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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Manufacturing control systems and logic for prognosis of defects in composite materials

Presented are manufacturing control systems for composite-material structures, methods for assembling/operating such systems, and transfer molding techniques for predicting and ameliorating void conditions in fiber-reinforced polymer panels. A method for forming a composite-material construction includes receiving a start signal indicating a fiber-based preform is inside a mold cavity, and transmitting a command signal to inject pressurized resin into the mold to induce resin flow within the mold cavity and impregnate the fiber-based preform. An electronic controller receives, from a distributed array of sensors attached to the mold, signals indicative of pressure and/or temperature at discrete locations on an interior face of the mold cavity. The controller determines a measurement deviation between a calibrated baseline value and the pressure and/or temperature values for each of the discrete locations. If any one of the respective measurement deviations exceeds a calibrated threshold, a void signal is generated to flag a detected void condition.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Prognostic importance of the preoperative New‐Naples prognostic score for patients with gastric cancer

Abstract Background The wide applicability of the Naples prognostic score (NPS) is still worthy of further study in gastric cancer (GC). This study aimed to construct a New‐NPS based on the differences in immunity and nutrition in patients with upper and lower gastrointestinal tumors to help obtain an individualized prediction of prognosis. Methods This study retrospectively analyzed patients who underwent radical gastrectomy from April 2014 to September 2016. The cutoff values of the preoperative neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), serum albumin (Alb), and total cholesterol (TC) were calculated by ROC curve analysis. ROC and t‐ROC were used to evaluate the accuracy of the prognostic markers. The Kaplan–Meier method and log‐rank test were used to analyze the overall survival probability. Univariate and multivariate analyses based on Cox risk regression were used to show the independent predictors. The nomogram was made by R studio. The predictive accuracy of nomogram was assessed using a calibration plot, concordance index (C‐index), and decision curve. Results A total of 737 patients were included in training cohort, 411 patients were included in validation cohort. ROC showed that the New‐NPS was more suitable for predicting the prognosis of GC patients. NPS = 2 indicated a poor prognosis. Multivariate analysis showed that CEA ( P = 0.026), Borrmann type ( P = 0.001), pTNM ( P < 0.001), New‐NPS ( P < 0.001), and nerve infiltration ( P = 0.035) were independent risk factors for prognosis. Conclusion The New‐NPS based on the cutoff values of NLR, LMR, Alb, and TC is not only suitable for predicting prognosis but can also be combined with clinicopathological characteristics to construct a nomogram model for GC patients.

Wang, Hao↗
DOE OSTI2021

sMicroRNA-28-5p acts as a metastasis suppressor in gastric cancer by targeting Nrf2

The transcription factor nuclear factor (erythroid-2)-related factor 2 (Nrf2) can principally serve a mode of protection for both the normal cells and cancer cells from cellular stress, and elevates cancer cell survival. microRNA-28 (miR-28) has been involved in the regulation of Nrf2 expression in breast epithelial cells. However, no comprehensive analysis has been conducted regarding the function of miR-28-5p regulating Nrf2 in gastric cancer (GC). In this study, we aimed to evaluate their interaction and biological roles in the migration and invasion of GC cells. The expression of Nrf2 in the cancer tissues harvested from 42 patients with GC was examined by an array of molecular techniques comprising of Immunohistochemical staining, RT-qPCR and Western blot analysis. Kaplan-Meier method was adopted for analysis of the correlation of Nrf2 with the prognosis of GC patients. Interaction between miR-28-5p and Nrf2 was determined using the bioinformatics analysis and dual luciferase reporter gene assay. Gain- and loss-of-function studies of miR-28-5p and Nrf2 were conducted to elucidate their effects on GC cell migration, invasion and metastasis, as well as expression pattern of several epithelial-mesenchymal transition (EMT)-related proteins. Results indicated that the expression pattern of Nrf2 was significantly upregulated in GC tissues and indicative of poor prognosis of GC patients. miR-28-5p was verified to target Nrf2 and downregulate its expression. GC cells with overexpression of miR-28-5p or Nrf2 knockdown exhibited a marked reduction in the migrated and invasive abilities, along with the N-cadherin expression yet an increase of E-cadherin expression. Furthermore, miR-28-5p exerted an inhibitory function on the metastatic and tumorigenicity of GC cells. In conclusion, miR-28-5p is a comprehensive tumor suppressor that inhibits GC cell migration and invasion through repressing the Nrf2 expression. Therefore, miR-28-5p may serve as a potential biomarker for the prognosis of GC and a novel therapeutic target in advanced GC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

