Evidence map›Paper›PMID 33789687›Full record

ReviewJournal of experimental & clinical cancer research : CR2021

Patient-derived organoids and high grade serous ovarian cancer: from disease modeling to personalized medicine.

Camilla Nero, Giuseppe Vizzielli, Domenica Lorusso, Eleonora Cesari, Gennaro Daniele, Matteo Loverro, Giovanni Scambia, Claudio Sette

Abstract readReview
In one paragraph

Review in Journal of experimental & clinical cancer research : CR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
–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

40 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  9. Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2025
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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.

Camilla NeroFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy.
Giuseppe VizzielliFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy.
Domenica LorussoFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy.
Eleonora CesariFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy.
Gennaro DanieleFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy.
Matteo LoverroFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy.
Giovanni ScambiaFondazione Policlinico Universitario A. Gemelli IRCCS, L.go Agostino gemelli, 8, 00168, Roma, Italy. giovanni.scambia@policlinicogemelli.it.
Claudio SetteDipartimento di Neuroscienze, Sezione di Anatomia Umana, Università Cattolica del Sacro Cuore, Roma, Italy. claudio.sette@unicatt.it.ORCID http://orcid.org/0000-0003-2864-8266

Funding

Associazione Italiana per la Ricerca sul Cancro IG23416Ministero della Salute GR-2019-12371435Università Cattolica del Sacro Cuore Linea D1, Linea 3.1
6 · The paper itself

Abstract

backgroundHigh grade serous ovarian cancer (HGSOC) is among the deadliest human cancers and its prognosis remains extremely poor. Tumor heterogeneity and rapid acquisition of resistance to conventional chemotherapeutic approaches strongly contribute to poor outcome of patients. The clinical landscape of HGSOC has been radically transformed since the advent of targeted therapies in the last decade. Nevertheless, the lack of predictive biomarkers informing on the differential clinical benefit in select subgroups, and allowing patient-centric approaches, currently limits the efficacy of these novel therapies. Thus, rational selection of the best possible treatment for each patient represents a clinical priority in order to improve outcome, while limiting undesirable effects. MAIN BODY: In this review, we describe the state of the art and the unmet needs in HGSOC management, illustrate the treatment options that are available and the biomarkers that are currently employed to orient clinical decisions. We also describe the ongoing clinical trials that are testing new therapeutic approaches for HGSOC. Next, we introduce the organoid technology as a promising, expanding strategy to study cancer and to develop personalized therapeutic approaches. In particular, we discuss recent studies that have characterized the translational potential of Patient's Derived Organoids (PDOs) to inform on drug sensitivity of HGSOC patients.

conclusionsPDOs can predict the response of patients to treatments and may therefore guide therapeutic decisions. Although preliminary results appear encouraging, organoids still need to be generated and expanded efficiently to enable drug screening in a clinically meaningful time window. A new generation of clinical trials based on the organoid technology should guarantee tailored approaches to ovarian cancer management, as it is now clear that the one-size-fits-all approach cannot lead to efficient and meaningful therapeutic advancements.

Indexed as

Cystadenocarcinoma, SerousFemaleHumansOrganoidsOvarian NeoplasmsPrecision MedicineSurvival Analysis3D culturesDrug screeningOrganoidsOvarian cancerTarget therapy

Identifiers

PMID33789687
PMCPMC8011220

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.