Genetic Intratumor Heterogeneity Remodels the Immune Microenvironment and Induces Immune Evasion in Brain Metastasis of Lung Cancer.

INTRODUCTION: Brain metastasis, with the highest incidence in patients with lung cancer, significantly worsens prognosis and poses challenges to clinical management. To date, how brain metastasis evades immune elimination remains unknown. METHODS: Whole-exome sequencing and RNA sequencing were performed on 30 matched brain metastasis, primary lung adenocarcinoma, and normal tissues. Data from The Cancer Genome Atlas primary lung adenocarcinoma cohort, including multiplex immunofluorescence, were used to support the findings of bioinformatics analysis. RESULTS: Our study highlights the key role of intratumor heterogeneity of genomic alterations in the metastasis process, mainly caused by homologous recombination deficiency or other somatic copy number alteration-associated mutation mechanisms, leading to increased genomic instability and genomic complexity. We further proposed a selection model of brain metastatic evolution in which intratumor heterogeneity drives immune remodeling, leading to immune escape through different mechanisms under local immune pressure. CONCLUSIONS: Our findings provide novel insights into the metastatic process and immune escape mechanisms of brain metastasis and pave the way for precise immunotherapeutic strategies for patients with lung cancer with brain metastasis.

Construction of a predictive model based on MIV-SVR for prognosis and length of stay in patients with traumatic brain injury: Retrospective cohort study.

Objective: To investigate the mean impact value (MIV) method for discerning the most efficacious input variables for the machine learning (ML) model. Subsequently, various ML algorithms are harnessed to formulate a more accurate predictive model that can forecast both the prognosis and the length of hospital stay for patients suffering from traumatic brain injury (TBI). Design: Retrospective cohort study. Participants: The study retrospectively accrued data from 1128 cases of patients who sought medical intervention at the Neurosurgery Center of the Second Affiliated Hospital of Anhui Medical University, within the timeframe spanning from May 2017 to May 2022. Methods: We performed a retrospective analysis of patient data obtained from the Neurosurgery Center of the Second Hospital of Anhui Medical University, covering the period from May 2017 to May 2022. Following meticulous data filtration and partitioning, 70% of the data were allocated for model training, while the remaining 30% served for model evaluation. During the construction phase of the ML models, a gamut of 11 independent variables-including, but not limited to, in-hospital complications and patient age-were utilized as input variables. Conversely, the length of stay (LOS) and the Glasgow Outcome Scale (GOS) scores were designated as output variables. The model architecture was initially refined through the MIV methodology to identify optimal input variables, whereupon five distinct predictive models were constructed, encompassing support vector regression (SVR), convolutional neural networks (CNN), backpropagation (BP) neural networks, artificial neural networks (ANN) and logistic regression (LR). Ultimately, SVR emerged as the most proficient predictive model and was further authenticated through an external dataset obtained from the First Hospital of Anhui Medical University. Results: Upon incorporating the optimal input variables as ascertained through MIV, it was observed that the SVR model exhibited remarkable predictive prowess. Specifically, the Mean Absolute Percentage Error (MAPE) of the SVR model in predicting the GOS score in the test dataset is only 6.30%, and the MAPE in the external validation set is only 7.61%. In terms of predicting hospitalization time, the accuracy of the test and external validation sets were 9.28% and 7.91%, respectively. This error indicator is significantly lower than the error of other prediction models, thus proving the excellent efficacy and clinical reliability of the MIV-optimized SVR model. Conclusion: This study unequivocally substantiates that the incorporation of MIV for selecting optimal input variables can substantially augment the predictive accuracy of machine learning models. Among the models examined, the MIV-SVR model emerged as the most accurate and clinically applicable, thereby rendering it highly conducive for future clinical decision-making processes.

Online dynamic nomogram for predicting pain recurrence after microvascular decompression in trigeminal neuralgia.