DYNC1H1 regulates NSCLC cell growth and metastasis by IFN-γ-JAK-STAT signaling and is associated with an aberrant immune response

Highlights: • DYNC1H1 is upregulated and its high expression predicted poor outcomes in NSCLC. • Loss of function of DYNC1H1 inhibits cell growth and metastasis of NSCLC cells in vitro. • DYNC1H1 knockdown inhibited metastasis of NSCLC cells in vivo. • DYNC1H1 loss of function suppresses IFN-γ-JAK-STAT signaling pathway in NSCLC. • DYNC1H1 expression is correlated with aberrant immune response in NSCLC indicated by analysis of TCGA immune data. It is urgent to identify new biomarkers and therapeutic targets to ameliorate the clinical prognosis of patients with lung cancer. The functional significance and molecular mechanism of dynein cytoplasmic 1 heavy chain 1 (DYNC1H1) in nonsmall cell lung cancer (NSCLC) progression is still elusive. In our current study, publicly available data and Western blotting experiments confirmed that DYNC1H1 expression was upregulated in lung cancer samples compared with noncancerous samples. Quantitative real-time PCR (qPCR) results indicated that high DYNC1H1 expression in lung cancer tissues was significantly associated with clinical tumor stage and distal metastasis; moreover, its high expression was negatively correlated with prognosis. Functional experiments demonstrated that DYNC1H1 loss of function caused a significant decrease in cell viability and cell proliferative ability, inhibition of the cell cycle, and promotion of both migration potential and invasion potential in vitro. Animal experiments by tail vein injection of lung cancer cells showed that DYNC1H1 knockdown significantly decreased lung cancer metastasis. Mechanistically, the results from a human protein array showed changes in the IFN-γ-JAK-STAT signaling pathway, and analysis of The Cancer Genome Atlas (TCGA) immune data demonstrated that disturbance of the immune microenvironment might be involved in the impaired growth and metastatic ability mediated by DYNC1H1 loss in NSCLC. DYNC1H1 might serve as a promising biological marker of prognosis and a potential clinical therapeutic target for patients with NSCLC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements

Here, this study presents a novel approach for the precise monitoring and prognosis of photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems. It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability of inverters, and the limitations of data-driven approaches that largely depend on simulated data. This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and weather-related factors based on domain knowledge. This approach effectively represents inverter stressors and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges operational data with domain knowledge features, redefining the prognosis challenge as a classification task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method developed on the well-trained model. The proposed models are rigorously trained and tested with real inverter data and a novel filtering method is included to address accidental failures in practical scenarios. The results validate the model's efficacy, and the directions for future research are also outlined.

42 ENGINEERING↗
DOE OSTI2021

Memory-Related Frontal Brainwaves Predict Transition to Mild Cognitive Impairment in Healthy Older Individuals Five Years Before Diagnosis

Background: Early prognosis of high-risk older adults for amnestic mild cognitive impairment (aMCI), using noninvasive and sensitive neuromarkers, is key for early prevention of Alzheimer’s disease. We have developed individualized measures in electrophysiological brain signals during working memory that distinguish patients with aMCI from age-matched cognitively intact older individuals. Objective: Here we test longitudinally the prognosis of the baseline neuromarkers for aMCI risk. We hypothesized that the older individuals diagnosed with incident aMCI already have aMCI-like brain signatures years before diagnosis. Methods: Electroencephalogram (EEG) and memory performance were recorded during a working memory task at baseline. The individualized baseline neuromarkers, annual cognitive status, and longitudinal changes in memory recall scores up to 10 years were analyzed. Results: Seven of the 19 cognitively normal older adults were diagnosed with incident aMCI for a median 5.2 years later. The seven converters’ frontal brainwaves were statistically identical to those patients with diagnosed aMCI (n = 14) at baseline. Importantly, the converters’ baseline memory-related brainwaves (reduced mean frontal responses to memory targets) were significantly different from those who remained normal. Furthermore, differentiation pattern of left frontal memory-related responses (targets versus nontargets) was associated with an increased risk hazard of aMCI (HR = 1.47, 95% CI 1.03, 2.08). Conclusion: The memory-related neuromarkers detect MCI-like brain signatures about five years before diagnosis. The individualized frontal neuromarkers index increased MCI risk at baseline. These noninvasive neuromarkers during our Bluegrass memory task have great potential to be used repeatedly for individualized prognosis of MCI risk and progression before clinical diagnosis.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Integrated Diagnostics and Prognostics for the Electrical Power System of a Planetary Rover

