Cancer therapy has undergone significant evolution over the past several decades, shifting from conventional treatments, such as surgery, chemotherapy, and radiation, to more sophisticated, targeted approaches. Immuno-oncology (also known as cancer immunotherapy) represents one of the most transformative advances in oncology, harnessing the body's immune system to recognize and eliminate malignant cells. Unlike traditional cancer treatments that directly attack tumors, immuno-oncology focuses on modulating immune responses, offering the potential for more durable and selective treatment outcomes. The significance of immuno-oncology lies in its ability to provide long-term cancer control by leveraging immune memory. This has led to groundbreaking therapies, such as immune checkpoint inhibitors, adoptive T cell therapies, oncolytic viruses, and cancer vaccines. While these advances have revolutionized oncology, challenges remain in patient response variability, immune-related toxicities, and the development of resistance mechanisms. Understanding the historical foundations of immuno-oncology provides critical context for how the field has reached its current state and where it is headed.
A Long History of Immunological Approaches to Cancers
Paul Ehrlich’s cancer immunosurveillance hypothesis (1908)
The concept that the immune system plays a role in suppressing tumor formation dates back to research conducted by Paul Ehrlich in the early 20th century. Ehrlich proposed that the immune system continuously eliminates cancerous cells before they become clinically detectable. However, this idea remained speculative for decades owing to the limited understanding of immune mechanisms and the absence of experimental models to validate the hypothesis.
Burnet and Thomas' immunosurveillance theory (1950s)
The cancer immunosurveillance hypothesis gained scientific credibility in the 1950s when Sir Frank Macfarlane Burnet and Lewis Thomas suggested that the immune system could recognize and destroy emerging cancer cells before they formed detectable tumors. This theory proposed that cellular immunity, particularly T cell–mediated immunity, played a central role in identifying and eliminating abnormal cells expressing tumor-specific antigens.
Early evidence supporting immunosurveillance emerged from studies showing increased cancer incidence in immunosuppressed individuals, such as organ transplant recipients and patients with immunodeficiency disorders. However, skepticism remained, as many cancers still developed despite an intact immune system. This led to the realization that tumors possess mechanisms to evade immune detection, shifting the focus from immunosurveillance alone to a more comprehensive view of the immune system’s interaction with cancer.
The inclusion of immune evasion in the "Hallmarks of Cancer"
For much of the 20th century, cancer research primarily focused on genetic mutations and signaling pathways within tumor cells. This perspective was formalized in the landmark publication "The Hallmarks of Cancer" by Douglas Hanahan and Robert Weinberg in 2000,1 which outlined six fundamental traits of cancer, including sustained proliferative signaling and evasion of apoptosis. However, this original framework did not include immune evasion as a defining characteristic of cancer.
A major paradigm shift occurred in 2011, when Hanahan and Weinberg updated their hallmarks to include “avoiding immune destruction” and “tumor-promoting inflammation.” This revision acknowledged that tumors not only escape immune detection but can actively manipulate immune responses to promote their survival. The recognition of immune evasion as a hallmark of cancer reinforced the importance of immuno-oncology as a therapeutic strategy and accelerated research into ways to overcome tumor-induced immune suppression.
Shift from Targeting Cancer Cells Directly to Harnessing the Immune System
Traditional cancer treatments, such as chemotherapy and radiation, operate by directly targeting rapidly dividing cells. While effective, these approaches often lack specificity, leading to significant collateral damage to healthy tissues and the risk of severe side effects. The shift toward immuno-oncology marked a fundamental change in cancer treatment by focusing on the immune system’s natural ability to distinguish between healthy and malignant cells.
Immunotherapy works by either enhancing the immune system’s ability to recognize and attack cancer cells or by removing inhibitory signals that prevent immune cells from functioning effectively. The key advantage of this approach is its potential to generate long-term immune memory, reducing the likelihood of cancer recurrence. The transition from direct tumor targeting to immune modulation has led to significant clinical successes, particularly with checkpoint inhibitors and adoptive T cell therapies.
The progression of immuno-oncology can be divided into three major phases:
Conceptual foundation (Early 1900s – 1980s): Theories of cancer immunosurveillance emerged, but limited experimental evidence led to skepticism.
Experimental breakthroughs (1990s – 2010s): The discovery of immune checkpoints, such as CTLA-4 and PD-1, provided a mechanistic understanding of immune regulation in cancer, leading to the first immunotherapies.
