USP13 drives lung squamous cell carcinoma by switching lung club cell lineage plasticity

Lung squamous cell carcinoma (LUSC) is associated with high mortality and limited targeted therapies. USP13 is one of the most amplified genes in LUSC, yet its role in lung cancer is largely unknown. Here, we established a novel mouse model of LUSC by overexpressing USP13 on KrasG12D/+; Trp53flox/flox background (KPU). KPU-driven lung squamous tumors faithfully recapitulate key pathohistological, molecular features, and cellular pathways of human LUSC. We found that USP13 altered lineage-determining factors such as NKX2-1 and SOX2 in club cells of the airway and reinforced the fate of club cells to squamous carcinoma development. We showed a strong molecular association between USP13 and c-MYC, leading to the upregulation of squamous programs in murine and human lung cancer cells. Collectively, our data demonstrate that USP13 is a molecular driver of lineage plasticity in club cells and provide mechanistic insight that may have potential implications for the treatment of LUSC.

Functional analysis reveals driver cooperativity and novel mechanisms in endometrial carcinogenesis

High-risk endometrial cancer has poor prognosis and is increasing in incidence. However, understanding of the molecular mechanisms which drive this disease is limited. We used genetically engineered mouse models (GEMM) to determine the functional consequences of missense and loss of function mutations in Fbxw7, Pten and Tp53, which collectively occur in nearly 90% of high-risk endometrial cancers. We show that Trp53 deletion and missense mutation cause different phenotypes, with the latter a substantially stronger driver of endometrial carcinogenesis. We also show that Fbxw7 missense mutation does not cause endometrial neoplasia on its own, but potently accelerates carcinogenesis caused by Pten loss or Trp53 missense mutation. By transcriptomic analysis, we identify LEF1 signalling as upregulated in Fbxw7/FBXW7-mutant mouse and human endometrial cancers, and in human isogenic cell lines carrying FBXW7 mutation, and validate LEF1 and the additional Wnt pathway effector TCF7L2 as novel FBXW7 substrates. Our study provides new insights into the biology of high-risk endometrial cancer and suggests that targeting LEF1 may be worthy of investigation in this treatment-resistant cancer subgroup.

Loss of p53 and mutational heterogeneity drives immune resistance in an autochthonous mouse lung cancer model with high tumor mutational burden

The role of tumor mutational burden (TMB) in shaping tumor immunity is a key question that has not been addressable using genetically engineered mouse models (GEMMs) of lung cancer. To induce TMB in lung GEMMs, we expressed an ultra-mutator variant of DNA polymerase-E (POLE)P286R in lung epithelial cells. Introduction of PoleP286R allele into KrasG12D and KrasG12D; p53L/L (KP) models significantly increase their TMB. Immunogenicity and sensitivity to immune checkpoint blockade (ICB) induced by Pole is partially dependent on p53. Corroborating these observations, survival of NSCLC patients whose tumors have TP53truncating mutations is shorter than those with TP53WT with immunotherapy. Immune resistance is in part through reduced antigen presentation and in part due to mutational heterogeneity. Total STING protein levels are elevated in Pole mutated KP tumors creating a vulnerability. A stable polyvalent STING agonist or p53 induction increases sensitivity to immunotherapy offering therapeutic options in these polyclonal tumors.

Relationship between the tumor microenvironment and the efficacy of the combination of radiotherapy and immunotherapy

Activating and recruiting the immune system is critical for successful cancer treatment. Since the discovery of immune checkpoint inhibitors, immunotherapy has become the standard of care for many types of cancers. However, many patients fail to respond to immunotherapy. Further research is needed to understand the mechanisms of resistance and adjuvant therapies that can help sensitize patients to immunotherapies. Here, we will discuss how radiotherapy can change the tumor microenvironment and work synergistically with immunotherapy. We will examine different pre-clinical models focusing on their limitations and their unique advantages in studying the efficacy of treatments and the tumor microenvironment. We will also describe emerging findings from clinical trials testing the combination of immunotherapy and radiotherapy.

Novel EGFR-mutant mouse models of lung adenocarcinoma reveal adaptive immunity requirement for durable osimertinib response

Lung cancers bearing oncogenically-mutated EGFR represent a significant fraction of lung adenocarcinomas (LUADs) for which EGFR-targeting tyrosine kinase inhibitors (TKIs) provide a highly effective therapeutic approach. However, these lung cancers eventually acquire resistance and undergo progression within a characteristically broad treatment duration range. Our previous study of EGFR mutant lung cancer patient biopsies highlighted the positive association of a TKI-induced interferon γ transcriptional response with increased time to treatment progression. To test the hypothesis that host immunity contributes to the TKI response, we developed novel genetically-engineered mouse models of EGFR mutant lung cancer bearing exon 19 deletions (del19) or the L860R missense mutation. Both oncogenic EGFR mouse models developed multifocal LUADs from which transplantable cancer cell lines sensitive to the EGFR-specific TKIs, gefitinib and osimertinib, were derived. When propagated orthotopically in the left lungs of syngeneic C57BL/6 mice, deep and durable shrinkage of the cell line-derived tumors was observed in response to daily treatment with osimertinib. By contrast, orthotopic tumors propagated in immune deficient nu/nu or Rag1-/- mice exhibited modest tumor shrinkage followed by rapid progression on continuous osimertinib treatment. Importantly, osimertinib treatment significantly increased intratumoral T cell content and decreased neutrophil content relative to diluent treatment. The findings provide strong evidence supporting the requirement for adaptive immunity in the durable therapeutic control of EGFR mutant lung cancer.

Deep Learning Accelerators' Configuration Space Exploration Effect on Performance and Resource Utilization: A Gemmini Case Study

Though custom deep learning (DL) hardware accelerators are attractive for making inferences in edge computing devices, their design and implementation remain a challenge. Open-source frameworks exist for exploring DL hardware accelerators. Gemmini is an open-source systolic array generator for agile DL accelerator exploration. This paper details the hardware/software components generated using Gemmini. The general matrix-to-matrix multiplication (GEMM) of different dataflow options, including output/weight stationary (OS/WS), was explored in Gemmini to estimate the performance relative to a CPU implementation. The Gemmini hardware was implemented on an FPGA device to explore the effect of several accelerator parameters, including array size, memory capacity, and the CPU/hardware image-to-column (im2col) module, on metrics such as the area, frequency, and power. This work revealed that regarding the performance, the WS dataflow offered a speedup of 3× relative to the OS dataflow, and the hardware im2col operation offered a speedup of 1.1× relative to the operation on the CPU. For hardware resources, an increase in the array size by a factor of 2 led to an increase in both the area and power by a factor of 3.3, and the im2col module led to an increase in area and power by factors of 1.01 and 1.06, respectively.