For electric vehicles, technology for monitoring, diagnosis, and prognosis of the electrical power system (EPS) becomes essential for safe and efficient operation. To this end, we develop a general system-level integrated diagnosis and prognosis framework, which detects, isolates, and identifies EPS faults, and predicts when the EPS will fail to deliver sufficient power. The approach takes advantage of recent work in structural model decomposition in order to distribute the global diagnosis and prognosis problems into local subproblems that can be solved in parallel, thus enabling implementation on distributed computational platforms. The framework is applied to the EPS of a planetary rover testbed, and is demonstrated using data from field experiments.

Daigle, Matthew↗
DOE OSTI2024

NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence

Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment. We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H’s (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels. We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPH ErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression. The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Enhancing the Operational Resilience of Advanced Reactors with Digital Twins by Recurrent Neural Networks

Because of a lack of operational data and uncertainty in evaluation model for abnormal and accident scenarios, the established operating procedures can be biased in characterizing the reactor states and ensuring operational resilience. To reduce uncertainty associated with actual plant conditions, digital twin (DT) technology is suggested to support operator’s decision-making by effectively extracting and using knowledge of the current and future plant states from the knowledge base. This study first builds a knowledge base based on the characterization of issue space and the simulation tool. Next, this study discusses diagnosis and prognosis DTs for enhancing operational resilience by recovering the complete states of reactors and by predicting the future reactor behaviors. Finally, the decision-making module of the control system can determine the optimal control strategy that meets operational goals during loss-of-flow scenarios. To demonstrate and evaluate the DTs capability for supporting the operations of nuclear reactors, this study develops and assesses both the diagnosis and prognosis DTs in a nearly autonomous management and control system for an Experimental Breeder Reactor-II simulator during different loss-of-flow scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Hydrogen Component Leak Rate Quantification for System Risk and Reliability Assessment through QRA and PHM Frameworks: Preprint

The National Renewable Energy Laboratory's (NREL) Hydrogen Safety Research and Development (HSR&D) program in collaboration with the University of Maryland's Systems Risk and Reliability Analysis Laboratory (SyRRA) are working to improve reliability and reduce risk in hydrogen systems. This approach strives to use quantitative data on component leaks and failures, together with Prognosis and Health Management (PHM), and Quantitative Risk Assessment (QRA) to identify at-risk components, reduce component failures and downtime, and predict when components require maintenance. Hydrogen component failures increase facility maintenance cost, facility downtime, and reduce public acceptance of hydrogen technologies, ultimately increasing facility size and cost because of potentially overly conservative requirements. Leaks are a predominant failure mode for hydrogen components. However, uncertainties in the amount of hydrogen emitted from leaking components and the frequency of those failure events limit the understanding of the risks that they present under real-world operational conditions. NREL has deployed a test fixture, the Leak Rate Quantification Apparatus (LRQA), to quantify the mass flow rate of leaking gases from medium and high-pressure components that have failed while in service. Quantitative hydrogen leak rate data from this system could ultimately be used to better inform risk assessment and Regulation Codes and Standards (RCS). Parallel activity explores the use of PHM and QRA techniques to assess and reduce risk, thereby improving safety and reliability of hydrogen systems. The results of QRAs could further provide a systematic and science-based foundation for the design and implementation of RCS, as in the latest versions of the NFPA 2 code for gaseous hydrogen stations. Alternatively, data-driven techniques of PHM could provide new damage diagnosis and health-state prognosis tools. This research will help end users, station owners and operators, and regulatory bodies move towards risk-informed preventative maintenance versus emergency corrective maintenance, reducing cost and improving reliability. Predictive modelling of failures could improve safety and affect RCS requirements such as setback distances at liquid refuelling sites. The combination of leak rate quantification research, PHM, and QRA can lead to better informed models enabling data-based decision to be made for hydrogen system safety improvements.

