细胞外囊泡带有转录的“暗物质”，揭示了组织特异性信息

从真核生物到原核生物，所有细胞都会分泌细胞外囊泡（EV），作为其常规稳态，细胞间通信和货物处置的一部分。累积的证据表明，小型电动汽车携带功能性的小RNA，可能是细胞外信使和液体生物记号标记物。然而，由于临界局限性，包括用于测序的方案，短读数（20-50 nt）的次优比对，以及未经表征的基因组注释的临界协议，疾病进展过程中与EV相关的小RNA的完整转录组景观差异很差。在这项研究中，我们研究了由内源基因引起的与EV相关的小型未注释的RNA，并且是基因组“暗物质”的一部分，该基因可能在调节基因表达和翻译机制中起关键作用。为了解决这个问题，我们从人类前列腺癌和良性组织中创建了一个独特的小型RNASEQ数据集，以及源自血液（前后和后切除术），尿液和人类前列腺癌上皮细胞系的电动汽车。然后，我们开发了一种无监督的基于数据的生物信息学管道，该管道识别与生物学相关的转录信号，而与其基因组注释无关。使用这种方法，我们发现了与组织特异性表型相关的转录组的未注销基因组区域（UGRS）出现的不同的EV-RNA表达模式。我们将这些新颖的EV相关的小RNA命名为“ EV-UGRS”或“ EV-DARK MATTER”。在这里，我们证明了来自侵略性前列腺癌受试者的循环血清EV中的EV-UGR基因表达被约100倍（FDR <0.05）下调。值得注意的是，这些EV-UGRS表达特征在同一随访患者中根治性前列腺切除术后恢复（上调）。最后，我们开发了一种STEM-LOOP RT-QPCR分析，该测定法验证了前列腺癌特异性EV-UGR，用于选择性液体的诊断。总体而言，使用无监督的数据驱动方法，我们研究了EV-转录组的“暗物质”，并证明EV-UGR携带组织特异性信息，这些信息会显着改变前列腺癌患者的前后切除术和后胸膜后切除术。尽管需要在随机临床试验中进行进一步验证，但这类新型的EV-RNA通过避免了前列腺癌中高度侵入性的活检程序，在液体生物检查中保持了希望。

From eukaryotes to prokaryotes, all cells secrete extracellular vesicles (EVs) as part of their regular homeostasis, intercellular communication, and cargo disposal. Accumulating evidence suggests that small EVs carry functional small RNAs, potentially serving as extracellular messengers and liquid-biopsy markers. Yet, the complete transcriptomic landscape of EV-associated small RNAs during disease progression is poorly delineated due to critical limitations including the protocols used for sequencing, suboptimal alignment of short reads (20-50 nt), and uncharacterized genome annotations-often denoted as the 'dark matter' of the genome. In this study, we investigate the EV-associated small unannotated RNAs that arise from endogenous genes and are part of the genomic 'dark matter', which may play a key emerging role in regulating gene expression and translational mechanisms. To address this, we created a distinct small RNAseq dataset from human prostate cancer & benign tissues, and EVs derived from blood (pre- & post-prostatectomy), urine, and human prostate carcinoma epithelial cell line. We then developed an unsupervised data-based bioinformatic pipeline that recognizes biologically relevant transcriptional signals irrespective of their genomic annotation. Using this approach, we discovered distinct EV-RNA expression patterns emerging from the un-annotated genomic regions (UGRs) of the transcriptomes associated with tissue-specific phenotypes. We have named these novel EV-associated small RNAs as 'EV-UGRs' or "EV-dark matter". Here, we demonstrate that EV-UGR gene expressions are downregulated by ∼100 fold (FDR < 0.05) in the circulating serum EVs from aggressive prostate cancer subjects. Remarkably, these EV-UGRs expression signatures were regained (upregulated) after radical prostatectomy in the same follow-up patients. Finally, we developed a stem-loop RT-qPCR assay that validated prostate cancer-specific EV-UGRs for selective fluid-based diagnostics. Overall, using an unsupervised data driven approach, we investigate the 'dark matter' of EV-transcriptome and demonstrate that EV-UGRs carry tissue-specific Information that significantly alters pre- and post-prostatectomy in the prostate cancer patients. Although further validation in randomized clinical trials is required, this new class of EV-RNAs hold promise in liquid-biopsy by avoiding highly invasive biopsy procedures in prostate cancer.