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      Prognostic value of preoperative hematological markers in patients with glioblastoma multiforme and construction of random survival forest model

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          Abstract

          Objective

          In recent years, an increasing number of studies have revealed that patients’ preoperative inflammatory response, coagulation function, and nutritional status are all linked to the occurrence, development, angiogenesis, and metastasis of various malignant tumors. The goal of this study is to determine the relationship between preoperative peripheral blood neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), platelet to lymphocyte ratio (PLR), and platelet to fibrinogen ratio (FPR). Prognostic nutritional index (PNI) and the prognosis of glioblastoma multiforme (GBM) patients, as well as establish a forest prediction model that includes preoperative hematological markers to predict the individual GBM patient’s 3-year survival status after treatment.

          Methods

          The clinical and hematological data of 281 GBM patients were analyzed retrospectively; overall survival (OS) was the primary endpoint. X-Tile software was used to determine the best cut-off values for NLR, SII, and PLR, and the survival analysis was carried out by the Kaplan–Meier method as well as univariate and multivariate COX regression. Afterward, we created a random forest model that predicts the individual GBM patient’s 3-year survival status after treatment, and the area under the curve (AUC) is used to validate the model’s effectiveness.

          Results

          The best cut-off values for NLR, SII, and PLR in GBM patients’ preoperative peripheral blood were 2.12, 537.50, and 93.5 respectively. The Kaplan–Meier method revealed that preoperative GBM patients with high SII, high NLR, and high PLR had shorter overall survival, and the difference was statistically significant. In addition to clinical and pathological factors. Univariate Cox showed NLR (HR = 1.456, 95% CI: 1.286 ~ 1.649, P < 0.001) MLR (HR = 1.272, 95% CI: 1.120 ~ 1.649, P < 0.001), FPR (HR = 1.183,95% CI: 1.049 ~ 1.333, P < 0.001), SII (HR = 0.218,95% CI: 1.645 ~ 2.127, P < 0.001) is related to the prognosis and overall survival of GBM. Multivariate Cox proportional hazard regression showed that SII (HR = 1.641, 95% CI: 1.430 ~ 1.884, P < 0.001) is also related to the overall survival of patients with GBM. In the random forest prognostic model with preoperative hematologic markers, the AUC in the test set and the validation set was 0.907 and 0.900, respectively.

          Conclusion

          High levels of NLR, MLR, PLR, FPR, and SII before surgery are prognostic risk factors for GBM patients. A high preoperative SII level is an independent risk factor for GBM prognosis. The random forest model that includes preoperative hematological markers has the potential to predict the individual GBM patient’s 3-year survival status after treatment,and assist the clinicians for making a good clinical decision.

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          Most cited references31

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          CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2013–2017

          The Central Brain Tumor Registry of the United States (CBTRUS), in collaboration with the Centers for Disease Control (CDC) and National Cancer Institute (NCI), is the largest population-based registry focused exclusively on primary brain and other central nervous system (CNS) tumors in the United States (US) and represents the entire US population. This report contains the most up-to-date population-based data on primary brain tumors (malignant and non-malignant) and supersedes all previous CBTRUS reports in terms of completeness and accuracy. All rates (incidence and mortality) are age-adjusted using the 2000 US standard population and presented per 100,000 population. The average annual age-adjusted incidence rate (AAAIR) of all malignant and non-malignant brain and other CNS tumors was 23.79 (Malignant AAAIR=7.08, non-Malignant AAAIR=16.71). This rate was higher in females compared to males (26.31 versus 21.09), Blacks compared to Whites (23.88 versus 23.83), and non-Hispanics compared to Hispanics (24.23 versus 21.48). The most commonly occurring malignant brain and other CNS tumor was glioblastoma (14.5% of all tumors), and the most common non-malignant tumor was meningioma (38.3% of all tumors). Glioblastoma was more common in males, and meningioma was more common in females. In children and adolescents (age 0-19 years), the incidence rate of all primary brain and other CNS tumors was 6.14. An estimated 83,830 new cases of malignant and non-malignant brain and other CNS tumors are expected to be diagnosed in the US in 2020 (24,970 malignant and 58,860 non-malignant). There were 81,246 deaths attributed to malignant brain and other CNS tumors between 2013 and 2017. This represents an average annual mortality rate of 4.42. The 5-year relative survival rate following diagnosis of a malignant brain and other CNS tumor was 36.0% and for a non-malignant brain and other CNS tumor was 91.7%.
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            The role of microglia and macrophages in glioma maintenance and progression.

