Visualizing allele-specific expression in single cells reveals epigenetic mosaicism in an H19 loss-of-imprinting mutant.

Imprinting is a classic mammalian epigenetic phenomenon that results in expression from a single parental allele. Imprinting defects can lead to inappropriate expression from the normally silenced allele, but it remains unclear whether every cell in a mutant organism follows the population average, which would have profound implications for human imprinting disorders. Here, we apply a new fluorescence in situ hybridization method that measures allele-specific expression in single cells to address this question in mutants exhibiting aberrant H19/Igf2 (insulin-like growth factor 2) imprinting. We show that mutant primary embryonic mouse fibroblasts are comprised of two subpopulations: one expressing both H19 alleles and another expressing only the maternal copy. Only in the latter cell population is Igf2 expression detected. Furthermore, the two subpopulations are stable in that cells do not interconvert between the two expression patterns. Combined small input methylation analysis and transcriptional imaging revealed that these two mutant subpopulations exhibit distinct methylation patterns at their imprinting control regions. Consistently, pharmacological inhibition of DNA methylation reduced the proportion of monoallelic cells. Importantly, we observed that the same two subpopulations are also present in vivo within murine cardiac tissue. Our results establish that imprinting disorders can display striking single-cell heterogeneity in their molecular phenotypes and suggest that such heterogeneity may underlie epigenetic mosaicism in human imprinting disorders.

Your mileage may vary: impact of data input method for a deep learning bone age app's predictions.

OBJECTIVE: The purpose of this study was to evaluate agreement in predictions made by a bone age prediction application ("app") among three data input methods. METHODS: The 16Bit Bone Age app is a browser-based deep learning application for predicting bone age on pediatric hand radiographs; recommended data input methods are direct image file upload or smartphone-capture of image. We collected 50 hand radiographs, split equally among 5 bone age groups. Three observers used the 16Bit Bone Age app to assess these images using 3 different data input methods: (1) direct image upload, (2) smartphone photo of image in radiology reading room, and (3) smartphone photo of image in a clinic. RESULTS: Interobserver agreement was excellent for direct upload (ICC = 1.00) and for photos in reading room (ICC = 0.96) and good for photos in clinic (ICC = 0.82), respectively. Intraobserver agreement for the entire test set across the 3 data input methods was variable with ICCs of 0.95, 0.96, and 0.57 for the 3 observers, respectively. DISCUSSION: Our findings indicate that different data input methods can result in discordant bone age predictions from the 16Bit Bone Age app. Further study is needed to determine the impact of data input methods, such as smartphone image capture, on deep learning app performance and accuracy.

One Algorithm May Not Fit All: How Selection Bias Affects Machine Learning Performance.

Machine learning (ML) algorithms have demonstrated high diagnostic accuracy in identifying and categorizing disease on radiologic images. Despite the results of initial research studies that report ML algorithm diagnostic accuracy similar to or exceeding that of radiologists, the results are less impressive when the algorithms are installed at new hospitals and are presented with new images. This phenomenon is potentially the result of selection bias in the data that were used to develop the ML algorithm. Selection bias has long been described by clinical epidemiologists as a key consideration when designing a clinical research study, but this concept has largely been unaddressed in the medical imaging ML literature. The authors discuss the importance of selection bias and its relevance to ML algorithm development to prepare the radiologist to critically evaluate ML literature for potential selection bias and understand how it might affect the applicability of ML algorithms in real clinical environments. ©RSNA, 2020.

Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.

PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment radiology residents by detecting missed pneumothoraces. METHODS: This was a retrospective study performed in September 2018. We obtained 112,120 chest radiographs (CXRs) from the NIH ChestXray14 database, of which 4360 cases (4%) were labeled as pneumothorax by natural language processing. We utilized 111,518 CXRs to train and validate the ResNet-152 DCNN pretrained on ImageNet to identify pneumothorax. DCNN testing was performed on a hold-out set of 602 CXRs, whose groundtruth was determined by a cardiothoracic radiologist. Two first-year radiology residents evaluated the test CXRs for presence of pneumothorax. Receiver operating characteristic (ROC) curves were generated for each evaluator with area under the curve (AUC) compared using the DeLong parametric method. RESULTS: The DCNN achieved AUC of 0.841 for identification of pneumothorax at a rate of 1980 images/min. In contrast, both first-year residents achieved significantly higher AUCs of 0.942 and 0.905 (p < 0.01 for both compared to DCNN), but at a slower rate of two images/min. The DCNN identified 3 of 31 (9.7%) additional pneumothoraces missed by at least one of the residents. CONCLUSION: A DLS for pneumothorax identification had lower AUC than 1st-year radiology residents, but interpreted images > 1000× as fast and identified 3 additional pneumothoraces missed by the residents. Our findings suggest that DLS could augment radiologists-in-training to identify potential urgent findings.

