Computational pathology model to assess acute and chronic transformations of the tubulointerstitial compartment in renal allograft biopsies

Managing patients with kidney allografts largely depends on biopsy diagnosis which is based on semiquantitative assessments of rejection features and extent of acute and chronic changes within the renal parenchyma. Current methods lack reproducibility while digital image data-driven computational models enable comprehensive and quantitative assays. In this study we aimed to develop a computational method for automated assessment of histopathology transformations within the tubulointerstitial compartment of the renal cortex. Whole slide images of modified Picrosirius red-stained biopsy slides were used for the training (n = 852) and both internal (n = 172) and external (n = 94) tests datasets. The pipeline utilizes deep learning segmentations of renal tubules, interstitium, and peritubular capillaries from which morphometry features were extracted. Seven indicators were selected for exploring the intrinsic spatial interactions within the tubulointerstitial compartment. A principal component analysis revealed two independent factors which can be interpreted as representing chronic and acute tubulointerstitial injury. A K-means clustering classified biopsies according to potential phenotypes of combined acute and chronic transformations of various degrees. We conclude that multivariate analyses of tubulointerstitial morphometry transformations enable extraction of and quantification of acute and chronic components of injury. The method is developed for renal allograft biopsies; however, the principle can be applied more broadly for kidney pathology assessment.

exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies

Background

Pathology reports contain key information about the patient's diagnosis as well as important gross and microscopic findings. These information-rich clinical reports offer an invaluable resource for clinical studies, but data extraction and analysis from such unstructured texts is often manual and tedious. While neural information retrieval systems (typically implemented as deep learning methods for natural language processing) are automatic and flexible, they typically require a large domain-specific text corpus for training, making them infeasible for many medical subdomains. Thus, an automated data extraction method for pathology reports that does not require a large training corpus would be of significant value and utility.

Objective

To develop a language model-based neural information retrieval system that can be trained on small datasets and validate it by training it on renal transplant-pathology reports to extract relevant information for two predefined questions: (1) "What kind of rejection does the patient show?"; (2) "What is the grade of interstitial fibrosis and tubular atrophy (IFTA)?"

Methods

Kidney BERT was developed by pre-training Clinical BERT on 3.4K renal transplant pathology reports and 1.5M words. Then, exKidneyBERT was developed by extending Clinical BERT's tokenizer with six technical keywords and repeating the pre-training procedure. This extended the model's vocabulary. All three models were fine-tuned with information retrieval heads.

Results

The model with extended vocabulary, exKidneyBERT, outperformed Clinical BERT and Kidney BERT in both questions. For rejection, exKidneyBERT achieved an 83.3% overlap ratio for antibody-mediated rejection (ABMR) and 79.2% for T-cell mediated rejection (TCMR). For IFTA, exKidneyBERT had a 95.8% exact match rate.

Conclusion

ExKidneyBERT is a high-performing model for extracting information from renal pathology reports. Additional pre-training of BERT language models on specialized small domains does not necessarily improve performance. Extending the BERT tokenizer's vocabulary library is essential for specialized domains to improve performance, especially when pre-training on small corpora.

Protein tyrosine phosphatase 1B is a regulator of alpha-actinin4 in the glomerular podocyte

Glomerular podocytes are instrumental for the barrier function of the kidney, and podocyte injury contributes to proteinuria and the deterioration of renal function. Protein tyrosine phosphatase 1B (PTP1B) is an established metabolic regulator, and the inactivation of this phosphatase mitigates podocyte injury. However, there is a paucity of data regarding the substrates that mediate PTP1B actions in podocytes. This study aims to uncover novel substrates of PTP1B in podocytes and validate a leading candidate. To this end, using substrate-trapping and mass spectroscopy, we identified putative substrates of this phosphatase and investigated the actin cross-linking cytoskeletal protein alpha-actinin4. PTP1B and alpha-actinin4 co-localized in murine and human glomeruli and transiently transfected E11 podocyte cells. Additionally, podocyte PTP1B deficiency in vivo and culture was associated with elevated tyrosine phosphorylation of alpha-actinin4. Conversely, reconstitution of the knockdown cells with PTP1B attenuated alpha-actinin4 tyrosine phosphorylation. We demonstrated co-association between alpha-actinin4 and the PTP1B substrate-trapping mutant, which was enhanced upon insulin stimulation and disrupted by vanadate, consistent with an enzyme-substrate interaction. Moreover, we identified alpha-actinin4 tandem tyrosine residues 486/487 as mediators of its interaction with PTP1B. Furthermore, knockdown studies in E11 cells suggest that PTP1B and alpha-actinin4 are modulators of podocyte motility. These observations indicate that PTP1B and alpha-actinin4 are likely interacting partners in a signaling node that modulates podocyte function. Targeting PTP1B and plausibly this one of its substrates may represent a new therapeutic approach for podocyte injury that warrants additional investigation.

Correlating Deep Learning-Based Automated Reference Kidney Histomorphometry with Patient Demographics and Creatinine

Key Points

The authors leverage the unique benefits of panoptic segmentation to perform the largest ever quantitation of reference kidney morphometry. Kidney features vary with age and sex; and glomeruli size may intricately link to creatinine, defying prior notions.

Background

Reference histomorphometric data of healthy human kidneys are largely lacking because of laborious quantitation requirements. Correlating histomorphometric features with clinical parameters through machine learning approaches can provide valuable information about natural population variance. To this end, we leveraged deep learning (DL), computational image analysis, and feature analysis to associate the relationship of histomorphometry with patient age, sex, serum creatinine (SCr), and eGFR in a multinational set of reference kidney tissue sections.

Methods

A panoptic segmentation neural network was developed and used to segment viable and sclerotic glomeruli, cortical and medullary interstitia, tubules, and arteries/arterioles in the digitized images of 79 periodic acid–Schiff-stained human nephrectomy sections showing minimal pathologic changes. Simple morphometrics (e.g. , area, radius, density) were quantified from the segmented classes. Regression analysis aided in determining the association of histomorphometric parameters with age, sex, SCr, and eGFR.

Results

Our DL model achieved high segmentation performance for all test compartments. The size and density of glomeruli, tubules, and arteries/arterioles varied significantly among healthy humans, with potentially large differences between geographically diverse patients. Glomerular size was significantly correlated with SCr and eGFR. Slight, albeit significant, differences in renal vasculature were observed between sexes. Glomerulosclerosis percentage increased, and cortical density of arteries/arterioles decreased, as a function of increasing age.

Conclusions

Using DL, we automated precise measurements of kidney histomorphometric features. In the reference kidney tissue, several histomorphometric features demonstrated significant correlation to patient demographics, SCr, and eGFR. DL tools can increase the efficiency and rigor of histomorphometric analysis.

Correlating Deep Learning-Based Automated Reference Kidney Histomorphometry with Patient Demographics and Creatinine

Background

Reference histomorphometric data of healthy human kidneys are largely lacking due to laborious quantitation requirements. Correlating histomorphometric features with clinical parameters through machine learning approaches can provide valuable information about natural population variance. To this end, we leveraged deep learning, computational image analysis, and feature analysis to investigate the relationship of histomorphometry with patient age, sex, and serum creatinine (SCr) in a multinational set of reference kidney tissue sections.

Methods

A panoptic segmentation neural network was developed and used to segment viable and sclerotic glomeruli, cortical and medullary interstitia, tubules, and arteries/arterioles in the digitized images of 79 periodic acid-Schiff-stained human nephrectomy sections showing minimal pathologic changes. Simple morphometrics (e.g., area, radius, density) were quantified from the segmented classes. Regression analysis aided in determining the relationship of histomorphometric parameters with age, sex, and SCr.

Results

Our deep-learning model achieved high segmentation performance for all test compartments. The size and density of nephrons and arteries/arterioles varied significantly among healthy humans, with potentially large differences between geographically diverse patients. Nephron size was significantly dependent on SCr. Slight, albeit significant, differences in renal vasculature were observed between sexes. Glomerulosclerosis percentage increased, and cortical density of arteries/arterioles decreased, as a function of age.

Conclusions

Using deep learning, we automated precise measurements of kidney histomorphometric features. In the reference kidney tissue, several histomorphometric features demonstrated significant correlation to patient demographics and SCr. Deep learning tools can increase the efficiency and rigor of histomorphometric analysis.

Discovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology

Background

The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice.

Methods

We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidney disease (ESKD) within two years of biopsy. Extending our previously published human-AI-loop pipeline, six renal sub-compartments were computationally segmented from each WSI. Hand-engineered image features for glomeruli and tubules, and urinary protein measurements, were used as inputs to deep-learning frameworks to predict ESKD outcome. Differential expression was correlated with digital image features using the Spearman rank sum coefficient.

Results

A total of 45 urinary proteins were differentially detected in progressors, which was most predictive of ESKD (AUC=0.95), while tubular and glomerular features were less predictive (AUC=0.71 and AUC=0.63, respectively). Accordingly, a correlation map between canonical cell-type proteins, such as epidermal growth factor and secreted phosphoprotein 1, and AI-based image features was obtained, which supports previous pathobiological results.

Conclusions

Computational method-based integration of urinary and image biomarkers may improve the pathophysiological understanding of DN progression as well as carry clinical implications in histopathological evaluation.

Improving quantification of renal fibrosis using Deep-DUET

Accurate quantification of renal fibrosis has profound importance in the assessment of chronic kidney disease (CKD). Visual analysis of a biopsy stained with trichrome under the microscope by a pathologist is the gold standard for evaluation of fibrosis. Trichrome helps to highlight collagen and ultimately interstitial fibrosis. However, trichrome stains are not always reproducible, can underestimate collagen content and are not sensitive to subtle fibrotic patterns. Using the Dual-mode emission and transmission (DUET) microscopy approach, it is possible to capture both brightfield and fluorescence images from the same area of a tissue stained with hematoxylin and eosin (H&E) enabling reproducible extraction of collagen with high sensitivity and specificity. Manual extraction of spectrally overlapping collagen signals from tubular epithelial cells and red blood cells is still an intensive task. We employed a UNet++ architecture for pixel-level segmentation and quantification of collagen using 760 whole slide image (WSI) patches from six cases of varying stages of fibrosis. Our trained model (Deep-DUET) used the supervised extracted collagen mask as ground truth and was able to predict the extent of collagen signal with a MSE of 0.05 in a holdout testing set while achieving an average AUC of 0.94 for predicting regions of collagen deposits. Expanding this work to the level of the WSI can greatly improve the ability of pathologists and machine learning (ML) tools to quantify the extent of renal fibrosis reproducibly and reliably.

From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.

Automated Tubular Morphometric Visualization for Whole Kidney Biopsy

One of the strongest prognostic predictors of chronic kidney disease is interstitial fibrosis and tubular atrophy (IFTA). The ultimate goal of IFTA calculation is an estimation of the functional nephritic area. However, the clinical gold standard of estimation by pathologist is imprecise, primarily due to the overwhelming number of tubules sampled in a standard kidney biopsy. Artificial intelligence algorithms could provide significant benefit in this aspect as their high-throughput could identify and quantitatively measure thousands of tubules in mere minutes. Towards this goal, we use a custom panoptic convolutional network similar to Panoptic-DeepLab to detect tubules from 87 WSIs of biopsies from native diabetic kidneys and transplant kidneys. We measure 206 features on each tubule, including commonly understood features like tubular basement membrane thickness and tubular diameter. Finally, we have developed a tool which allows a user to select a range of tubule morphometric features to be highlighted in corresponding WSIs. The tool can also highlight tubules in WSI leveraging multiple morphometric features through selection of regions-of-interest in a uniform manifold approximation and projection plot.

PodoSighter: A Cloud-Based Tool for Label-Free Podocyte Detection in Kidney Whole-Slide Images

BACKGROUND

Podocyte depletion precedes progressive glomerular damage in several kidney diseases. However, the current standard of visual detection and quantification of podocyte nuclei from brightfield microscopy images is laborious and imprecise.

METHODS

We have developed PodoSighter, an online cloud-based tool, to automatically identify and quantify podocyte nuclei from giga-pixel brightfield whole-slide images (WSIs) using deep learning. Ground-truth to train the tool used immunohistochemically or immunofluorescence-labeled images from a multi-institutional cohort of 122 histologic sections from mouse, rat, and human kidneys. To demonstrate the generalizability of our tool in investigating podocyte loss in clinically relevant samples, we tested it in rodent models of glomerular diseases, including diabetic kidney disease, crescentic GN, and dose-dependent direct podocyte toxicity and depletion, and in human biopsies from steroid-resistant nephrotic syndrome and from human autopsy tissues.

RESULTS

The optimal model yielded high sensitivity/specificity of 0.80/0.80, 0.81/0.86, and 0.80/0.91, in mouse, rat, and human images, respectively, from periodic acid-Schiff-stained WSIs. Furthermore, the podocyte nuclear morphometrics extracted using PodoSighter were informative in identifying diseased glomeruli. We have made PodoSighter freely available to the general public as turnkey plugins in a cloud-based web application for end users.

CONCLUSIONS

Our study demonstrates an automated computational approach to detect and quantify podocyte nuclei in standard histologically stained WSIs, facilitating podocyte research, and enabling possible future clinical applications.

Automated Computational Detection of Interstitial Fibrosis, Tubular Atrophy, and Glomerulosclerosis

BACKGROUND

Interstitial fibrosis, tubular atrophy (IFTA), and glomerulosclerosis are indicators of irrecoverable kidney injury. Modern machine learning (ML) tools have enabled robust, automated identification of image structures that can be comparable with analysis by human experts. ML algorithms were developed and tested for the ability to replicate the detection and quantification of IFTA and glomerulosclerosis that renal pathologists perform.

METHODS

A renal pathologist annotated renal biopsy specimens from 116 whole-slide images (WSIs) for IFTA and glomerulosclerosis. A total of 79 WSIs were used for training different configurations of a convolutional neural network (CNN), and 17 and 20 WSIs were used as internal and external testing cases, respectively. The best model was compared against the input of four renal pathologists on 20 new testing slides. Further, for 87 testing biopsy specimens, IFTA and glomerulosclerosis measurements made by pathologists and the CNN were correlated to patient outcome using classic statistical tools.

RESULTS

The best average performance across all image classes came from a DeepLab version 2 network trained at 40× magnification. IFTA and glomerulosclerosis percentages derived from this CNN achieved high levels of agreement with four renal pathologists. The pathologist- and CNN-based analyses of IFTA and glomerulosclerosis showed statistically significant and equivalent correlation with all patient-outcome variables.

CONCLUSIONS

ML algorithms can be trained to replicate the IFTA and glomerulosclerosis assessment performed by renal pathologists. This suggests computational methods may be able to provide a standardized approach to evaluate the extent of chronic kidney injury in situations in which renal-pathologist time is restricted or unavailable.

A Distributed System Improves Inter-Observer and AI Concordance in Annotating Interstitial Fibrosis and Tubular Atrophy

Histologic examination of interstitial fibrosis and tubular atrophy (IFTA) is critical to determine the extent of irreversible kidney injury in renal disease. The current clinical standard involves pathologist's visual assessment of IFTA, which is prone to inter-observer variability. To address this diagnostic variability, we designed two case studies (CSs), including seven pathologists, using HistomicsTK- a distributed system developed by Kitware Inc. (Clifton Park, NY). Twenty-five whole slide images (WSIs) were classified into a training set of 21 and a validation set of four. The training set was composed of seven unique subsets, each provided to an individual pathologist along with four common WSIs from the validation set. In CS 1, all pathologists individually annotated IFTA in their respective slides. These annotations were then used to train a deep learning algorithm to computationally segment IFTA. In CS 2, manual and computational annotations from CS 1 were first reviewed by the annotators to improve concordance of IFTA annotation. Both the manual and computational annotation processes were then repeated as in CS1. The inter-observer concordance in the validation set was measured by Krippendorff's alpha (KA). The KA for the seven pathologists in CS1 was 0.62 with CI [0.57, 0.67], and after reviewing each other's annotations in CS2, 0.66 with CI [0.60, 0.72]. The respective CS1 and CS2 KA were 0.58 with CI [0.52, 0.64] and 0.63 with CI [0.56, 0.69] when including the deep learner as an eighth annotator. These results suggest that our designed annotation framework refines agreement of spatial annotation of IFTA and demonstrates a human-AI approach to significantly improve the development of computational models.

