MYCN drives chemoresistance in small cell lung cancer while USP7 inhibition can restore chemosensitivity.

Small cell lung cancer (SCLC) is an aggressive neuroendocrine cancer characterized by initial chemosensitivity followed by emergence of chemoresistant disease. To study roles for MYCN amplification in SCLC progression and chemoresistance, we developed a genetically engineered mouse model of MYCN-overexpressing SCLC. In treatment-naïve mice, MYCN overexpression promoted cell cycle progression, suppressed infiltration of cytotoxic T cells, and accelerated SCLC. MYCN overexpression also suppressed response to cisplatin-etoposide chemotherapy, with similar findings made upon MYCL overexpression. We extended these data to genetically perturb chemosensitive patient-derived xenograft (PDX) models of SCLC. In chemosensitive PDX models, overexpression of either MYCN or MYCL also conferred a switch to chemoresistance. To identify therapeutic strategies for MYCN-overexpressing SCLC, we performed a genome-scale CRISPR-Cas9 sgRNA screen. We identified the deubiquitinase USP7 as a MYCN-associated synthetic vulnerability. Pharmacological inhibition of USP7 resensitized chemoresistant MYCN-overexpressing PDX models to chemotherapy in vivo. Our findings show that MYCN overexpression drives SCLC chemoresistance and provide a therapeutic strategy to restore chemosensitivity.

Mutant IDH1 regulates the tumor-associated immune system in gliomas.

Gliomas harboring mutations in isocitrate dehydrogenase 1/2 (IDH1/2) have the CpG island methylator phenotype (CIMP) and significantly longer patient survival time than wild-type IDH1/2 (wtIDH1/2) tumors. Although there are many factors underlying the differences in survival between these two tumor types, immune-related differences in cell content are potentially important contributors. In order to investigate the role of IDH mutations in immune response, we created a syngeneic pair mouse model for mutant IDH1 (muIDH1) and wtIDH1 gliomas and demonstrated that muIDH1 mice showed many molecular and clinical similarities to muIDH1 human gliomas, including a 100-fold higher concentration of 2-hydroxygluratate (2-HG), longer survival time, and higher CpG methylation compared with wtIDH1. Also, we showed that IDH1 mutations caused down-regulation of leukocyte chemotaxis, resulting in repression of the tumor-associated immune system. Given that significant infiltration of immune cells such as macrophages, microglia, monocytes, and neutrophils is linked to poor prognosis in many cancer types, these reduced immune infiltrates in muIDH1 glioma tumors may contribute in part to the differences in aggressiveness of the two glioma types.

New Immuno-oncology Targets and Resistance Mechanisms.

OPINION STATEMENT: Immune checkpoint inhibition (ICI) has revolutionized the field of non-small cell lung cancer (NSCLC); currently, most patients with advanced disease receive upfront ICI either alone or in combination with chemotherapy. These advances have recently extended into early-stage NSCLC, with ICI incorporation into neoadjuvant and adjuvant treatment regimens. However, despite these successes, immunotherapy (IO) resistance remains a fundamental challenge in NSCLC, introducing a central quandary of how to precisely select the appropriate IO therapy or IO combination therapy for each individual patient. To address this vital need in the field, there has been an explosion of research in immuno-oncology to identify mechanisms of resistance, ranging from genomic alterations in the tumor to immunosuppressive conditions in the tumor microenvironment (TME). There remain many questions about how this complex interplay between the tumor and the immune microenvironment translates into clinical phenotypes of primary and acquired resistance. In NSCLC, a number of novel therapeutics are being developed to prevent and overcome resistance to ICI. Particular promise has been shown with therapeutics targeting novel T cell immune checkpoint inhibitors and targeting innate immune cells in the TME, chief among these cells are natural killer cells, neutrophils, and macrophages. Further research into tissue-based and non-invasive biomarkers that can be prospectively integrated into therapeutic trial design will be critical to advance the field's understanding of individual resistance patterns and enable the ultimate goal of precision immuno-oncology.