Clinical implementation and next-generation therapies (2010s – present): Immunotherapies have become a standard component of cancer treatment, with ongoing efforts to optimize combination strategies and patient selection through biomarker research.
As the field continues to evolve, the focus is shifting toward overcoming resistance mechanisms, identifying predictive biomarkers, and integrating artificial intelligence to enhance patient stratification and therapeutic decision-making. The following sections will explore the mechanisms of cancer immunoediting, the major successes and limitations of immunotherapy, and emerging strategies shaping the future of immuno-oncology.
The Science of Cancer Immunoediting: How the Immune System Shapes Tumor Development
The relationship between the immune system and cancer is dynamic, involving both protective and permissive interactions. Initially, the immune system was thought to function primarily as a defense mechanism against tumor development, a concept known as cancer immunosurveillance. However, research over the past two decades has led to a more nuanced understanding of how immune activity not only eliminates cancer but can also shape its evolution. This process, known as cancer immunoediting, consists of three phases: elimination, equilibrium, and escape.2
The Three Phases of Cancer Immunoediting
In the elimination phase, the immune system successfully detects and destroys malignant cells before they establish a clinically detectable tumor. This process involves both innate and adaptive immune responses. Natural killer (NK) cells and macrophages serve as the first line of defense, recognizing and attacking transformed cells based on abnormal surface markers or stress signals. Dendritic cells capture tumor antigens from dying cells and present them to T cells, initiating a more specific immune response.
Once primed, cytotoxic CD8+ T cells become the key effectors, recognizing tumor cells via antigen presentation through major histocompatibility complex class I (MHC-I) molecules. These T cells induce apoptosis in cancer cells through the release of cytotoxic proteins such as perforin and granzyme B. Additionally, cytokines such as interferon-gamma (IFN-γ) and interleukin-12 (IL-12) amplify immune activation and suppress tumor proliferation.3 If the immune response is sufficiently robust, tumor cells are eliminated before they have the chance to grow and establish a neoplasm.
For tumors that manage to survive this initial immune assault, the equilibrium phase represents a prolonged period in which the immune system contains — but does not fully eradicate — malignant cells. During this phase, cancer cells and immune cells exist in a state of balance, with immune pressures selecting for tumor variants that are less recognizable or more resistant to immune attack.3 The immune response remains active, particularly through cytotoxic T cells and NK cells, but some cancer cells may persist in a dormant state, undergoing genetic and epigenetic changes that help them evade detection. Over time, mutations in tumor cells can allow them to reduce their expression of immunogenic antigens, alter their metabolic state to resist immune-mediated apoptosis, or recruit regulatory immune cells that suppress antitumor immunity. The equilibrium phase can last for years, and in some cases, tumors may remain in a dormant state indefinitely. However, if cancer cells acquire sufficient immune-evasive properties, they will progress to the escape phase.
In the escape phase, tumor cells overcome immune surveillance and begin to proliferate uncontrollably. By this stage, cancer cells employ multiple strategies to suppress or evade immune responses.5 One mechanism is the loss of antigenicity, where tumors downregulate MHC-I molecules, making them less visible to cytotoxic T cells. Another strategy involves the secretion of immunosuppressive cytokines, such as TGF-β and interleukin-10 (IL-10), which inhibit T cell activation and promote the recruitment of regulatory T (Treg) cells and myeloid-derived suppressor cells (MDSCs) that dampen the immune response. Additionally, tumor cells often express immune checkpoint molecules such as programmed death-ligand 1 (PD-L1), which binds to the PD-1 receptor on T cells, effectively shutting down their activity. As these mechanisms accumulate, the tumor is able to establish an immunosuppressive microenvironment, allowing it to thrive despite the presence of immune cells that would otherwise eliminate it.2
The Role of Immune Cells in Tumor Recognition and Clearance
Throughout the immunoediting process, several key immune cell types determine whether cancer is controlled or allowed to progress. CD8+ cytotoxic T cells play the most critical role in directly eliminating tumor cells, recognizing antigenic peptides presented on MHC-I molecules and inducing apoptosis. However, these cells require activation and support from CD4+ helper T cells, which secrete cytokines such as IL-2 to sustain their function.4
