Bone Metastasis Of Lung Cancer Research Articles

Development and validation of an early diagnosis model for bone metastasis in non-small cell lung cancer based on serological characteristics of the bone metastasis mechanism

Bone metastasis significantly impact the prognosis of non-small cell lung cancer (NSCLC) patients, reducing their quality of life and shortening their survival. Currently, there are no effective tools for the diagnosis and risk assessment of early bone metastasis in NSCLC patients. This study employed machine learning to analyze serum indicators that are closely associated with bone metastasis, aiming to construct a model for the timely detection and prognostic evaluation of bone metastasis in NSCLC patients. The derivation cohort consisted of 664 individuals with stage IV NSCLC, diagnosed between 2015 and 2018. The variables considered in this study included age, sex, and 18 specific serum indicators that have been linked to the occurrence of bone metastasis in NSCLC. Variable selection used multivariate logistic regression analysis and Lasso regression analysis. Six machine learning methods were utilized to develop a bone metastasis diagnostic model, assessed with Area Under the Curve (AUC), Decision Curve Analysis (DCA), sensitivity, specificity, and validation cohorts. External validation used 113 NSCLC patients from the Medical Alliance (2019-2020). Furthermore, a prospective validation study was conducted on a cohort of 316 patients (2019-2020) who were devoid of bone metastasis, and followed-up for at least two years to assess the predictive capabilities of this model. The model's prognostic value was evaluated using Kaplan-Meier survival curves. Through variable selection, 11 serum indictors were identified as independent predictive factors for NSCLC bone metastasis. Six machine learning models were developed using age, sex, and these serum indicators. A random forest (RF) model demonstrated strong performance during the training and internal validation cohorts, achieving an AUC of 0.98 (95% CI 0.95-0.99) for internal validation. External validation further confirmed the RF model's effectiveness, yielding an AUC of 0.97 (95% CI 0.94-0.99). The calibration curves demonstrated a high level of concordance between the anticipated risk and the observed risk of the RF model. Prospective validation revealed that the RF model could predict the occurrence of bone metastasis approximately 10.27±3.58 months in advance, according to the results of the SPECT. An online computing platform (https://bonemetastasis.shinyapps.io/shiny_cls_1model/) for this RF model is publicly available and free-to-use by doctors and patients. This study innovatively employs age, gender, and 11 serological markers closely related to the mechanism of bone metastasis to construct an RF model, providing a reliable tool for the early screening and prognostic assessment of bone metastasis in NSCLC patients. However, as an exploratory study, the findings require further validation through large-scale, multicenter prospective studies. This work is supported by the National Natural Science Foundation of China (NO.81974315); Shanghai Municipal Science and Technology Commission Medical Innovation Research Project (NO.20Y11903300); Shanghai Municipal Health Commission Health Industry Clinical Research Youth Program (NO.20204Y034).

Mechanically stimulated osteocytes maintain tumor dormancy in bone metastasis of non-small cell lung cancer by releasing small extracellular vesicles

Although preclinical and clinical studies have shown that exercise can inhibit bone metastasis progression, the mechanism remains poorly understood. Here, we found that non-small cell lung cancer (NSCLC) cells adjacent to bone tissue had a much lower proliferative capacity than the surrounding tumor cells in patients and mice. Subsequently, it was demonstrated that osteocytes, sensing mechanical stimulation generated by exercise, inhibit NSCLC cell proliferation and sustain the dormancy thereof by releasing small extracellular vesicles with tumor suppressor micro-RNAs, such as miR-99b-3p. Furthermore, we evaluated the effects of mechanical loading and treadmill exercise on the bone metastasis progression of NSCLC in mice. As expected, mechanical loading of the tibia inhibited the bone metastasis progression of NSCLC. Notably, bone metastasis progression of NSCLC was inhibited by moderate exercise, and combinations with zoledronic acid had additive effects. Moreover, exercise preconditioning effectively suppressed bone metastasis progression. This study significantly advances the understanding of the mechanism underlying exercise-afforded protection against bone metastasis progression.

