Blood Predictive Biomarkers for Patients With Non–small-cell Lung Cancer Associated With Clinical Response to Nivolumab

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.

Cancer-Associated Fibroblast-Derived IL-8 Upregulates PD-L1 Expression in Gastric Cancer Through the NF-κB Pathway

BACKGROUND

The expression of programmed death-ligand 1 (PD-L1) in tumor cells is a leading cause of tumor immune escape; however, the precise mechanism underlying the regulation of PD-L1 expression in gastric cancer (GC) cells remains unknown. In this study, we aimed to investigate the potential mechanism of cancer-associated fibroblasts (CAFs) regulating PD-L1 expression in GC cells.

METHODS

We evaluated the immunomodulatory effects of CAFs in GC cells in vitro via the transwell co-culture system, cytometric bead array, and Western blotting. We detected the role of interleukin (IL)-8 in affecting underlying pathways in GC cells via transfecting IL-8 small-interfering RNA (siRNA), and the protection effects of CAFs on GC cells exposed to CD8+ T cells via cytotoxicity assays.

RESULTS

The results revealed that CAFs upregulated PD-L1 expression of GC cells. IL-8 expression was increased after KATO III or MKN45 cells co-cultured with CAF. Additionally, CAF-derived IL-8 promoted PD-L1 expression in GC cells through the P38, JNK, and NF-κB pathways. Besides, repertaxin, an IL-8 receptors (CXCR1/2) inhibitor, reduced PD-L1 expression in GC cells by blocking the P38, JNK, and NF-κB pathways. Furthermore, the expressions of p-P38, p-JNK, and p-NF-κB decreased after GC cells co-cultured with siIL-8-treated CAF. Moreover, repertaxin attenuated the protection of CAFs to cancer cells that were resistant to CD8+ T-cell cytotoxicity, and improved the antibody effects of anti-PD-L1 facilitating CD8+ T-cell cytotoxicity by targeting IL-8.

CONCLUSION

Targeting CAF-derived IL-8 may defeat PD-L1 upregulation-mediated immune resistance in GC cells, which provides a novel approach to improve the immunotherapeutic efficacies of patients with GC.

Association of the Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) score with immune checkpoint inhibitor efficacy in patients with gastrointestinal and lung cancer

OBJECTIVE

This study aimed to conduct a comprehensive analysis, evaluating the prognostic significance of the baseline Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) Score in patients undergoing immune checkpoint inhibitor (ICI) therapy.

METHODS

A comprehensive search was performed across various databases, including PubMed, the Cochrane Library, EMBASE, and Google Scholar, until October 21, 2023, to compile relevant articles for analysis. The investigation encompassed diverse clinical outcomes, including overall survival (OS) and progression-free survival (PFS).

RESULTS

This analysis included a total of 15 articles, comprising 19 studies involving 3335 patients. Among the 19 studies, nine studies focused on NSCLC, and six studies were conducted on HCC. Pooled results revealed that patients with elevated ALI levels experienced prolonged OS (HR: 0.51, 95% CI: 0.37-0.70, p < 0.001) and extended PFS (HR: 0.61, 95% CI: 0.52-0.72, p < 0.001). Furthermore, a GRIm score > 1 was associated with reduced OS (HR: 2.07, 95% CI: 1.47-2.92, p < 0.001) and diminished PFS (HR: 1.78, 95% CI: 1.35-2.34, p < 0.001) in cancer patients receiving ICIs. Subgroup analysis indicated that ALI cutoff values of 18 exhibited enhanced predictive potential. Additionally, for HCC patients, those with HCC-GRIm score > 2 showed a substantially decreased risk of mortality compared to individuals with HCC-GRIm score ≤ 2 (HR: 2.63, 95% CI: 1.89-3.65, p < 0.001).

CONCLUSION

The ALI and GRIm score served as dependable prognostic indicators for patients undergoing ICI therapy in the context of cancer treatment.

Identification and validation of tryptophan metabolism-related lncRNAs in lung adenocarcinoma prognosis and immune response

BACKGROUND

Tryptophan (Trp) is an essential amino acid. Increasing evidence suggests that tryptophan metabolism plays a complex role in immune escape from Lung adenocarcinoma (LUAD). However, the role of long non-coding RNAs (lncRNAs) in tryptophan metabolism remains to be investigated.

