Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Outcomes with Nivolumab in Pretreated Non-Small Cell Lung Cancer (NSCLC): A Large Retrospective Multicenter Study

Mechanisms and strategies of immunosenescence effects on non-small cell lung cancer (NSCLC) treatment: A comprehensive analysis and future directions

Non-small cell lung cancer (NSCLC), the most prevalent form of lung cancer, remains a leading cause of cancer-related mortality worldwide, particularly among elderly individuals. The phenomenon of immunosenescence, characterized by the progressive decline in immune cell functionality with aging, plays a pivotal role in NSCLC progression and contributes to the diminished efficacy of therapeutic interventions in older patients. Immunosenescence manifests through impaired immune surveillance, reduced cytotoxic responses, and increased chronic inflammation, collectively fostering a pro-tumorigenic microenvironment. This review provides a comprehensive analysis of the molecular, cellular, and genetic mechanisms of immunosenescence and its impact on immune surveillance and the tumor microenvironment (TME) in NSCLC. We explore how aging affects various immune cells, including T cells, B cells, NK cells, and macrophages, and how these changes compromise the immune system's ability to detect and eliminate tumor cells. Furthermore, we address the challenges posed by immunosenescence to current therapeutic strategies, particularly immunotherapy, which faces significant hurdles in elderly patients due to immune dysfunction. The review highlights emerging technologies, such as single-cell sequencing and CRISPR-Cas9, which offer new insights into immunosenescence and its potential as a therapeutic target. Finally, we outline future research directions, including strategies for rejuvenating the aging immune system and optimizing immunotherapy for older NSCLC patients, with the goal of improving treatment efficacy and survival outcomes. These efforts hold promise for the development of more effective, personalized therapies for elderly patients with NSCLC.

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.

Clinical significance of the combined systemic immune-inflammatory index and prognostic nutritional index in predicting the prognosis of patients with extensive-stage small-cell lung cancer receiving immune-combination chemotherapy

BACKGROUND

The therapeutic efficacy and prognosis of various tumors can be assessed using the systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI). Despite their potential, no studies have investigated the prognostic value of the combined SII-PNI score for outcomes in patients with extensive small cell lung cancer (ES-SCLC) treated with chemotherapy and immune checkpoint inhibitors (ICIs).

MATERIALS AND METHODS

Our study retrospectively examined 213 ES-SCLC patients treated with chemotherapy and ICIs across two institutions. The patients were divided into three groups based on their SII-PNI scores. Cox regression analysis was employed to identify independent prognostic factors. A nomogram was constructed based on these independent factors. With 1000 repeated samples, the bootstrap method was used to validate the nomogram model internally. The model's performance was assessed using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

RESULT

Before and after chemotherapy with immune checkpoint inhibitors (ICIs), SII was significantly higher in the PD group compared with the PR group (both p < 0.05). In the meantime, PNI was considerably lower in the PD group than in the PR group (both p < 0.01). Kaplan-Meier curves demonstrated that patients with a low SII-PNI had prolonged progression-free survival (PFS) and overall survival (OS) compared to those with a high SII-PNI (all p < 0.01). Multivariate Cox analysis showed that PS = 1, bone metastasis, brain metastasis, and SII-PNI = 1,2 after four treatment cycles were independent risk factors for shorter OS and were included in the nomogram model. The ROC curves, C-index, and DCA curves confirm that the SII-PNI scores-based nomograms have strong predictive accuracy for OS.

CONCLUSION

There was a significant correlation between pre- and post-treatment SII-PNI and treatment effect in ES-SCLC. The SII-PNI score after four treatment cycles is a useful prognostic indicator for ES-SCLC patients receiving chemotherapy combined with immune checkpoint inhibitors (ICIs).

The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model

Background

Inflammation and immune evasion are associated with tumorigenesis and progression. The Systemic Inflammation Response Index (SIRI) has been proposed as a pre-treatment peripheral blood biomarker. This study aims to compare the relationship between SIRI, various serum biomarkers, and the prognosis of NSCLC patients before and after treatment.

Methods

A retrospective study was conducted on advanced NSCLC patients treated with anti-PD-1 drugs from December 2018 to September 2021. Peripheral blood markers were measured pre- and post-treatment, and hazard ratios were calculated to assess the association between serum biomarkers and progression-free survival (PFS) and overall survival (OS). Kaplan-Meier curves and Cox proportional hazards models were employed for survival analysis. A nomogram model was built based on multivariate Cox proportional hazards regression analysis using the R survival package, with internal validation via the bootstrap method (1,000 resamples). Predictive performance was expressed using the concordance index (C-index), and calibration plots illustrated predictive accuracy.The application value of the model was evaluated by decision curve analysis (DCA).

Results

Among 148 advanced NSCLC patients treated with PD-1 inhibitors, the median PFS was 12.9 months (range: 5.4-29.2 months), and the median OS was 19.9 months (range: 9.6-35.2 months). Univariate analysis identified pre- and post-treatment SIRI, mGRIm-Score, and PNI as independent prognostic factors for both PFS and OS (p < 0.05). Multivariate analysis demonstrated that high post-SIRI and post-mGRIm-Score independently predicted poor PFS (P < 0.001, P = 0.004) and OS (P = 0.048, P = 0.001). The C-index of the nomogram model for OS was 0.720 (95% CI: 0.693-0.747) and for PFS was 0.715 (95% CI: 0.690-0.740). Internal validation via bootstrap resampling (B = 1,000) showed good agreement between predicted and observed OS and PFS at 1, 2, and 3 years, as depicted by calibration plots.

Conclusion

SIRI is an important independent predictor of early progression in advanced NSCLC patients treated with PD-1 inhibitors and may assist in identifying patients who will benefit from PD-1 inhibitors therapy in routine clinical practice.

Association Between Baseline and Changes in Early Neutrophil-to-Lymphocyte Ratio on Survival in Patients with Metastatic Bladder Carcinoma Treated with Immunotherapy

Background and Objectives: A high baseline neutrophil-to-lymphocyte ratio (NLR) is a poor prognostic factor in various cancers. However, its predictive role in metastatic bladder cancer (mBC) treated with immunotherapy is unclear. In this study, we aimed to investigate the relationship between the baseline and change in NLR and overall survival in mBC patients treated with immunotherapy, with the potential to significantly impact patient care. Materials and Methods: A retrospective analysis was conducted on 56 mBC patients who received second-line immunotherapy after progressing on platinum-based chemotherapy. Patients were classified into high and low NLR groups using a cutoff value of 3.3. A further division was made based on NLR changes after two cycles of immunotherapy: whether NLR increased (≥10%) or decreased (≥10%). The endpoint was to estimate the association between clinicopathological features and survival outcomes. Results: The study included 56 patients, with a median age of 66.6 years and a male-to-female ratio of 2.3:1. A low baseline NLR was associated with better OS than a high baseline NLR (p = 0.005). After two immunotherapy cycles, patients with a decreased NLR (≥10%) had significantly longer OS than those with an increased NLR (≥10%), regardless of the baseline NLR (p = 0.003). The overall median survival was 15 months, with 10 months for the NLR-increased group and not reached for the NLR-decreased group. Conclusions: Our study highlights the potential of baseline NLR and early changes in NLR as valuable prognostic markers for mBC patients receiving immunotherapy. Elevated neutrophils and lymphopenia negatively impact prognosis and treatment effectiveness, and NLR shows promise as a prognostic marker, inspiring further research and potential improvements in patient care.

Effects of intravenous anesthesia and inhalation anesthesia on postoperative inflammatory markers in patients with esophageal cancer: a retrospective study

BACKGROUND

Inflammatory markers have been confirmed to be associated with the prognosis of cancer patients. In this study, we compared the impacts of intravenous anesthesia and inhalation anesthesia on the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), and the systemic immune-inflammation index (SII) after esophageal cancer surgery.

METHODS

We retrospectively reviewed the electronic medical records of patients who underwent esophagectomy from January 1, 2014 to December 31, 2016. Patients respectively received total intravenous anesthesia (TIVA) or inhalational anesthesia (INHA). Inverse probability of treatment weighting (IPTW) was employed to minimize differences. The Mann-Whitney U test or Kruskal Wallis test was utilized to compare the effect of the two groups on postoperative NLR, PLR and SII.

RESULTS

A total of 519 patients who had undergone esophageal cancer resection were recruited in this study, among whom 339 patients were eligible (TIVA group, n = 201, INHA group, n = 138). After IPTW, there was no statistically significant difference in NLR, PLR, and SII on the first postoperative day(P = 0.1951), (P = 0.5611), (P = 0.9684) and on the third postoperative day(P = 0.5961), (P = 0.1804), (P = 0.9653) between the two groups.