Mechanically stimulated osteocytes maintain tumor dormancy in bone metastasis of non-small cell lung cancer by releasing small extracellular vesicles.

Although preclinical and clinical studies have shown that exercise can inhibit bone metastasis progression, the mechanism remains poorly understood. Here, we found that non-small cell lung cancer (NSCLC) cells adjacent to bone tissue had a much lower proliferative capacity than the surrounding tumor cells in patients and mice. Subsequently, it was demonstrated that osteocytes, sensing mechanical stimulation generated by exercise, inhibit NSCLC cell proliferation and sustain the dormancy thereof by releasing small extracellular vesicles with tumor suppressor micro-RNAs, such as miR-99b-3p. Furthermore, we evaluated the effects of mechanical loading and treadmill exercise on the bone metastasis progression of NSCLC in mice. As expected, mechanical loading of the tibia inhibited the bone metastasis progression of NSCLC. Notably, bone metastasis progression of NSCLC was inhibited by moderate exercise, and combinations with zoledronic acid had additive effects. Moreover, exercise preconditioning effectively suppressed bone metastasis progression. This study significantly advances the understanding of the mechanism underlying exercise-afforded protection against bone metastasis progression.

Comparison of the relative diagnostic performance of 68Ga-DOTA-IBA and 18F-NaF for the detection of bone metastasis.

We aimed to compare the relative diagnostic efficacy of 68Ga-Labeled DOTA-ibandronic acid (68Ga-DOTA-IBA) to that of18F-NaF PET/CT as a mean of detecting bone metastases in patients with a range of cancer types. This study retrospectively enrolled patients with bone metastases associated with various underlying malignancies. All patients underwent both 68Ga-DOTA-IBA and 18F-NaF PET/CT scans. Histopathology and follow-up CT or MRI imaging results were used as reference criteria, with a minimum follow-up period of 3 months. The maximum Standardized Uptake Value (SUVmax) and number of bone metastases were recorded. The Target-Background Ratio (TBR) was calculated along with the detection rate, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of 68Ga-DOTA-IBA and 18F-NaF PET/CT imaging for overall and partial primary solid tumor bone metastases. Pearson chi-square test, McNemar test, and Kappa test was conducted to assess the correlation and consistency of diagnostic efficiency between the two imaging agents. Receiver Operating Characteristic curve (ROC curve) was performed to compare diagnostic performance and the area under the curve of the two imaging agents, determining optimal critical values for SUVmax and TBR in diagnosing bone metastasis. Differences in SUVmax and TBR values between the two imaging agents for detecting bone metastases were analyzed using the Wilcoxon signed rank test. The difference was statistically significant when P < 0.05. A total of 24 patients (13 women and 11 men) were included in this study, with a mean age of 52 (interquartile range, 49-64 years). The detection rate, sensitivity, specificity, PPV, NPV, accuracy, and AUC of 68Ga-DOTA-IBA and 18F-NaF PET/CT for bone metastases were 81%, 90%, 62%, 95%, 43%, 88%, 0.763, and 89%, 99%, 59%, 95%, 89%, 95%, 0.789, respectively. There was no significant difference between the two imaging methods (P < 0.01), and there was a significant correlation (X2=168.43, P < 0.001) and a strong consistency (Kappa=0.774,P < 0.001) between the diagnostic results of the two imaging agents. The SUVmax values of lesions measured by 68Ga-DOTA-IBA and 18F-NaF imaging in 22 patients with bone metastasis were 5.1 ± 5.4 and 19.6 ± 15.1, respectively, with statistically significant differences (P<0.05). The TBR values of the two imaging methods were 5.0 ± 5.0 and 6.7 ± 6.4, respectively, with statistically significant differences (P<0.05). The AUC of the SUVmax of 68Ga-DOTA-IBA and 18F-NaF curves were 0.824 and 0.862, respectively, with no statistically significant difference (P=0.490). No significant difference was found in the AUC of the TBR of 68Ga-DOTA-IBA and 18F-NaF (0.832 vs 0.890; P=0.248). Subgroup analysis showed significant correlation between the two imaging agents in the diagnosis of bone metastases in lung cancer and breast cancer, with consistent diagnostic results. However, in the diagnosis of bone metastases in prostate cancer, there was a significant difference (P<0.001) and lack of consistency (P=0.109). The diagnostic efficacy of 68Ga-DOTA-IBA for bone metastasis lesions is comparable to that of 18F-NaF. This finding holds significant clinical importance in terms of diagnosis of bone metastasis and selecting treatment plans for patients with malignant tumors.

