Chemotherapy-induced hyaluronan production: a novel chemoresistance mechanism in ovarian cancer

Background: Hyaluronan (HA) an important component of the extracellular matrix, has been linked to tumor progression and drug resistance in several malignancies. However, limited data is available for ovarian cancer. This study investigated the role of hyaluronan (HA) and a potential link between the HA-CD44 pathway and membrane ATP binding cassette (ABC) transporter proteins in ovarian cancer chemoresistance. Methods: We investigated the ability of HA to block the cytotoxic effects of the chemotherapy drug carboplatin, and to regulate the expression of ABC transporters in ovarian cancer cells. We also examined HA serum levels in ovarian cancer patients prior to and following chemotherapy and assessed its prognostic relevance. Results: HA increased the survival of carboplatin treated ovarian cancer cells expressing the HA receptor, CD44 (OVCAR-5 and OV-90). Carboplatin significantly increased expression of HAS2, HAS3 and ABCC2 and HA secretion in ovarian cancer cell conditioned media. Serum HA levels were significantly increased in patients following platinum based chemotherapy and at both 1st and 2nd recurrence when compared with HA levels prior to treatment. High serum HA levels (>50 μg/ml) prior to chemotherapy treatment were associated with significantly reduced progression-free (P = 0.014) and overall survival (P = 0.036). HA production in ovarian cancer cells was increased in cancer tissues collected following chemotherapy treatment and at recurrence. Furthermore HA treatment significantly increased the expression of ABC drug transporters (ABCB3, ABCC1, ABCC2, and ABCC3), but only in ovarian cancer cells expressing CD44. The effects of HA and carboplatin on ABC transporter expression in ovarian cancer cells could be abrogated by HA oligomer treatment. Importantly, HA oligomers increased the sensitivity of chemoresistant SKOV3 cells to carboplatin. Conclusions: Our findings indicate that carboplatin chemotherapy induces HA production which can contribute to chemoresistance by regulating ABC transporter expression. The HA-CD44 signaling pathway is therefore a promising target in platinum resistant ovarian cancer.Carmela Ricciardelli, Miranda P Ween, Noor A Lokman, Izza A Tan, Carmen E Pyragius, and Martin K Oehle

Transforming growth factor-beta-induced protein (TGFBI)/(Beta ig-H3): a matrix protein with dual functions in ovarian cancer

Transforming growth factor-beta-induced protein (TGFBI, also known as βig-H3 and keratoepithelin) is an extracellular matrix protein that plays a role in a wide range of physiological and pathological conditions including diabetes, corneal dystrophy and tumorigenesis. Many reports indicate that βig-H3 functions as a tumor suppressor. Loss of βig-H3 expression has been described in several cancers including ovarian cancer and promoter hypermethylation has been identified as an important mechanism for the silencing of the TGFBI gene. Our recent findings that βig-H3 is down-regulated in ovarian cancer and that high concentrations of βig-H3 can induce ovarian cancer cell death support a tumor suppressor role. However, there is also convincing data in the literature reporting a tumor-promoting role for βig-H3. We have shown βig-H3 to be abundantly expressed by peritoneal cells and increase the metastatic potential of ovarian cancer cells by promoting cell motility, invasion, and adhesion to peritoneal cells. Our findings suggest that βig-H3 has dual functions and can act both as a tumor suppressor or tumor promoter depending on the tumor microenvironment. This article reviews the current understanding of βig-H3 function in cancer cells with particular focus on ovarian cancer.Miranda P. Ween, Martin K. Oehler and Carmela Ricciardell

Transforming Growth Factor-Beta-Induced Protein (TGFBI)/(βig-H3): A Matrix Protein with Dual Functions in Ovarian Cancer

