bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the enzymatic activity and stability of N-carbamoyl hydrolase using deep learning approach
Authors: Zhang Fa , Naeem Muhammad , Yu Bo , Liu Feixia , Ju Jiansong
Published: June 2024

Background

Optically active D-amino acids are widely used as intermediates in the synthesis of antibiotics, insecticides, and peptide hormones. Currently, the two-enzyme cascade reaction is the most efficient way to produce D-amino acids using enzymes DHdt and DCase, but DCase is susceptible to heat inactivation. Here, to enhance the enzymatic activity and thermal stability of DCase, a rational design software “Feitian” was developed based on kcat prediction using the deep learning approach.

Results

According to empirical design and prediction of “Feitian” software, six single-point mutants with high kcat value were selected and successfully constructed by site-directed mutagenesis. Out of six, three mutants (Q4C, T212S, and A302C) showed higher enzymatic activity than the wild-type. Furthermore, the combined triple-point mutant DCase-M3 (Q4C/T212S/A302C) exhibited a 4.25-fold increase in activity (29.77 ± 4.52 U) and a 2.25-fold increase in thermal stability as compared to the wild-type, respectively. Through the whole-cell reaction, the high titer of D-HPG (2.57 ± 0.43 mM) was produced by the mutant Q4C/T212S/A302C, which was about 2.04-fold of the wild-type. Molecular dynamics simulation results showed that DCase-M3 significantly enhances the rigidity of the catalytic site and thus increases the activity of DCase-M3.

Conclusions

In this study, an efficient rational design software “Feitian” was successfully developed with a prediction accuracy of about 50% in enzymatic activity. A triple-point mutant DCase-M3 (Q4C/T212S/A302C) with enhanced enzymatic activity and thermostability was successfully obtained, which could be applied to the development of a fully enzymatic process for the industrial production of D-HPG.
Characterization of EpCAM in thyroid cancer biology by three-dimensional spheroids in vitro model
Authors: Ghiandai Viola , Grassi Elisa Stellaria , Gazzano Giacomo , Fugazzola Laura , Persani Luca
Published: June 2024

Background

Thyroid cancer (TC) is the most common endocrine malignancy. Nowadays, undifferentiated thyroid cancers (UTCs) are still lethal, mostly due to the insurgence of therapy resistance and disease relapse. These events are believed to be caused by a subpopulation of cancer cells with stem-like phenotype and specific tumor-initiating abilities, known as tumor-initiating cells (TICs). A comprehensive understanding of how to isolate and target these cells is necessary. Here we provide insights into the role that the protein Epithelial Cell Adhesion Molecule (EpCAM), a known TICs marker for other solid tumors, may have in TC biology, thus considering EpCAM a potential marker of thyroid TICs in UTCs.

Methods

The characterization of EpCAM was accomplished through Western Blot and Immunofluorescence on patient-derived tissue samples, adherent cell cultures, and 3D sphere cultures of poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) cell lines. The frequency of tumor cells with putative tumor-initiating ability within the 3D cultures was assessed through extreme limiting dilution analysis (ELDA). EpCAM proteolytic cleavages were studied through treatments with different cleavages’ inhibitors. To evaluate the involvement of EpCAM in inducing drug resistance, Vemurafenib (PLX-4032) treatments were assessed through MTT assay.

Results

Variable EpCAM expression pattern was observed in TC tissue samples, with increased cleavage in the more UTC. We demonstrated that EpCAM is subjected to an intense cleavage process in ATC-derived 3D tumor spheres and that the 3D model faithfully mimics what was observed in patient’s samples. We also proved that the integrity of the protein appears to be crucial for the generation of 3D spheres, and its expression and cleavage in a 3D system could contribute to drug resistance in thyroid TICs.

Conclusions

Our data provide novel information on the role of EpCAM expression and cleavage in the biology of thyroid TICs, and our 3D model reflects the variability of EpCAM cleavage observed in tissue samples. EpCAM evaluation could play a role in clinical decisions regarding patient therapy since its expression and cleavage may have a fundamental role in the switch to a drug-resistant phenotype of UTC cells.
Association between blood lipids and diabetes mellitus in older Chinese adults aged 65 years or older: a cross-sectional analysis of residents’ electronic health records
Authors: Lin Tianxiang , Zhao Yanrong , Yang Qing , Wang Wei , Jiang Xuewen , Qiu Yinwei
Published: June 2024

Aim

This study aimed to investigate how blood lipids are associated with diabetes among older Chinese adults.

Methods

3,268,928 older Chinese adults without known diabetes were included. Logistic regression and restricted cubic spline (RCS) models were conducted to study associations between blood lipids (total cholesterol [TC], triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) and diabetes.

Results

202,832 diabetes cases were included. Compared with the lowest quintiles, TC, TG, and LDL-C in the highest quintiles showed a higher diabetes prevalence risk and HDL-C presented a lower risk in multivariate-adjusted logistic regression models. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for the highest quintiles of TC, TG, and HDL-C were 1.39 (1.37–1.41), 2.56 (2.52–2.60), and 0.73 (0.72–0.74), respectively. For LDL-C, 3–5% lower risk was found in the second and third quintiles, and 4–23% higher risk was found in the fourth and fifth quintiles. RCS curves showed a non-linear relationship between each blood lipid parameters and diabetes (P-non-linear < 0.001). TG and HDL-C curves presented monotonically increasing and L-shaped patterns, respectively, whereas TC and LDL-C curves exhibited a J-shaped pattern. When TC < 4.04 mmol/L or LDL-C < 2.33 mmol/L, ORs of diabetes increased with the decrease of corresponding indexes. However, after excluding participants with lower LDL-C, the J-shaped association with TC disappeared.

