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22 pages, 6276 KiB  
Article
CHD1L Regulates Cell Survival in Breast Cancer and Its Inhibition by OTI-611 Impedes the DNA Damage Response and Induces PARthanatos
by Rita Sala, Hector Esquer, Timothy Kellett, Jeffrey T. Kearns, Paul Awolade, Qiong Zhou and Daniel V. LaBarbera
Int. J. Mol. Sci. 2024, 25(16), 8590; https://doi.org/10.3390/ijms25168590 - 6 Aug 2024
Viewed by 302
Abstract
The Chromodomain helicase DNA-binding protein 1-like (CHD1L) is a nucleosome remodeling enzyme, which plays a key role in chromatin relaxation during the DNA damage response. Genome editing has shown that deletion of CHD1L sensitizes cells to PARPi, but the effect of its pharmacological [...] Read more.
The Chromodomain helicase DNA-binding protein 1-like (CHD1L) is a nucleosome remodeling enzyme, which plays a key role in chromatin relaxation during the DNA damage response. Genome editing has shown that deletion of CHD1L sensitizes cells to PARPi, but the effect of its pharmacological inhibition has not been defined. Triple-negative breast cancer SUM149PT, HCC1937, and MDA-MB-231 cells were used to assess the mechanism of action of the CHD1Li OTI-611. Cytotoxicity as a single agent or in combination with standard-of-care treatments was assessed in tumor organoids. Immunofluorescence was used to assess the translocation of PAR and AIF to the cytoplasm or the nucleus and to study markers of DNA damage or apoptosis. Trapping of PARP1/2 or CHD1L onto chromatin was also assessed by in situ subcellular fractionation and immunofluorescence and validated by Western blot. We show that the inhibition of CHD1L’s ATPase activity by OTI-611 is cytotoxic to triple-negative breast cancer tumor organoids and synergizes with PARPi and chemotherapy independently of the BRCA mutation status. The inhibition of the remodeling function blocks the phosphorylation of H2AX, traps CHD1L on chromatin, and leaves PAR chains on PARP1/2 open for hydrolysis. PAR hydrolysis traps PARP1/2 at DNA damage sites and mediates PAR translocation to the cytoplasm, release of AIF from the mitochondria, and induction of PARthanatos. The targeted inhibition of CHD1L’s oncogenic function by OTI-611 signifies an innovative therapeutic strategy for breast cancer and other cancers. This approach capitalizes on CHD1L-mediated DNA repair and cell survival vulnerabilities, thereby creating synergy with standard-of-care therapies Full article
(This article belongs to the Special Issue Chromatin Remodelers as Players and Drivers in Pathological States)
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Figure 1
<p>CHD1Li synergizes with TNBC therapies in SUM149PT organoids. (<b>A</b>) Bliss synergy 3D plots showing synergy scores for each dose combination of OTI-611 (1.7–1.9 µM) and PARPi and SOC chemotherapy. (<b>B</b>) Dose–response matrices representing the percentage of cell death caused by OTI-611, PARPi and SOC therapy, and their combinations. (<b>C</b>) Dose–response curves showing OTI-611’s synergistic effect when combined with PARPi and SOC chemotherapy as measured by IC<sub>50</sub> values. SUM149PT organoids were treated with drug combinations for 72 h. Bliss synergy score values were calculated using the SynergyFinder R package version 3.12.0. To evaluate synergy, OTI-611 was treated at sub-lethal doses. Synergy score values above 10 are considered a synergistic interaction between drugs. Data are presented as the mean of two independent experiments ± S.E.M. See also <a href="#app1-ijms-25-08590" class="html-app">Figures S2 and S3</a>.</p>
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<p>CHD1Li synergizes with TNBC therapies in MDA-MB-231 and HCC1937 tumor organoids. (<b>A</b>) Dose–response curves showing OTI-611’s synergistic effect when combined with PARPi and SOC chemotherapy as measured by IC<sub>50</sub> values in MDA-MB-231 tumor organoids treated for 72 h. (<b>B</b>) Dose–response curves showing OTI-611’s synergistic effect when combined with PARPi and SOC chemotherapy as measured by IC<sub>50</sub> values in HCC1937 tumor organoids treated for 72 h. Data are presented as the mean of two independent experiments ± S.E.M. See also <a href="#app1-ijms-25-08590" class="html-app">Figure S2</a> for Bliss synergy scores quantification.</p>
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<p>Inhibition of CHD1L enhances chemotherapy and PARPi-mediated DNA damage. (<b>A</b>) Bliss synergy 3D plots showing synergy scores for each dose combination of OTI-611 (1.5–2 µM) and PARPi or SOC chemotherapy. (<b>B</b>) Dose–response matrices representing the percentage of DNA damage measured by γ-H2AX immunofluorescence, for doses of OTI-611, PARPi and SOC chemotherapy, and their combinations. OTI-611 was treated at sub-lethal doses to evaluate synergy. Bliss synergy scores were generated using the SynergyFinder R package. A synergistic drug interaction is considered when values are above 10. Data are presented as the mean of two independent experiments ± S.E.M. (<b>C</b>) Representative images of γ-H2AX immunofluorescence in SUM149PT cells treated for 4 h with OTI-611, PARPi and SOC chemotherapy, and their combinations. Scale bar = 100 µm. (<b>D</b>) Quantification of γ-H2AX foci number in SUM149PT. Data were normalized to DMSO-treated cells and presented as the mean of two independent experiments ± SEM, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Inhibition of CHD1L enhances chemotherapy and PARPi-mediated cell cycle arrest. (<b>A</b>) Representative flow cytometry profiles of SUM149PT cells treated for 24 h with OTI-611, PARPi and SOC chemotherapy, and their combinations. After treatment, cells were fixed and stained with DAPI. The distribution of cells in G1, S, or G2/M is indicated. (<b>B</b>) Quantification of the percentage of cells in each phase of the cell cycle (G1, S, or G2/M). The experiment was performed in two independent experimental replicates and data were shown as mean ± S.E.M, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Inhibition of CHD1L traps PARP1, PARP2, and CHD1L at DNA damage sites. (<b>A</b>) Trapping profiles of PARP1, PARP2, and CHD1L measured after dose-response treatment with olaparib. (<b>B</b>) Trapping profiles of PARP1, PARP2, and CHD1L measured after dose-response treatment with OTI-611. (<b>C</b>) Trapping profiles of PARP1, PARP2, and CHD1L measured after dose-response treatment with AZD5305. (<b>D</b>) Trapping profiles of PARP1, PARP2, and CHD1L measured after dose-response treatment with doxorubicin. Doxorubicin was used as a negative control of trapping. (<b>E</b>) Trapping profiles of PARP1, PARP2, and CHD1L measured after dose-response treatment with olaparib combined with OTI-611 or vice versa. For all the conditions, SUM149PT cells were treated with the drug of interest in combination and 0.001% MMS for 4 h. All data were normalized to MMS-treated cells and expressed as the mean of two independent experiments ± S.E.M.</p>
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<p>OTI-611 selectively inhibits CHD1L ATPase and nucleosome remodeling activities. (<b>A</b>) Nucleosome remodeling assay performed with 20 nM FRET-nucleosomes, 20 nM fl-CHD1L, 80 nM PARP1 (pre-incubated with NAD<sup>+</sup>), and 2 mM ATP. Reactions without ATP, fl-CHD1L, orPARP1 were added as controls. (<b>B</b>) Nucleosome remodeling assay performed with 20 nM FRET-nucleosomes, 20 nM fl-CHD1L (pre-incubated with 10 µM of OTI-611), 80 nM PARP1 (pre-incubated with NAD<sup>+</sup>), and 2 mM ATP. (<b>C</b>) Nucleosome remodeling assay performed with 20 nM FRET-nucleosome, 10 nM SMARCA5 (pre-incubated with 10 µM of OTI-611), and 1 mM ATP. Data are presented as the ratio of Cy3/Cy5 ± S.D. of one technical replicate. The experiments were repeated twice.</p>
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<p>CHD1Li-mediated PAR translocation to the cytoplasm activates PARthanatos. (<b>A</b>) Intensity of cytoplasmic PAR in SUM149PT cells treated for 6 h with OTI-611, olaparib, AZD5305, or doxorubicin, and their combinations. PAR localization is measured as the sum intensity in the cytoplasm and normalized by the number of nuclei per field. (<b>B</b>) Intensity of nuclear PAR in SUM149PT cells treated for 4 h with OTI-611, olaparib, AZD5305, or doxorubicin, and their combinations. PAR mean intensity is normalized by the number of nuclei per field. Data expressed as the mean of three independent experiments ± S.E.M. (<b>C</b>) Representative images of PAR immunofluorescence showing changes in nuclear PAR and its translocation to the cytoplasm with OTI-611 treatment. Scale bar = 50 µm. (<b>D</b>) Intensity of cytoplasmic AIF in SUM149PT cells treated for 18 h with OTI-611, olaparib, AZD5305, or doxorubicin, and their combinations. (<b>E</b>) Intensity of nuclear AIF in SUM149PT cells treated for 18 h with OTI-611, olaparib, AZD5305, or doxorubicin, and their combinations. AIF mean intensity is normalized by the number of nuclei per field and expressed as the mean of two independent experiments ± S.E.M. (<b>F</b>) Representative images showing changes in cytoplasmic AIF and its translocation to the nucleus with OTI-611 treatment. Scale bar = 50 µm, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>CHD1L ATPase inhibition traps CHD1L at DNA damage sites and induces PARthanatos. (<b>A</b>) Under normal conditions, upon DNA damage, PARP1/2 detect SSB and DSB and recruit repair machinery to damage sites by auto-PARylating themselves and through PARylating other repair proteins, and histones. One of these proteins is CHD1L, which binds to the PAR chains by its macro domain releasing its autoinhibition. Once CHD1L is activated, it can bind the histone and relax the chromatin through its ATPase-driven chromatin remodeling activity, promoting DNA repair and cell survival. PARP1 is released from the DNA damage site and PAR is recycled through PARG-mediated hydrolysis. (<b>B</b>) When CHD1L ATPase is inhibited by OTI-611, CHD1L becomes trapped near DNA damage sites and unable to relax the chromatin. Moreover, unprotection of the PAR chains causes their PARG-mediated hydrolysis, trapping PARP1/2. This mechanism of PARP trapping does not cause DNA damage, unlike PARPi entrapment of PARP on relaxed chromatin, which undergoes DNA repair and subsequent replication fork collapse in HR-deficient tumor cells. Additionally, CHD1L inhibition by OTI-611 leaves PAR chains unprotected, allowing PARG to hydrolyze PAR and enable PAR fragment translocation to the cytoplasm. In the cytoplasm, AIF binds to PAR fragments in the mitochondria, causing its release and subsequent translocation to the nucleus. Once in the nucleus, AIF triggers large-scale DNA fragmentation and a form of non-apoptotic cell death known as PARthanatos.</p>
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36 pages, 2854 KiB  
Review
Synergistic Strategies for Castration-Resistant Prostate Cancer: Targeting AR-V7, Exploring Natural Compounds, and Optimizing FDA-Approved Therapies
by Muntajin Rahman, Khadija Akter, Kazi Rejvee Ahmed, Md. Maharub Hossain Fahim, Nahida Aktary, Moon Nyeo Park, Sang-Won Shin and Bonglee Kim
Cancers 2024, 16(16), 2777; https://doi.org/10.3390/cancers16162777 - 6 Aug 2024
Viewed by 403
Abstract
Castration-resistant prostate cancer (CRPC) remains a significant therapeutic challenge due to its resistance to standard androgen deprivation therapy (ADT). The emergence of androgen receptor splice variant 7 (AR-V7) has been implicated in CRPC progression, contributing to treatment resistance. Current treatments, including first-generation chemotherapy, [...] Read more.
