bluuebunny/crossref_metadata_2025 huggingface dataset:
Model of Multi-Algorithmic-Based Optimization of 4D Approach Trajectory under Thunderstorm Weather
Authors: Lu Li , Lai Xin
Published: February 2024

Thunderstorms are recognized as perilous meteorological phenomena characterized by irregular and nonlinear movement, posing significant risks to approaching aircraft and necessitating technical methods to ensure safety to the aviation operations. This research specifically addresses the challenges associated with aircraft during the approach segment and introduces a multialgorithmic model focusing on the optimization of 4D approach trajectory. Firstly, the artificial neural network intelligent model was used to predict the thunderstorm movement track. Secondly, the multialgorithmic model combined by the rapidly exploring random tree with artificial potential field was built to plan the trajectory of the approaching aircraft under thunderstorm weather, and then, the mean filter was adopted to smooth the simulated approaching trajectory. Finally, the reliability of the model with a real case study was demonstrated. After optimized simulation by predicting the thunderstorm weather and trajectory-optimized multialgorithmic model mentioned above, the approach trajectory can be outputted successfully, but with some distortions, postprocessing with the mean filter results in a remarkably smooth approach trajectory, providing enhanced feasibility and efficiency for pilots navigating through thunderstorm weather conditions. It is ultimately proved that refined 4D trajectory operations under hazardous weather conditions hold substantial significance in advancing aviation safety and operational effectiveness.
Exploration of Moderated, Mediated, and Configurational Outcomes of Tourism-Related Content (TRC) on TikTok in Predicting Enjoyment and Behavioral Intentions
Authors: Huang Shu-Chin , Silalahi Andri Dayarana K. , Eunike Ixora Javanisa
Published: February 2024

The significance of social media content in consumers’ decision-making journeys has acquired substantial attention among scholars and business practitioners in recent times. However, the exploration of how marketing strategies should design social media content to influence behavioral intentions remains fairly inadequate, particularly within the tourism industry. This study is aimed at developing a model that includes the moderating, mediating, and configuration effects of tourism-related content (TRC) dimensions on TikTok to predict enjoyment and behavioral intention. This study employs a hybrid approach of structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) to test hypotheses and propositions using a sample of 319 participants who have experience watching TRC on TikTok and have the intention to visit the destinations presented in the content. The results from SEM confirm that content reliability and understandability significantly influence perceived enjoyment. Furthermore, visit intention is predicted to increase through the contributions of content understandability and perceived enjoyment. Insights from the mediating effect reveal that perceived enjoyment serves as a fully mediating factor between content understandability and visit intention. Moreover, the moderating effects of gender and frequency of use exhibit significant differences in their impacts on perceived enjoyment and visit intention. The outcomes of fsQCA confirm that various configurations of TRC dimensions and enjoyment provide valuable insights for designing content-marketing strategies. The consideration of different combinations of these constructs can impact behavioral intentions. This research makes significant contributions to both theory and marketing practice, as the comprehensive discussion of the combinations of configurations provides amplified insights into this study’s findings.
N − 1 Security Criteria Based Integrated Deterministic and Probabilistic Framework for Composite Power System Reliability
Authors: Jain Tanmay , Verma Kusum , Bhadu Mahendra
Published: February 2024

Unpredictable variations in load demand and unanticipated component failures are progressively impacting the operation of modern power systems, making system evaluation more stochastic in nature. Although deterministic approaches were formerly the norm for determining system status, probabilistic approaches have greatly improved the capacity to capture the stochastic behavior characteristic of power system operations. The presented work in the paper recommends the use of probabilistic modelling approaches with deterministic approaches, highlighting their crucial function in augmenting the reliability and security of contemporary power systems to unanticipated failures. In this paper, N − 1 security criteria based reliability of the composite power system (CPS) is proposed using an integrated deterministic and probabilistic framework (D-P) considering outage of the transmission line. For the deterministic approach (DA), line overloading on available lines is determined using the static security index (SSI). For the probabilistic approach (PA), reliability indices such as expected loss of power (ELOP), expected frequency of contingency (EFOC), expected loss of load (ELOL), probability of load curtailment (PLC), and expected duration of load curtailments (EDLC) are calculated. Further, for each contingency, a performance index is determined using both approaches to assess the severity of the contingency that occurred on the power system. Based on the N − 1 security criteria based reliability analysis using an integrated D-P framework, a credible critical set of transmission lines is obtained, which can serve as important information to system operators. The proposed techniques have been tested on IEEE 24 bus reliability test system (RTS).
Aquila Optimizer-Based Hybrid Predictive Model for Traffic Congestion in an IoT-Enabled Smart City
Authors: Chahal Ayushi , Gulia Preeti , Gill Nasib Singh , Sultana Nishat
Published: February 2024

Effective traffic congestion prediction is need of the hour in a modern smart city to save time and improve the quality of life for citizens. In this study, AB_AO (ARIMA Bi-LSTM using Aquila optimizer), a hybrid predictive model, is proposed using the most effective time-series data prediction statistical model ARIMA (Autoregressive Integrated Moving Average) and sequential predictive Deep Learning (DL) technique LSTM (Long Short-Term Memory) which helps in traffic congestion prediction with a minimum error rate. Also, the Aquila optimizer (AO) is used to elevate the adequacy of the AB_AO model. Three road traffic datasets of different cities from the “CityPulse EU FP7 project” are used to implement the proposed hybrid model. In a time-series dataset, two components need to be handled with care, i.e., linear and nonlinear. In this study, the ARIMA model has been used to manage linear components and Bi-LSTM is used to handle nonlinear components of the time-series dataset. The Aquila Optimizer (AO) is used for hyperparametric tuning to enhance the performance of Bi-LSTM. Error measurement parameters like the Mean Absolute Error (MAE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) are used to validate the results. A detailed mathematical and empirical analysis is given to justify the performance of the AB_AO model using an ablation study and comparative analysis. The AB_AO model acquires more stable and precise results with MSE as 18.78, MAE as 3.18, and MAPE as 0.21 than other models. It may further help to predict the vehicle count on the road, which may be of great help in reducing wastage of time in traffic congestion.
Tissue Distribution and Nutritional Regulation of Four Cholesterol Transport‐Related Genes in Tiger Puffer (Takifugu rubripes)
Authors: Xiong Haiyan , Song Ziling , Zhang Yanjiao , Meng Xiaoxue , Liao Zhangbin , Ma Qiang , Wei Yuliang , Liang Mengqing , Xu Houguo
Published: February 2024