Novel genetically engineered H3.3G34R model reveals cooperation with ATRX loss in upregulation of Hoxa cluster genes and promotion of neuronal lineage

Background

Pediatric high-grade gliomas (pHGGs) are aggressive pediatric CNS tumors and an important subset are characterized by mutations in H3F3A, the gene that encodes Histone H3.3 (H3.3). Substitution of Glycine at position 34 of H3.3 with either Arginine or Valine (H3.3G34R/V), was recently described and characterized in a large cohort of pHGG samples as occurring in 5-20% of pHGGs. Attempts to study the mechanism of H3.3G34R have proven difficult due to the lack of knowledge regarding the cell-of-origin and the requirement for co-occurring mutations for model development. We sought to develop a biologically relevant animal model of pHGG to probe the downstream effects of the H3.3G34R mutation in the context of vital co-occurring mutations.

Methods

We developed a genetically engineered mouse model (GEMM) that incorporates PDGF-A activation, TP53 loss and the H3.3G34R mutation both in the presence and loss of Alpha thalassemia/mental retardation syndrome X-linked (ATRX), which is commonly mutated in H3.3G34 mutant pHGGs.

Results

We demonstrated that ATRX loss significantly increases tumor latency in the absence of H3.3G34R and inhibits ependymal differentiation in the presence of H3.3G34R. Transcriptomic analysis revealed that ATRX loss in the context of H3.3G34R upregulates Hoxa cluster genes. We also found that the H3.3G34R overexpression leads to enrichment of neuronal markers but only in the context of ATRX loss.

Conclusions

This study proposes a mechanism in which ATRX loss is the major contributor to many key transcriptomic changes in H3.3G34R pHGGs.

Accession number

GSE197988.

An update on genetically engineered mouse models of pancreatic neuroendocrine neoplasms

Pancreatic neuroendocrine neoplasms (PanNENs) are rare and clinically challenging entities. At the molecular level, PanNENs' genetic profile is well characterized, but there is limited knowledge regarding the contribution of the newly identified genes to tumor initiation and progression. Genetically engineered mouse models (GEMMs) are the most versatile tool for studying the plethora of genetic variations influencing PanNENs' etiopathogenesis and behavior over time. In this review, we present the state of the art of the most relevant PanNEN GEMMs available and correlate their findings with the human neoplasms' counterparts. We discuss the historic GEMMs as the most used and with higher translational utility models. GEMMs with Men1 and glucagon receptor gene germline alterations stand out as the most faithful models in recapitulating human disease; RIP-Tag models are unique models of early-onset, highly vascularized, invasive carcinomas. We also include a section of the most recent GEMMs that evaluate pathways related to cell cycle and apoptosis, Pi3k/Akt/mTOR, and Atrx/Daxx. For the latter, their tumorigenic effect is heterogeneous. In particular, for Atrx/Daxx, we will require more in-depth studies to evaluate their contribution; even though they are prevalent genetic events in PanNENs, they have low/inexistent tumorigenic capacity per se in GEMMs. Researchers planning to use GEMMs can find a road map of the main clinical features in this review, presented as a guide that summarizes the chief milestones achieved. We identify pitfalls to overcome, concerning the novel designs and standardization of results, so that future models can replicate human disease more closely.

Decadal changes in PM2.5-related health impacts in China from 1990 to 2019 and implications for current and future emission controls

In China, the rapid development of the economy and implementation of multiple emission control policies in recent decades have been accompanied by dramatic changes in air quality. In this study, PM_2.5 concentrations estimated by using MERRA-2 reanalysis data were integrated into the Global Exposure Mortality Model (GEMM) to explore the spatiotemporal variation of nationwide PM_2.5-related premature mortality from 1990 to 2019, and the driving factors behind decadal changes were evaluated. Since 2000, as a result of PM_2.5 pollution, air quality in China has deteriorated substantially, especially in the fast-developing eastern and southern parts. In 2009, the nationwide population-weighted (PW) PM_2.5 concentration peaked at 41.4 μg/m³ (95% confidence interval [CI], 36.7-46.2). Simultaneously, the GEMM results revealed that nationwide PM_2.5-related deaths increased remarkably from 1089 (95% CI, 965-1210) thousand in 1990 to 1795 (1597-1986) thousand in 2009. The implementation of the toughest-ever Air Pollution Prevention and Control Action Plan (APPCAP) in 2013 effectively controlled PM_2.5 pollution in China. By 2018, the nationwide PW PM_2.5 concentration had decreased to 34.0 (29.2-38.9) μg/m³. Dynamic trend prediction revealed that, although the APPCAP achieved substantial health benefits, the policy did not result in further remarkable reductions in PM_2.5-related deaths; in 2019, deaths peaked at 1932 (1716-2140) thousand. PM_2.5-related deaths in 2030 were projected for each of four emission control scenarios. The results of the driving factor analysis and the future projections indicated that the health benefits from improving air quality are likely to be counterbalanced by changes in the population age structure. Because population ageing is becoming more and more rapid in China and the challenge of climate change is increasing, the results of this study imply that policymakers need to implement more stringent measures and set more ambitious emission control targets to reduce nationwide PM_2.5-related premature mortality in the future.

K-Ras and p53 mouse model with molecular characteristics of human rhabdomyosarcoma and translational applications

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children, with overall long-term survival rates of ∼65-70%. Thus, additional molecular insights and representative models are critical for identifying and evaluating new treatment modalities. Using MyoD-Cre-mediated introduction of mutant K-RasG12D and perturbations in p53, we developed a novel genetically engineered mouse model (GEMM) for RMS. The anatomic sites of primary RMS development recapitulated human disease, including tumors in the head, neck, extremities and abdomen. We confirmed RMS histology and diagnosis through Hematoxylin and Eosin staining, and positive immunohistochemical staining for desmin, myogenin, and phosphotungstic acid-Hematoxylin. Cell lines from GEMM tumors were established with the ability to engraft in immunocompetent mice with comparable histological and staining features as the primary tumors. Tail vein injection of cell lines had high metastatic potential to the lungs. Transcriptomic analyses of p53R172H/K-RasG12D GEMM-derived tumors showed evidence of high molecular homology with human RMS. Finally, pre-clinical use of these murine RMS lines showed similar therapeutic responsiveness to chemotherapy and targeted therapies as human RMS cell lines.

Designing Genetically Engineered Mouse Models (GEMMs) Using CRISPR Mediated Genome Editing

Genetically engineered mouse models (GEMMs) are very powerful tools to study lineage hierarchy and cellular dynamics of stem cells in vivo. Stem cell behavior in various contexts such as development, normal homeostasis and diseases have been investigated using GEMMs. The strategies to generate GEMMs have drastically changed in the last decade with the development of the CRISPR/Cas9 system for manipulation of the mammalian genome. The advantages of the CRISPR/Cas9 are its simplicity and efficiency. The bioinformatics tools available now allow us to quickly identify appropriate guide RNAs and design experimental conditions to generate the targeted mutation. In addition, the genome can be manipulated directly in the zygote which reduces the time to modify target genes compared to other technologies such as Embryonic Stem (ES) cells. Equally important is that we can manipulate the genome of any mouse background with the CRISPR/Cas9 system which omits time-consuming backcrossing processes, accelerates research and increases flexibility. Here, we will summarize basic allelic types and our standard strategies of how to generate them.

