start) or acquired (emerging after initial response), can result from diverse mechanisms. Tumors may evade immune detection by reducing antigen presentation, upregulating alternative immune checkpoints such as TIGIT or LAG-3, inducing T-cell exhaustion, or exploiting “don’t eat me” signals like CD47. Additionally, the tumor microenvironment can become immunosuppressive, further hindering therapeutic efficacy.

As the use of immunotherapy expands, understanding and overcoming resistance is becoming a top priority in oncology research. Novel biomarkers, targeted checkpoint inhibitors, combination regimens, and strategies to restore immune function are at the forefront of innovation. Addressing these mechanisms is essential to extend the benefits of immunotherapy to a broader patient population and improve long-term outcomes.

Understanding Checkpoint Inhibitor Resistance: Mechanistic Insights

Checkpoint inhibitors have redefined cancer therapy by unleashing cytotoxic T cells against tumor cells. However, their effectiveness can be undermined by both intrinsic and extrinsic resistance mechanisms that limit immune activation. Primary resistance occurs when tumors fail to respond from the outset, often due to low tumor immunogenicity, absence of targetable neoantigens, or defective antigen presentation machinery such as loss of MHC class I expression. Acquired resistance develops after an initial response and can involve adaptive immune escape strategies.

One major pathway involves the upregulation of alternative immune checkpoints like TIGIT, LAG-3, or TIM-3, which suppress T-cell activation despite PD-1/PD-L1 blockade. Tumor cells may also exploit CD47 to send a “don’t eat me” signal to macrophages, avoiding phagocytosis. In addition, chronic antigen exposure can drive T-cell exhaustion, marked by diminished cytokine production and cytolytic capacity.

The tumor microenvironment (TME) plays a critical role by fostering immunosuppression through regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and inhibitory cytokines such as TGF-β and IL-10. Understanding these mechanisms is crucial for designing next-generation immunotherapies, combination regimens, and biomarker-guided strategies that can bypass or reverse resistance, ultimately broadening the patient population that benefits from checkpoint blockade.

TIGIT as a Novel Immunotherapy Target: Clinical Trial Updates and Efficacy Data

TIGIT (T cell immunoreceptor with Ig and ITIM domains) is an emerging immune checkpoint receptor expressed on T cells and natural killer (NK) cells, functioning as a negative regulator of immune activation. By binding to its ligands, primarily CD155 on tumor or antigen-presenting cells, TIGIT dampens T-cell proliferation, cytokine production, and cytotoxic activity, contributing to tumor immune evasion.

Preclinical studies have shown that blocking TIGIT can restore effector T-cell function, enhance NK cell–mediated tumor killing, and synergize with PD-1/PD-L1 inhibitors. This has spurred a wave of clinical development, with multiple anti-TIGIT antibodies, such as tiragolumab, vibostolimab, and ociperlimab, under investigation.

Recent phase II trial data, particularly from the CITYSCAPE study, demonstrated that tiragolumab combined with atezolizumab improved objective response rates and progression-free survival in PD-L1–positive non–small cell lung cancer (NSCLC) compared to PD-L1 blockade alone. However, results from some subsequent trials have been mixed, highlighting the need for careful patient selection and biomarker integration.

Ongoing phase III studies aim to clarify TIGIT’s role across tumor types, including lung, gastrointestinal, and head and neck cancers. If confirmed effective, TIGIT blockade could become a key strategy for overcoming checkpoint inhibitor resistance and expanding durable immunotherapy benefits.

LAG-3 Blockade Strategies for Reversing Immunotherapy Resistance

Lymphocyte activation gene-3 (LAG-3) is an inhibitory receptor expressed on activated T cells, regulatory T cells (Tregs), and natural killer (NK) cells. It negatively regulates T-cell proliferation, cytokine secretion, and immune memory formation. In many cancers, LAG-3 expression is upregulated in the tumor microenvironment (TME), often co-expressed with PD-1 on exhausted T cells. This dual checkpoint expression is a hallmark of resistance to PD-1/PD-L1 inhibitors, as blocking PD-1 alone is insufficient to restore full T-cell function.

