Comparative genomics incorporating translocation renal cell carcinoma mouse model reveals molecular mechanisms of tumorigenesis.

Translocation renal cell carcinoma (tRCC) most commonly involves an ASPSCR1-TFE3 fusion, but molecular mechanisms remain elusive and animal models are lacking. Here, we show that human ASPSCR1-TFE3 driven by Pax8-Cre (a credentialed clear cell RCC driver) disrupted nephrogenesis and glomerular development, causing neonatal death, while the clear cell RCC failed driver, Sglt2-Cre, induced aggressive tRCC (as well as alveolar soft part sarcoma) with complete penetrance and short latency. However, in both contexts, ASPSCR1-TFE3 led to characteristic morphological cellular changes, loss of epithelial markers, and an epithelial-mesenchymal transition. Electron microscopy of tRCC tumors showed lysosome expansion, and functional studies revealed simultaneous activation of autophagy and mTORC1 pathways. Comparative genomic analyses encompassing an institutional human tRCC cohort (including a hitherto unreported SFPQ-TFEB fusion) and a variety of tumorgraft models (ASPSCR1-TFE3, PRCC-TFE3, SFPQ-TFE3, RBM10-TFE3, and MALAT1-TFEB) disclosed significant convergence in canonical pathways (cell cycle, lysosome, and mTORC1) and less established pathways such as Myc, E2F, and inflammation (IL-6/JAK/STAT3, interferon-γ, TLR signaling, systemic lupus, etc.). Therapeutic trials (adjusted for human drug exposures) showed antitumor activity of cabozantinib. Overall, this study provides insight into MiT/TFE-driven tumorigenesis, including the cell of origin, and characterizes diverse mouse models available for research.

Magnetic resonance imaging improves diagnosis of placenta accreta spectrum requiring hysterectomy compared to ultrasound.

BACKGROUND: Magnetic resonance imaging has been used increasingly as an adjunct for ultrasound imaging for placenta accreta spectrum assessment and preoperative surgical planning, but its value has not been established yet. The ultrasound-based placenta accreta index is a well-validated standardized approach for placenta accreta spectrum evaluation. Placenta accreta spectrum-magnetic resonance imaging markers have been outlined in a joint guideline from the Society of Abdominal Radiology and the European Society of Urogenital Radiology. OBJECTIVE: This study aimed to compare placenta accreta spectrum-magnetic resonance imaging parameters with the ultrasound-based placenta accreta index in pregnancies at high risk for placenta accreta spectrum and to assess the additional diagnostic value of magnetic resonance imaging for placenta accreta spectrum that requires a cesarean hysterectomy. STUDY DESIGN: This was a single-center, retrospective study of pregnant patients who underwent magnetic resonance imaging, in addition to ultrasonography, because of suspected placenta accreta spectrum. The ultrasound-based placenta accreta index and placenta accreta spectrum-magnetic resonance imaging parameters were obtained. Student's t test and Fisher's exact test were used to compare the groups in terms of the primary outcome (hysterectomy vs no hysterectomy). The diagnostic performance of magnetic resonance imaging and the ultrasound-based placenta accreta index was assessed using multivariable logistic regressions, receiver operating characteristics curves, the DeLong test, McNemar test, and the relative predictive value test. RESULTS: A total of 82 patients were included in the study, 41 of whom required a hysterectomy. All patients who underwent a hysterectomy met the International Federation of Gynecology and Obstetrics clinical evidence of placenta accreta spectrum at the time of delivery. Multiple parameters of the ultrasound-based placenta accreta index and placenta accreta spectrum-magnetic resonance imaging were able to predict hysterectomy, and the parameter of greatest dimension of invasion by magnetic resonance imaging was the best quantitative predictor. At 96% sensitivity for hysterectomy, the cutoff values were 3.5 for the ultrasound-based placenta accreta index and 2.5 cm for the greatest dimension of invasion by magnetic resonance imaging. Using this sensitivity, the parameter of greatest dimension of invasion measured by magnetic resonance imaging had higher specificity (P=.0016) and a higher positive predictive value (P=.0018) than the ultrasound-based placenta accreta index, indicating an improved diagnostic threshold. CONCLUSION: In a suspected high-risk group for placenta accreta spectrum, magnetic resonance imaging identified more patients who will not need a hysterectomy than when using the ultrasound-based placenta accrete index only. Magnetic resonance imaging has the potential to aid patient counseling, surgical planning, and delivery timing, including preterm delivery decisions for patients with placenta accreta spectrum requiring hysterectomy.

