Journal of Obstetrics and Gynaecology, 2014; Early Online: 1–4 © 2014 Informa UK, Ltd. ISSN 0144-3615 print/ISSN 1364-6893 online DOI: 10.3109/01443615.2014.912620
Mean platelet volume could be a useful biomarker for monitoring epithelial ovarian cancer Y. Kemal¹, G. Demirağ¹, K. Ekiz² & İ. Yücel¹
J Obstet Gynaecol Downloaded from informahealthcare.com by National University of Singapore on 06/12/14 For personal use only.
Departments of 1Medical Oncology and 2Internal Medicine, Faculty of Medicine, 19 Mayıs University, Samsun, Turkey
New studies show that inflammatory markers and blood cells may be related to epithelial ovarian cancer (EOC). We aimed to examine whether mean platelet volume would be a useful marker for EOC patients to predict tumour burden and prognosis, and investigate the difference in MPV values between EOC patients and healthy controls. We retrospectively investigated 113 ovarian cancer patients who underwent surgery between January 2008 and July 2012 and 90 healthy subjects. MPV levels were significantly higher in preoperative EOC patients compared with healthy subjects (8.26 fl vs 7.71 fl; p ⫽ 0.004). Also NLR and PLR values were significantly higher in EOC patients (NLR, 3.48 vs 2.37; p ⫽ 0.000; PLR, 241 vs 148; p ⫽ 0.000). Surgical tumour resection resulted in a significant decrease in MPV levels (8.26 fl vs 7.61 fl; p ⫽ 0.001). NLR values also decreased after tumour resection significantly similar to CA125 (NLR, 3.48 vs 2.49; p ⫽ 0.000). Our data suggests that MPV could be a promising and easily available biomarker for monitoring EOC patients. Keywords: Ovarian cancer, platelets
Introduction Epithelial ovarian cancer (EOC) accounts for 3.6% of all cancers among women worldwide, and is the leading cause of death from gynaecological cancer (Jemal et al. 2010). The incidence of ovarian cancer increases with age and is most prevalent in the 8th decade of life. The median age at the time of diagnosis is 63 years and more than 70% of patients present with advanced disease (Jelovac and Armstrong 2011) and only 40% of the women diagnosed with the disease expect to survive 5 years (McGuire et al. 1996). After initial treatment with debulking surgery and taxane and platinum-based chemotherapy, most patients will relapse (Cannistra et al. 2004). Many molecular markers have been proposed for the early diagnosis and prognostic factors of ovarian cancer, but most are not ready to be included as part of the routine diagnostic algorithm, because they still lack sensitivity, specificity or reproducibility. CA125 is the most useful and studied molecular marker in ovarian cancer. Recently, new studies have shown that inflammatory markers and blood cells may have a relationship with epithelial ovarian cancer (den Ouden et al. 1997). Elevated platelets, neutrophils and lymphocytes or neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) have been reported in EOC (den Ouden et al. 1997; Kim et al. 2009; Thavaramara et al.
2011). Many cancers arise from sites of infection and inflammation. In the development and progression of a cancer, inflammation is a crucial and essential process (Kim et al. 2009). In addition, the inflammatory response to a tumour takes place through neutrophils, leucocytic and other phagocytic mediators that induce damage to cellular DNA, inhibit apoptosis and promote angiogenesis around the cancer area. This will ultimately result in tumour growth, progression and metastasis (Balkwill and Mantovani 2001; Jackson et al. 1997). Similarly, platelets can release some growth factors, i.e. platelet-derived growth factor (PDGF), platelet factor 4, transforming growth factor beta (TGFb), vascular endothelial growth factor (VEGF) (Assoian and Sporn 1986) and thrombospondin, which function as a potent mitogen or adhesive glycoprotein for different cell types, including the ovarian surface epithelium (Dabrow et al. 1998; Qian and Tuszynski 1996). These growth factors can stimulate ovarian tumour cells proliferation and adhesion to other cells leading to tumour growth and metastases, respectively (Dabrow et al. 1998). Mean platelet volume (MPV), which can be easily evaluated by haematological analysers, is a convenient marker of platelet functions and activation. It shows the average size of platelets and reflects the platelet production rate and stimulation (Kai et al. 2005). Larger platelets are more metabolically and enzymatically active than smaller platelets (Mangalpally et al. 2010). In light of these findings, we aimed to examine whether MPV would be a useful inflammatory marker for EOC patients to predict tumour burden and prognosis and to investigate the difference in MPV values between EOC patients and healthy controls.
