bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 467: Integrative deep learning analysis identifies cross-talk between morphology, mutation, and clinical variables for colon adenocarcinoma patient outcomes
Authors: Zhou Jie , Foroughi pour Ali , Beydoun Rafic , Deirawan Hany , Daaboul Fayez , Ahmed Fahad Shabbir , Chuang Jeffrey H.
Published: June 2022

Colorectal cancer is one of the most common cancers in both men and women. Patient stratification in colorectal cancers is challenging and affects therapy decisions and patient care. In this study, we develop an integrative Inception V3-based deep learning approach to stratify TCGA-COAD patients from H&E images, showing that combining deep learning extracted morphological features with clinical and mutational status improves patient stratification. Morphological features within tumor regions can distinguish patients by short or long overall survival (OS) (OS<3 years v.s. OS>5 years, AUC 0.81±0.12), while they are less informative for intermediate OS (3<OS<5 years). Models that integrate morphological features with additional data modalities yield superior stratification to those that use only a single datatype or that use only clinical information and genomic markers. Remarkably, combining deep learning morphological features with clinical information and genomic markers also boosts stratification of patients with 3<OS<5 years, both at the 3-year time point (p <0.001) and 5-year time point (p <0.001). We validated our model on an external dataset (OS<3 years v.s. OS>5 years, AUC 0.78±0.20), and again found that combining morphological features and clinical data is superior to only using a single datatype. Our deep learning models were also able to perform reliable tumor segmentation (AUC>0.92). However, survival predictions based on deep learning tumor segmentation were inferior to those based on pathologist tumor annotations (OS<3 years v.s. OS>5 years, AUC 0.79±0.14). Furthermore, we show that the cross-talk between different data modalities is informative of patient risk. More precisely, models that directly combine image and clinical features performed superior to a naïve Bayes classifier combining predictions of models trained on each data type (integrative model AUC=0.81±0.06 and naïve Bayes AUC=0.76±0.11, p<0.01). Our results show integrative analysis utilizes the cross-talk between data modalities to boost patient risk stratification, and that deep learning is an efficient methodology for taking advantage of cross-talk between various data modalities.

Citation Format: Jie Zhou, Ali Foroughi pour, Rafic Beydoun, Hany Deirawan, Fayez Daaboul, Fahad Shabbir Ahmed, Jeffrey H. Chuang. Integrative deep learning analysis identifies cross-talk between morphology, mutation, and clinical variables for colon adenocarcinoma patient outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 467.
Abstract 480: Consensus subtypes of hepatocellular carcinoma associated with clinical outcomes, response to therapies, and multiple biomarkers
Authors: Lee Sung Hwan , Lee Ju-Seog
Published: June 2022

Background & aims: While many studies revealed genomic subtypes of hepatocellular carcinoma (HCC), they are not translated to the clinic yet due to lack of consensus. We aim to examine consensus of genomic subtypes and uncover their clinical significance.

Methods: We integrated 15 previously established genomic signatures for HCC to uncover consensus genomic subtypes. We also developed and validated a robust predictor of consensus subtype with 100 genes (PICS100). Informatics and statistics approaches were applied to find clinical relevant association of genomic features. Patient derived xenograft (PDX) models were used for testing hypothesis from analysis of genomic data.

Results: We identified 5 clinically and molecularly distinct consensus subtypes. STM (STeM) is characterized by high stem cell features, vascular invasion, and poor prognosis. CIN (Chromosomal INstability) has moderate stem cell features but high genomic instability and low immune activity. IMH (IMmune High) is characterized by high immune activity. BCM (Beta-Catenin with high Male predominance) is characterized by prominent β-catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. DLP (Differentiated and Low Proliferation) is differentiated with high HNF4A activity. We also identified potential serum biomarkers that can stratify patients into 5 subtypes. Because these subtypes are highly associated with currently available treatments, our findings may provide the foundation for rationalized biomarker-based clinical trials.

Conclusions: Five HCC subtypes are highly associated with response to standard and experimental treatments and highly conserved in pre-clinical models, providing a framework for selecting the most appropriate models for preclinical studies and rationalized clinical trials of new drugs.

Citation Format: Sung Hwan Lee, Ju-Seog Lee. Consensus subtypes of hepatocellular carcinoma associated with clinical outcomes, response to therapies, and multiple biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 480.
Abstract 5005: PSMB9/LMP2 as a controversial diagnostic biomarker for uterine leiomyosarcoma
Authors: Maia Raul , Kokaraki Georgia , Souza Jorge E. , Carlson Joseph W. , Petta Tirzah B.
Published: June 2022