Genetic Mutations of Pancreatic Cancer and Genetically Engineered Mouse Models

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Recent multi-gene analysis approaches such as next-generation sequencing have provided useful information on the molecular characterization of pancreatic tumors. Different types of pancreatic cancer and precursor lesions are characterized by specific molecular alterations. Genetically engineered mouse models (GEMMs) of PDAC are useful tools to understand the roles of altered genes. Most GEMMs are driven by oncogenic Kras, and can recapitulate the histological and molecular hallmarks of human PDAC and comparable precursor lesions. In this review, we summarize the main molecular alterations found in pancreatic neoplasms and GEMMs developed based on these alterations.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy, and the seventh leading cause of cancer-related deaths worldwide. An improved understanding of tumor biology and novel therapeutic discoveries are needed to improve overall survival. Recent multi-gene analysis approaches such as next-generation sequencing have provided useful information on the molecular characterization of pancreatic tumors. Different types of pancreatic cancer and precursor lesions are characterized by specific molecular alterations. Genetically engineered mouse models (GEMMs) of PDAC are useful to understand the roles of altered genes. Most GEMMs are driven by oncogenic Kras, and can recapitulate the histological and molecular hallmarks of human PDAC and comparable precursor lesions. Advanced GEMMs permit the temporally and spatially controlled manipulation of multiple target genes using a dual-recombinase system or CRISPR/Cas9 gene editing. GEMMs that express fluorescent proteins allow cell lineage tracing to follow tumor growth and metastasis to understand the contribution of different cell types in cancer progression. GEMMs are widely used for therapeutic optimization. In this review, we summarize the main molecular alterations found in pancreatic neoplasms, developed GEMMs, and the contribution of GEMMs to the current understanding of PDAC pathobiology. Furthermore, we attempted to modify the categorization of altered driver genes according to the most updated findings.

Atlas of Lobular Breast Cancer Models: Challenges and Strategic Directions

Invasive lobular carcinoma (ILC) accounts for up to 15% of all breast cancer (BC) cases and responds well to endocrine treatment when estrogen receptor α-positive (ER+) yet differs in many biological aspects from other ER+ BC subtypes. Up to 30% of patients with ILC will develop late-onset metastatic disease up to ten years after initial tumor diagnosis and may experience failure of systemic therapy. Unfortunately, preclinical models to study ILC progression and predict the efficacy of novel therapeutics are scarce. Here, we review the current advances in ILC modeling, including cell lines and organotypic models, genetically engineered mouse models, and patient-derived xenografts. We also underscore four critical challenges that can be addressed using ILC models: drug resistance, lobular tumor microenvironment, tumor dormancy, and metastasis. Finally, we highlight the advantages of shared experimental ILC resources and provide essential considerations from the perspective of the European Lobular Breast Cancer Consortium (ELBCC), which is devoted to better understanding and translating the molecular cues that underpin ILC to clinical diagnosis and intervention. This review will guide investigators who are considering the implementation of ILC models in their research programs.

Assessing eukaryotic initiation factor 4F subunit essentiality by CRISPR-induced gene ablation in the mouse

Eukaryotic initiation factor (eIF) 4F plays a central role in the ribosome recruitment phase of cap-dependent translation. This heterotrimeric complex consists of a cap binding subunit (eIF4E), a DEAD-box RNA helicase (eIF4A), and a large bridging protein (eIF4G). In mammalian cells, there are two genes encoding eIF4A (eIF4A1 and eIF4A2) and eIF4G (eIF4G1 and eIF4G3) paralogs that can assemble into eIF4F complexes. To query the essential nature of the eIF4F subunits in normal development, we used CRISPR/Cas9 to generate mouse strains with targeted ablation of each gene encoding the different eIF4F subunits. We find that Eif4e, Eif4g1, and Eif4a1 are essential for viability in the mouse, whereas Eif4g3 and Eif4a2 are not. However, Eif4g3 and Eif4a2 do play essential roles in spermatogenesis. Crossing of these strains to the lymphoma-prone Eμ-Myc mouse model revealed that heterozygosity at the Eif4e or Eif4a1 loci significantly delayed tumor onset. Lastly, tumors derived from Eif4e∆38 fs/+/Eμ-Myc or Eif4a1∆5 fs/+/Eμ-Myc mice show increased sensitivity to the chemotherapeutic agent doxorubicin, in vivo. Our study reveals that eIF4A2 and eIF4G3 play non-essential roles in gene expression regulation during embryogenesis; whereas reductions in eIF4E or eIF4A1 levels are protective against tumor development in a murine Myc-driven lymphoma setting.

Genetically engineered mouse models of esophageal cancer

BACKGROUND

Esophageal cancer is the most common cause of cancer-related death worldwide with a diverse geographical distribution, poor prognosis, and diagnosis in advanced stages of the disease. Identification of the mechanisms involved in esophageal cancer development is evaluative to improve outcomes for patients. Genetically engineered mouse models (GEMMs) of cancer provide the physiologic, molecular, and histologic features of the human tumors to determine the pathogenesis and treatments for cancer, hence exhibiting a source of tremendous potential for oncology research. The advancement of cancer modeling in mice has improved to the extent that researchers can observe and manipulate the disease process in a specific manner. Despite the significant differences between mice and humans, mice can be great models for human oncology researches due to similarities between them at the molecular and physiological levels. Due to most of the existing esophageal cancer GEMMs do not propose an ideal system for pathogenesis of the disease, genetic risks, and microenvironment exposure, so identification of challenges in GEM modeling and well-developed technologies are required to obtain the most value for patients. In this review, we describe the biology of human and mouse, followed by the exciting esophageal cancer mouse models with a discussion of applicability and challenges of these models for generating new GEMMs in future studies.

Mouse Models in Meningioma Research: A Systematic Review

Meningiomas are the most frequent primitive central nervous system tumors found in adults. Mouse models of cancer have been instrumental in understanding disease mechanisms and establishing preclinical drug testing. Various mouse models of meningioma have been developed over time, evolving in light of new discoveries in our comprehension of meningioma biology and with improvements in genetic engineering techniques. We reviewed all mouse models of meningioma described in the literature, including xenograft models (orthotopic or heterotopic) with human cell lines or patient derived tumors, and genetically engineered mouse models (GEMMs). Xenograft models provided useful tools for preclinical testing of a huge range of innovative drugs and therapeutic options, which are summarized in this review. GEMMs offer the possibility of mimicking human meningiomas at the histological, anatomical, and genetic level and have been invaluable in enabling tumorigenesis mechanisms, including initiation and progression, to be dissected. Currently, researchers have a range of different mouse models that can be used depending on the scientific question to be answered.

CyberKnife radiation therapy as a platform for translational mouse studies

PURPOSE

Radiation therapy (RT) is a common nonsurgical treatment in the management of patients with cancer. While genetically engineered mouse models (GEMM) recapitulate human disease, conventional linear particle accelerator systems are not suited for state-of-the-art, imageguided targeted RT (IGRT) of these murine tumors. We employed the CyberKnife (CK; Accuray) platform for IGRT of GEMM-derived non-small cell lung cancer (NSCLC) lesions.

