Evidence map›Paper›PMID 34075161›Full record

Trial reportScientific reports2021

Combination of gene set signatures correlates with response to nivolumab in platinum-resistant ovarian cancer.

Ryusuke Murakami, Junzo Hamanishi, J B Brown, Kaoru Abiko, Koji Yamanoi, Mana Taki, Yuko Hosoe, Ken Yamaguchi, Tsukasa Baba, Noriomi Matsumura and 2 more

Abstract readClinical Trial, Phase II
In one paragraph

Trial report in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Treatment of ovarian clear cell carcinoma with immune checkpoint blockade: a case series.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2022
    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

12 authors.

Ryusuke Murakami *Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Junzo Hamanishi *Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan. jnkhmns@kuhp.kyoto-u.ac.jp.
J B Brown *Laboratory for Molecular Biosciences, Life Science Informatics Research Unit, Kyoto University Graduate School of Medicine, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
Kaoru AbikoDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Koji YamanoiDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Mana TakiDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Yuko HosoeDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Ken YamaguchiDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Tsukasa BabaDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Noriomi MatsumuraDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Ikuo KonishiDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.
Masaki MandaiDepartment of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8501, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on our previous phase II clinical trial of anti-programmed death-1 (PD-1) antibody nivolumab for platinum-resistant ovarian cancer (n = 19, UMIN000005714), we aimed to identify the biomarkers predictive of response. Tumor gene expression was evaluated by proliferative, mesenchymal, differentiated, and immunoreactive gene signatures derived from high-grade serous carcinomas and a signature established prior for ovarian clear cell carcinoma. Resulting signature scores were statistically assessed with both univariate and multivariate approaches for correlation to clinical response. Analyses were performed to identify pathways differentially expressed by either the complete response (CR) or progressive disease (PD) patient groups. The clear cell gene signature was scored significantly higher in the CR group, and the proliferative gene signature had significantly higher scores in the PD group where nivolumab was not effective (respective p values 0.005 and 0.026). Combinations of gene signatures improved correlation with response, where a visual projection of immunoreactive, proliferative, and clear cell signatures differentiated clinical response. An applicable clinical response prediction formula was derived. Ovarian cancer-specific gene signatures and related pathway scores provide a robust preliminary indicator for ovarian cancer patients prior to anti-PD-1 therapy decisions.

Indexed as

Carcinoma, Ovarian EpithelialOvarian NeoplasmsAntineoplastic Agents, ImmunologicalBiomarkers, TumorFemaleHumansNivolumabProgrammed Cell Death 1 ReceptorAntineoplastic Agents, ImmunologicalBiomarkers, TumorNivolumabPDCD1 protein, humanProgrammed Cell Death 1 Receptor

Identifiers

PMID34075161
PMCPMC8169687

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.