Search

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non–small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research. Significance: Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Supplementary Figures S1-S3 from Monochromosome Transfer and Microarray Analysis Identify a Critical Tumor-Suppressive Region Mapping to Chromosome 13q14 and THSD1 in Esophageal Carcinoma

Loss of chromosome 13q regions in esophageal squamous cell carcinoma (ESCC) is a frequent event. Monochromosome transfer approaches provide direct functional evidence for tumor suppression by chromosome 13 in SLMT-1, an ESCC cell line, and identify critical regions at 13q12.3, 13q14.11, and 13q14.3. Differential gene expression profiles of three tumor-suppressing microcell hybrids (MCH) and their tumorigenic parental SLMT-1 cell line were revealed by competitive hybridization using 19k cDNA oligonucleotide microarrays. Nine candidate 13q14 tumor-suppressor genes (TSG), including RB1, showed down-regulation in SLMT-1, compared with NE1, an immortalized normal esophageal epithelial cell line; their average gene expression was restored in MCHs compared with SLMT-1. Reverse transcription-PCR validated gene expression levels in MCHs and a panel of ESCC cell lines. Results suggest that the tumor-suppressing effect is not attributed to RB1, but instead likely involves thrombospondin type I domain-containing 1 (THSD1), a novel candidate TSG mapping to 13q14. Quantitative reverse transcription-PCR detected down-regulation of THSD1 expression in 100% of ESCC and other cancer cell lines. Mechanisms for THSD1 silencing in ESCC involved loss of heterozygosity and promoter hypermethylation, as analyzed by methylation-specific PCR and clonal bisulfite sequencing. Transfection of wild-type THSD1 into SLMT-1 resulted in significant reduction of colony-forming ability, hence providing functional evidence for its growth-suppressive activity. These findings suggest that THSD1 is a good candidate TSG. (Mol Cancer Res 2008;6(4):592–603)

Supplementary Figure from A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non–Small Cell Lung Cancer

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non–small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.Significance:Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Supplementary Table from A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non–Small Cell Lung Cancer

Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable with that of lymph node status and tumor size. When incorporated into the Nottingham prognostic index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low- and high-grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression. (Cancer Res 2006; 66(21): 10292-301)

Supplementary File 2 from Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancer

Supplementary File 3 from Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancer

Supplementary Tables 1-3 from Gene Expression Preferentially Regulated by Tamoxifen in Breast Cancer Cells and Correlations with Clinical Outcome

FVB/N-Tg (MMTV-PyMT)634Mul-transgenic mice develop multifocal mammary tumors with a high incidence of pulmonary metastasis. We have demonstrated previously that mammary tumors derived from transgene-positive F1 progeny in particular inbred strains display altered latency, tumor growth rates, and metastatic rates when compared with the FVB/NJ homozygous parent. To identify genes with expression that might be critical in modifying the biological behavior of MMTV-PyMT tumors, we performed a detailed comparative analysis of expression profiles from mammary tumors arising in the parental FVB/NJ background and F1 progeny from crosses with I/LnJ, LP/J, MOLF/Ei, and NZB/B1NJ mice. Compared with normal mammary glands, gene expression profiles of tumors from all five strains exhibited up-regulation of genes involved in cell growth (e.g., Cks1 and CDC25C) and down-regulation of cell adhesion molecules, with many genes associated previously with human breast cancer such as STAT2, CD24 antigen, gelsolin, and lipocalin2. To identify genes with significant variation in expression between the five different genotypes, significance analysis of microarrays (SAM) and one-way ANOVA were used. Three definable groupings of tumors were identified: (a) tumors derived in the LP/J F1 and MOLF/Ei F1 strains in which tumor growth and dissemination are suppressed and latency prolonged; (b) the most aggressive tumors from the FVB/NJ parental strain and I/LnJ F1 genomic backgrounds; and (c) an intermediate virulence phenotype with tumors from NZB/B1NJ–F1 crosses. These array based assessments correlated well with a composite phenotype ranking using a “virulence” index. The gene expression signature that is associated with a high metastatic rate in the mouse contains the same 17 genes described recently as the signature gene set predictive of metastasis in human tumors (1) with 16 of the 17 genes exhibiting the same directional change in expression associated with human metastases. These results demonstrate that the genetic analysis of mouse models of tumorigenesis may be highly relevant to human cancer and that the metastatic phenotype of a tumor may be affected by the germline genetic configuration of the host.

The beneficial effect of the selective estrogen receptor (ER) modulator tamoxifen in the treatment and prevention of breast cancer is assumed to be through its ability to antagonize the stimulatory actions of estrogen, although tamoxifen can also have some estrogen-like agonist effects. Here, we report that, in addition to these mixed agonist/antagonist actions, tamoxifen can also selectively regulate a unique set of >60 genes, which are minimally regulated by estradiol (E2) or raloxifene in ERα-positive MCF-7 human breast cancer cells. This gene regulation by tamoxifen is mediated by ERα and reversed by E2 or ICI 182,780. Introduction of ERβ into MCF-7 cells reverses tamoxifen action on ∼75% of these genes. To examine whether these genes might serve as markers of tamoxifen sensitivity and/or the development of resistance, their expression level was examined in breast cancers of women who had received adjuvant therapy with tamoxifen. High expression of two of the tamoxifen-stimulated genes, YWHAZ/14-3-3z and LOC441453, was found to correlate significantly with disease recurrence following tamoxifen treatment in women with ER-positive cancers and hence seem to be markers of a poor prognosis. Our data indicate a new dimension in tamoxifen action, involving gene expression regulation that is tamoxifen preferential, and identify genes that might serve as markers of tumor responsiveness or resistance to tamoxifen therapy. This may have a potential effect on the choice of tamoxifen versus aromatase inhibitors as adjuvant endocrine therapy. (Cancer Res 2006; 66(14): 7334-40)