MATERIAL AND METHODS

GEMM-derived Kras^LSL-G12D/+/Trp53^fl/fl -driven NSCLC flank tumors were irradiated using the CK RT platform. We applied IGRT of 2, 4, 6, and 8 Gy using field sizes of 5-12.5 mm to average gross tumor volumes (GTV) of 0.9 cm3 using Xsight Spine Tracking (Accuray).

RESULTS

We found that 0 mm planning target volume (PTV) margin is sufficient for IGRT of murine tumors using the CK. We observed that higher RT doses (6-8 Gy) decreased absolute cell numbers of tumor infiltrating leukocytes (TIL) by approximately half compared to low doses (2-4 Gy) within 1 h, but even with low dose RT (2 Gy) TIL were found to be reduced after 8-24 h.

CONCLUSION

We here demonstrate that the CK RT system allows for targeted IGRT of murine tumors with high precision and constitutes a novel promising platform for translational mouse RT studies.

An Approximate GEMM Unit for Energy-Efficient Object Detection

Edge computing brings artificial intelligence algorithms and graphics processing units closer to data sources, making autonomy and energy-efficient processing vital for their design. Approximate computing has emerged as a popular strategy for energy-efficient circuit design, where the challenge is to achieve the best tradeoff between design efficiency and accuracy. The essential operation in artificial intelligence algorithms is the general matrix multiplication (GEMM) operation comprised of matrix multiplication and accumulation. This paper presents an approximate general matrix multiplication (AGEMM) unit that employs approximate multipliers to perform matrix–matrix operations on four-by-four matrices given in sixteen-bit signed fixed-point format. The synthesis of the proposed AGEMM unit to the 45 nm Nangate Open Cell Library revealed that it consumed only up to 36% of the area and 25% of the energy required by the exact general matrix multiplication unit. The AGEMM unit is ideally suited to convolutional neural networks, which can adapt to the error induced in the computation. We evaluated the AGEMM units’ usability for honeybee detection with the YOLOv4-tiny convolutional neural network. The results implied that we can deploy the AGEMM units in convolutional neural networks without noticeable performance degradation. Moreover, the AGEMM unit’s employment can lead to more area- and energy-efficient convolutional neural network processing, which in turn could prolong sensors’ and edge nodes’ autonomy.

Hindsight: Review of Preclinical Disease Models for the Development of New Treatments for Uveal Melanoma

The molecular, histopathological, genomic and transcriptomic characteristics of uveal melanoma (UM) have identified four molecular subgroups with different clinical outcomes. Despite the improvements in UM classification and biological pathology, current treatments do not reduce the occurrence of metastasis. The development of effective adjuvant and metastatic therapies for UM has been slow and extremely limited. Preclinical models that closely resemble the molecular and genetic UM subgroups are essential for translating molecular findings into improved clinical treatment. In this review, we provide a retrospective view of the existing preclinical models used to study UM, and give an overview of their strengths and limitations. We review targeted therapy clinical trial data to evaluate the gap in the translation of preclinical findings to human studies. Reflecting on the current high attrition rates of clinical trials for UM, preclinical models that effectively recapitulate the human in vivo situation and/or accurately reflect the subtype classifications would enhance the translational impact of experimental data and have crucial implications for the advancement of personalised medicine.

Evaluating the transcriptional fidelity of cancer models

BACKGROUND

Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors.

METHODS

We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence.

RESULTS

We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity.

CONCLUSIONS

CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

Differential Effects of Trp53 Alterations in Murine Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) development is a multi-step process resulting in the accumulation of genetic alterations. Despite its high incidence, there are currently no mouse models that accurately recapitulate this process and mimic sporadic CRC. We aimed to develop and characterize a genetically engineered mouse model (GEMM) of Apc/Kras/Trp53 mutant CRC, the most frequent genetic subtype of CRC.

METHODS

Tumors were induced in mice with conditional mutations or knockouts in Apc, Kras, and Trp53 by a segmental adeno-cre viral infection, monitored via colonoscopy and characterized on multiple levels via immunohistochemistry and next-generation sequencing.

RESULTS

The model accurately recapitulates human colorectal carcinogenesis clinically, histologically and genetically. The Trp53 R172H hotspot mutation leads to significantly increased metastatic capacity. The effects of Trp53 alterations, as well as the response to treatment of this model, are similar to human CRC. Exome sequencing revealed spontaneous protein-modifying alterations in multiple CRC-related genes and oncogenic pathways, resulting in a genetic landscape resembling human CRC.

CONCLUSIONS

This model realistically mimics human CRC in many aspects, allows new insights into the role of TP53 in CRC, enables highly predictive preclinical studies and demonstrates the value of GEMMs in current translational cancer research and drug development.

Genetic ablation of FASN attenuates the invasive potential of prostate cancer driven by Pten loss

Loss of the tumor suppressor gene Pten in murine prostate recapitulates human carcinogenesis and causes stromal proliferation surrounding murine prostate intraepithelial neoplasia (mPIN), which is reactive to microinvasion. In turn, invasion has been shown to be regulated in part by de novo fatty acid synthesis in prostate cancer. We therefore investigated the effects of genetic ablation of Fasn on invasive potential in prostate‐specific Pten knockout mice. Combined genetic ablation of Fasn and Pten reduced the weight and volume of all the prostate lobes when compared to single knockouts. The stromal reaction to microinvasion and the cell proliferation that typically occurs in Pten knockout were largely abolished by Fasn knockout. To verify that Fasn knockout indeed results in decreased invasive potential, we show that genetic ablation and pharmacologic inhibition of FASN in prostate cancer cells significantly inhibit cellular motility and invasion. Finally, combined loss of PTEN with FASN overexpression was associated with lethality as assessed in 660 prostate cancer patients with 14.2 years of median follow‐up. Taken together, these findings show that de novo lipogenesis contributes to the aggressive phenotype induced by Pten loss in murine prostate and targeting Fasn may reduce the invasive potential of prostate cancer driven by Pten loss. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Mouse models of high-risk neuroblastoma

Informative and realistic mouse models of high-risk neuroblastoma are central to understanding mechanisms of tumour initiation, progression, and metastasis. They also play vital roles in validating tumour drivers and drug targets, as platforms for assessment of new therapies and in the generation of drug sensitivity data that can inform treatment decisions for individual patients. This review will describe genetically engineered mouse models of specific subsets of high-risk neuroblastoma, the development of patient-derived xenograft models that more broadly represent the diversity and heterogeneity of the disease, and models of primary and metastatic disease. We discuss the research applications, advantages, and limitations of each model type, the importance of model repositories and data standards for supporting reproducible, high-quality research, and potential future directions for neuroblastoma mouse models.

