Tumor-educated platelets: biomarker mirage or reality? (EN)
Post on FEBS by Anneleen Decock
What is the EACR - Molecular Oncology Editorial Fellowship?
FEBS collaborated with the European Association for Cancer Research (EACR) to offer a
Fellowship to an EACR member for the opportunity to gain knowledge and experience of scientific publishing through a short-term fellowship with the
FEBS journal Molecular Oncology.
We are pleased to share here the call entry from the runner-up, Anneleen Decock (OncoRNALab, Cancer Research Institute Ghent, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium).
Molecular Oncology and EACR hope to run the Fellowship in the future (keep an eye out on their websites). In the meantime, to practice your writing skills, consider applying to the
2024 Molecular Oncology Writing Competition: Impact of the exposome on cancer risk.
Tumor-educated platelets: biomarker mirage or reality?
Molecular profiling of cancer patients is the cornerstone of precision oncology. The discovery that (parts of) tumor cells enter the bloodstream has spurred the use of blood-based liquid biopsies for precision oncology purposes. Different blood components have been analyzed to achieve this goal, including circulating tumor cells, cell-free DNA and RNA, and extracellular vesicles. Most recently, platelets have emerged as a novel biosource for liquid biopsy-based studies. Besides their function in hemostasis and wound healing, platelets contribute to tumor growth, cancer cell transmigration, and metastasis [1]. In addition, different studies have shown that cancer patients demonstrate altered platelet RNA profiles, resulting from either tumor-induced changes in the transcriptional state of bone-marrow megakaryocytes, the sequestration of tumor-derived transcripts, or the induction of specific splicing activity during platelet circulation [1–3]. Molecular interrogation of the RNA content from these so-called tumor-educated platelets (TEPs) may therefore reveal novel cancer biomarkers.
A pioneering study by Best et al. provided compelling evidence for the clinical relevance of platelets in molecular cancer diagnostics [2]. Using messenger RNA (mRNA) sequencing data obtained from platelets of both healthy individuals and cancer patients (diagnosed with different cancer types such as glioblastoma, non-small-cell lung, colorectal, pancreatic, hepatobiliary or breast cancer), they created a self-learning support vector machine (SVM)-based algorithm called ThromboSeq to accurately differentiate healthy and cancerous samples, as well as to classify specific cancer types. In addition, platelet mRNA onco-signatures could be used as a surrogate for tumor tissue biomarkers that enable cancer patient stratification and therapy selection [2]. Building upon these successes, the ThromboSeq classifier algorithm was further optimized and applied to a wide range of cancer types, and showed to be a promising tool for the clinical implementation of liquid biopsy-based precision oncology [3–6].
However, the enthusiasm to clinically apply this methodology somewhat dampened by a recent attempt to validate its use for breast cancer patient identification [7]. Various concerns related to the methodology were raised. Platelet mRNA, and particularly the abundance of genes associated with platelet activation, exhibited significant variability among samples collected at different hospital sites, even though these institutions followed identical standardized sample collection protocols. This led to the conclusion that the ThromboSeq platform seemed to be sensitive to within-protocol variation, possibly caused by differences in aspects such as the volume of the blood collection tubes, the time interval between blood withdrawal and platelet isolation, or the presence of leucocyte contamination. Furthermore, variances in the health and treatment of subjects may have contributed to the inability to validate the ThromboSeq platform. As such, thorough revision of the protocol is required before TEP RNA-based classifiers can be considered for clinical use [7].
In conclusion, while the concept of TEPs as cancer biomarkers is undeniably intriguing, we must ensure that our pursuit of innovative biomarkers does not outpace the rigorous scientific scrutiny required for their translation into effective clinical tools. Only in-depth examination and comprehensive independent validation can ascertain the true biomarker value of platelets and leverage their potential for meaningful advancements in cancer diagnostics.
References
-
Haemmerle M, Stone RL, Menter DG, Afshar-Kharghan V, Sood AK. The platelet lifeline to cancer: Challenges and Opportunities. Cancer Cell. 2018;33(6):965–83.
-
Best MG, Sol N, Kooi I, Tannous J, Westerman BA, Rustenburg F, et al. RNA-seq of tumor-educated platelets enables blood-based pan-cancer, multiclass, and molecular pathway cancer diagnostics. Cancer Cell. 2015;28(5):666–76.
-
Best MG, Sol N, In ‘t Veld SGJG, Vancura A, Muller M, Niemeijer ALN, et al. Swarm intelligence-enhanced detection of non-small-cell lung cancer using tumor-educated platelets. Cancer Cell. 2017;32(2):238–252.e9.
-
Best MG, In ’t Veld SGJG, Sol N, Wurdinger T. RNA sequencing and swarm intelligence–enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA. Protoc. 2019;14(4):1206–34.
-
In ’t Veld SGJG, Arkani M, Post E, Antunes-Ferreira M, D’Ambrosi S, Vessies DCL, et al. Detection and localization of early- and late-stage cancers using platelet RNA. Cancer Cell. 2022;40(9):999-1009.e6.
-
Heinhuis KM, In ’t Veld SGJG, Dwarshuis G, van den Broek D, Sol N, Best M, et al. RNA-sequencing of tumor-educated platelets, a novel biomarker for blood-based sarcoma diagnostics. 2020;12(6):1372.
-
Liefaard MC, Moore KS, Mulder L, van den Broek D, Wesseling J, Sonke GS, et al. Tumour-educated platelets for breast cancer detection: biological and technical insights. Br J Cancer. 2023;128(8):1572–81.
