Sex classification of 3D skull images using deep neural networks.

Determining the fundamental characteristics that define a face as "feminine" or "masculine" has long fascinated anatomists and plastic surgeons, particularly those involved in aesthetic and gender-affirming surgery. Previous studies in this area have relied on manual measurements, comparative anatomy, and heuristic landmark-based feature extraction. In this study, we collected retrospectively at Cedars Sinai Medical Center (CSMC) a dataset of 98 skull samples, which is the first dataset of this kind of 3D medical imaging. We then evaluated the accuracy of multiple deep learning neural network architectures on sex classification with this dataset. Specifically, we evaluated methods representing three different 3D data modeling approaches: Resnet3D, PointNet++, and MeshNet. Despite the limited number of imaging samples, our testing results show that all three approaches achieve AUC scores above 0.9 after convergence. PointNet++ exhibits the highest accuracy, while MeshNet has the lowest. Our findings suggest that accuracy is not solely dependent on the sparsity of data representation but also on the architecture design, with MeshNet's lower accuracy likely due to the lack of a hierarchical structure for progressive data abstraction. Furthermore, we studied a problem related to sex determination, which is the analysis of the various morphological features that affect sex classification. We proposed and developed a new method based on morphological gradients to visualize features that influence model decision making. The method based on morphological gradients is an alternative to the standard saliency map, and the new method provides better visualization of feature importance. Our study is the first to develop and evaluate deep learning models for analyzing 3D facial skull images to identify imaging feature differences between individuals assigned male or female at birth. These findings may be useful for planning and evaluating craniofacial surgery, particularly gender-affirming procedures, such as facial feminization surgery.

Tracing the origin of alveolar stem cells in lung repair and regeneration.

Alveolar type 2 (AT2) cells are stem cells of the alveolar epithelia. Previous genetic lineage tracing studies reported multiple cellular origins for AT2 cells after injury. However, conventional lineage tracing based on Cre-loxP has the limitation of non-specific labeling. Here, we introduced a dual recombinase-mediated intersectional genetic lineage tracing approach, enabling precise investigation of AT2 cellular origins during lung homeostasis, injury, and repair. We found AT1 cells, being terminally differentiated, did not contribute to AT2 cells after lung injury and repair. Distinctive yet simultaneous labeling of club cells, bronchioalveolar stem cells (BASCs), and existing AT2 cells revealed the exact contribution of each to AT2 cells post-injury. Mechanistically, Notch signaling inhibition promotes BASCs but impairs club cells' ability to generate AT2 cells during lung repair. This intersectional genetic lineage tracing strategy with enhanced precision allowed us to elucidate the physiological role of various epithelial cell types in alveolar regeneration following injury.

Dynamics of Endothelial Cell Generation and Turnover in Arteries During Homeostasis and Diseases.

BACKGROUND: Endothelial cell (EC) generation and turnover by self-proliferation contributes to vascular repair and regeneration. The ability to accurately measure the dynamics of EC generation would advance our understanding of cellular mechanisms of vascular homeostasis and diseases. However, it is currently challenging to evaluate the dynamics of EC generation in large vessels such as arteries because of their infrequent proliferation. METHODS: By using dual recombination systems based on Cre-loxP and Dre-rox, we developed a genetic system for temporally seamless recording of EC proliferation in vivo. We combined genetic recording of EC proliferation with single-cell RNA sequencing and gene knockout to uncover cellular and molecular mechanisms underlying EC generation in arteries during homeostasis and disease. RESULTS: Genetic proliferation tracing reveals that ≈3% of aortic ECs undergo proliferation per month in adult mice during homeostasis. The orientation of aortic EC division is generally parallel to blood flow in the aorta, which is regulated by the mechanosensing protein Piezo1. Single-cell RNA sequencing analysis reveals 4 heterogeneous aortic EC subpopulations with distinct proliferative activity. EC cluster 1 exhibits transit-amplifying cell features with preferential proliferative capacity and enriched expression of stem cell markers such as Sca1 and Sox18. EC proliferation increases in hypertension but decreases in type 2 diabetes, coinciding with changes in the extent of EC cluster 1 proliferation. Combined gene knockout and proliferation tracing reveals that Hippo/vascular endothelial growth factor receptor 2 signaling pathways regulate EC proliferation in large vessels. CONCLUSIONS: Genetic proliferation tracing quantitatively delineates the dynamics of EC generation and turnover, as well as EC division orientation, in large vessels during homeostasis and disease. An EC subpopulation in the aorta exhibits more robust cell proliferation during homeostasis and type 2 diabetes, identifying it as a potential therapeutic target for vascular repair and regeneration.