Point-activated ESR1Y541S has a dramatic effect on the development of sexually dimorphic organs

Mutations in the estrogen receptor α (ERα) occur in endocrine-resistant metastatic breast cancer. However, a major gap persists with the lack of genetically tractable immune competent mouse models to study disease. Hence, we developed a Cre-inducible murine model expressing a point-activated ESR1^Y541S (ESR1^Y537S in humans) driven by its endogenous promoter. Germline expression of mutant ESR1^Y541S reveals dramatic developmental defects in the reproductive organs, mammary glands, and bones of the mice. These observations provide critical insights into the tissue-specific roles of ERα during development and highlights the potential use of our model in further developmental and cancer studies.

Divergent Roles of PI3K Isoforms in PTEN-Deficient Glioblastomas

Loss of PTEN, the negative regulator of PI3K activity, is frequent in glioblastomas (GBMs). However, the role of the two major PI3K isoforms, p110α and p110β, in PTEN-deficient gliomagenesis remains unknown. We show that PTEN-deficient GBM largely depends on p110α for proliferation and p110β for migration. Genetic ablation of either isoform delays tumor progression in mice, but only ablating both isoforms completely blocks GBM driven by the concurrent ablation of Pten and p53. BKM120 (buparlisib) treatment only modestly prolongs survival in mice bearing intracranial Pten/p53 null tumors due to partial pathway inhibition. BKM120 extends the survival of mice bearing intracranial tumors in which p110β, but not p110α, has been genetically ablated in the Pten/p53 null glioma, indicating that BKM120 fails to inhibit p110β effectively. Our study suggests that the failure of PI3K inhibitors in GBM may be due to insufficient inhibition of p110β and indicates a need to develop brain-penetrant p110α/β inhibitors.

Xie et al. show that p110α and p110β isoforms of PI3K play overlapping and divergent roles in PTEN-deficient glioblastomas, suggesting the importance of blocking both PI3K isoforms to effectively treat PTEN-deficient glioblastomas. Moreover, this study also provides a potential mechanism explaining the failure of BKM120 in the clinic.

A conditional mouse expressing an activating mutation in NRF2 displays hyperplasia of the upper gastrointestinal tract and decreased white adipose tissue

Activation of the nuclear factor (erythroid-derived 2)-like 2 (NFE2L2 or NRF2) transcription factor is a critical and evolutionarily conserved cellular response to oxidative stress, metabolic stress, and xenobiotic insult. Deficiency of NRF2 results in hypersensitivity to a variety of stressors, whereas its aberrant activation contributes to several cancer types, most commonly squamous cell carcinomas of the esophagus, oral cavity, bladder, and lung. Between 10% and 35% of patients with squamous cell carcinomas display hyperactive NRF2 signaling, harboring activating mutations and copy number amplifications of the NFE2L2 oncogene or inactivating mutations or deletions of KEAP1 or CUL3, the proteins of which co-complex to ubiquitylate and degrade NRF2 protein. To better understand the role of NRF2 in tumorigenesis and more broadly in development, we engineered the endogenous Nfe2l2 genomic locus to create a conditional mutant LSL-Nrf2^E79Q mouse model. The E79Q mutation, one of the most commonly observed NRF2-activating mutations in human squamous cancers, codes for a mutant protein that does not undergo KEAP1/CUL3-dependent degradation, resulting in its constitutive activity. Expression of NRF2 E79Q protein in keratin 14 (KRT14)-positive murine tissues resulted in hyperplasia of squamous cell tissues of the tongue, forestomach, and esophagus, a stunted body axis, decreased weight, and decreased visceral adipose depots. RNA-seq profiling and follow-up validation studies of cultured NRF2^E79Q murine esophageal epithelial cells revealed known and novel NRF2-regulated transcriptional programs, including genes associated with squamous cell carcinoma (e.g. Myc), lipid and cellular metabolism (Hk2, Ppard), and growth factors (Areg, Bmp6, Vegfa). These data suggest that in addition to decreasing adipogenesis, KRT14-restricted NRF2 activation drives hyperplasia of the esophagus, forestomach, and tongue, but not formation of squamous cell carcinoma. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Genetically Engineered Mouse Models of Liver Tumorigenesis Reveal a Wide Histological Spectrum of Neoplastic and Non-Neoplastic Liver Lesions

Genetically engineered mouse models (GEMM) are an elegant tool to study liver carcinogenesis in vivo. Newly designed mouse models need detailed (histopathological) phenotyping when described for the first time to avoid misinterpretation and misconclusions. Many chemically induced models for hepatocarcinogenesis comprise a huge variety of histologically benign and malignant neoplastic, as well as non-neoplastic, lesions. Such comprehensive categorization data for GEMM are still missing. In this study, 874 microscopically categorized liver lesions from 369 macroscopically detected liver "tumors" from five different GEMM for liver tumorigenesis were included. The histologic spectrum of diagnosis included a wide range of both benign and malignant neoplastic (approx. 82%) and non-neoplastic (approx. 18%) lesions including hyperplasia, reactive bile duct changes or oval cell proliferations with huge variations among the various models and genetic backgrounds. Our study therefore critically demonstrates that models of liver tumorigenesis can harbor a huge variety of histopathologically distinct diagnosis and, depending on the genotype, notable variations are expectable. These findings are extremely important to warrant the correct application of GEMM in liver cancer research and clearly emphasize the role of basic histopathology as still being a crucial tool in modern biomedical research.

Harnessing Omics Approaches on Advanced Preclinical Models to Discovery Novel Therapeutic Targets for the Treatment of Metastatic Colorectal Cancer

Metastatic colorectal cancer (mCRC) remains challenging because of the emergence of resistance mechanisms to anti-epidermal growth factor receptor (EGFR) therapeutics, so more effective strategies to improve the patients’ outcome are needed. During the last decade, the application of a multi-omics approach has contributed to a deeper understanding of the complex molecular landscape of human CRC, identifying a plethora of drug targets for precision medicine. Target validation relies on the use of experimental models that would retain the molecular and clinical features of human colorectal cancer, thus mirroring the clinical characteristics of patients. In particular, organoids and patient-derived-xenografts (PDXs), as well as genetically engineered mouse models (GEMMs) and patient-derived orthotopic xenografts (PDOXs), should be considered for translational purposes. Overall, omics and advanced mouse models of cancer represent a portfolio of sophisticated biological tools that, if optimized for use in concert with accurate data analysis, could accelerate the anticancer discovery process and provide new weapons against cancer. In this review, we highlight success reached following the integration of omics and experimental models; moreover, results produced by our group in the field of mCRC are also presented.

Genetic Liver-Specific AMPK Activation Protects against Diet-Induced Obesity and NAFLD

The AMP-activated protein kinase (AMPK) is a highly conserved master regulator of metabolism, whose activation has been proposed to be therapeutically beneficial for the treatment of several metabolic diseases, including nonalcoholic fatty liver disease (NAFLD). NAFLD, characterized by excessive accumulation of hepatic lipids, is the most common chronic liver disease and a major risk factor for development of nonalcoholic steatohepatitis, type 2 diabetes, and other metabolic conditions. To assess the therapeutic potential of AMPK activation, we have generated a genetically engineered mouse model, termed iAMPK^CA, where AMPK can be inducibly activated in vivo in mice in a spatially and temporally restricted manner. Using this model, we show that liver-specific AMPK activation reprograms lipid metabolism, reduces liver steatosis, decreases expression of inflammation and fibrosis genes, and leads to significant therapeutic benefits in the context of diet-induced obesity. These findings further support AMPK as a target for the prevention and treatment of NAFLD.

