bluuebunny/crossref_metadata_2025_split huggingface dataset:
55 Baseline glycolytic tumor burden predicts response and survival in NSCLC and melanoma patients treated with immune checkpoint inhibitors
Authors: Silva Saulo , Wanderley Carlos Wagner , Marin Jose Flavio , Macedo Mariana De , Nascimento Ellen , Antonacio Fernanda , Cunha Fernando , Castro Gilberto de 
Published: November 2021

BackgroundTumor metabolic remodeling is considered one of the hallmarks of cancers and has been implicated in immune evasion. Highly glycolytic tumors can lead to immune suppression by both nutrient competition and toxic metabolite accumulation. Immune checkpoint inhibitors (ICIs) are essential in treating melanoma and non-small cell lung cancer (NSCLC) patients, but novel predictive biomarkers can significantly contribute to clinical practice. Herein we analyzed the predictive and prognostic value of baseline metabolic tumor volumes in NSCLC and melanoma patients treated with ICIs.MethodsThis retrospective, single-center study includes patients with metastatic NSCLC or melanoma and a baseline 18F-FDG-PET/CT (PET) performed before ICI. PET studied parameters were SUV (maximum standardized uptake value), wMTV (whole metabolic tumor value), and wTLG (whole total lesion glycolysis). Best response rates were analyzed through RECIST. High or low glycolytic tumor burden (GTB) patients were defined according to SUV, wMTV, and wTLG cut-offs that best discriminate progressive disease. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method, and curves were compared with log-rank.ResultsAmong 151 patients included, 107 had NSCLC and 44 melanoma. Regarding NSCLC patients, there was a significant correlation between GTB and responses among all PET parameters (figure 1). Noteworthily, only one patient with a low wTLG (<146) showed progressive disease after ICIs (figure 2C). In regard to the potential in predicting response to ICIs, the area under the curve (AUC) obtained for each glycolytic parameter was higher than that for PD-L1 expression (figure 2D-H). Furthermore, when patients were categorized according to ICI exposure (1st or ≥ 2nd line), AUC for glycolytic parameters was higher in ≥ 2nd line versus 1st line (figure 3). Lastly, a low GTB was associated with improved PFS (figure 4) and OS (figure 5).Regarding melanoma patients, wMTV and wTLG were significantly associated with response (figure 6), and a low GTB was significantly associated with improved PFS and OS (figure 7).Abstract 55 Figure 1Abstract 55 Figure 2Abstract 55 Figure 3Abstract 55 Figure 4Abstract 55 Figure 5Abstract 55 Figure 6Abstract 55 Figure 7ConclusionsGTB accessed through a baseline PET is associated with survival and response to ICIs in NSCLC and melanoma patients, suggesting that the tumor metabolism might impact immune responses and be a promising predictive tool.Ethics ApprovalThe study obtained ethics approval by Sírio-Libanês Hospital institutional review board. Study participants were not required to give an informed consent before taking part.
83 Spatially resolved transcriptomic and proteomic investigation of breast cancer and its immune microenvironment
Authors: Chew Jennifer , Uytingco Cedric , Spalinskas Rapolas , Yin Yifeng , Shuga Joe , Veire Benton , Anaparthy Naishitha , Hatori Ryo , Katsor Anna-Maria , Katiraee Layla , Hermes Alexander , Chiang Jun Ding , Roelli Patrick , Williams Stephen , Nitsch William , Weisenfeld Neil , Walkser Dan , Koth Jason , Basu Subham , Howat Will , Ganapathy Karthik , Stoeckius Marlon 
Published: November 2021

