The Levels of Interferon-gamma Release as a Biomarker for Non-small-cell Lung Cancer Patients Receiving Immune Checkpoint Inhibitors

Peripheral blood immune parameters, response, and adverse events after neoadjuvant chemotherapy plus durvalumab in early-stage triple-negative breast cancer

PURPOSE

We evaluated T- and B-cell receptor (TCR and BCR) repertoire diversity and 38 serum cytokines in pre- and post-treatment peripheral blood of 66 patients with triple-negative breast cancer (TNBC) who received neoadjuvant chemotherapy plus durvalumab and assessed associations with pathologic response and immune-related adverse events (irAEs) during treatment.

METHODS

Genomic DNA was isolated from buffy coat for TCR and BCR clonotype profiling using the Immunoseq platform and diversity was quantified with Pielou's evenness index. MILLIPLEX MAP Human Cytokine/Chemokine Magnetic Bead Panel was used to measure serum cytokine levels, which were compared between groups using moderated t-statistic with Benjamini-Hochberg correction for multiple testing.

RESULTS

TCR and BCR diversity was high (Pielou's index > 0.75) in all samples. Baseline receptor diversities and change in diversity pre- and post-treatment were not associated with pathologic response or irAE status, except for BCR diversity that was significantly lower post-treatment in patients who developed irAE (unadjusted p = 0.0321). Five cytokines increased after treatment in patients with pathologic complete response (pCR) but decreased in patients with RD, most prominently IL-8. IFNγ, IL-7, and GM-CSF levels were higher in pre-treatment than in post-treatment samples of patients who developed irAEs but were lower in those without irAEs.

CONCLUSION

Baseline peripheral blood cytokine levels may predict irAEs in patients treated with immune checkpoint inhibitors and chemotherapy, and increased post-treatment B-cell clonal expansion might mediate irAEs.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

Selective activation of IFNγ-ipilimumab enhances the therapeutic effect and safety of ipilimumab

INTRODUCTION

Immune checkpoint inhibitor therapy is a highly promising strategy for clinical treatment of cancer. Among these inhibitors, ipilimumab stands out for its ability to induce cytotoxic T cell proliferation and activation by binding to CTLA-4. However, ipilimumab also gives rise to systemic immune-related adverse effects and tumor immune evasion, limiting its effectiveness.

OBJECTIVES

We developed IFNγ-ipilimumab and confirmed that the addition of INF-γ does not alter the fundamental properties of ipilimumab.

RESULTS

IFNγ-ipilimumab can be activated by matrix metalloproteinases, thereby promoting the IFNγ signaling pathway and enhancing the cytotoxicity of T cells. In vivo studies demonstrated that IFNγ-ipilimumab enhances the therapeutic effect of ipilimumab against colorectal cancer by increasing CD8+ and CD4+ lymphocyte infiltration into the tumor area and inducing MHC-I expression in tumor cells. Mice treated with IFNγ-ipilimumab showed higher survival rates and body weight, as well as lower CD4+ and CD8+ lymphocyte activation rates in the blood and reduced organ damage.

CONCLUSION

IFNγ-ipilimumab improved the effectiveness of ipilimumab while reducing its side effects. It is likely that future immunotherapies would rely on such antibodies to activate local cancer cells or immune cells, thereby increasing the therapeutic effectiveness of cancer treatments and ensuring their safety.

Circulating cytokine dynamics as potential biomarker of response to anti-PD-1 immunotherapy in BRAFwt MM patients

BACKGROUND

The biomarkers of immune checkpoint inhibitors (ICIs) efficacy and safety are still urgently needed. As cytokines are easily detected and monitored in circulation, they could be used as potential predictors of response and immune-related adverse events (irAEs) for ICIs therapy.

METHODS

The levels of TGF-β, IFN-γ, IL-6, IL-8, IL-10 were measured in sera and plasma by ELISA method of 30 healthy controls (HC) and 32 BRAF wild type (wt) MM patients before and after every 12 weeks of Pembrolizumab, PD-1 inhibitor, until one year or disease progression (DP).

