Evidence map›Paper›PMID 37377606›Full record

ArticleCancer research communications2023

Optimizing Precision Medicine for Breast Cancer Brain Metastases with Functional Drug Response Assessment.

Aki Morikawa, Jinju Li, Peter Ulintz, Xu Cheng, Athena Apfel, Dan Robinson, Alex Hopkins, Chandan Kumar-Sinha, Yi-Mi Wu, Habib Serhan and 9 more

Open access · goldAbstract read
In one paragraph

Article in Cancer research communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

19 authors at 1 institution in 1 country.

Aki MorikawaDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-4764-4896
Jinju LiDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan.ORCID 0009-0001-4269-9150
Peter UlintzDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-2037-8655
Xu ChengDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0009-0009-8385-3108
Athena ApfelDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0003-1662-3598
Dan RobinsonDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-2337-7439
Alex HopkinsDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-0817-1889
Chandan Kumar-SinhaDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-8696-3400
Yi-Mi WuDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-3789-4445
Habib SerhanDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0009-0008-9592-8587
Kait VerbalDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.ORCID 0009-0000-8813-6874
Dafydd ThomasDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-0379-7460
Daniel F HayesDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0003-3620-7575
Arul M ChinnaiyanDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0001-9282-3415
Veerabhadran BaladandayuthapaniDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0001-9107-3157
Jason HethDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0001-5463-4066
Matthew B SoellnerDepartment of Chemistry, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0003-1394-8645
Sofia D Merajver *Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0002-6823-7130
Nathan Merrill *Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID 0000-0003-0757-3680
University of Michigan · US

Funding

Advanced development and validation of an in vitro platform to phenotype brain metastatic tumor cells using artificial intelligenceR33CA261696 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI FU, JIANPING, MERAJVER, SOFIA DIANA · 2022 to 2024
$1.1M
NCI NIH HHS R33 CA261696
6 · The paper itself

Abstract

The development of novel therapies for brain metastases is an unmet need. Brain metastases may have unique molecular features that could be explored as therapeutic targets. A better understanding of the drug sensitivity of live cells coupled to molecular analyses will lead to a rational prioritization of therapeutic candidates. We evaluated the molecular profiles of 12 breast cancer brain metastases (BCBM) and matched primary breast tumors to identify potential therapeutic targets. We established six novel patient-derived xenograft (PDX) from BCBM from patients undergoing clinically indicated surgical resection of BCBM and used the PDXs as a drug screening platform to interrogate potential molecular targets. Many of the alterations were conserved in brain metastases compared with the matched primary. We observed differential expressions in the immune-related and metabolism pathways. The PDXs from BCBM captured the potentially targetable molecular alterations in the source brain metastases tumor. The alterations in the PI3K pathway were the most predictive for drug efficacy in the PDXs. The PDXs were also treated with a panel of over 350 drugs and demonstrated high sensitivity to histone deacetylase and proteasome inhibitors. Our study revealed significant differences between the paired BCBM and primary breast tumors with the pathways involved in metabolisms and immune functions. While molecular targeted drug therapy based on genomic profiling of tumors is currently evaluated in clinical trials for patients with brain metastases, a functional precision medicine strategy may complement such an approach by expanding potential therapeutic options, even for BCBM without known targetable molecular alterations. Significance: Examining genomic alterations and differentially expressed pathways in brain metastases may inform future therapeutic strategies. This study supports genomically-guided therapy for BCBM and further investigation into incorporating real-time functional evaluation will increase confidence in efficacy estimations during drug development and predictive biomarker assessment for BCBM.

Indexed as

Brain NeoplasmsBreast NeoplasmsFemaleHumansPhosphatidylinositol 3-KinasesPrecision MedicinePhosphatidylinositol 3-Kinases

Identifiers

PMID37377606
PMCPMC10284082
OpenAlexW4379535736

What Socratic 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 Socratic graph.