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

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.

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

BACKGROUND: Short-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. OBJECTIVE: The 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. METHODS: This 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. RESULTS: The 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. CONCLUSIONS: This 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.

Prediction of diabetic kidney disease with machine learning algorithms, upon the initial diagnosis of type 2 diabetes mellitus.

INTRODUCTION: Diabetic kidney disease (DKD) accounts for the majority of increased risk of mortality for patients with diabetes, and eventually manifests in approximately half of those patients diagnosed with type 2 diabetes mellitus (T2DM). Although increased screening frequency can avoid delayed diagnoses, this is not uniformly implemented. The purpose of this study was to develop and retrospectively validate a machine learning algorithm (MLA) that predicts stages of DKD within 5 years upon diagnosis of T2DM. RESEARCH DESIGN AND METHODS: Two MLAs were trained to predict stages of DKD severity, and compared with the Centers for Disease Control and Prevention (CDC) risk score to evaluate performance. The models were validated on a hold-out test set as well as an external dataset sourced from separate facilities. RESULTS: The MLAs outperformed the CDC risk score in both the hold-out test and external datasets. Our algorithms achieved an area under the receiver operating characteristic curve (AUROC) of 0.75 on the hold-out set for prediction of any-stage DKD and an AUROC of over 0.82 for more severe endpoints, compared with the CDC risk score with an AUROC <0.70 on all test sets and endpoints. CONCLUSION: This retrospective study shows that an MLA can provide timely predictions of DKD among patients with recently diagnosed T2DM.

Next generation sequencing and functional pathway analysis to understand the mechanism of action of copper-tolfenamic acid against pancreatic cancer cells.

Anti-cancer activity of tolfenamic acid (TA) in preclinical models for pancreatic cancer (PaCa) is well established. Since the dosage for anti-cancer actions of TA is rather high, we recently demonstrated that IC50 values of Copper-TA are 30-80% less than TA in 12 cancer cell lines. This study elucidates the underlying mechanisms of Copper-TA in PaCa cells. Control and Copper-TA (IC50) treated PaCa cells were processed by next-generation sequencing (NGS) to determine differentially expressed genes using HTG EdgeSeq Oncology Biomarker panel. Ingenuity Pathway Analysis (IPA®) was used to identify functional significance of altered genes. The conformational studies for assessing the expression of key regulators and genes were conducted by Western blot and qPCR. IPA® identified several networks, regulators, as well as molecular and cellular functions associated with cancer. The top 5 molecular and cellular functions affected by Cu-TA treatment were cell death and survival, cellular development, cell growth and proliferation, cell cycle and cellular movement. The expression of top upstream regulators was confirmed by Western blot analysis while qPCR results of selected genes demonstrated that Copper-TA is efficacious at lower doses than TA. Results suggest that Copper-TA alters genes/key regulators associated with cancer and potentially serve as an effective anti-cancer agent.

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.

Combination of clotam and vincristine enhances anti-proliferative effect in medulloblastoma cells.

Medulloblastoma (MB) is characterized by highly invasive embryonal neuro-epithelial tumors that metastasize via cerebrospinal fluid. MB is difficult to treat and the chemotherapy is associated with significant toxicities and potential long-term disabilities. Previously, we showed that small molecule, clotam (tolfenamic acid: TA) inhibited MB cell proliferation and tumor growth in mice by targeting, survivin. Overexpression of survivin is associated with aggressiveness and poor prognosis in several cancers, including MB. The aim of this study was to test combination treatment involving Vincristine® (VCR), a standard chemotherapeutic drug for MB and TA against MB cells. DAOY and D283 MB cells were treated with 10 µg/mL TA or VCR (DAOY: 2 ng/mL; D283: 1 ng/mL) or combination (TA + VCR). These optimized doses were lower than individual IC50 values. The effect of single or combination treatment on cell viability (CellTiterGlo kit), Combination Index (Chou-Talalay method based on median-drug effect analysis), activation of apoptosis and cell cycle modulation (by flow cytometry using Annexin V and propidium iodide respectively) and the expression of associated markers including survivin (Western immunoblot) were determined. Combination Index showed moderate synergistic cytotoxic effect in both cells. When compared to individual agents, the combination of TA and VCR increased MB cell growth inhibition, induced apoptosis and caused cell cycle (G2/M phase) arrest. Survivin expression was also decreased by the combination treatment. TA is effective for inducing the anti-proliferative response of VCR in MB cells. MB has four distinct genetic/molecular subgroups. Experiments were conducted with MB cells representing two subgroups (DAOY: SHH group; D283: group 4/3). TA-induced inhibition of survivin expression potentially destabilizes mitotic microtubule assembly, sensitizing MB cells and enhancing the efficacy of VCR.

Copper-tolfenamic acid: evaluation of stability and anti-cancer activity.