RESULTS

Higher pretherapy levels of circulating TGF-β, IFN-γ, IL-6, and IL-10 were shown in MM patients compared to HC. In patients with disease control, TGF-β and IL-6 first decreased during the therapy, while then they started to successively increase reaching the initial values by the end of the follow up. Furthermore, in this group of patients IFN-γ increased, while IL-8 and IL-10 decreased at final points of the follow up. In patients with DP IL-6 increased at the time of progression, while IL-8 decreased when the best response was achieved. In patients with pseudoprogression IL-6 and IL-10 significantly increased compared to the pretreatment values. Melanoma patients with irAEs had increased baseline values of TGF-β, IFN-γ, IL-6, and IL-10 compared to HC. However, no significant changes in cytokines levels were found in these patients during therapy.

CONCLUSIONS

Inflammatory cytokines monitoring in circulation of BRAFwt MM patients could help in the selection of patients who will have the benefit from Pembrolizumab therapy.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

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.

Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

Serum cytokine levels and other associated factors as possible immunotherapeutic targets and prognostic indicators for lung cancer

Lung cancer is one of the most prevalent cancer types and the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) accounts for 80-85% of all cancer incidences. Lung cancer therapy and prognosis largely depend on the disease's degree at the diagnosis time. Cytokines are soluble polypeptides that contribute to cell-to-cell communication, acting paracrine or autocrine on neighboring or distant cells. Cytokines are essential for developing neoplastic growth, but they are also known to operate as biological inducers following cancer therapy. Early indications are that inflammatory cytokines such as IL-6 and IL-8 play a predictive role in lung cancer. Nevertheless, the biological significance of cytokine levels in lung cancer has not yet been investigated. This review aimed to assess the existing literature on serum cytokine levels and additional factors as potential immunotherapeutic targets and lung cancer prognostic indicators. Changes in serum cytokine levels have been identified as immunological biomarkers for lung cancer and predict the effectiveness of targeted immunotherapy.

Circulating Biomarkers for Prediction of Immunotherapy Response in NSCLC

Non-small cell lung cancer (NSCLC) constitutes the majority of the lung cancer population and the prognosis is poor. In recent years, immunotherapy has become the standard of care for advanced NSCLC patients as numerous trials demonstrated that immune checkpoint inhibitors (ICI) are more efficacious than conventional chemotherapy. However, only a minority of NSCLC patients benefit from this treatment. Therefore, there is an unmet need for biomarkers that could accurately predict response to immunotherapy. Liquid biopsy allows repeated sampling of blood-based biomarkers in a non-invasive manner for the dynamic monitoring of treatment response. In this review, we summarize the efforts and progress made in the identification of circulating biomarkers that predict immunotherapy benefit for NSCLC patients. We also discuss the challenges with future implementation of circulating biomarkers into clinical practice.

Immune checkpoint inhibitor-associated toxicity in advanced non-small cell lung cancer: An updated understanding of risk factors

Immune checkpoint inhibitors (ICIs), such as programmed death-1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T lymphocyte antigen 4 (CTLA-4) antibodies, etc, have revolutionized cancer treatment strategies, including non-small cell lung cancer (NSCLC). While these immunotherapy agents have achieved durable clinical benefits in a subset of NSCLC patients, they bring in a variety of immune-related adverse events (irAEs), which involve cardiac, pulmonary, gastrointestinal, endocrine and dermatologic system damage, ranging from mild to life-threatening. Thus, there is an urgent need to better understand the occurrence of irAEs and predict patients who are susceptible to those toxicities. Herein, we provide a comprehensive review of what is updated about the clinical manifestations, mechanisms, predictive biomarkers and management of ICI-associated toxicity in NSCLC. In addition, this review also provides perspective directions for future research of NSCLC-related irAEs.

Chinese expert consensus on the multidisciplinary management of pneumonitis associated with immune checkpoint inhibitor

Immune checkpoint inhibitors (ICIs) have successfully treated a number of different types of cancer, which is of great significance for cancer treatment. With the widespread use of ICIs in clinical practice, the increasing checkpoint inhibitor pneumonia (CIP) will be a challenge to clinicians. To guide the diagnosis and treatment of CIP, we conducted in-depth discussions based on the latest evidence, forming a consensus among Chinese experts on the multidisciplinary management of CIP.