Trigeminal neuralgia (TN) is one of the most common causes of facial pain. Microvascular decompression (MVD) is the first-choice surgical treatment. The present study aimed to develop a novel practical assessment system based on preoperative clinical and imaging factors for clinicians to predict the likelihood of pain recurrence following MVD in TN. A total of 56 patients with primary unilateral TN who underwent MVD were retrospectively analyzed. Patients were followed up to observe pain recurrence 1 year after MVD. An online dynamic nomogram was constructed for predicting the probability of pain recurrence after MVD in patients with TN based on multivariate logistic model. The concordance index (C-index) and receiver operating characteristic (ROC) were used to measure model discrimination. Bootstrap resampling was used for internal validation of the model and calibration curve was constructed. Decision curve analysis (DCA) was used to assess clinical applicability. Factors such as numeric rating scale (to score pain degree of patients with TN), response to neuroanalgesic drugs and neurovascular contact on magnetic resonance imaging were independent risk factors affecting the pain recurrence rate (all P<0.05). C-index was 0.973 (95%CI, 0.938-1.000) and the area under the ROC was 0.973 (95%CI, 0.938-1.000). Calibration curve with a 1,000 bootstrap resampling showed a good fit between dynamic nomogram prediction and actual observations. The DCA showed that at a threshold probability between 0 and 100%, this model can achieve a greater net benefit than if all patients had surgery or none had surgery. In conclusion, this online dynamic nomogram reliably predicted risk of pain recurrence in patients with TN following MVD.

Identification of FKBP10 prognostic value in lung adenocarcinoma patients with surgical resection of brain metastases: A retrospective single-institution cohort study.

OBJECTIVE: To explore the expression levels and clinical value of FKBP10 in lung adenocarcinoma brain metastases. DESIGN: A retrospective single-institution cohort study. PATIENTS: The perioperative records of 71 patients with lung adenocarcinoma brain metastases who underwent surgical resection at the authors' institution between November 2012 and June 2019 were retrospectively analyzed. METHODS: The authors evaluated FKBP10 expression levels using immunohistochemistry in tissue arrays of these patients. Kaplan-Meier survival curves were constructed, and a Cox proportional hazards regression model was used to identify independent prognostic biomarkers. A public database was used to detect FKBP10 expression and its clinical value in primary lung adenocarcinoma. RESULTS: The authors found that the FKBP10 protein was selectively expressed in lung adenocarcinoma brain metastases. Survival analysis showed that FKBP10 expression (p = 0.02, HR = 2.472, 95% CI [1.156, 5.289]), target therapy (p < 0.01, HR = 0.186, 95% CI [0.073, 0.477]), and radiotherapy (p = 0.006, HR = 0.330, 95% CI [0.149, 0.731]) were independent prognostic factors for survival in lung adenocarcinoma patients with brain metastases. The authors also detected FKBP10 expression in primary lung adenocarcinoma using a public database, found that FKBP10 is also selectively expressed in primary lung adenocarcinoma, and affects the overall survival and disease-free survival of patients. LIMITATIONS: The number of enrolled patients was relatively small and patients' treatment options varied. CONCLUSIONS: A combination of surgical resection, adjuvant radiotherapy, and precise target therapy may benefit the survival of selected patients with lung adenocarcinoma brain metastases. FKBP10 is a novel biomarker for lung adenocarcinoma brain metastases, which is closely associated with survival time and may serve as a potential therapeutic target.

Overexpression of Podoplanin Predicts Poor Prognosis in Patients With Glioma.

High podoplanin (PDPN) expression correlates with poor prognosis in various cancers. However, the expression and clinical value of PDPN in glioma are unclear. In this study, PDPN expression was compared in 227 glioma tissues and 22 paired non-neoplastic tissues, and its association with prognostic factors was statistically analyzed. The effect of PDPN knockdown on the proliferation ability of glioma cells (U87MG and U118MG cell lines) was assessed along with the underlying molecular mechanism. Overexpression of PDPN was observed in the majority of glioma tissues compared with the expression in normal tissues. PDPN overexpression was positively correlated with IDH wild-type status, TERT promoter mutation status, and ATRX retention status, and was negatively correlated with 1p/19q codeletion status. The expression level of PDPN was positively correlated with the glioma grade in the diffuse astrocytoma, IDH wild-type. High PDPN expression was also negatively correlated with survival in astrocytoma patients with IDH mutation or wild-type and in glioblastoma patients with IDH wild-type. Grade, radiochemotherapy, and PDPN overexpression emerged as independent indicators for a poor prognosis of glioma patients. PDPN knockdown suppressed proliferation and reduced p-Akt and p-mTOR protein expression in glioma cells. PDPN is a potential biomarker or therapeutic target for glioma that is closely associated with tumor grade and poor prognosis, which may play a role in enhancing cell proliferation via Akt/mTOR signaling.

Role of Systemic Immunoinflammation Landscape in the Overall Survival of Patients with Leptomeningeal Metastases from Lung Cancer.