Supplementary File 1 from Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancer

Supplementary Table 1a from Global Expression Profiling Identifies Signatures of Tumor Virulence in MMTV-PyMT-Transgenic Mice

Three-dimensional (3D) culture models, such as organoids, are flexible systems to interrogate cellular growth and morphology, multicellular spatial architecture, and cell interactions in response to drug treatment. However, new computational methods to segment and analyze 3D models at cellular resolution with sufficiently high throughput are needed to realize these possibilities. Here we reportCellos(Cell and Organoid Segmentation), an accurate, high throughput image analysis pipeline for 3D organoid and nuclear segmentation analysis.Cellossegments organoids in 3D using classical algorithms and segments nuclei using a Stardist-3D convolutional neural network which we trained on a manually annotated dataset of 3,862 cells from 36 organoids confocally imaged at 5 μm z-resolution. To evaluate the capabilities ofCelloswe then analyzed 74,450 organoids with 1.65 million cells, from multiple experiments on triple negative breast cancer organoids containing clonal mixtures with complex cisplatin sensitivities.Celloswas able to accurately distinguish ratios of distinct fluorescently labelled cell populations in organoids, with Celloswas able to recapitulate traditional luminescence-based drug response quantifications by analyzing 3D images, including parallel analysis of multiple cancer clones in the same well. Moreover,Celloswas able to identify organoid and nuclear morphology feature changes associated with treatment. Finally,Cellosenables 3D analysis of cell spatial relationships, which we used to detect ecological affinity between cancer cells beyond what arises from local cell division or organoid composition.Cellosprovides powerful tools to perform high throughput analysis for pharmacological testing and biological investigation of organoids based on 3D imaging.

Testing and isolation of infectious employees is one of the critical strategies to make the workplace safe during the pandemic for many organizations. Adaptive testing frequency reduces cost while keeping the pandemic under control at the workplace. However, most models aimed at estimating test frequencies were structured for municipalities or large organizations such as university campuses of highly mobile individuals. By contrast, the workplace exhibits distinct characteristics: employee positivity rate may be different from the local community because of rigorous protective measures at workplace, or self-selection of co-workers with common behavioral tendencies for adherence to pandemic mitigation guidelines. Moreover, dual exposure to COVID19 occurs at work and home that complicates transmission modelling, as does transmission tracing at the workplace. Hence, we developed bi-modal SEIR model and R-shiny tool that accounts for these differentiating factors to adaptively estimate the testing frequency for workplace. Our tool uses easily measurable parameters: community incidence rate, risks of acquiring infection from community and work-place, workforce size, and sensitivity of testing. Our model is best suited for moderate-sized organizations with low internal transmission rates, no-outward facing employees whose position demands frequent in-person interactions with the public, and low to medium population positivity rates. Simulations revealed that employee behavior in adherence to protective measures at work and in their community, and the onsite workforce size have large effects on testing frequency. Reducing workplace transmission rate through workplace mitigation protocols and higher sensitivity of the test deployed, though to a lesser extent. Furthermore, our simulations showed that sentinel testing leads to only marginal increase in the number of infections even for high community incidence rates, suggesting that this may be a cost-effective approach in future pandemics. We used our model to accurately guide testing regimen for three campuses of The Jackson Laboratory.

In 2021, the National Institutes of Health Advisory Committee to the Director (ACD) announced recommendations to improve the reproducibility of biomedical research using animals. In response, The Jackson Laboratory faculty and institutional leaders identified key strategies to further address this important issue. Taking inspiration from the evolution of clinical trials over recent decades in response to similar challenges, we identified opportunities for improvement, including establishment of common standards, use of genetically diverse populations, requirement for robust study design with appropriate statistical methods, and improvement in public databases to facilitate meta-analyses. In this Perspective, we share our response to ACD recommendations, with a specific focus on mouse models, with the aim of promoting continued active dialogue among researchers, using any animal system, worldwide. Such discussion will help to inform the biomedical community about these recommendations and further support their much-needed implementation.

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with BRCA1 promoter methylation ( BRCA1 meth) respond more poorly to alkylating agents compared to those bearing mutations in BRCA1 and BRCA2 ( BRCA mut). This is a conundrum given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic BRCA perturbations. We dissected this problem through detailed genomic analyses of TNBC and OvCa cohorts and experimentation with patient-derived xenografts and genetically engineered cell lines. We found that despite identical downstream genomic mutational signatures associated with BRCA1 meth and BRCA mut states, BRCA1 meth uniformly associates with poor outcomes. Exposure of BRCA1 meth TNBCs to platinum chemotherapy, either as clinical treatment of a patient or as experimental in vivo exposure of preclinical patient derived xenografts, resulted in allelic loss of BRCA1 methylation and increased BRCA1 expression and platinum resistance. These data suggest that, unlike BRCA mut cancers, where BRCA loss is a genetically “fixed” deficiency state, BRCA1 meth cancers are highly adaptive to genotoxin exposure and, through reversal of promoter methylation, recover BRCA1 expression and become resistant to therapy. We further found a specific augmented immune transcriptional signal associated with enhanced response to platinum chemotherapy but only in patients with BRCA-proficient cancers. We showed how integrating both this cancer immune signature and the presence of BRCA mutations results in more accurate predictions of patient response when compared to either HRD status or BRCA status alone. This underscores the importance of defining BRCA heterogeneity in optimizing the predictive precision of assigning response probabilities in TNBC and OvCa.

