Evidence map›Paper›PMID 33403451›Full record

ReviewAnnals of biomedical engineering2021

Microengineered 3D Tumor Models for Anti-Cancer Drug Discovery in Female-Related Cancers.

Farbod Amirghasemi, Emmanuela Adjei-Sowah, Barbara A Pockaj, Mehdi Nikkhah

Abstract readReview
PubMed Publisher
In one paragraph

Review in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.8field-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

13 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Three-DimensionalInternational journal of biological sciences · 2024
    Review
  7. Article
  8. Cancer 3D Models for Metallodrug Preclinical Testing.International journal of molecular sciences · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. 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

4 authors at 2 institutions in 1 country.

Farbod Amirghasemi *School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287-9709, USA.
Emmanuela Adjei-Sowah *School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287-9709, USA.
Barbara A PockajDivision of Surgical Oncology and Endocrine Surgery, Department of Surgery, Mayo Clinic, Phoenix, AZ, USA.
Mehdi NikkhahSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287-9709, USA. mnikkhah@asu.edu.ORCID http://orcid.org/0000-0001-5970-7666
Arizona State University · USWinnMed · US

Funding

Division of Chemical, Bioengineering, Environmental, and Transport Systems #1914680
6 · The paper itself

Abstract

The burden of cancer continues to increase in society and negatively impacts the lives of numerous patients. Due to the high cost of current treatment strategies, there is a crucial unmet need to develop inexpensive preclinical platforms to accelerate the process of anti-cancer drug discovery to improve outcomes in cancer patients, most especially in female patients. Many current methods employ expensive animal models which not only present ethical concerns but also do not often accurately predict human physiology and the outcomes of anti-cancer drug responsiveness. Conventional treatment approaches for cancer generally include systemic therapy after a surgical procedure. Although this treatment technique is effective, the outcome is not always positive due to various complex factors such as intratumor heterogeneity and confounding factors within the tumor microenvironment (TME). Patients who develop metastatic disease still have poor prognosis. To that end, recent efforts have attempted to use 3D microengineered platforms to enhance the predictive power and efficacy of anti-cancer drug screening, ultimately to develop personalized therapies. Fascinating features of microengineered assays, such as microfluidics, have led to the advancement in the development of the tumor-on-chip technology platforms, which have shown tremendous potential for meaningful and physiologically relevant anti-cancer drug discovery and screening. Three dimensional microscale models provide unprecedented ability to unveil the biological complexities of cancer and shed light into the mechanism of anti-cancer drug resistance in a timely and resource efficient manner. In this review, we discuss recent advances in the development of microengineered tumor models for anti-cancer drug discovery and screening in female-related cancers. We specifically focus on female-related cancers to draw attention to the various approaches being taken to improve the survival rate of women diagnosed with cancers caused by sex disparities. We also briefly discuss other cancer types like colon adenocarcinomas and glioblastoma due to their high rate of occurrence in females, as well as the high likelihood of sex-biased mutations which complicate current treatment strategies for women. We highlight recent advances in the development of 3D microscale platforms including 3D tumor spheroids, microfluidic platforms as well as bioprinted models, and discuss how they have been utilized to address major challenges in the process of drug discovery, such as chemoresistance, intratumor heterogeneity, drug toxicity, etc. We also present the potential of these platform technologies for use in high-throughput drug screening approaches as a replacements of conventional assays. Within each section, we will provide our perspectives on advantages of the discussed platform technologies.

Indexed as

Antineoplastic AgentsColonic NeoplasmsDrug DiscoveryGlioblastomaTissue EngineeringAnimalsDrug Screening Assays, AntitumorFemaleHumansMutationNeoplasm MetastasisTumor MicroenvironmentAntineoplastic AgentsAnti-cancer drugsBiomaterialsCancerMicroengineering technologiesMicrofluidicsMicroscaleScreening

Identifiers

PMID33403451
OpenAlexW3118924444

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.