codes and standards↗
DOE OSTI2021

HPRT promotes proliferation and metastasis in head and neck squamous cell carcinoma through direct interaction with STAT3

Highlights: • The higher expression of HPRT in HNSCC tissue was related to poor prognosis of patients. • Overexpression of HPRT increased the gene expression of epithelial mesenchymal transition markers. • HPRT directly interacted with STAT3. • Knocking down HPRT significantly decreased tumour growth and enhanced the anticancer effect against HNSCC xenografts. Increasing effort has been put into finding novel molecular pathways to improve the efficiency of EGFR inhibitors against head and neck squamous cell cancer (HNSCC). In this study, we performed data mining and bioinformatically analysed RNA-Seq data downloaded from TCGA and confirmed that higher expression of HPRT in HNSCC tissue was related to poor prognosis of patients. Then, we conducted in vitro and in vivo loss- and gain-of-function experiments to demonstrate the role of HPRT in HNSCC cell lines. Overexpression of HPRT increased the gene expression of epithelial mesenchymal transition markers via direct interaction with STAT3. Knocking down HPRT significantly decreased tumour growth and enhanced the anticancer effect of EGFR inhibitors against HNSCC xenografts. In conclusion, HPRT is a binding partner of STAT3 that promotes EMT and proliferation. Our findings support HPRT as a promising prognostic indicator and potential therapeutic target for HNSCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

AFF4 facilitates melanoma cell progression by regulating c-Jun activity

Melanoma is characterized by high mortality and poor prognosis due to metastasis. AFF4 (AF4/FMR2 family member 4), as a scaffold protein, is a component of the super elongation complex (SEC), and is involved in the progression of tumors, e.g., leukemia, head and neck squamous cell carcinoma (HNSCC). However, few studies on AFF4 have focused on melanoma. Here, AFF4 expression levels and clinicopathological features were evaluated in melanoma tissue samples. Then, we performed cell proliferation, migration and invasion assays in A375 and A2058 cells lines in vitro to evaluate the role of AFF4 in melanoma. The effects of AFF4 knockdown in vivo were characterized via a xenograft mouse model. Finally, the correlation between c-Jun and AFF4 protein levels in melanoma was analyzed by rescue assay and immunohistochemistry (IHC). We found that AFF4 expression was upregulated in melanoma tumor tissues and that AFF4 protein expression was also closely related to the prognosis of patients with cutaneous melanoma. Moreover, AFF4 could promote the invasion and migration of melanoma cells by mediating epithelial to mesenchymal transition (EMT). AFF4 might regulate c-Jun activity to promote the invasion and migration of melanoma cells. Importantly, c-Jun was regulated by the AFF4 promoted melanoma tumorigenesis in vivo. Taken together, AFF4 may be a novel oncogene that promotes melanoma progression through regulation of c-Jun activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Deubiquitinating enzyme USP46 suppresses the progression of hepatocellular carcinoma by stabilizing MST1

Highlights: • Low USP46 level is correlated with poor prognosis in HCC. • USP46 suppresses the proliferation and metastasis of HCC. • USP46 suppress the progression of HCC by inhibiting the expression of YAP1. • MST1 mediates the regulation of USP46 on YAP1. • USP46 stabilized MST1 protein through inhibiting its ubiquitination and degradation. The deubiquitinating enzyme USP46 (ubiquitin-specific protease 46) is implicated in various cancers. However, its role and regulatory mechanism in HCC (hepatocellular carcinoma) are still unknown. In this study, we showed that USP46 is downregulated in HCC tissues and that low USP46 levels are associated with poor prognosis in HCC patients. In functional experiments, overexpression of USP46 impaired proliferation and metastasis of HCC cells, whereas knockdown of USP46 enhanced cell proliferation and invasiveness in vitro and in vivo. Furthermore, we found that USP46 suppresses HCC cell proliferation and metastasis by inhibiting YAP1. Ectopic expression of YAP1 rescued the inhibition of cell proliferation and metastasis caused by USP46 overexpression. Mechanistically, USP46 promotes the degradation of YAP1 by increasing expression of MST1, and the increase in MST1 protein antagonizes YAP1 to suppress HCC progression. Finally, we demonstrated that USP46 stabilizes the MST1 protein by directly binding to it and decreasing its ubiquitination. Taken together, our results demonstrated that USP46 may be a novel tumor suppressor in HCC. Moreover, USP46 acts as a deubiquitinating enzyme of MST1 to potentiate MST1 kinase activity to suppress tumor growth and metastasis, indicating that USP46 activation may represent a potential treatment strategy for HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