CONCLUSIONS

In conclusion, there was no significant difference in NLR, PLR and SII between intravenous anesthesia or inhalational anesthesia. TIVA is not superior to INHA in reducing the perioperative inflammatory response of esophageal cancer.

SYNOPSIS

Inflammatory markers play an important role in the recurrence, metastasis and survival of tumor patients after surgery. In this study, we will compare the effects of different anesthesia methods on inflammatory markers.

Immuno-combined treatment versus radio-combined treatment in limited-stage small-cell lung cancer

Background

Although the approval of immunotherapy in patients with extensive-stage small-cell lung cancer (ES-SCLC) has significantly improved the patient's prognosis, synchronous chemoradiotherapy has always been the standard treatment for limited-stage small-cell lung cancer (LS-SCLC).

Objectives

Immuno-combined and radio-combined therapy in LS-SCLC has been applied in clinical practice, but what is the best for LS-SCLC?

Design

This was a retrospective cohort study.

Methods

Patients with LS-SCLC from January 2019 to December 2023 were retrospectively screened and divided into three groups according to the initial treatment regimen whether included immune-combined and radio-combined treatment. Univariate and multivariate Cox regression were used to analyze the predictors affecting the survival of LS-SCLC, and the progression pattern of patients and the occurrence of adverse events (AEs) were also recorded.

Results

In this study, the median overall survival (OS) was 15.8 months, not yet reached (NR) and NR, and the median progression-free survival (PFS) was 11.7, 20.9, and 18.9 months in the immunotherapy combined chemotherapy (N = 34), immune combined chemoradiotherapy (N = 26), and chemoradiotherapy (N = 53) groups, respectively. OS and PFS were significantly prolonged in the radio-combined groups compared with the non-radio-combined group, and there was no significant difference between the radio-combined groups, namely immunotherapy combined chemoradiotherapy and chemoradiotherapy groups. In this study, we also constructed some indexes to predict prognosis for LS-SCLC, derived neutrophil and lymphocyte ratios were significantly associated with worse survival, and systemic inflammatory index and neuron-specific enolase (NSE) levels were significantly associated with shorter PFS. The primary organs of progression remained the lung and brain, the main immune-related AE was hypothyroidism, and the radiation-related AE was pneumonia.

Conclusion

Radiation-combined therapy still plays an important role in LS-SCLC in the era of immunotherapy, and clinicians cannot abandon the use of radiation therapy in the initial treatment plan for LS-SCLC.

Analysis of the treatment efficacy and prognostic factors of PD-1/PD-L1 inhibitors for advanced gastric or gastroesophageal junction cancer: a multicenter, retrospective clinical study

Introduction

Immune checkpoint inhibitors (ICIs) have transformed advanced gastric cancer treatment, yet patient responses vary, highlighting the need for effective biomarkers. Common markers, such as programmed cell death ligand-1 (PD-L1), microsatellite instability/mismatch repair (MSI/MMR), tumor mutational burden, tumor-infiltrating lymphocytes, and Epstein-Barr virus, face sampling challenges and high costs. This study seeks practical, minimally invasive biomarkers to enhance patient selection and improve outcomes.

Methods

This multicenter retrospective study analyzed 617 patients with advanced gastric or gastroesophageal junction cancer treated with programmed cell death protein-1 (PD-1)/PD-L1 inhibitors from January 2019 to March 2023. Clinical data and peripheral blood marker data were collected before and after treatment. The primary endpoints were overall survival (OS) and progression-free survival (PFS); the secondary endpoints included the objective response rate (ORR) and disease control rate (DCR). Least absolute shrinkage and selection operator (LASSO)-Cox and LASSO logistic regression analyses identified independent factors for OS, PFS, and ORR. Predictive nomograms were validated using receiver operating characteristic (ROC) curves, areas under the curve (AUCs), C-indices, and calibration curves, with clinical utility assessed via decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

OS-related factors included treatment line, T stage, ascites, pretreatment indirect bilirubin (pre-IBIL), posttreatment CA125, CA199, CA724, and the PLR. PFS-related factors included treatment lines, T stage, metastatic sites, pre-IBIL, posttreatment globulin (GLOB), CA125, and CA199 changes. ORR-related factors included treatment line, T stage, N stage, liver metastasis, pretreatment red cell distribution width-to-platelet ratio (RPR), CA125, and CA724 changes. The nomograms showed strong predictive performance and clinical utility.

Conclusions

Early treatment, lower T stage, the absence of ascites, and lower pre-IBIL, post-CA125, CA199, CA724, and PLR correlate with better OS. Factors for improved PFS include early treatment, lower T stage, fewer metastatic sites, and lower pre-IBIL, post-GLOB, and post-CA125 levels. Nomogram models can help identify patients who may benefit from immunotherapy, providing valuable clinical guidance.

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.

A Review of the Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Nonhematologic Malignancies

Biomarkers are crucial in cancer diagnostics, prognosis, and surveillance. Extensive research has been dedicated to identifying biomarkers that are broadly applicable across multiple cancer types and can be easily obtained from routine investigations such as blood cell counts. One such biomarker, the neutrophil-to-lymphocyte ratio (NLR), has been established as a prognostic marker in cancer. However, due to the dynamic nature of cancer diagnosis and treatment, periodic updates are necessary to keep abreast of the vast amount of published data. In this review, we searched the PubMed database and analyzed and synthesized recent literature (2018-February 2024) on the role of NLR in predicting clinical outcomes in nonhematologic malignancies. The search was conducted using the PubMed database. We included a total of 88 studies, encompassing 28,050 human subjects, and categorized the findings into four major groups: gastrointestinal cancer, cancers of the urinary tract and reproductive system, lung cancer, and breast cancer. Our analysis confirms that NLR is a reliable prognostic indicator in cancer, and we discuss the specific characteristics, limitations, and exceptions associated with its use. The review concludes with a concise Q&A section, presenting the most relevant take-home messages in response to five key practical questions on this topic.

Inflammation-related markers and prognosis of alpha-fetoprotein producing gastric cancer

BACKGROUND

Inflammation-related markers including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI) and prognostic nutritional index (PNI) could reflect tumor immune microenvironment and predict prognosis of cancers. However, it had not been explored in alpha-fetoprotein (AFP) producing gastric cancer (GC).

AIM

To determine the predictive value of inflammation-related peripheral blood markers including as NLR, PLR, MLR, SII, SIRI and PNI in the prognosis of AFP- producing GC (AFPGC). Besides, this study would also compare the differences in tumor immune microenvironment, clinical characteristics and prognosis between AFPGC and AFP- GC patients to improve the understanding of this disease.

METHODS

573 patients enrolled were retrospectively studied. They were divided into AFP+ group (AFP ≥ 20 ng/mL) and AFP- group (AFP < 20 ng/mL), comparing the levels of NLR/PLR/MLR/SII/SIRI/PNI and prognosis. In AFP+ group, the impact of NLR/PLR/MLR/SII/SIRI/PNI and their dynamic changes on prognosis were further explored.

RESULTS

Compared with AFP- patients, AFP+ patients had higher NLR/PLR/MLR/SII/SIRI and lower PNI levels and poorer overall survival (OS). In the AFP+ group, mortality was significantly lower in the lower NLR/PLR/MLR/SII/SIRI group and higher PNI group. Moreover, the dynamic increase (NLR/PLR/MLR/SII/SIRI) or decrease (PNI) was associated with the rise of mortality within 1 year of follow-up.

CONCLUSION

Compared with AFP- patients, the level of inflammation-related peripheral blood markers significantly increased in AFP+ patients, which was correlated with OS of AFP+ patients. Also, the gradual increase of SII and SIRI was associated with the risk of death within one year in AFP+ patients. AFPGC should be considered as a separate type and distinguished from AFP- GC because of the difference in tumor immune microenvironment. It requires basic experiments and large clinical samples in the future.

