bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 7242: Immunostimulatory gene therapy co-expressing immune activators TMZ-CD40L and 4-1BBL with a PD-L1-targeting Affibody molecule to reactivate T cell immunity
Authors: White Luke Adam , Vaask Iris , Härdin Jonas , Eriksson Emma , Sandegren Anna , Frejd Fredrik Y. , Lövgren Tanja , Loskog Angelica
Published: March 2024

Immunotherapy has been used to make great strides in helping cancer patients, and new approaches to reactivate patient immunity are constantly being developed. We are developing immunostimulatory gene therapy using adenoviruses as gene vehicles to inflame the tumor microenvironment and drive anti-tumor immunity. One consequence of immune activation is PD-L1 upregulation, so to optimize our treatment, we are using a novel gene therapy vehicle expressing both immune activators and a PD-L1-blocking Affibody molecule. Affibody molecules are tri-helical proteins engineered to bind specific target molecules with high affinity. These molecules have successfully been used to image cancer cells in the body and can block target proteins. Affibody molecules are advantageous over other affinity molecules due to their small size, averaging about 6 kDa, and their high stability. The small size makes an Affibody molecule an ideal candidate for use in viral vectors, where genetic space is limited. In the present study, we tested the biological activity of a PD-L1 targeted Affibody molecule expressed from a viral vehicle compared to the synthetic protein, using a Bio-IC in vitro luciferase assay. Further, the capacity of the PD-L1-binding Affibody molecule to prevent inhibitory signaling was evaluated in an ovarian cancer/immune cell co-culture assay.

Our results demonstrate that cell lines infected with viral gene vehicles successfully express and release the Affibody molecule as demonstrated with PCR and ELISA. Furthermore, the supernatants containing the Affibody molecule and synthetic Affibody molecule inhibited the activity of PD-L1 in the BioIC assay. Next, an adenovirus vector containing trimerized-CD40L and 4-1BBL (LOAd703), known to upregulate PD-L1 in stimulated dendritic cells, was modified to co-express the anti-PD-L1 Affibody molecule (LOAd724). Gene expression was confirmed using PCR, flow cytometry (CD40L, 4-1BBL) and ELISA (anti-PD-L1 Affibody molecule). The tumor/immune cell co-culture is underway. In summary, Affibody molecules can be expressed from adenoviral gene vehicles alone or in combination with immunostimulatory genes. Further studies are warranted to understand the role of local PD-L1 blockade in the tumor microenvironment following LOAd724 therapy.

Citation Format: Luke Adam White, Iris Vaask, Jonas Härdin, Emma Eriksson, Anna Sandegren, Fredrik Y. Frejd, Tanja Lövgren, Angelica Loskog. Immunostimulatory gene therapy co-expressing immune activators TMZ-CD40L and 4-1BBL with a PD-L1-targeting Affibody molecule to reactivate T cell immunity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7242.
Abstract 7246: Enhancing PDAC therapy through in vivo correction of KRAS
G12D using enIscB-directed base editor combined with ICB
Authors: Yang Chao , Fang Qingxiao , Zhou Tianxing , Xie Yongjie , Yu Jun , Hao Jihui
Published: March 2024

In this study, we aim to investigate the therapeutic potential of in vivo genetic therapy using AAV-mediated adenine base editor (ABE) delivery for pancreatic ductal adenocarcinoma (PDAC) carrying the KRASG12D mutation (PDACG12D), and further explore its potential when combined with immune checkpoint blockade (ICB). The KRASG12D mutation is a dominant genetic alteration representing a highly sought-after and effective therapeutic target in PDAC. However, the in vivo genetic therapy for KRASG12D in PDAC has been rarely explored. Programmable base editors have been shown to install genetic mutations precisely and have significant therapeutic value, providing a promising strategy for genetic therapy of PDACG12D. Here, we engineered ABEs derived from various programmable nucleases, considering the protospacer adjacent motif (PAM) or target adjacent motif (TAM) sequence. The hypercompact A8e-enIscB demonstrated the highest editing efficiency in HEK293TG12D and PANC-1 cell lines. Subsequently, A8e-enIscB was packaged into a single-AAV system and delivered to humanized mice subcutaneously transplanted with patient-derived organoidG12D (PDOG12D). We found the delayed tumor progression with BE-based genetic therapy. Additionally, a substantial editing efficiency in tumor tissues and lower off-target editing in normal tissues was observed. By comparing single-cell transcriptome sequencing data between BE-treated and non-treated samples, we observed a reprogrammed immune microenvironment characterized by elevated infiltration of cytotoxic CD8+ T cells and NK cells, as well as decreased recruitment of suppressive PMN-MDSCs, Tregs and TAMs upon correction of KRASG12D. Furthermore, AAV-directed ABE genetic therapy could significantly sensitize PDAC to ICB therapy (anti-PD-1, anti-CTLA4) in humanized PDAC PDO/PDX mouse models. Accordingly, an ongoing work in which the genetic therapy combined with ICB phase IA investigator-initialized trial will be designed to evaluate the safety of this regimen. In summary, our study demonstrates the efficiency and safety of innovative genetic therapy for correcting the KRASG12D mutation in PDAC. Furthermore, we demonstrated the therapeutic potential of combining this genetic therapy with ICB.

