bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 5344: Novel melanoma leads demonstrate efficacy in A375 xenograft model in nude mice
Authors: Minond Dmitriy , Velayutham Sadeeshkumar 
Published: April 2023

Abstract
The purpose of this study was to evaluate efficacy of novel anti-melanoma leads for in vivo efficacy. Despite the recent advances in melanoma therapy, the need for new targets and novel approaches to therapy is urgent. We previously reported novel melanoma leads, 2155-14 and 2155-18, that work via binding and downregulating spliceosomal proteins hnRNPH1 and H2. To determine the therapeutic potential of these compounds we tested them in A375 cell-line derived xenograft in nu/nu mice. For determination of 2155-14 and 2155-18 potency in vivo, nude mice were inoculated subcutaneously with A375 cell line and tumors were allowed to reach 100mm3. Animals were then randomized into four groups to receive subcutaneous administration of vehicle, 10mg/kg vemurafenib, and 25mg/kg 2155-14 and 2155-18 three times per week for 15 days. The result revealed that both 2155-14 and 2155-18 significantly decreased the growth of A375 tumors, which was comparable to vemurafenib. These results are well correlated with the exposure of leads in plasma. In summary, these results suggest a therapeutic potential of targeting spliceosomal proteins hnRNPH1 and H2 and support potential of 2155-14 and 2155-18 as drug candidates for treatment of melanoma.
Keywords: Melanoma, drug discovery, A375, xenograft.
Citation Format: Dmitriy Minond, Sadeeshkumar Velayutham. Novel melanoma leads demonstrate efficacy in A375 xenograft model in nude mice. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5344.
Abstract 5345: The application of CDK16 inhibitors in the treatment of triple-negative breast cancer
Authors: Xiao Haihua , Jiang Huangyu , Feng Kunxian , Yang Mengli , Yang Jinping , Jian Chengfang , Tian Yuan , Vasilevich Natalya , Sun Lichun 
Published: April 2023

Abstract
Triple-negative breast cancer (TNBC) with estrogen receptor (ER), progesterone receptor (PR) and HER2 (c-erbB-2, neu) being negatively expressed in patient cancer tissues displayed its unique clinical pathological difference from other types of breast cancers. TNBC is more common in younger patients and more likely to have a family history of breast cancer. TNBCs more likely have poor prognosis and postsurgical recurrence, with strong invasiveness and metastasis. However, there is lack of effective and TNBC-targeting drugs. The non-typical CDK16 was found highly expressed in TNBCs and clearly associated with prognosis and survival of patients. CDK16 could promote the progression and metastasis of TNBC by phosphorylating PRC1. Knockdown of CDK16 could significantly suppress tumor growth and metastasis. Furthermore, in our studies, rebastinib acting as a CDK16 inhibitor displayed its strong suppression of TNBC tumor growth in a dose-dependent manner, indicating rebastinib or its analogs could be druggable and likely used to treat TNBC patients.
Citation Format: Haihua Xiao, Huangyu Jiang, Kunxian Feng, Mengli Yang, Jinping Yang, Chengfang Jian, Yuan Tian, Natalya Vasilevich, Lichun Sun. The application of CDK16 inhibitors in the treatment of triple-negative breast cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5345.
Abstract 5347: Selective targeting deacetylase 3 (HDAC3) and HDAC8 by PROTACs
Authors: Xiao Yufeng , Hale Seth , Awasthee Nikee , Zhang Xuan , Liu Yi , Huo Zhiguang , Lyu Dongwen , Wang Lei , Zhang Weizhou , Mosteiro Megan , Liao Daiqing , Zheng Guangrong 
Published: April 2023

