Low peripheral blood derived neutrophil-to-lymphocyte ratio (dNLR) is associated with increased tumor T-cell infiltration and favorable outcomes to first-line pembrolizumab in non-small cell lung cancer

Splenic index score as a predictor of outcomes in metastatic non small cell lung cancer patients treated with immune checkpoint inhibitors

Introduction Immune checkpoint inhibitors (ICIs) targeting PD-1 and PD-L1 have emerged as promising treatments for advanced NSCLC patients without actionable mutations. However, predicting treatment response remains challenging, especially in second-line settings. Although PD-L1 is the only validated biomarker, additional prognostic tools are needed. Systemic inflammation markers such as the neutrophil-to-lymphocyte ratio (NLR) show potential but remain underused. Myeloid-derived suppressor cells (MDSCs), linked to immunotherapy resistance, are associated with increased splenic volume. Therefore this study introduces a splenic index score, combining pre-immunotherapy splenic volume and NLR, to evaluate its prognostic value in NSCLC patients treated with nivolumab in the second-line setting. We analyzed 50 patients with metastatic non-small cell lung cancer (NSCLC) who received nivolumab as second-line or later therapy. Baseline splenic volume and neutrophil-to-lymphocyte ratio (NLR) were assessed using imaging and laboratory data prior to nivolumab initiation. The Splenic Index Score for each patient was calculated using the formula: (baseline splenic volume) × (NLR). Additionally, we evaluated the impact of other factors, including body mass index (BMI), tumor PD-L1 expression, Eastern Cooperative Oncology Group (ECOG) performance status, and sites of metastasis. The median Splenic Index score was 877.3 (range: 180-4830). A higher Splenic Index score was significantly associated with worse overall survival (OS) and progression-free survival (PFS) (p = 0.001 and p = 0.03, respectively). Specifically, patients with a high Splenic Index score had a median PFS of 3 months, compared to 8 months in those with a low Splenic Index score (HR 1.96, 95% CI 1-3.7, p = 0.03). Similarly, the median OS was 4 months for patients with a high Splenic Index score, while it was 15 months for those with a low score (HR 3.5, 95% CI 1.6-7.3, p = 0.001). Baseline splenic volume, basal NLR, and tumor PD-L1 expression were also evaluated; however, no significant differences in PFS or OS were observed for these parameters. Our study demonstrates that the splenic index score, derived from combining radiological and peripheral inflammatory biomarkers, serves as a predictive tool for progression-free survival (PFS) and overall survival (OS) in metastatic NSCLC patients receiving second-line nivolumab therapy.

Society for Immunotherapy of Cancer (SITC) consensus statement on essential biomarkers for immunotherapy clinical protocols

Immunotherapy of cancer is now an essential pillar of treatment for patients with many individual tumor types. Novel immune targets and technical advances are driving a rapid exploration of new treatment strategies incorporating immune agents in cancer clinical practice. Immunotherapies perturb a complex system of interactions among genomically unstable tumor cells, diverse cells within the tumor microenvironment including the systemic adaptive and innate immune cells. The drive to develop increasingly effective immunotherapy regimens is tempered by the risk of immune-related adverse events. Evidence-based biomarkers that measure the potential for therapeutic response and/or toxicity are critical to guide optimal patient care and contextualize the results of immunotherapy clinical trials. Responding to the lack of guidance on biomarker testing in early-phase immunotherapy clinical trials, we propose a definition and listing of essential biomarkers recommended for inclusion in all such protocols. These recommendations are based on consensus provided by the Society for Immunotherapy of Cancer (SITC) Clinical Immuno-Oncology Network (SCION) faculty with input from the SITC Pathology and Biomarker Committees and the Journal for ImmunoTherapy of Cancer readership. A consensus-based selection of essential biomarkers was conducted using a Delphi survey of SCION faculty. Regular updates to these recommendations are planned. The inaugural list of essential biomarkers includes complete blood count with differential to generate a neutrophil-to-lymphocyte ratio or systemic immune-inflammation index, serum lactate dehydrogenase and albumin, programmed death-ligand 1 immunohistochemistry, microsatellite stability assessment, and tumor mutational burden. Inclusion of these biomarkers across early-phase immunotherapy clinical trials will capture variation among trials, provide deeper insight into the novel and established therapies, and support improved patient selection and stratification for later-phase clinical trials.

Association of lung immune prognostic index with overall survival in pancreatic ductal adenocarcinoma patients treated using chemotherapy

Background: The lung immune prognostic index (LIPI) has attracted considerable interest for its prognostic value in several malignancies. However, its prognostic value in pancreatic ductal adenocarcinoma (PDAC) has not yet been clarified. Objective: This study aimed to assess the role of LIPI with regard to overall survival (OS) in locally advanced or metastatic PDAC patients undergoing chemotherapy. Methods: Data from 256 patients with PDAC treated via chemotherapy at the Chinese PLA General Hospital between January 1, 2011 and July 1, 2018 were retrospectively reviewed. Their neutrophil-to-lymphocyte ratio (dNLR) with lactate dehydrogenase (LDH) values were used to calculate each one's LIPI. The Cox proportional hazard model was used to identify the association between LIPI and OS. Results: Of the included patients, 154 were in the good LIPI group and 102 were in the intermediate/poor LIPI group. The OS in the two groups were 9.0 months (95% CI: 7.351-10.649) and 6.0 months (95% CI: 4.812-7.188), respectively. Patients in the good LIPI group had better OS compared to those in the intermediate/poor LIPI group (HR, 0.720; 95% CI: 0.554-0.935; P = 0.014). Conclusion: This study revealed LIPI is significantly associated with OS in PDAC and could play a significant role in helping clinicians make appropriate decisions for PDAC patients undergoing chemotherapy.

A Phase I Trial of Trebananib, an Angiopoietin 1 and 2 Neutralizing Peptibody, Combined with Pembrolizumab in Patients with Advanced Ovarian and Colorectal Cancer

Ovarian cancers and microsatellite stable (MSS) colorectal cancers are insensitive to anti-programmed cell death 1 (PD-1) immunotherapy, and new immunotherapeutic approaches are needed. Preclinical data suggest a relationship between immunotherapy resistance and elevated angiopoietin 2 levels. We performed a phase I dose escalation study of pembrolizumab and the angiopoietin 1/2 inhibitor trebananib (NCT03239145). This multicenter trial enrolled patients with metastatic ovarian cancer or MSS colorectal cancer. Trebananib was administered intravenously weekly for 12 weeks with 200 mg intravenous pembrolizumab every 3 weeks. The toxicity profile of this combination was manageable, and the protocol-defined highest dose level (trebananib 30 mg/kg weekly plus pembrolizumab 200 mg every 3 weeks) was declared the maximum tolerated dose. The objective response rate for all patients was 7.3% (90% confidence interval, 2.5%-15.9%). Three patients with MSS colorectal cancer had durable responses for ≥3 years. One responding patient's colorectal cancer harbored a POLE mutation. The other two responding patients had left-sided colorectal cancers, with no baseline liver metastases, and genomic analysis revealed that they both had KRAS wild-type, ERBB2-amplified tumors. After development of acquired resistance, biopsy of one patient's KRAS wild-type ERBB2-amplified tumor showed a substantial decline in tumor-associated T cells and an increase in immunosuppressive intratumoral macrophages. Future studies are needed to carefully assess whether clinicogenomic features, such as lack of liver metastases, ERBB2 amplification, and left-sided tumors, can predict increased sensitivity to PD-1 immunotherapy combinations.

Pretreatment neutrophil-to-lymphocyte ratio is associated with immunotherapy efficacy in patients with advanced cancer: a systematic review and meta-analysis

This study aimed to systematically investigate the value of the pre-treatment neutrophil-to-lymphocyte ratio (NLR) in prognosticating the outcome of patients with advanced cancer receiving immunotherapy. We searched Embase, PubMed, Web of Science, and Cochrane Library to identify studies about cancer patients with immunotherapy until November 29, 2024. Retrospective or prospective cohort studies with pretreatment NLR data were included. The odds ratio (OR) and 95% confidence interval (CI) were calculated to evaluate the predictive value of NLR in prognosis and immunotherapy efficacy. The random effect model was applied for meta-analysis and the risk of bias was assessed by Egger test and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method. A total of 129 articles involving 18780 cases were finally selected. Most cases were advanced cancers with the median follow-up period ranged 2-48.6 months. The high pretreatment NLR level was associated with the significantly reduced OS (HR (95%CI) = 2.26 (2.03, 2.53)), PFS (HR (95% CI) = 1.83 (1.69, 1.98)), ORR (OR (95%CI) = 0.53 (0.46, 0.61)) and DCR (OR (95% CI) = 0.36 (0.29, 0.43)) in patients with advanced cancer receiving immunotherapy. The quality of evidence was low, attributed to the serious risk of bias and incon¬sistency. An elevated NLR before immunotherapy was significantly associated with poor clinical outcomes in patients with advanced cancer.

