Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. GC is determined by multiple (epi)genetic and environmental factors; can occur at distinct anatomic positions of the stomach; and displays high heterogeneity, with different cellular origins and diverse histological and molecular features. This heterogeneity has hindered efforts to fully understand the pathology of GC and develop efficient therapeutics. In the past decade, great progress has been made in the study of GC, particularly in molecular subtyping, investigation of the immune microenvironment, and defining the evolutionary path and dynamics. Preclinical mouse models, particularly immunocompetent models that mimic the cellular and molecular features of human GC, in combination with organoid culture and clinical studies, have provided powerful tools for elucidating the molecular and cellular mechanisms underlying GC pathology and immune evasion, and the development of novel therapeutic strategies. Herein, we first briefly introduce current progress and challenges in GC study and subsequently summarize immunocompetent GC mouse models, emphasizing the potential application of genetically engineered mouse models in antitumor immunity and immunotherapy studies.

Pediatric high-grade gliomas (pHGG) are malignant and usually fatal central nervous system (CNS) WHO Grade 4 tumors. The majority of pHGG consist of diffuse midline gliomas (DMG), H3.3 or H3.1 K27 altered, or diffuse hemispheric gliomas (DHG) (H3.3 G34-mutant). Due to diffuse tumor infiltration of eloquent brain areas, especially for DMG, surgery has often been limited and chemotherapy has not been effective, leaving fractionated radiation to the involved field as the current standard of care. pHGG has only been classified as molecularly distinct from adult HGG since 2012 through Next-Generation sequencing approaches, which have shown pHGG to be epigenetically regulated and specific tumor sub-types to be representative of dysregulated differentiating cells. To translate discovery research into novel therapies, improved pre-clinical models that more adequately represent the tumor biology of pHGG are required. This review will summarize the molecular characteristics of different pHGG sub-types, with a specific focus on histone K27M mutations and the dysregulated gene expression profiles arising from these mutations. Current and emerging pre-clinical models for pHGG will be discussed, including commonly used patient-derived cell lines and in vivo modeling techniques, encompassing patient-derived xenograft murine models and genetically engineered mouse models (GEMMs). Lastly, emerging techniques to model CNS tumors within a human brain environment using brain organoids through co-culture will be explored. As models that more reliably represent pHGG continue to be developed, targetable biological and genetic vulnerabilities in the disease will be more rapidly identified, leading to better treatments and improved clinical outcomes.

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.

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.

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.

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.

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.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: This study proposes a mechanism in which ATRX loss is the major contributor to many key transcriptomic changes in H3.3G34R pHGGs.
UNASSIGNED: GSE197988.

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.

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.