Somatic loss of ATM is a late event in pancreatic tumorigenesis.

Understanding the timing and spectrum of genetic alterations that contribute to the development of pancreatic cancer is essential for effective interventions and treatments. The aim of this study was to characterize somatic ATM alterations in noninvasive pancreatic precursor lesions and invasive pancreatic adenocarcinomas from patients with and without pathogenic germline ATM variants. DNA was isolated and sequenced from the invasive pancreatic ductal adenocarcinomas and precursor lesions of patients with a pathogenic germline ATM variant. Tumor and precursor lesions from these patients as well as colloid carcinoma from patients without a germline ATM variant were immunolabeled to assess ATM expression. Among patients with a pathogenic germline ATM variant, somatic ATM alterations, either mutations and/or loss of protein expression, were identified in 75.0% of invasive pancreatic adenocarcinomas but only 7.1% of pancreatic precursor lesions. Loss of ATM expression was also detected in 31.0% of colloid carcinomas from patients unselected for germline ATM status, significantly higher than in pancreatic precursor lesions [pancreatic intraepithelial neoplasms (p = 0.0013); intraductal papillary mucinous neoplasms, p = 0.0040] and pancreatic ductal adenocarcinoma (p = 0.0076) unselected for germline ATM status. These data are consistent with the second hit to ATM being a late event in pancreatic tumorigenesis. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Molecular characterization of organoids derived from pancreatic intraductal papillary mucinous neoplasms.

Intraductal papillary mucinous neoplasms (IPMNs) are commonly identified non-invasive cyst-forming pancreatic neoplasms with the potential to progress into invasive pancreatic adenocarcinoma. There are few in vitro models with which to study the biology of IPMNs and their progression to invasive carcinoma. Therefore, we generated a living biobank of organoids from seven normal pancreatic ducts and ten IPMNs. We characterized eight IPMN organoid samples using whole genome sequencing and characterized five IPMN organoids and seven normal pancreatic duct organoids using transcriptome sequencing. We identified an average of 11,344 somatic mutations in the genomes of organoids derived from IPMNs, with one sample harboring 61,537 somatic mutations enriched for T→C transitions and T→A transversions. Recurrent coding somatic mutations were identified in 15 genes, including KRAS, GNAS, RNF43, PHF3, and RBM10. The most frequently mutated genes were KRAS, GNAS, and RNF43, with somatic mutations identified in six (75%), four (50%), and three (37.5%) IPMN organoid samples, respectively. On average, we identified 36 structural variants in IPMN derived organoids, and none had an unstable phenotype (> 200 structural variants). Transcriptome sequencing identified 28 genes differentially expressed between normal pancreatic duct organoid and IPMN organoid samples. The most significantly upregulated and downregulated genes were CLDN18 and FOXA1. Immunohistochemical analysis of FOXA1 expression in 112 IPMNs, 113 mucinous cystic neoplasms, and 145 pancreatic ductal adenocarcinomas demonstrated statistically significant loss of expression in low-grade IPMNs (p < 0.0016), mucinous cystic neoplasms (p < 0.0001), and pancreatic ductal adenocarcinoma of any histologic grade (p < 0.0001) compared to normal pancreatic ducts. These data indicate that FOXA1 loss of expression occurs early in pancreatic tumorigenesis. Our study highlights the utility of organoid culture to study the genetics and biology of normal pancreatic duct and IPMNs. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Prevalence of Germline Mutations Associated With Cancer Risk in Patients With Intraductal Papillary Mucinous Neoplasms.

BACKGROUND & AIMS: Many patients with pancreatic adenocarcinoma carry germline mutations associated with increased risk of cancer. It is not clear whether patients with intraductal papillary mucinous neoplasms (IPMNs), which are precursors to some pancreatic cancers, also carry these mutations. We assessed the prevalence of germline mutations associated with cancer risk in patients with histologically confirmed IPMN. METHODS: We obtained nontumor tissue samples from 315 patients with surgically resected IPMNs from 1997 through 2017, and we sequenced 94 genes with variants associated with cancer risk. Mutations associated with increased risk of cancer were identified and compared with individuals from the Exome Aggregation Consortium. RESULTS: We identified 23 patients with a germline mutation associated with cancer risk (7.3%; 95% confidence interval, 4.9-10.8). Nine patients had a germline mutation associated with pancreatic cancer susceptibility (2.9%; 95% confidence interval, 1.4-5.4). More patients with IPMNs carried germline mutations in ATM (P < .0001), PTCH1 (P < .0001), and SUFU (P < .0001) compared with controls. Patients with IPMNs and germline mutations associated with pancreatic cancer were more like to have concurrent invasive pancreatic carcinoma compared with patients with IPMNs without these mutations (P < .0320). CONCLUSIONS: In sequence analyses of 315 patients with surgically resected IPMNs, we found that almost 3% to carry mutations associated with pancreatic cancer risk. More patients with IPMNs and germline mutations associated with pancreatic cancer had concurrent invasive pancreatic carcinoma compared with patients with IPMNs without these mutations. Genetic analysis of patients with IPMNs might identify those at greatest risk for cancer.

