Metastasis In Lung Cancer Patients Research Articles

Abstract 5515: Low body mass index (BMI) induces neuronal NPY and promotes brain metastasis of lung cancer

Abstract Brain metastases (BrMs) are a common occurrence in lung cancer with a dismal outcome. To develop a more effective therapeutic strategy, it is crucial to understand the underlying pathological mechanism of brain metastasis. Recent clinical data has unveiled a significant association between low body mass index (BMI) and an increased risk of brain metastasis in lung cancer patients, leading to reduced survival rates compared to other primary tumors. However, the molecular mechanism underlying this paradoxical relationship, often referred to as the "obesity paradox," in the context of lung cancer mortality presents a complex and intriguing puzzle and warrants in-depth investigation. Here, we examined biological mechanism of how low BMI promotes lung cancer brain metastasis. In this study, we conducted a retrospective pan-analysis of 5,516 patient cohorts with brain metastasis originating from lung, breast, melanoma, and renal cancers with their BMI status. We found that lung cancer patients with low BMI have significantly higher brain metastatic incidence compared to the high BMI patients, in contrast to breast, melanoma, and renal cancers. Furthermore, we found that low BMI plays a pivotal role in mediating neuron activation within the brain and that the secretion of neuronal neuropeptide Y (NPY), a protein involved in appetite and energy homeostasis via GHSR-receptor manner, promotes metabolic switching through NPY/NPY5R axis in the tumor cells in the brain thereby enabling metastasis. Elevated levels of neuronal NPY in the brains of cancer-free subjects with low BMI suggest its potential utility as a promising prognostic biomarker for identifying the increased risk of metastatic disease in lung cancer patients with low BMI. We also demonstrated that reversing low BMI or blocking the NPY/Y5R interactions effectively abrogated brain metastasis in our animal model. Our findings suggest a novel pro-metastatic role of low BMI-induced NPY in the progression of brain metastasis. We emphasize the importance of elucidating the clinical implications of this relationship to develop an updated intervention strategy for the clinical care of patients with lung cancer and low BMI. Citation Format: Abhishek Tyagi, Shih-Ying Wu, Ravindra Deshpande, Kerui Wu, Liang Liu, Kounosuke Watabe. Low body mass index (BMI) induces neuronal NPY and promotes brain metastasis of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5515.

Optimizing outcomes in symptomatic spinal metastases from non-small cell lung cancer: Evaluating the role of salvage surgical intervention in a multidisciplinary context – A Narrative Review

Background: Lung cancer, a leading cause of cancer-related mortality worldwide, often metastasises to the spine, resulting in significant morbidity and complex treatment challenges. The management of spinal metastatic disease from lung cancer necessitates a multidisciplinary approach, given the array of potential interventions including surgery, radiation therapy, chemotherapy, and supportive care. The selection of appropriate therapeutic strategies is influenced by multiple factors, including disease staging, patient health status, and symptomatology. Aim: This review article aims to explore the current landscape of surgical intervention for spinal metastases from lung cancer, evaluating its role, efficacy, and the criteria for patient selection within the context of multidisciplinary care. Additionally, it seeks to provide an overview of the existing treatment modalities, highlighting the importance of a tailored approach based on individual patient needs. Methods: An extensive review of the literature was conducted, focusing on studies, clinical trials, and meta-analyses published on the treatment of spinal metastases in lung cancer patients. Special attention was given to works discussing the surgical outcomes, prognostic factors, and the evolution of treatment protocols over recent decades. Results: Surgical treatment for spinal metastases from lung cancer is beneficial for select patients, particularly those without prior systemic treatments and those in good overall health. The decision to pursue surgery should be made within a multidisciplinary team, taking into account the patient’s specific situation and potential to benefit from the intervention. Research advancements and technological innovations continue to refine surgical techniques and improve patient outcomes. Conclusion: While the role of surgery in treating spinal metastatic disease from lung cancer is limited, it remains a critical option for appropriately selected patients. Future research should aim to further define and expand the criteria for surgical candidacy, enhancing the precision of patient selection and tailoring of treatment strategies. Emphasis on a multidisciplinary approach is essential for optimising outcomes and advancing care for patients with this challenging condition.