Conclusions

This study demonstrates non-linear associations between lipids and diabetes. Low cholesterol levels are associated with a high risk of diabetes. The cholesterol paradox should be considered during lipid-lowering treatments.
Losing sleep influences dietary intake in children: a longitudinal compositional analysis of a randomised crossover trial
Authors: Haszard Jillian J. , Jackson Rosie , Morrison Silke , Meredith-Jones Kim A. , Galland Barbara C. , Beebe Dean W. , Elder Dawn E. , Taylor Rachael W.
Published: June 2024

Background

Although inadequate sleep increases the risk of obesity in children, the mechanisms remain unclear. The aims of this study were to assess how sleep loss influenced dietary intake in children while accounting for corresponding changes in sedentary time and physical activity; and to investigate how changes in time use related to dietary intake.

Methods

A randomized crossover trial in 105 healthy children (8–12 years) with normal sleep (~ 8–11 h/night) compared sleep extension (asked to turn lights off one hour earlier than usual for one week) and sleep restriction (turn lights off one hour later) conditions, separated by a washout week. 24-h time-use behaviors (sleep, wake after sleep onset, physical activity, sedentary time) were assessed using waist-worn actigraphy and dietary intake using two multiple-pass diet recalls during each intervention week. Longitudinal compositional analysis was undertaken with mixed effects regression models using isometric log ratios of time use variables as exposures and dietary variables as outcomes, and participant as a random effect.

Results

Eighty three children (10.2 years, 53% female, 62% healthy weight) had 47.9 (SD 30.1) minutes less sleep during the restriction week but were also awake for 8.5 (21.4) minutes less at night. They spent this extra time awake in the day being more sedentary (+ 31 min) and more active (+ 21 min light physical activity, + 4 min MVPA). After adjusting for all changes in 24-h time use, losing 48 min of sleep was associated with consuming significantly more energy (262 kJ, 95% CI:55,470), all of which was from non-core foods (314 kJ; 43, 638). Increases in sedentary time were related to increased energy intake from non-core foods (177 kJ; 25, 329) whereas increases in MVPA were associated with higher intake from core foods (72 kJ; 7,136). Changes in diet were greater in female participants.

Conclusion

Loss of sleep was associated with increased energy intake, especially of non-core foods, independent of changes in sedentary time and physical activity. Interventions focusing on improving sleep may be beneficial for improving dietary intake and weight status in children.

Trial Registration

Australian New Zealand Clinical Trials Registry ANZCTR ACTRN12618001671257, Registered 10th Oct 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true
Alpha-6 integrin deletion delays the formation of Brca1/p53-deficient basal-like breast tumors by restricting luminal progenitor cell expansion
Authors: Faraldo Marisa M. , Romagnoli Mathilde , Wallon Loane , Dubus Pierre , Deugnier Marie-Ange , Fre Silvia
Published: June 2024

Background

The aberrant amplification of mammary luminal progenitors is at the origin of basal-like breast cancers associated with BRCA1 mutations. Integrins mediate cell–matrix adhesion and transmit mechanical and chemical signals that drive epithelial stem cell functions and regulate tumor progression, metastatic reactivation, and resistance to targeted therapies. Consistently, we have recently shown that laminin-binding integrins are essential for the expansion and differentiation of mammary luminal progenitors in physiological conditions. As over-expression of the laminin-binding α6 integrin (Itgα6) is associated with poor prognosis and reduced survival in breast cancer, we here investigate the role of Itgα6 in mammary tumorigenesis.

Methods

We used Blg-Cre; Brca1F/F; Trp53F/F mice, a model that phenocopies human basal-like breast cancer with BRCA1 mutations. We generated mutant mice proficient or deficient in Itgα6 expression and followed tumor formation. Mammary tumors and pretumoral tissues were characterized by immunohistochemistry, flow cytometry, RT-qPCR, Western blotting and organoid cultures. Clonogenicity of luminal progenitors from preneoplastic glands was studied in 3D Matrigel cultures.

Results

We show that Itga6 deletion favors activation of p16 cell cycle inhibitor in the preneoplastic tissue. Subsequently, the amplification of luminal progenitors, the cell of origin of Brca1-deficient tumors, is restrained in Itgα6-deficient gland. In addition, the partial EMT program operating in Brca1/p53-deficient epithelium is attenuated in the absence of Itgα6. As a consequence of these events, mammary tumor formation is delayed in Itgα6-deficient mice. After tumor formation, the lack of Itgα6 does not affect tumor growth but rather alters their differentiation, resulting in reduced expression of basal cell markers.