Histomorphology of pancreatic cancer in patients with inherited ATM serine/threonine kinase pathogenic variants.

Germline pathogenic variants in the ATM serine/threonine kinase (ATM) gene are associated with an increased risk of pancreatic ductal adenocarcinoma. It is important to identify germline ATM pathogenic variants in pancreatic cancer patients because these alterations are potentially targetable with chemotherapeutic drugs and/or radiation and have implications for other family members. As germline pathogenic variants in other genes have been associated with distinct histologic subtypes of pancreatic cancer, we studied the histomorphology of pancreatic cancer in 23 patients with germline ATM pathogenic variants. The histologic subtype was ductal adenocarcinoma in 19/23 (83%) of the patients, adenosquamous carcinoma in 1/23 (4%), and colloid (mucinous non-cystic) carcinoma in 3/23 (13%). The percentage of colloid (mucinous non-cystic) carcinomas is higher than we have previously observed in patients with familial and sporadic pancreatic cancer (1 and 2% in prior reports, p < 0.01 and p < 0.01, respectively). Three carcinomas (2 colloid carcinomas, 1 ductal adenocarcinoma) arose in association with intraductal papillary mucinous neoplasms. Among the resected pancreata, non-invasive precursor lesions, including pancreatic intraepithelial neoplasia and incipient intraductal papillary mucinous neoplasms, were identified in 83%. We conclude that pancreatic cancers in patients with germline ATM pathogenic variants are more frequently of colloid (mucinous non-cystic) morphology but are overall morphologically diverse supporting the utility of universal germline genetic testing for patients with pancreatic cancer.

Immunolabeling of Cleared Human Pancreata Provides Insights into Three-Dimensional Pancreatic Anatomy and Pathology.

Visualizing pathologies in three dimensions can provide unique insights into the biology of human diseases. A rapid and easy-to-implement dibenzyl ether-based technique was used to clear thick sections of surgically resected human pancreatic parenchyma. Protocols were applicable to both fresh and formalin-fixed, paraffin-embedded tissue. The penetration of antibodies into dense pancreatic parenchyma was optimized using both gradually increasing antibody concentrations and centrifugal flow. Immunolabeling with antibodies against cytokeratin 19 was visualized using both light sheet and confocal laser scanning microscopy. The technique was applied successfully to 26 sections of pancreas, providing three-dimensional (3D) images of normal pancreatic tissue, pancreatic intraepithelial neoplasia, intraductal papillary mucinous neoplasms, and infiltrating pancreatic ductal adenocarcinomas. 3D visualization highlighted processes that are hard to conceptualize in two dimensions, such as invasive carcinoma growing into what appeared to be pre-existing pancreatic ducts and within venules, and the tracking of long cords of neoplastic cells parallel to blood vessels. Expanding this technique to formalin-fixed, paraffin-embedded tissue opens pathology archives to 3D visualization of unique biosamples and rare diseases. The application of immunolabeling and clearing to human pancreatic parenchyma provides detailed visualization of normal pancreatic anatomy, and can be used to characterize the 3D architecture of diseases including pancreatic intraepithelial neoplasia, intraductal papillary mucinous neoplasm, and pancreatic ductal adenocarcinomas.

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology.

The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

The species coalescent indicates possible bat and pangolin origins of the COVID-19 pandemic.

A consensus species tree is reconstructed from 11 gene trees for human, bat, and pangolin beta coronaviruses from samples taken early in the pandemic (prior to April 1, 2020). Using coalescent theory, the shallow (short branches relative to the hosts) consensus species tree provides evidence of recent gene flow events between bat and pangolin beta coronaviruses predating the zoonotic transfer to humans. The consensus species tree was also used to reconstruct the ancestral sequence of human SARS-CoV-2, which was 2 nucleotides different from the Wuhan sequence. The time to most recent common ancestor was estimated to be Dec 8, 2019 with a bat origin. Some human, bat, and pangolin coronavirus lineages found in China are phylogenetically distinct, a rare example of a class II phylogeography pattern (Avise et al. in Ann Rev Eco Syst 18:489-422, 1987). The consensus species tree is a product of evolutionary factors, providing evidence of repeated zoonotic transfers between bat and pangolin as a reservoir for future zoonotic transfers to humans.

Characterizing the gene-environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics.

Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.

Are we there yet? A machine learning architecture to predict organotropic metastases.