Uterine leiomyosarcoma (uLMS) are rare and malignant tumors that arise in the cells of the myometrium. Diagnosis is based on histopathological features. Developing effective therapies against uLMS is a challenge due its resistance to conventional radiation and chemotherapy. In vivo and in vitro models for uLMS are urgently needed and it has been proposed that knockout mice for the gene PSMB9 (MIM:177045), also known by LMP2, could be a good model to study uLMS. Previous studies using mice homozygous deficiency for PSMB9 presented abnormalities in the biological functions of the immunoproteasome and spontaneously developed uLMS thus suggesting this gene as a tumor suppressor gene. Furthermore, expression of PSMB9 was suggested to be a specific biomarker for the diagnosis of uLMS. The goal of this study was to evaluate the role of PSMB9 in uLMS using in silico analysis of transcriptomics data from a patient cohort, combined with publicly available datasets. Molecular data were integrated and used for a meta-analysis of RNA-seq in order to find Differentially Expressed Genes (DEGs). A total of 68, 66 and 67 samples from normal myometrium (MM), uterine leiomyoma (LM) and uLMS, respectively, were analyzed. A quality control followed by adapter removal and alignment step was assessed using FastQC, Trim-galore and HISAT2 software respectively and counting reads was performed using htseq-count. Expression values were calculated as Transcripts Per Million (TPM) in order to remove libraries dependencies. Differential expression analysis was done using DESeq2 and edgeR and genes were classified as DEG when that had adjusted p-value < 0.01 and |log2FC| ≥ 2 in both packages. Gene Set Enrichment Analysis was performed using fgsea package with 100,000 permutations and MSigDB collections (KEGG and Reactome) as input parameters. Our results showed an over-expression of PMSB9 in uLMS samples and immune-related pathways were significantly enriched. Moreover, the overall survival analysis for the outcome of uLMS patients based on PSMB9 expression in TCGA showed no significant changes, further questioning the importance of PSMB9 in uLMS malignancy. Finally, based on phylogenetic analysis we showed that PSMB9 conservation between Mus musculus and Homo sapiens is not closely related. This divergence suggests that the biological role of PSMB9 may differ between M. musculus and H. sapiens. Human uLMS exhibits an over-expression in PSMB9 and these findings suggest PSMB9-deficient mice are not an appropriate diagnostic-biomarker for uLMS.

Citation Format: Raul Maia, Georgia Kokaraki, Jorge E. Souza, Joseph W. Carlson, Tirzah B. Petta. PSMB9/LMP2 as a controversial diagnostic biomarker for uterine leiomyosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5005.
Abstract 501: Acute kidney injury induced by allogeneic hematopoietic stem cell transplantation: disease understanding and treatment with nanotechnology-based therapeutics
Authors: Panagiotakopoulou Magdalini , Grabarnik Emma , Jaimes Edgar A. , van den Brink Marcel R. , Heller Daniel A.
Published: June 2022

Allogeneic hematopoietic stem cell transplantation (allo-HCT) is a highly effective treatment for a variety of hematologic malignancies, but also associated with serious complications, such as graft-versus-host-disease (GVHD), a severe immune condition that manifests in multiple organs including the kidneys. Kidney injury in the setting of allo-HSCT has an incidence as high as 80% and leads to high patient morbidity and mortality, however, its progression and mechanisms remain poorly characterized. Moreover, no approved drugs for AKI of any etiology exist, as most experimental therapies have poor pharmacokinetic profiles and minimal efficacy in treating AKI in humans. We have characterized the pathology, genetic and molecular signatures of GVHD-mediated AKI in a murine model of HCT. GVHD results in AKI characterized predominantly by T-cell infiltration and activation of inflammatory pathways in both donor infiltrating inflammatory cells, as well as resident cells (i.e. tubules). By RNA sequencing, we have identified specific inflammatory pathways that are differentially expressed between healthy and GVHD mice and can serve as targets for therapeutic intervention. Moreover, we have synthesized nanoparticles that can specifically target proteins overexpressed in GVHD-kidneys and can encapsulate a variety of small molecule drugs. The complete understanding of this disease and development of this technology has a high potential to improve clinical practice and patient prognosis after allo-HCT, but it can also serve as a platform for treating other forms of cancer-associated kidney injury (e.g. induced by nephrotoxic chemotherapy), thus affecting the life of numerous patients.

Citation Format: Magdalini Panagiotakopoulou, Emma Grabarnik, Edgar A. Jaimes, Marcel R. van den Brink, Daniel A. Heller. Acute kidney injury induced by allogeneic hematopoietic stem cell transplantation: disease understanding and treatment with nanotechnology-based therapeutics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 501.
Abstract 5011: Meta-analysis of human cancer single cell RNAseq datasets using the fully integrated IMMUcan database
Authors: Camps Jordi , Noel Floriane , Liechti Robin , Goetz Lou , Hoffmann Caroline , Massenet-Regad Lucile , Amblard Elise , Saichi Melissa , Ibrahim Mahmoud M. , Pollard Jack , Medvedovic Jasna , Roider Helge G. , Soumelis Vassili
Published: June 2022

The development of single cell RNA-sequencing (scRNAseq) technologies has greatly contributed to deciphering the tumor microenvironment (TME) landscape, and a wealth of biological data is now publicly accessible. This represents a very valuable resource to researchers in the field, offering a reference for comparison of novel results, as well as opportunities for original meta-analysis studies. However, the massive amount of biological information renders its exploitation difficult in the absence of a well-structured and annotated resource. Marked heterogeneity and variability between studies in terms of cancer type, clinical context, technological platform, data quality, number and type of cells, create additional bottlenecks. We have developed a fully integrated scRNAseq database exclusively dedicated to human cancer. It gathers 134 datasets on 51 different cancer types, annotated in 50 fields containing precise clinical, technological and biological information. We developed an original data processing pipeline organized in 4 steps: first, data collection; second, data processing, which includes quality control, sample integration, cell clustering; third, cell ontology tree of the TME, built and used to annotate the clusters in a supervised and manual manner; and fourth, interface to analyze TME in a cancer type-specific or global manner. This integrated, accessible and user-friendly resource should be of great value to the biomedical community. It represents an unprecedented level of detailed annotation, offering vast possibilities for downstream exploitation of human cancer scRNAseq data for discovery and validation studies. The database is freely accessible at: https://immucanscdb.vital-it.ch.