Patients and methods After approval from the Ethics Committee of 19 Mayıs University, a retrospective review was made of ovarian cancer patients who had undergone cytoreductive surgery at 19 Mayıs University Hospital, between January 2008 and July 2012. Patients with hypertension, haematological and renal disease, heart failure, chronic infection, hepatic disorder, acute inflammatory disease, myeloproliferative disorders, autoimmune disease, splenectomy, other cancers and patients using drugs, which could affect the platelet count and/or function, were not included in the study. Histological staging and grading were performed according to the current International Federation of Gynecology and Obstetrics (FIGO) classification. Moreover, 22
Correspondence: Y. Kemal, Department of Medical Oncology, 19 Mayıs University, Faculty of Medicine, Samsun, Turkey. E-mail: [email protected]
2
Y. Kemal et al.
Table I. Mean values of the parameters.
Age Platelets MPV∗(fl) PLR∗∗ NLR∗∗∗
EOC patients (n ⫽ 113)
Healthy controls (n ⫽ 90)
P-value
55 362027 ⫾ 11478 8.27 ⫾ 0.10 241.57 ⫾ 16.93 3.49 ⫾ 0.18
54 295747 ⫾ 8014.48 7.71 ⫾ 0.85 148.28 ⫾ 10.59 2.37 ⫾ 0.27
0.000 0.040 0.000 0.000
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∗Mean platelet volume. ∗∗Platelet to lymphocyte ratio. ∗∗∗Neutrophil to lymphocyte ratio.
cases of epithelial ovarian cancer were excluded from the study due to lack of data. Data collection included patient demographics, clinicopathological parameters and preoperative haematological parameters. Control subjects were individually selected from patients attending the outpatient clinic for a check-up. The study groups were designed as early stage (stage I to II–IIIa,b) ovarian cancer and advanced stage (stage IIIc–IV) ovarian cancer. Optimal surgery was defined when the size of each of the foci of residual disease after surgery was ⱕ 1 cm. The preoperative data was obtained from the recorded computerised database and postoperative data were obtained 2 weeks after the operation. Routinely, in our hospital, complete blood counts (CBC) are measured by Siemens Healthcare Diagnostic Item ADVIA 2120i and blood samples are measured with potassium ethylenediamine tetra-acetic acid and are analysed 1 h after venepuncture. Normal MPV values in our laboratory range between 7.0 and 11.1 fl. NLR and PLR were obtained from the absolute neutrophil count or platelet count, respectively, divided by the absolute lymphocyte count.
Statistical analysis Statistical analyses were performed with SPSS software (SPSS 15.0, Chicago, IL). All parameters were expressed as mean ⫾ standard deviation. The normality of distribution was checked initially by the Shapiro–Wilk test and parametric or non-parametric tests were applied to data with normal or non-normal distributions, respectively. The paired sample test was used to compare the preoperative and postoperative variables. The Mann–Whitney U test was used to compare the parameters of preoperative ovarian cancer patients and control subjects. The results were expressed as mean ⫾ standard deviation (SD). A value of p ⱕ 0.05 was considered statistically significant.
Figure 2. NLR before and after surgery.
Results Between January 2008 and July 2012, 181 women with ovarian malignancy were identified. A total of 68 patients were excluded due to borderline ovarian tumours in 11; germ cell tumours in 35; and incomplete clinical data in 21. A total of 113 patients met all the inclusion criteria and were included in the study. The median age of the patients was 55 years (range, 23–85 years). The most common histopathology was serous carcinoma and the majority (n ⫽ 100) had high-grade tumours (moderately- or poorlydifferentiated). In total, 36 patients had early stage diseases (stage I–II–IIIa–IIIb). Optimal surgery with residual disease ⱕ 1 cm was achieved in approximately 30%. MPV levels were significantly higher in preoperative EOC patients compared with the healthy subjects (8.26 fl vs 7.71; p ⫽ 0.004). NLR and PLR values were also significantly higher in EOC patients (NLR, 3.48 vs 2.37; p ⫽ 0.000; PLR, 241 vs 148; p ⫽ 0.000) (Table I). Surgical tumour resection resulted in a significant decrease in MPV levels (8.26 fl vs 7.61 fl; p ⫽ 0.001) (Figure 1). NLR values also decreased significantly after tumour resection, similar to CA125 (NLR, 3.48 vs 2.49; p ⫽ 0.000) (Figure 2 and Table II). The relationship between MPV levels and TNM stages, grade and surgery success was also investigated. There was no statistical relationship between MPV and these parameters.
Discussion The results of this study indicated that the EOC patients had significantly higher MPV, NLR and PRL values, compared with the healthy controls. No relationship was observed between MPV, NLR values and TNM stages. Moreover, surgical tumour resection was found to result in a significant decrease in MPV and NLR values. The explanation for the association between elevated MPV and NLR values in many tumours is not fully understood. However, the probable mechanisms can be discussed. Many cancers arise
Table II. Comparison of the preoperative and postoperative results. Pre-operative Platelets CA125(U/mL) MPV∗ (fl) PLR∗∗ NLR∗∗∗
Figure 1. MPV befre and after surgery.
