Evidence map›Paper›PMID 35392854›Full record

ArticleBMC cancer2022

Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer.

Lavanya Sivapalan, Graeme J Thorn, Emanuela Gadaleta, Hemant M Kocher, Helen Ross-Adams, Claude Chelala

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2022. 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
1.9field-weighted citation impact, top 13% 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, 20 citations in OpenAlex.

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  6. Exploring the interactions of integrins and CEACAM6 (Review).Experimental and therapeutic medicine · 2025
    Review
  7. ctDNA in Pancreatic Adenocarcinoma: A Critical Appraisal.Current oncology (Toronto, Ont.) · 2025
    Review
  8. Observational
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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 1 institution in 1 country.

Lavanya SivapalanCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, EC1M 6BQ, UK.
Graeme J ThornCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, EC1M 6BQ, UK.
Emanuela GadaletaCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, EC1M 6BQ, UK.
Hemant M KocherCentre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, EC1M 6BQ, UK.
Helen Ross-AdamsCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, EC1M 6BQ, UK.
Claude ChelalaCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, EC1M 6BQ, UK. c.chelala@qmul.ac.uk.
Queen Mary University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe utility of circulating tumour DNA (ctDNA) for longitudinal tumour monitoring in pancreatic ductal adenocarcinoma (PDAC) has not been explored beyond mutations in the KRAS proto-oncogene. Here, we aimed to characterise and track patient-specific somatic ctDNA variants, to assess longitudinal changes in disease burden and explore the landscape of actionable alterations.

methodsWe followed 3 patients with resectable disease and 4 patients with unresectable disease, including 4 patients with ≥ 3 serial follow-up samples, of whom 2 were rare long survivors (> 5 years). We performed whole exome sequencing of tumour gDNA and plasma ctDNA (n = 20) collected over a ~ 2-year period from diagnosis through treatment to death or final follow-up. Plasma from 3 chronic pancreatitis cases was used as a comparison for analysis of ctDNA mutations.

resultsWe detected > 55% concordance between somatic mutations in tumour tissues and matched serial plasma. Mutations in ctDNA were detected within known PDAC driver genes (KRAS, TP53, SMAD4, CDKN2A), in addition to patient-specific variants within alternative cancer drivers (NRAS, HRAS, MTOR, ERBB2, EGFR, PBRM1), with a trend towards higher overall mutation loads in advanced disease. ctDNA alterations with potential for therapeutic actionability were identified in all 7 patients, including DNA damage response (DDR) variants co-occurring with hypermutation signatures predictive of response to platinum chemotherapy. Longitudinal tracking in 4 patients with follow-up > 2 years demonstrated that ctDNA mutant allele fractions and clonal trends were consistent with CA19-9 measurements and/or clinically reported disease burden. The estimated prevalence of 'stem clones' was highest in an unresectable patient where changes in ctDNA dynamics preceded CA19-9 levels. Longitudinal evolutionary trajectories revealed ongoing subclonal evolution following chemotherapy.

conclusionThese results provide proof-of-concept for the use of exome sequencing of serial plasma to characterise patient-specific ctDNA profiles, and demonstrate the sensitivity of ctDNA in monitoring disease burden in PDAC even in unresectable cases without matched tumour genotyping. They reveal the value of tracking clonal evolution in serial ctDNA to monitor treatment response, establishing the potential of applied precision medicine to guide stratified care by identifying and evaluating actionable opportunities for intervention aimed at optimising patient outcomes for an otherwise intractable disease.

Indexed as

Carcinoma, Pancreatic DuctalCirculating Tumor DNAPancreatic NeoplasmsBiomarkers, TumorCA-19-9 AntigenHumansMutationProto-Oncogene Proteins p21(ras)Biomarkers, TumorCA-19-9 AntigenCirculating Tumor DNAProto-Oncogene Proteins p21(ras)BiomarkersCirculating tumour DNALiquid biopsyMonitoring

Identifiers

PMID35392854
PMCPMC8991893
OpenAlexW4226335428

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.