Citation Format: Jordi Camps, Floriane Noel, Robin Liechti, Lou Goetz, Caroline Hoffmann, Lucile Massenet-Regad, Elise Amblard, Melissa Saichi, Mahmoud M. Ibrahim, Jack Pollard, Jasna Medvedovic, Helge G. Roider, Vassili Soumelis. Meta-analysis of human cancer single cell RNAseq datasets using the fully integrated IMMUcan database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5011.
Abstract 5024: Aging patterns in five disparate cancer entities indicate a novel senescent cell population with therapeutic targetability
Authors: Saul Dominik , Kosinsky Robyn Laura
Published: June 2022

Human aging is associated with molecular changes and cellular degeneration, resulting in a significant increase in cancer incidence with age. Whether aging as its own entity can be initiator of putative cancerous developments, the transcriptional changes underlying the cancerous development itself are largely unknown. Here, we analyzed publicly available bulk RNA sequencing data of 328 control vs. 453 cancer samples in combination with single cell sequencing datasets from 49 control vs. 105 cancer patients. Using widely accepted aging-associated gene sets, we assembled key features of aging and their reflection in cancer development in five distinct cancer entities with an age-dependent increase of incidence, i.e. chronic myeloid leukemia (CML), colorectal cancer (CRC), hepatocellular carcinoma (HCC), lung cancer (LC) and pancreatic ductal adenocarcinoma (PDAC). After confirmation of the aging/senescence-induced gene (ASIG) expression to be upregulated in malignant diseases compared to healthy controls, we elucidated the importance of ASIGs during single cell development, making use of pseudotime analyses. In each entity, distinct temporally late enrichment states were carved out, and their transcriptional connectivity next to epigenetic control verified. Remarkably, we were able to demonstrate that all cancer entities analyzed in this study comprised cell populations expressing ASIGs. Except for pancreatic cancer, all entities accounted for subpopulations with aging associated patterns. Using a novel pipeline to repurpose FDA-approved drugs and combinations on a single cell level, we discovered a path for novel treatment regimen on a tumor-specific basis. These respective cellular subpopulations demonstrate pillars of susceptibility within the complex tumor microenvironment and serve as a basis for future studies on the role of aging and senescence in human malignancies.

Citation Format: Dominik Saul, Robyn Laura Kosinsky. Aging patterns in five disparate cancer entities indicate a novel senescent cell population with therapeutic targetability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5024.
Abstract 5031: Improved deconvolution of combined bulk and single-cell RNA-sequencing data
Authors: Lei Haoyun , Guo Xiaoyan A. , Tao Yifeng , Ding Kai , Fu Xuecong , Oesterreich Steffi , Lee Adrian V. , Schwartz Russell
Published: June 2022

Identifying how cell types and their abundances evolve during tumor progression is critical to understanding the mechanisms and identifying predictors of metastasis. Single-cell RNA sequencing (scRNA-seq) has been especially promising in resolving heterogeneity of expression programs at the single cell level but is not always available, for example for large cohort studies or longitudinal analysis of archived samples. In such cases, cell subpopulations must be inferred by deconvolution, a process that can infer single-cell genomic data from bulk data but has limited ability to resolve fine clonal structure. We extend our previous bulk genomic deconvolution tool, Robust and Accurate Deconvolution (RAD), to establish a new method, scRAD, that can use reference scRNA-seq to interpret sample collections for which only bulk RNA-seq is available for some samples, e.g., clonally resolving archived primary (PRM) tissues using scRNA-seq from metastases (METs). We preprocess scRNA-seq data to accurately represent gene expression profiles, yielding a signature matrix S then extend our RAD method via a regularization term to deconvolve bulk data while maximizing consistency with S. We validate our method on semi-synthetic data derived from human PRM breast cancer cases and bone and ovary METs, showing that scRAD improves inference of single-cell gene expression profiles and their frequencies relative to the prior RAD with random initialization or initialization using the single-cell matrix S (Table 1). We then apply scRAD to a collection of paired PRM and MET tumors to quantify progression changes in common cell types. One-sided Kaplan-Meier analysis shows that tumors inferred to increase the mast cell fraction from PRM to MET exhibit lower overall survival (p<0.05), consistent with the role of mast cells in metastatic growth and propagation. Tumors that show increased macrophage cell fraction from PRM to MET show improved overall survival (p<0.04), consistent with the role of immune infiltration in survival.

mean square error (MSE) of gene expression and mixture fraction inference on semi-simulated data Method RAD with random initialization RAD with random initialization RAD with random initialization RAD initialized with S RAD initialized with S RAD initialized with S scRAD scRAD scRAD Sample number 2 4 8 2 4 8 2 4 8 Gene Expression MSE 0.41 0.28 0.37 0.31 0.27 0.37 0.22 0.15 0.13 Mixture fraction MSE 0.58 0.82 0.59 0.39 0.83 0.58 0.19 0.20 0.22

