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Elkholi IE, Rose AAN, Aguirre-Ghiso JA, Côté JF. How can we integrate the biology of breast cancer cell dormancy into clinical practice? Cancer Cell 2024; 42:1147-1151. [PMID: 38906154 DOI: 10.1016/j.ccell.2024.05.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/18/2024] [Accepted: 05/28/2024] [Indexed: 06/23/2024]
Abstract
Clinical practice and clinical research heavily rely on primary tumors, circulating tumor DNA, and/or overt metastases as sources of material for predicting or investigating breast cancer metastatic relapses. However, these approaches do not consider emerging fundamentals in the biology of metastatic dormancy and relapse. Conversely, the field of metastatic dormancy often discounts key clinical factors influencing relapse dynamics (e.g., patient's age and overall health condition). Here, we delineate these disparities into four gaps and propose a framework to bridge them.
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Affiliation(s)
- Islam E Elkholi
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada; Lady Davis Institute, Sir Mortimer B. Davis Jewish General Hospital, Montreal, QC, Canada; Montreal Clinical Research Institute (IRCM), Montreal, QC, Canada; Molecular Biology Programs, Université de Montréal, Montreal, QC, Canada.
| | - April A N Rose
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada; Lady Davis Institute, Sir Mortimer B. Davis Jewish General Hospital, Montreal, QC, Canada
| | - Julio A Aguirre-Ghiso
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, USA; Cancer Dormancy and Tumor Microenvironment Institute, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Bronx, NY, USA; Ruth L. & David S. Gottesman Institute for Stem Cell Research & Regenerative Medicine, Albert Einstein College of Medicine, Bronx, NY, USA; Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jean-François Côté
- Montreal Clinical Research Institute (IRCM), Montreal, QC, Canada; Molecular Biology Programs, Université de Montréal, Montreal, QC, Canada; Department of Biochemistry and Molecular Medicine, Université de Montréal, Montreal, QC, Canada; Department of Anatomy and Cell Biology, McGill University, Montreal, QC, Canada.
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2
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Hunt AL, Khan I, Wu AML, Makohon-Moore SC, Hood BL, Conrads KA, Abulez T, Ogata J, Mitchell D, Gist G, Oliver J, Wei D, Chung MA, Rahman S, Bateman NW, Zhang W, Conrads TP, Steeg PS. The murine metastatic microenvironment of experimental brain metastases of breast cancer differs by host age in vivo: a proteomic study. Clin Exp Metastasis 2024; 41:229-249. [PMID: 37917186 DOI: 10.1007/s10585-023-10233-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 09/07/2023] [Indexed: 11/04/2023]
Abstract
Breast cancer in young patients is known to exhibit more aggressive biological behavior and is associated with a less favorable prognosis than the same disease in older patients, owing in part to an increased incidence of brain metastases. The mechanistic explanations behind these findings remain poorly understood. We recently reported that young mice, in comparison to older mice, developed significantly greater brain metastases in four mouse models of triple-negative and luminal B breast cancer. Here we have performed a quantitative mass spectrometry-based proteomic analysis to identify proteins potentially contributing to age-related disparities in the development of breast cancer brain metastases. Using a mouse hematogenous model of brain-tropic triple-negative breast cancer (MDA-MB-231BR), we harvested subpopulations of tumor metastases, the tumor-adjacent metastatic microenvironment, and uninvolved brain tissues via laser microdissection followed by quantitative proteomic analysis using high resolution mass spectrometry to characterize differentially abundant proteins potentially contributing to age-dependent rates of brain metastasis. Pathway analysis revealed significant alterations in signaling pathways, particularly in the metastatic microenvironment, modulating tumorigenesis, metabolic processes, inflammation, and neuronal signaling. Tenascin C (TNC) was significantly elevated in all laser microdissection (LMD) enriched compartments harvested from young mice relative to older hosts, which was validated and confirmed by immunoblot analysis of whole brain lysates. Additional in vitro studies including migration and wound-healing assays demonstrated TNC as a positive regulator of tumor cell migration. These results provide important new insights regarding microenvironmental factors, including TNC, as mechanisms contributing to the increased brain cancer metastatic phenotype observed in young breast cancer patients.
