bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 6071: Identification of a molecular glue degrader targeting the full-length AR and AR-V7 splice variant
Authors: Liu Yuan , Larsen Mads B. , Lin Bo , Cardenal Irene A. , Kennerdell Jason , Finkel Toren , Chen Bill B.
Published: March 2024

Prostate cancer is the most common cancer in males and the fifth leading cause of cancer mortality worldwide. A variety of therapeutic approaches exist including steroid synthesis inhibitors and next-generation ligand binding domain (LBD) antagonists [e.g., enzalutamide (Enza)]. However, these approaches are only effective against tumors bearing the full-length androgen receptor (AR-FL). In the course of their disease, many patients acquire androgen receptor splice variant 7 (AR-V7), a mutant form of the receptor which lacks the LBD and is constitutively activated. To date, no effective therapy has been demonstrated for patients with metastatic prostate cancer bearing the AR-V7 signature. We have recently developed a high throughput platform that allows for the identification of ligands that can bind to a wide variety of protein targets. Using this approach, we screened a diverse chemical library of 100,000 small molecules to identify compounds that are bound to AR-V7. One such molecule, AR-600, directly bound to AR-V7 and moreover, induced proteasomal-mediated targeted protein degradation of both AR-V7 and AR-FL. In prostate cancer cell lines expressing AR-FL, AR-600 induced a gene expression profile similar to cells treated with Enza including a marked reduction in KLK3 (PSA) expression. Moreover, AR-600 inhibited the growth of 22RV1 cells (IC50=23 nM), a cell line that predominantly expresses AR-V7, as well as C4-2 cells that express predominantly full-length AR (IC50=51 nM). In contrast, the compound did not affect the growth of a wide variety of non-tumorigenic cells, non-prostate tumor cell lines or PC3 cells, a prostate cell line that exhibits AR-independent cell growth (IC50>100uM). Preliminary exploration of the mechanism of action of AR-600 (M.W. ~300 Daltons) demonstrates the compound works as a molecular glue. These results thereby identify a small molecule glue degrader that can specifically induce the targeted protein degradation of the AR-V7 splice variant. Given the strong association of this isoform with treatment resistance, this approach would appear to provide an attractive strategy for patients with metastatic castration resistant prostate cancer.

Citation Format: Yuan Liu, Mads B. Larsen, Bo Lin, Irene A. Cardenal, Jason Kennerdell, Toren Finkel, Bill B. Chen. Identification of a molecular glue degrader targeting the full-length AR and AR-V7 splice variant [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 6071.
Abstract 6177: Machine learning enables prediction of ADC targets from whole slide H&E images
Authors: McCaw Zachary Ryan , Shcherbina Anna , Shah Yajas ,   insitro Research Team, Tagari Philip , Koller Daphne , Probert Christopher
Published: March 2024

Background: The efficacy of antibody-drug conjugates (ADCs) depends on the expression and specificity of the target antigen by tumor cells. Although H&E-stained slides are routinely collected during cancer care, specialized IHC staining is typically required to ascertain antigen expression. Such stains are not always available or readily deployed. The need to perform separate IHC tests for each candidate ADC may burden clinical labs and can hinder access to care in resource-limited settings. Here we develop an ensemble of machine learning models to accurately predict the expression of 166 distinct ADC targets directly from H&E images.

Methods: For each ADC-targeted gene, patients with copy-number amplifications (CNAs) were identified from somatic whole exome sequencing. Genes differentially expressed in patients with CNAs were identified from bulk transcriptomics. For each gene, an expression signature was developed based on the expression levels of differentially upregulated genes. Next, whole-slide, H&E-stained histopathology images were embedded into a lower-dimensional representation via a transformer model trained with self-supervised learning. Neural networks were developed to predict a patient’s probability of having a CNA in an ADC-targeted gene, as indicated by an expression signature exceeding the p90. All evaluation metrics were ascertained by 5-fold cross-validation, with training and evaluation on independent patients.

Results: For each of the 166 ADC-targeted genes, a median of 154 patients were found to harbor a CNA, and the expression signature included a median of 180 genes. In all cases, patients with CNAs had significantly higher expression signatures than those without. For predicting likely CNA status directly from H&E histopathology images, the mean AUROC was 0.888 (95% CI, 0.876-0.900) and the mean AUPRC was 0.571 (95% CI, 0.531-0.611). Among the 166 ADC-targeted genes, the AUROC exceeded 0.95 for 31.3%, 0.8 for 80.7%, and 0.725 for 100%. The best-predicted ADC target was SLC7A5 (AUROC: 0.995 [95% CI, 0.994-0.998]; AUPRC: 0.967 [95% CI, 0.963-0.976]).

Conclusion: We have developed models that accurately predict the likely expression of ADC targets based solely on H&E images. The ability to accurately discern the presence of ADC antigens from H&E images has numerous potential applications, including cohort refinement, computer-aided diagnosis, and personalized treatment planning.