NK cells serve as a vital component of the innate immune system’s antitumor response, particularly against tumors that downregulate MHC-I expression as an immune evasion strategy. Unlike T cells, NK cells do not require antigen presentation and instead recognize cancer cells based on stress-induced ligands or the absence of inhibitory signals. They kill tumor cells through direct cytotoxicity and by secreting IFN-γ, which enhances the activity of other immune cells.2
Dendritic cells are the primary antigen-presenting cells in the tumor microenvironment, responsible for capturing tumor antigens and presenting them to naïve T cells in lymph nodes. Their ability to cross-present antigens is critical for initiating adaptive immune responses. However, tumors can interfere with dendritic cell function by promoting an immunosuppressive phenotype, limiting their ability to activate T cells.3
Another subset of immune cells, γδ T cells, bridges innate and adaptive immunity. These cells recognize stress-induced molecules on tumor cells and secrete inflammatory cytokines such as IFN-γ and TNF-α, contributing to antitumor immunity. However, depending on the tumor microenvironment, γδ T cells can also adopt immunosuppressive functions, complicating their role in cancer.5
Beyond cellular immune responses, cytokines and signaling molecules regulate tumor–immune interactions. IFN-γ is one of the most potent antitumor cytokines, promoting antigen presentation and directly inhibiting tumor growth. IL-12 plays a complementary role by enhancing T cell and NK cell activity. On the other hand, immunosuppressive factors, such as IL-10 and TGF-β, counteract these effects, dampening immune responses and facilitating tumor progression.2
A major focus of modern cancer immunotherapy is reversing the escape phase and restoring effective immune responses against tumors. Immune checkpoint inhibitors, such as anti-CTLA-4 and anti-PD-1/PD-L1 antibodies, are designed to block inhibitory signals that suppress T cell activity. By preventing tumors from shutting down immune responses, these therapies reinvigorate cytotoxic T cells and enhance antitumor immunity. Additionally, adoptive cell therapies, including CAR-T cells, seek to bypass immune evasion altogether by engineering T cells to recognize tumor antigens with high specificity, regardless of MHC-I expression.4
The interplay between tumor cells and the immune system is central to the progression and treatment of cancer. The immunoediting framework explains why some cancers are controlled by immune responses while others escape and become lethal. A deeper understanding of the mechanisms underlying tumor immune evasion is essential for developing more effective immunotherapies and ensuring that patients derive the maximum benefit from these revolutionary treatments.
Immuno-Oncology Successes: Transformative Therapies and Clinical Impact
Over the past two decades, immuno-oncology has fundamentally changed cancer treatment, offering novel approaches that harness the body's immune system to target and eliminate cancer cells. Unlike traditional therapies, which often cause significant collateral damage to healthy tissues, immunotherapy provides the potential for more selective and durable responses. Among the most successful and widely adopted immunotherapies are immune checkpoint inhibitors, adoptive cell therapies, and oncolytic virus therapy. Additionally, the use of biomarkers has enhanced the ability to predict which patients are most likely to benefit from these interventions.2
Checkpoint Inhibitors: Revolutionizing Cancer Treatment
One of the most groundbreaking advances in immuno-oncology has been the development of immune checkpoint inhibitors (ICIs). Checkpoint molecules, such as CTLA-4 and PD-1/ PD-L1, act as brakes on the immune system, preventing excessive immune activation and maintaining self-tolerance. However, many cancers exploit these checkpoints to evade immune detection, rendering T cells ineffective in attacking tumors.3
The first U.S. Food and Drug Administration (FDA)-approved checkpoint inhibitor, ipilimumab, is a monoclonal antibody targeting CTLA-4, which prevents it from dampening T cell activity. Approved in 2011 for metastatic melanoma, ipilimumab demonstrated the ability to induce long-term remission in a subset of patients who previously had limited treatment options.4
Checkpoint inhibitors targeting the PD-1/PD-L1 axis followed soon after, showing even broader success across multiple cancer types. Nivolumab and pembrolizumab (anti-PD-1) and atezolizumab (anti-PD-L1) work by preventing tumors from shutting down immune responses, thereby allowing T cells to mount a sustained attack. These therapies have demonstrated remarkable clinical benefits, particularly in melanoma, non-small cell lung cancer (NSCLC), renal cell carcinoma, and Hodgkin’s lymphoma. In some cases, checkpoint inhibitors have led to durable responses lasting years, an outcome rarely observed with chemotherapy or targeted therapies.2