Citation Format: Haoyun Lei, Xiaoyan A. Guo, Yifeng Tao, Kai Ding, Xuecong Fu, Steffi Oesterreich, Adrian V. Lee, Russell Schwartz. Improved deconvolution of combined bulk and single-cell RNA-sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5031.
Abstract 504: Membrane-associated heat shock protein mHsp70 is involved in cancer cell invasion and tumor recurrence in malignant brain tumors
Authors: Shevtsov Maxim , Tagaeva Ruslana , Yudintceva Natalia , Bobkov Danila , Goncharova Darya , Kim Alexander , Fedorov Evgeniy , Nechaeva Anastasia , Mihrina Anastasia , Patruhina Anna , Fedorov Vyacheslav , Samochernykh Konstantin
Published: June 2022

Heat shock proteins (HSPs) constitute a large family of highly conserved proteins acting as molecular chaperones that play a key role in intracellular proteostasis, regulation of apoptosis, and protection from various stress factors (including hypoxia, thermal stress, oxidative stress). Apart from their intracellular localization, members of different HSPs families such as Hsp70 have been found to be localized on the plasma membrane of malignantly transformed cells, including multiforme glioblastoma (GBM). However, the role of the membrane-bound mHsp70 has not yet been elucidated in the pathophysiology of GBM. We have assessed the mHsp70 expression in biopsies obtained from neuro-oncological patients employing inverted confocal microscopy (Leica Microsystems) and CellVoyager CQ1 Benchtop High-Content Analysis System (Yokogawa). Live-cell imaging of the patient-derived biopsy revealed the increased cellular density of mHsp70-positive tumor cells particularly in the tissue along the tumor-brain margin (biopsy was derived 3 mm from contrast-enhancing margin and also within hyperintense FLAIR). Time-lapse analysis of the tumor sample further demonstrated the migration of mHsp70-positive cells into the surrounding culture medium. Subsequent high-powered multiplex immunofluorescence analysis (Akoya Biosystems Inc.) confirmed markedly increased single-cell infiltration of mHsp70(+) tumor cells (that were also co-immunofluorescently stained for SOX2, Nestin, and Oct4) in the normal brain tissues. In conclusion, expression of mHsp70 on the plasma membrane of tumor cells corresponds to the highly invasive potential of the GBM cells and recurrence of these tumors in neuro-oncological patients. This research was funded by the Ministry of Science and Higher Education of the Russian Federation (Agreement № 075-15-2020-901).

Citation Format: Maxim Shevtsov, Ruslana Tagaeva, Natalia Yudintceva, Danila Bobkov, Darya Goncharova, Alexander Kim, Evgeniy Fedorov, Anastasia Nechaeva, Anastasia Mihrina, Anna Patruhina, Vyacheslav Fedorov, Konstantin Samochernykh. Membrane-associated heat shock protein mHsp70 is involved in cancer cell invasion and tumor recurrence in malignant brain tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 504.
Abstract 5045: Genomics and pathology based deep learning to predict cancers of unknown primary
Authors: Wang Yanan , Zhang Guanjun , Liu Xi , Xi Yanfeng , Wang Pan , Zhang Yuman , Li Xing
Published: June 2022

Background: Cancers of unknown primary (CUP) are a type of metastatic cancer. However, their primary anatomical site of origin cannot be clinically determined using routine history inquiries, laboratory tests, endoscopy, and imaging. CUP account for ~3-5% of cancers. Empirical chemotherapy (paclitaxel, carboplatin, etc.) is generally used, although the curative effect is poor. Finding the primary site of origin for CUP patients is of great significance for clinical treatment.

Method: Our study employed 10,001 pathological images and 9,775 gene detection data points based on whole-exome sequencing (WES) or YUANSU®(OrigiMed, Shanghai, China) for primary cancer within a database containing 32 common cancers. We applied machine learning algorithms (autoML, Transformers, attention) and constructed two diagnostic models. The models diagnosed by identifying pathological images (Model 1) and genomic data (Model 2). Accuracy for the two models was verified.

Result: Both models were evaluated using top-k differential diagnosis accuracy, in other words how often the ground truth label was found for k highest confidence predictions for the model. The pathological model (Model 1) achieved a top-3 accuracy of 83.38% and a top-5 accuracy of 90.36%. Using the same methodology, genomic model (Model 2) results were 87.5% and 92.2%, respectively.

Conclusion: Using deep learning, we developed diagnostic models for CUP based on pathological images and genomic data. Accuracy for both the pathological image model (Model 1) and the genomic data model (Model 2) was not satisfactory. To improve diagnostic accuracy, further studies on developing a diagnostic model that combines pathological imaging and genomic data are ongoing..

