| Literature DB >> 33142915 |
Demetra H Hufnagel1, Gabriella D Cozzi1, Marta A Crispens2,3, Alicia Beeghly-Fadiel3,4.
Abstract
Platelets are critical components of a number of physiologic processes, including tissue remodeling after injury, wound healing, and maintenance of vascular integrity. Increasing evidence suggests that platelets may also play important roles in cancer. In ovarian cancer, thrombocytosis, both at the time of initial diagnosis and at recurrence, has been associated with poorer prognosis. This review describes current evidence for associations between thrombocytosis and ovarian cancer prognosis and discusses the clinical relevance of platelet count thresholds and timing of assessment. In addition, we discuss several mechanisms from in vitro, in vivo, and clinical studies that may underlie these associations and recommend potential approaches for novel therapeutic targets for this lethal disease.Entities:
Keywords: ovarian cancer; platelets; prognosis; thrombocytosis
Mesh:
Year: 2020 PMID: 33142915 PMCID: PMC7663176 DOI: 10.3390/ijms21218169
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Characteristics of Studies on Thrombocytosis and Ovarian Cancer Outcomes.
| Author | Year | Platelet Measurement Timeframe(s) | Thrombocytosis Threshold(s) | Study Population | Statistical Analysis | Prognostic Association(s) * | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Description | Pretreatment | Additional | Patients | Description | Source (Country) | Outcome | Approach | PFS/DFS | OS/DSS | |||
| Allensworth | 2013 | Preoperative (NOS) | Yes | 450 | 578 | epithelial ovarian cancer | United States | DFS, OS | KM, PHreg | Worse | Worse * | |
| Andersen | 2014 | Up to 3-years prior to diagnosis | Yes | 400 (mild), 550 (severe) | 224 | ovarian cancer (NOS) | Denmark | All-Cause and Cancer-Specific Mortality | KM, PHreg | Worse | ||
| Barber | 2015 | Preoperative (NOS) | Yes | 450 | 1072 | ovarian cancer (NOS) | ACS NSQIP (US) | 30-Day Outcomes | Logistic Regression | Worse for major complications (unadj, adj) | ||
| Bottsford-Miller | 2015 | Pretreatment (at diagnosis) and at disease recurrence | Yes | Yes | 450 | 341 | recurrent epithelial ovarian cancer | United States | PFS, OS | KM | NS | Worse |
| Bozkurt | 2004 | Second-look laparotomy after chemotherapy (up to 5 days prior) | Yes | 380 (ROC), continuous | 37 | advanced stage (III/IV) epithelial ovarian cancer | Turkey | Presence of Disease | Wilcoxon Signed Rank Test | Worse | ||
| Canzler | 2020 | Pretreatment for recurrent disease | Yes | 400 | 300 | recurrent epithelial ovarian cancer | Germany | PFS, OS | KM, PHreg | NS | Worse * | |
| Chen, JP | 2019 | Pretreatment (NOS) | Yes | 400 | 108 | advanced stage (IV) epithelial ovarian cancer | China | PFS, OS | KM, PHreg | NS (KM), Worse in combination with CA-125 (unadj, adj) | Worse (KM), Worse in combination with CA-125 (unadj, adj) | |
| Chen, Y | 2015 | Pretreatment (NOS) | Yes | 400 | 816 | epithelial ovarian cancer | China | PFS, OS | KM, PHreg | Worse | Worse | |
| Cohen | 2014 | Cytoreductive surgery for recurrent disease | Yes | 350 | 107 | recurrent epithelial ovarian cancer | United States | OS | KM, PHreg | Worse | ||
| Cozzi | 2016 | Date of diagnosis and up to 1, 2, 4, and 8 weeks prior | Yes | 350, 400, 450 | 304 | epithelial ovarian cancer | United States | OS | KM, PHreg | Worse | ||
| Digklia | 2014 | Pretreatment | Yes | 350 | 91 | stage III/IV serous ovarian cancer | Switzerland | PFS, OS | KM, PHreg | Worse | Worse | |
| Eggemann | 2015 | At diagnosis, after surgery, before and after chemotherapy, and disease recurrence | Yes | Yes | 350 | 132 | ovarian cancer (NOS) | Germany | PFS, OS | KM, PHreg | Worse for <25% reduction (unadj, adj) | Worse for <25% reduction |
| Feng | 2016 | Preoperative (NOS) | Yes | 450 | 874 | high-grade serous ovarian cancer | China | PFS, OS | KM | NS | NS | |
| Gerestein | 2009 | Preoperative (within 1 week of surgery) | Yes | continuous | 118 | advanced stage (IIB-IV) epithelial ovarian cancer | The Netherlands | PFS, OS | KM, PHreg | Worse | Worse | |