The human placenta project: Funded studies, imaging technologies, and future directions.

The placenta plays a critical role in fetal development. It serves as a multi-functional organ that protects and nurtures the fetus during pregnancy. However, despite its importance, the intricacies of placental structure and function in normal and diseased states have remained largely unexplored. Thus, in 2014, the National Institute of Child Health and Human Development launched the Human Placenta Project (HPP). As of May 2023, the HPP has awarded over $101 million in research funds, resulting in 41 funded studies and 459 publications. We conducted a comprehensive review of these studies and publications to identify areas of funded research, advances in those areas, limitations of current research, and continued areas of need. This paper will specifically review the funded studies by the HPP, followed by an in-depth discussion on advances and gaps within placental-focused imaging. We highlight the progress within magnetic reasonance imaging and ultrasound, including development of tools for the assessment of placental function and structure.

Longitudinal assessment of placental perfusion in normal and hypertensive pregnancies using pseudo-continuous arterial spin-labeled MRI: preliminary experience.

OBJECTIVES: To evaluate longitudinal placental perfusion using pseudo-continuous arterial spin-labeled (pCASL) MRI in normal pregnancies and in pregnancies affected by chronic hypertension (cHTN), who are at the greatest risk for placental-mediated disease conditions. METHODS: Eighteen normal and 23 pregnant subjects with cHTN requiring antihypertensive therapy were scanned at 3 T using free-breathing pCASL-MRI at 16-20 and 24-28 weeks of gestational age. RESULTS: Mean placental perfusion was 103.1 ± 48.0 and 71.4 ± 18.3 mL/100 g/min at 16-20 and 24-28 weeks respectively in normal pregnancies and 79.4 ± 27.4 and 74.9 ± 26.6 mL/100 g/min in cHTN pregnancies. There was a significant decrease in perfusion between the first and second scans in normal pregnancies (p = 0.004), which was not observed in cHTN pregnancies (p = 0.36). The mean perfusion was not statistically different between normal and cHTN pregnancies at both scans, but the absolute change in perfusion per week was statistically different between these groups (p = 0.044). Furthermore, placental perfusion was significantly lower at both time points (p = 0.027 and 0.044 respectively) in the four pregnant subjects with cHTN who went on to have infants that were small for gestational age (52.7 ± 20.4 and 50.4 ± 20.9 mL/100 g/min) versus those who did not (85 ± 25.6 and 80.0 ± 25.1 mL/100 g/min). CONCLUSION: pCASL-MRI enables longitudinal assessment of placental perfusion in pregnant subjects. Placental perfusion in the second trimester declined in normal pregnancies whereas it remained unchanged in cHTN pregnancies, consistent with alterations due to vascular disease pathology. Perfusion was significantly lower in those with small for gestational age infants, indicating that pCASL-MRI-measured perfusion may be an effective imaging biomarker for placental insufficiency. CLINICAL RELEVANCE STATEMENT: pCASL-MRI enables longitudinal assessment of placental perfusion without administering exogenous contrast agent and can identify placental insufficiency in pregnant subjects with chronic hypertension that can lead to earlier interventions. KEY POINTS: • Arterial spin-labeled (ASL) magnetic resonance imaging (MRI) enables longitudinal assessment of placental perfusion without administering exogenous contrast agent. • ASL-MRI-measured placental perfusion decreased significantly between 16-20 week and 24-28 week gestational age in normal pregnancies, while it remained relatively constant in hypertensive pregnancies, attributed to vascular disease pathology. • ASL-MRI-measured placental perfusion was significantly lower in subjects with hypertension who had a small for gestational age infant at 16-20-week gestation, indicating perfusion as an effective biomarker of placental insufficiency.