BackgroundThe tumor microenvironment (TME) is composed of highly heterogeneous extracellular structures and cell types such as endothelial cells, immune cells, and fibroblasts that dynamically influence and communicate with each other. The constant interaction between a tumor and its microenvironment plays a critical role in cancer development and progression and can significantly affect a tumor’s response to therapy and capacity for multi-drug resistance. High resolution analyses of gene and protein expression with spatial context can provide deeper insights into the interactions between tumor cells and surrounding cells within the TME, where a better understanding of the underlying biology can improve treatment efficacy and patient outcomes. Here, we demonstrated the ability to perform streamlined multi-omic tumor analyses by utilizing the 10X Genomics Visium Spatial Gene Expression Solution for FFPE with multiplex protein enablement. This technique simultaneously assesses gene and protein expression to elucidate the immunological profile and microenvironment of different breast cancer samples in conjunction with standard pathological methods.MethodsSerial (5 µm) sections of FFPE human breast cancer samples were placed on Visium Gene Expression (GEX) slides. The Visium GEX slides incorporate ~5,000 molecularly barcoded, spatially encoded capture spots onto which tissue sections are placed, stained, and imaged. Following incubation with a human whole transcriptome, probe-based RNA panel and an immuno-oncology oligo-tagged antibody panel, developed with Abcam conjugated antibodies, the tissues are permeabilized and the representative probes are captured. Paired GEX and protein libraries are generated for each section and then sequenced on an Illumina NovaSeq at a depth of ~50,000 reads per spot. Resulting reads from both libraries are aligned and overlaid with H&E-stained tissue images, enabling analysis of both mRNA and protein expression. Additional analyses and data visualizations were performed on the Loupe Browser v4.1 desktop software.ConclusionsSpatial transcriptomics technology complements pathological examination by combining histological assessment with the throughput and deep biological insight of highly-multiplexed protein detection and RNA-seq. Taken together, our work demonstrated that Visium Spatial technology provides a spatially-resolved, multi-analyte view of the tumor microenvironment, where a greater understanding of cellular behavior in and around tumors can help drive discovery of new biomarkers and therapeutic targets.
318 Enforced tumor specific MHC-I heterogeneity in triple negative breast cancer drives immunotherapy resistance
Authors: Taylor Brandie , Balko Justin , Sanders Melinda , Gonzalez-Ericsson Paula , Sanchez Violeta 
Published: November 2021

BackgroundDespite the broad success of immune checkpoint inhibition (ICI e.g. anti-Programmed Death Ligand-1 [PD-L1]) in cancer treatment, tumor-intrinsic factors leading to intrinsic and acquired resistance are poorly understood. Tumor specific MHC-I expression is indispensable for anti-PD-1/L1 response as complete loss of MHC-I via B2M deletion results in inability of CD8+ T cells to recognize tumor-associated antigens. However, MHC-I is heterogeneously downregulated or lost in many tumor types. Tumor cell destruction can also occur through non-synaptic mechanisms, in a so-called ‘field effect’. Therefore, we modeled heterogeneous loss of MHC-I expression in breast cancer and experimentally evaluated how heterogeneous MHC-I loss affects response to anti-PD-L1 therapy.MethodsWe performed quantitative immunofluorescence for MHC-I and Pan-CK on breast cancer tumors (n=410). To determine the functional effect of MHC-I heterogeneity on anti-PD-L1 response, we used an immunocompetent EMT6 orthotopic mammary tumor model which ubiquitously expresses MHC-I at baseline. Using CRISPR/Cas9, we engineered EMT6 cells with B2m loci excision resulting in complete knockout of MHC-I on the cell surface. We then orthotopically implanted B2m-comtetent and B2m-KO cells at varying inoculum ratios (100:0, 90:10, 50:50, 10:90, 0:100) into syngeneic Balb/C mice and assessed immune responsiveness and efficacy of checkpoint inhibition. Additionally, to look at how loss of MHC-I affects the tumor microenvironment we will use the PanCancer Immune NanoString panel (n=770 genes) to evaluate gene expression patterns in tumor cells and infiltrating immune cells.ResultsIn patient samples, we identified high diversity in MHC-I expression across all clinical subtypes, with triple negative breast cancer (TNBC) having the highest MHC-I expression. Chemotherapy-treated tumors had higher MHC-I levels than untreated tumors. In mice when 10% of cells were B2m-KO, we observed a 50% reduction in complete eradication of EMT6 tumors with aPD-L1 treatment and reduced disease-stabilization and no complete responses when a 50% mixture of MHC-I deficient cells. An increasing percentage of B2m KO leads to worse outcomes overall and a decrease in infiltrating T cells.ConclusionsOur work suggests that there is an ICI-responsive phenotype that is driven by heterogeneity in MHC-I expression levels. As little as 10% of tumor specific MHC-I loss can lead to therapeutic resistance and a decrease in complete responders. This represents that early TNBC may be less responsive to single-agent PD-L1 due to specific percentages of MHC-I loss. MHC-I expression can influence therapy outcomes and potentially lead to novel observations of how to overcome lack of, or limited, MHC-I expression.
Generalized uncertainty principle: from the harmonic oscillator to a QFT toy model
Authors: Bosso Pasquale , Luciano Giuseppe Gaetano 
Published: November 2021

