Association of the neutrophil to lymphocyte ratio and clinical outcomes in patients with lung cancer receiving immunotherapy: a meta-analysis

Immune Checkpoint Inhibitor Score Predicts Survival Benefit of Immunotherapy in Patients with Non-small Cell Lung Cancer

BACKGROUND

The use of immune checkpoint inhibitors (ICIs) in patients with advanced lung cancer is increasing. Despite ongoing studies to predict the efficacy of ICIs, its use in clinical practice remains difficult. Thus, we aimed to discover a predictive marker by analyzing blood cell characteristics and developing a scoring system for patients treated with ICIs.

METHODS

This was a prospective multicenter study in patients with advanced nonsmall cell lung cancer (NSCLC) who received ICIs as second-line treatment from June 2021 to November 2022. Blood cell parameters in routine blood samples were evaluated using an automated hematology analyzer. Immune checkpoint inhibitor score (IChIS) was calculated as the sum of neutrophil count score and immature granulocyte score.

RESULTS

A total of 143 patients from four institutions were included. The treatment response was as follows: partial response, 8.4%; stable disease, 37.1%; and progressive disease, 44.8%. Median progression-free survival and overall survival after ICI treatment was 3.0 and 8.3 months, respectively. Median progression-free survival in patients with an IChIS of 0 was 4.0 months, which was significantly longer than 1.9 months in patients with an IChIS of 1 and 1.0 month in those with an IChIS of 2 (p=0.001). The median overall survival in patients with an IChIS of 0 was 10.2 months, which was significantly longer than 6.8 and 1.8 months in patients with an IChIS of 1 and 2, respectively (p<0.001).

CONCLUSION

Baseline IChIS could be a potential biomarker for predicting survival benefit of immunotherapy in NSCLC.

Radiomics nomogram for predicting chemo-immunotherapy efficiency in advanced non-small cell lung cancer

This study aimed to explore potential radiomics biomarkers in predicting the efficiency of chemo-immunotherapy in patients with advanced non-small cell lung cancer (NSCLC). Eligible patients were prospectively assigned to receive chemo-immunotherapy, and were divided into a primary cohort (n = 138) and an internal validation cohort (n = 58). Additionally, a separative dataset was used as an external validation cohort (n = 60). Radiomics signatures were extracted and selected from the primary tumor sites from chest CT images. A multivariate logistic regression analysis was conducted to identify the independent clinical predictors. Subsequently, a radiomics nomogram model for predicting the efficiency of chemo-immunotherapy was conducted by integrating the selected radiomics signatures and the independent clinical predictors. The receiver operating characteristic (ROC) curves demonstrated that the radiomics model, the clinical model, and the radiomics nomogram model achieved areas under the curve (AUCs) of 0.85 (95% confidence interval [CI] 0.78-0.92), 0.76 (95% CI 0.68-0.84), and 0.89 (95% CI 0.84-0.94), respectively, in the primary cohort. In the internal validation cohort, the corresponding AUCs were 0.93 (95% CI 0.86-1.00), 0.79 (95% CI 0.68-0.91), and 0.96 (95% CI 0.90-1.00) respectively. Moreover, in the external validation cohort, the AUCs were 0.84 (95% CI 0.72-0.96), 0.75 (95% CI 0.62-0.87), and 0.86 (95% CI 0.75-0.96), respectively. In conclusion, the radiomics nomogram provides a convenient model for predicting the effect of chemo-immunotherapy in advanced NSCLC patients.

Biomarkers to predict efficacy of immune checkpoint inhibitors in colorectal cancer patients: a systematic review and meta-analysis

Immune checkpoint inhibitors (ICIs) are approved to treat colorectal cancer (CRC) with mismatch-repair gene deficiency, but the response rate remains low. Value of current biomarkers to predict CRC patients' response to ICIs is unclear due to heterogeneous study designs and small sample sizes. Here, we aim to assess and quantify the magnitude of multiple biomarkers for predicting the efficacy of ICIs in CRC patients. We systematically searched MEDLINE, Embase, the Cochrane Library, and Web of Science databases (to June 2023) for clinical studies examining biomarkers for efficacy of ICIs in CRC patients. Random-effect models were performed for meta-analysis. We pooled odds ratio (OR) and hazard ratio (HR) with 95% confidence interval (CI) for biomarkers predicting response rate and survival. 36 studies with 1867 patients were included in systematic review. We found that a lower pre-treatment blood neutrophil-to-lymphocyte ratio (n=4, HR 0.37, 95%CI 0.21-0.67) predicts good prognosis, higher tumor mutation burden (n=10, OR 4.83, 95%CI 2.16-10.78) predicts response to ICIs, and liver metastasis (n=16, OR 0.32, 95%CI 0.16-0.63) indicates resistance to ICIs, especially when combined with VEGFR inhibitors. But the predictive value of tumor PD-L1 expression (n=9, OR 1.01, 95%CI 0.48-2.14) was insignificant in CRC. Blood neutrophil-to-lymphocyte ratio, tumor mutation burden, and liver metastasis, but not tumor PD-L1 expression, function as significant biomarkers to predict efficacy of ICIs in CRC patients. These findings help stratify CRC patients suitable for ICI treatments, improving efficacy of immunotherapy through precise patient management. (PROSPERO, CRD42022346716).

Dynamics of the neutrophil‑to‑lymphocyte ratio during lenvatinib treatment for unresectable hepatocellular carcinoma

Lenvatinib is an approved therapy for advanced hepatocellular carcinoma (HCC). Recently, immune checkpoint inhibitors have been approved as frontline chemotherapies for HCC, and the tumor immune microenvironment (TIME) has been demonstrated to significantly affect HCC treatment. The neutrophil-to-lymphocyte ratio (NLR) is associated with the TIME, and the dynamics of the NLR are associated with prognosis or treatment efficacy in various cancer types. The present study investigated the dynamics of the TIME using the NLR in 101 patients with HCC treated with lenvatinib. Immunostaining for CD8+ tumor-infiltrating lymphocytes (TILs) was also performed in 9 patients who underwent liver tumor biopsy prior to subsequent chemotherapy for progression or discontinuation due to adverse events on lenvatinib treatment. The NLR values measured at the start of treatment (SOT), after 1 month of treatment and after 3 months of treatment were 2.78±2.20, 2.61±1.86 and 2.66±2.36, respectively (P=0.733). Among the patients with no reduction in the initial dose, there was no significant difference between the NLR after 1 month (2.34±0.25) and that at the SOT (2.86±2.33) (P=0.613). In patients who achieved a complete or partial response, the NLR at the time of the best tumor response was 1.65±0.56, which was significantly lower than that at the SOT (2.05±0.78) (P=0.023). In patients who did not respond to lenvatinib, the NLR at the time of disease progression was 3.68±3.19, which was significantly higher than that at the SOT (2.78±1.79) (P=0.043). Overall, 5 out of the 6 patients who did not respond to lenvatinib had low CD8+ TIL counts at disease progression. Although the present study included a limited number of patients, the NLR was associated with the therapeutic effects of lenvatinib. These findings suggest the potential of lenvatinib as an immunomodulator.

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.

The correlation between systemic inflammatory markers and efficiency for advanced gastric cancer patients treated with ICIs combined with chemotherapy

Currently lacking research to explore the correlation between inflammatory markers and the efficacy of immune checkpoint inhibitors (ICIs) combined with chemotherapy in the treatment of advanced gastric cancer. This study is a retrospective study and included patients with advanced gastric cancer who receiving ICIs combined with chemotherapy from January 2020 to December 2022. We analysed the relationship between systemic inflammatory markers and the efficacy of ICIs combined chemotherapy and constructed a clinical prediction model. A nomogram was constructed based on the results of the bidirectional stepwise regression model. A total of 197 patients were enrolled in the training group, with a median follow-up period of time 26 months. Kaplan Meier analysis showed that the median OS of patients with low systemic immune-inflammatory index (SII) and low platelet to lymphocyte ratio (PLR) was superior to those with high SII and PLR. Univariate and multivariate Cox regression analysis showed that SII, NLR, PLR, and N stage as independent prognostic factors for OS. Adding SII to the conventional model improved the predictive ability of the 12-month OS. A total of 95 patients were included in the validation group, and external validation of the SII-based nomogram showed favourable predictive performance. Baseline SII, PLR, and N stage may serve as independent predictive factors for survival outcomes in advanced gastric cancer patients undergoing ICIs combined with chemotherapy. The SII-based nomogram can provide intuitive and accurate prognosis prediction of individual patients.

Heterogeneous characterization of neutrophilic cells in head and neck cancers

BACKGROUND

Neutrophilic cells are among the most abundant immune populations within the head and neck tumor microenvironment (TME) and harbor multiple mechanisms of immunosuppression. Despite these important features, neutrophilic cells may be underrepresented in contemporary studies that aim to comprehensively characterize the immune landscape of the TME due to discrepancies in tissue processing and analysis techniques. Here, we review the role of pathologically activated neutrophilic cells within the TME and pitfalls of various approaches used to study their frequency and function in clinical samples.

METHODS

The literature was identified by searching PubMed for "immune landscape" and "tumor immune microenvironment" in combination with keywords describing solid tumor malignancies. Key publications that assessed the immune composition of solid tumors derived from human specimens were included. The tumor and blood processing methodologies in each study were reviewed in depth and correlated with the reported abundance of neutrophilic cells.

