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Prostaglandin E2 (PGE2) is widely recognized as one of the major bioactive lipids that, with the striking regenerative potential, promote drug-resistance in cancer cells as well as immune evasion in the tumor microenvironment (TME). Primarily driven by apoptotic cell death, PGE2 is thought to elicit wound-healing responses to help provide an immunosuppressive and proliferative niche that supports cancer stem cell repopulation and thereby therapy-resistance. While COX1/2 inhibitors that attenuate PGE2 production have shown promising anti-cancer effects in various (pre-)clinical settings, the gastrointestinal- and cardiotoxicities precluded their development as anti-cancer agents. It is anticipated that specific targeting of PGE2 signaling via its cognate receptors constitutes a safer and potentially more effective approach. Of the receptor subtypes EP1-4, Gα,s-coupled EP2 and EP4 are believed to be directly involved in immunosuppressive effects of PGE2.OCT-598 is a novel, highly potent and selective EP2/EP4 dual antagonist with Ki values of 23 nM and 0.2 nM vs EP2 and EP4, respectively. PGE2 inhibited normal differentiation of human monocytes into CD1a+CD16- dendritic cells under the presence of GM-CSF and IL-4 and promoted differentiation towards CD1a-CD16+ macrophages in vitro. However, EP2/EP4 dual inhibition by OCT-598 reversed this phenomenon to a greater extent than either EP2- or EP4-specific inhibitor alone. In vivo, OCT-598 effected tumor growth inhibition in multiple syngeneic mouse models as a single agent as well as in combination with an immune checkpoint blocker (ICB). Furthermore, the addition of OCT-598 to the lung cancer standard-of-care regimen (anti-PD-1 plus chemotherapy) in TC-1 mouse lung adenocarcinoma model gave rise to complete tumor regression. In conclusion, dual blockade of EP2 and EP4 by OCT-598 is shown to be a compelling strategy to reinforce antitumor effects by thwarting PGE2-mediated therapy resistance and immune evasion.Findings from this study provide a rationale for clinical development of OCT-598 as a therapeutic option for human malignant cancers. Citation Format: Youngrae Lee, Sujeong Baek, Dong Kwon Kim, Yeri Lee, Donggeon Kim, Seongin Jo, Sang Kyun Lim, Young Sook Shin, Soonsang Kwon, Seung Min Yang, Young Taek Kim, Seong-San Kang, Chun-Bong Synn, Kwangmin Na, Mi Hyun Kim, Heekyung Han, Yu Jin Han, Sungwoo Lee, Jae Hwan Kim, Mi Ran Yun, Youngseon Byeon, Young Seob Kim, Ji Yun Lee, Jii Bum Lee, Chang Gon Kim, Min Hee Hong, Sun Min Lim, Kyoung-Ho Pyo, Byoung Chul Cho, Taeyoung Yoon. OCT-598, a novel EP2/EP4 dual antagonist, promotes anti-tumor immune responses in syngeneic mouse tumor models in combination with standard-of-care chemo- and immunotherapies [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 3234.

Heterogeneity in resistant to immunotherapies of tumor microenvironment (TME) has been implicated in immunotherapies to cause immune evasion or drug resistance. This study was conducted to explore the heterogeneity of TME through multiplex IHC, spatial and RNA sequencing analysis. We selected a sample from a lung adenocarcinoma patient without EGFR-activating mutation and expressing 30% of PD-L1. For quantitative analysis by multiplex IHC, various markers including CD4, CD8, FoxP3, granzyme B, CD20 and pan-cytokeratin were stained with 7 different fluorescence dyes, which was imaged with Vectra Polaris (Akoya). For scRNAseq and spatial RNAseq, we used 5’ chromium library kit (10X Genomics) to make library construction. Integrated raw data was generated using Cell ranger, Seurat pipeline and Azimuth package. The tumor area was divided into 16 clusters in which we selected 2 clusters based on CD3/45 expression. There was a noticeable distinction between the two clusters which were defined as the ‘High’ region (CD45highCD3high cluster) and the ‘Low’ region (CD45lowCD3low cluster). By multiplex IHC, percentage of CD8+T cells was higher in the ‘High’ region than in the ‘Low’ region (8.5% vs. 