Shitara, Kohei

380 Background: KRAS amplifications (amp) occur in ~2% of solid tumors, representing a high unmet need for effective targeted therapies. BI3706674 binds to GDP-bound KRAS and locks KRAS protein in an inactive form. In preclinical models, BI3706674 has shown potent inhibition of KRAS-amp tumors. Methods: This is a Phase Ia/b trial (NCT06056024) to explore the safety, pharmacokinetics (PK), pharmacodynamics (PD) and efficacy of BI 3706674 in patients (pts) with unresectable or metastatic KRAS wild type amp or KRAS G12V mutated (mut) solid tumors. The trial aimed to define the maximum tolerated dose (MTD). Pts (ECOG 0 -1) received BI 3706674 daily per os at 50 - 1200 mg doses. Dose escalation (DE) was guided by a Bayesian logistic regression model. This report focuses on KRAS wt amp pts from Phase Ia (DE). Results: As of 31 July 2025, 46 pts had received BI 3706674. Pts (n=15/46) with KRAS wt amp tumors had upper gastrointestinal tract (uGI) cancer [n=9: gastric (GAC;n=5), oesophageal (EAC; n=2), gastroesophageal junction (GEJC; n=2) cancers], Cholangiocarcinoma (n=1), colorectal (CRC; n=4), and ovarian (OC; n=1) cancers. Pts were treated at 200 mg (n=2), 400 mg (n=1), 800 mg (n=5), 1200 mg (n=7) doses; males: n=11; ECOG 1: n=10; median age - 62 years (range 38–83); median number of prior treatment lines was 3 (range 1-6). AEs were reported in 15 pts (100%), including 12 pts (80%) with treatment-related AEs (TRAE). High-grade AEs (Grade 3-5) were reported in 10 pts (66.7%), including 4 pts (26.7%) with TRAEs. SAEs were reported in 7 pts (46.7%), including 2 pts (13.3%) with TRAEs. The most-frequent AEs were mostly low-grade (Grade 1-2) diarrhoea (10 pts, 66.7%), nausea (10 pts, 66.7%), and vomiting (9 pts, 60.0%), often reported as TRAE. Two dose limiting toxicities were observed in 1200 mg group: nausea (Grade 3) and vomiting (Grade 3). MTD was not reached. BI 3706674 PK parameters followed the predicted non-linear PK model; dose dependent systemic exposure reached plateau at 800 mg. 12/15 pts with KRAS wt amp tumors, including 10/12 pts in 800 – 1200 mg groups, were efficacy evaluable; Disease control rate (DCR) was 58.3% (7/12 pts): 3/ 12 pts with partial response (PR), 4/12 had stable disease (SD), 5/12 pts - disease progression (PD). In 800 – 1200 mg groups 1 - OC, 2 – CRC pts achieved SD. PK/PD/efficacy correlation data is pending. Conclusions: BI 3706674 showed a tolerable safety profile and clinical efficacy in pts with KRAS amp tumors. Study results provide clinical proof of concept. KRAS wt amp is a druggable target and KRAS-targeting treatment is active in KRAS wt amp uGI cancer pts. Clinical trial information: NCT06056024 . Anticancer activity of BI 3706674 in efficacy evaluable pts with KRAS wt amp tumors. All pts, 200 – 1200 mg, N=12 Pts with uGI cancers,800 – 1200mg, N=7 ORR, n (%) 3* (25%) 3* (43%) SD, n (%) 4 (33.3%) 1 (14%) DCR, n (%) 7 (58.3%) 4 (57%) PD, n (%) 5 (41.7%) 3 (43%) *Tumor shrinkage: -60.3%, -34% and 34.3%.