Citation Format: Zachary Ryan McCaw, Anna Shcherbina, Yajas Shah, insitro Research Team, Philip Tagari, Daphne Koller, Christopher Probert. Machine learning enables prediction of ADC targets from whole slide H&E images [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 6177.
Abstract 6180: Tumor microenvironment phenotypes predict recurrence in African Americans diagnosed with colorectal cancer: A comparative study of manual grading with digital pathology
Authors: Wu Dongling , Xia Rong , Alawad Mouyed , Lee Lili , Gonda Tamas , Cao Wenqing , Hacking Sean
Published: March 2024

African Americans face a higher rate of colorectal cancer (CRC) incidence and mortality compared to other ethnicities. Identifying key prognostic factors is essential for better outcomes in this group. This study focused on the prognostic value of stromal grading in the tumor microenvironment (TME) of African American CRC patients, using both manual grading and digital pathology. A retrospective analysis of CRC cases in African Americans was conducted. Two cohorts were established: a control cohort (patients without recurrence) and a recurrence cohort (patients with recurrence). Stromal grading was performed manually, categorizing tumors into Grade 1 (low risk), Grade 2 (moderate risk), and Grade 3 (high risk), and we also quantified the TME percentages by digital pathology: myxoid, collagen, immune and tumor. In the control cohort (N=40), stromal grading identified 30 Grade 1, 7 Grade 2, and 3 Grade 3 cases. Conversely, the recurrence cohort (N=17) demonstrated a starkly different distribution, with 1 Grade 1, 3 Grade 2, and 13 Grade 3 cases. The Chi-square statistic was notably significant (p<0.0001), indicating a strong association between higher stromal grades and the likelihood of recurrence. By unpaired t-test, high myxoid stroma (p<0.0001), low collagen (p<0.0001), and low tumor (p=0.0002) by digital pathology were associated with recurrence. TME phenotypes are a significant prognostic and recurrence indicator in African American patients with CRC. The marked difference in stromal grades and digital pathology features between the control and recurrence cohorts suggests that higher stromal grades, along with higher myxoid, lower collagen and lower tumor percentages are associated with an increased risk of recurrence. These findings underscore the need for tailored therapeutic strategies and more vigilant surveillance in African American patients exhibiting high-risk TME phenotypes. The efficacy of manual and digital pathology evaluation of the TME also warrants further exploration to enhance prognostic accuracy and treatment personalization.

Citation Format: Dongling Wu, Rong Xia, Mouyed Alawad, Lili Lee, Tamas Gonda, Wenqing Cao, Sean Hacking. Tumor microenvironment phenotypes predict recurrence in African Americans diagnosed with colorectal cancer: A comparative study of manual grading with digital pathology [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 6180.
Abstract 6198: TP53 mutational clusters stratify the Li-Fraumeni syndrome spectrum
Authors: Fischer Nicholas W. , Laverty Brianne , Kafri Ran , Maxwell Kara N. , Woodward Emma R. , Kratz Christian , Malkin David
Published: March 2024

Li-Fraumeni syndrome (LFS) is a highly penetrant cancer predisposition disorder caused by germline variants in the TP53 tumor suppressor gene. LFS has recently been redefined as a ‘spectrum’ disorder to reflect the highly variable cancer types with largely unpredictable ages-of-onset and disease severity. The broad functional gradient associated with different TP53 variants is thought to contribute to LFS heterogeneity, although it is still poorly understood and there is an unmet clinical need for risk stratification strategies to improve variant interpretation and patient care. Here, we performed an unsupervised cluster analysis leveraging p53 mutagenesis datasets (Kato et al., 2003 & Giacomelli et al., 2018) that revealed five TP53 mutational clusters with unique mutation patterns, structural features, and functional consequences. Stratifying germline carriers based on the five clusters exposed important clinical characteristics to consider for patient management, such as ages-of-onset, tumor type development, and survival outcomes. In particular, we discovered an osteosarcoma-prone subgroup comprised of monomeric mutant p53 carriers with aggressive cancer phenotypes. We also identified a cluster of TP53 variants found more often in non-cancer and healthy older populations, and carriers of these variants that developed cancer had less “LFS-like” phenotypes including an older age-of-onset and a significantly higher frequency of colorectal cancers. Remarkably, our TP53 variant clustering strategy could also stratify breast cancer survival among germline carriers. This work provides a new framework to delineate the LFS spectrum toward the development of machine learning-based approaches for personalized cancer surveillance plans.

Citation Format: Nicholas W. Fischer, Brianne Laverty, Ran Kafri, Kara N. Maxwell, Emma R. Woodward, Christian Kratz, David Malkin. TP53 mutational clusters stratify the Li-Fraumeni syndrome spectrum [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 6198.
Abstract 6218: Haplotype-resolved analysis of cancer genomes and epigenomes using Oxford Nanopore sequencing
Authors: Rescheneder Philipp , James Phill , McKenzie Sean , Talenti Andrea , Aganezov Sergey , Turner Dan , Juul Sissel
Published: March 2024

