Cell-free RNA Research Articles

Abstract LB257: Possible involvement of PDL1 intrinsic signaling to acquired resistance to immunotherapy for renal cell carcinoma (RCC)

Abstract Immune checkpoint inhibitor (ICI) therapy has shown unprecedented results in RCC treatment, but durable responses have been hampered by acquired resistance (AR, initially respond but eventually develop cancer progression). Mechanisms for AR remain ambiguous. Previously, we reported elevated blood GPNMB to strongly associate with AR development. To study molecular mechanisms for AR-linked GPNMB elevation, we created an ICI-resistant RenCa (R-RenCa) mouse model by repeated selection of largest tumors in mice treated with PD1 Ab ICI. Parental cells (Gpnmblow) respond to ICI (S-RenCa), while R-RenCa is completely unresponsive to ICI and acquired Gpnmb overexpression (but PDL1 remained unchanged), recapitulating strong association of GPNMB with AR development. R-RenCa tumors displayed more immunosuppressive and angiogenic phenotypes and enhanced response to anti-Gpnmb Ab. In probing for genetic alterations unique to R-RenCa, whole exome seq analysis showed R-RenCa to bear a greater tumor mutation burden (184.9 and 174.6 mut/Mb for R- and S-RenCa, respectively) but no somatic mutations in beta-2 microglobulin and IFN-signal molecule genes known to be involved in AR. RNA-seq analysis showed; more transcriptionally active genes in R-RenCa tumors (heatmap analysis); more responsive genes to ICI (Volcano analysis); and dysregulation in microphthalmia (Mitf) family gene expression. Mitf RNA was upregulated 3-fold, but Tfe3 and other members downregulated 2-3-fold. RNA start sites of Mitf transcripts are highly heterogenous in R-RenCa compared to S-RenCa (Sashimi plot), indicating generation of more isoforms. Since Gpnmb promoter has E-boxes (DNA binding sites) for Mitf factor, we examined whether Mitf is responsible for Gpnmb expression using promoter-Luc reporter assays and found 4-fold higher in R-RenCa, which was lost completely in E-box-mutated promoter. In seeking transcriptional activators for Mitf gene, we found Sox10 factor to be upregulated in R-RenCa. The molecular link of Sox10-Mitf-Gpnmb was shown by the data of gene-knock down experiments that Sox10-siRNA diminished Mitf and Gpnmb expression completely, and Mitf-siRNA had no effect on Sox10 expression but diminished Gpnmb expression. We then studied mechanisms for Sox10 activation and found PDL1 signaling (triggered by Ab-crosslinking) to induce Sox10 RNA expression in tumor cells, which was 80% abrogated by deleting the RMLDVEKC cytoplasmic motif known to protect tumor cells from IFN cytotoxicity. For human relevance of Sox10-Mitf axis activation, we employed nested qRT-PCR of cell-free RNA (cfRNA) isolated from plasma of RCC patients (n=3) immediately before and after AR. SOX10 and MITF cfRNAs were increased by 2.3 ± 0.85 and 1.77 ± 0.05-fold, respectively, between these two time points. Thus, PDL1 signaling is involved in AR by dysregulating the SOX10-MITF-GPNMB cascade, indicating the potential of the cascade-targeting to break AR hindrance for ICI therapy. Citation Format: Jin-Sung Chung, Lei Guo, Vinita Popat, Ponciano D. Cruz, Lin Xu, Hans Hammers, Kiyoshi Ariizumi. Possible involvement of PDL1 intrinsic signaling to acquired resistance to immunotherapy for renal cell carcinoma (RCC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB257.

Prediction of preeclampsia using maternal circulating mRNAs in early pregnancy.

Preeclampsia (PE) is one of the most common and serious complications of pregnancy, and novel methods for the early prediction of PE are needed for clinical application. In this study, a circulating cell-free RNA (cfRNA) panel of target genes for PE prediction was designed and validated in a case-control cohort and a nested case-control cohort. The QPCR was applied to quantify the copy number of cfRNA, and the data were normalized as multiples of the median. Ratios of serum placental growth factor (PIGF) and soluble fms-like tyrosine kinase1 (sFLT-1) were also measured, and transabdominal ultrasonography was conducted for subjects in the prospective cohort. Binary logistic regression models for PE prediction were constructed and tested. Our results revealed that the women with PE showed significant alterations in serum cfRNA profiles from early pregnancy onward and before the onset of PE symptoms. Compared with PIGF/sFLT-1 measurement and ultrasonographic imaging, cfRNA test can detect PE at a very early stage of pregnancy. The predictive model exhibited the best performance at gestation week 32, with a detection rate of 100%. At 12weeks of gestation, the model still manifested an area under curve (AUC) of 0.9144, and sensitivity of 1.0000. If combined with clinical parameters and ultrasonographic indicators, the model can achieve the highest AUC for PE prediction at early gestation. Measurement of cfRNA can be used to effectively predict PE with high performance, providing an additional method for monitoring PE throughout the course of pregnancy.

Subpar reporting of pre-analytical variables in RNA-focused blood plasma studies.

