Evidence map›Paper›PMID 40491495›Full record

ArticleiScience2025

Catalyzing early ovarian cancer detection: Platelet RNA-based precision screening.

Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Hyejin Lee, Yeochan Kim, Sangick Park, Suyeon Lee, Dong Won Hwang, Heeyeon Kim and 6 more

Abstract read
In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

16 authors.

Eunyong AhnForetell My Health, lnc., 558 Handong-ro Buk-gu, Pohang 37554, Republic of Korea.
Se Ik KimDepartment of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul 03080, South Korea.
Sungmin ParkForetell My Health, lnc., 558 Handong-ro Buk-gu, Pohang 37554, Republic of Korea.
Sarah KimForetell My Health, lnc., 558 Handong-ro Buk-gu, Pohang 37554, Republic of Korea.
Hyejin LeeForetell My Health, lnc., 558 Handong-ro Buk-gu, Pohang 37554, Republic of Korea.
Yeochan KimSchool of Life Science, Handong Global University, Pohang 37554, Republic of Korea.
Sangick ParkSchool of Life Science, Handong Global University, Pohang 37554, Republic of Korea.
Suyeon LeeSchool of Life Science, Handong Global University, Pohang 37554, Republic of Korea.
Dong Won HwangDepartment of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul 03080, South Korea.
Heeyeon KimCancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
HyunA JoCancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
Untack ChoCancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
Juwon LeeCancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
Cheol LeeDepartment of Pathology, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
TaeJin AhnForetell My Health, lnc., 558 Handong-ro Buk-gu, Pohang 37554, Republic of Korea.
Yong-Sang SongDepartment of Obstetrics and Gynecology, Myongji Hospital, Gyeonggi-do 10475, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early detection of ovarian cancer is crucial for successful treatment, yet most cases are diagnosed at advanced stages due to a lack of effective screening. Recent advancements in RNA technology from platelets aid in early tumor detection. Here, we proposed our two-step method for assessing the existence of pelvic mass either located at ovaries or uterus with more than 99% specificity by utilizing exon-exon junction features with a sampling invariant normalization technique; then next our model finds the malignancy of detected mass with more than 99% negative predictive value for ovarian cancer to practically assist clinicians' further investigation via combined features of exon-exon junctions, and hematology parameters. We diverged from traditional methods by employing intron-spanning reads (ISR) counts rather than gene expression levels to use splice junctions as features in our models. If integrated with current screening methods, our algorithm holds promise for identifying ovarian or endometrial cancer in its early stages.

Indexed as

Health informaticsHealth sciencesHealth technologyMedicine

Identifiers

PMID40491495
PMCPMC12148375

What OpenQuestion holds

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Registered trials

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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.