Cancer is a complex and dynamic disease driven by somatic genomic and epigenomic alterations that accumulate over time. These changes give rise to heterogeneous collections of cells or clones, each with distinct (epi)genomic profiles within a single tumour. Accurate characterisation of these changes is crucial for understanding the mechanisms driving the disease, identifying potential therapeutic targets, and personalising treatment strategies. Due to the technological constraints of short-read and array-based approaches, cancer research has historically had a strong focus on detecting small genomic changes like SNPs and small indels (SNVs) as well as the broad characterisation of large-scale copy number changes (CNVs), mostly ignoring other important variant classes and epigenetic modifications. Here we demonstrate how Oxford Nanopore native long-read sequencing enables the direct detection of not only SNVs, but also break point-resolved simple and complex structural variants (SVs and CNVs), haplotype phasing of all variant types, and identification of DNA modifications like 5-methylcytosine (5mC) and 5-hydroxy-methylcytosine (5hmC) from a single tumour-normal dataset. We illustrate how our end-to-end somatic workflow streamlines analysis for the different variant classes and benchmark somatic SNV and SV calling performance using well characterised cancer cell lines and in-silico benchmarking datasets at different sequencing depths. Finally, we use real-world tumour-normal pairs to showcase a comprehensive sample to answer tumour-normal analysis using Nanopore sequencing. This includes the characterisation of complex patterns of somatic SVs in the different cancer samples, the identification of unique 5mC methylation patterns, exploring characteristic differences in 5hmC levels between tumour and normal samples as well as showing how Nanopore long reads enable haplotype and clone specific CNV calling as well as phasing of genetic and epigenetic variation.

Citation Format: Philipp Rescheneder, Phill James, Sean McKenzie, Andrea Talenti, Sergey Aganezov, Dan Turner, Sissel Juul. Haplotype-resolved analysis of cancer genomes and epigenomes using Oxford Nanopore sequencing [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 6218.
Abstract 6240: Mutation impact on mRNA versus protein expression across human cancers
Authors: Liu Yuqi , Elmas Abdulkadir , Huang Kuan-lin
Published: March 2024

Cancer mutations are often assumed to alter proteins, thus promoting tumorigenesis. However, how mutations affect protein expression has rarely been systematically investigated. We conduct a comprehensive analysis of mutation impacts on mRNA- and protein-level expressions of 953 cancer cases with paired genomics and global proteomic profiling across six cancer types. Protein-level impacts are validated for 47.2% of the somatic expression quantitative trait loci (seQTLs), including mutations from likely “long-tail” driver genes. Devising a statistical pipeline for identifying somatic protein-specific QTLs (spsQTLs), we reveal several gene mutations, including NF1 and MAP2K4 truncations and TP53 missenses showing disproportional influence on protein abundance not readily explained by transcriptomics. Cross-validating with data from massively parallel assays of variant effects (MAVE), TP53 missenses associated with high tumor TP53 proteins were experimentally confirmed as functional. Our study demonstrates the importance of considering protein-level expression to validate mutation impacts and identify functional genes and mutations.

Citation Format: Yuqi Liu, Abdulkadir Elmas, Kuan-lin Huang. Mutation impact on mRNA versus protein expression across human cancers [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 6240.
Abstract 6241: A large scale proteogenomic atlas for precision oncology research
Authors: Simchi Nitzan , Givton Ofer , Daitchman Dina , Seger Eran , Pevzner Kirill
Published: March 2024

Recent advances in the field of mass spectrometry proteomics have led to growth in proteomics research resulting in a massive and rapid increase in the volume of high-quality publicly available proteomics datasets. This growth creates an underutilized resource with potential for new discoveries. Effectively utilizing this vast resource of preclinical and clinical samples is a major challenge.

We utilize the growing availability of proteomics and post-translational modifications (PTMs) data for drug and biomarker discovery. This innovative computational approach enables the integration of preclinical and clinical data, both public and proprietary, with a specific emphasis on extracting valuable biological insights that are only observable at the protein level or through PTMs.

We developed a platform that combines multi-omic data curated from the public domain, together with internally generated high quality proteomic and phosphoproteomic data. The platform incorporates diverse clinical annotations, tumor and normal samples, drug sensitivity, patient outcomes and relevant bioinformatic knowledge bases.

The platform can be leveraged to generate insights addressing diverse clinical needs. For example, we demonstrate how our platform can be utilized to estimate the clinical prevalence of a certain protein or protein signature, in order to identify novel response biomarkers with the highest likelihood of success by confirming its presence and variance in clinical datasets. In addition, these insights enable novel understanding of response and resistance mechanisms, thus establishing a framework that expedites the generation of hypotheses for subsequent investigation and experimental validation.

