tbuckley/cabot-search huggingface dataset:
Abstract B023: Paracrine enhancement of tumor cell proliferation provides indirect stroma-mediated chemoresistance via acceleration of tumor recovery between chemotherapy cycles
Authors: Daria Miroshnychenko, Tatiana Miti, Pragya Kumar, Anna Miller, Mark Laurie, Nathalia Giraldo, Marilyn M. Bui, Philipp M. Altrock, David Basanta, Anriy Marusyk
Journal: Cancer Research (2024)

Abstract The ability of tumors to survive therapy reflects both cell-intrinsic and microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity by stroma-produced paracrine factors. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies. Our in vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. At the same time, consistent with prior studies, we observed treatment-independent enhancement of tumor cell proliferation by fibroblast-produced secreted factors. Using spatial statistics analyses, we found that proximity to stroma is often associated with enhanced tumor cell proliferation in vivo. Based on these observations, we hypothesized an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To evaluate the feasibility of this hypothesis, we developed a spatial agent-based model of stroma impact on proliferation/death dynamics. The model was quantitatively parameterized using inferences from histological analyses and experimental studies. We found that the observed enhancement of tumor cell proliferation within stroma-proximal niches can enable tumors to avoid elimination over multiple chemotherapy cycles. Therefore, our study supports the existence of a novel, indirect mechanism of environment-mediated chemoresistance that might contribute to the negative correlation between stromal content and poor therapy outcomes. Citation Format: Daria Miroshnychenko, Tatiana Miti, Pragya Kumar, Anna Miller, Mark Laurie, Nathalia Giraldo, Marilyn M. Bui, Philipp M. Altrock, David Basanta, Anriy Marusyk. Paracrine enhancement of tumor cell proliferation provides indirect stroma-mediated chemoresistance via acceleration of tumor recovery between chemotherapy cycles [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B023.
Abstract B013: Development of oropharyngeal tumor organoids for disease modeling and high throughput drug screening
Authors: Krishna K. Bommakanti, Luda Lin, Yazeed Alhiyari, Andreanne Sannajust, Brandon Mo, Lauran Evans, Peyton Tebon, Maie St. John, Alice Soragni
Journal: Cancer Research (2024)

Abstract Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide with approximately 550,000 new cases diagnosed each year. The oropharynx is one of the most common sites of occurrence, and disease in this region most often presents in the palatine tonsil, followed by the base of tongue and soft palate. Human papilloma virus (HPV) is a common cause of HNSCC, giving rise to a distinct subset of tumors with a different clinical presentation, disease course, and response to treatment. In order to further characterize HPV+ HNSCC tumors and their therapy response, we have leveraged our high throughput 3D tumor organoid screening platform. Our approach entails seeding tumor cells in extracellular matrix gels deposited around the perimeter of tissue culture wells in ring-like structures, with screening results available within a week from surgery (Phan et al, 2019; Al Shihabi et al, 2022; Nguyen et al, 2022; Al Shihabi et al 2023). We particularly focused on tonsil tumors, and develop organoids from both HNSCC and contralateral normal tonsil tissue. Thus far, we have procured tonsil samples from 31 patients to develop organoids, perform high throughput drug screening, and immunohistochemical characterization including H&amp;E staining, Ki67, p16 and p53 immunohistochemical staining. We have leveraged dynamic optical contrast imaging (DOCI), a label-free tissue autofluorescence imaging method that is being investigated clinically (Kim et al, 2017), to assist in distinguishing tumor organoids from normal tissue organoids. Lastly, given the importance of radiation as a treatment modality for HPV+ HNSCC, we have also optimized a chemoradiation pipeline to test possible combinatorial effects. Taken together, our results demonstrate that 3D organoids of HNSCC generated from patient samples can successfully preserve native tissue characteristics and can be used for high throughput drug screening and radiation de-escalation testing, affording critical insight into the management of HNSCC in patients. Citation Format: Krishna K. Bommakanti, Luda Lin, Yazeed Alhiyari, Andreanne Sannajust, Brandon Mo, Lauran Evans, Peyton Tebon, Maie St. John, Alice Soragni. Development of oropharyngeal tumor organoids for disease modeling and high throughput drug screening [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B013.
Abstract B043: Quantifying selection intensity and epistatic interactions among gene variants within angiosarcoma
Authors: Caralynn E. Hampson, Vincent L. Cannataro
Journal: Cancer Research (2024)

