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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Pan-cancer evaluation of clinical value of mitotic network activity index (MNAI) and its predictive value for immunotherapy

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

PET Imaging Agents (FES, FFNP, and FDHT) for Estrogen, Androgen, and Progesterone Receptors to Improve Management of Breast and Prostate Cancers by Functional Imaging

Many breast and prostate cancers are driven by the action of steroid hormones on their cognate receptors in primary tumors and in metastases, and endocrine therapies that inhibit hormone production or block the action of these receptors provide clinical benefit to many but not all of these cancer patients. Because it is difficult to predict which individuals will be helped by endocrine therapies and which will not, positron emission tomography (PET) imaging of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer, and androgen receptor (AR) in prostate cancer can provide useful, often functional, information on the likelihood of endocrine therapy response in individual patients. This review covers our development of three PET imaging agents, 16α-[ 18 F]fluoroestradiol (FES) for ER, 21-[ 18 F]fluoro-furanyl-nor-progesterone (FFNP) for PgR, and 16β-[ 18 F]fluoro-5α-dihydrotestosterone (FDHT) for AR, and the evolution of their clinical use. For these agents, the pathway from concept through development tracks with an emerging understanding of critical performance criteria that is needed for successful PET imaging of these low-abundance receptor targets. Progress in the ongoing evaluation of what they can add to the clinical management of breast and prostate cancers reflects our increased understanding of these diseases and of optimal strategies for predicting the success of clinical endocrine therapies.

60 APPLIED LIFE SCIENCES↗
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 OSTI2023

Analysis of tumor-immune functional responses in a mathematical model of neoantigen cancer vaccines

Cancer neoantigen vaccines have emerged as a promising approach to stimulating the immune system to fight cancer. We propose a simple model including key elements of cancer-immune interactions and conduct a phase plane analysis to understand the immunological mechanisms of cancer neoantigen vaccines. Analytical results are obtained for two widely used functional forms that represent the killing rate of tumor cells by immune cells: the law of mass action (LMA) and the dePillis-Radunskaya Law (LPR). Using the LMA, our results reveal that a slowly growing tumor can escape the immune surveillance and that there is a unique periodic solution. The LPR offers richer dynamics, in which tumor elimination and uncontrolled tumor growth are both present. We show that tumor elimination requires sufficient number of initial activated T cells in relationship to the malignant cells, which lends support to using the neoantigen cancer vaccine as an adjuvant therapy after the primary tumor is surgically removed or treated using radiotherapy. We also derive a sufficient condition for uncontrolled tumor growth under the assumption of the LPR. Here, the juxtaposition of analyses with these two different choices for the killing rate function highlights their importance on model behavior and biological implications, by which we hope to spur further theoretical and experimental work to understand mechanisms underlying different functional forms for the killing rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Logic-based analysis of gene expression data predicts association between TNF, TGFB1 and EGF pathways in basal-like breast cancer

For breast cancer, clinically important subtypes are well characterized at the molecular level in terms of gene expression profiles. In addition, signaling pathways in breast cancer have been extensively studied as therapeutic targets due to their roles in tumor growth and metastasis. However, it is challenging to put signaling pathways and gene expression profiles together to characterize biological mechanisms of breast cancer subtypes since many signaling events result from post-translational modifications, rather than gene expression differences. We designed a logic-based computational framework to explain the differences in gene expression profiles among breast cancer subtypes using Pathway Logic and transcriptional network information. Pathway Logic is a rewriting-logic-based formal system for modeling biological pathways including post-translational modifications. Our method demonstrated its utility by constructing subtype-specific path from key receptors (TNFR, TGFBR1 and EGFR) to key transcription factor (TF) regulators (RELA, ATF2, SMAD3 and ELK1) and identifying potential association between pathways via TFs in basal-specific paths, which could provide a novel insight on aggressive breast cancer subtypes. Lastly, codes and results are available at http://epigenomics.snu.ac.kr/PL/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Poly( N -vinylpyrrolidone)- block -Poly(dimethylsiloxane)- block -Poly( N -vinylpyrrolidone) Triblock Copolymer Polymersomes for Delivery of PARP1 siRNA to Breast Cancers

