Association of circulating protein biomarkers with clinical outcomes of durvalumab in head and neck squamous cell carcinoma

Immune mediators as predictive biomarkers for anti-PD-1 antibody therapy in urothelial carcinoma

Introduction: This study aimed to identify immune mediators, including cytokines, chemokines, and growth factors, in the plasma for predicting treatment efficacy and immune-related adverse events (irAEs) in advanced urothelial carcinoma (aUC) treated with immune checkpoint inhibitors (ICIs). Methods: We enrolled 57 patients with aUC who were treated with the anti-programmed cell death protein 1 (PD-1) antibody pembrolizumab after the failure of platinum-based chemotherapy between February 2018 and December 2020. Plasma levels of 73 soluble immune mediators were measured before and 6 weeks after initiating pembrolizumab therapy. The association of estimated soluble immune mediators with clinical outcomes, including overall survival (OS), progression-free survival (PFS), anti-tumor responses, and irAEs, were statistically evaluated. Results: In the multivariate analysis, levels of 18 factors at baseline and 12 factors during treatment were significantly associated with OS. Regarding PFS, baseline levels of 17 factors were significantly associated with PFS. Higher levels of interleukin (IL)-6, IL-8, soluble tumor necrosis factor receptor 1 (sTNF-R1), and IL-12 (p40), both at baseline and post-treatment, were significantly associated with worse OS. Conversely, low IL-6 and high TWEAK levels at baseline were associated with irAEs. Among identified factors, interferon (IFN) γ and IL-12 (p40) were repeatedly identified; high baseline levels of these factors were risk factors for worse OS and PFS, as well as progressive disease. Notably, using correlation and principal component analysis, factors significantly associated with clinical outcomes were broadly classified into three groups exhibiting similar expression patterns. Discussion: Measuring plasma levels of soluble immune mediators, such as IL-6, IL-8, sTNF-R1, IFNγ, and IL-12 (p40), could be recommended for predicting prognosis and irAEs in ICI-treated patients with aUC.

Baseline Values of Circulating IL-6 and TGF-β Might Identify Patients with HNSCC Who Do Not Benefit from Nivolumab Treatment

BACKGROUND

The immunotherapy of head and neck cancer induces a limited rate of long-term survivors at the cost of treating many patients exposed to toxicity without benefit, regardless of PD-L1 expression. The identification of better biomarkers is warranted. We analyzed a panel of cytokines, chemokines and growth factors, hereinafter all referred to as 'cytokines', as potential biomarkers in patients with head and neck cancer treated with nivolumab.

MATERIALS AND METHODS

A total of 18 circulating cytokines were analyzed. Samples were gathered at baseline (T0) and after 3 courses of nivolumab (T1) in patients with relapsed/metastatic disease. The data extracted at T0 were linked to survival; the comparison of T0-T1 explored the effect of immunotherapy.

RESULTS

A total of 22 patients were accrued: 64% current heavy smokers, 36% female and 14% had PS = 2. At T0, ROC analysis showed that IL-6, IL-8, IL-10 and TGF-β were higher in patients with poor survival. Cox analysis demonstrated that only patients with the IL-6 and TGF-β discriminate had good or poor survival, respectively. Longitudinal increments of CCL-4, IL-15, IL-2 and CXCL-10 were observed in all patients during nivolumab treatment.

CONCLUSION

In this small population with poor clinical characteristics, this study highlights the prognostic role of IL-6 and TGF-β. Nivolumab treatment is associated with a positive modulation of some Th1 cytokines, but it does not correlate with the outcome.

Prognostic role of IL-8 in cancer patients treated with immune checkpoint inhibitors: a system review and meta-analysis

Background

Immune checkpoint inhibitors (ICIs) have been proven to be an effective treatment strategy for a variety of malignant tumors. However, only a subset of patients can benefit from ICIs due to factors such as drug resistance. Therefore, it is crucial to identify biomarkers that can accurately predict the efficacy of ICIs and provide a basis for individualized immunotherapy. In this study, we conducted a systematic review and meta-analysis to explore whether the chemokine interleukin 8 (IL-8) can be used as a biomarker to evaluate the efficacy of ICIs treatment.