Beckwith-Wiedemann syndrome in diverse populations.

Beckwith-Wiedemann syndrome (BWS) is the most common epigenetic overgrowth disorder and presents with patients affected by a variety of clinical features. Although genotype-phenotype correlations have been demonstrated in BWS and although BWS has been reported to occur equally among racial and ethnic backgrounds, no study to date has evaluated the frequency of findings in different backgrounds. In this study, we evaluated the incidence of clinical features and molecular diagnoses among patients with BWS in Caucasian, Mixed, and non-Caucasian groups. These results suggest that clinical features and molecular diagnoses differ between race/ethnicity groups and raise the possibility of race and ethnicity effects on genotype-phenotype correlations in BWS.

Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.

Machine learning has several potential uses in medical imaging for semantic labeling of images to improve radiologist workflow and to triage studies for review. The purpose of this study was to (1) develop deep convolutional neural networks (DCNNs) for automated classification of 2D mammography views, determination of breast laterality, and assessment and of breast tissue density; and (2) compare the performance of DCNNs on these tasks of varying complexity to each other. We obtained 3034 2D-mammographic images from the Digital Database for Screening Mammography, annotated with mammographic view, image laterality, and breast tissue density. These images were used to train a DCNN to classify images for these three tasks. The DCNN trained to classify mammographic view achieved receiver-operating-characteristic (ROC) area under the curve (AUC) of 1. The DCNN trained to classify breast image laterality initially misclassified right and left breasts (AUC 0.75); however, after discontinuing horizontal flips during data augmentation, AUC improved to 0.93 (p < 0.0001). Breast density classification proved more difficult, with the DCNN achieving 68% accuracy. Automated semantic labeling of 2D mammography is feasible using DCNNs and can be performed with small datasets. However, automated classification of differences in breast density is more difficult, likely requiring larger datasets.

Development of a Combined MR Fingerprinting and Diffusion Examination for Prostate Cancer.

Purpose To develop and evaluate an examination consisting of magnetic resonance (MR) fingerprinting-based T1, T2, and standard apparent diffusion coefficient (ADC) mapping for multiparametric characterization of prostate disease. Materials and Methods This institutional review board-approved, HIPAA-compliant retrospective study of prospectively collected data included 140 patients suspected of having prostate cancer. T1 and T2 mapping was performed with fast imaging with steady-state precession-based MR fingerprinting with ADC mapping. Regions of interest were drawn by two independent readers in peripheral zone lesions and normal-appearing peripheral zone (NPZ) tissue identified on clinical images. T1, T2, and ADC were recorded for each region. Histopathologic correlation was based on systematic transrectal biopsy or cognitively targeted biopsy results, if available. Generalized estimating equations logistic regression was used to assess T1, T2, and ADC in the differentiation of (a) cancer versus NPZ, (b) cancer versus prostatitis, (c) prostatitis versus NPZ, and (d) high- or intermediate-grade tumors versus low-grade tumors. Analysis was performed for all lesions and repeated in a targeted biopsy subset. Discriminating ability was evaluated by using the area under the receiver operating characteristic curve (AUC). Results In this study, 109 lesions were analyzed, including 39 with cognitively targeted sampling. T1, T2, and ADC from cancer (mean, 1628 msec ± 344, 73 msec ± 27, and 0.773 × 10-3 mm2/sec ± 0.331, respectively) were significantly lower than those from NPZ (mean, 2247 msec ± 450, 169 msec ± 61, and 1.711 × 10-3 mm2/sec ± 0.269) (P < .0001 for each) and together produced the best separation between these groups (AUC = 0.99). ADC and T2 together produced the highest AUC of 0.83 for separating high- or intermediate-grade tumors from low-grade cancers. T1, T2, and ADC in prostatitis (mean, 1707 msec ± 377, 79 msec ± 37, and 0.911 × 10-3 mm2/sec ± 0.239) were significantly lower than those in NPZ (P < .0005 for each). Interreader agreement was excellent, with an intraclass correlation coefficient greater than 0.75 for both T1 and T2 measurements. Conclusion This study describes the development of a rapid MR fingerprinting- and diffusion-based examination for quantitative characterization of prostatic tissue. © RSNA, 2017 Online supplemental material is available for this article.