RESULTS

Neutrophilic cells do not survive cryopreservation, and many studies fail to identify and study neutrophilic cell populations due to cryopreservation of clinical samples for practical reasons. Additional single-cell transcriptomic studies filter out neutrophilic cells due to low transcriptional counts.

CONCLUSIONS

This report can help readers critically interpret studies aiming to comprehensively study the immune TME that fail to identify and characterize neutrophilic cells.

Prognostic Biomarkers of Systemic Inflammation in Non-Small Cell Lung Cancer: A Narrative Review of Challenges and Opportunities

Non-small cell lung cancer (NSCLC) is a common malignancy and is associated with poor survival outcomes. Biomarkers of systemic inflammation derived from blood tests collected as part of routine clinical care offer prognostic information for patients with NSCLC that may assist clinical decision making. They are an attractive tool, as they are inexpensive, easily measured, and reproducible in a variety of healthcare settings. Despite the wealth of evidence available to support them, these inflammatory biomarkers are not yet routinely used in clinical practice. In this narrative review, the key inflammatory indices reported in the literature and their prognostic significance in NSCLC are described. Key challenges limiting their clinical application are highlighted, including the need to define the optimal biomarker of systemic inflammation, a lack of understanding of the systemic inflammatory landscape of NSCLC as a heterogenous disease, and the lack of clinical relevance in reported outcomes. These challenges may be overcome with standardised recording and reporting of inflammatory biomarkers, clinicopathological factors, and survival outcomes. This will require a collaborative approach, to which this field of research lends itself. This work may be aided by the rise of data-driven research, including the potential to utilise modern electronic patient records and advanced data-analysis techniques.

Cancer biomarkers: Emerging trends and clinical implications for personalized treatment

The integration of cancer biomarkers into oncology has revolutionized cancer treatment, yielding remarkable advancements in cancer therapeutics and the prognosis of cancer patients. The development of personalized medicine represents a turning point and a new paradigm in cancer management, as biomarkers enable oncologists to tailor treatments based on the unique molecular profile of each patient's tumor. In this review, we discuss the scientific milestones of cancer biomarkers and explore future possibilities to improve the management of patients with solid tumors. This progress is primarily attributed to the biological characterization of cancers, advancements in testing methodologies, elucidation of the immune microenvironment, and the ability to profile circulating tumor fractions. Integrating these insights promises to continually advance the precision oncology field, fostering better patient outcomes.

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.

Neutrophil to lymphocyte ratio may predict efficacy of anti-PD-1 inhibitors in advanced EGFR-mutant non-small cell lung cancer: retrospective cohort study

This study aimed to investigate the associations between the clinical characteristics and effectiveness of anti-PD-1 inhibitors in patients with EGFR-sensitive mutations, aiming to identify the potential subgroup of patients who might benefit from anti-PD-1 inhibitor treatment. Patients with advanced non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR)-sensitive mutations who received subsequent anti-PD-1 inhibitors in combination with chemotherapy/antiangiogenic agents or alone after progression to tyrosine kinase inhibitors (TKIs) were screened. Clinical characteristics, including hematological parameters, were investigated for potential correlations with clinical outcomes. Subgroup and multivariate analyses were used for further confirmation of the relationship. Kaplan-Meier curves and Cox survival regression models using the log-rank test were used for progression-free survival (PFS) and overall survival (OS) assessments between the groups. Multiple regression analysis was performed using the standard regression coefficient values. The Wilcoxon test was used for the analysis of the variation in NLR. P ≤ 0.05 was considered to indicate statistical significance. This study was a retrospective study. Twenty-two patients met the inclusion criteria and were included in the study. The median PFS was 3.05 months (95% CI, 2.9-10.2 months). The median OS was 7.30 months (95% CI, 5.2-18.1 months). PFS in low neutrophil to lymphocyte ratio (NLR ≤ 4) was significantly longer than high NLR (NLR > 4, 5.7 months versus 2.0 months, HR, 0.35, 95% CI, 0.08-0.63, P = 0.0083). The OS in the low NLR group was also significantly better than that in the high NLR group (OS, 21.3 months versus 5.0 months, HR, 0.33; 95% CI, 0.09-0.74; P = 0.0163). In the multivariate analysis, NLR was the only significant factor for OS benefits (β = 3.535, 95% CI, 1.175-10.636, P = 0.025). Further investigation revealed that front-line TKIs exposure may contribute to the elevation or decrease of NLR, and finally lead to different efficacy outcomes by anti-PD-1 inhibitors. The findings suggest that a portion of advanced NSCLC patients with low NLR characteristics (NLR ≤ 4), even those harboring EGFR-sensitive mutations, could benefit from anti-PD-1 inhibitors as further line treatment after progression to EGFR-TKIs.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

Mean Platelet Volume to Lymphocyte Ratio: A New Biomarker Predicting Response in Patients with Solid Tumors Treated with Nivolumab

Introduction

Although immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, identifying factors that predict treatment response remains a challenge in clinical practice. There is a need for biomarkers to identify patients who may not benefit from these treatments. It is crucial to identify a simple and cost-effective biomarker that can be easily incorporated into clinical practice. This study aims to investigate the mean platelet volume to lymphocyte ratio (MPVLR), as measured by a hemogram test, and median overall survival (mOS) in patients with cancer treated with nivolumab.

Methods

A total of 131 adult patients with metastatic cancer, including malignant melanoma (MM), renal cell carcinoma (RCC), non-small cell lung cancer (NSCLC), and head and neck cancer (HNC), were included in this study. Baseline demographics, ECOG (Eastern Cooperative Oncology Group) performance status, tumor type, and blood count parameters were recorded. Univariate and multivariate analyses were conducted to evaluate potential risk factors.

Results

The median age of the patients was 59.87 ± 11.97 years, and the median follow-up period was 20.20 months (IQR, 12.80-27.60). RCC (43.5%) and MM (25.9%) were the most common diagnoses. Patients with ECOG scores of 0-1 had a longer mOS than those with scores of 2-3 (mOS: 20.60 months [95% CI, 14.94-25.29] vs. 5.24 months [95% CI, 0-16.42], p < 0.001). Additionally, patients with lactate dehydrogenase (LDH) levels within the normal range had a longer mOS than those with high LDH levels (mOS: 24.54 months [95% CI, 14.13-34.96] vs. 13.10 months [95% CI, 4.49-21.72], p = 0.038). Patients with low MPVLR also had a longer mOS than those with high MPVLR (mOS: 33.70 months [95% CI, 25.99-41.42] vs. 11.07 months [95% CI, 6.89-15.24], p < 0.001). In the multivariate Cox regression analysis, high MPVLR, ECOG score of 2-3, and high LDH level were associated with shorter mOS (p < 0.001, p = 0.001, and p = 0.046, respectively).

Conclusion

This study demonstrates that MPVLR could serve as a novel biomarker for predicting response to nivolumab treatment. Incorporating MPVLR into clinical practice may aid in identifying patients who are less likely to benefit from the treatment.

The prognostic impact of KRAS, TP53, STK11 and KEAP1 mutations and their influence on the NLR in NSCLC patients treated with immunotherapy

BACKGROUND

PD-L1 expression is used to predict NSCLC response to ICIs, but its performance is suboptimal. The impact of KRAS mutations in these patients is unclear. Studies evaluating co-mutations in TP53, STK11 and KEAP1 as well as the NLR showed that they may predict the benefit of ICIs.

PATIENTS & METHODS

This is a retrospective study of patients with NSCLC treated with ICIs at the CHUM between July 2015 and June 2020. OS and PFS were compared using Kaplan-Meier and logrank methods. Co-mutations in TP53, STK11 and KEAP1 as well as the NLR were accounted for. ORR and safety were compared using Wald method.

RESULTS

From 100 patients with known KRAS status, 50 were mutated (KRASMut). Mutation in TP53, STK11 and KEAP1 were present, and their status known in, respectively, 19/40 (47.5 %), 8/39 (20.5 %) and 4/38 (10.5 %) patients. STK11Mut and KEAP1Mut were associated with shorter overall survival when compared with wild type tumors (respectively median OS of 3.3 vs 20.4, p = 0.0001 and 10.1 vs 17.7, p = 0.24). When KRAS status was compounded with STK11/KEAP1, KRASMut trended to a better prognosis in STK11+KEAP1WT tumors (median OS 21.1 vs 15.8 for KRASWT, p = 0.15), but not for STK11+/-KEAP1Mut tumors. The NLR was strongly impacted by STK11 (6.0Mutvs 3.6WT, p = 0.014) and TP53 (3.2Mutvs 4.8WT, p = 0.048), but not by KEAP1 or KRAS mutations.

CONCLUSION

STK11Mut and KEAP1Mut are adverse predictors of ICI therapy benefit. The NLR is strongly impacted by STK11Mut but not by KEAP1Mut, suggesting differences in their resistance mechanism. In STK11-KEAP1WT tumors, KRASMut seem associated with improved survival in NSCLC patients treated with ICIs.

MICROABSTRACT

Response of NSCLC to immunotherapy is not easily predictable. We conducted a retrospective study in 100 patients with NSCLC and a known KRAS status. By accounting for different co-mutations, KRAS mutation was found to be associated with a better median overall survival in STK11 and KEAP1 wild-type tumors (21.1 vs 15.8, p = 0.15). NLR was impacted by STK11, but not KEAP1 mutation, suggesting a difference in their resistance mechanism.