Castration-resistant prostate cancer (CRPC) remains a significant therapeutic challenge due to its resistance to standard androgen deprivation therapy (ADT). The emergence of androgen receptor splice variant 7 (AR-V7) has been implicated in CRPC progression, contributing to treatment resistance. Current treatments, including first-generation chemotherapy, androgen receptor blockers, radiation therapy, immune therapy, and PARP inhibitors, often come with substantial side effects and limited efficacy. Natural compounds, particularly those derived from herbal medicine, have garnered increasing interest as adjunctive therapeutic agents against CRPC. This review explores the role of AR-V7 in CRPC and highlights the promising benefits of natural compounds as complementary treatments to conventional drugs in reducing CRPC and overcoming therapeutic resistance. We delve into the mechanisms of action underlying the anti-CRPC effects of natural compounds, showcasing their potential to enhance therapeutic outcomes while mitigating the side effects associated with conventional therapies. The exploration of natural compounds offers promising avenues for developing novel treatment strategies that enhance therapeutic outcomes and reduce the adverse effects of conventional CRPC therapies. These compounds provide a safer, more effective approach to managing CRPC, representing a significant advancement in improving patient care. Full article
(This article belongs to the Special Issue Natural Compounds in Cancers)
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<p>Structural and Functional Insights into the Androgen Receptor and Its Role in CRPC. The androgen receptor (AR) gene, located on the X chromosome at Xq11-12, encodes the AR-V7 protein, which includes four distinct domains: N-terminal domain (NTD), DNA-binding domain (DBD), hinge region, and ligand binding domains (LBD). Activation of the AR by androgens such as testosterone and dihydrotestosterone (DHT) initiates a cascade of events that promote prostate cancer cell proliferation. Aldo-keto reductase family 1 member C3 (AKR1C3) is overexpressed in castration-resistant prostate cancer (CRPC) and is crucial for the synthesis of DHT from weak androgens, contributing to the persistence of AR signaling in low-androgen environments. Furthermore, testosterone is converted to the more potent androgen DHT through the action of 5α reductase, further fueling the growth of CRPC cells despite androgen deprivation therapy.</p>
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<p>Overview of AR-V7 and AR splice variants. The androgen receptor (AR) gene, located on the X chromosome, comprises eight exons that encode four primary domains: The N-terminal domain (NTD), DNA-binding domain (DBD), hinge region (H), and ligand-binding domain (LBD). The AR gene can undergo alternative splicing, producing several splice variants, each with distinct structures and functions. In the full-length androgen receptor (AR-FL), exons 1–8 encode the complete set of domains. However, alternative splicing can involve cryptic exons (CE1-4) and exon 9, generating a unique sequence (U) not found in AR-FL. AR-V7, also known as AR3, is a significant splice variant that terminates at the end of exon 3, lacking the LBD, and includes 16 unique amino acids from cryptic exon 3 (CE3). This modification results in AR-V7’s constitutive activity, allowing it to activate AR signaling pathways without the need for androgen binding. Additionally, other constitutively active AR splice variants, such as ARv567es, AR-V3, and AR-V4, are described. Each variant arises from different exon combinations, producing unique open reading frames (ORFs) that encode their respective receptor proteins.</p>
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<p>Mechanism of action of first-generation chemotherapy (Docetaxel, cabazitaxel) in treating CRPC. Docetaxel and cabazitaxel, both taxane-based chemotherapeutic drugs, exert their anticancer effects primarily by targeting microtubules. These drugs bind to β-tubulin, stabilizing microtubules and preventing their proper assembly. This disruption inhibits the G2-M phase transition of the cell cycle, leading to cell cycle arrest and apoptosis. Additionally, taxanes inhibit androgen receptor (AR) transcriptional activity by blocking FOXO1-mediated AR function, which is crucial in treating castration-resistant prostate cancer (CRPC). By obstructing AR signaling, taxanes effectively disrupt the growth and survival mechanisms of CRPC cells. Taxanes also promote apoptosis through the activation of pro-apoptotic proteins such as BAK and BAX while inhibiting anti-apoptotic proteins like BCL-2 and BCL-XL. This dual action triggers the intrinsic apoptotic pathway, characterized by the release of cytochrome c from mitochondria, culminating in cell death. Overall, the combination of microtubule stabilization, inhibition of AR signaling, and promotion of apoptosis underscores the therapeutic efficacy of docetaxel and cabazitaxel in managing CRPC.</p>
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<p>Mechanism of action of androgen receptor blockers (Apalutamide, Darolutamide, and Enzalutamide) in treating CRPC. Enzalutamide, Apalutamide, and Darolutamide are androgen receptor (AR) antagonists that effectively inhibit the androgen signaling pathway, crucial for the progression of castration-resistant prostate cancer (CRPC). Enzalutamide binds to the AR, preventing testosterone from attaching to the receptor. This inhibition blocks the translocation of the AR into the cell nucleus, thereby preventing the activation of AR target genes that promote cancer cell growth. In addition to direct AR antagonism, Abiraterone acetate targets androgen synthesis. It inhibits the enzyme 17α-hydroxylase and C17,20-lyase, which are essential for androgen production, by blocking their activity on the CYP-17. This action significantly reduces the levels of testosterone and other androgens, preventing their binding to the AR. Apalutamide and Darolutamide function similarly to Enzalutamide by binding to the AR and preventing its activation by testosterone. This inhibition blocks AR-mediated transcriptional activity, thereby hindering the growth of CRPC cells. By disrupting the androgen signaling pathway through these different mechanisms, these treatments aim to reduce AR activity and slow the progression of CRPC.</p>
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<p>FDA-Approved Treatments for Castration-Resistant Prostate Cancer (CRPC). Radium-223 and Lutetium-177 are radiopharmaceuticals used in the treatment of CRPC. Radium-223 emits high-energy alpha particles, while Lutetium-177 emits beta particles. These particles directly damage the DNA of cancer cells, leading to cell death. Both treatments specifically target bone metastases, a common complication in CRPC, effectively reducing tumor burden. The precision of these therapies helps minimize damage to surrounding healthy tissues, providing a focused approach to treat metastatic bone lesions. Pembrolizumab, an immune checkpoint inhibitor, is a key immunotherapy approved for CRPC. It binds to PD-1 receptors on T cells, blocking the interaction between PD-1 on T cells and PD-L1 on tumor cells. This blockade lifts the immune suppression exerted by the tumor, thereby activating the immune system to recognize and attack cancer cells. The immune response is initiated by the detection of neoantigens presented on major histocompatibility complexes (MHC) by tumor cells. This mechanism enhances the body’s natural defense against cancer by overcoming one of the major immune evasion strategies employed by tumors.</p>
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<p>Mechanism of action of PARP inhibitors (Olaparib, Rucaparib, and Niraparib) in treating castration-resistant prostate cancer (CRPC). PARP inhibitors such as Olaparib, Rucaparib, and Niraparib block the PARP enzyme, which is crucial for repairing single-strand DNA breaks. Inhibition of PARP leads to the persistence of single-strand breaks, which during DNA replication, result in double-strand breaks. Cells with BRCA1 or BRCA2 mutations exhibit homologous recombination deficiency (HRD). These cells are unable to efficiently repair double-strand breaks through the homologous recombination pathway. The accumulation of unrepaired double-strand breaks in HRD cells triggers cell death, effectively targeting cancer cells harboring BRCA mutations. This targeted approach exploits the inherent weaknesses in the DNA repair mechanisms of CRPC cells, providing a potent and specific strategy to combat this challenging form of cancer.</p>
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16 pages, 5307 KiB  
Article
Genetic and Epigenetic Biomarkers Associated with Early Relapse in Pediatric Acute Lymphoblastic Leukemia: A Focused Bioinformatics Study on DNA-Repair Genes
by Walaa F. Albaqami, Ali A. Alshamrani, Ali A. Almubarak, Faris E. Alotaibi, Basil Jamal Alotaibi, Abdulrahman M. Alanazi, Moureq R. Alotaibi, Ali Alhoshani and Homood M. As Sobeai
Biomedicines 2024, 12(8), 1766; https://doi.org/10.3390/biomedicines12081766 - 5 Aug 2024
Viewed by 367
Abstract
Genomic instability is one of the main drivers of tumorigenesis and the development of hematological malignancies. Cancer cells can remedy chemotherapeutic-induced DNA damage by upregulating DNA-repair genes and ultimately inducing therapy resistance. Nevertheless, the association between the DNA-repair genes, drug resistance, and disease [...] Read more.
