Citations

Emerging evidence suggest that transcription factors play multiple roles in the development of pancreatitis, a necroinflammatory condition lacking specific therapy. Estrogen-related receptor γ (ERRγ), a pleiotropic transcription factor, has been reported to play a vital role in pancreatic acinar cell (PAC) homeostasis. However, the role of ERRγ in PAC dysfunction remains hitherto unknown. Here, we demonstrated in both mice models and human cohorts that pancreatitis is associated with an increase in ERRγ gene expression via activation of STAT3. Acinar-specific ERRγ haploinsufficiency or pharmacological inhibition of ERRγ significantly impaired the progression of pancreatitis both in vitro and in vivo. Using systematic transcriptomic analysis, we identified that voltage-dependent anion channel 1 (VDAC1) acts as a molecular mediator of ERRγ. Mechanistically, we showed that induction of ERRγ in cultured acinar cells and mouse pancreata enhanced VDAC1 expression by directly binding to specific site of the Vdac1 gene promoter and resulted in VDAC1 oligomerization. Notably, VDAC1, whose expression and oligomerization were dependent on ERRγ, modulates mitochondrial Ca 2+ and ROS levels. Inhibition of the ERRγ–VDAC1 axis could alleviate mitochondrial Ca 2+ accumulation, ROS formation and inhibit progression of pancreatitis. Using two different mouse models of pancreatitis, we showed that pharmacological blockade of ERRγ–VDAC1 pathway has therapeutic benefits in mitigating progression of pancreatitis. Likewise, using PRSS1 R122H -Tg mice to mimic human hereditary pancreatitis, we demonstrated that ERRγ inhibitor also alleviated pancreatitis. Our findings highlight the importance of ERRγ in pancreatitis progression and suggests its therapeutic intervention for prevention and treatment of pancreatitis.

Abstract Background: The Tumor Immune microenvironment (TME) plays an important role in tumor development, progression, and treatment response. Recent studies show that spatial heterogeneity of Tumor-Infiltrating Lymphocytes (TILs), consisting of lymphocytic cell populations, is an important histopathologic feature and a powerful prognostic and predictive marker correlating with cancer progression and treatment response. Detecting and quantifying TIL density in Whole Slide Images (WSIs) is, however, labor-intensive, and it is difficult to assess differences in the composition of immune cells. Therefore, it remains a challenge to establish the analysis of TILs in the complex TME. We present an automated spatial image analysis of TILs on gastric cancer to address cancer immunotherapy. Method: 1,031WSIs of hematoxylin and eosin-stained (H&E) formalin-fixed paraffin-embedded (FFPE) sections from four patient cohorts: TCGA-STAD (329), Yonsei-1 (620 patients), Yonsei-2 (45), and St. Mary (37), were analyzed. Two treatment groups in response were classified as CR + PR, while another two treatment groups in non-response were classified as PD + SD. H&E stained WSIs were normalized using the Reinhard normalization method at 20X magnification for reducing the color variability of the stained tissue images. We used U-Net architecture to predict the normalized H&E stained WSIs. Three U-Net models were trained for predicting tumor, TILs, and stroma, using Adam optimizer, 1e-4 learning rate, a binary loss function, L2 regularization, and 50 epochs. The normalized H&E stained WSIs were predicted using the trained U-Net models. Spatial analysis of TILs was conducted on the predicted WSIs. Regional quantification of TILs was performed by two immune phenotype groups: immune-immersed (TILs enriched in tumor cells) and immune-excluded (TILs not enriched in tumor cells but in stromal cells). Kaplan-Meier with a log-rank test was used to evaluate the survival differences between the groups. Results: In TCGA-STAD, the proportion of immune-immersed composition is significantly different from the immune-excluded (p-value 0.05). In Yonsei-1, the immune-excluded composition is significantly different among the three risk groups (p-value 3e-05). In the Yonsei-2 and St. Mary cohorts, including anti-PD1 treated gastric cancer patients, the immune-immersed composition is significantly different between two response groups (p-value 0.007) and represented the diagnostic accuracy (AUROC: 0.78) on CR + PR groups. Conclusion: These findings suggest that the proposed TIL quantification in the complex TME is strongly associated with patient prognosis and anti-PD1 treatment response in gastric cancer. Citation Format: Sanghoon Lee, Sunho Park, Jae-Ho Cheong, Sam C. Wang, Matthew R. Porembka, In-Ho Kim, Sung Hak Lee, Tae Hyun Hwang. Spatial image analysis of tumor-infiltrating lymphocytes on gastric cancer to predict anti-PD1 inhibitor response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1360.