The neutrophil-to-lymphocyte ratio as a new prognostic factor in cancers: a narrative review

The increasing incidence of cancer globally has highlighted the significance of early diagnosis and improvement of treatment strategies. In the 19th century, a connection was made between inflammation and cancer, with inflammation recognized as a malignancy hallmark. The neutrophil-to-lymphocyte ratio (NLR), calculated from a complete blood count, is a simple and accessible biomarker of inflammation status. NLR has also been proven to be a prognostic factor for various medical conditions, including mortality classification in cardiac patients, infectious diseases, postoperative complications, and inflammatory states. In this narrative review, we aim to assess the prognostic potential of NLR in cancer. We will review recent studies that have evaluated the association between NLR and various malignancies. The results of this review will help to further understand the role of NLR in cancer prognosis and inform future research directions. With the increasing incidence of cancer, it is important to identify reliable and accessible prognostic markers to improve patient outcomes. The study of NLR in cancer may provide valuable insights into the development and progression of cancer and inform clinical decision-making.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Neoadjuvant immune checkpoint inhibitor therapy in resectable non-small cell lung cancer

Only a minority of lung cancers are resectable at diagnosis, and many of these will eventually relapse. Adjuvant chemotherapy in this setting has a modest survival advantage, and there is significant need for new approaches to improve cure rates. Checkpoint inhibitor immunotherapy has transformed the prognosis for advanced lung cancer, and is increasingly being used in the neoadjuvant setting alone, or in combination with cytotoxic chemotherapy. While this has demonstrated convincing improvements in event-free survival and pathologic response, questions remain over optimal duration of therapy, predictive and prognostic biomarkers, response assessment and combination with other modalities. In addition, these results must be considered in the context of recent positive studies of adjuvant immunotherapy. Here, we summarise preclinical context and clinical trials in this space, discuss areas of controversy and pitfalls, and consider future challenges.

Clinical utility of the pan-immune-inflammation value in breast cancer patients

Background

The newly discovered pan-immune-inflammation value (PIV) has been illustrated to have good prognostic value for cancer patient prognosis. However, the prognostic usefulness of PIV in breast cancer patients is unknown. As a result, to aid the clinic in providing a distinctive and trustworthy biomarker to better assess breast cancer patient's prognosis, we conducted this meta-analysis to investigate the relationship between PIV and the survival of breast cancer patients.

Methods

We conducted a systematic search of Pubmed, Embase, the Cochrane Library, and the CNKI databases to screen for eligible studies published up to April 2023. Outcomes included overall survival (OS), progression-free survival (PFS), and pathological complete response (pCR). The hazard ratio (HR) and the corresponding 95% confidence interval (CI) were used as the indicators. STATA 15.0 software was used to perform meta-analysis, sensitivity analysis, and publication bias analysis.

Results

A total of eight articles, involving 2953 patients, met the inclusion criteria and were included in this meta-analysis. The results showed that patients with higher PIV levels had a significantly shorter OS (HR: 2.045, 95% CI: 1.355-3.086, P = 0.001) and PFS (HR: 1.466, 95% CI: 1.163-1.848, P = 0.001). Besides, the PIV value was negatively correlated with the efficacy of neoadjuvant chemotherapy. Sensitivity analysis showed that the results of this study were reliable and stable.

Conclusions

PIV has a good prognostic value in breast cancer patients and is expected to be a prognostic biomarker for breast cancer.

Biomarkers for immune checkpoint inhibition in sarcomas - are we close to clinical implementation?

Sarcomas are a group of diverse and complex cancers of mesenchymal origin that remains poorly understood. Recent developments in cancer immunotherapy have demonstrated a potential for better outcomes with immune checkpoint inhibition in some sarcomas compared to conventional chemotherapy. Immune checkpoint inhibitors (ICIs) are key agents in cancer immunotherapy, demonstrating improved outcomes in many tumor types. However, most patients with sarcoma do not benefit from treatment, highlighting the need for identification and development of predictive biomarkers for response to ICIs. In this review, we first discuss United States (US) Food and Drug Administration (FDA)-approved and European Medicines Agency (EMA)-approved biomarkers, as well as the limitations of their use in sarcomas. We then review eight potential predictive biomarkers and rationalize their utility in sarcomas. These include gene expression signatures (GES), circulating neutrophil-to-lymphocyte ratio (NLR), indoleamine 2,3-dioxygenase (IDO), lymphocyte activation gene 3 (LAG-3), T cell immunoglobin and mucin domain-containing protein 3 (TIM-3), TP53 mutation status, B cells, and tertiary lymphoid structures (TLS). Finally, we discuss the potential for TLS as both a predictive and prognostic biomarker for ICI response in sarcomas to be implemented in the clinic.

Immunotherapy with PD-1 Inhibitor Nivolumab in Recurrent/Metastatic Platinum Refractory Head and Neck Cancers-Early Experiences from Romania and Literature Review

Prognosis in recurrent/metastatic head and neck squamous-cell carcinoma (HNSCC) refractory to platinum-based chemotherapy is poor, making therapy optimization a priority. Anti-programmed cell death protein 1 (anti-PD-1) monoclonal antibody Nivolumab was approved in such cases. We present the early experience with Nivolumab immunotherapy at three cancer clinics from south and northeast Romania, aiming to describe the main characteristics and outcomes relative to literature reports, and to suggest patient selection criteria. Diagnostic, clinical, biological, therapeutic, and outcomes-related data from January 2020 until March 2023 were analyzed retrospectively. Eighteen patients with platinum refractory HNSCC (85.7% men, median age 58.9) were administered Nivolumab for 1-14 months (median 5.6 months) in addition to other treatments (surgery, radiotherapy, chemotherapy), and monitored for up to 25 months. Median neutrophil-to-lymphocyte ratio (NLR) ranged from 2.72 initially to 6.01 during treatment. Overall survival (OS) was 16 months, and patients who died early had the sharpest NLR increases (13.07/month). There were no severe immune-related adverse events. Lower NLR values and combined intensive chemotherapy, radiotherapy, and immunotherapy were related to better outcomes. To our knowledge, we also report the first two cases of second primary malignancy (SPM) in the head and neck region treated with Nivolumab in Romania (for which the sequential administration of radiotherapy and immunotherapy seems better). The work of other Romanian authors on the role of HPV status in HNC is also discussed. Multi-center trials are needed in order to investigate and confirm these observations.

Using Artificial Intelligence to Identify Tumor Microenvironment Heterogeneity in Non-Small Cell Lung Cancers

Lung cancer heterogeneity is a major barrier to effective treatments and encompasses not only the malignant epithelial cell phenotypes and genetics but also the diverse tumor-associated cell types. Current techniques used to investigate the tumor microenvironment can be time-consuming, expensive, complicated to interpret, and often involves destruction of the sample. Here we use standard hematoxylin and eosin-stained tumor sections and the HALO AI nuclear phenotyping software to characterize 6 distinct cell types (epithelial, mesenchymal, macrophage, neutrophil, lymphocyte, and plasma cells) in both murine lung cancer models and human lung cancer samples. CD3 immunohistochemistry and lymph node sections were used to validate lymphocyte calls, while F4/80 immunohistochemistry was used for macrophage validation. Consistent with numerous prior studies, we demonstrated that macrophages predominate the adenocarcinomas, whereas neutrophils predominate the squamous cell carcinomas in murine samples. In human samples, we showed a strong negative correlation between neutrophils and lymphocytes as well as between mesenchymal cells and lymphocytes and that higher percentages of mesenchymal cells correlate with poor prognosis. Taken together, we demonstrate the utility of this AI software to identify, quantify, and compare distributions of cell types on standard hematoxylin and eosin-stained slides. Given the simplicity and cost-effectiveness of this technique, it may be widely beneficial for researchers designing new therapies and clinicians working to select favorable treatments for their patients.

Peripheral CD4 memory T cells predict the efficacy of immune checkpoint inhibitor therapy in patients with non-small cell lung cancer

Immune checkpoint inhibitors have significantly improved the prognosis in patients with non-small cell lung cancer, compared with cytotoxic agents. However, the prediction of treatment response is often difficult, even after assessing the tumor programmed death-ligand 1 expression. We conducted this observational study to analyze the association between the differentiation of peripheral CD4 + T cells and the efficacy of immune checkpoint inhibitor therapy. We enrolled patients who were diagnosed with non-small cell lung cancer and received immune checkpoint inhibitor therapy between 2020 and 2022. Blood samples were collected at the start of immune checkpoint inhibitor therapy, and the expressions of PD-1, CCR7, and CD45RA in peripheral CD4 + T cells were analyzed by flow cytometry. The association between the findings of flow cytometry and survival after the initiation of the immune checkpoint inhibitor therapy was evaluated. Forty patients with non-small cell lung cancer were enrolled. The Cox proportional hazards model showed that an increased proportion of CD45RA-CD4 + T cells was associated with a reduced risk of progression after adjustment for performance status, tumor programmed death-ligand 1 expression level, mutation status of the epidermal growth factor receptor gene, and combined therapy with cytotoxic agents. The present study showed that the proportion of peripheral CD45RA- CD4 + T cells was associated with progression-free survival after the initiation of immune checkpoint inhibitor therapy, independent of several clinical factors.