Single protein encapsulated SN38 for tumor-targeting treatment.

BACKGROUND: The alkaloid camptothecin analog SN38 is a potent antineoplastic agent, but cannot be used directly for clinical application due to its poor water solubility. Currently, the prodrug approach on SN38 has resulted in 3 FDA-approved cancer therapeutics, irinotecan, ONIVYDE, and Trodelvy. However, only 2-8% of irinotecan can be transformed enzymatically in vivo into the active metabolite SN38, which severely limits the drug's efficacy. While numerous drug delivery systems have been attempted to achieve effective SN38 delivery, none have produced drug products with antitumor efficacy better than irinotecan in clinical trials. Therefore, novel approaches are urgently needed for effectively delivering SN38 to cancer cells with better efficacy and lower toxicity. METHODS: Based on the unique properties of human serum albumin (HSA), we have developed a novel single protein encapsulation (SPE) technology to formulate cancer therapeutics for improving their pharmacokinetics (PK) and antitumor efficacy and reducing their side effects. Previous application of SPE technology to doxorubicin (DOX) formulation has led to a promising drug candidate SPEDOX-6 (FDA IND #, 152154), which will undergo a human phase I clinical trial. Using the same SPE platform on SN38, we have now produced two SPESN38 complexes, SPESN38-5 and SPESN38-8. We conducted their pharmacological evaluations with respect to maximum tolerated dose, PK, and in vivo efficacy against colorectal cancer (CRC) and soft tissue sarcoma (STS) in mouse models. RESULTS: The lyophilized SPESN38 complexes can dissolve in aqueous media to form clear and stable solutions. Maximum tolerated dose (MTD) of SPESN38-5 is 250 mg/kg by oral route (PO) and 55 mg/kg by intravenous route (IV) in CD-1 mice. SPESN38-8 has the MTD of 45 mg/kg by IV in the same mouse model. PK of SPESN38-5 by PO at 250 mg/kg gave mouse plasma AUC0-∞ of 0.05 and 4.5 nmol × h/mL for SN38 and SN38 glucuronidate (SN38G), respectively, with a surprisingly high molar ratio of SN38G:SN38 = 90:1. However, PK of SPESN38-5 by IV at 55 mg/kg yielded much higher mouse plasma AUC0-∞ of 19 and 28 nmol × h/mL for SN38 and SN38G, producing a much lower molar ratio of SN38G:SN38 = 1.5:1. Antitumor efficacy of SPESN38-5 and irinotecan (control) was evaluated against HCT-116 CRC xenograft tumors. The data indicates that SPESN38-5 by IV at 55 mg/kg is more effective in suppressing HCT-116 tumor growth with lower systemic toxicity compared to irinotecan at 50 mg/kg. Additionally, SPESN38-8 and DOX (control) by IV were evaluated in the SK-LMS-1 STS mouse model. The results show that SPESN38-8 at 33 mg/kg is highly effective for inhibiting SK-LMS-1 tumor growth with low toxicity, in contrast to DOX's insensitivity to SK-LMS-1 with high toxicity. CONCLUSION: SPESN38 complexes provide a water soluble SN38 formulation. SPESN38-5 and SPESN38-8 demonstrate better PK values, lower toxicity, and superior antitumor efficacy in mouse models, compared with irinotecan and DOX.

Single Protein Encapsulated SN38 for Tumor-Targeting Treatment.

