Prognostic role of excision repair cross complementing-1 and topoisomerase-1 expression in epithelial ovarian cancer

Topoisomerase 1 inhibition modulates pyroptosis to improve recovery after spinal cord injury

Excessive neuroinflammation and neuronal loss contribute to mechanisms of spinal cord injury (SCI). Accumulating evidence has suggested that topoisomerase 1 (Top1) inhibition can suppress exacerbated immune responses and protect against lethal inflammation. Pyroptosis is a recently identified pro-inflammatory programmed mode of cell death. However, the effects and underlying mechanisms of Top1 inhibition in SCI remains unclear. Locomotor functional recovery in mice was evaluated through Basso Mouse Scale (BMS). Neuronal loss was evaluated by immunochemistry staining of NeuN. Pyroptosis was determined by immunofluorescence staining, western blot, flow cytometry, cell viability, and cytotoxicity assays. In the present study, we estimated the effects of chemical inhibition of Top1 in an SCI model. Administration of Top1 inhibitor camptothecin (CPT) to mice significantly improved locomotor functional recovery after SCI. Moreover, CPT reduced Top1 level, inhibited nucleotide-binding oligomerization domain-like receptor 3 (NLRP3) inflammasome activation and pyroptosis, attenuated proinflammatory cytokines levels, diminished the number of neutrophil and neuronal loss in mice. Furthermore, CPT in oxygen-glucose deprivation neurons down-regulated Top1 level, attenuated NLRP3 inflammasome activation, and suppressed pyroptosis and inflammatory response. Together, our findings indicate that inhibition of Top1 with CPT can inhibit pyroptosis, control neuroinflammation, and improve functional recovery after SCI.

Dichotomous role of microtubule associated protein tau as a biomarker of response to and a target for increasing efficacy of taxane treatment in cancers of epithelial origin

Cancer is the second leading cause of death worldwide, and the World Health Organization estimates that one in six deaths globally is due to cancer. Chemotherapy is one of the major modalities used to treat advanced cancers and their metastasis. However, the existence of acquired and intrinsic resistance to anti-cancer drugs often diminishes their therapeutic effect. In order to pre-select patients who could benefit the most from these treatments, the efforts of many research groups have been focused on identification of biomarkers of therapy response. Taxanes paclitaxel (Taxol) and docetaxel (Taxotere) have been introduced as chemotherapy for treatment of cancers of ovary in 1992 and breast in 1996, respectively. Since then, clinical use of taxanes has expanded to include lung, prostate, gastric, head and neck, esophageal, pancreatic, and cervical cancers, as well as Kaposi sarcoma. Several independent molecular mechanisms have been shown to support taxane chemoresistance. One such mechanism is dependent on microtubule associated protein tau. Tau binds to the same site on the inner side of the microtubules that is also occupied by paclitaxel or docetaxel, and several studies have demonstrated that low/no tau expression significantly correlated with better response to the taxane treatment, suggesting that levels of tau expression could have a predictive value in pre-selecting patient cohorts that are likely to benefit from the treatment. However, several other studies have found no correlation between tau expression and taxane response, introducing a controversy and precluding its wide use as a predictive biomarker. Based on the knowledge of tau biology accumulated thus far, in this review we attempt to critically analyze the studies that evaluated tau as a biomarker of taxane response. Further, we identify yet unknown aspects of tau biology understanding of which is necessary for improvement of development of tau as a biomarker of response and a target for increasing response to taxane treatment.

HIF Inactivation of p53 in Ovarian Cancer Can Be Reversed by Topotecan, Restoring Cisplatin and Paclitaxel Sensitivity

Ovarian cancer growth under hypoxic conditions results in hypoxia-inducible factor-1α (HIF1α) stabilization. HIF1α is an adverse prognostic factor that may contribute to worse outcomes via its capacity to bind to p53, potentially blocking p53-mediated apoptosis. We determined whether HIF1α-p53 binding occurred in hypoxic ovarian cancer cell lines, and if this blocked p53 transcriptional activity. Topotecan (TPT), used in the treatment of ovarian cancer, inhibits HIF1α translation via a topoisomerase-1 (TOPO1)-dependent mechanism. We examined if TPT knockdown of HIF1α restored p53 transcriptional function. TPT effects on HIF1α and p53-related transcriptional targets were assessed by PCR. Associations between TPT effects and TOPO1 expression levels were examined by Western blots and knockdown by siRNA. RNA-binding protein immunoprecipitation was used to assess if TOPO1 was resident on HIF1α mRNA. We determined if sublethal doses of TPT, used to knockdown HIF1α, reversed hypoxia-related cisplatin and paclitaxel resistance (XTT assay). Flow cytometry was used to assess HIF1α-mediated upregulation of ABCB1 and ABCB5 efflux pump expression. We found that HIF1α binding to, and inhibition of, p53 transcriptional activity in hypoxic ovarian cancer cells was associated with drug resistance. TPT-mediated downregulation of HIF1α in hypoxic cells required TOPO1 resident on HIF1α mRNA, restored p53 transcriptional activity, downregulated ABCB1/ABCB5 cell surface expression, and reversed hypoxia-related cisplatin and paclitaxel resistance. IMPLICATIONS: TPT-mediated reduction of HIF1α accumulation in hypoxic ovarian cancer cell lines restores p53 tumor-suppressor function, offering a novel approach to reverse chemoresistance. Further clinical investigation is warranted.

Gene set-based analysis of mucinous ovarian carcinoma

OBJECTIVE

Mucinous ovarian carcinoma (MOC) is an uncommon subtype of epithelial ovarian cancers, and the pathogenesis is still poorly understood because of its rarity. We conducted a gene set-based analysis to investigate the pathogenesis of MOC by integrating microarray gene expression datasets based on the regularity of functions defined by gene ontology or canonical pathway databases.

MATERIALS AND METHODS

Forty-five pairs of MOC and normal ovarian tissue sample gene expression profiles were downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. The gene expression profiles were converted to the gene set regularity indexes by measuring the change of gene expression ordering in a gene set. Then the pathogenesis of MOC was investigated with the differences of function regularity with the gene set regularity indexes between the MOC and normal control samples.

RESULTS

The informativeness of the gene set regularity indexes was sufficient for machine learning to accurately recognize and classify the functional regulation patterns with an accuracy of 99.44%. The statistical analysis revealed that the GTPase regulators and receptor tyrosine kinase erbB-2 (ERBB2) were the most important aberrations; the exploratory factor analysis revealed phosphoinositide 3-kinase-activating kinase, G-protein coupled receptor pathway, oxidoreductase activity, immune response, peptidase activity, regulation of translation, and transport and channel activity were also involved in the pathogenesis of MOC.

CONCLUSION

Investigating the pathogenesis of MOC with the functionome provided a comprehensive view of the deregulated functions of this disease. In addition to GTPase regulators and ERBB2, a plenty of deregulated functions such as phosphoinositide 3-kinase, G-protein coupled receptor pathway, and immune response also participated in the interaction network of MOC pathogenesis.