Tumor-derived Autoantibodies Identify Malignant Pulmonary Nodules.

Rationale: Screening for non-small cell lung cancer is associated with earlier diagnosis and reduced mortality but also increased harm caused by invasive follow-up of benign pulmonary nodules. Lung tumorigenesis activates the immune system, components of which could serve as tumor-specific biomarkers. Objectives: To profile tumor-derived autoantibodies as peripheral biomarkers of malignant pulmonary nodules. Methods: High-density protein arrays were used to define the specificity of autoantibodies isolated from B cells of 10 resected lung tumors. These tumor-derived autoantibodies were also examined as free or complexed to antigen in the plasma of the same 10 patients and matched benign nodule control subjects. Promising autoantibodies were further analyzed in an independent cohort of 250 nodule-positive patients. Measurements and Main Results: Thirteen tumor B-cell-derived autoantibodies isolated ex vivo showed greater than or equal to 50% sensitivity and greater than or equal to 70% specificity for lung cancer. In plasma, 11 of 13 autoantibodies were present both complexed to and free from antigen. In the larger validation cohort, 5 of 13 tumor-derived autoantibodies remained significantly elevated in cancers. A combination of four of these autoantibodies could detect malignant nodules with an area under the curve of 0.74 and had an area under the curve of 0.78 in a subcohort of indeterminate (8-20 mm in the longest diameter) pulmonary nodules. Conclusions: Our novel pipeline identifies tumor-derived autoantibodies that could effectively serve as blood biomarkers for malignant pulmonary nodule diagnosis. This approach has future implications for both a cost-effective and noninvasive approach to determine nodule malignancy for widespread low-dose computed tomography screening.

Comparison of prediction models with radiological semantic features and radiomics in lung cancer diagnosis of the pulmonary nodules: a case-control study.

PURPOSE: To compare the ability of radiological semantic and quantitative texture features in lung cancer diagnosis of pulmonary nodules. MATERIALS AND METHODS: A total of N = 121 subjects with confirmed non-small-cell lung cancer were matched with 117 controls based on age and gender. Radiological semantic and quantitative texture features were extracted from CT images with or without contrast enhancement. Three different models were compared using LASSO logistic regression: "CS" using clinical and semantic variables, "T" using texture features, and "CST" using clinical, semantic, and texture variables. For each model, we performed 100 trials of fivefold cross-validation and the average receiver operating curve was accessed. The AUC of the cross-validation study (AUCCV) was calculated together with its 95% confidence interval. RESULTS: The AUCCV (and 95% confidence interval) for models T, CS, and CST was 0.85 (0.71-0.96), 0.88 (0.77-0.96), and 0.88 (0.77-0.97), respectively. After separating the data into two groups with or without contrast enhancement, the AUC (without cross-validation) of the model T was 0.86 both for images with and without contrast enhancement, suggesting that contrast enhancement did not impact the utility of texture analysis. CONCLUSIONS: The models with semantic and texture features provided cross-validated AUCs of 0.85-0.88 for classification of benign versus cancerous nodules, showing potential in aiding the management of patients. KEY POINTS: • Pretest probability of cancer can aid and direct the physician in the diagnosis and management of pulmonary nodules in a cost-effective way. • Semantic features (qualitative features reported by radiologists to characterize lung lesions) and radiomic (e.g., texture) features can be extracted from CT images. • Input of these variables into a model can generate a pretest likelihood of cancer to aid clinical decision and management of pulmonary nodules.

Chronic Obstructive Pulmonary Disease Alters Immune Cell Composition and Immune Checkpoint Inhibitor Efficacy in Non-Small Cell Lung Cancer.

