Prognostic Impact of Programmed Death-ligand 1 and Surrounding Immune Status on Stage I Lung Cancer

Nonlinear association between PD-L1 expression levels and the risk of postoperative recurrence in non-small cell lung cancer

Accurate prediction of postoperative recurrence is important for optimizing the treatment strategies for non-small cell lung cancer (NSCLC). Previous studies identified the PD-L1 expression in NSCLC as a risk factor for postoperative recurrence. This study aimed to examine the contribution of PD-L1 expression to predicting postoperative recurrence using machine learning. The clinical data of 647 patients with NSCLC who underwent surgical resection were collected and stratified into training (80%), validation (10%), and testing (10%) datasets. Machine learning models were trained on the training data using clinical parameters including PD-L1 expression. The top-performing model was assessed on the test data using the SHAP analysis and partial dependence plots to quantify the contribution of the PD-L1 expression. Multivariate Cox proportional hazards model was used to validate the association between PD-L1 expression and postoperative recurrence. The random forest model demonstrated the highest predictive performance with the SHAP analysis, highlighting PD-L1 expression as an important feature, and the multivariate Cox analysis indicated a significant increase in the risk of postoperative recurrence with each increment in PD-L1 expression. These findings suggest that variations in PD-L1 expression may provide valuable information for clinical decision-making regarding lung cancer treatment strategies.

The combination of PD-L1 expression and the neutrophil-to-lymphocyte ratio as a prognostic factor of postoperative recurrence in non-small-cell lung cancer: a retrospective cohort study

BACKGROUND

While PD-L1 expression and neutrophil-to-lymphocyte ratio (NLR) are prognostic biomarkers for lung cancer, few studies have considered their interaction. We hypothesized that the product of PD-L1 expression (tumor proportion score) and the NLR (PD-L1 × NLR) might be a postoperative prognostic marker reflecting the immune microenvironment of lung cancer.

METHODS

We analyzed the association between PD-L1 × NLR and postoperative recurrence-free survival in 647 patients with NSCLC using multivariable Cox proportional hazards models.

RESULTS

In the analysis of PD-L1 × NLR as a categorical variable, the group with PD-L1 × NLR ≥ 25.8 had a significantly higher hazard ratio (HR) than the group with < 25.8 (adjusted HR 1.78, 95% confidence interval [CI] 1.23-2.60). The adjusted HR for PD-L1 × NLR, considered a continuous variable, was 1.004 (95% CI, 1.002-1.006). The risk of postoperative recurrence increased by 1.004-fold for each unit increase in PD-L1 × NLR, and a more than 2-fold increase in risk was observed for values ≥ 170.

CONCLUSIONS

PD-L1 × NLR may be used in real-world clinical practice as a novel factor for predicting the risk of postoperative recurrence after lung cancer surgery.

Expression Changes in Programmed Death Ligand 1 from Precancerous Lesions to Invasive Adenocarcinoma in Subcentimeter Pulmonary Nodules: A Large Study of 2022 Cases in China

PURPOSE

This large-scale, multicenter, retrospective observational study aimed to evaluate the clinicopathological and molecular profiles associated with programmed death-ligand 1 (PD-L1) expression in precancerous lesions and invasive adenocarcinoma in subcentimeter pulmonary nodules.

PATIENTS AND METHODS

Patients with histologically confirmed atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) were included. PD-L1 expression was evaluated at each center using a PD-L1 immunohistochemistry 22C3 pharmDx kit (Agilent, Santa Clara, CA, USA). The tumor proportion score (TPS) cutoff values were set at ≥ 1% and ≥ 50%.

RESULTS

A total of 2022 nodules from 1844 patients were analyzed. Of these, 9 (0.45%) nodules had PD-L1 TPS ≥ 50%, 187 (9.25%) had PD-L1 TPS 1-49%, and 1826 (90.30%) had PD-L1 TPS < 1%. A total of 378 (18.69%), 1016 (50.25%), and 628 (31.06%) nodules were diagnosed as AAH/AIS, MIA, and ADC, respectively, by pathology. A total of 1377 (68.10%), 591 (25.67%), and 54 (2.67%) nodules were diagnosed as pure ground-glass opacity (GGO), mixed GGO, and solid nodules, respectively, by computed tomography. There was a significant difference between PD-L1 expression and anaplastic lymphoma kinase (ALK) mutation status (P < 0.001). PD-L1 expression levels were significantly different from those determined using the International Association for the Study of Lung Cancer (IASLC) grading system (P < 0.001).

CONCLUSIONS

PD-L1 expression was significantly associated with radiological and pathological invasiveness and driver mutation status in subcentimeter pulmonary nodules. The significance of PD-L1 expression in the evolution of early-stage lung adenocarcinoma requires further investigation.

