Evidence map›Paper›PMID 38798665›Full record

ArticlebioRxiv : the preprint server for biology2024

Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions.

Christopher M Polleys, Pramesh Singh, Hong-Thao Thieu, Elizabeth M Genega, Narges Jahanseir, Andrea L Zuckerman, Francisca Rius Díaz, Abani Patra, Afshin Beheshti, Irene Georgakoudi

Abstract 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.

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

10 authors.

Christopher M PolleysDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.
Pramesh SinghData Intensive Studies Center, Tufts University, Medford, MA 02155, USA.
Hong-Thao ThieuDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, Boston, MA 02111, USA.
Elizabeth M GenegaDepartment of Pathology and Laboratory Medicine, Tufts University School of Medicine, Tufts Medical Center, Boston, MA 02111, USA.
Narges JahanseirDepartment of Pathology and Laboratory Medicine, Tufts University School of Medicine, Tufts Medical Center, Boston, MA 02111, USA.
Andrea L ZuckermanDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, Boston, MA 02111, USA.
Francisca Rius DíazDepartment of Preventive Medicine and Public Health, Faculty of Medicine, University of Málaga, 32 Louis Pasteur Boulevard, 29071 Málaga, Spain.
Abani PatraData Intensive Studies Center, Tufts University, Medford, MA 02155, USA.
Afshin BeheshtiBlue Marble Space Institute of Science, Seattle, WA, 98104 USA.
Irene GeorgakoudiDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.

Funding

Probe-based two photon microscopy for functional, label-free early cancer diagnosisR01EB030061 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI BEN-YAKAR, ADELA, GEORGAKOUDI, IRENE · 2020 to 2023
$3.2M
Acquisition of Leica confocal/multiphoton microscopeS10OD021624 · OD · TUFTS UNIVERSITY MEDFORD · PI GEORGAKOUDI, IRENE · 2016 to 2016
$600k
Label-free, high resolution, functional, two-photon imaging for non-invasive early cancer detectionR03CA235053 · NCI · TUFTS UNIVERSITY MEDFORD · PI GEORGAKOUDI, IRENE · 2019 to 2020
$150k
NCI NIH HHS R03 CA235053NIBIB NIH HHS R01 EB030061NIH HHS S10 OD021624
6 · The paper itself

Abstract

Purpose: Two-photon microscopy (2PM) is an emerging clinical imaging modality with the potential to non-invasively assess tissue metabolism and morphology in high-resolution. This study aimed to assess the translational potential of 2PM for improved detection of high-grade cervical precancerous lesions. Experimental Design: 2P images attributed to reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavoproteins (FP) were acquired from the full epithelial thickness of freshly excised human cervical tissue biopsies (N = 62). Fifteen biopsies harbored high-grade squamous intraepithelial lesions (HSILs), 14 biopsies harbored low-grade SILs (LSILs), and 33 biopsies were benign. Quadratic discriminant analysis (QDA) leveraged morphological and metabolic functional metrics extracted from these images to predict the presence of HSILs. We performed gene set enrichment analysis (GSEA) using datasets available on the Gene Expression Omnibus (GEO) to validate the presence of metabolic reprogramming in HSILs. Results: Integrating metabolic and morphological 2P-derived metrics from finely sampled, full-thickness epithelia achieved a high 90.8 ± 6.1% sensitivity and 72.3 ± 11.3% specificity of HSIL detection. Notably, sensitivity (91.4 ± 12.0%) and specificity (77.5 ± 12.6%) were maintained when utilizing metrics from only two images at 12- and 72-μm from the tissue surface. Upregulation of glycolysis, fatty acid metabolism, and oxidative phosphorylation in HSIL tissues validated the metabolic reprogramming captured by 2P biomarkers. Conclusion: Label-free 2P images from as few as two epithelial depths enable rapid and robust HSIL detection through the quantitative characterization of metabolic and morphological reprogramming, underscoring the potential of this tool for clinical evaluation of cervical precancers.

Identifiers

PMID38798665
PMCPMC11118292

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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.