Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications
Abstract
:1. Introduction
1.1. Overview of Bone Metastases
1.2. Precision Medicine Paradigm and Role of Biomarkers in Tailoring Individualized Treatment
2. Pathophysiology of Bone Metastases
2.1. Bone Microenvironment and Tumor Interactions
2.2. Molecular Pathways
2.2.1. RANK/RANKL/OPG Axis
2.2.2. Wnt Signaling
2.2.3. Angiogenesis and Hypoxia-Induced Pathways
2.2.4. Clinical Implications
3. Biomarkers in Bone Metastases
3.1. Introduction to Biomarkers
3.2. Classification of Biomarkers
3.3. Diagnostic Biomarkers
3.3.1. Circulating Tumor Cells (CTCs)
3.3.2. Bone Turnover Markers
3.3.3. Imaging-Based Biomarkers
Positron Emission Tomography (PET) and PET/CT
Computed Tomography (CT)
Magnetic Resonance Imaging (MRI)
Bone Scintigraphy
Clinical Utility and Limitations
3.4. Prognostic Biomarkers
3.4.1. Circulating DNA (ctDNA)
3.4.2. Bone Matrix Proteins
3.4.3. LncRNAs
3.5. Predictive Biomarkers
3.5.1. Response to Bone-Targeted Therapies as Predictive Biomarkers in Bone Metastasis
3.5.2. Biomarkers for Immunotherapy Response in Bone Metastases
3.5.3. Predictive Genomic Signatures
3.6. Monitoring Biomarkers for Treatment Efficacy in Bone Metastasis
3.6.1. Circulating Tumor Cells (CTCs) and Circulating Tumor DNA (ctDNA)
3.6.2. TRACP5b as a Biomarker for Treatment Monitoring
3.6.3. C-Terminal Telopeptide of Type I Collagen (CTX) and Other Bone Resorption Markers
4. Advances in Precision Medicine for Bone Metastases
4.1. Genomic Approaches
4.1.1. Next-Generation Sequencing (NGS) in Bone Metastases
4.1.2. NGS in Clinical Trials and Treatment Selection
4.1.3. Multi-Omics Integration (Proteomics and Metabolomics)
4.2. Emerging Therapeutics
4.2.1. Targeted Therapies: Precision Treatment in Bone Metastases
4.2.2. Tyrosine Kinase Inhibitors (TKIs) in Bone Metastases
4.2.3. Bisphosphonates in Bone Metastases
4.2.4. Emerging Nanoformulations for Enhanced Bone Targeting
4.2.5. Radiopharmaceuticals: Bone-Targeted Therapy
4.2.6. Immunotherapeutics in Bone Metastases
4.3. Personalized Treatment Protocols
4.3.1. Case Studies and Clinical Trials
4.3.2. Incorporation of Biomarkers into Therapeutic Algorithms
4.3.3. Future Directions in AI-Driven Precision Medicine
4.4. Clinical Challenges of Managing Bone Metastases
5. Challenges and Limitations
5.1. Heterogeneity of Bone Metastases
5.2. Standardization of Biomarker Assays
5.3. Challenges of Translating Research Findings into Clinical Practice
5.4. Regulatory and Ethical Considerations
5.4.1. Validation of Biomarkers for Clinical Use
5.4.2. Ethical Implications of Genetic Testing
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Zhao, C.; Lou, Y.; Wang, Y.; Wang, D.; Tang, L.; Gao, X.; Zhang, K.; Xu, W.; Liu, T.; Xiao, J. A Gene Expression Signature-Based Nomogram Model in Prediction of Breast Cancer Bone Metastases. Cancer Med. 2019, 8, 200–208. [Google Scholar] [CrossRef] [PubMed]
- Hernandez, R.K.; Wade, S.W.; Reich, A.; Pirolli, M.; Liede, A.; Lyman, G.H. Incidence of Bone Metastases in Patients with Solid Tumors: Analysis of Oncology Electronic Medical Records in the United States. BMC Cancer 2018, 18, 44. [Google Scholar] [CrossRef] [PubMed]
- Jiang, W.; Rixiati, Y.; Zhao, B.; Li, Y.; Tang, C.; Liu, J. Incidence, Prevalence, and Outcomes of Systemic Malignancy with Bone Metastases. J. Orthop. Surg. Hong Kong 2020, 28, 2309499020915989. [Google Scholar] [CrossRef]
- Rieunier, G.; Wu, X.; Macaulay, V.M.; Lee, A.V.; Weyer-Czernilofsky, U.; Bogenrieder, T. Bad to the Bone: The Role of the Insulin-Like Growth Factor Axis in Osseous Metastasis. Clin. Cancer Res. 2019, 25, 3479–3485. [Google Scholar] [CrossRef]
- Brown, J.E.; Cook, R.J.; Major, P.; Lipton, A.; Saad, F.; Smith, M.; Lee, K.-A.; Zheng, M.; Hei, Y.-J.; Coleman, R.E. Bone Turnover Markers as Predictors of Skeletal Complications in Prostate Cancer, Lung Cancer, and Other Solid Tumors. J. Natl. Cancer Inst. 2005, 97, 59–69. [Google Scholar] [CrossRef]
- Garcia, T.; Jackson, A.; Bachelier, R.; Clément-Lacroix, P.; Baron, R.; Clézardin, P.; Pujuguet, P. A Convenient Clinically Relevant Model of Human Breast Cancer Bone Metastasis. Clin. Exp. Metastasis 2008, 25, 33–42. [Google Scholar] [CrossRef] [PubMed]
- Zhang, L.; Gong, Z. Clinical Characteristics and Prognostic Factors in Bone Metastases from Lung Cancer. Med. Sci. Monit. Int. Med. J. Exp. Clin. Res. 2017, 23, 4087–4094. [Google Scholar] [CrossRef]
- Garajová, I.; Gelsomino, F.; Salati, M.; Leonardi, F.; De Lorenzo, S.; Granito, A.; Tovoli, F. Bone Metastases from Intrahepatic Cholangiocarcinoma Confer Worse Prognosis. Curr. Oncol. 2023, 30, 2613–2624. [Google Scholar] [CrossRef]
- Halvorson, K.G.; Kubota, K.; Sevcik, M.A.; Lindsay, T.H.; Sotillo, J.E.; Ghilardi, J.R.; Rosol, T.J.; Boustany, L.; Shelton, D.L.; Mantyh, P.W. A Blocking Antibody to Nerve Growth Factor Attenuates Skeletal Pain Induced by Prostate Tumor Cells Growing in Bone. Cancer Res. 2005, 65, 9426–9435. [Google Scholar] [CrossRef]
- Kimura, T.; Kuwata, T.; Ashimine, S.; Yamazaki, M.; Yamauchi, C.; Nagai, K.; Ikehara, A.; Feng, Y.; Dimitrov, D.S.; Saito, S.; et al. Targeting of Bone-Derived Insulin-like Growth Factor-II by a Human Neutralizing Antibody Suppresses the Growth of Prostate Cancer Cells in a Human Bone Environment. Clin. Cancer Res. 2010, 16, 121–129. [Google Scholar] [CrossRef]
- Yang, W.; Pan, Q.; Huang, F.; Hu, H.; Shao, Z. Research Progress of Bone Metastases: From Disease Recognition to Clinical Practice. Front. Oncol. 2022, 12, 1105745. [Google Scholar] [CrossRef] [PubMed]
- Karimanal, H.; Bandaru, D. A Review on Integration of Precision Medicine in Oncology Practice: Review Article. J. Pharma Insights Res. 2024, 2, 016–022. [Google Scholar] [CrossRef]
- Lee, S.-G. Molecular Target and Action Mechanism of Anti-Cancer Agents. Int. J. Mol. Sci. 2023, 24, 8259. [Google Scholar] [CrossRef] [PubMed]
- Sharifi-Noghabi, H.; Jahangiri-Tazehkand, S.; Smirnov, P.; Hon, C.; Mammoliti, A.; Nair, S.K.; Mer, A.S.; Ester, M.; Haibe-Kains, B. Drug Sensitivity Prediction from Cell Line-Based Pharmacogenomics Data: Guidelines for Developing Machine Learning Models. Brief. Bioinform. 2021, 22, bbab294. [Google Scholar] [CrossRef]
