Prognostic Value of White Blood Cells Detected for the First Time After Adjuvant Chemotherapy in Primary Operable Non-Small Cell Lung Cancer

Association between preoperative white blood cell counts and thirty-day surgical mortality after craniotomy in adult intracranial tumor patients

Objective

White blood cell (WBC) counts has been identified as a prognostic biomarker which frequently predict adverse outcomes and mortality risk in various conditions. However, evidence for the association between WBC counts and short-term outcomes after intracranial tumor resection remains limited. This study aimed to explore associations between preoperative WBC counts and thirty-day surgical mortality after craniotomy in adult intracranial tumor patients.

Methods

This retrospective cohort study performed secondary analysis of 18,049 intracranial tumor craniotomy patients from the ACS NSQIP database (2012-2015). The major exposure and outcome were preoperative WBC counts and thirty-day surgical mortality, respectively. Cox regression modeling assessed the linear association between them. Non-linear associations between them were evaluated by conducting smooth curve fitting using an additive Cox proportional hazard model in conjunction with segmented linear regression modeling. Subgroup analysis and interaction testing assessed effect modification. Sensitivity analysis evaluated result robustness.

Results

The total thirty-day surgical mortality after craniotomy was 2.49% (450/18,049). The mean of preoperative WBC counts was 9.501 ± 4.402 × 10^9/L. Fully adjusted model shows that elevated preoperative WBC counts was independently associated with increased thirty-day surgical mortality (HR = 1.057, 95%CI: 1.040, 1.076). Further analysis revealed a non-linear association between them: below a WBC threshold of 13.6 × 10^9/L, higher WBC counts elevated thirty-day mortality (HR = 1.117; 95%CI: 1.077, 1.158), while risk plateaued and no significant mortality rise occurred above this level (HR = 1.015, 95%CI: 0.982, 1.050). Steroid usage status has a significant effect modification on the WBC-mortality association (P for interaction = 0.002). The non-linear WBC-mortality association was only present for non-steroid users (HR = 1.158, 95%CI: 1.108, 1.210) but not steroid users (HR = 1.009, 95%CI: 0.966, 1.055). The sensitivity analysis confirmed the result robustness.

Conclusion

Elevated preoperative WBC counts were independently and non-linearly associated with an increased risk of thirty-day surgical mortality in adult non-steroid use patients undergoing craniotomy for intracranial tumors. As a convenient predictor, preoperative WBC data allows improved risk profiling and personalized management in adult intracranial tumor patients.

Characterization of the fatty acid metabolism-related genes in lung adenocarcinoma to guide clinical therapy

BACKGROUND

Lung adenocarcinoma (LUAD) is a common cancer with a bad prognosis. Numerous investigations have indicated that the metabolism of fatty acids plays an important role in the occurrence, progression, and treatment of cancer. Consequently, the objective of the current investigation was to elucidate the role and prognostic significance of genes associated with fatty acid metabolism in patients diagnosed with LUAD.

MATERIALS AND METHODS

The data files were acquired from The Cancer Genome Atlas database and GSE31210 dataset. Univariate Cox and least absolute shrinkage and selection operator regression analyses were conducted to establish a prognostic risk scoring model depending on fatty acid metabolism-associated genes to predict the prognosis of patients with LUAD. pRRophetic algorithm was utilized to evaluate the potential therapeutic agents. Gene set variation analysis combined with cell-type identification based on the estimation of relative subsets of RNA transcript and single-sample gene set enrichment analysis was used to determine the association between immune cell infiltration and risk score. Tumor immune dysfunction and exclusion algorithm was employed to predict immunotherapeutic sensitivity.

RESULTS

To forecast the prognosis of patients with LUAD, a risk scoring model based on five genes associated with fatty acid metabolism was developed, including LDHA, ALDOA, CYP4B1, DPEP2, and HPGDS. Using the risk score algorithm, patients were divided into higher- and lower-risk categories. Patients classified as minimal risk showed superior prognosis than those with elevated risk. In addition, individuals in the higher-risk group had a proclivity toward chemoresistance and amenable to immunotherapy.

CONCLUSION

The prognostic risk scoring model aids in estimating the prognosis of LUAD patients. It may also provide new insights into LUAD carcinogenesis and therapeutic strategies.

Investigation of white blood cell characteristics in cerebrospinal fluid samples at pediatric brain tumor diagnosis

PURPOSE

The role of white blood cells (WBC) in the pediatric central nervous system (CNS) tumor microenvironment is incompletely defined. We hypothesized that the WBC profile in cerebrospinal fluid (CSF) correlates with the presence of tumor cells and prognosis in pediatric CNS tumors, as well as other patient and disease characteristics, and differs by tumor type, thus giving insight into the tumor immune response.