Conclusions

Our data indicate that Itgα6 has a pro-tumorigenic role in Blg-Cre; Brca1F/F; Trp53F/F mice developing basal-like mammary tumors. In particular, we reveal that Itgα6 is required for the luminal progenitor expansion and the aberrant partial EMT program that precedes the formation of BRCA1 deficient tumors.
Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement
Authors: Gao Yan , Cui Yan
Published: June 2024

Background

Accurate prediction of an individual’s predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets.

Methods

We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer’s disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups.

Results

Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations.

Conclusions

This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.
There is a need to better take into account forest soils in the planned soil monitoring law of the European Union
Authors: Wellbrock Nicole , Cools Nathalie , de Vos Bruno , Jandl Robert , Lehtonen Aleksi , Leitgeb Ernst , Mäkipää Raisa , Pavlenda Pavel , Schwärtzel Kai , Šrámek Vít
Published: June 2024

Key message

A Soil Monitoring Law to improve soil health across all land uses has been proposed by the European Commission. As forests soils have different chemical and physical properties as well as biogeochemical dynamics compared to agricultural land, they also face different challenges in maintaining and restoring soil health. Examples are soil acidification, eutrophication by atmospheric deposition, responses to climate change, and loss of biodiversity. Therefore, we propose forest soil specific health descriptors and thresholds based on experience and knowledge from existing long-term monitoring programs.
Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework
Authors: He Hongxia , Li Xi , Chen Peng , Chen Juan , Liu Ming , Wu Lei
Published: June 2024

Cloud environment is a virtual, online, and distributed computing environment that provides users with large-scale services. And cloud monitoring plays an integral role in protecting infrastructures in the cloud environment. Cloud monitoring systems need to closely monitor various KPIs of cloud resources, to accurately detect anomalies. However, due to the complexity and highly dynamic nature of the cloud environment, anomaly detection for these KPIs with various patterns and data quality is a huge challenge, especially those massive unlabeled data. Besides, it’s also difficult to improve the accuracy of the existing anomaly detection methods. To solve these problems, we propose a novel Dynamic Graph Transformer based Parallel Framework (DGT-PF) for efficiently detect system anomalies in cloud infrastructures, which utilizes Transformer with anomaly attention mechanism and Graph Neural Network (GNN) to learn the spatio-temporal features of KPIs to improve the accuracy and timeliness of model anomaly detection. Specifically, we propose an effective dynamic relationship embedding strategy to dynamically learn spatio-temporal features and adaptively generate adjacency matrices, and soft cluster each GNN layer through Diffpooling module. In addition, we also use nonlinear neural network model and AR-MLP model in parallel to obtain better detection accuracy and improve detection performance. The experiment shows that the DGT-PF framework have achieved the highest F1-Score on 5 public datasets, with an average improvement of 21.6% compared to 11 anomaly detection models.
Observations of co-existing rising and falling tone emissions of electromagnetic ion cyclotron waves
Authors: Ojha Biswajit , Omura Yoshiharu , Singh Satyavir , Lakhina Gurbax S.
Published: June 2024

We report observations of co-existing rising and falling tone emissions of electromagnetic ion cyclotron (EMIC) waves by THEMIS E spacecraft. The investigation of these fine structures of the EMIC waves is essential from the point of view of understanding the connection between the proton holes and the proton hills in velocity phase-space. The wave packets of rising and falling tones are tracked by Poynting vector analysis, where we observe that the rising tones are propagating northward and the falling tones are propagating southward. The nonlinear wave growth theory supports our observations. We propose a model where the proton velocity distribution function evolves through the formation of proton holes on the negative side of the distribution function and mirrored resonant protons forming proton hills on the positive side of the distribution function, allowing us to observe the co-existing rising and falling tone EMIC waves.

Graphical abstract
Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity
Authors: Choi Yoon Kyoung , Feng Linqing , Jeong Won-Ki , Kim Jinhyun
Published: June 2024

Mapping neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow aging and diseases. Developments in imaging technology, such as microscopy and labeling tools, have allowed researchers to visualize this connectivity through high-resolution brain-wide imaging. With this, image processing and analysis have become more crucial. However, despite the wealth of neural images generated, access to an integrated image processing and analysis pipeline to process these data is challenging due to scattered information on available tools and methods. To map the neural connections, registration to atlases and feature extraction through segmentation and signal detection are necessary. In this review, our goal is to provide an updated overview of recent advances in these image-processing methods, with a particular focus on fluorescent images of the mouse brain. Our goal is to outline a pathway toward an integrated image-processing pipeline tailored for connecto-informatics. An integrated workflow of these image processing will facilitate researchers’ approach to mapping brain connectivity to better understand complex brain networks and their underlying brain functions. By highlighting the image-processing tools available for fluroscent imaging of the mouse brain, this review will contribute to a deeper grasp of connecto-informatics, paving the way for better comprehension of brain connectivity and its implications.
Unveiling determinants of household lighting preferences in rural Tanzania: insights for sustainable energy access
Authors: Kamuzora Aurelia Ngirwa
Published: June 2024