Purpose: Several biomarkers, such as baseline neutrophil-to-lymphocyte ratio (NLR), have been more investigated in patients with brain metastases (BM), while their role in patients with leptomeningeal metastases (LM) has not been clarified. Considering the difference between the clinical behaviour of BM and LM, there is the need for addressing the role of these biomarkers in LM. Methods: The present study retrospectively analyzed 95 consecutive patients with LM from lung cancer who were diagnosed at the National Cancer Center, Cancer Hospital of Chinese Academy of Medical Sciences between January 2016 and December 2019. Baseline NLR, platelet-to-lymphocyte ratio (PLR), systemic immunoinflammation index (SII), and lymphocyte-to-monocyte ratio at diagnosis of LM were calculated based on complete blood count and correlated, along with other characteristics, with overall survival (OS) using univariate and multivariate analyses. The best cutoff values for systemic immunoinflammation biomarkers were derived using the surv_cutpoint function in R software, which optimized the significance of the split between Kaplan-Meier survival curves. Results: Median OS of patients with LM was 12 months (95% CI 9-17 months). On univariate analysis, NLR, PLR, SII, LMR, sex, smoking history, ECOG performance status (PS) scores, histological subtypes and targeted therapy were all significantly associated with OS. Only NLR (P=0.034, 95% CI 1.060-4.578) and ECOG PS scores (P=0.019, 95% CI 0.137-0.839) maintained a significant association with OS on multivariate analysis. Furthermore, patients with baseline NLR >3.57 had significantly worse OS than patients with NLR ≤3.57 (median OS 7 vs 17 months), as did patients with ECOG PS scores >2 vs ≤2 (median OS 4 vs 15 months). Conclusion: Both baseline NLR and PS scores at the time of LM diagnosis are helpful and available prognostic biomarkers for patients with LM from lung cancer.

Clinical and genomic features in patients with second primary glioblastoma following first primary renal cell carcinoma.

PURPOSE: To explore the potential pathogenesis and clinical features of second primary glioblastoma (spGBM) following first primary renal cell carcinoma (fpRCC). METHODS: Patients with spGBM after fpRCC were enrolled from our institution and the SEER dataset. Sanger sequencing, whole genome sequencing, and immunehistochemistry were used to detect molecular biomarkers. RESULTS: Four and 122 cases from our institution and the SEER dataset, respectively, were collected with an overall median age of 69 years at spGBM diagnosis following fpRCC. The median interval time between fpRCC and spGBM was 50.7 months and 4 years, for the four and 122 cases respectively. The median overall survival time was 11.2 and 6.0 months for the two datasets. In addition, spGBM patients of younger age (< 75 years) or shorter interval time (< 1 year) had favorable prognosis (p = 0.081 and 0.05, respectively). Moreover, the spGBM cases were molecularly classified as TERT only paired with TP53 mutation, PIK3CA mutation, EGFR alteration, low tumor mutation burden, and stable microsatellite status. CONCLUSIONS: This is the first study to investigate the pathogenesis and clinical features of spGBM following spRCC. We found that spGBMs are old-age related, highly malignant, and have short survival time. Moreover, they might be misdiagnosed and treated as brain metastases from RCC. Thus, the incidence of spGBMs after fpRCC is underestimated. Further studies are needed to investigate the underlying molecular mechanisms and clinical biomarkers for the development of spGBM following fpRCC.

Identification of FKBP10 prognostic value in lung adenocarcinoma patients with surgical resection of brain metastases: A retrospective single-institution cohort study

Abstract Objective To explore the expression levels and clinical value of FKBP10 in lung adenocarcinoma brain metastases. Design A retrospective single-institution cohort study. Patients The perioperative records of 71 patients with lung adenocarcinoma brain metastases who underwent surgical resection at the authors' institution between November 2012 and June 2019 were retrospectively analyzed. Methods The authors evaluated FKBP10 expression levels using immunohistochemistry in tissue arrays of these patients. Kaplan-Meier survival curves were constructed, and a Cox proportional hazards regression model was used to identify independent prognostic biomarkers. A public database was used to detect FKBP10 expression and its clinical value in primary lung adenocarcinoma. Results The authors found that the FKBP10 protein was selectively expressed in lung adenocarcinoma brain metastases. Survival analysis showed that FKBP10 expression (p = 0.02, HR = 2.472, 95% CI [1.156, 5.289]), target therapy (p < 0.01, HR = 0.186, 95% CI [0.073, 0.477]), and radiotherapy (p = 0.006, HR = 0.330, 95% CI [0.149, 0.731]) were independent prognostic factors for survival in lung adenocarcinoma patients with brain metastases. The authors also detected FKBP10 expression in primary lung adenocarcinoma using a public database, found that FKBP10 is also selectively expressed in primary lung adenocarcinoma, and affects the overall survival and disease-free survival of patients. Limitations The number of enrolled patients was relatively small and patients' treatment options varied. Conclusions A combination of surgical resection, adjuvant radiotherapy, and precise target therapy may benefit the survival of selected patients with lung adenocarcinoma brain metastases. FKBP10 is a novel biomarker for lung adenocarcinoma brain metastases, which is closely associated with survival time and may serve as a potential therapeutic target.