AbstractSeveral models of quantum gravity predict the emergence of a minimal length at Planck scale. This is commonly taken into consideration by modifying the Heisenberg uncertainty principle into the generalized uncertainty principle. In this work, we study the implications of a polynomial generalized uncertainty principle on the harmonic oscillator. We revisit both the analytic and algebraic methods, deriving the exact form of the generalized Heisenberg algebra in terms of the new position and momentum operators. We show that the energy spectrum and eigenfunctions are affected in a non-trivial way. Furthermore, a new set of ladder operators is derived which factorize the Hamiltonian exactly. The above formalism is finally exploited to construct a quantum field theoretic toy model based on the generalized uncertainty principle.
Determination of composition of mixed biological samples using laser-induced fluorescence and combined classification/regression models
Authors: Fellner Lea , Kraus Marian , Walter Arne , Duschek Frank , Bocklitz Thomas , Gabbarini Valentina , Rossi Riccardo , Puleio Alessandro , Malizia Andrea , Gaudio Pasquale 
Published: November 2021

AbstractLaser-induced fluorescence (LIF) provides the ability to distinguish organic materials by a fast and distant in situ analysis. When detecting the substances directly in the environment, e.g., in an aerosol cloud or on surfaces, additional fluorescence signals of other fluorophores occurring in the surrounding are expected to mix with the desired signal. We approached this problem with a simplified experimental design for an evaluation of classification algorithms. An upcoming question for enhanced identification capabilities is the case of mixed samples providing different signals from different fluorophores. For this work, mixtures of up to four common fluorophores (NADH, FAD, tryptophan and tyrosine) were measured by a dual-wavelength setup and spectrally analyzed. Classification and regression are conducted with neural networks and show an excellent performance in predicting the ratios of the selected ingredients.
The role of noise in the tumor dynamics under chemotherapy treatment
Authors: Bashkirtseva Irina , Ryashko Lev , Duarte Jorge , Seoane Jesús M. , Sanjuan Miguel A. F. 
Published: November 2021

AbstractDynamical systems modeling tumor growth have been investigated to analyze the dynamics between tumor and healthy cells. Recent theoretical studies indicate that these interactions may lead to different dynamical outcomes under the effect of particular cancer therapies. In the present paper, we derive a system of nonlinear differential equations, in order to investigate solid tumors in vivo, taking into account the impact of chemotherapy on both tumor and healthy cells. We start by studying our model only in terms of deterministic dynamics under the variation of a drug concentration parameter. Later, with the introduction of noise, a stochastic model is used to analyze the impact of the unavoidable random fluctuations. As a result, new insights into noise-induced transitions are provided and illustrated in detail using techniques from dynamical systems and from the theory of stochastic processes.
Inhibition of FGFR Reactivates IFNγ Signaling in Tumor Cells to Enhance the Combined Antitumor Activity of Lenvatinib with Anti-PD-1 Antibodies
Authors: Adachi Yusuke , Kamiyama Hiroshi , Ichikawa Kenji , Fukushima Sayo , Ozawa Yoichi , Yamaguchi Shogo , Goda Satoshi , Kimura Takayuki , Kodama Kotaro , Matsuki Masahiro , Miyano Saori Watanabe , Yokoi Akira , Kato Yu , Funahashi Yasuhiro 
Published: November 2021

AbstractCombination therapies consisting of immune checkpoint inhibitors plus anti-VEGF therapy show enhanced antitumor activity and are approved treatments for patients with renal cell carcinoma (RCC). The immunosuppressive roles of VEGF in the tumor microenvironment are well studied, but those of FGF/FGFR signaling remain largely unknown. Lenvatinib is a receptor tyrosine kinase inhibitor that targets both VEGFR and FGFR. Here, we examine the antitumor activity of anti-PD-1 mAb combined with either lenvatinib or axitinib, a VEGFR-selective inhibitor, in RCC. Both combination treatments showed greater antitumor activity and longer survival in mouse models versus either single agent treatment, whereas anti-PD-1 mAb plus lenvatinib had enhanced antitumor activity compared with anti-PD-1 mAb plus axitinib. Flow cytometry analysis showed that lenvatinib decreased the population of tumor-associated macrophages and increased that of IFNγ-positive CD8+ T cells. Activation of FGFR signaling inhibited the IFNγ-stimulated JAK/STAT signaling pathway and decreased expression of its target genes, including B2M, CXCL10, and PD-L1. Furthermore, inhibition of FGFR signaling by lenvatinib restored the tumor response to IFNγ stimulation in mouse and human RCC cell lines. These preclinical results reveal novel roles of tumor FGFR signaling in the regulation of cancer immunity through inhibition of the IFNγ pathway, and the inhibitory activity of lenvatinib against FGFRs likely contributes to the enhanced antitumor activity of combination treatment comprising lenvatinib plus anti-PD-1 mAb.Significance:FGFR pathway activation inhibits IFNγ signaling in tumor cells, and FGFR inhibition with lenvatinib enhances antitumor immunity and the activity of anti-PD-1 antibodies.
Nanoparticle Delivery of miR-122 Inhibits Colorectal Cancer Liver Metastasis
Authors: Sendi Hossein , Yazdimamaghani Mostafa , Hu Mengying , Sultanpuram Nikhila , Wang Jie , Moody Amber S. , McCabe Ellie , Zhang Jiajie , Graboski Amanda , Li Liantao , Rojas Juan D. , Dayton Paul A. , Huang Leaf , Wang Andrew Z. 
Published: November 2021