Biomarkers for Predicting Anti-Programmed Cell Death-1 Antibody Treatment Effects in Head and Neck Cancer

In recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC), survival outcomes are significantly better in patients who receive anti-programmed cell death-1 (PD-1) monoclonal antibody therapy than in those who receive standard therapy. However, there is no established biomarker that can predict the anti-PD-1 antibody treatment effect and immune-related adverse events (irAEs) in these patients. This study investigated the inflammatory and nutritional status in 42 patients with R/M-HNSCC and programmed cell death ligand-1 (PD-L1) polymorphisms (rs4143815 and rs2282055) in 35 of the 42 patients. The 1- and 2-year overall survival was 59.5% and 28.6%, respectively; the 1- and 2-year first progression-free survival was 19.0% and 9.5%, respectively, and the respective second progression-free survival was 50% and 27.8%. Performance status and inflammatory and nutritional status (assessed by the geriatric nutritional risk index, modified Glasgow prognostic score, and prognostic nutritional index) were identified as significant indicators of survival outcomes in multivariate analysis. Patients with ancestral alleles in PD-L1 polymorphisms had less frequent irAEs. Performance status and inflammatory and nutritional status before treatment were closely related to survival outcomes after PD-1 therapy. These indicators can be calculated using routine laboratory data. PD-L1 polymorphisms may be biomarkers for predicting irAEs in patients receiving anti-PD-1 therapy.

Nivolumab or Atezolizumab in the Second-Line Treatment of Advanced Non-Small Cell Lung Cancer? A Prognostic Index Based on Data from Daily Practice

BACKGROUND

The efficacy of nivolumab and atezolizumab in advanced pre-treated NSCLC was documented in prospective trials. We aim to confirm the benefits and indicate predictive factors for immunotherapy in daily practice.

METHODS

This study was a retrospective analysis. The median PFS and OS were estimated using the Kaplan-Meier method. The log-rank test was used for comparisons. Multivariate analyses were performed using the Cox regression method.

RESULTS

A total of 260 patients (ECOG 0-1) with advanced NSCLC (CS III-IV) were eligible to receive nivolumab or atezolizumab as second-line treatment. Median PFS and OS were three months (95% confidence interval [CI] 2.57-3.42) and 10 months (95% CI 8.03-11.96), respectively, for the overall population. The median OS for the atezolizumab arm was eight months (95% CI 5.89-10.1), while for the nivolumab group, it was 14 months (95% CI 10.02-17.97) (p = 0.018). The sum of all measurable changes >100.5 mm (p = 0.007; HR = 1.003, 95% CI 1.001-1.005), PLT > 281.5 G/l (p < 0.001; HR = 1.003, 95% CI 1.001-1.003) and bone metastases (p < 0.004; HR = 1.58, 95% CI 1.04-2.38) were independent negative prognostic factors for OS in multivariate analysis. Based on preliminary analyses, a prognostic index was constructed to obtain three prognostic groups. Median OS in the subgroups was 16 months (95% CI 13.3-18.7), seven months (95% CI 4.83-9.17) and four months (95% CI 2.88-5.13), respectively (p < 0.001).

CONCLUSIONS

Nivolumab and atezolizumab provided clinical benefit in real life. Clinical and laboratory factors may help to identify subgroups likely to benefit. The use of prognostic indices may be valuable in clinical practice.

Systemic inflammation shapes clinical outcomes in response to immune checkpoint blockade treatment: moving toward optimizing antitumor immunity

BACKGROUND

Immune checkpoint blockade (ICB) treatment may induce durable disease remission, but only in a minority of patients with cancer. One important question is how to identify patients who may benefit from ICB treatment. ICB treatment relies on unleashing patients' pre-existing immune responses. Focusing on the key components of immune response, this study proposes the neutrophil-to-lymphocyte ratio (NLR) as a simplified indicator of patients' immune status to predict ICB treatment outcomes.

METHODS

This study analyzed a large pan-cancer cohort of 16 cancer types, including 1714 patients with cancer who received ICB treatment. Clinical outcomes in response to ICB treatment were measured by overall survival (OS), progression-free survival (PFS), objective response rate, and clinical benefit rate. The non-linear relationships of NLR with OS and PFS were investigated by a spline-based multivariate Cox regression model. A total of 1000 randomly resampled cohorts were bootstrapped to estimate the variability and reproducibility of NLR-related ICB responses.

RESULTS

By interrogating a clinically representative cohort, this study revealed a previously unreported finding that the pretreatment NLR levels were associated with ICB treatment outcomes in a U-shaped dose-dependent manner rather than a linear manner. An NLR range between 2.0 and 3.0 was remarkably associated with optimal ICB treatment outcomes, including increased patient survival, delayed disease progression, improved treatment response, and significant clinical benefit. Comparatively, either decreasing (< 2.0) or increasing (>3.0) NLR levels were indicators of worse ICB treatment outcomes. Furthermore, this study presents a comprehensive landscape of NLR-related ICB treatment outcomes across different patient populations defined by demographics, baseline characteristics, treatment, cancer-type-specific ICB responsiveness, and individual cancer type.

CONCLUSIONS

The NLR range from 2.0 to 3.0 might indicate an optimal balance between innate (neutrophils) and adaptive (lymphocytes) immune responses that potentiates antitumor immunity, which was observed in only 18.6% of patients. A majority of patients showed decreasing NLR (<2.00; 10.9% patients) or increasing NLR (>3.00; 70.5% patients), representing two distinct types of immune dysregulation associated with ICB resistance. This study translates routine blood tests into a precision medicine-based approach to immunotherapy, with important implications for clinicians in clinical decision-making as well as for regulatory agencies in drug approvals.

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.

Effect of Cancer-Related Cachexia and Associated Changes in Nutritional Status, Inflammatory Status, and Muscle Mass on Immunotherapy Efficacy and Survival in Patients with Advanced Non-Small Cell Lung Cancer

Immune checkpoint inhibitor (ICI)-based immunotherapy has significantly improved the survival of patients with advanced non-small cell lung cancer (NSCLC); however, a significant percentage of patients do not benefit from this approach, and predictive biomarkers are needed. Increasing evidence demonstrates that cachexia, a complex syndrome driven by cancer-related chronic inflammation often encountered in patients with NSCLC, may impair the immune response and ICI efficacy. Herein, we carried out a prospective study aimed at evaluating the prognostic and predictive role of cachexia with the related changes in nutritional, metabolic, and inflammatory parameters (assessed by the multidimensional miniCASCO tool) on the survival and clinical response (i.e., disease control rate) to ICI-based immunotherapy in patients with advanced NSCLC. We included 74 consecutive patients. Upon multivariate regression analysis, we found a negative association between IL-6 levels (odds ratio (OR) = 0.9036; 95%CI = 0.8408-0.9711; p = 0.0025) and the miniCASCO score (OR = 0.9768; 95%CI = 0.9102-0.9999; p = 0.0310) with the clinical response. As for survival outcomes, multivariate COX regression analysis found that IL-6 levels and miniCASCO-based cachexia severity significantly affected PFS (hazard ratio (HR) = 1.0388; 95%CI = 1.0230-1.0548; p < 0.001 and HR = 1.2587; 95%CI = 1.0850-1.4602; p = 0.0024, respectively) and OS (HR = 1.0404; 95%CI = 1.0221-1.0589; p < 0.0001 and HR = 2.3834; 95%CI = 1.1504-4.9378; p = 0.0194, respectively). A comparison of the survival curves by Kaplan-Meier analysis showed a significantly lower OS in patients with cachexia versus those without cachexia (p = 0.0323), as well as higher miniCASCO-based cachexia severity (p = 0.0428), an mGPS of 2 versus those with a lower mGPS (p = 0.0074), and higher IL-6 levels (>6 ng/mL) versus those with lower IL-6 levels (≤6 ng/mL) (p = 0.0120). In conclusion, our study supports the evidence that cachexia, with its related changes in inflammatory, body composition, and nutritional parameters, is a key prognostic and predictive factor for ICIs. Further larger studies are needed to confirm these findings and to explore the potential benefit of counteracting cachexia to improve immunotherapy efficacy.

Liquid biopsy approaches to capture tumor evolution and clinical outcomes during cancer immunotherapy

Circulating cell-free tumor DNA (ctDNA) can serve as a real-time biomarker of tumor burden and provide unique insights into the evolving molecular landscape of cancers under the selective pressure of immunotherapy. Tracking the landscape of genomic alterations detected in ctDNA may reveal the clonal architecture of the metastatic cascade and thus improve our understanding of the molecular wiring of therapeutic responses. While liquid biopsies may provide a rapid and accurate evaluation of tumor burden dynamics during immunotherapy, the complexity of antitumor immune responses is not fully captured through single-feature ctDNA analyses. This underscores a need for integrative studies modeling the tumor and the immune compartment to understand the kinetics of tumor clearance in association with the quality of antitumor immune responses. Clinical applications of ctDNA testing in patients treated with immune checkpoint inhibitors have shown both predictive and prognostic value through the detection of genomic biomarkers, such as tumor mutational burden and microsatellite instability, as well as allowing for real-time monitoring of circulating tumor burden and the assessment of early on-therapy responses. These efforts highlight the emerging role of liquid biopsies in selecting patients for cancer immunotherapy, monitoring therapeutic efficacy, determining the optimal duration of treatment and ultimately guiding treatment selection and sequencing. The clinical translation of liquid biopsies is propelled by the increasing number of ctDNA-directed interventional clinical trials in the immuno-oncology space, signifying a critical step towards implementation of liquid biopsies in precision immuno-oncology.

