Evidence map›Paper›PMID 36826026›Full record

ReviewCurrent issues in molecular biology2023

Immunotherapeutic Approaches in Ovarian Cancer.

Hyunho Yoon, Ayoung Kim, Hoon Jang

Open access · goldAbstract readReview
In one paragraph

Review in Current issues in molecular biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.7field-weighted citation impact, top 7% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Immune pathway through endometriosis to ovarian cancer.World journal of clinical oncology · 2024
    Review
  5. Review
  6. Review
  7. Article
  8. Recent Insight about HE4 Role in Ovarian Cancer Oncogenesis.International journal of molecular sciences · 2023
    Review
  9. 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

3 authors at 2 institutions in 1 country.

Hyunho YoonDepartment of Medical and Biological Sciences, The Catholic University of Korea, Bucheon 14662, Republic of Korea.
Ayoung KimDepartment of Medical and Biological Sciences, The Catholic University of Korea, Bucheon 14662, Republic of Korea.
Hoon JangDepartment of Life Sciences, Jeonbuk National University, Jeonju 54896, Republic of Korea.
Catholic University of Korea · KRJeonbuk National University · KR

Funding

Brain Korea 21 M2022B002600003National Research Foundation 2021R1C1C1011346
6 · The paper itself

Abstract

Ovarian cancer (OC) is gynecological cancer, and diagnosis and treatment are continuously advancing. Next-generation sequencing (NGS)-based diagnoses have emerged as novel methods for identifying molecules and pathways in cancer research. The NGS-based applications have expanded in OC research for early detection and identification of aberrant genes and dysregulation pathways, demonstrating comprehensive views of the entire transcriptome, such as fusion genes, genetic mutations, and gene expression profiling. Coinciding with advances in NGS-based diagnosis, treatment strategies for OC, such as molecular targeted therapy and immunotherapy, have also advanced. Immunotherapy is effective against many other cancers, and its efficacy against OC has also been demonstrated at the clinical phase. In this review, we describe several NGS-based applications for therapeutic targets of OC, and introduce current immunotherapeutic strategies, including vaccines, checkpoint inhibitors, and chimeric antigen receptor (CAR)-T cell transplantation, for effective diagnosis and treatment of OC.

Indexed as

immunotherapynext-generation sequencingovarian cancer

Identifiers

PMID36826026
PMCPMC9955550
OpenAlexW4319081190

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.