Differential prognostic effect of systemic inflammation in patients with non-small cell lung cancer treated with immunotherapy or chemotherapy: A post hoc analysis of the phase 3 OAK trial

Novel prediction model combining PET/CT metabolic parameters, inflammation markers, and TNM stage: prospects for personalizing prognosis in nasopharyngeal carcinoma

PURPOSE

This study aims to develop a novel prediction model and risk stratification system that could accurately predict progression-free survival (PFS) in patients with nasopharyngeal carcinoma (NPC).

METHODS

Herein, we included 106 individuals diagnosed with NPC, who underwent 18F-FDG PET/CT scanning before treatment. They were divided into training (n = 76) and validation (n = 30) sets. The prediction model was constructed based on multivariate Cox regression analysis results and its predictive performance was evaluated. Risk factor stratification was performed based on the nomogram scores of each case, and Kaplan-Meier curves were used to evaluate the model's discriminative ability for high- and low-risk groups.

RESULTS

Multivariate Cox regression analysis showed that N stage, M stage, SUVmax, MTV, HI, and SIRI were independent factors affecting the prognosis of patients with NPC. In the training set, the model considerably outperformed the TNM stage in predicting PFS (AUCs of 0.931 vs. 0.841, 0.892 vs. 0.785, and 0.892 vs. 0.804 at 1-3 years, respectively). The calibration plots showed good agreement between actual observations and model predictions. The DCA curves further justified the effectiveness of the model in clinical practice. Between high- and low-risk group, 3-year PFS rates were significantly different (high- vs. low-risk group: 62.8% vs. 9.8%, p < 0.001). Adjuvant chemotherapy was also effective for prolonging survival in high-risk patients (p = 0.009).

CONCLUSION

Herein, a novel prediction model was successfully developed and validated to improve the accuracy of prognostic prediction for patients with NPC, with the aim of facilitating personalized treatment.

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.

Association between platelet‑to‑lymphocyte ratio and serum prostate specific antigen

There is evidence that the systemic inflammatory response may have an impact on prostate-specific antigen (PSA) levels. However, the relationship between the platelet-to-lymphocyte ratio (PLR) and PSA remains unclear. As a result, the relationship between PLR and PSA using the National Health and Nutrition Examination Survey (NHANES) database was examined. After the screening, 6,638 participants out of 52,186 in the NHANES survey conducted between 2001 to 2010 were suitable for the present study. The PLR was the independent variable in the present study, and PSA was the dependent variable. The selected subjects in the present study had an average age of 58.563±11.848 years. After controlling for covariates, the results showed that with every increase in PLR, the PSA concentration increased by 0.004 ng/ml (0.001, 0.007). This difference was statistically significant. Furthermore, a smoothing curve based on a fully adjusted model was created to investigate the possibility of a linear relationship between PLR and PSA concentration in men from USA. In men from USA, an independent and positive correlation between PLR and PSA was identified, which could potentially result in overdiagnosis of asymptomatic prostate cancer in populations with higher PLR levels.

Neutrophil-to-Lymphocyte Ratio (NLR) in NSCLC, Gastrointestinal, and Other Solid Tumors: Immunotherapy and Beyond

In the era of immunotherapy, identifying biomarkers of immune system activation has become a high-priority challenge. The blood neutrophil-to-lymphocyte ratio (NLR) has been largely investigated as a biomarker in several cancer types. NLR values have been shown to mirror the tumor-induced inflammatory status and have been demonstrated to be a reliable prognostic tool across stages of disease and therapeutic approaches. When integrated with other biomarkers of response to immunotherapy, such as PD-L1, tumor mutational burden, and tumor-associated immune cells, the NLR may allow to further stratify patients with different likelihoods of deriving a significant clinical benefit. However, despite its accessibility, low cost, and easy interpretation, the NLR is still poorly used as a prognostic tool in daily clinical practice. In this review, we analyze the role of the NLR in defining the relationship between cancer and the immune system, its usefulness in daily clinical practice, and its relationship with other established or emerging biomarkers of immunotherapy outcomes.

