Bibliography

While immunotherapy has become the standard of care for lung adenocarcinoma (LUAD) patients without actionable genomic alterations, only a subset of patients benefits from a long-lasting response to immunotherapy. Activation of p53-related signals has emerged as a potential mediator of the lung tumor microenvironment (TME). Given that mutant-p53 interacts with p73 extensively and TAp73-deficient mice develop LUAD, we engineered a mouse model with conditional deletion of TAp73 to understand the interactions of the p53 family in the TME and in metabolic pathways that impact anti-tumor immunity. We demonstrated that TAp73 exerts a tumor-suppressive role in Kras G12D -driven LUAD by regulating lipid metabolism in the TME. We identified a TAp73-driven transcriptional signature involving genes in the arachidonic acid metabolism pathway operational in tumor-associated macrophages that favors T-cell activation and thus anti-tumor immunity. Similar transcriptional changes are seen in macrophages from LUAD patients with p53 mutations and in association with response to immunotherapy.

Significance: There is a need to understand how the LUAD TME impacts patient response to immunotherapy. We identified a transcriptional program enacted by TAp73 in tumor alveolar macrophages that supports T-cell activation. Transcriptional and metabolomic data from LUAD patients supports the relevance of this program in response to immune checkpoint inhibition.

Lung adenocarcinoma (LUAD), the most common histological subtype of lung cancer(1, 2), is a disease of the elderly, with an average age of diagnosis of about 70 years of age(3). Older age is associated with an increased incidence of KRAS-driven LUAD(4), a particularly deadly type of LUAD characterized by treatment resistance and relapse. Despite this, our understanding of how old age shapes KRAS-driven LUAD evolution remains incomplete. While the age-related increase in cancer risk was previously ascribed to the accumulation of mutations over time, we are now beginning to consider the role of host biology as an independent factor influencing cancer. Here, we use single-cell RNA-Sequencing of KP (KrasG12D/+; Trp53flox/flox) LUAD transplanted into young and old mice to define how old age affects LUAD evolution and map the changes that old age imposes onto LUAD's microenvironment. Our data demonstrates that the aged lung environment steers LUAD evolution towards a primitive stem-like state that is associated with poor prognosis. We ascribe this differential evolution, at least in part, to a population of rare and highly secretory damage-associated alveolar differentiation intermediate (ADI) cells that accumulate in the aged tumor microenvironment (TME) and that dominate the niche signaling received by LUAD cells. Overall, our data puts aging center stage in coordinating LUAD evolution, highlighting the need to model LUAD in its most common context and creating a framework to tailor future cancer therapeutic strategies to the age of the patient to improve outcomes in the largest and most vulnerable LUAD patient population, the elderly.

Pharmacological restoration of p53 tumor suppressor function is a conceptually appealing therapeutic strategy for the many deadly cancers with compromised p53 activity, including lung adenocarcinoma (LUAD). However, the p53 pathway has remained undruggable, partly because of insufficient understanding of how to drive effective therapeutic responses without toxicity. Here, we use mouse and human models to deconstruct the transcriptional programs and sequelae underlying robust therapeutic responses in LUAD. We show that p53 drives potent tumor regression by direct Tsc2 transactivation, leading to mTORC1 inhibition and TFEB nuclear accumulation, which in turn triggers lysosomal gene expression programs, autophagy, and cellular senescence. Senescent LUAD cells secrete factors to recruit macrophages, precipitating cancer cell phagocytosis and tumor regression. Collectively, our analyses reveal a surprisingly complex cascade of events underlying a p53 therapeutic response in LUAD and illuminate targetable nodes for p53 combination therapies, thus establishing a critical framework for optimizing p53-based therapeutics.

Mass Spectrometry Imaging (MSI) for small molecules has emerged as the optimal technique to ascertain meaningful biology from spatial distributions of metabolites, lipids, and other classes of molecules. The success or failure of this approach rests on the sample preparation. Each tissue can have its unique challenges. In addition, the established histological processes for embedding frozen tissue, such as optimal cutting temperature medium, produce large polyethylene glycol clusters that suppress and interfere with the signal of biological molecules. To address these challenges, we provide a reproducible protocol for sectioning lung cancer tissue using a commercially available histological embedding matrix using tissues from genetically engineered mouse models of lung adenocarcinoma with a fluorescent reporter cassette to highlight additional microscopy methods used in parallel with mass spectrometry imaging to select regions of interest to compare tumor and adjacent lung tissue. These improvements to existing techniques produce high-quality sections of frozen tissue for histology and mass spectrometry imaging.