Abstract

Liver metastasis is a leading cause of cancer morbidity and mortality. Thus, there has been strong interest in the development of therapeutics that can effectively prevent liver metastasis. One potential strategy is to utilize molecules that have broad effects on the liver microenvironment, such as miR-122, a liver-specific miRNA that is a key regulator of diverse hepatic functions. Here we report the development of a nanoformulation miR-122 as a therapeutic agent for preventing liver metastasis. We engineered a galactose-targeted lipid calcium phosphate (Gal-LCP) nanoformulation of miR-122. This nanotherapeutic elicited no significant toxicity and delivered miR-122 into hepatocytes with specificity and high efficiency. Across multiple colorectal cancer liver metastasis models, treatment with Gal-LCP miR-122 treatment effectively prevented colorectal cancer liver metastasis and prolonged survival. Mechanistic studies revealed that delivery of miR-122 was associated with downregulation of key genes involved in metastatic and cancer inflammation pathways, including several proinflammatory factors, matrix metalloproteinases, and other extracellular matrix degradation enzymes. Moreover, Gal-LCP miR-122 treatment was associated with an increased CD8+/CD4+ T-cell ratio and decreased immunosuppressive cell infiltration, which makes the liver more conducive to antitumor immune response. Collectively, this work presents a strategy to improve cancer prevention and treatment with nanomedicine-based delivery of miRNA.

Significance:
Highly specific and efficient delivery of miRNA to hepatocytes using nanomedicine has therapeutic potential for the prevention and treatment of colorectal cancer liver metastasis.
Translational Activation of ATF4 through Mitochondrial Anaplerotic Metabolic Pathways Is Required for DLBCL Growth and Survival
Authors: Li Meng , Teater Matthew R. , Hong Jun Young , Park Noel R. , Duy Cihangir , Shen Hao , Wang Ling , Chen Zhengming , Cerchietti Leandro , Davidson Shawn M. , Lin Hening , Melnick Ari M. 
Published: November 2021

Abstract
Diffuse large B-cell lymphomas (DLBCL) are broadly dependent on anaplerotic metabolism regulated by mitochondrial SIRT3. Herein we find that translational upregulation of ATF4 is coupled with anaplerotic metabolism in DLBCLs due to nutrient deprivation caused by SIRT3 driving rapid flux of glutamine into the tricarboxylic acid (TCA) cycle. SIRT3 depletion led to ATF4 downregulation and cell death, which was rescued by ectopic ATF4 expression. Mechanistically, ATF4 translation is inhibited in SIRT3-deficient cells due to the increased pools of amino acids derived from compensatory autophagy and decreased glutamine consumption by the TCA cycle. Absence of ATF4 further aggravates this state through downregulation of its target genes, including genes for amino acid biosynthesis and import. Collectively, we identify a SIRT3–ATF4 axis required to maintain survival of DLBCL cells by enabling them to optimize amino acid uptake and utilization. Targeting ATF4 translation can potentiate the cytotoxic effect of SIRT3 inhibitor to DLBCL cells.