First-line immunotherapy in non-small cell lung cancer: how to select and where to go

INTRODUCTION

Immunotherapy (IO) has established a new milestone in lung cancer treatment. Several registrational studies have approved immune checkpoint inhibitors (ICIs) in different settings, including the metastatic nonsmall cell lung cancer (NSCLC). As well known, responders are just a certain proportion of patients; therefore, their selection by using predictive factors has stood out as a crucial issue to address in tailoring a patient-centered care.

AREAS COVERED

In our review we propose a detailed yet handy cross section on ICIs as first-line treatment in metastatic NSCLC, regarding indications, histological, clinical, and blood-based biomarkers, other than their mechanisms of resistance and new immunological actionable targets. We performed a literature search through PubMed entering keywords complying with crucial features of immunotherapy.

EXPERT OPINION

IO represents the backbone of lung cancer treatment. Trials are currently testing novel immune blockade agents assessing combinatorial approaches with standard ICIs, or antibody drug conjugates (ADC), harboring immunological targets. Perfecting patients' selection is an ongoing challenge and a more and more urgent need in order to best predict responders who will consistently benefit from it.

Characterization of Age-Associated, Neutrophil-to-Lymphocyte Ratio (NLR) and Systemic Immune-Inflammatory Index (SII) as Biomarkers of Inflammation in Geriatric Patients with Cancer Treated with Immune Checkpoint Inhibitors: Impact on Efficacy and Survival

BACKGROUND

Geriatric patients (≥80 years) are underrepresented in immune checkpoint inhibitor (ICIs) clinical trials. However, their unique biology may affect their response to ICIs. There are currently no established biomarkers of the response to ICIs in adult patients with cancer that can help with patient selection.

METHODS

We built a multicenter, international retrospective study of 885 patients (<80 years: n = 417, 47.12%; ≥80 years: n = 468, 52.88%) with different tumor types treated with ICIs between 2011 and 2021 from 11 academic centers in the U.S. and Europe. The main outcome measures were objective response rates (ORR), progression-free survival (PFS) and overall survival (OS) stratified by age and circulating inflammatory levels (neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammatory index (SII)).

RESULTS

Patients ≥80 years with low NLR (NLR-L) and SII (SII-L) had significantly higher ORR (vs. high NLR [NLR-H], p < 0.01 and SII-H, p < 0.05, respectively). At median follow-ups (13.03 months), and compared to SII-H, patients with SII-L had significantly longer median PFS and OS in patients <80 (p < 0.001), and ≥80 years (p < 0.001). SII-L was independently associated with longer PFS and OS (HR: 0.61 and 0.62, respectively, p < 0.01).

CONCLUSION

Lower inflammation pre-ICI initiation may predict an improved response and survival in geriatric patients with cancer.

Increased interleukin-6/C-reactive protein levels are associated with the upregulation of the adenosine pathway and serve as potential markers of therapeutic resistance to immune checkpoint inhibitor-based therapies in non-small cell lung cancer

BACKGROUND

Systemic immune activation, hallmarked by C-reactive protein (CRP) and interleukin-6 (IL-6), can modulate antitumor immune responses. In this study, we evaluated the role of IL-6 and CRP in the stratification of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs). We also interrogated the underlying immunosuppressive mechanisms driven by the IL-6/CRP axis.

METHODS

In cohort A (n=308), we estimated the association of baseline CRP with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) in patients with NSCLC treated with ICIs alone or with chemo-immunotherapy (Chemo-ICI). Baseline tumor bulk RNA sequencing (RNA-seq) of lung adenocarcinomas (LUADs) treated with pembrolizumab (cohort B, n=59) was used to evaluate differential expression of purine metabolism, as well as correlate IL-6 expression with PFS. CODEFACS approach was applied to deconvolve cohort B to characterize the tumor microenvironment by reconstructing the cell-type-specific transcriptome from bulk expression. Using the LUAD cohort from The Cancer Genome Atlas (TCGA) we explored the correlation between IL-6 expression and adenosine gene signatures. In a third cohort (cohort C, n=18), plasma concentrations of CRP, adenosine 2a receptor (A2aR), and IL-6 were measured using ELISA.