Abstract
Histone deacetylases (HDACs) are enzymes that play an essential role in multiple cellular processes such as DNA transcription, translation, replication, recombination, repair, and metabolism, and their dysregulation can be linked to many different diseases. Most commonly, the overexpression of HDACs is found in various cancer types including hematologic cancers, as well as solid malignancies. Of the many HDACs found in the body, class I HDACs, which consist of HDACs 1, 2, 3, and 8, play an essential role in activating oncogenes underlying tumorigenesis, disease progression, and treatment resistance. Several HDAC inhibitors (HDACis) have been approved for cancer treatment, however, they are pan-inhibitors. This lack of specificity poses many disadvantages for HDACis, including toxicity and other off-target effects. Isozyme-selective inhibitors may reduce these off-target effects and thus enhance their safety. Though favorable, selectivity is difficult to achieve from conventional inhibitors due to the highly homologous catalytic domain among HDAC isozymes. In addition, several HDAC isozymes have deacetylase-independent scaffolding functions that cannot be blocked by traditional inhibitors. Recently, there have been advances in Proteolysis Targeting Chimera (PROTAC), an emerging drug discovery technology designed to hijack cell’s existing protein degradation machinery, the ubiquitin-proteasome system (UPS) to selectively degrade target proteins. Selective degradation by PROTAC is a potential solution to many of the concerns associated with current HDACis. Previously, we reported an HDAC3-selective PROTAC, XZ9002, and following that we reported the discovery of PROTAC YX968, which can degrade both HDAC3 and HDAC8 isozymes with single-digit nanomolar DC50, this highly potent dual degrader exhibits distinct effects on modulating gene expression and is much more potent in inhibiting cancer cell proliferation compared to XZ9002. Based on this, we are further modifying the PROTACs to be selective for HDAC8. The HDAC3, HDAC8 selective degrader and HDAC3 and HDAC8 dual degrader we developed could be useful chemical probes to dissect the complex biological function of HDAC3 and HDAC8 and potential therapeutics for treating cancer.
Citation Format: Yufeng Xiao, Seth Hale, Nikee Awasthee, Xuan Zhang, Yi Liu, Zhiguang Huo, Dongwen Lyu, Lei Wang, Weizhou Zhang, Megan Mosteiro, Daiqing Liao, Guangrong Zheng. Selective targeting deacetylase 3 (HDAC3) and HDAC8 by PROTACs. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5347.
Abstract 5424: A deep learning approach (AI) which accurately identifies breast tumor cells, tumor infiltrating lymphocytes (TILS) and fibroblasts from H&E slides
Authors: da Silva Luiz Augusto Zillmann , Williams Alistair R. , Kubeyev Aidan , Giorni Andrea , Laurie Jordan , Sivasubramaniam Prabu , Foster Matthew , Griffiths Matthew , Asghar Uzma 
Published: April 2023

Abstract
Background: Histopathology assessments of cancers require highly skilled pathologists, are labor intensive and prone to errors without proper training or fatigue. Machine learning can assist pathologists by increasing efficiency and minimizing individual variability. This study adapted a deep learning model to reliably identify 3 cell types from triple negative breast cancers fixed on H&E slides and verified performance with an expert pathologist.
Methods: We apply the U-Net architecture to analyse pathology slides fixed with triple negative breast cancer (TNBC) tissue. The public dataset NuCLS was used for training. Semantic segmentation was used to identify single cells of 3 types: tumor cells, fibroblasts, and tumor infiltrating lymphocyte (TILs). For validation, the pathologist annotated 8 random H&E tiles. The 3 cell types accuracy for NuCLS and the model was evaluated by our pathologist.
Results: Overall, there was a 73% agreement with the pathologists (Pathologist vs. NuCLS). A set of 1,555 (90%) TNBC slides were used for training and 173 for validation (10%; unseen data). Table 1 outlines the accuracy metrics for each cell type and for each comparison. Compared to our pathologist, the model accurately identified TILs (62%), followed by fibroblasts (42%) and lastly tumor cells (26%). A significant source of discrepancy was variation in labeled single cell boundaries. The model was better at identifying TILs. The pathologist took 1.5 hours to annotate 8 tiles for the 3 cells and our model 644ms.
Conclusion: It is possible to develop a deep learning model to identify breast cancer cells, fibroblasts and TILs from H&E stained slides, with similar accuracy levels as a trained pathologist. The model performed better than a pathologist in identifying TILs, but both struggled with fibroblasts. Accuracy of 71% overall and 87% for TILs, motivates expansion to further datasets and other cancer types.
Table 1. - Accuracy metrics. Quality assessment8 H&E tiles Pathologist vs. NuCLS U-Net model vs. NuCLs U-Net model vs. Pathologist U-Net model vs. NuCLs (Full) Background 86% 71% 62% 73% Tumour 43% 35% 26% 71% Fibroblast 45% 39% 42% 31% TILs 34% 96% 62% 87% Overall 73% 74% 61% 71%
Citation Format: Luiz Augusto Zillmann da Silva, Alistair R. Williams, Aidan Kubeyev, Andrea Giorni, Jordan Laurie, Prabu Sivasubramaniam, Matthew Foster, Matthew Griffiths, Uzma Asghar. A deep learning approach (AI) which accurately identifies breast tumor cells, tumor infiltrating lymphocytes (TILS) and fibroblasts from H&E slides. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5424.
Abstract 5437: Vision transformers for breast cancer human epidermal growth factor receptor 2 (HER2) expression staging without immunohistochemical (IHC) staining
Authors: Ayana Gelan , Lee Eonjin , Choe Se-woon 
Published: April 2023