Abstract Evolutionary processes underlie cancer development. Mutations occur and accumulate in somatic tissues, and some mutations result in increases in cell division or survival and fix in cell populations more often than expected by chance. Computational techniques that account for differences in mutation rate across the genome and between tissues have helped pinpoint which genes are contributing to tumor growth within a wide array of cancer types. However, rare cancers are often understudied due to lack of funding, availability of data, and applicable tools that are capable of incorporating data from different sources. Recent initiatives, such as the Angiosarcoma Project, have increased data availability for the study of angiosarcoma, a rare cancer with approximately 300 new cases a year. In this study, we incorporate whole-genome, whole-exome, and targeted sequencing data from different sources—accounting for study-specific differences in genome coverage—into an evolutionary analysis of angiosarcoma tumorigenesis. Prior to our study, potential genes with oncogenic activity for angiosarcoma have been primarily evaluated based on genetic variant prevalence among tumor samples, but substitution prevalence is dependent on intrinsic mutation rate and thus relative prevalence of variants may not correspond with relative tumorigenic potential. We calculate the intensity of selection, a measure of the magnitude of increase of cell division and survival, of individual variants driving angiosarcoma, and complement existing studies that have previously determined KDR and TP53 mutations to be a driver of angiosarcoma, and we also implicate novel putative drivers that have high calculated selection intensity, including BRAF V600E, IGDCC4 S1020A, and SETD2 Q1152E. Additionally, we evaluated epistatic interactions among genes and found that selection for TP53 is increased after mutation of other genes such as MUC16, FAT1, and NOTCH2. This study demonstrates the feasibility of applying computational models informed by evolutionary approaches to a rare disease as well as identifies gene variants that likely have a large impact on angiosarcoma tumorigenesis. Citation Format: Caralynn E. Hampson, Vincent L. Cannataro. Quantifying selection intensity and epistatic interactions among gene variants within angiosarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B043.
Abstract A035: Mutation of <i>NOTCH</i>1 is selected within normal esophageal tissues, yet leads to selective epistasis suppressive of further evolution into cancer
Authors: Kira A. Glasmacher, Vincent L. Cannataro, Jeffrey D. Mandell, Mia Jackson, J. Nic Fisk, Jeffrey P. Townsend
Journal: Cancer Research (2024)

Abstract Sequencing of tissues from histologically normal esophagus, among other organs, has revealed that normal tissues acquire somatic variants that are also found in cancers arising from the same tissue types. Our understanding of how somatic mutations that are commonly found in normal tissue can contribute to tumorigenesis is limited: common somatic mutations may or may not confer phenotypes compatible with oncogenesis. However, the strength of selection for somatic variants that appear in both normal and cancer tissues can be quantified in each context using evolutionary modeling approaches. We studied the evolutionary trajectory from normal esophageal tissue to esophageal squamous-cell carcinoma (ESCC) by analysis of sequencing data from previous studies on normal esophageal epithelium and ESCC to reveal the stepwise contributions of somatic mutations to increased cellular division and survival. We also analyzed pairwise selective epistasis between somatically mutated genes that may lead to stepwise substitution patterns. We found that NOTCH1 substitutions are at high prevalence in normal tissue, and scaled selection coefficients indicate that NOTCH1 mutations are highly selected in normal esophageal tissue. In contrast, there is little to no positive selection for NOTCH1 mutations in ESCC, suggesting that NOTCH1 substitutions do not drive tumorigenesis. Indeed, NOTCH1 mutations have recently been shown to favor clonal expansion in normal esophageal tissue. Furthermore, we calculate that mutations in NOTCH1 exhibit antagonistic epistasis with well-known cancer drivers, including TP53, reducing selection for progressive mutations in tumorigenesis. This antagonistic epistasis likely underlies the low likelihood of tumor progression in the presence of NOTCH1 mutations in the esophagus. Citation Format: Kira A. Glasmacher, Vincent L. Cannataro, Jeffrey D. Mandell, Mia Jackson, J. Nic Fisk, Jeffrey P. Townsend. Mutation of NOTCH1 is selected within normal esophageal tissues, yet leads to selective epistasis suppressive of further evolution into cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A035.
Abstract IA013: Using genetic ancestry in genomics of tumor evolution
Authors: Melissa B. Davis
Journal: Cancer Research (2024)