Bone marrow adipocytes and lung cancer bone metastasis: unraveling the role of adipokines in the tumor microenvironment.

Bone is a common site of metastasis for lung cancer. The "seed and soil" hypothesis suggests that the bone marrow microenvironment ("soil") may provide a conducive survival environment for metastasizing tumor cells ("seeds"). The bone marrow microenvironment, comprising a complex array of cells, includes bone marrow adipocytes (BMAs), which constitute about 70% of the adult bone marrow volume and may play a significant role in tumor bone metastasis. BMAs can directly provide energy for tumor cells, promoting their proliferation and migration. Furthermore, BMAs participate in the tumor microenvironment's osteogenesis regulation, osteoclast(OC) regulation, and immune response through the secretion of adipokines, cytokines, and inflammatory factors. However, the precise mechanisms of BMAs in lung cancer bone metastasis remain largely unclear. This review primarily explores the role of BMAs and their secreted adipokines (leptin, adiponectin, Nesfatin-1, Resistin, chemerin, visfatin) in lung cancer bone metastasis, aiming to provide new insights into the mechanisms and clinical treatment of lung cancer bone metastasis.

Poly (lactic-co-glycolic acid)-encapsulated Endostar-loaded calcium phosphate cement as anti-tumor bone cement for the treatment of bone metastasis in lung cancer.

Lung cancer is one of the most common malignant tumors in the world. In approximately 30%-40% of lung cancer patients, bone metastases ensues with osteolytic destruction. Worse still, intractable pain, pathological fracture, and nerve compression caused by bone metastases are currently the bottleneck of research, diagnosis, and treatment of lung cancer. Therefore, the present study aims at investigating the effectiveness of a new composite material made of calcium phosphate cement (CPC) and Endostar on repairing bone defects in vitro and in vivo. As indicated in results, the mechanical properties of CPC+Endostar and CPC+PLGA+Endostar do not differ from those of pure CPC. The PLGA-embedded Endostar slow-release microspheres were designed and prepared, and were combined with CPC. Poly (lactic-co-glycolic acid (PLGA) is a biodegradable polymer material in vivo, so the effect on its mechanical properties is negligible. CPC+Endostar and CPC+PLGA+Endostar have been proved to inhibit cell proliferation, promote apoptosis and block cell cycle in G2 phase; the expression levels of osteoclast-related genes CXCL2, TGF-β1, IGF-1, IL-6, and RANKL were significantly decreased while osteogenic ability and alkaline phosphatase activity observably enhanced. In vivo studies have revealed that the expression levels of TRAP, RANKL, and Caspase3 in CPC+PLGA+ENDO-treated tumor tissues after 3 weeks were higher than those in other groups with the prolongation of animal treatment time, while the expression levels of OPN and BCL2 were lower than those in other groups. In hematoxylin and eosin and TUNEL staining, 3 weeks of CPC+PLGA+ENDO-treatment yielded higher tissue necrosis and apoptosis than other groups; computed tomography and magnetic resonance imaging results showed the posterior edge bone damage reduced as a result of the CPC+PLGA+ENDO grafting in vertebral pedicle. Overall, the feasibility and reliability of CPC-loaded Endostar in the treatment of bone metastasis in lung cancer were investigated in this study, so as to promote the basic research and treatment of bone metastasis in lung cancer and other malignant tumors.

IL-17A deficiency inhibits lung cancer-induced osteoclastogenesis by promoting apoptosis of osteoclast precursor cells.