While the distant organ environment is known to support metastasis of primary tumors, its metabolic roles in this process remain underdetermined. Here, in breast cancer models, we found lung-resident mesenchymal cells (MCs) accumulating neutral lipids at the pre-metastatic stage. This was partially mediated by interleukin-1β (IL-1β)-induced hypoxia-inducible lipid droplet-associated (HILPDA) that subsequently represses adipose triglyceride lipase (ATGL) activity in lung MCs. MC-specific ablation of the ATGL or HILPDA genes in mice reinforced and reduced lung metastasis of breast cancer respectively, suggesting a metastasis-promoting effect of lipid-laden MCs. Mechanistically, lipid-laden MCs transported their lipids to tumor cells and natural killer (NK) cells via exosome-like vesicles, leading to heightened tumor cell survival and proliferation and NK cell dysfunction. Blockage of IL-1β, which was effective singly, improved the efficacy of adoptive NK cell immunotherapy in mitigating lung metastasis. Collectively, lung MCs metabolically regulate tumor cells and anti-tumor immunity to facilitate breast cancer lung metastasis.

Patient-derived xenograft models (PDXs) are an effective preclinical in vivo platform for testing the efficacy of novel drug and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathological features, mutational profiles, gene expression, and copy number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors of the same tumor type from The Cancer Genome Atlas (TCGA) and to previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted tumors. Treatment studies performed for a subset of the models recapitulated the responses expected based on the observed genomic profiles.SignificanceThe collection of lung cancer Patient Derived Xenograft (PDX) models maintained at The Jackson Laboratory retain both the histologic features and treatment-relevant genomic alterations observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents. The models serve as a valuable preclinical platform for translational cancer research. Information and data for the models are freely available from the Mouse Models of Human Cancer database (MMHCdb, http://tumor.informatics.jax.org/mtbwi/pdxSearch.do).

SUMMARYLoss of homologous recombination repair (HRR) via germline and somaticBRCA1orBRCA2gene mutations and viaBRCA1promoter methylation has been associated with better response to platinum agents and PARP inhibitors, in both triple negative breast cancer (TNBC) and ovarian carcinoma (OvCa). A major conundrum arising from recent clinical studies is why cancers withBRCA1promoter methylation (BRCA1meth) respond more poorly as compared to those bearing mutations inBRCA1andBRCA2(BRCAmut), given the biologically equivalent HRR deficiency in both states. We dissected this problem through detailed genomic analyses of primary TNBC and OvCa cohorts, as well as experimentation with patient-derived xenograft (PDX) models and genetically engineered cell lines. Using the precise genomic scar of the tandem duplicator phenotype as a precise genomic indicator of BRCA1 deficiency, we found that, in all cohorts,BRCA1mut andBRCA1meth cancers share an equivalent degree of BRCA1-linked genomic rearrangements. Nonetheless, we consistently found that patients withBRCAmut cancers, but not those withBRCA1meth cancers, had significantly better response outcomes when compared to those withBRCAproficient cancers. When fully promoter methylatedBRCA1PDX TNBCs were exposed to a single short course of platinum chemotherapy an unmethylatedBRCA1promoter allele emerged in resultant tumors associated with an increase inBRCA1expression. A separate analysis of PDXs derived from treatment naïve TNBCs featured complete methylation of theBRCA1promoter, whereas those derived from post-chemotherapy TNBCs invariably had only partial methylation. PDXs with partial methylation were significantly associated with lower response rates toin vivoplatinum-based therapy compared to those with complete promoter methylation. Using single cell clonal expansions from a partiallyBRCA1meth PDX, we confirmed that the reduced level of methylation was due to the demethylation of one of theBRCA1promoter alleles and not to the outgrowth of a non-methylated clone. Clinically, analysis of primary OvCas confirmed that high levels ofBRCA1methylation were significantly associated with reducedBRCA1gene expression whereas cancers with lower levels ofBRCA1methylation had expression levels approaching those found inBRCA1proficient cancers. These data suggest that unlikeBRCAmut cancers, where HRR deficiency is achieved via mutations that are genetically ‘fixed’,BRCA1meth cancers are highly adaptive to genotoxin exposure and more likely to recoverBRCA1expression, which may explain their poorer therapeutic response. We further found that an increased immune transcriptional signal, especially an elevated M1 macrophage signature, is associated with enhanced response to platinum-based chemotherapy only in patients withBRCAproficient cancers, in both TNBC and OvCa cohorts underscoring the importance of characterizing molecular heterogeneity to enhance predictive precision in assigning response probabilities in TNBC and OvCa.

Triple-negative breast cancer (TNBC) is a particularly aggressive form of breast cancer with high risk of recurrence and approximately 22% rate of five-year survival when the disease becomes metastatic. Thus, understanding of mechanisms supporting metastatic colonization of distant organs is of critical importance for the development of new therapies and possibly improved outcomes. Syngeneic mouse models suggest the role of innate immune cells, particularly neutrophils, in support of metastatic dissemination of TNBC. However, it is not possible to study human cancer in immunocompetent mice. Furthermore, organoids or other 3D tissue models do not allow investigations of distant organs colonization with metastatic TNBC tumors. Here, we used humanized mice and patient-derived xenograft (PDX) from treatment naïve primary TNBC tumors to investigate the mechanisms that promote metastasis. NSG mice with transgenic expression of human hematopoietic cytokines SCF/GM-CSF/IL-3 were engrafted with human CD34+ hematopoietic progenitor cells (HPCs) to generate humanized (h)NSG-SGM3 mice. All eleven (11) analyzed to date PDX tumors grew after orthotopic implantation at week 8-12. The presence of distant metastasis was determined by macroscopic evaluation of distant organs and further confirmed by E-cadherin and cytokeratin 19 expression using polychromatic immunofluorescence on frozen tissue section. Among 11 PDX tumors tested, five did not develop metastasis, four developed only lung metastasis and two developed multi-organ metastasis (lung and liver). Transcriptional profiling with RNAseq revealed significant differences in the immune landscape of primary and metastatic tumors. In particular, liver metastases were enriched in myeloid and plasma cell transcripts. Further analysis is ongoing to uncover specific pathways involved. Thus, our model enables mechanistic and pre-clinical studies of human TNBC metastasis. Citation Format: Chun I Yu, Te-Chia Wu, Kyung In Kim, Francesca Menghi, Vanessa Oliveira, Florentina Marches, Edison T Liu, Jacques Banchereau, Karolina Palucka. Patient-derived xenografts in humanized mice classify metastatic potential of primary triple negative breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-03-05.