Methods

We conducted a comprehensive search of several databases, including PubMed, Embase, Web of Science, and Cochrane, to identify relevant articles published up to June 08, 2023. Our inclusion criteria were limited to cohort studies and clinical trials that reported hazard ratios (HR) and 95% confidence intervals (CI) for overall survival (OS) and/or progression-free survival (PFS), as well as the objective response rate (ORR), in cancer patients with high and low IL-8 expression. For data analysis, we used Revman to generate forest plots, subgroup analysis, and assess publication bias. Additionally, Stata was utilized for sensitivity analysis and further examination of publication bias.

Results

A total of 24 datasets, involving 3190 participants, were selected from 14 studies. The meta-analysis revealed a reduction in ORR, OS, and/or PFS in the high IL-8 group after treatment with ICIs compared to the low IL-8 group.

Conclusion

IL-8 can serve as a biomarker for predicting the efficacy of ICIs. Patients with lower expression of IL-8 may benefit from ICIs treatment.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=383188, identifier CRD42022383188.

Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures

BACKGROUND

Immune checkpoint inhibitor (ICI) therapy has substantially improved the overall survival (OS) in patients with non-small-cell lung cancer (NSCLC); however, its response rate is still modest. In this study, we developed a machine learning-based platform, namely the Cytokine-based ICI Response Index (CIRI), to predict the ICI response of patients with NSCLC based on the peripheral blood cytokine profiles.

METHODS

We enrolled 123 and 99 patients with NSCLC who received anti-PD-1/PD-L1 monotherapy or combined chemotherapy in the training and validation cohorts, respectively. The plasma concentrations of 93 cytokines were examined in the peripheral blood obtained from patients at baseline (pre) and 6 weeks after treatment (early during treatment: edt). Ensemble learning random survival forest classifiers were developed to select feature cytokines and predict the OS of patients undergoing ICI therapy.

RESULTS

Fourteen and 19 cytokines at baseline and on treatment, respectively, were selected to generate CIRI models (namely preCIRI14 and edtCIRI19), both of which successfully identified patients with worse OS in two completely independent cohorts. At the population level, the prediction accuracies of preCIRI14 and edtCIRI19, as indicated by the concordance indices (C-indices), were 0.700 and 0.751 in the validation cohort, respectively. At the individual level, patients with higher CIRI scores demonstrated worse OS [hazard ratio (HR): 0.274 and 0.163, and p<0.0001 and p=0.0044 in preCIRI14 and edtCIRI19, respectively]. By including other circulating and clinical features, improved prediction efficacy was observed in advanced models (preCIRI21 and edtCIRI27). The C-indices in the validation cohort were 0.764 and 0.757, respectively, whereas the HRs of preCIRI21 and edtCIRI27 were 0.141 (p<0.0001) and 0.158 (p=0.038), respectively.

CONCLUSIONS

The CIRI model is highly accurate and reproducible in determining the patients with NSCLC who would benefit from anti-PD-1/PD-L1 therapy with prolonged OS and may aid in clinical decision-making before and/or at the early stage of treatment.

Nine-gene signature and nomogram for predicting survival in patients with head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinomas (HNSCCs) are derived from the mucosal linings of the upper aerodigestive tract, salivary glands, thyroid, oropharynx, larynx, and hypopharynx. The present study aimed to identify the novel genes and pathways underlying HNSCC. Despite the advances in HNSCC research, diagnosis, and treatment, its incidence continues to rise, and the mortality of advanced HNSCC is expected to increase by 50%. Therefore, there is an urgent need for effective biomarkers to predict HNSCC patients’ prognosis and provide guidance to the personalized treatment.

