Evidence map›Paper›PMID 31242667›Full record

ArticleCancers2019

Utility of Circulating Cell-Free RNA Analysis for the Characterization of Global Transcriptome Profiles of Multiple Myeloma Patients.

Maoshan Chen, Sridurga Mithraprabhu, Malarmathy Ramachandran, Kawa Choi, Tiffany Khong, Andrew Spencer

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
7.0field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 26 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Maoshan ChenMyeloma Research Group, Australian Centre for Blood Diseases (ACBD), Clinical Central School, Monash University, Melbourne 3004, Australia. maoshan.chen@monash.edu.ORCID 0000-0002-3827-4969
Sridurga MithraprabhuMyeloma Research Group, Australian Centre for Blood Diseases (ACBD), Clinical Central School, Monash University, Melbourne 3004, Australia. durga.mithraprabhu@monash.edu.ORCID 0000-0003-1034-5179
Malarmathy RamachandranMyeloma Research Group, Australian Centre for Blood Diseases (ACBD), Clinical Central School, Monash University, Melbourne 3004, Australia. malarmathy.ramachandran@monash.edu.
Kawa ChoiMyeloma Research Group, Australian Centre for Blood Diseases (ACBD), Clinical Central School, Monash University, Melbourne 3004, Australia. kawa.choi@monash.edu.
Tiffany KhongMyeloma Research Group, Australian Centre for Blood Diseases (ACBD), Clinical Central School, Monash University, Melbourne 3004, Australia. tiffany.khong@monash.edu.
Andrew SpencerMyeloma Research Group, Australian Centre for Blood Diseases (ACBD), Clinical Central School, Monash University, Melbourne 3004, Australia. aspencer@netspace.net.au.
The Alfred Hospital · AUMonash University · AU

Funding

International Myeloma Foundation's Black Swan Research Initiative BSRI-AH1701
6 · The paper itself

Abstract

In this study, we evaluated the utility of extracellular RNA (exRNA) derived from the plasma of multiple myeloma (MM) patients for whole transcriptome characterization. exRNA from 10 healthy controls (HC), five newly diagnosed (NDMM), and 12 relapsed and refractory (RRMM) MM patients were analyzed and compared. We showed that ~45% of the exRNA genes were protein-coding genes and ~85% of the identified genes were covered >70%. Compared to HC, we identified 632 differentially expressed genes (DEGs) in MM patients, of which 26 were common to NDMM and RRMM. We further identified 54 and 191 genes specific to NDMM and RRMM, respectively, and these included potential biomarkers such as LINC00863, MIR6754, CHRNE, ITPKA, and RGS18 in NDMM, and LINC00462, PPBP, RPL5, IER3, and MIR425 in RRMM, that were subsequently validated using droplet digital PCR. Moreover, single nucleotide polymorphisms and small indels were identified in the exRNA, including mucin family genes that demonstrated different rates of mutations between NDMM and RRMM. This is the first whole transcriptome study of exRNA in hematological malignancy and has provided the basis for the utilization of exRNA to enhance our understanding of the MM biology and to identify potential biomarkers relevant to the diagnosis and prognosis of MM patients.

Indexed as

biomarkercirculating transcriptomeextracellular RNAliquid biopsymyelomanon-coding RNArelapse

Identifiers

PMID31242667
PMCPMC6628062
OpenAlexW2955704173

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.