Deep learning based automatic segmentation of the placenta and uterine cavity on prenatal MR images.

Magnetic resonance imaging (MRI) has potential benefits in understanding fetal and placental complications in pregnancy. An accurate segmentation of the uterine cavity and placenta can help facilitate fast and automated analyses of placenta accreta spectrum and other pregnancy complications. In this study, we trained a deep neural network for fully automatic segmentation of the uterine cavity and placenta from MR images of pregnant women with and without placental abnormalities. The two datasets were axial MRI data of 241 pregnant women, among whom, 101 patients also had sagittal MRI data. Our trained model was able to perform fully automatic 3D segmentation of MR image volumes and achieved an average Dice similarity coefficient (DSC) of 92% for uterine cavity and of 82% for placenta on the sagittal dataset and an average DSC of 87% for uterine cavity and of 82% for placenta on the axial dataset. Use of our automatic segmentation method is the first step in designing an analytics tool for to assess the risk of pregnant women with placenta accreta spectrum.

Topography-based feature extraction of the human placenta from prenatal MR images.

Magnetic resonance imaging (MRI) has gained popularity in the field of prenatal imaging due to the ability to provide high quality images of soft tissue. In this paper, we presented a novel method for extracting different textural and morphological features of the placenta from MRI volumes using topographical mapping. We proposed polar and planar topographical mapping methods to produce common placental features from a unique point of observation. The features extracted from the images included the entire placenta surface, as well as the thickness, intensity, and entropy maps displayed in a convenient two-dimensional format. The topography-based images may be useful for clinical placental assessments as well as computer-assisted diagnosis, and prediction of potential pregnancy complications.

In vivo characterization of glutamine metabolism identifies therapeutic targets in clear cell renal cell carcinoma.

Targeting metabolic vulnerabilities has been proposed as a therapeutic strategy in renal cell carcinoma (RCC). Here, we analyzed the metabolism of patient-derived xenografts (tumorgrafts) from diverse subtypes of RCC. Tumorgrafts from VHL-mutant clear cell RCC (ccRCC) retained metabolic features of human ccRCC and engaged in oxidative and reductive glutamine metabolism. Genetic silencing of isocitrate dehydrogenase-1 or isocitrate dehydrogenase-2 impaired reductive labeling of tricarboxylic acid (TCA) cycle intermediates in vivo and suppressed growth of tumors generated from tumorgraft-derived cells. Glutaminase inhibition reduced the contribution of glutamine to the TCA cycle and resulted in modest suppression of tumorgraft growth. Infusions with [amide-15N]glutamine revealed persistent amidotransferase activity during glutaminase inhibition, and blocking these activities with the amidotransferase inhibitor JHU-083 also reduced tumor growth in both immunocompromised and immunocompetent mice. We conclude that ccRCC tumorgrafts catabolize glutamine via multiple pathways, perhaps explaining why it has been challenging to achieve therapeutic responses in patients by inhibiting glutaminase.

HIF2 Inactivation and Tumor Suppression with a Tumor-Directed RNA-Silencing Drug in Mice and Humans.