Changes of IL-6 And IFN-γ before and after the adverse events related to immune checkpoint inhibitors: A retrospective study

Immune checkpoint inhibitors (ICIs) have changed the status of tumor immunotherapy. ICIs-related adverse events (irAEs) have the high incidence and are difficult to predict and prevent. Researches have suggested that changes of cytokines were associated with irAEs. This study focused on the changes of interleukin-6 (IL-6) and interferon-γ in patients before and after irAEs and trying to find the biomarkers of irAEs. Collect basic data of patients who were treated with ICIs in China-Japan Friendship Hospital from January 2017 to August 2021 and had irAEs. Make statistics on IL-6 and INF-γ in the blood before and after irAEs. A total of 10 patients were enrolled, including 7 males and 3 females. According to statistical analysis, the IL-6 concentration level after irAEs was significantly higher than before, and the difference was statistically significant (P = .023); the interferon-γ concentration level was not changed significantly from before, the difference was not statistically significant (P = .853). The elevation of IL-6 was associated with the occurrence of adverse reactions in ICIs.

Therapeutic targets and biomarkers of tumor immunotherapy: response versus non-response

Cancers are highly complex diseases that are characterized by not only the overgrowth of malignant cells but also an altered immune response. The inhibition and reprogramming of the immune system play critical roles in tumor initiation and progression. Immunotherapy aims to reactivate antitumor immune cells and overcome the immune escape mechanisms of tumors. Represented by immune checkpoint blockade and adoptive cell transfer, tumor immunotherapy has seen tremendous success in the clinic, with the capability to induce long-term regression of some tumors that are refractory to all other treatments. Among them, immune checkpoint blocking therapy, represented by PD-1/PD-L1 inhibitors (nivolumab) and CTLA-4 inhibitors (ipilimumab), has shown encouraging therapeutic effects in the treatment of various malignant tumors, such as non-small cell lung cancer (NSCLC) and melanoma. In addition, with the advent of CAR-T, CAR-M and other novel immunotherapy methods, immunotherapy has entered a new era. At present, evidence indicates that the combination of multiple immunotherapy methods may be one way to improve the therapeutic effect. However, the overall clinical response rate of tumor immunotherapy still needs improvement, which warrants the development of novel therapeutic designs as well as the discovery of biomarkers that can guide the prescription of these agents. Learning from the past success and failure of both clinical and basic research is critical for the rational design of studies in the future. In this article, we describe the efforts to manipulate the immune system against cancer and discuss different targets and cell types that can be exploited to promote the antitumor immune response.

Risk factors and predictors of immune-related adverse events: implications for patients with non-small cell lung cancer

INTRODUCTION

Immune checkpoint inhibitors (ICI) are now utilized as a standard of care treatment for multiple cancers, including in both the metastatic setting as well as in earlier stages of disease. The identification of unique immune-related adverse events (irAE) that occur during ICI treatment has led to intense research to identify potential risk factors and biomarkers that may assist in clinical decision making. Although initial studies in ICI were primarily in advanced stage disease, the use of ICI in earlier stages of disease as adjuvant therapies requires a better understanding of patient risk stratification to mitigate or prevent serious irAE.

AREAS COVERED

In this review, we set out to describe the current state of research regarding potential risk factors for irAE in patients with non-small cell lung cancer, as well as explore the barriers to understanding irAE. We review data from irAE that occur in large phase 3 trials and prospective studies focusing on irAE, as well as the many retrospective studies that currently form the bulk of our understanding of irAE.

Emerging Blood-Based Biomarkers for Predicting Immunotherapy Response in NSCLC

Simple Summary

Treatment with immunotherapy has been established as a standard treatment for lung cancer in recent years. Unfortunately, still, only a small proportion of patients benefit from the treatment, being the first leading cause of cancer death worldwide. Therefore, there is an urgent need for predictive biomarkers to help clinicians to discern whose patients are more likely to respond to immunotherapy. Since liquid biopsy opens the door to select patients and monitor the response during the treatment in a non-invasive way, in this review, we focus on the most relevant and recent results based on blood soluble biomarkers.