RESULTS

In cohort A, 67.2% of patients had a baseline CRP≥10 mg/L (CRP-H). Patients with CRP-H achieved shorter OS (8.6 vs 14.8 months; p=0.006), shorter PFS (3.3 vs 6.6 months; p=0.013), and lower ORR (24.7% vs 46.3%; p=0.015). After adjusting for relevant clinical variables, CRP-H was confirmed as an independent predictor of increased risk of death (HR 1.51, 95% CI: 1.09 to 2.11) and lower probability of achieving disease response (OR 0.34, 95% CI: 0.13 to 0.89). In cohort B, RNA-seq analysis demonstrated higher IL-6 expression on tumor cells of non-responders, along with a shorter PFS (p<0.05) and enrichment of the purinergic pathway. Within the TCGA LUAD cohort, tumor IL-6 expression strongly correlated with the adenosine signature (R=0.65; p<2.2e-16). Plasma analysis in cohort C demonstrated that CRP-H patients had a greater median baseline level of A2aR (6.0 ng/mL vs 1.3 ng/mL; p=0.01).

CONCLUSIONS

This study demonstrates CRP as a readily available blood-based prognostic biomarker in ICI-treated NSCLC. Additionally, we elucidate a potential link of the CRP/IL-6 axis with the immunosuppressive adenosine signature pathway that could drive inferior outcomes to ICIs in NSCLC and also offer novel therapeutic avenues.

Gene Expressions and High Lymphocyte Count May Predict Durable Clinical Benefits in Patients with Advanced Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors

BACKGROUND

Not all patients with advanced non-small cell lung cancer (NSCLC) benefit from immune checkpoint inhibitors (ICIs). Therefore, we aimed to assess the predictive potential of gene expression profiling (GEP), peripheral immune cell counts, and clinical characteristics.

METHODS

The primary endpoint of this prospective, observational study was a durable clinical benefit (DCB) defined as progression-free survival >6 months. In a subgroup with histological biopsies of sufficient quality (n = 25), GEP was performed using the nCounter® PanCancer IO 360 panel.

RESULTS

DCB was observed in 49% of 123 included patients. High absolute lymphocyte count (ALC) and absence of liver metastases were associated with DCB (OR = 1.95, p = 0.038 and OR = 0.36, p = 0.046, respectively). GEP showed clustering of differentially expressed genes according to DCB, and a strong association between PD-L1 assessed by GEP (CD274) and immunohistochemistry (IHC) was observed (p = 0.00013). The TGF-β, dendritic cell, and myeloid signature scores were higher for patients without DCB, whereas the JAK/STAT loss signature scores were higher for patients with DCB (unadjusted p-values < 0.05).

CONCLUSIONS

ALC above 1.01 × 109/L and absence of liver metastases were significantly associated with DCB in ICI-treated patients with NSCLC. GEP was only feasible in 20% of the patients. GEP-derived signatures may be associated with clinical outcomes, and PD-L1 could be assessed by GEP rather than IHC.

Common nutritional/inflammatory indicators are not effective tools in predicting the overall survival of patients with small cell lung cancer undergoing first-line chemotherapy

Objective

Various studies have investigated the predictive significance of numerous peripheral blood biomarkers in patients with small cell lung cancer (SCLC). However, their predictive values have not been validated. This study assessed and evaluated the ability of common nutritional or inflammatory indicators to predict overall survival (OS) in patients with SCLC who received first-line chemotherapy.