Abstract Background: Recent studies indicate a correlation between increased stromal composition in tumors and resistance to immune checkpoint inhibitors (ICIs) across various cancer types. Specifically, the extracellular matrix (ECM) within the stromal compartment significantly influence the tumor microenvironment, affecting cancer cell proliferation and immune cell recruitment. However, identifying and quantifying the ECM at the collagen fiber level in whole slide images (WSIs) is challenging due to its inherent heterogeneity and complexity. In this work, we utilized statistical analysis and a deep learning (DL)-based approach to identify and assess collagen in the ECM, examining its characteristics in relation to the ICIs treatment response in gastric cancer. Methods: We analyzed 116 WSIs of hematoxylin and eosin (H&E) stained slides before ICIs treatment from three institutions. Responders were defined as those with a complete response or partial response (N=18); those with stable disease (SD) (N=34) or progressive disease (PD) (N=64) were considered non-responders (N=98). For non-responders, post-treatment H&E slides were available for 21 patients; SD (N=5) and PD (N=16). We applied a DL-based second harmonic generation (SHG) synthesis algorithm to tumor regions identified by a tumor detection model. We then calculated various collagen properties, including volume, fiber orientation and alignment, waviness, straightness, and fiber thickness, based on collagen fiber centerlines extracted from the generated SHG images. An attention-based multiple instance learning (ABMIL) model was trained to automatically predict the treatment response solely based on collagen features. The dataset of 116 pre-treatment slides was divided into training and validation subsets using stratified 3-fold cross-validation. The area under the curve (AUC) was used to assess the performance of the trained models. Results: Collagen fiber features were significantly associated with ICIs response. Notably, ICIs responders have a decrease in collagen waviness and fiber orientation variation (p-value<0.05, by Mann-Whitney U test). Among non-responders, the PD group showed a statistical decrease in waviness after treatment (p-value<0.05, by Mann-Whitney U test). The ABMIL model achieved a mean AUC score of 0.823, with a standard deviation of 0.023. Conclusion: This study provides a comprehensive analysis of collagen in the ECM, and its properties in relation to gastric cancer ICIs response within Tumor Immune Microenvironment. We also developed a model using collagen features and demonstrated high accuracy in predicting treatment response. Citation Format: Minji Kim, Ekaterina Redekop, Yoonho Choi, Sung Hak Lee, Jae-Ho Cheong, Yu Aoki, Kohei Shitara, Tae Hyun Hwang. AI-driven analysis of collagen characteristics in the tumor immune microenvironment predicts immune checkpoint inhibitors treatment responsiveness in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4262.

Abstract Traditional cancer research methodologies predominantly focus on 2D tumor modeling, including spatial profiling and AI-driven analysis at the 2D level. To advance beyond these limitations, we implemented Holotomography (HT), a 3D, label-free optical imaging method. This technique, leveraging refractive index contrasts, allows for enhanced visualization of tumor tissues, organoids, and cells in three dimensions. Using serial H&E sections and unstained slides, we created detailed 3D tumor models in gastric cancer, providing insights into tumor, immune, and stromal composition, as well as cell-cell interactions and extracellular matrix characteristics. AI algorithms further enhanced our 3D tumor modeling, offering novel perspectives on the initiation and progression of tumor, immune, and stromal components at the subcellular level. Analyzing gastric tumors treated with immune checkpoint inhibitors before, during, and after treatment revealed dynamic changes in spatial composition over time, offering unique insights into the evolution of the 3D tumor ecosystem. Additionally, by integrating spatial transcriptomic and in situ molecular imaging data, we developed a novel Multimodal 3D Tumor Model. This model not only uncovers subcellular-level molecular characteristics but also elucidates cellular interactions during treatment, suggesting potential biomarkers and therapeutic approaches. Lastly, by constructing 3D cellular interaction networks incorporating true 3D interactions, we provided an in-depth view of cellular communication within the tumor microenvironment. This pioneering approach, representing the first Multimodal 3D Tumor Model at the subcellular level, offers novel insights into gastric cancer's spatial evolution, potentially revolutionizing our understanding and treatment of gastric cancer. Citation Format: Yoon Ho Choi, Minji Kim, Katya Redekop, Inyeop Jang, Jean R. Clemenceau, Isabel Barnfather, Sumanth Reddy Nakkireddy, Changjin Hong, Sunho Park, Ji-Youn Sung, Jeong Hwan Park, Shitara Kohei, Aoki Yu, Sung Hak Lee, Sam Wang, Jaeho Cheong, Tae Hyun Hwang. AI-driven multimodal 3D tumor modeling with spatial molecular insights for predicting ICI response in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7400.