Citation Format: Yanan Wang, Guanjun Zhang, Xi Liu, Yanfeng Xi, Pan Wang, Yuman Zhang, Xing Li. Genomics and pathology based deep learning to predict cancers of unknown primary [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5045.
Abstract 5062: Identification of synthetic lethal gene interactions to discover novel cancer vulnerabilities and guide drug development
Authors: Parikh Mukti , García-Quismondo Manuel , Madhukar Neel S. , Gilvary Coryandar
Published: June 2022

Poor treatment responses in patients and drug resistance are main challenges in the clinic which can arise due an incomplete understanding of genetic dependencies within cancers and an ill defined patient population. Identifying synthetic lethal (SL) relationships between a gene pair, where loss of either of the participating genes has no effect on cancer cells, however simultaneous disruption of both genes leads to cancer cell death, can uncover major survival mechanisms and expose vulnerabilities within cancers. In spite of advances in CRISPR or RNAi based loss of function screening it is difficult to identify these gene interactions solely by experimentation due to the vast mutational landscape of cancers, inability of cell lines to capture clinically relevant mutations, and large number of possible SL gene combinations. Furthermore, large scale CRISPR/RNAi screens are prone to false positive results, leading to erroneous identification of gene interactions. We developed a machine learning model to identify SL genetic interactions by integrating pathway, ontology, genomic, and loss of function features on all gene pairs. This included features, which have been shown to be predictive of SL pairs such as, involvement in important cancer hallmark processes or signaling pathways, co-expression profile in patient cancers, and many more. The model was trained using SL pairs from published large scale experimental screens across several cancer types, ultimately enabling the prediction of cancer agnostic SL pairs. Non-SL pairs had to be computationally defined using post-perturbation gene expression profiles due to the lack of published data annotating non-SL pairs. The model showed significant predictive performance (AUROC = 0.94, AUPRC = 0.93, Specificity = 0.91), additionally, when tested on a gold standard, biologically verified set of SL gene pairs across several cancer types, the model showed good generalizability. We leveraged the model to identify key clinically relevant SL relationships and uncover complementary mechanisms tied to pro-survival processes. By identifying SL gene interacting pairs, our platform can help gain a better understanding of dominant mechanisms driving cancers and guide the discovery of novel therapies, biomarkers, and combination therapies early on during drug development.

Citation Format: Mukti Parikh, Manuel García-Quismondo, Neel S. Madhukar, Coryandar Gilvary. Identification of synthetic lethal gene interactions to discover novel cancer vulnerabilities and guide drug development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5062.
Abstract 5077: Proteomics analysis of extracellular vesicles from pancreatic cancer cells and cancer associated fibroblasts
Authors: Pan Sharon , Lai Lisa A. , Simeone Diane M. , Dawson David W. , Yan Yuanqing , Crnogorac-Jurcevic Tatjana , Chen Ru , Brentnall Teresa A.
Published: June 2022

Extracellular vesicles (EVs) are comprised of lipid bound vesicles secreted by cells into the extracellular environment with various roles in cell-to-cell communication. Recent studies have implicated EVs in cell proliferation, epithelial-mesenchymal transition (EMT), metastasis, angiogenesis, and mediating the interaction of tumor cells and tumor microenvironment. To systematically characterize the EVs associated with pancreatic cancer, we performed proteomic and functional analyses on the protein contents of EVs released from pancreatic cancer lines, CAF cell lines and a normal pancreatic epithelial cell line. More than 1400 non-redundant proteins were identified in each EV proteome derived from these cell lines. The common EV proteins identified in these cell lines were enriched in biological processes such as vesicle-mediated transport and exocytosis. Protein networks relevant to pancreatic tumorigenesis, such as of EMT, complement and coagulation components, were significantly enriched in the EVs from cancer cells or CAFs in comparison to normal pancreatic epithelial cells. These findings support the roles of EVs as a potential mediator in transmitting EMT signals and complement response in the tumor microenvironment and possibly contributing to coagulation defects related to cancer development.

Citation Format: Sharon Pan, Lisa A. Lai, Diane M. Simeone, David W. Dawson, Yuanqing Yan, Tatjana Crnogorac-Jurcevic, Ru Chen, Teresa A. Brentnall. Proteomics analysis of extracellular vesicles from pancreatic cancer cells and cancer associated fibroblasts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5077.
Abstract 5104: Extracellular vesicles expressing CEACAM proteins in the urine of bladder cancer patients
Authors: Igami Ko , Uchiumi Takeshi , Shiota Masaki , Ueda Saori , Eto Masatoshi , Kang Dongchon
Published: June 2022

Purpose: Early detection and long-term monitoring are important for urothelial carcinoma of the bladder (UCB). Urine cytology and existing markers have insufficient diagnostic performance. Here, we used medium-sized extracellular vesicles (EVs) in urine to find specific markers for UCB and evaluate their usefulness as diagnostic material.

Experimental Design: To search for specific markers in urinary EVs derived from UCB, we performed a comparative analysis using shotgun proteomics with urine from four UCB patients and four healthy subjects. Next, we used male 24 healthy specimens, 18 non-cancer specimens, and 29 UCB specimens for analysis of urinary EVs using a flow cytometer to evaluate the diagnostic performance of UCB-specific EVs.

Results. NTA analysis showed that the size of EVs extracted from urine by centrifugation was mostly less than 400 nm. By shotgun analysis of EVs, we detected several proteins characteristic of UCB and found that CEACAM proteins was increased in patients. Flow cytometric analysis revealed that the degree of expression of CEACAM1, 5, and 6 antigens on the surface of EVs varied among patients. EVs expressing CEACAM antigens also expressed MUC1, suggesting that they were derived from tumorigenic uroepithelial cells. The number of EVs expressing CEACAM1, 5, and 6 proteins (CEACAMs+EVs) was significantly increased in UCB (Mean9.5%±SD14%), non-bladder cancer (0.69±0.46), and healthy (0.37±0.31) by flow cytometry. The results of ROC analysis showed a good score of AUC=0.929. A provisional CEACAMs+EVs cutoff % was established with a sensitivity of 83% and specificity of 98%. Here, seven out of nine cases of negative urine cytology (class 2) were determined to be positive.