Three-Dimensional Printing Facilitates Successful Endovascular Closure of a Type II Abernethy Malformation Using an Amplatzer Atrial Septal Occluder Device.

Type II Abernethy malformations, characterized by side-to-side portosystemic shunting with preserved intrahepatic portal venous system, have been treated with shunt closure surgically and endovascularly. Three-dimensional printing has been used to develop highly accurate patient-specific representations for surgical and endovascular planning and intervention. This innovation describes 3-dimensional printing to successfully close a flush-oriented type II Abernethy malformation with discrepant dimensions on computed tomography, conventional venography, and intravascular ultrasound, using a 12-mm Amplatzer atrial septal occluder device.

Speech and Swallowing Outcomes of Surgically Managed Cervical Chordoma: A Case Series.

OBJECTIVES: Cervical chordoma is a rare, low-grade primary bone tumor occurring in the axial skeleton. Due to challenges in surgical exposure caused by anatomic location, patients may experience dysfunction in speech and swallowing. The objective of this study was to characterize speech and swallowing outcomes for patients undergoing surgical resection of cervical chordoma. Moreover, we detail in-depth two cases with similar initial presentations to compare prognostic factors and management strategies. METHODS: Eleven patients with histologically confirmed cervical chordoma treated between 1993 and 2020 were included in this retrospective case series. Outcomes measured included overall survival, disease-free survival, need for enteral feeds, as well as results of modified barium swallow study (MBSS) and fiberoptic laryngoscopy. RESULTS: The mean age at diagnosis was 55.9 years. The patient population was 81.8% male. Mean survival after diagnosis was 96 months. Four (36.4%) patients required post-operative MBSS and demonstrated aspiration. All four of these patients presented with tumors in the superior cervical spine and received surgeries utilizing anterior approaches. Of the four, 2 required enteral feeds long-term. Four (36.4%) patients endorsed dysphonia. One patient developed post-operative right vocal fold paresis. The remaining three patients experienced stable dysphonia pre- and post-operatively. Additionally, three (27%) patients required tracheostomy placement, two of which remained in place long-term. CONCLUSIONS: Dysphagia is a common side effect of cervical chordoma resection. It is associated with the use of an anterior approach during resection and with tumors located in the superior cervical spine. Patients with postoperative dysphagia should receive early multidisciplinary swallow rehabilitation. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:3706-3712, 2024.

Improved Survival of Advanced-Stage Anaplastic Thyroid Cancer With Systemic Therapy.

OBJECTIVES: Anaplastic thyroid cancer (ATC) is the most aggressive and fatal thyroid malignancy. Currently, there still exists a paucity of literature studying the relationship between available ATC-targeted therapy, immunotherapy, and survival. We aim to investigate how systemic therapies affect survival outcomes in ATC. METHODS: A single-tertiary-institution chart review of patients diagnosed with advanced-stage ATC, and who underwent surgery as part of their treatment, was performed between 2000 and 2023, with 41 patients included. Demographics, clinical characteristics, and survival data were collected and analyzed via Kaplan-Meier and Cox proportional hazards analyses. RESULTS: 54% of patients were female, and average age was 67.4 years old. The most common mutations identified were BRAF (15 patients), p53 (9 patients), and p63 (2 patients). A total of 18 patients utilized targeted or immunotherapy, with Trametinib and Dabrafenib (9 patients) as the most common agents used. Two-year overall survival was 24%, and 5-year overall survival was 23%, with median survival time of 7.6 months. Kaplan-Meier analysis demonstrated improved survival in patients who received chemotherapy (p = 0.048). Cox proportional hazards analysis demonstrated that patients treated with immunotherapy or targeted therapy had a statistically significant increase in survival compared with patients who did not receive these therapies (p = 0.016). Additionally, females and those with a p63 mutation demonstrated improved survival outcomes (p = 0.010, p = 0.001). CONCLUSIONS: Targeted therapy and immunotherapy use should be strongly considered when treating patients with ATC. Further studies into novel drugs targeting immune checkpoints and combination therapy are needed to better optimize treatment of patients with ATC. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Anaplastic Transformation of Differentiated Thyroid Carcinoma.