Nearly 20% of HER2-positive breast cancers develop resistance to HER2-targeted therapies requiring the use of advanced therapies. Silencing RNA therapy may be a powerful modality for treating resistant HER2 cancers due to its high specificity and low toxicity. However, the systemic administration of siRNAs requires a safe and efficient delivery platform because of siRNA’s low stability in physiological fluids, inefficient cellular uptake, immunoreactivity, and rapid clearance. We have developed theranostic polymeric vesicles to overcome these hurdles for encapsulation and delivery of small functional molecules and PARP1 siRNA for in vivo delivery to breast cancer tumors. The 100 nm polymer vesicles were assembled from biodegradable and non-ionic poly(N-vinylpyrrolidone) 14 -block-poly(dimethylsiloxane) 47 -block-poly(N-vinylpyrrolidone) 14 triblock copolymer PVPON 14 -PDMS 47 -PVPON 14 using nanoprecipitation and thin-film hydration. We demonstrated that the vesicles assembled from the copolymer covalently tagged with the Cy5.5 fluorescent dye for in vivo imaging could also encapsulate the model drug with high loading efficiency (40%). The dye-loaded vesicles were accumulated in tumors after 18 h circulation in 4TR breast tumor-bearing mice via passive targeting. We found that PARP1 siRNA encapsulated into the vesicles was released intact (13%) into solution by the therapeutic ultrasound treatment as quantified by gel electrophoresis. Additionally, the PARP1 siRNA-loaded polymersomes inhibited the proliferation of MDA-MB-361TR cells by 34% after 6 days of treatment by suppressing the NF-kB signaling pathway, unlike their scrambled siRNA-loaded counterparts. Finally, the treatment by PARP1 siRNA-loaded vesicles prolonged the survival of the mice bearing 4T1 breast cancer xenografts, with the 4-fold survival increase, unlike the untreated mice after 3 weeks following the treatment. These biodegradable, non-ionic PVPON 14 -PDMS 47 -PVPON 14 polymeric nanovesicles capable of the efficient encapsulation and delivery of PARP1 siRNA to successfully knock down PARP1 in vivo can provide an advanced platform for the development of precision-targeted therapeutic carriers, which could help develop highly effective drug delivery nanovehicles for breast cancer gene therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Superhydrophobic Array Devices for the Enhanced Formation of 3D Cancer Models

During the metastatic cascade, cancer cells travel through the bloodstream as circulating tumor cells (CTCs) to a secondary site. Clustered CTCs have greater shear stress and treatment resistance, yet their biology remains poorly understood. We therefore engineered a tunable superhydrophobic array device (SHArD). The SHArD-C was applied to culture a clinically relevant model of CTC clusters. Using our device, we cultured a model of cancer cell aggregates of various sizes with immortalized cancer cell lines. These exhibited higher E-cadherin expression and are significantly more capable of surviving high fluid shear stress-related forces compared to single cells and model clusters grown using the control method, helping to explain why clustering may provide a metastatic advantage. Additionally, the SHArD-S, when compared with the AggreWell 800 method, provides a more consistent spheroid-forming device culturing reproducible sizes of spheroids for multiple cancer cell lines. Overall, we designed, fabricated, and validated an easily tunable engineered device which grows physiologically relevant three-dimensional (3D) cancer models containing tens to thousands of cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Survival analysis of localized prostate cancer with deep learning

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthcare system in the United States, we have developed an automated, personalized risk prediction model to support the clinical decision-making process for localized prostate cancer patients. This method combines the representative power of deep learning and the analytical interpretability of parametric regression models and can implement both time-dependent and static input data. To collect a comprehensive evaluation of model performances, we calculate time-dependent C-statistics C td over 2-, 5-, and 10-year time horizons using either a composite outcome or prostate cancer mortality as the target event. The composite outcome combines the Prostate-Specific Antigen (PSA) test, metastasis, and prostate cancer mortality. Our longitudinal model Recurrent Deep Survival Machine (RDSM) achieved C td 0.85 (0.83), 0.80 (0.83), and 0.76 (0.81), while the cross-sectional model Deep Survival Machine (DSM) attained C td 0.85 (0.82), 0.80 (0.82), and 0.76 (0.79) for the 2-, 5-, and 10-year composite (mortality) outcomes, respectively. In addition to estimating the survival probability, our method can quantify the uncertainty associated with the prediction. The uncertainty scores show a consistent correlation with the prediction accuracy. We find PSA and prostate cancer stage information are the most important indicators in risk prediction. Our work demonstrates the utility of the data-driven machine learning model in prostate cancer risk prediction, which can play a critical role in the clinical decision system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Cancer Treatment-Associated Pericardial Disease: Epidemiology, Clinical Presentation, Diagnosis, and Management

