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Prognostic Genomic Tissue-Based Biomarkers in the Treatment of Localized Prostate Cancer

Ingrosso, Gianluca, Alì, Emanuele, Marani, Simona, Saldi, Simonetta, Bellavita, Rita, Aristei, Cynthia·2022·Journal of Personalized Medicine
DOI 10.3390/jpm12010065PMC PMC8781984
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Abstract

In localized prostate cancer clinicopathologic variables have been used to develop prognostic nomograms quantifying the probability of locally advanced disease, of pelvic lymph node and distant metastasis at diagnosis or the probability of recurrence after radical treatment of the primary tumor. These tools although essential in daily clinical practice for the management of such a heterogeneous disease, which can be cured with a wide spectrum of treatment strategies (i.e., active surveillance, RP and radiation therapy), do not allow the precise distinction of an indolent instead of an aggressive disease. In recent years, several prognostic biomarkers have been tested, combined with the currently available clinicopathologic prognostic tools, in order to improve the decision-making process. In the following article, we reviewed the literature of the last 10 years and gave an overview report on commercially available tissue-based biomarkers and more specifically on mRNA-based gene expression classifiers. To date, these genomic tests have been widely investigated, demonstrating rigorous quality criteria including reproducibility, linearity, analytical accuracy, precision, and a positive impact in the clinical decision-making process. Albeit data published in literature, the systematic use of these tests in prostate cancer is currently not recommended due to insufficient evidence.

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  • Prognostic classifiers are sometimes overinterpreted as treatment-directing tools, while predictive biomarkers with clear therapeutic implications remain underutilized.

    “Prognostic classifiers are sometimes overinterpreted as treatment-directing tools, while predictive biomarkers with clear therapeutic implications remain underutilized [4, 5].”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [4]

    The Conclusions (p. not provided) describe these classifiers as prognostic tools and caution that evidence is insufficient to recommend their systematic use in prostate cancer. That supports caution about using them to direct treatment, but the paper does not say they are sometimes overinterpreted or that predictive biomarkers with clear therapeutic implications are underutilized. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • Such disparities threaten to widen survival gaps precisely as biomarker-directed therapies become more central to standard care.

    “Such disparities threaten to widen survival gaps precisely as biomarker-directed therapies become more central to standard care [4, 22].”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [4]

    The Conclusions (page unavailable) note that many biomarker-validation results come from White Caucasian cohorts and suggest these tools may be incorporated into future treatment planning. They do not say that disparities threaten to widen survival gaps; they also state that systematic use of the tests is not currently recommended because evidence is insufficient, rather than describing biomarker-directed care as increasingly standard. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • In newly diagnosed localized disease, tissue-based genomic classifiers are generally used to refine baseline risk and guide decisions between active surveillance and definitive treatment.

    “In newly diagnosed localized disease, tissue-based genomic classifiers are generally used to refine baseline risk and guide decisions between active surveillance and definitive treatment [4–7].”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [4]

    The Conclusions say tissue-based genomic classifiers have been tested in newly diagnosed prostate cancer to refine risk stratification and guide management, including active surveillance decisions. But they also say routine use is not currently recommended because evidence is insufficient, so “generally used” overstates the paper’s position. No page numbers are provided in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Tissue-based genomic classifiers provide prognostic information regarding adverse pathology, biochemical recurrence, and metastatic risk but generally do not identify specific therapeutic targets.

    “These assays provide prognostic information regarding adverse pathology, biochemical recurrence, and metastatic risk but generally do not identify specific therapeutic targets.”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [4]

    The Data Synthesis sections on Oncotype (3.5–3.6; page unavailable) report prognostic associations with adverse pathology, biochemical recurrence, and metastasis, and the Conclusions describe these assays as prognostic tools. Our copy does not state that the classifiers generally fail to identify specific therapeutic targets, so that part of the claim is unsupported. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • A central limitation in current clinical practice is the misalignment between biomarker function and clinical decision context.

    “A central limitation in current clinical practice is the misalignment between biomarker function and clinical decision context.”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [4]

    The Conclusions describe these biomarkers as prognostic tools and say their specific clinical roles remain uncertain. They also say routine use is not recommended because evidence is insufficient. This supports a limitation in applying biomarkers to clinical decisions, but the paper does not identify a misalignment between biomarker function and decision context as a central limitation. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Ingrosso, G., Alì, E., Marani, S., Saldi, S., Bellavita, R., & Aristei, C.
Affiliations
  • Radiation Oncology Section, Department of Medicine and Surgery, Perugia General Hospital, University of Perugia, 06156 Perugia, Italy
  • Radiation Oncology Section, Perugia General Hospital, 06156 Perugia, Italy
ORCID
Venue
Journal of Personalized Medicine
Publisher
MDPI AG
Published
2022-01-07
Volume
12
Issue
1
Pages
65
ISSN
2075-4426
DOI
10.3390/jpm12010065
PMC
PMC8781984
Cited by
9
References
0
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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