Significance:
We discovered the link between SIRT3 and ATF4 in DLBCL cells, which connected lymphoma amino acid metabolism with ATF4 translation via metabolic stress signals. SIRT3–ATF4 axis is required in DLBCL cells regardless of subtype, which indicates a common metabolic vulnerability in DLBCLs and can serve as a therapeutic target.
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O tensionamento afetivo nas relações entre corpo e cidade através do Programa Performativo no espaço urbano
Authors: Faria Jéssica Sousa , Carvalho Marcelo Braga de , Pestana Sandra Regina Facioli 
Published: November 2021

Este artigo tem como objetivo principal analisar a relação entre espaço urbano e corpo – transeunte através de uma abordagem artística e pedagógica. Sendo assim, este projeto utilizará como ferramenta investigativa o Programa Performativo que, segundo Eleonora Fabião, conduz o corpo a experiências que lhe propiciam a criação de relações e circulações afetivas. Para construção da ação do referido programa foram utilizados conceitos da Teoria da Deriva de Guy Debórd e as experiências artísticas e poéticas desenvolvidas por Renato Almeida. Como campo de estudo, as imediações da Praça das Artes, localizada no centro histórico da cidade de São Paulo. Este sítio urbano, que contém patrimônios históricos e culturais da cidade, revela-se um campo fértil para a experimentação e investigação de práticas artísticas aqui propostas e disparador para a criação de ações instalativas.
Suppression of Arctic Sea Ice Growth in the Eurasian–Pacific Seas by Winter Clouds and Snowfall
Authors: Lim Won-Il , Park Hyo-Seok , Stewart Andrew L. , Seo Kyong-Hwan 
Published: November 2021

Abstract
The ongoing Arctic warming has been pronounced in winter and has been associated with an increase in downward longwave radiation. While previous studies have demonstrated that poleward moisture flux into the Arctic strengthens downward longwave radiation, less attention has been given to the impact of the accompanying increase in snowfall. Here, utilizing state-of-the-art sea ice models, we show that typical winter snowfall (snow water equivalent) anomalies of around 1.0 cm, accompanied by positive downward longwave radiation anomalies of ∼5 W m−2, can cause basinwide sea ice thinning by around 5 cm in the following spring over the Arctic seas in the Eurasian–Pacific seas. In extreme cases, this is followed by a shrinking of summer ice extent. In the winter of 2016/17, anomalously strong warm, moist air transport combined with ∼2.5-cm increase in snowfall (snow water equivalent) decreased spring ice thickness by ∼10 cm and decreased the following summer sea ice extent by 5%–30%. This study suggests that small changes in the pattern and volume of winter snowfall can strongly impact the sea ice thickness and extent in the following seasons.
ENSO Predictability over the Past 137 Years Based on a CESM Ensemble Prediction System
Authors: Liu Ting , Song Xunshu , Tang Youmin , Shen Zheqi , Tan Xiaoxiao 
Published: November 2021

AbstractIn this study, we conducted an ensemble retrospective prediction from 1881 to 2017 using the Community Earth System Model to evaluate El Niño–Southern Oscillation (ENSO) predictability and its variability on different time scales. To our knowledge, this is the first assessment of ENSO predictability using a long-term ensemble hindcast with a complicated coupled general circulation model (CGCM). Our results indicate that both the dispersion component (DC) and signal component (SC) contribute to the interannual variation of ENSO predictability (measured by relative entropy). Specifically, the SC is more important for ENSO events, whereas the DC is of comparable importance for short lead times and in weak ENSO signal years. The SC dominates the seasonal variation of ENSO predictability, and an abrupt decrease in signal intensity results in the spring predictability barrier feature of ENSO. At the interdecadal scale, the SC controls the variability of ENSO predictability, while the magnitude of ENSO predictability is determined by the DC. The seasonal and interdecadal variations of ENSO predictability in the CGCM are generally consistent with results based on intermediate complexity and hybrid coupled models. However, the DC has a greater contribution in the CGCM than that in the intermediate complexity and hybrid coupled models.Significance StatementEl Niño–Southern Oscillation (ENSO) is a prominent interannual signal in the global climate system with widespread climatic influence. Our current understanding of ENSO predictability is based mainly on long-term retrospective forecasts obtained from intermediate complexity and hybrid coupled models. Compared with those models, complicated coupled general circulation models (CGCMs) include more realistic physical processes and have the potential to reproduce the ENSO complexity. However, hindcast studies based on CGCMs have only focused on the last 20–60 years. In this study, we conducted an ensemble retrospective prediction from 1881 to 2017 using the Community Earth System Model in order to evaluate ENSO predictability and examine its variability on different time scales. To our knowledge, this is the first assessment of ENSO predictability using a long-term ensemble hindcast with a CGCM.