Automated detection and quantification of Wilms' Tumor 1-positive cells in murine diabetic kidney disease

In diabetic kidney disease (DKD), podocyte depletion, and the subsequent migration of parietal epithelial cells (PECs) to the tuft, is a precursor to progressive glomerular damage, but the limitations of brightfield microscopy currently preclude direct pathological quantitation of these cells. Here we present an automated approach to podocyte and PEC detection developed using kidney sections from mouse model emulating DKD, stained first for Wilms' Tumor 1 (WT1) (podocyte and PEC marker) by immunofluorescence, then post-stained with periodic acid-Schiff (PAS). A generative adversarial network (GAN)-based pipeline was used to translate these PAS-stained sections into WT1-labeled IF images, enabling in silico label-free podocyte and PEC identification in brightfield images. Our method detected WT1-positive cells with high sensitivity/specificity (0.87/0.92). Additionally, our algorithm performed with a higher Cohen's kappa (0.85) than the average manual identification by three renal pathologists (0.78). We propose that this pipeline will enable accurate detection of WT1-positive cells in research applications.

In Silico Multi-Compartment Detection Based on Multiplex Immunohistochemical Staining in Renal Pathology

With the rapid advancement in multiplex tissue staining, computer hardware, and machine learning, computationally-based tools are becoming indispensable for the evaluation of digital histopathology. Historically, standard histochemical staining methods such as hematoxylin and eosin, periodic acid-Schiff, and trichrome have been the gold standard for microscopic tissue evaluation by pathologists, and therefore brightfield microscopy images derived from such stains are primarily used for developing computational pathology tools. However, these histochemical stains are nonspecific in terms of highlighting structures and cell types. In contrast, immunohistochemical stains use antibodies to specifically detect and quantify proteins, which can be used to specifically highlight structures and cell types of interest. Traditionally, such immunofluorescence-based methods are only able to simultaneously stain a limited number of target proteins/antigens, typically up to three channels. Fluorescence-based multiplex immunohistochemistry (mIHC) is a new technology that enables simultaneous localization and quantification of numerous proteins/antigens, allowing for the possibility to detect a wide range of histologic structures and cell types within tissue. However, this method is limited by cost, specialized equipment, technical expertise, and time. In this study, we implemented a deep learning-based pipeline to synthetically generate in silico mIHC images from brightfield images of tissue slides-stained with routinely used histochemical stains, in particular PAS. Our tool was trained using fluorescence-based mIHC images as the ground-truth. The proposed pipeline offers high contrast detection of structures in brightfield imaged tissue sections stained with standard histochemical stains. We demonstrate the performance of our pipeline by computationally detecting multiple compartments in kidney biopsies, including cell nuclei, collagen/fibrosis, distal tubules, proximal tubules, endothelial cells, and leukocytes, from PAS-stained tissue sections. Our work can be extended for other histologic structures and tissue types and can be used as a basis for future automated annotation of histologic structures and cell types without the added cost of actually generating mIHC slides.

COVID-19 Manifesting as Renal Allograft Dysfunction, Acute Pancreatitis, and Thrombotic Microangiopathy: A Case Report

Coronavirus disease 2019 (COVID-19) is associated with high morbidity and mortality worldwide in both the general population and kidney transplant recipients. Acute kidney injury is a known complication of COVID-19 and appears to most commonly manifest as acute tubular injury on renal biopsy. Coagulopathy associated with COVID-19 is a known but poorly understood complication that has been reported to cause thrombotic microangiopathy on rare occasions in native kidneys of patients with COVID-19. Here, we report the first case of biopsy-proven thrombotic microangiopathy in a kidney transplant recipient with COVID-19 who developed acute pancreatitis and clinical features of microangiopathic hemolytic anemia. The patient recovered with supportive care alone.

Tonsillar Kaposi sarcoma in a renal transplant patient

Kaposi sarcoma (KS) is a vascular neoplasm caused by human herpesvirus-8 (HHV-8) infection. KS is most often seen in individuals with acquired immunodeficiency syndrome but can occur in patients who are on immunosuppressive therapy. While the skin and oral mucosa are the typical sites for KS, lesions of the tonsil are quite rare with only a few reported cases. Here, we present a case of tonsillar KS occurring in a renal transplant patient. He presented with dysphagia, odynophagia, and weight loss. Oral examination revealed tonsillar hypertrophy with purple discoloration. Imaging revealed diffuse enlargement of Waldeyer's ring with enlarged right cervical lymph nodes, worrisome for post-transplant lymphoproliferative disorder. Microscopic examination of the tonsillectomy specimen showed a vascular proliferation positive for HHV-8, consistent with KS. The patient was subsequently treated with immunosuppression reduction and the addition of sirolimus, which resulted in complete resolution of oropharyngeal and cervical lesions.

Anti-Cancer Activity of PAK4/NAMPT Inhibitor and Programmed Cell Death Protein-1 Antibody in Kidney Cancer

BACKGROUND

Kidney cancer (or renal cell carcinoma, RCC) is the sixth most common malignancy in the United States and is increasing in incidence. Despite new therapies, including targeted therapies and immunotherapies, most RCCs are resistant to treatment. Thus, several laboratories have been evaluating new approaches to therapy, both with single agents as well as combinations. Although we have previously shown efficacy of the dual PAK4/nicotinamide phosphoribosyltransferase (NAMPT) inhibitor KPT-9274, and the immune checkpoint inhibitors (CPI) have shown utility in the clinic, there has been no evaluation of this combination either clinically or in an immunocompetent animal model of kidney cancer.

METHODS

In this study, we use the renal cell adenocarcinoma (RENCA) model of spontaneous murine kidney cancer. Male BALB/cJ mice were injected subcutaneously with RENCA cells and, after tumors were palpable, they were treated with KPT-9274 and/or anti-programmed cell death 1 (PDCD1; PD1) antibody for 21 days. Tumors were measured and then removed at animal euthanasia for subsequent studies.

RESULTS

We demonstrate a significant decrease in allograft growth with the combination treatment of KPT-9274 and anti-PD1 antibody without significant weight loss by the animals. This is associated with decreased (MOUSE) Naprt expression, indicating dependence of these tumors on NAMPT in parallel to what we have observed in human RCC. Histology of the tumors showed substantial necrosis regardless of treatment condition, and flow cytometry of antibody-stained tumor cells revealed that the enhanced therapeutic effect of KPT-9274 and anti-PD1 antibody was not driven by infiltration of T cells into tumors.

CONCLUSIONS

This study highlights the potential of the RENCA model for evaluating immunologic responses to KPT-9274 and checkpoint inhibitor (CPI) and suggests that therapy with this combination could improve efficacy in RCC beyond what is achievable with CPI alone.

Abstract A23: A second site KrasG12D mutation that impairs PI3K binding rescues embryonic lethality, abrogates myeloproliferative disease, and delays lung tumorigenesis

