&lt;p&gt;Research status and progress of the RNA or protein biomarkers for prostate cancer&lt;/p&gt;

Song, Chuyi; Chen, Huan; Song, Chunyu

doi:10.2147/ott.s194138

Cited by 6 publications

(5 citation statements)

References 87 publications

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“…Currently, none of the clinical parameters (i.e., PSA and its derivatives such as PHI), biomarkers (i.e., PCA3), or combinations of biomarkers or clinical parameters (i.e., PCA3 combined with TMPRSS2:ERG, microRNA signatures, metabolomic biomarkers) used in clinical practice or reported in publications was able to diagnose PCa or stratify cancer risk with > 90% sensitivity and specificity, and AUC over 0.9, as shown in several recent reviews [ 2 , 4 – 6 , 8 – 10 , 25 – 27 ]. Our 25-Gene Panel urine test was validated for accurate cancer diagnosis by two independent multi-center study cohorts as well as the large combination cohort with uniformly high diagnostic sensitivity and specificity above 90% and AUC exceeding 0.9.…”

Section: Discussionmentioning

confidence: 83%

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up

Johnson

Guo

Zhang³

et al. 2020

BMC Med

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Background Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. Methods Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. Results The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963–0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929–0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956–0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980–0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947–0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. Conclusions The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

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Section: Discussionmentioning

confidence: 83%

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up

Johnson

Guo

Zhang³

et al. 2020

BMC Med

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“…Furthermore, lncRNAs expression was inhibited by the use of antisense oligonucleotide (ASO) or small molecule inhibitors [76]. Among them, some are undergoing Phase III clinical trials in prostate cancer, so far; however, most are still in the period of basic research [77].…”

Section: Clinical Utility Of Ncrnasmentioning

confidence: 99%

Noncoding RNAs Act as Tumor-Derived Molecular Components in Inducing Premetastatic Niche Formation

Zhang

Qiao

Zhang

et al. 2019

BioMed Research International

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Cancer metastasis has been demonstrated as it is the culmination of a cascade of priming steps. Increasing evidence has shown that tumor-derived molecular components (TDMCs) are known as extra cellular vesicle and nonvesicle factors and serve as versatile intercellular communication vehicles which can mediate signaling in the tumor microenvironment while creating the premetastatic niche. Noncoding RNAs (ncRNAs) as one of the TDMCs have been proved in participating in the formation of the premetastatic niche. Understanding the premetastatic niche formation mechanisms through TDMCs, especially ncRNAs may open a new avenue for cancer metastasis therapeutic strategies. In this review, recent findings regarding ncRNAs function were summarized, and then the interaction with the premetastatic niche formation was studied, which highlight the potential of using ncRNAs for cancer diagnosis and therapeutic effect.

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“…Many studies indicate that changes in DNA methylation contribute to cancer development and regulation. Cancers characteristically display extensive hypomethylation of DNA repeats as well as frequent focal DNA hypermethylation 22 , 23 . Toth et al 24 attain good prognostic performance with a Random Forest algorithm, to discriminate patients according to eventual recurrence-free survival as an outcome, measured by PSA levels.…”

Section: Discussionmentioning

confidence: 99%

Accurate prognosis for localized prostate cancer through coherent voting networks with multi-omic and clinical data

Pellegrini

2023

Sci Rep

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Localized prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing stratifications of patients into risk classes remarkably challenging. In particular, it is important an early detection and discrimination of the indolent forms of the disease, from the aggressive ones, requiring post-surgery closer surveillance and timely treatment decisions. This work extends a recently developed supervised machine learning (ML) technique, called coherent voting networks (CVN) by incorporating a novel model-selection technique to counter the danger of model overfitting. For the challenging problem of discriminating between indolent and aggressive types of localized prostate cancer, accurate prognostic prediction of post-surgery progression-free survival with a granularity within a year is attained, improving accuracy with respect to the current state of the art. The development of novel ML techniques tailored to the problem of combining multi-omics and clinical prognostic biomarkers is a promising new line of attack for sharpening the capability to diversify and personalize cancer patient treatments. The proposed approach allows a finer post-surgery stratification of patients within the clinical high-risk category, with a potential impact on the surveillance regime and the timing of treatment decisions, complementing existing prognostic methods.

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<p>Research status and progress of the RNA or protein biomarkers for prostate cancer</p>

Cited by 6 publications

References 87 publications

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up

Noncoding RNAs Act as Tumor-Derived Molecular Components in Inducing Premetastatic Niche Formation

Accurate prognosis for localized prostate cancer through coherent voting networks with multi-omic and clinical data

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