Abstract The burgeoning field of genomic science, particularly in the context of cancer research, has undergone a transformative shift with the incorporation of genetic ancestry in understanding tumor evolution. The work of Melissa B. Davis highlights this paradigm shift, revealing how biases within genomic data, primarily due to the underrepresentation of diverse ethnic groups, have historically influenced our understanding of cancer disparities. Davis's research emphasizes the critical importance of including diverse ethnic groups in genomic studies, not merely as a token inclusion but as a rigorous scientific necessity. Her research demonstrates that by integrating genetic ancestry into the study of tumor biology, we can gain a more comprehensive understanding of cancer's evolution and behavior. This approach is instrumental in identifying unique genetic markers and pathways influenced by ancestry, which may contribute to differences in cancer incidence, progression, and treatment response among different populations. Davis's work thus represents a significant stride towards personalized medicine, where treatment strategies can be tailored not just to the individual's genetic makeup but also to their ancestral background. This shift in focus towards a more inclusive genomic science has the potential to bridge the gap in cancer care disparities. By acknowledging and addressing these disparities, research spearheaded by scientists like Davis paves the way for more equitable healthcare outcomes. The inclusion of genetic ancestry in the study of tumor evolution is more than a scientific advancement; it's a step towards justice and equity in healthcare, ensuring that all groups benefit equally from the advancements in cancer research and treatment. Citation Format: Melissa B. Davis. Using genetic ancestry in genomics of tumor evolution [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA013.
Abstract B007: Reconstruction of cellular phylogenies and analysis of gene expression variation in single cells
Authors: Sayaka Miura, Sudhir Kumar
Journal: Cancer Research (2024)

Abstract In cancer, somatic mutations occur continuously, causing cell populations to evolve. These somatic mutations result in the evolution of cellular gene expression patterns that can also change due to epigenetic modifications and environmental changes. By exploring the concordance of gene expression changes with molecular evolutionary trajectories of cells, we can examine the role of somatic variation on the evolution of gene expression patterns. In these endeavors, reliable inference of the evolutionary relationship of single cells is a key step. However, single-cell sequences contain many errors and missing bases, which necessitate advancing standard molecular phylogenetics approaches for applications in analyzing these datasets. We first show our new computational approach (TopHap+) that integratively applies standard phylogenetic optimality principles and patterns of co-occurrence of sequence variations to produce more expansive and accurate cellular phylogenies from single-cell sequence datasets. We then present Multi-Omics Concordance Analysis (MOCA) software to jointly analyze gene expressions and genetic variations from single-cell RNA sequencing profiles. MOCA outputs cells and genes showing convergent and divergent gene expression patterns in functional genomics. Citation Format: Sayaka Miura, Sudhir Kumar. Reconstruction of cellular phylogenies and analysis of gene expression variation in single cells [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B007.
Enhanced ·OH‐Scavenging Activity of Cu‐CeO<i><sub>x</sub></i> Nanozyme via Resurrecting Macrophage Nrf2 Transcriptional Activity Facilitates Diabetic Wound Healing
Authors: Ziyang Zhu, Jingxin Ding, Muyan Qin, Lingtian Wang, Dajun Jiang, Jinhui Zhao, Deping Wang, Weitao Jia
Journal: Advanced Healthcare Materials (2024)

Diabetic wounds are a prevalent and devastating complication of diabetes, which may impede their healing and regeneration. In diabetic wounds, excess reactive oxygen species (ROS) activate the nuclear factor kappa-B pathway, leading to transcriptional silencing of nuclear factor erythroid 2-related factor 2 (Nrf2), resulting in a vicious cycle of oxidative stress and inflammation. Conventional nanozymes have limitations in preventing the continuous production of ROS, including the most oxidizing reactive hydroxyl radical (·OH), although they can remove pre-existing ROS. Herein, a novel antioxidant nanoplatform addresses this challenge by incorporating JSH-23 into the mesoporous of cupric-doped cerium oxide nanozymes. Additionally, for rapid wound adaptability and durable tissue adhesion, a nanozyme hydrogel spray consisting of oxidized sodium alginate and methacrylate gelatin is constructed, named OG@CCJs. This platform resurrects Nrf2 transcriptional activity of macrophages in vitro, curbing the production of ROS at its source, particularly ·OH, while enabling the nanozymes to scavenge previously generated ROS. OG@CCJs significantly alleviate oxidative stress in diabetic wounds in vivo, promoting wound healing. Overall, the proposed nanozyme-hydrogel spray with enhanced ·OH-scavenging activity uses a "two-track" antioxidant strategy to rebuild the antioxidant defense barrier of macrophages. This pioneering approach highlights the tremendous potential of OG@CCJs for facilitating diabetic wound healing.
Abstract B039: SAMPLER: Unsupervised representations of whole slide images for tumor phenotype prediction
Authors: Patience Mukashyaka, Todd B. Sheridan, Ali Foroughi pour, Jeffrey H. Chuang
Journal: Cancer Research (2024)