Genomic instability is one of the main drivers of tumorigenesis and the development of hematological malignancies. Cancer cells can remedy chemotherapeutic-induced DNA damage by upregulating DNA-repair genes and ultimately inducing therapy resistance. Nevertheless, the association between the DNA-repair genes, drug resistance, and disease relapse has not been well characterized in acute lymphoblastic leukemia (ALL). This study aimed to explore the role of the DNA-repair machinery and the molecular mechanisms by which it is regulated in early- and late-relapsing pediatric ALL patients. We performed secondary data analysis on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET)—ALL expansion phase II trial of 198 relapsed pediatric precursor B-cell ALL. Comprehensive genetic and epigenetic investigations of 147 DNA-repair genes were conducted in the study. Gene expression was assessed using Microarray and RNA-sequencing platforms. Genomic alternations, methylation status, and miRNA transcriptome were investigated for the candidate DNA-repair genes. We identified three DNA-repair genes, ALKBH3, NHEJ1, and PARP1, that were upregulated in early relapsers compared to late relapsers (p < 0.05). Such upregulation at diagnosis was significantly associated with disease-free survival and overall survival in precursor-B-ALL (p < 0.05). Moreover, PARP1 upregulation accompanied a significant downregulation of its targeting miRNA, miR-1301-3p (p = 0.0152), which was strongly linked with poorer disease-free and overall survivals. Upregulation of DNA-repair genes, PARP1 in particular, increases the likelihood of early relapse of precursor-B-ALL in children. The observation that PARP1 was upregulated in early relapsers relative to late relapsers might serve as a valid rationale for proposing alternative treatment approaches, such as using PARP inhibitors with chemotherapy. Full article
(This article belongs to the Section Molecular Genetics and Genetic Diseases)
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<p>Significantly upregulated DNA-repair genes in early-relapsing patients compared with late-relapsing patients. (<b>A</b>) 18 and 7 genes were found overexpressed in the early-relapse group relative to the late-relapse group using microarray and RNA seq, respectively. ALKBH3, NHEJ1, and PARP1 were found upregulated in the early-relapsing group (red) relative to the late-relapsing group (purple) in microarray (<b>B</b>) and RNA seq (<b>C</b>) datasets. Bold intermittent lines represent the mean values, while light intermittent lines represent 95% confidence interval values. Statistical analysis was computed using Student’s <span class="html-italic">t</span>-test.</p>
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<p>Free survival curves for low-expression (blue) and high-expression patients (red) based on the expression of <span class="html-italic">ALKBH3</span>, <span class="html-italic">NHEJ1</span>, <span class="html-italic">PARP1</span>, and the three candidate genes combined (microarray). The shaded area represents the 95% confidence interval (CI) for each curve. Hazard ratio (HR) and <span class="html-italic">p</span> value were calculated using the log–rank test.</p>
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<p>Free survival curves for low-expression (blue) and high-expression patients (red) based on the expression of <span class="html-italic">ALKBH3</span>, <span class="html-italic">NHEJ1</span>, <span class="html-italic">PARP1</span>, and the three candidate genes combined (RNA sequencing). The shaded area represents the 95% confidence interval (CI) for each curve. Hazard ratio (HR) and <span class="html-italic">p</span> value were calculated using a log–rank test.</p>
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<p>Survival curves for low-score patients (blue) and high-score patients (red) based on the expression of miR-1301-3p. (<b>A</b>) miR-1301-3p expression levels among early (red) and late relapsers (purple). Bold intermittent lines represent the mean values, while light intermittent lines represent 95% confidence interval values. Statistical analysis was computed using Student’s <span class="html-italic">t</span>-test. (<b>B</b>) validated binding sites between PARP1 and miR-1301-3p as identified by [<a href="#B43-biomedicines-12-01766" class="html-bibr">43</a>]. (<b>C</b>) The shaded areas represent the 95% confidence interval (CI) for each curve. Hazard ratio (HR) and <span class="html-italic">p</span>-value were calculated using a log–rank test.</p>
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17 pages, 8147 KiB  
Article
Niacinamide Antimicrobial Efficacy and Its Mode of Action via Microbial Cell Cycle Arrest
by Noa Ziklo, Maayan Bibi, Lior Sinai and Paul Salama
Microorganisms 2024, 12(8), 1581; https://doi.org/10.3390/microorganisms12081581 - 2 Aug 2024
Viewed by 325
Abstract
Niacinamide is a versatile compound widely used in the personal care industry for its ample skin benefits. As a precursor to nicotinamide adenine dinucleotide (NAD+), essential for ATP production and a substrate for poly-ADP-ribose polymerase-1 (PARP-1), studies have highlighted its roles in DNA [...] Read more.
Niacinamide is a versatile compound widely used in the personal care industry for its ample skin benefits. As a precursor to nicotinamide adenine dinucleotide (NAD+), essential for ATP production and a substrate for poly-ADP-ribose polymerase-1 (PARP-1), studies have highlighted its roles in DNA repair, cellular stress mechanisms, and anti-aging benefits. Niacinamide was also studied for its antimicrobial activity, particularly in the context of host-infection via host immune response, yet its direct antimicrobial activity and the mechanisms of action remain unclear. Its multifunctionality makes it an appealing bioactive molecule for skincare products as well as a potential preservative solution. This study explores niacinamide’s antimicrobial mode of action against four common cosmetic pathogens. Our findings indicate that niacinamide is causing microbial cell cycle arrest; while cells were found to increase their volume and length under treatment to prepare for cell division, complete separation into two daughter cells was prevented. Fluorescence microscopy revealed expanded chromatin, alongside a decreased RNA expression of the DNA-binding protein gene, dps. Finally, niacinamide was found to directly interact with DNA, hindering successful amplification. These unprecedented findings allowed us to add a newly rationalized preservative facete to the wide range of niacinamide multi-functionality. Full article
(This article belongs to the Special Issue Advantages and Disadvantages of Antimicrobials)
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<p><span class="html-italic">C. albicans</span> TEM image of control and niacinamide treated cells. (<b>A</b>–<b>C</b>) Control cells. (<b>D</b>–<b>F</b>) 5% Niacinamide treatment. N = nucleus, CM = cell membrane, CW = cell wall, V = vacuole, LD = lipid droplet, m = mitochondrion, Cy = cytoplasm, red lines = cell wall thickness, yellow arrows = budding cell, blue arrows = external cell wall modifications, green arrows = cell wall condensed material, orange arrows = invagination of cell membrane and cell wall. (<b>A</b>,<b>B</b>,<b>D</b>,<b>E</b>) have a 2 µm scale bar, (<b>C</b>,<b>F</b>) have a 1 µm scale bar.</p>
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<p>TEM images of control and niacinamide treated cells. (<b>A</b>,<b>B</b>) <span class="html-italic">E. coli</span> control cells. (<b>C</b>) <span class="html-italic">E. coli</span> under 2.5% Niacinamide treatment. (<b>D</b>) <span class="html-italic">E. coli</span> under 5% Niacinamide treatment. (<b>E</b>) <span class="html-italic">P. aeruginosa</span> control cells. (<b>F</b>) <span class="html-italic">P. aeruginosa</span> under 5% Niacinamide treatment N = nucleoid, Cy = cytoplasm, yellow arrows = dense granules. (<b>A</b>,<b>C</b>) have a 2 µm scale bar, (<b>B</b>,<b>D</b>) have a 5 µm scale bar and (<b>E</b>,<b>F</b>) have a 500 nm scale bar.</p>
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<p>Bacterial cell size analysis from microscopic phase images. Control treatment of microorganisms incubated in TSB medium of (<b>A</b>) <span class="html-italic">E. coli</span>, (<b>B</b>) <span class="html-italic">S. aureus</span> and (<b>C</b>) <span class="html-italic">P. aeruginosa</span>. Niacinamide treatment at concentrations of 0, 1 and 2.5% following 24 h incubation of (<b>D</b>) <span class="html-italic">E. coli</span>, (<b>E</b>) <span class="html-italic">S. aureus</span> and (<b>F</b>) <span class="html-italic">P. aeruginosa</span>. Corresponding phase images are located in Supplementary <a href="#app1-microorganisms-12-01581" class="html-app">Figures S2–S5</a>. (**** = <span class="html-italic">p</span> value &lt; 0.0001).</p>
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<p>Microscopic analysis of the microorganisms’ phase images. Cell number and percentage of dividing cells are presented under niacinamide treatment at 0, 1 and 2.5% at incubation time of 1, 3, and 24 h. The number of counted bacterial cells per image (<b>A</b>) <span class="html-italic">E. coli</span>, (<b>B</b>) <span class="html-italic">S. aureus</span>, and (<b>C</b>) <span class="html-italic">P. aeruginosa</span>. The number of dividing cells as a percentage from the total number of cells (<b>D</b>) <span class="html-italic">E. coli</span>, (<b>E</b>) <span class="html-italic">S. aureus</span> and (<b>F</b>) <span class="html-italic">P. aeruginosa</span>. (**** = <span class="html-italic">p</span> value &lt; 0.0001, *** = <span class="html-italic">p</span> value &lt; 0.001, ** = <span class="html-italic">p</span> value &lt; 0.01, * = <span class="html-italic">p</span> value &lt; 0.05, ns = not significant).</p>
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<p>Fluorescence images of DAPI staining, along with the comparative phase image in <span class="html-italic">E. coli</span> (<b>A</b>–<b>F</b>), <span class="html-italic">S. aureus</span> (<b>G</b>–<b>L</b>) and <span class="html-italic">C. albicans</span> (<b>M</b>–<b>R</b>), followed by 4 h treatment with either 2.5 or 5% of niacinamide.</p>
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<p><span class="html-italic">E. coli dps</span> RNA expression levels during incubation with 0–5% niacinamide, at various cell cycle stages, logarithmic phase of 1 h, stationary phase of 3 h and following 24 h. <span class="html-italic">dps</span> gene expression was assessed against the 16S rRNA housekeeping gene. Data are presented as 2<sup>−ΔΔCT</sup> normalized expression levels to the 0% negative control treatment at 1 h, ± SD. Significant differences are indicated in the graph (<span class="html-italic">p</span>-value **** &lt; 0.0001, *** &lt; 0.001, ** &lt; 0.01, ns = not significant).</p>
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<p>Niacinamide interaction with DNA amplicon by gel electrophoresis and qPCR. (<b>A</b>) Agarose gel image of DNA fragment incubated with niacinamide at increasing concentrations. (<b>B</b>) qPCR assay results (Cq = cycle of amplification, Tm = melting temperature of the amplicon) with amplicon’s relevant primers. (<b>C</b>) Clean PCR products of amplified DNA treated with increasing concentrations of niacinamide (5–20%), arrows represent fragmented DNA product.</p>
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29 pages, 3725 KiB  
Review
Targeted Nanocarrier-Based Drug Delivery Strategies for Improving the Therapeutic Efficacy of PARP Inhibitors against Ovarian Cancer
by Patrycja Gralewska, Arkadiusz Gajek, Agnieszka Marczak and Aneta Rogalska
Int. J. Mol. Sci. 2024, 25(15), 8304; https://doi.org/10.3390/ijms25158304 - 30 Jul 2024
Viewed by 580
Abstract
The current focus of ovarian cancer (OC) research is the improvement of treatment options through maximising drug effectiveness. OC remains the fifth leading cause of cancer-induced mortality in women worldwide. In recent years, nanotechnology has revolutionised drug delivery systems. Nanoparticles may be utilised [...] Read more.