ImportanceApproval by the US Food and Drug Administration of immune checkpoint inhibition (ICI) for advanced gastroesophageal cancer (aGEC) irrespective of PD-L1 status has generated controversy. Exploratory analyses from individual trials indicate a lack of meaningful benefit from ICI in patients with absent or low PD-L1 expression; however, analysis of a single variable while ignoring others may not consider the instability inherent in exploratory analyses.ObjectiveTo systematically examine the predictive value of tissue-based PD-L1 status compared with that of other variables for ICI benefit in aGEC to assess its stability.Data SourcesMEDLINE, Embase, Scopus, Web of Science, Cochrane Central Register (2000-2022).Study Selection, Data Extraction, and SynthesisRandomized clinical trials (RCTs) were included of adults with aGEC (adenocarcinoma [AC] or squamous cell carcinoma [SCC]) randomized to anti−PD-1 or PD-L1−containing treatment vs standard of care (SOC). Study screening, data abstraction, and bias assessment were completed independently by 2 reviewers. Of 5752 records screened, 26 were assessed for eligibility; 17 trials were included in the analysis.Main Outcomes and MeasuresThe prespecified primary end point was overall survival. The mean hazard ratio (HR) for ICI vs SOC was calculated (random-effects model). Predictive values were quantified by calculating the ratio of mean HRs between 2 levels of each variable.ResultsIn all, 17 RCTs (9 first line, 8 after first line) at low risk of bias and 14 predictive variables were included, totaling 11 166 participants (5067 with SCC, 6099 with ACC; 77.6% were male and 22.4% were female; 59.5% of patients were younger than 65 years, 40.5% were 65 years or older). Among patients with SCCs, PD-L1 tumor proportion score (TPS) was the strongest predictor of ICI benefit (HR, 0.60 [95% CI, 0.53-0.68] for high TPS; and HR, 0.84 [95% CI, 0.75-0.95] for low TPS), yielding a predictive value of 41.0% favoring high TPS (vs ≤16.0% for other variables). Among patients with AC, PD-L1 combined positive score (CPS) was the strongest predictor (after microsatellite instability high status) of ICI benefit (HR, 0.73 [95% CI, 0.66-0.81] for high CPS; and HR, 0.95 [95% CI, 0.84-1.07] for low CPS), yielding a predictive value of 29.4% favoring CPS-high (vs ≤12.9% for other variables). Head-to-head analyses of trials containing both levels of a variable and/or having similar design generally yielded consistent results.Conclusions and RelevanceTissue-based PD-L1 expression, more than any variable other than microsatellite instability-high, identified varying degrees of benefit from ICI-containing therapy vs SOC among patients with aGEC in 17 RCTs.