A Review of Biomarkers and Their Clinical Impact in Resected Early-Stage Non-Small-Cell Lung Cancer

The postoperative survival of early-stage non-small-cell lung cancer (NSCLC) patients remains unsatisfactory. In this review, we examined the relevant literature to ascertain the prognostic effect of related indicators on early-stage NSCLC. The prognostic effects of the epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), mesenchymal-epithelial transition (MET), C-ros oncogene 1 (ROS1), or tumour protein p53 (TP53) alterations in resected NSCLC remains debatable. Kirsten rat sarcoma viral oncogene homologue (KRAS) alterations indicate unfavourable outcomes in early-stage NSCLC. Meanwhile, adjuvant or neoadjuvant EGFR-targeted agents can substantially improve prognosis in early-stage NSCLC with EGFR alterations. Based on the summary of current studies, resected NSCLC patients with overexpression of programmed death-ligand 1 (PD-L1) had worsening survival. Conversely, PD-L1 or PD-1 inhibitors can substantially improve patient survival. Considering blood biomarkers, perioperative peripheral venous circulating tumour cells (CTCs) and pulmonary venous CTCs predicted unfavourable prognoses and led to distant metastases. Similarly, patients with detectable perioperative circulating tumour DNA (ctDNA) also had reduced survival. Moreover, patients with perioperatively elevated carcinoembryonic antigen (CEA) in the circulation predicted significantly worse survival outcomes. In the future, we will incorporate mutated genes, immune checkpoints, and blood-based biomarkers by applying artificial intelligence (AI) to construct prognostic models that predict patient survival accurately and guide individualised treatment.

Research progress of biomarkers in the prediction of anti-PD-1/PD-L1 immunotherapeutic efficiency in lung cancer

Currently, anti-PD-1/PD-L1 immunotherapy using immune checkpoint inhibitors is widely used in the treatment of multiple cancer types including lung cancer, which is a leading cause of cancer death in the world. However, only a limited proportion of lung cancer patients will benefit from anti-PD-1/PD-L1 therapy. Therefore, it is of importance to predict the response to immunotherapy for the precision treatment of patients. Although the expression of PD-L1 and tumor mutation burden (TMB) are commonly used to predict the clinical response of anti-PD-1/PD-L1 therapy, other factors such as tumor-specific genes, dMMR/MSI, and gut microbiome are also promising predictors for immunotherapy in lung cancer. Furthermore, invasive peripheral blood biomarkers including blood DNA-related biomarkers (e.g., ctDNA and bTMB), blood cell-related biomarkers (e.g., immune cells and TCR), and other blood-related biomarkers (e.g., soluble PD-L1 and cytokines) were utilized to predict the immunotherapeutic response. In this review, the current achievements of anti-PD-1/PD-L1 therapy and the potential biomarkers for the prediction of anti-PD-1/PD-L1 immunotherapy in lung cancer treatment were summarized and discussed.

The role of spatial interplay patterns between PD-L1-positive tumor cell and T cell in recurrence of locally advanced non-small cell lung cancer

PURPOSE

To explore the relationship between the spatial interaction of programmed death-ligand 1(PD-L1)-positive tumor cell and T cell with specific functions and the recurrence of non-small cell lung cancer (NSCLC) and optimize prognostic stratification.

MATERIALS AND METHODS

This study retrospectively included 104 patients with locally advanced NSCLC who underwent radical surgery. Tissue microarrays were constructed including tumor center (TC) and invasion margin (IM), and CK/CD4/CD8/PD-L1/programmed death-1 (PD-1) was labeled using multiplex immunofluorescence to decipher the counts and spatial distribution of tumor cells and T cells. The immune microenvironment and recurrence stratification were characterized using the Mann-Whitney U test and Cox proportional hazards model.

RESULT

Compared with the IM, the proportion of tumor cells (especially PD-L1⁺) was increased in the TC, while T cells (especially PD-1⁺) were decreased. An increase in TC PD-1⁺ CD8 T cells promoted relapse (HR = 2.183), while PD-L1⁺ tumor cells alone or in combination with T cells had no predictive value for relapse. In addition, in both TC and IM, CD8 were on average closer to PD-L1⁺ tumor cells than CD4, especially exhausted CD8. The effective density and percentage of PD-1⁺ CD4 T cells interacting with PD-L1⁺ tumor cells in the IM were both associated with recurrence, and the HRs increased sequentially (HRs were 2.809 and 4.063, respectively). Patients with low PD-1⁺CD4 count combined high PD-1⁺CD4 effective density showed significantly poorer RFS compared to those with high PD-1⁺CD4 count combined low PD-1⁺CD4 effective density, in both the TC and IM regions (HRs were 5.810 and 8.709, respectively).

CONCLUSION

Assessing the relative spatial proximity of PD-1/PD-L1 contributes to a deeper understanding of tumor immune escape and generates prognostic information in locally advanced NSCLC patients.

