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Competing Interests: Disclosure: Linda Peterson and Xuntian Jang are patent holders on the predictive value of the ceramide ratio for cardiovascular disease and congestive heart failure. Yin Cao previously served as a consultant for Geneoscopy for work unrelated to the subject matter. Joshua Mitchell has received research support from Abbott Laboratories, Myocardial Solutions, and Children’s Discovery Institute, unrelated to this manuscript, and has also received modest consulting fees from Alnylam, BridgeBio, Jazz Pharmaceuticals, Pfizer, Race Oncology, and Altathera for work unrelated to this manuscript. Usman Panni, Nicole Fergestrom, Adetunji T. Toriola, Timothy M. Nywening, S. Peter Goedegebuure, Jacqueline L. Mudd, Joseph Ippolito, Ryan C. Fields, and William G. Hawkins declare no potential conflicts of interest that may be relevant to the contents of this study.

Purpose: To establish HMGA2 as a marker of basal-like disease in pancreatic ductal adenocarcinoma (PDAC) and explore its use as a biomarker for prognosis and treatment resistance., Experimental Design: We identified high expression of HMGA2 in basal PDAC cells in a scRNAseq Atlas of 172 patient samples. We then analyzed HMGA2 expression, along with expression of the classical marker GATA6, in a cohort of 580 PDAC samples with multiplex immunohistochemistry. We further supplemented these data with an additional 30 diverse patient samples and multiple independent single-cell RNAseq databases., Results: We found that expression of HMGA2, but not previously described basal markers CK5 or CK17, predicted overall survival in our cohort. Combining HMGA2 and GATA6 status allowed for identification of two key study groups: an HMGA2+/GATA6- cohort with worse survival, low tumor-infiltrating CD8+ T cells, increased FAP+ fibroblasts, and poorer response to gemcitabine-based chemotherapies (n=94, median survival=11.2 months post-surgery); and an HMGA2-/GATA6+ cohort with improved survival, increased CD8+ T-cell infiltrate, decreased FAP+ fibroblasts, and improved survival with gemcitabine-based chemotherapy (n=198, median survival=21.7 months post-surgery). HMGA2 was also prognostic for overall survival in RNA sequencing from an independent cohort., Conclusions: IHC stratification of primary tumors by HMGA2 and GATA6 status in pancreatic cancer is associated with differential outcomes, survival following chemotherapy, and tumor microenvironments. As a nuclear marker for basal disease, HMGA2 complements GATA6 to identify disease subtypes in PDAC.

Background: Pancreatic ductal adenocarcinoma (PDAC) has a high fatality rate, with surgery as the only curative treatment. Identification of new biomarkers related to survival may help guide discovery of new pathophysiologic pathways and potential therapeutic targets. As long-chain ceramides have been linked to tumor proliferation, we sought to determine if ceramide levels were prognostic in PDAC., Methods: Patients from two phase I studies of PDAC were followed for all-cause mortality. Ceramide levels (C24:0, C22:0, and C16:0) were quantified before treatment and at study intervals. Multivariable Cox regression models assessed the association of ceramide levels and mortality after adjusting for other univariable predictors, including time-dependent tumor resection. The ability of repeated ceramide measures to discriminate patients at risk for mortality was also assessed using multivariable modeling and the c-statistic., Results: Higher plasma C16:0 concentration was associated with higher all-cause mortality in univariable and multivariable analysis (adjusted hazard ratio [aHR] 1.41, 95% confidence interval [CI] 1.09-1.82; p < 0.01). In contrast, a higher plasma C24:0/C16:0 ratio was associated with lower all-cause mortality in multivariable analysis (aHR 0.69, 95% CI 0.49-0.97; p = 0.032). Discrimination of mortality was significantly improved with the addition of either plasma C16:0 or C24:0/C16:0 levels, with optimal discrimination occurring using repeated measures of the C24:0/C16:0 ratio (c-statistic 0.73 vs. c-statistic 0.66; p < 0.001)., Conclusions: Higher plasma C16:0 and lower C24:0/C16:0 ratios are independently associated with mortality in PDAC and show an ability to improve discrimination of mortality in this deadly disease. Further studies are needed to confirm this association and evaluate this novel pathway for potential therapeutic targets., (© 2024. Society of Surgical Oncology.)

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories., (©2024 The Authors; Published by the American Association for Cancer Research.)

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs., Significance: The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors., (©2023 The Authors; Published by the American Association for Cancer Research.)