Extracellular RNA (cell-free RNA; exRNA) from blood-derived liquid biopsies is an appealing, minimally invasive source of disease biomarkers. As pre-analytical variables strongly influence exRNA measurements, their reporting is essential for meaningful interpretation and replication of results. The aim of this review was to chart to what extent pre-analytical variables are documented, to pinpoint shortcomings and to improve future reporting. In total, 200 blood plasma exRNA studies published in 2018 or 2023 were reviewed for annotation of 22 variables associated with blood collection, plasma preparation, and RNA purification. Our results show that pre-analytical variables are poorly documented, with only three out of 22 variables described in over half of the publications. The percentage of variables reported ranged from 4.6% to 54.6% (mean 24.84%) in 2023 and from 4.6% to 57.1% (mean 28.60%) in 2018. Recommendations and guidelines (i.e., BRISQ, ASCO-CAP, BloodPAC, PPMPT, and CEN standards) have currently not resulted in improved reporting. In conclusion, our results highlight the lack of reporting pre-analytical variables in exRNA studies and advocate for a consistent use of available standards, endorsed by funders and journals.

Accuracy of prenatal and postnatal biomarkers for estimating gestational age: a systematic review and meta-analysis

Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small for GA at a population level. Currently, the gold standard for pregnancy dating is measurement of the fetal crown rump length at 11-14 weeks of gestation. However, this is not possible for women first presenting in later pregnancy, or in settings where routine ultrasound is not available. A reliable, cheap and easy to measure GA-dependent biomarker would provide an important breakthrough in estimating the age of pregnancy. Therefore, the aim of this study was to determine the accuracy of prenatal and postnatal biomarkers for estimating gestational age (GA). Systematic review prospectively registered with PROSPERO (CRD42020167727) and reported in accordance with the PRISMA-DTA. Medline, Embase, CINAHL, LILACS, and other databases were searched from inception until September 2023 for cohort or cross-sectional studies that reported on the accuracy of prenatal and postnatal biomarkers for estimating GA. In addition, we searched Google Scholar and screened proceedings of relevant conferences and reference lists of identified studies and relevant reviews. There were no language or date restrictions. Pooled coefficients of correlation and root mean square error (RMSE, average deviation in weeks between the GA estimated by the biomarker and that estimated by the gold standard method) were calculated. The risk of bias in each included study was also assessed. Thirty-nine studies fulfilled the inclusion criteria: 20 studies (2,050 women) assessed prenatal biomarkers (placental hormones, metabolomic profiles, proteomics, cell-free RNA transcripts, and exon-level gene expression), and 19 (1,738,652 newborns) assessed postnatal biomarkers (metabolomic profiles, DNA methylation profiles, and fetal haematological components). Among the prenatal biomarkers assessed, human chorionic gonadotrophin measured in maternal serum between 4 and 9 weeks of gestation showed the highest correlation with the reference standard GA, with a pooled coefficient of correlation of 0.88. Among the postnatal biomarkers assessed, metabolomic profiling from newborn blood spots provided the most accurate estimate of GA, with a pooled RMSE of 1.03 weeks across all GAs. It performed best for term infants with a slightly reduced accuracy for preterm or small for GA infants. The pooled RMSEs for metabolomic profiling and DNA methylation profile from cord blood samples were 1.57 and 1.60 weeks, respectively. We identified no antenatal biomarkers that accurately predict GA over a wide window of pregnancy. Postnatally, metabolomic profiling from newborn blood spot provides an accurate estimate of GA, however, as this is known only after birth it is not useful to guide antenatal care. Further prenatal studies are needed to identify biomarkers that can be used in isolation, as part of a biomarker panel, or in combination with other clinical methods to narrow prediction intervals of GA estimation. The research was funded by the Bill and Melinda Gates Foundation (INV-000368). ATP is supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the NIHR Biomedical Research Centre funding scheme. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, the Department of Health, or the Department of Biotechnology. The funders of this study had no role in study design, data collection, analysis or interpretation of the data, in writing the paper or the decision to submit for publication.

Abstract 5018: Evaluation of whole blood fractionation conditions for optimal liquid biopsy NGS applications