This paper investigates the determinants and prospects of household lighting choices in rural Tanzania using a Multinomial Logit Regression Model. The analysis is based on data from 4671 households, focusing on three lighting options: electricity, solar energy, and candle lighting. The results reveal significant factors influencing these choices, including household head characteristics, household size, marital status, education, employment status, number of rooms, and income. Key findings indicate that the age of the household head negatively influences the likelihood of choosing grid-electricity, while having a male head of household significantly reduces the probability of opting for any lighting option. Larger household size is negatively associated with choosing electricity and candle lighting. Marital status shows that married households are more likely to use candle lighting. Employment status positively impacts the likelihood of adopting all three lighting options, with employed household heads being more likely to choose modern lighting solutions. Income levels are crucial, as higher income significantly increases the probability of selecting electricity and candle lighting, but not solar energy. These findings provide valuable insights for policymakers and stakeholders aiming to enhance sustainable energy access in rural Tanzania. It highlights the importance of addressing socio-economic factors to promote the adoption of modern and sustainable lighting technologies.
Synthesis and evaluation of [18F]FBNAF, a STAT3-targeting probe, for PET imaging of tumor microenvironment
Authors: Miyazaki Anna , Kanai Yasukazu , Wakamori Keita , Mizuguchi Serina , Futatsugi Mikiya , Hirano Fuko , Kondo Naoya , Temma Takashi
Published: June 2024

Background

Signal transducer and activator of transcription 3 (STAT3) is a protein that regulates cell proliferation and differentiation, and it is attracting attention as a new index for evaluating cancer pathophysiology, as its activation has been highly correlated with the development and growth of tumors. With the development of STAT3 inhibitors, the demand for imaging probes will intensify. Noninvasive STAT3 imaging can help determine the cancer status and predict the efficacy of STAT3 inhibitors. In this study, we aimed to develop an imaging probe targeting STAT3 and synthesized [18F]FBNAF, which was derived from a STAT3-selective inhibitor as the lead compound, followed by in vitro and in vivo evaluations of [18F]FBNAF in positron emission tomography for STAT3.

Results

The results revealed that FBNAF concentration-dependently inhibited STAT3 phosphorylation, similar to the lead compound, thereby supporting radiosynthesis. [18F]FBNAF was easily synthesized from the pinacol boronate ester precursor with suitable radiochemical conversion (46%), radiochemical yield (6.0%), and radiochemical purity (> 97%). [18F]FBNAF exhibited high stability in vitro and in vivo, and radioactivity accumulated in tumor tissues expressing STAT3 with an increasing tumor/blood ratio over time, peaking at 2.6 ± 0.8 at 120 min after injection in tumor-bearing mice. Tumor radioactivity was significantly reduced by the coinjection of a STAT3-selective inhibitor. Furthermore, the localization of radioactivity was almost consistent with STAT3 expression based on ex vivo autoradiography and immunohistochemistry using adjacent tumor sections.

Conclusions

Thus, [18F]FBNAF could be the first promising STAT3-targeting probe for PET imaging. A STAT3 imaging probe provides meaningful information on STAT3-associated cancer conditions and in tumor microenvironment.
Management of spontaneous pyogenic spondylodiscitis: a descriptive cohort study
Authors: Ibrahim Aly , Elshazly Khaled , AbdelFatah Mohamed A. R. , El-Gayar Abdelrahman , Hefny Sameh
Published: June 2024

Background

Spontaneous spondylodiscitis (SD) is an inflammation of the vertebral endplate and the intervertebral disc with no prior surgery or intervention. The treatment of spontaneous pyogenic SD mainly consists of systemic antibiotics and rest. Some cases require surgery due to failure of medical treatment or due to neurological compromise. Due to the disease heterogeneity, there are no standardized, widely adopted treatment protocols. We conducted this study to assess the clinical outcome of the different treatment modalities.

Results

This is a retrospective analysis of prospectively collected data of patients with spontaneous non-tuberculous spondylodiscitis. Thirty-eight patients were identified, including 14 males and 24 females. The mean age was 49 years. Twenty-three patients underwent surgery from the start while 15 patients received conservative medical treatment. Among the latter, 8 patients showed disease progression and required surgical intervention. The ODI/NDI at 1 year (mean = 8) was significantly better than before treatment (mean = 18). Among 11 patients with motor deficit at presentation, 8 improved and 3 remained stable. There were 14 complications, including 11 minor and 3 major, requiring one revision surgery.

Conclusions

Surgical decompression and debridement with or without instrumented fusion for complicated SD cases is a safe and effective treatment modality. Close follow-up is needed in case of conservative treatment for early detection of treatment failure and disease progression. Baseline characteristic variabilities in patients with spontaneous pyogenic SD could predict conservative treatment failure, but this needs to be validated in larger series.
Single-cell RNA sequencing opens a new era for cotton genomic research and gene functional analysis
Authors: Pan Xiaoping , Peng Renhai , Zhang Baohong
Published: June 2024

Single-cell RNA sequencing (scRNA-seq) is one of the most advanced sequencing technologies for studying transcriptome landscape at the single-cell revolution. It provides numerous advantages over traditional RNA-seq. Since it was first used to profile single-cell transcriptome in plants in 2019, it has been extensively employed to perform different research in plants. Recently, scRNA-seq was also quickly adopted by the cotton research community to solve lots of scientific questions which have been never solved. In this comment, we highlighted the significant progress in employing scRNA-seq to cotton genetic and genomic study and its future potential applications.
Identification of key functional pathways: arginine biosynthesis and IL-17 signalling in placental decidua of unexplained recurrent pregnancy loss through RNA sequencing—a case series
Authors: Sultana Shehnaz , Bhanu B. Divya , Ananthapur Venkateshwari
Published: June 2024

Background

Three or more consecutive pregnancy losses before the 20th week of gestation constitute recurrent pregnancy loss (RPL), and about half of these cases are still unsolved despite routine screening tests. The purpose of the current study was to identify the RPL-related placental decidual differential gene expression and to gain new knowledge about the biological mechanisms underlying RPL.

