| 1. |
- 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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| 2. |
- 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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| 3. |
- Klaubauf, Sylvia, 1981, et al.
(author)
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Similar is not the same: Differences in the function of the (hemi-)cellulolytic regulator XlnR (Xlr1/Xyr1) in filamentous fungi
- 2014
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In: Fungal Genetics and Biology. - 1096-0937 .- 1087-1845. ; 72, s. 73-81
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Journal article (peer-reviewed)abstract
- The transcriptional activator XlnR (Xlr1/Xyr1) is a major regulator in fungal xylan and cellulose degradation as well as in the utilization of d-xylose via the pentose catabolic pathway. XlnR homologs are commonly found in filamentous ascomycetes and often assumed to have the same function in different fungi. However, a comparison of the saprobe Aspergillus niger and the plant pathogen Magnaporthe oryzae showed different phenotypes for deletion strains of XlnR. In this study wild type and xlnR/xlr1/xyr1 mutants of five fungi were compared: Fusarium graminearum, M. oryzae, Trichoderma reesei, A. niger and Aspergillus nidulans. Growth profiling on relevant substrates and a detailed analysis of the secretome as well as extracellular enzyme activities demonstrated a common role of this regulator in activating genes encoding the main xylanolytic enzymes. However, large differences were found in the set of genes that is controlled by XlnR in the different species, resulting in the production of different extracellular enzyme spectra by these fungi. This comparison emphasizes the functional diversity of a fine-tuned (hemi-)cellulolytic regulatory system in filamentous fungi, which might be related to the adaptation of fungi to their specific biotopes. Data are available via ProteomeXchange with identifier PXD001190.
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