2021
DOI: 10.1158/1541-7786.mcr-21-0383
|View full text |Cite
|
Sign up to set email alerts
|

Platelet-Coated Circulating Tumor Cells Are a Predictive Biomarker in Patients with Metastatic Castrate-Resistant Prostate Cancer

Abstract: Metastatic castration-resistant prostate cancer (mCRPC) includes a subset of patients with particularly unfavorable prognosis characterized by combined defects in at least two of three tumor suppressor genes: PTEN, RB1, and TP53 as aggressive variant prostate cancer molecular signature (AVPC-MS). We aimed to identify circulating tumor cells (CTC) signatures that could inform treatment decisions of patients with mCRPC with cabazitaxel–carboplatin combination therapy versus cabazitaxel alone. Liquid biopsy sampl… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
33
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6

Relationship

1
5

Authors

Journals

citations
Cited by 31 publications
(39 citation statements)
references
References 33 publications
0
33
0
Order By: Relevance
“…For HDSCA analysis, each test consisted of two slides generated from the PB sample for an average of 0.74 mL blood analyzed. Slides were processed at room temperature using the IntelliPATH FLX™ autostainer (Biocare Medical LLC, Irvine, CA, USA) as previously described [12]. Briefly, samples were stained with 2.5 ug/mL of a mouse IgG1 antihuman CD31:Alexa Fluor ® 647 mAb (clone: WM59, MCA1738A647, BioRad, Hercules, CA, USA) and 100 ug/mL of a goat anti-mouse IgG monoclonal Fab fragments (115-007-003, Jackson ImmunoResearch, West Grove, PA, USA), permeabilized using 100% cold methanol, followed by an antibody cocktail consisting of mouse IgG1/Ig2a anti-human cytokeratins (CKs) 1, 4, 5, 6, 8, 10, 13, 18, and 19 (clones: C-11, PCK-26, CY-90, KS-1A3, M20, A53-B/A2, C2562, Sigma, St. Louis, MO, USA), mouse IgG1 anti-human CK 19 (clone: RCK108, GA61561-2, Dako, Carpinteria, CA, USA), mouse anti-human CD45:Alexa Fluor ® 647 (clone: F10-89-4, MCA87A647, AbD Serotec, Raleigh, NC, USA), and rabbit IgG antihuman vimentin (Vim) (clone: D21H3, 9854BC, Cell Signaling, Danvers, MA, USA).…”
Section: Blood Sample Staining and Imagingmentioning
confidence: 99%
See 4 more Smart Citations
“…For HDSCA analysis, each test consisted of two slides generated from the PB sample for an average of 0.74 mL blood analyzed. Slides were processed at room temperature using the IntelliPATH FLX™ autostainer (Biocare Medical LLC, Irvine, CA, USA) as previously described [12]. Briefly, samples were stained with 2.5 ug/mL of a mouse IgG1 antihuman CD31:Alexa Fluor ® 647 mAb (clone: WM59, MCA1738A647, BioRad, Hercules, CA, USA) and 100 ug/mL of a goat anti-mouse IgG monoclonal Fab fragments (115-007-003, Jackson ImmunoResearch, West Grove, PA, USA), permeabilized using 100% cold methanol, followed by an antibody cocktail consisting of mouse IgG1/Ig2a anti-human cytokeratins (CKs) 1, 4, 5, 6, 8, 10, 13, 18, and 19 (clones: C-11, PCK-26, CY-90, KS-1A3, M20, A53-B/A2, C2562, Sigma, St. Louis, MO, USA), mouse IgG1 anti-human CK 19 (clone: RCK108, GA61561-2, Dako, Carpinteria, CA, USA), mouse anti-human CD45:Alexa Fluor ® 647 (clone: F10-89-4, MCA87A647, AbD Serotec, Raleigh, NC, USA), and rabbit IgG antihuman vimentin (Vim) (clone: D21H3, 9854BC, Cell Signaling, Danvers, MA, USA).…”
Section: Blood Sample Staining and Imagingmentioning
confidence: 99%
“…As previously reported [12], rare cell candidates were detected using a custom computational methodology termed OCULAR (Outlier Clustering Unsupervised Learning Automated Report). Fluorescent images were used to segment each cell using the "EBImage" R package (EBImage_4.12.2) and extract 761 quantitative morphometric parameters based on the nuclear and cytoplasmic morphology and biomarker expression (CK, Vim, CD45/CD31) in a 4-channel immunofluorescence assay (DAPI, AlexaFluor ® 488, AlexaFluor ® 555, AlexaFluor ® 647).…”
Section: Rare Event Detection and Classificationmentioning
confidence: 99%
See 3 more Smart Citations