Clinical multi-dimensional prognostic nomogram for predicting the efficacy of immunotherapy in NSCLC

The advent of immunotherapy has greatly improved the prognosis of non-small cell lung (NSCLC) patients. However, given its low response rate and high cost of treatment, the search for valuable predictive markers of treatment efficacy is necessary. Considering the complexity and heterogeneity of the tumour and tumour microenvironment, the construction of a multi-dimensional prediction model is necessary. Therefore, we aimed to integrate clinical parameters, radiomic features, and immune signature data from NSCLC patients receiving immunotherapy to construct a multi-dimensional prediction model to better predict the efficacy of immunotherapy. The current study enrolled 137 NSCLC patients who received immunotherapy. We collected baseline clinical information, CT images, and tumour tissue specimens. Using 3D-Slicer software, radiomic features were extracted from patient CT images, and tumor tissue samples obtained before immunotherapy were subjected to immunohistochemical staining. Then, the least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to downscale the data, and the radiomic features and immune signatures associated with the prognosis of immunotherapy patients were identified. The modified lung immune predictive index (mLIPI), radiomics score (Radioscore), immune score and multi-dimensional model nomogram were constructed. The C-index and area under the curve (AUC) were applied to evaluate the predictive efficacy of the models. Three radiomic features and three immune signatures that could predict the efficacy of immunotherapy were eventually screened. Multivariate analysis showed that the mLIPI, Radioscore, and immune score were independent predictive factors for PFS and OS (P < 0.05 for all models). The multi-dimensional model combining the three models showed better predictive efficacy than the mLIPI, Radioscore, and immune score (PFS: 0.721 vs. 0.662 vs. 0.610 vs. 0.610; OS: 0.727 vs. 0.661 vs. 0.601 vs. 0.602 respectively). The multi-dimensional model showed the best predictive efficacy, with C-index for PFS and OS higher than mLIPI, radioscore and immune score: 0.721 vs. 0.662 vs. 0.610 vs. 0.610 for PFS and 0.727 vs. 0.661 vs. 0.601 vs. 0.602 for OS, respectively. The AUC for the multi-dimensional model also performed better than those of the individual models: 0.771 vs. 0.684 vs. 0.715 vs. 0.711 for PFS and 0.768 vs. 0.662 vs. 0.661 vs. 0.658 for OS, respectively. The multi-dimensional model combining the three models had better predictive efficacy than any single model and was more likely to help provide patients personalized and precision medicine.

Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratio: Side by Side with Molecular Mutations in Patients with Non-Small Cell Lung Cancer-The INOLUNG Study

Background and objective: Analysis of inflammatory biomarkers, along with the neutrophil/lymphocyte ratio (NLR) or platelet/lymphocyte ratio (PLR), supports the connection between inflammation and carcinogenesis. Methods: We conducted a retrospective observational study at the Clinical County Hospital Mureș involving patients with lung cancer. The parameters analyzed included histopathological type (NSCLC: squamous cell carcinoma or adenocarcinoma; SCLC), molecular mutations (EGFR, ALK, PD-L1), parameters from the complete blood count, inflammatory parameters, and associated comorbidities. Results: A total of 380 patients were included: 115 patients in the cancer group and 265 patients in the control group. Among patients in the lung cancer group, 88 were diagnosed with NSCLC (44 adenocarcinomas, 44 squamous cell carcinomas) and 27 with SCLC. Both NLR and PLR were significantly higher in cancer patients than in the control group (5.30 versus 2.60, p < 0.001; 217 versus 136, p < 0.001, respectively). NLR and PLR differ between men and women (p = 0.005 and p = 0.056, respectively). C-reactive protein was not correlated with either NLR (p-value: 0.0669) or PLR (p-value: 0.6733) in lung cancer patients. Conclusions: The NLR and PLR values may serve as new predictive biomarkers for the diagnosis of disease in patients with lung cancer, especially those with NSCLC.

Baseline Blood CD8+ T Cell Activation Potency Discriminates Responders from Non-Responders to Immune Checkpoint Inhibition Combined with Stereotactic Radiotherapy in Non-Small-Cell Lung Cancer

BACKGROUND

Tumor-infiltrating immune cells have been correlated with prognosis for patients treated with immune checkpoint inhibitor (ICI) treatment of various cancers. However, no robust biomarker has been described to predict treatment response yet. We hypothesized that the activation potency of circulating T cells may predict response to ICI treatment.

METHODS

An exploratory analysis was conducted to investigate the association between the response to immune checkpoint inhibition (ICI) combined with stereotactic radiotherapy (SBRT) and the potency of circulating T cells to be activated. Blood-derived lymphocytes from 14 patients were stimulated ex vivo with, among others, Staphylococcal enterotoxin B (SEB) and compared to healthy controls (HCs). Patients were grouped into responders (>median progression free survival (PFS)) and non-responders (

RESULTS

At baseline, a higher percentage of activated CD8+ T cells (15.8% vs. 3.5% (p = <0.01)) and IL-2+CD69+CD8+ T cells (8.8% vs. 2.9% (p = 0.02)) was observed in responders compared to non-responders upon ex vivo stimulation with SEB. The concurrently measured serum cytokine levels were not different between responders and non-responders.

CONCLUSION

Baseline blood CD8+ T cell activation potency, measured by intracellular cytokine production after ex vivo stimulation, is a potential biomarker to discriminate responders from non-responders to SBRT combined with ICI.

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Key Words

• NSCLC
• T cell function assay
• biomarker
• cytokines
• immune checkpoint inhibition
• immunotherapy
• liquid biopsy

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MESH Headings Collapse

Grants

• ESR 16-12461 / D4191C00075 AstraZeneca (Netherlands)

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Affiliation(s)

Hanneke Kievit Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
M. Benthe Muntinghe-Wagenaar Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
Wayel H. Abdulahad Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
Abraham Rutgers Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
Lucie B. M. Hijmering-Kappelle Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
Birgitta I. Hiddinga Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
J. Fred Ubbels Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
Robin Wijsman Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
Marcel J. van der Leij Department of Laboratory Medicine, Medical Immunology Laboratory, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
Johan Bijzet Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
Harry J. M. Groen Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
Huib A. M. Kerstjens Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
Anthonie J. van der Wekken Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)
Bart-Jan Kroesen Department of Laboratory Medicine, Medical Immunology Laboratory, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
T. Jeroen N. Hiltermann Department of Pulmonology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands (H.A.M.K.)

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Clinical Efficacy of Taxol Plus Platinum (TP) Chemotherapy Combined with Delayed Administration of PD-1 Inhibitors in Patients with Locally Advanced, Recurrent or Metastatic Esophageal Squamous Cell Carcinoma: A Retrospective Study

Purpose

Immune checkpoint inhibitors (ICIs) combined with chemotherapy have become the first-line standard treatment for locally advanced or metastatic esophageal squamous cell carcinoma (ESCC). The evidence also demonstrates improved synergistic effects of chemotherapy when combined with delayed administration of ICIs. In this study, we conducted a retrospective investigation into the treatment efficacy of taxol plus platinum (TP) chemotherapy combined with delayed administration of PD-1 inhibitors for ESCC patients.

Patients and Methods

Clinical data of ESCC patients who received PD-1 inhibitors 3-5 days after TP chemotherapy as first-line treatment was retrospectively reviewed between January 2019 and April 2023. Clinical outcomes and treatment safety were analyzed. The potential roles of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and pan-immune-inflammation value (PIV) were investigated.

Results

A total of 34 locally advanced, recurrent or metastatic ESCC patients received PD-1 inhibitors 3-5 days following TP chemotherapy were included. The objective response rate (ORR) and disease control rate (DCR) were 85.3% and 97.1% respectively. The median progression-free survival (PFS) and overall survival (OS) were 13.2 and 19.1 month respectively. Seven patients received radical surgery, 1 patient achieved pathologic complete response (pCR) and 3 patients achieved major pathologic response (MPR). Among the 27 patients without surgery, the median PFS and OS were 9.7 and 19.1 month respectively. A more favorable prognosis was correlated with NLR less than 3 at the 3rd and 4th cycle of immunochemotherapy. No significant correlations between other parameters (PLR, MLR and PIV) and prognosis were observed. A total of 22 patients developed grade 3-4 toxicity events.

Conclusion

The optimized sequence of PD-1 inhibitors administered 3-5 days after TP chemotherapy as the first-line treatment of ESCC demonstrated favorable treatment efficacy. Pretreatment NLR of less than 3 at the 3rd and 4th cycle of immunochemotherapy is associated with a better prognosis.

The effects of postoperative targeted immunotherapy on peripheral blood cytokines and immune cell profile in lung cancer patients

Objective

Cytokines and cell subsets are important components of the tumor microenvironment. Previous research has revealed that there are differences in cytokines and cell subsets in the peripheral blood of lung cancer (LCA) patients before and after eradication. The purpose of this study is to explore the monitoring value of cytokines and cellular subpopulations as biomarkers in post-immunotherapy monitoring of patients with LCA after surgery.

Methods

We conducted a case-control study using double-antibody sandwich magnetic microsphere flow cytometry with immunofluorescence technology and fluorescent monoclonal antibody multiparameter flow cytometry to detect differences in peripheral blood cytokines and cell subsets between LCA patients after immunotherapy and healthy controls.