METHODS

This study uses The Cancer Genome Atlas (TCGA)-LUAD dataset as the training cohort, and several datasets from the Gene Expression Omnibus (GEO) database are merged into the validation cohort. Genes related to tryptophan metabolism were identified from the Molecular Signatures Database (MSigDB) database and further screened for lncRNAs with Trp-related expression. Subsequently, a prognostic signature of lncRNAs related to tryptophan metabolism was constructed using Cox regression analysis, (Least absolute shrinkage and selection operator regression) and LASSO analysis. The predictive performance of this risk score was validated by Kaplan-Meier (KM) survival analysis, (receiver operating characteristic) ROC curves, and nomograms. We also explored the differences in immune cell infiltration, immune cell function, tumor mutational load (TMB), tumor immune dysfunction and exclusion (TIDE), and anticancer drug sensitivity between high- and low-risk groups. Finally, we used real-time fluorescence quantitative PCR, CCK-8, colony formation, wound healing, transwell, flow cytometry, and nude mouse xenotransplantation models to elucidate the role of ZNF8-ERVK3-1 in LUAD.

RESULTS

We constructed 16 tryptophan metabolism-associated lncRNA prognostic models in LUAD patients. The risk score could be used as an independent prognostic indicator for the prognosis of LUAD patients. Kaplan-Meier survival analysis, ROC curves, and risk maps validated the prognostic value of the risk score. The high-risk and low-risk groups showed significant differences in phenotypes, such as the percentage of immune cell infiltration, immune cell function, gene mutation frequency, and anticancer drug sensitivity. In addition, patients with high-risk scores had higher TMB and TIDE scores compared to patients with low-risk scores. Finally, we found that ZNF8-ERVK3-1 was highly expressed in LUAD tissues and cell lines. A series of in vitro experiments showed that knockdown of ZNF8-ERVK3-1 inhibited cell proliferation, migration, and invasion, leading to cell cycle arrest in the G0/G1 phase and increased apoptosis. In vivo experiments with xenografts have shown that knocking down ZNF8-ERVK3-1 can significantly inhibit tumor size and tumor proliferation.

CONCLUSION

We constructed a new prognostic model for tryptophan metabolism-related lncRNA. The risk score was closely associated with common clinical features such as immune cell infiltration, immune-related function, TMB, and anticancer drug sensitivity. Knockdown of ZNF8-ERVK3-1 inhibited LUAD cell proliferation, migration, invasion, and G0/G1 phase blockade and promoted apoptosis.

Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade

The paradigm of non-small cell lung cancer (NSCLC) treatment has been profoundly influenced by the development of immune checkpoint inhibitors (ICI), but the range of clinical responses observed among patients poses significant challenges. To date, analyses of tumor biopsies are the only parameter used to guide prognosis to ICI therapy. Tumor biopsies, however, are often difficult to obtain and tissue-based biomarkers are limited by intratumoral heterogeneity and temporal variability. In response, there has been a growing emphasis on the development of "liquid biopsy"‒ derived biomarkers, which offer a minimally invasive means to dynamically monitor the immune status of NSCLC patients either before and/or during the course of treatment. Here we review studies in which multiple blood-based biomarkers encompassing circulating soluble analytes, immune cell subsets, circulating tumor DNA, blood-based tumor mutational burden, and circulating tumor cells have shown promising associations with the clinical response of NSCLC patients to ICI therapy. These investigations have unveiled compelling correlations between the peripheral immune status of patients both before and during ICI therapy and patient outcomes, which include response rates, progression-free survival, and overall survival. There is need for rigorous validation and standardization of these blood-based assays for broader clinical application. Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. Further research aimed at longitudinal monitoring of circulating biomarkers is also crucial to comprehend immune dynamics and resistance mechanisms and should be used alongside tissue-based methods that interrogate the tumor microenvironment to guide treatment decisions and may inform on the development of novel therapeutic strategies. The data reviewed here reinforce the opportunity to refine patient stratification, optimize treatments, and improve outcomes not only in NSCLC but also in the wider spectrum of solid tumors undergoing immunotherapy.

Fever of unknown origin associated with immune checkpoint inhibitors

Since the approval for the treatment of melanoma in 2014, immune checkpoint inhibitors (ICIs) have revolutionized the therapy pattern across various malignancies. Coinciding with their frequent usage, their adverse effects, including fever, cannot be neglected. In the context of cancer diseases and cancer treatments, fever of unknown origin (FUO), which has long posed a challenge for clinicians in terms of diagnosis and management, brings forth new connotation and significance. In this paper review, we present the concept of ICIs-associated FUO, consider activated immune system and elevated cytokines as common mechanisms by which ICIs induce fever and various immune-related adverse events (irAEs), summarize and compare the primary etiologies of ICI-associated FUO, and compare it with conventional types of FUO.

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.