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Affiliation(s)
- Allison L Hunt
- Women's Health Integrated Research Center, Inova Women's Service Line, Inova Health System, 3289 Woodburn Rd, Annandale, VA, 22042, USA
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
| | - Imran Khan
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA
| | - Alex M L Wu
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA
- Zymeworks Inc, Vancouver, BC, V5T 1G4, Canada
| | - Sasha C Makohon-Moore
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Brian L Hood
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Kelly A Conrads
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Tamara Abulez
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Jonathan Ogata
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Dave Mitchell
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Glenn Gist
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Julie Oliver
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
| | - Debbie Wei
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA
| | - Monika A Chung
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA
- Rutgers New Jersey Medical School, 185 S Orange Ave, Newark, NJ, 07103, USA
| | - Samiur Rahman
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA
| | - Nicholas W Bateman
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, 6720A Rockledge Drive, Suite 100, Bethesda, MD, 20817, USA
- Department of Surgery, The John P. Murtha Cancer Center Research Program, Uniformed Services University, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA
| | - Wei Zhang
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA
| | - Thomas P Conrads
- Women's Health Integrated Research Center, Inova Women's Service Line, Inova Health System, 3289 Woodburn Rd, Annandale, VA, 22042, USA.
- Gynecologic Cancer Center of Excellence and the Women's Health Integrated Research Center, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University and Walter Reed National Military Medical Center, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.
- Department of Surgery, The John P. Murtha Cancer Center Research Program, Uniformed Services University, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA.
| | - Patricia S Steeg
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37, Room 1126, Bethesda, MD, 20892, USA.
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Liu K, Huang AL, Chen XQ, Wu SG. Patterns of distant metastasis and survival outcomes in de novo metastatic breast cancer according to age groups. Front Endocrinol (Lausanne) 2024; 15:1385756. [PMID: 38752173 PMCID: PMC11094241 DOI: 10.3389/fendo.2024.1385756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 04/12/2024] [Indexed: 05/18/2024] Open
Abstract
Background Is de novo metastatic breast cancer (dnMBC) the same disease in the elderly as in younger breast cancer remains unclear. This study aimed to determine the metastatic patterns and survival outcomes in dnMBC according to age groups. Methods We included patients from the Surveillance Epidemiology and End Results program. Chi-square test, multivariate logistic regression analyses, and multivariate Cox regression models were used for statistical analyses. Results A total of 17719 patients were included. There were 3.6% (n=638), 18.6% (n=3290), 38.0% (n=6725), and 39.9% (n=7066) of patients aged <35, 35-49, 50-64, and ≥65 years, respectively. Older patients had a significantly higher risk of lung metastasis and a significantly lower risk of liver metastasis. There were 19.1%, 25.6%, 30.9%, and 35.7% of patients with lung metastasis in those aged <35, 35-49, 50-64, and ≥65 years, respectively. Moreover, the proportion of liver metastasis was 37.6%, 29.5%, 26.3%, and 19.2%, respectively. Age was the independent prognostic factor associated with breast cancer-specific survival (BCSS) and overall survival (OS). Those aged 50-64 years had significantly inferior BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. Patients aged ≥65 years also had significantly lower BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. However, similar outcomes were found between those aged 35-49 and <35 years. Conclusion Our study suggests that different age groups may affect the metastatic patterns among patients with dnMBC and the survival of younger patients is more favorable than those of older patients.
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Affiliation(s)
- Ke Liu
- Xiamen Key Laboratory of Clinical Efficacy and Evidence Studies of Traditional Chinese Medicine, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - An-Le Huang
- Department of Gastrointestinal Oncology Surgery, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Xue-Qin Chen
- Xiamen Key Laboratory of Clinical Efficacy and Evidence Studies of Traditional Chinese Medicine, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - San-Gang Wu
- Department of Radiation Oncology, Xiamen Cancer Quality Control Center, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
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4
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Wen J, Zhao B, Yang Z, Erus G, Skampardoni I, Mamourian E, Cui Y, Hwang G, Bao J, Boquet-Pujadas A, Zhou Z, Veturi Y, Ritchie MD, Shou H, Thompson PM, Shen L, Toga AW, Davatzikos C. The genetic architecture of multimodal human brain age. Nat Commun 2024; 15:2604. [PMID: 38521789 PMCID: PMC10960798 DOI: 10.1038/s41467-024-46796-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 03/06/2024] [Indexed: 03/25/2024] Open
Abstract
The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine .
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Affiliation(s)
- Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ioanna Skampardoni
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mamourian
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yuhan Cui
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gyujoon Hwang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jingxuan Bao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Zhen Zhou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yogasudha Veturi
- Department of Biobehavioral Health and Statistics, Penn State University, University Park, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Haochang Shou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Zhou D, Gong Z, Wu D, Ma C, Hou L, Niu X, Xu T. Harnessing immunotherapy for brain metastases: insights into tumor-brain microenvironment interactions and emerging treatment modalities. J Hematol Oncol 2023; 16:121. [PMID: 38104104 PMCID: PMC10725587 DOI: 10.1186/s13045-023-01518-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/01/2023] [Indexed: 12/19/2023] Open
Abstract
Brain metastases signify a deleterious milestone in the progression of several advanced cancers, predominantly originating from lung, breast and melanoma malignancies, with a median survival timeframe nearing six months. Existing therapeutic regimens yield suboptimal outcomes; however, burgeoning insights into the tumor microenvironment, particularly the immunosuppressive milieu engendered by tumor-brain interplay, posit immunotherapy as a promising avenue for ameliorating brain metastases. In this review, we meticulously delineate the research advancements concerning the microenvironment of brain metastases, striving to elucidate the panorama of their onset and evolution. We encapsulate three emergent immunotherapeutic strategies, namely immune checkpoint inhibition, chimeric antigen receptor (CAR) T cell transplantation and glial cell-targeted immunoenhancement. We underscore the imperative of aligning immunotherapy development with in-depth understanding of the tumor microenvironment and engendering innovative delivery platforms. Moreover, the integration with established or avant-garde physical methodologies and localized applications warrants consideration in the prevailing therapeutic schema.
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Affiliation(s)
- Dairan Zhou
- Department of Neurosurgery, Changzheng Hospital, Naval Medical University, 415 Fengyang Road, Huangpu District, Shanghai, 200003, People's Republic of China
| | - Zhenyu Gong
- Department of Neurosurgery, Klinikum Rechts Der Isar, Technical University of Munich, Munich, 81675, Germany
| | - Dejun Wu
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, People's Republic of China
| | - Chao Ma
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, Anhui, People's Republic of China
| | - Lijun Hou
- Department of Neurosurgery, Changzheng Hospital, Naval Medical University, 415 Fengyang Road, Huangpu District, Shanghai, 200003, People's Republic of China
| | - Xiaomin Niu
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, 241 Huaihai West Road, Xuhui District, Shanghai, 200030, People's Republic of China.
| | - Tao Xu
- Department of Neurosurgery, Changzheng Hospital, Naval Medical University, 415 Fengyang Road, Huangpu District, Shanghai, 200003, People's Republic of China.
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Zhao Y, Gu S, Li L, Zhao R, Xie S, Zhang J, Zhou R, Tu L, Jiang L, Zhang S, Ma S. A novel risk signature for predicting brain metastasis in patients with lung adenocarcinoma. Neuro Oncol 2023; 25:2207-2220. [PMID: 37379245 PMCID: PMC10708939 DOI: 10.1093/neuonc/noad115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Indexed: 06/30/2023] Open
Abstract
BACKGROUND Brain metastasis (BM) are a devastating consequence of lung cancer. This study was aimed to screen risk factors for predicting BM. METHODS Using an in vivo BM preclinical model, we established a series of lung adenocarcinoma (LUAD) cell subpopulations with different metastatic ability. Quantitative proteomics analysis was used to screen and identify the differential protein expressing map among subpopulation cells. Q-PCR and Western-blot were used to validate the differential proteins in vitro. The candidate proteins were measured in LUAD tissue samples (n = 81) and validated in an independent TMA cohort (n = 64). A nomogram establishment was undertaken by performing multivariate logistic regression analysis. RESULTS The quantitative proteomics analysis, qPCR and Western blot assay implied a five-gene signature that might be key proteins associated with BM. In multivariate analysis, the occurrence of BM was associated with age ≤ 65 years, high expressions of NES and ALDH6A1. The nomogram showed an area under the receiver operating characteristic curve (AUC) of 0.934 (95% CI, 0.881-0.988) in the training set. The validation set showed a good discrimination with an AUC of 0.719 (95% CI, 0.595-0.843). CONCLUSIONS We have established a tool that is able to predict occurrence of BM in LUAD patients. Our model based on both clinical information and protein biomarkers will help to screen patient in high-risk population of BM, so as to facilitate preventive intervention in this part of the population.