L1CAM expression in either metastatic brain lesion or peripheral blood is correlated with peripheral platelet count in patients with brain metastases from lung cancer.

Background: Systemic immune-inflammation states across the heterogeneous population of brain metastases from lung cancer are very important, especially in the context of complex brain-immune bidirectional communication. Previous studies from our team and others have shown that the L1 cell adhesion molecule (L1CAM) is deeply involved in the aggressive phenotype, immunosuppressive tumor microenvironment (TME), and metastasis during multiple malignancies, which may lead to an unfavorable outcome. However, little is known about the relationship between the L1CAM expression and the systemic immune-inflammation macroenvironment beyond the TME in brain metastases from lung cancer. Methods: Two cohorts of patients with brain metastases from lung cancer admitted to the National Cancer Center, Cancer Hospital of Chinese Academy of Medical Sciences, were studied in the present research. The L1CAM expression in cranial metastatic lesions by immunohistochemistry was explored in patients treated with neurosurgical resection, whereas the L1CAM expression in peripheral blood by ELISA was tested in patients treated with non-surgical antitumor management. Furthermore, based on peripheral blood cell counts in the CBC test, six systemic immune-inflammation biomarkers [neutrophil count, lymphocyte count, platelet count, systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio] were calculated. Then, the relationship between the L1CAM expression and these systemic immune-inflammation biomarkers was analyzed. In addition, these systemic immune-inflammation biomarkers were also used to compare the systemic immune-inflammation states in two cohorts of patients with brain metastases from lung cancer. Results: Positive L1CAM expressions in the metastatic brain lesions were accompanied with significantly increased peripheral platelet counts in patients treated with neurosurgical tumor resection (P < 0.05). Similarly, in patients treated with non-surgical antitumor management, L1CAM expressions in the peripheral blood were positively correlated with peripheral platelet counts (P < 0.05). In addition, patients prepared for neurosurgical tumor resection were presented with poorer systemic immune-inflammation states in comparison with the one with non-surgical antitumor management, which was characterized by a significant increase in peripheral neutrophil counts (P < 0.01), SII (P < 0.05), and NLR (P < 0.05) levels. Conclusion: The L1CAM expression in either the metastatic brain lesion or peripheral blood is positively correlated with the peripheral platelet count in patients with brain metastases from lung cancer. In addition, brain metastases that are prepared for neurosurgical tumor resection show poor systemic immune-inflammation states.

Multidimensional modulation of systemic immune by neurosurgical tumor resection in patients with brain tumors.

OBJECTIVES: Immune perturbation induced by tumor burden has been showed as the hallmark of brain tumors. To date, the vast majority of studies have focused heavily on local immune responses in the tumor microenvironment. Little is known about how the systemic immune macroenvironment is modulated by neurosurgical tumor resection in patients with brain tumors. METHOD: Medical records from patients with brain tumors admitted to the Department of Neurosurgery at the National Cancer Center, Cancer Hospital of Chinese Academy of Medical Sciences between January 2021 and March 2022 were retrospectively reviewed. Forty-nine patients who have lymphocyte subsets, serum immunoglobulins, C-reactive protein, and complements levels before neurosurgical tumor resection and at least once test after surgery were included into the final analysis. RESULTS: Postoperative CD3+ lymphocytes, CD4+ lymphocytes and CD4+ /CD8+ lymphocyte ratio presented bi-phasic changes, which indicated an initial decrease and a subsequent increase after neurosurgical tumor resection. Moreover, neurosurgical tumor resection induced a decrease in natural killer lymphocytes and an increase in B lymphocytes that persisted through the entire observation period after surgery. Meanwhile, significant changes in humoral immunity characterized by a decrease in immunoglobulins (IgA, IgG, and IgM) levels and an increase in the CRP level occurred after neurosurgical tumor resection. In addition, patients with postoperative infection complication had a lower preoperative CD4+ /CD8+ lymphocyte ratio. CONCLUSIONS: These findings provide evidence that either cellular immunity or humoral immunity can be remodeled by neurosurgical tumor resection, and patients with disturbed systemic immunity have increased risk of infection after surgery.