Abstract “For research use only. Not for diagnostic procedures.” Introduction: Liquid biopsy is a non-invasive alternative to tissue biopsies for cancer profiling using cell-free total nucleic acids (cfTNA; including cell free DNA (cfDNA) and cell free RNA (cfRNA)), the biological analytes derived from tumor cells floating in blood. However, it is crucial to optimize the whole blood fractionation workflows, since limited access to a suitable centrifuge at blood collection sites poses a challenge to this critical fractionation step, causing delays in processing the blood, leading to decreased sensitivity of variant detection and increased occurrence of false positives. Current study shows a systematic comparison of the effects of 8 different blood fractionation conditions for spin speeds, temperatures and duration on the levels of cfTNA derived from K2-EDTA-derived blood from multiple healthy and non-small cell lung cancer (NSCLC) donors, using next generation sequencing (NGS). Methods: CfTNA from K2-EDTA derived plasma was isolated using the MagMAXTM Cell-Free Total Nucleic Acid kit and the Genexus™ Cell free total nucleic acid kit, utilizing the KingFisher TM Flex and GenexusTMpurification systems. Yield and integrity of cfTNA isolated was evaluated by Qubit™, Agilent Tapestation and quantitative real time PCR (qRT-PCR). Furthermore, the impact of these test conditions on quality control specifications of DNA and RNA was assessed by performing sequencing on an Ion TorrentTM GenexusTM sequencing instrument using the AmpliSeqTM HD target amplification assay, that reports sequence variations in DNA for 42 cancer related genes and RNA in 7 cancer related genes. Results: Results showed comparable performance for all the 8 blood fractionation conditions tested, for yield and cfDNA profiles compared to control condition, indicating that there is no significant impact of these conditions on either yield or integrity of the cfDNA isolated. In addition, NGS data also showed that on target reads and median molecular coverage for DNA are comparable for all the conditions tested. However, sequencing data demonstrated that one test condition showed significantly better performance for RNA quality control specifications in terms of RNA mapped reads and molecular coverage for process controls used in the assay, compared to all other conditions tested. Conclusion: Data suggests that one of the whole blood fractionation conditions tested impact the cfRNA recovery from plasma without negatively affecting the yield, and integrity of isolated cfDNA and shows increased sensitivity for RNA process controls in NGS. Citation Format: MADHU JASTI, Sergio Hernandez, Nick Siepert, Lokesh Kodandaramaswamy, Thilanka Jayaweera, Jeoffrey Schageman, Angie Cheng, Susanne Lopez, Miao Der Chen. Evaluation of whole blood fractionation conditions for optimal liquid biopsy NGS applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5018.

Abstract 5038: Validation of a comprehensive next-generation sequencing liquid biopsy assay for clinical diagnostics and clinical trial applications

Abstract Liquid biopsy next generation sequencing (NGS) provides a powerful non-invasive approach to detect solid tumor derived somatic variants in a massively parallel manner. Liquid biopsy NGS has rapidly become an invaluable choice of testing technologies for clinical utility where invasive tissue biopsy is inaccessible and/or inadequate for molecular characterization. We present here a targeted NGS gene panel assay designed and validated specifically for liquid biopsy characterization. The assay was designed to test cell free DNA and cell free RNA from blood plasma for detection of single nucleotide variants (SNV), insertion/deletion (Indel), copy number variants (CNV), and gene fusions present in 52 most commonly mutated genes in cancers. The validation was performed to assess assay accuracy, specificity, sensitivity, repeatability, and reproducibility, with including pre-characterized reference controls, retrospective plasma samples from cancer patients, and prospectively-collected clinic blood specimen. Triplicates were included and testing was performed at different times and by different operators to assess the assay precision. Over 100 clinic blood specimens were collected in Streck cfDNA tubes from multiple trial centers, including treatment naïve phase III-IV patients with solid tumor (lung cancer, breast cancer, brain cancer, prostate cancer, kidney cancer, melanoma, etc) as well as heathy donors, processed within 7 days for plasma separation and total nucleotide acid (TNA) extraction, and assessed by the NGS assay for mutation detection. The identified mutations and wild-types were verified with orthogonal ddPCR. Assay sensitivity as low as 0.1% for SNV and Indel, 1.3 fold change for CNV, and 10 copies for gene fusion were observed, with near-perfect assay specificity (>99.99%) at these sensitivity levels. In conclusion, a targeted NGS liquid biopsy assay was analytically validated under medical oversight, with a demonstrated rigor of the test by its high sensitivity/specificity and robust reproducibility. The validated assay has been utilized for clinical diagnostics and to support research and development efforts in clinical trials. Citation Format: Xin-Xing Tan, Tricia Peters, Meredith Berry, Kimberly Barber, Kristyn Jeter, Brigitte Lovell, Paula Elizondo, Yanglong Mou, Brad Thomas, Heng Xie, Jiannan Guo. Validation of a comprehensive next-generation sequencing liquid biopsy assay for clinical diagnostics and clinical trial applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5038.

Abstract 3678: Beyond detection: AI-based classification of breast cancer invasiveness using cell-free orphan non-coding RNAs