Depression in association with neutrophil-to-lymphocyte, platelet-to-lymphocyte, and advanced lung cancer inflammation index biomarkers predicting lung cancer survival

Lung cancer is a product of inflammation and a dysfunctional immune system, and depression has similar dysregulation. Depression disproportionately affects lung cancer patients, having the highest rates of all cancers. Systemic inflammation and depression are both predictive of non-small cell lung cancer (NSCLC) survival, but the existence and extent of any co-occurrence is unknown. Studied is the association between systemic inflammation ratio (SIR) biomarker levels and patients' depressive symptoms, with the hypothesis that depression severity would be significantly associated with prognostically poor inflammation. Newly diagnosed stage-IV non-small cell lung cancer (NSCLC; N = 186) patients were enrolled (ClinicalTrials.gov Identifier: NCT03199651) and blood draws and depression self-reports (Patient Health Questionnaire-9) were obtained. For SIRs, cell counts of neutrophils (N), lymphocytes (L), and platelets (P) were abstracted for ratio (R) calculations for NLR, PLR, and the Advanced Lung cancer Inflammation Index (ALI). Patients were followed and biomarkers were tested as predictors of 2-year overall survival (OS) to confirm their relevance. Next, multivariate linear regressions tested associations of depression with NLR, PLR, and ALI. Overall 2-year mortality was 61% (113/186). Cox model analyses confirmed higher NLR [hazard ratio (HR) = 1.91; p = 0.001] and PLR (HR = 2.08; p<0.001), along with lower ALI (HR = 0.53; p = 0.005), to be predictive of worse OS. Adjusting for covariates, depression was reliably associated with biomarker levels (p ≤ 0.02). Patients with moderate/severe depressive symptoms were 2 to 3 times more likely to have prognostically poor biomarker levels. Novel data show patients' depressive symptoms were reliably associated with lung-relevant systemic inflammation biomarkers, all assessed at diagnosis/pretreatment. The same SIRs were found prognostic for patients' 2-year OS. Intensive study of depression, combined with measures of cell biology and inflammation is needed to extend these findings to discover mechanisms of depression toxicity for NSCLC patients' treatment responses and survival.

Efficacy of Immunotherapy in Second-Line Treatment of KRAS-Mutated Patients with Non-Small-Cell Lung Cancer-Data from Daily Practice

Background The implementation of next-generation sequencing (NGS) into daily practice allows for the identification of a greater number of molecular abnormalities. We aimed to confirm the benefits of immunotherapy in the group of patients with KRAS aberrations treated within clinical practice. Methods This study was a retrospective analysis of the patients (pts) treated in routine practice within the National Drug Programme in Poland. The NGS was performed using a FusionPlex Comprehensive Thyroid and Lung (CTL) kit (ArcherDx) and sequenced using a MiniSeq (Illumina). The analyses were performed with the R language environment, version 4.1.3. Results A total of 96 pts with chemotherapy-pre-treated advanced NSCLC (CS III−IV) were qualified for nivolumab or atezolizumab treatment following a molecular diagnosis by the NGS and the exclusion of EGFR and ALK gene abnormalities. A mutation in the KRAS gene was found in 26 patients (27%); among them, the variant p.Gly12Cyc (G12C) was the most common (42%). The median PFS and OS for the overall population were 2 months (95% CI: 1.8−2.75) and 10 months (95% CI: 6.9−16.2), respectively. No differences were observed in terms of the mPFS between the KRAS-mutated and KRAS wild-type (WT) patients. A trend toward a longer OS was observed in the group of patients with the KRAS mutation, but the difference was not statistically significant (p = 0.43). In the multivariate analysis, the presence of mutations in the KRAS gene had no prognostic significance, while the occurence of grade 3 toxicity and the neutrophil-to-lymphocyte ratio (NLR) > 3.5 were found as statistically significant factors. Conclusions Immunotherapy in the second-line treatment of advanced NSCLC allows for a benefit regardless of the KRAS gene mutation status. The treatment sequence, including molecularly targeted drugs such as sotorasib and adagrasib, is still discussed. The NGS is a valuable method to identify a variety of molecular abnormalities in patients with NSCLC in daily practice.

Combination of Baseline and Variation of Prognostic Nutritional Index Enhances the Survival Predictive Value of Patients With Advanced Non-Small Cell Lung Cancer Treated With Programmed Cell Death Protein 1 Inhibitor

BACKGROUND

Low baseline prognostic nutritional index (PNI) scores are associated with poor survival for various malignancies; however, they vary based on the cohort and time resulting in inaccurate results. We determined the predictive value of the PNI score variations in addition to the baseline PNI scores for patients with advanced non-small cell lung cancer (NSCLC) who received programmed cell death protein 1 (PD-1) inhibitor.

METHODS

We retrospectively analysed 115 patients with advanced NSCLC who received PD-1 inhibitor. The median follow-up period was 28 months. Patients were clustered into four groups based on the combined PNI scores (combination of baseline and variation of PNI scores): ΔPNI-L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups. For instance, if PNI scores of patients with high baseline PNI score increased from baseline to 6 weeks after treatment, they were included in the ΔPNI-H-H subgroup. Cox regression models were used to identify the factors associated with survival.

RESULTS

The baseline PNI score was only related to the overall survival (OS) (P = .026), and not to the overall response rate (ORR) (P = .299) and progression-free survival (PFS) (P = .207). The ORR was associated with the combined PNI scores (P = .017). A multivariable Cox regression analysis confirmed that the combined PNI scores were independent factors for PFS (ΔPNI-L-H, 12 months, hazard ratio [HR] = 0.449, P = .009; ΔPNI-H-L, 14 months, HR = 0.500, P = .019; and ΔPNI-H-H, 17 months, HR = 0.390, P = .012; vs ΔPNI-L-L, 8 months) and OS (ΔPNI-L-H, 27 months, HR = 0.403, P = .019; ΔPNI-H-L, 28 months, HR = 0.369, P = .010; and ΔPNI-H-H, not reached, HR = 0.087, P = .002; vs ΔPNI-L-L, 15 months).

CONCLUSIONS

Patients with high baseline PNI and increased PNI score had the better survival outcome. On dynamic monitoring and comprehensive assessment, the combined PNI scores significantly enhanced the survival predictive ability of patients with NSCLC treated with PD-1 inhibitor.

Focus on the Dynamics of Neutrophil-to-Lymphocyte Ratio in Cancer Patients Treated with Immune Checkpoint Inhibitors: A Meta-Analysis and Systematic Review

Background: A number of studies have reported an association between the dynamics of neutrophil-to-lymphocyte ratio (NLR) and clinical efficacy in patients treated with immune checkpoint inhibitors (ICIs), but there is still a lack of a meta-analysis or systematic review. Methods: PubMed, Embase, Web of Science, and the Cochrane Library were searched until September 2022 for studies reporting on the association between the change in NLR after ICI treatment and clinical outcomes. Outcome measures of interest included: change in NLR before and after treatment, overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). Results: A total of 4154 patients in 38 studies were included. The pooled percentage of patients with increased NLR was 49.7% (95CI%: 43.7−55.8%). Six studies discussing the change in NLR in patients with different tumor responses all showed that the NLR level in patients without response to immunotherapy may increase after ICI treatment. The upward trend in NLR was associated with shorter OS (pooled HR: 2.05, 95%CI: 1.79−2.35, p < 0.001) and PFS (pooled HR: 1.89, 95%CI: 1.66−2.14, p < 0.001) and higher ORR (pooled OR: 0.27, 95%CI: 0.19−0.39, p < 0.001), and downward trend in NLR was associated with longer OS (pooled HR: 0.49, 95%CI: 0.42−0.58, p < 0.001) and PFS (pooled HR: 0.55, 95%CI: 0.48−0.63, p < 0.001) and lower ORR (pooled OR: 3.26, 95%CI: 1.92−5.53, p < 0.001). In addition, post-treatment high NLR was associated with more impaired survival than baseline high NLR (pooled HR of baseline high NLR: 1.82, 95%CI: 1.52−2.18; pooled HR of post-treatment high NLR: 2.93, 95%CI: 2.26−3.81), but the NLR at different time points may have a similar predictive effect on PFS (pooled HR of baseline high NLR: 1.68, 95%CI: 1.44−1.97; pooled HR of post-treatment high NLR: 2.00, 95%CI: 1.54−2.59). Conclusions: The NLR level of tumor patients after ICI treatment is stable overall, but the NLR level in patients without response to immunotherapy may increase after ICI treatment. Patients with an upward trend in NLR after ICI treatment were associated with worse clinical outcomes; meanwhile, the downward trend in NLR was associated with better clinical outcomes. Post-treatment high NLR was associated with more impaired survival than baseline high NLR.

The Predictive Value of Systemic Inflammatory Factors in Advanced, Metastatic Esophageal Squamous Cell Carcinoma Patients Treated with Camrelizumab

Objective

Systemic inflammatory factors are independent risk factors in the formation and progression of various solid tumors. However, whether systemic inflammatory factors are associated with effect and prognosis of esophageal squamous cell carcinoma patients treated with immunotherapy remains unknown. The aim of this study is to assess the value of systemic inflammatory factors in the efficacy of camrelizumab for patients with advanced, metastatic esophageal squamous cell carcinoma.