While checkpoint inhibitors have revolutionized cancer care, they are not effective for all patients. A significant portion of individuals do not respond or eventually develop resistance. Efforts to enhance efficacy include combining ICIs with chemotherapy, radiotherapy, or other immunotherapies, as well as identifying biomarkers to better predict responders.5
Adoptive Cell Therapy: The Rise of Personalized Cancer Treatments
Another major breakthrough in immuno-oncology is adoptive cell therapy (ACT), which involves harvesting a patient’s immune cells, modifying or expanding them, and reinfusing them to enhance their ability to recognize and attack tumors. The most well-known and successful form of ACT is chimeric antigen receptor (CAR)-T cell therapy.1
CAR-T therapy involves genetically engineering T cells to express receptors that recognize specific cancer antigens. This approach bypasses the need for antigen presentation via major histocompatibility complex (MHC) molecules, making CAR-T cells highly effective against certain hematologic malignancies. The first CAR-T therapies, targeting CD19, were approved for B cell acute lymphoblastic leukemia (ALL) and large B cell lymphoma, showing unprecedented complete response rates in patients with otherwise refractory disease.3
The success of CAR-T therapy in blood cancers has driven research into its potential for solid tumors. However, expansion into this area presents significant challenges, including heterogeneous antigen expression, an immunosuppressive tumor microenvironment, and T cell exhaustion. Efforts to improve CAR-T efficacy in solid tumors include engineering T cells to resist exhaustion, enhancing tumor infiltration, and using combinatorial antigen targeting strategies.4
Other ACT approaches include tumor-infiltrating lymphocyte (TIL) therapy, which involves isolating and expanding a patient’s own tumor-reactive T cells. While still largely experimental, TIL therapy has shown promise in melanoma and other solid tumors.2
Oncolytic Virus Therapy: A New Frontier
A more recent development in immuno-oncology is the use of oncolytic viruses (OVs), which are engineered to selectively infect and destroy tumor cells while simultaneously stimulating an antitumor immune response. Talimogene laherparepvec (T-VEC), a modified herpes simplex virus expressing granulocyte-macrophage colony-stimulating factor (GM-CSF), became the first oncolytic virus therapy to receive FDA approval in 2015 for the treatment of melanoma.3
T-VEC works through two primary mechanisms: direct tumor cell lysis and immune system activation. As the virus replicates within tumor cells, it causes them to burst, releasing tumor antigens that can be recognized by the immune system. The presence of GM-CSF further enhances dendritic cell activation and T cell priming.5
While T-VEC has demonstrated efficacy in melanoma, particularly in patients with injectable, localized lesions, its effect in metastatic disease remains limited. Current research is exploring ways to improve oncolytic virus therapy, including engineering OVs to express checkpoint inhibitors or proinflammatory cytokines, as well as using systemic delivery strategies to enhance tumor targeting.2
The Role of Biomarkers in Predicting Response to Immunotherapy
A key challenge in immuno-oncology is the variability in patient responses. Not all patients benefit from ICIs, CAR-T therapy, or oncolytic viruses, making it essential to identify biomarkers that can predict treatment success.4
One of the most widely used biomarkers in immuno-oncology is PD-L1 expression, which correlates with response to anti-PD-1/PD-L1 therapies. High levels of PD-L1 on tumor or immune cells have been associated with better responses in lung cancer, melanoma, and bladder cancer. However, PD-L1 alone is not always sufficient, as some patients with low expression still respond, while others with high expression do not.2
Tumor mutational burden (TMB) has emerged as another important predictive biomarker. Tumors with a high mutational load are more likely to generate neoantigens, making them more immunogenic and responsive to checkpoint blockade. This has been observed in cancers such as melanoma and lung cancer.3
Microsatellite instability (MSI) and mismatch repair deficiency (dMMR) have also been identified as strong predictors of response to immunotherapy. Tumors with MSI-high (MSI-H) status, commonly seen in colorectal, endometrial, and gastric cancers, have been shown to respond well to PD-1 blockade.2
Checkpoint inhibitors, CAR-T therapy, and oncolytic viruses have demonstrated remarkable potential in changing the way cancer is treated. However, challenges remain, including treatment resistance, toxicity, and patient selection. By integrating biomarker-driven strategies and exploring new combinations of immunotherapies, researchers are working toward more effective and personalized approaches to cancer treatment.