Osteoclasts are crucial in the events leading to bone metastasis of lung cancer. Interleukin-17A (IL-17A) affects osteogenesis by regulating the survival of osteoclast precursors (OCPs) and is enriched in lung cancer cells. However, how factors derived from tumor cells that metastasize to bone affect osteoclastogenesis remains poorly understood. We examined whether IL-17A derived from lung cancer cells affects osteoclast differentiation by regulating OCP apoptosis. IL-17A expression was inhibited in A549 non-small cell lung cancer cells using RNA interference. Compared with conditioned medium (CM) from A549 cells (A549-CM), CM from IL-17A-deficient A549 cells (A549-si-CM) suppressed osteoclastogenesis. The mRNA expression of osteoclast-specific genes was downregulated following A549-si-CM treatment. Furthermore, A549-si-CM promoted osteoclast precursor apoptosis at an early stage of osteoclastogenesis, which was related to the promotion of caspase-3 expression by A549-si-CM during osteoclast differentiation. In vivo experiments also showed that inhibition of IL-17A expression in A549 cells reduced osteoclast activation and bone tissue destruction. Collectively, our results indicate that IL-17A deficiency inhibits lung cancer-induced osteoclast differentiation by promoting apoptosis of osteoclast precursors in the early stage of osteoclast formation and that IL-17A is a potential therapeutic target for cancer-associated bone resorption in patients with lung cancer.

Automated Diagnosis of Bone Metastasis by Classifying Bone Scintigrams Using a Self-defined Deep Learning Model.

Patients with cancer can develop bone metastasis when a solid tumor invades the bone, which is the third most commonly affected site by metastatic cancer, after the lung and liver. The early detection of bone metastases is crucial for making appropriate treatment decisions and increasing survival rates. Deep learning, a mainstream branch of machine learning, has rapidly become an effective approach to analyzing medical images. To automatically diagnose bone metastasis with bone scintigraphy, in this work, we proposed to cast the bone metastasis diagnosis problem into automated image classification by developing a deep learning-based automated classification model. A self-defined convolutional neural network consisting of a feature extraction sub-network and feature classification sub-network was proposed to automatically detect lung cancer bone metastasis, with a feature extraction sub-network extracting hierarchal features from SPECT bone scintigrams and feature classification sub-network classifying high-level features into two categories (i.e., images with metastasis and without metastasis). Using clinical data of SPECT bone scintigrams, the proposed model was evaluated to examine its detection accuracy. The best performance was achieved if the two images (i.e., anterior and posterior scans) acquired from each patient were fused using pixel-wise addition operation on the bladder-excluded images, obtaining the best scores of 0.8038, 0.8051, 0.8039, 0.8039, 0.8036, and 0.8489 for accuracy, precision, recall, specificity, F-1 score, and AUC value, respectively. The proposed two-class classification network can predict whether an image contains lung cancer bone metastasis with the best performance as compared to existing classical deep learning models. The high accumulation of 99mTc MDP in the urinary bladder has a negative impact on automated diagnosis of bone metastasis. It is recommended to remove the urinary bladder before automated analysis.

Mass Spectrometry-Based Proteomics Identifies Serpin B9 as a Key Protein in Promoting Bone Metastases in Lung Cancer.

SB9 as a therapeutic target for LCBM.

Evaluating the predictive significance of systemic immune-inflammatory index and tumor markers in lung cancer patients with bone metastases.

This study aims to develop a predictive model for identifying lung cancer patients at elevated risk for bone metastases, utilizing the Unified Immunoinflammatory Index and various tumor markers. This model is expected to facilitate timely and effective therapeutic interventions, especially in the context of the growing significance of immunotherapy for lung cancer treatment. A retrospective analysis was conducted on 324 lung cancer patients treated between January 2019 and January 2021. After meeting the inclusion criteria, 241 patients were selected, with 56 exhibiting bone metastases. The cohort was divided into a training group (169 patients) and a validation group (72 patients) at a 7:3 ratio. Lasso regression was employed to identify critical variables, followed by logistic regression to construct a Nomogram model for predicting bone metastases. The model's validity was ascertained through internal and external evaluations using the Concordance Index (C-index) and Receiver Operating Characteristic (ROC) curve. The study identified several factors influencing bone metastasis in lung cancer, such as the Systemic Immune-Inflammatory Index (SII), Carcinoembryonic Antigen (CEA), Neuron Specific Enolase (NSE), Cyfra21-1, and Neutrophil-to-Lymphocyte Ratio (NLR). These factors were incorporated into the Nomogram model, demonstrating high validation accuracy with C-index scores of 0.936 for internal and 0.924 for external validation. The research successfully developed an intuitive and accurate Nomogram prediction model utilizing clinical indicators to predict the risk of bone metastases in lung cancer patients. This tool can be instrumental in aiding clinicians in developing personalized treatment plans, thereby optimizing patient outcomes in lung cancer care.