0.8%, respectively). Subsequent analysis of two clusters using spatial and single cell RNA seq, the ‘Low’ region was characterized by increased hypoxia-associated gene expressions including HIF1A, HIF3A and VEGFA. Various immune cells were abundant in the ‘High’ region and CD45 expression level was 11-fold higher in the ‘High’ region compared to the ‘Low’ region. Cytokine/chemokine network analysis via spatial RNAseq revealed that gene expression of tumor necrosis factor (TNF) family-associated factors increased in the 'High' region compared to the ‘Low’ region (TNF, FAS, TRAIL, RANKL and CD40), which is well-known to promotes apoptosis, programmed cell death, or necrosis of certain cancer. Additionally, the ‘High’ region also had elevated levels of the PD-1/PD-L1, CD155, CD122/TIGIT, Siglec10/CD24, LAG3/LAGLS3, and CD47/CD172a axes, suggesting active immune responses. Intriguingly, combined analyses showed that ‘High’ region showed enhanced level of CD44 expression as the leading-edged gene, which suggests the metastatic potential of tumor cells. Furthermore, scRNA analysis confirmed that CD44 expression was mainly higher in macrophages, suggesting that tumor-associated macrophages partially affected tumor cell metastasis in the ‘High’ region. Our finding suggests that understanding the intratumoral immunological heterogeneity of lung adenocarcinoma can help to study the mechanism of tumor heterogeneity by integrated spatial RNAseq and scRNAseq analyses. This type of technique could be applied to understand complex networks of anti-tumor immune activities, drug resistance mechanisms and immunotherapeutic response of cancer. Citation Format: Seul Lee, Jae-Hwan Kim, Kwangmin Na, Seung Min Yang, Dong Kwon Kim, Sujeong Baek, Seong-san Kang, Yu Jin Han, Chun-Bong Synn, Mi hyun Kim, Heekyung Han, Young Taek Kim, Sungwoo Lee, Youngseon Byeon, Young Seob Kim, Ji Yun Lee, Jii Bum Lee, Chang Gon Kim, Min Hee Hong, Sun Min Lim, Kyoung-Ho Pyo, Byoung Chul Cho. Characterization of immunological heterogeneity in the tumor microenvironment by integrated analyses using single cell RNAseq, spatial RNAseq and multiplex IHC [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 6780.

Background: The Aryl hydrocarbon receptor (AhR) is one of the most predominant regulators of cancer metabolism. The AhR exerts important immunosuppressive functions by activating Treg cells and myeloid-derived suppressor cells and repressing CD8+ effector T cells. Here, we propose that a best-in-class AhR inhibitor, DA-4505, improves anti-tumor efficacy via modulation of tumor immune surveillance compared to BAY2416964, an AHR antagonist drug candidate being studied in the clinical phase. Methods: To evaluate anti-tumor effects of DA-4505 and BAY2416964, the two AhR inhibitors were dosed at 10 mg/kg once daily alone or in combination with aPD-1 (10 mg/kg) in surgical and chemotherapy models, and a PDX model (YHIM2004). Tumor volume, relapse, and survival were evaluated, and immune profiles were analyzed with IHC, flow cytometry, and scRNAseq. Results: A significant tumor reduction appeared in the CT26 and 4T1 tumor models after the DA-4505 treatment compared to vehicle group (P Conclusion: The AhR inhibitor DA-4505 demonstrated an improvement in anti-tumor efficacy. In addition, it has shown a synergistic effect when combined with aPD-1. Discoveries from this study provide a preclinical rationale for future clinical implications in solid tumor. Citation Format: DongKwon Kim, Sujeong Baek, Seung Min Yang, Yu Jin Han, Seong-san Kang, Chun-Bong Synn, Mi Hyun Kim, Heekyung Han, Kwangmin Na, Young Taek Kim, Sungwoo Lee, Taedong Han, Hyounmie Doh, Jongho Cho, Dajeong Kim, Daewon Cha, Jae Hwan Kim, Youngseon Byeon, Young Seob Kim, Mi Ran Yun, Ji Yun Lee, Jii Bum Lee, Chang Gon Kim, Min Hee Hong, Sun Min Lim, Byoung Chul Cho, Kyoung-Ho Pyo. A novel AhR inhibitor ‘DA-4505’ improved the anti-cancer efficacy of surgical and chemotherapy via synergistic anti-tumor effects of aPD-1. [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 5107.