Garcia et al. present a GEMM, the “iAMPK^CA” mouse, where AMPK is inducibly activated in vivo in a tissue-specific and temporal on and off nature. Liver-specific AMPK activation in these mice protects from diet-induced obesity and reduces liver steatosis, inflammation, and fibrosis. These data further support AMPK as a therapeutic target for NAFLD.

The Complex Role of Autophagy in Melanoma Evolution: New Perspectives From Mouse Models

Despite tremendous efforts in the last decade to improve treatments, melanoma still represents a major therapeutic challenge and overall survival of patients remains poor. Therefore, identifying new targets to counteract melanoma is needed. In this scenario, autophagy, the “self-eating” process of the cell, has recently arisen as new potential candidate in melanoma. Alongside its role as a recycling mechanism for dysfunctional and damaged cell components, autophagy also clearly sits at a crossroad with metabolism, thereby orchestrating cell proliferation, bioenergetics and metabolic rewiring, all hallmarks of cancer cells. In this regard, autophagy, both in tumor and host, has been flagged as an essential player in melanomagenesis and progression. To pave the way to a better understanding of such a complex interplay, the use of genetically engineered mouse models (GEMMs), as well as syngeneic mouse models, has been undoubtedly crucial. Herein, we will explore the latest discoveries in the field, with particular focus on the potential of these models in unraveling the contribution of autophagy in melanoma, along with the therapeutic advantages that may arise.

CRISPR-mediated modeling and functional validation of candidate tumor suppressor genes in small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer that remains among the most lethal of solid tumor malignancies. Recent genomic sequencing studies have identified many recurrently mutated genes in human SCLC tumors. However, the functional roles of most of these genes remain to be validated. Here, we have adapted the CRISPR-Cas9 system to a well-established murine model of SCLC to rapidly model loss-of-function mutations in candidate genes identified from SCLC sequencing studies. We show that loss of the gene p107 significantly accelerates tumor progression. Notably, compared with loss of the closely related gene p130, loss of p107 results in fewer but larger tumors as well as earlier metastatic spread. In addition, we observe differences in proliferation and apoptosis as well as altered distribution of initiated tumors in the lung, resulting from loss of p107 or p130 Collectively, these data demonstrate the feasibility of using the CRISPR-Cas9 system to model loss of candidate tumor suppressor genes in SCLC, and we anticipate that this approach will facilitate efforts to investigate mechanisms driving tumor progression in this deadly disease.

RAS in pancreatic cancer

The pancreas is a gland composed mainly by endocrine and exocrine cells, giving rise to three main tumour types. Pancreatic neuroendocrine tumour or PNET arise from the endocrine portion of the pancreas. On the contrary, pancreatic exocrine neoplasms include pancreatic ductal adenocarcinoma (PDAC) and acinar cell carcinoma. PDAC is the most common type of pancreatic cancer and one of the leading causes of cancer-related death. It has been shown that less than 3% of PDAC patients have an overall survival of up to 5 years in the U.K. This mainly arises since the majority of patients diagnosed with PDAC present with advanced unresectable disease, which is highly resistant to all forms of chemotherapy and radiotherapy. Activating mutations of an isoform of the RAS protein, KRAS, are found in almost all PDAC cases and occur during early stages of malignant transformation. KRAS mutations play a critical role as they are involved in both initiating and maintaining PDAC development. The interaction of RAS with GDP/GTP along with its recruitment to the membrane affects transduction of its activating signals to downstream effectors. In this review, we aim to summarise different mutations of RAS and their prevalence in pancreatic cancer along with other RAS-induced tumours. In addition, we briefly discuss the genetically engineered mouse models that have been developed to study KRAS-mutated adenocarcinomas in the pancreas. These provide an opportunity to also address the importance of targeting RAS for better treatment response in PDAC patients along with the challenges incurred herein.

Fibroblasts in Pancreatic Ductal Adenocarcinoma: Biological Mechanisms and Therapeutic Targets

The desmoplastic reaction of pancreas cancer may begin as a wound healing response to the nascent neoplasm, but it soon creates an insidious shelter that can sustain the growing tumor and rebuff therapy. Among the many cell types subverted by transformed epithelial cells, fibroblasts are recruited and activated to lay a foundation of extracellular matrix proteins and glycosaminoglycans that alter tumor biophysics and signaling. Their near-universal presence in pancreas cancer and ostensible support of disease progression make fibroblasts attractive therapeutic targets. More recently, however, it has also become apparent that diverse subpopulations of fibroblasts with distinct phenotypes and secretomes inhabit the stroma, and that targeted depletion of particular fibroblast subsets could either provide substantial therapeutic benefit or accelerate disease progression. An improved characterization of these fibroblast subtypes, along with their potential relationships to tumor subtypes and mutational repertoires, is needed in order to make anti-fibroblast therapies clinically viable.

Optofluidic real-time cell sorter for longitudinal CTC studies in mouse models of cancer

Circulating tumor cells (CTCs) play a fundamental role in cancer progression. However, in mice, limited blood volume and the rarity of CTCs in the bloodstream preclude longitudinal, in-depth studies of these cells using existing liquid biopsy techniques. Here, we present an optofluidic system that continuously collects fluorescently labeled CTCs from a genetically engineered mouse model (GEMM) for several hours per day over multiple days or weeks. The system is based on a microfluidic cell sorting chip connected serially to an unanesthetized mouse via an implanted arteriovenous shunt. Pneumatically controlled microfluidic valves capture CTCs as they flow through the device, and CTC-depleted blood is returned back to the mouse via the shunt. To demonstrate the utility of our system, we profile CTCs isolated longitudinally from animals over 4 days of treatment with the BET inhibitor JQ1 using single-cell RNA sequencing (scRNA-Seq) and show that our approach eliminates potential biases driven by intermouse heterogeneity that can occur when CTCs are collected across different mice. The CTC isolation and sorting technology presented here provides a research tool to help reveal details of how CTCs evolve over time, allowing studies to credential changes in CTCs as biomarkers of drug response and facilitating future studies to understand the role of CTCs in metastasis.