METHODS

We conducted a retrospective analysis of CSF WBC profiles at CNS tumor diagnosis in 269 patients at our institution. We examined total nucleated cell count, absolute counts, and percentages by WBC subtype. We compared CSF WBC values by tumor cell presence, patient vital status, tumor location, and the most common tumor types.

RESULTS

Patients who died of their tumor had a lower CSF lymphocyte percentage and a higher absolute monocyte count in CSF at diagnosis. The presence of tumor cells in CSF was associated with fewer lymphocytes and monocytes. Ventricular tumors had higher CSF lymphocyte, monocyte, macrophage, and total nucleated cell counts than extraventricular tumors. Germ cell tumors, low-grade glioma, high-grade glioma, and ependymoma had lower macrophage counts or percentages compared to other tumor types.

CONCLUSIONS

WBC profile in CSF at pediatric CNS tumor diagnosis correlates with patient prognosis and presence of metastatic cells, along with tumor type and other tumor characteristics like relationship to the ventricles. Prospective CSF profiling and study may be useful to future immunotherapy and other pediatric CNS tumor clinical trials.

Circulating activated immune cells as a potential blood biomarkers of non-small cell lung cancer occurrence and progression

BACKGROUND

Treatment for non-small cell lung cancer (NSCLC) has greatly improved in recent years. However, noninvasive early screening for carcinogenesis and progression unclear. The aim of this study was to explore the predictive value of peripheral blood immune cells in untreated NSCLC patients.

METHODS

We retrospectively enrolled 305 untreated NSCLC patients and 132 healthy participants from February 2016 to August 2019 in Peking Union Medical College Hospital. Immune cell levels were determined by flow cytometry and routine blood tests.

RESULTS

NSCLC patients had lower levels of T lymphocytes, NK cells, CD8+ T cells, naïve CD4+/CD4+, naïve CD4+ T cells and higher levels of CD4+ T cells, memory CD4+/CD4+ T cells, memory CD4+ T cells, CD4+CD28+/CD4+ T cells, CD4+CD28+ T cells, CD8+CD28+/CD8+ T cells, CD8+HLA-DR+/CD8+ T cells, CD8+HLA-DR+ T cells T cells, CD8+CD38+/CD8+ T cells, CD8+CD38+ T cells and CD4+/CD8+ T cells than those in controls. The percentages of specific lymphocyte subtypes were significantly different in cancer patients versus healthy individuals. For instance, cancer patients had lower levels of B cells, CD4+ T cells, naïve CD4+/CD4+ T cells, naïve CD4+ T cells, CD4+CD28+ T cells, CD8+CD28+ T cells and higher levels of NK cells, white blood cells (WBC), monocytes, neutrophils, eosinophils, basophils, monocytes to lymphocyte ratio (MLR), neutrophils to lymphocyte ratio (NLR), eosinophil to lymphocyte ratio (ELR), basophil to lymphocyte ratio (BLR), and blood platelet to lymphocyte ratio (PLR).

CONCLUSIONS

Abnormal T cell levels can be used as an independent predictive biomarker for noninvasive early screening in NSCLC occurrence and progression.

Correlation of peripheral blood biomarkers with clinical outcomes in NSCLC patients with high PD-L1 expression treated with pembrolizumab

Background

Immune checkpoint inhibitors (ICIs) are currently the standard therapy in advanced non-small cell lung cancer (NSCLC); however, there is no well-established prognostic biomarker. We investigated the relationship between survival outcomes and three peripheral blood biomarkers, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR), as well as a new score termed the risk blood biomarker (RBB), calculated from the combination of the neutrophil-monocyte-to-lymphocyte ratio (NMLR) and white blood cell count (WBC).

Methods

This study included patients with stage IV or recurrent NSCLC confirmed with programmed death ligand 1 (PD-L1) expression ≥50% who received pembrolizumab monotherapy as first-line treatment at the Virgen del Rocío University Hospital in Seville, Spain. To establish the relationship between baseline peripheral blood biomarkers and survival outcomes, progression free survival (PFS) and overall survival (OS), we used the Kaplan-Meier method and multivariable Cox regression models.