Methods

In the current work, we used RNA sequencing (RNA-seq) technology to identify the differentially expressed genes (DEGs) in placental decidua from patients of unexplained recurrent pregnancy loss (RPL). To conduct RNA-seq, two healthy unwanted medically terminated pregnancies (MTPs) and four RPL patients were enlisted.

Results

A total number of 96 significant differentially expressed genes (DEGs) were obtained which includes 73 up- and 23 downregulated genes between the RPL and MTP groups. Histocompatibility genes were significantly upregulated in the RPL. Interleukin 6 (IL-6), matrix metalloproteinase-10 (MMP10), and protein phosphatase 1 regulatory inhibitor subunit 11 (PPP1R11) genes which were significantly upregulated in RPL were further validated in an extended sample size. The validation results were consistent with the sequencing results. To find potential biological pathways connected to RPL, the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out.

The study indicates that arginine biosynthesis is significantly downregulated, while IL-17 signalling pathway is significantly upregulated in RPL.

Conclusion

In conclusion, the findings of the present study indicate involvement of arginine biosynthesis, immune regulatory pathways, and histocompatibility genes in the pathogenesis of recurrent pregnancy loss (RPL). However, to validate these observations, further investigations with a larger sample size are warranted.
Outcomes with trastuzumab deruxtecan (T-DXd) by HER2 status and line of treatment in a large real-world database of patients with metastatic breast cancer.
Authors: Tarantino Paolo , Lee Do , Foldi Julia , Soulos Pamela R. , Gross Cary Philip , Grinda Thomas , Winer Eric P. , Lin Nancy U. , Krop Ian E. , Tolaney Sara M. , Lustberg Maryam B. , Sammons Sarah L
Published: June 2024

1077

Background: In the clinical trial setting, T-DXd improves survival for patients with HER2+ and HER2-low metastatic breast cancer (MBC), and has also shown preliminary activity in HER2-0 MBC. Little real-world evidence is available on the performance of T-DXd. Methods: We conducted a retrospective observational study using the nationwide Flatiron Health electronic health record (EHR)-derived deidentified database to evaluate the real-world activity of T-DXd. We included patients with MBC who initiated T-DXd between 12/2019 and 1/2023. Tumors were categorized as HER2+ if positive at any timepoint, with HER2- cases further divided into HER2-low (IHC 1+ or 2+ not amplified) and HER2-0 (IHC 0) according to the last biopsy before T-DXd. Real world progression-free survival (rwPFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Results: A total of 930 patients were included: 636 with HER2+, 268 with HER2-low and 26 with HER2-0 MBC. Among HER2- patients, 241 (82.0%) were HR+ and 53 (18.0%) were HR- (i.e., triple-negative). A total of 572 (61.5%) patients were White, 101 (10.9%) Black/African American, 88 (9.4%) Hispanic/Latino, 37 (4.0%) Asian and 132 (14.2%) other or missing. Median age was 59 [range 25, 84] and patients received T-DXd in the following lines of therapy (LOT): 54 (5.8%) as 1st line, 110 (11.8%) as 2nd line, 179 (19.2%) as 3rd line, 182 (19.6%) as 4th line and 405 (43.6%) as ≥5th line. Median number of LOT for advanced disease prior to T-DXd were 3 and 4, respectively, for HER2+ and HER2- patients. In patients with HER2+ MBC, rwPFS and OS were 12.1 and 26 months after initiating T-DXd, respectively. The longest rwPFS, 14.9 months, was observed in the 1st or 2nd LOT, followed by 14.1 months in LOT 3, 12.4 months in LOT 4, and 10.8 months in LOT ≥5. In patients with HER2- MBC, median rwPFS and OS were 6.3 and 15.5 months, respectively. The longest median rwPFS of 8.1 months was observed in the 1st or 2nd LOTs, followed by 6.9 months in LOT 4, 6.2 months in LOTs ≥5, and 6.0 months in LOT 3. Outcomes with T-DXd by HER2 and HR status are provided (Table). Updated data with a larger sample size will be presented. Conclusions: In the largest dataset to date, T-DXd showed favorable real-world activity for treating MBC, although rwPFS appeared shorter than what observed in clinical trials. Encouraging rwPFS was observed in understudied groups, such as patients with triple-negative and HR+/HER2-0 MBC. [Table: see text]
Pilot evaluation of portable scalp cooling for chemotherapy-associated alopecia in early-stage breast cancer.
Authors: Page David B. , Hong Erin , Kaur Lakhvir , Gauntt Sarah , Gedney Holley , Hobbs Evthokia , Perlewitz Kelly Shea , Seino Amanda , Topp Zheng Zhu , Conlin Alison Katherine
Published: June 2024