- Henderson, R.H.; French, D.; Stewart, E.; Smart, D.; Idica, A.; Redmond, S.; Eckstein, M.; Clark, J.; Sullivan, R.; Keeling, P.; et al. Delivering the Precision Oncology Paradigm: Reduced R&D Costs and Greater Return on Investment through a Companion Diagnostic Informed Precision Oncology Medicines Approach. J. Pharm. Policy Pract. 2023, 16, 84. [Google Scholar] [CrossRef]
- Liow, E.; Tran, B. Precision Oncology in Urothelial Cancer. ESMO Open 2020, 5, e000616. [Google Scholar] [CrossRef]
- Sadik, H.; Pritchard, D.; Keeling, D.-M.; Policht, F.; Riccelli, P.; Stone, G.; Finkel, K.; Schreier, J.; Munksted, S. Impact of Clinical Practice Gaps on the Implementation of Personalized Medicine in Advanced Non–Small-Cell Lung Cancer. JCO Precis. Oncol. 2022, 6, e2200246. [Google Scholar] [CrossRef]
- Yap, T.A.; Johnson, A.; Meric-Bernstam, F. Precision Medicine in Oncology—Toward the Integrated Targeting of Somatic and Germline Genomic Aberrations. JAMA Oncol. 2021, 7, 507. [Google Scholar] [CrossRef]
- Chen, F.; Han, Y.; Kang, Y. Bone Marrow Niches in the Regulation of Bone Metastasis. Br. J. Cancer 2021, 124, 1912–1920. [Google Scholar] [CrossRef]
- Wang, M.; Xia, F.; Wei, Y.; Wei, X. Molecular Mechanisms and Clinical Management of Cancer Bone Metastasis. Bone Res. 2020, 8, 30. [Google Scholar] [CrossRef]
- Haider, M.-T.; Smit, D.J.; Taipaleenmäki, H. The Endosteal Niche in Breast Cancer Bone Metastasis. Front. Oncol. 2020, 10, 335. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Chen, H.; Chen, T.; Qiu, G.; Han, Y. The Emerging Role of Osteoclasts in the Treatment of Bone Metastases: Rationale and Recent Clinical Evidence. Front. Oncol. 2024, 14, 1445025. [Google Scholar] [CrossRef] [PubMed]
- Böker, S.M.; Adams, L.C.; Bender, Y.Y.; Fahlenkamp, U.L.; Wagner, M.; Hamm, B.; Makowski, M.R. Differentiation of Predominantly Osteoblastic and Osteolytic Spine Metastases by Using Susceptibility-Weighted MRI. Radiology 2019, 290, 146–154. [Google Scholar] [CrossRef] [PubMed]
- Yang, Z.; Yue, Z.; Ma, X.; Xu, Z. Calcium Homeostasis: A Potential Vicious Cycle of Bone Metastasis in Breast Cancers. Front. Oncol. 2020, 10, 293. [Google Scholar] [CrossRef]
- Nyman, K.J.; Frieling, J.S.; Lynch, C.C. Emerging Roles for Stromal Cells in Bone Metastasis. J. Bone Oncol. 2024, 47, 100610. [Google Scholar] [CrossRef]
- Zhang, Y.; Liang, J.; Liu, P.; Wang, Q.; Liu, L.; Zhao, H. The RANK/RANKL/OPG System and Tumor Bone Metastasis: Potential Mechanisms and Therapeutic Strategies. Front. Endocrinol. 2022, 13, 1063815. [Google Scholar] [CrossRef]
- Ming, J.; Cronin, S.J.F.; Penninger, J.M. Targeting the RANKL/RANK/OPG Axis for Cancer Therapy. Front. Oncol. 2020, 10, 1283. [Google Scholar] [CrossRef]
- Ben-Ghedalia-Peled, N.; Vago, R. Wnt Signaling in the Development of Bone Metastasis. Cells 2022, 11, 3934. [Google Scholar] [CrossRef]
- Sottnik, J.L.; Hall, C.L.; Zhang, J.; Keller, E.T. Wnt and Wnt Inhibitors in Bone Metastasis. BoneKEy Rep. 2012, 1, 101. [Google Scholar] [CrossRef]
- Cui, J.; Chen, H.; Zhang, K.; Li, X. Targeting the Wnt Signaling Pathway for Breast Cancer Bone Metastasis Therapy. J. Mol. Med. 2022, 100, 373–384. [Google Scholar] [CrossRef]
- Galliera, E.; Massaccesi, L.; de Benedettis, E.; Longhi, E.; de Toma, D.; Corsi Romanelli, M.M.; Banfi, G. Longitudinal Evaluation of Wnt Inhibitors and Comparison with Others Serum Osteoimmunological Biomarkers in Osteolytic Bone Metastasis. J. Leukoc. Biol. 2020, 108, 697–704. [Google Scholar] [CrossRef] [PubMed]
- Elaasser, B.; Arakil, N.; Mohammad, K.S. Bridging the Gap in Understanding Bone Metastasis: A Multifaceted Perspective. Int. J. Mol. Sci. 2024, 25, 2846. [Google Scholar] [CrossRef] [PubMed]
- Hall, C.L.; Kang, S.; MacDougald, O.A.; Keller, E.T. Role of Wnts in Prostate Cancer Bone Metastases. J. Cell. Biochem. 2006, 97, 661–672. [Google Scholar] [CrossRef]
- Kar, S.; Jasuja, H.; Katti, D.R.; Katti, K.S. Wnt/β-Catenin Signaling Pathway Regulates Osteogenesis for Breast Cancer Bone Metastasis: Experiments in an In Vitro Nanoclay Scaffold Cancer Testbed. ACS Biomater. Sci. Eng. 2020, 6, 2600–2611. [Google Scholar] [CrossRef]
- Clézardin, P.; Coleman, R.; Puppo, M.; Ottewell, P.; Bonnelye, E.; Paycha, F.; Confavreux, C.B.; Holen, I. Bone Metastasis: Mechanisms, Therapies, and Biomarkers. Physiol. Rev. 2021, 101, 797–855. [Google Scholar] [CrossRef] [PubMed]
- Xu, H.; Lafage-Proust, M.-H.; Bouazza, L.; Geraci, S.; Clezardin, P.; Roche, B.; Peyrin, F.; Langer, M. Impact of Anti-Angiogenic Treatment on Bone Vascularization in a Murine Model of Breast Cancer Bone Metastasis Using Synchrotron Radiation Micro-CT. Cancers 2022, 14, 3443. [Google Scholar] [CrossRef]
- Das, A.; Barry, M.M.; Ernst, C.A.; Dahiya, R.; Kim, M.; Rosario, S.R.; Lo, H.C.; Yu, C.; Dai, T.; Gugala, Z.; et al. Differential Bone Morphology and Hypoxia Activity in Skeletal Metastases of ER+ and ER− Breast Cancer. Commun. Biol. 2024, 7, 1545. [Google Scholar] [CrossRef]
- Aboagye, E.O.; Barwick, T.D.; Haberkorn, U. Radiotheranostics in Oncology: Making Precision Medicine Possible. CA. Cancer J. Clin. 2023, 73, 255–274. [Google Scholar] [CrossRef]
- Wang, S.; Wu, W.; Lin, X.; Zhang, K.M.; Wu, Q.; Luo, M.; Zhou, J. Predictive and Prognostic Biomarkers of Bone Metastasis in Breast Cancer: Current Status and Future Directions. Cell Biosci. 2023, 13, 224. [Google Scholar] [CrossRef]
- Ying, M.; Mao, J.; Sheng, L.; Wu, H.; Bai, G.; Zhong, Z.; Pan, Z. Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction. J. Pers. Med. 2023, 13, 705. [Google Scholar] [CrossRef]
- Hao, Y.; Zhang, F.; Ma, Y.; Luo, Y.; Zhang, Y.; Yang, N.; Liu, M.; Liu, H.; Li, J. Potential Biomarkers for the Early Detection of Bone Metastases. Front. Oncol. 2023, 13, 1188357. [Google Scholar] [CrossRef]
- Wang, L.; Fang, D.; Xu, J.; Luo, R. Various Pathways of Zoledronic Acid against Osteoclasts and Bone Cancer Metastasis: A Brief Review. BMC Cancer 2020, 20, 1059. [Google Scholar] [CrossRef] [PubMed]
- Tardoski, S.; Ngo, J.; Gineyts, E.; Roux, J.-P.; Clézardin, P.; Melodelima, D. Low-Intensity Continuous Ultrasound Triggers Effective Bisphosphonate Anticancer Activity in Breast Cancer. Sci. Rep. 2015, 5, 16354. [Google Scholar] [CrossRef] [PubMed]
- Alix-Panabières, C.; Pantel, K. Liquid Biopsy: From Discovery to Clinical Implementation. Mol. Oncol. 2021, 15, 1617–1621. [Google Scholar] [CrossRef] [PubMed]
