Tumor Immune Microenvironment and Immunotherapy in Brain Metastasis From Non-Small Cell Lung Cancer

Cumulative incidence and risk factors of brain metastases in metastatic non-small cell lung cancer without baseline brain metastasis: Pooled analysis of individualized patient data from IMpower130, IMpower131, and IMpower150

BACKGROUND

The objective of this study was to explore the abilities of atezolizumab plus chemotherapy in preventing brain metastases (BMs) among metastatic non-small cell lung cancer (NSCLC) without initial BMs, as well as the risk factors of BMs.

METHODS

Individual patient data from three trials involving first-line atezolizumab for metastatic NSCLC (IMpower130, IMpower131, and IMpower150) were pooled. Among patients without baseline BMs and without epidermal growth factor receptor (EGFR) and/or anaplastic lymphoma kinase (ALK) mutations, those receiving atezolizumab + chemotherapy ± bevacizumab were classified as the atezolizumab plus chemotherapy group and those receiving placebo + chemotherapy ± bevacizumab were classified as the chemotherapy group. The cumulative incidences of BM (CI-BMs) between the two groups were compared. Other factors associated with the CI-BM were analyzed by Cox regression analyses.

RESULTS

With a median follow-up of 17.6 months (range, 0.03-33.64 months), 74 (3.1%) of the 2380 enrolled patients developed BMs, including 50 (3.1%) and 24 (3.0%) in the atezolizumab plus chemotherapy group (n = 1589) and the chemotherapy group (n = 791), respectively. The CI-BMs at 6, 12, and 24 months were 1.7%, 2.8%, and 3.3%, respectively. After taking competing risk events into account, there was no significant difference in the CI-BMs between the two groups (p = .888). Nevertheless, the use of bevacizumab and the histology of nonsquamous NSCLC were found to be independently associated with the risk of BMs.

CONCLUSIONS

In patients with metastatic EGFR/ALK wild-type NSCLC without baseline BMs, adding atezolizumab in the first-line treatment might not reduce the CI-BM. However, the administration of bevacizumab may reduce the risk of BMs.

Construction and validation of a TTN mutation associated immune prognostic model for evaluating immune microenvironment and outcomes of gastric cancer: An observational study

Gastric cancer (GC) is a prevalent form of cancer worldwide, and TTN (titin) mutations are frequently observed in GC. However, the association between TTN mutations and immunotherapy for GC remains unclear, necessitating the development of novel prognostic models. The prognostic value and potential mechanisms of TTN in stomach adenocarcinoma were evaluated by TCGA (The Cancer Genome Atlas)-stomach adenocarcinoma cohort analysis, and an immune prognostic model was constructed based on TTN status. We validated it using the GSE84433 dataset. We performed Gene Set Enrichment Analysis and screened for differentially expressed genes, and used lasso (least absolute shrinkage and selection operator) regression analysis to screen for survival genes to construct a multifactorial survival model. In addition, we evaluated the relative proportions of 22 immune cells using the CIBERSORT algorithm for immunogenicity analysis. Finally, we constructed the nomogram integrating immune prognostic model and other clinical factors. GESA showed enrichment of immune-related phenotypes in patients with TTN mutations. We constructed an immune prognostic model based on 16 genes could identify gastric cancer patients with higher risk of poor prognosis. Immuno-microenvironmental analysis showed increased infiltration of naive B cells, plasma cells, and monocyte in high-risk patients. In addition, Nomo plots predicted the probability of 1-year, 3-year, and 5-year OS (overall survival) in GC patients, showing good predictive performance. In this study, we identified that TTN gene may be a potential clinical biomarker for GC and TTN mutations may be a predictor of immunotherapy in patients. We constructed and validated a new model for prognosis of GC patients based on immune characteristics associated with TTN mutations. This study may provide potential therapeutic strategies for gastric cancer.