Abstract

Immunotherapy with Immune Checkpoint Inhibitors (ICIs) has demonstrated a profitable performance for Non-Small Cell Lung Cancer (NSCLC) cancer treatment in some patients; however, there is still a percentage of patients in whom immunotherapy does not provide the desired results regarding beneficial outcomes. Therefore, obtaining predictive biomarkers for ICI response will improve the treatment management in clinical practice. In this sense, liquid biopsy appears as a promising method to obtain samples in a minimally invasive and non-biased way. In spite of its evident potential, the use of these circulating biomarkers is still very limited in the real clinical practice, mainly due to the huge heterogeneity among the techniques, the lack of consensus, and the limited number of patients included in these previous studies. In this work, we review the pros and cons of the different proposed biomarkers, such as soluble PD-L1, circulating non-coding RNA, circulating immune cells, peripheral blood cytokines, and ctDNA, obtained from liquid biopsy to predict response to ICI treatment at baseline and to monitor changes in tumor and tumor microenvironment during the course of the treatment in NSCLC patients.

Risk Factors and Biomarkers for Immune-Related Adverse Events: A Practical Guide to Identifying High-Risk Patients and Rechallenging Immune Checkpoint Inhibitors

Immune-related adverse events (irAEs) are a range of complications associated with the use of immune-checkpoint inhibitors (ICIs). Two major classes of ICIs widely used are Cytotoxic T-Lymphocyte Antigen 4 (CTLA4) and Programmed Cell death-1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors. High-grade irAEs are life-threatening and often cause a severe decline in performance status in such that patients do not qualify for any further anticancer treatments. It is difficult to generalize the evidence in the current literature on risk factors or biomarkers for the entire class of ICIs as the studies so far are either disease-specific (e.g., lung cancer or melanoma) or ICI agent-specific (e.g., pembrolizumab, ipilimumab) or irAE-specific (e.g., pneumonitis or gastritis). In this review, risk factors and biomarkers to consider before initiating or monitoring ICI are listed with a practical purpose in day-to-day practice. Risk factors are grouped into demographics and social history, medical history, and medication history, tumor-specific and agent-specific risk factors. A higher risk of irAE is associated with age <60 years, high body mass index, women on CTLA4 and men on PD-1/PD-L1 agents, and chronic smokers. Patients with significant kidney (Stage IV-V), cardiac (heart failure, coronary artery disease, myocardial infarction, hypertension), and lung (asthma, pulmonary fibrosis, and chronic obstructive pulmonary disease) are at a higher risk of respective organ-specific irAEs. Pre-existing autoimmune disease and chronic use of certain drugs (proton pump inhibitors, diuretics, anti-inflammatory drugs) also increase the irAE-risk. Biomarkers are categorized into circulating blood counts, cytokines, autoantibodies, HLA genotypes, microRNA, gene expression profiling, and serum proteins. The blood counts and certain protein markers (albumin and thyroid-stimulating hormone) are readily accessible in current practice. High neutrophil-lymphocyte ratio, eosinophil/monocyte/lymphocyte counts; TSH and troponins at diagnosis and drop in the white count and lymphocyte count can predict irAE. Other biomarkers with limited evidence are cytokines, autoantibodies, HLA genotypes, microRNA, and gene expression profiling. With fast-expanding approvals for ICIs in various cancer types, knowledge on risk factors and biomarkers can help providers assess the irAE-risk of their patients. Prospective disease and agent-specific studies are needed to provide further insight on this essential aspect of ICI therapy.

CD19 CAR-T Cell Therapy Induced Immunotherapy Associated Interstitial Pneumonitis: A Case Report

Background

Chimeric antigen receptor-modified T cells (CAR-T) targeting CD19 has produced a high durable response in refractory or relapsed diffuse large B-cell lymphoma. Besides well-known cytokine release syndrome (CRS) or immune effector cell–associated neurotoxicity syndrome during CAR-T cell therapy, there were several rarely encountered fatal complications.

Case Report

A 63-year-old male patient with refractory EBV-positive diffuse large B-cell lymphoma, developed interstitial pneumonitis with prolonged hypoxemia at 16 weeks after CD19 CAR-T cell therapy. There was no evidence of CRS and any infections. The patient recovered after intravenous immunoglobulin without tocilizumab or glucocorticoid administration. Now he is still in remission without interstitial pneumonitis 3 years after CAR-T cell therapy.

Conclusion

This is the first report of immunotherapy-associated interstitial pneumonitis after CAR-T cell therapy. Our finding suggested the importance of careful follow-up and proper treatments for immunotherapy-associated pneumonitis in the CAR-T cell therapy schedule.

A Machine Learning Model to Predict the Triple Negative Breast Cancer Immune Subtype

Background

Immune checkpoint blockade (ICB) has been approved for the treatment of triple-negative breast cancer (TNBC), since it significantly improved the progression-free survival (PFS). However, only about 10% of TNBC patients could achieve the complete response (CR) to ICB because of the low response rate and potential adverse reactions to ICB.