Conclusions: The presence of CEA antigen in the urine of patients with bladder cancer is known, but it has not yet been practically used for diagnosis. We have discovered EVs that specifically express these antigens and have obtained useful diagnostic performance. EVs expressing CEACAM proteins in urine are expecting target as a new liquid biopsy for UCB patients.

Citation Format: Ko Igami, Takeshi Uchiumi, Masaki Shiota, Saori Ueda, Masatoshi Eto, Dongchon Kang. Extracellular vesicles expressing CEACAM proteins in the urine of bladder cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5104.
Abstract 5127: Significance of Trop-2 in HER2-positive breast cancer
Authors: Liu Chun-Yu , Chen Ji-Lin , Chu Pei-Yi , Huang Chun-Teng , Wang Wan-Lun , Huang Chi-Cheng , Lin Po-Han , Tseng Ling-Ming
Published: June 2022

Purpose: The glycoprotein Trop-2 is frequently overexpressed in human malignancies and linked to worse outcome. A Trop2-targeting antibody-drug conjugate, sacituzumab govitecan, has been approved by the FDA for patients with unresectable locally advanced or metastatic triple-negative breast cancer. Trop-2 enhances Akt phosphorylation in numerous cancer cell lines, while the opposite findings are also reported suggesting the cell context-dependent effect of Trop-2. Blockade of PI3K/Akt pathway mediates anti-tumor mechanism of anti-HER2 agents. In this study, we aim to investigate the role of Trop-2 in HER2-positive breast cancer.

Experimental design: The archival samples comprising different breast cancer subtypes were analyzed using immunohistochemical staining. The public databases, including, Metabric, KM plotter, ROC plotter, were used to verify the prognostic role and clinical significance of Trop-2 in HER2-positive breast cancer. In vitro tumor models, the transwell migration, invasion and sphere assays, were applied for evaluation of cancer progression. The apoptotic cells were determined by flow cytometry using Annexin V/propidium iodide double staining.

Results: We analyzed a cohort of 986 breast cancer patients and found that HER2-positive breast cancer harbored higher Trop-2 protein expression than other breast cancer subtypes. Higher levels of Trop-2 and phospho-Akt in HER2-positive breast cancer tissues compared with normal tissues. Trop-2 expression was correlated with tumor stage and phospho-Akt level. HER2-positive breast cancer patients with high level of Trop-2 protein were linked to worse recurrence-free survival. Consistently, data from the public databases exhibited patients with higher level of Trop-2 transcript had shorter recurrence-free survival and overall survival of HER2-positive breast cancer. Overexpression of Trop-2 increased cell migration, invasion and sphere number in SK-BR-3 and BT-474 cells. In contrast, knockdown of Trop-2 suppressed cell motility and sphere formation. Trop-2-expressing cells had better cell viability compared to control cells in the presence of lapatinib or neratinib treatment. Lapatinib- and neratinib-induced cell apoptosis was rescued by Trop-2 overexpression. Notably, patients responded to anti-HER2 therapy had lower Trop-2 transcript expression than non-responders.

Conclusion: These results suggested that the oncogenic role of Trop-2 in HER2-positive breast cancer and Trop-2 expression might confer resistance to anti-HER2 therapy.

Citation Format: Chun-Yu Liu, Ji-Lin Chen, Pei-Yi Chu, Chun-Teng Huang, Wan-Lun Wang, Chi-Cheng Huang, Po-Han Lin, Ling-Ming Tseng. Significance of Trop-2 in HER2-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5127.
Abstract 5147: The prion-like protein doppel as a seurm biomarker for epithelial ovarian cancer
Authors: Zhang Xiaojun , Kang Bowon , Karim Mazharul , Zhang Jianying , Song Jae Yun , Kim In-San , Al-Hilal Taslim A.
Published: June 2022

Ovarian cancer has a dire prognosis with an overall 5-year survival rate of ~40%, whereas stage III and IV has a survival rate of only 3-19%. Failure to detect early contributes highly to the poor survival rate of ovarian cancer. Thus, early detection of EOCs is likely to translate into mortality benefit. Two tests used clinically to detect ovarian cancer are serum cancer antigen-125 (CA-125) and transvaginal ultrasound. Both have limitations of specificity and sensitivity. CA-125 along with other biomarkers that are in clinical trials express both in the ovaries and serum of healthy females. Thus, the specific detection among cancer-free controls versus ovarian cancer cases remains highly variable. We hypothesize to assess the Doppel (PRND gene) as a serum biomarker in the detection of epithelial ovarian cancers (EOC) at the early stages. Doppel, a prion-like protein first identified in 1996, is known to express in testis and appears to regulate male fertility. Previously, we and others reported that Doppel is a highly specific tumor endothelium marker. In this study, to validate the potential of Doppel as an EOC serum biomarker, using ELISA, we detected Doppel concentration in the sera of 76 sera samples from patients with stage and histopathology information, and in 18 normal human sera (NHS). Doppel level was significantly higher in sera of EOC patients than NHS (0.720 vs 6.653 ng/ml, p<0.0001); 72 out of 76 patients were positive for Doppel expression (cut off value was calculated as Mean+3×SEM = 1.296 ng/mL) while only 3 out of 18 cases were positive for NHS. Receiver operating characteristic (ROC) analysis showed that Doppel can differentiate EOC patients from normal individuals with AUC of 0.957, sensitivity of 90.8%, and specificity of 90%. Doppel was markedly higher in all stages of EOC than NHS (Stage I, 6.261 ng/mL; Stage II, 8.045 ng/ml; Stage III, 7.040 ng/mL; and Stage IV, 5.726 ng/ml vs NHS 0.720 ng/ml; p<0.001). Interestingly, serum Doppel level was higher among EOC of serous adenocarcinoma (7.020 ng/mL; n = 39), mucinous (10.780 ng/mL; n = 8), and endometroid (7.295 ng/mL; n = 7) than clear cell (3.114 ng/mL; n = 7) or other types (4.855 ng/mL; n = 15). Together, our study showed the potential of Doppel as a serological biomarker for EOC detection.