Transforming growth factor-beta-induced protein (TGFBI, also known as βig-H3 and keratoepithelin) is an extracellular matrix protein that plays a role in a wide range of physiological and pathological conditions including diabetes, corneal dystrophy and tumorigenesis. Many reports indicate that βig-H3 functions as a tumor suppressor. Loss of βig-H3 expression has been described in several cancers including ovarian cancer and promoter hypermethylation has been identified as an important mechanism for the silencing of the TGFBI gene. Our recent findings that βig-H3 is down-regulated in ovarian cancer and that high concentrations of βig-H3 can induce ovarian cancer cell death support a tumor suppressor role. However, there is also convincing data in the literature reporting a tumor-promoting role for βig-H3. We have shown βig-H3 to be abundantly expressed by peritoneal cells and increase the metastatic potential of ovarian cancer cells by promoting cell motility, invasion, and adhesion to peritoneal cells. Our findings suggest that βig-H3 has dual functions and can act both as a tumor suppressor or tumor promoter depending on the tumor microenvironment. This article reviews the current understanding of βig-H3 function in cancer cells with particular focus on ovarian cancer

E-Cigarette Vapour Increases ACE2 and TMPRSS2 Expression in a Flavour- and Nicotine-Dependent Manner

COVID-19 infects via the respiratory system, but it can affect multiple systems and lead to multi system failure. There is growing evidence that smoking may be associated with higher rates of COVID-19 infections and worse outcomes due to increased levels of ACE2 in lung epithelial cells, but it is unknown whether E-cigarette use may lead to increased risk of COVID-19 infection from the SARS-CoV-2 virus. In this study, healthy donor bronchial epithelial cells (NHBE) and monocyte-derived macrophages (MDM) were exposed to cigarette smoke extract (CSE) or nicotine or flavoured E-cigarette vapour extract (EVE) before the assessment of SARS-CoV-2 recognition receptors ACE2 and TMPRSS2 genes. MDMs exposed to CSE and Tobacco EVE showed increased ACE2 expression; however, no treatment altered the TMPRSS2 expression. ACE2 was found to be upregulated by >2-fold in NHBE cells exposed to CSE, as well as nicotine, banana, or chocolate EVE, while TMPRSS2 was only upregulated by CSE or nicotine EVE exposure. These findings suggesting that flavourings can increase ACE2 expression in multiple cell types, while TMPRSS2 expression increases are limited to the epithelial cells in airways and may be limited to nicotine and/or cigarette smoke exposure. Therefore, increased risk of COVID-19 infection cannot be ruled out for vapers

The structure and metal binding properties of Chlamydia trachomatis YtgA

The obligate intracellular pathogen is a globally significant cause of sexually transmitted bacterial infections and the leading etiological agent of preventable blindness. The first-row transition metal iron (Fe) plays critical roles in chlamydial cell biology, and acquisition of this nutrient is essential for the survival and virulence of the pathogen. Nevertheless, how acquires Fe from host cells is not well understood, since it lacks genes encoding known siderophore biosynthetic pathways, receptors for host Fe storage proteins, and the Fe acquisition machinery common to many bacteria. Recent studies have suggested that directly acquires host Fe via the ATP-binding cassette permease YtgABCD. Here, we characterized YtgA, the periplasmic solute binding protein component of the transport pathway, which has been implicated in scavenging Fe(III) ions. The structure of Fe(III)-bound YtgA was determined at 2.0-Å resolution with the bound ion coordinated via a novel geometry (3 Ns, 2 Os [3N2O]). This unusual coordination suggested a highly plastic metal binding site in YtgA capable of interacting with other cations. Biochemical analyses showed that the metal binding site of YtgA was not restricted to interaction with only Fe(III) ions but could bind all transition metal ions examined. However, only Mn(II), Fe(II), and Ni(II) ions bound reversibly to YtgA, with Fe being the most abundant cellular transition metal in Collectively, these findings show that YtgA is the metal-recruiting component of the YtgABCD permease and is most likely involved in the acquisition of Fe(II) and Mn(II) from host cells. is the most common bacterial sexually transmitted infection in developed countries, with an estimated global prevalence of 4.2% in the 15- to 49-year age group. Although infection is asymptomatic in more than 80% of infected women, about 10% of cases result in serious disease. Infection by is dependent on the ability to acquire essential nutrients, such as the transition metal iron, from host cells. In this study, we show that iron is the most abundant transition metal in and report the structural and biochemical properties of the iron-recruiting protein YtgA. Knowledge of the high-resolution structure of YtgA will provide a platform for future structure-based antimicrobial design approaches