Abstract Background: While immune checkpoint inhibitors (ICI) extend survival for patients suffering from a variety of cancers, most gastric cancer (GC) patients do not respond to ICI. There is a critical need to identify novel biomarkers that guide the use of ICI or strategies to improve outcomes for GC patients. We aim to gain a deeper understanding of the GC tumor microenvironment (TME) to refine the use of ICI using spatial transcriptomes from ICI-treated gastric tumors. Method: We collected 12 pre-ICI treatment gastric tumor samples from five responders and seven nonresponders and performed spatial profiling to investigate spatial heterogeneity, functions, and phenotypes of tumor and neighboring stromal and immune cells to identify features associated with ICI response. We used pan-cytokeratin (pan-CK) to mark epithelial cells, CD45 for immune cells, and smooth muscle actin (SMA) for fibroblasts. We generated gene expression profiles of each cell type within regions of interest (ROI) with a NanoString GeoMx Cancer Transcriptome Atlas panel, comprised of 1,800 genes. A total of 58 ROIs were analyzed from responders and 62 ROIs from nonresponders. Results: We measured the spatial heterogeneity of each cell type in ROIs within and across tumors. We found the tumor, immune, and fibroblasts from nonresponders are transcriptionally more heterogeneous, compared to those from responders. This might indicate a higher degree of intratumor transcriptional heterogeneity is linked to ICI resistance. We found that nonresponse was associated with higher expression of VEGFA and VEGFB in tumor cells and higher ACTA2 in fibroblasts, not in other cell types. These findings are intriguing when considering our other finding that increased endothelial cell and fibroblast proportions in the TME are associated with ICI nonresponse. We also found that the TME of nonresponders had fewer M1 and more M2 macrophages, and there were more T cells that overexpressed gene programs consistent with dysfunction and exhaustion. These findings indicate that ICI-resistant TMEs are densely surrounded by immune-suppressive cellular components which might reduce ICI efficacy and result in ICI resistance. Finally, we performed cell-cell interaction and identified ligand-receptor interactions that are stronger in nonresponders, including CXCL12-CXCR4, CD74-MIF, and LGALS9-LRP1 ligand-receptor interactions. The predicted ligand-receptor interactions are present in cell-type-specific manners, indicating the functional role of each cell type in facilitating ICI response. Conclusion: We investigated how tumor and neighboring stromal and immune cells interact within GC TME to mediate ICI response, which demonstrate that spatial analysis could be used to identify novel biomarkers that predict response to ICI, and new therapies to enhance ICI efficacy in GC patients. Citation Format: Sunho Park, Changjing Hong, Jae-Ho Cheong, Sam C. Wang, Matthew R. Porembka, In-Ho Kim, Sung Hak Lee, Tae Hyun Hwang. Spatial architecture and cellular interactions of tumor immune microenvironment to discover biomarkers and predict immune checkpoint inhibitor response in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2262.