Inhibition of GFAT1 in lung cancer cells destabilizes PD-L1 protein

Immunotherapy using checkpoint blockers (antibodies) has been a major advance in recent years in the management of various types of solid cancers including lung cancer. One target of checkpoint blockers is programmed death ligand 1 (PD-L1) expressed by cancer cells, which engages programmed death 1 (PD-1) on T cells and Natural Killer (NK) cells resulting in suppression of their activation and cancer-killing function, respectively. Apart from antibodies, other clinically relevant agents that can inhibit PD-L1 are limited. PD-L1 protein stability depends on its glycosylation. Here we show that L-glutamine:D-fructose amidotransferase 1 (GFAT1) a rate-limiting enzyme of the hexosamine biosynthesis pathway (HBP) which produces uridine diphosphate-N-acetyl-β-glucosamine (UDP-GlcNAc), a precursor for glycosylation, is required for the stability of PD-L1 protein. Inhibition of GFAT1 activity markedly reduced interferon γ (IFNγ)-induced PD-L1 levels in various lung cancer cell lines. GFAT1 inhibition suppressed glycosylation of PD-L1 and accelerated its proteasomal degradation. Importantly, inhibition of GFAT1 in IFNγ-treated cancer cells enhanced the activation of T cells and the cancer-killing activity of NK cells. These findings support using GFAT1 inhibitors to manipulate PD-L1 protein level that could augment the efficacy of immunotherapy for lung cancer.

Immune Profiling Reveals Molecular Classification and Characteristic in Urothelial Bladder Cancer

Urothelial bladder cancer (UBC) is the most common malignant tumor of the urinary system. Most patients do not benefit from treatment with immune checkpoint inhibitors, which are closely associated with immune profiling in the context of UBC. Therefore, we aimed to characterize the immune profile of UBC to identify different immune subtypes that may influence therapy choice. We identified four subtypes of UBC based on immune profiling including immune ignorant, cold tumor, immune inactive, and hot tumor. After excluding the cold tumor subtype because of its unique pathology distinct from the other types, a high correlation between patient survival and immune characteristics was observed. Most immune cell types had highly infiltrated the hot tumor subtype compared to other subtypes. Interestingly, although immune cells infiltrated the tumor microenvironment, they exhibited an exhaustion phenotype. CCL4 may be the key molecule functioning in immune cell infiltration in the hot tumor subtype. Moreover, neutrophils may function as an important suppressor in the tumor microenvironment of the immune ignorant and immune inactive subtypes. Furthermore, different tumor-intrinsic signaling pathways were involved in immune cell infiltration and exclusion in these four different subtypes. Immune profiling could serve as a prognostic biomarker for UBC, and has potential to guide treatment decisions in UBC. Targeting tumor-intrinsic signaling pathways may be a promising strategy to treat UBC.

Prognostic value of the common tumour-infiltrating lymphocyte subtypes for patients with non-small cell lung cancer: A meta-analysis

Background

Many previous studies have revealed that tumour-infiltrating lymphocytes (TILs) are significantly associated with prognosis in various tumours. However, this finding remains controversial in non-small cell lung cancer (NSCLC). We performed this meta-analysis systematically to evaluate the prognostic value of TILs in NSCLC.

Methods

The references were collected by searching the PubMed, EMBASE and Web of Science databases. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were summarized using random or fixed effects models to evaluate the association between TILs and NSCLC survival outcomes.

Results

A total of 45 interrelated studies were eligible that included 11,448 patients. Pooled analysis showed that a high density of TILs indicated a better overall survival (HR = 0.80, 0.70–0.89) and progression-free survival (HR = 0.73, 0.61–0.85) for patients with NSCLC; a high density of CD3+ TILs in the tumour nest indicated a better overall survival (HR = 0.84, 0.69–0.99) and disease-specific survival (HR = 0.57, 0.34–0.80); a high density of CD4+ TILs in the tumor nest indicated a favourable overall survival (HR = 0.86, 0.76–0.96); a high density of CD8+ TILs indicated a favourable overall survival (HR = 0.995, 0.99–1.0), progression-free survival (HR = 0.52, 0.34–0.71), disease-free survival (HR = 0.64, 0.43–0.85), relapse/recurrence-free survival (HR = 0.42, 0.18–0.67) and disease-specific survival (HR = 0.56, 0.35–0.78); and a high density of CD20+ TILs in the tumour nest indicated a favourable overall survival (HR = 0.65, 0.36–0.94). However, a high density of Foxp3+ TILs in the tumour stroma indicated a worse relapse/recurrence-free survival (HR = 1.90, 1.05–2.76) in NSCLC.

Conclusions

Our meta-analysis confirmed that high densities of TILs, CD3+TILs, CD4+TILs, CD8+TILs and CD20+TILs in the tumour nest are favourable prognostic biomarkers for patients with NSCLC, and Foxp3+TILs in the tumour stroma are a poor prognostic biomarker.