This study characterized four cholesterol transport‐related genes, namely, lcat, acat1, acat2, and mttp, in juvenile tiger puffer in terms of tissue distribution (eye, heart, brain, skin, liver, spleen, muscle, and intestine) and nutritional regulation. Three feeding trials were conducted: (i) using diets with different cholesterol levels (0.11%, 0.65%, 1.10%, 2.32%, and 4.59% of dry matter); (ii) using diets with different lipid levels (8.05%, 12.02%, and 16.36% of dry matter); and (iii) a 1‐month starvation experiment with different sampling times (Days 1, 4, 9, 16, and 31). The lcat, acat1, and acat2 were the most abundantly expressed in the liver, while mttp was the most abundantly expressed in the intestine. The lcat had a medium expression level in the muscle and skin but the lowest expression level in the spleen and intestine. The acat1 and acat2 had similar tissue distribution patterns, except that acat2 had a lower expression level in the heart but a higher level in the intestine than acat1. The mttp had medium expression levels in the liver and spleen but had the lowest level in the eye and skin. Different dietary cholesterol levels did not significantly affect the expression of these cholesterol transport genes in the liver and intestine, except that higher cholesterol levels (1.10%–4.59%) significantly downregulated the acat2 expression in the liver. Dietary lipid levels also had a mild influence on the hepatic expression of these genes, except that the diet with 12.02% lipid resulted in significantly higher acat1 expression than the one with 16.36% lipid. The starvation time significantly affected the hepatic expression of these genes. Long‐term starvation (16 and 31 days) generally upregulated the hepatic gene expression of lcat, acat1, and mttp but generally downregulated that of acat2. This study provided preliminary knowledge about the tissue distribution and nutritional regulation of cholesterol transport‐related genes in marine teleost.
Mitochondria-Targeting and Oxygen Self-Supplying Eccentric Hollow Nanoplatform for Enhanced Breast Cancer Photodynamic Therapy
Authors: Li Jing , Wang Yu , Tao Jun , Su Xiaodan , Zhu Feipeng , Lu Wei , Han Xiaolin , Dang Meng , Weng Lixing
Published: February 2024

Photodynamic therapy (PDT) has received increasing attention for tumor therapy due to its minimal invasiveness and spatiotemporal selectivity. However, the poor targeting of photosensitizer and hypoxia of the tumor microenvironment limit the PDT efficacy. Herein, eccentric hollow mesoporous organic silica nanoparticles (EHMONs) are prepared by anisotropic encapsulation and hydrothermal etching for constructing PDT nanoplatforms with targeting and hypoxia-alleviating properties. The prepared EHMONs possess a unique eccentric hollow structure, a uniform size (300 nm), a large cavity, and ordered mesoporous channels (2.3 nm). The EHMONs are modified with the mitochondria-targeting molecule triphenylphosphine (CTPP) and photosensitizers chlorin e6 (Ce6). Oxygen-carrying compound perfluorocarbons (PFCs) are further loaded in the internal cavity of EHMONs. Hemolytic assays and in vitro toxicity experiments show that the EHMONs-Ce6-CTPP possesses very good biocompatibility and can target mitochondria of triple-negative breast cancer, thus increasing the accumulation of photosensitizers Ce6 at mitochondria after entering cancer cells. The EHMONs-Ce6-CTPP@PFCs with oxygen-carrying ability can alleviate hypoxia after entering in the cancer cell. Phantom and cellular experiments show that the EHMONs-Ce6-CTPP@PFCs produce more singlet oxygen reactive oxygen species (ROSs). Thus, in vitro and in vivo experiments demonstrated that the EHMONs-Ce6-CTPP@PFCs showed excellent treatment effects for triple-negative breast cancer. This research provides a new method for a targeting and oxygen-carrying nanoplatform for enhancing PDF effectiveness.
Digital Life Balance Scale: Validity and Reliability in the Turkish Context
Authors: Soysal Fatma Selda Oz , Kosar Egehan , Gursesli Mustafa Can , Guazzini Andrea , Duradoni Mirko
Published: February 2024

In our increasingly interconnected world, maintaining a healthy balance between online and offline activities is crucial for personal well-being. The Digital Life Balance (DLB) Scale has been introduced to understand the impact of Internet use on well-being, drawing upon the framework of the psychology of harmony and harmonization. This study is aimed at validating and assessing the reliability of the DLB Scale among Turkish university students. A sample of 424 university students (50.7% females, 49.3% males; age range: 20-31 years) participated. The scale was translated into Turkish, and its language validity was ensured through expert reviews. Confirmatory factor analysis supported the construct validity of the scale, effectively measuring Digital Life Balance in the Turkish context. Convergent validity analysis revealed significant correlations between the DLB Scale and measures of well-being and addiction tendencies. The DLB Scale exhibited good internal consistency (Cronbach’s alpha and composite reliability). Test-retest reliability analysis showed consistent responses over a three-week interval. These findings provide empirical evidence for the validity and reliability of the scale, making it a valuable tool for assessing individuals’ perceptions of balance in their online and offline activities.
Figure 6 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies
Authors: Hagos Yeman Brhane , Lecat Catherine S.Y. , Patel Dominic , Mikolajczak Anna , Castillo Simon P. , Lyon Emma J. , Foster Kane , Tran Thien-An , Lee Lydia S.H. , Rodriguez-Justo Manuel , Yong Kwee L. , Yuan Yinyin
Published: February 2024