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Affiliation(s)
- Yanyan Zhao
- Department of Translational Medicine Research Center, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, China
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, China
| | - Shen Gu
- Department of Translational Medicine Research Center, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, China
| | - Lingjie Li
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, China
| | - Ruping Zhao
- Department of Radiotherapy, Shanghai Jiahui International Hospital, China
| | - Shujun Xie
- Department of Translational Medicine Research Center, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, China
| | - Jingjing Zhang
- Department of Translational Medicine Research Center, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, China
| | - Rongjing Zhou
- Department of Pathology, Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, China
| | - Linglan Tu
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, China
| | - Lei Jiang
- Department of Pharmacology and Department of Pharmacy of the Second Affiliated Hospital, NHC and CAMS Key Laboratory of Medical Neurobiology, Department of Anatomy, Zhejiang University School of Medicine, China
| | - Shirong Zhang
- Department of Translational Medicine Research Center, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, China
| | - Shenglin Ma
- Department of Translational Medicine Research Center, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, China
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, China
- Department of Oncology, Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, China
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7
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Nolan E, Kang Y, Malanchi I. Mechanisms of Organ-Specific Metastasis of Breast Cancer. Cold Spring Harb Perspect Med 2023; 13:a041326. [PMID: 36987584 PMCID: PMC10626265 DOI: 10.1101/cshperspect.a041326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
Cancer metastasis, or the development of secondary tumors in distant tissues, accounts for the vast majority of fatalities in patients with breast cancer. Breast cancer cells show a striking proclivity to metastasize to distinct organs, specifically the lung, liver, bone, and brain, where they face unique environmental pressures and a wide variety of tissue-resident cells that together create a strong barrier for tumor survival and growth. As a consequence, successful metastatic colonization is critically dependent on reciprocal cross talk between cancer cells and host cells within the target organ, a relationship that shapes the formation of a tumor-supportive microenvironment. Here, we discuss the mechanisms governing organ-specific metastasis in breast cancer, focusing on the intricate interactions between metastatic cells and specific niche cells within a secondary organ, and the remarkable adaptations of both compartments that cooperatively support cancer growth. More broadly, we aim to provide a framework for the microenvironmental prerequisites within each distinct metastatic site for successful breast cancer metastatic seeding and outgrowth.
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Affiliation(s)
- Emma Nolan
- Tumour Host Interaction laboratory, The Francis Crick Institute, NW1 1AT London, United Kingdom
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand
| | - Yibin Kang
- Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
- Ludwig Institute for Cancer Research Princeton Branch, Princeton, New Jersey 08544, USA
| | - Ilaria Malanchi
- Tumour Host Interaction laboratory, The Francis Crick Institute, NW1 1AT London, United Kingdom
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8
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Wen J, Zhao B, Yang Z, Erus G, Skampardoni I, Mamourian E, Cui Y, Hwang G, Bao J, Boquet-Pujadas A, Zhou Z, Veturi Y, Ritchie MD, Shou H, Thompson PM, Shen L, Toga AW, Davatzikos C. The Genetic Architecture of Multimodal Human Brain Age. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.13.536818. [PMID: 37333190 PMCID: PMC10274645 DOI: 10.1101/2023.04.13.536818] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The complex biological mechanisms underlying human brain aging remain incompletely understood, involving multiple body organs and chronic diseases. In this study, we used multimodal magnetic resonance imaging and artificial intelligence to examine the genetic architecture of the brain age gap (BAG) derived from gray matter volume (GM-BAG, N=31,557 European ancestry), white matter microstructure (WM-BAG, N=31,674), and functional connectivity (FC-BAG, N=32,017). We identified sixteen genomic loci that reached genome-wide significance (P-value<5×10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG showed the highest heritability enrichment for genetic variants in conserved regions, whereas WM-BAG exhibited the highest heritability enrichment in the 5' untranslated regions; oligodendrocytes and astrocytes, but not neurons, showed significant heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several exposure variables on brain aging, such as type 2 diabetes on GM-BAG (odds ratio=1.05 [1.01, 1.09], P-value=1.96×10-2) and AD on WM-BAG (odds ratio=1.04 [1.02, 1.05], P-value=7.18×10-5). Overall, our results provide valuable insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at the MEDICINE knowledge portal: https://labs.loni.usc.edu/medicine.