Small nucleotide variants in non-coding regions of the genome can alter transcriptional regulation, leading to changes in gene expression which can activate oncogenic gene regulatory networks. Melanoma is heavily burdened by non-coding variants, representing over 99% of total genetic variation, including the well-characterized TERT promoter mutation. However, the compendium of regulatory non-coding variants is likely still functionally under-characterized. We developed a pipeline to identify hotspots, i.e. recurrently mutated regions, in melanoma containing putatively functional non-coding somatic variants that are located within predicted melanoma-specific regulatory regions. We identified hundreds of statistically significant hotspots, including the hotspot containing the TERT promoter variants, and focused on a hotspot in the promoter of CDC20. We found that variants in the promoter of CDC20, which putatively disrupt an ETS motif, lead to lower transcriptional activity in reporter assays. Using CRISPR/Cas9, we generated an indel in the CDC20 promoter in human A375 melanoma cell lines and observed decreased expression of CDC20, changes in migration capabilities, increased growth of xenografts, and an altered transcriptional state previously associated with a more proliferative and less migratory state. Overall, our analysis prioritized several recurrent functional non-coding variants that, through downregulation of CDC20, led to perturbation of key melanoma phenotypes., (© 2023. The Author(s).)

Colorectal cancer (CRC) is the most common gastrointestinal malignancy and a leading cause of cancer deaths in the United States. More than half of CRC patients develop metastatic disease (mCRC) with an average 5-year survival rate of 13%. Circular RNAs (circRNAs) have recently emerged as important tumorigenesis regulators; however, their role in mCRC progression remains poorly characterized. Further, little is known about their cell-type specificity to elucidate their functions in the tumor microenvironment (TME). To address this, we performed total RNA sequencing (RNA-seq) on 30 matched normal, primary and metastatic samples from 14 mCRC patients. Additionally, five CRC cell lines were sequenced to construct a circRNA catalog in CRC. We detected 47 869 circRNAs, with 51% previously unannotated in CRC and 14% novel candidates when compared to existing circRNA databases. We identified 362 circRNAs differentially expressed in primary and/or metastatic tissues, termed circular RNAs associated with metastasis (CRAMS). We performed cell-type deconvolution using published single-cell RNA-seq datasets and applied a non-negative least squares statistical model to estimate cell-type specific circRNA expression. This predicted 667 circRNAs as exclusively expressed in a single cell type. Collectively, this serves as a valuable resource, TMECircDB (accessible at https://www.maherlab.com/tmecircdb-overview), for functional characterization of circRNAs in mCRC, specifically in the TME., (© The Author(s) 2023. Published by Oxford University Press on behalf of NAR Cancer.)

Cancer-derived extracellular vesicles (EVs) promote tumorigenesis, premetastatic niche formation, and metastasis via their protein cargo. However, the proteins packaged by patient tumors into EVs cannot be determined in vivo because of the presence of EVs derived from other tissues. We therefore developed a cross-species proteomic method to quantify the human tumor-derived proteome of plasma EVs produced by patient-derived xenografts of four cancer types. Proteomic profiling revealed individualized packaging of novel protein cargo, and machine learning accurately classified the type of the underlying tumor., Competing Interests: Conflict of interest Dr. Li has received license fee from Envigo and research funding from Pfizer, Takeda Oncology, and Zenopharm not associated with this article., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Gastroenteropancreatic neuroendocrine neoplasms (GEP NENs) are rare cancers consisting of neuroendocrine carcinomas (NECs) and neuroendocrine tumors (NETs), which have been increasing in incidence in recent years. Few cell lines and pre-clinical models exist for studying GEP NECs and NETs, limiting the ability to discover novel imaging and treatment modalities. To address this gap, we isolated tumor cells from cryopreserved patient GEP NECs and NETs and injected them into the flanks of immunocompromised mice to establish patient-derived xenograft (PDX) models. Two of six mice developed tumors (NEC913 and NEC1452). Over 80% of NEC913 and NEC1452 tumor cells stained positive for Ki67. NEC913 PDX tumors expressed neuroendocrine markers such as chromogranin A (CgA), synaptophysin (SYP), and somatostatin receptor-2 (SSTR2), whereas NEC1452 PDX tumors did not express SSTR2. Exome sequencing revealed loss of TP53 and RB1 in both NEC tumors. To demonstrate an application of these novel NEC PDX models for SSTR2-targeted peptide imaging, the NEC913 and NEC1452 cells were bilaterally injected into mice. Near infrared-labelled octreotide was administered and the fluorescent signal was specifically observed for the NEC913 SSTR2 positive tumors. These 2 GEP NEC PDX models serve as a valuable resource for GEP NEN therapy testing.