Methods

We conducted a retrospective analysis of 90 patients with advanced, metastatic esophageal squamous cell carcinoma who received treatment with camrelizumab in Xinghua People's Hospital between August 2019 and October 2021. The optimal cut-off values of platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) for predicting efficacy and prognosis were identified based on the receiver operating characteristic (ROC) curve. Progression free survival (PFS) and overall survival (OS) were evaluated using the Kaplan-Meier method, and differences in PFS or OS between groups were compared by the Log rank test. Univariate and multivariate Cox proportional hazards regression models were performed to analyze prognostic values of each variable.

Results

The optimal cutoff values of PLR, NLR and SII predicted survival outcomes were 157.7, 3.84 and 750.8, respectively. Higher PLR, NLR and SII were associated with shorter PFS (HR for PLR = 2.899, P = 0.001; HR for NLR = 3.629, P < 0.001; HR for SII = 10.251, P < 0.001) and OS (HR for PLR = 4.583, P < 0.001; HR for NLR = 3.921, P < 0.001; HR for SII = 38.606, P < 0.001). Multivariate Cox regression analysis revealed that high PLR, NLR and SII were independent risk factors of PFS and OS in the advanced, metastatic esophageal squamous cell carcinoma patients receiving camrelizumab.

Conclusion

PLR, NLR and SII are potentially effective prognostic predictors in advanced, metastatic esophageal squamous cell carcinoma patients treated with camrelizumab.

Blood Based Biomarkers as Predictive Factors for Hyperprogressive Disease

Purpose: With the widespread use of immunotherapy agents, we encounter treatment responses such as hyperprogression disease (HPD) that we have not seen with previous standard chemotherapy and targeted therapies. It is known that survival in patients with HPD is shorter than in patients without HPD. Therefore, it is important to know the factors that will predict HPD. We aimed to identify HPD-related factors in patients treated with immunotherapy. Methods: A total of 121 adult metastatic cancer patients treated with immunotherapy for any cancer were included. Baseline demographics, the ECOG performance status, type of tumors and baseline blood count parameters were recorded. Possible predisposing factors were evaluated with univariate and multivariate analyses. Results: The median age was 62.28 (interquartile range (IQR) 54.02−67.63) years, and the median follow-up was 12.26 (IQR 5.6−24.36) months. Renal cell carcinoma (33%) and melanoma (33.8%) were the most common diagnoses. Twenty patients (16.5%) had HPD. A high LDH level (p: 0.001), hypoalbuminemia (p: 0.016) and an NLR > 5 (p: 0.007) were found to be associated with hyperprogression. Sex (female vs. male, p: 0.114), age (>65 vs. <65, p: 0.772), ECOG (0 vs. 1−4, p: 0.480) and the line of treatment (1−5, p: 0.112) were not found to be associated with hyperprogression. Conclusions: In this study, we observed HPD in 16.5% of immunotherapy-treated patients and increased HPD risk in patients with a high LDH level (p: 0.001), hypoalbuminemia (p: 0.016) and an NLR > 5 (p: 0.007).

Prognostic role of the platelet to lymphocyte ratio (PLR) in the clinical outcomes of patients with advanced lung cancer receiving immunotherapy: A systematic review and meta-analysis

Background

It remains controversial whether the platelet to lymphocyte ratio (PLR) serves as a potential indicator for the efficacy of immunotherapy in advanced lung cancer. This meta-analysis aimed to address this concern.

Methods

Up to March 2022, we searched PubMed, Embase, Web of Science and the Cochrane Library to retrieve potentially eligible articles. Combined hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated to assess the relationship between PLR and progression-free survival (PFS) as well as overall survival (OS), while the combined odds ratios (ORs) and 95% CIs were estimated to evaluate the relationship between PLR and the objective response rate (ORR) as well as the disease control rate (DCR). Subgroup analyses were further performed to detect the source of heterogeneity and potential predictive value of PLR in different groups in terms of OS and PFS.

Results

A total of 21 included studies involving 2312 patients with advanced lung cancer receiving immunotherapy were included. The combined results suggested that elevated PLR was associated with poorer OS (HR=2.24; 95% CI: 1.87-2.68; I² =44%; P=0.01) and PFS (HR=1.66; 95% CI: 1.36-2.04; I² =64%; P<0.01). Furthermore, elevated PLR showed a lower ORR (OR= 0.61; 95% CI: 0.43-0.87, I²=20%; P=0.29) and DCR (OR= 0.44; 95% CI: 0.27-0.72, I²=61%; P=0.02). In subgroup analyses, pretreatment PLR was significantly associated with adverse OS and PFS. The same results were observed in different PLRs in terms of cutoff value (>200 vs. ≤200). Furthermore, high PLR was significantly associated with poor OS and PFS in advanced non-small cell lung cancer (NSCLC); however, PLR was not associated with OS and PFS in advanced small cell lung cancer (SCLC). In addition, PLR predicted poor OS irrespective of regions and types of immune checkpoint inhibitors (ICIs).

Conclusion

On the whole, patients with low PLR had better OS and PFS, as well as higher ORR and DCR when receiving immunotherapy in advanced lung cancer especially for advanced NSCLC. And further investigations are warranted to confirm the prognostic value of PLR in advanced SCLC.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022315976.

Absolute eosinophil count may be an optimal peripheral blood marker to identify the risk of immune-related adverse events in advanced malignant tumors treated with PD-1/PD-L1 inhibitors: a retrospective analysis

Background

This study aimed to investigate the predictive values of serum biomarkers including absolute eosinophil count (AEC), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) with respect to immune-related adverse events (irAEs) during anti-PD-1/PD-L1 inhibitor treatment in patients with advanced malignant tumors.

Methods

We retrospectively analyzed 95 patients with advanced cancer who were treated with anti-PD-1/PD-L1 inhibitors from January 1, 2017, to May 1, 2020, in our cancer center. We then analyzed associations between irAEs and anti-PD-1/PD-L1 inhibitor responses and evaluated the predictive values of serum biomarkers with respect to the risk of irAEs.

Results

The incidence of irAEs was 55.8%. There were no statistically significant differences between the irAEs and no-irAEs groups in an objective response rate (ORR) or disease control rate (DCR). However, landmark analysis showed that the irAEs group had better survival after 120 days following the initiation of anti-PD-1/PD-L1 inhibitor treatment, compared with the no-irAEs group. The incidences of irAEs were greater in the high-AEC and low-NLR groups than in the low-AEC and high-NLR groups. Univariate logistic analysis showed that low NLR, ECOG performance status (0–1), and high AEC were risk factors for irAEs. Multivariate logistic analysis showed that high AEC and good ECOG performance status were independent predictors for irAEs.

Conclusions

irAEs may be associated with a survival benefit. Baseline AEC is a strong predictor of irAEs in patients undergoing treatment with anti-PD-1/PD-L1 inhibitors.

Inflammatory and autoimmune predictive markers of response to anti‑PD‑1/PD‑L1 therapy in NSCLC and melanoma

Immune checkpoint inhibitors (ICI) are a standard in cancer therapy, but few patients respond to the treatment. The aim of the present study was the determination of immunological markers for monitoring response to ICI. The present study included 74 patients receiving ICI in subsequent [group 1; non-small cell lung cancer (NSCLC)] and first-line setting (group 2; melanoma) and 30 patients with NSCLC receiving first-line chemotherapy. In groups 1 and 2 β-2 microglobulin (B2-MG), neopterin (NPT), IL-6, IL-18, HLA-DRB1 and autoantibodies were assessed after two months of ICI, and before the start of next administration in group 3. In group 1 low level of B2-MG (P<0.0001), NPT (P<0.0001), IL-6 (P<0.0001), IL-18 (P=0.0003), HLA-DRB1*03 (P=0.016) and anti-TPO antibodies (P=0.016) were associated with response >six months. In group 2 high level of B2-MG (P=0.0001), NPT (P=0.0016), IL-6 (P=0.013) and IL-18 (P=0.032) were associated with early disease progression (<six months). Univariate analysis demonstrated that immune-related adverse events were predictive marker of prolonged progression-free survival (PFS) in group 1 (P=0.038) and 2 (P=0.020). Neutrophil-lymphocyte ratio ≥5 before immunotherapy was correlated with shorter PFS in melanoma in multivariate analysis (P=0.007). B2-MG ≥2.5 mg/ml (P=0.006) and NPT ≥12 nmol/l (P=0.027) were predictors of shorter PFS in group 1. B2-MG ≥2.5 mg/ml was predictor of shorter PFS (P=0.008) in group 2. In group 1 levels of B2-MG, NPT, IL-6 and IL-18 were higher than in group 3. In summary, immunological markers are promising predictive markers for immunotherapy; however, it requires further prospective studies.

Prognostic role of neutrophil-to-lymphocyte ratio and EPSILoN score in advanced non-small-cell lung cancer patients treated with first-line chemo-immunotherapy

Background: Clinical and laboratory biomarkers in patients with advanced non-small-cell lung cancer (aNSCLC) receiving chemo-immunotherapy (CIT) are still poorly explored. Materials & methods: All consecutive aNSCLC patients who received at least one cycle of first-line CIT were enrolled. The impact of several clinical and laboratory biomarkers on outcomes was evaluated through Cox proportional hazard models. Results: Higher neutrophil-to-lymphocyte ratio was shown to be an independent prognostic biomarker of both worse progression-free survival and worse overall survival. The EPSILoN score was able to divide patients into three different prognostic groups, with a median overall survival of 73.2, 45.6 and 8.6 months for the favorable, intermediate and poor groups, respectively. Conclusion: The neutrophil-to-lymphocyte ratio and EPSILoN score were shown to have a prognostic value in aNSCLC patients treated with CIT.