A and B, Spatial neighborhood of immune and tumor cells (A and B) and between MGUS and NDMM (B). The P* indicate P values after multiple testing correction using the BH method. The points represent the mean and the bars are 95% CIs, indicating uncertainty. C, Sample images showing an increased number of BLIMP1+ cells in the neighborhood with CD8+ on NDMM samples (NDMM example shown here is the same image as Fig. 5L) compared with MGUS samples. D–I, Clustered or dispersed pattern of immune and tumor cells in BM trephine sample. Box plots showing the difference in NND and Z score between NDMM and posttreatment for CD8+ cells (D), BLIMP1+ cells (E), and FOXP3−CD4+ cells (F). Box plots showing the difference in NND and Z score between NDMM and MGUS for CD8+ cells (G) and BLIMP1+ cells (H), and between male and female for BLIMP1+ cells (I). The unit of NND is μmol/L. The Z score shows the significance of the difference between the NND distribution for a given cell type from a complete spatial random distribution and the observed NND (Supplementary Materials and Methods).
Figure 1 from Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies
Authors: Hagos Yeman Brhane , Lecat Catherine S.Y. , Patel Dominic , Mikolajczak Anna , Castillo Simon P. , Lyon Emma J. , Foster Kane , Tran Thien-An , Lee Lydia S.H. , Rodriguez-Justo Manuel , Yong Kwee L. , Yuan Yinyin
Published: February 2024

Overview of computational deep learning and image processing pipelines for BM MIHC images: A, MoSaicNet pipeline. The polygons (black) indicate superpixels. MoSaicNet dissects a tissue section into bone, blood, fat, and cellular tissue regions (Supplementary Materials and Methods). B, AwareNet for attention-based cell detection and classification (Supplementary Materials and Methods). The attention image pixel values were generated from the abundance of cell types. An attention image was applied to the objective function during model parameter optimization to regularize the algorithm by assigning high attention to rare cell types. The cell detection algorithm generates a cell probability map. A postprocessing algorithm was developed to find the cell nucleus center, (x, y) location, from the probability map (Supplementary Materials and Methods). A patch centered on each cell was extracted and fed to deep learning (DL)-based classifier to infer its class. C, Spatial and morphologic analysis of BM trephine samples. Bone texture and structural heterogeneity were investigated using an autoencoder-based machine learning method (Supplementary Materials and Methods). We used spatial proximity analysis to study the spatial relations of cells. r, radius. Cell density refers to the number of cells per unit of tissue area.
Supplementary Data from SUMOylation-Driven mRNA Circularization Enhances Translation and Promotes Lymphatic Metastasis of Bladder Cancer
Authors: Zhao Yue , Chen Jiancheng , Zheng Hanhao , Luo Yuming , An Mingjie , Lin Yan , Pang Mingrui , Li Yuanlong , Kong Yao , He Wang , Lin Tianxin , Chen Changhao
Published: February 2024

Figure S2
Supplementary Data from Neuronal Activity Promotes Glioma Progression by Inducing Proneural-to-Mesenchymal Transition in Glioma Stem Cells
Authors: Guo Xiaofan , Qiu Wei , Wang Chaochao , Qi Yanhua , Li Boyan , Wang Shaobo , Zhao Rongrong , Cheng Bo , Han Xiao , Du Hao , Gao Zijie , Pan Ziwen , Zhao Shulin , Li Gang , Xue Hao
Published: February 2024

Figure S7. A-NDEs do not change proliferation or apoptosis in GSCs
Supplementary Data from Neuronal Activity Promotes Glioma Progression by Inducing Proneural-to-Mesenchymal Transition in Glioma Stem Cells
Authors: Guo Xiaofan , Qiu Wei , Wang Chaochao , Qi Yanhua , Li Boyan , Wang Shaobo , Zhao Rongrong , Cheng Bo , Han Xiao , Du Hao , Gao Zijie , Pan Ziwen , Zhao Shulin , Li Gang , Xue Hao
Published: February 2024

Figure S13. miR-184-3p promotes GSC PMT and radioresistance in vitro
Supplementary Data 1 from Intratumoral Delivery of Chimeric Antigen Receptor T Cells Targeting CD133 Effectively Treats Brain Metastases
Authors: Kieliszek Agata M. , Mobilio Daniel , Upreti Deepak , Bloemberg Darin , Escudero Laura , Kwiecien Jacek M. , Alizada Zahra , Zhai Kui , Ang Patrick , Chafe Shawn C. , Vora Parvez , Venugopal Chitra , Singh Sheila K.
Published: February 2024

Unmarked.
Supplementary Table S1 from A Phase Ib First-In-Patient Study Assessing the Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of Ponsegromab in Participants with Cancer and Cachexia
Authors: Crawford Jeffrey , Calle Roberto A. , Collins Susie M. , Weng Yan , Lubaczewski Shannon L. , Buckeridge Clare , Wang Ellen Q. , Harrington Magdalena A. , Tarachandani Anil , Rossulek Michelle I. , Revkin James H.
Published: February 2024

Representativeness of Study Participants
Supplementary Methods 1 from A Phase Ib First-In-Patient Study Assessing the Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of Ponsegromab in Participants with Cancer and Cachexia
Authors: Crawford Jeffrey , Calle Roberto A. , Collins Susie M. , Weng Yan , Lubaczewski Shannon L. , Buckeridge Clare , Wang Ellen Q. , Harrington Magdalena A. , Tarachandani Anil , Rossulek Michelle I. , Revkin James H.
Published: February 2024