12141

Background: Chemotherapy-induced alopecia significantly impacts quality of life (QOL). First-generation scalp cooling systems PAXMAN and Dignicap, while effective in reducing alopecia, are not universally adopted due to their lack of portability. Amma is a second-generation, portable and battery-powered scalp cooling system that offers the opportunity for widespread clinical usage by allowing self-administration and mobility. Here, we report first-in-human outcomes of Amma in a preliminary cohort receiving curative-intent taxane-based chemotherapy for early-stage breast cancer. Methods: We conducted a pilot clinical trial (NCT05508984) of the Amma system at Providence Cancer Institute in Oregon. Key inclusion criteria included: no baseline alopecia [Dean’s scale 0], intent to receive 4-6 cycles of taxane-based, anthracycline-sparing therapy, willingness to participate in quality-of-life questionnaires, and serial scalp photography. The primary outcome was the feasibility of Amma devices for adoption within the clinic ascertained by patient reported outcomes (PRO) and provider feedback. The secondary outcome was efficacy defined as the proportion of subjects achieving < 50% hair loss [Dean’s scale 0-2] at 30 days post-treatment, and tolerability assessed by common terminology criteria for adverse events (CTCAE). Results: 14 participants were enrolled and evaluable from 9/2022-1/2024. Participants received docetaxel/cyclophosphamide (TC x 4, n=10) or weekly paclitaxel/trastuzumab+/- pertuzumab (TH(P), n=4). 93% of participants (n=13/14) successfully completed treatment. One participant discontinued scalp cooling prematurely. Primary efficacy endpoint of <50% hair loss was achieved in 64% participants (n=9/14, [95% CI: 0.39, 0.89]) (TC: n=5/10; TH(P): n=4/4). On the validated “Was it Worth It?” questionnaire, 92% reported the treatment “worthwhile”, 85% would repeat participation, and 100% would recommend it to others. After treatment, 93% reported a similar or increased QOL with participation and 71% deemed the experience “better than expected”, paralleling PRO outcomes from previously published trials using first-generation cooling devices. Provider feedback was favorable regarding feasibility of treatment. Conclusions: Scalp cooling with the portable Amma system was both feasible and effective in this pilot study. Point estimates of efficacy were like those reported for PAXMAN (Dean’s 0-2: 50%) and DigniCap (66%). A follow-up clinical trial is planned with a primary outcome of efficacy in patients receiving taxane-based chemotherapy (NCT06215469, PI: Rugo). Clinical trial information: NCT05508984 .
National implementation of an AI-based virtual dietitian for patients with cancer.
Authors: Buchan Marissa Lubin , Bratton Susan , Jones Eliza , Goel Keshav , Basch Ethan
Published: June 2024

1500

Background: Nutritional status is an established key driver of cancer outcomes and patient experience. However, the workforce of oncology dietitians is unable to meet the needs of the population, and 80% of patients seek but do not receive nutrition support. Advances in artificial intelligence (AI) and machine learning (ML) capabilities afford the opportunity to expand reach and rapidly hone in on clinical and contextual needs to deliver evidence-based nutritional guidance. Methods: To address this unmet need, an AI-based nutrition expert-platform was developed. Interventions were curated by oncology-nutrition experts based on peer-reviewed literature and clinical guidelines to facilitate self-management of cancer side effects and optimize nutrition. A growing database of over 114,000 evidence-based interventions powers Ina, a text-message based virtual nutrition assistant. Interventions are continually enhanced and refined using AI and ML applied to an extensive learning dataset. The tool was implemented nationally in partnership with 25 cancer advocacy organizations. Data on demographics, patient-reported outcomes, and utilization were systematically collected. Results: Between July 2019 and August 2023, 3,310 users from all 50 states registered for the virtual nutrition platform. Based on self-report, users were 73% female; mean age 57 years (18-91); most common cancer types were GU (22%), Breast (21%), Gyn (19%), GI (14%), and Lung (12%), representing nearly 90% of users. Users were medically complex, with 50% reporting Stage 3-4 disease, 64% with metastases, and 50% with 2+ chronic conditions. Nutritional challenges were highly prevalent: 58% were overweight/obese by BMI, 83% reported barriers to good nutrition, and 42% had food allergies/intolerances. Levels of engagement were high: 68% of users texted queries to Ina, 79% completed surveys, and median user retention duration was 8.8 months. Overall, 94% of users reported being satisfied with the platform and 98% found the guidance to be helpful. In an evaluation of outcomes, 84% reported actively using the nutrition advice to guide their diets, 47% used the recommended recipes, and 82% felt the program improved their quality of life. In this cohort with high symptom burden, 88% reported Ina helped them manage their symptoms and 34% noted improved symptom control during participation. Conclusions: Implementation of an evidence-based AI virtual dietitian is feasible, and is reported by patients to be beneficial on diet, quality of life, and symptom control. Ongoing evaluations are assessing impact on other outcomes.
Disparities uncovered: LGBTQ+ patients report on their cancer care journey.
Authors: Maingi Shail , Schabath Matthew B. , Dewald Ilona , Storey Janet , Dooyema Samuel , Carter Jeffrey D. , Heggen Cherilyn , McKinnon Kelly
Published: June 2024