Citation Format: Chao Yang, Qingxiao Fang, Tianxing Zhou, Yongjie Xie, Jun Yu, Jihui Hao. Enhancing PDAC therapy through in vivo correction of KRAS G12D using enIscB-directed base editor combined with ICB [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7246.
Abstract 7258: Combinatorial effects of viral oncolysis and miRNA modulation as a novel therapeutic of pancreatic ductal adenocarcinoma
Authors: Ruschel Monique Kanitz , Davis Isaiah , Mills Hannah Taylor , Gourishetti Karthik , Bhere Deepak
Published: March 2024

Pancreatic cancer is a devastating illness that affects numerous individuals each year. Unfortunately, pancreatic ductal adenocarcinoma (PDAC) is an aggressive form of this disease that accounts for a disproportionate number of cancer-related deaths. Despite representing only 3.3% of all cancer cases in the United States, pancreatic cancer is responsible for a staggering 8.3% of cancer-related fatalities. In 2023, 64,050 patients were diagnosed with PDAC alone. Current treatment options, which are limited to surgery, radiation, and chemotherapy, have failed to improve clinical outcomes. Recent research has revealed miRNA (miR) as a contributor to the suppression and progression of various cancers, including PDAC. Specifically, dysregulation of miR-7 has been associated with PDAC. Downregulation of miR-7 is linked to more aggressive cases of the disease. Another potential therapeutic approach to treating cancer is the use of oncolytic viruses (OV). These viruses can replicate in cancerous cells while leaving healthy cells unharmed, making them an attractive treatment option. In this study, we utilized exosomes isolated from human Umbilical Cord stem cells (hUCs) enriched with miR-7 and combined with OHSV to examine their effect on established PDAC cell lines. We utilized cell viability assays, microscopy, and western blot analysis to evaluate the impact of the combinatorial approach on the underlying molecular mechanisms. Our findings suggest that the successful transfer of miR cargo and treatment with oHSV into the target PDAC cells arrested cell proliferation by targeting apoptotic pathways.

Citation Format: Monique Kanitz Ruschel, Isaiah Davis, Hannah Taylor Mills, Karthik Gourishetti, Deepak Bhere. Combinatorial effects of viral oncolysis and miRNA modulation as a novel therapeutic of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7258.
Abstract 7362: Integrated analysis of scRNAseq and spatial omics in brain metastatic lung cancer tumor tissue
Authors: Hirose Haruka , Tsuji Takahiro , Kojima Yasuhiro , Yoshizawa Akihiko , Arakawa Yoshiki , Ozasa Hiroaki , Wake Hiroaki , Shimamura Teppei
Published: March 2024

Spatial omics technologies have made significant advances in recent years, improving our understanding of the spatial localization of cells and intercellular interactions. Intercellular interactions are essential for maintaining proper tissue function and homeostasis, and dysregulation of these interactions can contribute to various diseases, including cancer and autoimmune disorders. Ligand proteins, one of the signaling molecules responsible for cell-cell interactions, bind to cell surface receptors and trigger intracellular signaling pathways. The effective range of ligand signaling, i.e. the extent to which a cell spatially and directly transmits information via the ligand, has not been systematically studied, although it may determine the occurrence of cell-cell interactions. The authors have previously developed methodologies combining spatial transcriptomics and single-cell RNA sequencing to analyze intercellular interactions at the single-cell level in spatial dimensions. Additionally, we have devised a technique to model the spatial diffusion of ligands from spatial transcriptomics and estimate the spatial range of ligand action. In this study, we used these developed methods to elucidate events in the tumor microenvironment of brain metastatic lung cancer tissue. Specifically, an integrated analysis of metastatic brain tumor samples was performed using visium and single-cell data from the same patient. The results suggest the presence of a heterogeneous microglial subpopulation, including clusters enriched in cytokines and chemokines for angiogenesis and wound healing, clusters associated with immune tolerance via IL-10 signaling, clusters enriched in gene sets related to phagocytosis, antigen processing, and antigen presentation, and clusters related to clearance of pathogens and residues. The presence of homogeneous microglial subpopulations was suggested. Furthermore, these subpopulations exhibited different spatial distributions, suggesting that they interact with surrounding cancer cells through different mechanisms.