Assessment of PD-L1 Expression in Non-Small Cell Lung Cancers Using [68Ga]Ga-DOTA-WL12 PET/CT

Assessing programmed death ligand-1 (PD-L1) expression in non-small cell lung cancer (NSCLC), particularly in metastatic cases, remains challenging. In this study, surface plasmon resonance (SPR) analysis and [68Ga]Ga-DOTA-WL12 micro-PET/CT imaging are performed. [68Ga]Ga-DOTA-WL12 PET/CT and [18F]FDG PET/CT are performed on a cohort of 20 patients with NSCLC. Semi-quantitative assessments include SUVmax, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and target-to-background ratio (TBR). DOTA-WL12 exhibits robust PD-L1 binding with a KD value of 0.2 nM. Subsequent human studies reveal significant correlations between PD-L1 expression and the [68Ga]Ga-DOTA-WL12 SUVmax in primary and metastatic lesions, surpassing the [18F]FDG results (r = 0.8889, p <0.0001 vs r = 0.0469, p = 0.8127). Notably, [68Ga]Ga-DOTA-WL12 imaging discerned SUVmax and TBR differences between PD-L1 TPS ≤1% and PD-L1 TPS > 1% groups (p all <0.001). In an NSCLC patient with brain metastases, [68Ga]Ga-DOTA-WL12 shows a SUVmean of 0.04 in the brain background, with TBR values of 17 and 23, underscoring its potential for detecting brain metastases. The study provides initial evidence for the clinical utility of [68Ga]Ga-DOTA-WL12 PET/CT for lesion detection, immunotherapy selection, and therapeutic efficacy evaluation in PD-L1-expressing NSCLC, demonstrating its potential as a valuable tool in NSCLC research and management.

Blocking the MIF-CD74 axis augments radiotherapy efficacy for brain metastasis in NSCLC via synergistically promoting microglia M1 polarization

BACKGROUND

Brain metastasis is one of the main causes of recurrence and death in non-small cell lung cancer (NSCLC). Although radiotherapy is the main local therapy for brain metastasis, it is inevitable that some cancer cells become resistant to radiation. Microglia, as macrophages colonized in the brain, play an important role in the tumor microenvironment. Radiotherapy could activate microglia to polarize into both the M1 and M2 phenotypes. Therefore, searching for crosstalk molecules within the microenvironment that can specifically regulate the polarization of microglia is a potential strategy for improving radiation resistance.

METHODS

We used databases to detect the expression of MIF in NSCLC and its relationship with prognosis. We analyzed the effects of targeted blockade of the MIF/CD74 axis on the polarization and function of microglia during radiotherapy using flow cytometry. The mouse model of brain metastasis was used to assess the effect of targeted blockade of MIF/CD74 axis on the growth of brain metastasis.

RESULT

Our findings reveals that the macrophage migration inhibitory factor (MIF) was highly expressed in NSCLC and is associated with the prognosis of NSCLC. Mechanistically, we demonstrated CD74 inhibition reversed radiation-induced AKT phosphorylation in microglia and promoted the M1 polarization in combination of radiation. Additionally, blocking the MIF-CD74 interaction between NSCLC and microglia promoted microglia M1 polarization. Furthermore, radiation improved tumor hypoxia to decrease HIF-1α dependent MIF secretion by NSCLC. MIF inhibition enhanced radiosensitivity for brain metastasis via synergistically promoting microglia M1 polarization in vivo.

CONCLUSIONS

Our study revealed that targeting the MIF-CD74 axis promoted microglia M1 polarization and synergized with radiotherapy for brain metastasis in NSCLC.

The application of different machine learning models based on PET/CT images and EGFR in predicting brain metastasis of adenocarcinoma of the lung

OBJECTIVE

To explore the value of six machine learning models based on PET/CT radiomics combined with EGFR in predicting brain metastases of lung adenocarcinoma.

METHODS

Retrospectively collected 204 patients with lung adenocarcinoma who underwent PET/CT examination and EGFR gene detection before treatment from Cancer Hospital Affiliated to Shandong First Medical University in 2020. Using univariate analysis and multivariate logistic regression analysis to find the independent risk factors for brain metastasis. Based on PET/CT imaging combined with EGFR and PET metabolic indexes, established six machine learning models to predict brain metastases of lung adenocarcinoma. Finally, using ten-fold cross-validation to evaluate the predictive effectiveness.

RESULTS

In univariate analysis, patients with N2-3, EGFR mutation-positive, LYM%≤20, and elevated tumor markers(P<0.05) were more likely to develop brain metastases. In multivariate Logistic regression analysis, PET metabolic indices revealed that SUVmax, SUVpeak, Volume, and TLG were risk factors for lung adenocarcinoma brain metastasis(P<0.05). The SVM model was the most efficient predictor of brain metastasis with an AUC of 0.82 (PET/CT group),0.70 (CT group),0.76 (PET group).