Abstract
Purpose: Staging of human epidermal growth factor receptor 2 (HER2) expression is crucial for evaluating the effectiveness of breast cancer treatment. However, it involves an expensive and challenging immunohistochemical (IHC) staining in addition to hematoxylin and eosin (H&E) staining. Here, we argue that customized vision transformers are effective in breast cancer HER2 expression staging using only H&E-stained images.
Methods: Our algorithm has three modules: a localization module to weakly localize the necessary features of an image via spatial transformers, an attention module to learn global features from the image using vision transformers, and a loss module that determines the closest one to a HER2 expression level from input images by calculating the ordinal loss. We utilized a publicly available breast cancer HER2 expression dataset, the breast cancer immunohistochemical image (BCI) dataset, which contains paired H&E and IHC stained images. Results were calculated with 95% confidence intervals and t-test was used to evaluate the significance of the proposed model against other models.
Results: Our approach achieved area under receiver operating characteristics curve (AUC), precision, sensitivity, and specificity of 0.9202±0.01, 0.922±0.01, 0.876±0.01, and 0.959±0.02, respectively, averaged over five-fold cross-validation, in staging HER2 expression. The proposed method showed better performance than the conventional vision transformer model and state-of-the-art convolutional neural network models with statistical significance of p&lt;0.01 in all cases.
Conclusion: Our findings are important in assisting HER2 expression staging in breast cancer treatment, while avoiding the need for an expensive and time-consuming IHC staining procedure.
Comparison of the proposed model with state-of-the-art models. CNN-convolutional neural network Study Neural network Model AUC Couture et al. (2018) CNN VGG16 0.75 Shamai et al. (2019) CNN ResNet50 0.74 Yang et al. (2021) CNN ResNet50 0.76 Naik et al. (2020) CNN ResNet50 0.78 Khater et al. (2021) CNN ShuffleNet 0.75 Conde-Sousa et al. (2022) CNN EfficientNet 0.88 Farahmand et al. (2022) CNN InceptionV3 0.90 Proposed Vision transformer vitb_16 0.92
Citation Format: Gelan Ayana, Eonjin Lee, Se-woon Choe. Vision transformers for breast cancer human epidermal growth factor receptor 2 (HER2) expression staging without immunohistochemical (IHC) staining. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5437.
Abstract 5508: Artesunate increases enzalutamide efficacy in advanced prostate cancer
Authors: Wang Xinyi , Mao Fengyi , Liu Jinghui , Kong Yifan , he Dang , Wang Chi , Li Zhiguo , Liu Xiaoqi 
Published: April 2023

