T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology.

OBJECTIVES: To explore the associations between T1 and T2 magnetic resonance fingerprinting (MRF) measurements and corresponding tissue compartment ratios (TCRs) on whole mount histopathology of prostate cancer (PCa) and prostatitis. MATERIALS AND METHODS: A retrospective, IRB-approved, HIPAA-compliant cohort consisting of 14 PCa patients who underwent 3 T multiparametric MRI along with T1 and T2 MRF maps prior to radical prostatectomy was used. Correspondences between whole mount specimens and MRI and MRF were manually established. Prostatitis, PCa, and normal peripheral zone (PZ) regions of interest (ROIs) on pathology were segmented for TCRs of epithelium, lumen, and stroma using two U-net deep learning models. Corresponding ROIs were mapped to T2-weighted MRI (T2w), apparent diffusion coefficient (ADC), and T1 and T2 MRF maps. Their correlations with TCRs were computed using Pearson's correlation coefficient (R). Statistically significant differences in means were assessed using one-way ANOVA. RESULTS: Statistically significant differences (p < 0.01) in means of TCRs and T1 and T2 MRF were observed between PCa, prostatitis, and normal PZ. A negative correlation was observed between T1 and T2 MRF and epithelium (R = - 0.38, - 0.44, p < 0.05) of PCa. T1 MRF was correlated in opposite directions with stroma of PCa and prostatitis (R = 0.35, - 0.44, p < 0.05). T2 MRF was positively correlated with lumen of PCa and prostatitis (R = 0.57, 0.46, p < 0.01). Mean T2 MRF showed significant differences (p < 0.01) between PCa and prostatitis across both transition zone (TZ) and PZ, while mean T1 MRF was significant (p = 0.02) in TZ. CONCLUSION: Significant associations between MRF (T1 in the TZ and T2 in the PZ) and tissue compartments on corresponding histopathology were observed. KEY POINTS: • Mean T2 MRF measurements and ADC within cancerous regions of interest dropped with increasing ISUP prognostic groups (IPG). • Mean T1 and T2 MRF measurements were significantly different (p < 0.001) across IPGs, prostatitis, and normal peripheral zone (NPZ). • T2 MRF showed stronger correlations in the peripheral zone, while T1 MRF showed stronger correlations in the transition zone with histopathology for prostate cancer.

Multidisciplinary approach for repeat musculoskeletal lesion biopsy after nondiagnostic initial sampling: A 10-year single-center experience.

BACKGROUND AND OBJECTIVES: Success rates for initial image-guided biopsy of musculoskeletal (MSK) lesions have been well documented; evidence regarding success rates for repeat biopsy following initially nondiagnostic (ND) image-guided biopsy of MSK lesions is more limited. This study evaluates the outcomes of repeat computerized tomography-guided MSK biopsies following ND biopsies using a multidisciplinary approach. MATERIALS AND METHODS: Electronic medical record search covering a 10-year period identified patients that received two or more biopsies for an MSK tumor or tumor-like process. The decision for initial and repeat image-guided biopsy of each lesion was made following multidisciplinary MSK tumor board review. Lesion location, histopathology results, size of biopsy needle when available, and change in technique between biopsy attempts was documented. RESULTS: Repeat biopsy rate was 1.6%. 23 patients with repeat MSK biopsy were identified. A total of 17 of 23 (74%) repeat biopsy attempts were diagnostic. A total of 22 of 23 (96%) repeat biopsy attempts were clinically useful. Diagnostic repeat biopsies were described as employing one or more of five technical differences compared to the first biopsy attempt, the most common being improved targeting of the lesion itself. CONCLUSIONS: A multidisciplinary approach may yield improved repeat-biopsy rates and clinical utility of repeat MSK biopsies compared to prior reports.

Subtypes of Barrett's oesophagus and oesophageal adenocarcinoma based on genome-wide methylation analysis.