            There is a growing recognition that gliomas are complex tumors composed of neoplastic and non-neoplastic cells, which each individually contribute to cancer formation, progression and response to treatment. The majority of the non-neoplastic cells are tumor-associated macrophages (TAMs), either of peripheral origin or representing brain-intrinsic microglia, that create a supportive stroma for neoplastic cell expansion and invasion. TAMs are recruited to the glioma environment, have immune functions, and can release a wide array of growth factors and cytokines in response to those factors produced by cancer cells. In this manner, TAMs facilitate tumor proliferation, survival and migration. Through such iterative interactions, a unique tumor ecosystem is established, which offers new opportunities for therapeutic targeting.
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              Tumour-activated neutrophils in gastric cancer foster immune suppression and disease progression through GM-CSF-PD-L1 pathway

              Objective Neutrophils are prominent components of solid tumours and exhibit distinct phenotypes in different tumour microenvironments. However, the nature, regulation, function and clinical relevance of neutrophils in human gastric cancer (GC) are presently unknown. Design Flow cytometry analyses were performed to examine levels and phenotype of neutrophils in samples from 105 patients with GC. Kaplan-Meier plots for overall survival were performed using the log-rank test. Neutrophils and T cells were isolated, stimulated and/or cultured for in vitro and in vivo regulation and function assays. Results Patients with GC showed a significantly higher neutrophil infiltration in tumours. These tumour-infiltrating neutrophils showed an activated CD54+ phenotype and expressed high level immunosuppressive molecule programmed death-ligand 1 (PD-L1). Neutrophils activated by tumours prolonged their lifespan and strongly expressed PD-L1 proteins with similar phenotype to their status in GC, and significant correlations were found between the levels of PD-L1 and CD54 on tumour-infiltrating neutrophils. Moreover, these PD-L1+ neutrophils in tumours were associated with disease progression and reduced GC patient survival. Tumour-derived GM-CSF activated neutrophils and induced neutrophil PD-L1 expression via Janus kinase (JAK)-signal transducer and activator of transcription 3 (STAT3) signalling pathway. The activated PD-L1+ neutrophils effectively suppressed normal T-cell immunity in vitro and contributed to the growth and progression of human GC in vivo; the effect could be reversed by blocking PD-L1 on these neutrophils. Conclusions Our results illuminate a novel mechanism of PD-L1 expression on tumour-activated neutrophils in GC, and also provide functional evidence for these novel GM-CSF-PD-L1 pathways to prevent, and to treat this immune tolerance feature of GC.
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                Author and article information

                Contributors
                dxz181581@163.com
                yangbo96@163.com
                chengbinzhao2012@126.com
                zzuborantie@163.com
                zzucaolei@126.com
                gaoyvyuan@163.com
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                12 May 2023
                12 May 2023
                2023
                : 23
                : 432
                Affiliations
                GRID grid.412633.1, ISNI 0000 0004 1799 0733, The First Affiliated Hospital of Zhengzhou University, ; Zhengzhou, China
                Article
                10889
                10.1186/s12885-023-10889-0
                10176909
                37173662
                12eb9ee9-075b-46ea-9113-c92295a2cac2
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 4 December 2022
                : 26 April 2023
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Oncology & Radiotherapy
                glioblastoma multiforme,prognostic analysis,preoperative hematological markers,inflammatory immune index,random survival forest model

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