Dissociated response and treatment outcome with immune checkpoint blockade in advanced cancer

Immune-related dissociated response (DR) has been recently recognized and have become a subject of ongoing interest. The purpose of the present study was to evaluate the frequency, treatment outcome, and predictors of DR in cancer patients with immune checkpoint inhibitors. We retrospectively collected clinicopathological data from a cohort of patients with cancer who received PD-1/PD-L1 inhibitor-based monotherapy or combination therapy at a single institution (developing cohort). An independent cohort of advanced non-small cell lung cancer (NSCLC) patients treated with immunotherapy at two institutions was used as the validating cohort. Progression-free survival (PFS) and overall survival (OS) were used as outcome measures. The pantumor cohort included 177 patients. DR were observed in 12 (6.8%) patients. The median PFS and OS were significantly longer in patients with atypical response versus nonresponse but shorter versus true response. Patients with DR had a longer median PFS and OS than those with true progressive disease (PD). Local treatment seemed to have a positive influence on DR patient outcomes, with a median OS of 32.3 months versus 21.9 months for no local treatment. No clinical characteristics remained significant predictors for DR. In the NSCLC cohort, DR was observed in 10 (12.5%) patients. Inferior PFS and OS were validated in patients with real PD when compared with patients with DR. Patients who experience DR exhibit a relatively favorable prognosis. Some patients with DR may benefit from the continuation of ICI administration and local treatment to the growing lesions and achieve a longer survival.

Cancer-specific innate and adaptive immune rewiring drives resistance to PD-1 blockade in classic Hodgkin lymphoma

Hodgkin Reed-Sternberg (HRS) cells of classic Hodgkin lymphoma (cHL), like many solid tumors, elicit ineffective immune responses. However, patients with cHL are highly responsive to PD-1 blockade, which largely depends on HRS cell-specific retention of MHC class II and implicates CD4+ T cells and additional MHC class I-independent immune effectors. Here, we utilize single-cell RNA sequencing and spatial analysis to define shared circulating and microenvironmental features of the immune response to PD-1 blockade in cHL. Compared with non-responders, responding patients have more circulating CD4+ naïve and central memory T cells and B cells, as well as more diverse CD4+ T cell and B cell receptor repertoires. Importantly, a population of circulating and tumor-infiltrating IL1β+ monocytes/macrophages is detectable in patients with cHL but not healthy donors, and a proinflammatory, tumor-promoting signature of these circulating IL1β+ monocytes is associated with resistance to PD-1 blockade in cHL. Altogether, our findings reveal extensive immune rewiring and complementary roles of CD4+ T cells, B cells and IL1β+ monocytes in the response to PD-1 blockade and suggest that these features can be captured with a peripheral blood test.

Machine learning identifies immune-based biomarkers that predict efficacy of anti-angiogenesis-based therapies in advanced lung cancer

BACKGROUND

The anti-angiogenic drugs showed remarkable efficacy in the treatment of lung cancer. Nonetheless, the potential roles of the intra-tumoral immune cell abundances and peripheral blood immunological features in prognosis prediction of patients with advanced lung cancer receiving anti-angiogenesis-based therapies remain unknown. In this study, we aimed to develop an immune-based model for early identification of patients with advanced lung cancer who would benefit from anti-angiogenesis-based therapies.

METHODS

We assembled the real-world cohort of 1058 stage III-IV lung cancer patients receiving the anti-angiogenesis-based therapies. We comprehensively evaluated the tumor immune microenvironment characterizations (CD4, CD8, CD68, FOXP3, and PD-L1) by multiplex immunofluorescence (mIF), as well as calculated the systemic inflammatory index by flow cytometry and medical record review. Based on the light gradient boosting machine (LightGBM) algorithm, a machine-learning model with meaningful parameters was developed and validated in real-world populations.

RESULTS

In the first-line anti-angiogenic therapy plus chemotherapy cohort (n = 385), the intra-tumoral proportion of CD68 + Macrophages and several circulating inflammatory indexes were significantly related to drug response (p < 0.05). Further, neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), the systemic inflammation response index (SIRI), and myeloid to lymphoid ratio (M:L) were identified to construct the non-invasive prediction model with high predictive performance (AUC: 0.799 for treatment response and 0.7006-0.915 for progression-free survival (PFS)). Additionally, based on the unsupervised hierarchical clustering results, the circulating cluster 3 with the highest levels of NLR, MLR, SIRI, and M: L had the worst PFS with the first-line anti-angiogenic therapy plus chemotherapy compared to other circulating clusters (2.5 months, 95 % confidence interval 2.3-2.7 vs. 6.0-9.7 months, 95 % confidence interval 4.9-11.1, p < 0.01). The predictive power of the machine-learning model in PFS was also validated in the anti-angiogenic therapy plus immunotherapy cohort (n = 103), the anti-angiogenic monotherapy cohort (n = 284), and the second-line anti-angiogenic therapy plus chemotherapy cohort (n = 286).

CONCLUSIONS

Integrating pre-treatment circulating inflammatory biomarkers could non-invasively and early forecast clinical outcomes for anti-angiogenic response in lung cancer. The immune-based prognostic model is a promising tool to reflect systemic inflammatory status and predict clinical prognosis for anti-angiogenic treatment in patients with stage III-IV lung cancer.

The role of the CXCL12/CXCR4 axis in the immunotherapy of non-small cell lung cancer

INTRODUCTION

Peripheral blood mononuclear cells (PBMCs) trafficking is regulated by chemokines, which modulate leukocyte migration toward tumors and may collaborate in the efficacy of immunotherapy. In our study, we investigated whether the CXCL12/CXCR4 axis plays a role in the efficacy of immunotherapy in non-small cell lung cancer (NSCLC) by analyzing CXCR4 expression for CXCR4 in peripheral blood (PB), and the expression of its ligand CXCL12 in tumor.

METHODS

We identified PBMCs expressing CXCR4 using flow cytometry in a prospective cohort of NSCLC patients before starting anti-PD-1 immunotherapy. As a control, we studied patients with advanced cancer before starting any non-immunotherapy treatment. The relative frequency of PBMCs was correlated with treatment outcomes. Uni- and multivariate survival analyses were performed. The expression of CXCL12 in tumor tissue was studied and correlated with the expression of its receptor (CXCR4) in PBMCs.

RESULTS

The experimental group included 39 patients and the control group included 40. Low expression of CXCR4-expressing CD8 + T lymphocytes was correlated with a greater benefit from immunotherapy: median OS NR vs. 22.0 months, HR 0.6, p < 0.01; and median PFS 14.2 vs. 5.0 months, HR 0.38, p = 0.05. These differences were not observed in controls. Low expression in PB of these lymphocytes was correlated with a higher expression of CXCL12 in tumor (trend toward significance: p = 0.14).

CONCLUSION

Patients diagnosed with advanced NSCLC with low percentage of cytotoxic T lymphocytes expressing CXCR4 in PB, show greater benefit from immunotherapy, probably due to increased tumor infiltration by lymphocytes in response to CXCL12 produced by the tumor.

Biomarkers for immunotherapy resistance in non-small cell lung cancer

Immunotherapy has revolutionised the treatment landscape of non-small cell lung cancer (NSCLC), significantly improving survival outcomes and offering renewed hope to patients with advanced disease. However, the majority of patients experience limited long-term benefits from immune checkpoint inhibition (ICI) due to the development of primary or acquired immunotherapy resistance. Accurate predictive biomarkers for immunotherapy resistance are essential for individualising treatment strategies, improving survival outcomes, and minimising potential treatment-related harm. This review discusses the mechanisms underlying resistance to immunotherapy, addressing both cancer cell-intrinsic and cancer cell-extrinsic resistance processes. We summarise the current utility and limitations of two clinically established biomarkers: programmed death ligand 1 (PD-L1) expression and tumour mutational burden (TMB). Following this, we present a comprehensive review of emerging immunotherapy biomarkers in NSCLC, including tumour neoantigens, epigenetic signatures, markers of the tumour microenvironment (TME), genomic alterations, host-microbiome composition, and circulating biomarkers. The potential clinical applications of these biomarkers, along with novel approaches to their biomarker identification and targeting, are discussed. Additionally, we explore current strategies to overcome immunotherapy resistance and propose incorporating predictive biomarkers into an adaptive clinical trial design, where specific immune signatures guide subsequent treatment selection.