Introduction: EGFR mutations holds the major targets for drug in lung adenocarcinoma (LUAD). Despite the tremendous study of EGFR mutant (MT) LUAD, the comprehensive interpretation of the heterogeneous character of LUAD harboring EGFR MT remains a key challenge. Here, we investigated the heterogeneity of EGFR MT LUAD and explored the tumor microenvironment (TME) in EGFR MT LUAD. Method: We performed single-cell RNA sequencing (scRNA-seq) from 135 LUAD patients which consist of normal(n=24), EGFR wild (WT)(n=18), and MT(n=93). Also, we used whole genome sequencing and bulk-RNA sequencing to validate with scRNA-seq results. From 898,648 cells, main cell types were classified. To explore the various characteristics of MT LUAD tumor cells, we used two ways: i) We re-clustered epithelial cells populating the normal, WT, and MT. ii) We re-clustered only MT epithelial cells. In each analysis, we identified the tumor character in the clusters using differential expressed genes analysis, lineage tracing, clinical information, mutation, and trajectory analysis. Also, we extracted each main cell type except epithelial cells, and identified subtypes of main cell types. Finally, we revealed the interaction of cellular components in TME. Results: In the analysis of epithelial cells, we identified characteristics of specific EGFR MT by comparing of EGFR WT and MT tumors in clusters with similar biological features. The cluster represented by alveolar type 2 (AT2) known as initiation of LUAD was populating normal, WT, and MT. In this cluster, MT- and WT-associated pathway shared but differently significant between MT and WT in the pathway analysis. The cluster represented by proliferative is mostly comprised tumor cells and we found significantly increased the expression of MDK, CD24 in the MT of the cluster. In the analysis of only MT epithelial cells, 2 of clusters were stage-specific cluster: i) The cluster annotated as early stage cluster, ii) The cluster annotated as advanced stage cluster. Trajectory showed that there is a pseudotemporal continuum, following the stage from early stage cluster to advanced stage cluster. Also, based on the lineage tracing, 2 of clusters revealed lineage-specific clusters: i) The cluster annotated as AT2 was enriched from early stage cells, ii) The cluster annotated as basal cell known as origin of lung squamous cell carcinoma(LUSC) was enriched from advanced stage cells. Psedotemporal ordering of these cluster revealed AT2 cluster transdifferentiate into basal cell cluster which implied the possibility of LUAD to LUSC transition by drug resistance. In the interaction of MT and WT TME, the number of signaling received epithelial cells from myeloid cells, endothelial cells, and fibroblasts as sender increased compared with the interaction of normal. Conclusion: We shed light on the ecosystem of TME according to clinical and biological feature of tumor in EGFR mutant LUAD. Citation Format: You Won Lee, Eun Ji Lee, Seung Yeon Oh, Kyoung-Ho Pyo, Seong Gu Heo, YoungJoon Park, Su-Jin Choi, Kyumin Lim, Ju-hyeon Lee, Jae Hwan Kim, Jii Bum Lee, Ji Yoon Lee, Sun Min Lim, Chang Gon Kim, Min Hee Hong, Mi Ran Yun, Byoung Chul Cho. Phenotype profiling of tumor microenvironment in EGFR mutant lung adenocarcinoma with multi-omics data. [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 5935.

Introduction: Anaplastic lymphoma kinase (ALK)-tyrosine kinase inhibitors (TKIs) have improved an initial clinical response of non-small-cell lung cancer (NSCLC) patients with ALK-rearrangements. However, a subset of patients shows a poor response to ALK-TKIs. Here, we aimed to identify novel mechanism of primary resistance in preclinical model from a patient who presented an impressive resistance to sequential treatment with ALK TKIs. Experimental design: The PDC YU-1076 cells were established from pleural effusion of the patient at the time he was receiving chemotherapy and radiotherapy after failure of ALK-TKI treatment. Sanger sequencing confirmed ML4-ALK variant 1 detected at the initial diagnosis. No resistance mutations in the ALK kinase domain were detected. To investigate co-occurring genetic alterations, we performed whole exome sequencing (WES) on YU-1076 cells and the matched blood sample. We further