- Iuliani, M.; Simonetti, S.; Ribelli, G.; Napolitano, A.; Pantano, F.; Vincenzi, B.; Tonini, G.; Santini, D. Current and Emerging Biomarkers Predicting Bone Metastasis Development. Front. Oncol. 2020, 10, 789. [Google Scholar] [CrossRef]
- Saxby, H.; Mikropoulos, C.; Boussios, S. An Update on the Prognostic and Predictive Serum Biomarkers in Metastatic Prostate Cancer. Diagnostics 2020, 10, 549. [Google Scholar] [CrossRef]
- AlDoughaim, M.; AlSuhebany, N.; AlZahrani, M.; AlQahtani, T.; AlGhamdi, S.; Badreldin, H.; Al Alshaykh, H. Cancer Biomarkers and Precision Oncology: A Review of Recent Trends and Innovations. Clin. Med. Insights Oncol. 2024, 18, 11795549241298541. [Google Scholar] [CrossRef]
- Louie, A.D.; Huntington, K.; Carlsen, L.; Zhou, L.; El-Deiry, W.S. Integrating Molecular Biomarker Inputs Into Development and Use of Clinical Cancer Therapeutics. Front. Pharmacol. 2021, 12, 747194. [Google Scholar] [CrossRef]
- Duan, J.; Fang, W.; Xu, H.; Wang, J.; Chen, Y.; Ding, Y.; Dong, X.; Fan, Y.; Gao, B.; Hu, J.; et al. Chinese Expert Consensus on the Diagnosis and Treatment of Bone Metastasis in Lung Cancer (2022 Edition). J. Natl. Cancer Cent. 2023, 3, 256–265. [Google Scholar] [CrossRef]
- Marletta, S.; Rizzo, A.; Spoto, G.; Falzone, L. Predictive and Prognostic Biomarkers in Cancer: Towards the Precision Medicine Era. Explor. Target. Anti-Tumor Ther. 2024, 5, 1321–1325. [Google Scholar] [CrossRef]
- Pang, X.; Gong, K.; Zhang, X.; Wu, S.; Cui, Y.; Qian, B.-Z. Osteopontin as a Multifaceted Driver of Bone Metastasis and Drug Resistance. Pharmacol. Res. 2019, 144, 235–244. [Google Scholar] [CrossRef] [PubMed]
- Chai, X.; Yinwang, E.; Wang, Z.; Wang, Z.; Xue, Y.; Li, B.; Zhou, H.; Zhang, W.; Wang, S.; Zhang, Y.; et al. Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value. Front. Oncol. 2021, 11, 692788. [Google Scholar] [CrossRef]
- Nalejska, E.; Mączyńska, E.; Lewandowska, M.A. Prognostic and Predictive Biomarkers: Tools in Personalized Oncology. Mol. Diagn. Ther. 2014, 18, 273–284. [Google Scholar] [CrossRef]
- Nakamura, S.; Nagata, M.; Nagaya, N.; Ashizawa, T.; Hirano, H.; Lu, Y.; Ide, H.; Horie, S. The Detection and Negative Reversion of Circulating Tumor Cells as Prognostic Biomarkers for Metastatic Castration-Resistant Prostate Cancer with Bone Metastases Treated by Enzalutamide. Cancers 2024, 16, 772. [Google Scholar] [CrossRef] [PubMed]
- Xu, D.; Tang, M. Advances in the Study of Biomarkers Related to Bone Metastasis in Breast Cancer. Br. J. Radiol. 2023, 96, 20230117. [Google Scholar] [CrossRef]
- Rizzo, F.M.; Vesely, C.; Childs, A.; Marafioti, T.; Khan, M.S.; Mandair, D.; Cives, M.; Ensell, L.; Lowe, H.; Akarca, A.U.; et al. Circulating Tumour Cells and Their Association with Bone Metastases in Patients with Neuroendocrine Tumours. Br. J. Cancer 2019, 120, 294–300. [Google Scholar] [CrossRef] [PubMed]
- Yamamichi, G.; Kato, T.; Yumiba, S.; Tomiyama, E.; Koh, Y.; Nakano, K.; Matsushita, M.; Hayashi, Y.; Ishizuya, Y.; Watabe, T.; et al. Diagnostic and Prognostic Significance of Tartrate-Resistant Acid Phosphatase Type 5b in Newly Diagnosed Prostate Cancer with Bone Metastasis: A Real-World Multi-Institutional Study. Int. J. Urol. 2023, 30, 70–76. [Google Scholar] [CrossRef]
- Jung, K.; Lein, M. Bone Turnover Markers in Serum and Urine as Diagnostic, Prognostic and Monitoring Biomarkers of Bone Metastasis. Biochim. Biophys. Acta BBA Rev. Cancer 2014, 1846, 425–438. [Google Scholar] [CrossRef]
- D’Oronzo, S.; Brown, J.; Coleman, R. The Value of Biomarkers in Bone Metastasis. Eur. J. Cancer Care 2017, 26, e12725. [Google Scholar] [CrossRef]
- Dyrberg, E.; Hendel, H.W.; Huynh, T.H.V.; Klausen, T.W.; Løgager, V.B.; Madsen, C.; Pedersen, E.M.; Pedersen, M.; Thomsen, H.S. 68Ga-PSMA-PET/CT in Comparison with 18F-Fluoride-PET/CT and Whole-Body MRI for the Detection of Bone Metastases in Patients with Prostate Cancer: A Prospective Diagnostic Accuracy Study. Eur. Radiol. 2019, 29, 1221–1230. [Google Scholar] [CrossRef]
- Rong, J.; Wang, S.; Ding, Q.; Yun, M.; Zheng, Z.; Ye, S. Comparison of 18 FDG PET-CT and Bone Scintigraphy for Detection of Bone Metastases in Breast Cancer Patients. A Meta-Analysis. Surg. Oncol. 2013, 22, 86–91. [Google Scholar] [CrossRef] [PubMed]
- Arimura, A.; Sakai, K.; Kaneshiro, K.; Morisaki, T.; Hayashi, S.; Mizoguchi, K.; Yamada, M.; Kai, M.; Ono, M.; Nishio, K.; et al. TP53 and/or BRCA1 Mutations Based on CtDNA Analysis as Prognostic Biomarkers for Primary Triple-Negative Breast Cancer. Cancers 2024, 16, 1184. [Google Scholar] [CrossRef] [PubMed]
- Jia, J.; Huang, B.; Zhuang, Z.; Chen, S. Circulating Tumor DNA as Prognostic Markers for Late Stage NSCLC with Bone Metastasis. Int. J. Biol. Markers 2018, 33, 222–230. [Google Scholar] [CrossRef]
- Ye, Y.; Luo, Z.; Shi, D. Use of Cell Free DNA as a Prognostic Biomarker in Non-Small Cell Lung Cancer Patients with Bone Metastasis. Int. J. Biol. Markers 2019, 34, 381–388. [Google Scholar] [CrossRef] [PubMed]
- Song, S.; Zhu, Y.; Zhang, X.; Chen, S.; Liu, S. Prognostic Values of Long Noncoding RNA in Bone Metastasis of Prostate Cancer: A Systematic Review and Meta-Analysis. Front. Oncol. 2023, 13, 1085464. [Google Scholar] [CrossRef]
- Xiang, Z.-L.; Zeng, Z.-C.; Tang, Z.-Y.; Fan, J.; He, J.; Zeng, H.-Y.; Zhu, X.-D. Potential Prognostic Biomarkers for Bone Metastasis from Hepatocellular Carcinoma. Oncologist 2011, 16, 1028–1039. [Google Scholar] [CrossRef]
- Maroni, P.; Gomarasca, M.; Lombardi, G. Long Non-Coding RNAs in Bone Metastasis: Progresses and Perspectives as Potential Diagnostic and Prognostic Biomarkers. Front. Endocrinol. 2023, 14, 1156494. [Google Scholar] [CrossRef]
- Coleman, R. Bone-Targeted Agents and Metastasis Prevention. Cancers 2022, 14, 3640. [Google Scholar] [CrossRef] [PubMed]
- Yang, M.; Yu, X. Management of Bone Metastasis with Intravenous Bisphosphonates in Breast Cancer: A Systematic Review and Meta-Analysis of Dosing Frequency. Support. Care Cancer 2020, 28, 2533–2540. [Google Scholar] [CrossRef]
- So, A.; Chin, J.; Fleshner, N.; Saad, F. Management of Skeletal-Related Events in Patients with Advanced Prostate Cancer and Bone Metastases: Incorporating New Agents into Clinical Practice. Can. Urol. Assoc. J. 2012, 6, 465–470. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