Peripheral Circulating Blood Cells Deviation Based on Tumor Inflammatory Microenvironment Activity in Resected Upstaged Lung Adenocarcinomas

Background: The tumour inflammatory microenvironment (TIME) reflects a selective activation of the central immune system (IS), particularly T-cells expansion, which leads to immune cells migrating to the target, such as lung cancer, via the bloodstream and lymphatic vessels. In this study, the aim is to investigate whether the distribution of peripheral blood cells varies based on the immune status of patients with lung adenocarcinoma. Methods: This is a single-center retrospective study conducted in the Thoracic Surgery Unit of the University of Padua (Italy) between 1 January 2016 and 1 April 2024. It included patients (>18 years old) with lung adenocarcinoma deemed resectable (cT2bN0M0 or lower) who experienced pathological upstaging (IIB or higher). Patients were classified as TIME-active (with tumour-infiltrating lymphocytes-TILs and/or PD-L1 expression) or TIME-silent (without TILs or PD-L1). According to the TIME status, peripheral blood cell counts with clinical and pathological data were compared between groups using the Fisher's, Pearson's or Wilcoxon's test when appropriate. A Kaplan-Meier estimator investigated overall survival (OS) and recurrence-free survival (RFS) adopting the log-rank test. Results: Preoperatively, the TIME-a group demonstrated a significantly higher lymphocyte count (p = 0.02) and a lower absolute neutrophil rate (p = 0.01) than TIME-s. These differences persisted after resection (p = 0.06 and p = 0.02) while they became similar one month after surgery (p = 1 and p = 0.32). The neutrophil-to-lymphocyte ratio-NLR showed similar trends (p = 0.01 and p = 1). Better OS and RFS were shown in the TIME-a group (p = 0.02 and 0.03, respectively). Conclusions: Resected upstaged lung adenocarcinomas show distinct peripheral blood cell profiles based on immune status. TIME-active patients had a significantly lower NLR, which normalized post-surgery. Surgical resection may help restore native immune surveillance.

Computed Tomography-Based Intratumor Heterogeneity Predicts Response to Immunotherapy Plus Chemotherapy in Esophageal Squamous Cell Carcinoma

RATIONALE AND OBJECTIVES

This study explored the intratumor heterogeneity (ITH) of esophageal squamous cell carcinoma (ESCC) using computed tomography (CT) and investigated the value of CT-based ITH in predicting the response to immune checkpoint inhibitor (ICI) plus chemotherapy in patients with ESCC.

MATERIALS AND METHODS

This retrospective study included 416 patients with ESCC who received ICI plus chemotherapy at two independent hospitals between January 2019 and July 2022. Multiparametric CT features were extracted from ESCC lesions and screened using hierarchical clustering and dimensionality reduction algorithms. Logistic regression and machine learning models based on selected features were developed to predict treatment response and validated in separate datasets. ITH was quantified using the score calculated by the best-performing model and visualized through feature clustering and feature contribution heatmaps. A gene set enrichment analysis (GSEA) was performed to identify the biological pathways underlying the CT-based ITH.

RESULTS

The extreme gradient boosting model based on CT-derived ITH had higher discriminative power, with areas under the receiver operating characteristic curve of 0.864 (95% confidence interval [CI]: 0.774-0.954) and 0.796 (95% CI: 0.698-0.893) in the internal and external validation sets. The CT-based ITH pattern differed significantly between responding and non-responding patients. The GSEA indicated that CT-based ITH was associated with immunity-, keratinization-, and epidermal cell differentiation-related pathways.

CONCLUSION

CT-based ITH is an effective biomarker for identifying patients with ESCC who could benefit from ICI plus chemotherapy. Immunity-, keratinization-, and epidermal cell differentiation-related pathways may influence the patient's response to ICI plus chemotherapy.

Defining the optimal setting for transcriptomic analyses on blood samples for response prediction in immunotherapy-treated NSCLC patients

Transcriptomic profiling of blood immune cells offers a promising alternative to invasive, sampling bias-prone tissue-based biomarker assays for predicting immune checkpoint inhibitor (ICI) therapy response in non-small cell lung cancer (NSCLC) patients. However, the optimal analytical approach to identify systemic correlates of response still needs to be explored. We collected peripheral blood mononuclear cells and whole blood (WB) samples from 33 ICI-treated NSCLC patients before ICI treatment and at the first response evaluation. After bulk polyadenylated RNA-sequencing, we assessed differences in gene expression profiles between non-responders and responders using differential expression analysis, single sample gene set enrichment analysis (ssGSEA), and cell type deconvolution. We evaluated gene expression values, ssGSEA scores, and deconvolved cell type proportions to distinguish non-responders from responders via ROC curve (AUC) analysis, training a logistic regression classification model. Gene expression values and deconvolved proportions yielded the best results with WB samples after treatment (AUC = 0.87 and 0.85, respectively). Overall, ssGSEA scores showed superior classification performance across all sample types and timepoints (AUC > 0.7). In conclusion, transcriptomic analysis through ssGSEA demonstrated the best performance as a non-invasive biomarker for predicting clinical benefit in ICI-treated NSCLC patients, with gene expression and deconvolution on post-treatment WB samples also showing promising results.

Chemotherapy combined with immune checkpoint inhibitors may overcome the detrimental effect of high neutrophil-to-lymphocyte ratio prior to treatment in esophageal cancer patients

Introduction

Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for esophageal cancer (EC). Although ICIs enable long-term survival in some patients, the efficacy of ICIs varies widely among patients. Therefore, predictive biomarkers are necessary for identifying patients who are most likely to benefit from ICIs to improve the efficacy of the treatment. We retrospectively analyzed the outcomes of combination therapy, including nivolumab plus ipilimumab or chemotherapy plus anti-programmed cell death 1 (PD-1) antibodies in our institute to identify biomarkers.

Methods

Twenty-seven patients received nivolumab plus ipilimumab, and thirty-six patients received chemotherapy plus anti-PD-1 antibodies were included in this study. We analyzed patient characteristics, efficacy, and safety. Multivariable analysis of biomarkers evaluated the correlation among overall survival (OS), progression-free survival (PFS), and the following variables: body mass index, performance status, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein level, and albumin level before treatment.

Results

In multivariable analysis, albumin level was significantly correlated with PFS in the cisplatin plus 5-fluorouracil (CF) plus pembrolizumab group. NLR and albumin level were significantly correlated with OS in the nivolumab plus ipilimumab group. Other variables, including PS, BMI, and CRP did not correlate with any of the outcomes.

Conclusions

High NLR in EC patients prior to treatment was significantly less effective for ICIs. In chemotherapy combined with ICIs, NLR before the treatment was not associated with treatment efficacy, suggesting combination chemotherapy may be beneficial for EC patients with high NLR. NLR may be an indicator of immunocompetence in anti-tumor immunity and a convenient predictive biomarker for selecting appropriate treatments including ICIs.

Development and validation of a new tool to estimate early mortality in patients with advanced cancer treated with immunotherapy

BACKGROUND

Immune checkpoint inhibitors (ICIs) are standard treatments for advanced solid cancers. Resistance to ICIs, both primary and secondary, poses challenges, with early mortality (EM) within 30-90 days indicating a lack of benefit. Prognostic factors for EM, including the lung immune prognostic index (LIPI), remain underexplored.

METHODS

We performed a retrospective, observational study including patients affected by advanced solid tumors, treated with ICI as single agent or combined with other agents. Logistic regression models identified factors associated with EM and 90-day progression risks. A nomogram for predicting 90-day mortality was built and validated within an external cohort.

RESULTS

In total, 637 patients received ICIs (single agent or in combination with other drugs) for advanced solid tumors. Most patients were male (61.9%), with NSCLC as the prevalent tumor (61.8%). Within the cohort, 21.3% died within 90 days, 8.4% died within 30 days, and 34.5% experienced early progression. Factors independently associated with 90-day mortality included ECOG PS 2 and a high/intermediate LIPI score. For 30-day mortality, lung metastasis and a high/intermediate LIPI score were independent risk factors. Regarding early progression, high/intermediate LIPI score was independently associated. A predictive nomogram for 90-day mortality combining LIPI and ECOG PS achieved an AUC of 0.76 (95% CI 0.71-0.81). The discrimination ability of the nomogram was confirmed in the external validation cohort (n = 255) (AUC 0.72, 95% CI 0.64-0.80).

CONCLUSION

LIPI and ECOG PS independently were able to estimate 90-day mortality, with LIPI also demonstrating prognostic validity for 30-day mortality and early progression.

Granulocytes and mast cells in AllergoOncology-Bridging allergy to cancer: An EAACI position paper

Derived from the myeloid lineage, granulocytes, including basophils, eosinophils, and neutrophils, along with mast cells, play important, often disparate, roles across the allergic disease spectrum. While these cells and their mediators are commonly associated with allergic inflammation, they also exhibit several functions either promoting or restricting tumor growth. In this Position Paper we discuss common granulocyte and mast cell features relating to immunomodulatory functions in allergy and in cancer. We highlight key mechanisms which may inform cancer treatment and propose pertinent areas for future research. We suggest areas where understanding the communication between granulocytes, mast cells, and the tumor microenvironment, will be crucial for identifying immune mechanisms that may be harnessed to counteract tumor development. For example, a comprehensive understanding of allergic and immune factors driving distinct neutrophil states and those mechanisms that link mast cells with immunotherapy resistance, might enable targeted manipulation of specific subpopulations, leading to precision immunotherapy in cancer. We recommend specific areas of investigation in AllergoOncology and knowledge exchange across disease contexts to uncover pertinent reciprocal functions in allergy and cancer and allow therapeutic manipulation of these powerful cell populations. These will help address the unmet needs in stratifying and managing patients with allergic diseases and cancer.