Background/Objectives: Hepatocellular carcinoma (HCC) is one of the world’s deadliest cancers; however, the mechanisms that contribute to its aggressiveness are poorly understood. In the recent literature, overexpression of the Chromosome 19 MicroRNA Cluster (C19MC) has been associated with an aggressive phenotype and unfavorable prognosis in HCC. However, the molecular consequences of C19MC overexpression in HCC remain poorly understood. Methods: Here, we created a constitutive C19MC-overexpressing HCC model and used two different CRISPR-engineered C19MC-overexpressing HCC models to analyze phenotype and transcriptomic changes. Results: We observed that C19MC overexpression induces cancer stem cell (CSC) phenotypic features in vitro and analyzed transcriptomic changes in genes correlating with stemness, such as NFκB and EMT. Conclusions: C19MC induces changes in HCC that are consistent with stemness and aggression, which provides a better understanding of why C19MC could be a biomarker of poor prognosis.

Archived tumor specimens are routinely preserved by formalin fixation and paraffin embedding. Despite the conventional wisdom that proteomics might be ineffective due to the cross-linking and pre-analytical variables, these samples have utility for both discovery and targeted proteomics. Building on this capability, proteomics approaches can be used to maximize our understanding of cancer biology and clinical relevance by studying preserved tumor tissues annotated with the patients' medical histories. Proteomics of formalin-fixed paraffin-embedded (FFPE) tissues also integrates with histological evaluation and molecular pathology strategies, so that additional collection of research biopsies or resected tumor aliquots is not needed. The acquisition of data from the same tumor sample also overcomes concerns about biological variation between samples due to intratumoral heterogeneity. However, the protein extraction and proteomics sample preparation from FFPE samples can be onerous, particularly for small (i.e., limited or precious) samples. Therefore, we provide a protocol for a recently introduced kit-based EasyPep method with benchmarking against a modified version of the well-established filter-aided sample preparation strategy using laser-capture microdissected lung adenocarcinoma tissues from a genetically engineered mouse model. This model system allows control over the tumor preparation and pre-analytical variables while also supporting the development of methods for spatial proteomics to examine intratumoral heterogeneity. Data are posted in ProteomeXchange (PXD045879).

The chromosome-19 miRNA cluster (C19MC) restricts viruses depending on the multinucleated state of placental trophoblasts. However, the relationship of C19MC to multinucleation is unknown. Here we show that C19MC is coexpressed in multiple cancer type subsets with meiosis-related genes. We discovered a novel meiosis-III that exhibits simultaneous progression of meiotic nuclear division (MND) and cytokinesis. C19MC promotes meiotic bridged-chromosomes to block MND and cytokinesis to generate multinucleated cells. MND starts with the invagination of nuclear membrane to form nucle(ol)ar invasive cytoplasm (NiC), mitochondria and protein cargoes. Aurora-B regulates the efflux of cargos from NiC, whereas C19MC, CDK1, and autophagy promote cargo influx to inflate NiC size for MND progression. Using CRISPR human genetic engineering we demonstrate that the C19MC expression is required for NiC-driven MND and multinucleation. This discovery has impacts on cancer-pathogen interactions, immunotherapy, vertical transmission of viruses, antiviral research and SpCas9-CRISPR therapeutics.

Preclinical genetically engineered mouse models (GEMMs) of lung adenocarcinoma are invaluable for investigating molecular drivers of tumor formation, progression, and therapeutic resistance. However, histological analysis of these GEMMs requires significant time and training to ensure accuracy and consistency. To achieve a more objective and standardized analysis, we used machine learning to create GLASS-AI, a histological image analysis tool that the broader cancer research community can utilize to grade, segment, and analyze tumors in preclinical models of lung adenocarcinoma. GLASS-AI demonstrates strong agreement with expert human raters while uncovering a significant degree of unreported intratumor heterogeneity. Integrating immunohistochemical staining with high-resolution grade analysis by GLASS-AI identified dysregulation of Mapk/Erk signaling in high-grade lung adenocarcinomas and locally advanced tumor regions. Our work demonstrates the benefit of employing GLASS-AI in preclinical lung adenocarcinoma models and the power of integrating machine learning and molecular biology techniques for studying the molecular pathways that underlie cancer progression.