Phosphatidylinositol 3-kinase (PI3K) signaling is essential for RAS-driven transformation. To directly investigate the role of oncogenic K-Ras binding to PI3K in development and tumorigenesis, we generated KrasG12D/+,Y64G/+ mice that express, from the endogenous locus, a K-Ras oncoprotein that also contains a “second site” amino acid substitution at tyrosine 64 (Y64G) that disrupts the interaction between oncogenic K-Ras and PI3K. Surprisingly, KrasG12D,Y64G mice are viable, fertile, and phenotypically unremarkable, although they are born at a lower than expected Mendelian frequency (26% versus the expected 50% on a C57BL/6 strain background). As opposed to the enhanced proliferative rate observed in mouse embryonic fibroblasts (MEFs) from K-RasG12D mice, KrasG12D,Y64G MEFs exhibit wild-type rates of proliferation. Detailed analysis of the hematopoietic compartment in KrasG12D,Y64G mice reveals a reduced proportion of long-term hematopoietic stem cells, but no evidence of the aggressive myeloproliferative neoplasm observed when a conditional mutant KrasG12D is activated in hematopoietic cells. Consistent with these observations, bone marrow cells isolated from K-RasG12D,Y64G mice exhibit a normal pattern of myeloid progenitor colony growth in response to cytokine stimulation. In contrast to the lack of observed hematologic malignancy, 100% of KrasG12D,Y64G mice we examined at 1 year of age showed lung lesions, ultimately succumbing to lung tumors with a median survival of 496 days. Despite the ubiquitous KrasG12D,Y64G expression, these mice survive longer than models with mosaic, adenoviral-Cre recombinase-controlled KrasG12D (median survival of 185 days). The majority of the lung lesions that arise in KrasG12D, Y64G mice are low grade, classified pathologically as atypical lymphoid proliferation or papillary adenomas; a few adenocarcinomas are also observed. These studies reinforce the importance of oncogenic KRas-mediated activation of PI3K for transformation and demonstrate that expressing a Y64G amino acid substitution in the context of oncogenic KrasG12D normalizes cell proliferation, rescues embryonic lethality, abrogates myeloid disease, and attenuates lung tumorigenesis. Beyond the bone marrow and lung, this mutant strain is a potent genetic tool for dissecting the role of aberrant PI3K signaling in pancreatic, colon, and other tissues characterized by tumors driven by somatic KRAS mutations, and also have implications for treating human cancers with KRAS mutations.

Citation Format: Jasmine C. Wong, Pedro A. Perez-Mancera, Jangkyung Kim, Kuang-Yu Jen, Scott C. Kogan, Ari J. Firestone, Eric A. Collisson, David A. Tuveson, Kevin Shannon. A second site KrasG12D mutation that impairs PI3K binding rescues embryonic lethality, abrogates myeloproliferative disease, and delays lung tumorigenesis [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr A23.

Digital Whole Slide Imaging Compared With Light Microscopy for Primary Diagnosis in Surgical Pathology

Context.—

The adoption of digital capture of pathology slides as whole slide images (WSI) for educational and research applications has proven utility.

Objective.—

To compare pathologists' primary diagnoses derived from WSI versus the standard microscope. Because WSIs differ in format and method of observation compared with the current standard glass slide microscopy, this study is critical to potential clinical adoption of digital pathology.

Design.—

The study enrolled a total of 2045 cases enriched for more difficult diagnostic categories and represented as 5849 slides were curated and provided for diagnosis by a team of 19 reading pathologists separately as WSI or as glass slides viewed by light microscope. Cases were reviewed by each pathologist in both modalities in randomized order with a minimum 31-day washout between modality reads for each case. Each diagnosis was compared with the original clinical reference diagnosis by an independent central adjudication review.

Results.—

The overall major discrepancy rates were 3.64% for WSI review and 3.20% for manual slide review diagnosis methods, a difference of 0.44% (95% CI, −0.15 to 1.03). The time to review a case averaged 5.20 minutes for WSI and 4.95 minutes for glass slides. There was no specific subset of diagnostic category that showed higher rates of modality-specific discrepancy, though some categories showed greater discrepancy than others in both modalities.

Conclusions.—

WSIs are noninferior to traditional glass slides for primary diagnosis in anatomic pathology.

Generative modeling for label-free glomerular modeling and classification

Generative modeling using GANs has gained traction in machine learning literature, as training does not require labeled datasets. This is perfect for applications in biological datasets, where large labeled datasets are often difficult and expensive to acquire. However, generative models offer no easy way to encode real images into feature-sets, something that is desirable for network explainability and may yield potentially informative image features. For this reason, we test a VAE-GAN architecture for label-free modeling of glomerular structural features. We show that this network can generate realistic looking synthetic images, and be used to interpolate between images. To prove the biological relevance of the network encodings, we classify small-labeled sets of encoded glomeruli by biopsy Tervaert class and for the presence of sclerosis, obtaining a Cohen's kappa values of 0.87 and 0.78 respectfully.

Probabilistic modeling of Diabetic Nephropathy progression

Diabetic Nephropathy (DN) progression is stratified into several stages with different levels of proteinuria, albuminuria, and physical characteristics as observed by pathologists. These physical changes are primarily visible within a patient's glomeruli which function as filtration units for blood returning for oxygenation. As DN stage increases, it is possible to observe the thickening of the glomerular basement membrane, expansion of the mesangium, and development of nodular sclerosis. Classification of different stages of DN by pathologists is based on semi-qualitative assessments of these characteristics on an individual glomerulus basis. Being able to probabilistically infer stage membership of individual glomeruli based on a combination of easily observable and hidden image features would be an invaluable tool for furthering our understanding of the drivers of DN progression. Markov Particle filters, included in the bnlearn package in R, were used to query a Bayesian Network (BN) constructed using the structural Hill-Climbing algorithm on a set of glomerular features. These features included both traditional characteristics such as glomerular area and number of mesangial nuclei as well as more abstract features derived from Minimum Spanning Trees (MST) to quantify spatial distribution of mesangial nuclei. Our results using images from multiple institutions suggest that these abstract features exercise a variable influence on DN stage membership over the course of disease progression. Further research incorporating clinical data will give nephrologists a "white box" visual of quantitative factors present in DN patients.

Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice

Ionising radiation (IR) is a recognised carcinogen responsible for cancer development in patients previously treated using radiotherapy, and in individuals exposed as a result of accidents at nuclear energy plants. However, the mutational signatures induced by distinct types and doses of radiation are unknown. Here, we analyse the genetic architecture of mammary tumours, lymphomas and sarcomas induced by high (56Fe-ions) or low (gamma) energy radiation in mice carrying Trp53 loss of function alleles. In mammary tumours, high-energy radiation is associated with induction of focal structural variants, leading to genomic instability and Met amplification. Gamma-radiation is linked to large-scale structural variants and a point mutation signature associated with oxidative stress. The genomic architecture of carcinomas, sarcomas and lymphomas arising in the same animals are significantly different. Our study illustrates the complex interactions between radiation quality, germline Trp53 deficiency and tissue/cell of origin in shaping the genomic landscape of IR-induced tumours.

Dual-mode emission and transmission microscopy for virtual histochemistry using hematoxylin- and eosin-stained tissue sections

In the clinical practice of pathology, trichrome stains are commonly used to highlight collagen and to help evaluate fibrosis. Such stains do delineate collagen deposits but are not molecularly specific and can suffer from staining inconsistencies. Moreover, performing histochemical stain evaluation requires the preparation of additional sections beyond the original hematoxylin- and eosin-stained slides, as well as additional staining steps, which together add cost, time, and workflow complications. We have developed a new microscopy approach, termed DUET (DUal-mode Emission and Transmission) that can be used to extract signals that would typically require special stains or advanced optical methods. Our preliminary analysis demonstrates the potential of using the resulting signals to generate virtual histochemical images that resemble trichrome-stained slides and can support clinical evaluation. We demonstrate advantages of this approach over images acquired from conventional trichrome-stained slides and compare them with images created using second harmonic generation microscopy.

Diverse tumour susceptibility in Collaborative Cross mice: identification of a new mouse model for human gastric tumourigenesis

OBJECTIVE

The Collaborative Cross (CC) is a mouse population model with diverse and reproducible genetic backgrounds used to identify novel disease models and genes that contribute to human disease. Since spontaneous tumour susceptibility in CC mice remains unexplored, we assessed tumour incidence and spectrum.

DESIGN

We monitored 293 mice from 18 CC strains for tumour development. Genetic association analysis and RNA sequencing were used to identify susceptibility loci and candidate genes. We analysed genomes of patients with gastric cancer to evaluate the relevance of genes identified in the CC mouse model and measured the expression levels of ISG15 by immunohistochemical staining using a gastric adenocarcinoma tissue microarray. Association of gene expression with overall survival (OS) was assessed by Kaplan-Meier analysis.

RESULTS

CC mice displayed a wide range in the incidence and types of spontaneous tumours. More than 40% of CC036 mice developed gastric tumours within 1 year. Genetic association analysis identified Nfκb1 as a candidate susceptibility gene, while RNA sequencing analysis of non-tumour gastric tissues from CC036 mice showed significantly higher expression of inflammatory response genes. In human gastric cancers, the majority of human orthologues of the 166 mouse genes were preferentially altered by amplification or deletion and were significantly associated with OS. Higher expression of the CC036 inflammatory response gene signature is associated with poor OS. Finally, ISG15 protein is elevated in gastric adenocarcinomas and correlated with shortened patient OS.