Citation Format: Haruka Hirose, Takahiro Tsuji, Yasuhiro Kojima, Akihiko Yoshizawa, Yoshiki Arakawa, Hiroaki Ozasa, Hiroaki Wake, Teppei Shimamura. Integrated analysis of scRNAseq and spatial omics in brain metastatic lung cancer tumor tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7362.
Abstract 7400: AI-driven multimodal 3D tumor modeling with spatial molecular insights for predicting ICI response in gastric cancer
Authors: Choi Yoon Ho , Kim Minji , Redekop Katya , Jang Inyeop , Clemenceau Jean R. , Barnfather Isabel , Nakkireddy Sumanth Reddy , Hong Changjin , Park Sunho , Sung Ji-Youn , Park Jeong Hwan , Kohei Shitara , Yu Aoki , Lee Sung Hak , Wang Sam , Cheong Jaeho , Hwang Tae Hyun
Published: March 2024

Traditional cancer research methodologies predominantly focus on 2D tumor modeling, including spatial profiling and AI-driven analysis at the 2D level. To advance beyond these limitations, we implemented Holotomography (HT), a 3D, label-free optical imaging method. This technique, leveraging refractive index contrasts, allows for enhanced visualization of tumor tissues, organoids, and cells in three dimensions. Using serial H&E sections and unstained slides, we created detailed 3D tumor models in gastric cancer, providing insights into tumor, immune, and stromal composition, as well as cell-cell interactions and extracellular matrix characteristics. AI algorithms further enhanced our 3D tumor modeling, offering novel perspectives on the initiation and progression of tumor, immune, and stromal components at the subcellular level. Analyzing gastric tumors treated with immune checkpoint inhibitors before, during, and after treatment revealed dynamic changes in spatial composition over time, offering unique insights into the evolution of the 3D tumor ecosystem. Additionally, by integrating spatial transcriptomic and in situ molecular imaging data, we developed a novel Multimodal 3D Tumor Model. This model not only uncovers subcellular-level molecular characteristics but also elucidates cellular interactions during treatment, suggesting potential biomarkers and therapeutic approaches. Lastly, by constructing 3D cellular interaction networks incorporating true 3D interactions, we provided an in-depth view of cellular communication within the tumor microenvironment. This pioneering approach, representing the first Multimodal 3D Tumor Model at the subcellular level, offers novel insights into gastric cancer's spatial evolution, potentially revolutionizing our understanding and treatment of gastric cancer.

Citation Format: Yoon Ho Choi, Minji Kim, Katya Redekop, Inyeop Jang, Jean R. Clemenceau, Isabel Barnfather, Sumanth Reddy Nakkireddy, Changjin Hong, Sunho Park, Ji-Youn Sung, Jeong Hwan Park, Shitara Kohei, Aoki Yu, Sung Hak Lee, Sam Wang, Jaeho Cheong, Tae Hyun Hwang. AI-driven multimodal 3D tumor modeling with spatial molecular insights for predicting ICI response in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7400.
Abstract 7406: Visualization and analysis of cancer genomics data using UCSC Xena
Authors: Goldman Mary , Craft Brian , Zhu Jingchun , Haussler David
Published: March 2024

UCSC Xena (http://xena.ucsc.edu/) is a web-based visual integration and exploration tool for multi-omic data and associated clinical and phenotypic annotations. Researchers can easily view and explore public data, their own private data, or both using the Xena Browser. Private data are kept on the researcher's computer and are never uploaded to our public servers. We support Mac, Windows, and Linux.

Questions Xena can help you answer:* Is overexpression of this gene associated with lower/higher survival?* What genes are differentially expressed between these two groups of samples?* What is the relationship between mutation, copy number, expression, etc for this gene?

Xena showcases seminal cancer genomics datasets from TCGA, the Pan-Cancer Atlas, GDC, PCAWG, ICGC, and more; a total of more than 1500 datasets across 50 cancer types. We support virtually any type of functional genomics data: SNPs, INDELs, copy number variation, gene expression, ATAC-seq, DNA methylation, exon-, transcript-, miRNA-, lncRNA-expression and structural variants. We also support clinical data such as phenotype information, subtype classifications and biomarkers. All of our data is available for download via python or R APIs, or using our URL links.

Our signature Visual Spreadsheet view shows multiple data types side-by-side enabling discovery of correlations across and within genes and genomic regions. We also have dynamic Kaplan-Meier survival analysis, powerful filtering and subgrouping, differential gene expression analysis, GSEA, charts, statistical analyses, genomic signatures, and the ability to generate URLs to live views.

New features include:

* Genome-wide differential gene expression analysis

* GSEA analysis

* Select samples directly from the screen for filtering and creating subgroups

* Loading of Microsoft Excel files

Our beta prototype site for visualizing single-cell data delivers million-cell-scale multi-omics data for interactive visualization in a web browser. Contact us for access to our beta prototype site.