OBJECTIVE: To identify and characterise DNA methylation subtypes in oesophageal adenocarcinoma (EAC) and its precursor Barrett's oesophagus (BE). DESIGN: We performed genome-wide DNA methylation profiling on samples of non-dysplastic BE from cancer-free patients (n=59), EAC (n=23), normal squamous oesophagus (n=33) and normal fundus (n=9), and identified methylation subtypes using a recursively partitioned mixture model. We assessed genomic alterations for 9 BE and 22 EAC samples with massively parallel sequencing of 243 EAC-associated genes, and we conducted integrative analyses with transcriptome data to identify epigenetically repressed genes. We also carried out in vitro experiments treating EAC cell lines with 5-Aza-2'-Deoxycytidine (5-Aza-dC), short hairpin RNA knockdown and anticancer therapies. RESULTS: We identified and validated four methylation subtypes of EAC and BE. The high methylator subtype (HM) of EAC had the greatest number of activating events in ERBB2 (p<0.05, Student's t-test) and the highest global mutation load (p<0.05, Fisher's exact test). PTPN13 was silenced by aberrant methylation in the HM subtype preferentially and in 57% of EACs overall. In EAC cell lines, 5-Aza-dC treatment restored PTPN13 expression and significantly decreased its promoter methylation in HM cell lines (p<0.05, Welch's t-test). Inhibition of PTPN13 expression in the SK-GT-4 EAC cell line promoted proliferation, colony formation and migration, and increased phosphorylation in ERBB2/EGFR/Src kinase pathways. Finally, EAC cell lines showed subtype-specific responses to topotecan, SN-38 and palbociclib treatment. CONCLUSIONS: We identified and characterised methylator subtypes in BE and EAC. We further demonstrated the biological and clinical relevance of EAC methylator subtypes, which may ultimately help guide clinical management of patients with EAC.

Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging.

PURPOSE: To determine the best features to discriminate prostate cancer from benign disease and its relationship to benign disease class and cancer grade. MATERIALS AND METHODS: The institutional review board approved this study and waived the need for informed consent. A retrospective cohort of 70 patients (age range, 48-70 years; median, 62 years), all of whom were scheduled to undergo radical prostatectomy and underwent preoperative 3-T multiparametric magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging, were included. The digitized prostatectomy slides were annotated for cancer and noncancerous disease and coregistered to MR imaging with an interactive deformable coregistration scheme. Computer-identified features for each of the noncancerous disease categories (eg, benign prostatic hyperplasia [BPH], prostatic intraepithelial neoplasia [PIN], inflammation, and atrophy) and prostate cancer were extracted. Feature selection was performed to identify the features with the highest discriminatory power. The performance of these five features was evaluated by using the area under the receiver operating characteristic curve (AUC). RESULTS: High-b-value diffusion-weighted images were more discriminative in distinguishing BPH from prostate cancer than apparent diffusion coefficient, which was most suitable for distinguishing PIN from prostate cancer. The focal appearance of lesions on dynamic contrast-enhanced images may help discriminate atrophy and inflammation from cancer. Which imaging features are discriminative for different benign lesions is influenced by cancer grade. The apparent diffusion coefficient appeared to be the most discriminative feature in identifying high-grade cancer. Classification results showed increased performance by taking into account specific benign types (AUC = 0.70) compared with grouping all noncancerous findings together (AUC = 0.62). CONCLUSION: The best features with which to discriminate prostate cancer from noncancerous benign disease depend on the type of benign disease and cancer grade. Use of the best features may result in better diagnostic performance.

A practical approach to remote longitudinal follow-up of Parkinson's disease: the FOUND study.