5 Background: Management options for patients (pts) with advanced (locally advanced or metastatic) PeCa are limited. The GSRGT assembled an international cohort of pts with advanced PeCa treated with ICI to evaluate toxicity and clinical outcomes. Methods: We retrospectively collected data on pts with advanced PeCa receiving ≥1 cycle of ICI between 2015-2022 at 18 medical centers in the US, Europe, and Asia. Immune-related adverse events (irAE) were graded per the Common Terminology Criteria for Adverse Events v5.0. Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method. Objective response rate (ORR) was determined by the clinical investigator per RECIST 1.1 criteria, whenever feasible. Results: Among 72 pts with advanced PeCa treated with ICI, 24 (33%) were Hispanic and 7 (10%) were Black. 60 (83%) pts had metastases while the remainder had locally advanced disease. The median age was 64 (inter-quartile range (IQR): 54,70) years and 48 (67%) had ECOG performance status ≥1. Most pts (n=60, 83%) were treated in the ≥2nd line setting and received pembrolizumab (n=23), nivolumab (n=15), cemiplimab (n=15), nivolumab and ipilimumab (n=7), or other anti-PD1/L1-based therapies (n=12). Among 37 pts with available data on HPV status, 24 (65%) were HPV+. 3 (4%) pts were HIV+. irAE of any grade occurred in 18 (25%) pts, 7 (10%) were grade ≥3, 7 (10%) required steroids, 6 (9%) required hospitalization, and 8 (11%) led to treatment discontinuation. The median OS and 24-month OS and median PFS and 24-month PFS were 9.4 (95%CI: 6.8, 12.8) months and 19.3% (95%CI: 9.2, 32.1) and 2.8 (95%CI: 2.1, 3.9) months and 11.2 % (95%CI: 4.9, 20.2), respectively. Among 66 pts evaluable for response, ORR was 7/66 (11%) (2 with complete response, 5 with partial response), and 16 (24%) pts had stable disease for a disease control rate of 35%. The median duration of response was 7.9 (IQR: 3, not reached) months. Conclusions: In the largest retrospective cohort of ICI-treated advanced PeCa, ICI showed no new safety signals, however, overall anti-tumor activity was limited. Future translational studies are needed to identify pts that are more likely to derive clinical benefit from ICI.

Background and Aims: Hepatopulmonary syndrome (HPS) and a hyperdynamic circulation are common complications of advanced liver disease, but the relationship between HPS and cardiac index (CI) is poorly understood. We sought to compare CI in patients with and without HPS and to assess the relationship between CI and symptoms, quality of life, gas exchange, and exercise capacity among liver transplantation (LT) candidates. We performed a cross-sectional analysis within the Pulmonary Vascular Complications of Liver Disease 2 study, a multicenter prospective cohort study of patients being evaluated for LT. We excluded patients with obstructive or restrictive lung disease, intracardiac shunting, and portopulmonary hypertension. We included 214 patients (81 with HPS and 133 controls without HPS). Compared with controls, patients with HPS had a higher CI (least square mean 3.2 L/min/m2, 95% CI 3.1–3.4 vs. 2.8 L/min/m2, 95% CI 2.7–3.0, p < 0.001) after adjustment for age, sex, Model for End-stage Liver Disease-Sodium (MELD-Na) score and beta-blocker use, and a lower systemic vascular resistance. Among all LT candidates, CI was correlated with oxygenation (Alveolar-arterial oxygen gradient r=0.27, p< 0.001), intrapulmonary vasodilatation severity (p < 0.001), and biomarkers of angiogenesis. Higher CI was independently associated with dyspnea and worse functional class and physical quality of life after adjusting for age, sex, MELD-Na, beta-blocker use, and HPS status. HPS was associated with a higher CI among LT candidates. Independent of HPS, higher CI was associated with increased dyspnea and worse functional class, quality of life, and arterial oxygenation.

