Clinical markers predict the efficacy of several immune checkpoint inhibitors in patients with non-small cell lung cancer in China

The Predictive Value of Monocarboxylate Transporter 4 (MCT4) on Lung Adenocarcinoma Patients Treated with PD-1 Inhibitors

Purpose

Monocarboxylate transporter 4 (MCT4) can influence the amount of lactate in the tumor microenvironment and further control cancer cell proliferation, migration, and angiogenesis. This study aimed to evaluate the predictive value of MCT4 for prognosis and immunotherapy efficacy in advanced lung adenocarcinoma (LUAD).

Patients and methods

First, bioinformatics analysis was used to assess the relevance of MCT4 for survival and immunotherapy outcomes in LUAD. Subsequently, we performed a retrospective study involving 126 patients with stage IIIb to IV LUAD treated with programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors. MCT4 expression in LUAD tissues was detected by immunohistochemistry (IHC), then the patients were divided into high and low expression groups. The differences in the medical records of the two groups were compared using the X2 test. Kaplan-Meier (K-M) method was used for survival analysis. Univariate and multivariate analysis were used to pinpoint independent predictors, and a nomogram was developed based on the significant factors for overall survival (OS) in the multivariate analysis. The predictive ability of the nomogram was evaluated through C-index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

Both bioinformatics analysis and clinical study revealed that low MCT4 expression was associated with better prognosis and immunotherapy efficacy. Multivariate analysis of clinical characteristics showed that age >65 years, stage IV, high MCT4 expression, neutrophil-to-lymphocyte ratio (NLR)>3, lactate dehydrogenase (LDH)>250 (U/L) and carcinoembryonic antigen (CEA)>5 (ng/mL) were significantly associated with poor prognosis on immunotherapy. These factors were subsequently incorporated into the nomogram model. The C-index value of the model stood at 0.735 (95% CI= 0.662 ~ 0.807), indicating robust predictive performance of the model. The DCA curve showed that the model had a notable clinical application value.

Conclusion

High expression of MCT4 is associated with poor prognosis and reduced efficacy of immunotherapy in patients with advanced LUAD.

Systemic and local immunosuppression in glioblastoma and its prognostic significance

The effectiveness of tumor therapy, especially immunotherapy and oncolytic virotherapy, critically depends on the activity of the host immune cells. However, various local and systemic mechanisms of immunosuppression operate in cancer patients. Tumor-associated immunosuppression involves deregulation of many components of immunity, including a decrease in the number of T lymphocytes (lymphopenia), an increase in the levels or ratios of circulating and tumor-infiltrating immunosuppressive subsets [e.g., macrophages, microglia, myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs)], as well as defective functions of subsets of antigen-presenting, helper and effector immune cell due to altered expression of various soluble and membrane proteins (receptors, costimulatory molecules, and cytokines). In this review, we specifically focus on data from patients with glioblastoma/glioma before standard chemoradiotherapy. We discuss glioblastoma-related immunosuppression at baseline and the prognostic significance of different subsets of circulating and tumor-infiltrating immune cells (lymphocytes, CD4+ and CD8+ T cells, Tregs, natural killer (NK) cells, neutrophils, macrophages, MDSCs, and dendritic cells), including neutrophil-to-lymphocyte ratio (NLR), focus on the immune landscape and prognostic significance of isocitrate dehydrogenase (IDH)-mutant gliomas, proneural, classical and mesenchymal molecular subtypes, and highlight the features of immune surveillance in the brain. All attempts to identify a reliable prognostic immune marker in glioblastoma tissue have led to contradictory results, which can be explained, among other things, by the unprecedented level of spatial heterogeneity of the immune infiltrate and the significant phenotypic diversity and (dys)functional states of immune subpopulations. High NLR is one of the most repeatedly confirmed independent prognostic factors for shorter overall survival in patients with glioblastoma and carcinoma, and its combination with other markers of the immune response or systemic inflammation significantly improves the accuracy of prediction; however, more prospective studies are needed to confirm the prognostic/predictive power of NLR. We call for the inclusion of dynamic assessment of NLR and other blood inflammatory markers (e.g., absolute/total lymphocyte count, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, and systemic immune response index) in all neuro-oncology studies for rigorous evaluation and comparison of their individual and combinatorial prognostic/predictive significance and relative superiority.