Abstract B062: Activation of the MAPK pathway by altered RNA splicing in cancer

Many cancers carry recurrent, change-of-function mutations affecting RNA splicing factors, however, less is known about the consequences of upregulated RNA splicing factors (SFs) in cancer. Here, we describe a role of survival motor neuron domain containing 1 (SMNDC1) protein, a poorly studied SF that we found to be upregulated in pancreatic ductal adenocarcinoma (PDAC) and high-grade serous ovarian cancers (HGSOCs) and associated with poor patient prognosis. By loss- and gain-of- function approaches we found that SMNDC1 promotes cancer cell proliferation, clonal expansion and tumor growth. Mechanistically, SMNDC1 promoted the retention of A/C-rich exons which otherwise would be excluded or less retained after RNA splicing in normal cells. Inclusion of exon 4 (E4) of MAPK3 (ERK1), which encodes both phosphorylation sites (Thr202/Tyr204) of the kinase, was among the promoted exons by SMNDC1. Forced exclusion of MAPK3 E4 using anti-sense oligos in vitro and in vivo, inhibited the phosphorylation of ERK1/2, the expression of downstream genes (Cyclin D1, Elk1) and increased proapoptotic proteins. These data provide a novel mechanism by which PDAC and HGSOC cells exploit a “splicing switch” that increases ERK1 phosphorylation, and offer a druggable alternative to target these cancer cells by jointly blocking oncogenic signaling and altered RNA splicing.

Citation Format: Yushan Zhang, Md Afjalus Siraj, Prabir Chakrabarty, Robert Tseng, Shamik Das, Resham Bhattacharya, Luisa Escobar-Hoyos, Priyabrata Mukherjee. Activation of the MAPK pathway by altered RNA splicing in cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B062.

Abstract B045: Evaluating the role of altered RNA metabolism in pancreatic cancer therapy resistance

Pancreatic ductal adenocarcinomas (PDACs) are highly lethal, mostly because they quickly develop resistance to current chemotherapies: Gemcitabine (GEM)/paclitaxel or cocktail FOLFIRINOX. Both chemotherapies rely on nucleoside analogues (GEM and 5-fluorouracil [5-FU], and resistance is developed without acquiring mutations, suggesting the role of non-mutational mechanisms for therapy resistance. Our recent findings demonstrated that PDACs depend on RNA splicing proteins to maintain tumors and are exquisitely susceptible to a range of therapies directed at RNA splicing, supporting the role of aberrant RNA splicing in PDAC therapy resistance. Here we evaluated the role of altered RNA splicing in PDAC therapy resistance. Three murine and human isogenic lines with either sensitivity or resistance to GEM were developed. We performed deep RNA sequencing (RNASeq, 80-100 million reads, traditional is 20-40 million reads), differential gene expression, and splicing analyses. GEM resistant PDAC cells demonstrated >40% of non-canonical RNA splice variants and altered expression of 30% of RNA-binding proteins encoded in the human/murine genome, compared to GEM sensitive ones. Specific alternatively spliced exons with common cis-elements were identified in therapy resistant cells, suggesting that these splicing changes are guided by a splicing factor or other RNA-binding protein(s) (RBPs). Top splicing changes were associated to mRNAs encoding ether lipid and pyruvate metabolism. This finding is important as previous studies have linked these metabolic pathways to therapy resistance, however, they have overlooked if protein isoforms, resulting from aberrant splicing, have different impacts in therapy resistance. In addition, GEM and H3B-8800, a novel spliceosome inhibitor showed higher synergistic activity in GEM resistant PDAC cells compared to GEM sensitive cells, suggesting that the development of resistance in PDAC is highly dependent on RNA splicing. Combinedly, these data strongly suggest that resistance to chemotherapeutic agents in PDAC cells requires altered RNA splicing and aberrant expression of associated proteins. Further investigation is ongoing to identify the splicing events and RBPs related to chemotherapy resistance, which will uncover novel mechanisms of therapy resistance and therapeutic modalities by targeting RNA splicing in pancreatic cancer.

Citation Format: Md Afjalus Siraj, Xinning Shan, Robert Tseng, Luisa Escobar-Hoyos. Evaluating the role of altered RNA metabolism in pancreatic cancer therapy resistance [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B045.