The current focus of ovarian cancer (OC) research is the improvement of treatment options through maximising drug effectiveness. OC remains the fifth leading cause of cancer-induced mortality in women worldwide. In recent years, nanotechnology has revolutionised drug delivery systems. Nanoparticles may be utilised as carriers in gene therapy or to overcome the problem of drug resistance in tumours by limiting the number of free drugs in circulation and thereby minimising undesired adverse effects. Cell surface receptors, such as human epidermal growth factor 2 (HER2), folic acid (FA) receptors, CD44 (also referred to as homing cell adhesion molecule, HCAM), and vascular endothelial growth factor (VEGF) are highly expressed in ovarian cancer cells. Generation of active targeting nanoparticles involves modification with ligands that recognise cell surface receptors and thereby promote internalisation by cancer cells. Several poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are currently used for the treatment of high-grade serous ovarian carcinomas (HGSOC) or platinum-sensitive relapsed OC. However, PARP resistance and poor drug bioavailability are common challenges, highlighting the urgent need to develop novel, effective strategies for ovarian cancer treatment. This review evaluates the utility of nanoparticles in ovarian cancer therapy, with a specific focus on targeted approaches and the use of PARPi nanocarriers to optimise treatment outcomes. Full article
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<p>A simplified graphical illustration of various types of nanoparticles used in ovarian cancer treatment.</p>
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<p>The controlled release of drugs from nanoparticles that respond to tumour tissue microenvironment.</p>
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<p>Schematic representation of the mechanism of action of ovarian cancer nanoparticles. Free drugs accumulate at both normal and tumour tissue sites, whereas drugs encapsulated in nanocarriers are located in cancer tissue using the EPR effect. Receptor-mediated active targeting promotes drug accumulation predominantly in the tumour tissue because of the specific ligands present on the surface, leading to improved selectiveness and therapeutic responses.</p>
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<p>Types of liposomes used for chemotherapy and gene therapy in ovarian cancer: cationic liposomes; neutral liposomes; pegylated liposomes- PEG and ligands such as CD44, VEGFR, FR, or HER2 targeted liposomes.</p>
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<p>Proposed mechanism of action of PARP inhibitors.</p>
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11 pages, 1246 KiB  
Article
Effects of PARP Inhibitors on Subsequent Platinum-Based Chemotherapy in Patients with Recurrent Ovarian Cancer
by Tetsuya Kokabu, Yosuke Tarumi, Kota Aoki, Ayaka Okamura, Kohei Aoyama, Hisashi Kataoka, Kaori Yoriki and Taisuke Mori
Cancers 2024, 16(15), 2651; https://doi.org/10.3390/cancers16152651 - 25 Jul 2024
Viewed by 440
Abstract
The clinical outcomes in patients with ovarian cancer have been significantly improved by Poly(adenosine diphosphate–ribose) polymerase inhibitors (PARP-is). However, the best therapeutic strategy for recurrence during PARP-i maintenance therapy remains unknown. Herein, we elucidated the efficacy of platinum-based chemotherapy after PARP-i treatment in [...] Read more.
The clinical outcomes in patients with ovarian cancer have been significantly improved by Poly(adenosine diphosphate–ribose) polymerase inhibitors (PARP-is). However, the best therapeutic strategy for recurrence during PARP-i maintenance therapy remains unknown. Herein, we elucidated the efficacy of platinum-based chemotherapy after PARP-i treatment in recurrent ovarian cancer. Eligible patients had experienced relapses during PARP-i maintenance therapy lasting at least 6 months and had received subsequent platinum-based chemotherapy at our institution between January 2019 and March 2024. Progression-free survival (PFS), overall survival (OS), and risk factors for PFS were evaluated. Sixty-six patients were assessed for eligibility and eighteen were enrolled. The median follow-up period was 14.5 months. The PFS and OS of all patients were 6.5 and 17.6 months, respectively. The evaluation of the risk factors for PFS revealed that age, pathological type, duration of PARP-i maintenance therapy, prior lines of chemotherapy, and PARP-i dose reduction were not significant prognostic markers. However, bevacizumab use in subsequent therapies significantly extended the PFS. The median PFS was 3.1 months in the chemotherapy-alone group and 8.9 months in the chemotherapy with bevacizumab group (log-rank p = 0.022). Platinum-based chemotherapy with bevacizumab in subsequent therapies would provide substantial benefits in the PFS of patients with recurrent ovarian cancer. Full article
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<p>Flowchart of patients’ selection.</p>
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<p>Kaplan–Meier estimates of progression–free survival (<b>A</b>) and overall survival (<b>B</b>) in overall patients (n = 18).</p>
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<p>Kaplan–Meier estimates of progression–free survival (<b>A</b>) and overall survival (<b>B</b>) in subgroup analysis.</p>
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31 pages, 1953 KiB  
Review
The Anticancer Effects and Therapeutic Potential of Kaempferol in Triple-Negative Breast Cancer
by Sukhmandeep Kaur, Patricia Mendonca and Karam F. A. Soliman
Nutrients 2024, 16(15), 2392; https://doi.org/10.3390/nu16152392 - 23 Jul 2024
Viewed by 1076
Abstract
Breast cancer is the second-leading cause of cancer death among women in the United States. Triple-negative breast cancer (TNBC), a subtype of breast cancer, is an aggressive phenotype that lacks estrogen (ER), progesterone (PR), and human epidermal growth (HER-2) receptors, which is challenging [...] Read more.
Breast cancer is the second-leading cause of cancer death among women in the United States. Triple-negative breast cancer (TNBC), a subtype of breast cancer, is an aggressive phenotype that lacks estrogen (ER), progesterone (PR), and human epidermal growth (HER-2) receptors, which is challenging to treat with standardized hormonal therapy. Kaempferol is a natural flavonoid with antioxidant, anti-inflammatory, neuroprotective, and anticancer effects. Besides anti-tumorigenic, antiproliferative, and apoptotic effects, kaempferol protects non-cancerous cells. Kaempferol showed anti-breast cancer effects by inducing DNA damage and increasing caspase 3, caspase 9, and pAMT expression, modifying ROS production by Nrf2 modulation, inducing apoptosis by increasing cleaved PARP and Bax and downregulating Bcl-2 expression, inducing cell cycle arrest at the G2/M phase; inhibiting immune evasion by modulating the JAK-STAT3 pathway; and inhibiting the angiogenic and metastatic potential of tumors by downregulating MMP-3 and MMP-9 levels. Kaempferol holds promise for boosting the efficacy of anticancer agents, complementing their effects, or reversing developed chemoresistance. Exploring novel TNBC molecular targets with kaempferol could elucidate its mechanisms and identify strategies to overcome limitations for clinical application. This review summarizes the latest research on kaempferol’s potential as an anti-TNBC agent, highlighting promising but underexplored molecular pathways and delivery challenges that warrant further investigation to achieve successful clinical translation. Full article
(This article belongs to the Special Issue Anticancer Activities of Dietary Phytochemicals)
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<p>The chemical structure of kaempferol.</p>
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<p>Sources and pharmacological effects of kaempferol.</p>
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<p>The effect of the flavonoid kaempferol on the development and progression of breast cancer. Green arrows indicate induction and red arrows indicate inhibition.</p>
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<p>Summary of Pharmacological Effects of Kaempferol. (<b>A</b>) Oxidative stress modulation, apoptosis induction, and cell cycle arrest; (<b>B</b>) effect on inflammation and immune cells; (<b>C</b>) anti-estrogenic effect. Red arrows indicate inhibition, and green arrows indicate induction.</p>
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13 pages, 1474 KiB  
Article
Manuka Honey Inhibits Human Breast Cancer Progression in Preclinical Models
by Diana C. Márquez-Garbán, Cristian D. Yanes, Gabriela Llarena, David Elashoff, Nalo Hamilton, Mary Hardy, Madhuri Wadehra, Susan A. McCloskey and Richard J. Pietras
Nutrients 2024, 16(14), 2369; https://doi.org/10.3390/nu16142369 - 22 Jul 2024
Viewed by 1395
Abstract
Manuka honey (MH) exhibits potential antitumor activity in preclinical models of a number of human cancers. Treatment in vitro with MH at concentrations ranging from 0.3 to 5.0% (w/v) led to significant dose-dependent inhibition of proliferation of human breast [...] Read more.