Background. We recently described six distinct genomic configurations characterized by large numbers of distributed somatic tandem duplications (TDs) known as Tandem Duplicator Phenotypes (TDPs). Different TDPs feature TDs of different span sizes, and are enriched in TNBC, ovarian, and uterine cancers. Type 1 TDPs (i.e. groups 1, 1/2mix and 1/3mix) feature short span TDs (˜11Kb in size), invariably show abrogation of BRCA1 (via mutation or methylation) and of TP53, and affect ˜40% of TNBCs. We had observed, in limited in vitro and preclinical PDX models, that TDP status correlates with platinum sensitivity (1). Here, we assess TDP status across a cohort of 42 TNBC patients (pts) undergoing neoadjuvant carboplatin and NAB-paclitaxel to test the hypothesis that type 1 TDP status may be predictive of optimal response to platinum-based therapy. Methods. 42 pts with TNBC were enrolled in a phase II study of neoadjuvant carboplatin/nab-paclitaxel at the City of Hope National Medical Center (NCT01525966).Pathological complete response (pCR) was achieved in 50% of pts (21/42). WGS was performed using standard Illumina protocols. Structural variants were called using Crest, Delly and BreakDancer, and high confidence breakpoints were selected when called by at least two tools and by requiring split-read support. TDP status was ascertained as recently described (2). BRCA1 methylation was determined by methylation-specific PCR. Results. 45% of the tumors classified as TDP (19/42). Consistent with our previous observation, the vast majority were type 1 TDPs with short span TDs (n=17) and were strongly associated with BRCA1 mutation or methylation (16/17, P= 1.4E-8). However, there was no correlation between TDP status and pCR (OR=1.1, NS). In a more detailed analysis, we found that BRCA1 mutation correlated with pCR rate (6/7 pCR, P=0.01), whereas promoter methylation did not (4/11 pCR, NS). Moreover, both pts with mutant BRCA2 achieved pCR. Thus, as a group, pts with BRCA1/2 mutations (but not BRCA1 methylation) were more likely to achieve pCR than those with wild type BRCA1/2 (OR=11.9, P=1.7E-2). Results were unchanged when using RCB 0 and 1 vs. RCB 2 and 3 as the response criteria. Conclusions. This study confirmed that reduction of BRCA1 activity via either mutation or methylation robustly associates with type 1 TDPs in TNBC. However, TDP status did not predict good response, suggesting the separation of BRCA effects on genomic instability and platinum sensitivity. This indicates that genomic signature assessments, such as TDP and HRD, may not be sufficient in predicting pCR in TNBC. Importantly, we found that BRCA1/2 mutated TNBC pts were more likely to experience pCR (8/9) compared with pts with either BRCA1 methylation (4/11) or wild type BRCA1/2 (8/21). The exact genetic underpinnings of response in non-BRCA pts are currently under investigation. References. 1) Menghi et al, The Tandem Duplicator Phenotype is a Prevalent Genome-Wide Cancer Configuration Driven by Distinct Gene Mutations, Cancer Cell (2018). 2) Menghi et al, The tandem duplicator phenotype as a distinct genomic configuration in cancer, Proc Natl Acad Sci (2016). Citation Format: Menghi F, Yuan Y, Somlo G, Liu ET. BRCA mutations and not type 1 tandem duplicator phenotypes are associated with pathological complete response in patients with triple negative breast cancer undergoing neoadjuvant carboplatin/nab-paclitaxel [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-06-09.

Employers have begun to offer voluntary workplace genomic testing (wGT) as part of employee wellness benefit programs, but few empirical studies have examined the ethical, legal, and social implications (ELSI) of wGT. To better understand employee perspectives on wGT, employees were surveyed at a large biomedical research institution. Survey respondents were presented with three hypothetical scenarios for accessing health-related genomic testing: via (1) their doctor; (2) their workplace; and 3) a commercial direct-to-consumer (DTC) genetic testing company. Overall, 594 employees (28%) responded to the survey. Respondents indicated a preference for genomic testing in the workplace setting (70%; 95% CI 66–74%), followed by doctor’s office (54%; 95% CI 50–58%), and DTC testing (20%; 95% CI 17–24%). Prior to participating in wGT, respondents wanted to know about confidentiality of test results (79%), existence of relevant laws and policies (70%), and privacy protection (64%). Across scenarios, 92% of respondents preferred to view the test results with a genetic counselor. These preliminary results suggest that many employees are interested and even prefer genetic testing in the workplace and would prefer testing with support from genetic health professionals. Confirmation in more diverse employer settings will be needed to generalize such findings.

SummaryIn coronaviridae such as SARS-CoV-2, subgenomic RNAs (sgRNA) are replicative intermediates, therefore, their abundance and structures could infer viral replication activity and severity of host infection. Here, we systematically characterized the sgRNA expression and their structural variation in 81 clinical specimens collected from symptomatic and asymptomatic individuals with a goal of assessing viral genomic signatures of disease severity. We demonstrated the highly coordinated and consistent expression of sgRNAs from individuals with robust infections that results in symptoms, and found their expression is significantly repressed in the asymptomatic infections, indicating that the ratio of sgRNAs to genomic RNA (sgRNA/gRNA) is highly correlated with the severity of the disease. Using long read sequencing technologies to characterize full-length sgRNA structures, we also observed widespread deletions in viral RNAs, and identified unique sets of deletions preferentially found primarily in symptomatic individuals, with many likely to confer changes in SARS-CoV-2 virulence and host responses. Furthermore, based on the sgRNA structures, the frequently occurred structural variants in SARS-CoV-2 genomes serves as a mechanism to further induce SARS-CoV-2 proteome complexity. Taken together, our results show that differential sgRNA expression and structural mutational burden both appear to be correlated with the clinical severity of SARS-CoV-2 infection. Longitudinally monitoring sgRNA expression and structural diversity could further guide treatment responses, testing strategies, and vaccine development.