Results

Our research results show that there are differences in the levels of IL-4, IL-6, IL-10, IL-17, IFN-γ, TNF-α in the peripheral blood of LCA patients (n=70) after immunotherapy compared to the healthy controls (n=55) (P<0.05), and there are differences in 10 cell subgroups including DP T Cells, AT cells, and NLR in the peripheral blood compared to the healthy controls (n=35) (P<0.05). Further analysis revealed significant differences in the detection data of IL-6, IL-10, IFN-γ, CD56dim NK cells, Total B cells, Total NE cells, CD15+M cells, and NLR between LCA deceased patients (n=25) and LCA surviving patients (n=27) during the same period (P<0.05). The continuous monitoring of cytokines and cell subsets is far more valuable than a single-time test, as abnormal fluctuations in the data of cytokines and cell subsets are often associated with poor prognosis. In addition, IL-6 and NLR showed the strongest discriminative ability between postoperative immunotherapy-treated LCA patients and healthy controls, with AUC values of 0.840 and 0.822, respectively. There was a significant association between IFN-γ and distant metastasis in LCA (P<0.05), as well as between CD56dim NK cells and lymph node infiltration (P<0.05).

Conclusion

This research results support peripheral blood cytokines and cell subsets as biomarkers for monitoring the postoperative immune status and predicting the prognosis of LCA patients after immunotherapy. The continuous monitoring of cytokines and cell subsets is far more valuable than a single-time detection.

Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points

BACKGROUND AND PURPOSE

Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients.

METHODS

This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients' overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell's C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan-Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26.

RESULTS

This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell's C-index in the training and validation sets of the model was 0.85 (95% CI 0.76-0.93) and 0.88 (95% CI 0.76-0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy.

CONCLUSION

This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.

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 value of lung function assessment and Testin expression detection in clinicopathological features and prognosis of NSCLC patients

OBJECTIVE

The aim of this study is to investigate the clinical value and potential prognostic significance of lung function assessment and Testin expression in non-small cell lung cancer (NSCLC) patients.

METHODS

The NSCLC patients were classified into three groups according to lung function: group of normal lung function, group of PRISm (preserved ratio impaired spirometry) (FEV1, forced expiratory volume during the first second < 80% predicted and FEV1/FVC (forced vital capacity) ≥ 70%) and group of COPD (chronic obstructive pulmonary disease) (FEV1/FVC < 70%). The pre-operational clinicopathological characteristics of these patients were recorded and the markers of systemic inflammatory response, including neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR) and eosinophils (EOS), were compared between three groups. The expression of Testin in NSCLC samples was detected by IHC and we further explored the correlation between Testin expression and clinicopathological characteristics and prognosis of NSCLC patients. Finally, Cox regression analysis was conducted to study the prognostic factors of NSCLC patients.

RESULTS

Of the 158 NSCLC patients, percentages of normal lung function, PRISm and COPD were 41.4%, 22.8% and 36.1%, respectively. Patients with tumor in the left lung were more likely to have pulmonary dysfunction (PRISm and COPD) than the right lung. The markers of systemic inflammatory response showed differences to various degree in the three groups and NSCLC patients with PRISm or COPD presented more unfavorable prognosis than patients with normal function. The expression of Testin correlated with lymph node metastasis, TNM stage and tumor invasion of NSCLC patients. Moreover, patients with low Testin expression exhibited poorer disease-free survival and overall survival than those with high Testin expression. In Cox regression analysis, we found that PRISm, COPD and Testin expression served as prognostic factors in NSCLC patients.

CONCLUSIONS

The presence of COPD or PRISm influenced systemic inflammatory response and prognosis of NSCLC patients. Testin expression correlated with clinicopathological features and could be potentially used as a prognostic marker in NSCLC.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Influence of abdominal fat distribution and inflammatory status on post-operative prognosis in non-small cell lung cancer patients: a retrospective cohort study

PURPOSE

To evaluate the influence of visceral fat area (VFA), subcutaneous fat area (SFA), the systemic immune-inflammation index (SII) and total inflammation-based systemic index (AISI) on the postoperative prognosis of non-small cell lung cancers (NSCLC) patients.

METHODS

266 NSCLC patients received surgery from two academic medical centers were included. To assess the effect of abdominal fat measured by computed tomography (CT) imaging and inflammatory indicators on patients' overall survival (OS) and progression-free survival (PFS), Kaplan-Meier survival analysis and Cox proportional hazards models were used.

RESULTS

Kaplan-Meier analysis showed the OS and PFS of patients in high-VFA group was better than low-VFA group (p < 0.05). AISI and SII were shown to be risk factors for OS and PFS (p < 0.05) after additional adjustment for BMI (Cox regression model II). After further adjustment for VFA (Cox regression model III), low-SFA group had longer OS (p < 0.05). Among the four subgroups based on VFA (high/low) and SFA (high/low) (p < 0.05), the high-VFA & low-SFA group had the longest median OS (108 months; 95% CI 74-117 months) and PFS (85 months; 95% CI 65-117 months), as well as the lowest SII and AISI (p < 0.05). Low-SFA was a protective factor for OS with different VFA stratification (p < 0.05).

CONCLUSION

VFA, SFA, SII and AISI may be employed as significant prognostic markers of postoperative survival in NSCLC patients. Moreover, excessive SFA levels may encourage systemic inflammation decreasing the protective impact of VFA, which may help to provide targeted nutritional support and interventions for postoperative NSCLC patients with poor prognosis.

Prognostic value of the Scottish Inflammatory prognostic Score in patients with NSCLC expressing PD-L1 ≥ 50 % progressing on first-line pembrolizumab

BACKGROUND

Most patients with advanced non-small cell lung cancer (NSCLC) treated with first-line pembrolizumab monotherapy will experience progressive disease (PD). Only a minority will go on to receive subsequent systemic anticancer therapy for which outcomes are guarded. We investigated the prognostic significance of biomarkers of systemic inflammation following failure of first-line pembrolizumab for NSCLC to aid subsequent management decisions.

METHODS

Patients with radiological and/or clinical evidence of PD on first-line pembrolizumab for advanced NSCLC at a regional Scottish cancer centre were identified. Inflammatory biomarkers at the time of PD, including serum albumin, neutrophil count and the Scottish Inflammatory Prognostic Score (SIPS; combing albumin and neutrophils), and clinicopathological factors, including age, sex, histology, PDL1 expression and time to PD were recorded. The relationship between these and post-progression overall survival (ppOS) were examined.

RESULTS

Data were available for 211 patients. Median ppOS was 2.1 months. Only SIPS was predictive of ppOS on multivariate analysis (HR2.54 (95 %CI 1.81-3.56) (<0.001)), stratifying ppOS from 0.8 months (SIPS2), to 1.8 months (SIPS1), to 8.1 months (SIPS0) (p < 0.001). Thirty (14 %) patients received second-line systemic anticancer therapy with median ppOS 8.7 months. These patients had lower levels of systemic inflammation, as defined by albumin (p < 0.001), neutrophil count (p = 0.002), and SIPS (p = 0.004)), than all other patients.

CONCLUSIONS

SIPS, a simple biomarker of systemic inflammation, predicts ppOS after first-line pembrolizumab and may be useful alongside routine assessments of patient fitness to inform individualised discussions about subsequent treatment. We highlight poor outcomes in this patient group and a role for SIPS in signposting transition to best supportive care and early referral to palliative care. It may also help identify a small group of patients most likely to benefit from further lines of therapy.

Prognostic significance of pan-immune-inflammation value (PIV) in nasopharyngeal carcinoma patients

Background

Blood-based immune-inflammation indexes have been widely used to predict survival in a variety of cancers. In this research, we seeked to evaluate a novel immune-inflammation marker, named the pan-immune-inflammation value (PIV), in patients with nasopharyngeal carcinoma (NPC) undergoing definitive radiotherapy.

Methods

A group of 377 patients with NPC was retrospectived analyzed. Clinical data and laboratory data were collected. Receiver operating characteristic (ROC) curve analysis was performed in order to determine the optimal PIV cut-off value. Survival curves were estimated by Kaplan-Meier method, and prognostic variables were identified using a Cox regression model. Additionally, we developed a nomogram and assessed its acuracy using the concordance index (C-index) and a calibration curve.

Results

The optimal PIV cut-off value was 146.24 according to ROC analysis. High PIV was related to poorer Eastern Cooperative Oncology Group Performance Status (ECOG PS) score (p = 0.017), more advanced T (p＜0.001) and clinical stages (p = 0.024). In univariate analysis, older Age, poorer ECOG PS, higher Epstein-Barr virus DNA (EBV-DNA), advanced T, N and clinical stage, and higher PIV levels were related to patients' poorer overall survival (OS). Poorer ECOG PS, higher EBV-DNA, later T stage, later clinical stage, and higher PIV were associated with patients' poorer progression free survival (PFS). Male sex and later T stage were associated with patients' poorer locoregional recurrence free survival (LRRFS). Poorer ECOG PS, higher EBV-DNA, later T stage, later clinical stage, and higher PIV were associated with patients' poorer distant metastasis free survival (DMFS). Multivariate analysis demonstrated that PIV was an independent prognostic index for OS (HR 2.231, 95 % CI 1.241-4.011, P = 0.007), PFS (HR 1.664, 95 % CI 1.003-2.760, P = 0.049), and DMFS(HR 2.081, 95 % CI 1.071-4.044, P = 0.031). Nomogram C-indexes for the nomogram of OS were 0.684, and PFS were 0.62, respectively. Survival predictions and actual survival were consistent according to the calibration curve.