CONCLUSIONS

Radiomics combined with EGFR machine learning model as a new method have higher accuracy than EGFR mutation alone. SVM model is the most effective method for predicting brain metastases of lung adenocarcinoma, and the prediction efficiency of PET/CT group is better than PET group and CT group.

Animal models of brain and spinal cord metastases of NSCLC established using a brain stereotactic instrument

Objective

Animal models of brain and spinal cord metastases of non-small cell lung cancer were established through the intracranial injection of PC-9 Luc cells with a brain stereotaxic device. This method provides a reliable modeling method for studying brain and spinal cord metastases of non-small cell lung cancer.

Methods

PC-9 Luc cells at logarithmic growth stage were injected into the skulls of 5-week-old BALB/c nude mice at different cell volumes (30 × 104, 80 × 104) and different locations (using anterior fontanel as a location point, 1 mm from the coronal suture, and 1.5 mm from the sagittal suture on the right upper and right lower side of the skull). After 1 week of cell inoculation, fluorescence signals of tumor cells in the brain and spinal were detected using the IVIS Xenogen Imaging system. After 4 weeks, brain and spinal tissues from the nude mice were harvested. Following paraffin-embedded sectioning, HE staining was performed on the tissues.

Results

The fluorescence signals revealed that both brain and spinal cord metastasis occurred in the mice where the cells were injected at the lower right side of the skull. There was only brain metastasis in the nude mice injected with 30 × 104 cells at the upper right side of the skull. Both brain and spinal cord metastasis occurred in the nude mice injected with 80 × 104 cells. The HE staining revealed that both brain and spinal cord metastasis occurred in the mice injected with different amounts of PC-9 Luc cells, consistent with the results detected using the IVIS Xenogen Imaging system, thereby demonstrating the reliability of detecting fluorescent signals in vivo to determine tumor growth.

Conclusion

It is a reliable method to establish the animal model of brain and spinal cord metastases of non-small cell lung cancer by injecting different quantities of cells from different positions with a brain stereotaxic device. The IVIS Xenogen Imaging system has high reliability in detecting the fluorescence signals of brain and spinal cord metastatic tumors.

Exploring the Molecular Tumor Microenvironment and Translational Biomarkers in Brain Metastases of Non-Small-Cell Lung Cancer

Brain metastases represent a significant clinical challenge in the treatment of non-small-cell lung cancer (NSCLC), often leading to a severe decline in patient prognosis and survival. Recent advances in imaging and systemic treatments have increased the detection rates of brain metastases, yet clinical outcomes remain dismal due to the complexity of the metastatic tumor microenvironment (TME) and the lack of specific biomarkers for early detection and targeted therapy. The intricate interplay between NSCLC tumor cells and the surrounding TME in brain metastases is pivotal, influencing tumor progression, immune evasion, and response to therapy. This underscores the necessity for a deeper understanding of the molecular underpinnings of brain metastases, tumor microenvironment, and the identification of actionable biomarkers that can inform multimodal treatment approaches. The goal of this review is to synthesize current insights into the TME and elucidate molecular mechanisms in NSCLC brain metastases. Furthermore, we will explore the promising horizon of emerging biomarkers, both tissue- and liquid-based, that hold the potential to radically transform the treatment strategies and the enhancement of patient outcomes.

Exploring the prognostic potential of m6A methylation regulators in low-grade glioma: implications for tumor microenvironment modulation

BACKGROUND

The biological behavior of low-grade glioma (LGG) is significantly affected by N6-methyladenosine (m6A) methylation, an essential epigenetic alteration. Therefore, it is crucial to create a prognostic model for LGG by utilizing genes that regulate m6A methylation.

METHODS

Using TCGA and GTEx databases. We examined m6A modulator levels in LGG and normal tissues, and investigated PD-L1 and PD-1 expression, immune scores, immune cell infiltration, tumor immune microenvironment (TIME) and potential underlying mechanisms in different LGG clusters. We also performed immunohistochemistry and RT-qPCR to identify essential m6A adjustment factor.

RESULTS

The results showed that m6A regulatory element expression was significantly increased in LGG tissues and was significantly associated with TMIE. A substantial increase in PD-L1 and PD-1 levels in LGG tissues and high-risk cohorts was observed. PD-L1 expression was positively correlated with FTO, ZCCHC4, and HNRNPD, whereas PD-1 expression was negatively correlated with FTO, ZC3H7B, and HNRNPD. The prognostic signature created using regulators of m6A RNA methylation was shown to be strongly associated with the overall survival of LGG patients, and FTO and ZCCHC4 were confirmed as independent prognostic markers by clinical samples. Furthermore, the results revealed different TIME characteristics between the two groups of patients, indicating disrupted signaling pathways associated with LGG.