PURPOSE: HIF2α is a key driver of kidney cancer. Using a belzutifan analogue (PT2399), we previously showed in tumorgrafts (TG) that ∼50% of clear cell renal cell carcinomas (ccRCC) are HIF2α dependent. However, prolonged treatment induced resistance mutations, which we also identified in humans. Here, we evaluated a tumor-directed, systemically delivered, siRNA drug (siHIF2) active against wild-type and resistant-mutant HIF2α. EXPERIMENTAL DESIGN: Using our credentialed TG platform, we performed pharmacokinetic and pharmacodynamic analyses evaluating uptake, HIF2α silencing, target gene inactivation, and antitumor activity. Orthogonal RNA-sequencing studies of siHIF2 and PT2399 were pursued to define the HIF2 transcriptome. Analyses were extended to a TG line generated from a study biopsy of a siHIF2 phase I clinical trial (NCT04169711) participant and the corresponding patient, an extensively pretreated individual with rapidly progressive ccRCC and paraneoplastic polycythemia likely evidencing a HIF2 dependency. RESULTS: siHIF2 was taken up by ccRCC TGs, effectively depleted HIF2α, deactivated orthogonally defined effector pathways (including Myc and novel E2F pathways), downregulated cell cycle genes, and inhibited tumor growth. Effects on the study subject TG mimicked those in the patient, where HIF2α was silenced in tumor biopsies, circulating erythropoietin was downregulated, polycythemia was suppressed, and a partial response was induced. CONCLUSIONS: To our knowledge, this is the first example of functional inactivation of an oncoprotein and tumor suppression with a systemic, tumor-directed, RNA-silencing drug. These studies provide a proof-of-principle of HIF2α inhibition by RNA-targeting drugs in ccRCC and establish a paradigm for tumor-directed RNA-based therapeutics in cancer.

Automatic Segmentation of Uterine Cavity and Placenta on MR Images Using Deep Learning.

Magnetic resonance imaging (MRI) is useful for the detection of abnormalities affecting maternal and fetal health. In this study, we used a fully convolutional neural network for simultaneous segmentation of the uterine cavity and placenta on MR images. We trained the network with MR images of 181 patients, with 157 for training and 24 for validation. The segmentation performance of the algorithm was evaluated using MR images of 60 additional patients that were not involved in training. The average Dice similarity coefficients achieved for the uterine cavity and placenta were 92% and 80%, respectively. The algorithm could estimate the volume of the uterine cavity and placenta with average errors of less than 1.1% compared to manual estimations. Automated segmentation, when incorporated into clinical use, has the potential to quantify, standardize, and improve placental assessment, resulting in improved outcomes for mothers and fetuses.

CascadeNet for hysterectomy prediction in pregnant women due to placenta accreta spectrum.

In severe cases, placenta accreta spectrum (PAS) requires emergency hysterectomy, endangering the life of both mother and fetus. Early prediction may reduce complications and aid in management decisions in these high-risk pregnancies. In this work, we developed a novel convolutional network architecture to combine MRI volumes, radiomic features, and custom feature maps to predict PAS severe enough to result in hysterectomy after fetal delivery in pregnant women. We trained, optimized, and evaluated the networks using data from 241 patients, in groups of 157, 24, and 60 for training, validation, and testing, respectively. We found the network using all three paths produced the best performance, with an AUC of 87.8, accuracy 83.3%, sensitivity of 85.0, and specificity of 82.5. This deep learning algorithm, deployed in clinical settings, may identify women at risk before birth, resulting in improved patient outcomes.

Placenta Accreta Spectrum and Hysterectomy Prediction Using MRI Radiomic Features.

In women with placenta accreta spectrum (PAS), patient management may involve cesarean hysterectomy at delivery. Magnetic resonance imaging (MRI) has been used for further evaluation of PAS and surgical planning. This work tackles two prediction problems: predicting presence of PAS and predicting hysterectomy using MR images of pregnant patients. First, we extracted approximately 2,500 radiomic features from MR images with two regions of interest: the placenta and the uterus. In addition to analyzing two regions of interest, we dilated the placenta and uterus masks by 5, 10, 15, and 20 mm to gain insights from the myometrium, where the uterus and placenta overlap in the case of PAS. This study cohort includes 241 pregnant women. Of these women, 89 underwent hysterectomy while 152 did not; 141 with suspected PAS, and 100 without suspected PAS. We obtained an accuracy of 0.88 for predicting hysterectomy and an accuracy of 0.92 for classifying suspected PAS. The radiomic analysis tool is further validated, it can be useful for aiding clinicians in decision making on the care of pregnant women.

Deep learning-based segmentation of the placenta and uterus on MR images.