investigated the molecular profile of YU-1076 cells using RNA-sequencing analysis. Results: YU-1076 cells exhibited cross-resistance to clinically available ALK-TKIs including crizotinib, ceritinib, alectinib, and lorlatinib. However, immunoblot analysis of YU-1076 cells treated with incremental doses of TKIs unexpectedly revealed an effective reduction of ALK activity and downstream signals. We noticed that YU-1076 cells gradually changed from a small, round shape to a fibroblast-like shape following the treatment of ALK-TKIs. Transcriptome analysis confirmed enrichment for gene signatures related epithelial-to-mesenchymal transition (EMT) in ALK TKI-treated YU-1076 cells, suggesting that ALK-TKIs treatment promotes YU-1076 cells toward a more mesenchymal phenotype. WES analysis identified a major chromatin remodeling complex subunit, AT-rich interacting domain 1A (ARID1A), as well as MYC amplification, CDKN2A loss, and TP53 mutations. We focused on a synthetic lethal strategies using the SFK inhibitor dasatinib and the EZH2 inhibitor GSK126 in ARID1A mutant cancers. The combination of dasatinib with ALK-TKIs restored the sensitivity to the ALK TKIs in YU-1076 cells, accompanied by suppression of EMT marker genes VIM and CDH2 and increase of apoptotic markers BIM, PARP, and CAS3. Congruently, dasatinib significantly impaired tumor growth in YU-1076-xenografts. GSK126 also induced synergistic inhibition of cell growth with upregulation of apoptosis marker genes in YU-1076 cells, but did not affect the expression of EMT marker genes. Conclusion: Our data indicate that ARID1A could be potentially used as a predictive biomarker for unfavorable ALK-TKI response. In this context, a combination strategy of ALK TKI with dasatinib may be effective in overcoming primary resistance. Citation Format: Seung Yeon Oh, You Won Lee, Eun Ji Lee, Ju Young Kim, Sewon Park, Ju Yeon Park, Su-Jin Choi, Mi Ra Yu, Jii Bum Lee, Jiyun Lee, Chang Gon Kim, Sun Min Lim, Min Hee Hong, Mi Ran Yun, Byoung Chul Cho. Targeting the ARID1A mutations overcomes primary resistance to ALK inhibitors in EML4-ALK posistive NSCLC. [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 3884.

Introduction: Unmet needs exist for immunotherapy targeting PD-1/PD-L1 in head and neck squamous cell carcinoma (HNSCC) and lung squamous cell carcinoma (LUSC) due to its suboptimal response. Amivantamab, a bispecific antibody targeting epidermal growth factor receptor (EGFR) and c-Met, has been demonstrated to induce antibody-dependent cytotoxicity and trogocytosis in tumor cells. We hypothesized that combination of amivantamab with pembrolizumab may synergistically enhance antitumor immunity. In this study, we present comprehensive immunomodulatory and synergistic antitumor efficacy of amivantamab and pembrolizumab in humanized HNSCC and LUSC mice models. Methods: EGFR and MET-expressing tumors from a HNSCC and a LUSC patient were transplanted into Hu-CD34-NSG to establish humanized patient-derived xenograft (PDX) models. Tumor-bearing PDXs were treated with vehicle, pembrolizumab (10mpk, Q5D, n=10), amivantamab (10mpk, BIW, n=10), or a combination of pembrolizumab and amivantamab (n=10). Analysis of immune modulatory responses within the tumor microenvironment (TME) using multiplexed IHC, flow cytometry, and single cell RNA sequencing was performed. Results: Combination of amivantamab and pembrolizumab showed a significant reduction of tumor volume (p Conclusion: Our study demonstrated combinatorial benefits of amivantamab and pembrolizumab by effectively remodeling TME, providing a preclinical rationale to clinically combine amivantamab and PD-1 blockade treatments. Citation Format: Sun Min Lim, Chun-Bong Synn, Seong-san Kang, DongKwon Kim, Soo-Hwan Lee, Sujeong Baek, Seung Min Yang, Yu Jin Han, Mi hyun Kim, Heekyung Han, Kwangmin Na, Young Taek Kim, Sungwoo Lee, Mi Ran Yun, Jae Hwan Kim, Youngseon Byeon, Young Seob Kim, Jii Bum Lee, Ji Yun Lee, Chang Gon Kim, Min Hee Hong, Kyoung-Ho Pyo, Joshua Curtin, Bharvin Patel, Isabelle Bergiers. Combinatorial activity of amivantamab and pembrolizumab in head and neck squamous cell carcinoma and lung squamous cell carcinoma expressing wild-type EGFR and MET [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 5865.