Conclusions

Pre-treatment PIV is a promising biomarker for predicting survival in patients with NPC.

Predictability of Neutrophile to Lymphocyte Ratio and Platelet to Lymphocyte Ratio on the Effectiveness of Immune Checkpoint Inhibitors in Non-small Cell Lung Cancer patients: A Meta-Analysis

OBJECTIVES

The associations between the neutrophil-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) with the responses of non-small cell lung cancer (NSCLC) patients receiving immune checkpoint inhibitors (ICI) and the NLR/PLR predictive potential were evaluated via meta-analysis.

METHODS

A systematic review was conducted using the PubMed, Embase, and The Cochrane Library databases until October 2021. The relationship between NLR/PLR and overall survival (OS) and progression-free survival (PFS) was evaluated using pooled hazard ratios (HR). The relationship between NLR/PLR and overall response rate (ORR) and disease control rate (DCR) was assessed via pooled odds ratios (OR). Heterogeneity between studies, publication bias, subgroup and sensitivity analyses, trim and fill meta-analysis, and the contour-enhanced funnel plot were performed using the R software.

RESULTS

A total of 44 (out of 875) studies met the eligibility criteria, providing a sample size of 4597 patients. Patients with a high NLR were statistically significantly associated with worse outcomes, including OS (pooled HR = 2.44; P < 0.001), PFS (pooled HR = 2.06; P < 0.001), DCR (pooled OR = 0.71; P < 0.001), and ORR (pooled OR = 0.33; P < 0.001). Similarly, a high PLR was associated with poorer outcomes in response to ICI drugs, including OS (pooled HR = 2.13; P < 0.001) and PFS (pooled HR = 1.61; P < 0.001).

CONCLUSION

High NLR and PLR were associated with a statistically significant reduction in the efficacy of ICI drugs in NSCLC patients. Thereby, it is possible to use NLR and PLR as potential and available biomarkers in the clinical practice to predict the outcome of ICI treatment in NSCLC patients.

Predictive Value of NLR and PLR in Driver-Gene-Negative Advanced Non-Small Cell Lung Cancer Treated with PD-1/PD-L1 Inhibitors: A Single Institutional Cohort Study

OBJECTIVE

To investigate the predictive value of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) for the efficacy and prognosis of programmed cell death-1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors in driver-gene-negative advanced non-small-cell lung cancer (NSCLC).

METHODS

A retrospective analysis of 107 advanced NSCLC patients without gene mutations who received PD-1/PD-L1 inhibitors in our hospital from January 2020 to June 2022 was performed. NLR and PLR were collected before PD-1/PD-L1 inhibitors, the optimal cut-off values of NLR and PLR were determined according to the receiver operating characteristic (ROC) curve, and the effects of NLR and PLR on the efficacy of PD-1/PD-L1 inhibitors in advanced NSCLC patients were analyzed.

RESULTS

A total of 107 patients were included in this study. Receiver operating characteristic analysis showed that the optimal cut-off values of NLR and PLR were 3.825, 179, respectively. Kaplan-Meier curve showed that low baseline levels NLR and PLR were associated with an improvement in both progression-free survival (PFS) (P < .001, < .001, respectively) and overall survival (OS) (P = .009, .006, respectively). In first-line treatment and non-first-line treatment, low baseline levels NLR and PLR were associated with an improvement in PFS. In multivariate analysis, low baseline NLR and PLR showed a strong association with both better PFS (P = .011, .027, respectively) and longer OS (P = .042, .039, respectively).

CONCLUSION

Low baseline NLR and PLR levels are significantly associated with better response in advanced NSCLC patients treated with PD-1/PD-L1 inhibitors, which may be indicators to predict the efficacy of immunotherapy in advanced NSCLC with driver-gene-negative.

Predictive and Diagnostic Values of Systemic Inflammatory Indices in Bronchopulmonary Dysplasia

BACKGROUND

Bronchopulmonary dysplasia (BPD) is the most common respiratory complication in preterm infants, and there is a lag in the diagnosis of BPD. Inflammation is a vital pathogenic factor for BPD; we aim to evaluate the predictive and diagnostic values of systemic inflammatory indices in BPD.

METHODS

Between 1 January 2019 and 31 May 2023, the clinical data of 122 premature infants with a gestational age of <32 weeks in the Department of Neonatology, the Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, were retrospectively collected and classified into non-BPD (n = 72) and BPD (n = 50) groups based on the National Institute of Child Health and Human Development 2018 criteria. To compare the general characteristics of each group, we identified the independent risk variables for BPD using multivariate logistic regression analysis, compared the systemic inflammatory indices at birth, 72 h, 1 week, 2 weeks, and 36 weeks postmenstrual age (PMA), and constructed the receiver operating characteristic curves of neutrophil-to-lymphocyte ratio (NLR) diagnosis of BPD at different time points.

RESULTS

① The independent risk factors for BPD in preterm infants were birth weight, small for gestational age, and days of oxygen therapy (all p < 0.05). ② At 72 h and 1 week after birth, the serum NLR of the BPD group was higher than for the non-BPD group (p < 0.05). Furthermore, the neutrophil count (N), NLR, monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index, systemic inflammation response index (SIRI), and pan-immune-inflammation value of infants with BPD were higher than the non-BPD group at 3 weeks after birth (p < 0.05). Moreover, at 36 weeks of PMA, the serum N, NLR, MLR, and SIRI of BPD infants were higher than those of non-BPD infants (p < 0.05). ③ The NLR of infants with and without BPD gradually increased after birth, reaching a peak at 72 h and 1 week, respectively. At 3 weeks postnatal, the NLR had the highest predictive power for BPD, with an area under the curve (AUC) of 0.717 (p < 0.001); the sensitivity was 56% and specificity was 86.1%. In addition, the NLR at 36 weeks of PMA exhibited some diagnostic value for BPD. The AUC was 0.693 (p < 0.001), the sensitivity was 54%, and specificity was 83.3%.

CONCLUSIONS

At 3 weeks after birth and 36 weeks of PMA, some systemic inflammation indices (like N, NLR, SIRI) of preterm infants with BPD have specific predictive and diagnostic values; these indices may help the management of high-risk preterm infants with BPD.

Novel nomogram for predicting survival in advanced non-small cell lung cancer receiving anti-PD-1 plus chemotherapy with or without antiangiogenic therapy

Background

This study aimed to develop and validate a novel nomogram to predict survival in advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD-1) inhibitor plus chemotherapy with or without antiangiogenic therapy.

Methods

A total of 271 patients with advanced NSCLC who received anti-PD-1 plus chemotherapy with or without antiangiogenic therapy were enrolled in our center and randomized into the training cohort (n = 133) and the internal validation cohort (n = 138). Forty-five patients from another center were included as an independent external validation cohort. The nomogram was created based on the multivariate Cox regression analysis to predict overall survival (OS) and progression-free survival (PFS). The performance of the nomogram was assessed using the concordance index (C-index), the time-dependent area under the receiver operating (ROC) curves (AUCs), calibration curves, and decision curve analysis (DCA).

Results

Four factors significantly associated with OS were utilized to create a nomogram to predict OS: Eastern Cooperative Oncology Group performance status (ECOG PS), programmed cell death-ligand 1 (PD-L1) expression, chemotherapy cycle, and pretreatment lactate dehydrogenase-albumin ratio (LAR). Six variables significantly associated with PFS were incorporated into the development of a nomogram for predicting PFS: ECOG PS, histology, PD-L1 expression, chemotherapy cycle, pretreatment platelet to lymphocyte (PLR), and pretreatment LAR. The C-indexes of the nomogram for predicting OS and PFS were 0.750 and 0.747, respectively. The AUCs for predicting the 6-month, 12-month, and 18-month OS and PFS were 0.847, 0.791, and 0.776 and 0.810, 0.787, and 0.861, respectively. The calibration curves demonstrated a good agreement between predictions and actual observations. The DCA curves indicated that the nomograms had good net benefits. Furthermore, the nomogram model was well-validated in the internal and external cohorts.

Conclusion

The novel nomogram for predicting the prognosis of advanced NSCLC receiving anti-PD-1 plus chemotherapy with or without antiangiogenic therapy may help guide clinical treatment decisions.