Abstract Background: Approximately 1 in 8 women will be impacted by breast cancer in their lifetimes. Earlier detection of breast cancer through screening has improved survival. Liquid biopsies have the potential to complement existing screening methods by enabling earlier detection and differentiating invasive cancer (IBC) from ductal carcinoma in-situ (DCIS). We previously demonstrated high sensitivity and specificity for early detection of IBC by using a blood-based liquid biopsy platform to analyze a novel category of cancer-associated small RNAs, termed orphan RNAs (oncRNAs). Here, we developed a test that could not only detect the presence of cancer, but also classify the invasiveness of breast cancer. Methods: We utilized The Cancer Genome Atlas (TCGA) small RNA profiles to discover a library of 20,538 oncRNAs that were significantly enriched among 1,103 breast tumors compared to 349 controls from normal tissues spanning multiple tissue sites, limited to female samples. The diagnostic performance of these oncRNAs was assessed in an independent cohort of serum samples from 708 women, including 380 breast cancer patients (221 IBC and 159 DCIS; mean age: 58.0 ± 13.4 years) and 328 age-matched controls (mean age: 58.4 ± 13.7 years). We sequenced the small RNA content from 1 ml of serum from these patients at an average depth of 21.6 million 50-bp single-end reads. We detected 19,736 (96%) of the breast cancer-specific oncRNA library within at least one sample in this cohort. We then trained a multi-class generative AI model using 5-fold cross-validation to predict IBC, DCIS, and absence of breast cancer (IBC or DCIS). Results: Our oncRNA-based generative AI model achieved an overall AUC of 0.95 (95% CI: 0.94-0.97) for prediction of breast cancer versus cancer-free controls. At 90% specificity, overall model sensitivity is 90.0% (86.5%-92.8%). For DCIS and stage I IBC, the model has a sensitivity of 88.1% (82.0%-92.7%) and 90.4% (81.9%-95.8%) respectively, both at 90% specificity. In the second step, restricting to samples flagged as cancer, we observed an overall AUC of 0.9 (0.87-0.93) and sensitivity of 62.4% (55.3%-69.1%) at 90% specificity for discriminating against invasive breast cancer. Conclusions: We have demonstrated the potential utility of oncRNAs as the foundation for a liquid biopsy platform for sensitive and accurate early detection of breast cancer. Our liquid biopsy assay has the potential to complement standard of care by not only detecting breast cancer but also differentiating IBC from DCIS. Citation Format: Mehran Karimzadeh, Taylor B. Cavazos, Nae-Chyun Chen, Noura K. Tbeileh, David Siegel, Amir Momen-Roknabadi, Jennifer Yen, Jeremy Ku, Selina Chen, Diana Corti, Alice Huang, Dang Nguyen, Rose Hanna, Ti Lam, Seda Kilinc, Philip Murzynowski, Jieyang Wang, Xuan Zhao, Andy Pohl, Babak Behsaz, Helen Li, Lisa Fish, Kim H. Chau, Marra S. Francis, Laura J. Van't Veer, Laura J. Esserman, Patrick A. Arensdorf, Hani Goodarzi, Fereydoun Hormozdiari, Babak Alipanahi. Beyond detection: AI-based classification of breast cancer invasiveness using cell-free orphan non-coding RNAs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3678.

Abstract 5035: Use of Streck nucleic acid BCT with plasma nucleic acid next-generation sequencing workflows

Abstract Introduction: Liquid biopsies, which interrogate body fluids in search of analytes released by cancer cells, are becoming increasingly common in clinical oncology. Foremost among the technologies used are those that employ nucleic acids, such as cell-free DNA (cfDNA) and cell-free RNA (cfRNA). Currently, many NGS-based tests perform near the limit of assay detection, making the identification of critical mutations, fusions, or expression patterns like finding a needle in a haystack. Further hindering successful assay development is the variability in analyte availability and detectability that can occur prior to analysis due to blood collection, transport, and storage. Here, we demonstrate that Nucleic Acid BCT stabilizes draw-time levels of plasma nucleic acids for downstream use with NGS-based assays. Methods: Blood from self-proclaimed healthy donors was drawn into EDTA and Nucleic Acid BCT and stored at ambient temperature for up to 7 days before plasma isolation with a general double-spin protocol and storage at -80 °C. Plasma nucleic acids were isolated using the MAGicBead cfDNA Kit (Zymo, cfDNA) or the QIAamp Circulating Nucleic Acid Kit (QIAGEN, cfRNA). Library prep for cfDNA was carried out with added synthetic mutant spike-in oligonucleotides using the Illumina TruSight Tumor 15 kit (Illumina). cfRNA library prep was done with the NEBNext Ultra II RNA Library Prep Kit for Illumina with upfront rRNA depletion (New England Biolabs). Sequencing was performed using an Illumina NextSeq 500 system, and all data were saved in and analyzed with Illumina BaseSpace applications. Results: When blood samples were stored in EDTA tubes for up to 7 days, spiked mutant alleles (EGFRL858R, EGFRdel19, KRASG12D, and PIK3CAE545K) were no longer detected, likely due to a dilution of the spiked DNA concentration following the release of genomic DNA containing wildtype alleles during white blood cell degradation. In contrast, equivalent blood samples stored in Nucleic Acid BCTs displayed mutant allele frequencies reflective of draw-time levels. Interrogation of plasma RNA expression patterns in samples stored in Nucleic Acid BCT versus EDTA revealed similar results, where differentially expressed plasma transcripts in blood samples stored in EDTA were found at high levels (>1,000 transcripts) versus donor-matched blood samples stored in Nucleic Acid BCT (<50 transcripts). Conclusions: Our data demonstrate that Nucleic Acid BCT maintains mutant allele frequencies and the plasma transcriptome profile of blood samples during ambient temperature storage. This provides precious sample integrity during whole blood storage and transport, offering laboratories and assay developers reduced preanalytical variability for NGS-based analysis of gene mutations, fusions, indels, and the plasma transcriptome. Nucleic Acid BCT is for Research Use Only. Not for use in diagnostic procedures. Citation Format: Nicholas M. George, Lisa Bartron. Use of Streck nucleic acid BCT with plasma nucleic acid next-generation sequencing workflows [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5035.