A risk-scoring model based on endobronchial ultrasound multimodal imaging for predicting metastatic lymph nodes in lung cancer patients

ABSTRACT Background and Objectives Endobronchial ultrasound (EBUS) imaging is a valuable tool for predicting lymph node (LN) metastasis in lung cancer patients. This study aimed to develop a risk-scoring model based on EBUS multimodal imaging (grayscale, Doppler mode, elastography) to predict LN metastasis in lung cancer patients. Patients and Methods This retrospective study analyzed 350 metastatic LNs in 314 patients with lung cancer and 124 reactive LNs in 96 patients with nonspecific inflammation. The sonographic findings were compared with the final pathology results and clinical follow-up. Univariate and multivariate logistic regression analyses were performed to evaluate the independent risk factors of metastatic LNs. According to the β coefficients of corresponding indicators in logistic regression analysis, a risk-scoring model was established. Receiver operating characteristic curve was applied to evaluate the predictive capability of model. Results Multivariate analysis showed that short axis >10 mm, distinct margin, absence of central hilar structure, presence of necrosis, nonhilar vascularity, and elastography score 4 to 5 were independent predictors of metastatic LNs. Both short axis and margin were scored 1 point, and the rest of independent predictors were scored 2 points. The combination of 3 EBUS modes had the highest area under the receiver operating characteristic and accuracy of 0.884 (95% confidence interval, 0.846–0.922) and 87.55%, respectively. The risk stratification was as follows: 0 to 2 points, malignancy rate of 11.11%, low suspicion; 3 to 10 points, malignancy rate of 86.77%, high suspicion. Conclusions The risk-scoring model based on EBUS multimodal imaging can effectively evaluate metastatic LNs in lung cancer patients to support clinical decision making.

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.

Performance of [18F]FDG PET/CT versus FAPI PET/CT for lung cancer assessment: a systematic review and meta-analysis.

This article aims to compare the diagnostic performance of 18-fluorodeoxyglucose ([18F]FDG) PET/CT and fibroblast activating protein inhibitor (FAPI) PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer patients. A systematic search was conducted on the Cochrane Library, Embase, and PubMed/MEDLINE databases from inception until November 1, 2022. Included studies assessed the use of FAPI PET/CT and [18F]FDG PET/CT in patients with lung cancer. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the risk of bias. A random variable model was used to analyze the diagnostic tests of the two imaging modalities. The sensitivity of FAPI PET/CT in detecting primary lung cancer lesions was 0.98 (95% CI: 0.88-1.00), while the sensitivity of [18F]FDG PET/CT was 0.99 (95% CI: 0.74-1.00). For the detection of metastatic lesions (lymph node metastases and distant metastases), FAPI PET/CT had a sensitivity of 0.99 (95% CI: 0.90-1.00), while the sensitivity of [18F]FDG PET/CT was 0.77 (95% CI: 0.66-0.85). However, the specificity of the two imaging modalities could not be assessed due to the lack of sufficient information on pertinent true negatives. In the diagnosis of metastatic lung cancer lesions, FAPI PET/CT demonstrated a higher sensitivity compared to [18F]FDG PET/CT. Therefore, FAPI PET/CT may be considered an alternative imaging modality for the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases. FAPI may be an alternative to [18F]FDG in the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases, which plays a very important role in treatment. • This article is to compare the performance of [18F]FDG PET/CT withFAPI PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer. • However,FAPI PET/CT has a higher sensitivity for the diagnostic assessment of metastatic lung cancer lesions.

Racial disparities in the prevalence of extrathoracic metastases in lung cancer patients and survival: A SEER database study (2010–2019).