Manuka honey (MH) exhibits potential antitumor activity in preclinical models of a number of human cancers. Treatment in vitro with MH at concentrations ranging from 0.3 to 5.0% (w/v) led to significant dose-dependent inhibition of proliferation of human breast cancer MCF-7 cells, but anti-proliferative effects of MH were less pronounced in MDA-MB-231 breast cancer cells. Effects of MH were also tested on non-malignant human mammary epithelial cells (HMECs) at 2.5% w/v, and it was found that MH reduced the proliferation of MCF-7 cells but not that of HMECs. Notably, the antitumor activity of MH was in the range of that exerted by treatment of MCF-7 cells with the antiestrogen tamoxifen. Further, MH treatment stimulated apoptosis of MCF-7 cells in vitro, with most cells exhibiting acute and significant levels of apoptosis that correlated with PARP activation. Additionally, the effects of MH induced the activation of AMPK and inhibition of AKT/mTOR downstream signaling. Treatment of MCF7 cells with increased concentrations of MH induced AMPK phosphorylation in a dose-dependent manner that was accompanied by inhibition of phosphorylation of AKT and mTOR downstream effector protein S6. In addition, MH reduced phosphorylated STAT3 levels in vitro, which may correlate with MH and AMPK-mediated anti-inflammatory properties. Further, in vivo, MH administered alone significantly inhibited the growth of established MCF-7 tumors in nude mice by 84%, resulting in an observable reduction in tumor volume. Our findings highlight the need for further research into the use of natural compounds, such as MH, for antitumor efficacy and potential chemoprevention and investigation of molecular pathways underlying these actions. Full article
(This article belongs to the Section Phytochemicals and Human Health)
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<p>Manuka honey reduces the proliferation of ER-positive human breast cancer cells in vitro. ER-positive MCF-7 breast cancer cells and TNBC MDA-MB-231 cells were incubated in the presence of increasing concentrations of either (<b>A</b>) Manuka honey at 0.0 to 5.0% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) or (<b>B</b>) Manuka powder at 0.0–16%. After 72 h, cell counts were performed using an MTS assay and by manual cell counts. The figures show tumor cell proliferation expressed as the mean percentage of vehicle-treated controls with SEM. Experiments were performed at least three times in independent experiments. (<b>C</b>) Manuka honey reduces the proliferation of MCF-7 cancer cells but not that of non-malignant mammary cells in vitro and enhances the antitumor action of the antiestrogen tamoxifen. Human MCF-7 tumor cells and non-malignant HMECs were cultured in vitro with 2.5% <span class="html-italic">w/v</span> Manuka honey (MH), 10 μM tamoxifen (TM), or both agents combined for 48 h. Cell proliferation was then quantitated and expressed as a percentage of that recorded in appropriate vehicle-treated controls. A higher 5% <span class="html-italic">w/v</span> MH concentration was also tested without a significant effect on HMEC proliferation. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.01, n &gt; 3.</p>
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<p>Induction of apoptosis of breast cancer cells by Manuka honey. (<b>A</b>) MCF-7 cells were treated with vehicle control (CON), 2.5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) (MH 2.5) or 5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) (MH 5.0) Manuka honey, camptothecin 1 μM (Cam), 5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) (Dex) dextrose, or 5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) (HMesq) Mesquite honey. After 24 and/or 48 h, cells were harvested and stained with Annexin V and 7-AAD to assess early and late apoptosis. Treatments with Manuka honey, particularly at 5.0% (<span class="html-italic">w</span>/<span class="html-italic">v</span>), elicited significant increments in apoptotic cells as compared to controls (* <span class="html-italic">p</span> &lt; 0.05). Camptothecin, a positive control drug, elicited a similar increase in late apoptotic cells after 48 h, while treatment of MCF-7 cells with dextrose or Mesquite honey did not exhibit comparable increments in the numbers of apoptotic cells. (<b>B</b>) Treatment of MCF-7 cells with Manuka honey elicits increased poly (ADP-ribose) polymerase (PARP) cleavage. Cells were treated in vitro for 48 h with either control vehicle or Manuka honey at 0.6, 2.5, or 5.0% (<span class="html-italic">w</span>/<span class="html-italic">v</span>). Camptothecin was also used as a positive control.</p>
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<p>Manuka honey activates AMPK signaling and inhibits mTOR and STAT3 downstream signaling. (<b>A</b>) MCF7 cells were treated with increasing concentrations of Manuka honey (0–5%) and 5% Mesquite honey as control. After 24 h, cells were lysed and immunoblotted with specific antibodies. (<b>B</b>) MCF7 cells were treated with increasing concentrations of Manuka honey 0.3–5% (<span class="html-italic">w</span>/<span class="html-italic">v</span>). After 24 h, cells were lysed, and whole cell extracts were resolved by PAGE and immunoblotted with specific antibodies.</p>
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<p>Antitumor activity of Manuka honey in human breast cancer xenografts in vivo. Ovariectomized nude mice (nu<sup>−</sup>/nu<sup>−</sup>, Charles Rivers) with estradiol supplements were implanted with MCF-7 tumor xenografts SQ and treated with Manuka honey or control administered by oral gavage after tumors achieved a size of 50–75 cm<sup>3</sup>. Oral gavage (0.1 mL volume) with 50% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) Manuka honey or control was performed twice daily from days 1 to 14, then once daily thereafter to day 42. Treatment with Manuka honey administered orally elicited a significant suppression of MCF-7 xenograft progression as compared to controls (** <span class="html-italic">p</span> &lt; 0.01) n = 5–7 mice per group.</p>
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11 pages, 5149 KiB  
Article
The Role of IRF9 Upregulation in Modulating Sensitivity to Olaparib and Platinum-Based Chemotherapies in Breast Cancer
by SeokGyeong Choi, Han-Gyu Bae, Dong-Gyu Jo and Woo-Young Kim
Genes 2024, 15(7), 959; https://doi.org/10.3390/genes15070959 - 22 Jul 2024
Viewed by 489
Abstract
Poly(ADP-ribose) polymerase (PARP) inhibitors are targeted therapies that accumulate DNA damage by interfering with DNA repair mechanisms and are approved for treating several cancers with BRCA1/2 mutations. In this study, we utilized CRISPR-dCas9 interference screening to identify genes regulating sensitivity to PARP inhibitors [...] Read more.
Poly(ADP-ribose) polymerase (PARP) inhibitors are targeted therapies that accumulate DNA damage by interfering with DNA repair mechanisms and are approved for treating several cancers with BRCA1/2 mutations. In this study, we utilized CRISPR-dCas9 interference screening to identify genes regulating sensitivity to PARP inhibitors in breast cancer cell lines. Our findings indicated that the interferon (IFN) signaling gene IRF9 was critically involved in modulating sensitivity to these inhibitors. We revealed that the loss of IRF9 leads to increased resistance to the PARP inhibitor in MDA-MB-468 cells, and a similar desensitization was observed in another breast cancer cell line, MDA-MB-231. Further analysis indicated that while the basal expression of IRF9 did not correlate with the response to the PARP inhibitor olaparib, its transcriptional induction was significantly associated with increased sensitivity to the DNA-damaging agent cisplatin in the NCI-60 cell line panel. This finding suggests a mechanistic link between IRF9 induction and cellular responses to DNA damage. Additionally, data from the METABRIC patient tissue study revealed a complex network of IFN-responsive gene expressions postchemotherapy, with seven upregulated genes, including IRF9, and three downregulated genes. These findings underscore the intricate role of IFN signaling in the cellular response to chemotherapy. Collectively, our CRISPR screening data and subsequent bioinformatic analyses suggest that IRF9 is a novel biomarker for sensitivity to DNA-damaging agents, such as olaparib and platinum-based chemotherapeutic agents. Our findings for IRF9 not only enhance our understanding of the genetic basis of drug sensitivity, but also elucidate the role of IRF9 as a critical effector within IFN signaling pathways, potentially influencing the association between the host immune system and chemotherapeutic efficacy. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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<p>A CRISPR/dCas9 interference screen identifies IRF9 and other IRF/STAT family as resistance-inducing genes in TNBC cells. (<b>A</b>) Schematic of olaparib responsiveness screens. The response of cells to olaparib is represented by colors. Grey, neutrally responding; red, resistant; blue, sensitive. (<b>B</b>) Gene rank plots from dCas9-KRAB expressing MDA-MB-468 CRISPRi screens determined by comparing olaparib to DMSO vehicle treatment. Genes are ranked by the NormZ score derived from the DrugZ algorithm. IRF9 and STAT2 are marked in red and yellow, respectively. (<b>C</b>,<b>D</b>) qPCR analysis of IRF9 mRNA level and immunoblot analysis showing the IRF9 protein level in generated IRF9 TS MDA-MB-231 CRISPRi cell lines. (<b>E</b>) Clonogenic survival assay of IRF9 TS MDA-MB-231 cells. Cells were plated for clonogenic growth upon olaparib (2.8 and 5.8 μM) treatment. Data are presented as mean ± SD (<span class="html-italic">n</span> = 3). (<b>F</b>) Heatmap showing log2 fold change in sgRNA abundance. Each column represents one gene; each row represents one sgRNA. Five sgRNAs per gene except IRF4 and IRF5 (10 sgRNAs for these two).</p>
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<p>IRF/STAT family baseline expression does not correlate with sensitivity to olaparib or carboplatin in BRCA1/2 WT breast cancer cell lines. (<b>A</b>,<b>B</b>) Correlation analysis of each gene’s baseline expression versus olaparib sensitivity in 22 BRCA1/2 WT breast cancer cell lines, derived from DepMap Portal PRISM Repurposing screen data. Correlation analysis was conducted using Pearson correlation coefficient of gene expression versus olaparib or carboplatin responses (log2 fold change in abundance). Each dot represents a cell line, and the dashed red line indicates a linear regression line.</p>
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<p>The upregulation of IRF9 expression by DNA-damaging chemotherapy correlates with drug sensitivity in various cancer types. (<b>A</b>) Heatmap showing log2 fold change in IRF/STAT family expression in NCI-60 cell line panel treated with cisplatin 15 μM (left) or paclitaxel 100 nM (right) for 24 h. Gene expression upregulation and downregulation are indicated by red and blue, respectively. (<b>B</b>) Heatmap showing log2 fold change in each gene expression in 56 human cancer cell lines treated with cisplatin 15 μM for 2 h, 6 h, or 24 h. Cell lines are ranked from the lowest to highest log GI50. A cross is shown where data were not available. *: breast cancer cell lines. (<b>C</b>,<b>D</b>) Dot plot showing baseline expression (left) and log2 fold change in IRF9 at 6 h (right) against log GI50 values for cisplatin or paclitaxel. Cell lines with available GI50data (cisplatin; <span class="html-italic">n</span>  =  56, paclitaxel; <span class="html-italic">n</span> = 60) were separated into quartiles, with the most sensitive (red) to most resistant (blue) shown. Pearson correlation coefficient and <span class="html-italic">p</span> value is shown.</p>
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<p>Breast cancer patients treated with chemotherapy show alterations in IRF/STAT family expression. mRNA expression level of IRF/STAT family in breast cancer patients who had been treated with chemotherapy or not. Dots represent each patient and are shown with the mean and 95% confidence interval (red line). Data were obtained from METABRIC, Nature 2012 and Nat Commun 2016 (No, <span class="html-italic">n</span> = 1568; YES, <span class="html-italic">n</span> = 412) [<a href="#B27-genes-15-00959" class="html-bibr">27</a>,<a href="#B28-genes-15-00959" class="html-bibr">28</a>]. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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11 pages, 934 KiB  
Review
Expanding the Perspective on PARP1 and Its Inhibitors in Cancer Therapy: From DNA Damage Repair to Immunomodulation
by Flurina Böhi and Michael O. Hottiger
Biomedicines 2024, 12(7), 1617; https://doi.org/10.3390/biomedicines12071617 - 20 Jul 2024
Viewed by 717
Abstract
The emergence of PARP inhibitors as a therapeutic strategy for tumors with high genomic instability, particularly those harboring BRCA mutations, has advanced cancer treatment. However, recent advances have illuminated a multifaceted role of PARP1 beyond its canonical function in DNA damage repair. This [...] Read more.
