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Journal ArticleDOI

A combination of platelet features allows detection of early-stage cancer

TL;DR: Multiple platelet features, including platelet count, volume and protein content, were significantly changed in lung and head of pancreas cancer patients, and a cancer type-specific combination of these platelets features can be used to discriminate between patients with early-stage cancer and healthy individuals.
About: This article is published in European Journal of Cancer.The article was published on 2017-07-01 and is currently open access. It has received 42 citations till now. The article focuses on the topics: Cancer & Beta-thromboglobulin.

Summary (3 min read)

1. Introduction

  • Detection of cancer in its early stages radically improves the effectiveness of available treatment and overall prognosis of patients [1].
  • Up to now, studies searching for biomarkers are mostly based on blood plasma or serum parameters.
  • In addition, platelets may become activated systemically or within the tumour, potentially resulting in release of platelet content into the circulation [3].
  • Altogether, data from literature suggest that several platelet characteristics are affected in cancer patients.
  • These features, either alone or in combination, may be useful tools in the detection of (early stages of) cancer.

2.1. Study design and participants

  • This study was performed in accordance with the Declaration of Helsinki and approved by the medical ethical committee of Maastricht University Medical Centerþ.
  • Informed consent was obtained from all participants.
  • Patients with clinically established and histologically proven untreated primary lung (n Z 86) or head of pancreas cancer (n Z 42, including pancreas head cancer [n Z 28], distal cholangiocarcinoma [n Z 8] and duodenumcarcinoma [n Z 6]), that were eligible for surgical resection, were included between July 2012 and October 2014.
  • Exclusion criteria were previous history of cancer, neo-adjuvant chemotherapy or radiotherapy, use of platelet-influencing drugs such as aspirin, blood or platelet transfusion during the previous 14 days, active inflammatory disease, non-healing ulcers or fractures.
  • Staging was performed in accordance with the tumour-node-metastasis (TNM) classification (version 7) of the Union for International Cancer Control [9].

2.2. Procedures

  • Blood from all patients and healthy individuals was collected.
  • In case of cancer patients, sampling occurred within 1 week before initiation of treatment.
  • To prevent platelet activation during blood collection and sample preparation, blood was collected as described before [10].
  • The procedures for quantification of platelet count, volume and activation status, as well as concentrations of various growth factors and chemokines in platelets and plasma.
  • ELISA measurements in all patient and matching control samples were performed using the same assay, simultaneously and in the same institution.

2.3. Statistics

  • Statistical analyses were performed using SPSS (version 22; SPSS Inc, Chicago, USA) and R (version 3.2.2, R core development team).
  • Data are presented as means with standard errors of the mean unless otherwise indicated.
  • Patient data were compared to data from the healthy control groups using the t-test for continuous variables and Pearson’s chi-square test for categorical variables.
  • Spearman’s rank correlation was used to test the association between variables.
  • P-values less than 0.05 were considered statistically significant.

2.4. Development of diagnostic models

  • For both cancer groups, logistic regression was used to estimate diagnostic models.
  • Model performance was assessed by Nagelkerke’s R2 statistic and by quantifying discrimination.
  • Discrimination is the model’s ability to distinguish between those that have cancer and those who do not.
  • 1000 bootstrap samples of the original data were drawn, and similar diagnostic models were estimated using these data.
  • The average difference in diagnostic model performance between the bootstrap sample and the original sample provided estimates of optimism in the performance measures.

3. Results

  • Blood was collected from 86 lung cancer patients, 42 patients diagnosed with head of pancreas cancer and a total of 92 healthy individuals.
  • Importantly, the latter group contained individuals that were matched with respect to gender and age to both groups of cancer patients.
  • All cancer patients were treatment naive at the moment of blood sampling.
  • Detailed characteristics of the study populations are presented in Table 1.
  • In the healthy individuals, both gender and age appeared to be related to some of the platelet characteristics.

3.1. Platelet characteristics in patients with untreated lung cancer

  • Platelet counts were not different as compared to controls in patients with early-stage (stage IeII) lung cancer, but significantly increased in case of advanced (stage IIIeIV) lung cancer (Fig. 1A).
  • Concentrations of VEGF, PDGF, CTAPIII, PF4 and TSP-1 sented as means with standard errors of the means.
  • Strikingly, changes in platelet content did not correspond with concentration changes of the same proteins in PFP (Fig. 1HeL).
  • No differences between patients and controls were found (Supplemental Fig. 1A and B).
  • This suggests that the increase in PDGF, CTAPIII and PF4 plasma concentrations in patients with lung cancer is mainly due to systemic or intratumoural platelet activation, leading to secretion of their content.