CONCLUSION

Our results present that the m6A regulators play vital role in regulating PD-L1/PD-1 expression and the infiltration of immune cells, thereby exerting a sizable impact on the TIME of LGG. Therefore, m6A regulators have precise predictive value in the prognosis of LGG.

Patient-Derived Lung Cancer "Sandwich Cultures" with a Preserved Tumor Microenvironment

In the past, different spheroid-, organotypic-, and three-dimensional (3D) bioprinting lung cancer models were established for in vitro drug testing and personalized medicine. These tissue models cannot depict the tumor microenvironment (TME) and, therefore, research addressing tumor cell-TME interactions is limited. To overcome this hurdle, we applied patient-derived lung tumor samples to establish new in vitro models. To analyze the tissue model properties, we established two-dimensional (2D) and 3D coculture tissue models exposed to static and dynamic culture conditions that afforded tissue culture for up to 28 days. Our tissue models were characterized by hematoxylin eosin staining, M30 enzyme-linked immunosorbent assay, and immunofluorescence staining against specific lung cancer markers (TTF-1 and p40/p63), cancer-associated fibroblast (CAF) markers (α-SMA and MCT4), and fibronectin (FN). The 3D models were generated with higher success rate than the corresponding 2D model. The cell density of the static 3D model increased from 21 to 28 days, whereas the apoptosis decreased. The dynamic 3D model possessed an even higher cell density than the static 3D model. We identified lung cancer cells, CAFs, and FN. Therefore, a novel in vitro 3D lung cancer model was established, which simulated the TME for 28 days and possessed a structural complexity.

Harnessing immunotherapy for brain metastases: insights into tumor-brain microenvironment interactions and emerging treatment modalities

Brain metastases signify a deleterious milestone in the progression of several advanced cancers, predominantly originating from lung, breast and melanoma malignancies, with a median survival timeframe nearing six months. Existing therapeutic regimens yield suboptimal outcomes; however, burgeoning insights into the tumor microenvironment, particularly the immunosuppressive milieu engendered by tumor-brain interplay, posit immunotherapy as a promising avenue for ameliorating brain metastases. In this review, we meticulously delineate the research advancements concerning the microenvironment of brain metastases, striving to elucidate the panorama of their onset and evolution. We encapsulate three emergent immunotherapeutic strategies, namely immune checkpoint inhibition, chimeric antigen receptor (CAR) T cell transplantation and glial cell-targeted immunoenhancement. We underscore the imperative of aligning immunotherapy development with in-depth understanding of the tumor microenvironment and engendering innovative delivery platforms. Moreover, the integration with established or avant-garde physical methodologies and localized applications warrants consideration in the prevailing therapeutic schema.

Global research trends and prospects related to tumor microenvironment within Triple Negative Breast Cancer: a bibliometric analysis

Background and aims

The tumor microenvironment (TME) has pivotal parts within multiple tumor models of onset/progression, such as triple-negative breast cancer (TNBC). This bibliometric analysis was developed to explore trends and research niches revolving around TME in TNBC.

Methods

Web of Science Core Collection was queried for identifying studies linked with TME in TNBC, after which the VOSviewer, CiteSpace, and R software programs were used to conduct bibliometric analyses and to generate corresponding visualizations.

Results

In total, this study included 1,604 studies published from 2005-2023. The USA and China exhibited the highest numbers of citations, and the research institutions with the greatest output in this field included Harvard University, the University of Texas System, and Fudan University. Ying Wang from Sun Yat-Sen University was the most published and most cited author in this space. The highest number of articles were published in Cancer, while the greatest co-citation number was evident in Breast Cancer Research. Important keywords related to this research topic included metastasis, tumor-infiltrating lymphocytes, immunotherapy, chemotherapy, and nanoparticles. In particular, pembrolizumab, immunotherapy, nanoparticles, combination treatment, and biomarkers were topics of marked interest in recent reports.

Conclusion

The TME in TNBC is an area of rapidly growing and evolving research interest, with extensive global collaboration helping to drive this field forward. Antitumor therapies targeting the TME in TNBC patients represent an emerging topic of future research, providing opportunities for translational findings. The results of this analysis may provide additional guidance for work focused on the TME in TNBC.