- Hoff, B.A.; Brisset, J.-C.; Galbán, S.; Van Dort, M.; Smith, D.C.; Reichert, Z.R.; Jacobson, J.A.; Luker, G.D.; Chenevert, T.L.; Ross, B.D. Multimodal Imaging Provides Insight into Targeted Therapy Response in Metastatic Prostate Cancer to the Bone. Am. J. Nucl. Med. Mol. Imaging 2018, 8, 189–199. [Google Scholar] [PubMed]
- Bai, R.; Lv, Z.; Xu, D.; Cui, J. Predictive Biomarkers for Cancer Immunotherapy with Immune Checkpoint Inhibitors. Biomark. Res. 2020, 8, 34. [Google Scholar] [CrossRef]
- Simonaggio, A.; Epaillard, N.; Pobel, C.; Moreira, M.; Oudard, S.; Vano, Y.-A. Tumor Microenvironment Features as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors (ICI) in Metastatic Clear Cell Renal Cell Carcinoma (mccRCC). Cancers 2021, 13, 231. [Google Scholar] [CrossRef]
- Yin, X.; Song, Y.; Deng, W.; Blake, N.; Luo, X.; Meng, J. Potential Predictive Biomarkers in Antitumor Immunotherapy: Navigating the Future of Antitumor Treatment and Immune Checkpoint Inhibitor Efficacy. Front. Oncol. 2024, 14, 1483454. [Google Scholar] [CrossRef] [PubMed]
- Tang, Y.; Li, Y.; Zhang, L.; Tong, G.; Ou, Z.; Wang, Z.; Zhang, H.; Qiao, G. Pathologic Complete Response to Preoperative Immunotherapy in a Lung Adenocarcinoma Patient with Bone Metastasis: A Case Report. Thorac. Cancer 2020, 11, 1094–1098. [Google Scholar] [CrossRef] [PubMed]
- Savci-Heijink, C.D.; Halfwerk, H.; Koster, J.; van de Vijver, M.J. A novel gene expression signature for bone metastasis in breast carcinomas. Breast Cancer Res. Treat. 2016, 156, 249–259. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
- Westbrook, J.A.; Wood, S.L.; Cairns, D.A.; McMahon, K.; Gahlaut, R.; Thygesen, H.; Shires, M.; Roberts, S.; Marshall, H.; Oliva, M.R.; et al. Identification and Validation of DOCK4 as a Potential Biomarker for Risk of Bone Metastasis Development in Patients with Early Breast Cancer. J. Pathol. 2019, 247, 381–391. [Google Scholar] [CrossRef]
- Bhadresha, K.P.; Patel, M.; Jain, N.K.; Rawal, R.M. A Predictive Biomarker Panel for Bone Metastases: Liquid Biopsy Approach. J. Bone Oncol. 2021, 29, 100374. [Google Scholar] [CrossRef]
- Zhao, K.; Jia, C.; Wang, J.; Shi, W.; Wang, X.; Song, Y.; Peng, C. Exosomal Hsa-miR-151a-3p and Hsa-miR-877-5p Are Potential Novel Biomarkers for Predicting Bone Metastasis in Lung Cancer. Aging 2023, 15, 14864–14888. [Google Scholar] [CrossRef]
- Paule, B.; Deslandes, E.; Le Mouel, S.P.E.; Bastien, L.; Podgorniak, M.-P.; Allory, Y.; de la Taille, A.; Menashi, S.; Calvo, F.; Mourah, S. Identification of a Novel Biomarker Signature Associated with Risk for Bone Metastasis in Patients with Renal Cell Carcinoma. Int. J. Biol. Markers 2010, 25, 112–115. [Google Scholar] [CrossRef]
- Feng, C.; Zhan, Y.; Shao, H.; Wang, Z.; Zhu, S. Postoperative Expressions of TRACP5b and CA125 in Patients with Breast Cancer and Their Values for Monitoring Bone Metastasis. J. BUON 2020, 25, 688–695. [Google Scholar] [PubMed]
- Chung, Y.-C.; Ku, C.-H.; Chao, T.-Y.; Yu, J.-C.; Chen, M.M.; Lee, S.-H. Tartrate-Resistant Acid Phosphatase 5b Activity Is a Useful Bone Marker for Monitoring Bone Metastases in Breast Cancer Patients after Treatment. Cancer Epidemiol. Biomark. Prev. 2006, 15, 424–428. [Google Scholar] [CrossRef] [PubMed]
- Martín-Fernández, M.; Valencia, K.; Zandueta, C.; Ormazábal, C.; Martínez-Canarias, S.; Lecanda, F.; de la Piedra, C. The Usefulness of Bone Biomarkers for Monitoring Treatment Disease: A Comparative Study in Osteolytic and Osteosclerotic Bone Metastasis Models. Transl. Oncol. 2017, 10, 255–261. [Google Scholar] [CrossRef]
- Song, M.-K.; Park, S.I.; Cho, S.W. Circulating Biomarkers for Diagnosis and Therapeutic Monitoring in Bone Metastasis. J. Bone Miner. Metab. 2023, 41, 337–344. [Google Scholar] [CrossRef]
- Satam, H.; Joshi, K.; Mangrolia, U.; Waghoo, S.; Zaidi, G.; Rawool, S.; Thakare, R.P.; Banday, S.; Mishra, A.K.; Das, G.; et al. Next-Generation Sequencing Technology: Current Trends and Advancements. Biology 2023, 12, 997, Correct in Biology 2024, 13, 286. https://doi.org/10.3390/biology13050286. [Google Scholar] [CrossRef]
- Waarts, M.R.; Stonestrom, A.J.; Park, Y.C.; Levine, R.L. Targeting Mutations in Cancer. J. Clin. Investig. 2022, 132, e154943. [Google Scholar] [CrossRef] [PubMed]
- Martins, I.; Ribeiro, I.P.; Jorge, J.; Gonçalves, A.C.; Sarmento-Ribeiro, A.B.; Melo, J.B.; Carreira, I.M. Liquid Biopsies: Applications for Cancer Diagnosis and Monitoring. Genes 2021, 12, 349. [Google Scholar] [CrossRef]
- Ma, S.; Zhou, M.; Xu, Y.; Gu, X.; Zou, M.; Abudushalamu, G.; Yao, Y.; Fan, X.; Wu, G. Clinical Application and Detection Techniques of Liquid Biopsy in Gastric Cancer. Mol. Cancer 2023, 22, 7. [Google Scholar] [CrossRef]
- Mathew, A.; Joseph, S.; Boby, J.; Benny, S.; Veedu, J.; Rajappa, S.; Rohatgi, N.; Sirohi, B.; Jain, R.; Agarwala, V.; et al. Clinical Benefit of Comprehensive Genomic Profiling for Advanced Cancers in India. JCO Glob. Oncol. 2022, 8, e2100421. [Google Scholar] [CrossRef]
- Chawla, A.; Janku, F.; Wheler, J.J.; Miller, V.A.; Ryan, J.; Anhorn, R.; Zhou, Z.; Signorovitch, J. Estimated Cost of Anticancer Therapy Directed by Comprehensive Genomic Profiling in a Single-Center Study. JCO Precis. Oncol. 2018, 2, 1–11. [Google Scholar] [CrossRef]
- Remon, J.; Steuer, C.E.; Ramalingam, S.S.; Felip, E. Osimertinib and Other Third-Generation EGFR TKI in EGFR-Mutant NSCLC Patients. Ann. Oncol. 2018, 29, i20–i27. [Google Scholar] [CrossRef] [PubMed]
- El Helali, A.; Lam, T.-C.; Ko, E.Y.-L.; Shih, D.J.H.; Chan, C.K.; Wong, C.H.L.; Wong, J.W.H.; Cheung, L.W.T.; Lau, J.K.S.; Liu, A.P.Y.; et al. The Impact of the Multi-Disciplinary Molecular Tumour Board and Integrative next Generation Sequencing on Clinical Outcomes in Advanced Solid Tumours. Lancet Reg. Health West. Pac. 2023, 36, 100775. [Google Scholar] [CrossRef]
- Park, J.J.H.; Hsu, G.; Siden, E.G.; Thorlund, K.; Mills, E.J. An Overview of Precision Oncology Basket and Umbrella Trials for Clinicians. CA Cancer J. Clin. 2020, 70, 125–137. [Google Scholar] [CrossRef]
- Cai, Z.; Chiu, J.-F.; He, Q.-Y. Application of Proteomics in the Study of Tumor Metastasis. Genom. Proteom. Bioinform. 2004, 2, 152–166. [Google Scholar] [CrossRef]
- Bussard, K.M.; Gay, C.V.; Mastro, A.M. The Bone Microenvironment in Metastasis; What Is Special about Bone? Cancer Metastasis Rev. 2008, 27, 41–55. [Google Scholar] [CrossRef]