e20630 Background: Metastatic disease at the time of lung cancer diagnosis influences therapy choice and prognosis. Metastasis to the brain, bones, and liver may lead to higher morbidity. Differences in the prevalence of metastatic sites among patients (pts) of White (W) and Black (B) race and their association with overall survival need further elucidation. Methods: Utilizing the SEER database from 2010-2019, we identified W and B pts with metastatic small cell (SCLC), squamous cell (SQ-NSCLC), and adenocarcinoma (AD-NSCLC). Only pts with bone, brain, or liver metastasis (mets) at diagnosis were included. Metastatic site prevalence rates were determined. Cox proportional hazard ratios for survival were calculated while controlling for gender, ethnicity, other metastatic sites, chemotherapy, and radiation. Results: Total of 338,411 pts, 11.4% of B race. In SCLC, B pts had a higher prevalence of brain mets, while W pts demonstrated a higher prevalence of bone and liver mets. Survival between W and B pts with SCLC was comparable except for modest superior survival in B pts with liver mets. In SQ-NSCLC, metastatic disease for the 3 sites of interest was more prevalent in B pts, most notably in brain. However, survival did not differ. In AD-NSCLC, B pts were more likely to present with brain and liver mets. B pts with bone mets had inferior survival. Conclusions: Significant differences in patterns of mets at the time of lung cancer diagnosis between W and B pts exist. B pts with SCLC and liver mets had longer survival. Interestingly, B pts with bone mets and SQ-NSCLC had better survival while those with AD-NSCLC fared worse. Multiple factors, including socioeconomic, environmental/smoking patterns and access to healthcare, may have contributed. Further studies are needed. [Table: see text]

PD-0972 a pet/ct radiomics model for predicting distant metastasis in lung cancer patients treated with SBRT

PD-0972 a pet/ct radiomics model for predicting distant metastasis in lung cancer patients treated with SBRT

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.

Can PSMA-Targeting PET/CT Be a Valuable Instrument to Assess the Presence of Brain Metastases in Lung Cancer Patients?: A Case Report.

A 78-year-old man with synchronous diagnosis of prostate cancer and lung adenocarcinoma was referred to our institute for prostate cancer staging with [18F]F-prostate-specific membrane antigen (PSMA) 1007 PET/CT. In addition to the previously known lesion of the right lung, PSMA-targeted PET/CT highlighted 2 areas of abnormal uptake in the brain, in the left frontal and temporal lobes. A subsequent MRI confirmed the lesions observed on PET/CT. Because PSMA-targeting radiopharmaceuticals do not accumulate in healthy brain parenchyma, and recent literature reported promising performances of PSMA-targeted PET/CT in gliomas and metastases from tumors other than prostate cancer, this employment of PSMA radioligands needs to be further explored.

Can neutrophil-lymphocyte ratio and mean platelet volume be used to predict metastasis in individuals with lung cancer?

Chronic inflammation plays an important role in the etiopathogenesis of many life-threatening chronic diseases, including cancer. Currently, the relationship between inflammation, native immunity and cancer is widely accepted; however, many of the mechanisms mediating this relationship remain undetermined and the clinical significance of these markers is unclear. The purpose of this study was to investigate the potential of neutrophil-lymphocyte ratio (NLR) and mean platelet volume (MPV) to indicate the existence of metastasis in lung cancer. This retrospective cross-sectional study evaluated patients with lung cancer of any pathological type who was admitted to the Palliative Care Unit of the referral hospital in the region between January 2019 and February 2020. Patient characteristics, distant organ metastasis, treatments, NLR and MPV values were noted. Patients were grouped as with or without metastasis. Characters, NLR, MPV values were compared. One hundred twenty-six patients were included. The mean age of the patients was 61.17 ± 9.4 years and 7.9% (n = 10) were female. The patients with a history of chemotherapy were 47% (n = 60) and distant organ metastases were present in 38.9% (n = 49) of the patients. The mean MPV value of 49 patients with distant metastasis was 8.34 ± 0.8 fL. MPV values of those with metastasis were found to be significantly higher than those without (P = .010). There was no significant difference in NLR values between groups (P = .920). Lung cancer patients with metastasis were found with higher MPV values. MPV can be effective and most accessible test in prediction of metastasis in lung cancer patients regardless of the pathological type.

Perioperative lidocaine and dexmedetomidine intravenous infusion reduce the serum levels of NETs and biomarkers of tumor metastasis in lung cancer patients: A prospective, single-center, double-blinded, randomized clinical trial.