Purpose: Magnetic resonance imaging has been recently used to examine the abnormalities of the placenta during pregnancy. Segmentation of the placenta and uterine cavity allows quantitative measures and further analyses of the organs. The objective of this study is to develop a segmentation method with minimal user interaction. Approach: We developed a fully convolutional neural network (CNN) for simultaneous segmentation of the uterine cavity and placenta in three dimensions (3D) while a minimal operator interaction was incorporated for training and testing of the network. The user interaction guided the network to localize the placenta more accurately. In the experiments, we trained two CNNs, one using 70 normal training cases and the other using 129 training cases including normal cases as well as cases with suspected placenta accreta spectrum (PAS). We evaluated the performance of the segmentation algorithms on two test sets: one with 20 normal cases and the other with 50 images from both normal women and women with suspected PAS. Results: For the normal test data, the average Dice similarity coefficient (DSC) was 92% and 82% for the uterine cavity and placenta, respectively. For the combination of normal and abnormal cases, the DSC was 88% and 83% for the uterine cavity and placenta, respectively. The 3D segmentation algorithm estimated the volume of the normal and abnormal uterine cavity and placenta with average volume estimation errors of 4% and 9%, respectively. Conclusions: The deep learning-based segmentation method provides a useful tool for volume estimation and analysis of the placenta and uterus cavity in human placental imaging.

Transvaginal Color Mapping Ultrasound in the First Trimester Predicts Placenta Accreta Spectrum: A Retrospective Cohort Study.

OBJECTIVES: Ultrasound (US) prediction of placenta accreta spectrum (PAS) in the first trimester may be aided by postprocessing mechanisms employing color pixel quantification near the bladder-uterine serosal interface. Our objective was to create a postprocessing algorithm of color images to identify findings associated with PAS and compare quantification to sonologist impression in prospectively obtained cine US images. METHODS: Transverse transvaginal (TV) US color cines obtained in the first trimester as part of a prospective study were reviewed. Investigators blinded to clinical outcomes reviewed anonymized cines that were archived and labeled the bladder-uterine serosal interface. Color pixels within 2 cm of the defined bladder-uterine serosal interface were ascertained using a Python-based plugin in the Horos open-source DICOM viewer. A sonologist classified the findings as suspicious for invasion, indeterminate, or normal. Statistical analysis was performed using Wilcoxon rank-sum test, Cochran-Armitage trend test, and calculation of receiver-operating characteristic (ROC) curves. RESULTS: Fifty-four studies met inclusion criteria. Of those, six (11%) required hysterectomy with pathologic confirmation of PAS. Women requiring hysterectomy had a significantly higher color Doppler pixel area than those not requiring hysterectomy (P = .0205). A significant trend was identified in the sonologist impression of invasion (P = .0003). ROC's comparing sonologist impression to Doppler color imaging areas were comparable (P = .054). CONCLUSIONS: Color Doppler mapping in the first trimester showed an increase in color pixel area near the bladder-uterine serosal interface in women requiring cesarean hysterectomy with histologically confirmed PAS at time of delivery, compared to women without hysterectomy or pathologic evidence of PAS.

Assessing reproducibility in Magnetic Resonance (MR) Radiomics features between Deep-Learning segmented and Expert Manual segmented data and evaluating their diagnostic performance in Pregnant Women with suspected Placenta Accreta Spectrum (PAS).

A Deep-Learning (DL) based segmentation tool was applied to a new magnetic resonance imaging dataset of pregnant women with suspected Placenta Accreta Spectrum (PAS). Radiomic features from DL segmentation were compared to those from expert manual segmentation via intraclass correlation coefficients (ICC) to assess reproducibility. An additional imaging marker quantifying the placental location within the uterus (PLU) was included. Features with an ICC > 0.7 were used to build logistic regression models to predict hysterectomy. Of 2059 features, 781 (37.9%) had ICC >0.7. AUC was 0.69 (95% CI 0.63-0.74) for manually segmented data and 0.78 (95% CI 0.73-0.83) for DL segmented data.

How the Chemical Properties of GBCAs Influence Their Safety Profiles In Vivo.