Predictive value of neutrophil-to-lymphocyte ratio for distant metastasis in gastric cancer patients

As a systemic inflammatory marker, the significance of NLR in predicting tumor prognosis and early lymph node metastasis is well known, including gastric cancer (GC). However, whether NLR can reflect GC metastasis status remains to be explored. We retrospectively enrolled 1667 GC patients treated in our hospital from December 2010 to December 2018. Patients were grouped according to the presence or absence of metastases. Receiver operating characteristics (ROC) curve analysis was used to evaluate the diagnostic efficacy of markers in assessing GC metastasis. Then we conducted a joint ROC curve analysis. The effects of clinicopathological parameters on GC metastasis were assessed using multiple logistic regression analysis. 743 (44.6%) patients were diagnosed with metastatic GC. Patients with GC metastases have younger age, higher CEA, CA19-9, CA72-4 and NLR. Based on the comparison of AUC, NLR has diagnostic efficacy comparable to that of GC markers. The AUC of NLR combined with GC markers had significantly higher predicting efficacy than that without combination for assessing peritoneal metastasis (P = 0.013), osseous metastasis (P = 0.017) and hepatic metastasis (P < 0.001). In multiple logistic regression analysis, age, NLR, CEA, CA19-9 and CA72-4 were found to be independently associated with GC metastasis (all P < 0.05). NLR was a risk factor of GC metastasis. Combining CEA, CA19-9, CA72-4 and NLR could better predict metastases in GC.

The Association between the Pan-Immune-Inflammation Value and Cancer Prognosis: A Systematic Review and Meta-Analysis

Background: Prognostic scores derived from the blood count have garnered significant interest as an indirect measure of the inflammatory pressure in cancer. The recently developed pan-immune-inflammation value (PIV), an equation including the neutrophil, platelet, monocyte, and lymphocyte levels, has been evaluated in several cohorts, although with variations in the tumor types, disease stages, cut-offs, and treatments. Therefore, we evaluated the association between survival and PIV in cancer, performing a systematic review and meta-analysis. Methods: We conducted a systematic review from the Pubmed, Medline, and Embase databases to filter the published studies until 17 May 2022. The meta-analyses were performed with the generic inverse-variance method with a random-effects model. Results: Fifteen studies encompassing 4942 patients were included. In the pooled analysis of fifteen studies, the patients with higher PIV levels had significantly increased risk of death than those with lower PIV levels (HR: 2.00, 95% CI: 1.51−2.64, p < 0.001) and increased risk of progression or death (HR: 1.80, 95% CI: 1.39−2.32, p < 0.001). Analyses were consistent across several clinical scenarios, including non-metastatic or metastatic disease, different cut-offs (500, 400, and 300), and treatment with targeted therapy or immunotherapy (p < 0.001 for each). Conclusion: The available evidence demonstrates that PIV could be a prognostic biomarker in cancer. However, further research is needed to explore the promise of PIV as a prognostic biomarker in patients with non-metastatic disease or patients treated without immunotherapy or targeted therapy.

Modified-Dose Pembrolizumab and Prognostic Outcomes among Non-Small Cell Lung Cancer Patients: A Chart Review Study

The modified dose (MD) regimen of pembrolizumab (2 mg/kg or 100 mg every 3 weeks) is an alternative option to reduce the financial burden resulting from the extremely high cost of the standard dose (SD) regimen (200 mg every 3 weeks). However, the clinical effectiveness and prognostic outcomes have not been fully elucidated in real-word clinical practice. Sixty-four consecutive patients in Taiwan receiving pembrolizumab for advanced NSCLC between 2018 and 2020 were recruited in this study. Comparisons of overall survival (OS) and progression-free survival (PFS) were performed using Kaplan−Meier survival curves. Additionally, 12 predictors, including pembrolizumab regimen, dose, neutrophil-to-lymphocyte ratio (NLR), age, sex, histopathology, smoking history, ECOG PS, EGFR mutation, PD-L1 expression, distant metastases and treatment line, were analyzed in multivariable Cox models for predicting OS and PFS. The results showed that the MD group and the SD group had similar OS and PFS, especially in patients beyond first-line treatment or with a pretreatment NLR < 5. The NLR was the only independent factor associated with both OS (adjusted HR = 0.052; p = 0.010) and PFS (adjusted HR = 0.259; p = 0.021). The results of this study assure the clinical effectiveness of MD pembrolizumab and suggest that the pretreatment NLR could highlight patients who may benefit from MD pembrolizumab.

Biomarkers of systemic inflammation predict survival with first-line immune checkpoint inhibitors in non-small-cell lung cancer

INTRODUCTION

Pembrolizumab is an established first-line option for patients with advanced non-small-cell lung cancer (NSCLC) expressing programmed death-ligand 1 ≥50%. Durable responses are seen in a subset of patients; however, many derive little clinical benefit. Biomarkers of the systemic inflammatory response predict survival in NSCLC. We evaluated their prognostic significance in patients receiving first-line pembrolizumab for advanced NSCLC.

METHODS

Patients treated with first-line pembrolizumab for advanced NSCLC with programmed death-ligand 1 expression ≥50% at two regional Scottish cancer centres were identified. Pretreatment inflammatory biomarkers (white cell count, neutrophil count, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, albumin, prognostic nutritional index) were recorded. The relationship between these and progression-free survival (PFS) and overall survival (OS) were examined.

RESULTS

Data were available for 219 patients. On multivariate analysis, albumin and neutrophil count were independently associated with PFS (P < 0.001, P = 0.002, respectively) and OS (both P < 0.001). A simple score combining these biomarkers was explored. The Scottish Inflammatory Prognostic Score (SIPS) assigned 1 point each for albumin <35 g/l and neutrophil count >7.5 × 10⁹/l to give a three-tier categorical score. SIPS predicted PFS [hazard ratio 2.06, 95% confidence interval (CI) 1.68-2.52 (P < 0.001)] and OS [hazard ratio 2.33, 95% CI 1.86-2.92 (P < 0.001)]. It stratified PFS from 2.5 (SIPS2), to 8.7 (SIPS1) to 17.9 months (SIPS0) (P < 0.001) and OS from 5.1 (SIPS2), to 12.4 (SIPS1) to 28.7 months (SIPS0) (P < 0.001). The relative risk of death before 6 months was 2.96 (95% CI 1.98-4.42) in patients with SIPS2 compared with those with SIPS0-1 (P < 0.001).

CONCLUSIONS

SIPS, a simple score combining albumin and neutrophil count, predicts survival in patients with NSCLC receiving first-line pembrolizumab. Unlike many proposed prognostic scores, SIPS uses only routinely collected pretreatment test results and provides a categorical score. It stratifies survival across clinically meaningful time periods that may assist clinicians and patients with treatment decisions. We advocate validation of the prognostic utility of SIPS in this and other immune checkpoint inhibitor treatment settings.

Prognostic value of pretreatment advanced lung cancer inflammation index in non-small cell lung cancer: a meta-analysis

Purpose To identify the prognostic value of pretreatment advanced lung cancer inflammation index (ALI) in non-small cell lung cancer (NSCLC) including surgical patients who were diagnosed with early stage. Methods The PubMed, EMBASE and Web of Science electronic databases were searched up to January 12, 2022 for relevant studies. The hazard ratios (HRs) with 95% confidence intervals (CIs) were combined to assess the association between pretreatment ALI and overall survival (OS) or progression-free survival (PFS) of NSCLC patients. All statistical analyses were conducted by STATA 12.0 software. Results A total of 14 studies involving 3607 participates were included. The pooled results indicated that lower pretreatment ALI was significantly related with poorer OS (HR =2.20, 95% CI: 1.46-3.33, P<0.001) and PFS (HR =1.78, 95% CI: 1.49-2.13, P<0.001). Besides, subgroup analysis also demonstrated that lower pretreatment ALI was associated with worse OS in surgical (P<0.001) and non-metastatic (P<0.001) patients and worse PFS of surgical (P<0.001) NSCLC patients. Conclusion Pretreatment ALI was a novel and reliable prognostic indicator in NSCLC and lower pretreatment ALI predicted worse survival including patients diagnosed with early stage. However, more prospective high-quality studies are still needed to verify above findings.

The Prognostic Value of Albumin-Globulin Ratio and Eosinophil-Neutrophil Ratio in Patients with Advanced Tumors Undergoing Treatment with PD-1/PD-L1 Inhibitors

We investigated the prognostic value of peripheral serum biomarkers, including albumin-globulin ratio (AGR) and eosinophil-neutrophil ratio (ENR), in patients with advanced tumors treated with PD-1/PD-L1 inhibitors. We also retrospectively analyzed the clinical efficacy of PD-1/PD-L1 inhibition in 95 patients with advanced tumors treated at our center. The prognostic value of baseline AGR, baseline ENR, and baseline neutrophil-lymphocyte ratio (NLR) in the serum were evaluated. We also developed a risk scoring tool to stratify patients based on their prognosis. Univariate Cox regression analysis revealed that age, NLR, Eastern Cooperative Oncology Group (ECOG) performance status (PS), platelet-neutrophil ratio (PLR), ENR, AGR, lactate dehydrogenase levels, treatment line, and treatment type were correlated with progression-free survival (PFS). Multivariate Cox regression analysis showed that age, AGR, ENR, and treatment type were independent prognostic factors for PFS. Patients in the low-risk group had significantly longer PFS than those in the high-risk group. The nomogram concordance index (C-index) was 0.716. Patients with a decrease in AGR of over 20% after the first and second treatment cycles had significantly worse PFS than those without decreased AGR. These findings suggest that baseline AGR and ENR may be useful prognostic biomarkers for patients with advanced tumors treated with PD-1/PD-L1 inhibitors.