Abstract 2302: Innovative blood-based cell-free RNA whole transcriptome sequencing for comprehensive RNA profiling in patient plasma samples and its clinical applications

Abstract Background: Plasma cell-free RNA (cfRNA) holds promise for non-invasive cancer biomarker discovery, particularly in diseases like prostate cancer where specific biomarkers (AR splicing variants and TMPRSS2:ERG fusion) are detectable at the RNA level. Despite its potential, the technical challenges posed by blood cell-originated cfRNA abundance necessitates the development of robust and reliable assays for non-invasive cancer diagnostics. This study establishes and demonstrates the clinical utility of an innovative protocol for isolating and identifying tumor-originated cfRNA in plasma samples. Methods: A novel methodology was developed for the simultaneous extraction of cfDNA and cfRNA from a single blood sample tube, enabling whole transcriptome sequencing (WTS) analysis with minimal input as low as 1ng. A proprietary method was developed to selectively deplete blood cell-originated transcripts in the library. An enrichment-based WTS assay was conducted, and a customized RNASeq analysis pipeline was employed to enable expression profiling and cancer biomarker testing from the cfRNA samples. Results: The developed extraction method yielded substantial amounts of cfDNA and cfRNA from a 4 mL blood sample. Efficient depletion of blood cell-originated transcripts, achieving over 99% removal, enhanced the detection of a broader range of gene expressions in plasma. Implementation of the cfRNA WTS assay across healthy donor and cancer samples demonstrated consistency with documented biomarker status. The assay revealed significant differential clustering between cancer samples and healthy donors, with characteristic cancer genes contributing to the distinction. Reproducibility and analytical sensitivity of the developed cfRNA WTS assay were successfully validated. Conclusions: This study introduces Predicine's proprietary cfRNA WTS assay, enabling concurrent expression profiling and RNA biomarker detection in plasma samples. Overcoming technical challenges associated with blood cell-originated cfRNA, this assay represents a significant advancement in liquid biopsy-based cancer diagnostics. Citation Format: Fang Liu, Yong Huang, Min Wang, Xiangying Sun, Binggang Xiang, Shidong Jia, Pan Du, Shujun Luo. Innovative blood-based cell-free RNA whole transcriptome sequencing for comprehensive RNA profiling in patient plasma samples and its clinical applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2302.

Abstract 6560: Cell-free RNA analysis for non-invasive cancer detection and characterization

Abstract Blood-based liquid biopsies enable non-invasive characterization of cancers. Cell-free RNA (cfRNA) analysis could potentially complement circulating tumor DNA (ctDNA) analysis and allow broader molecular characterization of cancers but has not been extensively explored. Here, we describe RARE-Seq, a novel cfRNA sequencing method designed to maximize sensitivity by targeting rare, tissue-specific transcripts, and simultaneously detecting both tumor-derived expression signatures and somatic mutations in circulating tumor RNA (ctRNA). To interrogate samples for specific gene expression signatures, we developed and optimized a framework to measure tumor- and tissue-specific enrichment scores (ES) within cfRNA. We then empirically determined the limit of detection (LOD95) of RARE-Seq using admixtures of tumor cell line RNA and control cfRNA across a wide range of fractions. We found RARE-Seq to have an estimated LOD95 of 0.05% for cancer-derived RNA, which was 52-fold better than whole transcriptome cfRNA profiling. To explore its potential clinical utility, we profiled 192 samples from 170 subjects with various cancers and non-cancer controls using RARE-Seq. Non-small cell lung cancer (NSCLC) expression signatures were significantly detected in 40 out of 51 NSCLC samples (78% sensitivity at 90% specificity). Detection increased with stage, ranging from 40% in stage I to 87% in stage IV. In a subset of stage IV NSCLC patients with matching ctDNA data (n=16), ctRNA levels were significantly correlated with ctDNA allele frequencies (Pearson R=0.84, P=0.005). Intriguingly, 86% of samples with undetectable ctDNA contained detectable ctRNA, suggesting potential complementarity of ctRNA and ctDNA analysis for cancer detection. We also developed and benchmarked a direct ctRNA genotyping approach, allowing noninvasive detection of driver mutations in 42% of patients with advanced NSCLC. When applied to other tumors, RARE-Seq demonstrated 80-100% sensitivity at 90% specificity for detection of pancreatic adenocarcinomas (PAAD), prostate adenocarcinomas (PRAD), and hepatocellular carcinomas (LIHC). Furthermore, when evaluating tissue of origin (TOO) classification performance, RARE-Seq achieved 85% median accuracy for the top predicted tissue and 96% median accuracy for the top two tissues. These results highlight the potential value of ultrasensitive cfRNA analysis, providing proof-of-principle for detection of multiple tumor types using RARE-Seq. Citation Format: Monica C. Nesselbush, Bogdan A. Luca, Young-Jun Jeon, Isabel Jabara, Catherine B. Meador, Michael S. Binkley, Nova Xu, Angela B. Hui, Andrea Garofalo, William Y. Shi, Kevin J. Liu, Takeshi Sugio, Noah Kastelowitz, Emily G. Hamilton, Rene F. Bonilla, Yi Peng Wang, Alice Jiang, Brianna Lau, Jordan Eichholz, Mandeep Banwait, Joseph Schroers-Martin, Jan Boegeholz, Daniel A. King, Mohammad S. Esfahani, Tyler Raclin, Robert Tibshirani, Sandy Srinivas, Viswam S. Nair, James M. Isbell, Bob T. Li, Zofia Piotrowska, Lecia V. Sequist, Aaron N. Hata, Joel W. Neal, Heather A. Wakelee, Andrew J. Gentles, Ash A. Alizadeh, Maximilian Diehn. Cell-free RNA analysis for non-invasive cancer detection and characterization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6560.