Extracellular Zinc Competitively Inhibits Manganese Uptake and Compromises Oxidative Stress Management in <i>Streptococcus pneumoniae</i>

<div><p><i>Streptococcus pneumoniae</i> requires manganese for colonization of the human host, but the underlying molecular basis for this requirement has not been elucidated. Recently, it was shown that zinc could compromise manganese uptake and that zinc levels increased during infection by <i>S. pneumoniae</i> in all the niches that it colonized. Here we show, by quantitative means, that extracellular zinc acts in a dose dependent manner to competitively inhibit manganese uptake by <i>S. pneumoniae</i>, with an EC₅₀ of 30.2 µM for zinc in cation-defined media. By exploiting the ability to directly manipulate <i>S. pneumoniae</i> accumulation of manganese, we analyzed the connection between manganese and superoxide dismutase (SodA), a primary source of protection for <i>S. pneumoniae</i> against oxidative stress. We show that manganese starvation led to a decrease in <i>sodA</i> transcription indicating that expression of <i>sodA</i> was regulated through an unknown manganese responsive pathway. Intriguingly, examination of recombinant SodA revealed that the enzyme was potentially a cambialistic superoxide dismutase with an iron/manganese cofactor. SodA was also shown to provide the majority of protection against oxidative stress as a <i>S. pneumoniae</i> Δ<i>sodA</i> mutant strain was found to be hypersensitive to oxidative stress, despite having wild-type manganese levels, indicating that the metal ion alone was not sufficiently protective. Collectively, these results provide a quantitative assessment of the competitive effect of zinc upon manganese uptake and provide a molecular basis for how extracellular zinc exerts a ‘toxic’ effect on bacterial pathogens, such as <i>S. pneumoniae</i>.</p></div

<i>In vitro S. pneumoniae</i> growth and metal ion accumulation.

<p>(<b>A</b>) Growth curves of <i>S. pneumoniae</i> grown in CDM with the following Zn(II):Mn(II) ratios (in μM): 300:1 (orange line, open diamond), 100:1 (purple, open triangle), 30:1 (red, open square), 10:1 (blue, open inverted triangle), and 1 µM Mn(II) (black, filled circle), respectively. Data are mean (± SEM) absorbance measurements from three independent biological experiments. Error bars, where not visible, are overlapped by the data points. (<b>B</b> and <b>C</b>) <i>S. pneumoniae</i> total cellular accumulation of Mn(II) (B) and Zn(II) (C) determined by ICP-MS of cells grown in following Zn(II):Mn(II) ratios (in μM): 100:1 (purple), 30:1 (red), 10:1 (blue), and 1 µM Mn(II) (black). Data are mean (± SEM) µg metal.g dry cell mass⁻¹ from duplicate measurements of at least 3 independent biological experiments. (D) Growth curves of <i>S. pneumoniae</i> grown in CDM with the following Zn(II):Mn(II) ratios (in µM): 300:300 (orange line, filled diamond), 100:100 (purple, filled triangle), 30:1 (red, filled square), 10:1 (blue, filled inverted triangle), and 1 µM Mn(II) (black, filled circle), respectively. Data are means (± SEM) A₆₀₀ measurements from three independent biological experiments. (<b>E</b> and <b>F</b>) <i>S. pneumoniae</i> total cellular accumulation of Mn(II) (E) and Zn(II) (F) determined by ICP-MS of cells grown in following Zn(II):Mn(II) ratios (in μM): 300:300 (orange), 100:100 (purple), 30:30 (red), 10:10 (blue), and CDM + 1 µM Mn(II) (black). Data are mean (± SEM) µg metal.g dry cell mass⁻¹ from duplicate measurements of at least 3 independent biological experiments. Statistical significance of the differences in the means was determined by a two-tailed unpaired <i>t</i>-test (n.s. corresponds to not significant and **** to <i>P</i> value < 0.0001).</p

rSodA purification and characterization.

