Evidence map›Paper›PMID 33335027›Full record

ArticleJournal for immunotherapy of cancer2020

Antibody profiling of patients with prostate cancer reveals differences in antibody signatures among disease stages.

Hemanth K Potluri, Tun Lee Ng, Michael A Newton, Jin Zhang, Christopher A Maher, Peter S Nelson, Douglas G McNeel

Open access · goldAbstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
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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

7 authors at 3 institutions in 1 country.

Hemanth K PotluriMedicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Tun Lee NgBiostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Michael A NewtonBiostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Jin ZhangMedicine, Washington University in Saint Louis, Saint Louis, Missouri, USA.
Christopher A MaherMedicine, Washington University in Saint Louis, Saint Louis, Missouri, USA.
Peter S NelsonHuman Biology Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Douglas G McNeelMedicine, University of Wisconsin-Madison, Madison, Wisconsin, USA dm3@medicine.wisc.edu.ORCID 0000-0003-1471-6723
University of Wisconsin–Madison · USWashington University in St. Louis · USFred Hutch Cancer Center · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Christian Capitini · 1985 to 2026
$142.6M
TRANSCRIPTOME AND PROTEOME STRATIFICATION OF PROSTATE ADENOCARCINOMA PHENOTYPESP50CA097186 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETER S NELSON · 2002 to 2026
$58.1M
Radionuclide Production and Radiochemistry Core Description CoreP01CA250972 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BEDNARZ, BRYAN PATRICK · 2020 to 2024
$12.5M
INTEGRATED TRAINING FOR PHYSICIAN-SCIENTISTST32GM008692 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BURKARD, MARK E · 1998 to 2020
$10.3M
NRSA Training CoreTL1TR002375 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI Vivek Prabhakaran · 2017 to 2026
$8.4M
Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
Effective Anti-Tumor Vaccination - Targeting Checkpoint Regulation at the Time of T-cell ActivationR01CA219154 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI MCNEEL, DOUGLAS G. · 2017 to 2021
$1.7M
NCATS NIH HHS TL1 TR002375NCI NIH HHS P01 CA250972NCI NIH HHS P30 CA014520NCI NIH HHS P50 CA097186NCI NIH HHS R01 CA219154NIGMS NIH HHS T32 GM008692NIGMS NIH HHS T32 GM140935
6 · The paper itself

Abstract

backgroundPrevious studies of prostate cancer autoantibodies have largely focused on diagnostic applications. So far, there have been no reports attempting to more comprehensively profile the landscape of prostate cancer-associated antibodies. Specifically, it is unknown whether the quantity of antibodies or the types of proteins recognized change with disease progression.

methodsA peptide microarray spanning the amino acid sequences of the gene products of 1611 prostate cancer-associated genes was synthesized. Serum samples from healthy male volunteers (n=15) and patients with prostate cancer (n=85) were used to probe the array. These samples included patients with various clinical stages of disease: newly diagnosed localized prostate cancer (n=15), castration-sensitive non-metastatic prostate cancer (nmCSPC, n=40), castration-resistant non-metastatic prostate cancer (n=15) and castration-resistant metastatic disease (n=15). The patients with nmCSPC received treatment with either standard androgen deprivation therapy (ADT) or an antitumor DNA vaccine encoding prostatic acid phosphatase. Serial sera samples from these individuals were also used to probe the array, to secondarily determine whether this approach could be used to detect treatment-related changes.

resultsWe demonstrated that this peptide array yielded highly reproducible measurements of serum IgG levels. We found that the overall number of antibody responses did not increase with disease burden. However, the composition of recognized proteins shifted with clinical stage of disease. Our analysis revealed that the largest difference was between patients with castration-sensitive and castration-resistant disease. Patients with castration-resistant disease recognized more proteins associated with nucleic acid binding and gene regulation compared with men in other groups. Our longitudinal data showed that treatments can elicit antibodies detectable by this array, and notably vaccine-treated patients developed increased responses to more proteins over the course of treatment than did ADT-treated patients.

conclusionsThis study represents the largest survey of prostate cancer-associated antibodies to date. We have been able to characterize the classes of proteins recognized by patients and determine how they change with disease burden. Our findings further demonstrate the potential of this platform for measuring antigen spread and studying responses to immunomodulatory therapies.

Indexed as

AntibodiesDisease ProgressionHumansMaleNeoplasm StagingProstatic NeoplasmsAntibodiesantibodiesantigensneoplasmprostatic neoplasmsvaccination

Identifiers

PMID33335027
PMCPMC7745697
OpenAlexW3111700740

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.