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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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467 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PDRG1 predicts a poor prognosis and facilitates the proliferation and metastasis of colorectal cancer

Highlights: • PDRG1 is overexpressed in colorectal cancer tissues and is associated with poor prognosis of colorectal cancer patients. • PDRG1 regulates the proliferation, apoptosis, cell cycle progression and metastasis of colorectal cancer cells. • PDRG1 promotes the proliferation, migration and invasion of colorectal cancer via p21-mediated cell cycle progression. The incidence and mortality of colorectal cancer (CRC) is increasing yearly and CRC patients are becoming younger in global. Evidences have revealed the carcinogenic effect of p53 and DNA damage-regulated gene 1 (PDRG1) in several types of tumors. However, its biological function is yet to be investigated in CRC. This study aimed to unveil the prooncogenic role of PDRG1 in CRC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Ad-apoptin inhibits glycolysis, migration and invasion in lung cancer cells targeting AMPK/mTOR signaling pathway

Ad-apoptin is a recombinant oncolytic adenovirus constructed by our laboratory that can express apoptin. It can selectively kill tumor cells without damaging normal cells. This study investigated the effects of Ad-apoptin on glycolysis, migration and invasion of non-small cell lung cancer. Cell viability and apoptosis were detected by CCK-8 and flow cytometry, respectively. Glycolysis was investigated by glucose consumption, lactic acid production and glycolytic key enzyme protein levels. Migration and invasion were evaluated via wound healing, transwell assays and epithelial-mesenchymal transition (EMT) protein levels. The interaction between apoptin and AMPK was detected by Co-IP. A nude mice tumor model was established to investigate the anti-cancer role of Ad-apoptin in vivo. The results showed that Ad-apoptin inhibits cell viability and induces apoptosis of A549 and NCI–H23 cells. Ad-apoptin can reduce the glucose uptake and lactic production in lung cancer cells, and reduce the expression of related glycolysis-limiting enzymes. At the same time, Ad-apoptin inhibited the migration and invasion of lung cancer. Immunoprecipitation showed that apoptin and AMPK could interact directly. Moreover, knockdown of AMPK significantly attenuated the inhibitory effect of Ad-apoptin on glycolysis, migration and invasion of A549 and NCI–H23 cells. Ad-apoptin can inhibit the growth of tumors in nude mice. Compared with the control group, Ad-apoptin had a significant inhibitory effect on AMPK knockdown tumors. The immunohistochemical results of tumor tissues were consistent with those in vitro. Collectively, Ad-apoptin targets AMPK and inhibits glycolysis, migration and invasion of lung cancer cells through the AMPK/mTOR signaling pathway. This suggests that Ad-apoptin may have therapeutic potential for lung cancer by targeting AMPK activation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

PLEKHA7 signaling is necessary for the growth of mutant KRAS driven colorectal cancer

Plekha7 (Pleckstrin homology [PH] domain containing, family A member 7) regulates the assembly of proteins of the cytoplasmic apical zonula adherens junction (AJ), thus ensuring cell-cell adhesion and tight-junction barrier integrity. Little is known of Plekha7 function in cancer. In colorectal cancer (CRC) Plekha7 expression is elevated compared to adjacent normal tissue levels, increasing with clinical stage. Plekha7 was present at plasma membrane AJ with wild-type KRas (wt-KRas) but was dispersed in cells expressing mutant KRas (mut-KRas). Fluorescence lifetime imaging microscopy (FLIM) indicated a direct Plekha7 interaction with wt-KRas but scantily with mut-KRas. Inhibiting Plekha7 specifically decreased mut-KRas cell signaling, proliferation, attachment, migration, and retarded mut-KRAS CRC tumor growth. Binding of diC8-phosphoinositides (PI) to the PH domain of Plekha7 was relatively low affinity. This may be because a D175 amino acid residue plays a “sentry” role preventing PI(3,4)P{sub 2} and PI(3,4,5)P{sub 3} binding. Molecular or pharmacological inhibition of the Plekha7 PH domain prevented the growth of mut-KRas but not wt-KRas cells. Taken together the studies suggest that Plekha7, in addition to maintaining AJ structure plays a role in mut-KRas signaling and phenotype through interaction of its PH domain with membrane mut-KRas, but not wt-KRas, to increase the efficiency of mut-KRas downstream signaling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Research progress on the mechanism of ferroptosis and its clinical application