362027 ⫾ 11478 891.81 ⫾ 121.27 8.27 ⫾ 0.10 241.57 ⫾ 16.93 3.49 ⫾ 0.18
∗Mean platelet volume. ∗∗Platelet to lymphocyte ratio. ∗∗∗Neutrophil to lymphocyte ratio.
Post-operative 361000 ⫾ 12156 231.85 ⫾ 77.73 7.61 ⫾ 0.09 214.83 ⫾ 10.06 2.49 ⫾ 0.15
P-value 0.704 0.000 0.000 0.062 0.000
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Mean platelet volume could be a useful biomarker for monitoring epithelial ovarian cancer 3 from sites of infection and inflammation. In the development and progression of a cancer, inflammation is a crucial and essential process (Kim et al. 2009). The biological effects of inflammation include enhanced cellular proliferation and angiogenesis, an inability to adapt to oxidative stress and inhibition of apoptosis (Shacter and Weitzman 2002; Ziegler et al. 1998). Chronic inflammation may play a role in ovarian carcinogenesis. One hypothesis regarding ovarian carcinogenesis is that of incessant ovulation, which may increase the risk through repeated damage to and wound repair of the ovarian epithelium, a process that can induce inflammation (Fleming et al. 2006; Ness and Cottreau 1999). Epidemiological evidence supports this hypothesis; for example, events that interrupt ovulation (e.g. pregnancy, oral contraceptive use) or lower inflammation (e.g. tubal ligation) reduce the risk, while exposure that causes inflammation (e.g. talc use) increases the risk (Fleming et al. 2006; Riman et al. 2004). New studies have focussed on elevated serum concentrations of inflammatory parameters in the blood count (neutrophil count, platelet count, NLR, PLR and recently, MPV) on many cancer subtypes. Some demonstrated that thrombocytosis was associated with more advanced disease, inoperable cancer and was an independent prognostic factor of EOC (Li et al. 2004; Soonthornthum et al. 2007). Moreover, platelet size has been shown to reflect platelet activity (Thompson et al. 1983). MPV can reflect the level of platelet stimulation and the rate of platelet production (Threatte et al. 1993). Strong evidence indicates that MPV is an important biological variable and that larger platelets are more metabolically and enzymatically active than smaller platelets (Mangalpally et al. 2010). Platelets play a metabolic role in cancer through angiogenic, metastatic and proteolytic activities (Kisucka et al. 2006). Malignant cells produce cytokines, such as interleukin-1 and other growth factors, which induce platelet production. There is increasing evidence that tumours and endothelial cells are acted upon by VEGF, growth factors and interleukins secreted by platelets. This may therefore contribute to the transporters of VEGF and PDGF, which have been shown to function as a potent mitogen for different cell types (Dabrow et al. 1998; Apte et al. 2004). New drugs targeting these pathways are popular as anti-angiogenic agents (Apte et al. 2004). Such agents may also have an effect on platelet activity, which can be evaluated by measuring MPV. If platelets play an important role in tumour angiogenesis, then mean platelet volume, which reflects platelet activation, might be a marker for angiogenesis. It is well known that IL-6 can cause carcinogenesis and metastasis through several signal pathways. IL-6 induces the proliferation and differentiation of early progenitor cells, first megakaryocyte progenitors, and has a direct effect on megakaryocytes using specific receptors (Hsu et al. 2002). This platelet activator process may also play another role in tumour progression. What about the other blood count parameters? Tumour immunology states that the tumour microenvironment can educate and control invading leukocytes to promote angiogenesis, viability, motility and invasion (Balkwill and Mantovani 2001; Lin and Pollard 2004). Tumour-associated macrophages, which arise from blood monocytes, seem to play a crucial role in this interaction (Pollard et al. 2004). Neutrophils represent 50–60% of total leukocytes and their cytoplasm is rich in granules with high toxic potential against various types of tumour cells. Additionally, neutrophils express membrane receptors for the recognition and elimination of microorganisms and tumour cells (Koga et al. 2004). Cho et al. (2009) demonstrated that preoperative NLR in combination with CA125 is a useful discriminative marker for epithelial ovarian cancer. In another clinical study, Raungkaewmanee et al. (2012) showed that all blood components elevation was associated with adverse characteristic features and poor
prognosis in EOC. PLR was a better prognostic indicator for EOC compared with thrombocytosis or NLR. The current study has the advantage that to the best of our knowledge, it is the first study to evaluate the role of MPV in EOC. MPV has been previously evaluated in gastric carcinoma, hepatocellular carcinoma, pancreatic adenocarcinoma and endometrial carcinoma (Kılınçalp et al. 2013; Oge et al. 2013). Kılıncalp et al. (2013) determined that MPV levels were significantly higher in preoperative GC patients compared with healthy subjects. Similar to the current study, they showed that surgical tumour resection resulted in a significant decrease in MPV values. In another newly published report, Oge et al. (2013) demonstrated similar results in patients with endometrial carcinoma. There were also some limitations in the current study. First, the patient population in the study was heterogeneous, consisting of both early and advanced stage. Another limitation was surgery failure. Only one-third had optimal surgery in contrast to similar studies. In conclusion, this study documented that MPV and NLR were higher in preoperative EOC patients compared with postoperative values and healthy subjects. Pre- and postoperative MPV and NLR measurements in such patients may provide a simple method to demonstrate treatment effectiveness as for CA125. Further studies in a larger and more homogeneous population are required to validate the importance of MPV.
