Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Cancer”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Emerging roles of circular RNAs in thyroid cancer

As the most common endocrine-related malignant tumor, the prevalence of thyroid cancer (TC) has soared strikingly over the past thirty years then verged to stabilization or even descension temporally. Distributed in a cell-specific manner, circular RNAs (circRNAs) is a novel class of non-coding RNAs characterized by its covalently closed loop without 5′-terminal cap and 3′-terminal poly A tail, which guarantee its distinctive evolutionary conservation and exonucleases resistance. Emerging evidence indicates that circRNA participates in the pathogenesis and carcinogenesis of several cancers including thyroid cancer. In this review, we concentrated on the connection between circRNAs and thyroid cancer so as to obtain a more profound understanding. We aim to discuss this relationship between TC and circRNAs by summarizing the effect of various circRNAs on tumor biological behaviors and clinical application, and systematically outlook the conceivable application of circRNAs in TC diagnosis and therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

In vitro assessment of a synergistic combination of gemcitabine and zebularine in pancreatic cancer cells

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers with an extremely poor prognosis. Gemcitabine (Gem) is still the mainstay drug for the treatment of PDAC. However, rapid inactivation by cytidine deaminase (CDA) present in pancreatic cancer cells severely limits anticancer efficacy of Gem. In this study, we investigated the effect of a CDA inhibitor - Zebularine (Zeb) on anticancer activity of Gem in pancreatic cancer cell lines MiaPaCa-2, BxPC-3, and Panc-1. Zeb treatment synergistically increased Gem-induced cytotoxicity in all three pancreatic cancer cell lines. The strongest synergistic activity was found at 1:10 M ratio of Gem/Zeb (combination index 0.04–0.4). Additionally, Gem + Zeb treated cells showed marked decreased in the expressions of anti-apoptotic protein including Bcl-2 and survivin while significantly increased the cleaved caspase-3, and loss of mitochondrial membrane potential was observed. Multicellular 3D spheroids of MiaPaCa-2 cells treated with combination showed significant reduction (25–60%) in spheroid size, weight compared to single drug and control group. Live/dead cell imaging showed that Gem + Zeb treated spheroids exhibited a highly distorted surface with significantly higher number of dead cells (red). The results of the present study confirm that this synergistic combination is worthy of future investigations as a potential approach for the treatment of PDAC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

TRIM16 overexpression inhibits the metastasis of colorectal cancer through mediating Snail degradation

Highlights: • TRIM16 does significantly inhibit CRC cell migration and metastasis. • TRIM16 negatively regulates CRC cells EMT. • TRIM16 directly interacts with Snail. • TRIM16 promotes degradation of Snail via ubiquition proteasome pathway. Tripartite motif containing 16 (TRIM16) is a member of the tripartite motif protein family and functions as a potential tumor suppressor in several cancers. However, the specific function and clinical significance of TRIM16 in colorectal cancer (CRC) remains unclear. In this study, we observed that low TRIM16 expression was detected frequently in primary colorectal cancer (CRC) tissues and was closely associated with a better prognosis. Functional studies demonstrate that TRIM16 overexpression notably inhibits the metastasis abilities of CRC in vivo and in vitro. Mechanistically, our results demonstrated that TRIM16 directly bound and ubiquitinated Snail family transcriptional repressor 1 (Snail), an important transcriptional factor of the epithelial-mesenchymal transition (EMT) process suppressing the EMT in CRC. Additionally, our data revealed that the inhibition effect of TRIM16 on cancer metastasis was dependent on Snail degradation. Collectively, our study is the first to report that TRIM16 plays a crucial anti-tumor role in CRC tumorigenesis. We also provided novel evidence that TRIM16 might act as a prognostic and therapeutic target to assess and inhibit CRC progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Serum amyloid A1: Innocent bystander or active participant in cell migration in triple-negative breast cancer?