Citation Format: Nitzan Simchi, Ofer Givton, Dina Daitchman, Eran Seger, Kirill Pevzner. A large scale proteogenomic atlas for precision oncology research [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 6241.
Abstract 6244: MultiTME: A Bayesian method for integration and analysis of multimodal, multi-patient spatial profiling data
Authors: Zhang Haoran , Quinn Jeff , Yoffe Liron , Mittal Vivek , Tansey Wesley
Published: March 2024

The role of the tumor microenvironment (TME) in cancer evolution and progression is complex and multi-faceted. Multiple cellular phenotypes and patterns of cell-cell communication have been implicated as drivers of drug resistance and metastasis. The spatial architecture of the TME is emerging as particularly important in characterizing the trajectory of tumor growth and response to therapy. Accordingly, there has been a rapid rise in technologies to spatially profile the TME. Each technology focuses on a different modality (e.g. transcriptomics, proteomics, metabolomics) and operates at a different granularity, from coarse-grained tissue spots aggregating dozens of cells to fine-grained subcellular resolution. There is currently no computational method capable of drawing unified inferences across modalities. We introduce MultiTME, a single, holistic generative model for jointly modeling multimodal data across multiple samples in a cohort. MultiTME addresses these challenges through a two-dimensional integration of both samples and multimodal data. MultiTME incorporates a cohort of tissue samples, enabling the joint modeling of different samples within a single analytical framework. This integration allows for a comprehensive analysis of the spatial distribution of cell types across multiple samples, enhancing the understanding of TME variability and the identification of robust biomarkers. MultiTME also integrates multimodal data with varying resolutions, such as Spatial Transcriptomics (ST), single-cell RNA sequencing (scRNA-seq), and Imaging Mass Cytometry (IMC), and provides a multi-layered understanding of the TME. This integration enables the modeling of TME at a finer scale and the discovery of cell types and subtypes that are not distinguishable using single-modal approaches. It also provides concurrent expression profiles across different modalities, leading to the identification of novel biomarkers. We demonstrate MultiTME's efficiency and scalability with a dataset of coupled ST, scRNA-seq, and IMC from a cohort of 8 lung cancer patients. MultiTME's capability to handle both intra-cohort and inter-modality variability offers a panoramic view of TME and helps identify biomarkers and therapeutic targets for cancer screening and treatment. MultiTME is open source.

Citation Format: Haoran Zhang, Jeff Quinn, Liron Yoffe, Vivek Mittal, Wesley Tansey. MultiTME: A Bayesian method for integration and analysis of multimodal, multi-patient spatial profiling 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 6244.
Abstract 6257: Genome wide, high-throughput, high-resolution structural variation detection at low variant allele fraction for oncology samples
Authors: Hastie Alex R. , Lynch Pat
Published: March 2024

Structural variation detection remains an elusive undertaking. For decades, G-banded karyotyping has remained the standard practice for nearly all hematological malignancy samples. Cancers are diseases of the genome and structural variants (SVs) are a hallmark of nearly all cancers, are often drivers of oncogenicity, and can sometimes be targeted for treatment, as highlighted by the discovery of the Philadelphia chromosome and later the development of targeted kinase inhibitors. One of the most important limitations of karyotyping, its requirement for cells to divide in culture, has prevented its application for most solid tumors and therefore, there is considerably less understanding of the impact of SVs in solid tumors. Optical genome mapping is a technique that is revolutionizing cytogenomics and unlocking the understanding of SVs in the genome at a level never seen before. It not only can detect nearly all variants that a karyotype can, but it can provide 10,000x higher resolution and does not require cell culture. Because of this, it is being adopted for oncology studies across hematological malignancies and solid tumors. This study demonstrates the performance of a new high throughput Stratys instrument for generation of optical genome map data at extraordinarily high coverage depth. With this instrument, 12 samples can be loaded at once, each loaded onto its own cartridge and the instrument can collect 400x genome coverage for each of these samples in 24 hours. The instrument has random access to the cartridges so that completed samples can be swapped out to facilitate optimal instrument run efficiency. To date, this system has been demonstrated to run 60 samples in a week, each at 400x coverage. Data from the instrument can be processed by Bionano Access™ and VIA™ software to call SVs, copy number variants (CNVs), regions of loss of heterozygosity (LOH), on a genome wide basis, and to classify those variants automatically according to guidelines such as the National Comprehensive Cancer Network (NCCN), World Health Organization (WHO), and National Health Services (NHS, United Kingdom). This new high throughput system with advanced bioinformatic data analysis has the potential to further transform structural variation analysis in cancer research.

Citation Format: Alex R. Hastie, Pat Lynch. Genome wide, high-throughput, high-resolution structural variation detection at low variant allele fraction for oncology samples [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 6257.
Abstract 6275: Exposure to neighborhood violence rewires glucocorticoid receptor binding and drives proliferation and invasiveness in lung tumor samples
Authors: Heath Hannah , Yoo Jin Young , Sharma Vani , McGee Hannah , Soliman Aiman , Mohamed Abeer , Matthews Alicia K. , Winn Robert , Madak-Erdogan Zeynep , Kim Sage
Published: March 2024

Background: Despite smoking less, Black men experience higher incidence of lung cancer compared to white men. This health disparity is even more prevalent in Black men from Chicago, suggesting local neighborhood factors impacting tumorigenesis. Preliminary data indicate that, compared to white men, Black men are more likely to reside in neighborhoods with high levels of violence and have elevated levels of hair cortisol.

Objective: To understand the link between lung tumorigenesis and exposure to neighborhood violence, our objective is to investigate the chromatin recruitment of the receptor for cortisol, called the glucocorticoid receptor (GR), and to correlate this recruitment with target gene expression levels.

