Background: Organ crosstalk between the kidney and the heart has been suggested. Acute kidney injury (AKI) and acute heart failure (AHF) are well-known independent risk factors for mortality in hospitalized patients. This study aimed to investigate if these conditions have an additive effect on mortality in hospitalized patients, as this has not been explored in previous studies. Methods: We retrospectively reviewed the records of 101,804 hospitalized patients who visited two tertiary hospitals in the Republic of Korea over a period of 5 years. AKI was diagnosed using serum creatinine-based criteria, and AHF was classified using International Classification of Diseases codes within 2 weeks after admission. Patients were divided into four groups according to the two conditions. The primary outcome was all-cause mortality. Results: AKI occurred in 6.8% of all patients (n = 6,920) and AHF in 1.2% (n = 1,244). Three hundred thirty-one patients (0.3%) developed both conditions while AKI alone was present in 6,589 patients (6.5%) and AHF alone in 913 patients (0.9%). Among the 5,181 patients (5.1%) who died, 20.8% died within 1 month. The hazard ratio for 1-month mortality was 29.23 in patients with both conditions, 15.00 for AKI only, and 3.39 for AHF only. The relative excess risk of interaction was 11.85 (95% confidence interval, 2.43-21.27), and was more prominent in patients aged <75 years and those without chronic heart failure. Conclusion: AKI and AHF have a detrimental additive effect on short-term mortality in hospitalized patients.

LCB84 is a human Trop-2-targeting antibody drug conjugate (ADC) composed of monomethyl auristatin E (MMAE) as payload and the Hu2G10 (by Mediterranea Theranostic) humanized IgG1 antibody that selectively targets the ADAM10-activated Trop-2 protein selectively expressed in transformed cancer cells (1). LCB84 was prepared using ConjuAll࣪, a proprietary site-directed conjugation technology of LegoChem Biosciences, which incorporates a conjugation ‘handle’ joined by enzymatic prenylation to a specifically engineered recognition sequence (CaaX) on antibody light chains. This conjugation handle facilitates simple versatile chemical conjugation to the linker-payload. A proprietary plasma-stable cleavable linker that is recognized and cleaved by a cancer-associated lysosomal enzyme, β-glucuronidase, was used to enable efficient and traceless payload release in a cancer-specific manner. LCB84 has been evaluated for anti-tumor activity and showed superior anticancer efficacy in triple-negative breast cancer (TNBC), pancreatic ductal adenocarcinoma (PDAC), gastric cancer and non-small cell lung cancer (NSCLC) cell line-derived xenograft (CDX) models compared to the ADC competitors Trodelvy and DS-1062. The LCB84 treatments were well tolerated, with no changes in body weight compared to control animals, for all dosing groups. LCB84 has robust cross-reactivity against primate Trop-2, which allows rigorous toxicity studies in monkeys. Remarkably, preliminary toxicity studies using cynomolgus monkeys showed that LCB84 is well tolerated, with calculated therapeutic index (TI, MTD/MED) of ~30 for single dosing and ~40 for repeat dosing. In conclusion, LCB84 is highly effective against Trop-2-positive CDX models in mice at doses that are well tolerated in mice and in primate models. Use of this proprietary plasma-stable cancer-selective linker technology and the Hu2G10 anti-Trop-2 monoclonal antibody that targets cancer-activated Trop-2 has led to a greatly improved next generation ADC for the treatment of various Trop-2-positive solid cancers including TNBC, PDAC, NSCLC and gastric cancer. Citation Format: Hyejung Kim, Emanuela Guerra, Eunji Baek, Yeojin Jeong, Hyogeun You, Byeongjun Yu, Taeik Jang, Alberti Saverio, Chul-Woong Chung, Changsik Park. LCB84, a TROP2-targeted ADC, for treatment of solid tumors that express TROP-2 using the hu2G10 tumor-selective anti-TROP2 monoclonal antibody, a proprietary site-directed conjugation technology and plasma-stable tumor-selective linker chemistry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 328.

Backgrounds: Recently, alternative surrogate endpoints such as a 30% or 40% decline in estimated glomerular filtration rate (eGFR) or eGFR slope over 2 to 3 years have been proposed for predicting renal outcomes. However, the impact of GFR estimation methods on the accuracy and effectiveness of surrogate markers is unknown. Methods: We retrospectively enrolled participants in health screening programs at three hospitals from 1995 to 2009. We defined two different participant groups as YR1 and YR3, which had available 1-year or 3-year eGFR values along with their baseline eGFR levels. We compared the effectiveness of eGFR percentage change or slope to estimate end-stage renal disease (ESRD) risk according to two estimating equations (modified Modification of Diet in Renal Disease equation [eGFRm] and Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation [eGFRc]) for GFR. Results: In the YR1 and YR3 groups, 9,971 and 10,171 candidates were enrolled and ESRD incidence during follow-up was 0.26% and 0.19%, respectively. The eGFR percentage change was more effective than eGFR slope in estimating ESRD risk, regardless of the method of estimation. A 40% of decline in eGFR was better than 30%, and a 3-year baseline period was better than a 1-year period for prediction accuracy. Although some diagnostic indices from the CKD-EPI equation were better, we found no significant differences in the discriminative ability and hazard ratios for incident ESRD between eGFRc and eGFRm in either eGFR percentage change or eGFR slope. Conclusion: There were no significant differences in the prediction accuracy of GFR percentage change or eGFR slope between eG-FRc and eGFRm in the general population.