Introduction: Acquired resistance to ALK-tyrosine kinase inhibitors (ALK-TKIs) treatment, particularly target-off resistance, remains a clinical challenge for ALK-rearranged non-small cell lung cancer (NSCLC). To explore novel vulnerabilities of ALK TKI-resistant cancer cells, we focused on their distinct metabolic pathways for growth and survival. Experimental Design: To investigate metabolic pathways in resistance mechanisms, we generated ALK-TKIs -acquired-resistant in vitro/vivo models. We screened metabolite mechanisms using metabolite assay kit, Seahorse Extracellular Flux Analyzer, real-time PCR, western blot, RNA-seq in resistant models. Results: Through an integrated transcriptomic and metabolic assay screening approach, we identified the enhanced reliance on glutamine metabolism in target-off ALK-TKIs-resistant cells. Specifically, resistant cells were characterized by upregulation of glutaminase 1 (GLS1), a mitochondrial enzyme hydrolyzing glutamine into glutamate, simultaneously with downregulation of mitochondrial oxidative phosphorylation (OXPHOS). We demonstrated that this metabolic state intensively accelerates glutaminolysis and subsequent mitochondrial glutamine-derived aspartate synthesis, resulting in TKI resistance by reinforcing antioxidant capacity with increase of NADPH and glutathione. Mechanistically, GLS1 inhibition elicited a marked reduction of cell growth with increase of reactive oxygen species (ROS) in resistant cells, which was restored by supplementation of exogenous aspartate. The antitumor activity of GLS1 inhibition against resistant tumor cells was further validated in in vivo experiments, patient-derived xenograft (PDX) and EML4-ALK transgenic mice. More importantly, glutaminase inhibitor CB-839 enhanced the therapeutic efficacy of anti-PD-L1 treatment in immune checkpoint blockade (ICB)-resistant EML4-ALK transgenic mice. Conclusion: Our findings highlight a new metabolic vulnerability of ALK-TKIs resistant tumors and provide a rationale for targeting GLS1 as a potential treatment option to overcome ALK-TKIs resistance. Citation Format: You Won Lee, Hun Mi Choi, Seung Yeon Oh, Eun Ji Lee, Kyoung-Ho Pyo, Jae Hwan Kim, Youngseon Byeon, Seong Gu Heo, Sun Min Lim, Min Hee Hong, Chang Gon Kim, Hye Ryun Kim, Mi Ran Yun, Byoung Chul Cho. Targeting adaptive metabolic program as a novel treatment approach for TKIs-failed ALK-positive NSCLCs [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 LB544.

Cancer immunotherapy with anti-PD-1 therapy (αPD-1) has greatly improved the survival outcome of patients with non-small cell lung cancer (NSCLC). However, the response rates of αPD-1 are around 20-30% based on clinical trials. The presence of PD-L1, tumor infiltrating lymphocyte or tumor mutation burden may be used as indicators of response, but are still limited to predict αPD-1 response. In this study, we established the machine learning based clinical decision support system (CDSS) to predict the αPD-1 response by comprehensively combining clinical information and blood-based data which are easily assessable in routine practice.We enrolled 126 patients with NSCLC treated with the αPD-1 at Yonsei cancer center. Clinical data including patient characteristics, mutation, treatment outcomes, and adverse events were collected and analyzed. Forty patients additionally had blood-based immune data by flow cytometry. There were two data sets; clinical data set (n=126) with 15 variables, and immune data set (n=40) with 37 variables. We found that 27 variables out of 52 variables are selected by recursive feature elimination. The responders are defined as PR or SD ≥6 months and the non-responders are defined as the others. Supervised learning algorithms such as the LASSO, Ridge, Elastic Net, SVM, ANN, and RF were applied to each data set for predicting the αPD-1 response. The performances of each model were evaluated according to the ROC curve or cross-validation errors. Variable importance was measured by using the random forest and gradient boosting.Patient characteristics included male (69.8%), age ≥ 60 years (66.2%), ECOG 0/1 (77.7%), adenocarcinoma (69.8%), EGFR mutations (15.1%), and PD-L1 positive (61.2%). We classified the patients into responders (38%) and non-responders (62%) in total 126 patients. A result from the clinical data set of 126 patients demonstrated that the Ridge regression model (AUC: 0.78) can more accurately predict the αPD-1 response than others. Of 15 clinical variables, some are considered to be important in the following order; tumor burden,age, PD-L1, ECOG PS, and irAE based on the random forest. When we performed the machine learning process with clinical and immune data, The Ridge regression model (AUC:0.82) showed the good performance to predict αPD-1 response, compared to the single clinical model. The machine learning based CDSS for aPD-1 to NSCLC patients has benefit for predicting aPD-1 responses. Our prediction model could be easily accessible and fast processed in routine practice. The supervised machine learning based non-invasive predictive score (NIPS) demonstrates the rate of aPD-1 response on NSCLC patients. We will validate NIPS in independent patient cohort and currently are establishing the NIPS as web-based software. Citation Format: Kyoung-Ho Pyo, Beung-Chul Ahn, Chun-Feng Xin, Dongmin Jung, Chang Gon Kim, Min Hee Hong, Byoung Chul Cho, Hye Ryun Kim. A machine learning based clinical decision support system (CDSS) for anti-PD-1 therapy using non-invasive blood marker and clinical information for lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 683.