Methods: Utilizing CUT & RUN, we identified the gene binding sites of GR using 15 lung tumor and corresponding healthy tissue samples from lung cancer patients living in Chicago. GR recruitment to chromatin was correlated with the neighborhood homicide rate obtained using patients’ zip codes. Spatial transcriptome profiles for these 15 lung tumor samples were obtained from the Space Ranger pipeline and gene expression hot spots of GR target genes were visualized using Loupe Browser (10x Genomics).

Results: GR recruitment to regulatory regions of chromatin increases with greater zip code level violence rates. In patients from high violence neighborhoods, tumor samples had higher magnitude of binding compared to normal neighboring tissue. In tumor samples from patients living in high violence compared to low violence neighborhoods, GR binding is seen in genes that are associated with increased tumor aggressiveness. Hot-spot analysis of these genes found strong co-expression of genes associated with proliferation and invasion in samples from high violence but not low violence neighborhoods.

Conclusion: Exposure to neighborhood violence may impact tumor biology via increased GR recruitment to genes associated with proliferation and invasion.

Citation Format: Hannah Heath, Jin Young Yoo, Vani Sharma, Hannah McGee, Aiman Soliman, Abeer Mohamed, Alicia K. Matthews, Robert Winn, Zeynep Madak-Erdogan, Sage Kim. Exposure to neighborhood violence rewires glucocorticoid receptor binding and drives proliferation and invasiveness in lung tumor samples [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 6275.
Abstract 6346: IgG engineered to target PIGR-mediated transcytosis specifically targets intracellular oncoproteins and abrogated tumor growth
Authors: Galindo Carmen Maria Anadon , Lopez-Bailon Luis U. , Chaurio Ricardo A. , Mine Jessica A. , Plappert Noah E. , Conejo-Garcia Jose R.
Published: March 2024

Despite their long half-life, therapeutic antibodies are considered ineffective against intracellular antigens due to their perceived inability to penetrate epithelial cells. Using recombinant antibodies targeting common mutations in oncogenes, we have demonstrated that dimeric IgA, but not the same antibody on an IgG backbone, penetrates human epithelial cancer cells through PIGR-dependent directional transcytosis, specifically neutralizing mutated oncodrivers and expelling antigens outside the cell, bound to secretory IgA. Accordingly, targeting of KRASG12D abrogated tumor cell proliferation in cell culture assays. In vivo, KRASG12D-specific dIgA1 limited the growth of RASG12D-mutated ovarian and lung carcinomas, including in syngeneic tumor-bearing immunocompetent mice. Moreover, dIgA targeting of KRASG12D restricted tumor growth more effectively than small-molecule KRASG12D inhibitors, supporting the potential of this approach for the treatment of human cancers. Since producing dimeric IgA is more challenging than producing monomeric IgG, and because the half-life of IgA is shorter (4-7 days) than IgG (21 days), we have developed a new approach combining KRASG12D specific IgG with a peptide that could join PIGR and penetrates tumor cells through transcytosis, that showed the same effect than IgA controlling tumor growth. Our results provide a rationale for developing modified IgG cell-penetrating antibodies to effectively target common mutations in intracellular oncogenes that drive many aggressive and frequent human cancers. In addition, further experiments suggest that these antibodies could be effectively used to target tumors that have become resistant to existing KRAS inhibitors.

Citation Format: Carmen Maria Anadon Galindo, Luis U. Lopez-Bailon, Ricardo A. Chaurio, Jessica A. Mine, Noah E. Plappert, Jose R. Conejo-Garcia. IgG engineered to target PIGR-mediated transcytosis specifically targets intracellular oncoproteins and abrogated tumor growth [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 6346.
Abstract 6358: Arming tumor-associated macrophages to inhibit cancer progression
Authors: Reddy Joshua P. , Yu Ziqi , Shepard Ryan M. , Von Schalscha Tami , McCormack Stephen J. , Weis Sara M. , Cheresh David A. , Wettersten Hiromi I.
Published: March 2024

Integrin αvβ3 is a marker of cancer progression in a range of epithelial cancers. In the 1990s, a humanized anti-αvβ3 antibody (Etaracizumab) was developed to target αvβ3+ cancer cells via NK cell-mediated cytotoxicity. While it demonstrated safety and some efficacy in clinical trials, our recent study of the immune microenvironment in αvβ3+ human epithelial tumors revealed increased tumor-associated macrophages (TAMs) but minimal NK cell accumulation. Accordingly, we re-engineered Etaracizumab to favor TAM engagement over NK cells and compared the efficacy of this antibody (ABT101) to that of Etaracizumab in various αvβ3+ epithelial cancer models. While ABT101 and Etaracizumab exhibited identical affinity for αvβ3, ABT 101 showed superior anti-tumor activity in vivo. Notably, depleting NK cells in mice had no impact on ABT101’s effectiveness, while macrophage depletion completely abolished its anti-tumor activity. Interestingly, tumors in mice treated with ABT101 displayed a significant increase in TAMs. Here we define an “antigen-effector cell matching” strategy that allows for maximal anti-tumor activity for various drug resistant epithelial cancers. ABT101 will enter clinical trials for patients with drug resistant lung cancer in the first quarter of 2024.