The objective of this study was to examine a remote method for maintaining long-term contact with Parkinson's disease (PD) patients participating in clinical studies. Long-term follow-up of PD patients is needed to fill critical information gaps on progression, biomarkers, and treatment. Prospective in-person assessment can be costly and may be impossible for some patients. Remote assessment using mail and telephone contact may be a practical follow-up method. Patients enrolled in the multi-center Longitudinal and Biomarker Study in Parkinson's Disease (LABS-PD) in-person follow-up study in 2006 were invited to enroll in Follow-up of Persons With Neurologic Diseases (FOUND), which is overseen by a single center under a separate, central institutional review board protocol. FOUND uses mailed questionnaires and telephone interviews to assess PD status. FOUND follow-up continued when LABS-PD in-person visits ended in 2011. Retention and agreement between remote and in-person assessments were determined. In total, 422 of 499 (84.5%) of eligible patients volunteered, AND 96% of participants were retained. Of 60 patients who withdrew consent from LABS-PD, 51 were retained in FOUND. Of 341 patients who were active in LABS-PD, 340 were retained in FOUND (99.7%) when the in-person visits ceased. Exact agreement between remote and in-person assessments was ≥ 80% for diagnosis, disease features (eg, dyskinesias), and PD medication. Correlation between expert-rated and self-reported Unified Parkinson's Disease Rating Scale and Movement Disorder Society Unified Parkinson's Disease Rating Scale, which were examined at times separated by several months, was moderate or substantial for most items. Retention was excellent using remote follow-up of research participants with PD, providing a safety net when combined with in-person visits, and also is effective as a stand-alone assessment method, providing a useful alternative when in-person evaluation is not feasible.

An integrated radiology-pathology machine learning classifier for outcome prediction following radical prostatectomy: Preliminary findings.

Objectives: To evaluate the added benefit of integrating features from pre-treatment MRI (radiomics) and digitized post-surgical pathology slides (pathomics) in prostate cancer (PCa) patients for prognosticating outcomes post radical-prostatectomy (RP) including a) rising prostate specific antigen (PSA), and b) extraprostatic-extension (EPE). Methods: Multi-institutional data (N = 58) of PCa patients who underwent pre-treatment 3-T MRI prior to RP were included in this retrospective study. Radiomic and pathomic features were extracted from PCa regions on MRI and RP specimens delineated by expert clinicians. On training set (D1, N = 44), Cox Proportional-Hazards models MR, MP and MRaP were trained using radiomics, pathomics, and their combination, respectively, to prognosticate rising PSA (PSA > 0.03 ng/mL). Top features from MRaP were used to train a model to predict EPE on D1 and test on external dataset (D2, N = 14). C-index, Kalplan-Meier curves were used for survival analysis, and area under ROC (AUC) was used for EPE. MRaP was compared with the existing post-treatment risk-calculator, CAPRA (MC). Results: Patients had median follow-up of 34 months. MRaP (c-index = 0.685 ± 0.05) significantly outperformed MR (c-index = 0.646 ± 0.05), MP (c-index = 0.631 ± 0.06) and MC (c-index = 0.601 ± 0.071) (p < 0.0001). Cross-validated Kaplan-Meier curves showed significant separation among risk groups for rising PSA for MRaP (p < 0.005, Hazard Ratio (HR) = 11.36) as compared to MR (p = 0.64, HR = 1.33), MP (p = 0.19, HR = 2.82) and MC (p = 0.10, HR = 3.05). Integrated radio-pathomic model MRaP (AUC = 0.80) outperformed MR (AUC = 0.57) and MP (AUC = 0.76) in predicting EPE on external-data (D2). Conclusions: Results from this preliminary study suggest that a combination of radiomic and pathomic features can better predict post-surgical outcomes (rising PSA and EPE) compared to either of them individually as well as extant prognostic nomogram (CAPRA).

Generation and characterization of fully human monoclonal antibodies against human Orai1 for autoimmune disease.