Purpose of Review: Cancer therapeutics have seen tremendous growth in the last decade and have been effective in the treatment of several cancer types. However, with advanced therapies like kinase inhibitors and immunotherapies, there have been unintended consequences of cardiotoxicities. While traditional chemotherapy and radiation-induced cardiotoxicity have been well studied, further research is needed to understand the adverse effects of newer regimens. Recent Findings: Both immune-mediated and non-immune-medicated cytotoxicity have been noted with targeted therapies such as tyrosine kinase inhibitors and immune checkpoint inhibitors. In this manuscript, we describe the pericardial syndromes associated with cancer therapies and propose management strategies. Pericardial effusion and pericarditis are common presentations in cancer patients and often difficult to diagnose. Concomitant myocarditis may also present with pericardial toxicity, especially with immunotherapies. In addition to proper history and physical, additional testing such as cardiovascular imaging and tissue histology need to be obtained as appropriate. Holding the offending oncology drug, and institution of anti-inflammatory medications, and immunosuppressants such as steroids are indicated. Summary: A high index of suspicion, use of standardized definitions, and comprehensive evaluation are needed for early identification, appropriate treatment, and better outcomes for patients with cancer treatment-associated pericardial disease. Further research is needed to understand the pathophysiology and to evaluate how the management of pericardial conditions in these patients differ from traditional management and also evaluate new therapies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Combination therapy with lenvatinib and radiation significantly inhibits thyroid cancer growth by uptake of tyrosine kinase inhibitor

Highlights: • Lenvatinib combined with radiation significantly inhibits thyroid cancer growth. • Combined therapy induced apoptosis and G2/M phase cell cycle arrest. • Irradiation increased cellular uptake of lenvatinib into cancer cells. • Combined therapy suggests a new therapeutic strategy for advanced thyroid cancer. Although surgical treatment cures >90% of differentiated thyroid cancer (DTC) patients, the remaining patients, including advanced DTC cases, have poor clinical outcomes. These patients with inoperable disease have only two choices of radioactive iodine therapy and tyrosine kinase inhibitors such as lenvatinib, which have a high incidence of treatment-related adverse events and can only prolong progression free survival by approximately 5–15 months. In this study, we investigated the antitumor effects of combination therapy with lenvatinib and radiation (CTLR) for DTC. CTLR synergistically inhibited cell replication and colony formation in vitro and tumor growth in nude mice without apparent toxicities and suppressed the expression of proliferation marker (Ki-67). CTLR also induced apoptosis and G2/M phase cell cycle arrest. Moreover, quantitative analysis of the intracellular uptake of lenvatinib using liquid chromatography and mass spectrometry demonstrated that intracellular uptake of lenvatinib was significantly increased 48 h following irradiation. These data suggest that increased membrane permeability caused by irradiation increases the intracellular concentration of levatinib, contributing to the synergistic effect. This mechanism-based potential of combination therapy suggests a powerful new therapeutic strategy for advanced thyroid cancer with fewer side effects and might be a milestone for developing a regimen in clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

PCGF3 promotes the proliferation and migration of non-small cell lung cancer cells via the PI3K/AKT signaling pathway

