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De Wispelaere W, Annibali D, Tuyaerts S, Lambrechts D, Amant F. Resistance to Immune Checkpoint Blockade in Uterine Leiomyosarcoma: What Can We Learn from Other Cancer Types? Cancers (Basel) 2021; 13:cancers13092040. [PMID: 33922556 PMCID: PMC8122870 DOI: 10.3390/cancers13092040] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/19/2021] [Accepted: 04/20/2021] [Indexed: 12/23/2022] Open
Abstract
The onset of immune checkpoint blockade (ICB) therapy over the last decade has transformed the therapeutic landscape in oncology. ICB has shown unprecedented clinical activity and durable responses in a variety of difficult-to-treat cancers. However, despite these promising long-term responses, a majority of patients fail to respond to single-agent therapy, demonstrating primary or acquired resistance. Uterine leiomyosarcoma (uLMS) is a rare high-risk gynecological cancer with very limited treatment options. Despite research indicating a strong potential for ICB in uLMS, a clinical trial assessing the response to immunotherapy with single-agent nivolumab in advanced-stage uLMS showed no clinical benefit. Many mechanisms of resistance to ICB have been characterized in a variety of tumor types, and many more continue to be uncovered. However, the mechanisms of resistance to ICB in uLMS remain largely unexplored. By elucidating and targeting mechanisms of resistance, treatments can be tailored to improve clinical outcomes. Therefore, in this review we will explore what is known about the immunosuppressive microenvironment of uLMS, link these data to possible resistance mechanisms extrapolated from other cancer types, and discuss potential therapeutic strategies to overcome resistance.
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Affiliation(s)
- Wout De Wispelaere
- Department of Oncology, KU Leuven (University of Leuven) and Leuven Cancer Institute (LKI), 3000 Leuven, Belgium; (W.D.W.); (D.A.); (S.T.)
| | - Daniela Annibali
- Department of Oncology, KU Leuven (University of Leuven) and Leuven Cancer Institute (LKI), 3000 Leuven, Belgium; (W.D.W.); (D.A.); (S.T.)
- Division of Oncogenomics, Antoni Van Leeuwenhoek—Netherlands Cancer Institute (AvL-NKI), 1066 CX Amsterdam, The Netherlands
| | - Sandra Tuyaerts
- Department of Oncology, KU Leuven (University of Leuven) and Leuven Cancer Institute (LKI), 3000 Leuven, Belgium; (W.D.W.); (D.A.); (S.T.)
- Laboratory of Medical and Molecular Oncology (LMMO), Department of Medical Oncology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven (University of Leuven), 3000 Leuven, Belgium;
- VIB Center for Cancer Biology, Flemish Institute for Biotechnology (VIB), 3000 Leuven, Belgium
| | - Frédéric Amant
- Department of Oncology, KU Leuven (University of Leuven) and Leuven Cancer Institute (LKI), 3000 Leuven, Belgium; (W.D.W.); (D.A.); (S.T.)
- Centre for Gynecologic Oncology Amsterdam (CGOA), Antoni Van Leeuwenhoek—Netherlands Cancer Institute, University Medical Center (UMC), 1066 CX Amsterdam, The Netherlands
- Department of Obstetrics and Gynecology, University Hospitals Leuven (UZ Leuven), 3000 Leuven, Belgium
- Correspondence:
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Sahly NN, Banaganapalli B, Sahly AN, Aligiraigri AH, Nasser KK, Shinawi T, Mohammed A, Alamri AS, Bondagji N, Elango R, Shaik NA. Molecular differential analysis of uterine leiomyomas and leiomyosarcomas through weighted gene network and pathway tracing approaches. Syst Biol Reprod Med 2021; 67:209-220. [PMID: 33685300 DOI: 10.1080/19396368.2021.1876179] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Uterine smooth muscular neoplastic growths like benign leiomyomas (UL) and metastatic leiomyosarcomas (ULMS) share similar clinical symptoms, radiological and histological appearances making their clinical distinction a difficult task. Therefore, the objective of this study is to identify key genes and pathways involved in transformation of UL to ULMS through molecular differential analysis. Global gene expression profiles of 25 ULMS, 25 UL, and 29 myometrium (Myo) tissues generated on Affymetrix U133A 2.0 human genome microarrays were analyzed by deploying robust statistical, molecular interaction network, and pathway enrichment methods. The comparison of expression signals across Myo vs UL, Myo vs ULMS, and UL vs ULMS groups identified 249, 1037, and 716 significantly expressed genes, respectively (p ≤ 0.05). The analysis of 249 DEGs from Myo vs UL confirms multistage dysregulation of various key pathways in extracellular matrix, collagen, cell contact inhibition, and cytokine receptors transform normal myometrial cells to benign leiomyomas (p value ≤ 0.01). The 716 DEGs between UL vs ULMS were found to affect cell cycle, cell division related Rho GTPases and PI3K signaling pathways triggering uncontrolled growth and metastasis of tumor cells (p value ≤ 0.01). Integration of gene networking data, with additional parameters like estimation of