3.2. A combination of platelet features discriminates lung cancer patients from controls

  • Data from 172 individuals (86 patients with lung cancer and 86 sex- and age-matched controls) were available for multivariable modelling.
  • All measured parameters were entered into the model: platelet count, MPV and concentrations of VEGF, PDGF, PF4, CTAPIII and TSP-1 in platelets and PFP.
  • Nagelkerke’s R2 of the diagnostic model was 0.572, indicating that the model fits the data well.
  • This demonstrates that the model discriminated very well between lung cancer cases and controls in their study population.

3.3. A platelet-based marker for the presence of head of pancreas cancer

  • In patients diagnosed with head of pancreas cancer, several platelet parameters were found to be substantially different from the control group as well.
  • VEGF concentration was significantly increased in platelets of patients with early- and late-stage head of pancreas cancer (Fig. 3C), while no differences in platelet PDGF, CTAPIII, PF4 and TSP-1 concentrations were observed (Supplemental Fig. 2AeD).
  • Nagelkerke’s R2 of this model was 0.418, which is indicative of good model fit.
  • This parsimonious model discriminated well between patients with head of pancreas cancer and controls, as confirmed by the boxplots of predicted probability by the diagnostic model (Fig. 4B).

4. Discussion

  • The presence of a tumour in the human body appears to influence several platelet features.
  • The elevated PF4 and CTAPIII concentrations in plasma reveal the presence of activated platelets in the circulation of patients with lung or head of pancreas cancer.
  • Altogether, their study shows that multiple platelet characteristics are changed in patients with cancer, both in early and later stages of development.
  • One important issue in this interesting study is the nature of the control group, that is clearly younger and with a different gender distribution than most of the cancer groups.
  • Funding The Netherlands Organisation for Scientific Research (project number 017.008.143, to SS).

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Journal ArticleDOI
Guoqun Jia1, Jian Kong1, Changyu Yao1, Shilun Wu1, Wenbing Sun1 
TL;DR: Platelet lysates from HCC patients after RFA promoted the proliferation, migration, invasion and vasculogenic mimicry of HCC cells, which indicated that RFA in combination with anti-platelet drug may be used to improve the prognosis of H CC.
Abstract: Background: Platelets play important roles in tumorigenesis, angiogenesis and metastatic dissemination of tumor cells. Radiofrequency ablation (RFA) could increase the circulating tumor cells in patients with primary or metastatic lung tumors. Whether platelet lysates in hepatocellular carcinoma (HCC) after RFA promote tumor progression has not been elaborated. Methods: HCC patients within Milan Criteria and without taking anti-platelet drugs were selected in the study. MTT assay, colony formation assay, transwell assay, tube formation and western blot were used to evaluate the effect of platelet lysates on HCC cells in vitro. Lung metastatic assay was performed in vivo. Results: Platelet lysates from patients after RFA promoted cell proliferation, colony formation, migration, invasion and vasculogenic mimicry in Hep3B and HCCLM3 cells compared with those from patients before RFA. Platelet lysates after RFA significantly increased the expression of p-Akt, p-Smad3 and snail, and decreased the expression of E-cadherin compared with those before RFA in Hep3B and HCCLM3 cells. Hep3B-Luc2-tdT cells incubation with platelet lysates from patients after RFA displayed enhanced lung metastasis compared with those before RFA. Conclusions: Platelet lysates from HCC patients after RFA promoted the proliferation, migration, invasion and vasculogenic mimicry of HCC cells, which indicated that RFA in combination with anti-platelet drug may be used to improve the prognosis of HCC.

6 citations


Cites background from "A combination of platelet features ..."

  • ...Circulating platelets contain numerous proteins, including growth factors, chemokines and proteases, which are synthesized by megakaryocytes or absorbed from the blood by the platelets themselves [5]....

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TL;DR: It was found that patients with cancer had decreased numbers of platelets interacting, translocating and adhering to VWF and there were also reductions in the speed and distances that platelets traveled on VWF in comparison to healthy controls.
Abstract: Despite a fivefold increased risk of thromboembolism in patients with cancer, the mechanism of arterial thromboembolism is poorly understood. To address this, we investigated platelet function in c...

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TL;DR: The prognostic SS (SII-sarcopenia) was established based on SII and sarcopenia and is a reliable predictor of OS in patients with GC, and high SII is related to poor prognosis.