OBJECTIVES: Anaplastic thyroid carcinoma (ATC) is a rare but highly aggressive form of thyroid cancer. Increasingly, patients with ATC present with concurrent foci of well-differentiated thyroid carcinoma (WDTC); however, the significance of these pathologic findings remains unclear. The objective of this study is to determine whether the presence of WDTC within anaplastic tumors is a prognosticator of survival. METHODS: A retrospective cohort study of all cases of biopsy-proven ATC managed at a tertiary care academic medical center from 2002 to 2020 was performed. Mean age at diagnosis, median survival time, and locations of distant metastases were assessed. The impact of clinical markers such as presence of differentiation, demographic variables, and oncologic information on overall survival was also determined via univariate and multivariate analysis. RESULTS: Forty-five patients were included in this study. The mean age at diagnosis was 69.1 years. Median survival time was 6.1 months after diagnosis. The most common location of distant metastases was the lung (40%). The presence of limited areas of WDTC in patients with predominantly anaplastic thyroid tumors was not significantly associated with improved outcomes (p = 0.509). Smaller tumor size and use of chemotherapy in ATC patients were significantly associated with prolonged survival (p = 0.026 and 0.010, respectively). CONCLUSIONS: Clinical outcomes for ATC remain poor. The presence of foci of differentiation within anaplastic thyroid tumors does not appear to improve overall survival-the anaplastic component evidently drives outcomes. Further studies into novel therapies are needed to improve survival in ATC. LEVEL OF EVIDENCE: 4 Laryngoscope, 133:437-442, 2023.

Predictors of Death, Survival, Need for Intubation, and Need for Oxygen Support Among Admitted COVID-19 Patients of the Veterans Affairs Greater Los Angeles Healthcare System.

INTRODUCTION: While risk factors for severe COVID-19 infections have been well explored among the public, population-specific studies for the U.S. Veteran community are limited in the literature. By performing a comprehensive analysis of the demographics, comorbidities, and symptomatology of a population of COVID-19 positive Veterans Affairs (VA) patients, we aim to uncover predictors of death, survival, need for intubation, and need for nasal cannula oxygen support among this understudied community. MATERIALS AND METHODS: A retrospective review was conducted of 124 COVID-19 Veteran patients who were admitted from March to October 2020 to the VA Greater Los Angeles Healthcare System (IRB#2020-000272). Chi-square and Fisher's exact tests were employed to assess differences in baseline demographic and clinical variables between Veterans who survived COVID-19 versus those who succumbed to COVID-19 illness. Multivariate logistic regression and Cox regression analyses were employed to assess predictors of outcome variables, including death, survival, need for intubation, and need for oxygen support (via nasal cannula). Covariates included a wide range of demographic, comorbidity-related, symptom-related, and summary index variables. RESULTS: Our study population consisted of primarily senior (average age was 73) Caucasian and African American (52.5% and 40.7%, respectively) Veterans. Bivariate analyses indicated that need for intubation was significantly associated with mortality (P = 0.002). Multivariate analyses revealed that age (P < 0.001, adjusted odds ratio (OR) = 1.16), dyspnea (P = 0.015, OR = 7.73), anorexia (P = 0.022, OR = 16.55), initial disease severity as classified by WHO (P = 0.031, OR = 4.55), and having more than one of the three most common comorbidities (hypertension, diabetes, and cardiac disease) and symptoms (cough, fever, and dyspnea) among our sample (P = 0.009; OR = 19.07) were independent predictors of death. Furthermore, age (P < 0.001, hazard ratio (HR) = 1.14), cerebrovascular disease (P = 0.022, HR = 3.76), dyspnea (P < 0.001, HR = 7.71), anorexia (P < 0.001, HR = 16.75), and initial disease severity as classified by WHO (P = 0.025, HR = 3.30) were independent predictors of poor survival. Finally, dyspnea reliably predicted need for intubation (P = 0.019; OR = 29.65). CONCLUSIONS: Several independent predictors of death, survival, and need for intubation were identified. These risk factors may provide guidelines for risk-stratifying Veterans upon admission to VA hospitals. Additional investigations of COVID-19 prognosis should be conducted on the larger U.S. Veteran population to confirm our findings and add to the current body of literature.