Background and Aims Patients undergoing hemodialysis showed higher prevalence of sarcopenia than that of the healthy. As an intracellular water reservoir, skeletal muscle mass would be important to predict intradialytic hypotension. This study was designed to reveal the effect of skeletal muscle mass to intradialytic hypotension, which is also an indicator of volume status in patients under hemodialysis. Method 150 patients from three hemodialysis centers in 2016 and 38 patients from one center under maintenance hemodialysis in 2020 were enrolled in this study, and total 177 patients were finally analyzed. We measured skeletal muscle mass, intracellular water, extracellular water, total body water and phase angle in 50 kHz by bio-impedance analysis just after a hemodialysis session. Information including laboratory tests, chest x-ray, handgrip strength, mid-arm circumference and questionnaire to ask the patients’ general condition was collected. Intradialytic hypotension over three months was observed. We analyzed several factors including skeletal muscle mass which would have association with intradialytic hypotension over three months by multivariate logistic regression model. Results Tertile subgroups divided by the ratio of skeletal muscle to body weight defined as skeletal muscle index were compared. Patients in low skeletal muscle index had a higher rate of intradialytic hypotension (41%) while that of intermediate group was 20% and high group was 5%. Patients in low skeletal muscle mass index group was female-dominant, more obese, more diabetic and had lower handgrip strength than higher skeletal muscle index group. In patients who had higher skeletal muscle mass to body weight, the risk of Intradialytic hypotension was decreased (HR: 0.80 [95% CI 0.75-0.88], adjusted HR: 0.73 [95% CI 0.64–0.84]). Comparing tertile groups by skeletal muscle index, patients in the group of higher skeletal muscle mass index showed lower rate of intradialytic hypotension during hemodialysis, which was similar in inverse probability of treatment weighted analysis. Confounders were age, gender, diabetes mellitus, heart failure, ischemic heart disease, the ratio of ultrafiltration amount to body weight and skeletal muscle index. Model including skeletal muscle index and clinical parameters showed highest AUC area (0.877 [95% 0.823-0.930]) when the model including clinical parameters only (AUC area: 0.807 [95% CI 0.735-0.879]) or with each bioimpedance index (skeletal muscle mass to squared height, AUC area: 0.843 [95% CI 0.823-0.931]; the ratio of extracellular water to total water, AUC area: 0.809 [95% CI 0.736-0.883]; the ratio of intracellular water to total water, AUC area: 0.811 [95% CI 0.738-0.885] and phase angle, AUC area: 0.812 [95% CI 0.738-0.886]). Conclusion This study showed correlation between skeletal muscle mass by body weight and intradialytic hypotension. It especially suggested that skeletal muscle mass to weight would be a good predictor of intradialytic hypotension and would be helpful to decide appropriate dry body weight in hemodialysis.

2570 Background: TIGIT is a promising emerging immunotherapeutic target. However, the specific sources of TIGIT expression within the tumor microenvironment are largely unknown. Here, we present an AI-powered spatial tumor-infiltrating lymphocyte (TIL) analyzer, Lunit SCOPE IO, to integrate image analysis from whole slide images with single-cell molecular profiling. Methods: We used The Cancer Genome Atlas (TCGA) RNA expression data across 23 cancer types (n=6,930). Lunit SCOPE IO was developed, trained, and validated based on >17k H&E whole-slide images, to segment cancer area (CA) and cancer-associated stroma (CS) and to detect tumor cells and TILs. The intra-tumoral TIL, stromal TIL, and tumor cell purity (TCP) in the CA+CS area were calculated. The public spatial transcriptomics (ST) dataset for breast cancer was downloaded from the 10X Visium web page. Lunit SCOPE IO was applied to the associated H&E WSIs to match distinct TIGIT expression to single cells identified in the WSIs. Results: TIGIT was highly expressed in TGCT (3.45±0.11; median±SEM), LUAD (3.07±0.05), and HNSC (2.89±0.06), and was highly enriched in samples with microsatellite instability-high or tumor mutational burden-high (≥ 10/Mb) compared to those without them (fold change = 1.30, p < 0.001). At a macroscopic, bulk-level in the TCGA dataset, TIGIT expression was positively correlated with intra-tumoral TIL density (R=0.37, p<0.001) and stromal TIL density (R=0.42, p<0.001), but it was negatively correlated with TCP (R=-0.27, p<0.001). Lunit SCOPE IO analyzed the images from ST analysis and calculated intra-tumoral TIL, stromal TIL, and TCP of each region of interest, containing 2 (IQR 0-7) cells. Interestingly, at a microscopic, cell-level, TIGIT expression was still higher in areas of enriched stromal TIL (P < 0.001) and lower in tumor cell-dense areas, but it was not significantly correlated with enriched intra-tumoral TIL areas, meaning that TIGIT expression is likely derived from the excluded TILs in the CS area. Conclusions: Interactive analysis of spatial transcriptomics with AI-powered pathology image analysis revealed that TIGIT expression in the tumor microenvironment is exclusive to confined areas with stromal TIL enrichment, reflecting the exclusion of TIL from the tumor nest. [Table: see text]