In Vivo Pharmacology Models for Cancer Target Research

Experimental animal tumor models have been broadly used to evaluate anticancer drugs in the preclinical setting. They have also been widely applied for drug target discovery and validation, which usually follows four experimental strategies: first, assess the roles of putative drug targets using in vivo tumorigenicity and tumor growth kinetics assays of transplanted tumors, engineered through gain-of-function (GOF) by overexpressing transgene or knock-in (KI) or loss-of-function by gene silencing using knockdown (KD) or knockout (KO) or mutation via mutagenesis procedures; second, similarly genetically engineered mouse models (GEMM), through either germline or somatic cell procedures, are used to test the roles of potential targets in spontaneous tumorigenicity assays; third, patient-derived xenografts (PDXs), which most closely resemble patient genetics and histopathology, are used in tumor inhibition assays for evaluating target-/pathway-specific inhibitors, including large and small molecules, thus assessing the drug target; and fourth, the targets can be assessed in population-based trials, mouse clinical trials (MCT), so that the validation can be generally meaningful as performed in human clinical trials. This chapter outlines the commonly used protocols in cancer drug target research: the first four sections describe four sets of different, specific pharmacology protocols used in the respective cancer modeling stages, with the last section summarizing the common protocols applicable to all four pharmacology modeling steps.

PARP Inhibition Elicits STING-Dependent Antitumor Immunity in Brca1-Deficient Ovarian Cancer

PARP inhibitors have shown promising clinical activities for patients with BRCA mutations and are changing the landscape of ovarian cancer treatment. However, the therapeutic mechanisms of action for PARP inhibition in the interaction of tumors with the tumor microenvironment and the host immune system remain unclear. We find that PARP inhibition by olaparib triggers robust local and systemic antitumor immunity involving both adaptive and innate immune responses through a STING-dependent antitumor immune response in mice bearing Brca1-deficient ovarian tumors. This effect is further augmented when olaparib is combined with PD-1 blockade. Our findings thus provide a molecular mechanism underlying antitumor activity by PARP inhibition and lay a foundation to improve therapeutic outcome for cancer patients.

Back to the Bench? MEK and ERK Inhibitors for the Treatment of KRAS Mutant Lung Adenocarcinoma

BACKGROUND

Lung cancer accounts for one in five cancer deaths worldwide and mutations in the gene encoding for the Kirsten rat sarcoma (KRAS) oncoprotein define the largest molecular subset of non-small cell lung cancer (NSCLC). These tumors are characterized by activated MAPK signaling, however, no targeted inhibitors of mutant KRAS or of downstream signaling molecules have yet been approved for routine clinical use.

OBJECTIVE

The primary objective of this review is to critically summarize the current developmental state of MEK and ERK inhibitors in pre-clinical models and in human clinical trials for KRAS mutant lung cancer particularly in light of the newly emerging concept of immune checkpoint blockade.

METHOD

We performed a Pubmed-based literature search and considered publications from the fields of basic and translational biomedicinal and biochemistry research, as well as from past and ongoing human clinical trials (www.clinicaltrials.gov).

RESULTS AND CONCLUSIONS

MAPK pathway targeting agents are efficacious in pre-clinical models but their benefit is limited for patients with KRAS mutant NSCLC due to the lack of predictive factors, toxicity and the adaptive dynamic kinome reprogramming within the tumor. Overall, MEK inhibitors have advanced further in clinical development compared to ERK inhibitors. New treatment strategies as e.g. immune checkpoint blockade are currently revolutionizing the treatment paradigms and future clinical trials need to show if they replace MAPK targeting strategies or are used as add-on.

The impact of the MYB-NFIB fusion proto-oncogene in vivo

Recurrent fusion of the v-myb avian myelobastosis viral oncogene homolog (MYB) and nuclear factor I/B (NFIB) generates the MYB-NFIB transcription factor, which has been detected in a high percentage of individuals with adenoid cystic carcinoma (ACC). To understand the functional role of this fusion protein in carcinogenesis, we generated a conditional mutant transgenic mouse that expresses MYB-NFIB along with p53 mutation in tissues that give rise to ACC: mammary tissue, salivary glands, or systemically in the whole body. Expression of the oncogene in mammary tissue resulted in hyperplastic glands that developed into adenocarcinoma in 27.3% of animals. Systemic expression of the MYB-NFIB fusion caused more rapid development of this breast phenotype, but mice died due to abnormal proliferation in the glomerular compartment of the kidney, which led to development of glomerulonephritis. These findings suggest the MYB-NFIB fusion is oncogenic and treatments targeting this transcription factor may lead to therapeutic responses in ACC patients.

The adaptive immune system promotes initiation of prostate carcinogenesis in a human c-Myc transgenic mouse model

Increasing evidence from epidemiological and pathological studies suggests a role of the immune system in the initiation and progression of multiple cancers, including prostate cancer. Reports on the contribution of the adaptive immune system are contradictive, since both suppression and acceleration of disease development have been reported. This study addresses the functional role of lymphocytes in prostate cancer development using a genetically engineered mouse model (GEMM) of human c-Myc driven prostate cancer (Hi-Myc mice) combined with B and T cell deficiency (RAG1^-/- mice). From a pre-cancerous stage on, Hi-Myc mice showed higher accumulation of immune cells in their prostates then wild-type mice, of which macrophages were the most abundant. The onset of invasive adenocarcinoma was delayed in Hi-MycRAG1^-/- compared to Hi-Myc mice and associated with decreased infiltration of leukocytes into the prostate. In addition, lower levels of the cytokines CXCL2, CCL5 and TGF-β1 were detected in Hi-MycRAG1^-/- compared to Hi-Myc mouse prostates. These results from a GEMM of prostate cancer provide new insights into the promoting role of the adaptive immune system in prostate cancer development. Our findings indicate that the endogenous adaptive immune system does not protect against de novo prostate carcinogenesis in Hi-Myc transgenic mice, but rather accelerates the formation of invasive adenocarcinomas. This may have implications for the development of novel treatment strategies.

Modeling the process of childhood ETV6-RUNX1 B-cell leukemias

ETV6-RUNX1 is associated with the most common subtype of childhood leukemia. Pre-leukaemic clones carrying ETV6-RUNX1 oncogenic lesions are frequently found in neonatal cord blood, but only few ETV6-RUNX1 carriers develop pB-ALL. The highly demanding and pending challenge is to reveal the multistep natural history of ETV6-RUNX1 pB-ALL, because it can offer non-toxic prophylactic interventions to preleukemic carriers. However, the lack of a genetically engineered ETV6-RUNX1 mouse model mimicking the human pB-ALL has hampered our understanding of the pathogenesis of this disease. This rule has now been broken in a study of the effect of the ETV6-RUNX1 oncogene in cancer development in a mouse model in which oncogene expression is restricted to the stem cell compartment. In this article, we review the different attempts to model this disease, including the recent representative success stories and we discuss its potential application to both identify etiologic factors of childhood ETV6-RUNX1 pB-ALL and prevent the conversion of a preleukemic clone in an irreversible transformed state.

Family matters: How MYC family oncogenes impact small cell lung cancer

Small cell lung cancer (SCLC) is one of the most deadly cancers and currently lacks effective targeted treatment options. Recent advances in the molecular characterization of SCLC has provided novel insight into the biology of this disease and raises hope for a paradigm shift in the treatment of SCLC. We and others have identified activation of MYC as a driver of susceptibility to Aurora kinase inhibition in SCLC cells and tumors that translates into a therapeutic option for the targeted treatment of MYC-driven SCLC. While MYC shares major features with its paralogs MYCN and MYCL, the sensitivity to Aurora kinase inhibitors is unique for MYC-driven SCLC. In this review, we will compare the distinct molecular features of the 3 MYC family members and address the potential implications for targeted therapy of SCLC.