Highlights: • PCGF3 is highly expressed in non-small cell lung cancer (NSCLC) tissues. • PCGF3 overexpression positively correlates with lymph node metastasis and p-TNM staging. • PCGF3 promotes NSCLC cells proliferation by regulating CyclinB1, CyclinD1, and CDK4. • PCGF3 promotes NSCLC cells migration by regulating RhoA, RhoC, and CDC42. • PCGF3 promotes malignant behavior in NSCLC by positively regulating the PI3K/AKT signaling pathway. The Polycomb Group Ring Finger 3 (PCGF3) protein has been reported to be significantly upregulated in pancreatic islet tumors and related to signal transduction; however, its detailed mechanisms and biological roles in other tumors, including non-small cell lung cancer (NSCLC), remain unclear. This study investigated the function of PCGF3 in NSCLC and further elucidated its mechanism of action. The immunohistochemical analysis of 86 selected lung cancer tissues revealed that PCGF3 was highly expressed in NSCLC tissues and positively correlated with lymph node metastasis and p-TNM staging. Additionally, PCGF3 promoted cell proliferation in lung cancer by regulating CyclinB1, CyclinD1, and CDK4 expression, and also promoting their migration by regulating RhoA, RhoC, and CDC42. Furthermore, PCGF3 affected both the proliferation and migration of lung cancer cells by regulating the PI3K/AKT pathway, as verified by inhibiting this pathway using LY294002. The findings of this study suggested that PCGF3 is associated with poor prognosis in patients with NSCLC and could therefore be an important biomarker for treating and preventing NSCLC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Balancing DNA repair to prevent ageing and cancer

DNA damage is a constant stressor to the cell. Persistent damage to the DNA over time results in an increased risk of mutation and an accumulation of mutations with age. Loss of efficient DNA damage repair can lead to accelerated ageing phenotypes or an increased cancer risk, and the trade-off between cancer susceptibility and longevity is often driven by the cell's response to DNA damage. High levels of mutations in DNA repair mutants often leads to excessive cell death and stem cell exhaustion which may promote premature ageing. Stem cells themselves have distinct characteristics that enable them to retain low mutation rates. However, when mutations do arise, stem cell clonal expansion can also contribute to age-related tissue dysfunction as well as heightened cancer risk. In this review, we will highlight increasing DNA damage and mutation accumulation as hallmarks common to both ageing and cancer. We will propose that anti-ageing interventions might be cancer preventative and discuss the mechanisms through which they may act.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Preclinical tumor organoid models in personalized cancer therapy: Not everyone fits the mold

Highlights: • In personalized cancer medicine, each patient receives a specific treatment. • The tumor microenvironment and interpersonal differences can affect treatment. • Organoid culture systems fully recapitulate the tumor microenvironments. In contrast to conventional cancer treatment, in personalized cancer medicine each patient receives a specific treatment. The response to therapy, clinical outcomes, and tumor behavior such as metastases, tumor progression, carcinogenesis can be significantly affected by the heterogeneous tumor microenvironment (TME) and interpersonal differences. Therefore, using native tumor microenvironment mimicking models is necessary to improving personalized cancer therapy. Both in vitro 2D cell culture and in vivo animal models poorly recapitulate the heterogeneous tumor (immune) microenvironments of native tumors. The development of 3D culture models, native tumor microenvironment mimicking models, made it possible to evaluate the chemoresistance of tumor tissue and the functionality of drugs in the presence of cell-extracellular matrix and cell-cell interactions in a 3D construction. Various personalized tumor models have been designed to preserving the native tumor microenvironment, including patient-derived tumor xenografts and organoid culture strategies. In this review, we will discuss the patient-derived organoids as a native tumor microenvironment mimicking model in personalized cancer therapy. In addition, we will also review the potential and the limitations of organoid culture systems for predicting patient outcomes and preclinical drug screening. Finally, we will discuss immunotherapy drug screening in tumor organoids by using microfluidic technology.