The extracellular class of gadolinium-based contrast agents (GBCAs) is an essential tool for clinical diagnosis and disease management. In order to better understand the issues associated with GBCA administration and gadolinium retention and deposition in the human brain, the chemical properties of GBCAs such as relative thermodynamic and kinetic stabilities and their likelihood of forming gadolinium deposits in vivo will be reviewed. The chemical form of gadolinium causing the hyperintensity is an open question. On the basis of estimates of total gadolinium concentration present, it is highly unlikely that the intact chelate is causing the T1 hyperintensities observed in the human brain. Although it is possible that there is a water-soluble form of gadolinium that has high relaxitvity present, our experience indicates that the insoluble gadolinium-based agents/salts could have high relaxivities on the surface of the solid due to higher water access. This review assesses the safety of GBCAs from a chemical point of view based on their thermodynamic and kinetic properties, discusses how these properties influence in vivo behavior, and highlights some clinical implications regarding the development of future imaging agents.

Concentration-dependent Early Antivascular and Antitumor Effects of Itraconazole in Non-Small Cell Lung Cancer.

PURPOSE: Itraconazole has been repurposed as an anticancer therapeutic agent for multiple malignancies. In preclinical models, itraconazole has antiangiogenic properties and inhibits Hedgehog pathway activity. We performed a window-of-opportunity trial to determine the biologic effects of itraconazole in human patients. EXPERIMENTAL DESIGN: Patients with non-small cell lung cancer (NSCLC) who had planned for surgical resection were administered with itraconazole 300 mg orally twice daily for 10-14 days. Patients underwent dynamic contrast-enhanced MRI and plasma collection for pharmacokinetic and pharmacodynamic analyses. Tissues from pretreatment biopsy, surgical resection, and skin biopsies were analyzed for itraconazole and hydroxyitraconazole concentration, and vascular and Hedgehog pathway biomarkers. RESULTS: Thirteen patients were enrolled in this study. Itraconazole was well-tolerated. Steady-state plasma concentrations of itraconazole and hydroxyitraconazole demonstrated a 6-fold difference across patients. Tumor itraconazole concentrations trended with and exceeded those of plasma. Greater itraconazole levels were significantly and meaningfully associated with reduction in tumor volume (Spearman correlation, -0.71; P = 0.05) and tumor perfusion (Ktrans; Spearman correlation, -0.71; P = 0.01), decrease in the proangiogenic cytokines IL1b (Spearman correlation, -0.73; P = 0.01) and GM-CSF (Spearman correlation, -1.00; P < 0.001), and reduction in tumor microvessel density (Spearman correlation, -0.69; P = 0.03). Itraconazole-treated tumors also demonstrated distinct metabolic profiles. Itraconazole treatment did not alter transcription of GLI1 and PTCH1 mRNA. Patient size, renal function, and hepatic function did not predict itraconazole concentrations. CONCLUSIONS: Itraconazole demonstrates concentration-dependent early antivascular, metabolic, and antitumor effects in patients with NSCLC. As the number of fixed dose cancer therapies increases, attention to interpatient pharmacokinetics and pharmacodynamics differences may be warranted.

Glutamine uptake and utilization of human mesenchymal glioblastoma in orthotopic mouse model.

BACKGROUND: Glioblastoma (GBM) are highly heterogeneous on the cellular and molecular basis. It has been proposed that glutamine metabolism of primary cells established from human tumors discriminates aggressive mesenchymal GBM subtype to other subtypes. METHODS: To study glutamine metabolism in vivo, we used a human orthotopic mouse model for GBM. Tumors evolving from the implanted primary GBM cells expressing different molecular signatures were analyzed using mass spectrometry for their metabolite pools and enrichment in carbon 13 (13C) after 13C-glutamine infusion. RESULTS: Our results showed that mesenchymal GBM tumors displayed increased glutamine uptake and utilization compared to both control brain tissue and other GBM subtypes. Furthermore, both glutamine synthetase and transglutaminase-2 were expressed accordingly to GBM metabolic phenotypes. CONCLUSION: Thus, our results outline the specific enhanced glutamine flux in vivo of the aggressive mesenchymal GBM subtype.