Methods

Open datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were downloaded to perform an unsupervised clustering analysis to identify the immune subtype according to the expression profiles. The prognosis, enriched pathways, and the ICB indicators were compared between immune subtypes. Afterward, samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate the correlation of immune subtype with prognosis. Data from patients who received ICB were selected to validate the correlation of the immune subtype with ICB response. Machine learning models were used to build a visual web server to predict the immune subtype of TNBC patients requiring ICB.

Results

A total of eight open datasets including 931 TNBC samples were used for the unsupervised clustering. Two novel immune subtypes (referred to as S1 and S2) were identified among TNBC patients. Compared with S2, S1 was associated with higher immune scores, higher levels of immune cells, and a better prognosis for immunotherapy. In the validation dataset, subtype 1 samples had a better prognosis than sub type 2 samples, no matter in overall survival (OS) (p = 0.00036) or relapse-free survival (RFS) (p = 0.0022). Bioinformatics analysis identified 11 hub genes (LCK, IL2RG, CD3G, STAT1, CD247, IL2RB, CD3D, IRF1, OAS2, IRF4, and IFNG) related to the immune subtype. A robust machine learning model based on random forest algorithm was established by 11 hub genes, and it performed reasonably well with area Under the Curve of the receiver operating characteristic (AUC) values = 0.76. An open and free web server based on the random forest model, named as triple-negative breast cancer immune subtype (TNBCIS), was developed and is available from https://immunotypes.shinyapps.io/TNBCIS/.

Conclusion

TNBC open datasets allowed us to stratify samples into distinct immunotherapy response subgroups according to gene expression profiles. Based on two novel subtypes, candidates for ICB with a higher response rate and better prognosis could be selected by using the free visual online web server that we designed.

The Role of Cytokines in Predicting the Response and Adverse Events Related to Immune Checkpoint Inhibitors

Recently, the overall survival (OS) and progression-free survival (PFS) of patients with advanced cancer has been significantly improved due to the application of immune checkpoint inhibitors (ICIs). Low response rate and high occurrence of immune-related adverse events (irAEs) make urgently need for ideal predictive biomarkers to identity efficient population and guide treatment strategies. Cytokines are small soluble proteins with a wide range of biological activity that are secreted by activated immune cells or tumor cells and act as a bridge between innate immunity, infection, inflammation and cancer. Cytokines can be detected in peripheral blood and suitable for dynamic detection. During the era of ICIs, many studies investigated the role of cytokines in prediction of the efficiency and toxicity of ICIs. Herein, we review the relevant studies on TNF-α, IFN-γ, IL-6, IL-8, TGF-β and other cytokines as biomarkers for predicting ICI-related reactions and adverse events, and explore the immunomodulatory mechanisms. Finally, the most important purpose of this review is to help identify predictors of ICI to screen patients who are most likely to benefit from immunotherapy.

Systemic inflammation and pro-inflammatory cytokine profile predict response to checkpoint inhibitor treatment in NSCLC: a prospective study

Treatment with single agent immune checkpoint inhibitors (ICIs) has tremendously changed second line therapy in NSCLC. However, there are still no reliable biomarkers predicting response and survival in this group of patients. PD-L1 revealed to be a correlating, but no perfect marker. Therefore, we sought to investigate in this prospective study, whether inflammation status and cytokine profile could serve as additional biomarkers guiding treatment decision for single agent ICIs in NSCLC. 29 stage IV NSCLC patients receiving single agent PD-1 checkpoint-inhibitor in second line were prospectively enrolled. Inflammatory scores and cytokine profiles (IL-6, IL-8, IL-10, IFN-γ and TNFα) have been obtained before treatment and at the time of the first staging. Cytokine profiles were correlated with response and survival. Patients with signs of pre-therapeutic inflammation (elevated, NLR, SII, IL-6, IL-8) showed significantly lower response to ICI treatment and reduced PFS. Contrary, elevated levels of IFN-γ revealed to characterize a subgroup of patients, who significantly benefits from ICI treatment. Furthermore, low systemic inflammation and high levels of IFN-γ characterized patients with long term-response to ICI treatment. Pre-therapeutic assessment of inflammation and cytokine profiles has the ability to predict response and survival in NSCLC patients treated with single agent ICIs.

