Evidence map›Paper›PMID 38617252›Full record

ArticlebioRxiv : the preprint server for biology2024

Rapid differentiation of estrogen receptor status in patient biopsy breast cancer aspirates with an optical nanosensor.

Pooja V Gaikwad, Nazifa Rahman, Pratyusha Ghosh, Dianna Ng, Ryan M Williams

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 3 institutions in 1 country.

Pooja V GaikwadThe City College of New York, Department of Biomedical Engineering, New York, NY 10031.
Nazifa RahmanThe City College of New York, Department of Biomedical Engineering, New York, NY 10031.
Pratyusha GhoshThe City College of New York, Department of Biomedical Engineering, New York, NY 10031.
Dianna NgMemorial Sloan Kettering Cancer Center, New York, NY 10065.
Ryan M WilliamsThe City College of New York, Department of Biomedical Engineering, New York, NY 10031.ORCID 0000-0002-2381-8732
City College of New York · USThe Graduate Center, CUNY · USMemorial Sloan Kettering Cancer Center · US

Funding

Training and Career Development CoreU54CA132378 · NCI · CITY COLLEGE OF NEW YORK · PI Bao Q Vuong · 2008 to 2026
$28.9M
Training and Career Development and Education CoreU54CA137788 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Daniel Alan Heller · 2008 to 2026
$28.1M
NCI NIH HHS U54 CA132378NCI NIH HHS U54 CA137788
6 · The paper itself

Abstract

Breast cancer is a substantial source of morbidity and mortality worldwide. It is particularly more difficult to treat at later stages, and treatment regimens depend heavily on both staging and the molecular subtype of the tumor. However, both detection and molecular analyses rely on standard imaging and histological method, which are costly, time-consuming, and lack necessary sensitivity/specificity. The estrogen receptor (ER) is, along with the progesterone receptor (PR) and human epidermal growth factor (HER-2), among the primary molecular markers which inform treatment. Patients who are negative for all three markers (triple negative breast cancer, TNBC), have fewer treatment options and a poorer prognosis. Therapeutics for ER+ patients are effective at preventing disease progression, though it is necessary to improve the speed of subtyping and distribution of rapid detection methods. In this work, we designed a near-infrared optical nanosensor using single-walled carbon nanotubes (SWCNT) as the transducer and an anti-ERα antibody as the recognition element. The nanosensor was evaluated for its response to recombinant ERα in buffer and serum prior to evaluation with ER- and ER+ immortal cell lines. We then used a minimal volume of just 10 μL from 26 breast cancer biopsy samples which were aspirated to mimic fine needle aspirates. 20 samples were ER+, while 6 were ER-, representing 13 unique patients. We evaluated the potential of the nanosensor by investigating several SWCNT chiralities through direct incubation or fractionation deployment methods. We found that the nanosensor can differentiate ER- from ER+ patient biopsies through a shift in its center wavelength upon sample addition. This was true regardless of which of the three SWCNT chiralities we observed. Receiver operating characteristic area under the curve analyses determined that the strongest classifier with an AUC of 0.94 was the (7,5) chirality after direct incubation and measurement, and without further processing. We anticipate that further testing and development of this nanosensor may push its utility toward field-deployable, rapid ER subtyping with potential for additional molecular marker profiling.

Identifiers

PMID38617252
PMCPMC11014485
OpenAlexW4393996811

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.