mutation burden of tumors and cancer driver gene identification, has led to the finding of 4 hubs (JUN, VCAN, TOP2A, and COL1A1) and 8 bottleneck genes (PIK3R1, MYH11, KDR, ESR1, WT1, CCND1, EZH2, and CDKN2A), which showed a clear distinction in their distribution pattern among leiomyomas and leiomyosarcomas. This study provides vital clues for molecular distinction of UL and ULMS which could further assist in identification of specific diagnostic markers and therapeutic targets.Abbreviations UL: Uterine Leiomyomas; ULMS: Uterine Leiomyosarcoma; Myo: Myometrium; DEGs: Differential Expressed Genes; RMA: Robust Multiarray Average; DC: Degree of Centrality; BC: Betweenness of Centrality; CGC: Cancer Gene Census; FDR: False Discovery Rate; TCGA: Cancer Genome Atlas; BP: Biological Process; CC: Cellular Components; MF: Molecular Function; PPI: Protein-Protein Interaction.
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Affiliation(s)
- Nora Naif Sahly
- Department of Obstetrics and Gynecology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Babajan Banaganapalli
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ahmed N Sahly
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia.,Department of Neurosciences, King Faisal Specialist Hospital and Research Centre, Jeddah, Saudi Arabia
| | - Ali H Aligiraigri
- Department of Hematology, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
| | - Khalidah K Nasser
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia.,Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Thoraia Shinawi
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Arif Mohammed
- Department of Biology, College of Science, University of Jeddah, Jeddah, Saudi Arabia
| | - Abdulhakeem S Alamri
- Department of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia.,Centre of Biomedical Sciences Research (CBSR), Deanship of Scientific Research, Taif University, Saudi Arabia
| | - Nabeel Bondagji
- Department of Obstetrics and Gynecology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ramu Elango
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Noor Ahmad Shaik
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
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Candidate Biomarkers for Specific Intraoperative Near-Infrared Imaging of Soft Tissue Sarcomas: A Systematic Review. Cancers (Basel) 2021; 13:cancers13030557. [PMID: 33535618 PMCID: PMC7867119 DOI: 10.3390/cancers13030557] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 01/16/2021] [Accepted: 01/21/2021] [Indexed: 12/27/2022] Open
Abstract
Simple Summary Near-infrared imaging of tumors during surgery facilitates the oncologic surgeon to distinguish malignant from healthy tissue. The technique is based on fluorescent tracers binding to tumor biomarkers on malignant cells. Currently, there are no clinically available fluorescent tracers that specifically target soft tissue sarcomas. This review searched the literature to find candidate biomarkers for soft tissue sarcomas, based on clinically used therapeutic antibodies. The search revealed 7 biomarkers: TEM1, VEGFR-1, EGFR, VEGFR-2, IGF-1R, PDGFRα, and CD40. These biomarkers are abundantly present on soft tissue sarcoma tumor cells and are already being targeted with humanized monoclonal antibodies. The conjugation of these antibodies with a fluorescent dye will yield in specific tracers for image-guided surgery of soft tissue sarcomas to improve the success rates of tumor resections. Abstract Surgery is the mainstay of treatment for localized soft tissue sarcomas (STS). The curative treatment highly depends on complete tumor resection, as positive margins are associated with local recurrence (LR) and prognosis. However, determining the tumor margin during surgery is challenging. Real-time tumor-specific imaging can facilitate complete resection by visualizing tumor tissue during surgery. Unfortunately, STS specific tracers are presently not clinically available. In this review, STS-associated cell surface-expressed biomarkers, which are currently already clinically targeted with monoclonal antibodies for therapeutic purposes, are evaluated for their use in near-infrared fluorescence (NIRF) imaging of STS. Clinically targeted biomarkers in STS were extracted from clinical trial registers and a PubMed search was performed. Data on biomarker characteristics, sample size, percentage of biomarker-positive STS samples, pattern of biomarker expression, biomarker internalization features, and previous applications of the biomarker in imaging were extracted. The biomarkers were ranked utilizing a previously described scoring system. Eleven cell surface-expressed biomarkers were identified from which 7 were selected as potential biomarkers for NIRF imaging: TEM1, VEGFR-1, EGFR, VEGFR-2, IGF-1R, PDGFRα, and CD40. Promising biomarkers in common and aggressive STS subtypes are TEM1 for myxofibrosarcoma, TEM1, and PDGFRα for undifferentiated soft tissue sarcoma and EGFR for synovial sarcoma.
