Platelet RNA enables accurate detection of ovarian cancer: an intercontinental, biomarker identification study
Yue Gao1,2, Chun-Jie Liu3, Hua-Yi Li1,2, Xiao-Ming Xiong1,2,17, Gui-Ling Li4, Sjors G.J.G. In ”t Veld5,6, Guang-Yao Cai1,2, Gui-Yan Xie3, Shao-Qing Zeng1,2, Yuan Wu1,2, Jian-Hua Chi1,2, Jia-Hao Liu1,2, Qiong Zhang3, Xiao-Fei Jiao1,2, Lin-Li Shi4, Wan-Rong Lu1,2, Wei-Guo Lv7, Xing-Sheng Yang8, Jurgen M.J. Piek9, Cornelis D de Kroon10, C.A.R. Lok11, Anna Supernat12, Sylwia Łapińska-Szumczyk13, Anna Łojkowska13, Anna J Żaczek12, Jacek Jassem14, Bakhos A. Tannous15, Nik Sol5,16, Edward Post5, Myron G. Best5, Bei-Hua Kong8, Xing Xie7, Ding Ma1,2, Thomas Wurdinger5(), An-Yuan Guo3(), Qing-Lei Gao1,2()
1. Department of Gynecological Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China 2. National Clinical Research Center for Obstetrics and Gynecology, Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China 3. Center for Artificial Intelligence Biology, Hubei Bioinformatics & Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China 4. Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China 5. Department of Neurosurgery, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands 6. Brain Tumor Center Amsterdam, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands 7. Department of Gynecological Oncology, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310011, China 8. Gynecological Oncology Key Laboratory, Qilu Hospital, Shandong University, Jinan 250100, China 9. Department of Obstetrics and Gynecology, Catharina Hospital, Michelangelolaan 2, 5623EJ Eindhoven, Eindhoven, The Netherlands 10. Department of Obstetrics and Gynecology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, The Netherlands 11. Department of Gynecological Oncology, Center of Gynecologic Oncology Amsterdam, Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands 12. Laboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Gdańsk, Poland 13. Department of Gynecology, Gynecological Oncology and Gynecological Endocrinology, Medical University of Gdańsk, Gdańsk, Poland 14. Department of Oncology and Radiotherapy, Medical University of Gdańsk, Gdańsk, Poland 15. Department of Neurology, Massachusetts General Hospital and Neuroscience Program, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA 16. Department of Neurology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands 17. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
Platelets are reprogrammed by cancer via a process called education, which favors cancer development. The transcriptional profile of tumor-educated platelets (TEPs) is skewed and therefore practicable for cancer detection. This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n = 3; Netherlands, n = 5; Poland, n = 1) between September 2016 and May 2019. The main out-comes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889–0.948), 0.923 (0.855–0.990), 0.918 (0.872–0.963), and 0.887 (0.813–0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889–0.955) in the combined validation cohort; 0.955 (0.912–0.997) in VC1; 0.939 (0.901–0.977) in VC2; 0.917 (0.824–1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, and early-stage ovarian cancer. However, these observations warrant prospective validations in a larger population before clinical utilities.
S Anders, P Pyl, W. Huber HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics (Oxford, England) 2015;31:166–169. https://doi.org/10.1093/bioinformatics/btu638
2
MG Best, N Sol, A Vancura et al. Swarm intelligence-enhanced detection of non-small-cell lung cancer using tumor-educated platelets. Cancer Cell 2017;32:238–252 e9. https://doi.org/10.1016/j.ccell.2017.07.004
3
MG Best, N Sol, T Wurdinger et al. RNA sequencing and swarm intelligence- enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA. Nat Protocols 2019;14:1206–1234. https://doi.org/10.1038/s41596-019-0139-5
4
L Chen, K Wang, L Li et al. Plasma exosomal miR-1260a, miR-7977 and miR-192-5p as diagnostic biomarkers in epithelial ovarian cancer. Future Oncol 2022;18:2919–2931. https://doi.org/10.2217/fon-2022-0321
5
M Chiesa, GI Colombo, L. Piacentini DaMiRseq-an R/Bioconductor package for data mining of RNA-Seq data: normalization, feature selection and classification. Bioinformatics 2018;34:1416–1418. https://doi.org/10.1093/bioinformatics/btx795
6
MS Cho, J Bottsford-Miller, HG Vasquez et al. Platelets increase the proliferation of ovarian cancer cells. Blood 2012;120:4869–4872. https://doi.org/10.1182/blood-2012-06-438598
7