Acknowledgements We thank Professor Yuksel Bek and Dr Berkhan Topaktas for their advice on the statistical analyses. Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
References Apte SM, Fan D, Killion JJ, Fidler IJ. 2004. Targeting the platelet-derivedgrowth factor receptor in antivascular therapy for human ovarian carcinoma. Clinical Cancer Research 10:897–890. Assoian RK, Sporn MB. 1986. Type beta transforming growth factor in human platelets: release during platelet degranulation and action on vascular smooth muscle cells. Journal of Cell Biology 102:1217–1223. Balkwill F, Mantovani A. 2001. Inflammation and cancer: back to Virchow? Lancet 357:539–545. Cannistra SA. 2004. Cancer of the ovary. New England Journal of Medicine 351:2519–2529. Cho H, Hur HW, Kim SW, Kim SH, Kim JH, Kim YT et al. 2009. Pre-treatment neutrophil to lymphocyte ratio is elevated in epithelial ovarian cancer and predicts survival after treatment. Cancer Immunology, Immunotherapy 58:15–23. Dabrow MB, Francesco MR, McBrearty FX, Caradonna S. 1998. The effects of platelet-derived growth factor and receptor on normal and neoplastic human ovarian surface epithelium. Gynecologic Oncology 71:29–37. den Ouden M, Ubachs JM, Stoot JE, van Wersch JW. 1997. Whole blood cell counts and leucocyte differentials in patients with benign or malignant ovarian tumours. European Journal of Obstetrics, Gynecology, and Reproductive Biology 72:73–77. Fleming JS, Beaugié CR, Haviv I, Chenevix-Trench G, Tan OL. 2006. Incessant ovulation, inflammation and epithelial ovarian carcinogenesis: revisiting old hypotheses. Molecular and Cellular Endocrinology 247:4–21. Hsu HC, Lee YM, Tsai WH, Jiang ML, Ho CH, Ho CK et al. 2002. Circulating levels of thrombopoietic and inflammatory cytokines in patients with acute myeloblastic leukemia and myelodysplastic syndrome. Oncology 63:64–69. Jackson JR, Seed MP, Kircher CH, Willoughby DA, Winkler JD. 1997. The co-dependence of angiogenesis and chronic inflammation. FASEB Journal 11:457–465. Jelovac D, Armstrong DK. 2011. Recent progress in the diagnosis and treatment of ovarian cancer. CA: A Cancer Journal for Clinicians 61:183–203. Jemal A, Siegel R, Xu J, Ward E. 2010. Cancer statistics. CA: A Cancer Journal for Clinicians 60:277–300.
