Evidence map›Paper›PMID 33256706›Full record

ArticleBMC medical genomics2020

Utility of a custom designed next generation DNA sequencing gene panel to molecularly classify endometrial cancers according to The Cancer Genome Atlas subgroups.

Eirwen M Miller, Nicole E Patterson, Gregory M Gressel, Rouzan G Karabakhtsian, Michal Bejerano-Sagie, Nivedita Ravi, Alexander Maslov, Wilber Quispe-Tintaya, Tao Wang, Juan Lin and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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

14 authors at 3 institutions in 1 country.

Eirwen M MillerDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology and Women's Health, Montefiore Medical Center, Bronx, NY, 10461, USA.
Nicole E PattersonDepartment of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA.
Gregory M GresselDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology and Women's Health, Montefiore Medical Center, Bronx, NY, 10461, USA.
Rouzan G KarabakhtsianDepartment of Pathology, Montefiore Medical Center, Bronx, NY, 10461, USA.
Michal Bejerano-SagieDepartment of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA.
Nivedita RaviDepartment of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA.
Alexander MaslovDepartment of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA.
Wilber Quispe-TintayaDepartment of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA.
Tao WangDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
Juan LinDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
Harriet O SmithDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology and Women's Health, Montefiore Medical Center, Bronx, NY, 10461, USA.
Gary L GoldbergDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology and Women's Health, Montefiore Medical Center, Bronx, NY, 10461, USA.
Dennis Y S KuoDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology and Women's Health, Montefiore Medical Center, Bronx, NY, 10461, USA.
Cristina MontagnaDepartment of Genetics, Albert Einstein College of Medicine, Price Center/Block Research Pavilion, Room 401, 1301 Morris Park Avenue, Bronx, NY, 10461, USA. cristina.montagna@einsteinmed.org.ORCID 0000-0003-2343-5851
Albert Einstein College of Medicine · USMontefiore Medical Center · USNorthwell Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Cancer Genome Atlas identified four molecular subgroups of endometrial cancer with survival differences based on whole genome, transcriptomic, and proteomic characterization. Clinically accessible algorithms that reproduce this data are needed. Our aim was to determine if targeted sequencing alone allowed for molecular classification of endometrial cancer.

methodsUsing a custom-designed 156 gene panel, we analyzed 47 endometrial cancers and matching non-tumor tissue. Variants were annotated for pathogenicity and medical records were reviewed for the clinicopathologic variables. Using molecular characteristics, tumors were classified into four subgroups. Group 1 included patients with > 570 unfiltered somatic variants, > 9 cytosine to adenine nucleotide substitutions per sample, and < 1 cytosine to guanine nucleotide substitution per sample. Group 2 included patients with any somatic mutation in MSH2, MSH6, MLH1, PMS2. Group 3 included patients with TP53 mutations without mutation in mismatch repair genes. Remaining patients were classified as group 4. Analyses were performed using SAS 9.4 (SAS Institute Inc., Cary, North Carolina, USA).

resultsEndometrioid endometrial cancers had more candidate variants of potential pathogenic interest (median 6 IQR 4.13 vs. 2 IQR 2.3; p < 0.01) than uterine serous cancers. PTEN (82% vs. 15%, p < 0.01) and PIK3CA (74% vs. 23%, p < 0.01) mutations were more frequent in endometrioid than serous carcinomas. TP53 (18% vs. 77%, p < 0.01) mutations were more frequent in serous carcinomas. Visual inspection of the number of unfiltered somatic variants per sample identified six grade 3 endometrioid samples with high tumor mutational burden, all of which demonstrated POLE mutations, most commonly P286R and V411L. Of the grade 3 endometrioid carcinomas, those with POLE mutations were less likely to have risk factors necessitating adjuvant treatment than those with low tumor mutational burden. Targeted sequencing was unable to assign samples to microsatellite unstable, copy number low, and copy number high subgroups.

conclusionsTargeted sequencing can predict the presence of POLE mutations based on the tumor mutational burden. However, targeted sequencing alone is inadequate to classify endometrial cancers into molecular subgroups identified by The Cancer Genome Atlas.

Indexed as

High-Throughput Nucleotide SequencingMutationAgedCarcinoma, EndometrioidDNA Copy Number VariationsDNA Mismatch RepairDNA, NeoplasmDNA Polymerase IIEndometrial NeoplasmsFemaleHumansINDEL MutationMiddle AgedMolecular Sequence AnnotationNeoplasm ProteinsNeoplasms, Second PrimaryDNA, NeoplasmDNA Polymerase IINeoplasm ProteinsPOLE protein, humanPoly-ADP-Ribose Binding ProteinsEndometrial carcinomaEndometrioid uterine carcinomaGenomic profilingMolecular groupsNext generation sequencingTargeted sequencingUterine serous carcinoma

Identifiers

PMID33256706
PMCPMC7706212
OpenAlexW3109751112

What OpenQuestion holds

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LicenceCC BY
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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.