Abstract
Prostate cancer (PCa) is the most diagnosed worldwide. PCa development and progression require androgen receptor (AR) signaling, which stimulates its downstream gene expressions and cancer progression. While second-generation anti-androgen drugs plus androgen deprivation therapy (ADT) remains the first-line treatment for advanced prostate cancer patients, around one-third of patients will relapse in a short period. Advanced prostate cancer results in more mortalities than primary PCa patients. Evidence shows that the recurrence is caused by AR overexpression, AR variants, AR mutations, and signaling crosstalk. Thus, it is urgently needed to discover a novel therapeutic strategy for treating advanced prostate cancer. The heat shock protein family (HSP), including HSP90 and HSP70, play important roles in refolding aggregated protein for cancer cell proteomic equilibrium. HSP is induced primarily by heat shock factor (HSF1). As AR’s chaperone protein, HSP70 and HSP90 increase AR transcription activity. Inhibiting HSP70 and HSP90 promotes STUB1, an E3 ligase, binding to AR and AR - V7, and ubiquitination. Artesunate (ART) is a semi-synthetic ingredient from Artemisia annua and is the most common treatment for malaria throughout the world. It was approved for medical use by the FDA (Food and Drug Administration) (Food and Drug Administration). Recently ART has been unveiled for its anticancer properties. However, the efficacy of ART treatment in advanced prostate cancer and the direct target of ART have not been investigated yet. Herein, we have examined the efficacy of combining Enzalutamide (Enza) and ART in advanced prostate cancer cell lines. We also performed unbiased bioinformatics analysis using RNA seq results in enzalutamide-resistant cell line C4-2R cells and 22RV1 cells to investigate the cell response toward ART treatment. We identified ART could downregulate of AR signaling pathway. Moreover, we determined that ART treatment induces AR degradation in proteasome dependent manner. Interestingly, we found HSP70 and HSP90 are also decreased in RNA seq results. Taking these together suggests that ART may target HSF1 directly. Our results suggest ART induced AR degradation could be a promising clinical strategy for advanced prostate cancer.
Citation Format: Xinyi Wang, Fengyi Mao, Jinghui Liu, Yifan Kong, Dang he, Chi Wang, Zhiguo Li, Xiaoqi Liu. Artesunate increases enzalutamide efficacy in advanced prostate cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5508.
Abstract 5635: Joint secondary transcriptomic analysis of triple negative breast cancer offers a window into new therapeutic possibilities and biomarkers
Authors: Rapier-Sharman Naomi , Poulsen Jenna Birchall , Dobbs Mauri E. , Pickett Brett E. 
Published: April 2023

Abstract
Breast cancer is a harmful growth of mutated breast tissue that is diagnosed in 2.3 million women yearly, and kills 685,000 patients (15%) each year around the world. Left unchecked, breast cancer can grow proliferatively and metastasize to new tissue sites, monopolizing the body’s energy supply and ultimately causing organ failure and death. Due to increased use of treatments targeting the breast tumor-specific markers Estrogen Receptor (ER), Progesterone Receptor (PR), and Human Epidermal growth factor Receptor 2 (HER2), patient survival of breast cancer has increased in recent years. However, patients with triple-negative breast cancer (TNBC), tumors lacking all three commonly-targeted biomarkers, suffer greater illness, experience more frequent relapse, and enjoy a shorter lifespan compared to other breast cancer patients due to the paucity of tumor-selective treatments for TNBC. Further research on TNBC is needed to understand targetable mechanisms and develop treatments capable of targeting the key mechanisms. To investigate the transcriptomic profiles of TNBC tumors, we performed a joint secondary analysis of publicly available RNA-sequencing data for TNBC, consisting of 214 relevant samples across 11 distinct studies in the NCBI Gene Expression Omnibus (GEO). We found ~12,500 significant differentially expressed genes (FDR p-value ⇐ 0.05) and 67 significantly modulated pathways (FDR p-value ⇐ 0.05). Additionally, our novel findings include candidates for drug repurposing, high-integrity predictive biomarkers, and potential new TNBC molecular mechanisms. We found several TNBC drug targets that have not yet been fully leveraged along with drugs that could likely be successfully repurposed for use in TNBC based on previous target history and our transcriptomic results. This joint secondary analysis opens the door to future therapeutic options that could increase patient survival once validated in the wet lab.
Citation Format: Naomi Rapier-Sharman, Jenna Birchall Poulsen, Mauri E. Dobbs, Brett E. Pickett. Joint secondary transcriptomic analysis of triple negative breast cancer offers a window into new therapeutic possibilities and biomarkers. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5635.
Abstract 5646: Spatial transcriptomic profiling of the human and mouse retina prepared with CryoJane Tape Transfer System using GeoMx and CosMx spatial analysis
Authors: Glaser Charles , Ma Su , Yang Wei , Liang Yan , Beechem Joeseph , Bonilha Vera L. , Rao Sujata , Horrigan William , Anand-Apte Bela 
Published: April 2023