A narrative review of current and potential prognostic biomarkers for immunotherapy in small-cell lung cancer

Small-cell lung cancer (SCLC) is a highly invasive and rapidly proliferating pathologic subtype that accounts for 13-15% of all lung cancer cases. Recently in extensive-stage SCLC, treatments that combine immunotherapy and chemotherapy showed increased efficacy compared to chemotherapy alone in several trials. However, the combination of immunotherapy and conventional chemotherapy regimens was introduced only recently for extensive-stage SCLC, with relatively little real-world data. The demand for reliable biomarkers that can predict the efficacy of immunotherapy in SCLC is high. Several studies evaluated various parameters including programmed cell death ligand-1 (PD-L1) expression, tumor mutation burden (TMB), gene expression profiling, autoantibody, and blood cytokines for predictive value for response to immunotherapy in SCLC. Despite some observed correlations, there is a lack of concrete support for the use of PD-L1 expression levels for readily available biomarker. High TMB in combination with smoking history is predictive of a better response to immunotherapy, but validation of cutoffs and testing methods is necessary before it can be widely applied in clinical settings. Other candidate biomarkers such as immune cell distribution among tumor microenvironment, and systemic inflammatory markers can also be evaluated, after an accumulation of real-life data from SCLC patients under immunotherapy.

Narrative review: update on immunotherapy and pathological features in patients with bladder cancer

Over the last few years efficacy of immunotherapy using immune checkpoint inhibitors (ICI) has been investigated in patients with bladder cancer (BC) at all stages. The present article aims to assess new therapeutic options with emerging agents in BC patients, shedding light on ICI-based treatments encompassing all disease stages, from non-muscle invasive (NMIBC) to muscle-invasive (MIBC) BC, concluding with metastatic MIBC. In bacillus Calmette-Guerin (BCG) unresponsive patients with carcinoma in situ, pembrolizumab has been recently approved. In the neoadjuvant setting, results from two clinical trials seem to identify pathological and genomic features of highly responsive tumors. Squamous cells and lymphoepithelioma/like histotypes, programmed cell-death ligand 1 (PD-L1) expression and high levels of activate T cells have been associated with higher response rate. In the metastatic setting, only 30% of patient may respond to ICI. A panel of biomarkers for patient selection is an actual need since the correlation between response and PD-L1 expression seem inconsistent across clinical trials, with some exceptions. Molecular characterization of BC, tumor mutation burden and immune-gene expression profiling might introduce new molecular biomarkers, hopefully transferable into the clinical-pathological practice.

T lymphocytes related biomarkers for predicting immunotherapy efficacy in non-small cell lung cancer

The immune environment is a determinant of whether patients with cancer can benefit from immunotherapy. Immune checkpoint inhibitors (ICIs) have improved the prognosis of patients with different types of malignancies and have initiated a transformation in tumor therapy. However, some patients cannot achieve a long-term response and several patients even have no response to ICIs therapy. Thus, potential biomarkers that can effectively predict the efficacy of ICIs are essential for their clinical application and for the selection of patients. The accuracy of well-known biomarkers, such as expression of programmed cell death ligand 1 and tumor mutational burden, remains controversial. One of the critical factors for immune responses in the tumor microenvironment is tumor antigen-specific T cell. The density and distribution of tumor-infiltrating lymphocytes, T cells activation and T lymphocytes phenotypes in peripheral blood and serum cytokines have been observed in different types of solid cancer. Although the association with immunotherapy prognosis is in dispute, the prospect of T cell-related biomarkers is encouraged. The present review discusses whether these factors are associated with clinical outcomes of patients with non-small cell lung cancer. The association between several serum cytokines and ICIs therapy efficacy is also discussed.