Abstract A055: Altered RNA splicing causes pancreatic cancer and exposes a therapeutic vulnerability

With the aim to identify new second-hit mutations that cause pancreatic ductal adenocarcinoma (PDAC), other than mutations in p53, we performed a genetic interaction analysis based on the concept of mutually exclusive mutations, which suggests that mutations that are exclusive to one another function within the same pathway. Using our unbiased quantitative methods to evaluate the effects of somatic mutations on cancer we analyzed >3000 PDAC cases to prioritize mutations among hundreds that appear at low frequencies (5-10%) and that are mutually exclusive with mutations in p53. We found that mutations in RNA splicing factors SF3B1 and RBM10 (~15% of cases), were among the most significant, and mutually exclusive, to mutant p53. Thus, we hypothesized that aberrant RNA splicing promoted by SF3B1K700E and loss of RBM10 cause an oncogenic program that leads to tumorigenesis and therapy resistance. To test this hypothesis, first, we engineered mouse models to co-express KrasG12D with either Sf3b1K700E or loss of Rbm10 in Mist1 and Pdx1 driven expressing pancreatic cells. Interestingly, mice harboring KrasG12D and Sf3b1 K700E or loss of RBM10—like mutant p53—caused PDACs in mice. To identify the RNA splicing mechanism that leads to PDAC formation, we performed deep RNA sequencing and unbiased transcriptome-wide splicing analyses in isolated PDAC cells bearing wild-type, SF3B1K700E and loss of RBM10, derived from murine and patient PDACs. We found that like the splicing defects induced by p53mut—SF3B1K700E or loss of RBM10—induce splicing defects in sequence-specific coding exons in mRNAs derived from chromosomes 19, 7, 1 and 2 and impacting mainly GTPase activation and lipid metabolism pathways across species models. Consistent with this common mechanism, we found that PDAC cells do not tolerate the forced expression of mutant p53 with either SF3B1K700E or loss of Rbm10, supporting the mutual exclusivity findings from patient samples. To determine a personalized therapy pathway for patients bearing mutant splicing-factor tumors, we found that PDAC cells with SF3B1K700E or RBM10 loss cells are more sensitive to Gemcitabine rather than 5FU, which are the two main chemotherapeutic components of the two standard-of-care therapies. In addition, these mutations sensitize cells to small-molecule splicing inhibitor H3B-8800, which has advanced to phase 2 trial for hematologic malignancies. Lastly, we found that combination of Gemcitabine and H3B-8800 synergize to selective kill mutant splicing cells. We are currently testing these combination therapies in our genetically engineered mouse models and patient derived organoids. We are starting a phase 2 trial for Gemcitabine/Abraxane with escalating doses of H3B-8800 for tumors that have either SF3B1K700E, RBM10 loss or neomorphic p53, all which have aberrant RNA splicing. This work has determined novel drivers and mechanisms of PDAC development and a precision therapeutic strategy for the treatment of 45% pancreatic cancer patients (SF3B1K700E [5%], RBM10 loss [10%] and neomorphic p53 [30%]).

Citation Format: Natasha Pinto Medici, Diana Martinez Saucedo, Danny Lee, Li-Ting Ku, Robert Tseng, Vincent Cannataro, Deanne Yugawa, Sumedha Chowdhury, Jeffrey Townsend, Christine A. Iacobuzio-Donahue, Omar Abdel-Wahab, Steven D. Leach, Luisa Escobar-Hoyos. Altered RNA splicing causes pancreatic cancer and exposes a therapeutic vulnerability [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A055.

Abstract 663: Systemic targeting of therapeutic RNA to cancer via a novel, cell-penetrating and nucleic acid binding, monoclonal antibody