Ferroptosis is a mode of cell death dependent on iron ions, which is mainly induced by the decrease of the biological activity of glutathione peroxidase or the accumulation of lipid peroxidation and reactive oxygen species (ROS). It is significantly different from autophagy and other forms of cell death in terms of cell morphology and biochemistry. The exact mechanisms of ferroptosis are not clear. More and more studies have shown that various tumor diseases and nervous system diseases are closely related to ferroptosis. The occurrence and development of related diseases can be tolerated by stimulating or inhibiting the occurrence of ferroptosis. Therefore, ferroptosis has occupied a very important position in recent years. This article reviews the discovery process, characteristics, mechanisms, inducers, inhibitors of ferroptosis and its related clinical applications to lay a foundation for follow-up researchers to study ferroptosis and provide some reference value.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Targeting ROR1 in combination with osimertinib in EGFR mutant lung cancer cells

Highlights: • The role of ROR1 was investigated in EGFR mutant lung cancer cells in vitro. • Cell growth and colony formation were suppressed and apoptosis was increased in cell lines treated with siROR1. • A combination of osimertinib with siROR1 was effective for EGFR mutant cell lines. Lung cancer that exhibits epidermal growth factor receptor (EGFR) gene mutation is sensitive to EGFR-tyrosine kinase inhibitors (TKIs), such as osimertinib. Receptor tyrosine kinase-like orphan receptor 1 (ROR1) may be involved in overcoming EGFR-TKI resistance. Growth inhibition, colony formation, apoptosis, and mRNA/protein levels in four osimertinib-sensitive and resistant cell lines transfected with small interfering RNA (siRNA) targeting ROR1 (siROR1) were evaluated. Cell growth and colony formation were suppressed and apoptosis was increased in all cell lines treated with siROR1. Although EGFR, AKT, and ERK phosphorylation were not suppressed in all cell lines, TGF-β2, AXL, CDH2, PARP1, PEG10, and TYMS mRNA expression levels were reduced. The combination of osimertinib with siROR1 was effective for the four cell lines, particularly in the two osimertinib-sensitive lines. In conclusion, targeting ROR1 in combination with osimertinib in EGFR mutant lung cancer may be a novel therapeutic option.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Prevalence of Americans reporting a family history of cancer indicative of increased cancer risk: Estimates from the 2015 National Health Interview Survey

The collection and evaluation of family health history in a clinical setting presents an opportunity to discuss cancer risk, tailor cancer screening recommendations, and identify people with an increased risk of carrying a pathogenic variant who may benefit from referral to genetic counseling and testing. National recommendations for breast and colorectal cancer screening indicate that men and women who have a first-degree relative affected with these types of cancers may benefit from talking to a healthcare provider about starting screening at an earlier age and other options for cancer prevention. The prevalence of reporting a first-degree relative who had cancer was assessed among adult respondents of the 2015 National Health Interview Survey who had never had cancer themselves (n = 27,999). We found 35.6% of adults reported having at least one first-degree relative with cancer at any site. Significant differences in reporting a family history of cancer were observed by sex, age, race/ethnicity, educational attainment, and census region. Nearly 5% of women under age 50 and 2.5% of adults under age 50 had at least one first-degree relative with breast cancer or colorectal cancer, respectively. We estimated that 5.8% of women had a family history of breast or ovarian cancer that may indicate increased genetic risk. A third of U.S. adults who have never had cancer report a family history of cancer in a first-degree relative. Furthermore, this finding underscores the importance of using family history to inform discussions about cancer risk and screening options between healthcare providers and their patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Heating of aqueous suspensions of silicon nanoparticles by a 808-nm diode laser for application in local photohyperthermia

3D simulation of the distribution of thermal fields in aqueous suspensions of silicon nanoparticles upon irradiation by a high-power 808-nm laser diode operating in cw and quasi-cw repetitively pulsed regimes is performed. It is shown that irradiation by a repetitively pulsed laser with a peak power of 10 W and a pulse duration of 300 ms can form a region with a maximum temperature exceeding 42 °C, which is promising for application in cancer photohyperthermia for local heating of biotissues at a given depth. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Evaluation of temperature changes in a cell culture plate well with absorbing walls containing a 3D model of tumour spheroid under irradiation in the optical range

