Evidence map›Paper›PMID 37627132›Full record

ReviewCancers2023

Patient-Derived Ex Vivo Cultures and Endpoint Assays with Surrogate Biomarkers in Functional Testing for Prediction of Therapeutic Response.

Yoshiyuki Tsukamoto, Yuka Hirashita, Tomotaka Shibata, Shoichi Fumoto, Shusaku Kurogi, Chisato Nakada, Keisuke Kinoshita, Takafumi Fuchino, Kazunari Murakami, Masafumi Inomata and 2 more

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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 at 2 institutions in 1 country.

Yoshiyuki TsukamotoDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Yuka HirashitaDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Tomotaka ShibataDepartment of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita 879-5593, Japan.ORCID 0000-0001-8797-8877
Shoichi FumotoDepartment of Surgery, Oita Nakamura Hospital, Oita 879-5593, Japan.
Shusaku KurogiDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Chisato NakadaDepartment of Urology, Faculty of Medicine, Oita University, Oita 879-5593, Japan.
Keisuke KinoshitaDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Takafumi FuchinoDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Kazunari MurakamiDepartment of Gastroenterology, Faculty of Medicine, Oita University, Oita 879-5593, Japan.ORCID 0000-0003-2668-5039
Masafumi InomataDepartment of Gastroenterological and Pediatric Surgery, Faculty of Medicine, Oita University, Oita 879-5593, Japan.
Masatsugu MoriyamaDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Naoki HijiyaDepartment of Molecular Pathology, Faculty of Medicine, Oita University, 1-1 Hasama-machi, Oita 879-5593, Japan.
Oita University · JPNakamura Memorial Hospital · JP

Funding

Japan Society for the Promotion of Science JP21H02703
6 · The paper itself

Abstract

Prediction of therapeutic outcomes is important for cancer patients in order to reduce side effects and improve the efficacy of anti-cancer drugs. Currently, the most widely accepted method for predicting the efficacy of anti-cancer drugs is gene panel testing based on next-generation sequencing. However, gene panel testing has several limitations. For example, only 10% of cancer patients are estimated to have druggable mutations, even if whole-exome sequencing is applied. Additionally, even if optimal drugs are selected, a significant proportion of patients derive no benefit from the indicated drug treatment. Furthermore, most of the anti-cancer drugs selected by gene panel testing are molecularly targeted drugs, and the efficacies of cytotoxic drugs remain difficult to predict. Apart from gene panel testing, attempts to predict chemotherapeutic efficacy using ex vivo cultures from cancer patients have been increasing. Several groups have retrospectively demonstrated correlations between ex vivo drug sensitivity and clinical outcome. For ex vivo culture, surgically resected tumor tissue is the most abundant source. However, patients with recurrent or metastatic tumors do not usually undergo surgery, and chemotherapy may be the only option for those with inoperable tumors. Therefore, predictive methods using small amounts of cancer tissue from diagnostic materials such as endoscopic, fine-needle aspirates, needle cores and liquid biopsies are needed. To achieve this, various types of ex vivo culture and endpoint assays using effective surrogate biomarkers of drug sensitivity have recently been developed. Here, we review the variety of ex vivo cultures and endpoint assays currently available.

Indexed as

3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT)collagen droplet-embedded culture drug sensitivity test (CD-DST)extracellular matrix (ECM)functional testinglactate dehydrogenase (LDH)micro-organospheres (MOSs)organs on chipspatient derived cancer organoids (PDCOs)patient derived explants (PDEs)spheroid

Identifiers

PMID37627132
PMCPMC10452496
OpenAlexW4385835372

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.