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Kai H, Kitadai Y, Kodama M, Cho S, Kuroda T, Ito M et al. 2005. Involvement of proinflammatory cytokines IL-1beta and IL-6 in progression of human gastric carcinoma. Anticancer Research 25:709–713. Kılınçalp S, Ekiz F, Başar O, Ayte MR, Coban S, Yılmaz B, et al. 2013. Mean platelet volume could be possible biomarker in early diagnosis and monitoring of gastric cancer. Platelets 28 March [Epub ahead of print]. Kim DK, Oh SY, Kwon HC, Lee S, Kwon KA, Kim BG et al. 2009. Clinical significances of preoperative serum interleukin-6 and C-reactive protein level inoperable gastric cancer. BMC Cancer 9:155. Kisucka J, Butterfield CE, Duda DG, Eichenberger SC, Saffaripour S, Ware J et al. 2006. Platelets and platelet adhesion support angiogenesis while preventing excessive hemorrhage. Proceedings of the National Academy of Sciences USA 103:855–860. Koga Y, Matsuzaki A, Suminoe A, Hattori H, Hara T. 2004. Neutrophil-derived TNF-related apoptosis-inducing ligand (TRAIL): a novel mechanism of antitumour effect by neutrophils. Cancer Research 64:1037–1043. Li AJ, Madden AC, Cass I, Leuchter RS, Lagasse LD, Karlan BY. 2004. The prognostic significance of thrombocytosis in epithelial ovarian carcinoma. Gynecologic Oncology 92:211–214. Lin EY, Pollard JW. 2004. Role of infiltrated leucocytes in tumour growth and spread. British Journal of Cancer 90:2053–2058. Mangalpally KK, Siqueiros-Garcia A, Vaduganathan M, Dong JF, Kleiman NS, Guthikonda S. 2010. Platelet activation patterns in platelet size subpopulations: differential responses to aspirin in vitro. Journal of Thrombosis and Thrombolysis 30:251–262. McGuire WP, Hoskins WJ, Brady MF, Kucera PR, Partridge EE, Look KY et al. 1996. Cyclophosphamide and cisplatin compared with paclitaxel and cisplatin in patients with stage III and stage IV ovarian cancer. New England Journal of Medicine 334:1–6. Ness RB, Cottreau C. 1999. Possible role of ovarian epithelial inflammation in ovarian cancer. Journal of the National Cancer Institute 91:1459–1467.
Oge T, T Yalcin O, Ozalp SS, Isikci T. 2013. Platelet volume as a parameter for platelet activation in patients with endometrial cancer. Journal of Obstetrics and Gynaecology 33:301–304. Pollard JW. 2004. Tumour-educated macrophages promote tumour progression and metastasis. Nature Reviews. Cancer 4:71–78. Qian X, Tuszynski GP. 1996. Expression of thrombospondin-1 in cancer: a role in tumor progression. Proceedings of the Society for Experimental Biology and Medicine 212:199–207. Raungkaewmanee S, Tangjitgamol S, Manusirivithaya S, Srijaipracharoen S, Thavaramara T. 2012. Platelet to lymphocyte ratio as a prognostic factor for epithelial ovarian cancer. Gynecologic Oncology 23:265–273. Riman T, Nilsson S, Persson IR. 2004. Review of epidemiological evidence for reproductive and hormonal factors in relation to the risk of epithelial ovarian malignancies. Acta Obstetricia et Gynecologica Scandinavica 883:783–795. Shacter E, Weitzman SA. 2002. Chronic inflammation and cancer. Oncology (Williston Park) 116:217–226, 229. Soonthornthum T, Suraseraneewong V, Kengsakol K, Wijaithum K, Kasemsan P, Prommatt S. 2007. Thrombocytosis in advanced epithelial ovarian cancer. Journal of the Medical Association of Thailand 90:1495–1500. Thavaramara T, Phaloprakarn C, Tangjitgamol S, Manusirivithaya S. 2011. Role of neutrophil to lymphocyte ratio as a prognostic indicator for epithelial ovarian cancer. Journal of the Medical Association of Thailand 94:871–877. Thompson CB, Jakubowski JA, Quinn PG, Deykin D, Valeri CR. 1983. Platelet size as a determinant of platelet function. Journal of Laboratory and Clinical Medicine 101:205– 213. Threatte GA. 1993. Usefulness of the mean platelet volume. Clinics in Laboratory Medicine 13:937–950. Ziegler J. 1998. Cancer and arthritis share underlying processes. Journal of the National Cancer Institute 90:802–803.
Mean platelet volume could be a useful biomarker for monitoring epithelial ovarian cancer Y. Kemal¹, G. Demirağ¹, K. Ekiz² & İ. Yücel¹
J Obstet Gynaecol Downloaded from informahealthcare.com by National University of Singapore on 06/12/14 For personal use only.