RATIONALE: Chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC) are interrelated diseases with substantial mortality, and the pathogenesis of both involves aberrant immune functioning. OBJECTIVES: To profile immune cell composition and function in patients with NSCLC and describe the effects of COPD on lung and tumor microenvironments. METHODS: We profiled resected lung and tumor tissue using flow cytometry and T-cell receptor sequencing in patients with and without COPD from a prospective cohort of patients undergoing resection of NSCLC. A murine cigarette smoke exposure model was used to evaluate the effect on pulmonary immune populations. A separate retrospective cohort of patients who received immune checkpoint inhibitors (ICIs) was analyzed, and their survival was quantified. MEASUREMENTS AND MAIN RESULTS: We observed an increased number of IFN-γ-producing CD8+ and CD4+ (T-helper cell type 1 [Th1]) lymphocytes in the lungs of patients with COPD. In both humans and mice, increased Th17 content was seen with smoke exposure, but was not associated with the development or severity of COPD. COPD-affected lung tissue displayed increased Th1 differentiation that was recapitulated in the matching tumor sample. PD-1 (programmed cell death protein 1) expression was increased in tumors of patients with COPD, and the presence of COPD was associated with progression-free survival in patients treated with ICIs. CONCLUSIONS: In patients with COPD, Th1 cell populations were expanded in both lung and tumor microenvironments, and the presence of COPD was associated with longer progression-free intervals in patients treated with ICIs. This has implications for understanding the immune mediators of COPD and developing novel therapies for NSCLC.

Insulin receptor substrate-1 deficiency drives a proinflammatory phenotype in KRAS mutant lung adenocarcinoma.

Insulin receptor substrate-1 (IRS-1) is a signaling adaptor protein that interfaces with many pathways activated in lung cancer. It has been assumed that IRS-1 promotes tumor growth through its ability to activate PI3K signaling downstream of the insulin-like growth factor receptor. Surprisingly, tumors with reduced IRS-1 staining in a human lung adenocarcinoma tissue microarray displayed a significant survival disadvantage, especially within the Kirsten rat sarcoma viral oncogene homolog (KRAS) mutant subgroup. Accordingly, adenoviral Cre recombinase (AdCre)-treated LSL-Kras/Irs-1(fl/fl) (Kras/Irs-1(-/-)) mice displayed increased tumor burden and mortality compared with controls. Mechanistically, IRS-1 deficiency promotes Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling via the IL-22 receptor, resulting in enhanced tumor-promoting inflammation. Treatment of Kras/Irs-1(+/+) and Kras/Irs-1(-/-) mice with JAK inhibitors significantly reduced tumor burden, most notably in the IRS-1-deficient group.

Matrix Metalloproteinase-28 Is a Key Contributor to Emphysema Pathogenesis.

Chronic obstructive pulmonary disease (COPD) comprises chronic bronchitis and emphysema, and is a leading cause of morbidity and mortality. Because tissue destruction is the prominent characteristic of emphysema, extracellular proteinases, particularly those with elastolytic ability, are often considered to be key drivers in this disease. Several human and mouse studies have implicated roles for matrix metalloproteinases (MMPs), particularly macrophage-derived proteinases, in COPD pathogenesis. MMP-28 is expressed by the pulmonary epithelium and macrophage, and we have found that it regulates macrophage recruitment and polarization. We hypothesized that MMP-28 has contributory roles in emphysema via alteration of macrophage numbers and activation. Because of the established association of emphysema pathogenesis to macrophage influx, we evaluated the inflammatory changes and lung histology of Mmp28-/- mice exposed to 3 and 6 months of cigarette smoke. At earlier time points, we found altered macrophage polarization in the smoke-exposed Mmp28-/- lung consistent with other published findings that MMP-28 regulates macrophage activation. At both 3 and 6 months, Mmp28-/- mice had blunted inflammatory responses more closely resembling nonsmoked mice, with a reduction in neutrophil recruitment and CXCL1 chemokine expression. By 6 months, Mmp28-/- mice were protected from emphysema. These results highlight a previously unrecognized role for MMP-28 in promoting chronic lung inflammation and tissue remodeling induced by cigarette smoke and highlight another potential target to modulate COPD.

Lung Cancer Subtypes Generate Unique Immune Responses.