It is estimated that up to 80% of infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are asymptomatic and asymptomatic patients can still effectively transmit the virus and cause disease. While much of the effort has been placed on decoding single nucleotide variation in SARS-CoV-2 genomes, considerably less is known about their transcript variation and any correlation with clinical severity in human hosts, as defined here by the presence or absence of symptoms. To assess viral genomic signatures of disease severity, we conducted a systematic characterization of SARS-CoV-2 transcripts and genetic variants in 81 clinical specimens collected from symptomatic and asymptomatic individuals using multi-scale transcriptomic analyses including amplicon-seq, short-read metatranscriptome and long-read Iso-seq. Here we show a highly coordinated and consistent pattern of sgRNA expression from individuals with robust SARS-CoV-2 symptomatic infection and their expression is significantly repressed in the asymptomatic infections. We also observe widespread inter- and intra-patient variants in viral RNAs, known as quasispecies frequently found in many RNA viruses. We identify unique sets of deletions preferentially found primarily in symptomatic individuals, with many likely to confer changes in SARS-CoV-2 virulence and host responses. Moreover, these frequently occurring structural variants in SARS-CoV-2 genomes serve as a mechanism to further induce SARS-CoV-2 proteome complexity. Our results indicate that differential sgRNA expression and structural mutational burden are highly correlated with the clinical severity of SARS-CoV-2 infection. Longitudinally monitoring sgRNA expression and structural diversity could further guide treatment responses, testing strategies, and vaccine development. Wong and Ngan et al. characterize the expression and structural variation of SARS-CoV-2 subgenomic RNAs (sgRNAs) in diagnostic specimens from symptomatic and asymptomatic COVID-19 patients. In a series of genomic and transcriptomic analyses, the authors observe reduced sgRNA expression and a distinct set of structural deletions in asymptomatic infections compared with symptomatic infections. Infection with SARS-CoV-2 can lead to symptoms of different severity, with some individuals remaining entirely asymptomatic but still responsible for much of the viral transmission. Here, we sought to identify markers of the severity of symptoms of SARS-CoV-2 infection, as defined by the presence or absence of symptoms. We used a combination of methods to study SARS-CoV-2 genes and their readouts, known as transcripts, in clinical samples from people with symptomatic and asymptomatic infections. We demonstrate that transcripts responsible for making viral proteins are seen at lower levels in asymptomatic infections. We also identify structural changes in the viral genes and transcripts that potentially influence the host’s response to the virus. Our study defines potential markers of symptom severity that may ultimately guide risk mitigation and testing strategies.

SummaryConservative repair of stalled replication forks is important for the maintenance of a stable genome. However, the mechanisms that regulate repair pathway “choice” at stalled mammalian forks remain poorly understood. The Fanconi anemia complementation group M gene, FANCM, encodes a multi-domain scaffolding and motor protein that interacts with several distinct repair protein complexes at stalled forks. Here we use a chromosomally integrated reporter of stalled fork repair, in combination with defined mutations engineered within the endogenous Fancm gene in primary mammalian cells, to study how Fancm regulates stalled fork repair. We identify separation-of-function Fancm mutants, which reveal that distinct repair functions of FANCM are enacted by modular, molecularly separable scaffolding domains. These findings define FANCM as a key mediator of repair pathway choice at stalled replication forks and reveal its molecular mechanism. Notably, a mutation that inactivates the ATPase function of FANCM disables all FANCM-mediated repair functions and appears to “trap” FANCM at stalled forks. We find that Fancm null cells do not survive genetic inactivation of Brca1. This synthetic lethal interaction is recapitulated in Fancm ATPase-defective mutants. The ATPase function of FANCM may therefore represent a promising “druggable” target for therapy of BRCA1 mutant cancers.

On March 30, 2020, the AACR Board of Directors provided a letter to the U.S. Congressional leadership on behalf of its members in response to the COVID-19 public health emergency.

Triple-negative breast cancer (TNBC) is a particularly aggressive form of breast cancer with high risk of recurrence and approximately 22% rate of five-year survival when the disease becomes metastatic. Thus, understanding of mechanisms supporting metastatic colonization of distant organs is of critical importance for the development of new therapies and possibly improved outcomes. Syngeneic mouse models suggest the role of innate immune cells, particularly neutrophils, in support of metastatic dissemination of TNBC. However, it is not possible to study human cancer in immunocompetent mice. Furthermore, organoids or other 3D tissue models do not allow investigations of distant organs colonization with metastatic TNBC tumors. Here, we used humanized mice and patient-derived xenograft (PDX) from treatment naïve primary TNBC tumors to investigate the mechanisms that promote metastasis. NSG mice with transgenic expression of human hematopoietic cytokines SCF/GM-CSF/IL-3 were engrafted with human CD34+ hematopoietic progenitor cells (HPCs) to generate humanized (h)NSG-SGM3 mice. All PDX tumors grew after orthotopic implantation at week 8-12. The presence of distant metastasis was determined by macroscopic evaluation of distant organs and further confirmed by E-cadherin and cytokeratin 19 expression using polychromatic immunofluorescence on frozen tissue section. Among ten PDX tumors tested, four did not develop metastasis, four developed only lung metastasis and two developed multi-organ metastases (lung and liver). We find that different TNBC PDX tumors have different metastatic potential. Their metastatic potential is linked with differences in cellular composition and transcriptional signatures at the level of the primary tumor. Interferon Response signature is enriched in primary TNBC PDXs with metastatic potential, while non-metastatic primary tumors display a TNF signature as well as allograft rejection signature. Furthermore, liver metastases were enriched in myeloid transcripts. Thus, our model enables mechanistic and pre-clinical studies of human TNBC metastasis. Citation Format: Chun I Yu, Te-Chia Wu, Francesca Menghi, Joshy George, Kyung In Kim, Florentina Marches, Edison T Liu, Jacques Banchereau, Karolina Palucka. Transcriptional signature of metastatic triple negative breast cancer in humanized mice [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-01-05.