Neutrophil extracellular traps (NETs) can enhance the metastasis of non-small cell lung cancer (NSCLC). As biomarkers of tumor metastasis, metalloproteinases (MMPs) and vascular endothelial growth factor (VEGF) together with NETs are essential to endothelial-to-mesenchymal transition (EMT). We hypothesized that intravenous infusion of lidocaine and dexmedetomidine could reduce the production of NETs and biomarkers of tumor metastasis after video-assisted thoracic surgery (VATS) in NSCLC patients. The trial included 132 NSCLC patients undergoing VATS. The patients were equally randomized to a placebo group (Group C), a lidocaine group (Group L, intravenous lidocaine 8 mg/kg/h for 15 minutes before anesthesia, 2 mg/kg/h during surgery, and 1 mg/kg/h until 24 hours after surgery), a dexmedetomidine group (Group D, intravenous dexmedetomidine 2 μg/kg/h for 15 minutes before anesthesia, 0.5 μg/kg/h during surgery, and 0.25 μg/kg/h until 24 hours after surgery), and a dexmedetomidine plus lidocaine group (Group LD, combination use of lidocaine and dexmedetomidine). The primary outcome was the production of myeloperoxidase (MPO) and citrullinated histone-3 (H3Cit), biomarkers of NETs, on postoperative day (POD) 1. MMP-3, MMP-9, and VEGF-α, as biomarkers of tumor metastasis, were also evaluated on POD 1. The baseline patient characteristics and perioperative data did not differ between the study groups. MPO was significantly decreased in Groups L, D, and LD (-197.08 ± 34.01, -137.37 ± 32.41, and -189.45 ± 33.73 U/ml, P<0.001, respectively) compared with Group C (-106.51 ± 25.44 U/ml). H3Cit was also lessened in Groups L, D, and LD (-49.51 ± 9.11, -34.80 ± 10.37, and -51.82 ± 8.98 ng/ml, P<0.001, respectively) compared with Group C (-24.73 ± 7.65 ng/ml). Lidocaine and dexmedetomidine also reduced MMP-3 (-69.08 ± 13.22, -52.84 ± 13.78, -85.34 ± 12.59 vs. -40.55 ± 10.71 ng/ml in Group L, D, LD vs. Group C, P<0.001, respectively), MMP-9 (-8.46 ± 1.68, -6.07 ± 1.82, -9.67 ± 1.43 vs. -4.28 ± 1.29 ng/ml in Group L, D, LD vs. Group C, P<0.001, respectively), and VEGF-α (-95.55 ± 22.53, -71.65 ± 18.77, -104.89 ± 15.49 vs. -51.73 ± 16.27 pg/ml in Group L, D, LD vs. Group C, P<0.001, respectively) on POD 1. In NSCLC patients, continuous perioperative intravenous infusion of lidocaine and dexmedetomidine significantly reduced the production of NETs and tumor metastasis biomarkers on POD 1. Meanwhile, it also decreased inflammation, protected cellular immune function, reduced pain and opioid consumption, and improved the quality of postoperative recovery. chictr.org.cn, identifier: 187049.

Risk and prognostic factors of brain metastasis in lung cancer patients: a Surveillance, Epidemiology, and End Results population‑based cohort study.

Brain is a common metastasis site in lung cancer patients. However, homogeneous and heterogeneous risk/prognostic factors of brain metastasis for lung cancer patients have not been comprehensively elucidated. This study aimed to explore the brain metastasis risk and prognostic factors in lung cancer patients using the Surveillance, Epidemiology, and End Results (SEER) database. Lung cancer data were downloaded from SEER database to investigate risk factors for developing brain metastasis using logistic regression analysis. Univariate and multivariate Cox analyses were used to identify potential prognostic factors. Kaplan-Meier analysis was conducted to evaluate the survival. Propensity score matching was conducted to eliminate baseline differences between two groups. A total of 10 818 (14.1%) patients with brain metastasis were diagnosed among 76 483 lung cancer patients. For non-small-cell lung carcinoma (NSCLC), distant liver/bone/lymph node metastases, higher T, N stages were risk factors. Black race, bone metastases and distant lymph node metastases and T4 were brain metastasis risk factors for SCLC patients. Cox analysis suggested that older age, male, primary lesion at main bronchus, liver/ bone/distant lymph node metastases, T2-4, N1-3, no surgery/chemotherapy/radiotherapy were associated with worse prognosis of NSCLC-brain metastasis patients. Age older than 80, liver/bone metastases, without radiotherapy and chemotherapy were associated with worse prognosis of SCLC-brain metastasis patients. Surgery of primary site could prolong the overall survival (OS) of NSCLC patients with brain metastasis, but not SCLC. In this study, we analyzed the homogeneous and heterogeneous risk/prognostic factors of brain metastasis in lung cancer patients. What is more, our results showed that surgery of primary site was associated with longer OS of NSCLC patients with brain metastasis.