The emergence of PARP inhibitors as a therapeutic strategy for tumors with high genomic instability, particularly those harboring BRCA mutations, has advanced cancer treatment. However, recent advances have illuminated a multifaceted role of PARP1 beyond its canonical function in DNA damage repair. This review explores the expanding roles of PARP1, highlighting its crucial interplay with the immune system during tumorigenesis. We discuss PARP1’s immunomodulatory effects in macrophages and T cells, with a particular focus on cytokine expression. Understanding these immunomodulatory roles of PARP1 not only holds promise for enhancing the efficacy of PARP inhibitors in cancer therapy but also paves the way for novel treatment regimens targeting immune-mediated inflammatory diseases. Full article
(This article belongs to the Special Issue The Role of Inflammatory Cytokines in Cancer Progression 2.0)
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<p>PARPi effect in cancer cells and immune cells. Depicted in green are effects that are promoted by PARPi treatment, and effects that are inhibited by PARPi treatment are shown in red. (<b>A</b>) Synthetic lethality interaction of homologous recombination (HR)-deficient cancer cells and PARPi treatment leads to cancer cell death. (<b>B</b>) PARPi treatment also inhibits ADP-ribosylation of cGAS in cancer cells, thereby enhancing the cGAS/STING signaling pathway. (<b>C</b>) In macrophages, PARPi elevate levels of NAD<sup>+</sup> and ROS. This shift in metabolism enhances the anti-tumorigenic function of macrophages. (<b>D</b>–<b>G</b>) PARPi up- and downregulate the transcription of various cytokines in both macrophages and T cells. (<b>H</b>) In cancer cells, PARPi treatment upregulates PD-L1 expression, which may have implications for the interaction between cancer cells and the immune system.</p>
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<p>Comparable PARP1 gene effects across tumor cell lines. To compare the effect of PARP1 and its enzymatic activity across different cell lines, we used publicly available datasets of genome-wide CRISPR loss-of-function and drug sensitivity screens. These datasets provide scores for gene dependency and drug sensitivity (<a href="https://depmap.org/portal/" target="_blank">https://depmap.org/portal/</a>, accessed on 9 July 2024). (<b>A</b>) Dependency on PARP1 in several of the examined cell lines. Colored groups represent cell lines derived from breast, ovarian, fallopian tube, and pancreas tumors, all of which are treated with PARPi in clinics. (<b>B</b>) Correlation plot of PARP1 gene dependency scores (<span class="html-italic">x</span>-axis) vs. Talazoparib sensitivity scores (<span class="html-italic">y</span>-axis). Except for lung cancer cell lines (colored in red), which show a significant correlation between PARP1 gene effect and PARPi treatment efficacy, most cancer cell lines, including those derived from breast, ovarian, fallopian tube and pancreas tumors (colored in green/light blue/ dark blue), exhibit a low and non-significant correlation between PARP1 gene effect and PARPi efficacy. The cancer types shown in gray are those for which data on the PARP1 gene dependency score (<a href="#biomedicines-12-01617-f002" class="html-fig">Figure 2</a>A) or data on the PARP1 gene dependency score and on the Talazoparib sensitivity score (<a href="#biomedicines-12-01617-f002" class="html-fig">Figure 2</a>B) were available for at least 10 cell lines. In none of these cancer types was a strong or significant correlation found between PARP1 gene effect and PARP1 inhibition. * = <span class="html-italic">p</span> ≤ 0.05.</p>
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22 pages, 2884 KiB  
Article
Molecular Mechanisms Underlying the Anticancer Properties of Pitavastatin against Cervical Cancer Cells
by Ya-Hui Chen, Jyun-Xue Wu, Shun-Fa Yang, Yun-Chia Wu and Yi-Hsuan Hsiao
Int. J. Mol. Sci. 2024, 25(14), 7915; https://doi.org/10.3390/ijms25147915 - 19 Jul 2024
Viewed by 591
Abstract
Cervical cancer ranks as the fourth most prevalent form of cancer and is a significant contributor to female mortality on a global scale. Pitavastatin is an anti-hyperlipidemic medication and has been demonstrated to exert anticancer and anti-inflammatory effects. Thus, the purpose of this [...] Read more.
Cervical cancer ranks as the fourth most prevalent form of cancer and is a significant contributor to female mortality on a global scale. Pitavastatin is an anti-hyperlipidemic medication and has been demonstrated to exert anticancer and anti-inflammatory effects. Thus, the purpose of this study was to evaluate the anticancer effect of pitavastatin on cervical cancer and the underlying molecular mechanisms involved. The results showed that pitavastatin significantly inhibited cell viability by targeting cell-cycle arrest and apoptosis in Ca Ski, HeLa and C-33 A cells. Pitavastatin caused sub-G1- and G0/G1-phase arrest in Ca Ski and HeLa cells and sub-G1- and G2/M-phase arrest in C-33 A cells. Moreover, pitavastatin induced apoptosis via the activation of poly-ADP-ribose polymerase (PARP), Bax and cleaved caspase 3; inactivated the expression of Bcl-2; and increased mitochondrial membrane depolarization. Furthermore, pitavastatin induced apoptosis and slowed the migration of all three cervical cell lines, mediated by the PI3K/AKT and MAPK (JNK, p38 and ERK1/2) pathways. Pitavastatin markedly inhibited tumor growth in vivo in a cancer cell-originated xenograft mouse model. Overall, our results identified pitavastatin as an anticancer agent for cervical cancer, which might be expanded to clinical use in the future. Full article
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<p>Pitavastatin inhibited cervical cancer cell viability and colony formation in a dose-dependent manner. (<b>A</b>–<b>C</b>) After treatment with pitavastatin (0, 5 and 10 μM) for 24, 48 and 72 h, the viability of Ca Ski, HeLa and C-33 A cells was measured using a CCK-8 assay. (<b>D</b>,<b>E</b>) Colony formation of Ca Ski, HeLa and C-33 A cells treated with pitavastatin (0, 5 and 10 μM) for 48 h. The colony formation ability of Ca Ski, HeLa and C-33 A cells was quantified by measuring the absorbance of the solution obtained by crystal violet, at 100× magnification, scale bar = 200 μm. The values represent the means ± SDs of three replicates. * <span class="html-italic">p</span> ˂ 0.05, ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>†</sup> <span class="html-italic">p</span> ˂ 0.05, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>Pitavastatin induces cell apoptosis in cervical cancer cell lines after treatment with pitavastatin (0, 5 and 10 μM) for 48 h, (<b>A</b>) the nuclear condensation of Ca Ski, HeLa and C-33 A cells was measured with DAPI staining and analyzed by fluorescence microscopy at 400× magnification; scale bar = 50 μm. (<b>B</b>) The relative density of the ratio of cells with nuclear condensation. (<b>C</b>) Cells were stained with Annexin V/PI and analyzed by flow cytometry. (<b>D</b>) Quantitative relative density of the percentage of apoptotic cells (including cells in the early and late stages). The values represent the means ± SDs of three replicates. ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>†</sup> <span class="html-italic">p</span> ˂ 0.05, <sup>γ</sup> <span class="html-italic">p</span> ˂ 0.01, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>Pitavastatin leads to sub-G1, G0/G1 and G2/M cell cycle arrest in cervical cancer cell lines. (<b>A</b>) The cell cycle distribution of Ca Ski, HeLa and C-33 A cells treated with pitavastatin (0, 5 and 10 μM) for 48 h was analyzed by flow cytometry. (<b>B</b>) Quantitation of the cell cycle distribution (sub-G1, G0/G1, S and G2/M). The values represent the means ± SDs of three replicates. * <span class="html-italic">p</span> ˂ 0.05, ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>†</sup> <span class="html-italic">p</span> ˂ 0.05, <sup>γ</sup> <span class="html-italic">p</span> ˂ 0.01, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>Pitavastatin inhibits the migration of cervical cancer cell lines. (<b>A</b>) Ca Ski, HeLa and C-33 A cells were treated with pitavastatin (0, 5 and 10 μM) and photographed at 0, 24 and 48 h to measure the extent of wound closure, usually using a 200-μL sterile pipette tip, leaving two wound edges (red lines) separated by a void. (<b>B</b>) Semi-quantitative analysis of the relative wound closure of Ca Ski, HeLa and C-33 A cells were performed by measuring the width of the wounds. (<b>C</b>) Ca Ski, HeLa and C-33 A cells migration capacity were evaluated by using 24-well Boyden chamber. (<b>D</b>) Quantitative relative density of the percentage of migration numbers. The values represent the means ± SDs of three replicates. ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>γ</sup> <span class="html-italic">p</span> ˂ 0.01, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>Pitavastatin reduces the mitochondrial membrane potential (∆ψm<b>)</b> in cervical cancer cell lines. Ca Ski, HeLa and C-33 A cells were treated with pitavastatin (0, 5 and 10 μM) for 48 h and stained with JC-1 dye. (<b>A</b>) Flow cytometry analysis showing the distribution of JC-1 green-positive cells with lower ∆ψm. (<b>B</b>) Quantitative analysis of the percentage of red-polymer and green-monomer fluorescence. The values represent the means ± SDs of three replicates. *** <span class="html-italic">p</span> ˂ 0.001 and <sup>†††</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the CON with polymers- or CON with monomers-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>Pitavastatin causes cell apoptosis by activating apoptosis-related proteins in cervical cancer cell lines. Ca Ski (<b>A</b>), HeLa (<b>B</b>) and C-33 A (<b>C</b>) cells were treated with pitavastatin (0, 5 and 10 μM) for 48 h, and the PARP-1, Bcl-2, Bax, cleaved caspase 3 and p27<sup>KIP1</sup> levels were measured via Western blotting, with GAPDH serving as an internal control. The quantitative results are shown in the bottom plot. The values represent the means ± SDs of three replicates. * <span class="html-italic">p</span> ˂ 0.05, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>†</sup> <span class="html-italic">p</span> ˂ 0.05, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>The PI3K/AKT and MAPK pathways are involved in pitavastatin-induced apoptosis regulation in cervical cancer cell lines. After treatment with pitavastatin (0, 5 and 10 μM) for 48 h, total and phosphorylated PI3K (110α), AKT, p38, ERK1/2 and JNK1/2 levels in Ca Ski (<b>A</b>), HeLa (<b>B</b>) and C-33 A (<b>C</b>) cells were measured via Western blotting, with GAPDH serving as an internal control. The quantitative results are shown in the bottom plot. The values represent the means ± SDs of three replicates. * <span class="html-italic">p</span> ˂ 0.05, ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>†</sup> <span class="html-italic">p</span> ˂ 0.05, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 10—10 μM pitavastatin.</p>