Background: The alkaloid camptothecin analog SN38 is a potent antineoplastic agent, but cannot be used directly for clinical application due to its poor water solubility. Currently, the prodrug approach on SN38 has resulted in 3 FDA-approved cancer therapeutics, irinotecan, ONIVYDE, and Trodelvy. However, only 2-8% of irinotecan can be transformed enzymatically in vivo into the active metabolite SN38, which severely limits the drug's efficacy. While numerous drug delivery systems have been attempted to achieve effective SN38 delivery, none have produced drug products with antitumor efficacy better than irinotecan in clinical trials. Therefore, novel approaches are urgently needed for effectively delivering SN38 to cancer cells with better efficacy and lower toxicity. Methods: Based on the unique properties of human serum albumin (HSA), we have developed a novel single protein encapsulation (SPE) technology to formulate cancer therapeutics for improving their pharmacokinetics (PK) and antitumor efficacy and reducing their side effects. Previous application of SPE technology to doxorubicin (DOX) formulation has led to a promising drug candidate SPEDOX-6 (FDA IND #, 152154), which will undergo a human phase I clinical trial. Using the same SPE platform on SN38, we have now produced two SPESN38 complexes, SPESN38-5 and SPESN38-8. We conducted their pharmacological evaluations with respect to maximum tolerated dose, PK, and in vivo efficacy against colorectal cancer (CRC) and soft tissue sarcoma (STS) in mouse models. Results: The lyophilized SPESN38 complexes can dissolve in aqueous media to form clear and stable solutions. Maximum tolerated dose (MTD) of SPESN38-5 is 250 mg/kg by oral route (PO) and 55 mg/kg by intravenous route (IV) in CD-1 mice. SPESN38-8 has the MTD of 45 mg/kg by IV in the same mouse model. PK of SPESN38-5 by PO at 250 mg/kg gave mouse plasma AUC0-∞ of 0.0548 and 4.5007 (nmol × h/mL) for SN38 and SN38 glucuronidate (SN38G), respectively, with a surprisingly high molar ratio of SN38G:SN38 = 82:1. However, PK of SPESN38-5 by IV at 55 mg/kg yielded much higher mouse plasma AUC0-∞ of 18.80 and 27.78 nmol × h/mL for SN38 and SN38G, producing a much lower molar ratio of SN38G:SN38 = 1.48:1. Antitumor efficacy of SPESN38-5 and irinotecan (control) was evaluated against HCT-116 CRC xenograft tumors. The data indicates that SPESN38-5 by IV at 55 mg/kg is more effective in suppressing HCT-116 tumor growth with lower systemic toxicity compared to irinotecan at 50 mg/kg. Additionally, SPESN38-8 and DOX (control) by IV were evaluated in the SK-LMS-1 STS mouse model. The results show that SPESN38-8 at 33 mg/kg is highly effective for inhibiting SK-LMS-1 tumor growth with low toxicity, in contrast to DOX's insensitivity to SK-LMS-1 with high toxicity. Conclusion: SPESN38 complexes provide a water soluble SN38 formulation. SPESN38-5 and SPESN38-8 demonstrate better PK values, lower toxicity, and superior antitumor efficacy in mouse models, compared with irinotecan and DOX.

Bipotent transitional liver progenitor cells contribute to liver regeneration.

Following severe liver injury, when hepatocyte-mediated regeneration is impaired, biliary epithelial cells (BECs) can transdifferentiate into functional hepatocytes. However, the subset of BECs with such facultative tissue stem cell potential, as well as the mechanisms enabling transdifferentiation, remains elusive. Here we identify a transitional liver progenitor cell (TLPC), which originates from BECs and differentiates into hepatocytes during regeneration from severe liver injury. By applying a dual genetic lineage tracing approach, we specifically labeled TLPCs and found that they are bipotent, as they either differentiate into hepatocytes or re-adopt BEC fate. Mechanistically, Notch and Wnt/ß-catenin signaling orchestrate BEC-to-TLPC and TLPC-to-hepatocyte conversions, respectively. Together, our study provides functional and mechanistic insights into transdifferentiation-assisted liver regeneration.

Genetic Lineage Tracing of Pericardial Cavity Macrophages in the Injured Heart.

BACKGROUND: Macrophages play an important role in cardiac repair after myocardial infarction (MI). In addition to the resident macrophages and blood-derived monocytes, Gata6+ cavity macrophages located in the pericardial space were recently reported to relocate to the injured myocardium and prevent cardiac fibrosis. However, there is no direct genetic evidence to support it. METHODS: We used dual recombinases (Cre and Dre) to specifically label Gata6+ pericardial macrophages (GPCMs) in vivo. For functional study, we generated genetic systems to specifically ablate GPCMs by induced expression of DTR (diphtheria toxin receptor) or knockout of Gata6 (GATA binding protein 6) gene in GPCMs. We used these genetic systems to study GPCMs in pericardium intact MI model. RESULTS: Dual recombinases-mediated genetic system targeted GPCMs specifically and efficiently. Lineage tracing study revealed accumulation of GPCMs on the surface of MI heart without deep penetration into the myocardium. We did not detect significant change of cardiac fibrosis or function of MI hearts after cell ablation or Gata6 knockout in GPCMs. CONCLUSIONS: GPCMs minimally invade the injured heart after MI. Nor do they prevent cardiac fibrosis and exhibit reparative function on injured heart. This study also underlines the importance of using specific genetic tool for studying in vivo cell fates and functions.

