bluuebunny/crossref_metadata_2025_split huggingface dataset:
CRPA1A2: A novel TCR-based T-cell engager targeting MAGEA1-positive solid tumors.
Authors: Xie Xingwang , J Dong , Bi Jinglei , Zhai Jiahui , Yan Baoqi , Li Yonghong , Wang Jianghua , Zhu Yaping 
Published: June 2024

e14589 Background: MAGEA1, identified as a cancer/testis antigen, is highly expression in various solid tumors, including hepatocellular carcinoma, non-small cell lung cancer, but absent in normal tissues except male germ cells and placenta, both of which lacking HLA class molecules. This selective expression of HLA-MAGEA1 epitope makes it a promising target for cancer therapy. However, its intracellular localization poses a challenge for conventional antibodies designed to target surface-expressed antigens. TCR-based T-cell engagers, such as Tebentafusp, overcome this hurdle by targeting intracellular protein-derived peptides presented on cancer cell surfaces via HLA, enabling precise cytotoxic T cell attacks. Notably, Tebentafusp has shown significant clinical benefits by improving survival rates in metastatic uveal melanoma, underscoring the efficacy of TCR-based T-cell engagers in treating MAGEA1-positive tumors. Methods: We have developed an advanced structural format, CR62, consisting of a anti-CD3 single chain fragment, a soluble modified TCR, and an Fc region. Additionally, the use of CorreGene's SMART-TCR system has facilitated the acquisition of TCRs with high affinities in the pico-molar range. By leveraging CR62 and a high-affinity TCR, we have conceptualized the TCR-based T-cell engager, CRPA1A2. Comprehensive preclinical assessments have been conducted to evaluate CRPA1A2's safety and efficacy. Results: CRPA1A2 is designed to specifically target the HLA-A*02:01-restricted MAGEA1 epitope, effectively inhibiting tumor growth. CRPA1A2 is characterized by its exceptional soluble expression in CHO cells, minimal homodimer miss-assembly and simplifying purification. It is strategically engineered with a high-affinity TCR and a low-affinity anti-CD3 scFv to optimize the efficacy and safety. In vitro studies, CRPA1A2 showed strong ability to eliminate tumor cells and induce IFN-γ release, effective even at low MAGEA1 epitope densities, with a therapeutic window that spans over three orders of magnitude, suggesting a 1000-fold greater activity against antigen-positive cancer cells compared to antigen-negative cells. In vivo, using a tumor-bearing mouse model, CRPA1A2 has been shown to recruit T cells into subcutaneous solid tumors, expand CD8+ T cell populations, and significantly reduce tumor mass. Notably, CRPA1A2 has an extended half-life of 120 hours and demonstrates preferential accumulation in tumor tissues, thereby enhancing its therapeutic potential. Moreover, the safety assessments for CRPA1A2 highlight its exceptional specificity, with in vitro studies showing no evidence of off-target toxicity, on-target off-tumor toxicity, or alloreactivity and favorable tolerance in mice during in vivo studies. Conclusions: CRPA1A2 has emerged as a superior TCR-based T-cell engager with exceptional antitumor efficacy and promising safety profile.
Effect of aberrant N-glycosylation of PD-L1 on the potency of anti-PD-1 treatments.