Calcium entry into T cells following antigen stimulation is crucial for nuclear factor of activated T cells (NFAT)-mediated T cell activation. The movement of calcium is mediated by calcium release-activated calcium (CRAC) channels. There are two key components of this channel: Orai1 is the pore-forming subunit located in the plasma membrane, and stromal interaction molecule 1 (STIM1) functions as a Ca(2+) sensor in the endoplasmic reticulum. A subset of human patients carry mutations in either STIM1 or Orai1 that affect protein function or expression, resulting in defective store-operated Ca(2+) influx and CRAC channel function, and impaired T cell activation. These patients suffer from a hereditary form of severe combined immune deficiency syndrome, highlighting the importance of the CRAC channel for T lymphocyte function in humans. Since autoreactive T cells play an important role in the development of autoimmune diseases such as rheumatoid arthritis, multiple sclerosis, and organ transplantation, Orai1 becomes an attractive therapeutic target for ameliorating autoimmune disease. We developed a novel approach to inhibiting CRAC function by generating high-affinity fully human monoclonal antibodies to human Orai1. These antibodies inhibited ICRAC current, store-operated Ca(2+) influx, NFAT transcription, and cytokine release. These fully human antibodies to human Orai1 may represent a novel therapeutic approach for the treatment of autoimmunity.

Advancing Fellowship Training in Selective Pathology.

CONTEXT.­: Program requirements for Selective Pathology fellowships in the United States were established by the Accreditation Council for Graduate Medical Education (ACGME) in 2011 to govern fellowships providing advanced training in surgical pathology, focused anatomic pathology, or focused clinical pathology. Selective Pathology entered the ACGME's Next Accreditation System in 2015 with the introduction of the Selective Pathology Milestones 1.0, a set of benchmarks for evaluating fellow progress in each of the 6 ACGME core competencies. In 2019, the ACGME convened a work group for a planned periodic update to these milestones. OBJECTIVE.­: To summarize changes to the Selective Pathology milestones. DESIGN.­: The study design featured expert opinion and survey. RESULTS.­: The Patient Care milestones for anatomic pathology-focused fellowships contain a renewed emphasis on both gross and microscopic examination, whereas for clinical pathology-focused fellowships, the emphasis is on interpretation of laboratory assays. The milestones for the non-Patient Care, non-Medical Knowledge competencies have been updated to a harmonized set of milestones designed to extend across all specialties and subspecialties. New to the milestones program is a supplemental guide that provides examples, suggested assessment tools, and references to aid in implementation. Public comments were supportive of the changes. CONCLUSIONS.­: The Milestones 2.0 are set for implementation in July 2021. Updates in the new milestones are aimed at facilitating training and harmonizing evaluation across subspecialties.

Recurrence of Epidural Spinal Sarcoidosis.

Neurosarcoidosis involving the spine is uncommon. Sarcoidosis of the spine usually presents as an intramedullary lesion and rarely an epidural lesion. To have recurrence of neurosarcoidosis is an even rarer presentation. Here, we present a 37-year-old man with poorly controlled sarcoidosis who initially presented to our medical center in 2015 with thoracic myelopathy from epidural spinal sarcoidosis treated with thoracic decompression and fusion. He presented to the hospital 5 years later with a month history of progressive upper extremity weakness. MRI revealed recurrent stenosis and spinal cord compression in the cervicothoracic junction. Urgent surgical intervention along with medical management resulted in symptomatic and functional improvement. Surgical intervention and compliance with postoperative corticosteroid therapy seem to yield a favorable prognosis for patients with epidural spinal sarcoidosis and to avoid recurrence.

Hyaline fibromatosis syndrome: A rare case of multifocal intra-articular involvement.

Hyaline fibromatosis syndrome (HFS) is a rare, progressive, autosomal recessive disorder that presents with connective tissue deposition of amorphous hyaline material within the musculocutaneous tissue and/or visceral organs. HFS presents clinically in infancy or early childhood and can result in severe disability and life threatening complications. Given the rarity of the disorder, the imaging characteristics of HFS are seldom described in the literature. We describe a case of a 25-year-old patient presenting with bilateral knee pain, limited range of motion in her extremities, and lower extremity weakness with detailed MR imaging demonstrating the first case of multifocal intra-articular deposition of hyaline material within several joints.

Benign Metastasizing Leiomyoma in the Heart of a 45-Year-Old Woman.