Immunotherapy has revolutionized cancer therapy, largely attributed to the success of immune-checkpoint blockade. However, there are subsets of patients across multiple cancers who have not shown robust responses to these agents. A major impediment to progress in the field is the availability of faithful mouse models that recapitulate the complexity of human malignancy and immune contexture within the tumor microenvironment. These models are urgently needed across all malignancies to interrogate and predict antitumor immune responses and therapeutic efficacy in clinical trials. Herein, we seek to review pros and cons of different cancer mouse models, and how they can be used as platforms to predict efficacy and resistance to cancer immunotherapies. Significance: Although immunotherapy has shown substantial benefit in the treatment of a variety of malignancies, a key hurdle toward the advancement of these therapies is the availability of immunocompetent preclinical mouse models that recapitulate human disease. Here, we review the evolution of preclinical mouse models and their utility as coclinical platforms for mechanistic interrogation of cancer immunotherapies. Cancer Discov; 8(11); 1358–65. ©2018 AACR.

Acquired genomic structural variants (SVs) are major hallmarks of cancer genomes, but they are challenging to reconstruct from short-read sequencing data. Here we exploited the long reads of the nanopore platform using our customized pipeline, Picky ( https://github.com/TheJacksonLaboratory/Picky ), to reveal SVs of diverse architecture in a breast cancer model. We identified the full spectrum of SVs with superior specificity and sensitivity relative to short-read analyses, and uncovered repetitive DNA as the major source of variation. Examination of genome-wide breakpoints at nucleotide resolution uncovered micro-insertions as the common structural features associated with SVs. Breakpoint density across the genome is associated with the propensity for interchromosomal connectivity and was found to be enriched in promoters and transcribed regions of the genome. Furthermore, we observed an over-representation of reciprocal translocations from chromosomal double-crossovers through phased SVs. We demonstrate that Picky analysis is an effective tool for comprehensive detection of SVs in cancer genomes from long-read data.

Background. We recently discovered a unique chromotype, the Tandem Duplicator Phenotype (TDP), characterized by hundreds of somatic tandem duplications (TDs) scattered throughout the genome of a large percentage of triple negative breast cancers (TNBCs). Importantly, we observed that the TDP associates with a better response to cisplatin therapy in vitro and in vivo, suggesting that it is a tractable and quantitative biomarker of response to platinum-based therapy. Here, we expand on our initial findings by analyzing Whole-Genome (WG) sequences of over 2,700 tumors. Methods. TD coordinates from WG sequences relative to 2717 tumors were assembled from over 30 independent studies representing several cancer types, including 254 TNBCs. WG sequencing of mouse breast tumors was carried out using standard Illumina protocols. The number, distribution and span-size of somatic TDs from a training set of 992 tumors were used to develop a TDP classifier that identifies highly recurrent but clearly distinct TDP profiles. The TDP classifier was then applied to the remaining tumor sequences. WG mutation and copy number datasets were investigated to identify the genetic drivers associated with each TDP profile, and the genomic consequences of different TDPs were evaluated through identification of genomic hotspots for gene duplication and transection. Results. We describe six different TDPs featuring distinct TD span size distributions, with peaks at 10Kb (group 1), 300Kb (group 2) and 3Mb (group 3), or different combinations of these (mix12, mix13 and mix23). More than half of all TNBC display a TDP. Of these, 55% classify as group 1, 14% as group 2 and 15% as group mix12. Whereas all TDP groups show a higher TP53 mutation rate compared to non-TDP tumors, each TDP profile is characterized by specific additional gene perturbations, with loss of BRCA1 occurring in groups 1, mix12 and mix13; CCNE1 amplification in group 2; and CDK12 mutations in group mix23. We show that different TDPs are subject to the perturbation of specific oncogenic networks resulting from the duplication of oncogenes by larger TDs (>300Kb) or the disruption of tumor suppressors via double transections by shorter TDs (10Kb). Indeed, tumor suppressor genes such as PTEN, RB1 and MLL3 are frequently disrupted by TDs in TNBC TDP group 1 tumors, whereas TNBC TDP group 2 tumors commonly feature duplication of oncogenes such as MYC and MALAT1. Finally, through WG analyses of 18 mouse models (GEMMs) of breast cancer, we provide the first mechanistic evidence of the driving role of conjoint loss of TP53 and BRCA1, but not of BRCA2, in inducing the TDP group 1 profile. Conclusions. Our study shows a definitive genetic induction of one specific form of TDP (group 1) characterized by 10kb TD span. Different TDP profiles are characterized by alternative somatic genetic origins but always couple with disruptive TP53 mutations. The consequences of the massive TD formation in TDP TNBCs suggest a systems strategy to tumor induction involving heterogeneous combinations of oncogenes and tumor suppressors. That these TDP forms, accounting for ˜50% of TNBC, are associated with significant sensitivity to cisplatin suggest that this chromotype may identify TNBC patients who would benefit from upfront platinum-based chemotherapy. Citation Format: Liu ET, Menghi F, Barthel F, Yadav V, Tang M, Ji B, Carter G, Jonkers J, Verhaak R. Tandem duplicator phenotypes define 50% of triple negative breast cancers [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr GS1-05.

This abstract was not presented at the symposium.