1516

Background : In the U.S, LGBTQ+ people face higher cancer rates and worse outcomes than the general population. Few studies have described the experiences of LGBTQ+ people and their caregivers during treatment. As part of an implementation science initiative aimed at improving care for LGBTQ+ patients, we conducted a large survey (n=817) to understand treatment experiences of this population. Here we report our findings which provide insight into how stigma and incorrect assumptions may contribute to medical mistrust and worse experiences. Methods: In 2023, 817 diverse LGBTQ+ cancer patients from academic and community-based settings, as well as patient advocacy groups, completed web-based surveys evaluating their care experiences during cancer treatment. Participants included patients with gastric (n=165), breast (n=238), ovarian (n=218), prostate (n=56), and colorectal cancers (n=140), including 83 gender non-conforming patients. Results: Most LGBTQ+ patients (80%) reported not receiving appropriate preventative cancer screening, with top barriers including provider did not mention cancer screening tests (40%) and did not have a healthcare provider (28%). Additionally, only 24% felt at least moderately comfortable disclosing their LGBTQ+ status. Inclusive measures that helped patients feel most comfortable included care teams sharing/displaying their own pronouns (39%), making public statements of support (43%), or wearing personal items indicating acceptance (39%). Of those who did disclose their identity, only 50% of gender-expansive patients reported consistently being referred to by the correct names and pronouns. Importantly, patients reported that only 34% of their partners/caregivers felt welcome at appointments, and only 4% felt respected by the care team. Few patients reported receiving key supportive care services, including counseling/support groups (23%), quality-of-life related care, such as sexual function counseling (23%), and LGBTQ-specific resources/education (19%). Furthermore, less than half of LGBTQ+ patients discussed with HCPs how cancer treatment affects fertility (41%), fertility preferences (26%), or fertility preservation (14%), even though only 22% of patients reported not being eligible for fertility services. Interestingly, many of these gaps in care differed based on cancer type. For example, prostate, colorectal, and gastric patients were more likely to report not feeling safe disclosing their LGBTQ+ status (80%, 69%, and 54% respectively), while breast cancer patients were more likely to report having discussed fertility prior to starting treatment (64%). Conclusions: This study offers insights into experiences of LGBTQ+ patients and confirms disparities in care are real and pervasive. Ongoing education and inclusion efforts can help create a safe and welcoming environment, enabling equitable care and improved outcomes.
A United Kingdom prospective, multicentre, observational cohort study investigating tolerance of anti-cancer systemic therapy in the elderly: The TOASTIE study.
Authors: Dearden Helen Clare , Rowe Michael , Peters Adam , Rohan Maria , Marsh Alexandra , Gee Abigail Louise , Zucker Kieran , Quesne Gemma , Heseltine Jonathan , Prichard Rachel , Scott Deborah , ONeill Conor , Brunner Clair , Howells Joni , Conteh Veronica , Aujayeb Avinash , Yan Xiangfei , Rodgers Lisa Jane , Martin Sally , Baxter Mark
Published: June 2024

1521

Background: Older adults have a higher risk of developing chemotherapy (CTx) related toxicity. The Cancer Aging Research Group (CARG) score was developed and validated in the USA to predict risk of severe CTx induced toxicity in older adults; subsequent validation studies have had varying results. The TOASTIE study sought to evaluate the CARG score prospectively in a United Kingdom (UK) population. Methods: This multicentre, prospective, observational study recruited patients aged ≥65 years commencing first-line neo-adjuvant, adjuvant or palliative CTx for any solid organ malignancy. Those receiving non-CTx agents were excluded. Baseline demographics and established frailty measures were recorded, including Eastern Cooperative Oncology Group performance status (ECOG PS), Rockwood Clinical Frailty Scale (CFS), Geriatric-8 (G8) score and Charlson Co-morbidity Index (CCI). CARG score was calculated after initial Oncology consultation. Follow-up data including CTCAEv5 toxicity and hospital admissions were collected retrospectively. Results: 19 centres recruited 330 patients between Nov 2019 - Dec 2022. Median age was 73 years (range 65-92) and 51.9% were male. 54.9% had a primary tumour of gastrointestinal origin, 48.7% received CTx with palliative intent and 70.8% received doublet therapy. At baseline, 85% patients had an ECOG PS 0 or 1, with median CFS 3 (range 0-8), G8 score 12 (range 6-16) and CCI 6 (range 2-12). Follow-up data was available for 314 (92.6%) patients; the median CTx cycles received was 4 (range 1-16) with 124 (39%) patients dose reduced at cycle one. Treatment delays occurred in 83 (26.4%) patients and 123 (39.2%) stopped treatment early, with 60 (48.8%) cases due to treatment-related toxicity. 69(22.3%) patients experienced a CTCAE grade ≥3 toxicity and 84 (27%) requiring hospital admission. CARG score was available for 313 patients; 107 (34.2%) low risk, 167 (53.4%) medium risk and 39 (12.5%) high risk. Increasing CARG risk groups had increased toxicity rates (low 19.6%, medium 22.2%, high 28.2%) however this was non-significant with no evidence of robust predictive performance (Table). The performance of CFS and ECOG PS was superior to CARG. Conclusions: In this UK older patient population, baseline frailty was prevalent. CARG score was unable to robustly discriminate or predict risk of high-grade toxicity. ECOG showed superior, albeit limited, ability to predict and discriminate toxicity risk. This study highlights the need for development of further tools predictive of toxicity in this population. [Table: see text]
Assessing the environmental and downstream human health impacts of decentralizing cancer care.
Authors: Hantel Andrew , Cernik Colin , Walsh Thomas , Uno Hajime , Larios Dalia , Slutzman Jonathan , Abel Gregory A.
Published: June 2024