Summary of supplementary methods
Supplementary Figure S4 from A Phase Ib First-In-Patient Study Assessing the Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of Ponsegromab in Participants with Cancer and Cachexia
Authors: Crawford Jeffrey , Calle Roberto A. , Collins Susie M. , Weng Yan , Lubaczewski Shannon L. , Buckeridge Clare , Wang Ellen Q. , Harrington Magdalena A. , Tarachandani Anil , Rossulek Michelle I. , Revkin James H.
Published: February 2024

Median serum unbound and total ponsegromab and GDF-15 concentration–time profiles (semi-log scale)
Supplemental Table S6 from Aneuploidy Landscape in Precursors of Ovarian Cancer
Authors: Wang Yeh , Douville Christopher , Chien Yen-Wei , Wang Brant G. , Chen Chi-Long , Pinto Andre , Smith Saron Ann , Drapkin Ronny , Chui M. Herman , Numan Tricia , Vang Russell , Papadopoulos Nickolas , Wang Tian-Li , Shih Ie-Ming
Published: February 2024

Table cluster comparing the distribution of incidental active STIC to the active STIC associated with HGSC according to different aneuploidy groups.
Supplemental Table S4 from Aneuploidy Landscape in Precursors of Ovarian Cancer
Authors: Wang Yeh , Douville Christopher , Chien Yen-Wei , Wang Brant G. , Chen Chi-Long , Pinto Andre , Smith Saron Ann , Drapkin Ronny , Chui M. Herman , Numan Tricia , Vang Russell , Papadopoulos Nickolas , Wang Tian-Li , Shih Ie-Ming
Published: February 2024

Distribution of active STICs with CCNE1 and MYC/RECQL4 amplification.
Figure S4 from Paclitaxel plus Eftilagimod Alpha, a Soluble LAG-3 Protein, in Metastatic, HR+ Breast Cancer: Results from AIPAC, a Randomized, Placebo Controlled Phase IIb Trial
Authors: Wildiers Hans , Armstrong Anne , Cuypere Eveline , Dalenc Florence , Dirix Luc , Chan Steve , Marme Frederik , Schröder Carolina P. , Huober Jens , Duhoux Francois P. , Vuylsteke Peter , Jager Agnes , Brain Etienne , Kuemmel Sherko , Pápai Zsuzsanna , Menke-van der Houven van Oordt Catharina Willemien , Perjesi Luca , Mueller Christian , Brignone Chrystelle , Triebel Frederic
Published: February 2024

Kaplan-Meier plots of OS by blinded independent central review for AIPAC patient subgroups.
Supplementary Data 1 from PD-1 Blockade Induces Reactivation of Nonproductive T-Cell Responses Characterized by NF-κB Signaling in Patients with Pancreatic Cancer
Authors: Ali Lestat R. , Lenehan Patrick J. , Cardot-Ruffino Victoire , Dias Costa Andressa , Katz Matthew H.G. , Bauer Todd W. , Nowak Jonathan A. , Wolpin Brian M. , Abrams Thomas A. , Patel Anuj , Clancy Thomas E. , Wang Jiping , Mancias Joseph D. , Reilley Matthew J. , Stucky Chee-Chee H. , Bekaii-Saab Tanios S. , Elias Rawad , Merchant Nipun , Slingluff Craig L. , Rahma Osama E. , Dougan Stephanie K.
Published: February 2024

supplemental figures and legends
Supplementary Table 2 from Neoadjuvant Selicrelumab, an Agonist CD40 Antibody, Induces Changes in the Tumor Microenvironment in Patients with Resectable Pancreatic Cancer
Authors: Byrne Katelyn T. , Betts Courtney B. , Mick Rosemarie , Sivagnanam Shamilene , Bajor David L. , Laheru Daniel A. , Chiorean E. Gabriela , O'Hara Mark H. , Liudahl Shannon M. , Newcomb Craig , Alanio Cécile , Ferreira Ana P. , Park Byung S. , Ohtani Takuya , Huffman Austin P. , Väyrynen Sara A. , Dias Costa Andressa , Kaiser Judith C. , Lacroix Andreanne M. , Redlinger Colleen , Stern Martin , Nowak Jonathan A. , Wherry E. John , Cheever Martin A. , Wolpin Brian M. , Furth Emma E. , Jaffee Elizabeth M. , Coussens Lisa M. , Vonderheide Robert H.
Published: February 2024

Table S2 summarizes adverse events associated with chemotherapy administration.
Data from Absence of BTK, BCL2, and PLCG2 Mutations in Chronic Lymphocytic Leukemia Relapsing after First-Line Treatment with Fixed-Duration Ibrutinib plus Venetoclax
Authors: Jain Nitin , Croner Lisa J. , Allan John N. , Siddiqi Tanya , Tedeschi Alessandra , Badoux Xavier C. , Eckert Karl , Cheung Leo W.K. , Mukherjee Anwesha , Dean James P. , Szafer-Glusman Edith , Seymour John F.
Published: February 2024

