Evidence map›Paper›PMID 30085333›Full record

ReviewInternational journal of oncology2018

Liquid biopsy and PCR-free ultrasensitive detection systems in oncology (Review).

Alessia Finotti, Matteo Allegretti, Jessica Gasparello, Patrizio Giacomini, Demetrios A Spandidos, Giuseppe Spoto, Roberto Gambari

Open access · bronzeAbstract readReview
In one paragraph

Review in International journal of oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
3.7field-weighted citation impact, top 5% 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

38 citing papers in PubMed, 68 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Precision medicine in breast cancer (Review).Molecular and clinical oncology · 2024
    Review
  5. Article
  6. Article
  7. Review
  8. Liquid biopsies: the future of cancer early detection.Journal of translational medicine · 2023
    Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Liquid Biopsy for Cancer Cachexia: Focus on Muscle-Derived microRNAs.International journal of molecular sciences · 2021
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

7 authors at 3 institutions in 2 countries.

Alessia FinottiDepartment of Life Sciences and Biotechnology, Ferrara University, 44121 Ferrara, Italy.
Matteo AllegrettiOncogenomics and Epigenetic Unit, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy.
Jessica GasparelloDepartment of Life Sciences and Biotechnology, Ferrara University, 44121 Ferrara, Italy.
Patrizio GiacominiOncogenomics and Epigenetic Unit, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy.
Demetrios A SpandidosLaboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Crete, Greece.
Giuseppe SpotoDepartment of Chemistry, Catania University, 95125 Catania, Italy.
Roberto GambariDepartment of Life Sciences and Biotechnology, Ferrara University, 44121 Ferrara, Italy.
University of Ferrara · ITUniversity of Catania · ITUniversity of Crete · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In oncology, liquid biopsy is used in the detection of next-generation analytes, such as tumor cells, cell-free nucleic acids and exosomes in peripheral blood and other body fluids from cancer patients. It is considered one of the most advanced non-invasive diagnostic systems to enable clinically relevant actions and implement precision medicine. Medical actions include, but are not limited to, early diagnosis, staging, prognosis, anticipation (lead time) and the prediction of therapy responses, as well as follow-up. Historically, the applications of liquid biopsy in cancer have focused on circulating tumor cells (CTCs). More recently, this analysis has been extended to circulating free DNA (cfDNA) and microRNAs (miRNAs or miRs) associated with cancer, with potential applications for development into multi-marker diagnostic, prognostic and therapeutic signatures. Liquid biopsies avoid some key limitations of conventional tumor tissue biopsies, including invasive tumor sampling, under-representation of tumor heterogeneity and poor description of clonal evolution during metastatic dissemination, strongly reducing the need for multiple sampling. On the other hand, this approach suffers from important drawbacks, i.e., the fragmentation of cfDNA, the instability of RNA, the low concentrations of certain analytes in body fluids and the confounding presence of normal, as well as aberrant DNAs and RNAs. For these reasons, the analysis of cfDNA has been mostly focused on mutations arising in, and pathognomonicity of, tumor DNA, while the analysis of cfRNA has been mostly focused on miRNA patterns strongly associated with neoplastic transformation/progression. This review lists some major applicative areas, briefly addresses how technology is bypassing liquid biopsy limitations, and places a particular emphasis on novel, PCR-free platforms. The ongoing collaborative efforts of major international consortia are reviewed. In addition to basic and applied research, we will consider technological transfer, including patents, patent applications and available information on clinical trials aimed at verifying the potential of liquid biopsy in cancer.

Indexed as

Neoplastic Cells, CirculatingBiomarkers, TumorCell-Free Nucleic AcidsDNA, NeoplasmExosomesHumansLiquid BiopsyMicroRNAsMutationNeoplasmsPrecision MedicineBiomarkers, TumorCell-Free Nucleic AcidsDNA, NeoplasmMicroRNAs

Identifiers

PMID30085333
PMCPMC6086621
OpenAlexW2887391794

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.