Systemic immune-inflammation landscape in brain metastasis needing neurosurgical resection: Analysis of 230 consecutive cases in a single center.

BACKGROUND: Systemic immune-inflammation states across the heterogeneous population of brain metastases are very important in the context of brain-immune bidirectional communication, especially among the patients needing neurosurgical resection. Four blood cell ratios based on complete blood count (CBC) test serving as prognostic biomarkers have been highlighted by previous studies, including systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). However, the presurgical systemic immune-inflammation landscape in brain metastasis needing neurosurgical resection is limited. METHODS: Patients with brain metastases admitted to the Department of Neurosurgery at the National Cancer Center, Cancer Hospital of Chinese Academy of Medical Sciences between January 2016 and December 2019 were included. Based on peripheral blood cell counts in CBC test before neurosurgical resection, four systemic immune-inflammation biomarkers (SII, NLR, PLR, and LMR) were calculated. We characterized the changes of SII, NLR, PLR, and LMR in patients with brain metastasis before neurosurgical resection and the associations of these types of immune-inflammation states with patient demographics. In parallel, the corresponding data from the relative healthy populations without systemic diseases were enrolled as the control in the present study. RESULTS: Brain metastases induced systemic immune-inflammation perturbation, which was characterized by a significant increase in SII (p < .01) and NLR levels (p < .01) and a significant decrease in the LMR level (p < .01) in comparison with the healthy control group. Moreover, patients with male gender, less Karnofsky Performance Status (KPS) scores (<70), specific pathological subtypes, extracranial transfer, and history of both systemic and radiation therapy may have significant differences in one or more of these biomarkers, which indicated poorer systemic immune-inflammation states. CONCLUSIONS: This study provides evidence that brain metastasis is associated with perturbations in presurgical systemic immune-inflammation states. We should pay attention to the systemic immune-inflammation perturbations following brain metastasis in clinic, especially in the subpopulations with high risks.

Identifying Differential Expression Genes and Prognostic Signature Based on Subventricular Zone Involved Glioblastoma.

Background: Studies have suggested that glioblastoma (GBM) cells originate from the subventricular zone (SVZ) and that GBM contact with the SVZ correlated with worse prognosis and higher recurrence. However, research on differentially expressed genes (DEGs) between GBM and the SVZ is lacking. Methods: We performed deep RNA sequencing on seven SVZ-involved GBMs and paired tumor-free SVZ tissues. DEGs and enrichment were assessed. We obtained GBM patient expression profiles and clinical data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. The least absolute shrinkage and selection operator Cox regression model was utilized to construct a multigene signature in the CGGA cohort. GBM patient data from TCGA cohort were used for validation. Results: We identified 137 (97 up- and 40 down-regulated) DEGs between GBM and healthy SVZ samples. Enrichment analysis revealed that DEGs were mainly enriched in immune-related terms, including humoral immune response regulation, T cell differentiation, and response to tumor necrosis factor, and the MAPK, cAMP, PPAR, PI3K-Akt, and NF-κb signaling pathways. An eight-gene (BCAT1, HPX, NNMT, TBX5, RAB42, TNFRSF19, C16orf86, and TRPC5) signature was constructed. GBM patients were stratified into two risk groups. High-risk patients showed significantly reduced overall survival compared with low-risk patients. Univariate and multivariate regression analyses indicated that the risk score level represented an independent prognostic factor. High risk score of GBM patients negatively correlated with 1p19q codeletion and IDH1 mutation. Immune infiltration analysis further showed that the high risk score was negatively correlated with activated NK cell and monocyte counts, but positively correlated with macrophage and activated dendritic cell counts and higher PD-L1 mRNA expression. Conclusion: Here, a novel gene signature based on DEGs between GBM and healthy SVZ was developed for determining GBM patient prognosis. Targeting these genes may be a therapeutic strategy for GBM.

Maxillary Swing Approach for Central Skull Base Lesions in Extreme Situations: A Single-Institutional Case Series.

