ArticleThe Journal of molecular diagnostics : JMD2016
Application of a Clinical Whole-Transcriptome Assay for Staging and Prognosis of Prostate Cancer Diagnosed in Needle Core Biopsy Specimens.
Article in The Journal of molecular diagnostics : JMD, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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.
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.
Who cites it
29 citing papers in PubMed.
- Gene expression profiles in benign prostate tissue reflect tumor proximity, grade, and molecular subtype.Journal of translational medicine · 2026Article
- From prostate specific antigen to genomic signatures: Advances in biomarkers for prostate cancer diagnosis and prognosis.Translational oncology · 2026Review
- Genomic Signatures Correlating With Adverse Pathologic Features in Men Eligible for Active Surveillance.The Prostate · 2025Article
- A Perspective on Artificial Intelligence for Molecular Pathologists.The Journal of molecular diagnostics : JMD · 2025Review
- CTHRC1 expresses in cancer-associated fibroblasts and is associated with resistance to anti-androgen therapy in prostate cancer.Genes & genomics · 2025Article
- TAM Plasticity under androgen deprivation therapy and PARP inhibition in prostate cancer: a multi-omics perspective.Frontiers in immunology · 2025Review
- Genomics in active surveillance and post-prostatectomy patients: A review of when and how to use effectively.Current urology reports · 2024Review
- LINCATRA: Two-cycle method to amplify RNA for transcriptome analysis from formalin-fixed paraffin-embedded tissue.Heliyon · 2024Article
- Proteomic Analysis of Prostate Cancer FFPE Samples Reveals Markers of Disease Progression and Aggressiveness.Cancers · 2022Article
- Intraductal Carcinoma of the Prostate as a Cause of Prostate Cancer Metastasis: A Molecular Portrait.Cancers · 2022Review
- Prognostic Genomic Tissue-Based Biomarkers in the Treatment of Localized Prostate Cancer.Journal of personalized medicine · 2022Review
- Tissue-Based Biomarkers for the Risk Stratification of Men With Clinically Localized Prostate Cancer.Frontiers in oncology · 2021Review
- Commercialized Blood-, Urinary- and Tissue-Based Biomarker Tests for Prostate Cancer Diagnosis and Prognosis.Cancers · 2020Review
- Performance of clinicopathologic models in men with high risk localized prostate cancer: impact of a 22-gene genomic classifier.Prostate cancer and prostatic diseases · 2020Article
- Decipher identifies men with otherwise clinically favorable-intermediate risk disease who may not be good candidates for active surveillance.Prostate cancer and prostatic diseases · 2020Article
- Trends in the characteristics of human functional genomic data on the gene expression omnibus, 2001-2017.Laboratory investigation; a journal of technical methods and pathology · 2019Article
- Obtaining high quality transcriptome data from formalin-fixed, paraffin-embedded diagnostic prostate tumor specimens.Laboratory investigation; a journal of technical methods and pathology · 2018Article
- Robust transcriptional signatures for low-input RNA samples based on relative expression orderings.BMC genomics · 2017Article
- Biomarkers for Prostate Biopsy and Risk Stratification of Newly Diagnosed Prostate Cancer Patients.Urology practice · 2017Article
- Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer.Prostate cancer and prostatic diseases · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed, paraffin-embedded biopsy specimens has many unique challenges. Herein, we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers in diagnostic prostate needle core biopsy specimens. One-hundred fifty-eight samples from diagnostic needle core biopsy specimens (BX) and radical prostatectomies (RPs) were collected from 33 patients at three hospitals; each patient provided up to six tumor and benign samples. Genome-wide transcriptomic profiles were generated using Affymetrix Human Exon arrays for comparison of gene expression alterations and prognostic signatures between the BX and RP samples. A sufficient amount of RNA (>100 ng) was obtained from all RP specimens (n = 77) and from 72 of 81 of BX specimens. Of transcriptomic features detected in RP, 95% were detectable in BX tissues and demonstrated a high correlation (r = 0.96). Likewise, an expression signature pattern validated on RPs (Decipher prognostic test) showed correlation between BX and RP (r = 0.70). Of matched BX and RP pairs, 25% showed discordant molecular subtypes. Genome-wide exon arrays yielded data of comparable quality from biopsy and RP tissues. The high concordance of tumor-associated gene expression changes between BX and RP samples provides evidence for the adequate performance of the assay platform with samples from prostate needle biopsy specimens with limited tumor volume.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.