Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors

Albitar, Maher; Zhang, Hong; Charifa, Ahmad; Ip, Andrew; Ma, Wanlong; McCloskey, James; Donato, Michèle; Siegel, David S.; Waintraub, Stanley; Gutierrez, Martin; Pecora, Andrew L.; Goy, André

doi:10.1016/j.heliyon.2023.e16261

Cited by 8 publications

(8 citation statements)

References 34 publications

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“… 24 cfRNA proved overall more sensitive than cfDNA in detecting mutations and, thus, reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. 24 The liquid transcriptome, thus, can be used for diagnosis and staging, selecting therapy, predicting prognosis, and monitoring disease. Improved detection rates by these liquid biopsy strategies increase the certainty of LMD diagnosis, potentially enhancing prognostication and improving patient care by allowing for timely and appropriate radiotherapy, systemic therapy, and/or intrathecal chemotherapy selection.…”

Section: Discussionmentioning

confidence: 98%

“…Genomic Testing Cooperative (GTC) developed an approach to isolate cell-free total nucleic acid (cfDNA) followed by targeted NGS to sequence cell-free RNA (cfRNA) and cfDNA as novel liquid biopsy approach for both blood and CSF samples. 24 GTC combines cfRNA and cfDNA NGS to evaluate mutations, fusion genes, and chromosomal structural abnormalities in liquid samples. 24 cfRNA proved overall more sensitive than cfDNA in detecting mutations and, thus, reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses.…”

Section: Discussionmentioning

confidence: 99%

“… 24 GTC combines cfRNA and cfDNA NGS to evaluate mutations, fusion genes, and chromosomal structural abnormalities in liquid samples. 24 cfRNA proved overall more sensitive than cfDNA in detecting mutations and, thus, reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. 24 The liquid transcriptome, thus, can be used for diagnosis and staging, selecting therapy, predicting prognosis, and monitoring disease.…”

Section: Discussionmentioning

confidence: 99%

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Comparative evaluation of the diagnostic and prognostic performance of CNSide™ versus standard cytology for leptomeningeal disease

Appel,

Rubens,

Roy

et al. 2024

Neuro-Oncology Advances

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Background This retrospective study compares real-world performance of cerebrospinal fluid (CSF) CNSide™ versus cytology in leptomeningeal disease (LMD). Methods: Consecutive patients with suspected LMD who underwent lumbar punctures for CSF cytology and CNSide™ from January 2020 to December 2022 were reviewed. LMD was classified by EANO criteria. Descriptive statistics, confusion matrix, Kaplan Meier curves, and Cox proportional regression were used. Results Median age for 87 evaluable patients was 63 years (range:23-93); 82 (94%) met EANO criteria for possible/probable/confirmed LMD (EANO/LMD). The commonest primary cancers were breast (36,44.0%) and lung (34,41.5%). Primary lung harbored actionable mutations in 18 (53.0%); primary breast expressed hormone receptors in 27 (75%) and HER2 amplification in 8 (22%). Uncontrolled systemic disease was detected in 35 (40%), while 25 (46%) received systemic therapy with medium/high CNS penetrance at LMD diagnosis. Median time from initial cancer to LMD diagnosis was 31 months (range:13-73). LMD was confirmed by CSF cytology in 23/82 (28%), all identified by CNSide™. CNSide™ identified 13 additional cases (36/82,43.9%), increasing diagnostic yield by 56.5%. Median overall survival (mOS) was 31 weeks (95%CI:21-43), significantly worse for CNSide™ positive versus negative: 4.0 versus 16.0 weeks, respectively (HR=0.50,p=0.010). While survival since LMD diagnosis did not differ by histology, time to LMD diagnosis from initial cancer diagnosis was longer for breast (48.5 months,IQR:30.0-87.5) versus lung (8 months,IQR:0.5-16.0) cohorts. mOS was longer for patients eligible for intrathecal chemotherapy (HR:0.189, 95%CI:0.053-0.672, p=0.010). Conclusions This retrospective, real-world analysis of CNSide™ showed increased sensitivity versus cytology and provided clinically relevant molecular CSF analyses.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Comparative evaluation of the diagnostic and prognostic performance of CNSide™ versus standard cytology for leptomeningeal disease

