The presence of Alternative lengthening of telomeres (ALT) and/or ATRX loss, as well as the role of other telomere abnormalities, have not been formally studied across the spectrum of NF1-associated solid tumors. Utilizing a telomere-specific FISH assay, we classified tumors as either ALT-positive or having long (without ALT), short, or normal telomere lengths. A total of 426 tumors from 256 NF1 patients were evaluated, as well as 99 MPNST tumor samples that were sporadic or of unknown NF1 status. In the NF1-glioma dataset, ALT was present in the majority of high-grade gliomas: 14 (of 23; 60%) in contrast to only 9 (of 47; 19%) low-grade gliomas (p = 0.0009). In the subset of ALT-negative glioma cases, telomere lengths were estimated and we observed 17 (57%) cases with normal, 12 (40%) cases with abnormally long, and only 1 (3%) case with short telomeres. In the NF1-associated malignant nerve sheath tumor (NF1-MPNST) set (n = 75), ALT was present in 9 (12%). In the subset of ALT-negative NF1-MPNST cases, telomeres were short in 9 (38%), normal in 14 (58%) and long in 1 (3%). In the glioma set, overall survival was significantly decreased for patients with ALT-positive tumors (p < 0.0001). In the NF1-MPNST group, overall survival was superior for patients with tumors with short telomeres (p = 0.003). ALT occurs in a subset of NF1-associated solid tumors and is usually restricted to malignant subsets. In contrast, alterations in telomere lengths are more prevalent than ALT.

Intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs) are non-invasive neoplasms that are often observed in association with invasive pancreatic cancers, but their origins and evolutionary relationships are poorly understood. In this study, we analyze 148 samples from IPMNs, MCNs, and small associated invasive carcinomas from 18 patients using whole exome or targeted sequencing. Using evolutionary analyses, we establish that both IPMNs and MCNs are direct precursors to pancreatic cancer. Mutations in SMAD4 and TGFBR2 are frequently restricted to invasive carcinoma, while RNF43 alterations are largely in non-invasive lesions. Genomic analyses suggest an average window of over three years between the development of high-grade dysplasia and pancreatic cancer. Taken together, these data establish non-invasive IPMNs and MCNs as origins of invasive pancreatic cancer, identifying potential drivers of invasion, highlighting the complex clonal dynamics prior to malignant transformation, and providing opportunities for early detection and intervention.

Although venous invasion (VI) is a poor prognostic factor for patients with pancreatobiliary tract cancers, its histopathologic characteristics have not been well described. We evaluated the patterns of VI and the added benefit provided by CD31, desmin, and dual CD31‒desmin immunolabeling for identification of VI. We included 120 surgically resected pancreatobiliary tract cancer cases-59 cases as a test set with known VI and 61 cases as a validation set without information of VI. VI was classified into three patterns: intraepithelial neoplasia-like (IN-like), conventional, and destructive. Hematoxylin and eosin (H&E) staining and CD31, desmin, and dual CD31‒desmin immunolabeling were performed. Foci number and patterns of VI were compared with the test and validation sets. More foci of VI were detected by single CD31 (P = 0.022) than H&E staining in the test set. CD31 immunolabeling detected more foci of the conventional pattern of VI, and desmin immunolabeling detected more foci of the destructive pattern (all, P < 0.001). Dual CD31‒desmin immunolabeling identified more foci of VI (P = 0.012) and specifically detected more foci of IN-like (P = 0.045) and destructive patterns (P < 0.001) than H&E staining in the validation set. However, dual CD31‒desmin immunolabeling was not helpful for detecting the conventional pattern of VI in the validation set. Patients with VI detected by dual CD31‒desmin immunolabeling had shorter disease-free survival (P <0.001) than those without VI. VI detected by dual CD31‒desmin immunolabeling was a worse prognostic indicator (P = 0.009). More foci of VI could be detected with additional single CD31 or dual CD31‒desmin immunolabeling. The precise evaluation of VI with dual CD31‒desmin immunolabeling can provide additional prognostic information for patients with surgically resected pancreatobiliary tract cancers.

Migration is an essential cellular process that regulates human organ development and homeostasis as well as disease initiation and progression. In cancer, immune and tumor cell migration is strongly associated with immune cell infiltration, immune escape, and tumor cell metastasis, which ultimately account for more than 90% of cancer deaths. The biophysics and molecular regulation of the migration of cancer and immune cells have been extensively studied separately. However, accumulating evidence indicates that, in the tumor microenvironment, the motilities of immune and cancer cells are highly interdependent via secreted factors such as cytokines and chemokines. Tumor and immune cells constantly express these soluble factors, which produce a tightly intertwined regulatory network for these cells' respective migration. A mechanistic understanding of the reciprocal regulation of soluble factor-mediated cell migration can provide critical information for the development of new biomarkers of tumor progression and of tumor response to immuno-oncological treatments. We review the biophysical andbiomolecular basis for the migration of immune and tumor cells and their associated reciprocal regulatory network. We also describe ongoing attempts to translate this knowledge into the clinic.