CONCLUSIONS

CC strains exhibit tremendous variation in tumour susceptibility, and we present CC036 as a spontaneous laboratory mouse model for studying human gastric tumourigenesis.

Computational Segmentation and Classification of Diabetic Glomerulosclerosis

BACKGROUND

Pathologists use visual classification of glomerular lesions to assess samples from patients with diabetic nephropathy (DN). The results may vary among pathologists. Digital algorithms may reduce this variability and provide more consistent image structure interpretation.

METHODS

We developed a digital pipeline to classify renal biopsies from patients with DN. We combined traditional image analysis with modern machine learning to efficiently capture important structures, minimize manual effort and supervision, and enforce biologic prior information onto our model. To computationally quantify glomerular structure despite its complexity, we simplified it to three components consisting of nuclei, capillary lumina and Bowman spaces; and Periodic Acid-Schiff positive structures. We detected glomerular boundaries and nuclei from whole slide images using convolutional neural networks, and the remaining glomerular structures using an unsupervised technique developed expressly for this purpose. We defined a set of digital features which quantify the structural progression of DN, and a recurrent network architecture which processes these features into a classification.

RESULTS

Our digital classification agreed with a senior pathologist whose classifications were used as ground truth with moderate Cohen's kappa κ = 0.55 and 95% confidence interval [0.50, 0.60]. Two other renal pathologists agreed with the digital classification with κ₁ = 0.68, 95% interval [0.50, 0.86] and κ₂ = 0.48, 95% interval [0.32, 0.64]. Our results suggest computational approaches are comparable to human visual classification methods, and can offer improved precision in clinical decision workflows. We detected glomerular boundaries from whole slide images with 0.93±0.04 balanced accuracy, glomerular nuclei with 0.94 sensitivity and 0.93 specificity, and glomerular structural components with 0.95 sensitivity and 0.99 specificity.

CONCLUSIONS

Computationally derived, histologic image features hold significant diagnostic information that may augment clinical diagnostics.

Identification of high-risk human papillomavirus and Rb/E2F pathway genomic alterations in mutually exclusive subsets of colorectal neuroendocrine carcinoma

Colorectal neuroendocrine carcinomas, both small cell and large cell types, are highly aggressive tumors with poor prognosis compared with colorectal adenocarcinoma. The molecular drivers of neuroendocrine carcinoma are best defined in small cell lung cancer, which shows near-universal genomic alterations in TP53 and RB1. The genetics of colorectal neuroendocrine carcinoma remain poorly understood; recent studies demonstrated infrequent RB1 alterations and genetics closely resembling colorectal adenocarcinoma. To better define the molecular pathogenesis of colorectal neuroendocrine carcinoma, we performed capture-based next-generation sequencing on 25 cases and evaluated for expression of p53, Rb, p16, and high-risk human papillomavirus (HR-HPV) subtypes using immunohistochemistry, in situ hybridization, and polymerase chain reaction. Rb/E2F pathway dysregulation was identified in nearly all cases (23/25, 92%) and occurred via three distinct mechanisms. First, RB1 genomic alteration was present in 56% (14/25) of cases and was accompanied by Rb protein loss, high p16 expression, and absence of HR-HPV; these cases also had frequent genomic alterations in TP53, the PI3K/Ras and Wnt pathways, as well as in DNA repair genes, with 4/14 cases being hypermutated. Second, 16% (4/25) of cases, all left-sided, had TP53 alteration without RB1 alteration; half of these harbored high-level amplifications in CCNE1 and MYC or MYCN and arose in patients with ulcerative colitis. Finally, 28% (7/25) of cases, all rectal or anal, lacked genomic alterations in RB1 or TP53 but were positive for HR-HPV. Our data demonstrate that Rb/E2F pathway dysregulation is essential in the pathogenesis of colorectal neuroendocrine carcinoma, akin to neuroendocrine carcinomas in other anatomic sites. Moreover, colorectal neuroendocrine carcinomas stratify into three distinct molecular subgroups, which can be differentiated based on Rb protein and HR-HPV status. HR-HPV infection represents a distinct mechanism for Rb and p53 inactivation in cases lacking genomic alterations in either gene. Differential treatment strategies for hypermutated and HPV-driven cases could improve patient outcomes.

Examining Structural Patterns and Causality in Diabetic Nephropathy using inter-Glomerular Distance and Bayesian Graphical Models

In diabetic nephropathy (DN), hyperglycemia drives a progressive thickening of glomerular filtration surfaces, increased cell proliferation as well as mesangial expansion and a constriction of capillary lumens. This leads to progressive structural changes inside the Glomeruli. In this work, we make a study of structural glomerular changes in DN from a graph-theoretic standpoint, using features extracted from Minimal Spanning Trees (MSTs) constructed over intercellular distances in order to classify the "packing signatures" of different DN stages. We further investigate the significance of the competing effects of Volume change measured here in 2Dimensional Pixel span area (Area) on one hand and increased cell proliferation on the other in determining the packing patterns. Towards that we formulate the problem as Dynamic Bayesian Network (DBN). From our preliminary results we do postulate that volume expansion caused by internal pressure as capillary lumens constriction has perhaps has a greater effect in the early stages.

An integrated iterative annotation technique for easing neural network training in medical image analysis

Neural networks promise to bring robust, quantitative analysis to medical fields. However, their adoption is limited by the technicalities of training these networks and the required volume and quality of human-generated annotations. To address this gap in the field of pathology, we have created an intuitive interface for data annotation and the display of neural network predictions within a commonly used digital pathology whole-slide viewer. This strategy used a 'human-in-the-loop' to reduce the annotation burden. We demonstrate that segmentation of human and mouse renal micro compartments is repeatedly improved when humans interact with automatically generated annotations throughout the training process. Finally, to show the adaptability of this technique to other medical imaging fields, we demonstrate its ability to iteratively segment human prostate glands from radiology imaging data.

No difference in 4-nitroquinoline induced tumorigenesis between germ-free and colonized mice

Variations in oral bacterial communities have been linked to oral cancer suggesting that the oral microbiome is an etiological factor that can influence oral cancer development. The 4-nitroquinoline 1-oxide (4-NQO)-induced murine oral and esophageal cancer model is frequently used to assess the effects of preventive and/or therapeutic agents. We used this model to assess the impact of the microbiome on tumorigenesis using axenic (germ-free) and conventionally housed mice. Increased toxicity was observed in germ-free mice, however, no difference in tumor incidence, multiplicity, and size was observed. Transcriptional profiling of liver tissue from germ-free and conventionally housed mice identified 254 differentially expressed genes including ten cytochrome p450 enzymes, the largest family of phase-1 drug metabolizing enzymes in the liver. Gene ontology revealed that differentially expressed genes were enriched for liver steatosis, inflammation, and oxidative stress in livers of germ-free mice. Our observations emphasize the importance of the microbiome in mediating chemical toxicity at least in part by altering host gene expression. Studies on the role of the microbiome in chemical-induced cancer using germ-free animal models should consider the potential difference in dose due to the microbiome-mediated changes in host metabolizing capacity, which might influence the ability to draw conclusions especially for tumor induction models that are dose dependent.

Arginine reprogramming in ADPKD results in arginine-dependent cystogenesis

Research into metabolic reprogramming in cancer has become commonplace, yet this area of research has only recently come of age in nephrology. In light of the parallels between cancer and autosomal dominant polycystic kidney disease (ADPKD), the latter is currently being studied as a metabolic disease. In clear cell renal cell carcinoma (RCC), which is now considered a metabolic disease, we and others have shown derangements in the enzyme arginosuccinate synthase 1 (ASS1), resulting in RCC cells becoming auxotrophic for arginine and leading to a new therapeutic paradigm involving reducing extracellular arginine. Based on our earlier finding that glutamine pathways are reprogrammed in ARPKD, and given the connection between arginine and glutamine synthetic pathways via citrulline, we investigated the possibility of arginine reprogramming in ADPKD. We now show that, in a remarkable parallel to RCC, ASS1 expression is reduced in murine and human ADPKD, and arginine depletion results in a dose-dependent compensatory increase in ASS1 levels as well as decreased cystogenesis in vitro and ex vivo with minimal toxicity to normal cells. Nontargeted metabolomics analysis of mouse kidney cell lines grown in arginine-deficient versus arginine-replete media suggests arginine-dependent alterations in the glutamine and proline pathways. Thus, depletion of this conditionally essential amino acid by dietary or pharmacological means, such as with arginine-degrading enzymes, may be a novel treatment for this disease.