Lung cancer, the leading cause of cancer-related deaths worldwide, is a heterogeneous disease comprising multiple histologic subtypes that harbor disparate mutational profiles. Immune-based therapies have shown initial promise in the treatment of lung cancer patients but are limited by low overall response rates. We sought to determine whether the host immune response to lung cancer is dictated, at least in part, by histologic and genetic differences, because such correlations would have important clinical ramifications. Using mouse models of lung cancer, we show that small cell lung cancer (SCLC) and lung adenocarcinoma (ADCA) exhibit unique immune cell composition of the tumor microenvironment. The total leukocyte content was markedly reduced in SCLC compared with lung ADCA, which was validated in human lung cancer specimens. We further identified key differences in immune cell content using three models of lung ADCA driven by mutations in Kras, p53, and Egfr Although Egfr-mutant cancers displayed robust myeloid cell recruitment, they failed to mount a CD8+ immune response. In contrast, Kras-mutant tumors displayed significant expansion of multiple immune cell types, including CD8+ cells, regulatory T cells, IL-17A-producing lymphocytes, and myeloid cells. A human tissue microarray annotated for KRAS and EGFR mutations validated the finding of reduced CD8+ content in human lung ADCA. Taken together, these findings establish a strong foundational knowledge of the immune cell contexture of lung ADCA and SCLC and suggest that molecular and histological traits shape the host immune response to cancer.

Enhancing Autophagy with Drugs or Lung-directed Gene Therapy Reverses the Pathological Effects of Respiratory Epithelial Cell Proteinopathy.

Recent studies have shown that autophagy mitigates the pathological effects of proteinopathies in the liver, heart, and skeletal muscle but this has not been investigated for proteinopathies that affect the lung. This may be due at least in part to the lack of an animal model robust enough for spontaneous pathological effects from proteinopathies even though several rare proteinopathies, surfactant protein A and C deficiencies, cause severe pulmonary fibrosis. In this report we show that the PiZ mouse, transgenic for the common misfolded variant α1-antitrypsin Z, is a model of respiratory epithelial cell proteinopathy with spontaneous pulmonary fibrosis. Intracellular accumulation of misfolded α1-antitrypsin Z in respiratory epithelial cells of the PiZ model resulted in activation of autophagy, leukocyte infiltration, and spontaneous pulmonary fibrosis severe enough to elicit functional restrictive deficits. Treatment with autophagy enhancer drugs or lung-directed gene transfer of TFEB, a master transcriptional activator of the autophagolysosomal system, reversed these proteotoxic consequences. We conclude that this mouse is an excellent model of respiratory epithelial proteinopathy with spontaneous pulmonary fibrosis and that autophagy is an important endogenous proteostasis mechanism and an attractive target for therapy.

Macrophage elastase kills bacteria within murine macrophages.

Macrophages are aptly positioned to function as the primary line of defence against invading pathogens in many organs, including the lung and peritoneum. Their ability to phagocytose and clear microorganisms has been well documented. Macrophages possess several substances with which they can kill bacteria, including reactive oxygen species, nitric oxide, and antimicrobial proteins. We proposed that macrophage-derived proteinases may contribute to the antimicrobial properties of macrophages. Macrophage elastase (also known as matrix metalloproteinase 12 or MMP12) is an enzyme predominantly expressed in mature tissue macrophages and is implicated in several disease processes, including emphysema. Physiological functions for MMP12 have not been described. Here we show that Mmp12(-/-) mice exhibit impaired bacterial clearance and increased mortality when challenged with both gram-negative and gram-positive bacteria at macrophage-rich portals of entry, such as the peritoneum and lung. Intracellular stores of MMP12 are mobilized to macrophage phagolysosomes after the ingestion of bacterial pathogens. Once inside phagolysosomes, MMP12 adheres to bacterial cell walls where it disrupts cellular membranes resulting in bacterial death. The antimicrobial properties of MMP12 do not reside within its catalytic domain, but rather within the carboxy-terminal domain. This domain contains a unique four amino acid sequence on an exposed beta loop of the protein that is required for the observed antimicrobial activity. The present study represents, to our knowledge, the first report of direct antimicrobial activity by a matrix metallopeptidase, and describes a new antimicrobial peptide that is sequentially and structurally unique in nature.