If you use us please cite our publication in Nature Biotechnology: https://www.nature.com/articles/s41587-020-0546-8

Citation Format: Mary Goldman, Brian Craft, Jingchun Zhu, David Haussler. Visualization and analysis of cancer genomics data using UCSC Xena [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7406.
Abstract 7416: GeneSetR: A web server for gene set analysis based on genome-wide Perturb-Seq data
Authors: Kuzu Omer Faruk , Saatcioglu Fahri
Published: March 2024

Identification of genotype-phenotype relationships is of utmost importance and a core effort in biology. Recent developments in efficient and precise gene targeting approaches coupled to omics methods have significantly improved deciphering of molecular interactions and relationships. However, many single gene perturbations can affect the expression of hundreds of other genes and analysis of the resulting omics-derived gene lists currently remains a significant challenge. Here we present Perturb-Seq based Gene Set Analyzer (GeneSetR), a user-friendly web-server that can analyze user-defined gene lists based on the data from a recently published genome-wide Perturb-Seq study, which targeted 9,866 genes with 11,258 sgRNAs in the K562 cell line. Through this tool, users can cluster gene lists following dimensionality reduction by various algorithms, undertake network analysis from RNA sequencing data, identify key nodes among the submitted genes, perform gene signature analyses, and generate heatmaps based on perturbation or gene expression data. GeneSetR enables researchers to readily identify gene clusters associated with specific phenotypes or biological processes, providing insights into the potential functional roles of these clusters and the role of single genes in them. With robust analysis capabilities, GeneSetR is a powerful resource to facilitate the exploration of genotype-phenotype relationships.

Citation Format: Omer Faruk Kuzu, Fahri Saatcioglu. GeneSetR: A web server for gene set analysis based on genome-wide Perturb-Seq data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7416.
Abstract 7420: Optimizing proteomic data access and analysis in the cloud: Leveraging Terra's integration with the Proteomic Data Commons
Authors: LaPlante Emily , Huo Bingxing , Mani DR , Thangudu Ratna R.
Published: March 2024

The Proteomic Data Commons (PDC) hosts cancer proteomics data with the goal of making this data available to the public to support development of cancer diagnostics, treatment, and progression tracking. As a part of the Cancer Research Data Commons (CRDC), the Terra platform provides a cloud workbench for the PDC data. FireCloud is a Broad Institute project funded by NCI to empower cancer researchers to access data, run analysis tools and collaborate securely in the cloud. It is powered by Terra, a secure, scalable cloud-native platform developed by the Broad Institute, Microsoft, and Verily, an Alphabet company. It provides batch workflow execution, interactive analysis including data visualization, and ~2,900 publicly available tools with the ability to import more tools from Dockstore.

The integration of PDC and Terra enables researchers to leverage the data navigation and file-level search capabilities on the PDC web browser (pdc.cancer.gov) and export selected data manifests to a Terra workspace. This integrated hand-off specifically allows metadata and cloud links to PDC data in Portable Format for Bioinformatics (PFB) to be transferred to Terra and used in analysis with cloud resources. A featured workspace for Terra-PDC integration includes tools for (i) downloading data files and relevant additional metadata; (ii) organizing the data and metadata for running the FragPipe workflow, a comprehensive collection of tools for reading and processing raw Mass Spec (MS) data; and (iii) implementing a pre-configured FragPipe workflow to process isobarically labeled MS data from Tandem Mass Tag (TMT) or Isobaric tags for relative and absolute quantitation (iTRAQ) experiments using information automatically imported from PDC via the PFB import. The pipelines can also be customized as needed to process any type of raw MS data the PDC supports.

In addition, Terra connects to the NCI Genomic Data Commons (GDC) and hosts The Cancer Genome Atlas (TCGA) and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) datasets allowing users to pull in other data types for co-analysis. As a whole, using the CRDC cloud resources, in conjunction with Terra, allows analysis of data on a massive scale, enabling multi-omic integration spanning the genomic and proteomic commons data, with easy sharing of data and tools.

Citation Format: Emily LaPlante, Bingxing Huo, DR Mani, Ratna R. Thangudu. Optimizing proteomic data access and analysis in the cloud: Leveraging Terra's integration with the Proteomic Data Commons [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7420.
Abstract 7447: Understanding survivorship: A national survey of post-treatment experiences in Black prostate cancer survivors
Authors: Fullwood Dottington , Lee Daniel , Panagiotou Veronika , Siegel Samantha B. , Molina Mariel , Odedina Folakemi T.
Published: March 2024

Prostate cancer, impacts over 3.1 million survivors, poses persistent challenges in post-treatment care, creating uncertainties regarding the best course of follow-up actions for leading productive lives. Unfortunately, these concerns, especially among ethnically diverse Black men, are frequently overlooked. The post-treatment journey for Black prostate cancer survivors is dependent on how they navigate survivorship to determine how it impacts their quality of life and emotional wellbeing. This study evaluated the post-treatment cancer experience and gauge satisfaction with care among a cohort of Black survivors (n = 45). Utilizing data from the 2023 National Coalition for Cancer Survivorship State of Survivorship Study (n = 1303), conducted between May 9th to June 6th, 2023, the research specifically targets self-identified Black males, constituting 10% of the study population and spanning an age range from 18 to 80 years. Results revealed that oncologists (44%) managed post-treatment care more than primary care physicians (30%). While conversation about follow-up care monitoring cancer tests regularly occurred (68%), while topics such as quality of life (27%), mental and emotional health (21%), and post-treatment survivorship care plans (9%) received minimal attention. Although most survivors felt generally informed about side effects (62% very informed), less than half felt their health care team was very helpful in dealing with them. Symptoms reported by survivors included feeling overly tired (47%), depression, anxiety, and mental health impacts (40%), and uncertainty about the cancer status (34%). Survivors engaging in diverse integrative treatments, including such practices as prayer and exercise, represented 29% and 28%, respectfully. Notably, 80% and 60% of individuals utilizing these modalities reported finding them effective during the post-treatment care phase. The journey from the point of prostate cancer diagnosis to post-treatment can impose a significant mental and physical toll on survivors. To address the emotional and psychological challenges associated with a diagnosis and post-treatment, survivors adopting integrative oncology modalities and exercise prescriptions to cope are crucial. These strategies may help survivors maintain a positive outlook and achieve optimal post-treatment health, with a focus on providing tailored resources that cater to the unique needs of Black survivors.