Immunotherapy and biomarkers in patients with lung cancer with tuberculosis: Recent advances and future Directions

Lung cancer (LC) and tuberculosis (TB) are two major global public health problems, and the incidence of LC-TB is currently on the rise. Therefore effective clinical interventions are crucial for LC-TB. The aim of this review is to provide up-to-date information on the immunological profile and therapeutic biomarkers in patients with LC-TB. We discuss the immune mechanisms involved, including the immune checkpoints that play an important role in the treatment of patients with LC-TB. In addition, we explore the susceptibility of patients with LC to TB and summarise the latest research on LC-TB. Finally, we discuss future prospects in this field, including the identification of potential targets for immune intervention. In conclusion, this review provides important insights into the complex relationship between LC and TB and highlights new advances in the detection and treatment of both diseases.

Immunotherapy and brain metastasis in lung cancer: connecting bench side science to the clinic

Brain metastases (BMs) are the most common form of intracranial malignant neoplasms in adults, with a profound impact on quality of life and traditionally associated with a dismal prognosis. Lung cancer accounts for approximately 40%-50% of BM across different tumors. The process leading to BMs is complex and includes local invasion, intravasation, tumor cells circulation into the bloodstream, disruption of the blood-brain barrier, extravasation of tumor cells into the brain parenchyma, and interaction with cells of the brain microenvironment, among others. Once the tumor cells have seeded in the brain parenchyma, they encounter different glial cells of the brain, as well as immune cells. The interaction between these cells and tumor cells is complex and is associated with both antitumoral and protumoral effects. To overcome the lethal prognosis associated with BMs, different treatment strategies have been developed, such as immunotherapy with immune checkpoint inhibitors, particularly inhibitors of the PD-1/PD-L1 axis, which have demonstrated to be an effective treatment in both non-small cell lung cancer and small cell lung cancer. These antibodies have shown to be effective in the treatment of BM, alone or in combination with chemotherapy or radiotherapy. However, many unsolved questions remain to be answered, such as the sequencing of immunotherapy and radiotherapy, the optimal management in symptomatic BMs, the role of the addition of anti-CTLA-4 antibodies, and so forth. The complexity in the management of BMs in the era of immunotherapy requires a multidisciplinary approach to adequately treat this devastating event. The aim of this review is to summarize evidence regarding epidemiology of BM, its pathophysiology, current approach to treatment strategies, as well as future perspectives.

Advances in the application of neuroinflammatory molecular imaging in brain malignancies

The prevalence of brain cancer has been increasing in recent decades, posing significant healthcare challenges. The introduction of immunotherapies has brought forth notable diagnostic imaging challenges for brain tumors. The tumor microenvironment undergoes substantial changes in induced immunosuppression and immune responses following the development of primary brain tumor and brain metastasis, affecting the progression and metastasis of brain tumors. Consequently, effective and accurate neuroimaging techniques are necessary for clinical practice and monitoring. However, patients with brain tumors might experience radiation-induced necrosis or other neuroinflammation. Currently, positron emission tomography and various magnetic resonance imaging techniques play a crucial role in diagnosing and evaluating brain tumors. Nevertheless, differentiating between brain tumors and necrotic lesions or inflamed tissues remains a significant challenge in the clinical diagnosis of the advancements in immunotherapeutics and precision oncology have underscored the importance of clinically applicable imaging measures for diagnosing and monitoring neuroinflammation. This review summarizes recent advances in neuroimaging methods aimed at enhancing the specificity of brain tumor diagnosis and evaluating inflamed lesions.

Immunotherapy-based therapy as a promising treatment for EGFR-mutant advanced non-small cell lung cancer patients after EGFR-TKI resistance

INTRODUCTION

Traditionally, epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) has been regarded as a cold tumor based on the immunosuppressive tumor immune microenvironment (TIME). However, recent studies have found that EGFR-tyrosine kinase inhibitor (EGFR-TKI) treatment could shift host immunity from immunosuppressive to immunosupportive TIME, which has renewed hopes of immunotherapy.

AREAS COVERED

In this review, we highlight five main immunotherapy-based therapies for patients after EGFR-TKI failure, including safety and efficacy data from prospective and retrospective clinical studies.