Highlights: • SAA1 knockdown reduced cell viability in triple-negative breast cancer cells. • SAA1 knockdown induced a S to G{sub 2}/M cell cycle shift in MDA-MB-231 cells. • SAA1 silencing inhibited cell migration in MDA-MB-231 and HCC70 cells. • SAA1 silencing altered epithelial-to-mesenchymal transition markers in MDA-MB-231 cells. The Serum Amyloid A (SAA) family of proteins is associated with various pathological conditions, including cancer. However, their role in cancer is incompletely understood. Here, we investigated the role of SAA1 in cell cycle regulation, apoptosis, survival signaling, metabolism, and metastasis in models of triple-negative breast cancer (TNBC), using RNAi. Our data show that in untransformed epithelial cells (MCF12A), the knockdown of SAA1 induces the expression of cell cycle regulators (MCM2, p53), the activation of DNA repair (PARP synthesis), and survival signaling (NFκB). In contrast, knockdown of SAA1 in the TNBC cell line (MDA-MB-231) induced the expression p16 and shifted cells in the cell cycle from the S to G{sub 2}/M phase, without the activation of DNA repair. Moreover, in SAA1-deficient MDA-MB-231 and HCC70 cells, metabolism (NADH oxidation) continually increased while cell migration (% wound closure and the rate of wound closure) decreased. However, silencing of SAA1 altered epithelial and mesenchymal markers in MCF12A (E-cadherin, Laminin 1β, Vimentin) and MDA-MB-231 (α-Smooth muscle actin) cells, associated with the metastatic program of epithelial-mesenchymal transition. Nonetheless, our data provide evidence that SAA1 could potentially serve as a therapeutic target in TNBC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

CPT2 downregulation triggers stemness and oxaliplatin resistance in colorectal cancer via activating the ROS/Wnt/β-catenin-induced glycolytic metabolism

Highlights: • CPT2 was downregulated in CRC. • CPT2 suppressed the proliferation and glycolytic metabolism in CRC cells. • CPT2 inhibited cancer stem cell properties and oxaliplatin resistance in CRC. • CPT2 attenuated CRC tumor growth and enhanced oxaliplatin sensitivity in vivo. • CPT2 functioned via suppressing ROS/Wnt/β-catenin pathway in CRC. Carnitine palmitoyltransferase 2 (CPT2) has been demonstrated to act as a tumor promotor or suppressor in different types of cancers. However, little is known about the effect of CPT2 on colorectal cancer (CRC). In the present study, we analyzed CPT2 expression in CRC tissues and cells. CPT2 was overexpressed in CRC cell lines (SW480 and RKO), and its effects and molecular mechanism on the proliferation, glycolysis, stemness, and oxaliplatin sensitivity were investigated. The xenograft experiment was used to confirm the influence of CPT2 on CRC tumorigenesis in vivo. We found that CPT2 expression was significantly downregulated in CRC patients, and its lower expression was associated with the poor prognosis, large tumor size, advanced TNM stage, and poor histological grade differentiation of patients. Upregulation of CPT2 significantly inhibited the proliferation, glycolytic metabolism, cancer stem cell properties, and oxaliplatin resistance in CRC cells. Also, the increase of CPT2 inhibited tumorigenesis, stemness and glycolysis, while enhanced oxaliplatin sensitivity in mouse models. Mechanistically, CPT2 functioned via suppressing the activation of Wnt/β-catenin pathway through repressing ROS production. In conclusion, our results demonstrated that CPT2 was decreased in CRC, and CPT2 downregulation could trigger stemness and oxaliplatin resistance in CRC via activating the ROS/Wnt/β-catenin-induced glycolytic metabolism. This study indicates that CPT2 is a potential therapeutic target for CRC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Ultra-thermostable RNA nanoparticles for solubilizing and high-yield loading of paclitaxel for breast cancer therapy