AbstractPurpose:
Mutations in BTK, PLCG2, and BCL2 have been reported in patients with progressive disease (PD) on continuous single-agent BTK or BCL2 inhibitor treatment. We tested for these mutations in samples from patients with PD after completion of first-line treatment with fixed-duration ibrutinib plus venetoclax for chronic lymphocytic leukemia (CLL) in the phase II CAPTIVATE study.
Patients and Methods:
A total of 191 patients completed fixed-duration ibrutinib plus venetoclax (three cycles of ibrutinib then 12–13 cycles of ibrutinib plus venetoclax). Genomic risk features [del(11q), del(13q), del(17p), trisomy 12, complex karyotype, unmutated IGHV, TP53 mutated] and mutations in genes recurrently mutated in CLL (ATM, BIRC3, BRAF, CHD2, EZH2, FBXW7, MYD88, NOTCH1, POT1, RPS15, SF3B1, XPO1) were assessed at baseline in patients with and without PD at data cutoff; gene variants and resistance-associated mutations in BTK, PLCG2, or BCL2 were evaluated at PD.
Results:
Of 191 patients completing fixed-duration ibrutinib plus venetoclax, with median follow-up of 38.9 months, 29 (15%) developed PD. No baseline risk feature or gene mutation was significantly associated with development of PD. No previously reported resistance-associated mutations in BTK, PLCG2, or BCL2 were detected at PD in 25 patients with available samples. Of the 29 patients with PD, 19 have required retreatment (single-agent ibrutinib, n = 16, or ibrutinib plus venetoclax, n = 3); 17 achieved partial response or better, 1 achieved stable disease, and 1 is pending response assessment.
Conclusions:
First-line fixed-duration combination treatment with ibrutinib plus venetoclax may mitigate development of resistance mechanisms associated with continuous single-agent targeted therapies, allowing for effective retreatment.

See related commentary by Al-Sawaf and Davids, p. 471
Cytogenetic and Molecular Associations with Outcomes in Higher-Risk Myelodysplastic Syndromes Treated with Hypomethylating Agents plus Venetoclax
Authors: Bazinet Alexandre , Desikan Sai Prasad , Li Ziyi , Rodriguez-Sevilla Juan Jose , Venugopal Sangeetha , Urrutia Samuel , Montalban-Bravo Guillermo , Sasaki Koji , Chien Kelly S. , Hammond Danielle , Kanagal-Shamanna Rashmi , Ganan-Gomez Irene , Kadia Tapan M. , Borthakur Gautam , DiNardo Courtney D. , Daver Naval G. , Jabbour Elias J. , Ravandi Farhad , Kantarjian Hagop , Garcia-Manero Guillermo
Published: February 2024

Purpose:

Hypomethylating agents (HMA) combined with venetoclax are an emerging therapeutic strategy for higher-risk myelodysplastic syndromes (HR-MDS). The cytogenetic and molecular factors associated with outcomes with this combination for HR-MDS are incompletely understood.

Experimental Design:

We pooled patient data from 3 prospective trials evaluating HMA–venetoclax in HR-MDS to study associations between cytogenetic and molecular factors and overall response rate (ORR), overall survival (OS), and event-free survival (EFS). The Kaplan–Meier method was used to estimate time-to-event endpoints. Univariate and multivariate analyses using logistic regression (for ORR) or the Cox proportional hazards model (for OS and EFS) were used to identify associations between clinical, cytogenetic, and molecular factors and outcomes.

Results:

A total of 80 patients (52 HMA-naïve, 28 HMA-failure) were included. ORR was 90% in HMA-naïve and 57% in HMA-failure. Median OS was 28.2 and 8.3 months in HMA-naïve and HMA-failure, respectively. Median EFS was 17.9 and 5.5 months in HMA-naïve and HMA-failure, respectively. In addition, 24/52 (46%) of the HMA-naïve and 3/28 (11%) of the HMA-failure patients proceeded to allogeneic stem cell transplantation (SCT). Factors associated with inferior outcomes were prior HMA failure, complex cytogenetics, trisomy 8, TP53 mutations, and RAS pathway mutations. Mutations in RNA splicing, DNA methylation, and ASXL1 appeared favorable. Blast percentage was not predictive of outcomes.

Conclusions:

Knowledge of cytogenetic and molecular alterations may help identify which patients with HR-MDS benefit the most from venetoclax.
A Phase I Study of Acapatamab, a Half-life Extended, PSMA-Targeting Bispecific T-cell Engager for Metastatic Castration-Resistant Prostate Cancer
Authors: Dorff Tanya , Horvath Lisa G. , Autio Karen , Bernard-Tessier Alice , Rettig Matthew B. , Machiels Jean-Pascal , Bilen Mehmet A. , Lolkema Martijn P. , Adra Nabil , Rottey Sylvie , Greil Richard , Matsubara Nobuaki , Tan Daniel S.W. , Wong Alvin , Uemura Hiroji , Lemech Charlotte , Meran Johannes , Yu Youfei , Minocha Mukul , McComb Mason , Penny Hweixian Leong , Gupta Vinita , Hu Xuguang , Jurida Gabor , Kouros-Mehr Hosein , Janát-Amsbury Margit M. , Eggert Tobias , Tran Ben
Published: February 2024

Purpose:

Safety and efficacy of acapatamab, a prostate-specific membrane antigen (PSMA) x CD3 bispecific T-cell engager were evaluated in a first-in-human study in metastatic castration-resistant prostate cancer (mCRPC).

Patients and Methods:

Patients with mCRPC refractory to androgen receptor pathway inhibitor therapy and taxane-based chemotherapy received target acapatamab doses ranging from 0.003 to 0.9 mg in dose exploration (seven dose levels) and 0.3 mg (recommended phase II dose) in dose expansion intravenously every 2 weeks. Safety (primary objective), pharmacokinetics, and antitumor activity (secondary objectives) were assessed.

Results:

In all, 133 patients (dose exploration, n = 77; dose expansion, n = 56) received acapatamab. Cytokine release syndrome (CRS) was the most common treatment-emergent adverse event seen in 97.4% and 98.2% of patients in dose exploration and dose expansion, respectively; grade ≥ 3 was seen in 23.4% and 16.1%, respectively. Most CRS events were seen in treatment cycle 1; incidence and severity decreased at/beyond cycle 2. In dose expansion, confirmed prostate-specific antigen (PSA) responses (PSA50) were seen in 30.4% of patients and radiographic partial responses in 7.4% (Response Evaluation Criteria in Solid Tumors 1.1). Median PSA progression-free survival (PFS) was 3.3 months [95% confidence interval (CI): 3.0–4.9], radiographic PFS per Prostate Cancer Clinical Trials Working Group 3 was 3.7 months (95% CI: 2.0–5.4). Acapatamab induced T-cell activation and increased cytokine production several-fold within 24 hours of initiation. Treatment-emergent antidrug antibodies were detected in 55% and impacted serum exposures in 36% of patients in dose expansion.