Uniquely among mammalian organs, skin is capable of marked size change in adults, yet the mechanisms underlying this notable capacity are unclear. Here, we use a system of controlled tissue expansion in mice to uncover cellular and molecular determinants of skin growth. Through machine learning-guided three-dimensional tissue reconstruction, we capture morphometric changes in growing skin. We find that most growth is driven by the proliferation of the epidermis in response to mechanical tension, with more limited changes in dermal and subdermal compartments. Epidermal growth is achieved through preferential activation and differentiation of Lgr6+ stem cells of the epidermis, driven in part by the Hippo pathway. By single-cell RNA sequencing, we uncover further changes in mechanosensitive and metabolic pathways underlying growth control in the skin. These studies point to therapeutic strategies to enhance skin growth and establish a platform for understanding organ size dynamics in adult mammals.

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm 3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS , but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.

Multiple attributes of the three-dimensional (3D) extracellular matrix (ECM) have been independently implicated as regulators of cell motility, including pore size, crosslink density, structural organization, and stiffness. However, these parameters cannot be independently varied within a complex 3D ECM protein network. We present an integrated, quantitative study of these parameters across a broad range of complex matrix configurations using self-assembling 3D collagen and show how each parameter relates to the others and to cell motility. Increasing collagen density resulted in a decrease and then an increase in both pore size and fiber alignment, which both correlated significantly with cell motility but not bulk matrix stiffness within the range tested. However, using the crosslinking enzyme Transglutaminase II to alter microstructure independently of density revealed that motility is most significantly predicted by fiber alignment. Cellular protrusion rate, protrusion orientation, speed of migration, and invasion distance showed coupled biphasic responses to increasing collagen density not predicted by 2D models or by stiffness, but instead by fiber alignment. The requirement of matrix metalloproteinase (MMP) activity was also observed to depend on microstructure, and a threshold of MMP utility was identified. Our results suggest that fiber topography guides protrusions and thereby MMP activity and motility.

Advances in digital pathology, specifically imaging instrumentation and data management, have allowed for the development of computational pathology tools with the potential for better, faster, and cheaper diagnosis, prognosis, and prediction of disease. Images of tissue sections frequently vary in color appearance across research laboratories and medical facilities because of differences in tissue fixation, staining protocols, and imaging instrumentation, leading to difficulty in the development of robust computational tools. To address this challenge, we propose a novel nonlinear tissue-component discrimination (NLTD) method to register automatically the color space of histopathology images and visualize individual tissue components, independent of color differences between images. Our results show that the NLTD method could effectively discriminate different tissue components from different types of tissues prepared at different institutions. Further, we demonstrate that NLTD can improve the accuracy of nuclear detection and segmentation algorithms, compared with using conventional color deconvolution methods, and can quantitatively analyze immunohistochemistry images. Together, the NLTD method is objective, robust, and effective, and can be easily implemented in the emerging field of computational pathology.

Pathogenic germline CDKN2A variants are associated with an increased risk of pancreatic ductal adenocarcinoma (PDAC). CDKN2A variants of uncertain significance (VUSs) are reported in up to 4.3% of patients with PDAC and result in significant uncertainty for patients and their family members as an unknown fraction are functionally deleterious, and therefore, likely pathogenic. Functional characterization of CDKN2A VUSs is needed to reclassify variants and inform clinical management. Twenty-nine germline CDKN2A VUSs previously reported in patients with PDAC or in ClinVar were evaluated using a validated in vitro cell proliferation assay. Twelve of the 29 CDKN2A VUSs were functionally deleterious (11 VUSs) or potentially functionally deleterious (1 VUS) and were reclassified as likely pathogenic variants. Thus, over 40% of CDKN2A VUSs identified in patients with PDAC are functionally deleterious and likely pathogenic. When incorporating VUSs found to be functionally deleterious, and reclassified as likely pathogenic, the prevalence of pathogenic/likely pathogenic CDKN2A in patients with PDAC reported in the published literature is increased to up to 4.1% of patients, depending on family history. Therefore, CDKN2A VUSs may play a significant, unappreciated role in risk of pancreatic cancer. These findings have significant implications for the counselling and care of patients and their relatives.