Circulating Tumour Cells in the Prediction of Bone Metastasis.

Bone is the most common organ for the development of metastases in many primary tumours, including those of the breast, prostate and lung. In most cases, bone metastasis is incurable, and treatment is predominantly palliative. Much research has focused on the role of Circulating Tumour Cells (CTCs) in the mechanism of metastasis to the bone, and methods have been developed to isolate and count CTCs from peripheral blood. Several methods are currently being used in the study of CTCs, but only one, the CellSearchTM system has been approved by the United States Food and Drug Administration for clinical use. This review summarises the advantages and disadvantages, and outlines which clinical studies have used these methods. Studies have found that CTC numbers are predictive of bone metastasis in breast, prostate and lung cancer. Further work is required to incorporate information on CTCs into current staging systems to guide treatment in the prevention of tumour progression into bone.

Predictive nomogram for bone metastases in lung cancer based on monocyte infiltration.

The presence of bone metastases (BM) in patients with lung cancer is indicative of a worse prognosis. The present study aims to investigate the risk factors associated with BM in patients with lung cancer. Patients with lung cancer admitted to the First Affiliated Hospital of Anhui Medical University between June 2019 and September 2021 were enrolled in this study. A nomogram was constructed based on the outcomes derived from univariate and multivariate analyses. Concordance index, calibration plots, receiver operating characteristic curves, and decision curve analysis were used to evaluate the nomogram. To substantiate the influence of monocytes on lung cancer BM, various assays, including cell co-culture, Transwell, wound-healing assays, and immunohistochemistry and immunofluorescence staining, were conducted. Statistical analyses were performed using SPSS 22.0 software and GraphPad Prism 7.0. A total of 462 eligible patients were enrolled, comprising 220 with BM and 242 without. Multivariate analysis revealed that histological type, medical history, monocyte percentage, and LDH (Lactate Dehydrogenase) and ALP (Alkaline Phosphatase) levels were independent risk factors for BM in lung cancer. Transwell and wound-healing assays indicated that co-culture with monocytes significantly enhanced the migration and invasion capabilities of A549 cells in vitro. Immunohistochemistry and immunofluorescence analyses demonstrated a noteworthy increase in monocyte infiltration in the primary lesions of patients with lung cancer with BM. In conclusion, this study successfully constructed and validated a precise, straightforward, and cost-effective prognostic nomogram for patients with lung cancer with BM.

Exosomal hsa-miR-151a-3p and hsa-miR-877-5p are potential novel biomarkers for predicting bone metastasis in lung cancer.

Exosomal miRNAs (exo-miRNAs) have arisen as novel diagnostic biomarkers for various cancers. However, few reports on exo-miRNAs related to bone metastasis (BM) in lung cancer exist. This study aims to screen out key exo-miRNAs and estimate their prognostic values for predicting BM in lung cancer. The differentially expressed exo-miRNAs between the highly-metastatic (95D) and lowly-metastatic (A549) human lung cancer cell lines were comprehensively analyzed using high-throughput sequencing followed by bioinformatic analyses. 29 candidate exo-miRNAs were identified, and 101 BM-related target genes were predicted. Enrichment analysis revealed that these target genes were mainly involved in regulating transcription and pathways in cancer. An exosomal miRNA-mRNA regulatory network consisting of 7 key miRNAs and 10 hub genes was constructed. Further function analysis indicated that these 10 hub genes were mainly enriched in regulating cancer's apoptosis and central carbon metabolism. The survival analysis indicated that 7 of 10 hub genes were closely related to prognosis. Mutation analysis showed that lung cancer patients presented certain genetic alterations in the 7 real hub genes. GSEA for a single hub gene suggested that 6 of 7 real hub genes had close associations with lung cancer development. Finally, ROC analysis revealed that hsa-miR-151a-3p and hsa-miR-877-5p provided high diagnostic accuracy in discriminating patients with bone metastasis (BM+) from patients without bone metastasis (BM-). These findings provided a comprehensive analysis of exo-miRNAs and target genes in the regulatory network of BM in lung cancer. In particular, hsa-miR-151a-3p and hsa-miR-877-5p may be novel biomarkers for predicting BM in lung cancer.

