Gastric cancer remains one of the most prevalent and deadly cancers globally, ranking fifth in incidence and fourth in cancer-related deaths. Particularly burdensome in China, which accounts for nearly half of the global cases, the disease poses immense challenges despite advances in therapeutic modalities. Immune checkpoint inhibitors (ICIs) have emerged as a beacon of hope, offering durable responses in select patient populations. However, the variability in therapeutic outcomes necessitates reliable predictive biomarkers to optimize patient selection and avoid ineffective treatment exposure.

Historically, the expression of programmed death-ligand 1 (PD-L1) has served as a conventional biomarker to guide immunotherapy, yet its clinical utility is hampered by technical complexities and inconsistent interpretative concordance among pathologists. In a novel and comprehensive study leveraging single-cell transcriptome sequencing, the investigative team mapped the intricate tumor microenvironment of 46 LAGC patients undergoing combined neoadjuvant chemotherapy and ICI treatment. The analysis unveiled a distinctive upregulation of tumor-specific Major Histocompatibility Complex class II molecules (tsMHC-II) exclusively in tumors from patients who displayed treatment sensitivity.

This differential tsMHC-II expression underscores a robust mechanistic link between enhanced antigen presentation within tumor cells and augmented immune-mediated tumor eradication. Crucially, patients harboring tsMHC-II-positive tumors demonstrated a remarkable pathological complete response (pCR) rate of 36.84%, significantly surpassing the 11.11% observed in tsMHC-II-negative counterparts. Similarly, major pathological response (MPR) rates were markedly elevated at 63.16% versus 25.93%, further solidifying the biomarker’s predictive power.

To validate these transformative findings, a prospective clinical trial encompassing 30 patients specifically selected for tsMHC-II positivity was conducted. The outcomes were profound: 36.67% achieved pCR while 66.67% attained MPR, rates dramatically higher than historical averages in unselected LAGC populations. These results compellingly advocate for the integration of tsMHC-II assessment into clinical workflows to enhance treatment stratification.

Importantly, the tsMHC-II biomarker is amenable to detection via standard immunohistochemistry (IHC), a technique ubiquitously available in pathology laboratories worldwide. This pragmatic advantage addresses the critical issue of accessibility and reproducibility that plagues existing biomarker assays, particularly PD-L1. The tsMHC-II IHC evaluation provides unequivocal and reproducible results, thus enabling straightforward implementation across diverse clinical settings.

On a molecular level, mechanistic investigations revealed that interferon-gamma (IFN-γ) signaling dynamically upregulates MHC-II expression within tumor cells, thereby enhancing antigen presentation and potentiating immune surveillance. This insight not only elucidates the biomarker’s biological underpinnings but also opens avenues for therapeutic strategies aiming to amplify tsMHC-II expression, potentially converting non-responders into responders.

The clinical implications of this discovery are profound. By reliably identifying patients predisposed to benefit from neoadjuvant immunotherapy, oncologists can tailor treatments with greater precision, minimizing unnecessary exposure to toxic therapies in non-responders and maximizing clinical benefit in responsive populations. This precision medicine approach is poised to significantly improve survival outcomes and quality of life for patients afflicted with LAGC.

Professor Xiangdong Cheng, a corresponding author of the study, emphasized the transformative potential of this biomarker, stating that tsMHC-II evaluation could revolutionize patient selection for immunotherapy. The ability to predict treatment responsiveness with high fidelity stands to refine clinical decision-making and optimize resource utilization in oncology care.

Building upon this foundational work, the researchers are initiating larger multicenter clinical trials to further validate the tsMHC-II biomarker and assess its applicability across other cancer types. Such studies will be instrumental in confirming its broad utility and integrating this biomarker into global oncological practice.

Established in 1963, Zhejiang Cancer Hospital has long been at the forefront of cancer research and care in China, consistently recognized for excellence with the highest national rating in hospital performance assessments. Its collaboration with Peking University, another leading institution in biomedical research, underscores the study’s scientific rigor and potential impact.

This landmark discovery exemplifies the power of cutting-edge single-cell sequencing technologies combined with translational clinical research to unveil actionable biomarkers that will shape the future landscape of cancer immunotherapy. As gastric cancer continues to impose a heavy toll worldwide, innovations such as tsMHC-II-guided therapy offer new hope for precision oncology and improved patient outcomes.