TPS371 Background: Tucatinib (TUC), a highly selective HER2-directed tyrosine kinase inhibitor (TKI) approved in multiple regions for HER2+ metastatic breast cancer, is being developed as a novel therapy for patients (pts) with GI tumors including gastric or gastroesophageal junction adenocarcinoma (GEC). While trastuzumab (Tras) with chemotherapy is standard in the 1st-line setting for metastatic HER2+ GEC, no anti-HER2 therapy has demonstrated an OS benefit over chemotherapy as 2nd-line therapy, possibly due to loss of HER2 expression following Tras-based therapy. In GEC xenograft models, dual targeting of HER2 with TUC and Tras showed superior activity to either agent alone.(Kulukian 2020) Interim results from the MOUNTAINEER study have shown promising activity for TUC and Tras for HER2+ mCRC.(Strickler 2019) The MOUNTAINEER-02 study is evaluating the efficacy and safety of TUC with Tras, ramucirumab (Ram), and paclitaxel (Pac) in pts with HER2+ GEC in the 2nd-line setting. Methods: MOUNTAINEER-02 (NCT04499924) is a phase 2/3 study evaluating TUC + Tras with Ram and Pac. Pts receive TUC 300 mg or placebo PO BID, Tras (6 then 4 mg/kg) or placebo (IV on Days 1 and 15 of each 28-day cycle), Pac (IV on Days 1, 8, 15), and Ram (IV on Days 1 and 15). Eligible pts have locally-advanced unresectable or metastatic HER2+ GEC and have received a HER2-directed antibody and 1 prior line of therapy for advanced disease. Pts must be ≥18 years of age, with an ECOG ≤1, and have had no prior exposure to Ram, anti-HER2 or anti-EGFR TKI, HER2-directed antibody-drug conjugates, or taxanes ≤12 months before enrollment. Due to the potential impact of TUC on Pac metabolism, the study will include an initial Pac dose optimization stage. The open-label phase 2 part will determine the recommended dose of Pac (60 or 80 mg/m²) combined with TUC, Tras, and Ram in 6-18 pts, and evaluate safety and activity of the regimen in Cohorts 2A and 2B (30 pts each). The randomized, double-blind, phase 3 part will compare the efficacy and safety of TUC and Tras (Arm 3A; ̃235 pts) vs. placebo (Arm 3B; ̃235 pts), both in combination with Ram and Pac, and also evaluate activity of TUC with Ram and Pac (Arm 3C; ̃30 pts). The dual primary phase 3 endpoints are OS and PFS per investigator, with confirmed ORR as a key secondary endpoint. HER2 status is determined at baseline using a blood-based NGS assay, and IHC/ISH of fresh or archival tumor biopsies, if available. Pts must be HER2+ by blood-based NGS in Cohort 2A and phase 3; in Cohort 2B, pts must be HER2+ in a biopsy taken post-progression during/after 1st-line therapy, but HER2-negative by blood-based NGS. Disease assessments per RECISTv1.1 will occur q6 weeks for 36 weeks, then q9 weeks. The pharmacokinetics of TUC, Pac, and their metabolites will be evaluated in a subset of pts, including a cohort with gastrectomies. Enrollment in phase 2 is ongoing. Clinical trial information: NCT04499924.

TPS366 Background: Advanced Gastro-oesophageal Carcinoma (AGOC) has a poor prognosis, and there is no established standard treatment following failure of first- and second-line chemotherapy. Regorafenib (BAY 73-4506) is an investigational oral multi-targeted tyrosine kinase inhibitor (TKI) which targets angiogenic (VEGF, TIE-2), stromal (PDGF-β), and oncogenic (RAF, RET and KIT) receptor tyrosine kinases, and has shown activity in this setting. Single agent regorafenib prolonged progression free survival (PFS) versus placebo across all regions/subgroups in the INTEGRATE randomised phase 2 trial. Current options in refractory AOGC involves sequencing through chemotherapy with the latest active agent approved being trifluridine/tipiracil, TAS-102. Promising activity in refractory AOGC has been seen with the combination of regorafenib & nivolumab. INTEGRATE IIb–will compare the effectiveness of the combination of regorafenib & nivolumab in pre-treated patients with AGOC to current standard chemotherapy. Methods: Randomised phase III, open label study with 2:1 randomisation (RegoNivo : standard chemotherapy) and stratification by: Geographic region (Asia vs. Rest of World); Prior VEGF inhibitors (Yes vs No); Prior immunotherapy (Yes vs No). RegoNivo arm will receive 90mg (3x30mg) of regorafenib days 1-21 of each 28-day treatment cycle with intravenous nivolumab 240 mg day 1 of each 14 day cycle until disease progression or prohibitive adverse events as per protocol. The control arm will receive the investigator’s choice of the following chemotherapy; a taxane (paclitaxel or docetaxel), irinotecan or oral trifluridine/tipiracil (TAS102). Primary endpoint: OS. Secondary endpoints: PFS, response rate, quality of life, toxicity, exploratory correlative biomarkers. Clinical trial information: NCT04879368.

