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- In ’t Veld, Sjors G.J.G., et al.
(author)
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Detection and localization of early- and late-stage cancers using platelet RNA
- 2022
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In: Cancer Cell. - : Elsevier. - 1535-6108 .- 1878-3686. ; 40:9, s. 999-1009.e6
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Journal article (peer-reviewed)abstract
- Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I–IV cancer patients and in half of 352 stage I–III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening.
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2. |
- Best, Myron G., et al.
(author)
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Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets
- 2017
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In: Cancer Cell. - : Elsevier. - 1535-6108 .- 1878-3686. ; 32:2, s. 238-252
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Journal article (peer-reviewed)abstract
- Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.
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