Single and combined use of red cell distribution width, mean platelet volume, and cancer antigen 125 for differential diagnosis of ovarian cancer and benign ovarian tumors

Qin, Yuanyuan; Wu, Yangyang; Xian, Xiaoying; Qin, Jinqiu; Lai, Zhan-feng; Liao, Lin; Lin, Faquan

doi:10.1186/s13048-018-0382-3

Cited by 25 publications

(21 citation statements)

References 28 publications

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“…Despite a great progress in the diagnosis and therapy of it, the survival of patients with OC is still not optimistic. 19 In our study, we verified that SNHG3, overexpressed in OC, can be adopted for diagnosis of OC, and the high expression of it indicated a poor prognosis of patients. We found that knockdown of SNHG3 could inhibit the growth of OC cells and affect the biological function of OC cells through the miR-339-5p/TRPC3 axis, which confirmed that SNHG3 is expected to be a potential marker for diagnosis, treatment and prognosis evaluation of OC.…”

Section: Discussionsupporting

confidence: 65%

<p>Long-Chain Non-Coding RNA SNHG3 Promotes the Growth of Ovarian Cancer Cells by Targeting miR-339-5p/TRPC3 Axis</p>

Liu

Zhou

et al. 2020

OTT

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Background Long-chain non-coding RNA (lncRNA) small nucleolar RNA host gene 3 (SNHG3) is reportedly overexpressed in malignant tumors, but its regulatory role in human ovarian cancer (OC) is not fully understood. Methods A qRT-PCR assay was carried out to detect the level of SNHG3 in OC tissues, serum and cells, a CCK-8 assay to measure the proliferation of OC cells, a transwell assay to measure the invasion and migration of OC cells, and a flow cytometry to detect the cell cycle distribution and apoptosis rate of OC cells. In addition, in vivo experiment was also conducted to determine the effect of SNHG3 on the growth of OC cells. Results SNHG3 was overexpressed in OC tissues, serum, and cells, and the overexpression in serum indicated a poor prognosis of patients. It was also found that knockdown of SNHG3 could inhibit the malignant phenotypes of OC cells, cause G1/G0 cell cycle arrest, and intensify apoptosis. Furthermore, in in vitro experiments, the growth ability of OC cells was inhibited under knockdown of SNHG3. Assays for relationship verification showed that SNHG3 regulated the expression of miR-339-5p and the canonical transient receptor potential 3 (TRPC3), and the rescue experiment revealed that co-transfection of si-SNHG3+miR-339-5p-inhibitor or si-SNHG3+pcDNA3.1-TRPC3 could reverse the effects of knockdown of SNHG3 on the biological behavior of OC cells. Conclusion SNHG3 can be adopted as a marker for diagnosis and prognosis evaluation of OC and it plays a role in the progression of OC by enabling the miR-339-5p sponge to regulate TRPC3 expression.

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Section: Discussionsupporting

confidence: 65%

<p>Long-Chain Non-Coding RNA SNHG3 Promotes the Growth of Ovarian Cancer Cells by Targeting miR-339-5p/TRPC3 Axis</p>

Liu

Zhou

et al. 2020

OTT

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“…MPV is also a useful indicator in some inflammatory diseases, and it has been associated with disease activity and severity of inflammation [18]. Released inflammatory mediators in cancer increase platelet activation, leading to a subsequent change in MPV [19]. The current study showed that MPV increased in lung cancer patients compared to healthy subjects, showing that the process of lung cancer may be associated with platelet activity and result in the variation of MPV.…”

Section: Discussionsupporting

confidence: 51%

Absolute Neutrophil Count and Mean Platelet Volume in the Blood as Biomarkers to Detect Lung Cancer