Methods: Both HNSCC clinical and gene expression data were abstracted from The Cancer Genome Atlas (TCGA) database. Intersecting analysis was adopted between the gene expression matrix of HNSCC patients from TCGA database to extract TME-related genes. Differential gene expression analysis between HNSCC tissue samples and normal tissue samples was performed by R software. Then, HNSCC patients were categorized into clusters 1 and 2 via NMF. Next, TME-related prognosis genes (p &lt; 0.05) were analyzed by univariate Cox regression analysis, LASSO Cox regression analysis, and multivariate Cox regression analysis. Finally, nine genes were selected to construct a prognostic risk model and a prognostic gene signature. We also established a nomogram using relevant clinical parameters and a risk score. The Kaplan–Meier curve, survival analysis, time-dependent receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and the concordance index (C-index) were carried out to assess the accuracy of the prognostic risk model and nomogram. Potential molecular mechanisms were revealed by gene set enrichment analysis (GSEA). Additionally, gene correlation analysis and immune cell correlation analysis were conducted for further enriching our results.

Results: A novel HNSCC prognostic model was established based on the nine genes (GTSE1, LRRN4CL, CRYAB, SHOX2, ASNS, KRT23, ANGPT2, HOXA9, and CARD11). The value of area under the ROC curves (AUCs) (0.769, 0.841, and 0.816) in TCGA whole set showed that the model effectively predicted the 1-, 3-, and 5-year overall survival (OS). Results of the Cox regression assessment confirmed the nine-gene signature as a reliable independent prognostic factor in HNSCC patients. The prognostic nomogram developed using multivariate Cox regression analysis showed a superior C-index over other clinical signatures. Also, the calibration curve had a high level of concordance between estimated OS and the observed OS. This showed that its clinical net can precisely estimate the one-, three-, and five-year OS in HNSCC patients. The gene set enrichment analysis (GSEA) to some extent revealed the immune- and tumor-linked cascades.

Conclusion: In conclusion, the TME-related nine-gene signature and nomogram can effectively improve the estimation of prognosis in patients with HNSCC.

Peripheral cytokine levels as novel predictors of survival in cancer patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis

Background

Early identification of patients who will benefit from immune checkpoint inhibitors (ICIs) has recently become a hot issue in cancer immunotherapy. Peripheral cytokines are key regulators in the immune system that can induce the expression of immune checkpoint molecules; however, the association between peripheral cytokines and the efficiency of ICIs remains unclear.

Methods

A systematic review was conducted in several public databases from inception through 3 February 2022 to identify studies investigating the association between peripheral cytokines (i.e., IL-1β, IL-2, IL-2RA, IL-2R, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-15, IL-17, TNF-α, IFN-γ, and TGF-β) and ICI treatment. Survival data, including overall survival (OS) and/or progression-free survival (PFS), were extracted, and meta-analyses were performed.

Results

Twenty-four studies were included in this analysis. The pooled results demonstrated that the pretreatment peripheral levels of IL-6 (univariate analysis: HR = 2.53, 95% CI = 2.21–2.89, p < 0.00001; multivariate analysis: HR = 2.21, 95% CI = 1.67–2.93, p < 0.00001) and IL-8 (univariate analysis: HR = 2.17, 95% CI = 1.98–2.38, p < 0.00001; multivariate analysis: HR = 1.88, 95% CI= 1.70–2.07, p < 0.00001) were significantly associated with worse OS of cancer patients receiving ICI treatment in both univariate and multivariate analysis. However, high heterogeneity was found for IL-6, which might be attributed to region, cancer type, treatment method, sample source, and detection method.

Conclusion

The peripheral level of IL-8 may be used as a prognostic marker to identify patients with inferior response to ICIs. More high-quality prospective studies are warranted to assess the predictive value of peripheral cytokines for ICI treatment.