Citation Format: Xiaojun Zhang, Bowon Kang, Mazharul Karim, Jianying Zhang, Jae Yun Song, In-San Kim, Taslim A. Al-Hilal. The prion-like protein doppel as a seurm biomarker for epithelial ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5147.
Abstract 5190: Case report: long-term response to combination of Sintilimab, Bevacizumab and chemotherapy in a heavily pretreated refractory colon cancer patient with microsatellite stability
Authors: Cui Zhi , Wang Qi , Deng Muhong , Meng Erhong , Liu Sheng , Han Quanli
Published: June 2022

Background: Unlike patients with advanced colorectal cancer (CRC) with deficient DNA mismatch repair or microsatellite instability-high (dMMR/MSI-H) tumors, most patients with advanced CRC with proficient DNA mismatch repair or microsatellite-stability (pMMR/MSS) tumors are not sensitive to immune checkpoint inhibitor (ICI) therapy. The current challenge is to find out innovative therapeutic combinations with ICIs for such patients.

Case Presentation: In this study, we report a case of heavily pretreated refractory colon cancer with MSS but high-tumor mutation burden (TMB-H) tumors. After experiencing five lines of therapy, including chemotherapy and targeted therapy with anti-angiogenic inhibitor as well as anti-EGFR antibody, she received sixth-line therapy with combination of Sintilimab, Bevacizumab and chemotherapy, and obtained a durable clinical benefit. The patient’s progression-free survival (PFS) of sixth line therapy was about 9 months and overall survival (OS) has been over 4.6 years.

Conclusion: To the best of our knowledge, this study represented the longest PFS of response to combination of ICI with other agents with different mechanisms of action in a heavily pretreated refractory colon cancer patient with MSS.

Citation Format: Zhi Cui, Qi Wang, Muhong Deng, Erhong Meng, Sheng Liu, Quanli Han. Case report: long-term response to combination of Sintilimab, Bevacizumab and chemotherapy in a heavily pretreated refractory colon cancer patient with microsatellite stability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5190.
Abstract 5192: Efficacy and safety of second-line therapy by S-1 combined with Sintilimab and Anlotinib in pancreatic cancer patients with liver metastasis: A single-arm, phase II clinical trial
Authors: Du Juan , Qiu Xin , Lu Changchang , Sha Huizi , Zhu Yahui , Kong Weiwei , Li Xing , Qian Xiaoping , Liu Baorui
Published: June 2022

Background: The mortality of pancreatic cancer is increasing year by year, and the prognosis of pancreatic cancer with liver metastasis is worse. There is still no recognized effective second-line treatment strategy. In this trial, the efficacy and safety of the triple-drug regimen by S-1 chemotherapy combined with anti-PD-1 McAb (Sintilimab) and anti-angiogenic drug (Anlotinib) were evaluated in pancreatic cancer patients with liver metastasis.

Methods: Pancreatic cancer patients with liver metastases and ECOG 0~2 were recruited. These patients had never been given 5-FU, anti-PD-1 McAb and/or anti-angiogenic drugs in first-line treatment. S-1 was administered orally at 25 mg/m2 bid from day 1 to day 14, Sintilimab was administered intravenously at 200 mg on day 1, and Anlotinib was administered orally 12mg qd from day 1 to day 14. This method were repeated every 21 days till disease progression. The therapeutic effect was evaluated every 3 cycles. Progression-free survival (PFS) and overall survival (OS) were estimated via the K-M method. Some patients’ tumor tissues have done high-throughput sequencing and the relationship between with effect has been analyzed.

Results: From March 2020 to June 2021, a total of 23 patients were enrolled in this study and 19 patients had objective efficacy evaluation. Two patient (10.5%) had confirmed partial response and eight patients (42.1%) had stable disease. Median PFS and OS were 3.53 months and 7.15 months. Grade 3 adverse events were 26.3%, and there were no grade 4 or above adverse events. The tumor tissues of 16 patients have done high-throughput sequencing, and genetic test results show that 6 patients were evaluated as HRD-High and 10 patients as HRD-Low. Patients with HRD-H had shorter PFS than those with HRD-L (2.43 vs. 5.45 months; p = 0.043), However, OS was not significantly different between these two groups (4.43vs.9.35 months; P = 0.11).

