Evidence map›Paper›PMID 26942589›Full record

ReviewCurrent treatment options in oncology2016

New Approaches for Immune Directed Treatment for Ovarian Cancer.

Nicola Hardwick, Paul H Frankel, Mihaela Cristea

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Antigen-specific active immunotherapy for ovarian cancer.The Cochrane database of systematic reviews · 2018
    Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Organoid of ovarian cancer: genomic analysis and drug screening.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020
    Review
  7. Review
  8. Article
  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.

Nicola HardwickDepartment of Experimental Therapeutics, Beckman Research Institute of City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
Paul H FrankelDivision of Biostatistics, Beckman Research Institute of City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
Mihaela CristeaDepartment of Medical Oncology, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA. mcristea@coh.org.
Beckman Research InstituteCity Of Hope National Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

opinion statementThe immune system plays an active role in the pathogenesis of ovarian cancer (OC), as well as in the mechanisms of disease progression and overall survival (OS). Immunotherapy in gynecological cancers could help to revert immunosuppression and lymphocyte depletion due to prior treatments. Current immunotherapies for ovarian cancer, like all cancer immunotherapy, are based on either stimulating the immune system or reverting immune suppression. Several approaches have been used, including therapeutic vaccines, monoclonal antibodies; checkpoint inhibitors and adoptive T cell transfer. Most of these therapies are still in early-phase testing (phase I and II) for ovarian cancer, but the initial data in ovarian cancer and successful use in other types of cancers suggests some of these approaches may ultimately prove useful for ovarian cancer as well. Ovarian cancer vaccines have shown only a modest benefit in ovarian cancer when used as monotherapy, but these agents may be able to enhance antitumor activity when combined with chemotherapy, checkpoint inhibitors, or other immunotherapies. Monoclonal antibodies have been explored in ovarian cancer but despite encouraging phase II data, randomized studies failed to demonstrate significant clinical benefit. Check point inhibitors have promising activity in several solid tumors and have demonstrated a favorable toxicity profile. Data from early clinical trials utilizing PD1 and PD-L1 inhibitors showed encouraging results. Ongoing clinical trials are evaluating the role of check point inhibitors in combination with chemotherapy. Adoptive T cell transfer involves the infusion of ex vivo activated and expanded tumor specific T cells, using various sources and types of T cells. While this approach has been explored in several hematologic malignancies, it constitutes early research in ovarian cancer. Immunotherapy remains investigational in ovarian cancer and the benefit of this approach in improving progression-free survival (PFS) or OS is unknown. Previous clinical trials have not selected patients based on biomarkers and this may explain the negative results. We expect to discover that tumor response will relate to the patient's immune features and specific tumor characteristics. We are only beginning to realize the potential of immunotherapy for ovarian cancer patients, and one goal of future clinical trials will be to identify subsets of patient based on histologic, molecular, and immune characteristics.

Indexed as

ImmunotherapyAntibodies, MonoclonalB7-H1 AntigenCancer VaccinesClinical Trials as TopicDisease-Free SurvivalFemaleHumansImmunosuppression TherapyOvarian NeoplasmsProgrammed Cell Death 1 ReceptorT-LymphocytesAntibodies, MonoclonalB7-H1 AntigenCancer VaccinesCD274 protein, humanPDCD1 protein, humanProgrammed Cell Death 1 ReceptorAdoptive T cell transferCancer vaccineImmunotherapyMonoclonal antibodies check point inhibitorsOvarian cancer

Identifiers

PMID26942589
OpenAlexW2290214558

What OpenQuestion holds

Textmetadata
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.