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1.
EPMA J ; 13(1): 57-75, 2022 Mar.
Article in English | MEDLINE | ID: mdl-35273659

ABSTRACT

Background: Bone metastasis (BM) and skeletal-related events (SREs) happen to advanced lung cancer (LC) patients without warning. LC-BM patients are often passive to BM diagnosis and surgical treatment. It is necessary to guide the diagnosis and treatment paradigm for LC-BM patients from reactive medicine toward predictive, preventive, and personalized medicine (PPPM) step by step. Methods: Two independent study cohorts including LC-BM patients were analyzed, including the Surveillance, Epidemiology, and End Results (SEER) cohort (n = 203942) and the prospective Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 59). The epidemiological trends of BM in LC patients were depicted. Risk factors for BM were identified using a multivariable logistic regression model. An individualized nomogram was developed for BM risk stratification. Personalized surgical strategies and perioperative care were described for FUSCC cohort. Results: The BM incidence rate in LC patients grew (from 17.53% in 2010 to 19.05% in 2016). Liver metastasis was a significant risk factor for BM (OR = 4.53, 95% CI = 4.38-4.69) and poor prognosis (HR = 1.29, 95% CI = 1.25-1.32). The individualized nomogram exhibited good predictive performance for BM risk stratification (AUC = 0.784, 95%CI = 0.781-0.786). Younger patients, males, patients with high invasive LC, and patients with other distant site metastases should be prioritized for BM prevention. Spine is the most common site of BM, causing back pain (91.5%), pathological vertebral fracture (27.1%), and difficult walking (25.4%). Spinal surgery with personalized spinal reconstruction significantly relieved pain and improved daily activities. Perioperative inflammation, immune, and nutrition abnormities warrant personalized managements. Radiotherapy needs to be recommended for specific postoperative individuals. Conclusions: The presence of liver metastasis is a strong predictor of LC-BM. It is recommended to take proactive measures to prevent BM and its SREs, particularly in young patients, males, high invasive LC, and LC with liver metastasis. BM surgery and perioperative management are personalized and required. In addition, adjuvant radiation following separation surgery must also be included in PPPM-guided management. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-022-00270-9.

2.
Biomolecules ; 10(12)2020 12 10.
Article in English | MEDLINE | ID: mdl-33321708

ABSTRACT

Metastasis represents a major obstacle in cancer treatment and the leading cause of cancer-related deaths. Therefore, the identification of compounds targeting the multi-step and complex process of metastasis could improve outcomes in the management of cancer patients. Carotenoids are naturally occurring pigments with a plethora of biological activities. Carotenoids exert a potent anti-cancer capacity in various cancer models in vitro and in vivo, mediated by the modulation of signaling pathways involved in the migration and invasion of cancer cells and metastatic progression, including key regulators of the epithelial-mesenchymal transition and regulatory molecules, such as matrix metalloproteinases (MMPs), tissue inhibitors of metalloproteinases (TIMPs), urokinase plasminogen activator (uPA) and its receptor (uPAR), hypoxia-inducible factor-1α (HIF-1α), and others. Moreover, carotenoids modulate the expression of genes associated with cancer progression and inflammatory processes as key mediators of the complex process involved in metastasis. Nevertheless, due to the predominantly preclinical nature of the known anti-tumor effects of carotenoids, and unclear results from certain carotenoids in specific cancer types and/or specific parts of the population, a precise analysis of the anti-cancer effects of carotenoids is essential. The identification of carotenoids as effective compounds targeting the complex process of cancer progression could improve the outcomes of advanced cancer patients.


Subject(s)
Antineoplastic Agents, Phytogenic/therapeutic use , Carotenoids/therapeutic use , Epithelial-Mesenchymal Transition/drug effects , Gene Expression Regulation, Neoplastic/drug effects , Neoplasm Metastasis/drug therapy , Neoplasms/drug therapy , Antineoplastic Agents, Phytogenic/chemistry , Antineoplastic Agents, Phytogenic/classification , Carotenoids/chemistry , Carotenoids/classification , Chemotherapy, Adjuvant , Epithelial-Mesenchymal Transition/genetics , Humans , Hypoxia-Inducible Factor 1, alpha Subunit/genetics , Hypoxia-Inducible Factor 1, alpha Subunit/metabolism , Machine Learning , Matrix Metalloproteinases/genetics , Matrix Metalloproteinases/metabolism , Neoplasm Invasiveness , Neoplasm Metastasis/genetics , Neoplasm Metastasis/pathology , Neoplasms/genetics , Neoplasms/metabolism , Neoplasms/pathology , Precision Medicine , Receptors, Urokinase Plasminogen Activator/genetics , Receptors, Urokinase Plasminogen Activator/metabolism , Signal Transduction , Tissue Inhibitor of Metalloproteinases/genetics , Tissue Inhibitor of Metalloproteinases/metabolism , Urokinase-Type Plasminogen Activator/genetics , Urokinase-Type Plasminogen Activator/metabolism
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