There is intense interest in the development of nucleic acid ligands for immune stimulation of the tumor microenvironment via pattern recognition receptors (PRRs), particularly for the treatment of “cold” tumors. However, delivery of these ligands in a tumor-specific manner to avoid systemic toxicity has been a challenge. Many current efforts rely on direct intra-tumoral injection of RNAs or other stimulatory immune ligands, which is therapeutically sub-optimal, especially for metastatic disease. Here we report studies evaluating the utility of a lupus-derived, cell-penetrating antibody, to deliver nucleic acids to tumors in vivo. This antibody, a modified version of 3E10-D31N, designated GMAB, forms non-covalent complexes with RNAs and can mediate highly specific delivery into tumors via intravenous injection by targeting the nucleoside transporter ENT2, which is highly expressed in tumor cells. Studies with labeled RNAs showed tumor specific delivery and functional expression by imaging, with minimal delivery to healthy tissues. Following these proof-of-concept studies, we investigated whether our antibody could be used to deliver RIG-I agonists to tumors. Using a known agonist of RIG-I, 3p-hpRNA, we demonstrated single agent activity of our GMAB/RNA complexes in multiple tumor models, including a mouse model of melanoma (B16) and an orthotopic model of pancreatic cancer (KPC). Measuring 3p-hpRNA by RT-PCR, there was a 1000X fold difference in RNA uptake in KPC tumor cells relative to CD45+ cells isolated from tumors. In addition, synergy between our GMAB/RNA complexes and anti-PD-1 was additionally observed in mouse models of breast (EMT6) and colon (MC38) cancer. Given the expression of ENT2 along the blood brain barrier (BBB), we demonstrate single agent activity of our GMAB/RNA complexes in an orthotopic mouse model of medulloblastoma, resulting in suppression of tumor growth and spinal metastases. Together, these studies demonstrate that the GMAB antibody can 1) localize to orthotopic and flank tumor models, 2) cross the BBB, and 3) deliver RNA payloads to tumors, providing a novel platform for delivery of immunogenic RNAs, as well as mRNAs and siRNAs, directly to tumors with high specificity following systemic administration.

Citation Format: Elias Quijano, Diana Martinez Saucedo, Minsoo Khang, Yanfeng Liu, Dale Ludwig, Bruce C. Turner, Stephen Squinto, Ranjit Bindra, W. Mark Saltzman, Luisa Escobar-Hoyos, Peter M. Glazer. Systemic targeting of therapeutic RNA to cancer via a novel, cell-penetrating and nucleic acid binding, monoclonal antibody [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 663.

Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images

BACKGROUND

Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel.

METHODS

Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and ensemble methods that employ both ColorAE and U-Net, collectively referred to as (3) ColorAE:U-Net. We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor).

RESULTS

We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect 6 different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net into ensemble methods outperform using either ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME). We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also present a use case, wherein we apply the ColorAE:U-Net ensemble method across 3 mIHC WSIs and use the predictions to quantify all stained cell populations and perform nearest neighbor spatial analysis. Thus, we provide proof of concept that these methods can be employed to quantitatively describe the spatial distribution immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.

Abstract B50: Keratin 17 drives tumor aggression and could be targeted for treatment of pancreatic ductal adenocarcinoma

Our aims are to uncover the molecular mechanisms through which keratin 17 (K17), a prognostic biomarker, drives tumor aggression and to target these mechanisms to provide more effective treatment for pancreatic ductal adenocarcinoma (PDAC). In murine orthotopic xenografts, we found that K17-positve PDACs survive for a shorter interval than controls. Prompted by previous reports that post-translational modifications (PTMs) regulate intermediate filament dynamics, we established in vitro that phosphorylated K17 detaches from the cytoskeleton and enters the nucleus, where it promotes tumor growth by targeting tumor suppressor proteins, including p27, for nuclear export and degradation. To further understand the events that control K17 solubilization, we sequenced K17 from primary PDACs by liquid chromatography-mass spectrometry and identified serine sites within the N-terminus that are phosphorylated only in soluble K17. Furthermore, phosphorylation is required to maintain K17 solubility and soluble K17 accumulates in the nucleus of PDAC cells. By an unbiased screen of 80 small-molecule kinase inhibitors in PDAC, we determined that SYK kinase inhibitors, already in clinical trials for other malignancies, abrogated K17 solubilization. Prompted by our finding that K17 serves as a nuclear shuttle of p27, we identified two amino acid sequences in K17 that have similar polarity to sequences that are used by cyclins to dock to p27. Point mutations in two of these domain key residues blocked K17-mediated degradation of nuclear p27, and we identified similar effects in the background of wild-type and oncogenic KrasG12D PDAC cells. Current studies are under way to find additional protein and RNA targets for potential therapeutic intervention. Using patient-derived organoids, human and murine PDAC cells, we determined that K17-expressing PDAC cells are more than twice as resistant as isogenic K17-negative cells to gemcitabine (Gem) and 5-fluorouracil (5-FU), two key components of current chemotherapeutic regimens. By unbiased liquid chromatography-coupled tandem mass spectrometry metabolomics, RNA-sequencing analyses (TCGA), and in vivo magnetic resonance spectroscopy, we found that K17 induces metabolic reprogramming by increasing glycolysis and pyrimidine biosynthesis, pathways that have been linked to chemoresistance. We are extending this work to determine if disruption of K17-mediated metabolic rewiring by small-molecule inhibitors will resensitize tumor cells to pyrimidine analogues. In conclusion, K17 undergoes key post-translational modifications that enable solubilization and nuclear translocation, the targeting of tumor suppressor proteins, and enhanced pyrimidine biosynthesis to drive chemoresistance. Uncovering these mechanisms could ultimately lead to the identification of novel approaches to target the oncogenic functions of K17, and thereby, to enable the development of more effective treatment options for PDAC.