Subject of Research: Identification of tumor-specific MHC-II (tsMHC-II) as a predictive biomarker for neoadjuvant immunotherapy response in locally advanced gastric cancer.

Article Title: Tumor-specific MHC-II Expression Predicts Response to Neoadjuvant Immune Checkpoint Inhibition in Locally Advanced Gastric Cancer

News Publication Date: Not specified

Web References: Not specified

References: DOI 10.1016/j.scib.2026.01.004

Image Credits: ©Science China Press

Keywords: gastric cancer, immunotherapy, immune checkpoint inhibitors, neoadjuvant therapy, biomarker, tumor-specific MHC-II, tsMHC-II, single-cell transcriptome sequencing, pathological complete response, major pathological response, interferon-gamma, precision oncology

Tumor mutation burden quantifies the number of somatic mutations within a tumor genome and has been firmly established as a predictor of response to immune checkpoint inhibitors, which have gained traction in recent years as a frontline therapeutic modality for NSCLC. However, the reliance on WES to evaluate TMB limits its application, particularly in resource-constrained settings. Motivated to bridge this gap, the study involved comprehensive genomic profiling of tumor tissues and matched peripheral blood samples from 72 lung adenocarcinoma patients. The investigation aimed to delineate mutation landscapes across patients with varying TMB levels, while concurrently profiling systemic inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR).

Through meticulous analysis, the researchers confirmed that missense mutations predominate this cancer subtype, with single nucleotide variants (SNVs) constituting the bulk of these alterations. Among the frequently mutated genes, EGFR, TP53, and TTN emerged as the most prominent players, occurring in 35%, 33%, and 24% of cases respectively. Strikingly, patients with high TMB demonstrated a distinct genetic signature characterized by a higher prevalence of C > A transversions and significantly elevated mutation frequencies in TP53 and TTN compared to their low TMB counterparts. These genetic disparities underline the heterogeneity within lung adenocarcinoma and hint at the diverse mutational processes driving tumorigenesis.

Further advancing the understanding of mutational processes, the study identified five de novo mutational signatures, each variably contributing to different TMB strata. This nuance offers vital insight into the etiological factors underpinning genomic instability and mutation accumulation within tumors, which may influence both disease progression and treatment response. By capturing these signatures, researchers can better appreciate the complex interplay between environmental insults, endogenous mechanisms, and immune responses in shaping tumor genomes.

Central to this research was the evaluation of systemic inflammatory markers as surrogate predictors for TMB. Inflammatory mediators circulating in the peripheral blood have garnered attention for their role in cancer biology, particularly due to their interaction with the tumor microenvironment and immune modulation. Employing multivariate generalized linear models, the team uncovered significant associations between elevated NLR and PLR values and high TMB, while lower LMR was also linked to increased mutation burden. These findings suggest that inflammatory status, accessible through routine blood work, might reflect underlying tumor genomic complexity.

The utilization of restricted cubic spline (RCS) plots further illuminated the nature of these relationships, revealing non-linear associations between TMB and the inflammatory indices NLR and PLR. This indicates that the relationship is not simply a direct proportional increase but instead involves more complex dynamics that could reflect threshold effects or nonlinear biological responses. Such insights are critical in refining predictive models and tailoring clinical decision-making strategies.

Recognizing the multifactorial dimensions influencing TMB, the study harnessed the machine learning capabilities of the XGBoost model to evaluate variable importance in TMB prediction. This quantitative assessment underscored the predominant influence of tumor staging (T stage), LMR, and body mass index (BMI) in forecasting mutation burden. Notably, the significant involvement of T stage aligns with the understanding that tumor size and local invasion impact genomic alterations and immune landscape, while systemic factors reflected by BMI and inflammatory profiles play contributory roles.

The integration of systemic inflammatory markers into predictive frameworks for TMB assessment promises tangible benefits in clinical oncology. By circumventing the limitations posed by WES, oncologists may deploy less invasive, cost-effective blood-based biomarkers to identify candidates likely to benefit from immunotherapies, streamlining patient stratification and treatment planning. This approach aligns with the burgeoning paradigm of liquid biopsy, emphasizing minimally invasive diagnostics and real-time monitoring of tumor evolution.

