Evidence map›Paper›PMID 37900283›Full record

ReviewFrontiers in cell and developmental biology2023

An update on methods for detection of prognostic and predictive biomarkers in melanoma.

Oluwaseyi Adeuyan, Emily R Gordon, Divya Kenchappa, Yadriel Bracero, Ajay Singh, Gerardo Espinoza, Larisa J Geskin, Yvonne M Saenger

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
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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

8 authors at 3 institutions in 1 country.

Oluwaseyi AdeuyanColumbia University Vagelos College of Physicians and Surgeons, New York, NY, United States.
Emily R GordonColumbia University Vagelos College of Physicians and Surgeons, New York, NY, United States.
Divya KenchappaAlbert Einstein College of Medicine, Bronx, NY, United States.
Yadriel BraceroAlbert Einstein College of Medicine, Bronx, NY, United States.
Ajay SinghAlbert Einstein College of Medicine, Bronx, NY, United States.
Gerardo EspinozaAlbert Einstein College of Medicine, Bronx, NY, United States.
Larisa J GeskinDepartment of Dermatology, Columbia University Irving Medical Center, New York, NY, United States.
Yvonne M SaengerAlbert Einstein College of Medicine, Bronx, NY, United States.
Albert Einstein College of Medicine · USColumbia University · USColumbia University Irving Medical Center · US

Funding

Applying pathomics to establish a biosignature for aggressive skin melanoma.R01CA260375 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Rui Chang, Yvonne Margaret Saenger · 2021 to 2026
$3.1M
NCI NIH HHS R01 CA260375
6 · The paper itself

Abstract

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

Indexed as

checkpoint inhibitionimmunotherapymelanomapredictive biomarkerprognostic biomarker

Identifiers

PMID37900283
PMCPMC10611507
OpenAlexW4387607961

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.