T-lymphoma invasion and metastasis 1 promotes invadopodia formation and is regulated by the PI3K/Akt signaling pathway in hepatocellular carcinoma

Highlights: • High Tiam1 expression in HCC is related to the poor prognosis after surgery. • Tiam1 promotes invadopodia formation in HCC cells. • Tiam1-mediated invadopodia formation is regulated by the PI3K/Akt pathway. • PIP2 is an important factor in Tiam1-mediated invadopodia formation. At present, there are still many poorly understood aspects of the mechanisms underlying hepatocellular carcinoma (HCC) invasion and metastasis. Invadopodia are important structures for cancer cell invasion and metastasis. We determined that high T-lymphoma invasion and metastasis 1 (Tiam1) expression is associated with HCC invasion and metastasis and poor patient prognosis after surgery. Gain- and loss-of-function studies confirmed that Tiam1 promotes invadopodia formation in HCC by activating Rac1. A series of biochemical experiments confirmed that this effect is regulated by the PI3K/Akt signaling pathway. We also confirmed that PIP2 facilitates this effect. In summary, these findings reveal that Tiam1 plays an important role in invadopodia formation in HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

INTS6 promotes colorectal cancer progression by activating of AKT and ERK signaling

Highlights: • INTS6 is upregulated in colorectal cancer and correlated with poor prognosis. • INTS6 promotes the growth of colorectal cancer cells in vitro and in vivo. • INTS6 affects the cell cycle distribution of colorectal cancer cells. • INTS6 activates the AKT and ERK signaling in colorectal cancer. INTS6 (integrator complex subunit 6) has been reported as a tumor suppressor in many cancers. However, the expression and biological function of INTS6 in colorectal cancer (CRC) has not been investigated yet. In this study, we found that INTS6 expression was significantly increased in CRC tissues when compared with normal tissues and was associated with poor prognosis. Downregulation of INTS6 induced G1/S-phase cell cycle arrest, and markedly suppressed the growth of CRC cells and the derived tumors, while overexpression of INTS6 showed opposite effect. Mechanism study revealed that INTS6 increased the levels of phosphorylated AKT (p-AKT) and ERK (p-ERK), and the growth-promoting effect of INTS6 was inhibited by AKT and ERK inhibitors. Besides, INTS6 also affected the expression of two targets of PI3K/AKT and MAPK signaling, c-Myc and CDK2, which contributed to cell cycle alteration. Altogether, the present study has revealed the oncogenic role of INTS6 in CRC, providing a novel therapeutic target for this malignant cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Abstract Maintenance optimization is a process for improving the efficiency of maintenance strategies and activities, considering various aspects of the target system and components, such as the probabilities of system failures and the cost of repair and replacement of a failed component. The improvement of maintenance optimization algorithms generally requires information from various data sources. For example, it may require the system risk information derived from risk analysis tools or the residual lifetime of a component from fault prognosis tools. The requirements of data acquisition (DAQ) and aggregation pose new challenges for maintenance management systems (MMSs) that implement and use these maintenance optimization algorithms. This paper proposes a multiple aspects maintenance ontology-based framework to facilitate DAQ from MMSs, online monitoring systems, fault detection and discrimination tools, risk assessment tools, decision-making tools, and component identification tools, and accelerate the implementation and verification of contemporary maintenance optimization models and algorithms. The proposed framework consists of a multi-aspect maintenance ontology with critical information for maintenance optimization and application interfaces for collecting information from various data sources, such as fault prognosis tools, online monitoring tools, risk assessment tools, and decision-making algorithms. In addition, this paper proposes a heuristic method for integrating concepts and properties from other existing ontologies into the proposed framework when the existing ontology is not fully compatible with the ontology under construction. Finally, the paper verifies the proposed ontology framework using a feedwater system designed for nuclear power plants with valves and filters as the components under maintenance.