Short-term early exposure to thirdhand cigarette smoke increases lung cancer incidence in mice

Exposure to thirdhand smoke (THS) is a recently described health concern that arises in many indoor environments. However, the carcinogenic potential of THS, a critical consideration in risk assessment, remains untested. Here we investigated the effects of short-term early exposure to THS on lung carcinogenesis in A/J mice. Forty weeks after THS exposure from 4 to 7 weeks of age, the mice had increased incidence of lung adenocarcinoma, tumor size and, multiplicity, compared with controls. In vitro studies using cultured human lung cancer cells showed that THS exposure induced DNA double-strand breaks and increased cell proliferation and colony formation. RNA sequencing analysis revealed that THS exposure induced endoplasmic reticulum stress and activated p53 signaling. Activation of the p53 pathway was confirmed by an increase in its targets p21 and BAX. These data indicate that early exposure to THS is associated with increased lung cancer risk.

Hepatic steatosis after pediatric liver transplant

Hepatic steatosis develops after liver transplantation (LT) in 30% of adults, and nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in nontransplanted children. However, posttransplant steatosis has been minimally studied in pediatric LT recipients. We explored the prevalence, persistence, and association with chronic liver damage of hepatic steatosis in these children. In this single-center study of pediatric patients transplanted 1988-2015 (n = 318), 31% of those with any posttransplant biopsy (n = 271) had ≥ 1 biopsy with steatosis. Median time from transplant to first biopsy with steatosis was 0.8 months (interquartile range [IQR], 0.3-6.5 months) and to last biopsy with steatosis was 5.5 months (IQR, 1.0-24.5 months); 85% of patients with steatosis also had for-cause biopsies without steatosis. All available for-cause biopsies were re-evaluated (n = 104). Of 9 biopsies that could be interpreted as nonalcoholic steatohepatitis (NASH)/borderline NASH, with steatosis plus inflammation or ballooning, 8 also had features of cholestasis or rejection. Among 70 patients with surveillance biopsies 3.6-20.0 years after transplant, only 1 overweight adolescent had a biopsy with NAFLD (grade 1 steatosis, mild inflammation, no ballooning or fibrosis)-despite a 30% prevalence of overweight/obesity in the cohort and 27% with steatosis on previous for-cause biopsy. Steatosis on preceding for-cause biopsy was not associated with portal (P = 0.49) or perivenular fibrosis (P = 0.85) on surveillance biopsy. Hepatic steatosis commonly develops early after transplant in children and adolescents, but it rarely persists. Biopsies that did have steatosis with NASH characteristics were all for-cause, mostly in patients with NAFLD risk factors and/or confounding causes of liver damage. Prospective studies that follow children into adulthood will be needed to evaluate if and when hepatic steatosis presents a longterm risk for pediatric LT recipients. Liver Transplantation 23 957-967 2017 AASLD.

MET Exon 14 Mutation Encodes an Actionable Therapeutic Target in Lung Adenocarcinoma

Targeting somatically activated oncogenes has revolutionized the treatment of non-small cell lung cancer (NSCLC). Mutations in the gene mesenchymal-epithelial transition (MET) near the exon 14 splice sites are recurrent in lung adenocarcinoma and cause exon skipping (METΔ14). Here, we analyzed 4,422 samples from 12 different malignancies to estimate the rate of said exon skipping. METΔ14 mutation and transcript were most common in lung adenocarcinoma. Endogenously expressed levels of METΔ14 transformed human epithelial lung cells in a hepatocyte growth factor-dependent manner. In addition, overexpression of the orthologous mouse allele induced lung adenocarcinoma in a novel, immunocompetent mouse model. Met inhibition showed clinical benefit in this model. In addition, we observed a clinical response to crizotinib in a patient with METΔ14-driven NSCLC, only to observe new missense mutations in the MET activation loop, critical for binding to crizotinib, upon clinical progression. These findings support genomically selected clinical trials directed toward METΔ14 in a fraction of NSCLC patients, confirm second-site mutations for further therapeutic targeting prior to and beyond acquired resistance, and provide an in vivo system for the study of METΔ14 in an immunocompetent host. Cancer Res; 77(16); 4498-505. ©2017 AACR.

Whole exome and targeted deep sequencing identify genome-wide allelic loss and frequent SETDB1 mutations in malignant pleural mesotheliomas

Malignant pleural mesothelioma (MPM), a rare malignancy with a poor prognosis, is mainly caused by exposure to asbestos or other organic fibers, but the underlying genetic mechanism is not fully understood. Genetic alterations and causes for multiple primary cancer development including MPM are unknown. We used whole exome sequencing to identify somatic mutations in a patient with MPM and two additional primary cancers who had no evidence of venous, arterial, lymphovascular, or perineural invasion indicating dissemination of a primary lung cancer to the pleura. We found that the MPM had R282W, a key TP53 mutation, and genome-wide allelic loss or loss of heterozygosity, a distinct genomic alteration not previously described in MPM. We identified frequent inactivating SETDB1 mutations in this patient and in 68 additional MPM patients (mutation frequency: 10%, 7/69) by targeted deep sequencing. Our observations suggest the possibility of a new genetic mechanism in the development of either MPM or multiple primary cancers. The frequent SETDB1 inactivating mutations suggest there could be new diagnostic or therapeutic options for MPM.

Abstract 108: Whole exome and targeted deep sequencing identify genome-wide allelic loss and frequent SETDB1 mutations in malignant pleural mesotheliomas

Malignant pleural mesothelioma (MPM) is a rare malignancy with a highly unfavorable prognosis. A strong link has been established between increased risk for MPM and exposure to asbestos or erionite. As asbestos had widely been used in different industries, the incidence of MPM in the United States is expected to steadily rise and peak with about 70,000 new MPM cases over the next 20 years. Median survival has ranged from 10-17 months. But the underlying genetic mechanism is not fully understood. Moreover, genetic alterations and causes for multiple primary cancer development including MPM are unknown.

We used whole exome sequencing to identify somatic mutations in a patient with MPM and two additional primary cancers who had no evidence of venous, arterial, lymphovascular, or perineural invasion indicating dissemination of a primary lung cancer to the pleura. The development of multiple primary malignancies including a rare MPM led us to search for underlying genetic alterations. Interestingly, most mutations identified in the MPM patient were highly enriched for the mutant allele, suggesting a homozygous alteration or deletion of wild-type allele when minimal contamination of normal pleura in the MPM is taken into consideration. We found that most variants identified showed a high frequency of mutant alleles, except variants on chromosomes 7, 16 and 20. Analysis of tumor allelic ratio to normal using all variants in exome sequencing revealed that this mesothelioma showed genome-wide allelic loss or loss of heterozygosity (LOH), which appears to be distinct from other cancers that have many genetic alterations with focal allelic loss. To the best of our knowledge, this type of extensive genome-wide allelic loss has not been described in MPM.

Whole exome sequencing analysis revealed the MPM had R282W, a key TP53 mutation, and genome-wide allelic loss or loss of heterozygosity, a distinct genomic alteration not previously described in MPM. We identified frequent inactivating SETDB1 mutations in this patient and in 77 additional MPM patients (mutation frequency: 9%, 7/78) by targeted deep sequencing.

In summary, we identified genome-wide allelic loss in a patient who had MPM and two additional primary cancers, results which suggest that careful analysis in exome sequencing is needed to detect genome-wide deletion in MPM samples with or without multiple primary cancers. The high frequency of mutations in SETDB1 that we found suggests that this and other histone-related genes are important in MPM.

Citation Format: Hio Chung Kang, Hong Kwan Kim, Sharon Lee, Pedro Mendez, James Kim, Gavitt Woodard, Kuang-Yu Jen, Li Tai Fang, Kirk Jones, David Jablons, Il Jin Kim. Whole exome and targeted deep sequencing identify genome-wide allelic loss and frequent SETDB1 mutations in malignant pleural mesotheliomas. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 108.