EXPERT OPINION

The efficacy of immunotherapy alone is extremely limited. Immunotherapy plus chemotherapy show an ORR of 29.5%-59.3% and an mPFS of about 7 months. There is still scarce evidence for immunotherapy plus antiangiogenesis therapy. A combination of immunotherapy with EGFR-TKIs exhibits higher treatment-related adverse events and lower clinical outcomes compared to EGFR-TKI alone. Importantly, immunotherapy plus antiangiogenesis and chemotherapy achieves an mPFS of 6.9-10.2 months. In general, the strategy of combining immunotherapy with chemotherapy and/or an antiangiogenic drug is a novel and promising method for treating advanced NSCLC after EGFR-TKI failure. Therefore, the dominant population of EGFR-TKI resistant patients were characterized by EGFR uncommon mutation, EGFR L858R mutation, PD-L1 ≥ 50%, prior antiangiogenic drugs, and negative T790 M mutation for immunotherapy-based therapy.

Microenvironment and the progress of immunotherapy in clinical practice of NSCLC brain metastasis

One of the most frequent distant metastases of lung cancer occurs in the brain. The average natural survival duration for patients with lung cancer who have brain metastases is about 1 to 2 months. Knowledge about brain metastases is currently restricted since they are more difficult to acquire than other metastases. This review begins with an analysis of the immune microenvironment of brain metastases; focuses primarily on the functions of microglia, astrocytes, neurons, and tumor-infiltrating lymphocytes in the microenvironment of brain metastases; and offers an atlas of the immune microenvironment of brain metastases involving significant cells. In an effort to give researchers new research ideas, the study also briefly covers how immunotherapy for non-small cell lung cancer with brain metastases is currently faring.

The pathogenesis of idiopathic normal pressure hydrocephalus based on the understanding of AQP1 and AQP4

Idiopathic normal pressure hydrocephalus (iNPH) is a neurological disorder without a recognized cause. Aquaporins (AQPs) are transmembrane channels that carry water through cell membranes and are critical for cerebrospinal fluid circulation and cerebral water balance. The function of AQPs in developing and maintaining hydrocephalus should be studied in greater detail as a possible diagnostic and therapeutic tool. Recent research indicates that patients with iNPH exhibited high levels of aquaporin 1 and low levels of aquaporin 4 expression, suggesting that these AQPs are essential in iNPH pathogenesis. To determine the source of iNPH and diagnose and treat it, it is necessary to examine and appreciate their function in the genesis and maintenance of hydrocephalus. The expression, function, and regulation of AQPs in iNPH are reviewed in this article, in order to provide fresh targets and suggestions for future research.

Construction and evaluation of a prognostic risk model of tumor metastasis-related genes in patients with non-small cell lung cancer

Background

Lung cancer is a high-incidence cancer, and it is also the most common cause of cancer death worldwide. 80–85% of lung cancer cases can be classified as non-small cell lung cancer (NSCLC).

Methods

NSCLC transcriptome data and clinical information were downloaded from the TCGA database and GEO database. Firstly, we analyzed and identified the differentially expressed genes (DEGs) between non-metastasis group and metastasis group of NSCLC in the TCGA database, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were consulted to explore the functions of the DEGs. Thereafter, univariate Cox regression and LASSO Cox regression algorithms were applied to identify prognostic metastasis-related signature, followed by the construction of the risk score model and nomogram for predicting the survival of NSCLC patients. GSEA analyzed that differentially expressed gene-related signaling pathways in the high-risk group and the low-risk group. The survival of NSCLC patients was analyzed by the Kaplan–Meier method. ROC curve was plotted to evaluate the accuracy of the model. Finally, the GEO database was further applied to verify the metastasis‑related prognostic signature.

Results

In total, 2058 DEGs were identified. GO functions and KEGG pathways analysis results showed that the DEGs mainly concentrated in epidermis development, skin development, and the pathway of Neuro active ligand -receptor interaction in cancer. A six-gene metastasis-related risk signature including C1QL2, FLNC, LUZP2, PRSS3, SPIC, and GRAMD1B was constructed to predict the overall survival of NSCLC patients. The reliability of the gene signature was verified in GSE13213. The NSCLC patients were grouped into low-risk and high-risk groups based on the median value of risk scores. And low-risk patients had lower risk scores and longer survival time. Univariate and multivariate Cox regression verified that this signature was an independent risk factor for NSCLC.

Conclusion

Our study identified 6 metastasis biomarkers in the NSCLC. The biomarkers may contribute to individual risk estimation, survival prognosis.