60 APPLIED LIFE SCIENCES↗
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 OSTI2022

Unconventional isoquinoline-based SERMs elicit fulvestrant-like transcriptional programs in ER+ breast cancer cells

Estrogen receptor alpha (ERα) is a ligand-dependent master transcriptional regulator and key driver of breast cancer pathology. Small molecule hormones and competitive antagonists favor unique ERα conformational ensembles that elicit ligand-specific transcriptional programs in breast cancer and other hormone-responsive tissues. By affecting disparate ligand binding domain structural features, unconventional ligand scaffolds can redirect ERα genomic binding patterns to engage novel therapeutic transcriptional programs. To improve our understanding of these ERα structure-transcriptional relationships, we develop a series of chemically unconventional antagonists based on the antiestrogens elacestrant and lasofoxifene. High-resolution x-ray co-crystal structures show that these molecules affect both classical and unique structural motifs within the ERα ligand binding pocket. They show moderately reduced antagonistic potencies on ERα genomic activities but are effective anti-proliferative agents in luminal breast cancer cells. Interestingly, they favor a 4-hydroxytamoxifen-like accumulation of ERα in breast cancer cells but lack uterotrophic activities in an endometrial cell line. Importantly, RNA sequencing shows that the lead molecules engage transcriptional pathways similar to the selective estrogen receptor degrader fulvestrant. This advance shows that fulvestrant-like genomic activities can be achieved without affecting ERα accumulation in breast cancer cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Visible light-activatable platinum( IV ) prodrugs harnessing CD36 for ovarian cancer therapy

We hereby engineered photoactivatable Pt( IV ) metallodrugs that harness CD36 to target ovarian cancer cells. Pt( IV ) compounds mimic the structure of fatty acids and take advantage of CD36 as a “Trojan horse” to gain entry into the cells. We confirmed that CD36-dependent entry occurs using graphite furnace atomic absorption spectroscopy with ovarian cancer cells expressing different levels of CD36 and a CD36 inhibitor, SSO. Once the Pt( IV ) metallodrugs enter the cancer cells, they can be activated to form Pt(II) with characteristics of cisplatin under visible light (490 nm) irradiation, promoting photoinduced electron transfer from the attached fluorophore to the metal center. Finally, this light-induced activation can increase the cytotoxicity of the Pt( IV ) metallodrugs by up to 20 times toward ovarian cancer cells, inducing DNA damage and enabling efficient elimination of drug-resistant cancer cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports

One of the goals of the Surveillance, Epidemiology, and End Results (SEER) program is to estimate incidence, prevalence, and mortality of all cancers. To that end, cancer registries across the country maintain a massive database of cancer pathology reports which contain rich information to understand cancer trends. However, these reports are stored in the form of unstructured text, and human annotators are required to read and extract relevant information. In this article, we show that existing deep learning models for automating information extraction from cancer pathology reports can be significantly improved by using ensemble model distillation. We found that by training multiple predictive models and transferring their knowledge to a single, low-resource model, we can reduce the number of highly confident wrong predictions. Our results show that our implemented methods could save 1000s of manual annotation hours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Antitumor T-cell Immunity Contributes to Pancreatic Cancer Immune Resistance

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the United States. Pancreatic tumors are minimally infiltrated by T cells and are largely refractory to immunotherapy. Accordingly, the role of T-cell immunity in pancreatic cancer has been somewhat overlooked. Here, we hypothesized that immune resistance in pancreatic cancer was induced in response to antitumor T-cell immune responses and that understanding how pancreatic tumors respond to immune attack may facilitate the development of more effective therapeutic strategies. We now provide evidence that T-cell–dependent host immune responses induce a PDAC-derived myeloid mimicry phenomenon and stimulate immune resistance. Three KPC mouse models of pancreatic cancer were used: the mT3-2D (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) subcutaneous and orthotopic models, as well as the KP1 (p48-CRE/LSL-Kras/Trp53 flox/flox ) subcutaneous model. KPC cancer cells were grown in immunocompetent and immunodeficient C57BL/6 mice and analyzed to determine the impact of adaptive immunity on malignant epithelial cells, as well as on whole tumors. We found that induced T-cell antitumor immunity, via signal transducer and activator of transcription 1 (STAT1), stimulated malignant epithelial pancreatic cells to induce the expression of genes typically expressed by myeloid cells and altered intratumoral immunosuppressive myeloid cell profiles. Targeting the Janus Kinase (JAK)/STAT signaling pathway using the FDA-approved drug ruxolitinib overcame these tumor-protective responses and improved anti–PD-1 therapeutic efficacy. Overall, these findings provide future directions for treatments that specifically disable this mechanism of resistance in PDAC.

60 APPLIED LIFE SCIENCES↗