Long Term Outcomes of Conventional Palliative Radiotherapy in Bone Metastases of Lung Cancer: A Prospective Study

Bone metastases (BM) are highly prevalent in metastatic lung cancer (LC) leading to consequential morbidity and a decline in quality of life. The identification of oncogenes mutation and introduction of targeted therapy has prolonged the survival and therefore evaluation of long-term pain response rates, durability and re-irradiation (Re-RT) with conventional radiotherapy (RT) is crucial, especially in LMIC where penetration of stereotactic body radiotherapy for BM is poor. This prospective observational study included consecutive patients with histologically proven LC with radiologically confirmed BM. The primary objective was to evaluate the pain response rates in lung cancer patients with bone metastases treated with palliative RT. Palliative RT to BM was delivered using a conventional/conformal technique. The International Bone Metastases Consensus response criteria using Numeric Pain Rating Scale (NPRS) and Oral Morphine Equivalent Dose (OMED) was used to evaluate the pain response at 12, 24, and 52 weeks. Assuming the worst-case scenario, pain progression-free survival (PPFS) was calculated from the date of baseline assessment to the date of pain progression (PP) or death using Kaplan-Meier survival analysis. Known prognostic factors were evaluated using Cox regression analysis. From June 2020 to August 2022, 250 patients of NSCLC (94%) were accrued. The majority were male (66%), smokers (35%), lytic lesions (75%) and in the axial skeleton (82%). The oncogenic mutation was seen in 123 (49%) patients. At baseline, the mean OMED was 20mg/day (SD-21), and the mean pain score was 6 (SD-2.3). The majority (66%) received an 8 Gy single fraction with only 3% treated with SBRT. In evaluable patients, the CR and PR rates at 12 (n-161) and 24 weeks (n-121) were 34%, 40%, and 44%, 35% respectively. The indeterminate response rate (IRR) at 3 and 6 months were 18% while the rate of PP was 6%. On multivariate analysis, negative oncogene mutation {HR-0.34 (CI 0.22- 0.50), p<0.0001} and soft tissue mass {HR-0.46 (CI 0.31- 0.68) p<0.0001} were significant prognostic factors for pain progression. Of 71 evaluable patients at 1 year, 56% had a complete response with an ORR of 87%. In patients with oncogene mutation, the CR rates at 12 (n-101), 24 (n-77), and 52 weeks were 40%, 47%, and 60% with an ORR of 86%. PP is observed in less than 4%. Pain response was significantly more durable than mutation negative (8 vs 3 months, p-0.003). Re-RT rate was overall 11% (n = 27) and 8.2% in oncogene mutation patients. Re-RT rate with single-fraction was 8% and 3% with fractionated RT. The median time to Re-RT was 9.7 weeks. The PPFS was 70% and 60% at 12 and 24 weeks, respectively. This prospective study in an LC-specific population demonstrated excellent CR and PR rates with conventional RT. Durable pain relief with modest Re-RT rates with single fraction, particularly in oncogene mutation compels us to evaluate the role of SBRT for BM, especially in LMIC in a randomized setting.

Deletion of osteopontin in non-small cell lung cancer cells affects bone metabolism by regulating miR-34c/Notch1 axis: a clue to bone metastasis.