The Trp53 delta proline (Trp53ΔP) mouse exhibits increased genome instability and susceptibility to radiation-induced, but not spontaneous, tumor development

The tumor suppressor TP53 can initiate a plethora of anti-proliferative effects to maintain genomic integrity under conditions of genotoxic stress. The N-terminal proline-rich domain (PRD) of TP53 is important in the regulation of TP53 activity and stability. A common polymorphism at codon 72 in this region has been associated with altered cancer risk in humans. The Trp53ΔP mouse, which carries a germline homozygous deletion of a region of the PRD, does not develop spontaneous tumors in a mixed 129/Sv and C57BL/6 genetic background, but is highly susceptible to a broad range of tumor types following total body exposure to 4 Gy gamma (γ) radiation. This contrasts with the tumor spectrum in Trp53 null (-/-) mice, which mainly develop thymic lymphomas and osteosarcomas. Analysis of genomic instability in tissues and cells from Trp53ΔP mice demonstrated elevated basal levels of aneuploidy, but this is not sufficient to drive spontaneous tumorigenesis, which requires an additional DNA damage stimulus. Levels of genomic instability did not increase significantly in Trp53ΔP mice following irradiation exposure, suggesting that other radiation effects including tissue inflammation, altered metabolism or autophagy, may play an important role. The Trp53ΔP mouse is a novel model to dissect the mechanisms of tumor development induced by radiation exposure. © 2015 Wiley Periodicals, Inc.

Pathologic manifestations of levamisole-adulterated cocaine exposure

ᅟ

Rheumatic manifestations of cocaine have been well described, but more recently, a dramatic increase in the levamisole-adulterated cocaine supply in the United States has disclosed unique pathologic consequences that are distinct from pure cocaine use. Most notably, patients show skin lesions and renal dysfunction in the setting of extremely high perinuclear anti-neutrophil cytoplasmic antibodies (p-ANCA). Unexpectedly, antibodies to myeloperoxidase, the typical target of p-ANCA, are relatively low if at all present. This discrepancy is due to the fact that p-ANCA seen in association with levamisole-adulterated cocaine exposure is often directed against atypical p-ANCA-associated antigens within the neutrophil granules such as human neutrophil elastase, lactoferrin, and cathepsin G. Biopsies of the skin lesions reveal leukocytoclastic vasculitis often involving both superficial and deep dermal vessels. Renal injury most typically manifests as crescentic and necrotizing pauci-immune glomerulonephritis. In this review, the manifestations of levamisole-adulterated cocaine-induced vasculitis are discussed with an emphasis on the typical histomorphologic findings seen on biopsy.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1764738711370019.

Noninvasive in vivo imaging of diabetes-induced renal oxidative stress and response to therapy using hyperpolarized 13C dehydroascorbate magnetic resonance

Oxidative stress has been proposed to be a unifying cause for diabetic nephropathy and a target for novel therapies. Here we apply a new endogenous reduction-oxidation (redox) sensor, hyperpolarized (HP) (13)C dehydroascorbate (DHA), in conjunction with MRI to noninvasively interrogate the renal redox capacity in a mouse diabetes model. The diabetic mice demonstrate an early decrease in renal redox capacity, as shown by the lower in vivo HP (13)C DHA reduction to the antioxidant vitamin C (VitC), prior to histological evidence of nephropathy. This correlates with lower tissue reduced glutathione (GSH) concentration and higher NADPH oxidase 4 (Nox4) expression, consistent with increased superoxide generation and oxidative stress. ACE inhibition restores the HP (13)C DHA reduction to VitC with concomitant normalization of GSH concentration and Nox4 expression in diabetic mice. HP (13)C DHA enables rapid in vivo assessment of altered redox capacity in diabetic renal injury and after successful treatment.

The mutational landscapes of genetic and chemical models of Kras-driven lung cancer

Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding factors that induce driver mutations, and the processes that shape their selection during tumourigenesis. We performed whole-exome sequencing (WES) on adenomas from three mouse models of non-small cell lung cancer (NSCLC), induced by exposure to carcinogens (Methylnitrosourea (MNU) and Urethane), or by genetic activation of Kras (Kras^LA2). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the Kras^LA2 model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single nucleotide variants (SNVs), compared to only 6 in tumours from the Kras^LA2 model. In contrast, the Kras^LA2 tumours exhibited a significantly higher level of aneuploidy and copy number alterations (CNAs) compared to the carcinogen-induced tumours, suggesting that carcinogen and genetically-engineered models adopt different routes to tumour development. The wild type (WT) allele of Kras has been shown to act as a tumour suppressor in mouse models of NSCLC. We demonstrate that urethane-induced tumours from WT mice carry mostly (94%) Q61R Kras mutations, while those from Kras heterozygous animals carry mostly (92%) Q61L mutations, indicating a major role of germline Kras status in mutation selection during initiation. The exome-wide mutation spectra in carcinogen-induced tumours overwhelmingly display signatures of the initiating carcinogen, while adenocarcinomas acquire additional C>T mutations at CpG sites. These data provide a basis for understanding the conclusions from human tumour genome sequencing that identified two broad categories based on relative frequency of SNVs and CNAs¹, and underline the importance of carcinogen models for understanding the complex mutation spectra seen in human cancers.

Pauci-immune glomerulonephritis in individuals with disease associated with levamisole-adulterated cocaine: a series of 4 cases

Exposure to levamisole-adulterated cocaine can induce a distinct clinical syndrome characterized by retiform purpura and/or agranulocytosis accompanied by an unusual constellation of serologic abnormalities including antiphospholipid antibodies, lupus anticoagulants, and very high titers of antineutrophil cytoplasmic antibodies. Two recent case reports suggest that levamisole-adulterated cocaine may also lead to renal disease in the form of pauci-immune glomerulonephritis. To explore this possibility, we reviewed cases of pauci-immune glomerulonephritis between 2010 and 2012 at an inner city safety net hospital where the prevalence of levamisole in the cocaine supply is known to be high. We identified 3 female patients and 1 male patient who had biopsy-proven pauci-immune glomerulonephritis, used cocaine, and had serologic abnormalities characteristic of levamisole-induced autoimmunity. Each also had some other form of clinical disease known to be associated with levamisole, either neutropenia or cutaneous manifestations. One patient had diffuse alveolar hemorrhage. Three of the 4 patients were treated with short courses of prednisone and cyclophosphamide, 2 of whom experienced stable long-term improvement in their renal function despite ongoing cocaine use. The remaining 2 patients developed end-stage renal disease and became dialysis-dependent. This report supports emerging concern of more wide spread organ toxicity associated with the use of levamisole-adulterated cocaine.

Monoclonal light chain deposits within the stomach manifesting as immunotactoid gastropathy

Immunotactoid deposits are defined by their ultrastructural appearance and are characterized by microtubular or cylindrical structures typically measuring greater than 30 nm in diameter. Although a rare entity, immunotactoid deposition most often manifests as immunotactoid glomerulopathy and is associated with underlying lymphoplasmacytic disorders. Corneal immunotactoid deposition known as immunotactoid keratopathy has also been reported in patients with paraproteinemia. Here, we describe the first reported case of immunotactoid deposition in the stomach. The deposits were composed solely of kappa immunoglobulin light chains without significant lambda light chain or immunoglobulin heavy chain components. The patient displayed no renal signs or symptoms, and additional thorough clinical examination failed to detect any evidence of a paraproteinemia or plasma cell dyscrasia. Thus, the gastric immunotactoid deposits in this case appear to be an isolated finding of light chain deposition, of which the significance and etiology are unclear.

Lupus-like membranous nephropathy: Is it lupus or not?

BACKGROUND

Membranous glomerulonephritis is typically classified as idiopathic or secondary to systemic lupus erythematosus (SLE), hepatitis B, drugs, toxins, other infections, or malignancy. Not infrequently in some patients without a definite diagnosis of SLE, pathologic features of secondary membranous nephropathy are seen e.g., mesangial and/or subendothelial deposits, tubuloreticular inclusions, and full house immunofluorescence. In these patients, there is uncertainty about the etiology, response to therapy, and prognosis of membranous GN.