LAG-3 blockade aims to reinvigorate exhausted T cells, enhance antigen-specific responses, and improve tumor clearance. The most notable clinical advance is relatlimab, an anti-LAG-3 antibody approved in combination with nivolumab for advanced melanoma, based on the RELATIVITY-047 trial. This combination demonstrated improved progression-free survival compared to nivolumab monotherapy, with manageable toxicity.

Other LAG-3–targeting agents, such as favezelimab and ieramilimab, are in early- and mid-stage trials for melanoma, non–small cell lung cancer, and hematologic malignancies. Combination strategies with PD-1, PD-L1, or CTLA-4 inhibitors appear particularly promising.

As clinical research advances, biomarker-driven patient selection and optimal sequencing with other immunotherapies will be key to fully leveraging LAG-3 blockade as a strategy to overcome checkpoint inhibitor resistance.

CD47 and Tumor Immune Evasion: Advances in ‘Don’t Eat Me’ Signal Blockade

CD47 is a transmembrane protein broadly expressed on normal cells, acting as a critical “self-recognition” marker by binding to signal regulatory protein alpha (SIRPα) on macrophages. This interaction delivers a “don’t eat me” signal that inhibits phagocytosis. Many tumor cells exploit this pathway by overexpressing CD47, thereby evading innate immune clearance and facilitating metastatic spread.

Targeting CD47 has emerged as a promising therapeutic strategy to restore macrophage-mediated tumor cell elimination and enhance antigen presentation for downstream T-cell activation. Several anti-CD47 antibodies and SIRPα-Fc fusion proteins are under clinical evaluation, including magrolimab, evorpacept (ALX148), and lemzoparlimab.

Magrolimab, in combination with azacitidine, has shown encouraging results in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), with high response rates and durable remissions. In solid tumors, early-phase studies suggest that CD47 blockade may synergize with checkpoint inhibitors by bridging innate and adaptive immunity.

However, given CD47’s expression on healthy red blood cells, anemia remains a key on-target toxicity, requiring careful dosing strategies and priming regimens. Ongoing trials are refining safety profiles, optimal combinations, and biomarker-driven patient selection, positioning CD47 blockade as a potential cornerstone in next-generation immunotherapy for resistant cancers.

T-Cell Exhaustion: Key Biomarkers and Their Role in Resistance Pathways

T-cell exhaustion is a dysfunctional state that arises during chronic antigen exposure, such as in cancer or persistent viral infections. Exhausted T cells exhibit reduced proliferative capacity, diminished cytokine production (e.g., IL-2, IFN-γ, TNF-α), and impaired cytotoxic function, limiting their ability to control tumor growth. In the tumor microenvironment (TME), persistent stimulation by tumor antigens and immunosuppressive signals accelerates this process.

Key biomarkers of T-cell exhaustion include sustained expression of inhibitory receptors such as PD-1, TIM-3, LAG-3, TIGIT, and CTLA-4. Transcription factors like TOX, Eomes, and T-bet also play pivotal roles in establishing and maintaining the exhausted phenotype. These markers not only identify dysfunctional T cells but also predict limited responsiveness to PD-1/PD-L1 blockade, making them critical for treatment stratification.

Reversing exhaustion requires targeted strategies to restore T-cell function, including dual or triple checkpoint blockade, cytokine therapy (e.g., IL-15, IL-21), and metabolic reprogramming to enhance energy utilization. Novel therapies are also exploring epigenetic modulation to reset T-cell differentiation states.

By integrating exhaustion biomarkers into clinical decision-making, oncologists can better identify patients at risk of immunotherapy resistance and tailor combination regimens to reinvigorate anti-tumor immunity.

Enhancing Antigen Presentation to Boost Immunotherapy Effectiveness

Effective cancer immunotherapy depends on the immune system’s ability to recognize tumor cells, a process initiated by antigen presentation. Tumor-associated antigens are processed by antigen-presenting cells (APCs), such as dendritic cells, and displayed via major histocompatibility complex (MHC) molecules to activate T cells. However, many tumors evade detection by downregulating MHC expression, impairing antigen processing machinery, or altering dendritic cell function, leading to immune escape and resistance to checkpoint inhibitors.