Combination of pembrolizumab and pelareorep promotes anti-tumour immunity in advanced pancreatic adenocarcinoma (PDAC)

BACKGROUND

We previously reported activity of pelareorep, pembrolizumab and chemotherapy. Patients developed new T-cell clones and increased peripheral T-cell clonality, leading to an inflamed tumour. To evaluate a chemotherapy-free regimen, this study assesses if pelareorep and pembrolizumab has efficacy by inducing anti-tumour immunological changes (NCT03723915).

METHODS

PDAC patients who progressed after first-line therapy, received iv pelareorep induction with pembrolizumab every 21-days. Primary objective is overall response rate. Secondary objectives included evaluation of immunological changes within tumour and blood.

RESULTS

Clinical benefit rate (CBR) was 42% amongst 12 patients. One patient achieved partial response (PR) and four stable disease (SD). Seven progressed, deemed non-responders (NR). VDAC1 expression in peripheral CD8+ T cells was higher at baseline in CBR than NR but decreased in CBR upon treatment. On-treatment peripheral CD4+ Treg levels decreased in CBR but not in NR. Analysis of tumour demonstrated PD-L1+ cells touching CD8+ T cells, and NK cells were more abundant post-treatment vs. baseline. A higher intensity of PD-L1 in tumour infiltrates at baseline, particularly in CBR vs. NR. Finally, higher levels of soluble (s)IDO, sLag3, sPD-1 observed at baseline among NR vs. CBR.

CONCLUSION

Pelareorep and pembrolizumab showed modest efficacy in unselected patients, although potential immune and metabolic biomarkers were identified to warrant further evaluation.

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.

Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has one of the highest mortality rates among solid cancers. Late diagnosis and a lack of efficacious treatment options contribute to the dismal prognosis of HCC. Immune checkpoint inhibitor (ICI)-based immunotherapy has presented a new milestone in the treatment of cancer. Immunotherapy has yielded remarkable treatment responses in a range of cancer types including HCC. Based on the therapeutic effect of ICI alone (programmed cell death (PD)-1/programmed death-ligand1 (PD-L)1 antibody), investigators have developed combined ICI therapies including ICI + ICI, ICI + tyrosine kinase inhibitor (TKI), and ICI + locoregional treatment or novel immunotherapy. Although these regimens have demonstrated increasing treatment efficacy with the addition of novel drugs, the development of biomarkers to predict toxicity and treatment response in patients receiving ICI is in urgent need. PD-L1 expression in tumor cells received the most attention in early studies among various predictive biomarkers. However, PD-L1 expression alone has limited utility as a predictive biomarker in HCC. Accordingly, subsequent studies have evaluated the utility of tumor mutational burden (TMB), gene signatures, and multiplex immunohistochemistry (IHC) as predictive biomarkers. In this review, we aim to discuss the current state of immunotherapy for HCC, the results of the predictive biomarker studies, and future direction.

Targeting programmed cell death protein 1 (PD-1) for treatment of non-small-cell lung carcinoma (NSCLC); the recent advances

The immune system uses various immune checkpoint axes to adjust responses, support homeostasis, and deter self-reactivity and autoimmunity. Nevertheless, non-small-cell lung carcinoma (NSCLC) can use protective mechanisms to facilitate immune evasion, which leads to potentiated cancer survival and proliferation. In this light, many blocking anti-bodies have been developed to negatively regulate checkpoint molecules, in particular, programmed cell death protein 1 (PD-1) / PD-ligand 1 (L1), and bypass these immune suppressive mechanisms. Meanwhile, anti-PD-1 anti-bodies such as nivolumab, pembrolizumab, cemiplimab, and sintilimab have shown excellent competence in successfully inspiring immune responses versus NSCLC. Accordingly, the United States Food and Drug Administration (FDA) has recently approved nivolumab (alone or in combination with ipilimumab) and pembrolizumab (alone or in combination with chemotherapy) as first-line treatment for advanced NSCLC patients. However, PD-1 blockade monotherapy remains inefficient in more than 60% of NSCLC patients, and many patients don't respond or acquire resistance to this modality. Also, toxicities related to anti-PD-1 anti-body have been progressively identified in clinical trials and oncology practice. Herein, we will outline the clinical benefits of PD-1 blockade therapy alone or in combination with other treatments (e.g., chemotherapy, radiotherapy, anti-angiogenic therapy) in NSCLC patients. Moreover, we will take a glimpse into the recently identified predictive biomarkers to determine patients most likely to suffer serious adverse events to decrease untoward toxicity risk and diminish treatment costs.