ObjectiveIdentifying cerebrospinal fluid measures of the microtubule binding region of tau (MTBR‐tau) species that reflect tau aggregation could provide fluid biomarkers that track Alzheimer's disease related neurofibrillary tau pathological changes. We examined the cerebrospinal fluid (CSF) MTBR‐tau species in dominantly inherited Alzheimer's disease (DIAD) mutation carriers to assess the association with Alzheimer's disease (AD) biomarkers and clinical symptoms.MethodsCross‐sectional and longitudinal CSF from 229 DIAD mutation carriers and 130 mutation non‐carriers had sequential characterization of N‐terminal/mid‐domain phosphorylated tau (p‐tau) followed by MTBR‐tau species and tau positron emission tomography (tau PET), other soluble tau and amyloid biomarkers, comprehensive clinical and cognitive assessments, and brain magnetic resonance imaging of atrophy.ResultsCSF MTBR‐tau species located within the putative “border” region and one species corresponding to the “core” region of aggregates in neurofibrillary tangles (NFTs) increased during the presymptomatic stage and decreased during the symptomatic stage. The “border” MTBR‐tau species were associated with amyloid pathology and CSF p‐tau; whereas the “core” MTBR‐tau species were associated stronger with tau PET and CSF measures of neurodegeneration. The ratio of the border to the core species provided a continuous measure of increasing amounts that tracked clinical progression and NFTs.InterpretationChanges in CSF soluble MTBR‐tau species preceded the onset of dementia, tau tangle increase, and atrophy in DIAD. The ratio of 4R‐specific MTBR‐tau (border) to the NFT (core) MTBR‐tau species corresponds to the pathology of NFTs in DIAD and change with disease progression. The dynamics between different MTBR‐tau species in the CSF may serve as a marker of tau‐related disease progression and target engagement of anti‐tau therapeutics. ANN NEUROL 2023;93:1158–1172

Aims:Increased left ventricular (LV) wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. Methods and Results: Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 and 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4-chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: HCM: 0.93, CA: 0.90, and HTN/other: 0.92). Conclusion: The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.

Abstract Aims An artificial intelligence-enabled electrocardiogram (AI-ECG) is a promising tool to detect patients with aortic stenosis (AS) before developing symptoms. However, functional, structural, or haemodynamic components reflected in AI-ECG responsible for its detection are unknown. Methods and results The AI-ECG model that was developed at Mayo Clinic using a convolutional neural network to identify patients with moderate–severe AS was applied. In patients used as the testing group, the correlation between the AI-ECG probability of AS and echocardiographic parameters was investigated. This study included 102 926 patients (63.0 ± 16.3 years, 52% male), and 28 464 (27.7%) were identified as AS positive by AI-ECG. Older age, atrial fibrillation, hypertension, diabetes, coronary artery disease, and heart failure were more common in the positive AI-ECG group than in the negative group (P &lt; 0.001). The AI-ECG was correlated with aortic valve area (ρ = −0.48, R2 = 0.20), peak velocity (ρ = 0.22, R2 = 0.08), and mean pressure gradient (ρ = 0.35, R2 = 0.08). The AI-ECG also correlated with left ventricular (LV) mass index (ρ = 0.36, R2 = 0.13), E/e′ (ρ = 0.36, R2 = 0.12), and left atrium volume index (ρ = 0.42, R2 = 0.12). Neither LV ejection fraction nor stroke volume index had a significant correlation with the AI-ECG. Age correlated with the AI-ECG (ρ = 0.46, R2 = 0.22) and its correlation with echocardiography parameters was similar to that of the AI-ECG. Conclusion A combination of AS severity, diastolic dysfunction, and LV hypertrophy is reflected in the AI-ECG to detect AS. There seems to be a gradation of the cardiac anatomical/functional features in the model and its identification process of AS is multifactorial.

Background This study aimed to validate the concept of notching of the ulna component of the first-generation latitude total elbow prosthesis to reduce the rate of aseptic loosening and improve implant survival. Methods A total of 18 total elbow arthroplasty cases were performed between June 2001 and May 2002 using the latitude first-generation ulnar stem. A total of 14 cases with at least 2 years of follow-up were evaluated following the exclusion of four infected cases. The senior author roughened the stem surface with notches in 10 cases (notched group) to prevent loosening. The effects of notching on implant failure were retrospectively analyzed. Results Average participant age and follow-up were 56 ± 20 years and 72 ± 44 months, respectively. The notched and unnotched implant groups were demographically equivalent. 3/4(75%) of unnotched group implants failed due to aseptic loosening. 1/10(10%) of the notched group implants failed. All unnotched group aseptic loosening cases occurred at the bone–cement interface within 2 years after total elbow arthroplasty. The single patient with aseptic loosening in the notched group had a history of multiple surgeries due to an open fracture preceding the primary total elbow arthroplasty. Discussion Notching of the ulna component of the first-generation latitude total elbow prosthesis reduced the rate of aseptic loosening and improved implant survival. Level of evidence Level IV, retrospective comparative study.