Hemochorial placentas have evolved defense mechanisms to prevent the vertical transmission of viruses to the immunologically underdeveloped fetus. Unlike somatic cells that require pathogen-associated molecular patterns to stimulate interferon production, placental trophoblasts constitutively produce type III interferons (IFNL) through an unknown mechanism. We demonstrate that transcripts of short interspersed nuclear elements (SINEs) embedded in miRNA clusters within the placenta trigger a viral mimicry response that induces IFNL and confers antiviral protection. Alu SINEs within primate-specific chromosome 19 (C19MC) and B1 SINEs within rodent-specific microRNA cluster on chromosome 2 (C2MC) produce dsRNAs that activate RIG-I-like receptors (RLRs) and downstream IFNL production. Homozygous C2MC knockout mouse trophoblast stem (mTS) cells and placentas lose intrinsic IFN expression and antiviral protection, whereas B1 RNA overexpression restores C2MC D/D mTS cell viral resistance. Our results uncover a convergently evolved mechanism whereby SINE RNAs drive antiviral resistance in hemochorial placentas, placing SINEs as integral players in innate immunity.

SP100 is an antiviral protein that restricts the productive stage of human papillomavirus (HPV) and multiple other viruses, and viruses in turn block SUMO-1-mediated stabilization of SP100 and promotes its degradation . Interferon (IFN) signaling could still produce more SP100 through transcription to counteract viruses. Viruses also disable the transcriptional up-regulation of SP100 to achieve persistent infection in hosts. Chromosome-19 miRNA cluster (C19MC) miRNAs confer variable levels of resistance to different types of viral infections and here we use SP100 mRNA as our target for understanding the tumor context in which it is expressed or suppressed, and its relationship with C19MC-directed antiviral response miRNAs in human cutaneous melanoma (SKCM-TCGA). We show that, high SP100 mRNA expression reflects better survival in melanoma patients and that, the genomic landscape of the SP100 gene is subjected to copy number alteration in SP100 Low melanomas with recurrent breakpoints in chromosome-2q between SP100 and SP110 gene loci and centromere. Besides, the C19MC miRNA-520G promotes SP100 mRNA expression and impedes melanin biosynthesis with down-regulated SLC45A2 and increased HTR2B mRNAs which are known indirect regulators of the tyrosine pool and melanin biosynthesis.

The tumor immune microenvironment (TIME) encompasses many heterogeneous cell types that engage in extensive crosstalk among the cancer, immune, and stromal components. The spatial organization of these different cell types in TIME could be used as biomarkers for predicting drug responses, prognosis and metastasis. Recently, deep learning approaches have been widely used for digital histopathology images for cancer diagnoses and prognoses. Furthermore, some recent approaches have attempted to integrate spatial and molecular omics data to better characterize the TIME. In this review we focus on machine learning-based digital histopathology image analysis methods for characterizing tumor ecosystem. In this review, we will consider three different scales of histopathological analyses that machine learning can operate within: whole slide image (WSI)-level, region of interest (ROI)-level, and cell-level. We will systematically review the various machine learning methods in these three scales with a focus on cell-level analysis. We will provide a perspective of workflow on generating cell-level training data sets using immunohistochemistry markers to "weakly-label" the cell types. We will describe some common steps in the workflow of preparing the data, as well as some limitations of this approach. Finally, we will discuss future opportunities of integrating molecular omics data with digital histopathology images for characterizing tumor ecosystem.

Cardiovascular disease is the leading cause of death and disability worldwide. Effective delivery of cell-selective therapies that target atherosclerotic plaques and neointimal growth while sparing the endothelium remains the Achilles heel of percutaneous interventions. The current study utilizes synthetic microRNA switch therapy that self-assembles to form a compacted, nuclease-resistant nanoparticle <200 nM in size when mixed with cationic amphipathic cell-penetrating peptide (p5RHH). These nanoparticles possess intrinsic endosomolytic activity that requires endosomal acidification. When administered in a femoral artery wire injury mouse model in vivo, the mRNA-p5RHH nanoparticles deliver their payload specifically to the regions of endothelial denudation and not to the lungs, liver, kidney, or spleen. Moreover, repeated administration of nanoparticles containing a microRNA switch, consisting of synthetically modified mRNA encoding for the cyclin-dependent kinase inhibitor p27Kip1 that contains one complementary target sequence of the endothelial cell-specific miR-126 at its 5' UTR, drastically reduced neointima formation after wire injury and allowed for vessel reendothelialization. This cell-selective nanotherapy is a valuable tool that has the potential to advance the fight against neointimal hyperplasia and atherosclerosis.

