Evidence map›Paper›PMID 25155861›Full record

ArticleCancer2015

Serum-based miRNAs in the prediction and detection of recurrence in melanoma patients.

Nathaniel H Fleming, Judy Zhong, Inês Pires da Silva, Eleazar Vega-Saenz de Miera, Bobbi Brady, Sung Won Han, Doug Hanniford, Jinhua Wang, Richard L Shapiro, Eva Hernando and 1 more

Abstract readHistorical Article
In one paragraph

Article in Cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
–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

62 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. A New Approach to Melanoma Treatment: microRNAs.Current topics in medicinal chemistry · 2024
    Review
  9. Liquid biopsy for diagnostic and prognostic evaluation of melanoma.Frontiers in cell and developmental biology · 2024
    Review
  10. Review
  11. Article
  12. Human CD79bFrontiers in immunology · 2023
    Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Prognostic Biomarkers in Melanoma: Tailoring Treatments to the Patient.The Journal of clinical and aesthetic dermatology · 2021
    Review
  18. Article
  19. Article
  20. Article

2 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

11 authors.

Nathaniel H FlemingRonald O. Perelman Department of Dermatology, New York University School of Medicine, New York, New York; Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, New York.
Judy Zhong
Inês Pires da Silva
Eleazar Vega-Saenz de Miera
Bobbi Brady
Sung Won Han
Doug Hanniford
Jinhua Wang
Richard L Shapiro
Eva Hernando
Iman Osman

Funding

Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ADRIANA HEGUY · 1985 to 2026
$83.1M
MUC1-C Oncoprotein Evades Immune Destruction in Non-small Cell Lung CancerR01CA166480 · NCI · DANA-FARBER CANCER INST · PI KUFE, DONALD W., WONG, KWOK KIN · 2012 to 2021
$6.3M
Prognostic and Functional Role of microRNAs in Melanoma Brain MetastasisR01CA163891 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HERNANDO, EVA, OSMAN, IMAN · 2013 to 2017
$1.7M
Network based biosignature developmentR21GM110450 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ZHONG, HUA JUDY · 2014 to 2014
$167k
NCI NIH HHS 5 P30 CA016087-27NCI NIH HHS P30 CA016087NCI NIH HHS R01 CA163891NCI NIH HHS R01 CA166480NIGMS NIH HHS 1R21 GM110450-01NIGMS NIH HHS R21 GM110450
6 · The paper itself

Abstract

backgroundIdentification of primary melanoma patients at the highest risk of recurrence remains a critical challenge, and monitoring for recurrent disease is limited to costly imaging studies. We recently reported our array-based discovery of prognostic serum miRNAs in melanoma. In the current study, we examined the clinical utility of these serum-based miRNAs for prognosis as well as detection of melanoma recurrence.

methodsSerum levels of 12 miRNAs were tested using qRT-PCR at diagnosis in 283 melanoma patients (training cohort, n = 201; independent validation, n = 82; median follow-up, 68.8 months). A refined miRNA signature was chosen and evaluated. We also tested the potential clinical utility of the miRNAs in early detection and monitoring of recurrence using multiple longitudinal samples (pre- and postrecurrence) in a subset of 82 patients (n = 225). In addition, we integrated our miRNA signature with publicly available Cancer Genome Atlas data to examine the relevance of these miRNAs to melanoma biology.

resultsFour miRNAs (miR-150, miR-30d, miR-15b, and miR-425) in combination with stage separated patients by recurrence-free survival (RFS) and overall survival (OS) and improved prediction of recurrence over stage alone in both the training and validation cohorts (training RFS and OS, P < .001; validation RFS, P < .001; OS, P = .005). Serum miR-15b levels significantly increased over time in recurrent patients (P < .001), adjusting for endogenous controls as well as age, sex, and initial stage. In nonrecurrent patients, miR-15b levels were not significantly changed with time (P =.17).

conclusionsData demonstrate that serum miRNAs can improve melanoma patient stratification over stage and support further testing of miR-15b to guide patient surveillance.

Indexed as

AdultAgedAged, 80 and overEarly Detection of CancerFemaleGene Expression Regulation, NeoplasticHistory, AncientHumansMaleMelanomaMicroRNAsMiddle AgedNeoplasm Recurrence, LocalYoung AdultMicroRNAsMIRN15 microRNA, humanbiomarkersmelanomamicroRNAsrecurrenceserum markers

Identifiers

PMID25155861
PMCPMC4270907

What OpenQuestion holds

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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.