Conclusions: This study suggests that S-1 chemotherapy combined with anti-PD-1 McAb (Sintilimab) and anti-angiogenic drug (Anlotinib) is efficacy and safety as a second-line treatment for pancreatic cancer patients with liver metastasis. Subgroup analysis showed that patients with HRD-L had longer PFS. HRD-H were found to be related to worsen PFS, which may indicate that other therapies should be explored regarding to these patients.

Citation Format: Juan Du, Xin Qiu, Changchang Lu, Huizi Sha, Yahui Zhu, Weiwei Kong, Xing Li, Xiaoping Qian, Baorui Liu. Efficacy and safety of second-line therapy by S-1 combined with Sintilimab and Anlotinib in pancreatic cancer patients with liver metastasis: A single-arm, phase II clinical trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5192.
Abstract 5201: Enhanced production of IL-2 from anti CD3-stimulated mouse spleen cells by artepillin C, a major component of Brazilian green propolis
Authors: Kondoh Nobuo , Kamiya Masako , Tsuruta Hanemi , Takahashi Moe , Ikeno Kumiko , Ueno Kyohei , Umemura Naoki , Takayama Eiji , Kawaki Harumi , Nakamura Genjiro , Nikaido Toru , Muramatsu Yasunori , Ando Megumi
Published: June 2022

Objectives: It has been reported that Brazilian green propolis (BGP) possesses anti-tumor and chemo-preventive properties against prostate cancer (Szliszaka E, 2011). And bioactive components from propolis have been shown to have anti-cancerous effects upon hepatocellular carcinoma (Liu X, 2021). These observations revealed that propolis can be an anti-cancer drugs, however the immunological effects upon tumor microenvironments of these naturally occurring components has not been elucidated. In this report, we attempt to clarify immune modulatory effects of BGP and the major component, artepillin C, by observing cytokine production from activated T cells.

Methods: The mouse spleen cell stimulated by anti-CD3 monoclonal antibody were co-cultured with BGP, artepillin C and HC030031, an antagonist of TRPA1 Ca2+ channel. The productions of IFN-γ, IL-6, IL-17, IL-4, IL-10 and IL-2 was assayed by ELISA.

Results: Our results demonstrated the production of IL-2 was markedly enhanced, while the production of IL-4 and IL-10 was not significantly affected; by contrast, the production of IFN-γ, IL-6 and IL-17 were markedly reduced, in the highly viable stimulated spleen cells treated with BGP. These effects were also reproduced in the cells treated with artepillin C, a major component of BGP. The enhancement of IL-2 production by artepillin C was significantly alleviated by adding 10 HC030031, an antagonist of TRPA1 Ca2+ channel, suggesting the enhancement of the cytokine production by artepillin C could be mediated by Ca2+ influx.

Conclusions: The artepillin C, a major component of BGP, is an important regulator of activated T lymphocytes and specifically augmented the expression of IL-2 vie Ca2+-permeable cation channel, TRPA1. These effects may exert immunomodulatory effects upon tumor microenvironments.

Citation Format: Nobuo Kondoh, Masako Kamiya, Hanemi Tsuruta, Moe Takahashi, Kumiko Ikeno, Kyohei Ueno, Naoki Umemura, Eiji Takayama, Harumi Kawaki, Genjiro Nakamura, Toru Nikaido, Yasunori Muramatsu, Megumi Ando. Enhanced production of IL-2 from anti CD3-stimulated mouse spleen cells by artepillin C, a major component of Brazilian green propolis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5201.
Abstract 5204: Optimization of novel anti-human CD47 antibody prodrugs as cancer therapeutics with low on-target toxicity
Authors: Zhang Richard , Lin Haishan
Published: June 2022

CD47 is a well-studied target for cancer immunotherapy. Blocking of CD47 binding to its receptor, SIRPα, on macrophages leads to inhibition of macrophage activation and phagocytosis. Several monoclonal anti-CD47 antibodies are currently in various stages of clinical development. However, since CD47 is also expressed on normal cells such as red blood cells and platelets, anti-CD47 antibodies also caused on-target side effects during clinical evaluations, such as anemia and red blood cell hemagglutination. To minimize the on-target side effects of anti-CD47 antibodies, we have generated anti-CD47 prodrugs. By screening a phage peptide library, we identified peptides that can specifically block the anti-CD47 antibody binding activity. These peptides were fused to the humanized anti-CD47 antibody via a linker containing protease substrate sequences to derive the anti-CD47 antibody prodrug. We demonstrated that these anti-CD47 antibody prodrugs had significantly diminished CD47 binding activity and were unable to block CD47:SIRPα interaction. Upon cleavage of the anti-CD47 antibody prodrug with proteases, the antibody regained full activities in both binding to CD47 and blocking CD47:SIRPα interaction. Importantly, we showed that the anti-CD47 antibody prodrug had minimal hemagglutination and RBC binding activities. Since different tumors may have different types of protease activities, anti-CD47 prodrugs with different types of protease substrates have been generated to demonstrate that the anti-CD47 prodrug can be used for treating various tumor types. These data suggest that novel anti-CD47 antibody prodrugs are promising candidates for the next generation anti-CD47 therapeutics with improved safety profile.

Citation Format: Richard Zhang, Haishan Lin. Optimization of novel anti-human CD47 antibody prodrugs as cancer therapeutics with low on-target toxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5204.