Abstract 5031: Identification of predictive/prognostic biomarkers in metastatic castration-resistant prostate cancer patients using plasma cell-free total RNA-sequencing

Abstract Background Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease that is still lacking an optimal patient selection strategy and a validated sequence of therapies. Therefore, there is an urgent need to identify non-invasive biomarkers to guide treatment choice in a perspective of personalized medicine. Plasma cell-free RNA profiling has emerged as a tool to investigate potential liquid biopsy biomarkers. In this study, we aimed to evaluate a method to capture total RNA content deriving from plasma and to identify potential biomarkers for mCRPC. Methods Plasma samples of 41 mCRPC patients treated with first line Abiraterone or Enzalutamide and 7 healthy donors were collected and stored from 2015 to 2022. Plasma cell-free RNA was purified using miRNeasy Serum/Plasma Advanced Kit (Qiagen) with DNase treatment. Bioanalyzer (Agilent) was used for the evaluation of RNA content and integrity profile of the samples. Sequencing libraries were generated using SMARTer Stranded Total RNA-Seq Kit v3 - Pico Input Mammalian (Takara Bio). An average of 80 millions reads pairs were sequenced on Novaseq 6000 (Illumina) using 100 bpx2 approach. After demultiplexing, reads were trimmed and aligned on hg19. Sequencing metrics were evaluated using Picard. Kallisto was used for gene expression analysis. Results A median of 10x109 bases per sample were aligned on hg19, of which a mean of 45% were located on coding or UTR regions. Storage time was investigated as a potential variable for RNA content and sequencing metrics, but no difference related to the year of storage was found. Unsupervised principal component analysis confirmed the absence of batch effects (including storage and sequencing analysis). PC1 seemed to reflect the different tumor RNA content of each sample, in which healthy donors and cancer patients were distinguished. Higher androgen receptor (AR) gene expression was found in mCRPC patients compared to healthy donors. Conclusions Despite enormous interest in extracellular nucleic acids, RNA-sequencing methods for total RNA content outside cells are rare and not standardized. In this study, we found a method to identify plasma non-invasive RNA biomarkers in mCRPC samples, retrieving coding and non-coding RNAs. Case series enlargement and differential gene expression analyses are ongoing. Citation Format: Giorgia Gurioli, Milena Urbini, Alessandra Virga, Chiara Casadei, Emilio Francesco Giunta, Nicole Brighi, Michela Cortesi, Michele Zanoni, Sara Bravaccini, Giovanni Martinelli, Paola Ulivi, Ugo De Giorgi. Identification of predictive/prognostic biomarkers in metastatic castration-resistant prostate cancer patients using plasma cell-free total RNA-sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5031.

Reanalysis of single-cell RNA sequencing data does not support herpes simplex virus 1 latency in non-neuronal ganglionic cells in mice.

Most individuals are latently infected with herpes simplex virus type 1 (HSV-1), and it is well-established that HSV-1 establishes latency in sensory neurons of peripheral ganglia. However, it was recently proposed that latent HSV-1 is also present in immune cells recovered from the ganglia of experimentally infected mice. Here, we reanalyzed the single-cell RNA sequencing (scRNA-Seq) data that formed the basis for that conclusion. Unexpectedly, off-target priming in 3' scRNA-Seq experiments enabled the detection of non-polyadenylated HSV-1 latency-associated transcript (LAT) intronic RNAs. However, LAT reads were near-exclusively detected in mixed populations of cells undergoing cell death. Specific loss of HSV-1 LAT and neuronal transcripts during quality control filtering indicated widespread destruction of neurons, supporting the presence of contaminating cell-free RNA in other cells following tissue processing. In conclusion, the reported detection of latent HSV-1 in non-neuronal cells is best explained using compromised scRNA-Seq datasets.IMPORTANCEMost people are infected with herpes simplex virus type 1 (HSV-1) during their life. Once infected, the virus generally remains in a latent (silent) state, hiding within the neurons of peripheral ganglia. Periodic reactivation (reawakening) of the virus may cause fresh diseases such as cold sores. A recent study using single-cell RNA sequencing (scRNA-Seq) proposed that HSV-1 can also establish latency in the immune cells of mice, challenging existing dogma. We reanalyzed the data from that study and identified several flaws in the methodologies and analyses performed that invalidate the published conclusions. Specifically, we showed that the methodologies used resulted in widespread destruction of neurons which resulted in the presence of contaminants that confound the data analysis. We thus conclude that there remains little to no evidence for HSV-1 latency in immune cells.