An Ensemble of U-Net Models for Kidney Tumor Segmentation With CT Images.

We present here the Arkansas AI-Campus solution method for the 2019 Kidney Tumor Segmentation Challenge (KiTS19). Our Arkansas AI-Campus team participated the KiTS19 Challenge for four months, from March to July of 2019. This paper provides a summary of our methods, training, testing and validation results for this grand challenge in biomedical imaging analysis. Our deep learning model is an ensemble of U-Net models developed after testing many model variations. Our model has consistent performance on the local test dataset and the final competition independent test dataset. The model achieved local test Dice scores of 0.949 for kidney and tumor segmentation, and 0.601 for tumor segmentation, and the final competition test earned Dice scores 0.9470 and 0.6099 respectively. The Arkansas AI-Campus team solution with a composite DICE score of 0.7784 has achieved a final ranking of top fifty worldwide, and top five among the United States teams in the KiTS19 Competition.

Spatial Pyramid Pooling With 3D Convolution Improves Lung Cancer Detection.

Lung cancer is the leading cause of cancer deaths. Low-dose computed tomography (CT)screening has been shown to significantly reduce lung cancer mortality but suffers from a high false positive rate that leads to unnecessary diagnostic procedures. The development of deep learning techniques has the potential to help improve lung cancer screening technology. Here we present the algorithm, DeepScreener, which can predict a patient's cancer status from a volumetric lung CT scan. DeepScreener is based on our model of Spatial Pyramid Pooling, which ranked 16th of 1972 teams (top 1 percent)in the Data Science Bowl 2017 competition (DSB2017), evaluated with the challenge datasets. Here we test the algorithm with an independent set of 1449 low-dose CT scans of the National Lung Screening Trial (NLST)cohort, and we find that DeepScreener has consistent performance of high accuracy. Furthermore, by combining Spatial Pyramid Pooling and 3D Convolution, it achieves an AUC of 0.892, surpassing the previous state-of-the-art algorithms using only 3D convolution. The advancement of deep learning algorithms can potentially help improve lung cancer detection with low-dose CT scans.

Genetic fate-mapping reveals surface accumulation but not deep organ invasion of pleural and peritoneal cavity macrophages following injury.

During injury, monocytes are recruited from the circulation to inflamed tissues and differentiate locally into mature macrophages, with prior reports showing that cavity macrophages of the peritoneum and pericardium invade deeply into the respective organs to promote repair. Here we report a dual recombinase-mediated genetic system designed to trace cavity macrophages in vivo by intersectional detection of two characteristic markers. Lineage tracing with this method shows accumulation of cavity macrophages during lung and liver injury on the surface of visceral organs without penetration into the parenchyma. Additional data suggest that these peritoneal or pleural cavity macrophages do not contribute to tissue repair and regeneration. Our in vivo genetic targeting approach thus provides a reliable method to identify and characterize cavity macrophages during their development and in tissue repair and regeneration, and distinguishes these cells from other lineages.

Detecting Asymmetric Patterns and Localizing Cancers on Mammograms.

One in eight women develops invasive breast cancer in her lifetime. The frontline protection against this disease is mammography. While computer-assisted diagnosis algorithms have made great progress in generating reliable global predictions, few focus on simultaneously producing regions of interest (ROIs) for biopsy. Can we combine ROI-oriented algorithms with global classification of cancer status, which simultaneously highlight suspicious regions and optimize classification performance? Can the asymmetry of breasts be adopted in deep learning for finding lesions and classifying cancers? We answer the above questions by building deep-learning networks that identify masses and microcalcifications in paired mammograms, exclude false positives, and stepwisely improve performance of the model with asymmetric information regarding the breasts. This method achieved a co-leading place in the Digital Mammography DREAM Challenge for predicting breast cancer. We highlight here the importance of this dual-purpose process that simultaneously provides the locations of potential lesions in mammograms.

Lung regeneration by multipotent stem cells residing at the bronchioalveolar-duct junction.

Characterizing the stem cells responsible for lung repair and regeneration is important for the treatment of pulmonary diseases. Recently, a unique cell population located at the bronchioalveolar-duct junctions has been proposed to comprise endogenous stem cells for lung regeneration. However, the role of bronchioalveolar stem cells (BASCs) in vivo remains debated, and the contribution of such cells to lung regeneration is not known. Here we generated a genetic lineage-tracing system that uses dual recombinases (Cre and Dre) to specifically track BASCs in vivo. Fate-mapping and clonal analysis showed that BASCs became activated and responded distinctly to different lung injuries, and differentiated into multiple cell lineages including club cells, ciliated cells, and alveolar type 1 and type 2 cells for lung regeneration. This study provides in vivo genetic evidence that BASCs are bona fide lung epithelial stem cells with deployment of multipotency and self-renewal during lung repair and regeneration.