Prognostic evaluation of stage I lung adenocarcinoma based on systematic inflammatory response

BACKGROUND

This study aimed to construct an effective nomogram based on the clinical and laboratory characteristics to predict the prognosis of stage I lung adenocarcinoma with EGFR alteration.

METHODS

A retrospective study was performed of 913 eligible patients with EGFR alteration after surgery at Shanghai Pulmonary Hospital. The peripheral blood indicators were included in the nomogram. Calibration plots, concordance index, decision curve analysis, and X-tile software were used in this study. Recurrence-free survival (RFS) and overall survival were estimated by the Kaplan-Meier method and compared using the log-rank test.

RESULTS

Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio were independent risk factors for RFS. The calibration curves for RFS probabilities showed good agreement between the nomogram prediction and actual observation. Furthermore, the nomogram, including neutrophil to lymphocyte ratio and platelet to lymphocyte ratio had a higher concordance index (0.732, 95% confidence interval = 0.706 to 0.758) than that without neutrophil to lymphocyte ratio or platelet to lymphocyte ratio (0.713, 95% confidence interval = 0.686 to 0.740), and decision curve analysis plots showed that the nomogram with neutrophil to lymphocyte ratio and platelet to lymphocyte ratio had better clinical practicability. Additionally, the patients were divided into 2 groups according to cutoff values of risk points, and statistically significant differences in RFS and overall survival were observed between the high-risk and low-risk groups (P < .001).

CONCLUSIONS

High pretreatment levels of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio were strongly associated with a worse prognosis in stage I EGFR-altered lung adenocarcinomas. Besides, the proposed nomogram with neutrophil to lymphocyte ratio and platelet to lymphocyte ratio presented a better prediction ability for the survival of those patients.

Baseline and early changes in the neutrophil-lymphocyte ratio (NLR) predict survival outcomes in advanced colorectal cancer patients treated with immunotherapy

BACKGROUND

Systemic inflammation plays a role in carcinogenesis and is related to overall survival in patients with different cancer types, including those treated with immune checkpoint blockade (ICB). The neutrophil-lymphocyte ratio (NLR) is calculated by circulating neutrophil to lymphocyte counts, which represents an indicator of the balance between the deleterious roles of neutrophilia and the beneficial roles of lymphocyte-mediated immunity. We hypothesized that the NLR may predict outcomes in metastatic colorectal cancer (mCRC) patients treated with immunotherapy.

MATERIALS AND METHODS

This retrospective study included 110 mCRC patients who were treated with immunotherapy at Sun Yat-sen University Cancer Center. Several inflammatory biomarkers were measured at baseline and after two cycles of treatment. The X-tile program was used to obtain the cutoff values. We examined the impact of both baseline and posttreatment inflammatory index levels on overall survival (OS).

RESULTS

In univariate analysis, both a low baseline NLR (P = 0.014) and a decreased NLR after 2 cycles of immunotherapy (P < 0.001) were considerably correlated with better OS. In multivariate analysis, age, liver metastasis, baseline lymphocyte-monocyte ratio (LMR), baseline NLR and early changes in NLR independently predicted OS. Patients with both a low baseline NLR and an early NLR reduction had the longest OS (median, 29.63 months). The best outcomes were remarkably observed in patients who had both an early NLR reduction and a high tumor mutational burden (TMB) (≥10 mut/Mb) (P < 0.0001).

CONCLUSIONS

Both a low baseline NLR and an early NLR reduction are significantly associated with a better prognosis in mCRC patients treated with immunotherapy. Further analysis indicated that the combination of NLR and TMB could obtain additional predictive power.

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.

The prognostic biological markers of immunotherapy for non-small cell lung cancer: current landscape and future perspective

The emergence of immunotherapy, particularly programmed cell death 1 (PD-1) and programmed cell death ligand-1 (PD-L1) produced profound transformations for treating non-small cell lung cancer (NSCLC). Nevertheless, not all NSCLC patients can benefit from immunotherapy in clinical practice. In addition to limited response rates, exorbitant treatment costs, and the substantial threats involved with immune-related adverse events, the intricate interplay between long-term survival outcomes and early disease progression, including early immune hyperprogression, remains unclear. Consequently, there is an urgent imperative to identify robust predictive and prognostic biological markers, which not only possess the potential to accurately forecast the therapeutic efficacy of immunotherapy in NSCLC but also facilitate the identification of patient subgroups amenable to personalized treatment approaches. Furthermore, this advancement in patient stratification based on certain biological markers can also provide invaluable support for the management of immunotherapy in NSCLC patients. Hence, in this review, we comprehensively examine the current landscape of individual biological markers, including PD-L1 expression, tumor mutational burden, hematological biological markers, and gene mutations, while also exploring the potential of combined biological markers encompassing radiological and radiomic markers, as well as prediction models that have the potential to better predict responders to immunotherapy in NSCLC with an emphasis on some directions that warrant further investigation which can also deepen the understanding of clinicians and provide a reference for clinical practice.

Using the neutrophil-to-lymphocyte ratio to predict the outcome of individuals with nonsquamous non-small cell lung cancer receiving pembrolizumab plus platinum and pemetrexed

BACKGROUND

Factors predicting the response to pembrolizumab plus platinum and pemetrexed combination therapy (Pemb-Plt-PEM) in nonsquamous non-small cell lung cancer (non-sq NSCLC) are unclear. We investigated the Glasgow Prognostic (GP) score, neutrophil-to-lymphocyte ratio (NLR), and body mass index (BMI) as predictors of response to initial treatment with combination therapy in individuals with advanced non-sq NSCLC.

METHODS

We retrospectively reviewed 236 patients who received initial treatment with combination therapy for non-sq NSCLC at 13 institutions between December 2018 and December 2020. The usefulness of the GP score, NLR, and BMI as prognostic indicators was assessed. Cox proportional hazard models and the Kaplan-Meier method were used to compare progression-free survival (PFS) and overall survival (OS).

RESULTS

The response rate was 51.2% (95% CI: 44.9-57.5%). The median PFS and OS after beginning Pemb-Plt-PEM were 8.8 (95% CI: 7.0-11.9) months and 23.6 (95% CI: 18.7-28.6) months, respectively. The NLR independently predicted the efficacy of Pemb-Plt-PEM-the PFS and OS were more prolonged in individuals with NLR <5 than in those with NLR ≥5 (PFS: 12.8 vs. 5.3 months, p = 0.0002; OS: 29.4 vs. 12.0 months, p < 0.0001). BMI predicted the treatment response-individuals with BMI ≥22.0 kg/m2 had longer OS than did those with BMI < 22.0 kg/m2 (OS: 28.4 vs. 18.4 months, p = 0.0086).

CONCLUSIONS

The NLR significantly predicted PFS and OS, whereas BMI predicted OS, in individuals who initially received Pemb-Plt-PEM for non-sq NSCLC. These factors might be prognosis predictors in non-sq NSCLC.

Prognostic Potential of the Prognostic Nutritional Index in Non-Small Cell Lung Cancer Patients Receiving Pembrolizumab Combination Therapy with Carboplatin and Paclitaxel/Nab-Paclitaxel

INTRODUCTION

Pembrolizumab (Pemb) therapy in conjunction with carboplatin and paclitaxel (PTX)/nab-PTX has been efficacious in treating non-small cell lung cancer (NSCLC). However, the response predictors of this combination therapy (Pemb-combination) remain undetermined. We aimed to evaluate whether Glasgow prognostic score (GPS), neutrophil-to-lymphocyte ratio (NLR), body mass index (BMI), platelet-to-lymphocyte ratio (PLR), and prognostic nutritional index (PNI) are potential factors in prognosticating the response to Pemb-combination therapy in advanced NSCLC patients.

METHODS

We retrospectively recruited 144 NSCLC patients receiving first-line treatment with Pemb-combination therapy from 13 institutions between December 1, 2018, and December 31, 2020. GPS, NLR, BMI, PLR, and PNI were assessed for their efficacy as prognostic indicators. Cox proportional hazard models and the Kaplan-Meier method were used to compare the progression-free survival (PFS) and overall survival (OS) of the patients.

RESULTS

The treatment exhibited a response rate of 63.1% (95% confidence interval [CI]: 55.0-70.6%). Following Pemb-combination administration, the median PFS and OS were 7.3 (95% CI: 5.3-9.4) and 16.5 (95% CI: 13.9-22.1) months, respectively. Contrary to PNI, NLR, GPS, BMI, and PLR did not display substantially different PFS in univariate analysis. However, multivariate analysis did not identify PNI as an independent prognostic factor for PFS. Furthermore, univariate analysis revealed that GPS, BMI, and PLR exhibited similar values for OS but not NLR and PNI. Patients with PNI ≥45 were predicted to have better OS than those with PNI <45 (OS: 23.4 and 13.9 months, respectively, p = 0.0028). Multivariate analysis did not establish NLR as an independent prognostic factor for OS.