Conclusions:

Acapatamab was safe and tolerated and had a manageable CRS profile. Preliminary signs of efficacy with limited durable antitumor activity were observed. Acapatamab demonstrated pharmacokinetic and pharmacodynamic activity.
Supplementary Data from Design and Evaluation of Phosphonamidate-Linked Exatecan Constructs for Highly Loaded, Stable, and Efficacious Antibody–Drug Conjugates
Authors: Schmitt Saskia , Machui Paul , Mai Isabelle , Herterich Sarah , Wunder Swetlana , Cyprys Philipp , Gerlach Marcus , Ochtrop Philipp , Hackenberger Christian P.R. , Schumacher Dominik , Helma Jonas , Vogl Annette M. , Kasper Marc-André
Published: February 2024

EC50 values and maximum killing for DXd, SN38 and exatecan on several cell lines.
Supplementary Table S9-1 from Novel Methionine Aminopeptidase 2 Inhibitor M8891 Synergizes with VEGF Receptor Inhibitors to Inhibit Tumor Growth of Renal Cell Carcinoma Models
Authors: Friese-Hamim Manja , Ortiz Ruiz Maria J. , Bogatyrova Olga , Keil Marina , Rohdich Felix , Blume Beatrix , Leuthner Birgitta , Czauderna Frank , Hahn Diane , Jabs Julia , Jaehrling Frank , Heinrich Timo , Kellner Roland , Chan Katherine , Tong Amy H.Y. , Wienke Dirk , Moffat Jason , Blaukat Andree , Zenke Frank T.
Published: February 2024

Antitumor activity of M8891 monotherapy evaluated in vivo in 10 PDX models (NSCLC, head and neck, colon, osteosarcoma, and gastric cancer) selected from the PDX in vitro evaluation (IC50 <1E−06 M)
Supplementary Table S4-1 from Novel Methionine Aminopeptidase 2 Inhibitor M8891 Synergizes with VEGF Receptor Inhibitors to Inhibit Tumor Growth of Renal Cell Carcinoma Models
Authors: Friese-Hamim Manja , Ortiz Ruiz Maria J. , Bogatyrova Olga , Keil Marina , Rohdich Felix , Blume Beatrix , Leuthner Birgitta , Czauderna Frank , Hahn Diane , Jabs Julia , Jaehrling Frank , Heinrich Timo , Kellner Roland , Chan Katherine , Tong Amy H.Y. , Wienke Dirk , Moffat Jason , Blaukat Andree , Zenke Frank T.
Published: February 2024

Tabulated IC50 and efficacy in PDX cancer cell (No. 1–125) and cancer cell line (No. 126–130) models in soft agar assays in vitro
Figure S5 from Effects of Combined Therapeutic Targeting of AXL and ATR on Pleural Mesothelioma Cells
Authors: Hirai Soichi , Yamada Tadaaki , Katayama Yuki , Ishida Masaki , Kawachi Hayato , Matsui Yohei , Nakamura Ryota , Morimoto Kenji , Horinaka Mano , Sakai Toshiyuki , Sekido Yoshitaka , Tokuda Shinsaku , Takayama Koichi
Published: February 2024

Figure S5
Supplementary Figure S11-5 from Novel Methionine Aminopeptidase 2 Inhibitor M8891 Synergizes with VEGF Receptor Inhibitors to Inhibit Tumor Growth of Renal Cell Carcinoma Models
Authors: Friese-Hamim Manja , Ortiz Ruiz Maria J. , Bogatyrova Olga , Keil Marina , Rohdich Felix , Blume Beatrix , Leuthner Birgitta , Czauderna Frank , Hahn Diane , Jabs Julia , Jaehrling Frank , Heinrich Timo , Kellner Roland , Chan Katherine , Tong Amy H.Y. , Wienke Dirk , Moffat Jason , Blaukat Andree , Zenke Frank T.
Published: February 2024

Body weight curves for renal cancer PDX model RXF-2717-bearing mice treated with vehicle, M8891 (100 mg/kg, daily, per os), axitinib (4 mg/kg, twice daily, per os), or the combination are shown
Supplementary Fig. S1 from Amelioration of Tumor-promoting Microenvironment via Vascular Remodeling and CAF Suppression Using E7130: Biomarker Analysis by Multimodal Imaging Modalities
Authors: Ito Ken , Yamaguchi Masayuki , Semba Taro , Tabata Kimiyo , Tamura Moe , Aoyama Muneo , Abe Takanori , Asano Osamu , Terada Yasuhiko , Funahashi Yasuhiro , Fujii Hirofumi
Published: February 2024

The design of gaiting information for IMC
Abstract A017: Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer
Authors: Veerla Srinivas , Hohmann Lennart , Nacer Deborah F. , Vallon-Christersson Johan , Staaf Johan
Published: February 2024

PAM50 gene expression subtypes represent a cornerstone in molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor’s underlying clinical subgroup defined by ER, PR and HER2 status. To do this we used a population-representative and clinically annotated primary breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we observed a tight connection between a tumor’s nearest and second nearest PAM50 centroid. Additionally, we show that second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node negative disease. We also note that ERBB2 has little impact on PAM50 classification in HER2-positive disease regardless of ER-status, and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum that may have clinical implications.