Citation Format: Dottington Fullwood, Daniel Lee, Veronika Panagiotou, Samantha B. Siegel, Mariel Molina, Folakemi T. Odedina. Understanding survivorship: A national survey of post-treatment experiences in Black prostate cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7447.
Abstract 7479: Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy
Authors: Borker Parth , Bao Yi , Qiao Yuanyuan , Chinnaiyan Arul , Choi Jae Eun , Zhang Yuping , Mannan Rahul , Cheng Caleb , He Tongchen , Zheng Yang , Yu Jiali , Gondal Mahnoor , Cruz Gabriel , Grove Sara Sara , Cao Xuhong , Su Fengyun , Wang Rui , Chang Yu , Kryczek Ilona , Cieslik Marcin , Green Michael D. , Zou Weiping
Published: March 2024

The widespread success of cancer immunotherapies suggests a promising future - but has been subverted by unresponsiveness and resistance. Current research has furthered the understanding of immunotherapy resistance through the findings of “hot” (responsive) and “cold” (unresponsive) tumors. Here, we focus on the genetic and pharmacological inhibition of PIKfyve, a lipid kinase regulator of autophagic flux and lysosomal biogenesis. We find that inhibition of PIKfyve results in the upregulation of major histocompatibility complex class I (MHC-I) surface expression in cancer cells (through inhibition of autophagic flux), resulting in increased CD8+ T cell-mediated cancer cell death. These findings were corroborated in multiple syngeneic mouse models, which also displayed increased intratumoral functional CD8+ T cells. In addition, the Pikfyve-depletion antitumor responses are CD8+ T cell and MHC-I dependent - as CD8+ T cell and B2m knockout rescued tumor growth - resulting in improved response to immune checkpoint blockable (ICB), adoptive cell therapy, and a therapeutic vaccine. Further, high PIKfyve expression predicts poor ICB response and is prognostic of poor survival in ICB-treated cohorts. Ultimately, these findings collectively suggest PIKfyve as an effective target to enhance immunotherapies through elevation of MHC-I surface expression in cancer cells, and accordingly, PIKfyve inhibitors have novel potential to increase immunotherapy response in cancer patients.

Citation Format: Parth Borker, Yi Bao, Yuanyuan Qiao, Arul Chinnaiyan, Jae Eun Choi, Yuping Zhang, Rahul Mannan, Caleb Cheng, Tongchen He, Yang Zheng, Jiali Yu, Mahnoor Gondal, Gabriel Cruz, Sara Sara Grove, Xuhong Cao, Fengyun Su, Rui Wang, Yu Chang, Ilona Kryczek, Marcin Cieslik, Michael D. Green, Weiping Zou. Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7479.
Abstract 7513: Tumor treating fields (TTFields) can induce immunogenic cell death in GBM resulting in enhanced immune modulation
Authors: Nitta Ryan T. , Lee Si Yeon , Lim Michael , Li Gordon
Published: March 2024

Glioblastoma (GBM) is the most common and aggressive form of malignant primary brain tumors. Despite current standard of care, the overall survival for GBM is ~15 months. While immunotherapy using immune checkpoint inhibitors such as anti-PD-1/PD-L1 have been efficacious for solid malignancies, very little progress has been made in a clinical setting for GBM. This is mainly due to GBM being known as a “cold” and non-immunogenic tumor. It has been previously established that a tumor may become “hot” if the T cell responses can be enhanced by increasing the presentation of tumor-specific antigens to the immune system. Tumor Treating Fields (TTFields) are alternating electric fields in a specific frequency range (100-500 kHz) delivered to the human body through transducer arrays. Treatment with TTFields have been approved and have shown efficacy in GBM. TTFields have induced immunogenic cell death in GBM, which in turn can elicit anti-tumoral immunity by inducing damage-associated molecular patterns (DAMP). These patterns are important for promoting engulfment of lung cancer cells by dendritic cells and recruitment of immune cells. These findings suggest that TTFields may enhance the immune response in GBM by increasing tumor specific antigens. In this study we show in vitro that TTFields enhanced the immune response to GBM. We initially demonstrated that GBM cells (GL261 or CT2A) treated with TTFields (200 kHz) can elicit DAMP emissions as evident by the increase in secretion of ATP and HMGB1 and the enhanced translocation of calreticulin to the cell surface. Additionally, TTFields stimulated the phagocytotic activity of antigen presenting cells (Raw264.7) and increased T-cell early activation (CD69/CD4+, CD69/CD8+) and activity (IFNγ and perforin). Since our findings in vitro indicate TTFields enhanced the immune response to GBM, we studied the therapeutic potential of using TTFields together with anti- PD1 in a syngeneic mouse model. We applied TTFields to GBM cells prior to intracranial injections. While our survival studies are preliminary, our findings suggest that systemic anti-PD1 and TTFields may result in a myeloid and T-cell mediated anti-tumor response and enhanced survival. Our findings indicate that TTFields treatment may help transform GBM into a “hot” tumor thereby making it an attractive target for immunotherapy.