Challenges and Failures: Why Immunotherapy Doesn’t Work for Everyone
While immunotherapy has revolutionized cancer treatment, it remains ineffective for a significant portion of patients. Many individuals either do not respond to treatment from the outset (primary resistance) or initially respond but later develop mechanisms to evade immune attack (acquired resistance). Additionally, some patients experience immune-related adverse events (irAEs) due to excessive immune activation. Beyond biological limitations, computational and clinical challenges continue to hinder efforts to optimize patient selection, treatment strategies, and clinical trial design. Addressing these barriers is critical to expanding the benefits of immunotherapy to a larger patient population.2
Primary and Acquired Resistance to Immunotherapies
One of the major limitations of immunotherapy is that not all tumors are equally susceptible to immune attack. Some cancers possess intrinsic resistance mechanisms that prevent them from being recognized by the immune system in the first place (primary resistance), while others adapt and evade immune pressure after initial treatment (acquired resistance).3
A key mechanism of resistance involves the loss or alteration of tumor antigens, which prevents immune cells from identifying and attacking the cancer. In response to selective immune pressure, tumors may undergo antigenic drift, where they stop expressing certain antigens targeted by CAR-T cells or cytotoxic T lymphocytes. This is particularly problematic for adoptive T cell therapies, as CAR-T cells are highly specific and cannot adapt to recognize new antigens.4
Another major resistance mechanism is the downregulation of MHC class I molecules, which tumors use to present antigenic peptides to CD8+ cytotoxic T cells. Without MHC-I expression, T cells cannot recognize tumor cells, rendering checkpoint inhibitors and vaccine-based therapies ineffective.2 Cancers can also upregulate inhibitory immune checkpoints, such as PD-L1 and CTLA-4, to suppress T cell activity. This immune escape strategy has been observed in patients who initially respond well to PD-1/PD-L1 inhibitors but later relapse as tumors adapt to therapy.5
To counteract these resistance mechanisms, researchers are exploring combination therapies that target multiple pathways simultaneously. For example, combining checkpoint inhibitors with cancer vaccines or CAR-T cells may help maintain immune pressure and prevent tumors from evading detection. Additionally, epigenetic reprogramming strategies are being investigated to restore MHC-I expression and enhance immune recognition.3
Toxicity and Adverse Effects of Immunotherapy
While immunotherapy can effectively enhance antitumor immunity, it can also disrupt immune homeostasis, leading to immune-related adverse events (irAEs). Unlike chemotherapy, which primarily affects rapidly dividing cells, immunotherapy activates the immune system in a systemic and unpredictable manner, increasing the risk of autoimmune-like complications.2
The most common irAEs affect the gastrointestinal, pulmonary, endocrine, and dermatologic systems. Colitis, characterized by severe inflammation of the intestines, is frequently observed in patients receiving CTLA-4 inhibitors (e.g., ipilimumab). Pneumonitis, an inflammatory reaction in the lungs, is a serious complication associated with PD-1/PD-L1 inhibitors. Endocrine dysfunction, including hypophysitis (pituitary inflammation) and thyroiditis, can lead to long-term hormonal imbalances requiring lifelong hormone replacement therapy.4
Although immune checkpoint inhibitors tend to have fewer systemic toxicities than chemotherapy, the severity of irAEs varies widely, and some cases can be life-threatening. Early detection and intervention are critical to managing these toxicities. Corticosteroids are the first-line treatment for severe irAEs, while newer immunosuppressive agents, such as TNF inhibitors and IL-6 blockers, are being tested for steroid-refractory cases.3
To reduce the risk of toxicity, researchers are exploring biomarker-based patient selection strategies, identifying individuals who are more likely to experience irAEs. For instance, patients with preexisting autoimmune disorders or high levels of proinflammatory cytokines may be at greater risk. Another approach involves combining lower doses of checkpoint inhibitors with other immunomodulatory agents, rather than using high-dose monotherapy, to achieve efficacy while minimizing toxicity.5
Computational and Clinical Challenges
Beyond biological limitations, there are significant computational and clinical hurdles in immuno-oncology research. A major challenge is the lack of predictive models to accurately determine who will respond to immunotherapy. While biomarkers such as PD-L1 expression, TMB, and MSI-H/dMMR have been useful, they do not fully predict treatment outcomes, and many patients with high biomarker levels still fail to respond.2
To improve predictive accuracy, researchers are turning to artificial intelligence (AI) and big data analytics. Machine learning algorithms can analyze genomic, proteomic, and immunologic data to identify patterns that correlate with response or resistance to therapy. AI models are also being used to optimize clinical trial design, enabling adaptive trial protocols that modify treatment strategies in real-time based on patient responses.5