Soluble interleukin-2 receptor as a predictive biomarker for poor efficacy of combination treatment with anti-PD-1/PD-L1 antibodies and chemotherapy in non-small cell lung cancer patients

Soluble interleukin-2 receptor (sIL-2R) suppresses effector T-cells. Few studies have assessed serum sIL-2R in patients receiving immunotherapy. We evaluated the association between serum sIL-2R levels and the efficacy of anti-programmed cell death 1/ programmed death-ligand 1 (anti-PD-1/PD-L1) antibody combined with chemotherapy in non-small cell lung cancer (NSCLC) patients. We prospectively enrolled NSCLC patients who received anti-PD-1/PD-L1 antibody combined with platinum-based chemotherapy between 8/2019 and 8/2020 and measured their serum sIL-2R. The patients were divided into high and low sIL-2R groups based on the median of sIL-2R levels at pretreatment. Progression-free survival (PFS) and overall survival (OS) of patients in the high and low sIL-2R groups were compared. The Kaplan-Meier curves of PFS and OS were evaluated using the log-rank test. The multivariate analysis of PFS and OS was performed using the Cox proportional hazard models. Among 54 patients (median age 65, range 34-84), 39 were male and 43 had non-squamous cell carcinoma. The sIL-2R cut-off value was 533 U/mL. Median PFS was 5.1 months (95% CI, 1.8-7.5 months) and 10.1 months (95% CI, 8.3-not reached [NR] months) in the high and low sIL-2R groups (P = 0.007), respectively. Median OS was 10.3 months (95% CI, 4.0-NR months) and NR (95% CI, 10.3-NR months) in the high and low sIL-2R groups (P = 0.005), respectively. Multivariate Cox regression analysis showed that high sIL-2R was significantly associated with shorter PFS and OS. SIL-2R may be a biomarker for the poor efficacy of anti-PD-1/PD-L1 antibody combined with chemotherapy.

Interleukin 8 in plasma is an efficacy marker for advanced non-small cell lung cancer treated with hypofractionated radiotherapy and PD-1 blockade

BACKGROUND

Programmed death-1 (PD-1) blockade promotes combination therapy in advanced non-small cell lung cancer (NSCLC), hypofractionated radiotherapy (HFRT) and chemotherapy combined with immunotherapy improves the outcome of prognosis in advanced NSCLC, while effective biomarkers to follow prognostic efficacy are still to be found.

METHODS

We enrolled 44 NSCLC patients with HFRT combined with PD-1 blockade, 13 patients with chemotherapy combined with immunotherapy, additionally collected tissue samples from 8 patients with earlystage NSCLC without therapy, and peripheral whole blood from 16 healthy donors, detected the expression differences of cytokines Interleukin 6 (IL-6), Interleukin 8 (IL-8) and Interleukin 17A (IL-17A) in the peripheral plasma and tissues by flow cytometry, immunofluorescence, and real-time fluorescence quantitative PCR. Cultured peripheral blood mononuclear cell (PBMC) and tumor-infiltrating T cells with recombinant human IL-8 in vitro to observe the changes of immune memory T cell subtypes and apoptosis.

RESULTS

Our results show that IL-6, IL-8, and IL-17A are highly expressed in advanced NSCLC, high levels of IL-8 are significantly associated with poor prognosis in advanced NSCLC patients treated with HFRT + PD1 blockade, high circulating IL-8 in NSCLC increased apoptosis of effector memory RA (TemRA; CD45RA⁺CCR7^-) T cell subsets and CD8⁺ T cell subsets in tissues, resulting in decreased peripheral TemRA and stem cell-like memory T cells (TSCM: CD45RA ⁺CCR7 ⁺ CD95 ⁺) in tissue.

CONCLUSION

We suggest that IL-8 can impair immune memory function in NSCLC. It is a useful biomarker to evaluate the efficacy of HFRT + PD1 blockade in advanced NSCLC. Further exploration of easily available plasma biomarkers for personalized treatment of NSCLC is required.

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.

Correlation of preclinical and clinical biomarkers with efficacy and toxicity of cancer immunotherapy

Immune checkpoint inhibitors (ICIs) have revealed significant clinical values in different solid tumors and hematological malignancy, changing the landscape for the treatment of multiple types of cancer. However, only a subpopulation of patients has obvious tumor response and long-term survival after ICIs treatment, and many patients may experience other undesirable clinical features. Therefore, biomarkers are critical for patients to choose exact optimum therapy. Here, we reviewed existing preclinical and clinical biomarkers of immunotherapeutic efficacy and immune-related adverse events (irAEs). Based on efficacy prediction, pseudoprogression, hyperprogressive disease, or irAEs, these biomarkers were divided into cancer cell-derived biomarkers, tumor microenvironment-derived biomarkers, host-derived biomarkers, peripheral blood biomarkers, and multi-modal model and artificial intelligence assessment-based biomarkers. Furthermore, we describe the relation between ICIs efficacy and irAEs. This review provides the overall perspective of biomarkers of immunotherapeutic outcome and irAEs prediction during ICIs treatment.