Citation Format: Ryan T. Nitta, Si Yeon Lee, Michael Lim, Gordon Li. Tumor treating fields (TTFields) can induce immunogenic cell death in GBM resulting in enhanced immune modulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7513.
Abstract 7584: The solute transported xCT (SLC7A11) modulates lysosome biogenesis and microRNA trafficking in drug resistant renal cell carcinoma
Authors: Jawadwala Abbas , Rupert Christopher , Adelaiye-Ogala Remi , Pili Roberto , Chintala Sreenivasulu , Orillion Ashley , Elbanna May , Damayanti Nur , Fontane Ilaria Delle
Published: March 2024

Multi-tyrosine kinase inhibitors (TKIs) like sunitinib bind to over 50 kinases and inhibit several receptors such as VEGFR-1, VEGFR-2, and VEGFR-3 receptors, PDGFRa and PDGFRb, RET, cKIT, and FLT3. TKIs are effective drugs for the treatment of renal cell carcinoma (RCC) but intrinsic/acquired resistance remains a major hurdle. One of the proposed models for TKI resistance is drug sequestration by lysosomes. The solute transporter xCT is a cystine/glutamate antiporter that plays a role in the production of antioxidants in cancer cells. Our lab has found that SLC7A11, the gene that encodes xCT, is overexpressed in sunitinib resistant RCC cells. LAMP1 expression was also increased in sunitinib resistant RCC cells, suggesting an upregulation of lysosome biogenesis. The biochemical knock down of SLC7A11 by shRNA showed a decrease in LAMP1 expression, suggesting a decrease in lysosome biogenesis. SEC24D is a key catalytic component of COPII complex involved in formation of exosomes and secretory pathways. Our preliminary data showed that reduction in xCT expression was associated with a decrease in SEC24D protein levels which was associated with a reduction in the extracellular export and, consequently, an increase in intracytoplasmic levels of miRNA 605, a known tumor suppressor. We are currently testing the hypothesis that xCT may modulate lysosomes biogenesis and micro-RNA trafficking in several clear cell and translation renal cell carcinoma models. In summary, a better understanding of the role of xCT in the regulation of intracytoplasmic organelles may lead to the identification of a novel therapeutic strategy to overcome TKI resistance in RCC.

Citation Format: Abbas Jawadwala, Christopher Rupert, Remi Adelaiye-Ogala, Roberto Pili, Sreenivasulu Chintala, Ashley Orillion, May Elbanna, Nur Damayanti, Ilaria Delle Fontane. The solute transported xCT (SLC7A11) modulates lysosome biogenesis and microRNA trafficking in drug resistant renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7584.
Abstract 7633: CXCR6 positive circulating mucosal-associated invariant T cells play the anti-tumor effect in non-small cell lung caner immunotherapy
Authors: Qu Jingjing , Wu Binggen , Li Yuekang , Shen Qian , Sun Wenjia , Chen Lijun , Zhou Jianya , Zhou Jianying
Published: March 2024

Background: Mucosal-associated invariant T (MAIT) cells is are unconventional innate-like T lymphocytes abundant in human tissues. Recent studies have shown that MAIT cells play important roles in regulating tumor immunity. However, the immune characteristics of MAIT cells in non-small cell lung cancer (NSCLC) and its correlation with ICIs treatment efficacy remain unclear.

Method: In this study, we used single-cell RNA-sequencing (scRNA-seq), flow cytometry and multiplex immunofluorescence to assess the proportion and characteristics of CD8+MAIT cells in metastatic NSCLC patients who respond or not respond to anti-PD-1 therapy.

Results: The proportions of activated and proliferating CD8+ T cells and MAIT cells were significantly higher in responders-derived PBMC or lung tissues prior to anti-PD-1 therapy. Both peripheral and tumor-infiltrating CD8MAIT cells displayed upregulated CXCR6(P<0.05). Besides, CXCR6+CD8MAIT cells from responders had higher expression of cytotoxicity-related genes, like CST7, GNLY, KLRG1, NKG7 and PRF1. Moreover, we found that patients with >1.7% of MAIT among peripheral CD8+ population showed a better response to immunotherapy.

Conclusion: CD8MAIT cells may be considered a predictive biomarker for patients responding to anti-PD-1 therapy in NSCLC. The correlation between CD8MAIT and immunotherapy sensitivity may ascribe to high expression of CXCR6.