Lung cancer is prone to bone metastasis, and osteopontin (OPN) has an important significance in maintaining bone homeostasis. The goal of this study was to explore the impact of OPN level on bone metabolism and the molecular mechanism of inhibiting bone metastasis in non-small cell lung cancer (NSCLC). The expression of OPN in NSCLC was ascertained by Western blot and immunohistochemistry, and the correlation between the expression level of OPN and survival of patients was analyzed. Then the shRNA technology was applied to reduce the expression of OPN in NSCLC cells, and CCK-8 assay was carried out to investigate the effect of low expression of OPN on the proliferation of NSCLC cells. In addition, the effects of low expression of OPN on osteoclast differentiation, osteoblast generation and mineralization were studied using osteoclast precursor RAW264.7 and human osteoblast SaOS-2 cells, and whether OPN could regulate miR-34c/ Notch pathway to affect bone metabolism was further explored. The findings showed that the high level of OPN in NSCLC was closely related to the poor prognosis of patients and the abnormal proliferation of NSCLC cell lines. The suppression of OPN was beneficial to inhibit the differentiation of osteoclasts and promote the mineralization of osteoblasts. Besides, this study confirmed that the deletion of OPN can regulate bone metabolism through the regulation of miR-34c/Notch1 pathway, which will contribute to inhibiting the occurrence of osteolytic bone metastasis in NSCLC.

Expression of MEF2D in Lung Adenocarcinoma and Its Correlation with Prognosis

Myocyte enhancer factor 2D (MEF2D) can participate in the process of tumor lesions by regulating the transcription of oncogenes. In a previous study, MEF2D was demonstrated to enhance the proliferation and metastasis of lung adenocarcinoma cells A549 and H1299 by promoting the transcription of NUSAP1. The research aimed to explore the expression level and clinical significance of MEF2D in lung adenocarcinoma. A total of 199 patients with lung adenocarcinoma were collected. Immunohistochemical staining was used to detect MEF2D expression levels in cancer and adjacent tissues. After the clinical and follow-up data were collated, the correlation between MEF2D expression level and clinical characteristics and prognosis of the patients was analyzed. In the lung adenocarcinoma, the high expression rate of MEF2D in cancer tissues was significantly higher than that in adjacent tissues (P<0.05). According to immunohistochemical score, MEF2D expression level in lung adenocarcinoma tissues was correlated with tumor differentiation, N stage, M stage and intrapulmonary metastasis (P<0.05). Kaplan-Meier analysis showed that patients with low MEF2D expression had significantly better prognosis than patients with high MEF2D expression (P<0.05). Cox multivariate analysis showed that MEF2D expression level, M stage, N stage and bone metastasis of lung cancer were independent risk factors for prognosis of lung adenocarcinoma patients. MEF2D expression level is closely related to the metastasis of lung adenocarcinoma and other clinical characteristics, and can be used as an independent risk factor for the prognosis of patients with lung adenocarcinoma, which has the potential to be developed as a clinical diagnosis and treatment target of lung adenocarcinoma.

Retracted: Exploration of the Effect of Icariin on Nude Mice with Lung Cancer Bone Metastasis via the OPG/RANKL/RANK System.

[This retracts the article DOI: 10.1155/2022/2011625.].

Identification of the potential ferroptosis key genes in lung cancer with bone metastasis.