Citation Format: Srinivas Veerla, Lennart Hohmann, Deborah F. Nacer, Johan Vallon-Christersson, Johan Staaf. Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A017.
Abstract A062: Somatic engineering of rat models to recapitulate human breast cancer evolution and heterogeneity
Authors: Lutz Catrin , Song Ji-Ying , Messal Hendrik A , Badoux Madelon , Eijkman Timo , de Klein Bim , Wesseling Jelle , Jonkers Jos
Published: February 2024

Estrogen receptor (ER) positive breast cancer accounts for over 75% of all presenting clinical cases. In addition, almost all Ductal Carcinoma in situ (DCIS) lesions, now accounting for about 25% of all newly diagnosed ‘breast cancers’, are ER-dependent. Despite the high occurrence, the molecular underpinnings regulating DCIS initiation and progression to invasive disease remain elusive. This gap in knowledge is primarily due to the dearth of suitable preclinical models that accurately emulate breast cancer heterogeneity. To overcome this impediment, we developed a platform of somatic models by engineering the rat mammary gland and manipulating the genes most frequently mutated in hormone-dependent (pre-)breast cancer. This has successfully led to the generation of ER-positive disease models that provide a nuanced understanding of ER functionality and the complex mechanisms of ER signaling, which we show to be dependent on the cancer genotype. This has potential implications for the formulation of innovative endocrine therapy treatment regimens. Our models have generated an array of tumor types, including ductal and lobular carcinomas, manifesting both in situ and invasive phenotypes, faithfully recapitulating human breast disease and the evolution of tumorigenesis. Intriguingly, our results indicate how different oncogenic mutations modulate not only the architectural and histopathological characteristics of cancer but also the immune microenvironment, thereby generating possibilities for future therapeutic testing. Our research augments the range of available ER-positive in situ and invasive breast cancer models, benefitting the stratification of indolent from aggressive disease and facilitating the exploration of novel treatment strategies for this pervasive breast cancer subtype.

Citation Format: Catrin Lutz, Ji-Ying Song, Hendrik A Messal, Madelon Badoux, Timo Eijkman, Bim de Klein, Jelle Wesseling, Jos Jonkers. Somatic engineering of rat models to recapitulate human breast cancer evolution and heterogeneity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A062.
Abstract A077: Investigating the relationship of socioeconomic status on the molecular biology of ER+ breast cancer
Authors: DeWitt Jerry T
Published: February 2024

Black women in the US have worse health care options, poorer educational opportunities, and decreased income quality which collectively contribute to an overall lower socioeconomic status (SES) compared to White women. Furthermore, although the incidence of estrogen receptor positive (ER+) breast cancer is similar for Black and White women in the US, Black patients have significantly worse outcomes. The field has traditionally focused on systemic factors such as SES to explain outcome disparities. Consequently, differences in the molecular biology between tumors from Black and White women remains a gap in knowledge in the field. Recent studies have found that Black cancer patients have a unique gene expression profile that may modulate treatment response. For instance, ER+ breast tumors in Black women have distinct signatures of defective DNA damage repair (DDR) that associate with more aggressive tumor growth. However, how SES contributes to these differences in molecular biology and whether these differences alter treatment response remain unknown. One challenge to addressing these questions is that existing datasets significantly underrepresent Black women and are not sufficiently annotated to understand the complex interplay between molecular biology and factors of SES. Here, we present analysis of RNA expression datasets from 60 ER+ patient tumors (38 Black, 22 White), with corresponding SES and patient outcome annotations. Altogether, these data begin to define the complex interplay between factors of SES and changes in gene expression in addition to patient outcomes for women with ER+ breast cancer.

Citation Format: Jerry T DeWitt. Investigating the relationship of socioeconomic status on the molecular biology of ER+ breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A077.
Abstract B019: The bone microenvironment's impact on the heterogeneity of resistance to proteasome inhibitors in multiple myeloma
Authors: Basanta David , Bishop Ryan , Miller Anna , Lynch Conor C. , Froid Matthew , Silva Ariosto S. , Shain Kenneth H.
Published: February 2024

Multiple myeloma (MM) is an osteolytic plasma cell malignancy that, despite being responsive to therapies such as proteasome inhibitors, frequently relapses. Understanding the mechanism and the niches where resistant disease evolves remains of major clinical importance. Cancer cell intrinsic mechanisms and bone ecosystem factors are known contributors to the evolution of resistant MM but the exact contribution of each is difficult to define with current in vitro and in vivo models. Using a novel bmathematical model that incorporates key cellular species of the bone ecosystem that control normal bone remodeling and, in MM, yields a protective environment we studied how, under therapy, the bone ecosystem contributes to the evolutionary dynamics of resistant MM under control and proteasome inhibitor treatment. Our results show that Environmentally-Mediated Drug Resistance (EMDR) might not be sufficient to explain resistant disease. But our results highlight the importance of EMDR in facilitating the emergence of resistance, and more importantly facilitating the survival of tolerant cells, allowing the tumor multiple routes for resistant disease. Our results also provide evidence that intervention with therapies targetting the bone ecosystem would significantly improve the ability of treatment to increase the time to progression for patients with multiple myeloma and, potentially, other diseases where EMDR plays a role.