Another major issue is disparities in access to immunotherapy. While checkpoint inhibitors and CAR-T therapies have been approved for a variety of cancers, they remain extremely expensive, limiting access in low- and middle-income countries (LMICs). Even in high-income nations, racial and socioeconomic disparities affect clinical trial enrollment, with underrepresentation of Black, Hispanic, and indigenous populations in pivotal immunotherapy studies. Addressing these disparities requires policy interventions to improve access, as well as inclusive clinical trial recruitment strategies to ensure diverse patient populations are studied.4
Additionally, there are logistical challenges in scaling up personalized immunotherapies like CAR-T cell therapy, which require individualized manufacturing and complex supply chain logistics. Efforts are underway to develop off-the-shelf CAR-T therapies, using gene-edited universal donor cells to reduce costs and improve accessibility.3
Emerging Frontiers in Immuno-Oncology: The Next Generation of Cancer Treatments
As immuno-oncology continues to evolve, researchers are exploring new strategies to expand the efficacy and reach of immunotherapies. While ICIs, ACTs, and OVs have transformed cancer treatment, challenges such as immune resistance, limited response rates, and tumor microenvironment-induced immunosuppression persist. The next generation of immunotherapies aims to enhance immune activation, personalize treatments, and leverage AI to optimize therapeutic design and patient selection. Key areas of advancement include new immune checkpoint targets, cancer vaccines, tumor microenvironment modulation, and computational approaches to improve drug discovery and clinical trial efficiency.2
New Checkpoint Targets and Combination Therapies
Checkpoint blockade therapy has achieved remarkable success by targeting CTLA-4, PD-1, and PD-L1, but many patients do not respond, and tumors often develop resistance. To address these limitations, researchers are investigating new checkpoint targets, including LAG-3, TIM-3, and TIGIT, which play complementary roles in suppressing immune responses.3
LAG-3 is expressed on exhausted T cells and contributes to immune suppression by downregulating T cell activation. LAG-3 inhibitors have shown promise in melanoma and lung cancer, particularly in combination with PD-1 inhibitors. Relatlimab, the first LAG-3–blocking antibody, demonstrated improved progression-free survival in melanoma when combined with nivolumab, leading to its FDA approval in 2022.4
TIM-3 functions as an inhibitory receptor that suppresses antitumor immunity by promoting T cell exhaustion and reducing dendritic cell activity. TIM-3 inhibitors are currently being tested in solid tumors and hematologic malignancies, often in combination with PD-1 blockade.2
TIGIT is another emerging checkpoint molecule that dampens immune responses by interacting with CD155 on tumor and antigen-presenting cells. Tiragolumab, a TIGIT-blocking antibody, has shown potential in NSCLC when used alongside PD-1/PD-L1 inhibitors.5
Beyond single-agent therapies, combination approaches are gaining traction. ICIs are being paired with CAR-T therapies, OVs, and radiation therapy to enhance their impact. CAR-T cells engineered to resist exhaustion and express immune checkpoint inhibitors are being tested in solid tumors, an area where traditional CAR-T therapies have struggled. OVs, which typically selectively infect and destroy tumor cells, can also be engineered to deliver checkpoint inhibitors directly to the tumor microenvironment, reducing systemic toxicity while enhancing immune activation. Radiation therapy, known to increase tumor antigen release and promote immune activation, is also being integrated into combination regimens to boost checkpoint blockade efficacy.3
The Rise of Next-Generation Cancer Vaccines
Cancer vaccines have long been pursued as a means of stimulating immune responses against tumors, but early attempts using whole tumor lysates or general tumor antigens had limited success. The emergence of neoantigen-based vaccines has revitalized interest in this approach.2
Advances in next-generation sequencing (NGS) and bioinformatics have enabled the rapid identification of patient-specific neoantigens, allowing for personalized cancer vaccine development. RNA-based vaccines, such as those used in COVID-19 immunization, have also demonstrated potential for rapid neoantigen vaccine production. Early clinical trials suggest that neoantigen vaccines combined with checkpoint inhibitors can enhance tumor-specific immune responses and improve survival in cancers such as melanoma and glioblastoma.4
Modulating the Tumor Microenvironment for Better Response
A major challenge in immunotherapy is the presence of an immunosuppressive tumor microenvironment (TME), which limits T cell infiltration and activity. The TME consists of Treg cells, MDSCs, tumor-associated macrophages (TAMs), and fibroblasts, all of which contribute to immune evasion.5 Targeting Treg cells is one promising approach to overcoming immune suppression. Treg cells express CTLA-4, CD25, and FOXP3, making them an attractive target for selective depletion. Low-dose anti-CTLA-4 therapy has been investigated for preferentially depleting Treg cells while sparing effector T cells.3
MDSCs, which suppress T cell responses through arginase, reactive oxygen species (ROS), and nitric oxide, are also a focus of new therapeutic strategies. Drugs targeting CSF1R, IL-6, and STAT3, which are involved in MDSC recruitment and function, are being explored to enhance immunotherapy responses.2 Fibroblasts in the TME contribute to tumor stiffness and immune exclusion, preventing T cells from infiltrating tumors. TGF-β inhibitors have been proposed to reprogram cancer-associated fibroblasts, making tumors more susceptible to immune attack. In pancreatic cancer, for example, combining TGF-β blockade with ICIs has led to increased T cell infiltration and better tumor control.4