Abstract
The goal of this study is to identify key transcriptomic markers within layers of the retina by individually profiling layers using cellular and subcellular spatial transcriptomics, additionally, comparing the results between each level. Both human and mouse retina samples, prepared fresh frozen and fixed frozen, are analyzed using the GeoMx® Digital Spatial Profiler (DSP) and CosMx® Spatial Molecular Imager (SMI) using the whole mouse transcriptome atlas and 1000-plex mouse neuro panel, respectively. Samples are fixed using Cryo-Jane Taper Transfer system. Samples are mounted on to adhesive coated slides as well as adhesive tape to mount samples to glass slides. This method is used to secure fragile frozen tissue, such as the retina. Human and mouse samples were stained using immunofluorescent microscopy targeting neurofilament H (NF-H), glial fibrillary acidic protein (GFAP) and NeuN on DSP and 18s rRNA, amyloid-beta and GFAP on SMI. Staining allows for identification of structural layers in the retina. Simultaneously, regions of interest (ROI) for spatial profiling are selected based on immunofluorescent stains. On DSP, each sample had 3x ROIs in the photoreceptor layer, inner nuclear layer and ganglion cell layer, then, oligonucleotides were collected and sequenced. Finally, raw counts were Q3 normalized for analysis. For SMI data analysis, 6 field of views (FOVs) were put on each section to cover most regions with multiple layers. ~8000 genes were detected on human retina samples using DSP. Around 500 unique genes were detected between the photoreceptor and inner nuclear layer using DSP. Preliminary SMI results show we were able to identify cell types (amacrine, horizontal cell, biopolar cell, ganglion cell, etc) and cell specific markers for outer nuclear layer, inner nuclear layer and ganglion cell layer. Data between DSP and SMI showed high concordance with one another, identifying many genes in each layer.
Citation Format: Charles Glaser, Su Ma, Wei Yang, Yan Liang, Joeseph Beechem, Vera L. Bonilha, Sujata Rao, William Horrigan, Bela Anand-Apte. Spatial transcriptomic profiling of the human and mouse retina prepared with CryoJane Tape Transfer System using GeoMx and CosMx spatial analysis. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5646.
Abstract 5653: LCB97, an antibody drug conjugate (ADC) targeting a novel tumor antigen for the treatment of multiple solid tumors
Authors: Jeong Yeojin , Spohn Gunther , Mehli Flavio , Chung Chul-Woong , Park Changsik 
Published: April 2023

Abstract
LCB97 is an antibody-drug conjugate (ADC) directed against a novel tumor antigen, composed of monomethyl auristatin E (MMAE) as payload (DAR 4) and the humanized IgG1 antibody AFF4 generated by Elthera. AFF4 targets a novel antigen preferentially expressed in various solid tumors including pancreatic cancer, ovarian cancer, colon cancer, breast cancer and melanoma. LCB97 generated by using LCB’s ConjuAllTM technology with AFF4 showed potent cytotoxicity in various cancer cell lines including breast cancer (BC), ovarian cancer (OC), pancreatic cancer (PaC), small cell lung cancer (SCLC), colorectal cancer (CRC) and melanoma. LCB97 also showed excellent anticancer efficacy in several cell line-derived xenograft (CDX) models, including BC, CRC, OC and melanoma. Preliminary toxicity assessment in cynomolgus monkeys (an AFF4 cross reactive species) demonstrated that LCB97 was well tolerated within the estimated therapeutic index of ~20 for repeat dosing. In conclusion, LCB97, generated by combining theAFF4 monoclonal antibody of Elthera and the highly innovative ConjuAllTM platform technology of LegoChem Biosciences is a promising next-generation ADC for the treatment of various solid cancers, including BC, CRC, melanoma, OC and PaC.
Citation Format: Yeojin Jeong, Gunther Spohn, Flavio Mehli, Chul-Woong Chung, Changsik Park. LCB97, an antibody drug conjugate (ADC) targeting a novel tumor antigen for the treatment of multiple solid tumors. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5653.