Macrophage elastase suppresses white adipose tissue expansion with cigarette smoking.

Macrophage elastase (MMP12) is a key mediator of cigarette smoke (CS)-induced emphysema, yet its role in other smoking related pathologies remains unclear. The weight suppressing effects of smoking are a major hindrance to cessation efforts, and MMP12 is known to suppress the vascularization on which adipose tissue growth depends by catalyzing the formation of antiangiogenic peptides endostatin and angiostatin. The goal of this study was to determine the role of MMP12 in adipose tissue growth and smoking-related suppression of weight gain. Whole body weights and white adipose depots from wild-type and Mmp12-deficient mice were collected during early postnatal development and after chronic CS exposure. Adipose tissue specimens were analyzed for angiogenic and adipocytic markers and for content of the antiangiogenic peptides endostatin and angiostatin. Cultured 3T3-L1 adipocytes were treated with adipose tissue homogenate to examine its effects on vascular endothelial growth factor (VEGF) expression and secretion. MMP12 content and activity were increased in the adipose tissue of wild-type mice at 2 weeks of age, leading to elevated endostatin production, inhibition of VEGF secretion, and decreased adipose tissue vascularity. By 8 weeks of age, adipose MMP12 levels subsided, and the protein was no longer detectable. However, chronic CS exposure led to macrophage accumulation and restored adipose MMP12 activity, thereby suppressing adipose tissue mass and vascularity. Our results reveal a novel systemic role for MMP12 in postnatal adipose tissue expansion and smoking-associated weight loss by suppressing vascularity within the white adipose tissue depots.

Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions.

We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.

Clathrin pit-mediated endocytosis of neutrophil elastase and cathepsin G by cancer cells.

Neutrophil elastase (NE) is a neutrophil-derived serine proteinase with broad substrate specificity. We have recently demonstrated that NE is capable of entering tumor cell endosomes and processing novel intracellular substrates. In the current study, we sought to determine the mechanism by which NE enters tumor cells. Our results show that NE enters into early endosomal antigen-1(+) endosomes in a dynamin- and clathrin-dependent but flotillin-1- and caveolin-1-independent fashion. Cathepsin G (but not proteinase-3) also enters tumor endosomes via the same mechanism. We utilized (125)I-labeled NE to demonstrate that NE binds to the surface of cancer cells. Incubation of radiolabeled NE with lung cancer cells displays a dissociation constant (K(d)) of 284 nm. Because NE is known to bind to heparan sulfate- and chondroitin sulfate-containing proteoglycans, we treated cells with glycanases to remove these confounding factors, which did not significantly diminish cell surface binding or endosomal entry. Thus, NE and CG bind to the surface of cancer cells, presumably to a cell surface receptor, and subsequently undergo clathrin pit-mediated endocytosis.

Altered Treg Infiltration after Discoidin Domain Receptor 1 (DDR1) Inhibition and Knockout Promotes Tumor Growth in Lung Adenocarcinoma.

Lung cancer is the leading cause of cancer-related death worldwide. Discoidin domain receptor 1 (DDR1), a tyrosine kinase receptor, has been associated with poor prognosis in patients with non-small cell lung cancer (NSCLC). However, its role in tumorigenesis remains poorly understood. This work aimed to explore the impact of DDR1 expression on immune cell infiltration in lung adenocarcinoma. Pharmacological inhibition and knockout of DDR1 were used in an immunocompetent mouse model of KRAS/p53-driven lung adenocarcinoma (LUAD). Tumor cells were engrafted subcutaneously, after which tumors were harvested for investigation of immune cell composition via flow cytometry. The Cancer Genome Atlas (TCGA) cohort was used to perform gene expression analysis of 509 patients with LUAD. Pharmacological inhibition and knockout of DDR1 increased the tumor burden, with DDR1 knockout tumors showing a decrease in CD8+ cytotoxic T cells and an increase in CD4+ helper T cells and regulatory T cells. TCGA analysis revealed that low-DDR1-expressing tumors showed higher FoxP3 (regulatory T-cell marker) expression than high-DDR1-expressing tumors. Our study showed that under certain conditions, the inhibition of DDR1, a potential therapeutic target in cancer treatment, might have negative effects, such as inducing a pro-tumorigenic tumor microenvironment. As such, further investigations are necessary.