Methods

Between January 2008 and July 2019, 560 patients with SCLC were enrolled at the Sichuan University West China Hospital. Eleven nutritional or inflammatory indices obtained before chemotherapy were evaluated. The cutoff values of continuous peripheral blood indices were confirmed through maximally selected rank statistics. The relationship of peripheral blood indices with OS was investigated through univariate and multivariate Cox regression analyses. Harrell's concordance (C-index) and time-dependent receiver operating characteristic curve were used to evaluate the performance of these indices.

Results

A total of 560 patients with SCLC were enrolled in the study. All the patients received first-line chemotherapy. In the univariate Cox analysis, all indices, except the Naples score, were related to OS. In the multivariate analysis, albumin-globulin ratio was an independent factor linked with prognosis. All indices exhibited poor performance in OS prediction, with the area under the curve ranging from 0.500 to 0.700. The lactic dehydrogenase (LDH) and prognostic nutritional index (PNI) were comparatively superior predictors with C-index of 0.568 and 0.550, respectively. The LDH showed incremental predictive values, whereas the PNI showed diminishing values as survival time prolonged, especially for men or smokers. The LDH with highest sensitivity (0.646) and advanced lung cancer inflammation index (ALI) with highest specificity (0.952) were conducive to identifying death and survival at different time points.

Conclusion

Common inflammatory or nutritional biomarkers are only marginally useful in predicting outcomes in patients with SCLC receiving first-line chemotherapy. Among them, LDH, PNI, and ALI are relatively promising biomarkers for prognosis evaluation.

Development and validation of prognostic risk prediction models for hepatocellular carcinoma patients treated with immune checkpoint inhibitors based on a systematic review and meta-analysis of 47 cohorts

Objective

To identify the risk factors associated with prognosis in patients with hepatocellular carcinoma (HCC) treated with immune checkpoint inhibitors (ICI) via meta-analysis. And to construct prediction models to aid in the prediction and improvement of prognosis.

Methods

We searched PubMed, Embase, Web of Science and Cochrane Library for relevant studies from inception to March 29, 2023. After completing literature screening and data extraction, we performed meta-analysis, sensitivity analysis, and subgroup analysis to identify risk factors associated with OS and PFS. Using the pooled hazard ratio value for each risk factor, we constructed prediction models, which were then validated using datasets from 19 centers in Japan and two centers in China, comprising a total of 204 patients.

Results

A total of 47 studies, involving a total of 7649 ICI-treated HCC patients, were included in the meta-analysis. After analyzing 18 risk factors, we identified AFP, ALBI, NLR, ECOG performance status, Child-Pugh stage, BCLC stage, tumor number, vascular invasion and combination therapy as predictors for OS prediction model, while AFP, ALBI, NLR, ECOG performance status, Child-Pugh stage, BCLC stage, tumor number and vascular invasion were selected as predictors for PFS model. To validate the models, we scored two independent cohorts of patients using both prediction models. Our models demonstrated good performance in these cohorts. In addition, in the pooled cohort of 204 patients, Our models also showed good performance with area under the curve (AUC) values of 0.712, 0.753, and 0.822 for the OS prediction model at 1-year, 2-year, and 3-year follow-up points, respectively, and AUC values of 0.575, 0.749 and 0.691 for the PFS prediction model Additionally, the calibration curve, decision curve analysis, and Kaplan-Meier curves in the pooled cohort all supported the validity of both models.

Conclusion

Based on the meta-analysis, we successfully constructed the OS and PFS prediction models for ICI-treated HCC patients. We also validated the models externally and observed good discrimination and calibration. The model's selected indicators are easily obtainable, making them suitable for further application in clinical practice.

Lung Immune Therapy Evaluation (LITE) Risk, a Novel Prognostic Model for Patients With Advanced Non-Small Cell Lung Cancer Treated With Immune Checkpoint Blockade

INTRODUCTION/BACKGROUND

Immune checkpoint inhibitors (ICI) have revolutionized non-small cell lung cancer (NSCLC). We aimed to identify baseline characteristics, that are prognostic factors for overall survival (OS) in patients with NSCLC treated with ICI monotherapy, in order to derive the Lung Immune Therapy Evaluation (LITE) risk, a prognostic model.