Purpose: FOLFIRINOX has demonstrated promising results for patients with pancreatic ductal adenocarcinoma (PDAC). Chemotherapy-induced immunogenic cell death can prime antitumor immune responses. We therefore performed high-dimensional profiling of immune cell subsets in peripheral blood to evaluate the impact of FOLFIRINOX on the immune system., Experimental Design: Peripheral blood mononuclear cells (PBMC) were obtained from treatment-naïve ( n = 20) and FOLFIRINOX-treated patients ( n = 19) with primary PDAC tumors at the time of resection. PBMCs were characterized by 36 markers using mass cytometry by time of flight (CyTOF)., Results: Compared with treatment-naïve patients, FOLFIRINOX-treated patients showed distinct immune profiles, including significantly decreased inflammatory monocytes and regulatory T cells (Treg), increased Th1 cells, and decreased Th2 cells. Notably, both monocytes and Treg expressed high levels of immune suppression-associated CD39, and the total CD39 + cell population was significantly lower in FOLFIRINOX-treated patients compared with untreated patients. Cellular alterations observed in responders to FOLFIRINOX included a significantly decreased frequency of Treg, an increased frequency of total CD8 T cells, and an increased frequency of CD27 - Tbet + effector/effector memory subsets of CD4 and CD8 T cells., Conclusions: Our study reveals that neoadjuvant chemotherapy with FOLFIRINOX enhances effector T cells and downregulates suppressor cells. These data indicate that FOLFIRINOX neoadjuvant therapy may improve immune therapy and clinical outcome in patients with PDAC., (©2021 The Authors; Published by the American Association for Cancer Research.)

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors., (© 2021. The Author(s).)

Induced pluripotent stem cells (iPSCs) have tremendous potential as a tool for disease modeling, drug testing, and other applications. Since the generation of iPSCs "captures" the genetic history of the individual cell that was reprogrammed, iPSC clones (even those derived from the same individual) would be expected to demonstrate genetic heterogeneity. To assess the degree of genetic heterogeneity, and to determine whether some cells are more genetically "fit" for reprogramming, we performed exome sequencing on 24 mouse iPSC clones derived from skin fibroblasts obtained from two different sites of the same 8-week-old C57BL/6J male mouse. While no differences in the coding regions were detected in the two parental fibroblast pools, each clone had a unique genetic signature with a wide range of heterogeneity observed among the individual clones: a total of 383 iPSC variants were validated for the 24 clones (mean 16.0/clone, range 0-45). Since these variants were all present in the vast majority of the cells in each clone (variant allele frequencies of 40-60% for heterozygous variants), they most likely preexisted in the individual cells that were reprogrammed, rather than being acquired during reprogramming or cell passaging. We then tested whether this genetic heterogeneity had functional consequences for hematopoietic development by generating hematopoietic progenitors in vitro and enumerating colony forming units (CFUs). While there was a range of hematopoietic potentials among the 24 clones, only one clone failed to differentiate into hematopoietic cells; however, it was able to form a teratoma, proving its pluripotent nature. Further, no specific association was found between the mutational spectrum and the hematopoietic potential of each iPSC clone. These data clearly highlight the genetic heterogeneity present within individual fibroblasts that is captured by iPSC generation, and suggest that most of the changes are random, and functionally benign.

Laminins are components of all basement membranes and have well demonstrated roles in diverse developmental processes, from the peri-implantation period onwards. Laminin 1 (alpha1beta1gamma1) is a major laminin found at early stages of embryogenesis in both embryonic and extraembryonic basement membranes. The laminin gamma1 chain has been shown by targeted mutation to be required for endodermal differentiation and formation of basement membranes; Lamc1(-/-) embryos die within a day of implantation. We report the generation of mice lacking laminin alpha1 and laminin beta1, the remaining two laminin 1 chains. Mutagenic insertions in both Lama1 and Lamb1 were obtained in a secretory gene trap screen. Lamb1(-/-) embryos are similar to Lamc1(-/-) embryos in that they lack basement membranes and do not survive beyond embryonic day (E) 5.5. However, in Lama1(-/-) embryos, the embryonic basement membrane forms, the embryonic ectoderm cavitates and the parietal endoderm differentiates, apparently because laminin 10 (alpha5beta1gamma1) partially compensates for the absent laminin 1. However, such compensation did not occur for Reichert's membrane, which was absent, and the embryos died by E7. Overexpression of laminin alpha5 from a transgene improved the phenotype of Lama1(-/-) embryos to the point that they initiated gastrulation, but this overexpression did not rescue Reichert's membrane, and trophoblast cells did not form blood sinuses. These data suggest that both the molecular composition and the integrity of basement membranes are crucial for early developmental events.

