Biomarkers and T Cell Traits Emerge as Key Predictors of Cancer Immunotherapy Response

Researchers have uncovered compelling biomarkers that could predict patient responsiveness to immune checkpoint inhibitors (ICIs) with unprecedented accuracy, potentially reshaping the landscape of immunotherapy for lung cancer and other malignancies. The inquiry, led by Ito, Iida, Hirano, and colleagues, delves deep into the phenotypic characteristics of circulating tumor-reactive T cells (CTRTs) in patients afflicted with non-small cell lung cancer (NSCLC), unraveling key immunological insights that may ultimately tailor and optimize treatment regimens.

The team's meticulous investigation harnessed advanced flow cytometry and single-cell RNA sequencing to interrogate the functional and phenotypic landscape of T cells circulating in the peripheral blood of NSCLC patients prior to and during ICI treatment. Their analyses revealed that the abundance and activation states of a specific subset of tumor-reactive T cells correlate strongly with therapeutic outcomes. These CTRTs exhibited distinct surface marker signatures indicating an effector memory phenotype coupled with high expression of exhaustion markers, suggesting a poised but dysfunctional state that ICIs can robustly reinvigorate.

Further molecular dissection highlighted key transcriptional programs governing CTRT activation and exhaustion, driven by complex interplay between chronic antigen stimulation and immunosuppressive tumor microenvironmental signals. Notably, enriched expression of genes such as TOX, NR4A, and PDCD1 delineated CTRTs from other T cell populations, underscoring the nuanced balance between immune exhaustion and reinvigoration potential.

Longitudinal monitoring revealed that patients with a higher baseline proportion of these tumor-reactive, yet partially exhausted T cells were far more likely to experience durable clinical benefit from ICIs. Conversely, patients with low CTRT levels or skewed toward terminally differentiated, non-responsive T cells exhibited poorer outcomes, elucidating a critical mechanistic underpinning for therapeutic resistance. This suggests that the mere presence of T cell infiltration within the tumor is insufficient; rather, precise functional states govern anti-tumor efficacy.

The study highlights the practicality of liquid biopsy approaches leveraging peripheral blood samples to monitor tumor-specific immune activity without invasive tissue biopsies. This noninvasive snapshot of systemic antitumor immunity may enable real-time treatment monitoring and early intervention strategies to enhance patient survival.

The global PD-L1 biomarker testing market was valued at US$ 3.79 billion in 2025 and is anticipated to reach US$ 36.44 billion by 2032, witnessing a CAGR of 38.7% during the forecast period 2026-2032. PD-L1 biomarker testing measures the amount of PDL1 on cancer cells. PDL1 is a protein that helps keep immune cells from attacking nonharmful cells in the body. Some cancer cells have high amounts of PDL1, which allows the cancer cells to "trick" the immune system and avoid being attacked as foreign, harmful substances. Current PD-L1 testing is based on immunohistochemistry (IHC) methods.

PD-L1 is a ligand that binds to PD-1 (programmed cell death-1), expressed on activated T cells, to evade anti-tumor responses. PD-L1 plays a role in inhibiting T cell activation and proliferation and has emerged as an important target in cancer treatment. PD-L1 protein detection by immunohistochemistry (IHC) testing is widely used as a predictive biomarker assay for anti-PD-1/PD-L1 therapies. PDL1 testing is used to find out if you have a cancer that may benefit from immunotherapy.

The PD‐L1 biomarker testing market is being propelled by the rapid expansion of immune checkpoint inhibitor therapies, particularly those targeting the PD‐1/PD‐L1 axis, which have shown remarkable clinical success in treating various advanced cancers-spurring widespread demand for stratifying patients based on PD‐L1 expression to optimize treatment outcomes. Additionally, the shift toward precision medicine has heightened the importance of molecular diagnostics. Clinicians and pharmaceutical developers are increasingly emphasizing personalized approaches, using PD‐L1 testing to guide therapeutic decisions and enable companion diagnostics-especially as diagnostic technologies advance to include automated IHC systems, NGS platforms, and AI-enhanced analysis.

Despite these positive trends, the PD‐L1 testing landscape faces significant obstacles due to a lack of standardization across protocols, assay clones, scoring systems, and cut-off thresholds. This inconsistency manifests in discordant results (with variability rates reported between 19-32% across different assays), undermining diagnostic reliability and complicating clinical decision-making. Moreover, high costs associated with advanced testing techniques (IHC, NGS) and uneven reimbursement frameworks create economic barriers, particularly in developing regions, impeding broad accessibility and exacerbating healthcare disparities.

Chronic inflammation is both a driver and suppressor of cancer depending on context. Key players—NF-κB, IL-6, STAT3, TAMs, MDSCs, and Tregs—orchestrate a tumor-permissive microenvironment. Immunotherapy, particularly immune checkpoint inhibitors, has revolutionized treatment, but responses remain heterogeneous. Up to 20% of cancers are linked to chronic infections, autoimmunity, or environmental exposures. Inflammation drives all stages of tumorigenesis and modulates therapeutic response.

Inflammatory biomarkers including CRP, IL-6, NLR, and PIV (pan-immune-inflammation value) predict prognosis and ICI response. Predictive biomarkers include PD-L1 IHC, TMB, MSI, and emerging ctDNA and microbiome signatures. Anti-PD-1/PD-L1/CTLA-4 checkpoint inhibitors yield 20–40% response rates; elevated IL-6 predicts resistance. LAG-3 blockade (relatlimab) was approved in 2024.

Translational advances include drug repurposing, with aspirin reducing CRC/metastasis risk and COX-2 inhibitors in FAP. Cytokine targeting approaches include tocilizumab (anti-IL-6R), siltuximab (anti-IL-6), and infliximab (anti-TNF) in trials; 2025 studies combine IL-6 blockade with ICIs in pancreatic cancer. Bortezomib (proteasome inhibitor) suppresses NF-κB, while novel STAT3 inhibitors reduce MDSCs preclinically.

Combination approaches include ICIs with aspirin, VEGF inhibitors, chemotherapy, or radiation; 2024 CRC trials combine ICIs with microbiome modulators. AI-driven multi-omic models enable patient stratification and real-time treatment adjustment. Emerging technologies including microbiome modulation, AI, gene editing, and single-cell technologies position the field for transformative progress. CRISPR-edited CAR-T cells show improved persistence in inflammatory tumor microenvironments, while lipid nanoparticles reprogramming TAMs to M1 phenotype show promise in breast cancer models.