Potential predictive value of change in inflammatory cytokines levels subsequent to initiation of immune checkpoint inhibitor in patients with advanced non-small cell lung cancer

For a definite indication for immunotherapy, finding appropriate biomarkers that are predictive of treatment responses is necessary. Inflammatory cytokines which play critical roles in immunity against infectious sources or cancer cells are suggested to activate immune cells after initiation of immune checkpoint inhibitors (ICI). Through activation of immune cells such as T cells, natural killer cells, macrophages, or tumor infiltrating dendritic cells, inflammatory cytokines usually increase after programmed death (PD)-1/PD-L1 axis blockade. There have been several studies evaluating the predictive value of early changes in inflammatory cytokines in non-small cell lung cancer (NSCLC) patients undergoing immunotherapy. In this mini-review, we went through recent articles on potential blood level values of inflammatory cytokines in NSCLC patients receiving ICI and their early change around commencement of ICIs in predicting response to treatment and disease progression. The studies evaluated cytokines including interleukin (IL)-2, 6, 8, interferon (IFN)-γ, and tumor necrosis factor (TNF)-α for predictability for responses to ICI. A combination cytokine panel can help predict the response and prognosis of patients with NSCLC who are receiving ICI treatment. Furthermore, a more individualized ICI treatment will be available if responses and change in tumor burden can be predicted. However, most of the studies on cytokines in NSCLC patients receiving ICIs had a small number of patients, and the heterogeneous measurement time points. Nevertheless, cytokines such as IL-8 and IFN- γ have considerable potential predictive value for immunotherapy response, which is worthy of further studies. To utilize blood cytokines levels as biomarkers for immunotherapy, a larger study with uniform measurement protocol is necessary.

Investigational Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Event Prediction and Diagnosis

BACKGROUND

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of multiple cancers. However, these promising therapies may also cause immune-related adverse events (irAEs) in a substantial proportion of patients. These autoimmune phenomena may affect almost any organ system and may occur at almost any point in therapy. In some instances, these toxicities are life-threatening and potentially permanent. Diverse clinical presentation and unpredictable timing further complicate their anticipation and diagnosis.

CONTENT

To improve patient safety and selection for ICI use, biomarkers for irAE diagnosis and prediction are under development. Clinicians may use traditional laboratory markers such as routine chemistries, creatinine clearance, thyroid function tests, and serum cortisol/adrenocorticotrophic hormone to monitor for specific irAEs, but noted aberrations may not necessarily represent an immune-mediated etiology. Novel biomarkers have the potential to be more specific to assist in the diagnosis of irAEs. The prediction of irAEs is more challenging. Apart from a history of autoimmune disease, no other clinical parameters are routinely used to project risk. Biomarker candidates under investigation for irAE diagnosis and prediction include blood cell analysis, chemokines/cytokines, autoantibodies, and genetic predisposition, such as human leukocyte antigen haplotype. Among other emerging candidates are immune-cell subsets, T-cell repertoire, fecal microbiome, tumor genomics, and radiomic characterization.

SUMMARY

Several conventional laboratory indexes of end-organ dysfunction are currently in routine clinical use for irAE monitoring and diagnosis. Novel biomarkers for the prediction and diagnosis of these irAEs, which primarily characterize patient immune function, represent an area of active investigation.

Immune Cell Subtypes and Cytokines in Lung Tumor Microenvironment: Influence of COPD

Background: The immune microenvironment plays a role in tumorigenesis. Chronic Obstructive Pulmonary Disease (COPD) is an independent risk factor for lung cancer (LC). We hypothesized that immune profile characterized by T regulatory (Treg), natural killer (NK), and plasma cells, as well as interleukin (IL)-10 and interferon-gamma, may differ within tumors of LC patients with/without COPD. Methods: Treg (anti-CD3 and anti-forkhead boxP3 antibodies), NK (anti-NCR1 antibody), IgG (anti-CD138-IgG antibody), IgA (anti-CD138-IgA antibody) using immunohistochemistry, and both IL-10 and interferon-gamma (ELISA) were quantified in tumor and non-tumor specimens (thoracotomy for lung tumor resection) from 33 LC–COPD patients and 20 LC-only patients. Results: Immune profile in tumor versus non-tumor specimens: Treg cell counts significantly increased in tumors of both LC and LC–COPD patients, while in tumors of the latter group, IgG-secreting plasma cells significantly decreased and IL-10 increased. No significant differences were seen in levels of NK cells, IgA-secreting cells, IgA/IgG, or interferon-gamma. Immune profile in tumors of LC–COPD versus LC: No significant differences were observed in tumors between LC–COPD and LC patients for any study marker. Conclusions: Immune cell subtypes and cytokines are differentially expressed in lung tumors, and the presence of COPD elicited a decline in IgG-secreting plasma cell levels but not in other cell types.