Original post can be found
here.
Image by
fernando zhiminaicela from
Pixabay
FEBS collaborated with the European Association for Cancer Research (EACR) to offer a Fellowship to an EACR member for the opportunity to gain knowledge and experience of scientific publishing through a short-term fellowship with the FEBS journal Molecular Oncology.
We are pleased to share here the call entry from the runner-up, Anneleen Decock (OncoRNALab, Cancer Research Institute Ghent, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium).
Molecular Oncology and EACR hope to run the Fellowship in the future (keep an eye out on their websites). In the meantime, to practice your writing skills, consider applying to the 2024 Molecular Oncology Writing Competition: Impact of the exposome on cancer risk.
Tumor-educated platelets: biomarker mirage or reality?
Molecular profiling of cancer patients is the cornerstone of precision oncology. The discovery that (parts of) tumor cells enter the bloodstream has spurred the use of blood-based liquid biopsies for precision oncology purposes. Different blood components have been analyzed to achieve this goal, including circulating tumor cells, cell-free DNA and RNA, and extracellular vesicles. Most recently, platelets have emerged as a novel biosource for liquid biopsy-based studies. Besides their function in hemostasis and wound healing, platelets contribute to tumor growth, cancer cell transmigration, and metastasis [1]. In addition, different studies have shown that cancer patients demonstrate altered platelet RNA profiles, resulting from either tumor-induced changes in the transcriptional state of bone-marrow megakaryocytes, the sequestration of tumor-derived transcripts, or the induction of specific splicing activity during platelet circulation [1–3]. Molecular interrogation of the RNA content from these so-called tumor-educated platelets (TEPs) may therefore reveal novel cancer biomarkers.
A pioneering study by Best et al. provided compelling evidence for the clinical relevance of platelets in molecular cancer diagnostics [2]. Using messenger RNA (mRNA) sequencing data obtained from platelets of both healthy individuals and cancer patients (diagnosed with different cancer types such as glioblastoma, non-small-cell lung, colorectal, pancreatic, hepatobiliary or breast cancer), they created a self-learning support vector machine (SVM)-based algorithm called ThromboSeq to accurately differentiate healthy and cancerous samples, as well as to classify specific cancer types. In addition, platelet mRNA onco-signatures could be used as a surrogate for tumor tissue biomarkers that enable cancer patient stratification and therapy selection [2]. Building upon these successes, the ThromboSeq classifier algorithm was further optimized and applied to a wide range of cancer types, and showed to be a promising tool for the clinical implementation of liquid biopsy-based precision oncology [3–6].
However, the enthusiasm to clinically apply this methodology somewhat dampened by a recent attempt to validate its use for breast cancer patient identification [7]. Various concerns related to the methodology were raised. Platelet mRNA, and particularly the abundance of genes associated with platelet activation, exhibited significant variability among samples collected at different hospital sites, even though these institutions followed identical standardized sample collection protocols. This led to the conclusion that the ThromboSeq platform seemed to be sensitive to within-protocol variation, possibly caused by differences in aspects such as the volume of the blood collection tubes, the time interval between blood withdrawal and platelet isolation, or the presence of leucocyte contamination. Furthermore, variances in the health and treatment of subjects may have contributed to the inability to validate the ThromboSeq platform. As such, thorough revision of the protocol is required before TEP RNA-based classifiers can be considered for clinical use [7].
In conclusion, while the concept of TEPs as cancer biomarkers is undeniably intriguing, we must ensure that our pursuit of innovative biomarkers does not outpace the rigorous scientific scrutiny required for their translation into effective clinical tools. Only in-depth examination and comprehensive independent validation can ascertain the true biomarker value of platelets and leverage their potential for meaningful advancements in cancer diagnostics.
References
-
Haemmerle M, Stone RL, Menter DG, Afshar-Kharghan V, Sood AK. The platelet lifeline to cancer: Challenges and Opportunities. Cancer Cell. 2018;33(6):965–83.
-
Best MG, Sol N, Kooi I, Tannous J, Westerman BA, Rustenburg F, et al. RNA-seq of tumor-educated platelets enables blood-based pan-cancer, multiclass, and molecular pathway cancer diagnostics. Cancer Cell. 2015;28(5):666–76.
-
Best MG, Sol N, In ‘t Veld SGJG, Vancura A, Muller M, Niemeijer ALN, et al. Swarm intelligence-enhanced detection of non-small-cell lung cancer using tumor-educated platelets. Cancer Cell. 2017;32(2):238–252.e9.
-
Best MG, In ’t Veld SGJG, Sol N, Wurdinger T. RNA sequencing and swarm intelligence–enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA. Protoc. 2019;14(4):1206–34.
-
In ’t Veld SGJG, Arkani M, Post E, Antunes-Ferreira M, D’Ambrosi S, Vessies DCL, et al. Detection and localization of early- and late-stage cancers using platelet RNA. Cancer Cell. 2022;40(9):999-1009.e6.
-
Heinhuis KM, In ’t Veld SGJG, Dwarshuis G, van den Broek D, Sol N, Best M, et al. RNA-sequencing of tumor-educated platelets, a novel biomarker for blood-based sarcoma diagnostics. 2020;12(6):1372.
-
Liefaard MC, Moore KS, Mulder L, van den Broek D, Wesseling J, Sonke GS, et al. Tumour-educated platelets for breast cancer detection: biological and technical insights. Br J Cancer. 2023;128(8):1572–81.
Original post can be found here.
Image by fernando zhiminaicela from Pixabay