Appel,

Rubens,

Roy

et al. 2024

Neuro-Oncology Advances

View full text Add to dashboard Cite

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“…To this end, the combinations of circulating aberrant methylated DNA and miRNAs for early detection of colorectal cancer [ 166 ] and lung cancer [ 167 ]. In another study, Albitar et al [ 168 ] demonstrated that combining the analysis of cfRNA with cfDNA has the potential to predict genomic abnormalities, diagnose neoplasms, and evaluate both tumor biology and host response. Some examples of multi-analyte liquid biopsies involving c-miRNAs as one of the analytes are shown in Table 4 .…”

Section: Combinatorial Potential Of C-mirnas With Cfdnas and Proteins...mentioning

confidence: 99%

The Circulating Biomarkers League: Combining miRNAs with Cell-Free DNAs and Proteins

Felekkis,

Papaneophytou

2024

IJMS

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The potential of liquid biopsy for the prognosis and diagnosis of diseases is unquestionable. Within the evolving landscape of disease diagnostics and personalized medicine, circulating microRNAs (c-miRNAs) stand out among the biomarkers found in blood circulation and other biological fluids due to their stability, specificity, and non-invasive detection in biofluids. However, the complexity of human diseases and the limitations inherent in single-marker diagnostics highlight the need for a more integrative approach. It has been recently suggested that a multi-analyte approach offers advantages over the single-analyte approach in the prognosis and diagnosis of diseases. In this review, we explore the potential of combining three well-studied classes of biomarkers found in blood circulation and other biofluids—miRNAs, DNAs, and proteins—to enhance the accuracy and efficacy of disease detection and monitoring. Initially, we provide an overview of each biomarker class and discuss their main advantages and disadvantages highlighting the superiority of c-miRNAs over the other classes of biomarkers. Additionally, we discuss the challenges and future directions in integrating these biomarkers into clinical practice, emphasizing the need for standardized protocols and further validation studies. This integrated approach has the potential to revolutionize precision medicine by offering insights into disease mechanisms, facilitating early detection, and guiding personalized therapeutic strategies. The collaborative power of c-miRNAs with other biomarkers represents a promising frontier in the comprehensive understanding and management of complex diseases. Nevertheless, several challenges must be addressed before this approach can be translated into clinical practice.

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“…where C is the index for pesudo-biomarkers, and both v C and σ C are trainable parameters. This pseudo-biomarker mining phase can be seen as an Large Language Model (LLM) alignment process, aligning the information in GeneLLM with the pseudo-biomarkers by minimising L pm in Equation (2). After this process, the pseudobiomarker vectors v 1 , .…”

Section: Pesudo-biomarker Miningmentioning

confidence: 99%

GeneLLM: A Large cfRNA Language Model for Cancer Screening from Raw Reads

Deng,

Sha,

Jin

et al. 2024

Preprint

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Plasma cell-free RNA (cfRNA) has recently emerged as a promising biomarker for non-invasive early cancer detection and treatment monitoring [8, 28, 31, 32, 38, 40]. Here, we introduce GeneLLM, a novel large language model de-signed to interpret cfRNA sequences directly, bypassing the need for genome annotations. GeneLLM significantly advances the detection accuracy of various cancer types. Our study demonstrates that this method achieves higher accuracy than traditional biomarkers and effectively handles large datasets from different centres, even with low sequencing depth. By avoiding the use of bioinformatics tools to count known genes, GeneLLM also discovered cfRNAs from previously unknown genes, referred to as ‘dark matters’ in the genome, as cancer detec-tion ‘pseudo-biomarkers’. Our results showcase the potential of GeneLLM to revolutionise cancer detection, making it more accessible and cost-effective. By offering a method that does not depend on bioinformatics tools to count known genes, GeneLLM opens new avenues for biomarker discovery and enhances our understanding of intercellular communication through novel RNA molecules.

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Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors

Cited by 8 publications

References 34 publications

Comparative evaluation of the diagnostic and prognostic performance of CNSide™ versus standard cytology for leptomeningeal disease

Comparative evaluation of the diagnostic and prognostic performance of CNSide™ versus standard cytology for leptomeningeal disease

The Circulating Biomarkers League: Combining miRNAs with Cell-Free DNAs and Proteins

GeneLLM: A Large cfRNA Language Model for Cancer Screening from Raw Reads

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