Authors: Kaufman Bar , Erlichman Nofar , Meshel Tsipi , Ben-Baruch Adit , Elkabets Moshe , Porgador Angel 
Published: June 2024

e14599 Background: Immune checkpoint inhibitors (ICIs) targeting the PD1/PDL1 axis have revolutionized the way we treat cancer patient. Yet, response rate to these treatments remains low. Post translational modifications of PD-L1 in the form of N-glycosylation play a crucial role in both receptor-ligand interaction and in the potency of PD1/PDL1 ICIs. Understanding the effect of each N-glycosylation site is crucial for patient stratification for treatment groups and may help to increase response rate to anti-PD1/PDL1 ICIs. We recently developed the Immune-Checkpoint Artificial Reporter (IcAR) technology to assess specific ICI potency for target tumors including clinical samples. Using IcAR expressing recombinant human PD1 receptor we can analyze clinical response of patients to PD1-PDL1 blocking drugs and analyze the glycan-modified PDL1 expressing cancer cells. Methods: We have created two cell lines (MDA-MB231 and MCF7) overexpressing PD-L1 in its wildtype form, single mutated glycosylation sites (N35A, N192A, N200A, N219A) and all sites mutated together (Nx4). Using IcAR-PD1 we measured the functional binding of the different mutated cell lines, cell derived xenografts (CDX) and fixed cell samples to evaluate baseline binding. Later we have incubated IcAR-PD1 and mutated cell liens together with multiple clinically used PD1/PDL1 ICIs to evaluate the inhibition of interaction of each ICI. Results: While staining and functional interaction of PDL1 and single mutants is similar, removing all four N-glycosylation sites (Nx4) decreased both the staining of PDL1 and functional binding. Interestingly, blocking capacity of different ICIs was impaired by N35A PDL1 mutation, and was absolute through all concentration (2.5 to 40 ug/mL) when employed on the Nx4 cell lines. While anti-PDL1 ICIs were managed to block PD-1/PD-L1 interaction trough all cell lines and mutants, the inhibitory capacity of anti-PD1 ICIs was impaired by glycosylation, especially on N35. Conclusions: Aberrant glycosylation of PD-L1 impair the potency of anti-PD-1 treatment in cancer cell lines. These results might explain why patients with negative PD-L1 staining (Nx4), might respond to ICIs, and suggest an explanation of mechanism in which patients with high PD-L1 staining (i.e. N35), might not respond to anti-PD-1 treatments. Our results shed a light on the mechanism of ICI resistance and response – using this knowledge patient will be stratify better into treatment groups, getting oncology a step closer to precision immunology.
Risk factors for thrombotic events among patients taking immune checkpoint inhibitors: A systematic review and meta-analysis.
Authors: Song Junmin , Caceres Lessa Ana Yasmin , Lee Pei-Lun , Chowdhury Ishmum , Chang Yu , Chang Yu-Cheng , Schwartz Rachel , Chi Kuan-Yu , Kumar Abhishek 
Published: June 2024

e14610 Background: Cancer is well known to be a hypercoagulable state, and several studies suggest that targeted therapies, including immune checkpoint inhibitors (ICIs), may also cause thrombotic events. Despite the identification of multiple risk factors associated with ICI administration, no studies have definitively clarified these factors. This study aims to comprehensively investigate the risk factors of thrombotic events upon ICI use. Methods: We conducted a systematic review and meta-analysis. Search terms included immune checkpoint inhibitors (PD-1, PD-L1, and CTLA-4 inhibitors) and thrombotic events (venous, arterial thrombosis, and immune-related adverse events). The primary endpoint was calculating each risk factor's aggregated odds ratio (OR) for any kind of thrombotic event, including venous and arterial thrombosis. The secondary endpoint was to combine the hazard ratio (HR) for each risk factor on thrombosis formation. Results: Out of 8718 studies found, a total of 13 studies with 10608 patients were included. Most patients had non-small cell lung cancer (37.2%) or melanoma (24.8%) and had advanced disease (stage IV being 84.9%). All possible risk factors included in the studies were extracted, and their OR and HR were aggregated. Notably, previous history of thrombus (OR: 3.01; 95% CI: 1.53-5.92), history of COPD (OR: 1.87; 95% CI: 1.00-3.51), smoking history (OR: 1.69; 95% CI: 1.15-2.48), and BMI higher than 30 (OR: 1.68, 1.37-2.07) were associated with a higher risk of thrombotic events. In multivariate analysis, poor performance status of ECOG PS ≥ 2 (HR: 1.55, 95% CI: 1.02-2.36, I2: 35%) and Khorana risk score ≥ 2 (HR: 1.5, 95% CI: 1.23-1.84, I2: 0%) showed higher thrombotic risk. Conclusions: Similar to the known risk factors for thrombosis, previous history of thrombus, smoking history, and obesity are predictors of future thrombus in patients on ICI treatment. Further studies are needed to know if arterial and venous events happen at different rates and/or are associated with different risk factors. [Table: see text]
Relationship of angiotensin II receptor blocker (ARB) to the effectiveness of immune checkpoint blockade (ICB) in non-small-cell lung cancer (NSCLC) and inhibition of angiotensin II/AGTR1 signaling in fibroblasts to reduce collagen deposition in the tumor microenvironment (TME).