Moreover, the study’s exploration into the distinct mutational features among Chinese lung adenocarcinoma patients broadens the demographic scope of precision oncology research. Genetic and environmental factors influencing mutation spectra and systemic inflammation may vary across populations, necessitating diverse cohort studies to ensure predictive models are universally applicable or properly tailored to genetic ancestries. The comprehensive analysis here thus contributes valuable genomic and clinical data, enriching the global cancer research repository.

Equally important is the potential impact on health economics and clinical workflows. Should systemic inflammation markers validate as robust predictors of TMB, routine pre-treatment blood tests could reduce diagnostic turnaround times and healthcare expenditure related to genomic testing. This would democratize access to immunotherapy indicators, especially in healthcare settings where WES is not readily available, ultimately enhancing equitable cancer care delivery.

However, challenges remain in fully operationalizing inflammation markers as standalone surrogates for TMB. The inflammatory milieu is influenced by myriad factors including infections, comorbidities, and medications, which could confound biomarker specificity. Therefore, ongoing research will be pivotal in refining algorithms, incorporating additional variables, and validating findings across larger, multi-institutional cohorts to bolster reliability and clinical utility.

The pioneering work by Fang, Li, Xu, and colleagues represents a critical step towards integrating systemic inflammatory biomarkers into the diagnostic toolkit for lung adenocarcinoma. By bridging genomic insights with accessible clinical parameters, this research heralds a new era of precision immuno-oncology, where blood-based inflammation indices complement genetic profiling to identify patients most likely to benefit from novel therapies. As immunotherapy continues to reshape lung cancer treatment paradigms, such advancements portend improved survival outcomes and optimized personalized care in one of the world’s deadliest malignancies.

In summary, this landmark study elucidates the intricate relationship between systemic inflammation and tumor genomic characteristics, supporting the feasibility of using easily measurable peripheral blood markers to predict high TMB status in lung adenocarcinoma. It underscores the relevance of inflammation as both a biomarker and a biological modulator in cancer progression, offering a cost-effective, minimally invasive approach to patient stratification. The incorporation of machine learning further enhances predictive accuracy, underscoring the power of integrative analytic methods in modern oncology research. Collectively, these findings pave the way for innovative diagnostic strategies and highlight the immense potential of combining genomic and immunological data to personalize cancer treatment.

Subject of Research: Identification of high tumor mutation burden in lung adenocarcinoma using systemic inflammation biomarkers.

Article Title: Systemic inflammation biomarkers can identify high tumor mutation burden in lung adenocarcinoma.

Article References:
Fang, J., Li, Q., Xu, N. et al. Systemic inflammation biomarkers can identify high tumor mutation burden in lung adenocarcinoma. BMC Cancer 25, 1543 (2025). https://doi.org/10.1186/s12885-025-14894-3

Image Credits: Scienmag.com

DOI: https://doi.org/10.1186/s12885-025-14894-3

The research was conducted retrospectively on a cohort of 171 patients diagnosed with advanced NSCLC who underwent combined immune checkpoint inhibitor (ICI) therapy and chemotherapy. The investigators meticulously gathered clinical data alongside peripheral blood inflammatory markers to construct predictive models that could serve as reliable biomarkers for therapy efficacy and prognosis. Their focus centered on the systemic inflammatory response, particularly examining the NLR, fibrinogen levels, and other hematologic indices as potential indicators of therapeutic success or failure.

Among patients receiving first-line ICI plus chemotherapy, the study identified a critical threshold for pre-treatment NLR: values exceeding 3.3 correlated strongly with diminished progression-free survival (PFS). Elevated fibrinogen levels (greater than 3.196 g/L) similarly signaled poorer treatment outcomes. These findings underscore the interplay between systemic inflammation and cancer progression, highlighting how an imbalanced immune milieu marked by neutrophilia relative to lymphocytes may foster an environment conducive to tumor resistance and progression.

Crucially, the researchers developed a composite prognostic score combining NLR and fibrinogen—termed the NLR-Fib (NF) score—which demonstrated superior predictive accuracy compared to programmed cell death ligand 1 (PD-L1) expression assessed from tumor biopsies. PD-L1 has traditionally been utilized as a biomarker to select candidates for immunotherapy, but its variability and limitations have prompted the search for alternative or complementary measures. The NF score, derived from routine blood tests, offers a noninvasive, cost-effective, and reproducible tool for risk stratification in clinical practice.