Citation Format: Joshua P. Reddy, Ziqi Yu, Ryan M. Shepard, Tami Von Schalscha, Stephen J. McCormack, Sara M. Weis, David A. Cheresh, Hiromi I. Wettersten. Arming tumor-associated macrophages to inhibit cancer progression [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 6358.
Abstract 6363: The biparatopic antibody KA-3005 against MET is suitable for developing antibody-drug conjugates (ADCs) to treat MET-expressing cancers
Authors: Wu Guojin , Liang Jiabei , Peng Hao , Hao Feng , Liu Tongtong , Ning Jinying
Published: March 2024

MET is overexpressed in a significant fraction of lung (25%-50%) and gastroesophageal cancers, making the targeting of MET with an antibody-drug conjugate (ADC) an attractive approach. Here, we developed a bispecific antibody (BsAb) named KA-3005, targeting two different epitopes within the extracellular domain of MET using our common light chain antibody discovery platform. KA-3005 has a regular antibody structure with an identical light chain, developed using knob-into-hole technology. This antibody exhibits significantly higher avidity to MET expressed on tumor cells, with an EC50 of less than 0.1nM compared to its parent antibodies. It also completely blocks the binding of HGF to MET and the MET downstream pathway at a concentration as low as 1nM. This biparatopic antibody demonstrates a faster internalization rate upon binding to the surface of tumor cells expressing MET than its parent antibodies. KA-3005 effectively suppressed the growth of HCC827-HGF tumors in a xenograft mouse model. Additionally, it has a half-life of more than five days in the blood of Balb/c mice. Finally, we assessed the developability of KA-3005 under different treatments such as high concentration, low pH, repeated freezing and thawing, and high temperature, and it showed neither aggregation nor degradation. In conclusion, this biparatopic antibody, KA-3005, developed with our common light chain antibody discovery platform, is stable and holds potential for the development of ADCs targeting MET.

Citation Format: Guojin Wu, Jiabei Liang, Hao Peng, Feng Hao, Tongtong Liu, Jinying Ning. The biparatopic antibody KA-3005 against MET is suitable for developing antibody-drug conjugates (ADCs) to treat MET-expressing cancers [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 6363.
Abstract 6426: Identification of potential immune biomarkers for GSK-3 inhibitor elraglusib (9-ING-41) in patients with relapsed/refractory metastatic cancer
Authors: Weiskittel Taylor , Huntington Kelsey , Zhang Leiqing , Koukol Austin , Carneiro Benedito A. , Li Hu , Ugolkov Andrey , El-Deiry Wafik , Mazar Andrew
Published: March 2024

Cytokines mediate strong immunomodulatory effects in cancer. Elraglusib (9-ING-41), an inhibitor of GSK-3, is a potent antitumor and immune-modulatory agent in phase 2 clinical trials for the treatment of various cancers. Here, we examined the immune environment of elraglusib-treated cancer patients by measuring peripheral blood protein levels to explore whether the expression level of cytokines/chemokines/soluble cell receptors/growth factors (CCSG) is correlated with clinical outcome. Using a customized Luminex platform, the expression of forty CCSG hypothesized to be linked to GSK-3 activity was assessed in pre-dose plasma samples obtained from 45 cancer patients with relapsed/refractory metastatic disease (NCT03678883; the 1801 trial). All patients in the 1801 trial were treated with elraglusib (dose range: 1-15 mg/kg) either as a single agent (Part 1; n=21) or in combination with chemotherapy (Part 2; n=24). Pre-dose peripheral blood protein levels were examined as binary predictors of clinical outcome using optimal cutoff points determined by maximally selected rank statistics. In the aggregate Part 1 and 2 populations (n=45), we identified 13 CCSG that significantly stratified the cohort by overall survival (OS). High pre-dose levels of CD95 and TNFRSF10C were associated with better OS. CD95 was a better prognostic of OS than TNFRSF10C (HR: 2.27, 95% CI: 1.10-4.67, p-value: 0.023). Low pre-dose levels of 11 CCSG were also significantly associated with favorable OS, with IL-8 being the most predictive (HR: 0.137, 95% CI: 0.0545-0.346, p-value: <0.0001). Part 1 and 2 predose samples were also analyzed separately, and many of the biomarkers identified in the aggregate analysis retained significance in the separated analysis. In Part 1, CXCL5, IFN-alpha, and IL-18 emerged as unique markers, and in Part 2, CCL22 was the single unique marker.The results of our exploratory study identified several putative biomarkers of elraglusib clinical benefit and demonstrated potential immunomodulatory mechanisms of elraglusib that will be used to inform the further clinical development of elraglusib for the treatment of metastatic cancer.