OBJECTIVE: Radical resection of complex lesions occupying multiple compartments at the central skull base remains a significant challenge, since surgical outcomes may be compromised by insufficient exposure and inappropriate techniques. However, the efficiency of the maxillary swing approach for these lesions has not been sufficiently evaluated. Careful assessment of lesion characteristics must be performed when selecting the appropriate procedure. METHODS: Between May 2006 and February 2017, 17 patients underwent resection of extensive lesions in the central skull base using the maxillary swing approach. As shown in the representative cases, data regarding clinical findings and technical considerations were reviewed. RESULTS: Complete resection was achieved in all patients. The pathological findings were diverse, and the majority were schwannomas (9 cases, 52.94%), followed by meningiomas (World Health Organization II) (3 cases, 17.65%). Complications were managed as described in the case illustrations, and symptoms improved with time. The follow-up duration ranged from 62 to 192 months (median, 114 months), while 2 patients were lost to the follow-up. No mortality was observed. Two patients who experienced malignancy relapse were still under observation due to their asymptomatic status. CONCLUSIONS: Our preliminary results suggest that the maxillary swing approach can be an alternative option for managing extreme cases, such as large, extensive, hypervascularized masses with fibrous or calcified consistency, or for recurrent lesions in the central skull base. En bloc resection can be successfully obtained, resulting in long-term local control.

Cerebrospinal Fluid Cell-Free DNA-Based Detection of High Level of Genomic Instability Is Associated With Poor Prognosis in NSCLC Patients With Leptomeningeal Metastases.

Introduction: Leptomeningeal metastasis (LM) commonly occurs in non-small cell lung cancer (NSCLC) patients and has a poor prognosis. Due to limited access to leptomeningeal lesions, the genetic characteristics of LM have not been explored to date. Cerebrospinal fluid (CSF) may be the most representative liquid biopsy medium to obtain genomic information from LM in NSCLC. Methods: CSF biopsies and matched peripheral blood biopsies were collected from 33 NSCLC patients with LM. We profiled genetic alterations from LM by comparing CSF cell-free DNA (cfDNA) with plasma cfDNA. Somatic mutations were examined using targeted sequencing. Genomic instability was analyzed by low-coverage whole-genome sequencing (WGS). Results: Driver mutations were detected in 100% of CSF cfDNA with much higher variant allele frequency than that in matched plasma cfDNA (57.5%). Furthermore, we found that the proportions of CSF cfDNA fragments below 150 bp were significantly higher than those in plasma cfDNA. These findings indicate enrichment of circulating tumor DNA (ctDNA) in CSF and explain the high sensitivity of mutation detection in the CSF. The absence of some mutations in CSF cfDNA-especially the first-/second-generation mutation T790M, which confers resistance to epidermal growth factor receptor (EGFR)-Tyrosine kinase inhibitors (TKIs)-that were present in plasma cfDNA samples indicates different mechanisms of cancer evolution between LM and extracranial lesions. In addition, 86.6% of CSF ctDNA samples revealed high levels of genomic instability compared with 2.5% in plasma cfDNA samples. A higher number of large-scale state transitions (LSTs) in CSF cfDNA were associated with a shorter overall survival (OS). Conclusion: Our results suggest that LM and extracranial lesions develop independently. Both CSF cfDNA genetic profiling and plasma cfDNA genetic profiling are necessary for clinical decision-making for NSCLC patients with LM. Through CSF-based low-coverage WGS, a high level of LSTs was identified as a potential biomarker of poor prognosis.

L1 cell adhesion molecule high expression is associated with poor prognosis in surgically resected brain metastases from lung adenocarcinoma.

OBJECTIVES: Accurate prognosis assessment across the heterogeneous population of brain metastases is very important, which may facilitate clinical decision-making and appropriate stratification of future clinical trials. Previous studies have shown the L1 Cell Adhesion Molecule (L1CAM) is potentially involved in human malignancies of multiple different samples and unfavorable survival. However, no data of L1CAM are available for the brain metastases from lung adenocarcinoma, especially for the one with neurosurgical resection. METHOD: The authors investigated the L1CAM expression in cranial metastatic lesions for patients with brain metastases from lung adenocarcinoma after neurosurgical resection using tissue microarrays that were obtained from the Department of Neurosurgery at the Cancer Hospital of the Chinese Academy of Medical Sciences. Furthermore, the relationship between L1CAM expression and clinic-pathological parameters, including overall survival time, was analyzed to assess the prognostic value of L1CAM. RESULTS: L1CAM high expression was found in 62.30% of brain metastases from lung adenocarcinoma and significantly correlated with brain metastasis number (p = 0.028) and Lung-molGPA score (p = 0.042). Moreover, L1CAM expression was an independent predictor of survival for brain metastases after neurosurgical resection in a multivariate analysis. Patients with L1CAM high expression had unfavorable overall survival time (p = 0.016). In addition, the multivariate analysis also showed age and extracranial transfer were also the independent prognostic factors for this type of patient with brain metastases. CONCLUSIONS: A subset of brain metastases from lung adenocarcinoma aberrantly expresses L1CAM. L1CAM is a novel independent prognostic factor for brain metastasis from lung adenocarcinoma after neurosurgical resection.