1522

Background: Greenhouse gas emissions from healthcare are substantial and harm persons with cancer. Emissions from outpatient cancer care visits are not well described, nor are the downstream reduction in human harms that could be obtained through visit “decentralization” (telemedicine and local care when possible). Methods: This life-cycle assessment (LCA)-based study evaluated changes in emissions and downstream health harms associated with (1) telemedicine visits using retrospective observational analysis and (2) fully decentralized visits using counterfactual modeling. The retrospective observational cohort included persons receiving cancer care at Dana-Farber Cancer Institute (DFCI) and 20 affiliated facilities between 5/2015-12/2020. The main outcome was the adjusted per visit-day difference in emissions (in kilograms carbon dioxide equivalents: kgCO2e) between two periods: an in-person care period (5/2015-2/2020; “Pre”) and a telemedicine period (3/2020-12/2020; “Post”). Mixed effects log-linear model assessed emissions changes adjusted for age, sex, race, ethnicity, and cancer type, with random effects on person. The counterfactual model assessed emissions changes between actual in-person visits during the Pre period and a counterfactual with maximal decentralization. Visit-day eligibility for decentralization was obtained by categorizing appointments (e.g., clinician visit, infusion) as DFCI required, local care possible, or telemedicine possible. This cohort was matched to a national population diagnosed with cancer over the same period (Cancer in North America [CiNA] dataset) using mixed-effects linear modeling, through which annual changes in disability-adjusted life-years (DALY) from clinician visit decentralization were estimated using Eckelman’s mortality cost of carbon conversion. Results: There were123,890 unique patients in the DFCI cohort seen over 1.6 million visit-days (Pre N=110,180, Post N=61,691) at a median of 6 visit-days per patient (IQR 2, 15). An estimated 72,554,006 kgCO2e were within scope of the LCA emitted during the study period. In mixed-effects log-linear regression, the adjusted mean absolute reduction in per visit-day emissions between Pre and Post periods was 36.4 kgCO2e (95%CI 36.2,36.6), or a reduction of 81.3% (95%CI 80.8,81.7) compared to the baseline model. In the counterfactual decentralized care model of the Pre period, there was a relative emissions reduction of 33.1% (95%CI 32.9,33.3). When demographically matched to 10.3 million persons in the CiNA dataset, decentralized care would have reduced national emissions by 75.3 million kgCO2e annually; this corresponds to an estimated annual reduction of 15.0-47.7 DALYs. Conclusions: Employing decentralization through telemedicine and local care can substantially reduce emissions during cancer care delivery; this corresponds to a small reduction in human mortality.
Identifying states for targeted alloHCT access initiatives using social vulnerability, physician density, and unmet need.
Authors: Watters Samantha , Meyer Christa , Preussler Jaime , Senneka Mary
Published: June 2024

1528

Background: Access to allogeneic hematopoietic cell transplantation (alloHCT) is limited by many factors, with only 1 in 3 patients who may need a transplant receiving one. This study examined associations between social vulnerability index (SVI), physician density (PD), and alloHCT unmet need across the United States (U.S.) to identify geographic areas that may be most at-risk of access challenges. Methods: A retrospective analysis aggregated public data across 3,141 U.S. counties, including: SVI [Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry]; National Provider Identifier [Center for Medicare and Medicaid Services] data for all registered hematology-oncology and HCT physicians; and 2017 – 2021 alloHCT unmet need [Center for International Blood and Marrow Transplant Research (CIBMTR), NMDP]. PD was defined as providers per 10,000 population. All variables were collapsed into ordinal categories (very low, low, moderate, high) based on quartiles. Counties with moderate/high SVI and unmet need and low/very low PD were defined as at-risk. By state, linear regression and mediation analysis assessed exploratory relationships. Results: Among 396 counties defined as at-risk, top states are shown (Table). State (n=51) percent unmet need was correlated with SVI (r=0.494, p<0.001) and PD (r=-0.295, p=0.036). Univariate analysis revealed SVI (b=0.223, p<0.001) and PD (b=-0.187, p=0.036) as predictors of unmet need. However, multivariate regression showed only SVI as significant when included with PD. Race/ethnicity as 1 of 4 SVI subthemes (socioeconomic status [SES], household characteristics [including age], race/ethnicity, and housing/transportation) was not correlated with PD, but all other themes were. SES and household characteristics were found to fully mediate the relationship between PD and unmet need. Conclusions: This study can help prioritize targeted initiatives through a better understanding of how SVI, PD, and unmet need relate to alloHCT access. This study cannot draw causal conclusions and uses multiple population-level data sources. However, data can examine trends on a regional level within at-risk states to allocate resources to overcome barriers to alloHCT, with special attention on SES and household factors like age. Relationships between variables should be further examined. [Table: see text]