Plasma secretome analyses identify IL-8 and nitrites as predictors of poor prognosis in nasopharyngeal carcinoma patients

Predicting tumor recurrence and death in patients with nasopharyngeal carcinoma (NPC) remains to date challenging. We here analyzed the plasmatic secretomes of NPC untreated and relapsing patients, and explored possible correlations with the clinical and pathological features and survival characteristics of the corresponding patient cohorts, with the aim of identifying novel prognostic biomarkers. This study included 27 controls, 45 untreated NPC and 11 relapsed patients. A set of 14 plasma cytokines were analyzed using Millipore multiplex assay. Nitrites were assessed by Griess method. A comparative analysis of each groups' secretome showed upregulation of IL-8, IL-12p70, IL-10 and IP-10 in untreated patients, and of IL-6, IL-10, MCP-1 and IP-10 in relapsing patients. Nitrites significantly correlated with IL-8 during relapse. Secretomes' network analyses revealed prevalence of high correlations between IL8/IL-17A and IFN-γ/IL12p70 in the control group, between TNF-α/IL-8/IL-6, TNF-α/VEGF/IFN-γ and IL-10/MCP-1 in the untreated group, and between IL-8/IL-6/IL-10, TNF-α/IL-8/IL-6, IL12-p70/VEGF/IL-10/IFN-γ, IL-6/IL-10/IFN-γ and IL-8/IP-10 in the relapse group. IL-12p70, IP-10 and MCP-1 levels respectively associated with gender, age and node metastasis respectively. Recurrence-free survival (RFS) analysis showed that patients presenting High IL-8/Low NO immunological scores presented a combined 80% probability of relapse/death after 53 months (combined log-rank test p = 0.0034; individual p = 0.012 and p = 0.016). Multivariate Cox hazard regression analysis revealed that IL-8 (HR = 7.451; 95% CI [2.398-23.152]; p = 0.001) and treatment type (HR = 0.232; 95% CI 0.072-0.749; p = 0.015) were independent prognostic factors. C&RT decision tree analysis showed that High IL-8/Low NO immunological scores predicted treatment failure in 50% cases starting the 36th month of follow-up (AUC = 1) for all of the studied cases and in 57% cases for patients receiving chemotherapy alone (AUC = 1). Altogether, our results showed that NPC development is accompanied with cytokines deregulation to form specific interaction networks at time of diagnosis and relapse, and demonstrate that High IL-8/Low NO signature may constitute a predictor of poor prognosis which may be useful to improve risk stratification and therapy failure management.

The Predictive Potential of the Baseline C-Reactive Protein Levels for the Efficiency of Immune Checkpoint Inhibitors in Cancer Patients: A Systematic Review and Meta-Analysis

Background

The relationship between baseline C-reactive protein (CRP) level and the prognosis of cancer patients receiving immune checkpoint inhibitor (ICI) treatment remains controversial. The aim of this meta-analysis was to clarify whether baseline CRP level can serve as a biomarker to predict the efficiency of ICI therapy.

Methods

All associated articles published in the Cochrane Library, EMBASE, and PubMed databases from the inception of the database to December 30, 2021, were retrieved. Progression-free survival (PFS) and overall survival (OS) outcomes were meta-analyzed using the random-effects model and adjusted using the trim-and-fill method because of publication bias.

Results

Thirty-three studies (6,124 patients) conducted between 2013 and 2021 were identified. The pooled outcomes implied that high baseline CRP level patients had significantly worse OS (adjusted pooled value for univariate and multivariate analysis outcomes: HR = 1.48, 95% CI = 1.41-1.56; HR = 1.46, 95% CI = 1.34-1.59) and PFS (adjusted pooled value for univariate and multivariate analysis outcomes: HR = 1.29, 95% CI = 1.15-1.45; HR = 1.20, 95% CI = 1.02-1.40) than low baseline CRP level patients, irrespective of cancer or ICI type. Further analysis indicated that 1 mg/dl was appropriate as a cutoff value for determining the low or high level of baseline CRP to predict the OS or PFS of cancer patients receiving ICI treatment (univariate analysis: HR = 1.56, 95% CI = 1.24-1.97, P = 0.909; multivariate analysis: HR = 1.58, 95% CI = 1.23-2.03, P = 0.521).

Conclusions

High baseline CRP level (>1 mg/dl) may be an indicator for worse OS and PFS of cancer patients treated with ICIs. More high-quality prospective studies are warranted to assess the predictive value of CRP for ICI treatment.