Derived neutrophil-to-lymphocyte ratio has the potential to predict safety and outcomes of durvalumab after chemoradiation in non-small cell lung cancer

The usefulness of the derived neutrophil-to-lymphocyte ratio (dNLR) and its dynamics before/after durvalumab consolidation therapy to predict safety or efficacy remains unclear. We retrospectively reviewed patients with locally advanced non-small cell lung cancer treated with durvalumab consolidation therapy after chemoradiotherapy (D group) or chemoradiotherapy alone (non-D group) at multiple institutions. We investigated the association between dNLR, or its dynamics, and pneumonitis, checkpoint inhibitor-related pneumonitis (CIP), irAEs, and efficacy. Ninety-eight and fifty-six patients were enrolled in the D and non-D groups, respectively. The dNLR at baseline was significantly lower in patients who experienced irAEs or CIP than in those who did not. The low dNLR group, 28 days following durvalumab consolidation therapy (dNLR28 ≤ 3), demonstrated longer progression-free survival (PFS) and overall survival (OS) than the high dNLR group (dNLR28 > 3) (PFS, hazard ratio [HR] 0.44, 95% confidence interval [CI] 0.22-0.88, p = 0.020; OS, HR 0.39, 95% CI 0.16-0.94, p = 0.037). Among patients with high dNLR at baseline (dNLR > 3), the dNLR28 ≤ 3 group showed longer PFS than the dNLR28 > 3 group (p = 0.010). The dNLR is a predictive factor for irAEs and CIP in patients receiving durvalumab consolidation therapy. The dNLR at 28 days after durvalumab consolidation therapy and its dynamics predict favorable outcomes.

Derived Neutrophils to Lymphocyte Ratio Predicts Survival Benefit from TPF Induction Chemotherapy in Local Advanced Oral Squamous Cellular Carcinoma

BACKGROUND

This study aimed to evaluate the derived neutrophil to lymphocyte ratio (dNLR) in predicting the prognosis of patients with locally advanced oral squamous cell carcinoma (LAOSCC) and to assess the survival benefits from docetaxel, cisplatin, and 5-fluorouracil (5-FU) (TPF) induction chemotherapy (IC).

METHODS

Patients from a phase III trial involving TPF IC in stage III/IVA OSCC patients (NCT01542931) were enrolled. Receiver operating characteristic curves were constructed, and the area under the curve was computed to determine dNLR cutoff points. Kaplan-Meier survival estimates and Cox proportional hazards models were used for longitudinal analysis.

RESULTS

A total of 224 patients were identified (median age: 55.4 years; range: 26 to 75 years; median follow-up: 90 months; range: 3.2 to 93 months). The cutoff point for the dNLR was 1.555. Multivariate analysis showed that the dNLR was an independent negative predictive factor for survival (overall survival (OS): hazard ratio (HR) = 1.154, 95% confidence interval (CI): 1.018-1.309, p = 0.025; disease-free survival (DFS): HR = 1.123, 95% CI: 1.000-1.260, p = 0.050; local recurrence-free survival (LRFS): HR = 1.134, 95% CI: 1.002-1.283, p = 0.047; distant metastasis-free survival (DMFS): HR = 1.146, 95% CI: 1.010-1.300, p = 0.035). A low dNLR combined with cTNM stage III disease predicted benefit from TPF IC for the patients [OS (χ2 = 4.674, p = 0.031), DFS (χ2 = 7.134, p = 0.008), LRFS (χ2 = 5.937, p = 0.015), and DMFS (χ2 = 4.832, p = 0.028)].

CONCLUSIONS

The dNLR is an independent negative predictive factor in LAOSCC patients. Patients with cTNM stage III disease and a low dNLR can benefit from TPF IC.

Machine learning models for predicting of PD-1 treatment efficacy in Pan-cancer patients based on routine hematologic and biochemical parameters

Immune checkpoint blockade therapy targeting the programmed death-1(PD-1) pathway has shown remarkable efficacy and durable response in patients with various cancer types. Early prediction of therapeutic efficacy is important for optimizing treatment plans and avoiding potential side effects. In this work, we developed an efficient machine learning prediction method using routine hematologic and biochemical parameters to predict the efficacy of PD-1 combination treatment in Pan-Cancer patients. A total of 431 patients with nasopharyngeal carcinoma, esophageal cancer and lung cancer who underwent PD-1 checkpoint inhibitor combination therapy were included in this study. Patients were divided into two groups: progressive disease (PD) and disease control (DC) groups. Hematologic and biochemical parameters were collected before and at the third week of PD-1 therapy. Six machine learning models were developed and trained to predict the efficacy of PD-1 combination therapy at 8-12 weeks. Analysis of 57 blood biomarkers before and after three weeks of PD-1 combination therapy through statistical analysis, heatmaps, and principal component analysis did not accurately predict treatment outcome. However, with machine learning models, both the AdaBoost classifier and GBDT demonstrated high levels of prediction efficiency, with clinically acceptable AUC values exceeding 0.7. The AdaBoost classifier exhibited the highest performance among the 6 machine learning models, with a sensitivity of 0.85 and a specificity of 0.79. Our study demonstrated the potential of machine learning to predict the efficacy of PD-1 combination therapy based on changes in hematologic and biochemical parameters.

The Multifaceted Role of Neutrophils in NSCLC in the Era of Immune Checkpoint Inhibitors

Lung cancer is the most common cause of cancer-related death in both males and females in the U.S. and non-small-cell lung cancer (NSCLC) accounts for 85%. Although the use of first- or second-line immune checkpoint inhibitors (ICIs) exhibits remarkable clinical benefits, resistance to ICIs develops over time and dampens the efficacy of ICIs in patients. Tumor-associated neutrophils (TANs) have an important role in modulating the tumor microenvironment (TME) and tumor immune response. The major challenge in the field is to characterize the TANs in NSCLC TME and understand the link between TAN-related immunosuppression with ICI treatment response. In this review, we summarize the current studies of neutrophil interaction with malignant cells, T-cells, and other components in the TME. Ongoing clinical trials are aimed at utilizing reagents that have putative effects on tumor-associated neutrophils, in combination with ICI. Elevated neutrophil populations and neutrophil-associated factors could be potential therapeutic targets to enhance anti-PD1 treatment in NSCLC.

Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer

Background

Immune checkpoint inhibitors (ICIs) have reshaped the treatment landscape of small cell lung cancer (SCLC), but only a minority of patients benefit from this therapy. Therefore, it is critical to identify potential risk factors that could predict the efficacy of ICI treatment in SCLC patients and identify patient subgroups who may benefit the most from ICI therapy.

Methods

Our study included a total of 183 SCLC patients who had received at least one dose of ICI treatment. We utilized both logistic regression and Cox proportional hazard regression to evaluate whether various patient clinical factors and serum biomarkers could serve as predictors of patient response to treatment and overall survival (OS) during ICI therapy.

Results

Logistic regression showed that patients with a history of surgery (p=0.003, OR 9.06, 95% CI: (2.17, 37.9)) and no metastasis (p=0.008, OR 7.82, 95% CI: (1.73, 35.4)) exhibited a higher odds of response to ICI treatment. Cox regression analyses demonstrated that pretreatment blood albumin (p=0.003, HR 1.72, 95% CI: (1.21, 2.45)) and derived neutrophil to lymphocyte ratio (dNLR) (p=0.003, HR 1.71, 95% CI: (1.20-2.44)) were independent predictors for OS in SCLC patients. By establishing a pre-treatment prognostic scoring system based on baseline albumin and dNLR, we found that patients with high albumin and low dNLR exhibited a significantly better prognosis than those with low albumin and high dNLR in both the full (P<.0001, HR 0.33, 95% CI: 0.20-0.55) and the metastatic cohort (P<.0001, HR 0.28, 95% CI: 0.15-0.51). The better prognostic group also had younger age, higher BMI and lower systemic inflammatory biomarker values than the unfavorable group (P<.0001).

Conclusion

Our data reveals the significant role of metastasis status and treatment history in predicting the initial response of SCLC patients to ICI treatment. However, baseline serum albumin and dNLR provide a more precise prognostic prediction for patient OS. The scoring system based on albumin and dNLR enhances the ability to stratify patient prognosis and holds the potential to guide clinical decision-making for SCLC patients undergoing ICI therapy.