Authors: Yang Kai , Chu Jiahui , Mei Jie , Yin Yongmei 
Published: June 2024

e14618 Background: Immune checkpoint blockade (ICB) has achieved remarkable success. However, not all patients with advanced tumors respond to ICB. Remodeling of the tumor microenvironment (TME) has emerged as a strategy to facilitate the development of cancer therapies. As the most notable features of TME, immune cells and collagens play a significant role in influencing anti-tumor immunity, with collagen deposition is the most significant physical barrier that hinders immune cell infiltration. Cancer patients are often prescribed multiple medications to address pre-existing comorbidities or side effects from anti-tumor therapy. Given the high prevalence of concurrent medications and the potential for interactions between them and ICB, we identified that the angiotensin II receptor 1 (AGTR1) was positively expressed in CAFs and AGTR1 inhibitor angiotensin receptor blocker (ARB) suppressed the expression of type I collagen and promote immune infiltration. Methods: Retrospective clinical study: An in-house cohort was a multi-center cohort and included 270 patients with non-small-cell lung cancer (NSCLC) receiving ICB therapy from 2020 to 2021 from The Affiliated Wuxi People's Hospital of Nanjing Medical University and The First Affiliated Hospital of Nanjing Medical University. Meta-analysis: 4 studies involving 1,268 participants in total and an in-house cohort with 270 participants were included. We performed an additional meta-analysis on the association between the use of ARBs in cancer patients receiving ICB therapy. Animal models: Xenograft tumor models were randomly divided into two groups, including control and Losartan-treated groups, and mouse cancer models were randomly divided into three groups at the first round and four groups at the second round. Three groups included control, Losartan-treated, and Losartan-treated & CD8-deleted groups, and four groups included control, Losartan-treated, anti-PD-1-treated, and Losartan & anti-PD-1-treated groups. Results: Patients with NSCLC who received ARBs showed improved overall survival and response to immunotherapy compared to those who did not receive ARBs. Losartan, a representative drug of the ARB class, significantly increased collagen deposition in mice tumors, elevated levels of immune cell infiltration, and sensitized anti-PD-1 therapy. Conclusions: We reported that Losartan shaped an inflamed TME by inhibiting collagen I expression of CAFs and enhanced anti-PD-1 immunotherapy in the mouse tumor model. We recommend that ARB should be selected as much as possible for patients receiving ICB therapy and requiring antihypertensive treatment.
Utility of the NLR and the ratio of NLR after and before adverse events for identifying irAEs and bacterial infections in patients with cancer during PD-(L)1 inhibitors treatment.
Authors: Han Lu , Huang Beibei , Li Linlin , Yang Yonghao , Fu Xiaomin , Zhao Lingdi , Wang Zibing , Gao Quanli 
Published: June 2024

e14620 Background: Identifying immune-related adverse events (irAEs) or bacterial infections in cancer patients undergoing treatment with PD-(L)1 inhibitors can be challenging. This study aimed to assess the effectiveness of the neutrophil-to-lymphocyte ratio (NLR) in distinguishing between irAEs and bacterial infections in cancer patients receiving PD-(L)1 inhibitors. Methods: We conducted a retrospective analysis of cancer patients who received at least one dose of PD-(L)1 inhibitors at Affiliated Cancer Hospital of Zhengzhou University from 2018 to 2023. We compared the changes in peripheral blood cell counts before and after the occurrence of adverse events, as well as the ratio of the NLR at the time of adverse events (post-NLR) to the NLR before adverse events (pre-NLR). Bacterial infections were diagnosed based on clear etiology and/or controlled adverse events through the use of antibiotics without systemic glucocorticoid administration during treatment. irAEs were diagnosed based on clinicolaboratory criteria, or the improvement of immune system disorders after withdrawal of PD-(L)1 inhibitors or systemic glucocorticoid administration, excluding bacterial infection. Data were collected from microbiology, radiography, serology, and physician notes. Results: Among the 4173 patients who were administered PD-(L)1 inhibitors, 217 individuals experienced a total of 249 irAEs, while 256 patients were diagnosed with 257 bacterial infections. When comparing pre-infection levels with those after bacterial infection, it was observed that the NLR increased significantly. Similarly, in the group experiencing irAEs, the NLR also showed a significant increase after the occurrence of the irAEs. Notably, the NLR was significantly higher in patients with bacterial infections compared to those with irAEs [11.08 (6.63, 19.29) vs 2.78 (1.92, 4.31), P < 0.001]. Furthermore, the post-NLR/pre-NLR ratio was higher in the bacterial infection group than in the irAEs group [2.86 (1.56, 6.20) vs 1.16 (0.82, 1.76), P < 0.001]. Appraising the potential of NLR and the post-NLR/pre-NLR ratio in identifying irAEs and bacterial infections in cancer patients, the receiver operating characteristic (ROC) curve analysis was performed. The area under the curve (AUC) was 0.91 for NLR and 0.81 for the post-NLR/pre-NLR ratio, respectively. Using a cut-off value of 4.56 for NLR and 1.96 for the post-NLR/pre-NLR ratio yielded the highest sensitivity and specificity. Conclusions: The NLR along with the post-NLR/pre-NLR ratio could serve as valuable diagnostic indicators for irAEs and bacterial infections in cancer patients undergoing treatment with PD-(L)1 inhibitors.