Results

A total of 51 patients were included in this study. In multivariate analysis, baseline NLR and PLR showed a strong association with PFS [NLR hazard ratio (HR): 0.19, 95% confidence interval (CI): 0.09–0.44, P<0.001; PLR HR: 0.46, 95% CI: 0.23–0.92, P=0.03] and OS (NLR HR: 0.07, 95% CI: 0.02–0.19, P<0.001; PLR HR: 0.29, 95% CI: 0.13–0.67, P=0.004), and the MLR was associated with OS (MLR HR: 0.34, 95% CI: 0.15–0.76, P=0.01). According to the RBB score, groups with lower scores were associated with superior PFS (group 0: HR: 0.16, 95% CI: 0.06–0.41, P<0.001 and group 1: HR: 0.29, 95% CI: 0.12–0.73, P=0.01) and OS (group 0: HR: 0.04, 95% CI: 0.01–0.17, P<0.001 and group 1: HR: 0.15, 95% CI: 0.05–0.42, P<0.001).

Conclusions

Low baseline NLR, MLR and PLR are significantly associated with better PFS, and low baseline NLR and PLR are associated with better OS. Additionally, we identified three subgroups of patients using the RBB score, and low scores were associated with improved survival outcomes and response to therapy.

Prediction System for the Lung Cancer Patients and Classification Accuracy Enhancement Using Ensemble Method

Lung cancer is the biggest challenge in the research world. Blood samples for lung cancer patients are significant for the prediction method in the research environment. Accurate prediction is essential to increase the survival period and may help to take proper medication. The feature selection is an essential part of this prediction system. In this method, the essential features are analyzed from lung cancer patient’s blood. Biomarkers can be identified from blood and other tests. Biomarkers are used in many scientific fields. The Serum CKAP4 levels were analyzed from lung cancer patient’s blood at the TNM stages. White blood counts and Hemoglobin are viewed as an analysis of immunity, and CKAP4 is located at an immunity level that has been recognized in the body fluid of patients with lung cancer. The system is analyzed immunity from collected real health information by a proposed Gaussian Kb Ensemble Weighting Classifier method. The novel attributes are composed of a cancer research center and cancer sanatoriums. The measurement of weighting value {low = 0, high = 1} of blood in Serum CKAP4, Hemoglobin, and the WBC are classified by immunity range. High immunity people’s survival rate is high at TNM stage 1. If not, high immunity was survival rate is low at TNM stage 1. Lung cancer patient’s survivability classification was performed by various supervised machine learning models such as Ada boost, neural networks, and SVM model. The Gaussian Kb Ensemble Weighting Classifier method helped to improve the classification accuracy by feature selection and the algorithm was implemented in the MATLAB environment. Kaplan–Meier curve method used to analyzes results. The classified labels are compared with existing results. The area proved the Gaussian Kb Ensemble weighting classifier algorithm under the Curve through the ROC method.

The value of blood biomarkers of progression and prognosis in ALK-positive patients with non-small cell lung cancer treated with crizotinib

AIM

Valuable and convenient prognostic predictors are essential for targeted therapy of non-small cell lung cancer (NSCLC). Patients with early-stage cancer and EGFR mutations who's neutrophils-to-lymphocytes rate (NLR) could be prognostic factor to evaluate efficacy. However, the prognostic role of NLR in patients receiving ALK inhibitors has not been established. Additionally, the relation between the efficacy of ALK inhibitors and derived NLR (dNLR), platelets-to-lymphocytes rate (PLR), white blood cells (WBC) and hemoglobin (HGB) are still unknown.

METHODS

This is a retrospective single-center study and enrolled 113 staged IIIB-IV ALK-positive NSCLC patients who had received crizotinib treatment. Pretreatment NLR, dNLR, PLR, WBC, HGB were collected and calculated. Cox regression analysis were conducted to study the prognostic roles of NLR, dNLR, PLR, WBC, and HGB on progression-free survival (PFS) and overall survival (OS). Z-test was utilized to identify the difference among all predictive factors' receiver-operating characteristics (ROC) curves.

RESULTS

The median PFS and OS were 10.1 and 23.4 months. Elevated NLR, dNLR, PLR and decreased HGB were associated with worse PFS (95% confidence interval [CI], 1.078-2.304, P = 0.018; 95% CI, 1.043-2.222, P = 0.028; 95% CI, 1.257-2.757, P = 0.002; 95% CI, 0.368-0.843, P = 0.005, respectively) and OS (95% CI, 1.698-5.721, P < 0.001; 95% CI, 1.273-3.984, P = 0.005; 95% CI, 2.174-6.347, P < 0.001; 95% CI, 0.246-0.710, P = 0.001, respectively). Z-test revealed there were no significant differences between single factors or combination of them to predict the efficacy.

CONCLUSIONS

Trend of NLR, dNLR, PLR and WBC could be used to identify patients progress status in ALK-positive NSCLC patients receiving crizotinib. Combination of all biomarkers is no superior to single biomarker.