Paclitaxel is widely used in cancer treatments, but poor water-solubility and toxicity raise serious concerns. Here we report an RNA four-way junction nanoparticle with ultra-thermodynamic stability to solubilize and load paclitaxel for targeted cancer therapy. Each RNA nanoparticle covalently loads twenty-four paclitaxel molecules as a prodrug. The RNA-paclitaxel complex is structurally rigid and stable, demonstrated by the sub-nanometer resolution imaging of cryo-EM. Using RNA nanoparticles as carriers increases the water-solubility of paclitaxel by 32,000-fold. Intravenous injections of RNA-paclitaxel nanoparticles with specific cancer-targeting ligand dramatically inhibit breast cancer growth, with nearly undetectable toxicity and immune responses in mice. No fatalities are observed at a paclitaxel dose equal to the reported LD 50 . The use of ultra-thermostable RNA nanoparticles to deliver chemical prodrugs addresses issues with RNA unfolding and nanoparticle dissociation after high-density drug loading. This finding provides a stable nano-platform for chemo-drug delivery as well as an efficient method to solubilize hydrophobic drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

RAD51C-XRCC3 structure and cancer patient mutations define DNA replication roles

$RAD51C$ is an enigmatic predisposition gene for breast, ovarian, and prostate cancer. Currently, missing structural and related functional understanding limits patient mutation interpretation to homology-directed repair (HDR) function analysis. Here we report the RAD51C-XRCC3 (CX3) X-ray co-crystal structure with bound ATP analog and define separable RAD51C replication stability roles informed by its three-dimensional structure, assembly, and unappreciated polymerization motif. Mapping of cancer patient mutations as a functional guide confirms ATP-binding matching RAD51 recombinase yet highlights distinct CX3 interfaces. Analyses of CRISPR/Cas9-edited human cells with $RAD51C$ mutations combined with single-molecule, single-cell and biophysics measurements uncover discrete CX3 regions for DNA replication fork protection, restart and reversal, accomplished by separable functions in DNA binding and implied 5’ RAD51 filament capping. Collective findings establish CX3 as a cancer-relevant replication stress response complex, show how HDR-proficient variants could contribute to tumor development, and identify regions to aid functional testing and classification of cancer mutations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A cross-study analysis of drug response prediction in cancer cell lines

Abstract To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm development efforts have relied on cross-validation within a single study to assess model accuracy. While an essential first step, cross-validation within a biological data set typically provides an overly optimistic estimate of the prediction performance on independent test sets. To provide a more rigorous assessment of model generalizability between different studies, we use machine learning to analyze five publicly available cell line-based data sets: National Cancer Institute 60, ancer Therapeutics Response Portal (CTRP), Genomics of Drug Sensitivity in Cancer, Cancer Cell Line Encyclopedia and Genentech Cell Line Screening Initiative (gCSI). Based on observed experimental variability across studies, we explore estimates of prediction upper bounds. We report performance results of a variety of machine learning models, with a multitasking deep neural network achieving the best cross-study generalizability. By multiple measures, models trained on CTRP yield the most accurate predictions on the remaining testing data, and gCSI is the most predictable among the cell line data sets included in this study. With these experiments and further simulations on partial data, two lessons emerge: (1) differences in viability assays can limit model generalizability across studies and (2) drug diversity, more than tumor diversity, is crucial for raising model generalizability in preclinical screening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Epidemiological Studies of Low-Dose Ionizing Radiation and Cancer: Rationale and Framework for the Monograph and Overview of Eligible Studies

Abstract Whether low-dose ionizing radiation can cause cancer is a critical and long-debated question in radiation protection. Since the Biological Effects of Ionizing Radiation report by the National Academies in 2006, new publications from large, well-powered epidemiological studies of low doses have reported positive dose-response relationships. It has been suggested, however, that biases could explain these findings. We conducted a systematic review of epidemiological studies with mean doses less than 100 mGy published 2006–2017. We required individualized doses and dose-response estimates with confidence intervals. We identified 26 eligible studies (eight environmental, four medical, and 14 occupational), including 91 000 solid cancers and 13 000 leukemias. Mean doses ranged from 0.1 to 82 mGy. The excess relative risk at 100 mGy was positive for 16 of 22 solid cancer studies and 17 of 20 leukemia studies. The aim of this monograph was to systematically review the potential biases in these studies (including dose uncertainty, confounding, and outcome misclassification) and to assess whether the subset of minimally biased studies provides evidence for cancer risks from low-dose radiation. Here, we describe the framework for the systematic bias review and provide an overview of the eligible studies.