This study aims at clarifying the prognostic role of high-grade tumor budding (TB) in pancreatic ductal adenocarcinoma (PDAC) with the first systematic review and meta-analysis on this topic. Furthermore, we analyzed with a systematic review the relationship between TB and a recently suggested TB-associated mechanism: the epithelial to mesenchymal transition (EMT). Analyzing a total of 613 patients, 251 of them (40.9%) with high grade-TB, we found an increased risk of all-cause mortality (RR, 1.46; 95% CI, 1.13⁻1.88, p = 0.004; HR, 2.65; 95% CI, 1.79⁻3.91; p < 0.0001) and of recurrence (RR, 1.61; 95% CI, 1.05⁻2.47, p = 0.03) for PDAC patients with high-grade TB. Moreover, we found that EMT is a central process in determining the presence of TB in PDAC. Thanks to this meta-analysis, we demonstrate the potential clinical significance of high-grade TB for prognostic stratification of PDAC. TB also shows a clear association with the process of EMT. Based on the results of the present study, TB should be conveyed in pathology reports and taken into account by future oncologic staging systems.

High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian cancer and has a poor outcome. It has been proposed that fallopian tube cancers may be precursors of HGSOC but evolutionary evidence for this hypothesis has been limited. Here, we perform whole-exome sequence and copy number analyses of laser capture microdissected fallopian tube lesions (p53 signatures, serous tubal intraepithelial carcinomas (STICs), and fallopian tube carcinomas), ovarian cancers, and metastases from nine patients. The majority of tumor-specific alterations in ovarian cancers were present in STICs, including those affecting TP53, BRCA1, BRCA2 or PTEN. Evolutionary analyses reveal that p53 signatures and STICs are precursors of ovarian carcinoma and identify a window of 7 years between development of a STIC and initiation of ovarian carcinoma, with metastases following rapidly thereafter. Our results provide insights into the etiology of ovarian cancer and have implications for prevention, early detection and therapeutic intervention of this disease.

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated; however, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present a xenotransplantation model of PDAC in which neoplasms originate from patient-derived organoids injected directly into murine pancreatic ducts. Our model enables distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively. Parameters that influence PDAC subtype specification in this intraductal model include cell plasticity and hyperactivation of the RAS pathway. Finally, through intratumoral dissection and the direct manipulation of RAS gene dosage, we identify a suite of RAS-regulated secreted and membrane-bound proteins that may represent potential candidates for therapeutic intervention in patients with PDAC. SIGNIFICANCE: Accurate modeling of the molecular subtypes of pancreatic cancer is crucial to facilitate the generation of effective therapies. We report the development of an intraductal organoid transplantation model of pancreatic cancer that models the progressive switching of subtypes, and identify stochastic and RAS-driven mechanisms that determine subtype specification.See related commentary by Pickering and Morton, p. 1448.This article is highlighted in the In This Issue feature, p. 1426.

A central goal of precision medicine is to predict disease outcomes and design treatments based on multidimensional information from afflicted cells and tissues. Cell morphology is an emergent readout of the molecular underpinnings of a cell's functions and, thus, can be used as a method to define the functional state of an individual cell. We measured 216 features derived from cell and nucleus morphology for more than 30,000 breast cancer cells. We find that single cell-derived clones (SCCs) established from the same parental cells exhibit distinct and heritable morphological traits associated with genomic (ploidy) and transcriptomic phenotypes. Using unsupervised clustering analysis, we find that the morphological classes of SCCs predict distinct tumorigenic and metastatic potentials in vivo using multiple mouse models of breast cancer. These findings lay the groundwork for using quantitative morpho-profiling in vitro as a potentially convenient and economical method for phenotyping function in cancer in vivo.

The vast majority of human pancreatic ductal adenocarcinomas (PDACs) harbor TP53 mutations, underscoring p53's critical role in PDAC suppression. PDAC can arise when pancreatic acinar cells undergo acinar-to-ductal metaplasia (ADM), giving rise to premalignant pancreatic intraepithelial neoplasias (PanINs), which finally progress to PDAC. The occurrence of TP53 mutations in late-stage PanINs has led to the idea that p53 acts to suppress malignant transformation of PanINs to PDAC. However, the cellular basis for p53 action during PDAC development has not been explored in detail. Here, we leverage a hyperactive p53 variant-p5353,54-which we previously showed is a more robust PDAC suppressor than wild-type p53, to elucidate how p53 acts at the cellular level to dampen PDAC development. Using both inflammation-induced and KRASG12D-driven PDAC models, we find that p5353,54 both limits ADM accumulation and suppresses PanIN cell proliferation and does so more effectively than wild-type p53. Moreover, p5353,54 suppresses KRAS signaling in PanINs and limits effects on the extracellular matrix (ECM) remodeling. While p5353,54 has highlighted these functions, we find that pancreata in wild-type p53 mice similarly show less ADM, as well as reduced PanIN cell proliferation, KRAS signaling, and ECM remodeling relative to Trp53-null mice. We find further that p53 enhances chromatin accessibility at sites controlled by acinar cell identity transcription factors. These findings reveal that p53 acts at multiple stages to suppress PDAC, both by limiting metaplastic transformation of acini and by dampening KRAS signaling in PanINs, thus providing key new understanding of p53 function in PDAC.