Computational Immuno-Oncology and AI-Driven Insights
Advancements in computational immunology are reshaping how researchers develop and test immunotherapies. Machine learning algorithms are being trained on clinical, genomic, and imaging data to predict patient responses to immunotherapy with greater accuracy than traditional biomarkers.5
AI models can identify complex immune signatures that correlate with response or resistance, providing a more holistic view of the tumor–immune interaction than individual biomarkers like PD-L1 expression or TMB. Deep learning algorithms have also been applied to pathology images to detect subtle immune infiltration patterns that might predict which tumors will respond to checkpoint inhibitors.2
In addition to patient stratification, AI-powered drug discovery is accelerating the development of novel immune-modulating agents. Generative AI models trained on molecular structures and protein interactions are being used to design new checkpoint inhibitors, cytokine-based therapies, and tumor-targeting antibodies.3 AI-driven simulations can predict optimal drug combinations by analyzing millions of potential interactions, helping to design more effective and personalized immunotherapy regimens.4
The Future of Immuno-Oncology: Opportunities and Next Steps
Immuno-oncology has already transformed cancer treatment, but significant challenges remain in translating cutting-edge research into widespread clinical application. While ICIs, CAR-T therapies, and OVs have reshaped treatment paradigms, their impact is still limited by patient response variability, cost, and logistical hurdles. The future of immuno-oncology will be defined by enhancing precision medicine approaches, improving global accessibility, and leveraging emerging biotechnologies such as gene editing and synthetic biology to refine and expand immunotherapy’s potential.3
Bridging the Gap Between Research and Clinical Application
One of the major areas of focus for the future of immuno-oncology is optimizing patient selection through biomarker-driven precision medicine. While PD-L1 expression, TMB, and MSI) have been useful indicators of response to checkpoint inhibitors, they fail to fully predict outcomes, as many patients with high biomarker levels do not respond, while some with low levels do. Advances in multi-omics approaches, integrating genomics, transcriptomics, proteomics, and immune profiling, could lead to more refined patient stratification. AI-powered biomarker discovery is also expected to play a major role in identifying new immune signatures that correlate with treatment efficacy.4
Beyond biomarkers, the clinical trial model for immuno-oncology drugs is evolving. Traditional randomized controlled trials (RCTs) may not be the best approach for assessing personalized immunotherapies, as response rates and immune dynamics vary significantly across patients. Adaptive trial designs that allow for modifications based on early patient data could optimize drug development. Similarly, the use of real-world evidence (RWE) and patient registries may provide more comprehensive insights into long-term treatment efficacy and safety.5
Regulatory agencies are also adapting to the fast-paced development of immunotherapies. The FDA’s breakthrough designation for cell and gene therapies has helped expedite approvals, but further streamlining of regulatory processes could accelerate access while maintaining safety standards. One proposed strategy involves harmonizing global regulatory frameworks, allowing for faster international approvals.2
Overcoming Financial and Accessibility Barriers
Despite its success, immuno-oncology remains prohibitively expensive for many patients, particularly in LMICs. ICIs cost upwards of $100,000 per year, and CAR-T cell therapies can exceed $400,000 per patient, placing them out of reach for most healthcare systems. Addressing these financial barriers will be crucial to ensuring that immunotherapy is not a treatment reserved for the wealthiest patients.3
Several strategies are being explored to reduce the cost of immunotherapy. One approach is to optimize dosing regimens, potentially lowering costs by reducing the frequency or amount of drug needed while maintaining efficacy. Research is also underway to develop biosimilars for checkpoint inhibitors, which could significantly reduce prices once patents expire.3
For CAR-T and other cell therapies, automation and manufacturing standardization could help scale production and drive down costs. Current CAR-T production involves individualized manufacturing, where a patient’s own T cells are engineered and expanded in specialized facilities, contributing to high costs and long turnaround times. The development of off-the-shelf (allogeneic) CAR-T cells, derived from healthy donors and mass-produced, could make this treatment more accessible.5
Global initiatives are also working to expand immunotherapy access. The World Health Organization (WHO) and non-governmental organizations (NGOs) are advocating for increased funding for cancer immunotherapy programs in LMICs, while certain drug manufacturers are partnering with governments to implement tiered pricing models. Another promising approach is the development of locally produced immunotherapies, leveraging mRNA-based and viral vector platforms to create regionally manufactured cancer vaccines and cell therapies.2
A Look Ahead: What’s Next for Immuno-Oncology?