CONCLUSION

The PNI evidently predicted OS in NSCLC patients treated with Pemb-combination as first-line therapy, thereby validating its efficiency as a prognostic indicator of NSCLC.

Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy

Background

We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection.

Methods

The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR.

Results

Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response.

Conclusion

Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.

Comprehensive genomic analysis of primary bone sarcomas reveals different genetic patterns compared with soft tissue sarcomas

Introduction

Sarcomas are classified into two types, bone sarcoma and soft tissue sarcoma (STS), which account for approximately 1% of adult solid malignancies and 20% of pediatric solid malignancies. There exist more than 50 subtypes within the two types of sarcoma. Each subtype is highly diverse and characterized by significant variations in morphology and phenotypes. Understanding tumor molecular genetics is helpful in improving the diagnostic accuracy of tumors that have been difficult to classify based on morphology alone or that have overlapping morphological features. The different molecular characteristics of bone sarcoma and STS in China remain poorly understood. Therefore, this study aimed to analyze genomic landscapes and actionable genomic alterations (GAs) as well as tumor mutational burden (TMB), microsatellite instability (MSI), and programmed death ligand-1 (PD-L1) expression among Chinese individuals diagnosed with primary bone sarcomas and STS.

Methods

This retrospective study included 145 patients with primary bone sarcomas (n = 75) and STS (n = 70), who were categorized based on the 2020 World Health Organization classification system.

Results

Patients diagnosed with bone sarcomas were significantly younger than those diagnosed with STS (p < 0.01). The top 10 frequently altered genes in bone sarcoma and STS were TP53, CDKN2A, CDKN2B, MAP3K1, LRP1B, MDM2, RB1, PTEN, MYC, and CDK4.The EWSR1 fusions exhibited statistically significant differences (p < 0.01) between primary bone sarcoma and STS in terms of their altered genes. Based on the actionable genes defined by OncoKB, actionable GAs was found in 30.7% (23/75) of the patients with bone sarcomas and 35.7% (25/70) of those with STS. There were 4.0% (3/75) patients with bone sarcoma and 4.3% (3/70) patients with STS exhibited high tumor mutational burden (TMB-H) (TMB ≥ 10). There was only one patient with STS exhibited MSI-L, while the remaining cases were microsatellite stable. The positive rate of PD-L1 expression was slightly higher in STS (35.2%) than in bone sarcoma (33.3%), however, this difference did not reach statistical significance. The expression of PD-L1 in STS patients was associated with a poorer prognosis (p = 0.007). Patients with STS had a better prognosis than those with bone sarcoma, but the observed difference did not attain statistical significance (p = 0.21). Amplification of MET and MYC genes were negatively correlated with clinical prognosis in bone tumors (p<0.01).

Discussion

In conclusion, bone sarcoma and STS have significantly different clinical and molecular characteristics, suggesting that it is vital to diagnose accurately for clinical treatment. Additionally, comprehensive genetic landscape can provide novel treatment perspectives for primary bone sarcoma and STS. Taking TMB, MSI, PD-L1 expression, and OncoKB definition together into consideration, there are still many patients who have the potential to respond to targeted therapy or immunotherapy.

Prognostic significance of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is characterized by diagnosis at an advanced stage, low rate of operability and poor survival. Therefore, there is a need for a biomarker in NSCLC patients to predict the likely outcome and to accurately stratify the patients in terms of the most appropriate treatment modality. To evaluate prognostic value of pretreatment neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in NSCLC. A total of 124 NSCLC patients (mean ± standard deviation age: 60.7 ± 9.3 years, 94.4% were males) were included in this retrospective study. Data were retrieved from the hospital records. The association of NLR and PLR with clinicopathological factors and overall survival was analyzed. One-year, 2-year and 5-year survival rates were 59.2%, 32.0%, and 16.2%, respectively. Median duration of survival was shorter in patient groups with elevated NLR and PLR. Five-year survival rate was quite lower in patient groups with elevated NLR and PLR. Hazard rate (HR) for mortality was 1.76 (95% confidence interval [CI]: 1.19-2.61, P = .005) for NLR ≥ 3 over NLR < 3. HR was 1.64 (95%CI: 1.11-2.42, P = .013) for PLR ≥ 150 over PLR < 150. Cox-regression analysis revealed that, when adjusted for other independent predictors of survival, NLR and PLR still remain significant predictors of poorer survival. Our findings indicate that elevated pretreatment NLR and PLR are associated with advanced disease and poor survival in NSCLC patients, NLR and PLR values are correlated with each other.

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.

Construction of the prognostic model for small-cell lung cancer based on inflammatory markers: A real-world study of 612 cases with eastern cooperative oncology group performance score 0-1

OBJECTIVES

This research aimed to explore the relationship between pre-treatment inflammatory markers and other clinical characteristics and the survival of small-cell lung cancer (SCLC) patients who received first-line platinum-based treatment and to construct nomograms for predicting overall survival (OS) and progression-free survival (PFS).

METHODS

A total of 612 patients diagnosed with SCLC between March 2008 and August 2021 were randomly divided into two cohorts: a training cohort (n = 459) and a validation cohort (n = 153). Inflammatory markers, clinicopathological factors, and follow-up information of patients were collected for each case. Cox regression was used to conduct univariate and multivariate analyses and the independent prognostic factors were adopted to develop the nomograms. Harrell's concordance index (C-index) and time-dependent receiver operating characteristic curve were used to verify model differentiation, calibration curve was used to verify consistency, and decision curve analysis was used to verify the clinical application value.

RESULTS

Our results showed that baseline C-reactive protein/albumin ratio, neutrophil/lymphocyte ratio, NSE level, hyponatremia, the efficacy of first-line chemotherapy, and stage were independent prognostic factors for both OS and PFS in SCLC. In the training cohort, the C-index of PFS and OS was 0.698 and 0.666, respectively. In the validation cohort, the C-index of PFS and OS was 0.727 and 0.747, respectively. The nomograms showed good predictability and high clinical value. Also, our new clinical models were superior to the US Veterans Administration Lung Study Group (VALG) staging for predicting the prognosis of SCLC.

CONCLUSIONS

The two prognostic nomograms of SCLC including inflammatory markers, VALG stage, and other clinicopathological factors had good predictive value and could individually assess the survival of patients.

PD-1 blockade plus chemoradiotherapy as preoperative therapy for patients with BRPC/LAPC: A biomolecular exploratory, phase II trial

This is a phase II study of PD-1 blockade plus chemoradiotherapy as preoperative therapy for patients with locally advanced or borderline resectable pancreatic cancer (LAPC or BRPC, respectively). Twenty-nine patients are enrolled in the study. The objective response rate (ORR) is 60%, and the R0 resection rate is 90% (9/10). The 12-month progression-free survival (PFS) rate and 12-month overall survival (OS) rate are 64% and 72%, respectively. Grade 3 or higher adverse events are anemia (8%), thrombocytopenia (8%), and jaundice (8%). Circulating tumor DNA analysis reveals that patients with a >50% decline in maximal somatic variant allelic frequency (maxVAF) between the first clinical evaluation and baseline have a longer survival outcome and a higher response rate and surgical rate than those who are not. PD-1 blockade plus chemoradiotherapy as preoperative therapy displays promising antitumor activity, and multiomics potential predictive biomarkers are identified and warrant further verification.

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.

Prognostic value of inflammatory and nutritional indexes among advanced NSCLC patients receiving PD-1 inhibitor therapy

Though immunotherapy has to some extent improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), only a few patients benefit. Furthermore, immunotherapy efficacy is affected by inflammatory and nutritional status of patients. To investigate whether dynamics of inflammatory and nutritional indexes were associated with prognosis, 223 patients were analysed retrospectively. The inflammatory indexes of interest were neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) while prognostic nutritional index (PNI) and the haemoglobin, albumin, lymphocyte and platelet (HALP) score were considered as nutritional indexes. Patients were divided into high and low groups or into 'increase' and 'decrease' groups based on pre-treatment cut-off values and index dynamics after 6-week follow-up respectively. High pre-treatment PLR (OR = 2.612) and increase in NLR during follow-up (OR = 2.516) were significantly associated with lower objective response rates. Using multivariable analysis, high pre-treatment PLR (HR, 2.319) and increase in SII (HR, 1.731) predicted shorter progression-free survival, while high pre-treatment NLR (HR, 1.635), increase in NLR (HR, 1.663) and PLR (HR, 1.691) and decrease in PNI (HR, 0.611) predicted worse overall survival. The nomogram's C-index in inside validation was 0.718 (95% CI: 0.670-0.766). Our results indicated both nutritional and inflammatory indexes are associated with survival outcomes. Inflammatory indexes were additionally linked to treatment response. Index dynamics are better predictors than baseline values in predicting survival in advanced NSCLC patients receiving PD-1 inhibitor combined with chemotherapy as first-line.