N Colombo, C Sessa, A du Bois et al; ESMO-ESGO Ovarian Cancer Consensus Conference Working Group. ESMO-ESGO consensus conference recommendations on ovarian cancer: pathology and molecular biology, early and advanced stages, borderline tumours and recurrent disease. Ann Oncol 2019;30:672–705. https://doi.org/10.1093/annonc/mdz062
LC Edelstein, LM Simon, RT Montoya et al. Racial differences in human platelet PAR4 reactivity reflect expression of PCTP and miR-376c. Nat Med 2013;19:1609–1616. https://doi.org/10.1038/nm.3385
12
J Friedman, T Hastie, R. Tibshirani Regularization paths for generalized linear models via coordinate descent. J Stat Softw 2010;33:1–22. https://doi.org/10.18637/jss.v033.i01
Z Gu, R Eils, M. Schlesner Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 2016;32:2847–2849. https://doi.org/10.1093/bioinformatics/btw313
16
M Haemmerle, RL Stone, DG Menter et al. The platelet lifeline to cancer: challenges and opportunities. Cancer Cell 2018;33:965–983. https://doi.org/10.1016/j.ccell.2018.03.002
17
M Haemmerle, ML Taylor, T Gutschner et al. Platelets reduce anoikis and promote metastasis by activating YAP1 signaling. Nat Commun 2017;8:310. https://doi.org/10.1038/s41467-017-00411-z
18
JT Henderson, EM Webber, GF. Sawaya Screening for ovarian cancer: updated evidence report and systematic review for the US preventive services task force. JAMA 2018;319:595–606. https://doi.org/10.1001/jama.2017.21421
JT. Leek svaseq: removing batch effects and other unwanted noise from sequencing data. Nucleic Acids Res 2014;42:e161. https://doi.org/10.1093/nar/gku864
24
S Lheureux, M Braunstein, AM. Oza Epithelial ovarian cancer: evolution of management in the era of precision medicine. CA Cancer J Clin 2019a;69:280–304. https://doi.org/10.3322/caac.21559
M Love, W Huber, S. Anders Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014;15:550. https://doi.org/10.1186/s13059-014-0550-8
29
Q Meng, P Duan, L Li et al. Expression of placenta growth factor is associated with unfavorable prognosis of advanced-stage serous ovarian cancer. Tohoku J Exp Med 2018;244:291–296. https://doi.org/10.1620/tjem.244.291
30
U Menon, A Gentry-Maharaj, M Burnell et al. Ovarian cancer population screening and mortality after long-term follow-up in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): a randomised controlled trial. The Lancet 2021;397:2182–2193. https://doi.org/10.1016/S0140-6736(21)00731-5
31
T Motohara, K Masuda, M Morotti et al. An evolving story of the metastatic voyage of ovarian cancer cells: cellular and molecular orchestration of the adipose-rich metastatic microenvironment. Oncogene 2019;38:2885–2898. https://doi.org/10.1038/s41388-018-0637-x
32
J Prat, DG. Mutch Pathology of cancers of the female genital tract including molecular pathology. Int J Gynaecol Obstet 2018;143:93–108. https://doi.org/10.1002/ijgo.12617
R Sabatier, S Garnier, A Guille et al. Whole-genome/exome analysis of circulating tumor DNA and comparison to tumor genomics from patients with heavily pre-treated ovarian cancer: subset analysis of the PERMED-01 trial. Front Oncol 2022;12:946257. https://doi.org/10.3389/fonc.2022.946257
RL Stone, AM Nick, IA McNeish et al. Paraneoplastic thrombocytosis in ovarian cancer. N Engl J Med 2012;366:610–618. https://doi.org/10.1056/NEJMoa1110352
S Vaughan, JI Coward, sRC Bast et al. Rethinking ovarian cancer: recommendations for improving outcomes. Nat Rev Cancer 2011;11:719–725. https://doi.org/10.1038/nrc3144
40
R Wang, RL Stone, JT Kaelber et al. Electron cryotomography reveals ultrastructure alterations in platelets from patients with ovarian cancer. Proc Natl Acad Sci USA 2015;112:14266–14271. https://doi.org/10.1073/pnas.1518628112
41
T Wang, Y Gao, X Wang et al. Establishment of an optimized CTC detection model consisting of EpCAM, MUC1 and WT1 in epithelial ovarian cancer and its correlation with clinical characteristics. Chin J Cancer Res 2022;34:95–108. https://doi.org/10.21147/j.issn.1000-9604.2022.02.04
42
XR Xu, GM Yousef, H. Ni Cancer and platelet crosstalk: opportunities and challenges for aspirin and other antiplatelet agents. Blood 2018;131:1777–1789. https://doi.org/10.1182/blood-2017-05-743187
43
AD Yates, P Achuthan, W Akanni et al. Ensembl 2020. Nucleic Acids Res 2020;48:D682–D688.
44
C Yuan, X Liu, X Liu et al. The GADD45A (1506T>C) polymorphism is associated with ovarian cancer susceptibility and prognosis. PLoS One 2015;10:e0138692. https://doi.org/10.1371/journal.pone.0138692
45
M Zhang, S Cheng, Y Jin et al. Roles of CA125 in diagnosis, prediction, and oncogenesis of ovarian cancer. Biochim Biophys Acta Rev Cancer 2021;1875:188503. https://doi.org/10.1016/j.bbcan.2021.188503
46
A Zhu, JG Ibrahim, MI. Love Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Bioinformatics 2019;35:2084–2092. https://doi.org/10.1093/bioinformatics/bty895
