Evidence map›Paper›PMID 34773243›Full record

ReviewMolecular diagnosis & therapy2022

Current and Emerging Applications of Droplet Digital PCR in Oncology: An Updated Review.

Susana Olmedillas-López, Rocío Olivera-Salazar, Mariano García-Arranz, Damián García-Olmo

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular diagnosis & therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
6.6field-weighted citation impact, top 2% 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

73 citing papers in PubMed, 108 citations in OpenAlex.

  1. Trial
  2. Article
  3. The prognostic value of methylated ctDNA, soluble PD-L1, and NK-cell activity on the risk of relapse after curative radiotherapy of non-small cell lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  4. Article
  5. A Modular and Programmable Cas13d Platform for RNA Single Nucleotide Variant Detection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Diagnostic and prognostic performance ofClinical transplantation and research · 2026
    Article
  11. Review
  12. Review
  13. Article
  14. Novel Liquid Biopsy in Gastrointestinal Cancers.Journal of gastroenterology and hepatology · 2026
    Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Review
  20. Article

13 more citing papers are in PubMed but not listed here.

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

4 authors at 1 institution in 1 country.

Susana Olmedillas-LópezNew Therapies Laboratory, Health Research Institute-Fundación Jiménez Díaz University Hospital (IIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain. solmedillas@gmail.com.ORCID 0000-0002-6535-5852
Rocío Olivera-SalazarNew Therapies Laboratory, Health Research Institute-Fundación Jiménez Díaz University Hospital (IIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain.ORCID 0000-0001-6832-9695
Mariano García-ArranzNew Therapies Laboratory, Health Research Institute-Fundación Jiménez Díaz University Hospital (IIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain.ORCID 0000-0002-6266-9055
Damián García-OlmoNew Therapies Laboratory, Health Research Institute-Fundación Jiménez Díaz University Hospital (IIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain.ORCID 0000-0002-9369-2338
Hospital Universitario Fundación Jiménez Díaz · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of personalized medicine and targeted therapies for the management of patients with cancer, ultrasensitive detection methods for tumor genotyping, such as next-generation sequencing or droplet digital polymerase chain reaction (ddPCR), play a significant role. In the search for less invasive strategies for diagnosis, prognosis and disease monitoring, the number of publications regarding liquid biopsy approaches using ddPCR has increased substantially in recent years. There is a long list of malignancies in which ddPCR provides a reliable and accurate tool for detection of nucleic acid-based markers derived from cell-free DNA, cell-free RNA, circulating tumor cells, extracellular vesicles or exosomes when isolated from whole blood, plasma and serum, helping to anticipate tumor relapse or unveil intratumor heterogeneity and clonal evolution in response to treatment. This updated review describes recent developments in ddPCR platforms and provides a general overview about the major applications of liquid biopsy in blood, including its utility for molecular response and minimal residual disease monitoring in hematological malignancies or the therapeutic management of patients with colorectal or lung cancer, particularly for the selection and monitoring of treatment with tyrosine kinase inhibitors. Although plasma is the main source of genetic material for tumor genomic profiling, liquid biopsy by ddPCR is being investigated in a wide variety of biologic fluids, such as cerebrospinal fluid, urine, stool, ocular fluids, sputum, saliva, bronchoalveolar lavage, pleural effusion, mucin, peritoneal fluid, fine needle aspirate, bile or pancreatic juice. The present review focuses on these "alternative" sources of genetic material and their analysis by ddPCR in different kinds of cancers.

Indexed as

Cell-Free Nucleic AcidsCirculating Tumor DNALung NeoplasmsBiomarkers, TumorHumansLiquid BiopsyMutationNeoplasm Recurrence, LocalPolymerase Chain ReactionBiomarkers, TumorCell-Free Nucleic AcidsCirculating Tumor DNA

Identifiers

PMID34773243
OpenAlexW3212238494

What OpenQuestion holds

Textmetadata
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.