Looking to the future, one of the biggest questions is whether immunotherapy will become the backbone of all cancer treatments. While chemotherapy and radiation remain standard treatments for many cancers, there is a growing movement toward combining immunotherapy with traditional modalities to improve efficacy and durability of response. Some experts predict that immune-based therapies could replace chemotherapy entirely in certain cancers, particularly melanoma, lung cancer, and hematologic malignancies, where checkpoint inhibitors and CAR-T therapies have already demonstrated superior outcomes.3
Beyond checkpoint blockade and CAR-T, gene editing and synthetic biology are expected to revolutionize the next generation of immunotherapies. CRISPR and base-editing technologies are already being used to engineer T cells with enhanced tumor-killing abilities and resistance to immune suppression. Future applications may include programmable immune cells that can dynamically adjust their activity in response to tumor evolution, preventing resistance from developing.4
Synthetic biology is also enabling the creation of immune cell circuits, where T cells or NK cells can be engineered to recognize multiple tumor antigens simultaneously, reducing the risk of antigen escape. Some teams are working on T cell receptor (TCR)-engineered therapies that can recognize intracellular tumor antigens, expanding the reach of adoptive cell therapies beyond surface antigens.5
Another frontier in immuno-oncology involves reprogramming the TME to make it more conducive to immune attack. Targeting metabolic pathways in the TME to deplete suppressive myeloid cells and fibroblasts could enhance the effectiveness of existing immunotherapies. Microbiome research is also revealing how gut bacteria influence immune responses, with early trials investigating whether modifying the microbiome can improve responses to checkpoint inhibitors.2
The Future of Immuno-Oncology
Immuno-oncology has already transformed cancer treatment, but the next decade will see even greater advancements. Personalized immunotherapies, AI-driven drug development, and gene editing technologies will drive new breakthroughs, while efforts to reduce costs and expand access will determine how widely these innovations benefit patients around the world.
If current trends continue, we may see a future where cancer is primarily treated through immune system modulation, with chemotherapy and radiation playing only secondary roles. The integration of synthetic biology, computational immunology, and global policy changes will shape the future of cancer care, potentially leading to curative immunotherapies for previously untreatable malignancies.
As research continues, the ultimate goal is to make immuno-oncology treatments safer, more effective, and accessible to all patients, regardless of location or socioeconomic status. The path ahead is complex, but the progress made so far suggests that immunotherapy is well on its way to becoming the foundation of next-generation cancer medicine.
References
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Hamdan F and V Cerullo. “Cancer immunotherapies: A hope for the uncurable?” Front. Mol. Med. 3:1140977 (2023).
Franklin MR, S Platero, KS Saini KS, et al. “Immuno-oncology trends: preclinical models, biomarkers, and clinical development.” Journal for ImmunoTherapy of Cancer. 10: e003231 (2022). doi:10.1136/jitc-2021-003231
Iyer, Kavita A, Julian Ivanov, Rumiana Tenchov, Krittika Ralhan, et al. “Emerging Targets and Therapeutics in Immuno-Oncology: Insights from Landscape Analysis.” J. Med. Chem. 67: 8519−8544 (2024)
Bao R, A Hutson, A Madabhushi, et al. “Ten challenges and opportunities in computational immuno-oncology.” Journal for ImmunoTherapy of Cancer. 12: e009721 (2024).