Citation Format: Jingjing Qu, Binggen Wu, Yuekang Li, Qian Shen, Wenjia Sun, Lijun Chen, Jianya Zhou, Jianying Zhou. CXCR6 positive circulating mucosal-associated invariant T cells play the anti-tumor effect in non-small cell lung caner immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7633.
Abstract 7641: Prognostic impact of functional germline mutations in muscle-invasive bladder cancer identified by neural network analysis
Authors: Sonpavde Guru P. , Nassar Amin H. , Ravi Arvind , Sadler Layne
Published: March 2024

Background: An accurate prognostic algorithm based on germline whole exome sequencing (WES) would complement tumor omics as a non-invasive source of biomarkers for guiding cancer patient therapy. In a previous study, we used WES and RNA-seq data from muscle-invasive bladder cancer (MIBC) and normal host cells to train a survival model, wherein we discovered that mutated germline genes accounted for 90% of feature importance. We have since defined a larger cohort to identify key germline biomarkers of overall survival (OS) that may be scalable for application in the clinic.

Methods: 169 patients from The Cancer Genome Atlas (TCGA) with MIBC stages T2-T4 that underwent radical cystectomy (RC) w/o neoadjuvant treatment were eligible. OS at 4 years was the primary clinical endpoint as it is associated with death due to metastatic tumor recurrence. Patients were dichotomized to control survivors who were alive at 4+ years, and cases who died within 4 years but no less than 4 months after RC. 49 qualifying survivors were propensity matched against 49 dead patients by stage, adjuvant treatment, gender, race, and age. The remaining 71 dead patients served as a holdout. Only high (e.g. frameshift) and moderate (e.g. indel) impact germline variants were included. Mutations were weighted for allele frequency (penalize common) and genotype (reward homozygous) before grouping at the gene level. A panel of the 21 most differential genes in stratified patients were selected for neural network training using AIQC. The model forced protective/pathogenic genes to interact and produced individual survival probabilities. Gene importance was determined via permutation.

Results: OS was accurately predicted for 98.2% of patients: 1 FN, 2 FP, 37 TN, 119 TP. The top 3 permuted genes (and related pathways) were: SORL1 (Aβ), KIF27 (hedgehog), CUL7 (p53). The most differential gene was CUL7: 31% of survivors mutated vs 2% of dead.

Conclusion: Neural network analysis identified the promise of germline genetics as an accurate predictor of survival and tumor recurrence in MIBC patients. Upon validation in an external cohort, these biomarkers could be used to inform adjuvant therapy and complement molecular residual disease alongside circulating tumor (ct)-DNA.

Citation Format: Guru P. Sonpavde, Amin H. Nassar, Arvind Ravi, Layne Sadler. Prognostic impact of functional germline mutations in muscle-invasive bladder cancer identified by neural network analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7641.
Abstract 7653: Role of ITGB2 in patients with luminal B1 breast cancer
Authors: Liu Chun-Yu , Chen Ji-Lin , Tsai Yi-Fang , Chao Ta-Chung , Wang Wan-Lun , Lien Pei-Ju , Hsu Chih-Yi , Lai Jiun-I , Huang Chi-Cheng , Chiu Jen-Hwey , Tseng Ling-Ming
Published: March 2024

Purpose: Luminal-type breast cancers are the most commonly diagnosed in women. Among them, the luminal B1 subtype exhibits higher proliferation rates and a worse prognosis compared to the luminal A subtype. Despite significant advancements in detection and therapies, recurrence still occurs after primary treatment. In this study, our aim is to identify genomic alterations in early recurrent luminal B1 breast cancer.

Experimental Design: In this VGHTPE cohort, we recruited a total of 42 patients diagnosed with stage I-III luminal B1 breast cancer, comprising 15 subjects who experienced recurrence within five years and 27 subjects who did not. Genomic DNA was extracted from formalin-fixed paraffin-embedded samples and subjected to targeted next-generation sequencing. We assessed cell aggressiveness through in vitro transwell migration, invasion, and sphere assays.

Results: Luminal B1 breast cancer patients with advanced stage and poorly differentiated tumors were associated with recurrence within five years. Driver gene mutation analysis revealed that TP53 mutations were present in 46.7% of patients who experienced recurrence within five years, compared to 29.6% in the non-recurrence group. In the analysis of copy number variations, the most common amplifications/gains observed in luminal B1 breast cancer patients were in MCL1, MYC, and KLF6. Remarkably, patients who experienced recurrence within five years showed a higher occurrence of gain in ITGB2, the gene encoding the integrin β chain, compared to those who remained recurrence-free. Patients with ITGB2 amplifications/gains had a shorter 5-year recurrence-free survival compared to those with a neutral status. In vitro studies revealed that the knockdown of ITGB2 suppressed cell migration, invasion, and sphere formation in estrogen receptor-positive HER2-negative breast cancer cells.

Conclusion: Our study has identified ITGB2 amplifications/gains as a potential biomarker for early recurrence in luminal B1 breast cancer.