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.

Interleukin-11: A Potential Biomarker and Molecular Therapeutic Target in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer and is a fast progressive disease when left untreated. Identification of potential biomarkers in NSCLC is an ongoing area of research that aims to detect, diagnose, and prognosticate patients early to optimize treatment. We review the role of interleukin-11 (IL11), a stromal-cell derived pleiotropic cytokine with profibrotic and cellular remodeling properties, as a potential biomarker in NSCLC. This review identifies the need for biomarkers in NSCLC, the potential sources of IL11, and summarizes the available information leveraging upon published literature, publicly available datasets, and online tools. We identify accumulating evidence suggesting IL11 to be a potential biomarker in NSCLC patients. Further in-depth studies into the pathophysiological effects of IL11 on stromal-tumor interaction in NSCLC are warranted and current available literature highlights the potential value of IL11 detection as a diagnostic and prognostic biomarker in NSCLC.

Changes in the Gustave Roussy Immune Score as a Powerful Prognostic Marker of the Therapeutic Sensitivity of Nivolumab in Advanced Gastric Cancer: A Multicenter, Retrospective Study

BACKGROUND

Identification of positive biomarkers for the effects of nivolumab on patients with advanced gastric cancer (AGC) is significant. The Gustave Roussy Immune Score (GRIm-s) is associated with therapeutic resistance of immune checkpoint inhibitors (ICIs) in other cancers. This multicenter, retrospective study was designed to analyze the association of GRIm-s with therapeutic sensitivity of nivolumab in patients with AGC.

METHODS

We reviewed 58 patients with AGC treated with nivolumab from October 2017 to November 2018 at five participating institutions. We performed blood tests before the start of nivolumab and after administration of two courses. We evaluated the correlation between the best overall response and GRIm-s. Additionally, we focused on the changes in GRIm-s before the start of nivolumab and after administration of two courses.

RESULTS

Of the 58 patients, 21 (36.2%) were classified into the disease control (DC) group and 37 (63.8%) into the progressive disease (PD) group. GRIm-s before nivolumab treatment did not correlate with the best therapeutic response (p = 0.086). However, GRIm-s after two courses of nivolumab showed that significantly more PD cases were in the high-risk group (p < 0.0001). After two courses of nivolumab, overall survival was significantly worse in the high-risk group (p < 0.0001). For progression-free survival, the high-risk group had a significantly worse prognosis both before (p = 0.04) and after two courses of nivolumab treatment (p < 0.0001).

CONCLUSIONS

GRIm-s after two courses of nivolumab and its changes compared to pretreatment values proved beneficial in predicting nivolumab sensitivity.

The Predictive Value of Pretreatment Lactate Dehydrogenase and Derived Neutrophil-to-Lymphocyte Ratio in Advanced Non-Small Cell Lung Cancer Patients Treated With PD-1/PD-L1 Inhibitors: A Meta-Analysis

Background

The Lung Immune Prognostic Index (LIPI) combines the lactate dehydrogenase (LDH) level and the derived neutrophil-to-lymphocyte ratio (dNLR). A lot of studies have shown that LDH and dNLR are associated with the prognosis of advanced non-small cell lung cancer (NSCLC) in patients treated with programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitors. However, previous results were inconsistent, and the conclusions remain unclear. This meta-analysis aimed to investigate the predictive value of pretreatment LDH and dNLR for NSCLC progression in patients treated with PD-1/PD-L1 inhibitors.

Methods

PubMed, Embase, and the Cochrane Library were searched by two researchers independently for related literature before March 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) for progression-free survival (PFS) and overall survival (OS) were extracted to assess the predictive value of LDH and dNLR. STATA 15. 0 was used to perform the meta-analysis.

Results

A total of 3,429 patients from 26 studies were included in this meta-analysis. The results revealed that high pretreatment LDH was related to poor OS (HR = 1.19, 95%CI = 1.11–1.24, p < 0.001), but not closely related to poor PFS (HR = 1.02, 95%CI = 1.00–1.04, p = 0.023 < 0.05). The pooled results for dNLR suggested that high pretreatment dNLR was related to poor OS (HR = 1.55, 95%CI = 1.33–1.80, p < 0.001) and PFS (HR = 1.33, 95%CI = 1.16–1.54, p < 0.001).