Departments of 1Medical Oncology and 2Internal Medicine, Faculty of Medicine, 19 Mayıs University, Samsun, Turkey
New studies show that inflammatory markers and blood cells may be related to epithelial ovarian cancer (EOC). We aimed to examine whether mean platelet volume would be a useful marker for EOC patients to predict tumour burden and prognosis, and investigate the difference in MPV values between EOC patients and healthy controls. We retrospectively investigated 113 ovarian cancer patients who underwent surgery between January 2008 and July 2012 and 90 healthy subjects. MPV levels were significantly higher in preoperative EOC patients compared with healthy subjects (8.26 fl vs 7.71 fl; p ⫽ 0.004). Also NLR and PLR values were significantly higher in EOC patients (NLR, 3.48 vs 2.37; p ⫽ 0.000; PLR, 241 vs 148; p ⫽ 0.000). Surgical tumour resection resulted in a significant decrease in MPV levels (8.26 fl vs 7.61 fl; p ⫽ 0.001). NLR values also decreased after tumour resection significantly similar to CA125 (NLR, 3.48 vs 2.49; p ⫽ 0.000). Our data suggests that MPV could be a promising and easily available biomarker for monitoring EOC patients. Keywords: Ovarian cancer, platelets
Introduction Epithelial ovarian cancer (EOC) accounts for 3.6% of all cancers among women worldwide, and is the leading cause of death from gynaecological cancer (Jemal et al. 2010). The incidence of ovarian cancer increases with age and is most prevalent in the 8th decade of life. The median age at the time of diagnosis is 63 years and more than 70% of patients present with advanced disease (Jelovac and Armstrong 2011) and only 40% of the women diagnosed with the disease expect to survive 5 years (McGuire et al. 1996). After initial treatment with debulking surgery and taxane and platinum-based chemotherapy, most patients will relapse (Cannistra et al. 2004). Many molecular markers have been proposed for the early diagnosis and prognostic factors of ovarian cancer, but most are not ready to be included as part of the routine diagnostic algorithm, because they still lack sensitivity, specificity or reproducibility. CA125 is the most useful and studied molecular marker in ovarian cancer. Recently, new studies have shown that inflammatory markers and blood cells may have a relationship with epithelial ovarian cancer (den Ouden et al. 1997). Elevated platelets, neutrophils and lymphocytes or neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) have been reported in EOC (den Ouden et al. 1997; Kim et al. 2009; Thavaramara et al.
2011). Many cancers arise from sites of infection and inflammation. In the development and progression of a cancer, inflammation is a crucial and essential process (Kim et al. 2009). In addition, the inflammatory response to a tumour takes place through neutrophils, leucocytic and other phagocytic mediators that induce damage to cellular DNA, inhibit apoptosis and promote angiogenesis around the cancer area. This will ultimately result in tumour growth, progression and metastasis (Balkwill and Mantovani 2001; Jackson et al. 1997). Similarly, platelets can release some growth factors, i.e. platelet-derived growth factor (PDGF), platelet factor 4, transforming growth factor beta (TGFb), vascular endothelial growth factor (VEGF) (Assoian and Sporn 1986) and thrombospondin, which function as a potent mitogen or adhesive glycoprotein for different cell types, including the ovarian surface epithelium (Dabrow et al. 1998; Qian and Tuszynski 1996). These growth factors can stimulate ovarian tumour cells proliferation and adhesion to other cells leading to tumour growth and metastases, respectively (Dabrow et al. 1998). Mean platelet volume (MPV), which can be easily evaluated by haematological analysers, is a convenient marker of platelet functions and activation. It shows the average size of platelets and reflects the platelet production rate and stimulation (Kai et al. 2005). Larger platelets are more metabolically and enzymatically active than smaller platelets (Mangalpally et al. 2010). In light of these findings, we aimed to examine whether MPV would be a useful inflammatory marker for EOC patients to predict tumour burden and prognosis and to investigate the difference in MPV values between EOC patients and healthy controls.
Patients and methods After approval from the Ethics Committee of 19 Mayıs University, a retrospective review was made of ovarian cancer patients who had undergone cytoreductive surgery at 19 Mayıs University Hospital, between January 2008 and July 2012. Patients with hypertension, haematological and renal disease, heart failure, chronic infection, hepatic disorder, acute inflammatory disease, myeloproliferative disorders, autoimmune disease, splenectomy, other cancers and patients using drugs, which could affect the platelet count and/or function, were not included in the study. Histological staging and grading were performed according to the current International Federation of Gynecology and Obstetrics (FIGO) classification. Moreover, 22
Correspondence: Y. Kemal, Department of Medical Oncology, 19 Mayıs University, Faculty of Medicine, Samsun, Turkey. E-mail: [email protected]
2
Y. Kemal et al.
Table I. Mean values of the parameters.
Age Platelets MPV∗(fl) PLR∗∗ NLR∗∗∗
EOC patients (n ⫽ 113)
Healthy controls (n ⫽ 90)
P-value
55 362027 ⫾ 11478 8.27 ⫾ 0.10 241.57 ⫾ 16.93 3.49 ⫾ 0.18
54 295747 ⫾ 8014.48 7.71 ⫾ 0.85 148.28 ⫾ 10.59 2.37 ⫾ 0.27
0.000 0.040 0.000 0.000
J Obstet Gynaecol Downloaded from informahealthcare.com by National University of Singapore on 06/12/14 For personal use only.
