Evidence map›Paper›PMID 30550805›Full record

ArticleNanomedicine : nanotechnology, biology, and medicine2019

Label-free characterization of exosome via surface enhanced Raman spectroscopy for the early detection of pancreatic cancer.

Joseph Carmicheal, Chihiro Hayashi, Xi Huang, Lei Liu, Yao Lu, Alexey Krasnoslobodtsev, Alexander Lushnikov, Prakash G Kshirsagar, Asish Patel, Maneesh Jain and 4 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nanomedicine : nanotechnology, biology, and medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
5.7field-weighted citation impact, top 3% 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

55 citing papers in PubMed, 148 citations in OpenAlex.

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  8. Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
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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

14 authors at 2 institutions in 1 country.

Joseph CarmichealDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA.
Chihiro HayashiDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA.
Xi HuangDepartment of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA.
Lei LiuDepartment of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA.
Yao LuDepartment of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA.
Alexey KrasnoslobodtsevDepartment of Physics University of Nebraska at Omaha 6001 Dodge Street, Omaha, NE, USA; Nanoimaging Core Facility, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE, USA.
Alexander LushnikovNanoimaging Core Facility, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE, USA.
Prakash G KshirsagarDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA.
Asish PatelDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA.
Maneesh JainDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA.
Yuri L LyubchenkoNanoimaging Core Facility, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE, USA.
Yongfeng LuDepartment of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA. Electronic address: ylu2@unl.edu.
Surinder K BatraDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA. Electronic address: sbatra@unmc.edu.
Sukhwinder KaurDepartment of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA. Electronic address: skaur@unmc.edu.
University of Nebraska Medical Center · USUniversity of Nebraska–Lincoln · US

Funding

Project 9 - Renal Drug Targeting for the Treatment of Lupus NephritisP20GM103480 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI BRONICH, TATIANA K · 2012 to 2017
$13.3M
Pancreatic Cancer Detection ConsortiumU01CA210240 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI Michael A. Hollingsworth · 2017 to 2026
$12.9M
Validation of biomarkers for risk prediction and early diagnosis of Pancreatic AdenocarcinomaU01CA200466 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Surinder K. Batra, Randall Brand · 2016 to 2026
$11.3M
Nebraska Center for Nanomedicine- Pilot ProjectsP30GM127200 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI BRONICH, TATIANA K · 2018 to 2022
$5.7M
Seromic Mucin Signature for the Early Diagnosis of Pancreatic CancerR44CA224619 · NCI · SANGUINE DIAGNOSTICS AND THERAPEUTICS · PI JAIN, MANEESH, SOUCHEK, JOSHUA JAMES · 2018 to 2019
$1.5M
Ultrasensitive SERS Nano-Sensors for Pancreatic Cancer Diagnosis and PrognosisR41CA213718 · NCI · SANGUINE DIAGNOSTICS AND THERAPEUTICS · PI JUNKER, WADE M, KAUR, SUKHWINDER · 2016 to 2016
$300k
NCI NIH HHS R41 CA213718NCI NIH HHS R44 CA224619NCI NIH HHS U01 CA200466NCI NIH HHS U01 CA210240NIGMS NIH HHS P20 GM103480NIGMS NIH HHS P30 GM127200
6 · The paper itself

Abstract

Pancreatic cancer is a highly lethal malignancy. Lack of early diagnostic markers makes timely detection of pancreatic cancer a highly challenging endeavor. Exosomes have emerged as information-rich cancer specific biomarkers. However, characterization of tumor-specific exosomes has been challenging. This study investigated the proof of principle that exosomes could be used for the detection of pancreatic cancer. Label-free analysis of exosomes purified from normal and pancreatic cancer cell lines was performed using surface enhanced Raman Spectroscopy (SERS) and principal component differential function analysis (PC-DFA), to identify tumor-specific spectral signatures. This method differentiated exosomes originating from pancreatic cancer or normal pancreatic epithelial cell lines with 90% accuracy. The cell line trained PC-DFA algorithm was next applied to SERS spectra of serum-purified exosomes. This method exhibited up to 87% and 90% predictive accuracy for HC and EPC individual samples, respectively. Overall, our study identified utility of SERS spectral signature for deciphering exosomal surface signature.

Indexed as

AlgorithmsBiomarkers, TumorEarly Detection of CancerExosomesHumansMicroscopy, Electron, TransmissionPancreatic NeoplasmsPrincipal Component AnalysisSpectrum Analysis, RamanBiomarkers, TumorExosomeLabel-freeLiquid biopsyPancreatic cancerSurface enhanced Raman spectroscopy

Identifiers

PMID30550805
PMCPMC6532067
OpenAlexW2904840918

What OpenQuestion holds

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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.