Immunohistochemistry assessment of tissue neutrophil-to-lymphocyte ratio predicts outcomes in melanoma patients treated with anti-programmed cell death 1 therapy

Elevated neutrophil-to-lymphocyte ratio (NLR) is associated with diminished immunotherapy response in metastatic melanoma. Although NLR assessment in peripheral blood is established, tissue dynamics remain insufficiently explored. This study aimed to evaluate tissue NLR (tNLR)'s predictive potential through immunohistochemistry in immunotherapy-treated melanoma. Fifty melanoma patients who underwent anti-programmed cell death 1 (PD-1) therapy were assessed. Hematological, clinical and tumor features were collected from medical records. Responses were categorized using the Response Evaluation Criteria in Solid Tumors for immunotherapy (iRECIST) guidelines. Immunohistochemistry for tumor-infiltrating T cells (cluster differentiation 3) and neutrophils (myeloperoxidase) was performed on formalin-fixed paraffin-embedded tumor samples. NLR, derived NLR (dNLR) and tNLR were calculated. Overall survival (OS) and survival following immunotherapy (SFI) were calculated from diagnosis or immunotherapy start to loss of follow-up or death. Patients with high tNLR presented improved OS ( P =  0.038) and SFI with anti-PD-1 therapy ( P =  0.006). Both NLR and dNLR were associated with OS ( P =  0.038 and P =  0.046, respectively) and SFI ( P =  0.001 and P =  0.019, respectively). NLR was also associated with immunotherapy response ( P =  0.007). In conclusion, tNLR emerged as a novel potential biomarker of enhanced survival post anti-PD-1 therapy, in contrast to classical NLR and dNLR markers.

Predictive impact of sarcopenia in advanced non-small cell lung cancer patients treated with immune checkpoint inhibitors: A retrospective study

Background

Sarcopenia, characterised by an ongoing loss of skeletal muscle mass and reduced strength and function, is frequently observed in patients with non-small cell lung cancer (NSCLC). However, the relationship between sarcopenia and the prognosis of NSCLC treated with immune checkpoint inhibitors (ICIs) remains unclear. This aimed to assess whether sarcopenia is an independent prognostic factor for survival in patients with advanced NSCLC receiving ICIs.

Methods

For this retrospective cohort study, we analysed the medical records of patients attending our hospital aged 18-75 years who were newly diagnosed with stage IIIB to stage IV NSCLC, and who had received ICIs as first- or second-line therapy between May 2019 and April 2022. The skeletal muscle index (SMI) was calculated from computed tomography (CT) images and relevant clinical characteristics within 4 weeks of initiating treatment and used to diagnose sarcopenia status. The Kaplan-Meier method and log-rank test were used to calculate and compare patients' progression-free survival (PFS). Cox proportional hazard regression was used to examine the associations between sarcopenia and survival outcomes. The chi-square test was used to compare treatment response outcomes, such as the objective response rate (ORR), disease control rate (DCR), and immunotherapy-related adverse events (irAEs), between individuals with and without sarcopenia. Additionally, the Student's t-test was utilised to compare SMI values between patients by their objective response (OR) and disease control (DC). Finally, the Mann-Whitney U test was used to compare nutritional and inflammatory indicators between the sarcopenia groups.

Results

The study enrolled 70 patients, of whom 34 (48.6%) were diagnosed with sarcopenia. The median PFS of patients with and without sarcopenia was 7.5 vs. 13.4 months, respectively (p = 0.006). The proportional hazards regression analysis showed sarcopenia to be an independent prognostic factor for shorter PFS (hazard ratio (HR): 0.504, 95% CI: 0.265-0.962, p = 0.038). Using chi square tests, we found significant differences in the ORR (20.59% vs. 58.33%, p = 0.001) and occurrence of any irAEs (44.1% vs. 22.2%, p = 0.028) between the sarcopenia and the non-sarcopenia groups, respectively. The Student's t-test showed a significant difference in SMI between the ORR group and the non-ORR group (49.99 ± 7.00 vs. 42.98 ± 2.18 cm2/m2, p = 0.0015). While the sarcopenia group were with significantly a lower CD4+/CD8+ ratios and a higher C-reactive protein (CRP) level (p = 0.026, p = 0.011, respectively). Conclusions: This study found that sarcopenia is a significant predictor of a poor prognosis for patients with advanced NSCLC receiving ICIs. Multiple inflammatory and immune functions related to prognosis also differ by sarcopenia status.

Dynamic surveillance of lymphocyte subsets in patients with non-small cell lung cancer during chemotherapy or combination immunotherapy for early prediction of efficacy

BACKGROUND

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths worldwide. Lymphocytes are the primary executors of the immune system and play essential roles in tumorigenesis and development. We investigated the dynamic changes in peripheral blood lymphocyte subsets to predict the efficacy of chemotherapy or combination immunotherapy in NSCLC.

METHODS

This retrospective study collected data from 81 patients with NSCLC who received treatments at the First Affiliated Hospital of Zhengzhou University from May 2021 to May 2023. Patients were divided into response and non-response groups, chemotherapy and combination immunotherapy groups, and first-line and multiline groups. We analyzed the absolute counts of each lymphocyte subset in the peripheral blood at baseline and after each treatment cycle. Within-group and between-group differences were analyzed using paired Wilcoxon signed-rank and Mann-Whitney U tests, respectively. The ability of lymphocyte subsets to predict treatment efficacy was analyzed using receiver operating characteristic curve and logistic regression.

RESULTS

The absolute counts of lymphocyte subsets in the response group significantly increased after the first cycle of chemotherapy or combination immunotherapy, whereas those in the non-response group showed persistent decreases. Ratios of lymphocyte subsets after the first treatment cycle to those at baseline were able to predict treatment efficacy early. Combination immunotherapy could increase lymphocyte counts compared to chemotherapy alone. In addition, patients with NSCLC receiving chemotherapy or combination immunotherapy for the first time mainly presented with elevated lymphocyte levels, whereas multiline patients showed continuous reductions.

CONCLUSION

Dynamic surveillance of lymphocyte subsets could reflect a more actual immune status and predict efficacy early. Combination immunotherapy protected lymphocyte levels from rapid decrease and patients undergoing multiline treatments were more prone to lymphopenia than those receiving first-line treatment. This study provides a reference for the early prediction of the efficacy of clinical tumor treatment for timely combination of immunotherapy or the improvement of immune status.

Biomarkers of pembrolizumab efficacy in advanced anal squamous cell carcinoma: analysis of a phase II clinical trial and a cohort of long-term responders

BACKGROUND

Recent trials suggest that programmed cell death 1 (PD-1)-directed immunotherapy may be beneficial for some patients with anal squamous cell carcinoma and biomarkers predictive of response are greatly needed.

METHODS

This multicenter phase II clinical trial (NCT02919969) enrolled patients with metastatic or locally advanced incurable anal squamous cell carcinoma (n=32). Patients received pembrolizumab 200 mg every 3 weeks. The primary endpoint of the trial was objective response rate (ORR). Exploratory objectives included analysis of potential predictive biomarkers including assessment of tumor-associated immune cell populations with multichannel immunofluorescence and analysis of circulating tumor tissue modified viral-human papillomavirus DNA (TTMV-HPV DNA) using serially collected blood samples. To characterize the clinical features of long-term responders, we combined data from our prospective trial with a retrospective cohort of patients with anal cancer treated with anti-PD-1 immunotherapy (n=18).

RESULTS

In the phase II study, the ORR to pembrolizumab monotherapy was 9.4% and the median progression-free survival was 2.2 months. Despite the high level of HPV positivity observed with circulating TTMV-HPV DNA testing, the majority of patients had low levels of tumor-associated CD8+PD-1+ T cells on pretreatment biopsy. Patients who benefited from pembrolizumab had decreasing TTMV-HPV DNA scores and a complete responder's TTMV-HPV DNA became undetectable. Long-term pembrolizumab responses were observed in one patient from the trial (5.3 years) and three patients (2.5, 6, and 8 years) from the retrospective cohort. Long-term responders had HPV-positive tumors, lacked liver metastases, and achieved a radiological complete response.

CONCLUSIONS

Pembrolizumab has durable efficacy in a rare subset of anal cancers. However, despite persistence of HPV infection, indicated by circulating HPV DNA, most advanced anal cancers have low numbers of tumor-associated CD8+PD-1+ T cells and are resistant to pembrolizumab.

Neutrophil-to-lymphocyte ratio is a prognostic factor reflecting immune condition of tumor microenvironment in squamous cell lung cancer

Inflammatory factors in the peripheral blood, such as the C-reactive protein level and neutrophil-to-lymphocyte ratio (NLR), are prognostic markers in multiple types of cancer, including non-small cell lung cancer (NSCLC). However, the association between inflammatory factors and prognosis based on histological types has not been adequately reported. In addition, the relationship between these factors and the immune condition of the tumor microenvironment (TME) is unclear. In this single center, retrospective study, we first investigated the relationship between preoperative inflammatory markers and clinical outcomes in 176 patients with NSCLC who underwent surgery. Lung adenocarcinoma (LUAD) showed no significant prognostic marker, whereas for lung squamous cell carcinoma (LUSC), a multivariate analysis showed that a high NLR was significantly associated with postoperative recurrence. In LUSC patients, the median time of postoperative recurrence-free survival in patients with a low NLR was longer than that in patients with a high NLR. We then compared the tumor-infiltrating lymphocyte (TIL) profile with inflammatory markers in peripheral blood and found that the NLR was negatively correlated with the frequencies of T cells and B cells in LUSC tissues. Thus, the NLR is a useful predictive biomarker for postoperative recurrence and may reflect the immune condition of the TME in LUSC.