Serum cross-linked N-telopeptide of type I collagen as a potential diagnostic marker for bone metastasis in lung cancer: An updated meta-analysis.

To investigate the clinical value of serum type I collagen cross-linked amino terminal peptide (NTx) for the diagnosis of bone metastasis in lung cancer patients by evidence-based medicine. Diagnostic studies relevant to NTx as a serum marker for the diagnosis of bone metastasis in lung cancer patients included in the China National Knowledge Infrastructure, Wanfang, PubMed, Embase, and VIP database from the establishment of the databases to November 2022 were retrieved. Meta-analysis was conducted with Stata 16.0 software to calculate the combined sensitivity (SEN), specificity (SPN), positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR), and its 95% confidence interval (CI). The total subject working characteristic curve (summary receiver operating characteristic (SROC) curve) was drawn, and the area under the curve was calculated to evaluate its diagnostic value. A total of 1742 patients with lung cancer were included in 14 articles. Meta-analysis showed heterogeneity among the studies. The results of random-effect model analysis demonstrated that the combined SEN, SPN, +LR, -LR, and DOR were 0.76 (95% CI 0.66-0.83), 0.80 (95% CI 0.74-0.85), 3.80 (95% CI 2.90-4.80), 0.30 (95% CI 0.22-0.42), and 12 (95% CI 8-19), respectively, and the area under SROC was 0.85. Serum NTx has a high clinical value in the diagnosis of bone metastasis in lung cancer patients and can be used as an effective complementary means for imaging diagnosis of bone metastasis in lung cancer patients.

Abstract B031: A multi-gene predictor for detection and monitoring liver metastasis in lung cancer patients: An algorithmic, in-vitro and in-vivo approach

Abstract Liver metastasis has known to affect outcome in prostate, pancreatic and colorectal cancers, but it is less explored in lung cancer with an extensively low 5-year survival rate. Late-stage diagnosis is one of the major confounders for poor prognosis, as there are no disease-specific biomarkers available for early risk prediction. Some of the major limitations of invasive tissue biopsies are inadequacy of tissue, difficulty in accessing deep sites, and potential risk for the patient. Therefore, it is crucial to identify sensitive and specific circulatory biomarkers using non-invasive techniques. In this study, we validated 8 gene panel, in CTC, cfRNA and exosomes using real time PCR in primary lung cancer patients with &amp; without metastasis and healthy controls, identified in our previous study in the tissue samples of the same cohort. ROC curve analysis was used to determine the sensitivity and specificity of the shortlisted gene panel and its correlation with the most accurate source of liquid biopsy component for early prediction of liver metastasis. Further DEP expression, clinic-pathological factors and survival analysis correlations were performed. Lastly, the role of exosomes was identified in the development of liver metastasis by generating an in vitro and in-vivo model. Our results demonstrated that in comparison to our tissue data from the previous study, exosomes demonstrated a good discriminative value for lung cancer liver metastasis and the AUC was 0.7247, with specificity and sensitivity of 72.48 % and 96.87% respectively for the shortlisted 8 gene panel. Further when we analyzed the genes based on the individual gene patterns we shortlisted a 5- gene panel that showed an AUC of 0.9488 (p = &amp;lt;0.001) and 0.9924 (p = &amp;lt;0.001) respectively for tissue and exosomes suggesting that exosomes could be used as a non-invasive component for the early prediction of liver metastasis. Survival analysis suggested that four out of five gene expression levels in exosomal fraction, were independently associated with poor overall survival. Moreover, the in-vitro study demonstrated that exosome uptake by A549 cells induced migratory/invasive changes in a concentration and time- dependent manner and activated the cell cycle phases leading to cell proliferation. Moreover, we observed that these five genes were differentially expressed when A549 cells were treated with exosomes demonstrating an important role in altering the tumor microenvironment. In –vivo model showed an elevated level of serum SGPT &amp; SGOT whereas histopathological examination showed patches of pneumonitis in lung and severe inflammation in the liver. Conclusively this study suggests that these exosomal gene panel could be used as potential surrogate non-invasive biomarkers for early detection and monitoring of liver metastasis in lung cancer patients. Furthermore, it depicts an undisputable role of these exosomes as key modulators in the formation of the pre-metastatic niche ultimately leading to distant metastasis. Citation Format: Kanisha Shah, Rakesh Rawal. A multi-gene predictor for detection and monitoring liver metastasis in lung cancer patients: An algorithmic, in-vitro and in-vivo approach [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr B031.