Summary: The heterogeneous cell types of the tumor-immune microenvironment (TIME) play key roles in determining cancer progression, metastasis, and response to treatment. We report the development of TIMEx, a novel tumor-immune microenvironment deconvolution method emphasizing on estimating infiltrating immune cells for bulk transcriptomics using pan-cancer single-cell RNA-seq signatures. We also implemented a comprehensive, user-friendly web-portal for users to evaluate TIMEx and other deconvolution methods with bulk transcriptomic profiles.

Availability: TIMEx web portal is freely accessible at http://timex.moffitt.org.

Supplementary information: Supplementary data are available at Bioinformatics online.

During implantation, cytotrophoblasts undergo epithelial-to-mesenchymal transition (EMT) as they differentiate into invasive extravillous trophoblasts (EVTs). The primate-specific microRNA cluster on chromosome 19 (C19MC) is exclusively expressed in the placenta, embryonic stem cells and certain cancers however, its role in EMT gene regulation is unknown. In situ hybridization for miR-517a/c, a C19MC cistron microRNA, in first trimester human placentas displayed strong expression in villous trophoblasts and a gradual decrease from proximal to distal cell columns as cytotrophoblasts differentiate into invasive EVTs. To investigate the role of C19MC in the regulation of EMT genes, we employed the CRISPR/dCas9 Synergistic Activation Mediator (SAM) system, which induced robust transcriptional activation of the entire C19MC cistron and resulted in suppression of EMT associated genes. Exposure of human iPSCs to hypoxia or differentiation of iPSCs into either cytotrophoblast-stem-like cells or EVT-like cells under hypoxia reduced C19MC expression and increased EMT genes. Furthermore, transcriptional activation of the C19MC cistron induced the expression of OCT4 and FGF4 and accelerated cellular reprogramming. This study establishes the CRISPR/dCas9 SAM as a powerful tool that enables activation of the entire C19MC cistron and uncovers its novel role in suppressing EMT genes critical for maintaining the epithelial cytotrophoblasts stem cell phenotype.

As one of the most widespread metabolic diseases, atherosclerosis affects nearly everyone as they age; arteries gradually narrow from plaque accumulation over time reducing oxygenated blood flow to central and periphery causing heart disease, stroke, kidney problems, and even pulmonary disease. Personalized medicine promises to bring treatments based on individual genome sequencing that precisely target the molecular pathways underlying atherosclerosis and its symptoms, but to date only a few genotypes have been identified. A promising alternative to this genetic approach is the identification of pathways altered in atherosclerosis by transcriptome analysis of atherosclerotic tissues to target specific aspects of disease. Transcriptomics is a potentially useful tool for both diagnostics and discovery science, exposing novel cellular and molecular mechanisms in clinical and translational models, and depending on experimental design to identify and test novel therapeutics. The cost and time required for transcriptome analysis has been greatly reduced by the development of next generation sequencing. The goal of this resource article is to provide background and a guide to appropriate technologies and downstream analyses in transcriptomics experiments generating ever-increasing amounts of gene expression data.

mRNA therapeutics hold great promise for the treatment of human diseases. While incorporating naturally occurring modified nucleotides during synthesis has greatly increased their potency and safety, challenges in selective expression have hindered clinical applications. MicroRNA (miRNA)-regulated in vitro-transcribed mRNAs, called miRNA switches, have been used to control the expression of exogenous mRNA in a cell-selective manner. However, the effect of nucleotide modifications on miRNA-dependent silencing has not been examined. Here we show that the incorporation of pseudouridine, N1-methylpseudourdine, or pseudouridine and 5-methylcytidine, which increases translation, tends to decrease the regulation of miRNA switches. Moreover, pseudouridine and 5-methylcytidine modification enables one miRNA target site at the 3' UTR to be as effective as four target sites. We also demonstrate that the effects of pseudouridine, pseudouridine and 5-methylcytidine, and N1-methylpseudourdine modification are miRNA switch specific and do not correlate with the proportion of modified nucleotides in the miRNA target site. Furthermore, modified miRNA switches containing seed-complementary target sites are poorly regulated by miRNA. We also show that placing the miRNA target site in the 5' UTR of the miRNA switch abolishes the effect of nucleotide modification on miRNA-dependent silencing. This work provides insights into the influence of nucleotide modifications on miRNA-dependent silencing and informs the design of optimal miRNA switches.