Citation Format: Taylor Weiskittel, Kelsey Huntington, Leiqing Zhang, Austin Koukol, Benedito A. Carneiro, Hu Li, Andrey Ugolkov, Wafik El-Deiry, Andrew Mazar. Identification of potential immune biomarkers for GSK-3 inhibitor elraglusib (9-ING-41) in patients with relapsed/refractory metastatic 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 6426.
Abstract 644: PKC-iota specific inhibitor ICA-1S causes the degradation of mutant p53 in ovarian cancer cell lines
Authors: Marzan Mahfuza , Oishee Nuzhat Nowshin , Olatunji Abigail , Acevedo-Duncan Mildred
Published: March 2024

Ovarian cancer is the most lethal malignant disease of female. Treatment options for ovarian cancer are mostly the use of chemotherapeutics, surgery, or radiotherapy. However, due to resistance to drugs, relapse occurs and thus 5 years survival rate is only 47%. The tumor suppressor protein p53 works as a transcription factor to transcribe several proteins such as p21, p16 and PUMA that lead to halt cell cycle and also induce apoptosis when there is a damage in DNA. Mutation in several regions of p53 (mutp53) is quite common in cancers and can lead to the accumulation of p53 with loss of functions or sometimes gain of oncogenic functions. Thus there is a search for drugs that can degrade the mut53 and can restore the functions of normal p53. In this research, it was observed that the treatment of ovarian cancer cell lines (ES-2, HEY and OVCAR3) with atypical protein kinase C-iota (aPKCɩ) specific inhibitors ICA-1S can cause the degradation of mutp53 (53.6%, N=6 trials). Treatment with ICA-1S also lowered the level of phosphorylated p53 (ser15, 87%, N=3 trials). However, the level of MDM2 protein (murine double minute 2), a known p53 E3 ligase was not significantly (98%, N=2 trials) affected by ICA-1S in ES-2 cell line with mut p53 as well as p21 was also not affected. However level of PUMA was decreased both in ES-2 and HEY cell lines. Immunoprecipitation (IP) with aPKCɩ specific beads showed the aPKCɩ is associated with p53, though reverse IP with p53 beads was not able to show the association. Application of proteasome inhibitor MG-132 at a single dose of 0.5µM could not completely inhibit the degradation of mut53 and WTp53 in ICA-1S treated ES-2 cell line and HEY cell line, respectively, indicating the drug may be affecting the transcription of p53 as well. It is therefore postulated that aPKCɩ can phosphorylate p53, stabilizing it and may be affecting the transcription of p53 as well in those cell lines. Further research (kinase activity assay, immunoprecipitation, immunofluorescence) is going on to reveal the mode of this degradation.

Citation Format: Mahfuza Marzan, Nuzhat Nowshin Oishee, Abigail Olatunji, Mildred Acevedo-Duncan. PKC-iota specific inhibitor ICA-1S causes the degradation of mutant p53 in ovarian cancer cell lines [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 644.
Abstract 6462: Somatic mutational profile in MUTYH- associated colorectal cancers (MUTYH-CRCs)
Authors: Kaldas David , de Castria Tiago Biachi
Published: March 2024

Background: Biallelic inactivation of MUTYH leads to hereditary predisposition to colorectal polyposis and CRC. Herein we evaluated co-alterations in somatic next-generation sequencing (NGS) in patients with MUTYH-CRC, mainly KRAS G12C, high tumor mutational burden and microsatellite instability (MSI-H)/mismatch repair deficiency (dMMR).

Methods: Data was collected on patients with MUTYH-CRC in the period between 2015 and 2023 at Moffitt Cancer Center (Tampa, Florida, United States). All patients with MUTYH-CRC were included regardless disease stage. Different germline panels were used to detect MUTYH and Foundation One, Caris and Moffitt STAR (in house NGS) were used to detect somatic co-alterations.

Results: A total of 36 patients were identified with MUTYH- CRC, the median age at diagnosis was 44-year-old, 55% were men. All patients had a somatic NGS available, 18 patients (50%) had KRAS mutation, and specifically KRAS G12C was detected in 9 patients (24%), 6 patients (17%) had MSI-H/dMMR, 5 patients (14%) had BRAF mutation and 4 patients (11%) with BRCA2 mutation.

Conclusion: MUTYH-CRC is associated with a high incidence of targetable alterations including KRAS G12C and BRAF. Considering unique characteristics in MUTYH-CRC tumor microenvironment, including T cell infiltrate, trials combining KRAS G12C/BRAF inhibitors and immune checkpoint inhibitors are warranted.

Citation Format: David Kaldas, Tiago Biachi de Castria. Somatic mutational profile in MUTYH- associated colorectal cancers (MUTYH-CRCs) [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 6462.
Abstract 6479: Metastases in uveal melanoma patients: Trends and risk factors
Authors: Beneke Alice A. , Taneja Kamil , Ladehoff Lauren , Root Kevin , Toloza Eric
Published: March 2024

Purpose: Uveal melanoma has a high tendency to metastasize. Due to its rarity, there has not been large population studies that have demonstrated the effect of demographic variables on a patient’s risk to have metastases.

Methods: The Nationwide Emergency Department Sample was queried from the last quarter of 2015 to 2019 to identify patients with a diagnosis of uveal melanoma. Multivariable logistic regression, with patient- and hospital-level characteristics as covariates, was used to identify factors associated with a higher chance of developing a metastasis and specific metastasis locations.