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Affiliation(s)
- Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Ioanna Skampardoni
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Elizabeth Mamourian
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yuhan Cui
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Gyujoon Hwang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Jingxuan Bao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | | | - Zhen Zhou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yogasudha Veturi
- Department of Biobehavioral Health and Statistics, Penn State University, University Park, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Haochang Shou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, California
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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9
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Ma W, Oliveira-Nunes MC, Xu K, Kossenkov A, Reiner BC, Crist RC, Hayden J, Chen Q. Type I interferon response in astrocytes promotes brain metastasis by enhancing monocytic myeloid cell recruitment. Nat Commun 2023; 14:2632. [PMID: 37149684 PMCID: PMC10163863 DOI: 10.1038/s41467-023-38252-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 04/20/2023] [Indexed: 05/08/2023] Open
Abstract
Cancer metastasis to the brain is a significant clinical problem. Metastasis is the consequence of favorable interactions between invaded cancer cells and the microenvironment. Here, we demonstrate that cancer-activated astrocytes create a sustained low-level activated type I interferon (IFN) microenvironment in brain metastatic lesions. We further confirm that the IFN response in astrocytes facilitates brain metastasis. Mechanistically, IFN signaling in astrocytes activates C-C Motif Chemokine Ligand 2 (CCL2) production, which further increases the recruitment of monocytic myeloid cells. The correlation between CCL2 and monocytic myeloid cells is confirmed in clinical brain metastasis samples. Lastly, genetically or pharmacologically inhibiting C-C Motif Chemokine Receptor 2 (CCR2) reduces brain metastases. Our study clarifies a pro-metastatic effect of type I IFN in the brain even though IFN response has been considered to have anti-tumor effects. Moreover, this work expands our understandings on the interactions between cancer-activated astrocytes and immune cells in brain metastasis.
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Affiliation(s)
- Weili Ma
- Immunology, Microenvironment and Metastasis Program, The Wistar Institute, Philadelphia, PA, 19104, USA
| | - Maria Cecília Oliveira-Nunes
- Immunology, Microenvironment and Metastasis Program, The Wistar Institute, Philadelphia, PA, 19104, USA
- Carisma Therapeutics, Philadelphia, PA, 19104, USA
| | - Ke Xu
- MD/PhD Program, Boston University School of Medicine, Boston, MA, 02215, USA
| | - Andrew Kossenkov
- Gene Expression & Regulation Program, The Wistar Institute, Philadelphia, PA, 19104, USA
| | - Benjamin C Reiner
- Department of Psychiatry, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Richard C Crist
- Department of Psychiatry, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James Hayden
- Imaging Shared Resource, The Wistar Institute, Philadelphia, PA, 19104, USA
| | - Qing Chen
- Immunology, Microenvironment and Metastasis Program, The Wistar Institute, Philadelphia, PA, 19104, USA.
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10
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Hebert JD, Neal JW, Winslow MM. Dissecting metastasis using preclinical models and methods. Nat Rev Cancer 2023; 23:391-407. [PMID: 37138029 DOI: 10.1038/s41568-023-00568-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/27/2023] [Indexed: 05/05/2023]
Abstract
Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them.