Immune-related adverse event prediction and influential factor identification.
Authors: Zhang Yili , Lev-Ari Shaked , Shah Neil J. , Gupta Samir , Zaemes Jacob Peter , Alaoui Adil , McGarvey Peter , Atkins Michael B. 
Published: June 2024

e14650 Background: Immune checkpoint inhibitors (ICIs), have demonstrated efficacy in treating patients with non-small cell lung cancer (NSCLC) and advanced melanoma. However, ICIs can lead to immune-related adverse events (irAE), which will cause discontinuance of the ICI treatment. The objective of this study is to identify factors that predict which patients with NSCLC or melanoma will develop irAE(s) from ICIs. Methods: We curated the patient cohort from the Immune-Oncology data repository developed at the Georgetown-Lombardi Comprehensive Cancer Center. This cohort encompassed 466 patients (245 individuals with NSCLC and 221 with advanced melanoma) who received single-agent anti-PD-(L)1 or combination of anti-PD-1 and anti-CTLA4 therapy. Parameters selected for prediction comprises baseline demographics, laboratory results, treatment information, and cancer-related mutations. The classification of irAE were identified by CTCAE V4.03 guidelines. Overall, 219 patients experienced one or more irAE, while the remaining 247 patients were irAE-free. We employed machine learning models for prediction, which were trained using 80% of the dataset with a five-fold cross-validation, and their performance was evaluated using the area under the receiver-operating curve (AUROC) and F1 score. Furthermore, we identified the key factors that significantly impacted the model by SHAP values. Results: Nine machine learning models were deployed, including logistic regression, support vector machine, gradient boosting (GB), etc. The GB model demonstrated the highest performance, achieving an AUROC score of 75% and an F1 score of 77%. According to the SHAP value obtained from the GB model, NSCLC patients exhibited a higher propensity for irAE development compared to melanoma patients. The top three features associated with a heightened likelihood of irAE development are the treatment of the combination of anti PD-1 and anti CTLA-4, a higher albumin/globulin ratio, and a pre-treatment ECOG Performance Status score of 0. The top three features associated with a lower likelihood of irAE development are an elevated red cell distribution width, the treatment with single agent anti-PD-1, and a higher globulin level. Conclusions: Our research harnesses a comprehensive set of variables to forecast the development of irAEs in NSCLC and melanoma patients undergoing ICI treatment. The results underscore the predictive capabilities of ML models. Investigating the connections between pivotal biomarkers, such as globulin and red cell distribution width, has the potential to offer insights that enable patients to mitigate irAE. These findings emphasize the promising potential of ML techniques not only in predicting the likelihood of irAE but also in the grade of irAE. To mitigate the limitation of a relatively small sample size, we are actively working to expand the data registry by collaborating with additional institutions.
Predictive cytokine biomarkers for immune-related adverse events associated with immune checkpoint inhibitor therapy in Hodgkin lymphoma.