2020

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Objective. Inflammation plays an extremely considerable role in the development and progression of malignancies. Absolute neutrophil count (ANC) and mean platelet volume (MPV) in blood are associated with various inflammatory conditions and resulted in independent prognostic factors for lung cancer. However, whether ANC and MPV can be diagnostic markers for lung cancer remains unknown. This retrospective study investigated the roles of ANC and MPV, either alone or combined, in diagnosing lung cancer. Methods. This study analyzed data from lung cancer patients and healthy individuals in Wuxi People’s Hospital Affiliated with Nanjing Medical University. The Mann–Whitney U-test was performed to compare differences between lung cancer patients and healthy individuals. Spearman’s correlation analysis was used to assess correlations. Receiver operating characteristic (ROC) curves were performed to determine diagnostic accuracy. Results. 209 patients diagnosed with lung cancer and 236 healthy subjects were enrolled in this study. Levels of ANC and MPV increased in lung cancer patients compared with healthy individuals (P<0.001). ANC had statistically significant negative weak correlation with albumin concentrations (r=‐0.154, P=0.026), and MPV had statistically significant negative weak correlation with total protein concentrations (r=‐0.153, P=0.027) in lung cancer patients. ANC and neutrophil-to-lymphocyte ratio had statistically significant positive correlation in both lung cancer patients (r=0.756, P<0.001) and healthy subjects (r=0.639, P<0.001). MPV and platelet-to-lymphocyte ratio had statistically significant negative weak correlation in both lung cancer patients (r=‐0.242, P<0.001) and healthy subjects (r=‐0.325, P<0.001). ANC had sensitivity (SEN) and specificity (SPE) of 0.512 and 0.809, respectively, and the area under the curve (AUC) with 95% confidence interval (95% CI) was 0.656 (0.603-0.710). SEN and SPE of MPV were 0.928 and 0.708, respectively, and the AUC (95% CI) was 0.913 (0.889-0.938). When ANC and MPV were combined, SEN and SPE became 0.842 and 0.835, respectively, and the AUC (95% CI) became 0.919 (0.895-0.943). Conclusions. Compared with ANC or MPV alone, the combination of ANC and MPV can improve diagnostic ability to distinguish lung cancer patients from healthy subjects.

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“…The DD level seemed to outperform the CA-125 as a diagnostic biomarker, even for early stage EOC, where 73–83% of patients had elevated DD and 33–39% had elevated CA-125 [20, 22]. Interestingly, CA-125 in combinations with the red cell volume distribution width and the mean platelet volume (parameters usually measured as part of the whole blood cell count) may facilitate the early detection and differential diagnosis of ovarian cancer compared with benign ovarian tumors [58]. Measurement of serum CA-125 is routinely used to aid diagnosis and in a follow-up of patients with EOC.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study

Stukan

Badocha

Ratajczak³

2019

BMC Cancer

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Background Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA) method and previously described models. Methods This prospective, single-center observational study included consecutive patients. We collected systematic ultrasound and clinical data, including cancer antigen 125, D-dimer (DD) levels and platelet count. Histological examinations served as the reference standard. We performed univariate and multivariate regressions, and Bayesian information criterion (BIC) to assess the optimal model. Data were split into 2 subsets: training, for model development (190 observations) and testing, for model validation ( n = 100). Results Among 290 patients, 52% had malignant disease, including epithelial ovarian cancer (72.8%), metastatic disease (14.5%), borderline tumors (6.6%), and non-epithelial malignancies (4.6%). Significant variables were included into a multivariate analysis. The optimal model, included three independent factors: solid areas, the color score, and the DD level. Malignant and benign lesions had mean DD values of 2.837 and 0.354 μg/ml, respectively. We transformed established formulae into a web-based calculator ( http://gin-onc-calculators.com/gynonc.php ) for calculating the adnexal mass malignancy risk. The areas under the curve (AUCs) for models compared in the testing set were: our model (0.977), Simple Rules risk calculation (0.976), Assessment of Different NEoplasias in the adneXa (ADNEX) (0.972), Logistic Regression 2 (LR2) (0.969), Risk of Malignancy Index (RMI) 4 (0.932), SUA (0.930), and RMI3 (0.912). Conclusions Two simple ultrasound predictors and the DD level (also included in a mathematical model), when used by gynecologist oncologist, discriminated malignant from benign ovarian lesions as well or better than other more complex models and the SUA method. These parameters (and the model) may be clinically useful for planning adequate management in the cancer center. The model needs substantial validation. Electronic supplementary material The online version of this article (10.1186/s12885-019-5629-x) contains supplementary material, which is available to authorized users.

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Single and combined use of red cell distribution width, mean platelet volume, and cancer antigen 125 for differential diagnosis of ovarian cancer and benign ovarian tumors

Cited by 25 publications

References 28 publications

<p>Long-Chain Non-Coding RNA SNHG3 Promotes the Growth of Ovarian Cancer Cells by Targeting miR-339-5p/TRPC3 Axis</p>

<p>Long-Chain Non-Coding RNA SNHG3 Promotes the Growth of Ovarian Cancer Cells by Targeting miR-339-5p/TRPC3 Axis</p>

Absolute Neutrophil Count and Mean Platelet Volume in the Blood as Biomarkers to Detect Lung Cancer

Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study

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