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An Y, Wang Q, Sun F, Zhang G, Wang F, Zhang L, Li Y, Ren W, Zhu W, Li Y, Ji S, Guo X. OSucs: An Online Prognostic Biomarker Analysis Tool for Uterine Carcinosarcoma. Genes (Basel) 2020; 11:genes11091040. [PMID: 32899312 PMCID: PMC7563768 DOI: 10.3390/genes11091040] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 08/24/2020] [Accepted: 09/02/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Uterine carcinosarcoma (UCS) is a type of rare and aggressive tumor. The standard treatment for UCS involves surgical treatment followed by radiochemotherapy. Clinical outcomes of UCS patients are poor due to high metastasis and relapse rate. Therefore, new targeted therapy strategies for UCS are needed. Because UCS is highly heterogenous, it is critical to identify and develop prognostic biomarkers to distinguish molecular subtypes of UCS for better treatment guidance. METHODS Using gene expression profiles and clinical follow-up data, we developed an online consensus survival analysis tool named OSucs. This web tool allows researchers to conveniently analyze the prognostic abilities of candidate genes in UCS. RESULTS To test the reliability of this server, we analyzed five previously reported prognostic biomarkers, all of which showed significant prognostic impacts. In addition, ETV4 (ETS variant transcription factor 4), ANGPTL4 (Angiopoietin-like protein 4), HIST1H1C (Histone cluster 1 H1 family member c) and CTSV (Cathepsin V) showed prognostic potential in a molecular subtype-specific manner. CONCLUSION We built a platform for researchers to analyze if genes have prognostic potentials in UCS.
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Affiliation(s)
- Yang An
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Qiang Wang
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Fengjie Sun
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Guosen Zhang
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Fengling Wang
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Lu Zhang
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Yanan Li
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Weinan Ren
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Wan Zhu
- Department of Anesthesia, Stanford University, Stanford, CA 94305, USA;
| | - Yongqiang Li
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Shaoping Ji
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
| | - Xiangqian Guo
- Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, School of Basic Medical Sciences, School of Software, Henan University, Kaifeng 475004, China; (Y.A.); (Q.W.); (F.S.); (G.Z.); (F.W.); (L.Z.); (Y.L.); (W.R.); (Y.L.); (S.J.)
- Correspondence: ; Tel.: +86-0371-22892860
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Anjum S, Sahar T, Nigam A, Wajid S. Transcriptome Analysis of mRNA in Uterine Leiomyoma Using Next-generation RNA Sequencing. Anticancer Agents Med Chem 2019; 19:1703-1718. [DOI: 10.2174/1871520619666190409102855] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 03/18/2019] [Accepted: 03/22/2019] [Indexed: 12/14/2022]
Abstract
Background:
Uterine leiomyoma is a benign smooth muscle tumor of monoclonal nature in the
female reproductive tract and is one of the major health problems. More than 70% of the female population
suffers from uterine leiomyoma in their lifetime and in the advanced condition, it is associated with pregnancy
complications and infertility.
Objective:
Characterization and relative expression of mRNA transcripts through transcriptome profiling in
uterine leiomyoma and adjacent normal myometrium.