Conclusion

Both pretreatment LDH and dNLR have the potential to serve as peripheral blood biomarkers for patients with advanced NSCLC treated with PD-1/PD-L1 inhibitors. However, more studies on LDH are needed to evaluate its predictive value for PFS in patients with NSCLC.

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.

Three models that predict the efficacy of immunotherapy in Chinese patients with advanced non-small cell lung cancer

Background

Many tools have been developed to predict the efficacy of immunotherapy, such as lung immune prognostic index (LIPI), EPSILoN [Eastern Cooperative Oncology Group performance status (ECOG PS), smoking, liver metastases, lactate dehydrogenase (LDH), neutrophil‐to‐lymphocyte ratio (NLR)], and modified lung immune predictive index (mLIPI) scores. The aim of this study was to determine the ability of three predictive scores to predict the outcomes in Chinese advanced non‐small cell lung cancer (aNSCLC) patients treated with immune checkpoint inhibitors (ICIs).

Methods

We retrospectively analyzed 429 patients with aNSCLC treated with ICIs at our institution. The predictive ability of these models was evaluated using area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis. Calibration was assessed using the Hosmer–Lemeshow test (H–L test) and Spearman's correlation coefficient. Progression‐free survival (PFS) and overall survival (OS) curves were generated using the Kaplan–Meier method.

Results

The AUC values of LIPI, mLIPI, and EPSILoN scores predicting PFS at 6 months were 0.642 [95% confidence interval (CI):0.590–0.694], 0.720 (95% CI: 0.675–0.762), and 0.633 (95% CI: 0.585–0.679), respectively (p < 0.001 for all models). The AUC values of LIPI, mLIPI, and EPSILON scores predicting objective response rate (ORR) were 0.606 (95% CI: 0.546–0.665), 0.683 (95% CI: 0.637–0.727), and 0.666 (95% CI: 0.620–0.711), respectively (p < 0.001 for all models). The C‐indexes of LIPI, mLIPI, and EPSILoN scores for PFS were 0.627 (95% CI 0.611–6.643), 0.677 (95% CI 0.652–0.682), and 0.631 (95% CI 0.617–0.645), respectively.

Conclusions

As mLIPI scores had the highest accuracy when used to predict the outcomes in Chinese aNSCLC patients, this tool could be used to guide clinical immunotherapy decision‐making.

Tryptophan and Its Metabolites in Lung Cancer: Basic Functions and Clinical Significance

Lung cancer is the most lethal malignancy worldwide. Recently, it has been recognized that metabolic reprogramming is a complex and multifaceted factor, contributing to the process of lung cancer. Tryptophan (Try) is an essential amino acid, and Try and its metabolites can regulate the progression of lung cancer. Here, we review the pleiotropic functions of the Try metabolic pathway, its metabolites, and key enzymes in the pathogenic process of lung cancer, including modulating the tumor environment, promoting immune suppression, and drug resistance. We summarize the recent advance in therapeutic drugs targeting the Try metabolism and kynurenine pathway and their clinical trials.

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.

An Immune-Gene-Based Classifier Predicts Prognosis in Patients With Cervical Squamous Cell Carcinoma

Objective: Immunity plays a vital role in the human papilloma virus (HPV) persistent infection, and closely associates with occurrence and development of cervical squamous cell carcinoma (CSCC). Herein, we performed an integrated bioinformatics analysis to establish an immune-gene signature and immune-associated nomogram for predicting prognosis of CSCC patients. Methods: The list of immunity-associated genes was retrieved from ImmPort database. The gene and clinical information of CSCC patients were obtained from The Cancer Genome Atlas (TCGA) website. The immune gene signature for predicting overall survival (OS) of CSCC patients was constructed using the univariate Cox-regression analysis, random survival forests, and multivariate Cox-regression analysis. This signature was externally validated in GSE44001 cohort from Gene Expression Omnibus (GEO). Then, based on the established signature and the TCGA cohort with the corresponding clinical information, a nomogram was constructed and evaluated via Cox regression analysis, concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots and decision curve analyses (DCAs). Results: A 5-immune-gene prognostic signature for CSCC was established. Low expression of ICOS, ISG20 and high expression of ANGPTL4, SBDS, LTBR were risk factors for CSCC prognosis indicating poor OS. Based on this signature, the OS was significantly worse in high-risk group than in low-risk group (p-value < 0.001), the area under curves (AUCs) for 1-, 3-, 5-years OS were, respectively, 0.784, 0.727, and 0.715. A nomogram incorporating the risk score of signature and the clinical stage was constructed. The C-index of this nomogram was 0.76. AUC values were 0.811, 0.717, and 0.712 for 1-, 3-, 5-years OS. The nomogram showed good calibration and gained more net benefits than the 5-immune-gene signature and the clinical stage. Conclusion: The 5-immune-gene signature may serve as a novel, independent predictor for prognosis in patients with CSCC. The nomogram incorporating the signature risk score and clinical stage improved the predictive performance than the signature and clinical stage alone for predicting 1-year OS.