Measurement of sarcopenia in lung cancer inpatients and its association with frailty, nutritional risk, and malnutrition

Background

Sarcopenia, frailty, and malnutrition are associated with undesirable clinical outcomes in cancer patients. Sarcopenia-related measurements may be promising fast biomarkers for frailty. Our objectives were to assess the prevalence of nutritional risk, malnutrition, frailty, and sarcopenia in lung cancer inpatients, and describe the relationship of them.

Methods

Stage III and IV lung cancer inpatients were recruited before chemotherapy. The skeletal muscle index (SMI) was assessed by multi-frequency bioelectric impedance analysis (m-BIA). Sarcopenia, frailty, nutritional risk, and malnutrition were diagnosed according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019), Fried Frailty Phenotype (FFP), nutritional risk screening-2002 (NRS-2002), and Global Leadership Initiative on Malnutrition criteria (GLIM), and correlation analysis was performed between them with Pearson's r correlation coefficients. A univariate and multivariate logistic regression analysis was conducted for all patients, gender and age-stratified subgroups to obtain odds ratios (ORs) and 95% confidence intervals (95%CIs).

Results

The cohort included 97 men (77%) and 29 women (23%), with mean age of 64.8 ± 8.7 years. Among the 126 patients, 32 (25.4%) and 41 (32.5%) had sarcopenia and frailty, and the prevalence of nutritional risk and malnutrition was 31.0% (n = 39) and 25.4% (n = 32). Adjusted for age and gender, SMI was correlated with FFP (r = -0.204, p = 0.027), and did not remain significantly when stratified by gender. Stratification according to age revealed in ≥65-years-old population, SMI and FFP were significantly correlated (r = -0.297, p = 0.016), which is not seen in <65-years-old group (r = 0.048, p = 0.748). The multivariate regression analysis showed FFP, BMI, and ECOG were the independent variables associated with sarcopenia (OR 1.536, 95%CI 1.062-2.452, p = 0.042; OR 0.625, 95%CI 0.479-0.815, p = 0.001; OR 7.286, 95%CI 1.779-29.838, p = 0.004).

Conclusion

Comprehensively assessed sarcopenia is independently associated with frailty based on FFP questionnaire, BMI, and ECOG. Therefore, sarcopenia assessment including m-BIA based SMI, and muscle strength and function could be used to indicate frailty to help select the targeting patients for care. Moreover, in addition to muscle mass, muscle quality should not be ignored in clinical practice.

Prognostic Value of the Lung Immune Prognostic Index for Metastatic Non-Small Cell Lung Cancer Patients: A Chinese Cohort Study

Background

Most cancer-related deaths around the globe are caused by lung cancer. The present treatments for metastatic non-small cell lung cancer (mNSCLC) are cytotoxic chemotherapy (CCT), targeted therapy (TT) and immunotherapy, but the benefit of the same regime varies greatly. Hence, it is important to identify biomarkers to predict the efficacy of modalities. Previous literature suggested certain parameters might be predictive factors. Nevertheless, the utility of these parameters is limited due to the types of solid tumors.

Purpose

The study aimed to examine whether the lung immune prognostic index (LIPI) was related to outcomes of CCT, immune checkpoint inhibitors (ICIs) and TT for mNSCLC patients.

Materials and Methods

A retrospective cohort study between September 2012 and May 2020 was conducted on 350 Chinese mNSCLC patients, including 147 patients receiving ICIs, 103 TT, and 100 CCT. The data were examined to analyze the prognostic value of LIPI among various treatments.

Main Outcomes and Measures

The associations between PFS and good, intermediate, or poor prognostic LIPI scores in ICIs, TT, and CCT were determined, respectively.

Results

In univariable analyses, there was a relevance between a good LIPI score and better PFS among patients receiving ICIs (HR, 0.81; 95% CI, 0.44-1.51), TT (HR, 0.35; 95% CI, 0.16-1.74), and CCT (HR, 0.39; 95% CI, 0.19-0.80). In multivariable analyses, the intermediate LIPI score was linked to better PFS only in patients receiving TT (HR, 0.31; 95% CI, 0.17-0.92) rather than ICIs (HR, 1.12; 95% CI, 0.66-2.45) or CCT (HR, 1.24; 95% CI, 0.49-4.55).

Conclusion

Baseline LIPI value is an important prognostic biomarker for mNSCLC patients treated with TT. Shorter PFS with TT was associated with poor baseline LIPI. Poor LIPI score may be considered as a promising indicator showing which patients are unlikely to respond well to TT. The prognostic value of LIPI can be more clearly determined through prospective clinical study.

Quantifying causal effects from observed data using quasi-intervention

BACKGROUND

Causal inference is a crucial element within medical decision-making. There have been many methods for investigating potential causal relationships between disease and treatment options developed in recent years, which can be categorized into two main types: observational studies and experimental studies. However, due to the nature of experimental studies, financial resources, human resources, and patients' ethical considerations, researchers cannot fully control the exposure of the research participants. Furthermore, most existing observational research designs are limited to determining causal relationships and cannot handle observational data, let alone determine the dosages needed for medical research.

RESULTS

This paper presents a new experimental strategy called quasi-intervention for quantifying the causal effect between disease and treatment options in observed data by using a causal inference method, which converts the potential effect of different treatment options on disease into computing differences in the conditional probability. We evaluated the accuracy of the quasi-intervention by quantifying the impact of adjusting Chinese patients' neutrophil-to-lymphocyte ratio (NLR) on their overall survival (OS) (169 lung cancer patients and 79 controls).The results agree with the literature in this study, consisting of nine papers on cohort studies on the NLR and the prognosis of lung cancer patients, proving that our method is correct.

CONCLUSION

Taken together, the results imply that quasi-intervention is a promising method for quantifying the causal effect between disease and treatment options without clinical trials, and it could improve confidence about treatment options' efficacy and safety.

Prognostic and Clinical Value of the Systemic Immune-Inflammation Index in Biliary Tract Cancer: A Meta-Analysis

Previous studies that explored the prognostic and clinical value of the systemic immune-inflammation index (SII) in biliary tract cancer (BTC) had inconsistent results. We conducted this meta-analysis to evaluate the prognostic and clinicopathological role of the SII in biliary tract cancer. Combined analysis demonstrated that high SII levels had worse overall survival (HR = 1.92, 95% CI: 1.66-2.21, p < 0.001) than those with low SII levels. And an elevated SII was associated with lymph node metastasis (OR = 1.44, 95% CI = 1.18-1.76; p < 0.001), TNM stage (OR = 1.49, 95% CI = 1.05-2.13; p = 0.028), and vascular invasion (OR = 1.49, 95% CI = 1.05-2.13; p = 0.028). Conversely, no significant association between a high SII and sex or tumor differentiation was found. Our findings demonstrate that high SII levels were correlated with unfavorable survival outcomes among patients with BTC and that they were also correlated with some higher malignancy features of BTC.

Platelets upregulate tumor cell programmed death ligand 1 in an epidermal growth factor receptor-dependent manner in vitro

Programmed death ligand 1 (PD-L1) is an immune checkpoint protein that suppresses cytotoxic T lymphocytes and is often overexpressed in cancers. Due to favorable clinical trial results, immune checkpoint inhibition (ICI) is part of Food and Drug Administration approved immuno-oncology therapies; however, not all patients benefit from ICI therapy. High blood platelet-to-lymphocyte ratio has been associated with failure of ICI treatment, but whether platelets have a role in hindering ICI response is unclear. Here, we report that coculturing platelets with cancer cell lines increased protein and gene expression of tumor cell PD-L1, which was reduced by antiplatelet agents, such as aspirin and ticagrelor. Platelet cytokine arrays revealed that the well-established cytokines, including interferon-γ, were not the main regulators of platelet-mediated PD-L1 upregulation. Instead, the high molecular weight epidermal growth factor (EGF) is abundant in platelets, which caused an upregulation of tumor cell PD-L1. Both an EGF-neutralizing antibody and cetuximab (EGF receptor [EGFR] monoclonal antibody) inhibited platelet-induced increases in tumor cell PD-L1, suggesting that platelets induce tumor cell PD-L1 in an EGFR-dependent manner. Our data reveal a novel mechanism for platelets in tumor immune escape and warrant further investigation to determine if targeting platelets improves ICI therapeutic responses.

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.

Clinlabomics: leveraging clinical laboratory data by data mining strategies

The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.