- Anborgh, P.H.; Mutrie, J.C.; Tuck, A.B.; Chambers, A.F. Role of the Metastasis-Promoting Protein Osteopontin in the Tumour Microenvironment. J. Cell. Mol. Med. 2010, 14, 2037–2044. [Google Scholar] [CrossRef] [PubMed]
- Bădilă, A.E.; Rădulescu, D.M.; Niculescu, A.-G.; Grumezescu, A.M.; Rădulescu, M.; Rădulescu, A.R. Recent Advances in the Treatment of Bone Metastases and Primary Bone Tumors: An Up-to-Date Review. Cancers 2021, 13, 4229. [Google Scholar] [CrossRef]
- Huang, Y.; Gong, M.; Chen, H.; Deng, C.; Zhu, X.; Lin, J.; Huang, A.; Xu, Y.; Tai, Y.; Song, G.; et al. Mass Spectrometry–Based Proteomics Identifies Serpin B9 as a Key Protein in Promoting Bone Metastases in Lung Cancer. Mol. Cancer Res. 2024, 22, 402–414. [Google Scholar] [CrossRef] [PubMed]
- Peng, Z.; Ahsan, N.; Yang, Z. Proteomics Analysis of Interactions between Drug-Resistant and Drug-Sensitive Cancer Cells: Comparative Studies of Monoculture and Coculture Cell Systems. J. Proteome Res. 2024, 23, 2608–2618. [Google Scholar] [CrossRef]
- Benito, J.; Ramirez, M.S.; Millward, N.Z.; Velez, J.; Harutyunyan, K.G.; Lu, H.; Shi, Y.; Matre, P.; Jacamo, R.; Ma, H.; et al. Hypoxia-Activated Prodrug TH-302 Targets Hypoxic Bone Marrow Niches in Preclinical Leukemia Models. Clin. Cancer Res. 2016, 22, 1687–1698. [Google Scholar] [CrossRef]
- Yoo, H.C.; Yu, Y.C.; Sung, Y.; Han, J.M. Glutamine Reliance in Cell Metabolism. Exp. Mol. Med. 2020, 52, 1496–1516. [Google Scholar] [CrossRef] [PubMed]
- Tufail, M.; Jiang, C.-H.; Li, N. Altered Metabolism in Cancer: Insights into Energy Pathways and Therapeutic Targets. Mol. Cancer 2024, 23, 203. [Google Scholar] [CrossRef]
- San-Millán, I.; Brooks, G.A. Reexamining Cancer Metabolism: Lactate Production for Carcinogenesis Could Be the Purpose and Explanation of the Warburg Effect. Carcinogenesis 2017, 38, 119–133. [Google Scholar] [CrossRef] [PubMed]
- Jin, J.; Byun, J.-K.; Choi, Y.-K.; Park, K.-G. Targeting Glutamine Metabolism as a Therapeutic Strategy for Cancer. Exp. Mol. Med. 2023, 55, 706–715. [Google Scholar] [CrossRef] [PubMed]
- Lu, J.; Hu, D.; Zhang, Y.; Ma, C.; Shen, L.; Shuai, B. Current Comprehensive Understanding of Denosumab (the RANKL Neutralizing Antibody) in the Treatment of Bone Metastasis of Malignant Tumors, Including Pharmacological Mechanism and Clinical Trials. Front. Oncol. 2023, 13, 1133828. [Google Scholar] [CrossRef]
- Jiang, L.; Cui, X.; Ma, H.; Tang, X. Comparison of Denosumab and Zoledronic Acid for the Treatment of Solid Tumors and Multiple Myeloma with Bone Metastasis: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials. J. Orthop. Surg. 2021, 16, 400. [Google Scholar] [CrossRef]
- Link, T.; Blohmer, J.-U.; Schmitt, W.D.; Kuhlmann, J.D.; Just, M.; Untch, M.; Stotzer, O.; Fasching, P.A.; Thill, M.; Reinisch, M.; et al. RANK Expression as an Independent Predictor for Response to Neoadjuvant Chemotherapy in Luminal-Like Breast Cancer: A Translational Insight from the GeparX Trial. Clin. Cancer Res. 2023, 29, 4606–4612. [Google Scholar] [CrossRef]
- Pant, S.; Schuler, M.; Iyer, G.; Witt, O.; Doi, T.; Qin, S.; Tabernero, J.; Reardon, D.A.; Massard, C.; Minchom, A.; et al. Tumour-Agnostic Efficacy and Safety of Erdafitinib in Patients with Advanced Solid Tumours with Prespecified FGFR Alterations: RAGNAR Phase 2 Study Primary Analysis. Lancet Oncol. 2023, 24, 925–935. [Google Scholar] [CrossRef]
- Glaviano, A.; Foo, A.S.C.; Lam, H.Y.; Yap, K.C.H.; Jacot, W.; Jones, R.H.; Eng, H.; Nair, M.G.; Makvandi, P.; Geoerger, B.; et al. PI3K/AKT/mTOR Signaling Transduction Pathway and Targeted Therapies in Cancer. Mol. Cancer 2023, 22, 138. [Google Scholar] [CrossRef]
- Zhu, Y.; She, J.; Sun, R.; Yan, X.; Huang, X.; Wang, P.; Li, B.; Sun, X.; Wang, C.; Jiang, K. Impact of Bone Metastasis on Prognosis in Non-Small Cell Lung Cancer Patients Treated with Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. Front. Immunol. 2024, 15, 1493773. [Google Scholar] [CrossRef]
- Peters, S.; Camidge, D.R.; Shaw, A.T.; Gadgeel, S.; Ahn, J.S.; Kim, D.-W.; Ou, S.-H.I.; Pérol, M.; Dziadziuszko, R.; Rosell, R.; et al. Alectinib versus Crizotinib in Untreated ALK-Positive Non–Small-Cell Lung Cancer. N. Engl. J. Med. 2017, 377, 829–838. [Google Scholar] [CrossRef]
- Chang, X.; Liu, Z.; Man, S.; Roys, A.; Li, Z.; Zuo, D.; Wu, Y. Metastasis Manners and the Underlying Mechanisms of ALK and ROS1 Rearrangement Lung Cancer and Current Possible Therapeutic Strategies. RSC Adv. 2019, 9, 17921–17932. [Google Scholar] [CrossRef] [PubMed]
- Polascik, T.J. Bisphosphonates in Oncology: Evidence for the Prevention of Skeletal Events in Patients with Bone Metastases. Drug Des. Devel. Ther. 2009, 3, 27–40. [Google Scholar] [CrossRef]
- Li, X.; Valdes, S.A.; Alzhrani, R.F.; Hufnagel, S.; Hursting, S.D.; Cui, Z. Zoledronic Acid-Containing Nanoparticles With Minimum Premature Release Show Enhanced Activity Against Extraskeletal Tumor. ACS Appl. Mater. Interfaces 2019, 11, 7311–7319. [Google Scholar] [CrossRef] [PubMed]
- Sun, W.; Han, Y.; Li, Z.; Ge, K.; Zhang, J. Bone-Targeted Mesoporous Silica Nanocarrier Anchored by Zoledronate for Cancer Bone Metastasis. Langmuir ACS J. Surf. Colloids 2016, 32, 9237–9244. [Google Scholar] [CrossRef] [PubMed]
- Parker, C.; Nilsson, S.; Heinrich, D.; Helle, S.I.; O’Sullivan, J.M.; Fosså, S.D.; Chodacki, A.; Wiechno, P.; Logue, J.; Seke, M.; et al. Alpha Emitter Radium-223 and Survival in Metastatic Prostate Cancer. N. Engl. J. Med. 2013, 369, 213–223. [Google Scholar] [CrossRef]
- Sartor, O.; de Bono, J.; Chi, K.N.; Fizazi, K.; Herrmann, K.; Rahbar, K.; Tagawa, S.T.; Nordquist, L.T.; Vaishampayan, N.; El-Haddad, G.; et al. Lutetium-177–PSMA-617 for Metastatic Castration-Resistant Prostate Cancer. N. Engl. J. Med. 2021, 385, 1091–1103. [Google Scholar] [CrossRef]
- Aggarwal, R.; Starzinski, S.; de Kouchkovsky, I.; Koshkin, V.; Bose, R.; Chou, J.; Desai, A.; Kwon, D.; Kaushal, S.; Trihy, L.; et al. Single-Dose 177Lu-PSMA-617 Followed by Maintenance Pembrolizumab in Patients with Metastatic Castration-Resistant Prostate Cancer: An Open-Label, Dose-Expansion, Phase 1 Trial. Lancet Oncol. 2023, 24, 1266–1276. [Google Scholar] [CrossRef]
- Nassar, A.H.; Mouw, K.W.; Jegede, O.; Shinagare, A.B.; Kim, J.; Liu, C.-J.; Pomerantz, M.; Harshman, L.C.; Van Allen, E.M.; Wei, X.X.; et al. A Model Combining Clinical and Genomic Factors to Predict Response to PD-1/PD-L1 Blockade in Advanced Urothelial Carcinoma. Br. J. Cancer 2020, 122, 555–563. [Google Scholar] [CrossRef]