The usefulness of a specific technology often hits a ceiling based on technical limitations. Then, a single advance, frequently orthogonal to the core methodology, dramatically expands the utility of this technology. The effectiveness of early surgeons wielding a scalpel was severely limited by how much a patient could withstand the pain of an operation. Anesthesia was the core discovery that permitted surgery to become a consistently effective medical intervention. Molecular cloning was a powerful technology to understand the importance of genes in biology, but it had limited utility in population genetics and in medicine, because of the arduous requirements for cloning a single gene. The invention of polymerase chain reaction dramatically expanded the utility of molecular biology into high‐throughput sequencing, epidemiology, forensics, diagnostics, and gene therapy. We believe that the advent of powerful gene editing technologies such as the CRISPR/CAS system will be this transformative technology for murine genetics. The subsequent massive sequencing efforts to define the mutational spectrum of human diseases have uncovered a bewildering number of genetic changes. It is now recognized that most diseases are genetically complex and that their dissection requires the enrollment of many hundreds of thousands of individuals to achieve adequate statistical power to ensure the validity of an association. This purely statistical approach is clearly impracticable, given the many variants and mutations that are being uncovered with each sequence‐based study. Thus, the translation of human genome research into health care heavily relies on appropriate organismal models that accurately reflect the human condition. This is where the laboratory mouse ( Mus musculus ) comes in. For many diseases that require an intact organ system in an intact animal—such as neurological disorders, renal disease, complex cardiopulmonary syndromes, and aging—the mouse has been a primary experimental model for mammalian biology since the turn of the last century. > … …

834 Background: CUP presents a unique niche and challenge for application of GP. Absence of a primary limits consensus regarding site-directed and availability of tissue specific targeted therapy. We evaluated the real time feasibility and clinical utility of GP in CUP. Methods: Treatment eligible CUP pts were prospectively enrolled. A novel next-gen targeted sequencing (NGS) assay (ActionSeq/FusionSeq) was used to find genomic alterations (GAs) (somatic mutations in 212 and fusions in 53 cancer-associated genes). The primary objective was to determine prevalence of GAs and to assess the clinical impact via change in pre-test planned therapy (either referral to biomarker pertinent clinical trial (CT) or off label use of FDA approved drugs). With 54 pts we achieved 80% power (α 0.05) to a treatment change in 10% (5% to 15%) pts. Results: Between 9/2016 and 8/2019, 150 pts were consented. Tissue for GP was available in 59 (39%) pts (for 91 pts, samples had exhausted or insufficient tissue). Test was successfully performed on 54 (92%) pts. Cohort characteristics include: median age: 58 yr, male 43%, ECOG PS ≤1 96%, median IHC 8 (range 2-26), median survival 33 m (95% CI 18-47). Median reporting time was 23 days. Four (7%) pts had no identifiable GAs. A fusion ( PTRPK) was seen in 1 (2%) pt. Among 50 pts, total number of GAs were 487; 123 (26%) were “clinically relevant” (median 2.5/pt, range 1-11) while 364 (76%) were variants of unknown significance. Of the 123 GAs, 94 were mutations and 29 were amplifications. The 5 most common mutations were TP53, KRAS, PIK3CA, ARID1A, and NRAS and amplifications were CCND1, FGFR3, ERBB2, EGFR, and MYC. Planned therapy change post ActionSeq occurred in 13 pts (22%, 95% CI 13-34) (2 received an off-label drug; 9 were CT eligible [2 enrolled, 5 had PS decline, 2 pending]; 2 were lost to follow-up). Responses were seen in 2 of 4 pts who received GP based treatment. Conclusions: Comprehensive GP should be offered early to CUP pts. GP can help identify novel therapy and clinical trial options. Given the high rate of insufficient tissue cases, integrating a tissue sensitive algorithm involving IHC and GP in therapeutic management of CUP is merited.

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertainty

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertainty AUTHOR SUMMARYAn overarching challenge of cancer is that patients develop resistance to treatment -- an essentially evolutionary process. However, there is currently very little understanding of how tumor evolution can be exploited to improve treatment. One reason for this is that usually only 1-2 samples can be obtained per patient, so cancer evolutionary processes are still poorly understood. To solve this problem, we created many dozens of copies of the tumors from two breast cancer patients using xenografting and cell culture methods. We then compared the evolution in these tumor copies in response to different treatments, including four of the most common breast cancer chemotherapies. These studies present the most exhaustive comparisons of treatment-induced evolution that have yet been performed for individual cancer patients. Unexpectedly, high-resolution sequencing of these samples revealed a special dynamically treatable ecology in one tumor, in which tumor growth during platinum therapy was determined by the ecological balance of two tumor cell populations. Our work shows that ecologies that can be targeted by dynamic treatment strategies arise spontaneously in breast cancers. Population heterogeneity is common within cancers, and our work suggests how tracking of intratumoral evolution can be used to optimize treatment.

© 2015 Elsevier Inc. New approaches to optimization of cancer drug development in the laboratory and the clinic will be required to fully achieve the goal of individualized, precision cancer therapy. Improved preclinical models that more closely reflect the now recognized genomic complexity of human cancers are needed. Here we describe a collaborative research project that integrates core resources of The Jackson Laboratory Basic Science Cancer Center with genomics and clinical research facilities at the UC Davis Comprehensive Cancer Center to establish a clinically and genomically annotated patient-derived xenograft (PDX) platform designed to enhance new drug development and strategies for targeted therapies. Advanced stage non-small-cell lung cancer (NSCLC) was selected for initial studies because of emergence of a number of "druggable" molecular targets, and recent recognition of substantial inter- and intrapatient tumor heterogeneity. Additionally, clonal evolution after targeted therapy interventions make this tumor type ideal for investigation of this platform. Using the immunodeficient NOD scid gamma mouse, > 200 NSCLC tumor biopsies have been xenotransplanted. During the annotation process, patient tumors and subsequent PDXs are compared at multiple levels, including histomorphology, clinically applicable molecular biomarkers, global gene expression patterns, gene copy number variations, and DNA/chromosomal alterations. NSCLC PDXs are grouped into panels of interest according to oncogene subtype and/or histologic subtype. Multiregimen drug testing, paired with next-generation sequencing before and after therapy and timed tumor pharmacodynamics enables determination of efficacy, signaling pathway alterations, and mechanisms of sensitivity-resistance in individual models. This approach should facilitate derivation of new therapeutic strategies and the transition to individualized therapy.