Laminins exert numerous effects on neurons in vitro, but expression of laminin subunit genes by neurons in vivo remains controversial. To reexamine this issue, we generated mice from ES cells in which the laminin alpha1, alpha5, beta1, and gamma1 genes had been "trapped" by insertion of a histochemically detectable selectable marker, betageo (beta-galactosidase fused to neomycin phosphotransferase). The presence of laminin-betageo fusion proteins was assayed histochemically and immunochemically, revealing expression of laminin beta1 and gamma1 genes, but not alpha chain genes, by defined subsets of neurons in brain and retina. We also used the gene traps in a novel way to assay expression of endogenous laminin subunits, which were barely detectable by ordinary immunohistochemical methods. The trapping vector included a transmembrane domain that anchors proteins otherwise destined for secretion. Laminin alpha/beta/gamma heterotrimers are assembled intracellularly, and we show that the trapped laminin gamma1 fusion protein "co-trapped" endogenous beta1 intracellularly. The laminin gamma1 fusion was also able to co-trap transgene-derived alpha chains, but we detected no co-trapped endogenous alpha chains. The co-trapping method may be generally useful for identifying proteins or isolating protein complexes associated with trapped gene products., (Copyright 2003 Wiley-Liss, Inc.)

Alport syndrome is a human hereditary glomerulonephritis which results in end-stage renal failure (ESRF) in most cases. It is caused by mutations in any one of the collagen alpha3(IV), alpha4(IV), or alpha5(IV) chain genes (COL4A3-COL4A5). Patients carrying identical mutations can exhibit very different disease courses, suggesting that other genes or the environment influence disease progression. We previously generated a knockout mouse model of Alport syndrome by mutating Col4a3. Here, we show that genetic background strongly influences the timing of onset of disease and rate of progression to ESRF in these mice. On the 129X1/SvJ background, Col4a3 -/- mice reached ESRF at approximately 66 days of age, while on the C57BL/6J background, the mean age at ESRF was 194 days of age. This suggests the existence of modifier genes that influence disease progression. A detailed histopathological analysis revealed that glomerular basement membrane lesions typical of Alport syndrome were significantly more frequent in homozygotes on the 129X1/SvJ background than on the C57BL/6J background as early as two weeks of age, suggesting that modifier genes act by influencing glomerular basement membrane structure. Additional data indicated that differential physiological responses to basement membrane splitting also underlie the differences in disease progression. We attempted to map the modifier genes as quantitative trait loci (QTLs) using age at ESRF as the quantitative trait. Genome scans were performed on mice at the two extremes in a cohort of mutant F1 x C57BL/6J backcross mice. Analysis with Map Manager QT revealed QTLs linked to markers on chromosomes 9 and 16. A more detailed understanding of how these QTLs act could lead to new approaches for therapy in diverse renal diseases.

The observed total interlaboratory uncertainty in restriction fragment length polymorphism (RFLP) measurements is sufficiently small to be of little significance given current forensic needs. However, as the number of RFLP data increase, further reduction in the total uncertainty could help minimize the resources required to evaluate potential profile matches. The large number of data available enable quantitative estimation of the within-laboratory imprecision and among-laboratory bias contributions to the total uncertainty. Some small but consistent among-laboratory measurement biases can be attributed to specific procedural or materials differences. The bias direction is often fragment-specific and thus unpredictable for unknown samples. Actions that would minimize currently recognized sources of interlaboratory bias include the following: (1) all laboratories should use the same algorithm for data interpolation, (2) all laboratories should use the same sizing ladders, (3) each laboratory should prepare control DNA and sample DNA in the same manner and with the identical reagents, (4) all laboratories should adopt a uniform policy on ethidium bromide use, and (5) all laboratories should adopt the same control DNA sizing acceptability criteria.

Identifying the intrinsic sources of measurement uncertainty greatly facilitates control and further optimization of a measurement system. We have developed a model which quantitatively describes the observed interlaboratory variability of autoradiographic DNA band sizing. The model focuses on optical imaging measurements of band position and the calibration techniques used to convert measured band position to reported band size. The imaging component of measurement variability is described as a 0.05-0.2% standard deviation in determining the relative location of sample and calibration bands on a given film image. While developed solely with optical imaging information, the model is consistent with interlaboratory band sizing measurement variability observed with pristine samples. This interlaboratory variability can be modeled as a 0.2-0.4% standard deviation in the relative positions of sample and calibration bands across different electrophoretic gels. Further band sizing protocol standardization among laboratories would thus be expected to achieve at best a 2-fold reduction in interlaboratory band sizing variability.