Management of post-COVID-19 olfactory dysfunction.

Purpose of Review: Olfactory dysfunction is a frequent complication of SARS-CoV-2 infection. This review presents the current literature regarding the management of post-COVID-19 olfactory dysfunction (PCOD). Recent Findings: A systematic review of the literature using the PubMed/MEDLINE, EMBASE, and Cochrane databases for the following keywords, "Covid-19," "SARS-CoV-2," "anosmia," "olfactory," "treatment," and "management" was performed. While most cases of post-COVID-19 olfactory dysfunction resolve spontaneously within 2 weeks of symptom onset, patients with symptoms that persist past 2 weeks require medical management. The intervention with the greatest degree of supporting evidence is olfactory training, wherein patients are repeatedly exposed to potent olfactory stimuli. To date, no large-scale randomized clinical trials exist that examine the efficacy of pharmacologic therapies for PCOD. Limited clinical trials and prospective controlled trials suggest intranasal corticosteroids and oral corticosteroids may alleviate symptoms. Summary: Olfactory training should be initiated as soon as possible for patients with PCOD. Patients may benefit from a limited intranasal or oral corticosteroid course. Further research on effective pharmacologic therapies for PCOD is required to manage the growing number of patients with this condition.

External Validation of Deep Learning Algorithms for Radiologic Diagnosis: A Systematic Review.

Purpose: To assess generalizability of published deep learning (DL) algorithms for radiologic diagnosis. Materials and Methods: In this systematic review, the PubMed database was searched for peer-reviewed studies of DL algorithms for image-based radiologic diagnosis that included external validation, published from January 1, 2015, through April 1, 2021. Studies using nonimaging features or incorporating non-DL methods for feature extraction or classification were excluded. Two reviewers independently evaluated studies for inclusion, and any discrepancies were resolved by consensus. Internal and external performance measures and pertinent study characteristics were extracted, and relationships among these data were examined using nonparametric statistics. Results: Eighty-three studies reporting 86 algorithms were included. The vast majority (70 of 86, 81%) reported at least some decrease in external performance compared with internal performance, with nearly half (42 of 86, 49%) reporting at least a modest decrease (≥0.05 on the unit scale) and nearly a quarter (21 of 86, 24%) reporting a substantial decrease (≥0.10 on the unit scale). No study characteristics were found to be associated with the difference between internal and external performance. Conclusion: Among published external validation studies of DL algorithms for image-based radiologic diagnosis, the vast majority demonstrated diminished algorithm performance on the external dataset, with some reporting a substantial performance decrease.Keywords: Meta-Analysis, Computer Applications-Detection/Diagnosis, Neural Networks, Computer Applications-General (Informatics), Epidemiology, Technology Assessment, Diagnosis, Informatics Supplemental material is available for this article. © RSNA, 2022.

Association of Intraoperative Frozen Section Controls With Improved Margin Assessment During Transoral Robotic Surgery for Human Papillomavirus-Positive Oropharyngeal Squamous Cell Carcinoma.