METHODS

We retrospectively reviewed the charts of 98 patients with membranous GN at San Francisco General Hospital and John Stroger Hospital of Cook County over a 10-year period. Data were collected and analyzed using SPSS.18.

RESULTS

Thirty-nine (40 %) had idiopathic membranous GN (Group 1), thirty-six (37 %) had lupus membranous GN (Group 2) and twenty-three (23 %) had some pathological features of secondary membranous GN, but no definite etiology of membranous GN (Group 3). At baseline (at time of renal biopsy) and after mean follow-up of 3.5 years, the average serum creatinine (in mg/dL) in Group 1 was (1.6 ± 1.0 versus 1.6 ± 1.7), Group 2 was (1.8 ± 2.5 versus 1.2 ± 0.9) and Group 3 was (1.1 ± 0.4 versus 1.27 ± 0.83), respectively. For the same time points, the average urine protein to creatinine ratio (g/g) in Group 1 was (9.8 ± 7.1 versus 5.7 ± 6.7), Group 2 was (4.2 ± 3.9 versus 1.7 ± 2.2), and Group 3 was (7.4 ± 5.7 versus 3.1 ± 3.8). In addition, during the follow-up period, eleven of 39 (28 %) in Group 1, two of 36 (6 %) in Group 2, and three of 23 (13 %) in Group 3 progressed to end-stage renal disease and were started on dialysis.

CONCLUSIONS

It appears that patients with lupus membranous GN have better renal prognosis than patients with idiopathic membranous GN. The renal prognosis for patients with pathological features of lupus membranous but no diagnosis of systemic lupus (lupus-like membranous GN) falls in between. Further studies are needed to determine if Group 3 patients can (a) definitively be classified as true idiopathic membranous GN or lupus membranous GN or (b) they have a separate disease from either M-type phospholipase A2 receptor membranous nephropathy or systemic lupus-induced membranous nephropathy.

CUL4A induces epithelial-mesenchymal transition and promotes cancer metastasis by regulating ZEB1 expression

The ubiquitin ligase CUL4A has been implicated in tumorigenesis, but its contributions to progression and metastasis have not been evaluated. Here, we show that CUL4A is elevated in breast cancer as well as in ovarian, gastric, and colorectal tumors in which its expression level correlates positively with distant metastasis. CUL4A overexpression in normal or malignant human mammary epithelial cells increased their neoplastic properties in vitro and in vivo, markedly increasing epithelial-mesenchymal transition (EMT) and the metastatic capacity of malignant cells. In contrast, silencing CUL4A in aggressive breast cancer cells inhibited these processes. Mechanistically, we found that CUL4A modulated histone H3K4me3 at the promoter of the EMT regulatory gene ZEB1 in a manner associated with its transcription. ZEB1 silencing blocked CUL4A-driven proliferation, EMT, tumorigenesis, and metastasis. Furthermore, in human breast cancers, ZEB1 expression correlated positively with CUL4A expression and distant metastasis. Taken together, our findings reveal a pivotal role of CUL4A in regulating the metastatic behavior of breast cancer cells.

Inflammation and Hras signaling control epithelial-mesenchymal transition during skin tumor progression

Epithelial-mesenchymal transition (EMT) is thought to be an important, possibly essential, component of the process of tumor dissemination and metastasis. About 20%-30% of Hras mutant mouse skin carcinomas induced by chemical initiation/promotion protocols have undergone EMT. Reduced exposure to TPA-induced chronic inflammation causes a dramatic reduction in classical papillomas and squamous cell carcinomas (SCCs), but the mice still develop highly invasive carcinomas with EMT properties, reduced levels of Hras and Egfr signaling, and frequent Ink4/Arf deletions. Deletion of Hras from the mouse germline also leads to a strong reduction in squamous tumor development, but tumors now acquire activating Kras mutations and exhibit more aggressive metastatic properties. We propose that invasive carcinomas can arise by different genetic and biological routes dependent on exposure to chronic inflammation and possibly from different target cell populations within the skin. Our data have implications for the use of inhibitors of inflammation or of Ras/Egfr pathway signaling for prevention or treatment of invasive cancers.

Recurrent HIV-associated immune complex glomerulonephritis with lupus-like features after kidney transplantation

A spectrum of kidney diseases besides classic human immunodeficiency virus (HIV)-associated nephropathy (HIVAN) exists in HIV-infected patients. Immune complex-mediated glomerulonephritis has emerged as a significant contributor to the burden of kidney disease in this population, particularly in patients of non-African descent. Lupus-like nephritis, a form of immune complex glomerulonephritis with histologic features identical to lupus nephritis in the absence of clinical or serologic markers of lupus, is well recognized as a cause of end-stage renal disease in HIV-infected patients. None of the HIV-associated kidney lesions, whether classic HIVAN or non-HIVAN, has been reported to recur in kidney transplants. We report here for the first time clinical and histologic recurrence of HIV-associated lupus-like nephritis after successful kidney transplantation, causing proteinuria, hematuria, and impaired kidney transplant function.

Reliability of whole slide images as a diagnostic modality for renal allograft biopsies

The use of digital whole slide images (WSI) in the field of pathology has become feasible for routine diagnostic purposes and has become more prevalent in recent years. This type of technology offers many advantages but must show the same degree of diagnostic reliability as conventional glass slides. Several studies have examined this issue in various settings and indicate that WSI are a reliable method for diagnostic pathology. Since transplant pathology is a highly specialized field that requires not only accurate but rapid diagnostic evaluation of biopsy materials, this field may greatly benefit from the use of WSI. In this study, we assessed the reliability of using WSI compared to conventional glass slides in renal allograft biopsies. We examined morphologic features and diagnostic categories defined by the Banff 07 Classification of Renal Allograft Pathology as well as additional morphologic features not included in this classification scheme. We found that intraobserver scores, when comparing the use of glass slides versus WSI, showed substantial agreement for both morphologic features (κ = 0.68) and acute rejection diagnostic categories (κ = 0.74). Furthermore, interobserver reliability was comparable for morphologic features (κ = 0.44 [glass] vs 0.42 [WSI]) and acute rejection diagnostic categories (κ = 0.49 [glass] vs 0.51 [WSI]). These data indicate that WSI are as reliable as glass slides for the evaluation of renal allograft biopsies.

Pten regulates Aurora-A and cooperates with Fbxw7 in modulating radiation-induced tumor development

The Aurora-A kinase gene is frequently amplified and/or overexpressed in a variety of human cancers, leading to major efforts to develop therapeutic agents targeting this pathway. Here, we show that Aurora-A is targeted for ubiquitination and subsequent degradation by the F-box protein FBXW7 in a process that is regulated by GSK3β. Using a series of truncated Aurora-A proteins and site-directed mutagenesis, we identified distinct FBXW7 and GSK3β-binding sites in Aurora-A. Mutation of critical residues in either site substantially disrupts degradation of Aurora-A. Furthermore, we show that loss of Pten results in the stabilization of Aurora-A by attenuating FBXW7-dependent degradation of Aurora-A through the AKT/GSK3β pathway. Moreover, radiation-induced tumor latency is significantly shortened in Fbxw7(+/-)Pten(+/-) mice as compared with either Fbxw7(+/-) or Pten(+/-) mice, indicating that Fbxw7 and Pten appear to cooperate in suppressing tumorigenesis. Our results establish a novel posttranslational regulatory network in which the Pten and Fbxw7 pathways appear to converge on the regulation of Aurora-A level.

Kidney microvasculature in health and disease

The renal microvasculature is composed of the glomerular and peritubular capillary beds which supply the cellular constituents of the kidney with oxygen and nutrients as well as maintain renal function by providing an adequate glomerular filtration rate. As a result, endothelial dysfunction within the kidney can lead to devastating consequences. Recently, a plethora of information regarding the molecular players involved in kidney microvasculature development and disease has emerged. Many of these studies focus on intricate signaling pathways within the local microenvironment of endothelial cells. Here, we highlight some of these studies and relate them to the molecular pathogenesis of glomerular and peritubular endothelial cells in both native and transplant renal diseases.