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  • Open Access

    ARTICLE

    Role of PTX3 and complement modulation in the tumor microenvironment

    GIUSEPPE STEFANO NETTI1,*, FEDERICA SPADACCINO1, VALERIA CATALANO1, GIUSEPPE CASTELLANO2, GIOVANNI STALLONE3, ELENA RANIERI1

    BIOCELL, Vol.46, No.10, pp. 2235-2239, 2022, DOI:10.32604/biocell.2022.020209

    Abstract Pentraxin-3 (PTX3), the prototype of long pentraxins, seems to influence complement system (CS) modulation. PTX3 and CS sustain carcinogenesis, enriching tumor microenvironment (TME) with pro-inflammatory molecules promoting angiogenesis in prostate cancer (PC) and renal cell carcinoma (RCC). Furthermore, cancer cells overexpress complement regulatory proteins, such as CD46, CD55 and CD59, which negatively affect complement pathways for support cancer cells survival. This viewpoint aims to elucidate the ambivalent role of PTX3 and the CS in the context of tumor microenvironment (TME). More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Prostate Cancer Classification Model Using Biomedical Images

    Areej A. Malibari1, Reem Alshahrani2, Fahd N. Al-Wesabi3,*, Siwar Ben Haj Hassine3, Mimouna Abdullah Alkhonaini4, Anwer Mustafa Hilal5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3799-3813, 2022, DOI:10.32604/cmc.2022.026131

    Abstract Medical image processing becomes a hot research topic in healthcare sector for effective decision making and diagnoses of diseases. Magnetic resonance imaging (MRI) is a widely utilized tool for the classification and detection of prostate cancer. Since the manual screening process of prostate cancer is difficult, automated diagnostic methods become essential. This study develops a novel Deep Learning based Prostate Cancer Classification (DTL-PSCC) model using MRI images. The presented DTL-PSCC technique encompasses EfficientNet based feature extractor for the generation of a set of feature vectors. In addition, the fuzzy k-nearest neighbour (FKNN) model is utilized More >

  • Open Access

    ARTICLE

    KIFC1 overexpression promotes prostate cancer cell survival and proliferation in vitro by clustering of amplified centrosomes via interaction with Centrin 2

    ANZANA PARVIN1,3, BANG-HONG WEI1, SHUANG-LI HAO1, WAN-XI YANG1,*, FU-QING TAN1,2,*

    BIOCELL, Vol.45, No.5, pp. 1369-1391, 2021, DOI:10.32604/biocell.2021.016654

    Abstract Mitotic kinesin KIFC1 plays critical roles in mitosis by regulating the spindle length, pole formation, and known for clustering extra centrosomes in cancer cells. Centrosome clustering is associated with the survival of cancer cells, but this phenomenon remains obscure in prostate cancer (PCa). The present study demonstrated that PCa cells showed centrosome amplification and clustering during interphase and mitosis, respectively. KIFC1 is highly expressed in PCa cells and tumor tissues of prostatic adenocarcinoma (PAC) patients. Up-regulation of KIFC1 facilitated the PCa cell survival in vitro by ensuring bipolar mitosis through clustering the multiple centrosomes, suggesting centrosome… More >

  • Open Access

    ARTICLE

    Machine Learning Techniques Applied to Electronic Healthcare Records to Predict Cancer Patient Survivability

    Ornela Bardhi1,2,*, Begonya Garcia Zapirain1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326

    Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178… More >

  • Open Access

    ARTICLE

    Comparison of Amino Acid Metabolisms in Normal Prostate (PNT-1A) and Cancer Cells (PC-3)

    Erkan Arslan1,*, Ismail Koyuncu2

    Oncologie, Vol.23, No.1, pp. 105-117, 2021, DOI:10.32604/Oncologie.2021.014764

    Abstract Prostate cancer is the second most common cancer in men. Prostate-specific antigen (PSA) levels, commonly used in the diagnosis of prostate cancer, are increased in both malign and benign conditions, such as prostate hyperplasia (BPH) and prostatitis. Thus, more specific markers are urgently needed to discriminate between prostate cancer and benign diseases of the prostate. The purpose of this study is to examine both the intracellular and extracellular free amino acid profiles of metastatic prostate cancer cells (PC-3), normal prostate cells (PNT-1A), and metabolic changes (e.g., pH). In this study, cancer and normal cells were… More >

  • Open Access

    ARTICLE

    Genetically Encoded FRET Biosensor Detects the Enzymatic Activity of Prostate-Specific Antigen

    Hui Yao1, Liqun Wang3, Jia Guo1, Weimin Liu4, Jingjing Li1, Yingxiao Wang2, Linhong Deng1,*, Mingxing Ouyang1,2,3,*

    Molecular & Cellular Biomechanics, Vol.17, No.3, pp. 101-111, 2020, DOI:10.32604/mcb.2020.09595

    Abstract Prostate cancer is the most common cancer among men beyond 50 years old, and ranked the second in mortality. The level of Prostate-specific antigen (PSA) in serum has been a routine biomarker for clinical assessment of the cancer development, which is detected mostly by antibody-based immunoassays. The proteolytic activity of PSA also has important functions. Here a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) technology was developed to measure PSA activity. In vitro assay showed that the biosensor containing a substrate peptide ‘RLSSYYSGAG’ had 400% FRET change in response to 1 µg/ml… More >

  • Open Access

    ARTICLE

    Association of hypoxia-inducible factor-1α (HIF1α) 1772C/T gene polymorphism with susceptibility to renal cell carcinoma/prostate cancer

    HONGYAN LI1,#, CHUNLING LIAO2,#, WENJUAN WENG2, HONGZHEN ZHONG2, TIANBIAO ZHOU2,*

    BIOCELL, Vol.44, No.2, pp. 257-262, 2020, DOI:10.32604/biocell.2020.08826

    Abstract In this study, we used a meta-analysis method to evaluate the relationship between hypoxia-inducible factor-1α (HIF1α) 1772C/T gene polymorphism (rs 11549465) and renal cell carcinoma (RCC)/prostate cancer risk. We searched for relevant studies (before March 1, 2019) on Cochrane Library, Embase, and PubMed. Studies meeting the inclusion criteria were recruited into this meta-analysis. The outcome of dichotomous data was showed in the way of odds ratios (OR), and 95% confidence intervals (CI) were also counted. In this investigation, there was no association between HIF1α 1772C/T gene polymorphism and susceptibility to RCC in Caucasians, Asians as More >

  • Open Access

    ARTICLE

    SPAG9 promotes prostate cancer growth and metastasis

    Chunhua YANG1,2,3, Ye TIAN1,2,3

    BIOCELL, Vol.43, No.3, pp. 207-214, 2019, DOI:10.32604/biocell.2019.07258

    Abstract Sperm-associated antigen 9 (SPAG9) expression is increased in prostate tissues of prostate cancer patients. This experimental study aimed to investigate the role of SPAG9 in bone metastasis of prostate cancer. Immunohistochemical analysis showed that SPAG9 staining was positive in 81.67% of 240 cases of prostatic carcinoma but only in 6.67% of 120 cases of benign prostate hyperplasia. Strong PAG9 staining was positively correlated with Gleason score and bone metastasis in 240 prostate cancer patients (p < 0.05), but not with the age or serum prostatespecific antigen level (p > 0.05). PC-3 cells were transfected with shRNA… More >

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