Methods:
Uterine leiomyoma tissue of an Indian female, age 32 years, with a family history of leiomyoma
(evident from mother’s hysterectomy for the same pathology) was used. Patient showed 9 multiple large lesions
appearing heterogeneously, deforming the uterine contour and causing distortion and splaying of the endometrial
cavity showing disease aggressiveness was taken for Next-generation sequencing (NGS) to develop
whole transcriptome profile along with the adjacent normal myometrium as control. The validation of the
relative expression of the selective transcripts was done using Real-Time PCR.
Results:
The transcriptome profile indicated 128 genes up-regulated and 98 down-regulated, with the Log2 fold
change ≥ 2 and P ≤ 0.05, highlighting the molecular network closely associated with focal adhesion, hyaluronan
and MAPK-signaling pathways. The mean relative fold change obtained from quantitative PCR as well as the
P-values of 10 selected transcripts evaluated from student’s t-test were as follows: BCAN: 7.93 fold (p-value
=0.0013); AAK1: 2.2 fold (p-value =0.0036); PCBP3: 3.4 fold (p-value =0.0197); MOV10L1: 3.4 fold (p-value
=0.0062); TWISTNB: 1.8 fold (p-value =0.006); TMSB15A: 2.1 fold (p-value =0.0023); SMAD1: 0.8 fold
(p-value =0.0112); ANXA1: 0.6 fold (p-value =0.0012); FOS: 0.6 fold (p-value =0.0191); SLFN11: 0.56 fold
(p-value =0.0001).
Conclusion:
The present study provides a roadmap, towards the analysis of genes and their roles in corresponding
pathways throwing light on their possible involvement in the pathology of the disease.
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Affiliation(s)
- Shadab Anjum
- Department of Biotechnology, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi, 110062, India
| | - Tahreem Sahar
- Department of Biotechnology, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi, 110062, India
| | - Aruna Nigam
- Department of Obstetrics and Gynecology, HIMSR and HAH Centenary Hospital, Jamia Hamdard, New Delhi, 110062, India
| | - Saima Wajid
- Department of Biotechnology, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi, 110062, India
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Agulnik M, Costa RLB, Milhem M, Rademaker AW, Prunder BC, Daniels D, Rhodes BT, Humphreys C, Abbinanti S, Nye L, Cehic R, Polish A, Vintilescu C, McFarland T, Skubitz K, Robinson S, Okuno S, Van Tine BA. A phase II study of tivozanib in patients with metastatic and nonresectable soft-tissue sarcomas. Ann Oncol 2017; 28:121-127. [PMID: 27771610 DOI: 10.1093/annonc/mdw444] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Background Soft tissue sarcomas (STSs) overexpress vascular endothelial growth factors (VEGF) and VEGF-receptors (VEGFR) activation have been associated with tumor aggressiveness. Tivozanib is a potent small molecule tyrosine kinase inhibitor against VEGFR1-3, with activity against PDGFRα/β and cKIT. The primary endpoint of this study was progression free survival (PFS) rate at 16 weeks. Secondary end points were overall survival (OS), response rate, safety and correlative studies. Patients and methods A Simon two-stage phase II trial was performed using tivozanib given orally at 1.5 mg daily, 3 week on 1 week off on a 28 day cycle until disease progression or intolerable toxicity. Results Fifty-eight patients were enrolled and treated with tivozanib. Leiomyosarcoma was the most common STS histological type in our cohort (47%) and 27 patients (46%) had received at least 3 lines of therapy prior to study entry. Up to 24 patients (41%) had prior VEGF targeted therapies. Partial response and stable disease were observed in 2 (3.6%) and 30 (54.5%) patients. The 16 week PFS rate was 36.4% [95% confidence interval (CI) 23.7-49.1] and a median PFS of 3.5 months (95% CI 1.8-3). Median OS observed was 12.2 months (95% CI 8.1-16.8). The most frequent all grade toxicities were fatigue (48.3%), hypertension (43.1%), nausea (31%) and diarrhea (27.6%). The most common grade three toxicity was hypertension (22.4%). Correlative studies demonstrate no correlation between the expression of VEGFR 1, 2 or 3, PDGFRα/β or FGF, and activity of tivozanib. Conclusion Tivozanib was well tolerated and showed antitumor activity with a promising median PFS and PFS rate at 4 months in a heavily pretreated population of metastatic STSs. Our results support further studies to assess the clinical efficacy of tivozanib in STS. Clinical Trial Number NCT01782313.