Berrington de Gonzalez, Amy↗
DOE OSTI2020

Beyond regulations at DNA levels: A review of epigenetic therapeutics targeting cancer stem cells

Abstract In the past few years, the paramount role of cancer stem cells (CSCs), in terms of cancer initiation, proliferation, metastasis, invasion and chemoresistance, has been revealed by accumulating studies. However, this level of cellular plasticity cannot be entirely explained by genetic mutations. Research on epigenetic modifications as a complementary explanation for the properties of CSCs has been increasing over the past several years. Notably, therapeutic strategies are currently being developed in an effort to reverse aberrant epigenetic alterations using specific chemical inhibitors. In this review, we summarize the current understanding of CSCs and their role in cancer progression, and provide an overview of epigenetic alterations seen in CSCs. Importantly, we focus on primary cancer therapies that target the epigenetic modification of CSCs by the use of specific chemical inhibitors, such as histone deacetylase (HDAC) inhibitors, DNA methyltransferase (DNMT) inhibitors and microRNA‐based (miRNA‐based) therapeutics.

Zhang, Shunhao↗
DOE OSTI2022

Longitudinal Trajectories of Memory Performance in Patients with Early-Stage Breast Cancer

Background. While breast cancer and its treatments may affect cognition, the longitudinal trajectories of cognition among those receiving differing cancer treatment types remain poorly understood. Prior research suggests hippocampal-prefrontal cortex network integrity may influence cognition, although how this network predicts performance over time remains unclear. Methods. We conducted a prospective trial including 69 patients with early-stage breast cancer receiving adjuvant therapy and 12 controls. Longitudinal cognitive testing was conducted at four visits: pretreatment-baseline, 6-7 months, 14-15 months, and 23-24 months. Cognitive composite scores of episodic memory, executive functioning, and processing speed were assessed at each timepoint. Baseline structural MRI was obtained in a subset of these participants, and hippocampal and prefrontal cortex regional volumes were extracted. Results. Longitudinal linear mixed modeling revealed significant group by time interactions on memory performance, controlling for age and education. Post hoc analyses revealed this effect was driven by patients treated with chemotherapy or chemotherapy plus hormone therapy, who demonstrated the least improvement in memory scores over time. Treatment group did not significantly influence the relationship between time and processing speed or executive functioning. Neither pretreatment hippocampal nor prefrontal volume differed between groups, and there were no significant group by time by baseline regional volume effects on cognition. Conclusion. Patients with early-stage breast cancer treated with chemotherapy or chemotherapy plus hormone therapy benefit less from practice effects seen in healthy controls on memory tests. Loss of longitudinal practice effect may be a new and clinically relevant measure for capturing patients’ experience of cognitive difficulties after treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Colorectal Cancer Metastases in the Liver Establish Immunosuppressive Spatial Networking between Tumor-Associated SPP1 + Macrophages and Fibroblasts

Abstract Purpose: The liver is the most frequent metastatic site for colorectal cancer. Its microenvironment is modified to provide a niche that is conducive for colorectal cancer cell growth. This study focused on characterizing the cellular changes in the metastatic colorectal cancer (mCRC) liver tumor microenvironment (TME). Experimental Design: We analyzed a series of microsatellite stable (MSS) mCRCs to the liver, paired normal liver tissue, and peripheral blood mononuclear cells using single-cell RNA sequencing (scRNA-seq). We validated our findings using multiplexed spatial imaging and bulk gene expression with cell deconvolution. Results: We identified TME-specific SPP1-expressing macrophages with altered metabolism features, foam cell characteristics, and increased activity in extracellular matrix (ECM) organization. SPP1+ macrophages and fibroblasts expressed complementary ligand–receptor pairs with the potential to mutually influence their gene-expression programs. TME lacked dysfunctional CD8 T cells and contained regulatory T cells, indicative of immunosuppression. Spatial imaging validated these cell states in the TME. Moreover, TME macrophages and fibroblasts had close spatial proximity, which is a requirement for intercellular communication and networking. In an independent cohort of mCRCs in the liver, we confirmed the presence of SPP1+ macrophages and fibroblasts using gene-expression data. An increased proportion of TME fibroblasts was associated with the worst prognosis in these patients. Conclusions: We demonstrated that mCRC in the liver is characterized by transcriptional alterations of macrophages in the TME. Intercellular networking between macrophages and fibroblasts supports colorectal cancer growth in the immunosuppressed metastatic niche in the liver. These features can be used to target immune-checkpoint–resistant MSS tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Treatment of Prostate Cancer with CD46-targeted 225 Ac Alpha Particle Radioimmunotherapy

