Evidence map›Paper›PMID 34721546›Full record

ArticleFrontiers in genetics2021

Signatures Beyond Oncogenic Mutations in Cell-Free DNA Sequencing for Non-Invasive, Early Detection of Cancer.

Subhajyoti De

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 56% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

1 author at 1 institution in 1 country.

Subhajyoti DeRutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States.
Rutgers Cancer Institute of New Jersey

Funding

Computational approaches for identifying epigenomic contexts of somatic mutationsR01GM129066 · NIGMS · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI DE, SUBHAJYOTI · 2019 to 2023
$1.7M
Inference of tumor growth dynamics using genomic dataR21CA248122 · NCI · RBHS -CANCER INSTITUTE OF NEW JERSEY · PI DE, SUBHAJYOTI · 2020 to 2021
$402k
NCI NIH HHS R21 CA248122NIGMS NIH HHS R01 GM129066
6 · The paper itself

Abstract

Early detection of cancer saves lives, but an effective detection strategy in public health settings requires a delicate balance - periodic screening should neither miss rapidly progressing disease nor fail to detect rare tumors at unusual locations; on the other hand, even a modest false positive rate carries risks of over-diagnosis and over-treatment of relatively indolent non-malignant disease. Genomic profiling of cell-free DNA from liquid biopsy using massively parallel sequencing is emerging as an attractive, non-invasive screening platform for sensitive detection of multiple types of cancer in a single assay. Genomic data from cell-free DNA can not only identify oncogenic mutation status, but also additional molecular signatures related to potential tissue of origin, the extent of clonal growth, and malignant disease states. Utilization of the full potential of the molecular signatures from cfDNA sequencing data can guide clinical management strategies for targeted follow-ups using imaging or molecular marker-based diagnostic platforms and treatment options.

Indexed as

cancercell-free DNAearly detectionnon-invasivesequencing

Identifiers

PMID34721546
PMCPMC8551553
OpenAlexW3207737995

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.