Long-term monitoring of ultratrace nucleic acids using tetrahedral nanostructure-based NgAgo on wearable microneedles

Real-time and continuous monitoring of nucleic acid biomarkers with wearable devices holds potential for personal health management, especially in the context of pandemic surveillance or intensive care unit disease. However, achieving high sensitivity and long-term stability remains challenging. Here, we report a tetrahedral nanostructure-based Natronobacterium gregoryi Argonaute (NgAgo) for long-term stable monitoring of ultratrace unamplified nucleic acids (cell-free DNAs and RNAs) in vivo for sepsis on wearable device. This integrated wireless wearable consists of a flexible circuit board, a microneedle biosensor, and a stretchable epidermis patch with enrichment capability. We comprehensively investigate the recognition mechanism of nucleic acids by NgAgo/guide DNA and signal transformation within the Debye distance. In vivo experiments demonstrate the suitability for real-time monitoring of cell-free DNA and RNA with a sensitivity of 0.3 fM up to 14 days. These results provide a strategy for highly sensitive molecular recognition in vivo and for on-body detection of nucleic acid.

Genetic profiling of azoospermic men to identify the etiology and predict reproductive potential.

To identify germline mutations related to azoospermia etiology and reproductive potential of surgically retrieved spermatozoa, and to investigate the feasibility of predicting seminiferous tubule function of nonobstructive azoospermic men by transcriptomic profiling of ejaculates. Sperm specimens were obtained from 30 men (38.4 ± 6years) undergoing epididymal sperm aspiration for obstructive azoospermia (OA, n = 19) acquired by vasectomy, or testicular biopsy for nonobstructive azoospermia (NOA, n = 11). To evaluate for a correlation with azoospermia etiology, DNAseq was performed on surgically retrieved spermatozoa, and cell-free RNAseq on seminal fluid (n = 23) was performed to predict spermatogenesis in the seminiferous tubule. Overall, surgically retrieved sperm aneuploidy rates were 1.7% and 1.8% among OA and NOA cohorts, respectively. OA men carried housekeeping-related gene mutations, while NOA men displayed mutations on genes involved in crucial spermiogenic functions (AP1S2, AP1G2, APOE). We categorized couples within each cohort according to ICSI clinical outcomes to investigate genetic causes that may affect reproductive potential. All OA-fertile men (n = 9) carried mutations in ZNF749 (sperm production), whereas OA-infertile men (n = 10) harbored mutations in PRB1, which is essential for DNA replication. NOA-fertile men (n = 8) carried mutations in MPIG6B (stem cell lineage differentiation), whereas NOA-infertile individuals (n = 3) harbored mutations in genes involved in spermato/spermio-genesis (ADAM29, SPATA31E1, MAK, POLG, IFT43, ATG9B) and early embryonic development (MBD5, CCAR1, PMEPA1, POLK, REC8, REPIN1, MAPRE3, ARL4C). Transcriptomic assessment of cell-free RNAs in seminal fluid from NOA men allowed the prediction of residual spermatogenic foci. Sperm genome profiling provides invaluable information on azoospermia etiology and identifies gene-related mechanistic links to reproductive performance. Moreover, RNAseq assessment of seminal fluid from NOA men can help predict sperm retrieval during testicular biopsies.

A Highly Sensitive XNA-Based RT-qPCR Assay for the Identification of ALK, RET, and ROS1 Fusions in Lung Cancer.

Lung cancer is often triggered by genetic alterations that result in the expression of oncogenic tyrosine kinases. Specifically, ALK, RET, and ROS1 chimeric receptor tyrosine kinases are observed in approximately 5-7%, 1-2%, and 1-2% of NSCLC patients, respectively. The presence of these fusion genes determines the response to tyrosine kinase inhibitors. Thus, accurate detection of these gene fusions is essential in cancer research and precision oncology. To address this need, we have developed a multiplexed RT-qPCR assay using xeno nucleic acid (XNA) molecular clamping technology to detect lung cancer fusions. This assay can quantitatively detect thirteen ALK, seven ROS1, and seven RET gene fusions in FFPE samples. The sensitivity of the assay was established at a limit of detection of 50 copies of the synthetic template. Our assay has successfully identified all fusion transcripts using 50 ng of RNA from both reference FFPE samples and cell lines. After validation, a total of 77 lung cancer patient FFPE samples were tested, demonstrating the effectiveness of the XNA-based fusion gene assay with clinical samples. Importantly, this assay is adaptable to highly degraded RNA samples with low input amounts. Future steps involve expanding the testing to include a broader range of clinical samples as well as cell-free RNAs to further validate its applicability and reliability.

Utilizing nullomers in cell-free RNA for early cancer detection.

Early detection of cancer can significantly improve patient outcomes; however, sensitive and highly specific biomarkers for cancer detection are currently missing. Nullomers are the shortest sequences that are absent from the human genome but can emerge due to somatic mutations in cancer. We examine over 10,000 whole exome sequencing matched tumor-normal samples to characterize nullomer emergence across exonic regions of the genome. We also identify nullomer emerging mutational hotspots within tumor genes. Finally, we provide evidence for the identification of nullomers in cell-free RNA from peripheral blood samples, enabling detection of multiple tumor types. We show multiple tumor classification models with an AUC greater than 0.9, including a hepatocellular carcinoma classifier with an AUC greater than 0.99.

High-Throughput Microfluidic Extraction of Platelet-free Plasma for MicroRNA and Extracellular Vesicle Analysis.