To identify the potential key genes of ferroptosis in the pathogenesis of lung cancer with bone metastasis (LCBM) by bioinformatics analysis to provide new targets for treating LCBM and an indicator for early monitoring. We first obtained differentially expressed genes (DEGs) associated with ferroptosis from the Gene Expression Omnibus (GEO) database. MiRWalk 2.0 was used to predict the key microRNAs (miRNAs) and construct related gene-miRNA interaction networks. The functional enrichment analysis of key miRNAs was performed using the miEAA database. Finally, the clinical data of 105 lung cancer patients were retrospectively analyzed, and logistic regression analysis was conducted to assess the relationship between serum alkaline phosphatase (ALP), neuron-specific enolase (NSE), and bone metastasis in lung cancer patients, and a receiver operating characteristic (ROC) curve was drawn. We identified 15 ferroptosis-related genes that were differentially expressed in lung cancer bone metastasis. GO and KEGG enrichment analyses suggested that these genes may affect the oxidative stress response, hypoxia response, rough endoplasmic reticulum, mitochondrial outer membrane, iron-sulfur cluster binding, virus receptor activity, central carbon metabolism in cancer, the interleukin-17 (IL-17) signaling pathway, and other aspects to participate in the occurrence and development of lung cancer bone metastasis. Among the 105 lung cancer patients included in the study, 39 cases had bone metastasis, and the incidence rate was 37.14%. A high Eastern Cooperative Oncology Group (ECOG) score and serum ALP and NSE overexpression were associated with bone metastasis in patients with lung cancer. By assessing the risk of bone metastasis in patients with lung cancer, we found that the Area Under Curves (AUCs) of serum ALP and NSE alone and combined were >0.70. The differentially expressed ferroptosis-related genes and predicted miRNA regulatory network in lung cancer bone metastasis and the related functional enrichment analysis provide new targets for the treatment of lung cancer bone metastasis. At the same time, from a serological perspective, it was found that early monitoring of serum ALP and NSE expression in patients with lung cancer could be considered to assess the risk of bone metastasis in the future.

A novel microRNA-182/Interleukin-8 regulatory axis controls osteolytic bone metastasis of lung cancer

Bone metastasis is one of the main complications of lung cancer and most important factors that lead to poor life quality and low survival rate in lung cancer patients. However, the regulatory mechanisms underlying lung cancer bone metastasis are still poor understood. Here, we report that microRNA-182 (miR-182) plays a critical role in regulating osteoclastic metastasis of lung cancer cells. We found that miR-182 was significantly upregulated in both bone-metastatic human non–small cell lung cancer (NSCLC) cell line and tumor specimens. We further demonstrated that miR-182 markedly enhanced the ability of NSCLC cells for osteolytic bone metastasis in nude mice. Mechanistically, miR-182 promotes NSCLC cells to secrete Interleukin-8 (IL-8) and in turn facilitates osteoclastogenesis via activating STAT3 signaling in osteoclast progenitor cells. Importantly, systemically delivered IL-8 neutralizing antibody inhibits NSCLC bone metastasis in nude mice. Collectively, our findings identify the miR-182/IL-8/STAT3 axis as a key regulatory pathway in controlling lung cancer cell-induced osteolytic bone metastasis and suggest a promising therapeutic strategy that targets this regulatory axis to interrupt lung cancer bone metastasis.

Heterogeneity in the immune microenvironment of bone metastasis in driver-positive non-small cell lung cancer.

Mutations in epidermal growth factor receptor and anaplastic lymphoma kinase are common driver events in non-small cell lung cancer (NSCLC), which are associated with a high frequency of bone metastases (BMs). While the bone marrow represents a specialized immune microenvironment, the immune repertoire of BMs remains unknown. Considering the higher incidence of BMs in driver gene-positive NSCLCs, and the unique biology of the bone, herein, we assessed the infiltrating immune cells and T cell receptor (TCR) profile of BMs in driver-positive NSCLCs. Immune profile of BMs in driver gene-positive NSCLC were assessed in 10 patients, where 6 had driver gene-positive mutation. TCR and bulk RNA sequencing were performed on malignant bone samples. The diversity and clonality of the TCR repertoire were analyzed. The cellular components were inferred from bulk gene expression profiles computationally by CIBERSORT. Although BMs were generally regarded as immune-cold tumors, immune cell composition analyses showed co-existence of cytotoxic and suppressor immune cells in driver-positive BM samples, as compared to primary lung. Analysis of the TCR repertoire indicated a trend of higher diversity and similar clonality in the driver-positive compared with the driver-negative subsets. In addition, we identified two cases that showed the opposite response to immune checkpoint blockade. A comparison of these two patients' BM samples showed more highly amplified clones, fewer M2 macrophages and more activated natural killer cells in the responder. In summary, BMs in NSCLC are heterogeneous in their immune microenvironment, which might be related to differential clinical outcomes to immune checkpoint blockade.