Importance: Intraoperative margin assessment is an important technique for ensuring complete tumor resection in malignant cancers. However, in patients undergoing transoral robotic surgery (TORS) for oropharyngeal carcinomas, tissue artifact may provide pathologic uncertainty. Objective: To assess the benefit of providing frozen section control samples ("positive tumor biopsies") for use during intraoperative margin assessment for patients undergoing TORS for human papillomavirus (HPV)-16-positive oropharyngeal squamous cell carcinoma (OPSCC). Design, Setting, and Participants: In this cohort study, patients receiving curative-intent TORS for biopsy-proven HPV-16-positive OPSCC performed by a single attending surgeon (A.H.M.) at Ronald Reagan UCLA Medical Center from 2017 to 2021 were included in a retrospective data analysis. Exclusion criteria included HPV-negative status, participation in clinical trials, and tumors of unknown primary origin. Main Outcomes and Measures: Survival outcomes investigated included overall and disease-free survival. Adverse pathologic outcomes measured included occurrence of nondiagnostic margins and margin reversal from frozen to fixed pathology. Results: Of the 170 patients included (mean [SD] age, 61.8 [9.9] years; 140 [82%] male), 50% of patients (n = 85) received a frozen section control. Use of a frozen section control was associated with statistically significantly improved sensitivity of intraoperative margin assessment, from 82.8% to 88.9% (difference, 6.1%; 95% CI, 3.9%-8.3%). Eleven percent (n = 18) of all tumors evaluated exhibited at least 1 nondiagnostic intraoperative margin, and 11% (n = 18) experienced margin reversal from frozen to fixed pathology. In patients with nondiagnostic margins, use of frozen section controls was associated with statistically significantly reduced time spent in the operating room (Cohen d, 1.14; 95% CI, 0.12-2.14). Conclusions and Relevance: In this cohort study, frozen intraoperative margins assessed during TORS resections of HPV-16-positive OPSCC were diagnostically challenging. Adverse pathologic outcomes, such as margin status reversal from positive on frozen pathology to negative on formal analysis, were common. Providing intraoperative frozen section control biopsies may offer clarity in cases with nondiagnostic margins, reducing the need for additional sampling and time spent in the operating room.

Secondary syphilis of the oropharynx and cervical lymph nodes: a case report.

Secondary syphilis rarely affects the head and neck including the oropharynx and cervical lymph nodes. These patients present with throat pain, cystic/necrotic lymphadenopathy, and mucosal swelling. Sometimes this constellation of symptoms can be mistaken for head and neck cancer. We report a case of an enlarging throat and painless cystic neck mass in a transgender woman in her forties who was initially suspected to have oropharyngeal squamous cell carcinoma. A subsequent workup revealed the presence of spirochetes without cellular atypia consistent with secondary syphilis. We include the ultrasonography images as well as an endoscopic photograph of the oropharyngeal manifestation in this report.

Histone deacetylase inhibition is synthetically lethal with arginine deprivation in pancreatic cancers with low argininosuccinate synthetase 1 expression.

Arginine (Arg) deprivation is a promising therapeutic approach for tumors with low argininosuccinate synthetase 1 (ASS1) expression. However, its efficacy as a single agent therapy needs to be improved as resistance is frequently observed. Methods: A tissue microarray was performed to assess ASS1 expression in surgical specimens of pancreatic ductal adenocarcinoma (PDAC) and its correlation with disease prognosis. An RNA-Seq analysis examined the role of ASS1 in regulating the global gene transcriptome. A high throughput screen of FDA-approved oncology drugs identified synthetic lethality between histone deacetylase (HDAC) inhibitors and Arg deprivation in PDAC cells with low ASS1 expression. We examined HDAC inhibitor panobinostat (PAN) and Arg deprivation in a panel of human PDAC cell lines, in ASS1-high and -knockdown/knockout isogenic models, in both anchorage-dependent and -independent cultures, and in multicellular complex cultures that model the PDAC tumor microenvironment. We examined the effects of combined Arg deprivation and PAN on DNA damage and the protein levels of key DNA repair enzymes. We also evaluated the efficacy of PAN and ADI-PEG20 (an Arg-degrading agent currently in Phase 2 clinical trials) in xenograft models with ASS1-low and -high PDAC tumors. Results: Low ASS1 protein level is a negative prognostic indicator in PDAC. Arg deprivation in ASS1-deficient PDAC cells upregulated asparagine synthetase (ASNS) which redirected aspartate (Asp) from being used for de novo nucleotide biosynthesis, thus causing nucleotide insufficiency and impairing cell cycle S-phase progression. Comprehensively validated, HDAC inhibitors and Arg deprivation showed synthetic lethality in ASS1-low PDAC cells. Mechanistically, combined Arg deprivation and HDAC inhibition triggered degradation of a key DNA repair enzyme C-terminal-binding protein interacting protein (CtIP), resulting in DNA damage and apoptosis. In addition, S-phase-retained ASS1-low PDAC cells (due to Arg deprivation) were also sensitized to DNA damage, thus yielding effective cell death. Compared to single agents, the combination of PAN and ADI-PEG20 showed better efficacy in suppressing ASS1-low PDAC tumor growth in mouse xenograft models. Conclusion: The combination of PAN and ADI-PEG20 is a rational translational therapeutic strategy for treating ASS1-low PDAC tumors through synergistic induction of DNA damage.