We report a rare case of benign metastasizing leiomyoma in the heart of a 45-year-old woman 2 years after a uterine leiomyoma had been discovered during hysterectomy. Computed tomograms at presentation showed a large mixed cystic mass in the pelvis and bilateral lung nodules suggestive of metastatic disease. A large cardiac mass, attached to the chordae of the tricuspid valve and later shown to be histopathologically consistent with uterine leiomyoma, was successfully resected through a right atriotomy. This case suggests that benign metastasizing leiomyoma should be considered in the differential diagnosis of right-sided cardiac tumors.

Molecular Profiling of Pediatric and Adult Glioblastoma.

OBJECTIVES: Although glioblastoma (GBM) is rare in the pediatric population, it is the most common cause of death among children with central nervous system neoplasms. Recent molecular profiling of these neoplasms has demonstrated distinct differences in comparison to their adult counterparts. Moreover, many pediatric GBMs occur within the context of cancer predisposition syndromes, such as constitutional mismatch repair deficiency syndrome (CMMRD). Children with CMMRD who develop GBM exhibit a high tumor mutational burden and may benefit from treatment with immune checkpoint inhibitors. METHODS: We performed next-generation sequencing and immunohistochemistry for mismatch repair proteins in our cohort of pediatric and adult GBMs to further characterize the molecular profiles of these groups. RESULTS: We examined a total of 11 pediatric and 11 adult GBMs. Pediatric patients had a higher number of alterations compared to their adult counterparts. They also had a higher frequency of alterations in the mismatch repair genes, which can be detected by immunohistochemistry (IHC). We also identified one pediatric patient with CMMRD syndrome. CONCLUSIONS: Our study highlighted the distinct molecular differences between pediatric and adult GBM. We also demonstrated that pediatric patients have a higher frequency of alterations in the mismatch repair genes, which may render them susceptible to treatment with immune checkpoint inhibitors. These alterations can be detected using routine IHC and should be performed on all pediatric GBM.

Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2.

BACKGROUND: The presence of invasive cribriform adenocarcinoma (ICC), an expanse of cells containing punched-out lumina uninterrupted by stroma, in radical prostatectomy (RP) specimens has been associated with biochemical recurrence (BCR). However, ICC identification has only moderate inter-reviewer agreement. OBJECTIVE: To investigate quantitative machine-based assessment of the extent and prognostic utility of ICC, especially within individual Gleason grade groups. DESIGN, SETTING, AND PARTICIPANTS: A machine learning approach was developed for ICC segmentation using 70 RP patients and validated in a cohort of 749 patients from four sites whose median year of surgery was 2007 and with median follow-up of 28 mo. ICC was segmented on one representative hematoxylin and eosin RP slide per patient and the fraction of tumor area composed of ICC, the cribriform area index (CAI), was measured. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR). RESULTS AND LIMITATIONS: CAI was correlated with BCR (c index 0.62) in the validation set of 411 patients with ICC morphology, especially those with Gleason grade group 2 cancer (n = 192; c index 0.66), and was less prognostic when patients without ICC were included (c index 0.54). A doubling of CAI in the group with ICC morphology was prognostic after controlling for Gleason grade, surgical margin positivity, preoperative prostate-specific antigen level, pathological T stage, and age (HR 1.19, 95% confidence interval 1.03-1.38; p = 0.018). CONCLUSIONS: Automated image analysis and machine learning could provide an objective, quantitative, reproducible, and high-throughput method of quantifying ICC area. The performance of CAI for grade group 2 cancer suggests that for patients with little Gleason 4 pattern, the ICC fraction has a strong prognostic role. PATIENT SUMMARY: Machine-based measurement of a specific cell pattern (cribriform; sieve-like, with lots of spaces) in images of prostate specimens could improve risk stratification for patients with prostate cancer. In the future, this could help in expanding the criteria for active surveillance.

Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study.

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests.

Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance.