Enhancing antigen presentation can significantly improve immunotherapy responses. Strategies include using toll-like receptor (TLR) agonists, STING pathway activators, and oncolytic viruses to stimulate dendritic cell maturation and antigen cross-presentation. Radiotherapy and certain chemotherapies can also induce immunogenic cell death, releasing tumor antigens in a form more easily recognized by APCs.

Cancer vaccines, both peptide-based and neoantigen-targeted, are being developed to prime robust T-cell responses, while epigenetic drugs are explored to restore MHC and antigen-processing gene expression. Combining these approaches with PD-1, PD-L1, or CTLA-4 inhibitors may overcome primary resistance by ensuring that T cells have sufficient targets to attack.

By restoring and amplifying antigen presentation, oncologists can unlock the full potential of immune checkpoint blockade and expand durable benefits to more patients.

Adaptive vs Primary Resistance: Clinical Implications for Treatment Planning

Checkpoint inhibitor resistance in cancer immunotherapy can be broadly classified as primary (intrinsic) or adaptive (acquired), each with distinct biological underpinnings and treatment implications.

Primary resistance occurs when patients fail to respond to immunotherapy from the outset. This is often due to low tumor immunogenicity, absence of targetable neoantigens, defects in antigen presentation pathways (e.g., loss of MHC class I), or a “cold” tumor microenvironment lacking T-cell infiltration. For these patients, combination strategies such as adding radiotherapy, oncolytic viruses, or agents that stimulate innate immunity may be required to initiate an effective immune response.

Adaptive resistance, on the other hand, develops after an initial clinical benefit. Tumors evolve under immune pressure, upregulating alternative checkpoints like TIGIT, LAG-3, or TIM-3, recruiting immunosuppressive cells (Tregs, MDSCs), or altering cytokine profiles to dampen T-cell activity. In these cases, sequential or multi-checkpoint blockade, targeted therapy combinations, and modulation of the tumor microenvironment can help restore anti-tumor immunity.

Recognizing whether resistance is primary or adaptive is critical for treatment planning, as it guides biomarker selection, combination regimen choice, and trial enrollment. Personalizing therapy based on resistance type can improve response rates, extend progression-free survival, and optimize long-term patient outcomes.

Resistance Mechanisms Across Tumor Types: Common Patterns and Unique Challenges

While checkpoint inhibitor resistance is a challenge across oncology, the mechanisms and clinical implications can vary significantly between tumor types. Common patterns include loss of antigen presentation (via β2-microglobulin or MHC class I downregulation), upregulation of alternative immune checkpoints (TIGIT, LAG-3, TIM-3), T-cell exhaustion, and recruitment of immunosuppressive cells such as regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). These mechanisms are observed in diverse cancers including melanoma, non–small cell lung cancer (NSCLC), and renal cell carcinoma (RCC).

However, unique challenges arise from tumor-specific biology and microenvironmental factors. For example, pancreatic ductal adenocarcinoma is characterized by a dense desmoplastic stroma and low mutational burden, creating an immune-excluded phenotype resistant to infiltration. Glioblastoma presents an additional hurdle with the blood–brain barrier limiting immune cell access. In triple-negative breast cancer (TNBC), dynamic changes in PD-L1 expression and intratumoral heterogeneity complicate sustained responses.

Understanding both the shared and tumor-specific resistance pathways is critical for selecting optimal immunotherapy strategies. Tailoring approaches such as combining checkpoint inhibitors with stroma-modifying agents in pancreatic cancer or with radiation in brain tumors can help overcome these barriers and expand the therapeutic reach of immuno-oncology across diverse malignancies.