Preoperative blood testing for glioblastoma, brain metastases, and primary central nervous system lymphoma differentiation.

Background: Differentiating glioblastoma (GBM), brain metastases, and primary central nervous system lymphoma (PCNSL) in clinical practice is difficult. This study aimed to evaluate the diagnostic value of routine blood biomarkers in patients with GBM, brain metastases, and PCNSL and find a preoperative differential diagnostic tool for these tumors. Methods: The perioperative medical records of 70 GBM, 41 PCNSL, and 81 brain metastases patients and their preoperative blood test results were compared and analyzed, and a diagnostic model to differentiate among them established. Results: Patient age, plateletcrit, international normalized ratio (INR), and thrombin time (TT) were independently associated with differential diagnosis by multinomial logistic regression. Compared with GBM patients, brain metastases patients were significantly older (OR =1.055, 95% CI: 1.016-1.094, P=0.005) and had lower plateletcrit levels (OR =0.008, 95% CI: 0.004-0.017, P=0.027). In addition, patients with GBM had lower INR and higher TT than patients with the other two tumor types. A diagnostic model including these parameters, had an accuracy of 88.2% and 76.1% for brain metastases and GBM, respectively. Conclusions: Preoperative plateletcrit, INR, and TT may be used as inexpensive blood diagnostic biomarkers for differentiating brain metastases from other intracranial malignant tumors.

Identification of prognostic biomarkers for breast cancer brain metastases based on the bioinformatics analysis.

PURPOSE: The prognosis of breast cancer (BC) patients who develop into brain metastases (BMs) is very poor. Thus, it is of great significance to explore the etiology of BMs in BC and identify the key genes involved in this process to improve the survival of BC patients with BMs. PATIENTS AND METHODS: The gene expression data and the clinical information of BC patients were downloaded from TCGA and GEO database. Differentially expressed genes (DEGs) in TCGA-BRCA and GSE12276 were overlapped to find differentially expressed metastatic genes (DEMGs). The protein-protein interaction (PPI) network of DEMGs was constructed via STRING database. ClusterProfiler R package was applied to perform the gene ontology (GO) enrichment analysis of DEMGs. The univariate Cox regression analysis and the Kaplan-Meier (K-M) curves were plotted to screen DEMGs associated with the overall survival and the metastatic recurrence survival, which were identified as the key genes associated with the BMs in BC. The immune infiltration and the expressions of immune checkpoints for BC patients with brain relapses and BC patients with other relapses were analyzed respectively. The correlations among the expressions of key genes and the differently infiltrated immune cells or the differentially expressed immune checkpoints were calculated. The gene set enrichment analysis (GSEA) of each key gene was conducted to investigate the potential mechanisms of key genes involved in BC patients with BMs. Moreover, CTD database was used to predict the drug-gene interaction network of key genes. RESULTS: A total of 154 DEGs were identified in BC patients at M0 and M1 in TCGA database. A total of 667 DEGs were identified in BC patients with brain relapses and with other relapses. By overlapping these DEGs, 17 DEMGs were identified, which were enriched in the cell proliferation related biological processes and the immune related molecular functions. The univariate Cox regression analysis and the Kaplan-Meier curves revealed that CXCL9 and GPR171 were closely associated with the overall survival and the metastatic recurrence survival and were identified as key genes associated with BMs in BC. The analyses of immune infiltration and immune checkpoint expressions showed that there was a significant difference of the immune microenvironment between brain relapses and other relapses in BC. GSEA indicated that CXCL9 and GPR171 may regulate BMs in BC via the immune-related pathways. CONCLUSION: Our study identified the key genes associated with BMs in BC patients and explore the underlying mechanisms involved in the etiology of BMs in BC. These findings may provide a promising approach for the treatments of BC patients with BMs.