Citation Format: Kenneth R. Shroyer, Luisa Escobar-Hoyos, Cindy Leiton, Chun-Hao Pan, Ryan Kawalerski, Lucia Roa-Peña, Sruthi Babu. Keratin 17 drives tumor aggression and could be targeted for treatment of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr B50.

Overview of established and emerging immunohistochemical biomarkers and their role in correlative studies in MRI

Clinical practice in radiology and pathology requires professional expertise and many years of training to visually evaluate and interpret abnormal phenotypic features in medical images and tissue sections to generate diagnoses that guide patient management and treatment. Recent advances in digital image analysis methods and machine learning have led to significant interest in extracting additional information from medical and digital whole-slide images in radiology and pathology, respectively. This has led to significant interest and research in radiomics and pathomics to correlate phenotypic features of disease with image analytics in order to identify image-based biomarkers. The expanding role of big data in radiology and pathology parallels the development and role of immunohistochemistry (IHC) in the daily practice of pathology. IHC methods were initially developed to provide additional information to help classify tumors and then transformed into an indispensable tool to guide treatment in many types of cancer. IHC markers are used in daily practice to identify specific types of cells and highlight their distributions in tissues in order to distinguish benign from neoplastic cells, determine tumor origin, subclassify neoplasms, and support and confirm diagnoses. In this regard, radiomics, pathomics, and IHC methods are very similar since they enable the extraction of image-based features to characterize various properties of diseases. Due to the dramatic advancements in recent radiomics research, we provide a brief overview of the role of established and emerging IHC biomarkers in various tumor types that have been correlated with radiologic biomarkers to improve diagnostic accuracy, predict prognosis, guide patient management, and select treatment strategies. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:341-354.

Aberrant RNA Splicing in Cancer

RNA splicing, the enzymatic process of removing segments of premature RNA to produce mature RNA, is a key mediator of proteome diversity and regulator of gene expression. Increased systematic sequencing of the genome and transcriptome of cancers has identified a variety of means by which RNA splicing is altered in cancer relative to normal cells. These findings, in combination with the discovery of recurrent change-of-function mutations in splicing factors in a variety of cancers, suggest that alterations in splicing are drivers of tumorigenesis. Greater characterization of altered splicing in cancer parallels increasing efforts to pharmacologically perturb splicing and early-phase clinical development of small molecules that disrupt splicing in patients with cancer. Here we review recent studies of global changes in splicing in cancer, splicing regulation of mitogenic pathways critical in cancer transformation, and efforts to therapeutically target splicing in cancer.

Unmet clinical needs in cervical cancer screening

Cancer rates worldwide are expected to increase disproportionally in coming decades relative to the projected increase in population, especially in the developing world. The general unavailability of the Pap test and the cost of the HPV test in the developing world have precluded the deployment of effective cervical cancer screening programs in many developing countries. Recent improvements in testing technology arise from a need to overcome the significant limitations of the Pap test and HPV test, but results require first-world technology and validation. Developing countries, where cervical cancer remains one of the most important causes of cancer death, have the greatest need for an affordable, easy-to-use, and highly reliable cancer screening method that can return a diagnosis through efficient laboratory analysis or, more easily, at a woman's point of care. While research, testing, and vaccine improvements in recent years continue to lower the incidence of cervical cancer in some developed countries such as the U.S., HPV testing research needs to do more than test for the presence of virus. The tests must determine the presence and progression of cervical disease. Tests should be more sensitive and specific than Pap tests and Pap-related tests, and should be accurate in more than 90 percent of cases. Tests also need to be low-cost, objective, and easy to perform so screening programs can be widely implemented in developing countries where the need for a better cervical cancer screening test is highest. Such tests may be available through the recent advances in specific biomarkers of cervical cancer and multiplex detection technologies. Development of the next generation of cervical cancer tests that are more specific, sensitive, and informative than the traditional Pap or HPV test will make a significant impact on the reduction of cervical cancer worldwide.