SUMMARY The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian, and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 kb, 231 kb, and 1.7 Mb, respectively. TDPs with ~11 kb TDs feature loss of TP53 and BRCA1. TDPs with ~231 kb and ~1.7 Mb TDs associate with CCNE1 pathway activation and CDK12 disruptions, respectively. We demonstrate that p53 and BRCA1 conjoint abrogation drives TDP induction by generating short-span TDP mammary tumors in genetically modified mice lacking them. Lastly, we show how TDs in TDP tumors disrupt heterogeneous combinations of tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers., Graphical Abstract, In Brief Menghi et al. stratify tandem duplicator phenotype tumors by classifying their tandem duplications (TDs) into three span sizes associated with different pathway alterations and show how TDs disrupt tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers.

Establishment of an in vivo small animal model of human tumor and human immune system interaction would enable preclinical investigations into the mechanisms underlying cancer immunotherapy. To this end, nonobese diabetic (NOD).Cg- PrkdcscidIL2rgtm1Wjl/Sz (null; NSG) mice were transplanted with human (h)CD34+ hematopoietic progenitor and stem cells, which leads to the development of human hematopoietic and immune systems [humanized NSG (HuNSG)]. HuNSG mice received human leukocyte antigen partially matched tumor implants from patient-derived xenografts [PDX; non-small cell lung cancer (NSCLC), sarcoma, bladder cancer, and triple-negative breast cancer (TNBC)] or from a TNBC cell line-derived xenograft (CDX). Tumor growth curves were similar in HuNSG compared with nonhuman immune-engrafted NSG mice. Treatment with pembrolizumab, which targets programmed cell death protein 1, produced significant growth inhibition in both CDX and PDX tumors in HuNSG but not in NSG mice. Finally, inhibition of tumor growth was dependent on hCD8+ T cells, as demonstrated by antibody-mediated depletion. Thus, tumor-bearing HuNSG mice may represent an important, new model for preclinical immunotherapy research.-Wang, M., Yao, L.-C., Cheng, M., Cai, D., Martinek, J., Pan, C.-X., Shi, W., Ma, A.-H., De Vere White, R. W., Airhart, S., Liu, E. T., Banchereau, J., Brehm, M. A., Greiner, D. L., Shultz, L. D., Palucka, K., Keck, J. G. Humanized mice in studying efficacy and mechanisms of PD-1-targeted cancer immunotherapy.

Acquired genomic structural variants (SVs) are major hallmarks of the cancer genome. Their complexity has been challenging to reconstruct from short-read sequencing data. Here, we exploit the long-read sequencing capability of the nanopore platform using our customized pipeline,Picky, to reveal SVs of diverse architecture in a breast cancer model. From modest sequencing coverage, we identified the full spectrum of SVs with superior specificity and sensitivity relative to short-read analyses and uncovered repetitive DNA as the major source of variation. Examination of the genome-wide breakpoints at nucleotide-resolution uncovered micro-insertions as the common structural features associated with SVs. Breakpoint density across the genome is associated with propensity for inter-chromosomal connectivity and transcriptional regulation. Furthermore, an over-representation of reciprocal translocations from chromosomal double-crossovers was observed through phased SVs. The comprehensive characterization of SVs using the robust long-read sequencing approach in cancer cohorts will facilitate strategies to monitor genome stability during tumor evolution and improve therapeutic intervention.

A recent publication questions the suitability of mice as a model for the human inflammatory response and has fueled the continuing debate about the suitability of mice as models for human disease. We discuss recent advances in disease modeling using mice, and the genetic factors that need to be considered when trying to recapitulate aspects of human disease. Failure to appreciate the important differences between human and mouse biology and genetics underlying attempts to generate faithful models frequently leads to poor outcomes. Closely coordinated human and model organism studies are essential to provide traction for translational research.

CSP LED packages are soldered directly on printed circuit bords (PCB). Voids in the solder joints and tilting of the LED package influence the reliability of the LED module and need to be inspected directly after assambl. By X-Ray and optical 3D inspection combined with transient thermal analysis the required quality of the assembly can be insured. The impact of tilting on the thermal and thermomechanical performance of the modules is investigated by experiments, i.e. transient thermal analysis, and finite element simulations. The impact of tilting on mechanical stress and strain is simulated.

Although elongation of telomeres is thought to be the prime function of reactivated telomerase in cancers, this activity alone does not account for all of the properties that telomerase reactivation attributes to human cancer cells. Here, we uncover a link between telomerase and NF-κB, a master regulator of inflammation. We observe that while blocking NF-κB signalling can inhibit effects of telomerase overexpression on processes relevant to transformation, increasing NF-κB activity can functionally substitute for reduced telomerase activity. Telomerase directly regulates NF-κB-dependent gene expression by binding to the NF-κB p65 subunit and recruitment to a subset of NF-κB promoters such as those of IL-6 and TNF-α, cytokines that are critical for inflammation and cancer progression. As NF-κB can transcriptionally upregulate telomerase levels, our findings suggest that a feed-forward regulation between them could be the key mechanistic basis for the coexistence of chronic inflammation and sustained telomerase activity in human cancers.

SUMMARY Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic through evolution. Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the least-evolving key genomic domains against random genetic or transcriptional errors in the genome. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions.