A Brand New Era of Cancer Immunotherapy: Breakthroughs and Challenges

Cancer immunotherapy has ushered in a transformative era in oncology, marked by unprecedented breakthroughs and persistent challenges. Immune checkpoint inhibitors (ICIs), particularly those targeting the programmed cell death 1 (PD-1)/PD ligand 1 (PD-L1) axis, have revolutionized the treatment landscape for various solid tumors, significantly improving survival rates. Despite these advances, the efficacy of immunotherapy remains variable, with only a minority of patients achieving durable responses. This variability underscores the complexity of the tumor immune microenvironment (TIME) and the multifaceted mechanisms underlying resistance to therapy.

The Complexity of Tumor Immunity and Resistance Mechanisms

The success of immunotherapy hinges on the dynamic interplay between tumor cells and the immune system. However, tumors exhibit intrinsic adaptability and heterogeneity, enabling them to evade immune surveillance. The TIME, a complex ecosystem comprising fibroblasts, macrophages, lymphocytes, and antigen-presenting cells (APCs), plays a pivotal role in shaping therapeutic outcomes. Three distinct immunophenotypes have been identified: immune-inflamed, immune-excluded, and immune-desert. These subtypes reflect varying degrees of immune infiltration and responsiveness to therapy. For instance, immune-desert tumors, characterized by sparse immune cell presence, are typically resistant to ICIs, whereas immune-inflamed tumors often respond better due to pre-existing T-cell infiltration.

Resistance to immunotherapy manifests as primary resistance (no initial response), acquired resistance (relapse after initial response), or adaptive resistance (tumor evasion through microenvironmental adaptation). Key mechanisms include:

1. Tumor-intrinsic factors: Loss of antigen presentation (e.g., MHC-I downregulation), aberrant tumor antigen expression, and activation of immunosuppressive pathways (e.g., Wnt/β-catenin signaling).
2. TIME-mediated suppression: Recruitment of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs); secretion of inhibitory cytokines (e.g., TGF-β, IL-10); and metabolic dysregulation (e.g., indoleamine 2,3-dioxygenase [IDO] activity).
3. Host-related factors: Age, gut microbiota composition, and systemic inflammation.

Strategies to Overcome Resistance and Enhance Efficacy

1. Combination Therapies

Combining ICIs with conventional therapies or novel agents aims to synergize mechanisms of action, overcome resistance, and broaden clinical benefits.

ICIs with Chemotherapy or Radiotherapy

Chemotherapy and radiotherapy can modulate the TIME by inducing immunogenic cell death, releasing tumor antigens, and reducing immunosuppressive cells. For example:

• Pembrolizumab + chemotherapy: In the KEYNOTE-021, KEYNOTE-189, and KEYNOTE-407 trials, this combination improved overall survival (OS) and progression-free survival (PFS) in advanced non-small cell lung cancer (NSCLC), regardless of PD-L1 expression.
• Radiotherapy + ICIs: Localized radiation enhances antigen presentation and promotes T-cell infiltration. The PEMBRO-RT trial demonstrated improved response rates in metastatic NSCLC patients receiving pembrolizumab with radiotherapy.

Next-Generation Immune Checkpoint Targets

Emerging inhibitory receptors (IRs) such as LAG-3, TIM-3, and TIGIT are being explored to address resistance to PD-1/PD-L1 blockade. For instance:

• LAG-3 inhibitors: Relatlimab (BMS-986916) combined with nivolumab showed enhanced T-cell activation in melanoma models.
• TIM-3 blockade: Preclinical studies indicate that TIM-3 upregulation correlates with PD-1 resistance, and dual inhibition restores T-cell function.

Bispecific Antibodies and Dual-Target Agents

Bispecific antibodies (bsAbs) simultaneously target multiple pathways. Bintrafusp alfa (M7824), a PD-L1/TGF-β trap, demonstrated promising activity in phase I trials for NSCLC and biliary tract cancers by neutralizing TGF-β-mediated immunosuppression while blocking PD-L1.

Angiogenesis Inhibitors

Anti-angiogenic agents normalize tumor vasculature, improving immune cell infiltration. The JVDF trial reported that ramucirumab (VEGFR-2 inhibitor) combined with pembrolizumab enhanced antitumor immunity in NSCLC and gastric cancer.

Immunomodulatory Agents

Drugs targeting metabolic or cytokine pathways in the TIME include:

• Adenosine pathway inhibitors: CPI-444 (anti-ADORA2A) and oleclumab (anti-CD73) reverse adenosine-mediated immunosuppression.
• IDO inhibitors: Despite the failure of the ECHO-301 trial, IDO remains a target for combination strategies.

2. Personalized Neoantigen Vaccines

Neoantigen-based vaccines exploit tumor-specific mutations to elicit T-cell responses. In the NEO-PV-01 trial, personalized vaccines combined with nivolumab induced robust immune activation in NSCLC patients. mRNA-based vaccines like RO7198457 have shown early promise in phase Ib trials, with clinical benefits observed across multiple tumor types.

3. Cellular Immunotherapy Integration

Adoptive cell therapies, such as chimeric antigen receptor (CAR) T cells, are being combined with ICIs to enhance persistence and efficacy. For example:

• CAR-T cells with PD-1 dominant negative receptors: These engineered cells resist PD-L1-mediated inhibition, showing durable responses in preclinical models.
• NK cell therapies: Allogeneic NK cells combined with pembrolizumab improved survival in NSCLC patients, highlighting the potential of innate immunity in checkpoint blockade.

Precision Immunotherapy: Biomarkers and Patient Stratification

Accurate biomarkers are critical for identifying patients likely to benefit from immunotherapy. Current biomarkers include:

• PD-L1 expression: High PD-L1 (≥50%) correlates with pembrolizumab efficacy in NSCLC (KEYNOTE-024).
• Tumor mutational burden (TMB): TMB ≥10 mutations/Mb predicts response to pembrolizumab in solid tumors (KEYNOTE-158).
• Tumor-infiltrating lymphocytes (TILs): High CD8+ T-cell density associates with improved outcomes.

However, no single biomarker is universally predictive. Integrating multi-omics data (genomic, transcriptomic, proteomic) and leveraging artificial intelligence (AI) for biomarker discovery are emerging trends. For instance, machine learning models analyzing T-cell receptor clonality and cytokine profiles may refine patient selection.

Challenges and Future Directions

1. Clinical Trial Design

Traditional trial designs are inadequate for evaluating combination therapies. Innovative platforms like umbrella trials (histology-specific) and basket trials (biomarker-driven) enable rapid assessment of multiple agents. The CANOPY trials (NCT03631199, NCT03447769) exemplify this approach, testing pembrolizumab with chemotherapy and canakinumab (IL-1β inhibitor) in NSCLC.

2. Drug Delivery and Nanotechnology

Nanoparticle-based systems enhance immunotherapy by targeting specific immune cells or tumor sites. Examples include:

• Exosome-mimetic nanovesicles (M1NVs): Derived from M1 macrophages, these repolarize TAMs to pro-inflammatory phenotypes.
• Membrane-coated nanoparticles: PD-L1-expressing vesicles deliver immune agonists (e.g., 1-MT) to disrupt IDO activity.

3. Overcoming Adaptive Resistance

Understanding temporal changes in the TIME during therapy is crucial. Sequential targeting of pathways (e.g., OX40 agonist followed by PD-1 inhibitor) may optimize efficacy. The phase III trial of sitravatinib (TAM kinase inhibitor) plus nivolumab in NSCLC (NCT03906071) aims to reverse myeloid-mediated resistance.

4. Global Collaboration and Data Sharing

Large-scale initiatives like The Cancer Genome Atlas (TCGA) and International Cancer Immunotherapy Consortium (ICIC) are essential for deciphering resistance mechanisms and identifying novel targets.

Conclusion

The evolution of cancer immunotherapy has transformed oncology, yet significant challenges persist. The interplay between tumor heterogeneity, TIME dynamics, and host factors necessitates innovative strategies to overcome resistance. Combination therapies, personalized vaccines, and advanced biomarker-driven approaches hold immense potential. Future success will depend on collaborative research, adaptive trial designs, and the integration of cutting-edge technologies like nanotechnology and AI. As the field advances, the ultimate goal of achieving durable remissions and curing cancer becomes increasingly attainable.

doi.org/10.1097/CM9.0000000000001490

Was this helpful?

YesNo

0 / 0