- Labidi, S.; Meti, N.; Barua, R.; Li, M.; Riromar, J.; Jiang, D.M.; Fallah-Rad, N.; Sridhar, S.S.; Del Rincon, S.V.; Pezo, R.C.; et al. Clinical Variables Associated with Immune Checkpoint Inhibitor Outcomes in Patients with Metastatic Urothelial Carcinoma: A Multicentre Retrospective Cohort Study. BMJ Open 2024, 14, e081480. [Google Scholar] [CrossRef]
- Arellano, D.L.; Juárez, P.; Verdugo-Meza, A.; Almeida-Luna, P.S.; Corral-Avila, J.A.; Drescher, F.; Olvera, F.; Jiménez, S.; Elzey, B.D.; Guise, T.A.; et al. Bone Microenvironment-Suppressed T Cells Increase Osteoclast Formation and Osteolytic Bone Metastases in Mice. J. Bone Miner. Res. 2022, 37, 1446–1463. [Google Scholar] [CrossRef] [PubMed]
- Sheykhhasan, M.; Ahmadieh-Yazdi, A.; Vicidomini, R.; Poondla, N.; Tanzadehpanah, H.; Dirbaziyan, A.; Mahaki, H.; Manoochehri, H.; Kalhor, N.; Dama, P. CAR T Therapies in Multiple Myeloma: Unleashing the Future. Cancer Gene Ther. 2024, 31, 667–686. [Google Scholar] [CrossRef]
- Pascual-Pasto, G.; McIntyre, B.; Hines, M.G.; Giudice, A.M.; Garcia-Gerique, L.; Hoffmann, J.; Mishra, P.; Matlaga, S.; Lombardi, S.; Shraim, R.; et al. CAR T-Cell-Mediated Delivery of Bispecific Innate Immune Cell Engagers for Neuroblastoma. Nat. Commun. 2024, 15, 7141. [Google Scholar] [CrossRef] [PubMed]
- Mateo, J.; McKay, R.; Abida, W.; Aggarwal, R.; Alumkal, J.; Alva, A.; Feng, F.; Gao, X.; Graff, J.; Hussain, M.; et al. Accelerating Precision Medicine in Metastatic Prostate Cancer. Nat. Cancer 2020, 1, 1041–1053. [Google Scholar] [CrossRef] [PubMed]
- Mangat, P.K.; Halabi, S.; Bruinooge, S.S.; Garrett-Mayer, E.; Alva, A.; Janeway, K.A.; Stella, P.J.; Voest, E.; Yost, K.J.; Perlmutter, J.; et al. Rationale and Design of the Targeted Agent and Profiling Utilization Registry Study. JCO Precis. Oncol. 2018, 2, 1–14. [Google Scholar] [CrossRef]
- Flaherty, K.T.; Gray, R.; Chen, A.; Li, S.; Patton, D.; Hamilton, S.R.; Williams, P.M.; Mitchell, E.P.; Iafrate, A.J.; Sklar, J.; et al. The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design. JNCI J. Natl. Cancer Inst. 2020, 112, 1021–1029. [Google Scholar] [CrossRef]
- de Bono, J.; Mateo, J.; Fizazi, K.; Saad, F.; Shore, N.; Sandhu, S.; Chi, K.N.; Sartor, O.; Agarwal, N.; Olmos, D.; et al. Olaparib for Metastatic Castration-Resistant Prostate Cancer. N. Engl. J. Med. 2020, 382, 2091–2102. [Google Scholar] [CrossRef]
- Renfro, L.A.; Mallick, H.; An, M.-W.; Sargent, D.J.; Mandrekar, S.J. Clinical Trial Designs Incorporating Predictive Biomarkers. Cancer Treat. Rev. 2016, 43, 74–82. [Google Scholar] [CrossRef]
- Coleman, R.; Hadji, P.; Body, J.-J.; Santini, D.; Chow, E.; Terpos, E.; Oudard, S.; Bruland, Ø.; Flamen, P.; Kurth, A.; et al. Bone Health in Cancer: ESMO Clinical Practice Guidelines. Ann. Oncol. 2020, 31, 1650–1663. [Google Scholar] [CrossRef]
- Faiella, E.; Santucci, D.; Calabrese, A.; Russo, F.; Vadalà, G.; Zobel, B.B.; Soda, P.; Iannello, G.; de Felice, C.; Denaro, V. Artificial Intelligence in Bone Metastases: An MRI and CT Imaging Review. Int. J. Environ. Res. Public Health 2022, 19, 1880. [Google Scholar] [CrossRef]
- Ma, L.; Guo, H.; Zhao, Y.; Liu, Z.; Wang, C.; Bu, J.; Sun, T.; Wei, J. Liquid Biopsy in Cancer: Current Status, Challenges and Future Prospects. Signal Transduct. Target. Ther. 2024, 9, 336. [Google Scholar] [CrossRef]
- Wang, K.; Wang, X.; Pan, Q.; Zhao, B. Liquid Biopsy Techniques and Pancreatic Cancer: Diagnosis, Monitoring, and Evaluation. Mol. Cancer 2023, 22, 167. [Google Scholar] [CrossRef]
- Diel, I.; Ansorge, S.; Hohmann, D.; Giannopoulou, C.; Niepel, D.; Intorcia, M. Real-World Use of Denosumab and Bisphosphonates in Patients with Solid Tumours and Bone Metastases in Germany. Support. Care Cancer 2020, 28, 5223–5233. [Google Scholar] [CrossRef] [PubMed]
- Hildenbrand, N.; Thiele, W.; Tripel, E.; Renkawitz, T.; Kermani, F.; El-Fiqi, A.; Westhauser, F. Fe-Doped 45S5 Bioactive Glass Compositions Impair the Metabolic Activity and Proliferation of Metastatic Human Breast Cancer Cells in Vitro. Biomed. Mater. 2024, 19, 055028. [Google Scholar] [CrossRef]
- Kitagawa, T.; Kitagawa, Y.; Aoyagi, Y.; Majima, T. Difficulties Nurses Report in Caring for Patients with Bone Metastases and Their Expectations after Participating in a Bone Metastasis Cancer Board: A Questionnaire Study. J. Nippon Med. Sch. 2024, 91, 198–206. [Google Scholar] [CrossRef] [PubMed]
- Cleeland, C.; von Moos, R.; Walker, M.S.; Wang, Y.; Gao, J.; Chavez-MacGregor, M.; Liede, A.; Arellano, J.; Balakumaran, A.; Qian, Y. Burden of Symptoms Associated with Development of Metastatic Bone Disease in Patients with Breast Cancer. Support. Care Cancer 2016, 24, 3557–3565. [Google Scholar] [CrossRef] [PubMed]
- Garcia Perlaza, J.; Aziziyeh, R.; Zhou, A.; De Sousa Barbosa, V.; Amaya, J.; Caporale, J.; Alva, M.E.; Forero, J.; Tanaka, S.; Suri, G.; et al. The Burden of Skeletal-Related Events in Four Latin American Countries: Argentina, Brazil, Colombia, and Mexico. J. Med. Econ. 2021, 24, 983–992. [Google Scholar] [CrossRef]
- Knapp, B.J.; Cittolin-Santos, G.F.; Flanagan, M.E.; Grandhi, N.; Gao, F.; Samson, P.P.; Govindan, R.; Morgensztern, D. Incidence and Risk Factors for Bone Metastases at Presentation in Solid Tumors. Front. Oncol. 2024, 14, 1392667. [Google Scholar] [CrossRef]
- Baldessari, C.; Pipitone, S.; Molinaro, E.; Cerma, K.; Fanelli, M.; Nasso, C.; Oltrecolli, M.; Pirola, M.; D’Agostino, E.; Pugliese, G.; et al. Bone Metastases and Health in Prostate Cancer: From Pathophysiology to Clinical Implications. Cancers 2023, 15, 1518. [Google Scholar] [CrossRef]
- Svensson, E.; Christiansen, C.F.; Ulrichsen, S.P.; Rørth, M.R.; Sørensen, H.T. Survival after Bone Metastasis by Primary Cancer Type: A Danish Population-Based Cohort Study. BMJ Open 2017, 7, e016022. [Google Scholar] [CrossRef]
- Song, X.; Wei, C.; Li, X. The Signaling Pathways Associated With Breast Cancer Bone Metastasis. Front. Oncol. 2022, 12, 855609. [Google Scholar] [CrossRef] [PubMed]
- Gentile, M.; Centonza, A.; Lovero, D.; Palmirotta, R.; Porta, C.; Silvestris, F.; D’Oronzo, S. Application of “Omics” Sciences to the Prediction of Bone Metastases from Breast Cancer: State of the Art. J. Bone Oncol. 2020, 26, 100337. [Google Scholar] [CrossRef] [PubMed]