Preeclampsia (PE) is a common cause of maternal morbidity, characterized by impaired trophoblast invasion and spiral artery transformation resulting in progressive uteroplacental hypoxia. Given the primary role of LIN28A and LIN28B in modulating cell metabolism, differentiation, and invasion, we hypothesized that LIN28A and/or LIN28B regulates trophoblast differentiation and invasion, and that its dysregulation may contribute to PE. Here we show that LIN28B is expressed ∼1300-fold higher than LIN28A in human term placenta and is the predominant paralog expressed in primary human trophoblast cultures. The expression of LIN28B mRNA and protein levels are significantly reduced in gestational age-matched preeclamptic vs. normal placentas, whereas LIN28A expression is not different. First trimester human placental sections displayed stronger LIN28B immunoreactivity in extravillous (invasive) cytotrophoblasts and syncytial sprouts vs. villous trophoblasts. LIN28B overexpression increased HTR8 cell proliferation, migration, and invasion, whereas LIN28B knockdown in JEG3 cells reduced cell proliferation. Moreover, LIN28B knockdown in JEG3 cells suppressed syncytin 1 (SYN-1), apelin receptor early endogenous ligand (ELABELA), and the chromosome 19 microRNA cluster, and increased mRNA expression of ITGβ4 and TNF-α. Incubation of BeWo and JEG3 cells under hypoxia significantly decreased expression of LIN28B and LIN28A, SYN-1, and ELABELA, whereas TNF-α is increased. These results provide the first evidence that LIN28B is the predominant paralog in human placenta and that decreased LIN28B may play a role in PE by reducing trophoblast invasion and syncytialization, and by promoting inflammation.

Objective: Infantile hemangiomas (IHs) are the most common benign vascular neoplasms of infancy, characterized by a rapid growth phase followed by a spontaneous involution, or triggered by propranolol treatment by poorly understood mechanisms. LIN28/let-7 axis plays a central role in the regulation of stem cell self-renewal and tumorigenesis. However, the role of LIN28B/let-7 signaling in IH pathogenesis has not yet been elucidated.

Approach and results: LIN28B is highly expressed in proliferative IH and is less expressed in involuted and in propranolol-treated IH samples as measured by immunofluorescence staining and quantitative RT-PCR. Small RNA sequencing analysis of IH samples revealed a decrease in microRNAs that target LIN28B, including let-7, and an increase in microRNAs in the mir-498(46) cistron. Overexpression of LIN28B in HEK293 cells induced the expression of miR-516b in the mir-498(46) cistron. Propranolol treatment of induced pluripotent stem cells, which express mir-498(46) endogenously, reduced the expression of both LIN28B and mir-498(46) and increased the expression of let-7. Furthermore, propranolol treatment reduced the proliferation of induced pluripotent stem cells and induced epithelial-mesenchymal transition.

Conclusions: This work uncovers the role of the LIN28B/let-7 switch in IH pathogenesis and provides a novel mechanism by which propranolol induces IH involution. Furthermore, it provides therapeutic implications for cancers in which the LIN28/let-7 pathway is imbalanced.

Keywords: C19MC; induced pluripotent stem cells; methylation; microRNA; vascular neoplasms.

Successful use of anticancer designer drugs is likely to depend on simultaneous combinations of these drugs to minimize the development of resistant cancer cells. Considering the knowledge base of cancer signaling pathways, mechanisms of designer drug resistance should be anticipated, and early clinical trials could be designed to include arms that combine new drugs specifically with currently US Food and Drug Administration (FDA)-approved drugs expected to blunt alternative signaling pathways. In this review, we indicate examples of alternative signal pathways for recent anticancer drugs, and the use of original, Python-based software to systematically identify signaling pathways that could facilitate resistance to drugs targeting a particular protein. Pathway alternatives can be assessed at http://www.alternativesignalingpathways.com, developed with this review article.