Results: From the last quarter of 2015 to 2019, there were 7,561 ED encounters with a diagnosis of uveal melanoma. Of these patients, 5.8% had at least one metastasis. Most patients with a metastasis were at least 65 years of age (47.1%), male (54.4%), a Medicare beneficiary (45.2%), and belonged to a family in the highest income quartile (29.7%). The median age of these patients was 61 years (IQR: 32-74). Most patients presented to hospitals in the South (40.7%), with a Trauma Level I designation (56.1%), and to a metropolitan teaching hospital (72.9%). The most common sites of metastasis were liver (17.0%), brain (5.3%), and bone (2.0%). Multivariable logistic regression identified the following factors to be associated with increased risk of developing a metastasis: private insurance (odds ratio [OR]=1.62; p=0.012), highest income quartile (OR=2.30; p<0.001), and 2nd highest income quartile (OR=1.78; p=0.002). The following factors were associated with higher odds of developing a liver metastasis specifically: no-charge/charity work (OR=15.8; p=0.012), highest income quartile (OR=1.99; p=0.003), and second highest income quartile (OR=1.66; p=0.035). Presenting to a Trauma Level I hospital was associated with decreased risk of developing a liver metastasis (OR=0.57; p=0.016). Belonging to the highest income quartile was associated with a higher chance of developing a brain metastasis (OR=2.13; p=0.023) or a bone metastasis (OR=2.74; p=0.045). Among patients with a metastasis, the in-hospital mortality rate was 8.3%.

Conclusion: Metastasis is an important complication to monitor in uveal melanoma patients. In this study, we have demonstrated that income and insurance status are factors that are associated with higher rates of metastases. Physicians should place special attention to these groups to ensure that metastases are minimized.

Citation Format: Alice A. Beneke, Kamil Taneja, Lauren Ladehoff, Kevin Root, Eric Toloza. Metastases in uveal melanoma patients: Trends and risk factors [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 6479.
Abstract 6512: BPI-501836: A highly potent small molecule inhibitor targeting KRASG12D mutation
Authors: Yang Xiang , Lu Yuan , Xu Renqi , Kong Xiaoqiang , Sun Yongqing , Zhu Xingjie , Liu Xiaoyun , Zou Zhengyao , Chen Haibo , Liu Yanju , Sun Jialing , Han Han , Yang Cheng , Guo Jing , Lan Hong , Zhou Quan , Ding Lieming , Wu Hao , Wang Jiabing
Published: March 2024

As one of the most notorious un-druggable oncogenes, mutant KRAS impairs the transition of RAS from its active GTP-binding form to the inactive GDP-binding form, leading to sustained activation of downstream MAPK pathway and ultimately tumorigenesis. The recent approved KRASG12C inhibitors have demonstrated clinical benefits in KARSG12C mutant patients. However, the other prevalent KRAS mutations, such as KRASG12D, remain a huge unmet medical challenge. There’s no approved KRASG12D specific inhibitors yet. Here we present BPI-501836, a highly potent and selective small molecular inhibitor for KRASG12D. In vitro, BPI-501836 exhibited very high potency by disrupting the KRASG12D and cRAF interaction in a cell-free assay. In cell-based assays, BPI-501836 inhibited proliferation of KRASG12D mutant cell lines with sub-nanomolar IC50 values, without affecting wide type or non-G12D KRAS mutant cell lines. Moreover, it also attenuated ERK phosphorylation in KRASG12D mutant cells. In vivo, tumor regression was observed following the administration of 6 mg/kg (iv, QW) BPI-501836 in KRASG12D human pancreatic Panc04.03 xenograft mouse models, or in the KRASG12D human pancreatic PK-59 xenograft mouse models with an intraperitoneal injection of 20 mg/kg per week. Noteworthy was the prolonged half-life of BPI-501836 observed across various species, coupled with its high distribution in tumor tissues. Moreover, sustained suppression of ERK phosphorylation in tumor tissues persisted for up to 144 hours after the last dose of BPI-501836 in both xenograft mouse models. This extended pharmacodynamic effect supports the feasibility of a once-weekly dosing schedule in clinical applications. Safety assessments conducted through a 4-week repeated infusion (intravenous, twice weekly) of BPI-501836 in beagle dog demonstrated favorable safety profiles. In conclusion, BPI-501836 emerges as a highly potent and selective KRASG12D inhibitor, exhibiting promising pharmacokinetics, pharmacodynamics, and safety profiles in pre-clinicalstudies. BPI-501836 is currently in IND-enabling stage and holds potential for further development as a therapeutic agent.

Citation Format: Xiang Yang, Yuan Lu, Renqi Xu, Xiaoqiang Kong, Yongqing Sun, Xingjie Zhu, Xiaoyun Liu, Zhengyao Zou, Haibo Chen, Yanju Liu, Jialing Sun, Han Han, Cheng Yang, Jing Guo, Hong Lan, Quan Zhou, Lieming Ding, Hao Wu, Jiabing Wang. BPI-501836: A highly potent small molecule inhibitor targeting KRASG12D mutation [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 6512.