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

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

Calculated inflammatory markers derived from complete blood count results, along with routine laboratory and clinical data, predict treatment failure of acute peritonitis in chronic peritoneal dialysis patients

BACKGROUND & AIMS

Complete blood count (CBC)-derived inflammatory markers are predictive biomarkers for the prognosis of many diseases. However, there was no study on patients with peritoneal dialysis-associated peritonitis (PDAP). We aimed to investigate the value of these markers in predicting treatment failure of acute peritonitis in chronic PD patients.

METHODS

The records of 138 peritonitis episodes were reviewed and divided into treatment success or failure groups in a single center for 10 years. CBC-derived markers and other routine data were recorded before peritonitis treatment was initiated. Univariate and multivariate regression analyses and the receiver operating characteristic (ROC) curve about the predictors of treatment outcomes were performed.

RESULTS

Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and derived NLR were significantly higher in the failure group. Univariate logistic regression results showed that NLR and PLR were risk factors of treatment outcomes. The backward stepwise multivariate logistic regression results demonstrated that NLR [adjusted odds ratio (aOR), 1.376; 95% confidence intervals (CI), 1.105-1.713; p = .004], PLR (aOR, 1.010; 95%CI, 1.004-1.017; p = .002) were risk factors, but hemoglobin-to-lymphocyte ratio (HLR) (aOR, 0.977; 95%CI, 0.963-0.991; p = .001), and SII (aOR, 0.999; 95%CI, 0.998-1.000; p = .040) were protective factors. A combination of age, PD vintage, Gram-positive peritonitis, staphylococcus aureus, culture-negative, NLR, PLR, HLR, and SII would improve prognostic performance. The area under this ROC curve was 0.85, higher than other factors.

CONCLUSIONS

NLR, PLR, HLR, and SII were associated with PDAP outcomes. Age, PD vintage, NLR, and PLR were significant risk factors in PDAP patients.

Associations of circulating immunomarkers with the efficacy of immunotherapy for primary hepatic carcinoma

BACKGROUND

Peripheral blood immunomarkers are associated with prognosis in patients with solid tumors receiving chemotherapy or immunotherapy. In this study, the associations of circulating neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR), as well as their dynamic changes were investigated in relation to the efficacy of immunotherapy in patients with primary liver cancer.

METHODS

Comparisons were made between NLR, MLR, and PLR among individuals exhibiting disease control (defined as the best response of partial response [PR] or stable disease [SD]) and those with progressive disease (PD). Additionally, disease control rate (DCR), overall survival (OS), and progression-free survival (PFS) were compared between individuals with different NLR, MLR, and PLR levels before initiating palliative immunotherapy. Furthermore, comparisons were made between patients with different alterations in the ratios at the second cycle of immunotherapy compared to baseline. These analyses were performed using univariate and multivariate approaches. A total of 119 Chinese patients with liver cancer who underwent immunotherapy were included in this study, which focused on hepatocellular carcinoma (HCC).

RESULTS

In cases with HCC (n = 104), the cutoffs of NLR, MLR, and PLR to differentiate treatment responders from nonresponders were 3.38, 0.28, and 227.18, respectively. Patients with the best response of PR or SD had significantly lower NLR and MLR. Patients with NLR <3.38 and those with MLR <0.28 significantly had longer OS and PFS than their counterparts, and those with PLR <227.18 had significantly longer PFS, both in overall patients and in various patient subgroups. Lower NLR, MLR, or PLR was associated with earlier BCLC stage, fewer metastatic sites, less frequent extrahepatic metastasis, or better performance status. For individuals who had an unfavorable baseline NLR ≥3.38, MLR ≥0.28, or a favorable baseline PLR <227.18 prior to first immunotherapy, a decrease in NLR, MLR, or PLR at Cycle 2 of immunotherapy was significantly associated with a higher DCR.

CONCLUSIONS

Among patients with HCC who received immunotherapy, lower NLR, and MLR at baseline in overall patients were significantly associated with better disease control and more favorable survival outcomes (both OS and PFS), and lower PLR was significantly associated with longer PFS. The findings of this research may offer useful hints foranoptimized selection of patients with liver cancer who may benefit more from immunotherapy.

Targeting tumor-associated macrophage: an adjuvant strategy for lung cancer therapy

The emergence of immunotherapy has revolutionized the treatment landscape for various types of cancer. Nevertheless, lung cancer remains one of the leading causes of cancer-related mortality worldwide due to the development of resistance in most patients. As one of the most abundant groups of immune cells in the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play crucial and complex roles in the development of lung cancer, including the regulation of immunosuppressive TME remodeling, metabolic reprogramming, neoangiogenesis, metastasis, and promotion of tumoral neurogenesis. Hence, relevant strategies for lung cancer therapy, such as inhibition of macrophage recruitment, TAM reprograming, depletion of TAMs, and engineering of TAMs for drug delivery, have been developed. Based on the satisfactory treatment effect of TAM-targeted therapy, recent studies also investigated its synergistic effect with current therapies for lung cancer, including immunotherapy, radiotherapy, chemotherapy, anti-epidermal growth factor receptor (anti-EGFR) treatment, or photodynamic therapy. Thus, in this article, we summarized the key mechanisms of TAMs contributing to lung cancer progression and elaborated on the novel therapeutic strategies against TAMs. We also discussed the therapeutic potential of TAM targeting as adjuvant therapy in the current treatment of lung cancer, particularly highlighting the TAM-centered strategies for improving the efficacy of anti-programmed cell death-1/programmed cell death-ligand 1 (anti-PD-1/PD-L1) treatment.

Clinical and Molecular Features of Long-term Response to Immune Checkpoint Inhibitors in Patients with Advanced Non-Small Cell Lung Cancer

PURPOSE

We sought to identify features of patients with advanced non-small cell lung cancer (NSCLC) who achieve long-term response (LTR) to immune checkpoint inhibitors (ICI), and how these might differ from features predictive of short-term response (STR).

EXPERIMENTAL DESIGN

We performed a multicenter retrospective analysis of patients with advanced NSCLC treated with ICIs between 2011 and 2022. LTR and STR were defined as response ≥ 24 months and response < 12 months, respectively. Tumor programmed death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), next-generation sequencing (NGS), and whole-exome sequencing (WES) data were analyzed to identify characteristics enriched in patients achieving LTR compared with STR and non-LTR.

RESULTS

Among 3,118 patients, 8% achieved LTR and 7% achieved STR, with 5-year overall survival (OS) of 81% and 18% among LTR and STR patients, respectively. High TMB (≥50th percentile) enriched for LTR compared with STR (P = 0.001) and non-LTR (P < 0.001). Whereas PD-L1 ≥ 50% enriched for LTR compared with non-LTR (P < 0.001), PD-L1 ≥ 50% did not enrich for LTR compared with STR (P = 0.181). Nonsquamous histology (P = 0.040) and increasing depth of response [median best overall response (BOR) -65% vs. -46%, P < 0.001] also associated with LTR compared with STR; no individual genomic alterations were uniquely enriched among LTR patients.

CONCLUSIONS

Among patients with advanced NSCLC treated with ICIs, distinct features including high TMB, nonsquamous histology, and depth of radiographic improvement distinguish patients poised to achieve LTR compared with initial response followed by progression, whereas high PD-L1 does not.

Progresses in biomarkers for cancer immunotherapy

Currently, checkpoint inhibitor-based immunotherapy has emerged as prevailing treatment modality for diverse cancers. However, immunotherapy as a first-line therapy has not consistently yielded durable responses. Moreover, the risk of immune-related adverse events increases with combination regimens. Thus, the development of predictive biomarkers is needed to optimize individuals benefit, minimize risk of toxicities, and guide combination approaches. The greatest focus has been on tumor programmed cell death-ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational burden (TMB). However, there remains a subject of debate due to thresholds variability and significant heterogeneity. Major unmet challenges in immunotherapy are the discovery and validation of predictive biomarkers. Here, we show the status of tumor PD-L1, MSI, TMB, and emerging data on novel biomarker strategies with oncogenic signaling and epigenetic regulation. Considering the exploration of peripheral and intestinal immunity has served as noninvasive alternative in predicting immunotherapy, this review also summarizes current data in systemic immunity, encompassing solute PD-L1 and TMB, circulating tumor DNA and infiltrating lymphocytes, routine emerging inflammatory markers and cytokines, as well as gut microbiota. This review provides up-to-date information on the evolving field of currently available biomarkers in predicting immunotherapy. Future exploration of novel biomarkers is warranted.

Role of neutrophils on cancer cells and other immune cells in the tumor microenvironment

The notion that neutrophils only perform a specific set of single functions in the body has changed with the advancement of research methods. As the most abundant myeloid cells in human blood, neutrophils are currently emerging as important regulators of cancer. Given the duality of neutrophils, neutrophil-based tumor therapy has been clinically carried out in recent years and has made some progress. But due to the complexity of the tumor microenvironment, the therapeutic effect is still not satisfactory. Therefore, in this review, we discuss the direct interaction of neutrophils with the five most common cancer cells and other immune cells in the tumor microenvironment. Also, this review covered current limitations, potential future possibilities, and therapeutic approaches targeting neutrophil function in cancer therapy.