Multi-Omic Biomarkers Improve Indeterminate Pulmonary Nodule Malignancy Risk Assessment.

The clinical management of patients with indeterminate pulmonary nodules is associated with unintended harm to patients and better methods are required to more precisely quantify lung cancer risk in this group. Here, we combine multiple noninvasive approaches to more accurately identify lung cancer in indeterminate pulmonary nodules. We analyzed 94 quantitative radiomic imaging features and 41 qualitative semantic imaging variables with molecular biomarkers from blood derived from an antibody-based microarray platform that determines protein, cancer-specific glycan, and autoantibody-antigen complex content with high sensitivity. From these datasets, we created a PSR (plasma, semantic, radiomic) risk prediction model comprising nine blood-based and imaging biomarkers with an area under the receiver operating curve (AUROC) of 0.964 that when tested in a second, independent cohort yielded an AUROC of 0.846. Incorporating known clinical risk factors (age, gender, and smoking pack years) for lung cancer into the PSR model improved the AUROC to 0.897 in the second cohort and was more accurate than a well-characterized clinical risk prediction model (AUROC = 0.802). Our findings support the use of a multi-omics approach to guide the clinical management of indeterminate pulmonary nodules.

Posttranslational modifications induce autoantibodies with risk prediction capability in patients with small cell lung cancer.

Small cell lung cancer (SCLC) elicits the generation of autoantibodies that result in unique paraneoplastic neurological syndromes. The mechanistic basis for the formation of such autoantibodies is largely unknown but is key to understanding their etiology. We developed a high-dimensional technique that enables detection of autoantibodies in complex with native antigens directly from patient plasma. Here, we used our platform to screen 1009 human plasma samples for 3600 autoantibody-antigen complexes, finding that plasma from patients with SCLC harbors, on average, fourfold higher disease-specific autoantibody signals compared with plasma from patients with other cancers. Across three independent SCLC cohorts, we identified a set of common but previously unknown autoantibodies that are produced in response to both intracellular and extracellular tumor antigens. We further characterized several disease-specific posttranslational modifications within extracellular proteins targeted by these autoantibodies, including citrullination, isoaspartylation, and cancer-specific glycosylation. Because most patients with SCLC have metastatic disease at diagnosis, we queried whether these autoantibodies could be used for SCLC early detection. We created a risk prediction model using five autoantibodies with an average area under the curve of 0.84 for the three cohorts that improved to 0.96 by incorporating cigarette smoke consumption in pack years. Together, our findings provide an innovative approach to identify circulating autoantibodies in SCLC with mechanistic insight into disease-specific immunogenicity and clinical utility.

An Online Repository for Pre-Clinical Imaging Protocols (PIPs).

Providing method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis. Furthermore, the need for additional information must be counterbalanced by the additional time burden placed upon researchers who may be already overtasked. To address these competing issues, this white paper describes protocol templates for positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) that can be leveraged by the broad community of quantitative imaging experts to write and self-publish protocols in protocols.io. Similar to the Structured Transparent Accessible Reproducible (STAR) or Journal of Visualized Experiments (JoVE) articles, authors are encouraged to publish peer reviewed papers and then to submit more detailed experimental protocols using this template to the online resource. Such protocols should be easy to use, readily accessible, readily searchable, considered open access, enable community feedback, editable, and citable by the author.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.