L1 cell adhesion molecule high expression is associated with poor prognosis in surgically resected brain metastases from lung adenocarcinoma

Abstract Objectives Accurate prognosis assessment across the heterogeneous population of brain metastases is very important, which may facilitate clinical decision-making and appropriate stratification of future clinical trials. Previous studies have shown the L1 Cell Adhesion Molecule (L1CAM) is potentially involved in human malignancies of multiple different samples and unfavorable survival. However, no data of L1CAM are available for the brain metastases from lung adenocarcinoma, especially for the one with neurosurgical resection. Method The authors investigated the L1CAM expression in cranial metastatic lesions for patients with brain metastases from lung adenocarcinoma after neurosurgical resection using tissue microarrays that were obtained from the Department of Neurosurgery at the Cancer Hospital of the Chinese Academy of Medical Sciences. Furthermore, the relationship between L1CAM expression and clinic-pathological parameters, including overall survival time, was analyzed to assess the prognostic value of L1CAM. Results L1CAM high expression was found in 62.30% of brain metastases from lung adenocarcinoma and significantly correlated with brain metastasis number (p = 0.028) and Lung-molGPA score (p = 0.042). Moreover, L1CAM expression was an independent predictor of survival for brain metastases after neurosurgical resection in a multivariate analysis. Patients with L1CAM high expression had unfavorable overall survival time (p = 0.016). In addition, the multivariate analysis also showed age and extracranial transfer were also the independent prognostic factors for this type of patient with brain metastases. Conclusions A subset of brain metastases from lung adenocarcinoma aberrantly expresses L1CAM. L1CAM is a novel independent prognostic factor for brain metastasis from lung adenocarcinoma after neurosurgical resection.

Highly expressed of SERPINA3 indicated poor prognosis and involved in immune suppression in glioma.

INTRODUCTION: The prognosis of patients with glioma is dismal. It has been reported that Serpin peptidase inhibitor clade A member 3 (SERPINA3) is associated with the mobility and invasion of tumor cells. Our study was designed to explore the value of SERPINA3 messenger RNA (mRNA) expression in the biological process, prognosis, and immune significance in glioma. METHODS: We analyzed the biological functions of SERPINA3 through data from the Chinese Glioma Genome Atlas databases. Differentially expressed genes and enrichment analysis were performed and correlations between SERPINA3 expression and immune cell infiltration were analyzed. Further, we validated the expression and the survival prediction role of SERPINA3 by using tissue microarrays and RNAscope in situ hybridization in 321 gliomas. The correlations between the expression and clinical-pathological parameters as well as other biomarkers were examined. RESULTS: Univariate and multivariate regression both indicated that the level of SERPINA3 transcript represented an independent prognostic factor. High levels of SERPINA3 correlated with poor survival in patients with glioma. Expression of SERPINA3 mRNA was observed positively correlated with MCM6, IGFBP2, and FKBP10. Enrichment analysis showed SERPINA3 mainly enriched in immune-related terms and signaling pathways including MAPK, TNF, P53, PI3K-Akt, nuclear factor-κB. Immune infiltration analysis further declare the SERPINA3 expression negatively correlated with levels of Macrophages M1, native CD4+ T cell, monocytes, and Mast cell activated. And overexpression of SERPINA3 correlated with low CD4+ T cell infiltration in glioma tissues. CONCLUSIONS: SERPINA3 may play a key role in the biological process of glioma cells especially in immune suppression activities. SERPINA3 may serve as an independent survival prediction factor in glioma patients.

Ubiquitination Destabilizes Protein Sphingosine Kinase 2 to Regulate Glioma Malignancy.

Gliomas are the most common and lethal malignant tumor in the central nervous system. The tumor oncogene sphingosine kinase 2 (SphK2) was previously found to be upregulated in glioma tissues and enhance glioma cell epithelial-to-mesenchymal transition through the AKT/ß-catenin pathway. Nevertheless, ubiquitination of SphK2 protein has yet to be well elucidated. In this study, mass spectrometry analysis was performed to identify proteins that interacted with SphK2 protein. Co-immunoprecipitation (co-IP) and immunoblotting (IB) were used to prove the specific interaction between SphK2 protein and the neural precursor cell-expressed developmentally downregulated 4-like (NEDD4L) protein. Fluorescence microscopy was used for detecting the distribution of related proteins. Ubiquitylation assay was utilized to characterize that SphK2 was ubiquitylated by NEDD4L. Cell viability assay, flow cytometry assay, and transwell invasion assay were performed to illustrate the roles of NEDD4L-mediated SphK2 ubiquitination in glioma viability, apoptosis, and invasion, respectively. We found that NEDD4L directly interacted with SphK2 and ubiquinated it for degradation. Ubiquitination of SphK2 mediated by NEDD4L overexpression suppressed glioma cell viability and invasion but promoted glioma apoptosis. Knockdown of NEDD4L presented opposite results. Moreover, further results suggested that ubiquitination of SphK2 regulated glioma malignancy via the AKT/ß-catenin pathway. in vivo assay also supported the above findings. This study reveals that NEDD4L mediates SphK2 ubiquitination to regulate glioma malignancy and may provide some meaningful suggestions for glioma treatment.