Novel Survivin Inhibitor for Suppressing Pancreatic Cancer Cells Growth via Downregulating Sp1 and Sp3 Transciption Factors

Background/Aims: Targeting survivin, an anti-apoptotic protein and mitotic regulator, is considered as an effective therapeutic option for pancreatic cancer (PaCa). Tolfenamic acid (TA) showed anti-cancer activity in pre-clinical studies. A recent discovery demonstrated a copper(II) complex of TA (Cu-TA) can result in higher activity. In this study, the ability of Cu-TA to inhibit survivin and its transcription factors, Specificity protein (Sp) 1 and 3 in PaCa cell lines and tumor growth in mouse xenograft model were evaluated. Methods: Cell growth inhibition was measured in MIA PaCa-2 and Panc1 cells for 2 days using CellTiter-Glo kit. Sp1, Sp3 and survivin expression (by Western blot and qPCR), apoptotic cells and cell cycle phase distribution (by flow cytometry) were evaluated. A pilot study was performed using athymic nude mice [treated with vehicle/Cu-TA (25 or 50 mg/kg) 3 times/week for 4 weeks. Results: The IC50 value for Cu-TA was about half than TA. Both agents repressed the protein expression of Sp1/Sp3/survivin, Cu-TA was more effective than TA. Especially effect on survivin inhibition was 5.2 (MIA PaCa-2) or 6.4 (Panc1) fold higher and mRNA expression of only survivin was decreased. Apoptotic cells increased with Cu-TA treatment in both cell lines, while Panc1 showed both effect on apoptosis and cell cycle (G2/M) arrest. Cu-TA decreased the tumor growth in mouse xenografts (25 mg/kg: 48%; 50 mg/kg: 68%). Additionally, there was no change observed in mice body weights, indicating no overt toxicity was occurring. Conclusion: These results show that Cu-TA can serve as an effective survivin inhibitor for inhibiting PaCa cell growth

Novel Survivin Inhibitor for Suppressing Pancreatic Cancer Cells Growth via Downregulating Sp1 and Sp3 Transcription Factors

Background/Aims: Targeting survivin, an anti-apoptotic protein and mitotic regulator, is considered as an effective therapeutic option for pancreatic cancer (PaCa). Tolfenamic acid (TA) showed anti-cancer activity in pre-clinical studies. A recent discovery demonstrated a copper(II) complex of TA (Cu-TA) can result in higher activity. In this study, the ability of Cu-TA to inhibit survivin and its transcription factors, Specificity protein (Sp) 1 and 3 in PaCa cell lines and tumor growth in mouse xenograft model were evaluated. Methods: Cell growth inhibition was measured in MIA PaCa-2 and Panc1 cells for 2 days using CellTiter-Glo kit. Sp1, Sp3 and survivin expression (by Western blot and qPCR), apoptotic cells and cell cycle phase distribution (by flow cytometry) were evaluated. A pilot study was performed using athymic nude mice [treated with vehicle/Cu-TA (25 or 50 mg/kg) 3 times/week for 4 weeks. Results: The IC50 value for Cu-TA was about half than TA.Both agents repressed the protein expression of Sp1/Sp3/survivin, Cu-TA was more effective than TA. Especially effect on survivin inhibition was 5.2 (MIA PaCa-2) or 6.4 (Panc1) fold higher and mRNA expression of only survivin was decreased. Apoptotic cells increased with Cu-TA treatment in both cell lines, while Panc1 showed both effect on apoptosis and cell cycle (G2/M) arrest. Cu-TA decreased the tumor growth in mouse xenografts (25 mg/kg: 48%; 50 mg/kg: 68%). Additionally, there was no change observed in mice body weights, indicating no overt toxicity was occurring. Conclusion: These results show that Cu-TA can serve as an effective survivin inhibitor for inhibiting PaCa cell growth

Tamoxifen-associated vasculitis in a breast cancer patient

BACKGROUND: Estrogen plays a critical role in breast cancer. Thereafter, endocrine therapy is a standard of care in patients with breast carcinoma, expressing ER or PR. CASE PRESENTATION: Herein we report the case of a 53-year old patient, who developed cholestasis and vasculitis during the treatment with tamoxifen. This toxicity was reversable after the removal of the drug. Thereafter she continued adjuvant treatment for breast carcinoma with anastrazole. Since tamoxifen has been widely indicated for patients with breast carcinoma, we did a literature review, looking for other cases with this type of toxicity. CONCLUSION: This case is the third with vasculitis informed in the literature, but the first one that additionally developed cholestasis and arthritis. Although it is rare, we discuss the indication of this drug in the actual era, where aromatase inhibitors offer a better security profile

Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records

Abstract Background Prostate cancer (PCa) screening is not routinely conducted in men aged 55 and younger, although this age group accounts for more than 10% of cases. Polygenic risk scores (PRSs) and patient data applied toward early prediction of PCa may lead to earlier interventions and increased survival. We have developed machine learning (ML) models to predict PCa risk in men 55 and under using PRSs combined with patient data. Methods We conducted a retrospective study on 91,106 male patients aged 35–55 using the UK Biobank database. Five gradient boosting models were developed and validated utilizing routine screening data, PRSs, additional clinical data, or combinations of the three. Results Combinations of PRSs and patient data outperformed models that utilized PRS or patient data only, and the highest performing models achieved an area under the receiver operating characteristic curve of 0.788. Our models demonstrated a substantially lower false positive rate (35.4%) in comparison to standard screening using prostate‐specific antigen (60%–67%). Conclusion This study provides the first preliminary evidence for the use of PRSs with patient data in a ML algorithm for PCa risk prediction in men aged 55 and under for whom screening is not standard practice

Tamoxifen-associated vasculitis in a breast cancer patient

Abstract Background Estrogen plays a critical role in breast cancer. Thereafter, endocrine therapy is a standard of care in patients with breast carcinoma, expressing ER or PR. Case presentation Herein we report the case of a 53-year old patient, who developed cholestasis and vasculitis during the treatment with tamoxifen. This toxicity was reversable after the removal of the drug. Thereafter she continued adjuvant treatment for breast carcinoma with anastrazole. Since tamoxifen has been widely indicated for patients with breast carcinoma, we did a literature review, looking for other cases with this type of toxicity. Conclusion This case is the third with vasculitis informed in the literature, but the first one that additionally developed cholestasis and arthritis. Although it is rare, we discuss the indication of this drug in the actual era, where aromatase inhibitors offer a better security profile.</p

Deletion of indoleamine 2,3 dioxygenase (Ido)1 but not Ido2 exacerbates disease symptoms of MOG35-55-induced experimental autoimmune encephalomyelitis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) with pathological features of inflammation, demyelination, and neurodegeneration. Several lines of evidence suggest that the enzymes indoleamine 2,3-dioxygenase (Ido)1 and/or Ido2 influences susceptibility to autoimmune diseases. Deletion of Ido1 exacerbates experimental autoimmune encephalomyelitis (EAE) an animal model of MS. However, no data exist on the role of Ido2 in the pathogenesis of EAE. We investigated whether deletion of Ido2 affected the pathogenesis of EAE. Temporal expression of interferon gamma (Ifng), Ido1 variants, Ido2 variants, as well as genes encoding enzymes of the kynurenine pathway in the spleen and spinal cord of C57BL/6 mice with or without EAE were determined by RT-qPCR. Moreover, EAE was induced in C57BL/6, two Ido1 knockout strains (Ido1KO and Ido1TK) and one Ido2 knockout mouse strain (Ido2−/−) and disease monitored by clinical scores and weight change. Performance on the rotarod was performed on days 0, 5, 10 and 15 post induction. The extent of demyelination in the spinal cord was determined after staining with Oil red O. The development of EAE altered gene expression in both the spleen and spinal cord. Deletion of Ido1 exacerbated the clinical symptoms of EAE. In stark contrast, EAE in Ido2−/− mice did not differ clinically or histologically from control mice. These results confirm a protective role for Ido1, on the pathogenesis of MOG35-55-induced EAE in C57BL/6J mice

Predicting Falls in Long-term Care Facilities: Machine Learning Study

BackgroundShort-term fall prediction models that use electronic health records (EHRs) may enable the implementation of dynamic care practices that specifically address changes in individualized fall risk within senior care facilities. ObjectiveThe aim of this study is to implement machine learning (ML) algorithms that use EHR data to predict a 3-month fall risk in residents from a variety of senior care facilities providing different levels of care. MethodsThis retrospective study obtained EHR data (2007-2021) from Juniper Communities’ proprietary database of 2785 individuals primarily residing in skilled nursing facilities, independent living facilities, and assisted living facilities across the United States. We assessed the performance of 3 ML-based fall prediction models and the Juniper Communities’ fall risk assessment. Additional analyses were conducted to examine how changes in the input features, training data sets, and prediction windows affected the performance of these models. ResultsThe Extreme Gradient Boosting model exhibited the highest performance, with an area under the receiver operating characteristic curve of 0.846 (95% CI 0.794-0.894), specificity of 0.848, diagnostic odds ratio of 13.40, and sensitivity of 0.706, while achieving the best trade-off in balancing true positive and negative rates. The number of active medications was the most significant feature associated with fall risk, followed by a resident’s number of active diseases and several variables associated with vital signs, including diastolic blood pressure and changes in weight and respiratory rates. The combination of vital signs with traditional risk factors as input features achieved higher prediction accuracy than using either group of features alone. ConclusionsThis study shows that the Extreme Gradient Boosting technique can use a large number of features from EHR data to make short-term fall predictions with a better performance than that of conventional fall risk assessments and other ML models. The integration of routinely collected EHR data, particularly vital signs, into fall prediction models may generate more accurate fall risk surveillance than models without vital signs. Our data support the use of ML models for dynamic, cost-effective, and automated fall predictions in different types of senior care facilities