Cell-free RNAs and extracellular vesicles (EVs) are valuable biomarkers in liquid biopsies, but they are prone to preanalytical variabilities such as nonstandardized centrifugation or ex vivo blood degradation. Herein, we report a high-throughput and label-free inertial microfluidic device (ExoArc) for isolation of platelet-free plasma from blood for RNA and EV analysis. Unlike conventional inertial microfluidic devices widely used for cell sorting, a submicrometer size cutoff (500 nm) was achieved which completely removed all leukocytes, RBCs, platelets, and cellular debris based on differential lateral migration induced by Dean vortices. The single-step operation also reduced platelet-associated miRNAs (∼2-fold) compared to centrifugation. We clinically validated ExoArc for plasma miRNA profiling (39 samples) and identified a 7-miRNA panel that detects non-small cell lung cancer with ∼90% sensitivity. ExoArc was also coupled with size exclusion chromatography (SEC) to isolate EVs within 50 min with ∼10-fold higher yield than ultracentrifugation. As a proof-of-concept for EV-based transcriptomics analysis, we performed miRNA analysis in healthy and type 2 diabetes mellitus (T2DM) subjects (n = 3 per group) by coupling ExoArc and ExoArc+SEC with quantitative polymerase chain reaction (RT-qPCR) assay. Among 293 miRNAs detected, plasmas and EVs showed distinct differentially expressed miRNAs in T2DM subjects. We further demonstrated automated in-line EV sorting from low volume culture media for continuous EV monitoring. Overall, the developed ExoArc offers a convenient centrifugation-free workflow to automate plasma and EV isolation for point-of-care diagnostics and quality control in EV manufacturing.

Liquid Biopsy Based on Cell-Free DNA and RNA.

This review delves into the rapidly evolving landscape of liquid biopsy technologies based on cell-free DNA (cfDNA) and cell-free RNA (cfRNA) and their increasingly prominent role in precision medicine. With the advent of high-throughput DNA sequencing, the use of cfDNA and cfRNA has revolutionized noninvasive clinical testing. Here, we explore the physical characteristics of cfDNA and cfRNA, present an overview of the essential engineering tools used by the field, and highlight clinical applications, including noninvasive prenatal testing, cancer testing, organ transplantation surveillance, and infectious disease testing. Finally, we discuss emerging technologies and the broadening scope of liquid biopsies to new areas of diagnostic medicine. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 26 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Agarose amplification based sequencing characterization cell-free RNA in preimplantation spent embryo medium

BackgroundThe cell-free RNA (cf-RNA) of spent embryo medium (SEM) has aroused a concern of academic and clinical researchers for its potential use in non-invasive embryo screening. However, comprehensive characterization of cf-RNA from SEM still presents significant technical challenges, primarily due to the limited volume of SEM. Hence, there is urgently need to a small input liquid volume and ultralow amount of cf-RNA library preparation method to unbiased cf-RNA sequencing from SEM. (75) ResultHere, we report a high sensitivity agarose amplification-based cf-RNA sequencing method (SEM-Acf) for human preimplantation SEM cf-RNA analysis. It is a cf-RNA sequencing library preparation method by adding agarose amplification. The agarose amplification sensitivity (0.005 pg) and efficiency (105.35 %) were increased than that of without agarose addition (0.45 pg and 96.06 %) by ∼ 90 fold and 9.29 %, respectively. Compared with SMART sequencing (SMART-seq), the correlation of gene expression was stronger in different SEM samples by using SEM-Acf. The cf-RNA number of detected and coverage uniformity of 3′ end were significantly increased. The proportion of 5′ end adenine, alternative splicing events and short fragments (<400 bp) were increased. It is also found that 4‐mer end motifs of cf-RNA fragments was significantly differences between different embryonic stage by day3 spent cleavage medium and day5/6 spent blastocyst medium. (141) SignificanceThis study established an efficient SEM amplification and library preparation method. Additionally, we successfully described the characterizations of SEM cf-RNA in preimplantation embryo using SEM-Acf, including expression features and fragment lengths. SEM-Acf facilitates the exploration of cf-RNA as a noninvasive embryo screening biomarker, and opens up potential clinical utilities of small input liquid volume and ultralow amount cf-RNA sequencing. (59).

Terminal modifications independent cell-free RNA sequencing enables sensitive early cancer detection and classification

Cell-free RNAs (cfRNAs) offer an opportunity to detect diseases from a transcriptomic perspective, however, existing techniques have fallen short in generating a comprehensive cell-free transcriptome profile. We develop a sensitive library preparation method that is robust down to 100 µl input plasma to analyze cfRNAs independent of their 5’-end modifications. We show that it outperforms adapter ligation-based method in detecting a greater number of cfRNA species. We perform transcriptome-wide characterizations in 165 lung cancer, 30 breast cancer, 37 colorectal cancer, 55 gastric cancer, 15 liver cancer, and 133 cancer-free participants and demonstrate its ability to identify transcriptomic changes occurring in early-stage tumors. We also leverage machine learning analyses on the differentially expressed cfRNA signatures and reveal their robust performance in cancer detection and classification. Our work sets the stage for in-depth study of the cfRNA repertoire and highlights the value of cfRNAs as cancer biomarkers in clinical applications.