Radiopharmaceutical therapy is changing the standard of care in prostate cancer and other malignancies. We previously reported high CD46 expression in prostate cancer and developed an antibody–drug conjugate and immunoPET agent based on the YS5 antibody, which targets a tumor-selective CD46 epitope. Here, we present the preparation, preclinical efficacy, and toxicity evaluation of [ 225 Ac]DOTA-YS5, a radioimmunotherapy agent based on the YS5 antibody. [ 225 Ac]DOTA-YS5 was developed, and its therapeutic efficiency was tested on cell-derived (22Rv1, DU145), and patient-derived (LTL-545, LTL484) prostate cancer xenograft models. Biodistribution studies were carried out on 22Rv1 tumor xenograft models to confirm the targeting efficacy. Toxicity analysis of the [ 225 Ac]DOTA-YS5 was carried out on nu/nu mice to study short-term (acute) and long-term (chronic) toxicity. Biodistribution study shows that [ 225 Ac]DOTA-YS5 agent delivers high levels of radiation to the tumor tissue (11.64% ± 1.37%ID/g, 28.58% ± 10.88%ID/g, 29.35% ± 7.76%ID/g, and 31.78% ± 5.89%ID/g at 24, 96, 168, and 408 hours, respectively), compared with the healthy organs. [ 225 Ac]DOTA-YS5 suppressed tumor size and prolonged survival in cell line–derived and patient-derived xenograft models. Toxicity analysis revealed that the 0.5 μCi activity levels showed toxicity to the kidneys, likely due to redistribution of daughter isotope 213 Bi. [ 225 Ac]DOTA-YS5 suppressed the growth of cell-derived and patient-derived xenografts, including prostate-specific membrane antigen–positive and prostate-specific membrane antigen–deficient models. Overall, this preclinical study confirms that [ 225 Ac]DOTA-YS5 is a highly effective treatment and suggests feasibility for clinical translation of CD46-targeted radioligand therapy in prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Lung Cancer in the Mayak Workers Cohort: Risk Estimation and Uncertainty Analysis

The workers at the Mayak nuclear facility near Ozyorsk, Russia are a primary source of information about exposure to radiation at low-dose rates, since they were subject to protracted exposures to external gamma rays and to internal exposures from plutonium inhalation. Here we re-examine lung cancer mortality rates and assess the effects of external gamma and internal plutonium exposures using recently developed Monte Carlo dosimetry systems. Using individual lagged mean annual lung doses computed from the dose realizations, we fit excess relative risk (ERR) models to the lung cancer mortality data for the Mayak Workers Cohort using risk-modeling software. We then used the corrected information matrix (CIM) approach to widen the confidence intervals of ERR by taking into account the uncertainty in doses represented by multiple realizations from the Monte Carlo dosimetry systems. Findings of this work revealed that there were 930 lung cancer deaths during follow-up. Plutonium lung doses (but not gamma doses) were generally higher in the new dosimetry systems than those used in the previous analysis. This led to a reduction in the risk per unit dose compared to prior estimates. The estimated ERR/Gy for external gamma-ray exposure was 0.19 (95% CI: 0.07 to 0.31) for both sexes combined, while the ERR/Gy for internal exposures based on mean plutonium doses were 3.5 (95% CI: 2.3 to 4.6) and 8.9 (95% CI: 3.4 to 14) for males and females at attained age 60. Accounting for uncertainty in dose had little effect on the confidence intervals for the ERR associated with gamma-ray exposure, but had a marked impact on confidence intervals, particularly the upper bounds, for the effect of plutonium exposure [adjusted 95% CIs: 1.5 to 8.9 for males and 2.7 to 28 for females]. In conclusion, lung cancer rates increased significantly with both external gamma-ray and internal plutonium exposures. Accounting for the effects of dose uncertainty markedly increased the width of the confidence intervals for the plutonium dose response but had little impact on the external gamma dose effect estimate. Adjusting risk estimate confidence intervals using CIM provides a solution to the important problem of dose uncertainty. This work demonstrates, for the first time, that it is possible and practical to use our recently developed CIM method to make such adjustments in a large cohort study.