Diao, Xiaoxu (ORCID:0000000346726352)↗
DOE OSTI2024

Steroid responsiveness in alcohol-associated hepatitis is linked to glucocorticoid metabolism, mitochondrial repair, and heat shock proteins

Alcohol-associated hepatitis (AH) is one of the clinical presentations of alcohol-associated liver disease. AH has poor prognosis, and corticosteroids remain the mainstay of drug therapy. However, ~40% of patients do not respond to this treatment, and the mechanisms underlying the altered response to corticosteroids are not understood. The current study aimed to identify changes in hepatic protein expression associated with responsiveness to corticosteroids and prognosis in patients with AH. Patients with AH were enrolled based on the National Institute on Alcohol Abuse and Alcoholism inclusion criteria for acute AH and further confirmed by a diagnostic liver biopsy. Proteomic analysis was conducted on liver samples acquired from patients with AH grouped as nonresponders (AH-NR, n = 7) and responders (AH-R, n = 14) to corticosteroids, and nonalcohol-associated liver disease controls (n = 10). The definition of responders was based on the clinical prognostic model, the Lille Score, where a score < 0.45 classified patients as AH-R and a score > 0.45 as AH-NR. Primary outcomes used to assess steroid response were Lille Score (eg, improved liver function) and survival at 24 weeks. Reduced levels of the glucocorticoid receptor and its transcriptional co-activator, glucocorticoid modulatory element-binding protein 2, were observed in the hepatic proteome of AH-NR versus AH-R. The corticosteroid metabolizing enzyme, 11-beta-hydroxysteroid dehydrogenase 1, was increased in AH-NR versus AH-R along with elevated mitochondrial DNA repair enzymes, while several proteins of the heat shock pathway were reduced. Analysis of differentially expressed proteins in AH-NR who survived 24 weeks relative to AH-NR nonsurvivors revealed several protein expression changes, including increased levels of acute phase proteins, elevated coagulation factors, and reduced mast cell markers. This study identified hepatic proteomic changes that may predict responsiveness to corticosteroids and mortality in patients with AH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In search of autophagy biomarkers in breast cancer: Receptor status and drug agnostic transcriptional changes during autophagy flux in cell lines

Autophagy drives drug resistance and drug-induced cancer cell cytotoxicity. Targeting the autophagy process could greatly improve chemotherapy outcomes. The discovery of specific inhibitors or activators has been hindered by challenges with reliably measuring autophagy levels in a clinical setting. We investigated drug-induced autophagy in breast cancer cell lines with differing ER/PR/Her2 receptor status by exposing them to known but divergent autophagy inducers each with a unique molecular target, tamoxifen, trastuzumab, bortezomib or rapamycin. Differential gene expression analysis from total RNA extracted during the earliest sign of autophagy flux showed both cell- and drug-specific changes. We analyzed the list of differentially expressed genes to find a common, cell- and drug-agnostic autophagy signature. Twelve mRNAs were significantly modulated by all the drugs and 11 were orthogonally verified with Q-RT-PCR (Klhl24, Hbp1, Crebrf, Ypel2, Fbxo32, Gdf15, Cdc25a, Ddit4, Psat1, Cd22, Ypel3). The drug agnostic mRNA signature was similarly induced by a mitochondrially targeted agent, MitoQ. In-silico analysis on the KM-plotter cancer database showed that the levels of these mRNAs are detectable in human samples and associated with breast cancer prognosis outcomes of Relapse-Free Survival in all patients (RSF), Overall Survival in all patients (OS), and Relapse-Free Survival in ER + Patients (RSF ER + ). High levels of Klhl24, Hbp1, Crebrf, Ypel2, CD22 and Ypel3 were correlated with better outcomes, whereas lower levels of Gdf15, Cdc25a, Ddit4 and Psat1 were associated with better prognosis in breast cancer patients. This gene signature uncovers candidate autophagy biomarkers that could be tested during preclinical and clinical studies to monitor the autophagy process.

60 APPLIED LIFE SCIENCES↗