Total mutational load and clinical features as predictors of the metastatic status in lung adenocarcinoma and squamous cell carcinoma patients

BackgroundRecently, extensive cancer genomic studies have revealed mutational and clinical data of large cohorts of cancer patients. For example, the Pan-Lung Cancer 2016 dataset (part of The Cancer Genome Atlas project), summarises the mutational and clinical profiles of different subtypes of Lung Cancer (LC). Mutational and clinical signatures have been used independently for tumour typification and prediction of metastasis in LC patients. Is it then possible to achieve better typifications and predictions when combining both data streams?MethodsIn a cohort of 1144 Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LSCC) patients, we studied the number of missense mutations (hereafter, the Total Mutational Load TML) and distribution of clinical variables, for different classes of patients. Using the TML and different sets of clinical variables (tumour stage, age, sex, smoking status, and packs of cigarettes smoked per year), we built Random Forest classification models that calculate the likelihood of developing metastasis.ResultsWe found that LC patients different in age, smoking status, and tumour type had significantly different mean TMLs. Although TML was an informative feature, its effect was secondary to the "tumour stage" feature. However, its contribution to the classification is not redundant with the latter; models trained using both TML and tumour stage performed better than models trained using only one of these variables. We found that models trained in the entire dataset (i.e., without using dimensionality reduction techniques) and without resampling achieved the highest performance, with an F1 score of 0.64 (95%CrI [0.62, 0.66]).ConclusionsClinical variables and TML should be considered together when assessing the likelihood of LC patients progressing to metastatic states, as the information these encode is not redundant. Altogether, we provide new evidence of the need for comprehensive diagnostic tools for metastasis.

Gastric Metastasis of Primary Lung Cancer: Case Report and Systematic Review With Pooled Analysis

BackgroundGastric metastasis from lung cancer (GMLC) is a rare occurrence. The clinicopathological characteristics, outcomes, and prognostic factors remain largely elusive.MethodsWe conducted a systematic review on case reports and case series of GMLC by scanning MEDLINE, Embase, and ISI Web of Knowledge. Data involving the clinicopathological features, treatment, and outcomes were extracted and analyzed. Survival analysis was performed using Kaplan–Meier method. The Cox proportional hazards regression model was used to identify potential prognostic factors associated with survival. Furthermore, a case of metastatic gastric adenocarcinoma of pulmonary origin with epidermal growth factor receptor (EGFR) L858R+T790M mutation was also described and included.ResultsSeventy-eight records involving 114 cases (including ours) were finally included. The median age on admission was 65 years with a male predominance of 79.8%. Lung adenocarcinoma (42.1%), located in the right upper lobe (30.3%), was the most frequent primary tumor. Bleeding (36.7%) and abdominal pain (35.8%) were the two most common symptoms. Endoscopically, gastric lesions were typically presented as elevated lesions with or without volcano-like ulceration, or ulcerative lesions, mostly involving the gastric corpus. The median overall survival time and survival time after diagnosis of metastatic cancer were 11 months [95% confidence interval (CI): 7–14] and 4.5 months (95% CI: 3–9), respectively. The survival analyses revealed that surgical interventions (including lung surgery and/or abdominal surgery) and systemic therapy (including chemotherapy, radiotherapy, and/or targeted therapy) seemed to be positive prognostic factors for both overall survival and survival after diagnosis of metastatic cancer.ConclusionsClinicians should be alerted to the occurrence of gastric metastasis in lung cancer patients. Comprehensive evaluation and appropriate treatment for specific patients may improve the survival rate of GMLC patients.

WITHDRAWN: Proteomic analysis of plasma-derived exosomes identifies biomarkers that distinguish brain and liver metastasis in lung cancer patients

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Machine Learning for the Prediction of Synchronous Organ-Specific Metastasis in Patients With Lung Cancer.