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Journal ArticleDOI
TL;DR: A risk prediction model based on these factors exhibited moderate predictive value for CP patients and had the best balance between sensitivity and specificity in the derivation and validation cohorts, respectively.
Abstract: Background: Patients with chronic pancreatitis (CP) have an increased risk of developing pancreatic cancer (PC). The purpose of this study was to identify predictors of PC in CP patients. Methods: Electronic medical records (EMRs) of CP patients from two cohorts were collected, and a logistic regression analysis was performed to investigate the risk factors for PC. Subsequently, we validated the value of the risk prediction model with the EMRs of a third cohort. Results: The derivation cohort consisted of 2,545 CP patients, and among them, 14 patients developed PC 7 years after CP diagnosis. Cyst of the pancreas [COP; odds ratio (OR): 4.37, 95% confidence interval (CI): 1.11 to 18.40, P=0.033], loss of weight (LW; OR: 3.21, 95% CI: 0.76 to 12.91, P=0.096) and high platelet (PLT) count (OR: 1.01 per 1 increment, 95% CI: 1.00 to 1.01, P=0.042) were independent risk factors for PC among CP patients. A risk prediction equation was constructed as follows: ln[p/(1–p)] = –6.68 + 1.55COP + 1.23LW + 0.0046PLT. The areas under the receiver operating characteristic (ROC) curve of our risk score were 0.83 and 0.72 in the derivation and validation cohorts, respectively. A score >0.0128 and >0.0122 had the best balance between sensitivity and specificity in the derivation and validation cohorts, respectively. Conclusions: In CP patients, LW, COP and high PLT count were identified as novel predictors of PC. A risk prediction model based on these factors exhibited moderate predictive value for CP patients.

4 citations


Cites background from "A combination of platelet features ..."

  • ...Similarly, the level of PLT in PC patients in an early tumor-node-metastasis (TNM) stage (I, II) was significantly higher than that in healthy controls (22)....

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Journal ArticleDOI
TL;DR: Clinical applications of platelet detection using the platelet count, mean platelet volume, platelet RNA and protein profiles for human cancers are focused on and the gap in bringing these implementations into the clinic is discussed.
Abstract: Cancer is still a leading cause of death worldwide and liquid biopsy is a powerful tool that can be applied to different stages of cancer screening and treatment. However, as the second most abundant cell type in the bloodstream, platelets are isolated through well-established and fast methods in clinic but their value as a BioSource of cancer biomarkers is relatively recent. Many studies demonstrated the bidirectional interaction between cancer cells and platelets. Platelets transfer various proteins (e.g., growth factors, cytokine, chemokines) and RNAs (e.g., mRNA, lncRNA, miRNA, circRNA) into the tumor cells and microenvironment, leading the stimulation of tumor growth and metastasis. In turn, the platelet clinical characteristics (e.g., count and volume) and contents (e.g., RNA and protein) are altered by the interactions with cancer cells and this enables the early cancer detection using these features of platelets. In addition, platelet-derived microparticles also demonstrate the prediction power of being cancer biomarkers. In this review, we focus on the clinical applications of platelet detection using the platelet count, mean platelet volume, platelet RNA and protein profiles for human cancers and discuss the gap in bringing these implementations into the clinic.

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TL;DR: The number of cancer survivors continues to increase because of both advances in early detection and treatment and the aging and growth of the population and for the public health community to better serve these survivors, the American Cancer Society and the National Cancer Institute collaborate to estimate the number of current and future cancer survivors.
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TL;DR: This paper presents a case study on survival analysis: Prediction of secondary cardiovascular events and lessons from case studies on overfitting and optimism in prediction models.
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TL;DR: Suggested that could be demonstrated a live birth and data and demonstrated that were excluded, and developed and could be appropriate aac evidence.
Abstract: Suggested that could be demonstrated a live birth and data. Supplementary file appendix statistics table, demonstrated that were excluded. Accessed for the therapy process light microscopic evaluation and others. Most relevant and templeton et al quiz ref idbecause. High blood cell count admission to, patients at a thorough review. Were excluded although over either a strong test sample. We developed and could be appropriate aac evidence. Setting number of a language activity they. Training programs still do not however it may differ from keynote papers on epidemiology. We excluded all studies but predictive performance three oocytes. High blood cell count less than that were drawn from to reduce the growing database containing. Consequently the basis of patients making clinical signs and other sbis. Implementation elsewhere enhances the performance measurement, methods of female age were responsible for my patients. In models are limited generalizability for aac institute public reporting results were. We did find that can be used a model. Informed consent was defined according to, permit meta analysis process starts. In predicted risks was assessed by phone at increased. In socioeconomically disadvantaged populations we used, and evidence mckibbon wilczynski hayward. That diagnoses we abstracted the performance of or patient data and increasing odds ratios. Practical aspects of how we excluded university this for antibiotic prescription. Other sbis in the primary or inhibin levels of observed clinical experience.

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Frequently Asked Questions (2)
Q1. What are the contributions in "A combination of platelet features allows detection of early-stage cancer" ?

• A submitted manuscript is the version of the article upon submission and before peer-review. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher 's website. The final author version and the galley proof are versions of the publication after peer review. The final published version features the final layout of the paper including the volume, issue and page numbers. 

Future research is needed to further investigate the clinical relevance of their findings. Platelets are a new and uncharted source of information, which need to be further explored in blood-based biomarker research.