∗Mean platelet volume. ∗∗Platelet to lymphocyte ratio. ∗∗∗Neutrophil to lymphocyte ratio.
cases of epithelial ovarian cancer were excluded from the study due to lack of data. Data collection included patient demographics, clinicopathological parameters and preoperative haematological parameters. Control subjects were individually selected from patients attending the outpatient clinic for a check-up. The study groups were designed as early stage (stage I to II–IIIa,b) ovarian cancer and advanced stage (stage IIIc–IV) ovarian cancer. Optimal surgery was defined when the size of each of the foci of residual disease after surgery was ⱕ 1 cm. The preoperative data was obtained from the recorded computerised database and postoperative data were obtained 2 weeks after the operation. Routinely, in our hospital, complete blood counts (CBC) are measured by Siemens Healthcare Diagnostic Item ADVIA 2120i and blood samples are measured with potassium ethylenediamine tetra-acetic acid and are analysed 1 h after venepuncture. Normal MPV values in our laboratory range between 7.0 and 11.1 fl. NLR and PLR were obtained from the absolute neutrophil count or platelet count, respectively, divided by the absolute lymphocyte count.
Statistical analysis Statistical analyses were performed with SPSS software (SPSS 15.0, Chicago, IL). All parameters were expressed as mean ⫾ standard deviation. The normality of distribution was checked initially by the Shapiro–Wilk test and parametric or non-parametric tests were applied to data with normal or non-normal distributions, respectively. The paired sample test was used to compare the preoperative and postoperative variables. The Mann–Whitney U test was used to compare the parameters of preoperative ovarian cancer patients and control subjects. The results were expressed as mean ⫾ standard deviation (SD). A value of p ⱕ 0.05 was considered statistically significant.
Figure 2. NLR before and after surgery.
Results Between January 2008 and July 2012, 181 women with ovarian malignancy were identified. A total of 68 patients were excluded due to borderline ovarian tumours in 11; germ cell tumours in 35; and incomplete clinical data in 21. A total of 113 patients met all the inclusion criteria and were included in the study. The median age of the patients was 55 years (range, 23–85 years). The most common histopathology was serous carcinoma and the majority (n ⫽ 100) had high-grade tumours (moderately- or poorlydifferentiated). In total, 36 patients had early stage diseases (stage I–II–IIIa–IIIb). Optimal surgery with residual disease ⱕ 1 cm was achieved in approximately 30%. MPV levels were significantly higher in preoperative EOC patients compared with the healthy subjects (8.26 fl vs 7.71; p ⫽ 0.004). NLR and PLR values were also significantly higher in EOC patients (NLR, 3.48 vs 2.37; p ⫽ 0.000; PLR, 241 vs 148; p ⫽ 0.000) (Table I). Surgical tumour resection resulted in a significant decrease in MPV levels (8.26 fl vs 7.61 fl; p ⫽ 0.001) (Figure 1). NLR values also decreased significantly after tumour resection, similar to CA125 (NLR, 3.48 vs 2.49; p ⫽ 0.000) (Figure 2 and Table II). The relationship between MPV levels and TNM stages, grade and surgery success was also investigated. There was no statistical relationship between MPV and these parameters.
Discussion The results of this study indicated that the EOC patients had significantly higher MPV, NLR and PRL values, compared with the healthy controls. No relationship was observed between MPV, NLR values and TNM stages. Moreover, surgical tumour resection was found to result in a significant decrease in MPV and NLR values. The explanation for the association between elevated MPV and NLR values in many tumours is not fully understood. However, the probable mechanisms can be discussed. Many cancers arise
Table II. Comparison of the preoperative and postoperative results. Pre-operative Platelets CA125(U/mL) MPV∗ (fl) PLR∗∗ NLR∗∗∗
Figure 1. MPV befre and after surgery.
362027 ⫾ 11478 891.81 ⫾ 121.27 8.27 ⫾ 0.10 241.57 ⫾ 16.93 3.49 ⫾ 0.18
∗Mean platelet volume. ∗∗Platelet to lymphocyte ratio. ∗∗∗Neutrophil to lymphocyte ratio.