The temperature conditions for photodynamic therapy of the culture of tumour cells organised in 3D spheroids are studied. The spheroids are placed in the cell culture medium in the well of a special cell culture plate with absorbing walls. A mathematical model is presented that describes the temperature distribution in a well with a cell culture plate heated by optical radiation. It is shown that the temperature in the well volume is not uniformly distributed, and the temperature on the well surface can differ significantly from the temperature in its volume. (laser medicine)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1). To address the critical need for novel therapeutics in MPNST, we aimed to establish an ex vivo 3D platform that accurately captured the genomic diversity of MPNST and could be utilized in a medium-throughput manner for drug screening studies to be validated in vivo using patient-derived xenografts (PDX). Genomic analysis was performed on all PDX-tumor pairs. Selected PDX were harvested for assembly into 3D microtissues. Based on prior work in our labs, we evaluated drugs (trabectedin, olaparib, and mirdametinib) ex vivo and in vivo. For 3D microtissue studies, cell viability was the endpoint as assessed by Zeiss Axio Observer. For PDX drug studies, tumor volume was measured twice weekly. Bulk RNA sequencing was performed to identify pathways enriched in cells. We developed 13 NF1-associated MPNST-PDX and identified mutations or structural abnormalities in NF1 (100%), SUZ12 (85%), EED (15%), TP53 (15%), CDKN2A (85%), and chromosome 8 gain (77%). We successfully assembled PDX into 3D microtissues, categorized as robust (>90% viability at 48 h), good (>50%), or unusable (<50%). We evaluated drug response to “robust” or “good” microtissues, namely MN-2, JH-2-002, JH-2-079-c, and WU-225. Drug response ex vivo predicted drug response in vivo, and enhanced drug effects were observed in select models. These data support the successful establishment of a novel 3D platform for drug discovery and MPNST biology exploration in a system representative of the human condition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4 + and CD8 + T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Differential methods for assessing sensitivity in biological models

Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to determine which method is best suited for a particular model. In this paper, we explain a variety of differential sensitivity methods and assess their value in some typical biological models. First, we explain the mathematical basis for three numerical methods: adjoint sensitivity analysis, complex perturbation sensitivity analysis, and forward mode sensitivity analysis. We then carry out four instructive case studies. (a) The CARRGO model for tumor-immune interaction highlights the additional information that differential sensitivity analysis provides beyond traditional naive sensitivity methods, (b) the deterministic SIR model demonstrates the value of using second-order sensitivity in refining model predictions, (c) the stochastic SIR model shows how differential sensitivity can be attacked in stochastic modeling, and (d) a discrete birth-death-migration model illustrates how the complex perturbation method of differential sensitivity can be generalized to a broader range of biological models. Finally, we compare the speed, accuracy, and ease of use of these methods. We find that forward mode automatic differentiation has the quickest computational time, while the complex perturbation method is the simplest to implement and the most generalizable.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Outgrowth of erlotinib-resistant subpopulations recapitulated in patient-derived lung tumor spheroids and organoids

A model that recapitulates development of acquired therapeutic resistance is needed to improve oncology drug development and patient outcomes. To achieve this end, we established methods for the preparation and growth of spheroids from primary human lung adenocarcinomas, including methods to culture, passage, monitor growth, and evaluate changes in mutational profile over time. Primary lung tumor spheroids were cultured in Matrigel® with varying concentrations of erlotinib, a small molecule kinase inhibitor of epidermal growth factor receptor (EGFR) that is ineffective against KRAS mutant cells. Subtle changes in spheroid size and number were observed within the first two weeks of culture. Spheroids were cultured for up to 24 weeks, during which time interactions between different cell types, movement, and assembly into heterogeneous organoid structures were documented. Allele-specific competitive blocker PCR (ACB-PCR) was used to quantify low frequency BRAF V600E, KRAS G12D, KRAS G12V, and PIK3CA H1047R mutant subpopulations in tumor tissue residue (TR) samples and cultured spheroids. Mutant subpopulations, including multiple mutant subpopulations, were quite prevalent. Twelve examples of mutant enrichment were found in eight of the 14 tumors analyzed, based on the criteria that a statistically-significant increase in mutant fraction was observed relative to both the TR and the no-erlotinib control. Of the mutants quantified in erlotinib-treated cultures, PIK3CA H1047 mutant subpopulations increased most often (5/14 tumors), which is consistent with clinical observations. Thus, this ex vivo lung tumor spheroid model replicates the cellular and mutational tumor heterogeneity of human lung adenocarcinomas and can be used to assess the outgrowth of mutant subpopulations. Spheroid cultures with characterized mutant subpopulations could be used to investigate the efficacy of lung cancer combination therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improving five-year survival prediction via multitask learning across HPV-related cancers