Abstract Deep learning has revolutionized digital pathology, allowing for automatic analysis of hematoxylin and eosin (H&amp;E) stained whole slide images (WSIs) for various tasks, such as the classification of cancers into clinical subtypes. In such analyses, WSIs are broken down into smaller images, hereafter called tiles, for efficient processing, with each tile encoded by a deep learning backbone. To reconstruct a slide level representation, a widely applied approach is to combine tile-level features using attention-based deep learning models for each downstream prediction task. These training strategies are (a) computationally intensive, (b) challenging to optimize, (c) sensitive to stain variations across datasets, and (d) require sufficiently large and labeled datasets for supervised training, which are not always available. We propose SAMpling of multiscale empirical distributions for LEarning Representations (SAMPLER), a fully statistical approach to generate WSI representations by encoding the empirical cumulative distribution function (CDF) of multiscale tile features. We evaluated this approach by training logistic regression classifiers from SAMPLER representations. SAMPLER-based classifiers were able to accurately separate subtypes of breast carcinoma (BRCA: AUC=0.911 ± 0.029), subtypes of non-small cell lung carcinoma (NSCLC: AUC=0.940±0.018), and subtypes of renal cell carcinoma (RCC: AUC=0.987±0.006) diagnostic slides of the cancer genome atlas (TCGA). Performance was similar to fully deep learning attention models but &amp;gt;100 times faster. We further validated out models on external test sets. Histopathological review confirms that SAMPLER-identified high attention tiles contain tumor morphological features specific to the tumor type, while low attention tiles contain fibrous stroma, blood, or tissue folding artifacts. SAMPLER is a fast and accurate approach for analyzing WSIs, with greatly improved scalability over attention methods to benefit digital pathology analysis. Citation Format: Patience Mukashyaka, Todd B. Sheridan, Ali Foroughi pour, Jeffrey H. Chuang. SAMPLER: Unsupervised representations of whole slide images for tumor phenotype prediction [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B039.
Abstract B041: Identification of m3C modification sites within mRNAs of pancreatic cancer cells by long-read direct RNA sequencing
Authors: Shuhei Mitsutomi, Anzu Sugawara, Kenji Takahashi, Yusuke Mizukami, Nobuyoshi Akimitsu, Kenzui Taniue
Journal: Cancer Research (2024)

Abstract Chemical modification is a precise and effective way to control the biogenesis, stability, and function of biological molecules, such as nucleic acids, proteins, and lipids. More than 170 different types of modifications have been discovered in coding and non-coding RNAs, constituting a diverse RNA modification landscape, called epitranscriptome. RNA modifications were mediated by three types of proteins: writers, erasers, and readers. Recently, RNA modification machinery has been dysregulated in several types of cancers and may be promising targets for cancer therapy. 3-methylcytidine (m3C), which is catalyzed by METTL2A, 2B, 6, and 8, is found at position 32 of cytoplasmic tRNAs in organisms ranging from yeast to humans, however, their functions and regulatory machinery in mRNA and non-coding RNA has not been clarified because there were no effective anti- m3C antibodies. Here we discovered that the expression of m3C writers was higher in pancreatic tumors than in noncancerous tissues. We further found that METTL2A expression is associated with a poor prognosis in pancreatic cancer patients. We also showed that METTL2A depletion led to a reduction in the growth of AsPC1 cells. We next attempted to identify the m3C sites in cellular transcripts regulated by METTL2A in AsPC1 cells using long-read direct RNA sequencing. We corrected the transcriptome using ESPRESSO and searched for the RNA modifications using Nanocompore. We then found that METTL2A targets the NYCYN motif in mRNAs and mitochondrial rRNAs. Moreover, we found that transcripts with METTL2A-mediated m3C modification were upregulated in AsPC-1 cells knocked down by METTL2A. Our study provides evidence for METTL2A-mediated down-regulation of target mRNAs via m3C modification in the survival of pancreatic tumor cells. Citation Format: Shuhei Mitsutomi, Anzu Sugawara, Kenji Takahashi, Yusuke Mizukami, Nobuyoshi Akimitsu, Kenzui Taniue. Identification of m3C modification sites within mRNAs of pancreatic cancer cells by long-read direct RNA sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B041.