Pembrolizumab Alone or Combined With Chemotherapy in Advanced NSCLC With PD-L1 ≥50%: Results of a Retrospective Study

Objectives

Pembrolizumab plus platinum-based chemotherapy and pembrolizumab monotherapy (PM) both become standard of care in patients with advanced non-small-cell lung cancer (NSCLC) and a programmed death ligand 1 (PD-L1) tumor proportion score (TPS) greater than 50%. This study aimed to figure out the better treatment choice.

Method

In this retrospective analysis, we compared the clinical efficacy of PM and PC as first-line treatment in NSCLC patients with a PD-L1 ≥50% and negative for genomic alterations in the EGFR and ALK genes.

Result

Among the population, 115 patients received PC, and 91 patients received PM. Up to Dec 30, 2020, median follow-up was 17.13 months. The median progression-free survival (PFS) rates of PC and PM were 12.37 and 9.60 months (HR: 0.44, p < 0.001), respectively. The median overall survival (OS) rates were NE and 28.91 months (HR: 0.40, p = 0.005), respectively. Subgroup analysis found that the PFS benefit of PC was evident in most subgroups excepting patients with brain metastasis. The 1-year overall survival rates of PC and PM were 89.3% and 76.1%, respectively. The ORR was 61.7 and 46.9% (p = 0.004), respectively.

Conclusion

In patients with previously untreated, PD-L1 ≥50%, advanced NSCLC without EGFR or ALK mutations, the addition of pembrolizumab to standard platinum-based chemotherapy seems to be the preferred treatment, which needs to be validated by further prospective trials.

Second-line nivolumab in relapsed small-cell lung cancer: CheckMate 331☆

BACKGROUND

Patients with relapsed small-cell lung cancer (SCLC) have few treatment options and dismal survival. Phase I/II data show activity of nivolumab in previously treated SCLC.

PATIENTS AND METHODS

CheckMate 331 is a randomized, open-label, phase III trial of nivolumab versus standard chemotherapy in relapsed SCLC. Patients with relapse after first-line, platinum-based chemotherapy were randomized 1 : 1 to nivolumab 240 mg every 2 weeks or chemotherapy (topotecan or amrubicin) until progression or unacceptable toxicity. Primary endpoint was overall survival (OS).

RESULTS

Overall, 284 patients were randomized to nivolumab and 285 to chemotherapy. Minimum follow-up was 15.8 months. No significant improvement in OS was seen with nivolumab versus chemotherapy [median OS, 7.5 versus 8.4 months; hazard ratio (HR), 0.86; 95% confidence interval (CI), 0.72-1.04; P = 0.11]. A survival benefit with nivolumab was suggested in patients with baseline lactate dehydrogenase ≤ upper limit of normal and in those without baseline liver metastases. OS (nivolumab versus chemotherapy) was similar in patients with programmed death-ligand 1 combined positive score ≥1% versus <1%. Median progression-free survival was 1.4 versus 3.8 months (HR, 1.41; 95% CI, 1.18-1.69). Objective response rate was 13.7% versus 16.5% (odds ratio, 0.80; 95% CI, 0.50-1.27); median duration of response was 8.3 versus 4.5 months. Rates of grade 3 or 4 treatment-related adverse events were 13.8% versus 73.2%.

CONCLUSION

Nivolumab did not improve survival versus chemotherapy in relapsed SCLC. No new safety signals were seen. In exploratory analyses, select baseline characteristics were associated with improved OS for nivolumab.