BACKGROUND & AIMS: Cancer metastasis into distant organs is an evolutionarily selective process. A better understanding of the driving forces endowing proliferative plasticity of tumor seeds in distant soils is required to develop and adapt better treatment systems for this lethal stage of the disease. To this end, we aimed to utilize transcript expression profiling features to predict the site-specific metastases of primary tumors and second, to identify the determinants of tissue specific progression. METHODS: We used statistical machine learning for transcript feature selection to optimize classification and built tree-based classifiers to predict tissue specific sites of metastatic progression. RESULTS: We developed a novel machine learning architecture that analyzes 33 types of RNA transcriptome profiles from The Cancer Genome Atlas (TCGA) database. Our classifier identifies the tumor type, derives synthetic instances of primary tumors metastasizing to distant organs and classifies the site-specific metastases in 16 types of cancers metastasizing to 12 locations. CONCLUSIONS: We have demonstrated that site specific metastatic progression is predictable using transcriptomic profiling data from primary tumors and that the overrepresented biological processes in tumors metastasizing to congruent distant loci are highly overlapping. These results indicate site-specific progression was organotropic and core features of biological signaling pathways are identifiable that may describe proliferative plasticity in distant soils.

Wild Isolates of Neurospora crassa Reveal Three Conidiophore Architectural Phenotypes.

The vegetative life cycle in the model filamentous fungus, Neurospora crassa, relies on the development of conidiophores to produce new spores. Environmental, temporal, and genetic components of conidiophore development have been well characterized; however, little is known about their morphological variation. We explored conidiophore architectural variation in a natural population using a wild population collection of 21 strains from Louisiana, United States of America (USA). Our work reveals three novel architectural phenotypes, Wild Type, Bulky, and Wrap, and shows their maintenance throughout the duration of conidiophore development. Furthermore, we present a novel image-classifier using a convolutional neural network specifically developed to assign conidiophore architectural phenotypes in a high-throughput manner. To estimate an inheritance model for this discrete complex trait, crosses between strains of each phenotype were conducted, and conidiophores of subsequent progeny were characterized using the trained classifier. Our model suggests that conidiophore architecture is controlled by at least two genes and has a heritability of 0.23. Additionally, we quantified the number of conidia produced by each conidiophore type and their dispersion distance, suggesting that conidiophore architectural phenotype may impact N. crassa colonization capacity.

Metabolic Reprogramming in Cancer Is Induced to Increase Proton Production.

Considerable metabolic reprogramming has been observed in a conserved manner across multiple cancer types, but their true causes remain elusive. We present an analysis of around 50 such reprogrammed metabolisms (RM) including the Warburg effect, nucleotide de novo synthesis, and sialic acid biosynthesis in cancer. Analyses of the biochemical reactions conducted by these RMs, coupled with gene expression data of their catalyzing enzymes, in 7,011 tissues of 14 cancer types, revealed that all RMs produce more H+ than their original metabolisms. These data strongly support a model that these RMs are induced or selected to neutralize a persistent intracellular alkaline stress due to chronic inflammation and local iron overload. To sustain these RMs for survival, cells must find metabolic exits for the nonproton products of these RMs in a continuous manner, some of which pose major challenges, such as nucleotides and sialic acids, because they are electrically charged. This analysis strongly suggests that continuous cell division and other cancerous behaviors are ways for the affected cells to remove such products in a timely and sustained manner. As supporting evidence, this model can offer simple and natural explanations to a range of long-standing open questions in cancer research including the cause of the Warburg effect. SIGNIFICANCE: Inhibiting acidifying metabolic reprogramming could be a novel strategy for treating cancer.

mTORC1 feedback to AKT modulates lysosomal biogenesis through MiT/TFE regulation.

The microphthalmia family of transcription factors (MiT/TFEs) controls lysosomal biogenesis and is negatively regulated by the nutrient sensor mTORC1. However, the mechanisms by which cells with constitutive mTORC1 signaling maintain lysosomal catabolism remain to be elucidated. Using the murine epidermis as a model system, we found that epidermal Tsc1 deletion resulted in a phenotype characterized by wavy hair and curly whiskers, and was associated with increased EGFR and HER2 degradation. Unexpectedly, constitutive mTORC1 activation with Tsc1 loss increased lysosomal content via upregulated expression and activity of MiT/TFEs, whereas genetic deletion of Rheb or Rptor or prolonged pharmacologic mTORC1 inactivation had the reverse effect. This paradoxical increase in lysosomal biogenesis by mTORC1 was mediated by feedback inhibition of AKT, and a resulting suppression of AKT-induced MiT/TFE downregulation. Thus, inhibiting hyperactive AKT signaling in the context of mTORC1 loss-of-function fully restored MiT/TFE expression and activity. These data suggest that signaling feedback loops work to restrain or maintain cellular lysosomal content during chronically inhibited or constitutively active mTORC1 signaling, respectively, and reveal a mechanism by which mTORC1 regulates upstream receptor tyrosine kinase signaling.