Combining Checkpoint Inhibitors with Targeted Therapies for Resistance Management

Combining checkpoint inhibitors with targeted therapies has emerged as a promising strategy to overcome immunotherapy resistance and enhance anti-tumor efficacy. Targeted agents such as tyrosine kinase inhibitors (TKIs), VEGF pathway blockers, and BRAF/MEK inhibitors can modify the tumor microenvironment (TME) in ways that make it more receptive to immune attack. For example, VEGF inhibition can normalize tumor vasculature, improve T-cell infiltration, and reduce immunosuppressive cell populations, thereby synergizing with PD-1/PD-L1 blockade.

In melanoma, the combination of BRAF/MEK inhibitors with checkpoint inhibitors has shown improved progression-free survival by simultaneously controlling tumor growth and boosting immune recognition. In renal cell carcinoma, regimens pairing PD-1/PD-L1 antibodies with VEGF-targeted TKIs (such as pembrolizumab plus axitinib) have become frontline standards due to superior response rates compared to monotherapy.

Beyond approved combinations, ongoing clinical trials are testing checkpoint inhibitors with PARP inhibitors, IDO1 inhibitors, and epigenetic modulators, aiming to restore antigen presentation and reverse T-cell exhaustion. However, these combinations must be optimized for safety, as overlapping toxicities can limit tolerability.

Strategically pairing immunotherapy with targeted therapy offers a rational approach to managing both primary and adaptive resistance, expanding treatment options and improving outcomes for patients with resistant malignancies.

Emerging Role of Novel Immune Checkpoints Beyond PD-1, PD-L1, and CTLA-4

While PD-1, PD-L1, and CTLA-4 inhibitors have transformed cancer therapy, resistance remains a major limitation, prompting exploration of novel immune checkpoints. Targets such as TIGIT, LAG-3, TIM-3, VISTA, and B7-H3 are gaining attention for their roles in modulating T-cell activity, natural killer (NK) cell function, and antigen-presenting cell responses. These checkpoints often become upregulated in the tumor microenvironment (TME) following PD-1/PD-L1 blockade, serving as alternative inhibitory pathways that sustain immune suppression.

For example, TIGIT blockade can enhance cytotoxic T-cell and NK cell activity, while LAG-3 inhibition restores function to exhausted T cells. TIM-3, often co-expressed with PD-1, contributes to adaptive resistance and may be a key target in combination regimens. VISTA regulates myeloid cell–mediated suppression, making it a promising focus in “cold” tumors with low T-cell infiltration.

Several agents targeting these novel checkpoints are in early- and late-phase clinical trials, frequently tested in combination with established checkpoint inhibitors. The goal is to achieve deeper and more durable responses, particularly in patients who fail first-line immunotherapy.

By expanding the repertoire of checkpoint targets, oncologists can develop more personalized and multi-faceted immunotherapy strategies, potentially overcoming resistance and improving long-term outcomes across diverse cancers.

Biomarker-Driven Patient Selection for Overcoming Resistance

Biomarker-driven patient selection is becoming a cornerstone in optimizing immunotherapy outcomes and overcoming resistance. By identifying predictive and prognostic markers, oncologists can tailor treatments to patients most likely to benefit, while avoiding ineffective therapies. Key biomarkers include PD-L1 expression, tumor mutational burden (TMB), microsatellite instability (MSI) status, and specific gene expression profiles linked to immune activity.

In the context of resistance, additional markers such as alternative checkpoint expression (TIGIT, LAG-3, TIM-3), T-cell exhaustion signatures, and mutations in antigen presentation machinery (e.g., B2M loss) can guide combination strategies. Circulating tumor DNA (ctDNA) and immune gene signatures from RNA sequencing are also emerging tools for real-time monitoring of response and resistance development.

For example, patients with high TIGIT or LAG-3 expression may benefit from novel dual checkpoint blockade, while those with low antigen presentation could be directed toward treatments that enhance dendritic cell function or restore MHC expression.

Integrating biomarker analysis into clinical workflows not only improves treatment precision but also supports clinical trial design by enriching for responsive populations. Ultimately, biomarker-guided immunotherapy personalization has the potential to maximize efficacy, minimize toxicity, and expand the durability of responses in resistant cancers.