Combination of multiple omics techniques for a personalized therapy or treatment selection

Despite targeted therapies and immunotherapies have revolutionized the treatment of cancer patients, only a limited number of patients have long-term responses. Moreover, due to differences within cancer patients in the tumor mutational burden, composition of the tumor microenvironment as well as of the peripheral immune system and microbiome, and in the development of immune escape mechanisms, there is no "one fit all" therapy. Thus, the treatment of patients must be personalized based on the specific molecular, immunologic and/or metabolic landscape of their tumor. In order to identify for each patient the best possible therapy, different approaches should be employed and combined. These include (i) the use of predictive biomarkers identified on large cohorts of patients with the same tumor type and (ii) the evaluation of the individual tumor with "omics"-based analyses as well as its ex vivo characterization for susceptibility to different therapies.

Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies

Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.

Real-world outcomes of pembrolizumab for platinum-refractory advanced urothelial carcinoma: Efficacy, safety, and evidence for trial-unfit patients

Pembrolizumab, monoclonal antibody targeting programmed cell death 1, is widely used for platinum-refractory urothelial carcinoma (UC) patients. Although the survival benefit of pembrolizumab was proven in the well-designed phase III trial, these data represent only a part of patients due to strictly defined eligibility criteria. The patients' characteristics in the clinical practice are much more heterogenous than those of trial participants. The real-world experience is useful to validate the trial result and find suitable candidates for the treatment. Similarly, real-world data plays a significant role in addressing the efficacy and safety of special populations, such as poor performance status or older patients. This review summarizes the real-world evidence on pembrolizumab for platinum-refractory UCs and discusses the clinical risk factors and efficacy for trial-ineligible patients.

Circulating immune cell dynamics as outcome predictors for immunotherapy in non-small cell lung cancer

The use of immune checkpoint inhibitors (ICIs) continues to transform the therapeutic landscape of non-small cell lung cancer (NSCLC), with these drugs now being evaluated at every stage of the disease. In contrast to these advances, little progress has been made with respect to reliable predictive biomarkers that can inform clinicians on therapeutic efficacy. All current biomarkers for outcome prediction, including PD-L1, tumor mutational burden or complex immune gene expression signatures, require access to tumor tissue. Besides the invasive nature of the sampling procedure, other disadvantages of tumor tissue biopsies are the inability to capture the complete spatial heterogeneity of the tumor and the difficulty to perform longitudinal follow-up on treatment. A concept emerges in which systemic immune events developing at a distance from the tumor reflect local response or resistance to immunotherapy. The importance of this cancer 'macroenvironment', which can be deciphered by comprehensive analysis of peripheral blood immune cell subsets, has been demonstrated in several cutting-edge preclinical reports, and is corroborated by intriguing data emerging from ICI-treated patients. In this review, we will provide the biological rationale underlying the potential of blood immune cell-based biomarkers in guiding treatment decision in immunotherapy-eligible NSCLC patients. Finally, we will describe new techniques that will facilitate the discovery of more immune cell subpopulations with potential to become predictive biomarkers, and reflect on ways and the remaining challenges to bring this type of analysis to the routine clinical care in the near future.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil

BACKGROUND

The cellular dynamics in the tumour microenvironment (TME) along with non-small cell lung cancer (NSCLC) progression remain unclear.

METHODS

Multiplex immunofluorescence test detecting 10 immune-related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single-cell transcriptomic atlas of PT (n = 4) and paired tumour-draining lymph nodes (TDLNs) (n = 5 for tumour-invaded, n = 3 for tumour-free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array-Express databases were also used to validate the discoveries.

RESULTS

Spatial distances of CD4+ T cells-CD38+ T cells, CD4+ T cells-neutrophils and CD38+ T cells-neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location-dependent prognostic effects. A high abundance of stromal neutrophils improved disease-free survival in the early-stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid-to-late-stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour-associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN-0 with antigen-presenting function, TAN-1 with strong expression of interferon (IFN)-stimulated genes, the pro-tumour TAN-2 subcluster, the classical subset (TAN-3) and the pro-inflammatory subtype (TAN-4). Loss of IFN-stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes-based model was established, showing that low-risk patients had longer overall survival time and may respond better to immunotherapy.

CONCLUSIONS

The cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.

Real-world outcomes of immunotherapy with or without chemotherapy in first-line treatment of advanced non-small cell lung cancer

Background

Immunotherapy alone (mono-IT) or combined with chemotherapy (chemo-IT) has recently become the cornerstone of first-line treatment for advanced non-small cell lung cancer (NSCLC) patients. Here, real-world outcomes of first-line mono-IT and chemo-IT of advanced NSCLC treated within routine clinical practice at a single academic center in the Central Eastern European (CEE) region are presented.

Materials and methods

A total of 176 consecutive patients with advanced NSCLC treated with mono-IT (118 patients) or chemo-IT (58 patients) were included. At the participating institution, all medical data relevant for providing oncology care are collected prospectively and in a standardized manner using purposely created pro-forms. Adverse events (AEs) were recorded and graded according to Common Terminology Criteria for Adverse Events (CTCAE). The Kaplan-Meier method was used to estimate median overall survival (mOS) and median duration of treatment (mDOT).

Results

The 118 patients in the mono-IT cohort had a median age of 64 years, most were male (59%), 20% had ECOG PS ≥2, and 14% had controlled CNS metastases at baseline. With a median follow-up time (mFU) of 24.1 months, the mOS was 19.4 months (95% CI, 11.1-27.6), and the mDOT was 5.0 months (95% CI, 3.5-6.5). The 1-year OS was 62%. The 58 patients in the chemo-IT cohort had a median age of 64 years, most were male (64%), 9% had ECOG PS ≥2, and 7% had controlled CNS metastases at baseline. With a mFU of 15.5 months, the mOS was 21.3 months (95% CI, 15.9-26.7), and the mDOT was 12.0 months (95% CI, 8.3-15.6). The 1-year OS was 75%. Adverse events of severe grade were recorded in 18% and 26% of patients, and immunotherapy discontinuation due to AEs occurred in 19% and 9% in the mono-IT and chemo-IT groups, respectively. No treatment-related deaths were recorded.

Conclusion

The results from the present real-world observational study from a CEE country suggest similar effectiveness and safety of first-line mono-IT and chemo-IT in patients with advanced NSCLC to those observed in randomized clinical trials. However, continuous follow-up will offer better insight into the magnitude of long-term benefits in routine clinical practice.

Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction

Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15-60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy.

Modeling mortality risk in patients with severe COVID-19 from Mexico

Background

Severe acute respiratory syndrome caused by a coronavirus (SARS-CoV-2) is responsible for the COVID-19 disease pandemic that began in Wuhan, China, in December 2019. Since then, nearly seven million deaths have occurred worldwide due to COVID-19. Mexicans are especially vulnerable to the COVID-19 pandemic as Mexico has nearly the worst observed case-fatality ratio (4.5%). As Mexican Latinos represent a vulnerable population, this study aimed to determine significant predictors of mortality in Mexicans with COVID-19 who were admitted to a large acute care hospital.

Methods

In this observational, cross-sectional study, 247 adult patients participated. These patients were consecutively admitted to a third-level referral center in Yucatan, Mexico, from March 1st, 2020, to August 31st, 2020, with COVID-19-related symptoms. Lasso logistic and binary logistic regression were used to identify clinical predictors of death.

Results

After a hospital stay of about eight days, 146 (60%) patients were discharged; however, 40% died by the twelfth day (on average) after hospital admission. Out of 22 possible predictors, five crucial predictors of death were found, ranked by the most to least important: (1) needing to be placed on a mechanical ventilator, (2) reduced platelet concentration at admission, (3) increased derived neutrophil to lymphocyte ratio, (4) increased age, and (5) reduced pulse oximetry saturation at admission. The model revealed that these five variables shared ~83% variance in outcome.

Conclusion

Of the 247 Mexican Latinos patients admitted with COVID-19, 40% died 12  days after admission. The patients' need for mechanical ventilation (due to severe illness) was the most important predictor of mortality, as it increased the odds of death by nearly 200-fold.

Soluble biomarkers to predict clinical outcomes in non-small cell lung cancer treated by immune checkpoints inhibitors

Lung cancer remains the first cause of cancer-related death despite many therapeutic innovations, including immune checkpoint inhibitors (ICI). ICI are now well used in daily practice at late metastatic stages and locally advanced stages after a chemo-radiation. ICI are also emerging in the peri-operative context. However, all patients do not benefit from ICI and even suffer from additional immune side effects. A current challenge remains to identify patients eligible for ICI and benefiting from these drugs. Currently, the prediction of ICI response is only supported by Programmed death-ligand 1 (PD-L1) tumor expression with perfectible results and limitations inherent to tumor-biopsy specimen analysis. Here, we reviewed alternative markers based on liquid biopsy and focused on the most promising biomarkers to modify clinical practice, including non-tumoral blood cell count such as absolute neutrophil counts, platelet to lymphocyte ratio, neutrophil to lymphocyte ratio, and derived neutrophil to lymphocyte ratio. We also discussed soluble-derived immune checkpoint-related products such as sPD-L1, circulating tumor cells (detection, count, and marker expression), and circulating tumor DNA-related products. Finally, we explored perspectives for liquid biopsies in the immune landscape and discussed how they could be implemented into lung cancer management with a potential biological-driven decision.