Post-operative 361000 ⫾ 12156 231.85 ⫾ 77.73 7.61 ⫾ 0.09 214.83 ⫾ 10.06 2.49 ⫾ 0.15
P-value 0.704 0.000 0.000 0.062 0.000
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Mean platelet volume could be a useful biomarker for monitoring epithelial ovarian cancer 3 from sites of infection and inflammation. In the development and progression of a cancer, inflammation is a crucial and essential process (Kim et al. 2009). The biological effects of inflammation include enhanced cellular proliferation and angiogenesis, an inability to adapt to oxidative stress and inhibition of apoptosis (Shacter and Weitzman 2002; Ziegler et al. 1998). Chronic inflammation may play a role in ovarian carcinogenesis. One hypothesis regarding ovarian carcinogenesis is that of incessant ovulation, which may increase the risk through repeated damage to and wound repair of the ovarian epithelium, a process that can induce inflammation (Fleming et al. 2006; Ness and Cottreau 1999). Epidemiological evidence supports this hypothesis; for example, events that interrupt ovulation (e.g. pregnancy, oral contraceptive use) or lower inflammation (e.g. tubal ligation) reduce the risk, while exposure that causes inflammation (e.g. talc use) increases the risk (Fleming et al. 2006; Riman et al. 2004). New studies have focussed on elevated serum concentrations of inflammatory parameters in the blood count (neutrophil count, platelet count, NLR, PLR and recently, MPV) on many cancer subtypes. Some demonstrated that thrombocytosis was associated with more advanced disease, inoperable cancer and was an independent prognostic factor of EOC (Li et al. 2004; Soonthornthum et al. 2007). Moreover, platelet size has been shown to reflect platelet activity (Thompson et al. 1983). MPV can reflect the level of platelet stimulation and the rate of platelet production (Threatte et al. 1993). Strong evidence indicates that MPV is an important biological variable and that larger platelets are more metabolically and enzymatically active than smaller platelets (Mangalpally et al. 2010). Platelets play a metabolic role in cancer through angiogenic, metastatic and proteolytic activities (Kisucka et al. 2006). Malignant cells produce cytokines, such as interleukin-1 and other growth factors, which induce platelet production. There is increasing evidence that tumours and endothelial cells are acted upon by VEGF, growth factors and interleukins secreted by platelets. This may therefore contribute to the transporters of VEGF and PDGF, which have been shown to function as a potent mitogen for different cell types (Dabrow et al. 1998; Apte et al. 2004). New drugs targeting these pathways are popular as anti-angiogenic agents (Apte et al. 2004). Such agents may also have an effect on platelet activity, which can be evaluated by measuring MPV. If platelets play an important role in tumour angiogenesis, then mean platelet volume, which reflects platelet activation, might be a marker for angiogenesis. It is well known that IL-6 can cause carcinogenesis and metastasis through several signal pathways. IL-6 induces the proliferation and differentiation of early progenitor cells, first megakaryocyte progenitors, and has a direct effect on megakaryocytes using specific receptors (Hsu et al. 2002). This platelet activator process may also play another role in tumour progression. What about the other blood count parameters? Tumour immunology states that the tumour microenvironment can educate and control invading leukocytes to promote angiogenesis, viability, motility and invasion (Balkwill and Mantovani 2001; Lin and Pollard 2004). Tumour-associated macrophages, which arise from blood monocytes, seem to play a crucial role in this interaction (Pollard et al. 2004). Neutrophils represent 50–60% of total leukocytes and their cytoplasm is rich in granules with high toxic potential against various types of tumour cells. Additionally, neutrophils express membrane receptors for the recognition and elimination of microorganisms and tumour cells (Koga et al. 2004). Cho et al. (2009) demonstrated that preoperative NLR in combination with CA125 is a useful discriminative marker for epithelial ovarian cancer. In another clinical study, Raungkaewmanee et al. (2012) showed that all blood components elevation was associated with adverse characteristic features and poor
prognosis in EOC. PLR was a better prognostic indicator for EOC compared with thrombocytosis or NLR. The current study has the advantage that to the best of our knowledge, it is the first study to evaluate the role of MPV in EOC. MPV has been previously evaluated in gastric carcinoma, hepatocellular carcinoma, pancreatic adenocarcinoma and endometrial carcinoma (Kılınçalp et al. 2013; Oge et al. 2013). Kılıncalp et al. (2013) determined that MPV levels were significantly higher in preoperative GC patients compared with healthy subjects. Similar to the current study, they showed that surgical tumour resection resulted in a significant decrease in MPV values. In another newly published report, Oge et al. (2013) demonstrated similar results in patients with endometrial carcinoma. There were also some limitations in the current study. First, the patient population in the study was heterogeneous, consisting of both early and advanced stage. Another limitation was surgery failure. Only one-third had optimal surgery in contrast to similar studies. In conclusion, this study documented that MPV and NLR were higher in preoperative EOC patients compared with postoperative values and healthy subjects. Pre- and postoperative MPV and NLR measurements in such patients may provide a simple method to demonstrate treatment effectiveness as for CA125. Further studies in a larger and more homogeneous population are required to validate the importance of MPV.
Acknowledgements We thank Professor Yuksel Bek and Dr Berkhan Topaktas for their advice on the statistical analyses. Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
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