Citation Format: Chun-Yu Liu, Ji-Lin Chen, Yi-Fang Tsai, Ta-Chung Chao, Wan-Lun Wang, Pei-Ju Lien, Chih-Yi Hsu, Jiun-I Lai, Chi-Cheng Huang, Jen-Hwey Chiu, Ling-Ming Tseng. Role of ITGB2 in patients with luminal B1 breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7653.
Abstract 7662: Convolutional neural network algorithms and hematoxylin-and-eosin-stained images predict clinical outcomes in high-grade serous ovarian cancer patients with advanced age and stage
Authors: Ng Chun Wai , Wong Kwong-kwok , Lawson Berrett , Ferri-Borgogno Sammy , Mok Samuel
Published: March 2024

Ovarian cancer is the deadliest among gynecologic cancers. It is partly due to the mild symptoms in early stages and relatively high diagnostic age (about 63-year-old median age). These factors contribute to the short chemotherapy response time and survival time with about 18- and 36-months median progression-free survival and overall survival duration, respectively. The advancements of convolutional neural network (CNN) machine learning algorithms provide opportunities for the development of cost- and time-effective models which is urgently needed for ovarian cancer patients, especially for those with elevated risk. A CNN model was trained with hematoxylin and eosin (H&E) stained tumor whole slide images (WSIs) from ovarian cancer patients with advanced stages. 773 WSIs of 335 patients from TCGA-OV dataset were separated randomly for training and testing cohort. The model was then applied on testing cohort with advanced stage and age patients for H&E survival score. The c-index of the predicted risk on overall survival (OS) and progression-free survival (PFS) were 0.66 and 0.63, respectively. The log-rank p-values of patients between low and high risk were 0.00137 and 0.00138, respectively. The model was then further evaluated with an external dataset. The c-index of the predicted risk were 0.64 and 0.72 for OS and PFS, respectively. And the log-rank test between patients with low and high risk achieved p-values 0.017 and 0.0047 for OS and PFS, respectively. In conclusion, a novel prognostic CNN model was developed for ovarian cancer patients with advanced age and stage for better disease management.

Citation Format: Chun Wai Ng, Kwong-kwok Wong, Berrett Lawson, Sammy Ferri-Borgogno, Samuel Mok. Convolutional neural network algorithms and hematoxylin-and-eosin-stained images predict clinical outcomes in high-grade serous ovarian cancer patients with advanced age and stage [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7662.
Abstract 784: Proteome-wide mendelian randomization identifies causal association between plasma proteins and lung cancer
Authors: Si Guojin , Li Wenxuan , Zhang Yacong , Lyu Zhangyan , Song Fengju , Chen Kexin
Published: March 2024

Background: Lung cancer is one of the world's main health issues, and the exploration of novel protein markers can help to understand the mechanisms of lung cancer development and the discovery of therapeutic targets. Based on this, we used proteome-wide Mendelian Randomization to determine causal associations between plasma protein levels and the risk of developing lung cancer and subtypes. Methods: We performed a two-sample Mendelian Randomization analysis using genome-wide association data for 4907 proteins from the deCODE genetics study and five lung cancer and its subtypes from the FinnGen database. Causal effects were estimated using the Wald-ratio method or the inverse variance weighted (IVW) method, with additional analyses using the other four common methods when the number of SNPs was more than one. The Steiger filter method was used to test the correct direction of the causal effect. Multiple corrections were utilized by the Benjamini-Hochberg method. Results: After filtering, we finally analyzed 4645 proteins for the causal association with lung cancer, and the F-statistic of the instrumental variable for each protein was more than 10. After multiple tests, the levels of four genetically predictive proteins were found to be associated with the risk of lung cancer, and one protein was associated with the risk of small-cell lung cancer. In detail, elevated levels of three genetically predicted proteins were significantly associated with increased risk of lung cancer, namely, SYSC (OR:4.75, 95%CI: 2.47-9.16, FDR=0.007), TM11D (OR: 1.34, 95%CI: 1.17-1.53, FDR=0.02), and PDC6I (OR: 2.35, 95%CI: 1.58-3.49, FDR=0.03). Elevated levels of FASLG (OR: 0.87, 95%CI: 0.82-0.92, FDR=0.007) were associated with a reduced risk of lung cancer. In addition, genetically predicted elevated levels of GRP (OR: 0.05, 95%CI: 0.01-0.17, FDR=0.02) were associated with an increased risk of small-cell lung cancer. The Steiger filter test showed that all directions were from proteins to lung cancer. Conclusion: In this study, we found that five proteins may have effects on the risk of lung cancer, in which genetically predicted SYSC, TM11D, and PDC6I were significantly associated with an increased risk of lung cancer, whereas FASLG and GRP were associated with a decreased risk of lung cancer and small-cell lung cancer, respectively. The above may help to explore the pathogenesis of lung cancer, but further comprehensive studies are still needed.

Citation Format: Guojin Si, Wenxuan Li, Yacong Zhang, Zhangyan Lyu, Fengju Song, Kexin Chen. Proteome-wide mendelian randomization identifies causal association between plasma proteins and lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 784.