| Gungor | 2009 | Preoperative (within 14 days of surgery) | Yes | 400 | 292 | epithelial ovarian cancer | Turkey | OS | KM, PHreg | Worse | ||
| Hefler-Frischmuth | 2018 | Preoperative (24–72 h prior to initial surgery) | Yes | 450, continuous | 498 | epithelial ovarian cancer | Austria | OS | KM, PHreg | Worse * | ||
| Hu | 2020 | Pretreatment, 14 days after chemotherapy, and disease recurrence | Yes | Yes | 300 | 104 | recurrent epithelial ovarian cancer | China | PFS, OS | KM, PHreg | Worse | Worse |
| Komura | 2019 | Lowest measure between diagnosis and treatment | Yes | 427 (ROC) | 308 | epithelial ovarian cancer | Japan | DSS | KM, PHreg | Worse | ||
| Lee | 2011 | Preoperative (within 7 days prior to surgery) and after adjuvant chemotherapy | Yes | Yes | 400 | 179 | advanced stage (III/IV) epithelial ovarian cancer | Korea | PFS, OS | KM, PHreg | NS | Worse |
| Li | 2004 | Preoperative (within 14 days of surgery) | Yes | 400 | 144 | advanced stage (III/IV) epithelial ovarian cancer | United States | DFS, OS | KM, PHreg | Worse | Worse | |
| Ma | 2013 | Preoperative (within 7 days prior to surgery) | Yes | 400 | 182 | epithelial ovarian cancer | China | PFS, OS | KM, PHreg | Worse in combination with MAR (unadj, adj) | Worse in combination with MAR (unadj, adj) | |
| Man | 2015 | Pretreatment (up to 7 days prior) | Yes | 300 | 190 | epithelial ovarian cancer | China | PFS, OS | KM, PHreg | Worse | Worse | |
| Matsuo | 2015 | At diagnosis and at disease progression or recurrence | Yes | Yes | 400 | 1308 | clear cell and serous ovarian cancer | 10 academic institutions | PFS, OS | KM, PHreg | Worse | Worse |
| Menczer | 1998 | Preoperative (NOS) | Yes | 400 | 70 | epithelial ovarian cancer | Israel | OS | KM | Worse | ||
| Nakao | 2020 | Pretreatment (mean of initial and pre-treatment evaluations) | Yes | 400 | 280 | epithelial ovarian cancer | Japan | PFS, OS | KM, PHreg | Worse | Worse | |
| Okunade | 2020 | Pretreatment (at diagnosis) | Yes | 450 | 72 | epithelial ovarian cancer | Nigeria | PFS, OS | KM, PHreg | Worse | Worse | |
| Qiu | 2012 | Preoperative (2–4 days prior) | Yes | 400 | 136 | epithelial ovarian cancer | China | PFS, OS | KM, PHreg | Worse * | Worse * | |
| Słabuszewska-Jóźwiak | 2015 | Preoperative (1 day before surgery) | Yes | 350 | 97 | ovarian cancer (not all epithelial) | Poland | DFS, OS | Mann-Whitney U Test | NS | Worse | |
| Soonthornthum | 2007 | Preoperative (within 14 days of surgery) | Yes | 305 (ROC), 400 | 74 | epithelial ovarian cancer | Thailand | OS | KM | Worse | ||
| Stone | 2012 | Preoperative (NOS) | Yes | 450 | 619 | epithelial ovarian cancer | United States | PFS, OS | KM, PHreg | Worse | Worse | |
| Tang | 2017 | Preoperative (NOS) | Yes | 300, 327 (ROC), 350, 400 | 171 | epithelial ovarian cancer | China | OS | KM | Worse | ||
| Zeimet | 1994 | Preoperative (NOS) | Yes | 400 | 130 | epithelial ovarian cancer | Austria | OS (4-year) | KM | NS | ||
Abbreviations: adj—adjusted; DFS—disease-free survival; DSS—disease-specific survival; KM—Kaplan–Meier analysis; MAR—Mean Aggregation Rate; NOS—not otherwise specified; NS—not significant; OS—overall survival; P—p-value; PFS—progression-free survival; PHreg—proportional hazards regression; ROC—receiver operating curve; unadj—unadjusted; US—United States. * Denotes that adjusted proportional hazards regression model was not significant.
Figure 1Contributions of platelets to ovarian cancer progression. (1) Tumor cells produce the cytokine interleukin-6 (IL-6). (2) IL-6 drives production of thrombopoietin (TPO) directly from tumor cells as well as the liver. (3) TPO stimulates production and release of platelets from bone marrow. (4) Platelets support cancer cell proliferation, invasion, angiogenesis, migration, and metastasis through release of growth factors, mitogens, metabolites, and proteases. They may also act as sites of seeding for metastasis and form aggregates with tumor cells to shield them from immune surveillance. Figure 1 is an original figure that was created by the authors using BioRender.com.