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Affiliation(s)
- Jess D Hebert
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Joel W Neal
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Monte M Winslow
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
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11
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Gao Y, Rosen JM, Zhang XHF. The tumor-immune ecosystem in shaping metastasis. Am J Physiol Cell Physiol 2023; 324:C707-C717. [PMID: 36717100 PMCID: PMC10027084 DOI: 10.1152/ajpcell.00132.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 01/03/2023] [Accepted: 01/25/2023] [Indexed: 02/01/2023]
Abstract
A better understanding of the mechanisms regulating cancer metastasis is critical to develop new therapies and decrease mortality. Emerging evidence suggests that the interactions between tumor cells and the host immune system play important roles in establishing metastasis. Tumor cells are able to recruit immune cells, which in turn promotes tumor cell invasion, intravasation, survival in circulation, extravasation, and colonization in different organs. The tumor-host immunological interactions also generate a premetastatic niche in distant organs which facilitates metastasis. In this review, we summarize the recent findings on how tumor cells and immune cells regulate each other to coevolve and promote the formation of metastases at the major organ sites of metastasis.
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Affiliation(s)
- Yang Gao
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, United States
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, United States
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, United States
| | - Jeffrey M Rosen
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, United States
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, United States
| | - Xiang H-F Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, United States
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, United States
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, United States
- McNair Medical Institute, Baylor College of Medicine, Houston, Texas, United States
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12
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Adler O, Zait Y, Cohen N, Blazquez R, Doron H, Monteran L, Scharff Y, Shami T, Mundhe D, Glehr G, Kanner AA, Horn S, Yahalom V, Haferkamp S, Hutchinson JA, Bleckmann A, Nahary L, Benhar I, Yust Katz S, Pukrop T, Erez N. Reciprocal interactions between innate immune cells and astrocytes facilitate neuroinflammation and brain metastasis via lipocalin-2. NATURE CANCER 2023; 4:401-418. [PMID: 36797502 DOI: 10.1038/s43018-023-00519-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/17/2023] [Indexed: 04/19/2023]
Abstract
Brain metastasis still encompass very grim prognosis and therefore understanding the underlying mechanisms is an urgent need toward developing better therapeutic strategies. We uncover the intricate interactions between recruited innate immune cells and resident astrocytes in the brain metastatic niche that facilitate metastasis of melanoma and breast cancer. We show that granulocyte-derived lipocalin-2 (LCN2) induces inflammatory activation of astrocytes, leading to myeloid cell recruitment to the brain. LCN2 is central to inducing neuroinflammation as its genetic targeting or bone-marrow transplantation from LCN2-/- mice was sufficient to attenuate neuroinflammation and inhibit brain metastasis. Moreover, high LCN2 levels in patient blood and brain metastases in multiple cancer types were strongly associated with disease progression and poor survival. Our findings uncover a previously unknown mechanism, establishing a central role for the reciprocal interactions between granulocytes and astrocytes in promoting brain metastasis and implicate LCN2 as a prognostic marker and potential therapeutic target.
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Affiliation(s)
- Omer Adler
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yael Zait
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Noam Cohen
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Raquel Blazquez
- Department of Internal Medicine III, Hematology and Medical Oncology, University Hospital Regensburg, Regensburg, Germany
| | - Hila Doron
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lea Monteran
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yeela Scharff
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tamar Shami
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Dhanashree Mundhe
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Gunther Glehr
- Department of Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Andrew A Kanner
- Department of Neurosurgery, Rabin Medical Center and Sackler Faculty of Medicine Tel Aviv University, Tel Aviv, Israel
| | - Suzana Horn
- Department of Pathology, Rabin Medical Center and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Vered Yahalom
- Blood Services & Apheresis Institute, Rabin Medical Center and Tel Aviv University, Tel Aviv, Israel
| | - Sebastian Haferkamp
- Department of Dermatology, University Hospital Regensburg, Regensburg, Germany
| | - James A Hutchinson
- Department of Surgery, University Hospital Regensburg, Regensburg, Germany
| | - Annalen Bleckmann
- Department of Hematology/Medical Oncology, University Medical Center Göttingen, Göttingen, Germany
- Medical Clinic A, Haematology, Haemostasiology, Oncology and Pulmonology, University Hospital Münster, Münster, Germany
- West German Cancer Center, University Hospital Münster, Münster, Germany
| | - Limor Nahary
- The Shmunis School of Biomedicine and Cancer Research, the George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Itai Benhar
- The Shmunis School of Biomedicine and Cancer Research, the George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Shlomit Yust Katz