Clinical correlates for immune checkpoint therapy: significance for CNS malignancies

Immune checkpoint inhibitors (ICIs) have revolutionized the field of cancer immunotherapy. Most commonly, inhibitors of PD-1 and CTLA4 are used having received approval for the treatment of many cancers like melanoma, non-small-cell lung carcinoma, and leukemia. In contrast, to date, clinical studies conducted in patients with CNS malignancies have not demonstrated promising results. However, patients with CNS malignancies have several underlying factors such as treatment with supportive medications like corticosteroids and cancer therapies including radiation and chemotherapy that may negatively impact response to ICIs. Although many clinical trials have been conducted with ICIs, measures that reproducibly and reliably indicate that treatment has evoked an effective immune response have not been fully developed. In this article, we will review the history of ICI therapy and the correlative biology that has been performed in the clinical trials testing these therapies in different cancers. It is our aim to help provide an overview of the assays that may be used to gauge immunologic response. This may be particularly germane for CNS tumors, where there is currently a great need for predictive biomarkers that will allow for the selection of patients with the highest likelihood of responding.

Complete response to immunotherapy combined with an antiangiogenic agent in multiple hepatic metastases after radical surgery for advanced gallbladder cancer: a case report

Most advanced gallbladder cancers (GBCa) are unresectable or metastatic once diagnosed, and even patients who undergo surgery have a high risk of recurrence and metastasis. Immunotherapy, especially immune checkpoint inhibitors (ICIs), combined with an antiangiogenic agent, is an emerging prospective treatment for GBCa. However, the efficacy and safety of this combination therapy have not yet been investigated. We report the case of a 70-year-old female patient with recurrent metastatic GBCa (stage IVB) after radical surgery. Immunohistochemical examination revealed that 10% of the tumor cells expressed programmed cell death protein-1 (PD-1) and programmed cell death receptor ligand 1 (PD-L1). Whole-exome sequencing showed cancer tissues with a low tumor mutational burden (TMB) and microsatellite stability (MSS). The patient received Camrelizumab (200 mg, every three weeks) and Apatinib (40 mg/d). The clinical and immunological responses were observed, and the patient achieved a complete response after five cycles. This is the first case describing the efficacy and safety of Camrelizumab plus Apatinib in a GBCa patient with weak PD-1 and PD-L1 expression, and low TMB and MSS. The treatment had a tolerable safety profile and a complete response in the patient. Also, we found that the cluster of differentiation (CD)16+CD56+natural killer (NK) cell ratio in peripheral blood was increased after the combined treatment. Immunotherapy with antiangiogenic drugs may be a potential treatment option for patients with recurrent GBC or GBCa.

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.

Nivolumab for Previously Treated Patients with Non-Small-Cell Lung Cancer-Daily Practice versus Clinical Trials

Based on the results of the CheckMate 017 and CheckMate 057 studies, nivolumab therapy has become a new standard treatment for both squamous and non-squamous non-small-cell lung cancer (NSCLC). However, due to the specific inclusion criteria of these clinical trials, the efficacy and safety of nivolumab in real-world practice were not certain. In general, the real-world results of nivolumab treatment have been consistent with those obtained in clinical trials. Additional analyses of the real-world data have made the identification of prognostic factors possible. Good performance status is the most significant predictor of clinical benefit. Brain metastases, liver metastases, EGFR mutation, malignant pleural effusion, and a high number of metastatic sites were identified as negative prognostic factors. By contrast, a longer time to disease progression (>6 months) from the beginning of prior chemotherapy and an objective response to chemotherapy seem to have positive prognostic value in the case of nivolumab treatment. In terms of patient age, the data are inconclusive. Some blood biomarkers can also be considered significant prognostic factors.

Profiles of Immune Infiltration and Prognostic Immunoscore in Lung Adenocarcinoma

Lung tissue is abundant with immune cells that form a powerful first defense against exotic particles and microbes. The malignant phenotype of lung adenocarcinoma (LUAD) is defined not only by intrinsic tumor cells but also by tumor-infiltrating immune cells (TIICs) recruited to the immune microenvironment. Understanding more about the immune microenvironment of LUAD could function in sorting out patients more likely with high risk and benefit from immunotherapy. Twenty-two types of TIICs were estimated based on large public LUAD cohorts from the TCGA and GEO datasets using the CIBERSORT algorithm. Then principal component analysis (PCA), meta-analysis, and single-sample gene set enrichment analysis (ssGSEA) were used to measure and evaluate the specific immune responses and relative mechanisms. Moreover, an immunoscore model based on the percent of immune cells was constructed via the univariate and multivariate Cox regression models, which provided an in-depth overview of the LUAD immune microenvironment and shed light on the immune regulatory mechanism. The differential expression genes (DEGs) were acquired based on the immunoscore model, and prognostic immune-related genes were further identified. GSEA and the protein–protein interaction network (PPI) further revealed that these genes were mostly enriched in many immune-related biological processes. It is hoped that this immune landscape could provide a more accurate understanding for LUAD development and tumor immune therapy.