- Hunter, K.W.; Amin, R.; Deasy, S.; Ha, N.-H.; Wakefield, L. Genetic Insights into the Morass of Metastatic Heterogeneity. Nat. Rev. Cancer 2018, 18, 211–223. [Google Scholar] [CrossRef]
- Wood, S.L.; Brown, J.E. Personal Medicine and Bone Metastases: Biomarkers, Micro-RNAs and Bone Metastases. Cancers 2020, 12, 2109. [Google Scholar] [CrossRef] [PubMed]
- Aguilar-Mahecha, A.; Kuzyk, M.A.; Domanski, D.; Borchers, C.H.; Basik, M. The Effect of Pre-Analytical Variability on the Measurement of MRM-MS-Based Mid- to High-Abundance Plasma Protein Biomarkers and a Panel of Cytokines. PLoS ONE 2012, 7, e38290. [Google Scholar] [CrossRef] [PubMed]
- De Gramont, A.; Watson, S.; Ellis, L.M.; Rodón, J.; Tabernero, J.; De Gramont, A.; Hamilton, S.R. Pragmatic Issues in Biomarker Evaluation for Targeted Therapies in Cancer. Nat. Rev. Clin. Oncol. 2015, 12, 197–212. [Google Scholar] [CrossRef]
- Drugan, T.; Leucuța, D. Evaluating Novel Biomarkers for Personalized Medicine. Diagnostics 2024, 14, 587. [Google Scholar] [CrossRef]
- Chae, Y.K.; Arya, A.; Chiec, L.; Shah, H.; Rosenberg, A.; Patel, S.; Raparia, K.; Choi, J.; Wainwright, D.A.; Villaflor, V.; et al. Challenges and Future of Biomarker Tests in the Era of Precision Oncology: Can We Rely on Immunohistochemistry (IHC) or Fluorescence in Situ Hybridization (FISH) to Select the Optimal Patients for Matched Therapy? Oncotarget 2017, 8, 100863–100898. [Google Scholar] [CrossRef]
- Park, Y.; Koh, J.; Na, H.Y.; Kwak, Y.; Lee, K.-W.; Ahn, S.-H.; Park, D.J.; Kim, H.-H.; Lee, H.S. PD-L1 Testing in Gastric Cancer by the Combined Positive Score of the 22C3 PharmDx and SP263 Assay with Clinically Relevant Cut-Offs. Cancer Res. Treat. 2020, 52, 661–670. [Google Scholar] [CrossRef]
- Tsimberidou, A.M.; Sireci, A.; Dumanois, R.; Pritchard, D. Strategies to Address the Clinical Practice Gaps Affecting the Implementation of Personalized Medicine in Cancer Care. JCO Oncol. Pract. 2024, 20, 761–766. [Google Scholar] [CrossRef]
- Haider, M.-T.; Taipaleenmäki, H. Targeting the Metastatic Bone Microenvironment by MicroRNAs. Front. Endocrinol. 2018, 9, 202. [Google Scholar] [CrossRef] [PubMed]
- Zhao, Q.; Luo, F.; Ma, J.; Yu, X. Bone Metastasis-Related MicroRNAs: New Targets for Treatment? Curr. Cancer Drug Targets 2015, 15, 716–725. [Google Scholar] [CrossRef] [PubMed]
- Dawalibi, A.; Alosaimi, A.A.; Mohammad, K.S. Balancing the Scales: The Dual Role of Interleukins in Bone Metastatic Microenvironments. Int. J. Mol. Sci. 2024, 25, 8163. [Google Scholar] [CrossRef] [PubMed]
- Ellington, A.A.; Kullo, I.J.; Bailey, K.R.; Klee, G.G. Antibody-Based Protein Multiplex Platforms: Technical and Operational Challenges. Clin. Chem. 2010, 56, 186–193. [Google Scholar] [CrossRef]
- Pennello, G.A. Analytical and Clinical Evaluation of Biomarkers Assays: When Are Biomarkers Ready for Prime Time? Clin. Trials Lond. Engl. 2013, 10, 666–676. [Google Scholar] [CrossRef]
- Hirt-Minkowski, P.; Schaub, S. Urine CXCL10 as a Biomarker in Kidney Transplantation. Curr. Opin. Organ Transplant. 2024, 29, 138–143. [Google Scholar] [CrossRef]
- Hess, R.; Laaff, H. Biorepositories and Biomarker Development: Regulatory Challenges. Biomark. J. 2017, 3, 15. [Google Scholar] [CrossRef]
- Bundell, C.; Tan, E.; Brusch, A.; Wienholt, L. Quality Assurance and Quality Control Highlight the Variability between and within Assay Methods. Pathology 2019, 51, S129–S130. [Google Scholar] [CrossRef]
- Andreoletti, M.; Haller, L.; Vayena, E.; Blasimme, A. Mapping the Ethical Landscape of Digital Biomarkers: A Scoping Review. PLOS Digit. Health 2024, 3, e0000519. [Google Scholar] [CrossRef]
- Kim, S.Y.H.; Karlawish, J.; Berkman, B.E. Ethics of Genetic and Biomarker Test Disclosures in Neurodegenerative Disease Prevention Trials. Neurology 2015, 84, 1488–1494. [Google Scholar] [CrossRef]
- Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
- Landeck, L.; Lessl, M.; Reischl, J.; Busch, A.; Carrigan, P.; Gottwald, M.; Reinke, P.; Asadullah, K. Collaboration for Success: The Value of Strategic Collaborations for Precision Medicine and Biomarker Development. Adv. Precis. Med. 2016, 1, 25–33. [Google Scholar] [CrossRef]
- Chapman, C.R.; Mehta, K.S.; Parent, B.; Caplan, A.L. Genetic Discrimination: Emerging Ethical Challenges in the Context of Advancing Technology. J. Law Biosci. 2019, 7, lsz016. [Google Scholar] [CrossRef] [PubMed]
- Green, R.C.; Lautenbach, D.; McGuire, A.L. GINA, Genetic Discrimination, and Genomic Medicine. N. Engl. J. Med. 2015, 372, 397–399. [Google Scholar] [CrossRef] [PubMed]
- Chen, D. Ethical Frameworks of Informed Consent in the Age of Pediatric Precision Medicine. Camb. Prisms Precis. Med. 2024, 2, e6. [Google Scholar] [CrossRef] [PubMed]
- Lehmann, L.S.; Snyder Sulmasy, L.; Burke, W.; Opole, I.O.; Deep, N.N.; Abraham, G.M.; Burnett, J.; Callister, T.B.; Carney, J.K.; Cooney, T.G.; et al. Ethical Considerations in Precision Medicine and Genetic Testing in Internal Medicine Practice: A Position Paper From the American College of Physicians. Ann. Intern. Med. 2022, 175, 1322–1323. [Google Scholar] [CrossRef]
- Baynam, G.; Gomez, R.; Jain, R. Stigma Associated with Genetic Testing for Rare Diseases—Causes and Recommendations. Front. Genet. 2024, 15, 1335768. [Google Scholar] [CrossRef]
- Ioannou, K.I.; Constantinidou, A.; Chatzittofis, A. Genetic Testing in Psychiatry, the Perceptions of Healthcare Workers and Patients: A Mini Review. Front. Public Health 2024, 12, 1466585. [Google Scholar] [CrossRef]
- Moffitt, L.R.; Karimnia, N.; Wilson, A.L.; Stephens, A.N.; Ho, G.-Y.; Bilandzic, M. Challenges in Implementing Comprehensive Precision Medicine Screening for Ovarian Cancer. Curr. Oncol. 2024, 31, 8023–8038. [Google Scholar] [CrossRef]
Biomarker | Category | Cancer Type(s) | Clinical Relevance | Limitations |
---|---|---|---|---|
CTCs | Diagnostic, Prognostic, Monitoring | Breast, Prostate, Lung, NETs | Associated with metastases and survival; aids in diagnosis and treatment monitoring | Detection challenges due to heterogeneity and low abundance; EMT subtypes may escape detection |
ctDNA | Diagnostic, Prognostic, Monitoring | Breast, Prostate, Lung | Non-invasive tumor profiling; tracks mutations and resistance; correlates with prognosis | Low levels in bone-dominant disease; false negatives; lack of standard thresholds |