344 Background: ICI with anti-PD-1 therapy was approved by the US FDA as 1st/2nd-line treatment of advanced GEC regardless of PD-L1 status. It is argued that patients (pts) with PD-L1-low GEC do not benefit from ICI. To avoid spurious exclusion of pts, we systematically reviewed phase 3 trials to assess the magnitude and consistency of PD-L1 to predict benefit from ICI. We also examined other potential predictive factors to understand their magnitude and consistency in comparison with PD-L1 status. Methods: MEDLINE, Embase, Scopus, Web of Science, and Cochrane Central Register were searched for all randomized clinical trials (RCT; 2000-2021) in advanced GEC comparing ICI, alone or with chemotherapy, vs standard of care (SOC). The primary endpoint was overall survival (OS). Study screening, data abstraction, and bias assessment were done independently by two reviewers per PRISMA guidelines. The mean HR for ICI vs SOC was calculated by random effects model. The predictive value of a factor was quantified using relative magnitude and consistency (table). Results: 14 RCTs at low risk of bias were included (N = 9,210 pts; KN62, CM649, CM648, ESCORT1st, KN590, ATT4, JAV100, KN181, KN61, ATT3, ESCORT, RATIONALE302, JAV300, ATT2). 6 trials were 1st-line, 8 were after 1st-line. Treatment comparisons were ICI + chemo vs chemo (6 trials), ICI vs chemo (9 trials), and ICI vs placebo (1 trial). ICI was always anti-PD-1/-L1 (1 trial also had anti-CTLA-4). Table shows primary results. To enable head to head comparisons, subgroup analyses of trials containing both levels of a factor or having similar design were done and generally yielded consistent results. Conclusions: PD-L1 CPS is the strongest predictive biomarker, after MSI, for OS benefit from ICI-containing therapy vs SOC. Additional research on gender is warranted.[Table: see text]

TPS4136 Background: AGOC has a poor prognosis with no established standard treatment following failure of chemotherapy (CT). Regorafenib (BAY 73-4506)(REG) is an oral multi-kinase inhibitor targeting kinases involved in angiogenesis (VEGFR1-3, TIE-2), tumor microenvironment (PDGFR-β, FGFR), and oncogenesis (RAF, RET and KIT). INTEGRATE (phase 2) demonstrated REG was highly effective in prolonging PFS across a range of AGOC pts, with a positive OS trend. Regional differences were found in magnitude of effect, but REG was effective in all regions/subgroups. The phase 3 INTEGRATE II will explore whether REG is effective in prolonging survival in patients overall, and in the Asian sub-population. Methods: International (Australia/New Zealand (NHMRC CTC); Canada (CCTG), Korea, Japan, Taiwan, USA (ACCRU)) randomised phase III, double-blind, placebo-controlled trial with 2:1 (REG:placebo)(PBO) randomisation and stratification by: Location of tumour, Geographic region, prior VEGF inhibitors. Eligible patients (histologically confirmed AGOC), with evaluable metastatic or locally advanced disease refractory to, or relapsed following second line CT, will receive best supportive care plus 160mg REG or matched placebo orally on days 1-21 of each 28 day cycle until disease progression or prohibitive adverse events. Primary endpoint is OS. Secondary endpoints: PFS, response rate, quality of life, safety, identification of prognostic/predictive biomarkers for study endpoints, and REG PK across geographical regions. 350 patients (50% from Asia) randomized in a 2:1 ratio will provide 90% power to detect a hazard ratio (HR) for OS of 0.67 with a 2-sided α of 0.05 assuming PBO median survival is 4.5 mos. The sample size accommodates 2 interim analyses undertaken at 1/3 and 2/3 of required events. As of January 2017, 12 of 28 planned ANZ sites are open, with 4 patients enrolled. Regulatory approval has been received for 12 Canadian sites, and 12 Korean sites. Korean recruitment is expected to commence in February 2017. Regulatory submissions are pending in Taiwan, Japan, and the USA. Clinical trial information: NCT02773524.