Efficacy of radiotherapy in combination with first-line immunotherapy and chemotherapy for advanced lung squamous cell carcinoma: a propensity score analysis

Aim

To compare the efficacy and safety of radiotherapy in combination with immunotherapy after achieving disease control from the first-line combination therapy of platinum-based chemotherapy and immunotherapy for advanced lung squamous cell carcinoma (LUSC).

Methods

This study retrospectively evaluated the patients with advanced LUSC treated with the combination of radiotherapy with immunotherapy and chemotherapy (ICRT group, n = 52) or immunotherapy and chemotherapy (ICT group, n = 63) as the first-line treatment from April 2018 to April 2022. Using propensity score matching (PSM), 50 pairs were created, while the confounders and bias were controlled. The objective response rate (ORR), duration of overall response (DOR), progression-free survival (PFS), overall survival (OS), and adverse events were analyzed in the two groups. The PFS and OS were re-analyzed separately for patients treated with thoracic radiotherapy.

Results

After PSM, the median PFS (12.23 vs. 7.43 months; P <0.001) and median OS (19.7 vs. 12.9 months; P <0.001) were significantly longer in the ICRT group than those in the ICT group. Both the PFS and OS rates were also significantly higher in the ICRT group than those in the ICT group, except for the OS rates in the 6th and 12th months. The mDOR of the ICRT group patients (17.10 vs. 8.27 months; P <0.001) was significantly higher than that of the ICT group patients. The median PFS, median OS, and local control rate were significantly longer in the thoracic radiotherapy group than in the control group. Radiation pneumonia was the most common adverse effect after radiotherapy; however, no treatment-related deaths occurred. The Cox regression analysis showed that ECOG scores 0-1, presence of necrosis in the tumor, radiotherapy, and optimal efficacy better than the stable disease (SD) were independent factors, affecting the PFS, while the patients with recurrent post-operative, pre-treatment NLR, radiotherapy, and optimal efficacy better than SD were the independent factors, affecting the OS.

Conclusions

The combination of radiotherapy with systematic immunotherapy and chemotherapy for the advanced LUSC was effective with tolerable adverse effects.

Albumin-derived Neutrophil-to-Lymphocyte Ratio Score as a Marker of Nivolumab Treatment Sensitivity in Gastric Cancer: A Multicenter Study

BACKGROUND/AIM

Establishment of powerful and easy-to-evaluate biomarkers that can predict immune checkpoint inhibitor sensitivity in patients with gastric cancer (GC) would be highly useful. The albumin-derived neutrophil-to-lymphocyte ratio (Alb-dNLR) score reportedly is an excellent measure of both immunity and nutritional status. However, the association between nivolumab treatment sensitivity and Alb-dNLR in GC has also not been adequately investigated. This multicenter retrospective study was designed to evaluate the association of Alb-dNLR with therapeutic sensitivity of nivolumab in GC patients.

PATIENTS AND METHODS

This was a retrospective multicenter study with patients from five sites. The data from 58 patients who received nivolumab for postoperative recurrent or unresectable advanced GC between October 2017 and December 2018 were analyzed. Blood tests had been performed before nivolumab administration. We analyzed the correlation between the Alb-dNLR score and clinicopathological factors, including best overall response.

RESULTS

Of the 58 patients, 21 (36.2%) comprised the disease control (DC) group and 37 (63.8%) comprised the progressive disease (PD) group. The nivolumab treatment responses were subjected to receiver operating characteristic analysis. The cutoff value was set to 2.90 g/dl for Alb and to 3.55 for dNLR. All eight patients in the high Alb-dNLR group had PD (p=0.0049). The low Alb-dNLR group had significantly better overall survival (p=0.0023) and progression-free survival rates (p<0.0001).

CONCLUSION

The Alb-dNLR score was a very simple and sensitive predictor of nivolumab therapeutic sensitivity and has very good biomarker properties.

The predictive value of inflammatory biomarkers for major pathological response in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy and its association with the immune-related tumor microenvironment: a multi-center study

BACKGROUND

Inflammatory biomarkers in the peripheral blood have been established as predictors for immunotherapeutic efficacy in advanced non-small cell lung cancer (NSCLC). Whether they can also predict major pathological response (MPR) in neoadjuvant setting remains unclear.

METHODS

In this multi-center retrospective study, 122 and 92 stage I-IIIB NSCLC patients from six hospitals who received neoadjuvant chemoimmunotherapy followed by surgery were included in the discovery and external validation cohort, respectively. Baseline and on-treatment neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) were calculated and associated with MPR. Furthermore, resected tumor samples from 37 patients were collected for RNA-sequencing to investigate the immune-related tumor microenvironment.

RESULTS

In both the discovery and validation cohorts, the on-treatment NLR, dNLR, PLR, and SII levels were significantly lower in the patients with MPR versus non-MPR. On-treatment SII remained an independent predictor of MPR in multivariate logistic regression analysis. The area under the curve (AUC) of on-treatment SII for predicting MPR was 0.75 (95%CI, 0.67-0.84) in the discovery cohort. Moreover, the predictive value was further improved by combining the on-treatment SII and radiological tumor regression data, demonstrating an AUC of 0.82 (95%CI, 0.74-0.90). The predictive accuracy was validated in the external cohort. Compared with the SII-high group, patients with SII-Low were associated with the activated B cell receptor signaling pathway and a higher intratumoral immune cell infiltration level.

CONCLUSIONS

On-treatment SII was independently associated with MPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy. Further prospective studies are warranted.

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.

Impact of Frailty on Outcomes of First-Line Pembrolizumab Monotherapy in a Real-World Population with Advanced Non-Small Cell Lung Cancer

ICIs have been able to improve overall survival in advanced-stage lung cancer. The benefit of this therapy is limited in patients with poor ECOG PS. However, this scale is imprecise and can be influenced by different factors, such as frailty. Cancer patients have a high risk of frailty independently of age. In this observational, single-center, retrospective study, we investigated the effect of frailty on the effectiveness of pembrolizumab in first-line use in a cohort of 101 patients with metastatic NSCLC. Frailty was determined using a frailty score system developed by Sakakida et al. Univariate and multivariate analysis was performed to determine the prognostic role of frailty on OS and PFS. Median OS was significantly higher in patients with low frailty compared with intermediate and high frailty (23.8 vs. 7.0 and 1.8 months, respectively; p < 0.001). Median PFS was also significantly higher in patients with low frailty compared with intermediate and high frailty (10.5 vs. 3.9 and 1.6 months; p < 0.001, respectively). Frailty was the only variable that showed significant differences in OS and PFS. Multivariate analysis confirms frailty as an independent predictor of OS and PFS. Frailty assessment could help to select which patients are candidates for ICIs in NSCLC.

Folate receptor-positive circulating tumor cell count, lymphocyte count and derived neutrophil-to- lymphocyte ratio for diagnosing lung cancer relapse

The folate receptor-positive circulating tumor cell (FR⁺-CTC) count can be used to improve the diagnosis rate of lung cancer. The lymphocyte count (LC) and derived neutrophil-to-lymphocyte ratio (dNLR) are involved in inflammatory processes. Whether the FR⁺-CTC count combined with the dNLR or LC is helpful for diagnosing lung cancer recurrence is not clear. Sixty-eight patients who were initially diagnosed with lung cancer and received first-line treatment were included. The clinicopathological characteristics, routine blood examination results and CTC examination results of the patients were collected. The role of the complete blood count and FR⁺-CTC count in lung cancer treatment response and prognosis was analyzed. The FR⁺-CTC count after treatment was significantly correlated with the T stage (p=0.005). Multivariate analysis showed that the pathological type and FR⁺-CTC count were independent predictors of disease-or progression-free survival (DFS/PFS) in patients with lung cancer (p=0.010 and p=0.030, respectively). The FR⁺-CTC count, LC and dNLR predicted the recurrence of lung cancer (sensitivity and specificity of the FR⁺-CTC count, 69.2% and 71.4%; the LC, 50.0% and 88.5%; and the dNLR, 50.0% and 88.1%, respectively). The FR⁺-CTC count combined with the LC or dNLR improved the diagnostic rate of lung cancer recurrence (sensitivity and specificity of the FR⁺-CTC count plus the LC, 53.8% and 90.5%, and the FR⁺-CTC count plus the dNLR, 73.1% and 73.8%, respectively). When these three indicators were combined to predict lung cancer recurrence, the AUC value was 0.817. The FR⁺-CTC count combined with the dNLR and/or LC after treatment can improve the diagnostic rate of lung cancer recurrence. A higher FR⁺-CTC count predicts worse DFS/PFS in patients with lung cancer.