MATERIALS AND METHODS

Multi-center observational cohort study of patients with advanced NSCLC that received ≥1 dose of ICI monotherapy. The training set (n=342) consisted of patients with NSCLC who received first line ICI. The test set (n=153) used for external validation was a discrete cohort of patients who received second line ICI. 20 candidate prognostic factors were examined. Penalized Cox regression was used for variable selection. Multiple imputation was used to address missingness.

RESULTS

Three baseline characteristics populated the final model: ECOG (0, 1 or ≥2), lactate dehydrogenase>upper limit of normal, and derived neutrophil to lymphocyte ratio ≥3. Patients were parsed into 3 risk groups; favorable (n=146, risk score 0-1), intermediate (n=101, risk score 2) and poor (n=95, risk score ≥3). The c-statistic of the training cohort was 0.702 and 0.694 after bootstrapping. The test cohort c-statistic was 0.664. The median OS for favorable, intermediate and poor LITE risk were; 28.3 months, 9.1 months and 2.1 months respectively. Improving LITE risk group was associated with improved OS, intermediate vs favorable HR 2.08 (95%CI 1.46-2.97, P < .001); poor vs favorable HR 5.21 (95%CI 3.69-7.34, P < .001).

CONCLUSION

A simple prognostic model, utilizing accessible clinical data, can discriminate survival outcomes in patients with advanced NSCLC.

Emerging Biomarkers in Immune Oncology to Guide Lung Cancer Management

Over the last decade, the use of targeted therapies and immune therapies led to drastic changes in the management lung cancer and translated to improved survival outcomes. This growing arsenal of therapies available for the management of non-small cell lung cancer added more complexity to treatment decisions. The genomic profiling of tumors and the molecular characterization of the tumor microenvironment gradually became essential steps in exploring and identifying markers that can enhance patient selection to facilitate treatment personalization and narrow down therapy options. The advent of innovative diagnostic platforms, such as next-generation sequencing and plasma genotyping (also known as liquid biopsies), has aided in this quest. Currently, programmed cell death ligand 1 expression remains the most recognized and fully validated predictive biomarker of response to immune checkpoint inhibitors. Other markers such as tumor mutational burden, tumor infiltrating lymphocytes, driver mutations, and other molecular elements of the tumor microenvironment bear the potential to be predictive tools; however, the majority are still investigational. In this review, we describe the advances noted thus far on currently validated as well as novel emerging biomarkers that have the potential to guide the use of immunotherapy agents in the management of non-small cell lung cancer.

Biological Rationale for Peripheral Blood Cell-Derived Inflammatory Indices and Related Prognostic Scores in Patients with Advanced Non-Small-Cell Lung Cancer

PURPOSE OF REVIEW

To describe the biological rationale of peripheral blood cells (PBC)-derived inflammatory indexes and assess the related prognostic scores for patients with advanced non-small cell lung cancer (aNSCLC) treated with immune-checkpoint inhibitors (ICI).

RECENT FINDINGS

Inflammatory indexes based on PBC may indicate a pro-inflammatory condition affecting the immune response to cancer. The lung immune prognostic index (LIPI), consisting of derived neutrophils-to-lymphocyte ratio (NLR) and lactate dehydrogenase, is a validated prognostic tool, especially for pretreated aNSCLC patients, where the combination of NLR and PD-L1 tumour expression might also be predictive of immunotherapy benefit. In untreated high-PD-L1 aNSCLC patients, the Lung-Immune-Prognostic score (LIPS), including NLR, ECOG PS and concomitant steroids, is prognostic, and its modified version might indicate patients with favourable outcomes despite an ECOG PS of 2. NLR times platelets (i.e., SII), included in the NHS-Lung score, might improve the prognostication for combined chemoimmunotherapy. PBC-derived inflammatory indexes and related scores represent accurate, reproducible and non-expensive prognostic tools with clinical and research utility.