Evidence map›Paper›PMID 38105959›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Multiplexed RNA-FISH-guided Laser Capture Microdissection RNA Sequencing Improves Breast Cancer Molecular Subtyping, Prognostic Classification, and Predicts Response to Antibody Drug Conjugates.

Evan D Paul, Barbora Huraiová, Natália Valková, Natalia Birknerova, Daniela Gábrišová, Sona Gubova, Helena Ignačáková, Tomáš Ondris, Silvia Bendíková, Jarmila Bíla and 15 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors at 6 institutions in 5 countries.

Evan D PaulMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0002-7011-8050
Barbora HuraiováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0001-8784-8001
Natália ValkováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0003-3898-7229
Natalia BirknerovaMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0002-2006-6694
Daniela GábrišováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0009-0001-3154-2369
Sona GubovaMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0009-0005-4791-7056
Helena IgnačákováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0002-3854-1641
Tomáš OndrisMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0009-0009-2112-4006
Silvia BendíkováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.
Jarmila BílaMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.
Katarína BuranovskáMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.
Diana DrobnáMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.
Zuzana KrchnakovaMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0003-4736-5181
Maryna KryvokhyzhaMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0002-3444-9792
Daniel LovíšekMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0001-5654-3504
Viktoriia MamoilykMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.
Veronika MančíkováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0002-8155-9927
Nina VojtaššákováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.
Michaela RistováMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0003-1519-3805
Iñaki Comino-MéndezUnidad de Gestión Clínica Intercentros de Oncología Medica, Hospitales Universitarios Regional y Virgen de la Victoria. The Biomedical Research Institute of Málaga (IBIMA-CIMES-UMA), Málaga, Spain.ORCID 0000-0003-1926-9432
Igor AndrašinaDepartment of Radiotherapy and Oncology, East Slovakia Institute of Oncology, Košice, Slovakia.ORCID 0000-0002-6186-1846
Pavel MorozovLaboratory for RNA Molecular Biology, The Rockefeller University, New York NY, USA.
Thomas TuschlLaboratory for RNA Molecular Biology, The Rockefeller University, New York NY, USA.ORCID 0000-0002-6483-5678
Fresia ParejaDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0003-3748-8049
Pavol ČekanMultiplexDX, s.r.o., Comenius University Science Park, Bratislava, Slovakia.ORCID 0000-0001-8806-9958
Comenius University Bratislava · SKRockefeller University · USCharles University · CZInstituto de Investigación Biomédica de Málaga · ESMemorial Sloan Kettering Cancer Center · USWellcome Centre for Cell Biology · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

On a retrospective cohort of 1,082 FFPE breast tumors, we demonstrated the analytical validity of a test using multiplexed RNA-FISH-guided laser capture microdissection (LCM) coupled with RNA-sequencing (mFISHseq), which showed 93% accuracy compared to immunohistochemistry. The combination of these technologies makes strides in i) precisely assessing tumor heterogeneity, ii) obtaining pure tumor samples using LCM to ensure accurate biomarker expression and multigene testing, and iii) providing thorough and granular data from whole transcriptome profiling. We also constructed a 293-gene intrinsic subtype classifier that performed equivalent to the research based PAM50 and AIMS classifiers. By combining three molecular classifiers for consensus subtyping, mFISHseq alleviated single sample discordance, provided near perfect concordance with other classifiers (κ > 0.85), and reclassified 30% of samples into different subtypes with prognostic implications. We also use a consensus approach to combine information from 4 multigene prognostic classifiers and clinical risk to characterize high, low, and ultra-low risk patients that relapse early (< 5 years), late (> 10 years), and rarely, respectively. Lastly, to identify potential patient subpopulations that may be responsive to treatments like antibody drug-conjugates (ADC), we curated a list of 92 genes and 110 gene signatures to interrogate their association with molecular subtype and overall survival. Many genes and gene signatures related to ADC processing (e.g., antigen/payload targets, endocytosis, and lysosome activity) were independent predictors of overall survival in multivariate Cox regression models, thus highlighting potential ADC treatment-responsive subgroups. To test this hypothesis, we constructed a unique 19-feature classifier using multivariate logistic regression with elastic net that predicted response to trastuzumab emtansine (T-DM1; AUC = 0.96) better than either

Indexed as

antibody drug-conjugatesbreast cancerlaser capture microdissectionRNA-FISHRNA-sequencingspatial biology

Identifiers

PMID38105959
PMCPMC10723508
OpenAlexW4389376320

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.