Prostate Cancer Theranostics - An Overview

Abou, Diane S.; Benabdallah, Nadia; Jiang, Wangjie; Lu, Peng; Zhang, Hanwen; Villmer, Alexandria; Longtine, Mark S.; Thorek, Daniel L.J.

doi:10.3389/fonc.2020.00884

Cited by 19 publications

(8 citation statements)

References 90 publications

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“…It was estimated that almost 1.3 million new cases of PCa were diagnosed and that 359,000 associated deaths occurred worldwide in 2018 (Bray et al, 2018). Currently, the conventional treatment modalities for PCa include surgical resection, hormone therapy, radiotherapy, and chemotherapy (Abou et al, 2020). Moreover, the dichotomy of overtreatment and tumor progression of PCa poses a new challenge for modern medicine, owing to the substantial heterogeneity of PCa.…”

Section: Discussionmentioning

confidence: 99%

Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer

Hua

Chen

et al. 2020

Front. Genet.

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Prostate cancer (PCa) is a common lethal malignancy in men. RNA binding proteins (RBPs) have been proven to regulate the biological processes of various tumors, but their roles in PCa remain less defined. In the present study, we used bioinformatics analysis to identify RBP genes with prognostic and diagnostic values. A total of 59 differentially expressed RBPs in PCa were obtained, comprising 28 upregulated and 31 downregulated RBP genes, which may play important roles in PCa. Functional enrichment analyses showed that these RBPs were mainly involved in mRNA processing, RNA splicing, and regulation of RNA splicing. Additionally, we identified nine RBP genes (EXO1, PABPC1L, REXO2, MBNL2, MSI1, CTU1, MAEL, YBX2, and ESRP2) and their prognostic values by a protein-protein interaction network and Cox regression analyses. The expression of these nine RBPs was validated using immunohistochemical staining between the tumor and normal samples. Further, the associations between the expression of these nine RBPs and pathological T staging, Gleason score, and lymph node metastasis were evaluated. Moreover, these nine RBP genes showed good diagnostic values and could categorize the PCa patients into two clusters with different malignant phenotypes. Finally, we constructed a prognostic model based on these nine RBP genes and validated them using three external datasets. The model showed good efficiency in predicting patient survival and was independent of other clinical factors. Therefore, our model could be used as a supplement for clinical factors to predict patient prognosis and thereby improve patient survival.

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Section: Discussionmentioning

confidence: 99%

Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer

Hua

Chen

et al. 2020

Front. Genet.

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“…Unfortunately, long-term androgen deprivation can ultimately lead to castration-resistant PCa (CRPC), which favors metastasis and poor prognosis (45)(46)(47). Although much effort has been made to improve PCa treatment, it is still needed to identify more sensitive biomarkers to guide early diagnosis and treatment (37,48,49). Several studies have shown that lncRNA DRAIC is dysregulated in PCa LNCaP and C4-2B cells as well as in 7 PCa tumor biopsies by androgens in a dose and time-dependent manner (14)(15)(16)(17)(18).…”

Section: Prostate Cancermentioning

confidence: 99%

The emerging potentials of lncRNA DRAIC in human cancers

2022

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Long non-coding RNA (lncRNA) is a subtype of noncoding RNA that has more than 200 nucleotides. Numerous studies have confirmed that lncRNA is relevant during multiple biological processes through the regulation of various genes, thus affecting disease progression. The lncRNA DRAIC, a newly discovered lncRNA, has been found to be abnormally expressed in a variety of diseases, particularly cancer. Indeed, the dysregulation of DRAIC expression is closely related to clinicopathological features. It was also reported that DRAIC is key to biological functions such as cell proliferation, autophagy, migration, and invasion. Furthermore, DRAIC is of great clinical significance in human disease. In this review, we discuss the expression signature, clinical characteristics, biological functions, relevant mechanisms, and potential clinical applications of DRAIC in several human diseases.

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“…Radiopharmaceutical therapies (RPTs) with α-particle emitting isotopes are showing significant promise in multiple clinical and pre-clinical studies [1,2]. This cancer therapy approach sees the localized emission of cytotoxic, high linear energy transfer, helium nuclei at sites of disease.…”

Section: Introductionmentioning

confidence: 99%

A list-mode multi-energy window low-count SPECT reconstruction method for isotopes with multiple emission peaks

Rahman

et al. 2023

EJNMMI Phys

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Background Single-photon emission computed tomography (SPECT) provides a mechanism to perform absorbed-dose quantification tasks for $$\alpha$$ α -particle radiopharmaceutical therapies ($$\alpha$$ α -RPTs). However, quantitative SPECT for $$\alpha$$ α -RPT is challenging due to the low number of detected counts, the complex emission spectrum, and other image-degrading artifacts. Towards addressing these challenges, we propose a low-count quantitative SPECT reconstruction method for isotopes with multiple emission peaks. Methods Given the low-count setting, it is important that the reconstruction method extracts the maximal possible information from each detected photon. Processing data over multiple energy windows and in list-mode (LM) format provide mechanisms to achieve that objective. Towards this goal, we propose a list-mode multi energy window (LM-MEW) ordered-subsets expectation–maximization-based SPECT reconstruction method that uses data from multiple energy windows in LM format and include the energy attribute of each detected photon. For computational efficiency, we developed a multi-GPU-based implementation of this method. The method was evaluated using 2-D SPECT simulation studies in a single-scatter setting conducted in the context of imaging [$$^{223}$$ 223 Ra]RaCl$${_2}$$ 2 , an FDA-approved RPT for metastatic prostate cancer. Results The proposed method yielded improved performance on the task of estimating activity uptake within known regions of interest in comparison to approaches that use a single energy window or use binned data. The improved performance was observed in terms of both accuracy and precision and for different sizes of the region of interest. Conclusions Results of our studies show that the use of multiple energy windows and processing data in LM format with the proposed LM-MEW method led to improved quantification performance in low-count SPECT of isotopes with multiple emission peaks. These results motivate further development and validation of the LM-MEW method for such imaging applications, including for $$\alpha$$ α -RPT SPECT.

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Prostate Cancer Theranostics - An Overview

Cited by 19 publications

References 90 publications

Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer

Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer

The emerging potentials of lncRNA DRAIC in human cancers

A list-mode multi-energy window low-count SPECT reconstruction method for isotopes with multiple emission peaks

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