Citation Format: David Basanta, Ryan Bishop, Anna Miller, Conor C. Lynch, Matthew Froid, Ariosto S. Silva, Kenneth H. Shain. The bone microenvironment's impact on the heterogeneity of resistance to proteasome inhibitors in multiple myeloma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B019.
Abstract B039: SAMPLER: Unsupervised representations of whole slide images for tumor phenotype prediction
Authors: Mukashyaka Patience , Sheridan Todd B. , Foroughi pour Ali , Chuang Jeffrey H.
Published: February 2024

Deep learning has revolutionized digital pathology, allowing for automatic analysis of hematoxylin and eosin (H&E) stained whole slide images (WSIs) for various tasks, such as the classification of cancers into clinical subtypes. In such analyses, WSIs are broken down into smaller images, hereafter called tiles, for efficient processing, with each tile encoded by a deep learning backbone. To reconstruct a slide level representation, a widely applied approach is to combine tile-level features using attention-based deep learning models for each downstream prediction task. These training strategies are (a) computationally intensive, (b) challenging to optimize, (c) sensitive to stain variations across datasets, and (d) require sufficiently large and labeled datasets for supervised training, which are not always available. We propose SAMpling of multiscale empirical distributions for LEarning Representations (SAMPLER), a fully statistical approach to generate WSI representations by encoding the empirical cumulative distribution function (CDF) of multiscale tile features. We evaluated this approach by training logistic regression classifiers from SAMPLER representations. SAMPLER-based classifiers were able to accurately separate subtypes of breast carcinoma (BRCA: AUC=0.911 ± 0.029), subtypes of non-small cell lung carcinoma (NSCLC: AUC=0.940±0.018), and subtypes of renal cell carcinoma (RCC: AUC=0.987±0.006) diagnostic slides of the cancer genome atlas (TCGA). Performance was similar to fully deep learning attention models but >100 times faster. We further validated out models on external test sets. Histopathological review confirms that SAMPLER-identified high attention tiles contain tumor morphological features specific to the tumor type, while low attention tiles contain fibrous stroma, blood, or tissue folding artifacts. SAMPLER is a fast and accurate approach for analyzing WSIs, with greatly improved scalability over attention methods to benefit digital pathology analysis.

Citation Format: Patience Mukashyaka, Todd B. Sheridan, Ali Foroughi pour, Jeffrey H. Chuang. SAMPLER: Unsupervised representations of whole slide images for tumor phenotype prediction [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B039.
Supplementary Figure 5 from Spatial Transcriptomics Suggests That Alterations Occur in the Preneoplastic Breast Microenvironment of BRCA1/2 Mutation Carriers
Authors: Caputo Anthony , Vipparthi Kavya , Bazeley Peter , Downs-Kelly Erinn , McIntire Patrick , Duckworth Lauren A. , Ni Ying , Hu Bo , Keri Ruth A. , Karaayvaz Mihriban
Published: February 2024

Expression of spatially correlated receptor-ligand pairs
Uncropped Blots from SOX10 Loss Sensitizes Melanoma Cells to Cytokine-Mediated Inflammatory Cell Death
Authors: Rosenbaum Sheera R. , Caksa Signe , Stefanski Casey D. , Trachtenberg Isabella V. , Wilson Haley P. , Wilski Nicole A. , Ott Connor A. , Purwin Timothy J. , Haj Jelan I. , Pomante Danielle , Kotas Daniel , Chervoneva Inna , Capparelli Claudia , Aplin Andrew E.
Published: February 2024

Uncropped Western blots.
dataset 4 from Integrating Clinical Cancer and PTM Proteomics Data Identifies a Mechanism of ACK1 Kinase Activation
Authors: Balasooriya Eranga R. , Madhusanka Deshan , López-Palacios Tania P. , Eastmond Riley J. , Jayatunge Dasun , Owen Jake J. , Gashler Jack S. , Egbert Christina M. , Bulathsinghalage Chanaka , Liu Lu , Piccolo Stephen R. , Andersen Joshua L.
Published: February 2024

Supplementary data set 4. PTMs disrupting potential missense driver mutations.
Data from PKCδ Regulates Chromatin Remodeling and DNA Repair through SIRT6
Authors: Affandi Trisiani , Haas Ami , Ohm Angela M. , Wright Gregory M. , Black Joshua C. , Reyland Mary E.
Published: February 2024

Abstract
Irradiation (IR) is a highly effective cancer therapy; however, IR damage to tumor-adjacent healthy tissues can result in significant comorbidities and potentially limit the course of therapy. We have previously shown that protein kinase C delta (PKCδ) is required for IR-induced apoptosis and that inhibition of PKCδ activity provides radioprotection in vivo. Here we show that PKCδ regulates histone modification, chromatin accessibility, and double-stranded break (DSB) repair through a mechanism that requires Sirtuin 6 (SIRT6). Overexpression of PKCδ promotes genomic instability and increases DNA damage and apoptosis. Conversely, depletion of PKCδ increases DNA repair via nonhomologous end joining (NHEJ) and homologous recombination (HR) as evidenced by increased formation of DNA damage foci, increased expression of DNA repair proteins, and increased repair of NHEJ and HR fluorescent reporter constructs. Nuclease sensitivity indicates that PKCδ depletion is associated with more open chromatin, while overexpression of PKCδ reduces chromatin accessibility. Epiproteome analysis reveals increased chromatin associated H3K36me2 in PKCδ-depleted cells which is accompanied by chromatin disassociation of KDM2A. We identify SIRT6 as a downstream mediator of PKCδ. PKCδ-depleted cells have increased SIRT6 expression, and depletion of SIRT6 reverses changes in chromatin accessibility, histone modification and DSB repair in PKCδ-depleted cells. Furthermore, depletion of SIRT6 reverses radioprotection in PKCδ-depleted cells. Our studies describe a novel pathway whereby PKCδ orchestrates SIRT6-dependent changes in chromatin accessibility to regulate DNA repair, and define a mechanism for regulation of radiation-induced apoptosis by PKCδ.
Implications:
PKCδ controls sensitivity to irradiation by regulating DNA repair.
Supplementary Figure S5 from Genome-wide p63-Target Gene Analyses Reveal TAp63/NRF2-Dependent Oxidative Stress Responses
Authors: Napoli Marco , Deshpande Avani A. , Chakravarti Deepavali , Rajapakshe Kimal , Gunaratne Preethi H. , Coarfa Cristian , Flores Elsa R.
Published: February 2024

TAp63 and NRF2 coordinately regulate the expression of TAp63-specific target genes