The Impact of Microenvironment on the Synovial Sarcoma Transcriptome

Synovial sarcoma (SS) is initiated by a t(X;18) chromosomal translocation and resultant SS18-SSX fusion oncogene. Only a few SS cell lines exist. None has been compared to its source tumor. In order to compare matched tumor and cell line pairs, we performed RNAseq on 3 tumor/cell line pairs from a genetically engineered mouse model of SS, as well as 2 pairs from human SS tumors. Transcriptomes of mouse tumors and derivative cell lines deviated significantly. Differentially expressed genes highlighted inflammatory infiltrates and metabolism. The same was found for the human tumor and cell line pairs. More was shared between different tumors than between any tumor and its cell line. Direct xenografting generated transcriptomes that more closely resembled the primary tumor than did its derivative cell line. SS tumor transcriptomes are powerfully impacted by the environment wherein they reside, especially with regard to immune interaction and metabolism.

In vivo models in breast cancer research: progress, challenges and future directions

Research using animal model systems has been instrumental in delivering improved therapies for breast cancer, as well as in generating new insights into the mechanisms that underpin development of the disease. A large number of different models are now available, reflecting different types and stages of the disease; choosing which one to use depends on the specific research question(s) to be investigated. Based on presentations and discussions from leading experts who attended a recent workshop focused on in vivo models of breast cancer, this article provides a perspective on the many varied uses of these models in breast cancer research, their strengths, associated challenges and future directions. Among the questions discussed were: how well do models represent the different stages of human disease; how can we model the involvement of the human immune system and microenvironment in breast cancer; what are the appropriate models of metastatic disease; can we use models to carry out preclinical drug trials and identify pathways responsible for drug resistance; and what are the limitations of patient-derived xenograft models? We briefly outline the areas where the existing breast cancer models require improvement in light of the increased understanding of the disease process, reflecting the drive towards more personalised therapies and identification of mechanisms of drug resistance.

Experimental animal modeling for immuno-oncology

Immuno-oncology (I/O) research has intensified significantly in recent years due to the breakthrough development and the regulatory approval of several immune checkpoint inhibitors, leading to the rapid expansion of the new discovery of novel I/O therapies, new checkpoint inhibitors and beyond. However, many I/O questions remain unanswered, including why only certain subsets of patients respond to these treatments, who the responders would be, and how to expand patient response (the conversion of non-responders or maximizing response in partial responders). All of these require relevant I/O experimental systems, particularly relevant preclinical animal models. Compared to other oncology drug discovery, e.g. cytotoxic and targeted drugs, a lack of relevant animal models is a major obstacle in I/O drug discovery, and an urgent and unmet need. Despite the obvious importance, and the fact that much I/O research has been performed using many different animal models, there are few comprehensive and introductory reviews on this topic. This article attempts to review the efforts in development of a variety of such models, as well as their applications and limitations for readers new to the field, particularly those in the pharmaceutical industry.

Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity.

Mouse models of intestinal cancer

Murine models of intestinal cancer are powerful tools to recapitulate human intestinal cancer, understand its biology and test therapies. With recent developments identifying the importance of the tumour microenvironment and the potential for immunotherapy, autochthonous genetically engineered mouse models (GEMMs) will remain an important part of preclinical studies for the foreseeable future. This review will provide an overview of the current mouse models of intestinal cancer, from the Apc(Min/+) mouse, which has been used for over 25 years, to the latest 'state-of-the-art' organoid models. We discuss here how these models have been used to define fundamental processes involved in tumour initiation and the attempts to generate metastatic models, which is the ultimate cause of cancer mortality. Together these models will provide key insights to understand this complex disease and hopefully will lead to the discovery of new therapeutic strategies.

Origins, genetic landscape, and emerging therapies of small cell lung cancer

Lung cancer is the leading cause of cancer deaths, with small cell lung cancer (SCLC) representing the most aggressive subtype. Standard treatments have not changed in decades, and the 5-year survival rate has remained <7%. Genomic analyses have identified key driver mutations of SCLC that were subsequently validated in animal models of SCLC. To provide better treatment options, a deeper understanding of the cellular and molecular mechanisms underlying SCLC initiation, progression, metastasis, and acquisition of resistance is required. In this review, we describe the genetic landscape of SCLC, features of the cell of origin, and targeted therapeutic approaches.

Control of bacterial exoelectrogenesis by c-AMP-GMP

Major changes in bacterial physiology including biofilm and spore formation involve signaling by the cyclic dinucleotides c-di-GMP and c-di-AMP. Recently, another second messenger dinucleotide, c-AMP-GMP, was found to control chemotaxis and colonization by Vibrio cholerae. We have identified a superregulon of genes controlled by c-AMP-GMP in numerous Deltaproteobacteria, including Geobacter species that use extracellular insoluble metal oxides as terminal electron acceptors. This exoelectrogenic process has been studied for its possible utility in energy production and bioremediation. Many genes involved in adhesion, pilin formation, and others that are important for exoelectrogenesis are controlled by members of a variant riboswitch class that selectively bind c-AMP-GMP. These RNAs constitute, to our knowledge, the first known specific receptors for c-AMP-GMP and reveal that this molecule is used by many bacteria to control specialized physiological processes.

The putative tumor suppressor gene EphA3 fails to demonstrate a crucial role in murine lung tumorigenesis or morphogenesis

Treatment of non-small cell lung cancer (NSCLC) is based on histological analysis and molecular profiling of targetable driver oncogenes. Therapeutic responses are further defined by the landscape of passenger mutations, or loss of tumor suppressor genes. We report here a thorough study to address the physiological role of the putative lung cancer tumor suppressor EPH receptor A3 (EPHA3), a gene that is frequently mutated in human lung adenocarcinomas. Our data shows that homozygous or heterozygous loss of EphA3 does not alter the progression of murine adenocarcinomas that result from Kras mutation or loss of Trp53, and we detected negligible postnatal expression of EphA3 in adult wild-type lungs. Yet, EphA3 was expressed in the distal mesenchyme of developing mouse lungs, neighboring the epithelial expression of its Efna1 ligand; this is consistent with the known roles of EPH receptors in embryonic development. However, the partial loss of EphA3 leads only to subtle changes in epithelial Nkx2-1, endothelial Cd31 and mesenchymal Fgf10 RNA expression levels, and no macroscopic phenotypic effects on lung epithelial branching, mesenchymal cell proliferation, or abundance and localization of CD31-positive endothelia. The lack of a discernible lung phenotype in EphA3-null mice might indicate lack of an overt role for EPHA3 in the murine lung, or imply functional redundancy between EPHA receptors. Our study shows how biological complexity can challenge in vivo functional validation of mutations identified in sequencing efforts, and provides an incentive for the design of knock-in or conditional models to assign the role of EPHA3 mutation during lung tumorigenesis.