The study also delved into a subset of NSCLC patients harboring targetable oncogenic driver mutations and treated with ICI plus chemotherapy beyond the first line. Here, a slightly higher NLR threshold of 3.53 was indicative of worse therapeutic responses and independently predicted both progression-free and overall survival (OS). Interestingly, prior duration of tyrosine kinase inhibitor (TKI) therapy exceeding 12 months emerged as an independent favorable prognostic factor for overall survival. This observation suggests that sustained disease control with targeted agents before immunotherapy may prime tumors for better responsiveness.

Further complexity was added by the identification of other factors influencing outcomes in this patient group. Secondary mutations such as the epidermal growth factor receptor (EGFR) T790M variant were associated with reduced PFS, as were a platelet-to-lymphocyte ratio (PLR) above 196.81 and hypoalbuminemia with albumin levels below 40.25 g/L. These markers collectively reflect the tumor’s evolving biology and systemic host factors that potentially modulate therapeutic efficacy.

Building on these insights, the authors formulated another prognostic metric termed the NLR-TKI-PFS (NTP) score, incorporating NLR levels and prior TKI progression-free survival time. This score stratified patients into three distinct risk categories — favorable, intermediate, and poor — correlating with median OS of 21, 12, and 5.3 months, respectively. Such a tool holds promise for guiding personalized treatment decisions and counseling patients regarding their prognosis in advanced disease stages.

The impact of this study extends beyond its immediate clinical findings. It challenges the current reliance on tissue-based biomarkers like PD-L1, which are often hampered by tumor heterogeneity, sampling bias, and dynamic expression changes. By contrast, systemic inflammation markers measured through blood tests provide a holistic snapshot of the host-tumor interaction and can be serially monitored to adapt treatment strategies.

Moreover, the accessibility and cost-effectiveness of blood-based biomarkers ensure the applicability of these prognostic scores even in resource-limited settings. As immunotherapy revolutionizes oncology care worldwide, such practical tools are imperative to optimize patient outcomes, avoid unnecessary toxicities, and contain healthcare costs.

The biological rationale underpinning the prognostic significance of NLR and fibrinogen is grounded in their roles in cancer pathophysiology. Neutrophils promote tumor progression by secreting pro-angiogenic factors and immunosuppressive cytokines, while lymphocytes, particularly cytotoxic T cells, are critical for anti-tumor immunity. A high NLR thus reflects a state of immune dysregulation favoring tumor escape. Elevated fibrinogen, a key coagulation factor, is implicated in tumor metastasis and inflammatory processes, further aggravating disease progression.

Beyond the statistical associations, this study advocates for integrating inflammatory markers into comprehensive clinical algorithms. Such integration may improve patient selection for immunotherapy and inform the timing of therapeutic interventions, combining or sequencing agents to overcome resistance mechanisms.

Future directions informed by this work include prospective validation trials to confirm the robustness of the NF and NTP scores across diverse populations and treatment regimens. Additionally, research into mechanistic links between inflammation and immunotherapy response could unveil novel therapeutic targets, potentially allowing modulation of the inflammatory milieu to enhance treatment efficacy.

Importantly, this research touches upon the personalized medicine paradigm, where nuanced patient stratification transcends conventional histological and genetic classifications. By incorporating systemic factors reflective of the host-tumor ecosystem, clinicians can better predict clinical trajectories and tailor interventions accordingly.

In summary, the study published in BMC Cancer heralds a promising advance in the prognostication of advanced NSCLC patients receiving ICI plus chemotherapy. Through innovative use of simple hematologic parameters, it provides a window into the complex interplay between cancer, host immunity, and treatment response. These insights bear the potential to refine therapeutic precision, improve survival outcomes, and ultimately transform patient care paradigms in oncology.

Subject of Research: Prognostic biomarkers in advanced non-small cell lung cancer treated with immunotherapy plus chemotherapy.

Article Title: Neutrophil-to-lymphocyte ratio-based prognostic score can predict outcomes in patients with advanced non-small cell lung cancer treated with immunotherapy plus chemotherapy.

Article References:
Liao, S., Sun, H., Lu, H. et al. Neutrophil-to-lymphocyte ratio-based prognostic score can predict outcomes in patients with advanced non-small cell lung cancer treated with immunotherapy plus chemotherapy.
BMC Cancer 25, 697 (2025). https://doi.org/10.1186/s12885-025-13811-y

Image Credits: Scienmag.com

DOI: https://doi.org/10.1186/s12885-025-13811-y