uncertainty, radiation risk estimation, Mayak Prod↗
DOE OSTI2023

The Effect of Prostate-Specific Antigen (PSA) Test on Radiation Risk Estimate for Prostate Cancer Incidence among Atomic-Bomb Survivors

Following our previous report on the radiation doseresponse for prostate cancer incidence rates in the Life Span Study (LSS) cohort of atomic bomb survivors, we reevaluated the radiation-related risk adjusting for differences in baseline cancer incidence rates among three subsets of the LSS cohort defined by the timing of their first participation in biennial health examinations offered to the Adult Health Study (AHS) sub-cohort members and prostate-specificantigen (PSA) testing status for AHS participants: 1. nonAHS participants, 2. AHS participants before receiving PSA test, and 3. AHS participants after receiving PSA test. We found a 2.9-fold increase in the baseline incidence rates among AHS participants after receiving PSA test. After adjusting for the PSA-testing-status effects on the baseline rates the estimated excess relative risk (ERR) per Gy was 0.54 (95% CI: 0.15, 1.05), which was almost identical to the previously reported unadjusted ERR estimate (0.57, 95% CI: 0.21, 1.00). The current results confirmed that, while the PSA testing among AHS participants increased the baseline incidence rates, it did not impact the radiation risk estimate, strengthening the previously reported dose-response relationship for prostate cancer incidence in the LSS. As the use of PSA tests continue in screening and medical settings, analyses of possible effects of PSA testing should be an important aspect of future epidemiological studies of the association between radiation exposure and prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Breast Cancer Imaging and Characterization

Researchers at Los Alamos National Laboratory are developing a suite of ultrasound-waveform tomography and super-resolution ultrasound imaging technology that, while investigational at this time, may be able to provide significantly improved image resolution and characterization of early-stage cancers in a non-invasive and cost-effective manner. Breast cancer is the most frequently diagnosed cancer in U.S. women. Although current medical imaging technologies have improved, false positive rates for mammograms still range 50-60% after 10 yearly mammograms. This innovative ultrasound-imaging technology is patented and copyright protected. It has great potential to differentiate between cancerous and healthy tissue without the negative side effects of mammography. We are seeking a commercialization partner to license these technologies or participate in a Cooperative Research and Development Agreement (CRADA) to further develop a practical suite of products for commercial purposes, and where applicable seek any necessary FDA authorization of the technology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

My Virtual Cancer

Since each cancer has its own unique characteristics, each one can respond differently to the same treatments. Therefore, the creation of a digital twin (DT) of cancer can assist us in predicting the evolution of an individual's cancer through modeling each tumor's characteristics and response to treatment. Hence, we propose to take advantage of new advances in computational approaches and combine mechanistic, machine learning, and stochastic modeling approaches to create “My Virtual Cancer", a DT platform. To establish a personalized DT, we use patient-specific data for parameter estimations, sensitivity analysis, and uncertainty quantification. For each patient, we will estimate the values of parameters of their QSP model using the patient's data. We perform a multi-dimensional sensitivity analysis and uncertainty quantification on the mechanistic model to find a set of critical interactions and predict the intervals of confidence. Since this QSP model includes the data-driven mechanistic model of cells and molecules' interaction networks, one of the ultimate results of this DT would be the prediction of evolution of tumors.

60 APPLIED LIFE SCIENCES↗