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<p>The caspase 3-dependent apoptosis pathway is activated by pitavastatin in cervical cancer cell lines. Ca Ski, HeLa and C-33 A cells were pretreated with z-DEVD-fmk (2.5 or 5.0 μM) for 2 h and then treated with pitavastatin (5 μM) for 48 h. Ca Ski (<b>A</b>), HeLa (<b>B</b>) and C-33A (<b>C</b>) cell viability were measured through the CCK-8 assay. PARP-1, cleaved caspase 3, p-p38 and p38 levels were detected by Western blotting. GAPDH was used as an internal control. The quantitative results are shown in the bottom plot. The values represent the means ± SDs of three replicates. ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>†</sup> <span class="html-italic">p</span> ˂ 0.05, <sup>γ</sup> <span class="html-italic">p</span> ˂ 0.01, <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—0.1% DMSO; Pita 5—5 μM pitavastatin; Pita 5+ z-DEVD—5 μM pitavastatin + 2.5 μM z-DEVD or 5 μM pitavastatin + 5.0 μM z-DEVD.</p>
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<p>Pitavastatin effectively suppresses C-33 A xenograft tumor growth. C-33 A cells (1 × 107 cells) were injected subcutaneously into the right flank of BALB/c nude mice, and pitavastatin at 5 mg/kg or 10 mg/kg was then given by intraperitoneal injection every day to the mice. (<b>A</b>) Schematic representation of the experiment. (<b>B</b>) Representative images of tumors in C-33 A xenograft nude mice and tumor volume, as well as tumor weight (<b>C</b>) and body weight (<b>D</b>). The quantitative results are shown in the bottom plot. The values represent the means ± SDs (n = 8/group). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with the CON group. CON—control; Pita 5—5 mg/kg pitavastatin; Pita 10—10 mg/kg pitavastatin.</p>
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<p>Pitavastatin effectively reduces ki67 expression and enhances cleaved caspase 3 and p-p38 expression in mammary tumor tissues from C-33 A xenograft nude mice. Mammary tissues were collected from pitavastatin-treated and untreated mice (<span class="html-italic">n</span> = 8/group). Representative histological sections of tumor tissue were stained with hematoxylin and eosin, a proliferation marker (ki67), an apoptosis marker (cleaved caspase 3), and p-p38 (shown as brown staining; H&amp;E, 200× magnification, scale bar = 50 μm; immunohistochemical analysis, 400× magnification, scale bar = 20 μm). The quantitative results are shown in the bottom plot. The values represent the means ± SDs. ** <span class="html-italic">p</span> ˂ 0.01, *** <span class="html-italic">p</span> ˂ 0.001 compared with the CON group; <sup>δ</sup> <span class="html-italic">p</span> ˂ 0.001 compared with the Pita 5-treated group. CON—control; Pita 5—5 mg/kg pitavastatin; Pita 10—10 mg/kg pitavastatin.</p>
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15 pages, 1767 KiB  
Case Report
PARP Inhibitors in Brain Metastases from Epithelial Ovarian Cancer through a Multimodal Patient Journey: Case Reports and Literature Review
by Simona Frezzini, Giulia Tasca, Lucia Borgato, Lucia Sartor, Annamaria Ferrero, Grazia Artioli, Alessandra Modena and Alessandra Baldoni
Int. J. Mol. Sci. 2024, 25(14), 7887; https://doi.org/10.3390/ijms25147887 - 18 Jul 2024
Viewed by 497
Abstract
Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Brain metastasis (BM) is quite an uncommon presentation. However, the likelihood of central nervous system (CNS) metastasization should be considered in the context of disseminated disease. The therapeutic management of BMs is an [...] Read more.
Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Brain metastasis (BM) is quite an uncommon presentation. However, the likelihood of central nervous system (CNS) metastasization should be considered in the context of disseminated disease. The therapeutic management of BMs is an unmet clinical need, to date. We identified, across different cancer centers, six cases of both BRCA wild-type and BRCA-mutated EOCs spreading to the CNS. They presented either with a single brain lesion or with multiple lesions and most of them had intracranial-only disease. All cases received Poly-ADP ribose polymerase inhibitor (PARPi) maintenance, as per clinical practice, for a long time within a multimodal treatment approach. We also provide an insight into the available body of work regarding the management of this intriguing disease setting, with a glimpse of future therapeutic challenges. Despite the lack of unanimous guidelines, multimodal care pathways should be encouraged for the optimal disease control of this unfortunate patient subset. Albeit not being directly investigated in BM patients, PARPi maintenance is deemed to have a valuable role in this setting. Prospective research, aimed to implement worthwhile strategies in the multimodal patient journey of BMs from EOC, is eagerly awaited. Full article
(This article belongs to the Special Issue Current Research on Cancer Biology and Therapeutics: 2nd Edition)
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Figure 1

Figure 1
<p>Timeline of patient treatment journey in <span class="html-italic">case one</span>. Abbreviations. CC0: completeness of cytoreduction score 0. CHT: chemotherapy. CP: Carboplatin plus Paclitaxel. BEV: Bevacizumab. SRS: stereotactic radiosurgery. Sept: September. Apr: April. Oct: October. Aug: August.</p>
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<p>Timeline of patient treatment journey in <span class="html-italic">case two</span>. Abbreviations. CC0: completeness of cytoreduction score 0. CP: Carboplatin plus Paclitaxel. CHT: chemotherapy. BEV: Bevacizumab. SRS: stereotactic radiosurgery. Apr: April. Sept: September. Dec: December.</p>
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<p>Timeline of patient treatment journey in <span class="html-italic">case three</span>. Abbreviations. CC0: completeness of cytoreduction score 0. CHT: chemotherapy. CP: Carboplatin plus Paclitaxel. C + PLD: Carboplatin + Pegylated liposomal doxorubicin. SRS: stereotactic radiosurgery. PD: progressive disease. Nov: November. Jan: January. Nov: November. Jan: January.</p>
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<p>Timeline of patient treatment journey in <span class="html-italic">case four</span>. Abbreviations. CC0: completeness of cytoreduction score 0. CHT: chemotherapy. CP: Carboplatin plus Paclitaxel. CR: complete response. PD: progressive disease. SRS: stereotactic radiosurgery. Apr: April. Aug: August. Dec: December.</p>
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<p>Timeline of patient treatment journey in <span class="html-italic">case five</span>. Abbreviations. CC0: completeness of cytoreduction score 0. CHT: chemotherapy. CP: Carboplatin plus Paclitaxel. C + PLD: Carboplatin + Pegylated liposomal doxorubicin. SRS: stereotactic radiosurgery. Jan: January. Dec: December. Jun: June.</p>
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<p>Timeline of patient treatment journey in <span class="html-italic">case six</span>. Abbreviations. CC0: completeness of cytoreduction score 0. CHT: chemotherapy. CP: Carboplatin plus Paclitaxel. CLL/SLL: chronic lymphocytic leukemia/small lymphocytic lymphoma. HRP: homologous recombination proficient. SRS: stereotactic radiosurgery. Dec: December. Aug: August.</p>
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20 pages, 1152 KiB  
Review
Antibody-Drug Conjugates: The New Treatment Approaches for Ovarian Cancer
by Sho Sato, Tadahiro Shoji, Ami Jo, Haruka Otsuka, Marina Abe, Shunsuke Tatsuki, Yohei Chiba, Eriko Takatori, Yoshitaka Kaido, Takayuki Nagasawa, Masahiro Kagabu and Tsukasa Baba
Cancers 2024, 16(14), 2545; https://doi.org/10.3390/cancers16142545 - 15 Jul 2024
Viewed by 849
Abstract
Ovarian cancer (OC), accounting for approximately 200,000 deaths worldwide annually, is a heterogeneous disease showing major differences in terms of its incidence, tumor behavior, and outcomes across histological subtypes. In OC, primary chemotherapy, paclitaxel carboplatin, bevacizumab, and PARP inhibitors have shown prolonged progression-free [...] Read more.
Ovarian cancer (OC), accounting for approximately 200,000 deaths worldwide annually, is a heterogeneous disease showing major differences in terms of its incidence, tumor behavior, and outcomes across histological subtypes. In OC, primary chemotherapy, paclitaxel carboplatin, bevacizumab, and PARP inhibitors have shown prolonged progression-free survival and a favorable overall response rate compared to conventional treatments. However, treatment options for platinum-resistant recurrence cases are limited, with no effective therapies that significantly prolong the prognosis. Recently, mirvetuximab soravtansine, an alpha-folate receptor (FRα)-targeted antibody-drug conjugate (ADC), was approved by the US Food and Drug Administration for patients with FRα-positive recurrent epithelial OC (EOC). This approval was based on a Phase II study, which demonstrated its efficacy in such patients. ADCs comprise an antibody, a linker, and a payload, representing new concept agents without precedence. Advanced clinical studies are developing ADCs for patients with OC, targeting solid tumors such as gynecologic cancer. Ongoing clinical trials are evaluating ADCs targeting FRα and human epidermal growth factor receptor 2, trophoblast cell surface antigen-2, sodium-dependent phosphate transport protein 2B, and cadherin-6 in Phase II/III studies. In this review, we summarize the existing evidence supporting the use of ADCs in OC, discuss ongoing clinical trials and preclinical studies, and explore the potential of these innovative agents to address the challenges in OC treatment. Full article
(This article belongs to the Section Cancer Drug Development)
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Figure 1
<p>(<b>A</b>) Antibody-drug conjugates (ADCs) consist of an antibody, a linker, and a payload. (<b>B</b>) The mechanism of ADC action for inhibiting tumor cells; (1) the antibody in an ADC combines with an antigen as the ADC-receptor complex on the tumor. <span style="color:red">‖</span>: showing combined antibody with antigen. (2) ADC is internalized via antigen-mediated through receptor-mediated endocytosis and (3) cleaved into antibody and payload through endolysosomal processing. <span class="html-fig-inline" id="cancers-16-02545-i001"><img alt="Cancers 16 02545 i001" src="/cancers/cancers-16-02545/article_deploy/html/images/cancers-16-02545-i001.png"/></span>: showing released payload from linker. (4) The payload in a bioactive form that is released into the cytoplasm. Payloads that disrupt microtubule bind to tubulin. DNA-targeting payloads diffuse from the cytoplasm into the nucleus. Intracellular accumulation of the active payload results in cell death.</p>
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26 pages, 8995 KiB  
Article
The Induction of G2/M Phase Cell Cycle Arrest and Apoptosis by the Chalcone Derivative 1C in Sensitive and Resistant Ovarian Cancer Cells Is Associated with ROS Generation
by Šimon Salanci, Mária Vilková, Lola Martinez, Ladislav Mirossay, Radka Michalková and Ján Mojžiš
Int. J. Mol. Sci. 2024, 25(14), 7541; https://doi.org/10.3390/ijms25147541 - 9 Jul 2024
Viewed by 757
Abstract
Ovarian cancer ranks among the most severe forms of cancer affecting the female reproductive organs, posing a significant clinical challenge primarily due to the development of resistance to conventional therapies. This study investigated the effects of the chalcone derivative 1C on sensitive (A2780) [...] Read more.