Genetic lineage tracing of resident stem cells by DeaLT.

Unraveling the fates of resident stem cells during tissue regeneration is an important objective in clinical and basic research. Genetic lineage tracing based on Cre-loxP recombination provides an effective strategy for inferring cell fate and cell conversion in vivo. However, the determination of the exact fates of resident stem cells or their derivatives in disease states and during tissue regeneration remains controversial in many fields of study, partly because of technical limitations associated with Cre-based lineage tracing, such as, for example, off-target labeling. Recently, we generated a new lineage-tracing platform we named DeaLT (dual-recombinase-activated lineage tracing) that uses the Dre-rox recombination system to enhance the precision of Cre-mediated lineage tracing. Here, we describe as an example a detailed protocol using DeaLT to trace the fate of c-Kit+ cardiac stem cells and their derivatives, in the absence of any interference from nontarget cells such as cardiomyocytes, during organ homeostasis and after tissue injury. This lineage-tracing protocol can also be used to delineate the fate of resident stem cells of other organ systems, and takes ~10 months to complete, from mouse crossing to final tissue analysis.

Highly accurate model for prediction of lung nodule malignancy with CT scans.

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://bioinformatics.astate.edu/NoduleX .

Genetic Targeting of Organ-Specific Blood Vessels.

RATIONALE: Organs of the body require vascular networks to supply oxygen and nutrients and maintain physiological function. The blood vessels of different organs are structurally and functionally heterogeneous in nature. To more precisely dissect their distinct in vivo function in individual organs, without potential interference from off-site targets, it is necessary to genetically target them in an organ-specific manner. OBJECTIVE: The objective of this study was to generate a genetic system that targets vascular endothelial cells in an organ- or tissue-specific manner and to exemplify the potential application of intersectional genetics for precise, target-specific gene manipulation in vivo. METHODS AND RESULTS: We took advantage of 2 orthogonal recombination systems, Dre-rox and Cre-loxP, to create a genetic targeting system based on intersectional genetics. Using this approach, Cre activity was only detectable in cells that had expressed both Dre and Cre. Applying this new system, we generated a coronary endothelial cell-specific Cre (CoEC-Cre) and a brain endothelial cell-specific Cre (BEC-Cre). Through lineage tracing, gene knockout and overexpression experiments, we demonstrated that CoEC-Cre and BEC-Cre efficiently and specifically target blood vessels in the heart and brain, respectively. By deletion of vascular endothelial growth factor receptor 2 using BEC-Cre, we showed that vascular endothelial growth factor signaling regulates angiogenesis in the central nervous system and also controls the integrity of the blood-brain barrier. CONCLUSIONS: We provide 2 examples to illustrate the use of intersectional genetics for more precise gene targeting in vivo, namely manipulation of genes in blood vessels of the heart and brain. More broadly, this system provides a valuable strategy for tissue-specific gene manipulation that can be widely applied to other fields of biomedical research.

Genetic Fate Mapping Defines the Vascular Potential of Endocardial Cells in the Adult Heart.

RATIONALE: Endocardium is the major source of coronary endothelial cells (ECs) in the fetal and neonatal hearts. It remains unclear whether endocardium in the adult stage is also the main origin of neovascularization after cardiac injury. OBJECTIVE: To define the vascular potential of adult endocardium in homeostasis and after cardiac injuries by fate-mapping studies. METHODS AND RESULTS: We generate an inducible adult endocardial Cre line (Npr3 [natriuretic peptide receptor C]-CreER) and show that Npr3-CreER efficiently and specifically labels endocardial cells but not coronary blood vessels in the adult heart. The adult endocardial cells do not contribute to any vascular ECs during cardiac homeostasis. To examine the formation of blood vessels from endocardium after injury, we generate 4 cardiac injury models with Npr3-CreER mice: myocardial infarction, myocardial ischemia-reperfusion, cryoinjury, and transverse aortic constriction. Lineage tracing experiments show that adult endocardium minimally contributes to coronary ECs after myocardial infarction. In the myocardial ischemia-reperfusion, cryoinjury, or transverse aortic constriction models, adult endocardial cells do not give rise to any vascular ECs, and they remain on the inner surface of myocardium that connects with lumen circulation. In the myocardial infarction model, very few endocardial cells are trapped in the infarct zone of myocardium shortly after ligation of coronary artery, indicating the involvement of endocardial entrapment during blood vessels formation. When these adult endocardial cells are relocated and trapped in the infarcted myocardium by transplantation or myocardial constriction model, very few endocardial cells survive and gain vascular EC properties, and their contribution to neovascularization in the injured myocardium remains minimal. CONCLUSIONS: Unlike its fetal or neonatal counterpart, adult endocardium naturally generates minimal, if any, coronary arteries or vascular ECs during cardiac homeostasis or after injuries.