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Affiliation(s)
- M Agulnik
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - R L B Costa
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - M Milhem
- Division of Hematology/Oncology, University of Iowa Hospitals and Clinics, Iowa City, USA
| | - A W Rademaker
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - B C Prunder
- Division of Hematology/Oncology, Washington University in St. Louis, St Louis, USA
| | - D Daniels
- Division of Hematology/Oncology, Washington University in St. Louis, St Louis, USA
| | - B T Rhodes
- Division of Hematology/Oncology, Washington University in St. Louis, St Louis, USA
| | - C Humphreys
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - S Abbinanti
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - L Nye
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - R Cehic
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - A Polish
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - C Vintilescu
- Division of Hematology/Oncology, Northwestern University, Feinberg School of Medicine, Chicago, USA
| | - T McFarland
- Division of Hematology/Oncology, University of Wisconsin, Madison, USA
| | - K Skubitz
- Division of Hematology/Oncology, University of Minnesota, Minneapolis, USA
| | - S Robinson
- Division of Hematology/Oncology, Mayo Clinic, Rochester, USA
| | - S Okuno
- Division of Hematology/Oncology, Mayo Clinic, Rochester, USA
| | - B A Van Tine
- Division of Hematology/Oncology, Washington University in St. Louis, St Louis, USA
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Islam MS, Protic O, Stortoni P, Grechi G, Lamanna P, Petraglia F, Castellucci M, Ciarmela P. Complex networks of multiple factors in the pathogenesis of uterine leiomyoma. Fertil Steril 2013; 100:178-93. [DOI: 10.1016/j.fertnstert.2013.03.007] [Citation(s) in RCA: 103] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2012] [Revised: 03/04/2013] [Accepted: 03/06/2013] [Indexed: 01/07/2023]
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Mackay HJ, Buckanovich RJ, Hirte H, Correa R, Hoskins P, Biagi J, Martin LP, Fleming GF, Morgan R, Wang L, Polintan R, Oza AM. A phase II study single agent of aflibercept (VEGF Trap) in patients with recurrent or metastatic gynecologic carcinosarcomas and uterine leiomyosarcoma. A trial of the Princess Margaret Hospital, Chicago and California Cancer Phase II Consortia. Gynecol Oncol 2011; 125:136-40. [PMID: 22138373 DOI: 10.1016/j.ygyno.2011.11.042] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2011] [Revised: 11/18/2011] [Accepted: 11/22/2011] [Indexed: 12/22/2022]
Abstract
OBJECTIVE The aim of this multi-institutional non randomized phase II trial was to determine the efficacy and safety of single agent aflibercept (VEGF Trap), a recombinant fusion protein that blocks multiple vascular endothelial growth factor isoforms, in women with gynecologic soft tissue sarcoma. METHODS Patients were enrolled in two cohorts each with Simon two stage designs: uterine leiomyosarcoma and carcinosarcoma of endometrial, ovarian or fallopian tube origin. Eligibility criteria included ≤2 prior lines of chemotherapy for metastatic disease and ECOG performance status of ≤2. Aflibercept 4mg/kg was administered intravenously on day 1 of a 14 day cycle. Primary endpoints were objective response and disease stabilization (Progression Free Survival (PFS) at 6 months). RESULTS 41 patients with uterine leiomyosarcoma and 22 patients with carcinosarcoma (19 uterine, 3 ovarian) were enrolled on study. In the leiomyosarcoma cohort, eleven (27%) patients had stable disease (SD), 4 with SD lasting at least 24 weeks. The 6 month PFS was 17%, with median time to progression (TTP) of 1.8 (95% CI:1.6-2.1) months. In the carcinosarcoma cohort, two (9%) patients had SD, one lasting >24 weeks, median TTP was 1.6 months (95%CI: 1.1-1.7) No partial responses were observed in patients from either cohort. Grade 3 or more aflibercept related toxicity was uncommon and included hypertension, fatigue, headache and abdominal pain. CONCLUSIONS Single agent aflibercept has modest activity in patients with uterine leiomyosarcoma and minimal activity in women with carcinosarcoma.
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Affiliation(s)
- H J Mackay
- Princess Margaret Hospital, Ontario, Canada
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