Ovarian cancer ranks among the most severe forms of cancer affecting the female reproductive organs, posing a significant clinical challenge primarily due to the development of resistance to conventional therapies. This study investigated the effects of the chalcone derivative 1C on sensitive (A2780) and cisplatin-resistant (A2780cis) ovarian cancer cell lines. Our findings revealed that 1C suppressed cell viability, induced cell cycle arrest at the G2/M phase, and triggered apoptosis in both cell lines. These effects are closely associated with generating reactive oxygen species (ROS). Mechanistically, 1C induced DNA damage, modulated the activity of p21, PCNA, and phosphorylation of Rb and Bad proteins, as well as cleaved PARP. Moreover, it modulated Akt, Erk1/2, and NF-κB signaling pathways. Interestingly, we observed differential effects of 1C on Nrf2 levels between sensitive and resistant cells. While 1C increased Nrf2 levels in sensitive cells after 12 h and decreased them after 48 h, the opposite effect was observed in resistant cells. Notably, most of these effects were suppressed by the potent antioxidant N-acetylcysteine (NAC), underscoring the crucial role of ROS in 1C-induced antiproliferative activity. Moreover, we suggest that modulation of Nrf2 levels can, at least partially, contribute to the antiproliferative effect of chalcone 1C. Full article
(This article belongs to the Special Issue Programmed Cell Death and Oxidative Stress 2.0)
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Figure 1

Figure 1
<p>Antiproliferative effect of 1C on A2780 and A2780cis cells after 48 h exposure determined by MTT assay. Results show mean ± standard deviation calculated from three independent experiments. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. control (DMSO).</p>
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<p>Effect of NAC on A2780 and A2780cis cells after 48 h exposure determined by MTT assay. Results show the mean ± standard deviation calculated from three independent experiments. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (culture medium).</p>
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<p>Effect of NAC/1C on A2780 and A2780cis cells viability after 12 h exposure determined by MTT assay. Results show the mean ± standard deviation calculated from three independent experiments. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (Ctrl) and ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. IC<sub>50</sub> (1C).</p>
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<p>Effect of NAC/1C on A2780 and A2780cis cells viability after 24 h exposure determined by MTT assay. Results show the mean ± standard deviation calculated from three independent experiments. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (Ctrl) and # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. IC<sub>50</sub> (1C).</p>
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<p>Effect of NAC/1C on A2780 and A2780cis cells viability after 48 h exposure determined by MTT assay. Results show the mean ± standard deviation calculated from three independent experiments. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (Ctrl) and # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, vs. IC<sub>50</sub> (1C).</p>
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<p>The influence of 1C, NAC, and their combination on ROS production in A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells after 12, 24, and 48 h exposure. Data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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<p>Effect on superoxide anion production in A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells after 12, 24, and 48 h exposure to 1C, NAC, and combination NAC/1C. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 vs. 1C.</p>
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<p>Impact of 1C, NAC, and their combination on lipid peroxidation in A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells treated for 12, 24, and 48 h. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 vs. 1C.</p>
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<p>Analysis of cell cycle of A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells affected by 12, 24, and 48 h lasting treatment with 1C, NAC and NAC/1C. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 vs. 1C.</p>
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<p>Effect of 1C, NAC, and their combination on the loss of mitochondrial membrane potential in A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells after 12, 24, and 48 h exposure. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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<p>An/PI staining cytometric analysis of apoptosis influenced by 1C, NAC, and their combination in A2780 (upper (<b>A</b>)) and A2780cis (lower (<b>B</b>)) cells after 12, 24, and 48 h incubation. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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<p>Western blot analysis of DNA damage, cell cycle, and apoptosis-associated proteins affected by 1C, NAC, and their combination in A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells after 12, 24, and 48 h incubation. Representative figure.</p>
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<p>Densitometric analysis of phosphorylation of histone H2A.X (<b>A</b>), PCNA (<b>B</b>), phospho-Rb (<b>C</b>), p21 (<b>D</b>), phospho-Bad (<b>E</b>) and cleaved PARP (<b>F</b>) after 12, 24 and 48, and 72 h of 1C treatment in A2780 cells. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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<p>Densitometric analysis of phosphorylation of histone H2A.X (<b>A</b>), PCNA (<b>B</b>), phospho-Rb (<b>C</b>), p21 (<b>D</b>), phospho-Bad (<b>E</b>) and cleaved PARP (<b>F)</b> after 12, 24 and 48, and 72 h of 1C treatment in A2780cis cells. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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<p>Western blot analysis of oxidative stress response associated proteins affected by 1C, NAC, and their combination in A2780 (<b>A</b>) and A2780cis (<b>B</b>) cells after 12, 24, and 48 h incubation. Representative figure.</p>
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<p>Densitometric analysis of phosphorylation of Akt (<b>A</b>), phospho-Erk1/2 (<b>B</b>), Nrf2 (<b>C</b>), NF-κB1 105/p50 (<b>D</b>) and p65 (<b>E</b>) after 12, 24 and 48, and 72 h of 1C treatment in A2780 cells. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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<p>Densitometric analysis of phosphorylation of Akt (<b>A</b>), phospho-Erk1/2 (<b>B</b>), Nrf2 (<b>C</b>), NF-κB1 105/p50 (<b>D</b>), and p65 (<b>E</b>) after 12, 24 and 48, and 72 h of 1C treatment in A2780cis cells. Presented data were obtained from three independent acquisitions. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control (DMSO); # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. 1C.</p>
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Article
Germline Sequencing of DNA Damage Repair Genes in Two Hereditary Prostate Cancer Cohorts Reveals New Disease Risk-Associated Gene Variants
by Georgea R. Foley, James R. Marthick, Sionne E. Lucas, Kelsie Raspin, Annette Banks, Janet L. Stanford, Elaine A. Ostrander, Liesel M. FitzGerald and Joanne L. Dickinson
Cancers 2024, 16(13), 2482; https://doi.org/10.3390/cancers16132482 - 7 Jul 2024
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Abstract
Rare, inherited variants in DNA damage repair (DDR) genes have a recognised role in prostate cancer (PrCa) susceptibility. In addition, these genes are therapeutically targetable. While rare variants are informing clinical management in other common cancers, defining the rare disease-associated variants in PrCa [...] Read more.
Rare, inherited variants in DNA damage repair (DDR) genes have a recognised role in prostate cancer (PrCa) susceptibility. In addition, these genes are therapeutically targetable. While rare variants are informing clinical management in other common cancers, defining the rare disease-associated variants in PrCa has been challenging. Here, whole-genome and -exome sequencing data from two independent, high-risk Australian and North American familial PrCa datasets were interrogated for novel DDR risk variants. Rare DDR gene variants (predicted to be damaging and present in two or more family members) were identified and subsequently genotyped in 1963 individuals (700 familial and 459 sporadic PrCa cases, 482 unaffected relatives, and 322 screened controls), and association analyses accounting for relatedness (MQLS) undertaken. In the combined datasets, rare ERCC3 (rs145201970, p = 2.57 × 10−4) and BRIP1 (rs4988345, p = 0.025) variants were significantly associated with PrCa risk. A PARP2 (rs200603922, p = 0.028) variant in the Australian dataset and a MUTYH (rs36053993, p = 0.031) variant in the North American dataset were also associated with risk. Evaluation of clinicopathological characteristics provided no evidence for a younger age or higher-grade disease at diagnosis in variant carriers, which should be taken into consideration when determining genetic screening eligibility criteria for targeted, gene-based treatments in the future. This study adds valuable knowledge to our understanding of PrCa-associated DDR genes, which will underpin effective clinical screening and treatment strategies. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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Figure 1

Figure 1
<p><b>Variant Filtering and Prioritisation Schematic</b>. Flow chart outlining genetic analysis pipeline including variant filtering and prioritisation of variants for follow-up.</p>
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<p><b>Age at diagnosis of DDR gene variant carriers* compared to available population-based datasets</b>. Age at diagnosis of variant carriers compared with a comparable population dataset (presented as proportion of individuals versus age at diagnosis). Dashed vertical lines represent the median age of diagnosis. Top Panel: Familial PrCa variant carriers (n = 31) overlayed with unscreened PCOR-TAS case population (n = 2126); Middle Panel: Sporadic PrCa variant carriers (n = 22) compared with unscreened PCOR-Tas case population (n = 2126); and Bottom Panel: <span class="html-italic">PROGRESS</span> dataset variant carriers (n = 28) compared with non-variant carriers from the <span class="html-italic">PROGRESS</span> dataset. * DDR variant carriers = those carrying a pathogenic variant in <span class="html-italic">BRIP1</span>, <span class="html-italic">BRCA2, ERCC3</span>, <span class="html-italic">MUTYH</span>, <span class="html-italic">PARP2</span>, or <span class="html-italic">RAD51C</span>. Bolded text indicates significant results.</p>
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