BALP | Diagnostic | Prostate | Marker of osteoblastic activity; diagnostic performance comparable to imaging | May be influenced by non-malignant bone conditions |
P1NP | Diagnostic | Breast, Prostate | Indicates osteoblastic activity in metastatic lesions | Specificity limited due to elevations in other bone conditions |
P1CP | Prognostic | Prostate | Linked to metastatic progression and survival | Requires further validation |
Osteocalcin | Diagnostic | General | Reflects bone turnover | Affected by systemic conditions; low specificity |
CTX | Diagnostic, Monitoring | Breast, Prostate | Assesses osteoclastic activity; reduced post-treatment | Does not always correlate with tumor burden |
NTX | Diagnostic, Prognostic | Breast, Prostate | Correlates with disease severity and skeletal events | Affected by physiological bone turnover |
DPD | Diagnostic | Breast, Prostate, Lung | Urinary marker of bone resorption | Variable results due to urinary excretion differences |
TRACP-5b | Diagnostic, Monitoring | Breast, Prostate | Reliable resorption marker; unaffected by renal function | Assay standardization and specificity remain challenges |
Imaging biomarkers (PET/CT, MRI, etc.) | Diagnostic | Prostate, Breast, Lung | Enhance metastasis detection and staging | Cost, accessibility, and modality-specific limitations |
Bone matrix proteins (OPN, BSP) | Prognostic | Prostate, Lung | Elevated levels correlate with poor prognosis | Influenced by non-malignant conditions; needs validation |
CTGF | Prognostic | HCC | Associated with increased risk of bone metastasis | Not validated across cancer types |
IL-11 | Prognostic | HCC | Linked to osteoclastogenesis and worse outcomes | Cancer-type-specific relevance |
MMP-1 | Prognostic | HCC | Marker for bone metastasis risk | Requires further clinical validation |
lncRNAs (MALAT1, HOTAIR, ANCR, ZEB1-AS1) | Prognostic | Breast, Prostate, NSCLC | Linked to EMT, metastasis, and prognosis | Detection and sample stability are challenging |
Bisphosphonate response | Predictive | Breast, Prostate | Response stratified by MAF status and menopausal state | Varying response across cancers; more markers needed |
RANKL inhibitors (Denosumab) | Predictive | Prostate | Delays SREs; useful in treatment response prediction | No clear OS benefit; limited specificity |
PD-L1 | Predictive | NSCLC, Kidney, Melanoma | Correlates with ICI treatment response | Immunosuppressive bone environment reduces utility |
TMB | Predictive | NSCLC | High TMB = better ICI response | Lower TMB in bone mets limits predictive value |
MSI | Predictive | Colorectal, Gastric | Predicts ICI response | Limited evidence in bone mets |
KRAS/TP53 (lung) | Predictive | NSCLC | Co-mutations linked to improved immunotherapy outcomes | Requires broader validation |
PTEN/STK11 loss | Predictive | NSCLC | Associated with resistance to ICIs | Negative predictive marker; not universal |
DOCK4 | Predictive | Breast | Identifies patients who benefit from bisphosphonates | Effect may be negated by zoledronic acid |
Exosomal miRNAs (miR-151a-3p, miR-877-5p) | Predictive | Lung | Differentiate patients with and without bone mets | Isolation and reproducibility challenges |
VEGFR-1, VEGFR-2, HIF-1α, uPA, PAI-1 | Predictive | RCC | Upregulated in bone mets; indicate aggressive behavior | Early-phase research; needs broader trials |
aBSI (Automated Bone Scan Index) | Prognostic | Prostate | Quantitative scan-based biomarker; predicts survival | Expensive; requires standardization |
Biomarker (Sample/Modality) | Dominant Pathway/Target | Matched Drug or Clinical Decision | Highest Level of Evidence | Primary Utility |
---|---|---|---|---|
RANKL: OPG ratio (serum/tissue) | RANK–RANKL–OPG osteoclast axis | Start or intensify denosumab to delay skeletal-related events | Phase III; guideline endorsed for breast and prostate SRE prevention | Predictive/ Monitoring |
C-telopeptide (CTX) (serum) | Bone resorption | Gauge response to bisphosphonates (zoledronic acid); falling CTX = biochemical response | Prospective biomarker–response correlations in metastatic models | Monitoring |
TRACP-5b (serum) | Osteoclast activity | Early signal of bisphosphonate efficacy or biochemical progression | Multi-institutional real-world data (prostate) and breast cohorts | Monitoring |
PD-L1 TPS/CPS (tissue) | PD-1/PD-L1 checkpoint | Select pembrolizumab, nivolumab, atezolizumab, etc. | Multiple Phase III ICI trials; FDA-approved companion assays in NSCLC and RCC | Predictive |
ctDNA EGFR/KRAS/ALK (plasma) | Driver mutations and resistance mechanisms | Choose or switch EGFR/ALK TKIs (e.g., osimertinib) or clinical-trial enrollment | ≥Phase II concordance/utility studies in metastatic NSCLC | Predictive/ Monitoring |
DOCK4 over-expression (tumor) | Cytoskeletal GEF; metastasis biology | Identifies early-stage breast patients most likely to benefit from adjuvant bisphosphonate chemoprevention | AZURE tissue-microarray correlative study (exploratory) | Predictive |
Automated Bone-Scan Index (aBSI) (99mTc-MDP planar scan) | Quantitative tumor burden on bone scintigraphy | Prognostic stratification; informs timing of radium-223 or systemic intensification | Phase III secondary-analysis validation (mCRPC) | Prognostic |
Serum VEGF (±uNTx) | Angiogenesis/hypoxia | Consider bevacizumab (±TKI) in high-VEGF, bone-dominant settings; monitor anti-angiogenic response | Pre-clinical bone-metastasis models; ongoing clinical trials | Monitoring/ Exploratory |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Elshimy, Y.; Alkhatib, A.R.; Atassi, B.; Mohammad, K.S. Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications. Biomedicines 2025, 13, 1160. https://doi.org/10.3390/biomedicines13051160
Elshimy Y, Alkhatib AR, Atassi B, Mohammad KS. Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications. Biomedicines. 2025; 13(5):1160. https://doi.org/10.3390/biomedicines13051160
Chicago/Turabian StyleElshimy, Youssef, Abdul Rahman Alkhatib, Bilal Atassi, and Khalid S. Mohammad. 2025. "Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications" Biomedicines 13, no. 5: 1160. https://doi.org/10.3390/biomedicines13051160
APA StyleElshimy, Y., Alkhatib, A. R., Atassi, B., & Mohammad, K. S. (2025). Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications. Biomedicines, 13(5), 1160. https://doi.org/10.3390/biomedicines13051160