<p>(<b>A</b>) Purified rSodA electrophoretically separated on a 12.5% SDS polyacrylamide gel, with the major band stained by PAGE Blue. (<b>B</b>) Determination of the apparent molecular mass of the purified rSodA by gel-permeation chromatography on a Superdex 200 10/300 column. Inset is the linear regression of the protein molecular mass standards used to calibrate the column (carbonic anhydrase  = 29 kDa, bovine serum albumin  = 66 kDa, yeast alcohol dehydrogenase  =  150 kDa, sweet potato β-Amylase  =  200kDa). rSodA eluted with a calculated molecular mass of 60.8 kDa. (<b>C</b>) The SOD activity of apo-rSodA (white) and rSodA loaded with Mn(II) (black) or Fe(II) (light gray) was measured. The data are presented as SOD activity units (U) per µM protein. Data are means (± SEM) of three biological replicates.</p

<i>S. pneumoniae</i> response to oxidative stress.

<p>(<b>A</b>) Paraquat killing of the <i>S. pneumoniae</i> wild-type (D39) and Δ<i>sodA</i> mutant grown in CDM + 1 µM Mn(II) (white), and <i>S. pneumoniae</i> (D39) grown in 100 µM Zn(II):100 µM Mn(II) (black) or 100 µM Zn(II):1 µM Mn(II) (light gray) conditions. Survival was calculated as a percentage of c.f.u. after 30 minutes paraquat challenge compared to 30 minutes without challenge. The experiment was performed with 3 independent biological samples and data are the means (± SEM). The statistical significance of the differences in mean survival was determined by a two-tailed unpaired <i>t</i>-test (n.s. corresponds to not significant, * corresponds to <i>P</i> value < 0.05, and **** P value < 0.0001). (<b>B</b>) <i>S. pneumoniae</i> D39 mRNA transcription levels were examined after growth in CDM + 1 µM Mn(II) or 100 µM Zn(II):1 µM Mn(II). Real-time RT-PCR data for the indicated conditions were normalized against those obtained for the 16S rRNA control. Data are means (± SEM) of at least three biological replicates. The statistical significance of the differences in relative transcription level was determined by a two-tailed unpaired <i>t</i>-test (* corresponds to <i>P</i> value < 0.05, and ** to <i>P</i> value < 0.01). (<b>C</b>) <i>S. pneumoniae</i> D39 (filled) and Δ<i>sodA</i> (open) were grown in CDM supplemented with 1 µM Mn(II) until an A₆₀₀ of 0.3 was reached. Cells were washed in CDM and then inoculated to an A₆₀₀ of 0.05 in CDM consisting of in CDM + 1 µM Mn(II) (circle) or 300 µM Zn(II):1 µM Mn(II) (square). Data are means (± SEM) A₆₀₀ measurements from three independent biological experiments. Error bars, where not visible, are overlapped by the data points.</p

Competitive effect of Zn(II) on metal ion accumulation.

<p>(<b>A</b>) The concentration response curve fitting data for Mn(II) accumulation in <i>S. pneumoniae</i> D39 under extracellular Zn(II) stress. Data were normalized by comparison with non-competitive growth conditions [CDM + 1 µM Mn(II)]. Curve fitting was performed in Graphpad Prism version 5.0d (Graphpad). (<b>B</b>, <b>C</b>, <b>D</b>, and <b>E</b>) <i>S. pneumoniae</i> total cellular accumulation of Fe(II/III) (B), Co(II) (C), Ni(II) (D), and Cu(II) (E), determined by ICP-MS, when grown in CDM supplemented with 1 µM Mn(II), 10 µM Zn(II):1 µM Mn(II), 30 µM Zn(II):1 µM Mn(II), and 100 µM Zn:1 µM Mn. Data are mean (± SEM) µg metal.g dry cell mass⁻¹ measurements from duplicate measurements of at least 3 independent biological experiments. The statistical significance of the differences in concentrations was determined by a two-tailed unpaired <i>t</i>-test (n.s. corresponds to not significant, * to <i>P</i> value < 0.05, and ** to <i>P</i> value < 0.01).</p