Authors: Luke Neeti , Pratt Maria , Gong Judy , Borghi Sara , Diefenbach Catherine S. , Hillier Kirsty 
Published: June 2024

e14651 Background: Immune checkpoint inhibitors (ICIs) show great promise in the treatment of relapsed/refractory classical Hodgkin Lymphoma (cHL) and are being considered for up-front treatment. However, use of ICIs can be limited by immune-related adverse events (irAEs). Identifying predictive biomarkers for the development of irAEs could identify high-risk patients to potentially mitigate AEs. Methods: Eighteen patients with cHL were included; 11 patients treated with ICIs (pembrolizumab, nivolumab and/or ipilimumab) as cases (Cohort A) and 7 patients treated with standard of care chemotherapy as controls (Cohort B). The electronic medical record was reviewed for patient clinical characteristics. T cell cytokine expression and autoantibody profiles were performed on baseline pre-ICI treatment peripheral blood plasma samples using Luminex technology in the NYU Langone Immune Monitoring Core Laboratory; cytokine expression was analyzed by 2-way ANOVA. Results: All patients treated with ICIs had been previously treated with other therapy as opposed to Cohort B which included all newly diagnosed patients. Eight patients developed irAEs, with rash being most frequent (n=5) (Table). Analysis of cytokines showed significant elevation in ITAC for irAE compared to no irAE (p<0.01). Increased IL-6, IL-13, and IL-17 expression and decreased MIP-1b expression in those with irAEs all trended towards significance. There was no identified correlation between autoantibodies and irAEs. Conclusions: irAEs can be a significant challenge in cHL patients treated with ICIs, causing comorbidities and limiting benefit from vital therapies. In patients who developed irAEs, we found a significant elevation in ITAC, a chemokine induced by IFN-gamma that attracts activated T cells. Other inflammatory cytokines such as IL-6, IL-13, IL-17, and MIP-1b trended towards significance, likely due to the small sample size. Expansion of this study in a larger cohort of patients is planned. [Table: see text]
Prediction accuracy of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer: A systematic review and meta-analysis.
Authors: Zhuang Wei , Zhao Jie , Sun Boyang , Bai Hua , Wang Zhijie , Zhong Jia , Wan Rui , Liu Lihui , Duan Jianchun , Wang Jie 
Published: June 2024

e14652 Background: To compare the predictive accuracy of PD-L1 IHC, tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profiling (GEP), driver gene mutation, and combined marker for immunotherapy response of advanced non-small cell lung cancer (NSCLC). Methods: Systematic searches of PubMed, Cochrane CENTRAL, and Embase were conducted from inception to July 6, 2023. Clinical trials involved with predictive biomarkers exploration for immune checkpoint inhibitors (ICIs) in advanced NSCLC were eligible. The response according to the biomarkers were extracted. The primary outcome was the area under the curve (AUC) of the summary receiver operating characteristic (SROC). Sensitivity, specificity, likelihood ratios and predictive values were evaluated. The subgroup analysis of different PD-L1 cut-off, TMB test and driver gene mutation were performed. Results: 36 articles of 59 biomarker tests were included. The AUC of combined marker (0.75; 95%CI, 0.71-0.78) was higher than PD-L1 (0.64; 95%CI, 0.60-0.68), tTMB (0.64; 95%CI, 0.60-0.68), bTMB (0.68; 95%CI, 0.64-0.72), GEP (0.67; 95%CI, 0.63-0.71), and driver gene mutation (0.51; 95%CI, 0.47-0.55). Combined marker also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers (Table). In subgroup analysis, PD-L1 with cut-off 50% had higher AUC (0.67; 95%CI, 0.63-0.71) than cut-off 1% (0.62; 95%CI, 0.58-0.66); EGFR mutation had higher AUC (0.69; 95%CI, 0.65-0.73) than KRAS (0.53; 95%CI, 0.49-0.58); tTMB measured by Whole Exosome Sequencing (WES) had approximate AUC to that measure by targeted gene panel. The predictive accuracy of the biomarkers was further compared for patients receiving ICI-based combination therapy. The AUC of combined marker (0.70; 95%CI, 0.66-0.74) remained the highest for combination therapy. Conclusions: Combined marker (PD-L1+tTMB/bTMB/GEP) has superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. bTMB is a promising liquid biopsy biomarker. The prescription of ICI for patients with EGFR mutation should be cautious. Further investigation is warranted to precisely identify biomarkers in various clinical settings. [Table: see text]