Identification of a hybrid myocardial zone in the mammalian heart after birth.

Noncompaction cardiomyopathy is characterized by the presence of extensive trabeculations, which could lead to heart failure and malignant arrhythmias. How trabeculations resolve to form compact myocardium is poorly understood. Elucidation of this process is critical to understanding the pathophysiology of noncompaction disease. Here we use genetic lineage tracing to mark the Nppa+ or Hey2+ cardiomyocytes as trabecular and compact components of the ventricular wall. We find that Nppa+ and Hey2+ cardiomyocytes, respectively, from the endocardial and epicardial zones of the ventricular wall postnatally. Interposed between these two postnatal layers is a hybrid zone, which is composed of cells derived from both the Nppa+ and Hey2+ populations. Inhibition of the fetal Hey2+ cell contribution to the hybrid zone results in persistence of excessive trabeculations in postnatal heart. Our findings indicate that the expansion of Hey2+ fetal compact component, and its contribution to the hybrid myocardial zone, are essential for normal formation of the ventricular walls.Fetal trabecular muscles in the heart undergo a poorly described morphogenetic process that results into a solidified compact myocardium after birth. Tian et al. show that cardiomyocytes in the fetal compact layer also contribute to this process, forming a hybrid myocardial zone that is composed of cells derived from both trabecular and compact layers.

Identification of driver modules in pan-cancer via coordinating coverage and exclusivity.

It is widely accepted that cancer is driven by accumulated somatic mutations during the lifetime of an individual. Cancer mutations may target relatively small number of cell functional modules. The heterogeneity in different cancer patients makes it difficult to identify driver mutations or functional modules related to cancer. It is biologically desired to be capable of identifying cancer pathway modules through coordination between coverage and exclusivity. There have been a few approaches developed for this purpose, but they all have limitations in practice due to their computational complexity and prediction accuracy. We present a network based approach, CovEx, to predict the specific patient oriented modules by 1) discovering candidate modules for each considered gene, 2) extracting significant candidates by harmonizing coverage and exclusivity and, 3) further selecting the patient oriented modules based on a set cover model. Applying CovEx to pan-cancer datasets spanning 12 cancer types collecting from public database TCGA, it demonstrates significant superiority over the current leading competitors in performance. It is published under GNU GENERAL PUBLIC LICENSE and the source code is available at: https://sourceforge.net/projects/cancer-pathway/files/.

Genetic tracing of hepatocytes in liver homeostasis, injury, and regeneration.

The liver possesses a remarkable capacity to regenerate after damage. There is a heated debate on the origin of new hepatocytes after injuries in adult liver. Hepatic stem/progenitor cells have been proposed to produce functional hepatocytes after injury. Recent studies have argued against this model and suggested that pre-existing hepatocytes, rather than stem cells, contribute new hepatocytes. This hepatocyte-to-hepatocyte model is mainly based on labeling of hepatocytes with Cre-recombinase delivered by the adeno-associated virus. However, the impact of virus infection on cell fate determination, consistency of infection efficiency, and duration of Cre-virus in hepatocytes remain confounding factors that interfere with the data interpretation. Here, we generated a new genetic tool Alb-DreER to label almost all hepatocytes (>99.5%) and track their contribution to different cell lineages in the liver. By "pulse-and-chase" strategy, we found that pre-existing hepatocytes labeled by Alb-DreER contribute to almost all hepatocytes during normal homeostasis and after liver injury. Virtually all hepatocytes in the injured liver are descendants of pre-existing hepatocytes through self-expansion. We concluded that stem cell differentiation is unlikely to be responsible for the generation of a substantial number of new hepatocytes in adult liver. Our study also provides a new mouse tool for more precise in vivo genetic study of hepatocytes in the field.