In this work, we assessed the ability of computerized features of nuclear morphology from diagnostic biopsy images to predict prostate cancer (CaP) progression in active surveillance (AS) patients. Improved risk characterization of AS patients could reduce over-testing of low-risk patients while directing high-risk patients to therapy. A total of 191 (125 progressors, 66 non-progressors) AS patients from a single site were identified using The Johns Hopkins University's (JHU) AS-eligibility criteria. Progression was determined by pathologists at JHU. 30 progressors and 30 non-progressors were randomly selected to create the training cohort D1 (n = 60). The remaining patients comprised the validation cohort D2 (n = 131). Digitized Hematoxylin & Eosin (H&E) biopsies were annotated by a pathologist for CaP regions. Nuclei within the cancer regions were segmented using a watershed method and 216 nuclear features describing position, shape, orientation, and clustering were extracted. Six features associated with disease progression were identified using D1 and then used to train a machine learning classifier. The classifier was validated on D2. The classifier was further compared on a subset of D2 (n = 47) against pro-PSA, an isoform of prostate specific antigen (PSA) more linked with CaP, in predicting progression. Performance was evaluated with area under the curve (AUC). A combination of nuclear spatial arrangement, shape, and disorder features were associated with progression. The classifier using these features yielded an AUC of 0.75 in D2. On the 47 patient subset with pro-PSA measurements, the classifier yielded an AUC of 0.79 compared to an AUC of 0.42 for pro-PSA. Nuclear morphometric features from digitized H&E biopsies predicted progression in AS patients. This may be useful for identifying AS-eligible patients who could benefit from immediate curative therapy. However, additional multi-site validation is needed.

Extraprostatic extension in prostate cancer: primer for radiologists.

The presence of extraprostatic extension (EPE) on multiparametric MRI (mpMRI) is an important factor in determining the management of prostate cancer. EPE is an established risk factor for biochemical recurrence of prostate cancer after radical prostatectomy (RP) and patients with EPE may be considered for wider resection margins, non-nerve-sparing surgery, adjuvant radiation therapy (RT), or androgen deprivation therapy (ADT). Several statistical nomograms and scoring systems have been developed to predict pathological stage at time of RP but with varying accuracies. Using the current PI-RADS v2 mpMRI staging guidelines results in high specificity but lacks in sensitivity. These findings reveal the need for more standardization and further refinement of existing MRI protocols and prostate cancer prediction tools. Current studies have looked into indirect additional imaging criteria such as index tumor volume, length of capsular contact, and apparent diffusion coefficient. Measuring for these features can improve the robustness of mpMRI in staging prostate cancer, as they have been shown to be independent predictors of EPE. MRI/ultrasound fusion-guided targeted biopsy can detect EPE not found on standard biopsy. Collectively, these measurements and imaging techniques can augment the detection of EPE and subsequent risk stratification.

The crucial p53-dependent oncogenic role of JAB1 in osteosarcoma in vivo.

Osteosarcoma (OS) is the most common primary bone cancer and ranks amongst the leading causes of cancer mortality in young adults. Jun activation domain-binding protein 1 (JAB1) is overexpressed in many cancers and has recently emerged as a novel target for cancer treatment. However, the role of JAB1 in osteosarcoma was virtually unknown. In this study, we demonstrate that JAB1-knockdown in malignant osteosarcoma cell lines significantly reduced their oncogenic properties, including proliferation, colony formation, and motility. We also performed RNA-sequencing analysis in JAB1-knockdown OS cells and identified 4110 genes that are significantly differentially expressed. This demonstrated for the first time that JAB1 regulates a large and specific transcriptome in cancer. We also found that JAB1 is overexpressed in human OS and correlates with a poor prognosis. Moreover, we generated a novel mouse model that overexpresses Jab1 specifically in osteoblasts upon a TP53 heterozygous sensitizing background. Interestingly, by 13 months of age, a significant proportion of these mice spontaneously developed conventional OS. Finally, we demonstrate that a novel, highly specific small molecule inhibitor of JAB1, CSN5i-3, reduces osteosarcoma cell viability, and has specific effects on the ubiquitin-proteasome system in OS. Thus, we show for the first time that the overexpression of JAB1 in vivo can result in accelerated spontaneous tumor formation in a p53-dependent manner. In summary, JAB1 might be a unique target for the treatment of osteosarcoma and other cancers.