- Neuro-Oncology Unit, Davidoff Cancer Center at Rabin Medical Center and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tobias Pukrop
- Department of Internal Medicine III, Hematology and Medical Oncology, University Hospital Regensburg, Regensburg, Germany
- Division of Personalized Tumor Therapy, Fraunhofer Institute for Toxicology and Experimental Medicine, Regensburg, Germany
| | - Neta Erez
- Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
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13
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Zheng X, Mu S, Wang L, Tao H, Huang D, Huang Z, Li X, Cui P, Li T, Liu Q, Hu Y. Factors for incidence risk and prognosis of synchronous brain metastases in pulmonary large cell carcinoma patients: a population-based study. BMC Pulm Med 2023; 23:12. [PMID: 36635639 PMCID: PMC9835350 DOI: 10.1186/s12890-023-02312-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 01/05/2023] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Patients with pulmonary large cell carcinoma (LCC) have a high incidence of synchronous brain metastases (SBM) and a poor prognosis. Our study was to evaluate the predictive and prognostic value of the clinical characteristics of pulmonary LCC patients with SBM at initial diagnosis by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. METHODS LCC patients, diagnosed from 2010 to 2019, were identified from the latest SEER database which was released in April 2022. Logistic regression and Cox regression were used to identify the predictive and prognostic factors for LCC patients with SBM. Propensity score matching (PSM) and Kaplan-Meier analyses were applied to assess different therapy modalities. RESULTS A total of 1375 LCC patients were enrolled in this study and 216 (15.7%) of them had SBM at the initial diagnosis. The median overall survival (OS) of LCC patients with SBM was 4 months. Multivariate Cox regression identified age 60-79 (OR 0.57; 95% CI 0.41-0.78; p < 0.001), age ≥ 80 (OR 0.23; 95% CI 0.12-0.45; p < 0.001) and bone metastases (OR 1.75; 95% CI 1.22-2.51; p < 0.001) as significant independent predictors for developing SBM. Multivariable Cox regression revealed that age 60-79, T stage, bone metastases and chemotherapy were independent prognostic factor for OS. The surgery combined with chemotherapy and radiotherapy group, in which all patients were N0 stage and had no other site-specific metastases, exhibited the best median OS of 15 months. CONCLUSIONS LCC patients with age < 60 or bone metastases were more likely to have SBM at initial diagnosis. Age, T stage, bone metastases and chemotherapy were independent prognostic factors for OS of LCC patients with SBM. Highly selected patients might achieve the best survival benefit from surgery combined with chemotherapy and radiotherapy.
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Affiliation(s)
- Xuan Zheng
- grid.488137.10000 0001 2267 2324Medical School of Chinese PLA, Beijing, China ,grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Shuai Mu
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Lijie Wang
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Haitao Tao
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Di Huang
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Ziwei Huang
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Xiaoyan Li
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Pengfei Cui
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Tao Li
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Qingyan Liu
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
| | - Yi Hu
- grid.414252.40000 0004 1761 8894Department of Oncology, The First Medical Center of PLA General Hospital, Beijing, China
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14
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Recent Advances in the Aging Microenvironment of Breast Cancer. Cancers (Basel) 2022; 14:cancers14204990. [PMID: 36291773 PMCID: PMC9599409 DOI: 10.3390/cancers14204990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary The incidence of breast cancer has increased rapidly in recent years. Aging is one of the risk factors for advanced breast cancer. More and more studies have been conducted on the influence of the aging microenvironment on breast cancer. In this review, we summarize the effects of physical changes in the aging microenvironment, senescence-associated secretory phenotypes, and senescent stromal cells on the initiation and progression of breast cancer and the underlying mechanisms. In addition, we also discuss potential targets for senotherapeutics and senescence-inducing agents in the aging microenvironment of breast cancer. We hope this review can provide some directions for future research on the aging microenvironment in breast cancer. Abstract Aging is one of the risk factors for advanced breast cancer. With the increasing trend toward population aging, it is important to study the effects of aging on breast cancer in depth. Cellular senescence and changes in the aging microenvironment in vivo are the basis for body aging and death. In this review, we focus on the influence of the aging microenvironment on breast cancer. Increased breast extracellular matrix stiffness in the aging breast extracellular matrix can promote the invasion of breast cancer cells. The role of senescence-associated secretory phenotypes (SASPs) such as interleukin-6 (IL-6), IL-8, and matrix metalloproteases (MMPs), in breast cancer cell proliferation, invasion, and metastasis is worthy of exploration. Furthermore, the impact of senescent fibroblasts, adipocytes, and endothelial cells on the mammary matrix is discussed in detail. We also list potential targets for senotherapeutics and senescence-inducing agents in the aging microenvironment of breast cancer. In conclusion, this review offers an overview of the influence of the aging microenvironment on breast cancer initiation and progression, with the aim of providing some directions for future research on the aging microenvironment in breast cancer.