Oncology is a highly siloed field of research in which sub-disciplinary specialization has limited the amount of information shared between researchers of distinct cancer types. This can be attributed to legitimate differences in the physiology and carcinogenesis of cancers affecting distinct anatomical sites. However, underlying processes that are shared across seemingly disparate cancers probably affect prognosis. The objective of the current study is to investigate whether multitask learning improves 5-year survival cancer patient survival prediction by leveraging information across anatomically distinct HPV related cancers. Furthermore, data were obtained from the Surveillance, Epidemiology, and End Results (SEER) program database. The study cohort consisted of 29,768 primary cancer cases diagnosed in the United States between 2004 and 2015. Ten different cancer diagnoses were selected, all with a known association with HPV risk. In the analysis, the cancer diagnoses were categorized into three distinct topography groups of varying specificity. The most specific topography grouping consisted of 10 original cancer diagnoses differentiated by the first two digits of the ICD-O-3 topography code. The second topography grouping consisted of cancer diagnoses categorized into six distinct organ groups. Finally, the third topography grouping consisted of just two groups, head-neck cancers and ano-genital cancers. The tasks were to predict 5-year survival for patients within the different topography groups using 14 predictive features which were selected among descriptive variables available in the SEER database. The information from the predictive features was shared between tasks in three different ways, resulting in three distinct predictive models: 1) Information was not shared between patients assigned to different tasks (single task learning); 2) Information was shared between all patients, regardless of task (pooled model); 3) Only relevant information was shared between patients grouped to different tasks (multitask learning). Prediction performance was evaluated with Brier scores. All three models were evaluated against one another on each of the three distinct topography-defined tasks. The results showed that multitask classifiers achieved relative improvement for the majority of the scenarios studied compared to single task learning and pooled baseline methods. In this study, we have demonstrated that sharing information among anatomically distinct cancer types can lead to improved predictive survival models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cancer survival in the United States 2007–2016: Results from the National Program of Cancer Registries

Background Cancer survival has improved for the most common cancers. However, less improvement and lower survival has been observed in some groups perhaps due to differential access to cancer care including prevention, screening, diagnosis, and treatment. Methods To further understand contemporary relative cancer survival (one- and five- year), we used survival data from CDC’s National Program of Cancer Registries (NPCR) for cancers diagnosed during 2007–2016. We examined overall relative cancer survival by sex, race and ethnicity, age, and county-level metropolitan and non-metropolitan status. Relative cancer survival by metropolitan and non-metropolitan status was further examined by sex, race and ethnicity, age, and cancer type. Results Among persons with cancer diagnosed during 2007–2016 the overall one-year and five-year relative survival was 80.6% and 67.4%, respectively. One-year relative survival for persons living in metropolitan counties was 81.1% and 77.8% among persons living in non-metropolitan counties. We found that persons who lived in non-metropolitan counties had lower survival than those who lived in metropolitan counties, and this difference persisted across sex, race and ethnicity, age, and most cancer types. Conclusion Further examination of the differences in cancer survival by cancer type or other characteristics might be helpful for identifying potential interventions, such as programs that target screening and early detection or strategies to improve access to high quality cancer treatment and follow-up care, that could improve long-term outcomes. Impact This analysis provided a high-level overview of contemporary cancer survival in the United States.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Helix-Loop-Helix motif of human EIF3A regulates translation of proliferative cellular mRNAs

Improper regulation of translation initiation, a vital checkpoint of protein synthesis in the cell, has been linked to a number of cancers. Overexpression of protein subunits of eukaryotic translation initiation factor 3 (eIF3) is associated with increased translation of mRNAs involved in cell proliferation. In addition to playing a major role in general translation initiation by serving as a scaffold for the assembly of translation initiation complexes, eIF3 regulates translation of specific cellular mRNAs and viral RNAs. Mutations in the N-terminal Helix-Loop-Helix (HLH) RNA-binding motif of the EIF3A subunit interfere with Hepatitis C Virus Internal Ribosome Entry Site (IRES) mediated translation initiation in vitro . Here we show that the EIF3A HLH motif controls translation of a small set of cellular transcripts enriched in oncogenic mRNAs, including MYC . We demonstrate that the HLH motif of EIF3A acts specifically on the 5' UTR of MYC mRNA and modulates the function of EIF4A1 on select transcripts during translation initiation. In Ramos lymphoma cell lines, which are dependent on MYC overexpression, mutations in the HLH motif greatly reduce MYC expression, impede proliferation and sensitize cells to anti-cancer compounds. These results reveal the potential of the EIF3A HLH motif in eIF3 as a promising chemotherapeutic target.

59 BASIC BIOLOGICAL SCIENCES↗