The relationship between NLR/PLR/LMR levels and survival prognosis in patients with non-small cell lung carcinoma treated with immune checkpoint inhibitors

BACKGROUND

The relationship between neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) and the dire prognosis of non-small cell lung carcinoma patients who received immune checkpoint inhibitors (ICIs) are not known yet.

METHODS

We screened the articles that meet the criteria from the database. The relationship between NLR/PLR/LMR levels and the survival and prognosis of non-small cell lung cancer patients treated with ICIs was analyzed. Summarize hazard ratio (HR) with 95% confidence interval (CI) to study progression-free survival (PFS) and overall survival (OS).

RESULTS

Thirty-four studies involving 3124 patients were enrolled in the final analysis. In short, high pre-treatment NLR was related to poor OS (HR = 2.13, 95% CI:1.74-2.61, P < .001, I2 = 83.3%, P < .001) and PFS (HR = 1.77, 95% CI:1.44-2.17, P < .001, I2 = 79.5%, P < .001). Simultaneously, high pre-treatment PLR was related to poor OS (HR = 1.49, 95% CI:1.17-1.91, P < .001, I2 = 57.6%, P = .003) and PFS (HR = 1.62, 95% CI:1.38-1.89, P < .001, I2 = 47.1%, P = .036). In all subgroup analysis, most subgroups showed that low LMR was related to poor OS (HR = 0.45, 95% CI: 0.34-0.59, P < .001) and PFS (HR = 0.60, 95% CI: 0.47-0.77, P < 0.001, I2 = 0.0%, P < .001).

CONCLUSION

High pre-treatment NLR and pre-treatment PLR in non-small cell lung carcinoma patients treated with ICIs are associated with low survival rates. Low pre-treatment and post-treatment LMR are also related to unsatisfactory survival outcomes. However, the significance of post-treatment NLR and post-treatment PLR deserve further prospective research to prove.

Prognostic and predictive value of neutrophil-to-lymphocyte ratio with adjuvant immunotherapy in stage III non-small-cell lung cancer

BACKGROUND

Elevated pre-treatment neutrophil-to-lymphocyte ratio (NLR) may reflect immune dysfunction and is negatively prognostic in cancer patients treated with immunotherapy, but it is unclear if NLR is predictive of immunotherapy benefit.

METHODS

We identified stage III non-small-cell lung cancer (NSCLC) patients treated with definitive chemoradiation and adjuvant durvalumab within the national Veterans Affairs system from 2017 to 2021. We compared the prognostic value of NLR measured before durvalumab start to a control group of stage III NSCLC patients treated with definitive chemoradiation alone from 2015 to 2016 (no-durvalumab group) before the approval of adjuvant durvalumab. We estimated the predictive value of NLR through the statistical interaction of durvalumab group by NLR level. Outcomes included progression-free survival (PFS) and overall survival (OS).

RESULTS

The primary analysis for NLR included 821 durvalumab patients and 445 no-durvalumab patients. Higher NLR was associated with inferior PFS in both groups (no-durvalumab: adjusted HR [aHR] 1.14 per 7.43 unit increase in NLR, 95% confidence interval [CI] 1.06-1.23; durvalumab: aHR 1.42, 95% CI 1.23-1.64), though this effect was greater in durvalumab patients (p for interaction = 0.009). Similar results were found for OS (no-durvalumab: aHR 1.16, 95% CI 1.09-1.24; durvalumab: aHR 1.48, 95% CI 1.25-1.76; p for interaction = 0.010). Absolute lymphocytes, eosinophils, and basophils were not prognostic in either group. Estimates of durvalumab treatment efficacy suggested declining efficacy with higher NLR.

CONCLUSION

Pre-treatment NLR is especially prognostic among stage III NSCLC patients treated with adjuvant immunotherapy compared to control patients treated without immunotherapy and may be a predictive biomarker of immunotherapy benefit.

The association between albumin-globulin ratio (AGR) and survival in patients treated with immune checkpoint inhibitors

BACKGROUND

The albumin-globulin ratio (AGR) could be a prognostic biomarker in patients with cancer, although the data is limited in patients treated with immune-checkpoint inhibitors (ICIs).

OBJECTIVES

We aimed to evaluate the association between AGR and survival in ICI-treated patients.

METHODS

The data of 212 advanced-stage patients were retrospectively evaluated in this cohort study. The association between AGR with overall (OS) and progression-free survival (PFS) were evaluated with multivariate analyses. Additionally, receptor operating curve (ROC) analysis was conducted to assess the AGR's predictive power in the very early progression (progression within two months) and long-term benefit (more than twelve months survival).

RESULTS

The median AGR was calculated as 1.21, and patients were classified into AGR-low and high subgroups according to the median. In the multivariate analyses, patients with lower AGR (< 1.21) had decreased OS (HR: 1.530, 95% CI: 1.100-2.127, p= 0.011) and PFS (HR: 1.390, 95% CI: 1.020-1.895, p= 0.037). The area under curve of AGR to detect early progression and long-term benefit were 0.654 (95% CI: 0.562-0.747, p= 0.001) and 0.671 (95% CI: 0.598-0.744, p< 0.001), respectively.

CONCLUSIONS

In our experience, survival with ICIs was impaired in patients with lower AGR. Additionally, the AGR values could detect the very early progression and long-term benefit ICIs.

Immunotherapeutic early-phase clinical trials and malignant gliomas: A single-center experience and comprehensive immunophenotyping of circulating leukocytes

Background

Immunotherapeutic early-phase clinical trials (ieCTs) increasingly adopt large expansion cohorts exploring novel agents across different tumor types. High-grade glioma (HGG) patients are usually excluded from these trials.

Methods

Data of patients with recurrent HGGs treated within multicohort ieCTs between February 2014 and August 2019 (experimental group, EG) at our Phase I Unit were retrospectively reviewed and compared to a matched control group (CG) of patients treated with standard therapies. We retrospectively evaluated clinical, laboratory, and molecular parameters through univariate and multivariate analysis. A prospective characterization of circulating leukocyte subpopulations was performed in the latest twenty patients enrolled in the EG, with a statistical significance cutoff of P < .1.

Results

Thirty HGG patients were treated into six ieCTs. Fifteen patients received monotherapies (anti-PD-1, anti-CSF-1R, anti-TGFβ, anti-cereblon), fifteen patients combination regimens (anti-PD-L1 + anti-CD38, anti-PD-1 + anti-CSF-1R). In the EG, median progression-free survival and overall survival (OS) from treatment initiation were 1.8 and 8.6 months; twelve patients survived more than 12 months, and two of them more than 6 years. Univariate analysis identified O⁶-methylguanine DNA methyltransferase (MGMT) promoter methylation and total protein value at six weeks as significantly correlated with a better outcome. Decreased circulating neutrophils and increased conventional dendritic cells levels lead to significantly better OS.

Conclusions

A subgroup of EG patients achieved remarkably durable disease control. MGMT promoter methylation identifies patients who benefit more from immunotherapy. Monitoring dynamic changes of innate immune cell populations may help to predict clinical outcomes.

Smoking signature is superior to programmed death-ligand 1 expression in predicting pathological response to neoadjuvant immunotherapy in lung cancer patients

Background

There is a paucity of biomarkers that can predict the degree of pathological response [e.g., pathological complete response (pCR) or major response (pMR)] to immunotherapy. Neoadjuvant immunotherapy provides an ideal setting for exploring responsive biomarkers because the pathological responses can be directly and accurately evaluated.

Methods

We retrospectively collected the clinicopathological characteristics and treatment outcomes of non-small cell lung cancer (NSCLC) patients who received neoadjuvant immunotherapy or chemo-immunotherapy followed by surgery between 2018 and 2020 at a large academic thoracic cancer center. Clinicopathological factors associated with pathological response were analyzed.

Results

A total of 39 patients (35 males and 4 females) were included. The most common histological subtype was lung squamous cell carcinoma (LUSC) (n=28, 71.8%), followed by lung adenocarcinoma (LUAD) (n=11, 28.2%). After neoadjuvant treatment, computed tomography (CT) scan-based evaluation showed poor agreement with the postoperatively pathological examination (weighted kappa =0.0225; P=0.795), suggesting the poor performance of CT scans in evaluating the response to immunotherapy. Importantly, we found that the smoking signature displayed a better performance than programmed death-ligand 1 (PD-L1) expression in predicting the pathological response (area under the curve: 0.690 vs. 0.456; P=0.0259), which might have resulted from increased tumor mutational burden (TMB) and/or microsatellite instability (MSI) relating to smoking exposure.

Conclusions

These findings suggest that CT scan-based evaluation is not able to accurately reflect the pathological response to immunotherapy and that smoking signature is a superior marker to PD-L1 expression in predicting the benefit of immunotherapy in NSCLC patients.