The non-steroidal anti-inflammatory drug, Tolfenamic acid (TA) acts as an anti-cancer agent in several adult and pediatric cancer models. Copper (Cu) is an important element with multiple biological functions and has gained interest in medical applications. Recently, [Cu(TA)2(bpy)] (Cu-TA) has been synthesized in order to enhance therapeutic activity. In this study, we synthesized Cu-TA using an established method, characterized it by UV visible spectroscopy and Fourier-transform infrared spectroscopy (FTIR), and tested its anti-cancer activity using twelve cell lines representing various cancers, such as Ewing sarcoma, glioblastoma, medulloblastoma, neuroblastoma, pancreatic and prostate. The anti-proliferative activity of Cu-TA was determined at 48 h post-treatment and compared with the parental compound, TA. The IC50 values were calculated using GraphPad Prism software. The biological stability of Cu-TA was evaluated using twelve-month-old powder and six-month-old stock solution. Cardiomyocytes (H9C2) were used to test the cytotoxicity in non-malignant cells. Cu-TA showed higher anti-proliferative activity, and the IC50 values were 30 to 80% lower when compared with TA. H9C2 cells were non-responsive to Cu-TA, suggesting that it is selective towards malignant cells. Comparison of the twelve-month-old powder and six-month-old stock solution using the Panc1 cell line showed similar IC50 values (<5% variation), confirming the stability of Cu-TA either in powder or solution form. These findings demonstrate the potential of Cu-TA as an effective anti-cancer agent. Further studies to delineate the detailed mechanism of action of Cu-TA for specific cancer model are underway.

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.

Investigational agents to enhance the efficacy of chemotherapy or radiation in pancreatic cancer.

Pancreatic cancer (PC) continues to be a fatal malignancy. With standard treatments having modest impact, alternative courses of actions are being investigated such as enhancing the efficacy of standard treatment through sensitization of PC cells to chemotherapy or radiation. This review emphasizes investigational agents that increase the responses to chemotherapy or radiation in PC models. Our group has extensively investigated on Curcumin (Cur), analogs (EF31, UBS109, and L49H37), nanoparticles and a small molecule Tolfenamic acid (TA) for enhancing therapeutic efficacy in both in vitro and in vivo assays. Cur has a low level of toxicity and promising anti-cancer activity, however, its clinical development has been limited by low bioavailability. Cur analogs and nanoparticles were synthesized to improve Cur's efficacy and bioavailability. These compounds were found to be effective in enhancing the therapeutic effects of chemotherapy in pre-clinical models. Small molecules such as NSAIDs have also been tested for the anti-cancer activity and induction of response of chemotherapy and radiation. Interest in TA, a NSAID, has recently increased due to promising preclinical data demonstrating its anti-cancer properties with minimum toxicity. TA also synergistically increased the response of XRT in PC cells and in an orthotropic mouse model. With strong preclinical evidence, research aimed at developing less toxic therapies for PC using Cur analogues or TA is ready for translation into clinical testing.

Tolfenamic acid-induced alterations in genes and pathways in pancreatic cancer cells.

Non-steroidal anti-inflammatory drugs (NSAIDs) are being tested extensively for their role in the treatment and prevention of several cancers. Typically NSAIDs exhibit anti-tumor activities via modulation of cyclooxygenase (COX)-dependent mechanisms, however, an anti-cancer NSAID tolfenamic acid (TA) is believed to work through COX-independent pathways. Results from our laboratory and others have demonstrated the anti-cancer activity of TA in various cancer models including pancreatic cancer. TA has been shown to modulate certain cellular processes including, apoptosis, reactive oxygen species and signaling. In this study, molecular profiling was performed to precisely understand the mode of action of TA. Three pancreatic cancer cell lines, L3.6pl, MIA PaCa-2, and Panc1 were treated with TA (50 µM for 48 h) and the changes in gene expression was evaluated using the Affymetrix GeneChip Human Gene ST Array platform. Microarray results were further validated using quantitative PCR for seven genes altered by TA treatment in all three cell lines. Functional analysis of differentially expressed genes (2 fold increase or decrease, p < 0.05) using Ingenuity Pathway Analysis software, revealed that TA treatment predominantly affected the genes involved in cell cycle, cell growth and proliferation, and cell death and survival. Promoter analysis of the differentially expressed genes revealed that they are enriched for Sp1 binding sites, suggesting that Sp1 could be a major contributor in mediating the effect of TA. The gene expression studies identified new targets involved in TA's mode of action, while supporting the hypothesis about the association of Sp1 in TA mediated effects in pancreatic cancer.

Combination of tolfenamic acid and curcumin induces colon cancer cell growth inhibition through modulating specific transcription factors and reactive oxygen species.

Curcumin (Cur) has been extensively studied in several types of malignancies including colorectal cancer (CRC); however its clinical application is greatly affected by low bioavailability. Several strategies to improve the therapeutic response of Cur are being pursued, including its combination with small molecules and drugs. We investigated the therapeutic efficacy of Cur in combination with the small molecule tolfenamic acid (TA) in CRC cell lines. TA has been shown to inhibit the growth of human cancer cells in vitro and in vivo, via targeting the transcription factor specificity protein1 (Sp1) and suppressing survivin expression. CRC cell lines HCT116 and HT29 were treated with TA and/or Cur and cell viability was measured 24-72 hours post-treatment. While both agents caused a steady reduction in cell viability, following a clear dose/ time-dependent response, the combination of TA+Cur showed higher growth inhibition when compared to either single agent. Effects on apoptosis were determined using flow cytometry (JC-1 staining to measure mitochondrial membrane potential), Western blot analysis (c-PARP expression) and caspase 3/7 activity. Reactive oxygen species (ROS) levels were measured by flow cytometry and the translocation of NF-kB into the nucleus was determined using immunofluorescence. Results showed that apoptotic markers and ROS activity were significantly upregulated following combination treatment, when compared to the individual agents. This was accompanied by decreased expression of Sp1, survivin and NF-kB translocation. The combination of TA+Cur was more effective in HCT116 cells than HT29 cells. These results demonstrate that TA may enhance the anti-proliferative efficacy of Cur in CRC cells.