Evidence map›Paper›PMID 29988526›Full record

ArticleBiological procedures online2018

Optimization of Immunofluorescent Detection of Bone Marrow Disseminated Tumor Cells.

Haley D Axelrod, Kenneth J Pienta, Kenneth C Valkenburg

Open access · goldAbstract read
In one paragraph

Article in Biological procedures online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.0field-weighted citation impact, top 20% 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

13 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Multiplex Immunofluorescence of Bone Marrow Core Biopsies: Visualizing the Bone Marrow Immune Contexture.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2020
    Article
  10. Article
  11. Article
  12. Article
  13. 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

3 authors at 1 institution in 1 country.

Haley D Axelrod1The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, 600 North Wolfe St., Marburg Building Room 121, Baltimore, MD 21287 USA.
Kenneth J Pienta1The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, 600 North Wolfe St., Marburg Building Room 121, Baltimore, MD 21287 USA.
Kenneth C Valkenburg1The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, 600 North Wolfe St., Marburg Building Room 121, Baltimore, MD 21287 USA.
Johns Hopkins University · US

Funding

Tumor microvesicle-mediated modulation of the bone microenvironmentP01CA093900 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PIENTA, KENNETH J. · 2004 to 2024
$29.6M
Training Program in Cellular and Molecular MedicineT32GM008752 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI RAO, RAJINI · 2000 to 2019
$11.7M
Targeting SDF1/CXCR4 signaling to mobilize and kill circulating and disseminated prostate tumor cellsF32CA206394 · NCI · JOHNS HOPKINS UNIVERSITY · PI VALKENBURG, KENNETH C · 2016 to 2017
$112k
NCI NIH HHS F32 CA206394NCI NIH HHS P01 CA093900NIGMS NIH HHS T32 GM008752
6 · The paper itself

Abstract

backgroundCancer metastasis is the primary cause of cancer-related deaths and remains incurable. Current clinical methods for predicting metastatic recurrence are not sensitive enough to detect individual cancer cells in the body; therefore, current efforts are directed toward liquid biopsy-based assays to capture circulating and disseminated tumor cells (CTCs and DTCs) in the blood and bone marrow, respectively. The most promising strategy is fluorescence-based immunostaining using cancer cell-specific markers. However, despite recent efforts to develop robust processing and staining platforms, results from these platforms have been discordant among groups, particularly for DTC detection. While the choice of cancer cell-specific markers is a large factor in this discordance, we have found that marker-independent factors causing false signal are just as critical to consider. Bone marrow is particularly challenging to analyze by immunostaining because endogenous immune cell properties and bone marrow matrix components typically generate false staining. For immunostaining of whole tumor tissue containing ample cancer cells, this background staining can be overcome. Application of fluorescent-based staining for rare cells, however, is easily jeopardized by immune cells and autofluorescence that lead to false signal.

resultsWe have specifically found two types of background staining in bone marrow samples: autofluorescence of the tissue and non-specific binding of secondary antibodies. We systematically optimized a basic immunofluorescence protocol to eliminate this background using cancer cells spiked into human bone marrow. This enhanced the specificity of automated scanning detection software. Our optimized protocol also outperformed a commercial rare cell detection protocol in detecting candidate DTCs from metastatic patient bone marrow.

conclusionsRobust optimization to increase the signal-to-noise ratio of immunofluorescent staining of bone marrow is required in order to achieve the necessary sensitivity and specificity for rare cell detection. Background immunofluorescent staining in bone marrow causes uncertainty and inconsistency among investigators, which can be overcome by systematically addressing each contributing source. Our optimized assay eliminates sources of background signal, and is adaptable to automated staining platforms for high throughput analysis.

Indexed as

BloodBone MarrowCancerCTCDetectionDTCImmunofluorescence

Identifiers

PMID29988526
PMCPMC6026516
OpenAlexW2805271503

What OpenQuestion 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 OpenQuestion graph.