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15
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Malla R, Padmaraju V, Kundrapu DB. Tumor-associated macrophages: Potential target of natural compounds for management of breast cancer. Life Sci 2022; 301:120572. [PMID: 35489567 DOI: 10.1016/j.lfs.2022.120572] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 12/15/2022]
Abstract
A large body of experimental research reveals that tumor-associated macrophages (TAMs) are the major immunosuppressor cells in the breast tumor microenvironment (TME). The infiltration of macrophages is correlated with inverse outcomes like disease-free survival and overall survival of cancer patients. They are responsible for heterogeneity, metastasis, and drug resistance. Further, their density in tumor beds is correlated with stage and therapy response. The current review is aimed at summarizing mechanisms and signaling pathways that modulate immune-suppressive phenotype and expansion of TAMs. The review presents an overview of the interdependence of tumor cells and TAMs in TME to promote metastasis, drug resistance and immune suppressive phenotype. This review also presents the potential natural compounds that modulate the immune-suppressive functions of TAMs and their signaling pathways. Finally, this review provides nanotechnology approaches for the targeted delivery of natural products. This review shed light on BC management including clinical studies on the prognostic relevance of TAMs and natural compounds that sensitizes BC.
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Affiliation(s)
- RamaRao Malla
- Cancer Biology Laboratory, Dept. of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam 531001, Andhra Pradesh, India; Dept of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam 531001, Andhra Pradesh, India.
| | - Vasudevaraju Padmaraju
- Dept of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam 531001, Andhra Pradesh, India
| | - Durga Bhavani Kundrapu
- Cancer Biology Laboratory, Dept. of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam 531001, Andhra Pradesh, India; Dept of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam 531001, Andhra Pradesh, India
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16
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Cowan MN, Sethi I, Harris TH. Microglia in CNS infections: insights from Toxoplasma gondii and other pathogens. Trends Parasitol 2022; 38:217-229. [PMID: 35039238 PMCID: PMC8852251 DOI: 10.1016/j.pt.2021.12.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/11/2022]
Abstract
Microglia, the resident immune cells of the central nervous system (CNS), are poised to respond to neuropathology. Microglia play multiple roles in maintaining homeostasis and promoting inflammation in numerous disease states. The study of microglial innate immune programs has largely focused on exploring neurodegenerative disease states with the use of genetic targeting approaches. Our understanding of how microglia participate in immune responses against pathogens is just beginning to take shape. Here, we review existing animal models of CNS infection, with a focus on how microglial physiology and inflammatory processes control protozoan and viral infections of the brain. We further discuss how microglial participation in over-exuberant immune responses can drive immunopathology that is detrimental to CNS health and homeostasis.
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Affiliation(s)
- Maureen N. Cowan
- Center for Brain Immunology and Glia, Department of Neuroscience, University of Virginia, Charlottesville, VA, United States
| | - Ish Sethi
- Center for Brain Immunology and Glia, Department of Neuroscience, University of Virginia, Charlottesville, VA, United States
| | - Tajie H. Harris
- Center for Brain Immunology and Glia, Department of Neuroscience, University of Virginia, Charlottesville, VA, United States,Correspondence: (T. H. Harris)
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