Immunotherapy Sequencing and Treatment Timing to Prevent Resistance Development

The sequencing and timing of immunotherapy relative to other cancer treatments can significantly influence outcomes and help prevent resistance. Administering checkpoint inhibitors at an optimal stage in the disease course whether upfront, in combination, or after targeted therapy can determine the degree and durability of immune activation.

For some cancers, frontline immunotherapy combined with targeted agents or chemotherapy has shown superior results by simultaneously debulking tumors and priming the immune system. In other cases, initiating targeted therapy first to normalize the tumor microenvironment before introducing immunotherapy may enhance T-cell infiltration and responsiveness.

Neoadjuvant immunotherapy, given before surgery, is an emerging approach that can elicit strong systemic immune responses and reduce micrometastatic disease, potentially lowering recurrence rates. Likewise, timely switching to alternative checkpoint inhibitors or combination regimens at early signs of adaptive resistance can prevent full immune escape.

Precision in sequencing also involves adjusting treatment intervals to avoid T-cell exhaustion, managing immune-related adverse events to sustain therapy, and integrating biomarkers to guide timing decisions.

By strategically sequencing and timing immunotherapy with other modalities, clinicians can reduce the likelihood of resistance, preserve long-term efficacy, and expand the therapeutic window for durable cancer control.

Current and Future Clinical Trials Targeting Resistance Mechanisms

A growing number of clinical trials are focused on overcoming immunotherapy resistance through novel targets, combination regimens, and biomarker-driven strategies. Current studies are evaluating dual checkpoint blockade such as PD-1 inhibitors combined with emerging targets like TIGIT (e.g., tiragolumab), LAG-3 (e.g., relatlimab), and TIM-3 in cancers that have progressed on standard immunotherapy. Trials combining checkpoint inhibitors with VEGF blockers, PARP inhibitors, or epigenetic modulators aim to remodel the tumor microenvironment and restore antigen presentation.

CD47 blockade agents, including magrolimab and evorpacept, are in advanced-phase trials for hematologic malignancies and solid tumors, often paired with PD-1 or PD-L1 inhibitors to bridge innate and adaptive immunity. Studies of STING and TLR agonists are exploring how to activate dendritic cells and enhance T-cell priming in resistant “cold” tumors.

Future directions include personalized vaccine trials delivering patient-specific neoantigens, adoptive T-cell therapies designed to bypass checkpoint pathways, and real-time biomarker–adaptive protocols that modify treatment based on evolving resistance profiles.

By addressing resistance at multiple biological levels, these trials aim to expand the fraction of patients who achieve durable benefit from immunotherapy and transform resistance from an insurmountable barrier into a manageable clinical challenge.

Conclusion: The Future of Personalized Immuno-Oncology in the Era of Resistance Mitigation

The challenge of immunotherapy resistance is reshaping the future of cancer care, pushing oncology toward more personalized and adaptive treatment strategies. Advances in understanding resistance mechanisms ranging from alternative checkpoint pathways like TIGIT and LAG-3 to antigen presentation deficits and T-cell exhaustion are fueling the development of targeted interventions that address these barriers head-on.

Personalized immuno-oncology will increasingly rely on comprehensive biomarker profiling to match patients with the most effective therapies, whether through dual checkpoint blockade, tumor microenvironment modulation, or antigen presentation enhancement. Dynamic treatment approaches, such as real-time monitoring of resistance evolution via circulating tumor DNA and immune signatures, will enable earlier intervention and therapy adjustment.

The integration of novel immune checkpoints, next-generation vaccines, oncolytic viruses, and precision sequencing of therapies promises to extend durable responses to a broader patient population. At the same time, thoughtful trial design and multidisciplinary collaboration will be essential to translate these innovations into routine practice.

In the era of resistance mitigation, the ultimate goal is clear: to transform immunotherapy from a breakthrough option for a subset of patients into a reliable, long-term solution for the majority, achieving sustained cancer control and improved quality of life.

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