BackgroundThis study aimed to develop an artificial neural network (ANN) model for predicting synchronous organ-specific metastasis in lung cancer (LC) patients.MethodsA total of 62,151 patients who diagnosed as LC without data missing between 2010 and 2015 were identified from Surveillance, Epidemiology, and End Results (SEER) program. The ANN model was trained and tested on an 75/25 split of the dataset. The receiver operating characteristic (ROC) curves, area under the curve (AUC) and sensitivity were used to evaluate and compare the ANN model with the random forest model.ResultsFor distant metastasis in the whole cohort, the ANN model had metrics AUC = 0.759, accuracy = 0.669, sensitivity = 0.906, and specificity = 0.613, which was better than the random forest model. For organ-specific metastasis in the cohort with distant metastasis, the sensitivity in bone metastasis, brain metastasis and liver metastasis were 0.913, 0.906 and 0.925, respectively. The most important variable was separate tumor nodules with 100% importance. The second important variable was visceral pleural invasion for distant metastasis, while histology for organ-specific metastasis.ConclusionsOur study developed a “two-step” ANN model for predicting synchronous organ-specific metastasis in LC patients. This ANN model may provide clinicians with more personalized clinical decisions, contribute to rationalize metastasis screening, and reduce the burden on patients and the health care system.

One-step nucleic acid amplification for intraoperative diagnosis of lymph node metastasis in lung cancer patients: a single-center prospective study

One-step nucleic acid amplification (OSNA) is a rapid intraoperative molecular detection technique for sentinel node assessment via the quantitative measurement of target cytokeratin 19 (CK19) mRNA to determine the presence of metastasis. It has been validated in breast cancer but its application in lung cancer has not been adequately investigated. 214 LNs from 105 patients with 100 primary lung cancers, 2 occult primary lung tumors, and 3 metastatic lung tumors, who underwent surgical lung resection with LN dissection between February 2018 and January 2020, were assessed. Resected LNs were divided into two parts: one was snap-frozen for OSNA and the other underwent rapidly frozen histological examination. Intraoperatively collected LNs were evaluated by OSNA using loop-mediated isothermal amplification and compared with intraoperative pathological diagnosis as a control. Among 214 LNs, 14 were detected as positive by OSNA, and 11 were positive by both OSNA and intraoperative pathological diagnosis. The sensitivity and specificity of OSNA was 84.6% and 98.5%, respectively. The results of 5 of 214 LNs were discordant, and the remainder all matched (11 positive and 198 negative) with a concordance rate of 97.7%. Although the analysis of public mRNA expression data from cBioPortal showed that CK19 expression varies greatly depending on the cancer type and histological subtype, the results of the five cases, except for primary lung cancer, were consistent. OSNA provides sufficient diagnostic accuracy and speed and can be applied to the intraoperative diagnosis of LN metastasis for non-small cell lung cancer.

Bone metastases in non-small cell lung cancer: a narrative review.

Background and ObjectiveBone metastases are common in patients with non-small cell lung cancer (NSCLC) and remain a significant source of morbidity, mortality, and diminished quality of life, despite the considerable progress made in the overall management of patients with metastatic NSCLC over the last decade. Understanding the molecular pathogenesis of bone metastases is critical to improving survival, preserving function, and managing symptoms in this patient population. The objective of our review is to provide a comprehensive review of the pathophysiology, clinical presentation, management, and factors predicting the development and prognosis of patients with NSCLC with bone metastases.MethodsAn online electronic search was performed on PubMed and Google Scholar of all English-language literature using combinations of the following keywords: bone metastases, non-small cell lung cancer, pathophysiology, skeletal related events, response to therapy, predictive factors, and immunotherapy. Bibliographies of identified papers were reviewed for additional articles of interest. Observational cohort, retrospective studies, randomized controlled trials (RCTs), meta-analyses, and review articles were examined for this review.Key Content and FindingsBone metastases in lung cancer patients remain a common occurrence, impacting morbidity, mortality, and quality of life. Patients with skeletal related events (SREs) have worse prognosis. There is data supporting use of bisphosphonates and/or denosumab, and these should be considered in all patients with bone metastases. Novel studies comparing the genomic alterations of skeletal metastases and primary tumors are needed. As therapy for patients with advanced disease evolves, more studies are needed to evaluate the interplay between immunotherapy and bone metastases, and in determining the response to treatment in bone.ConclusionsPredicting development and progression of bone metastases could allow earlier and targeted therapy in patients with bone metastases. Predicting and evaluating response to conventional chemotherapy and immune checkpoint inhibitors in NSCLC patients with bone metastases remains an unmet need and merits further study.