Aberrant expression of claudin18.2 (CLDN18.2) has frequently been observed in gastric and gastroesophageal junction (G/GEJ) adenocarcinoma, making it a promising therapeutic target for this aggressive cancer. While a monoclonal antibody targeting CLDN18.2 has been approved for G/GEJ adenocarcinoma, antibody–drug conjugates (ADCs) have also emerged as therapeutic modalities. IBI343 is an ADC consisting of a fully humanized anti-CLDN18.2 monoclonal antibody conjugated to exatecan via site-specific glycol conjugation and a cleavable linker with a drug-to-antibody ratio of 4. Here we present the results from a phase 1 dose escalation and dose expansion study of the IBI343 ADC. A total of 127 patients were enrolled and dosed (19 in the escalation phase and 108 in the expansion phase). Dose-limiting toxicities occurred in two of six participants at a dose of 10 mg kg⁻¹, including one with myelosuppression (grade 4) and one with both neutropenia (grade 4) and febrile neutropenia (grade 3). Minimal gastrointestinal adverse events (grade ≥3) were observed and no interstitial lung disease was reported. The recommended phase 2 dose of IBI343 was determined to be 6 mg kg⁻¹ every 3 weeks with a confirmed objective response rate of 29% and median progression-free survival of 5.5 months in CLDN18.2-high (2+/3+ ≥ 75%) G/GEJ adenocarcinoma. IBI343 was well tolerated, with a manageable safety profile and promising efficacy in G/GEJ adenocarcinoma. Further research is required to understand optimal sequencing, and biomarker-informed combination therapy, in G/GEJ tumors given the development of multiple therapies targeting CLDN18.2 in addition to human epidermal growth factor receptor 2 and programmed cell death 1 ligand 1. ClinicalTrials.gov registration: NCT05458219.

Background: Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) require multi‐modality treatment. Immune checkpoint inhibitors (ICIs) are now standard of care in management of recurrent/metastatic HNSCC. However, its role in the definitive and neoadjuvant setting remains unclear.Methods: A literature search was conducted that included all articles investigating ICI in untreated locally advanced (LA) HNSCC. Data was extracted and summarised and rated for quality using the Cochrane risk of bias tool.Results: Of 1086 records, 29 met the final inclusion criteria. In both concurrent and neoadjuvant settings, the addition of ICI was safe and did not delay surgery or reduce chemoradiotherapy completion. In the concurrent setting, although ICI use demonstrates objective responses in all published trials, there has not yet been published data to with PFS or OS benefit. In the neoadjuvant setting, combination ICI resulted in superior major pathological response rates compared to ICI monotherapy without a significant increase adverse event profiles, but its value in improving survival is not clear. ICI efficacy appears to be affected by tumour characteristics, in particular PD‐L1 combined positive score, HPV status and the tumour microenvironment.Conclusions: There is significant heterogeneity of ICI use in untreated LA HNSCC with multiple definitive concurrent and neoadjuvant protocols used. Resultantly, conclusions regarding the survival benefits of adding ICI to standard‐of‐care regimens cannot be made. Further trials and translational studies are required to elucidate optimal ICI sequencing in the definitive setting as well as better define populations more suited for neoadjuvant protocols.

PURPOSE: Fear of cancer recurrence (FCR) affects 50%-70% of cancer survivors. This multicenter, single-arm study sought to determine the participant-rated usefulness of an oncologist-delivered FCR intervention.METHODS: Women who completed treatment for early breast cancer (could be receiving endocrine therapy) with baseline FCR > 0 were invited to participate. FCR was measured using a validated 42-item FCR Inventory. The brief oncologist-delivered intervention entailed (1) FCR normalization; (2) provision of personalized prognostic information; (3) recurrence symptoms education, (4) advice on managing worry, and (5) referral to psycho-oncologist if FCR was high. FCR, depression, and anxiety were assessed preintervention (T0), at 1 week (T1), and 3 months (T2) postintervention. The primary outcome was participant-rated usefulness. Secondary outcomes included feasibility and efficacy.RESULTS: Five oncologists delivered the intervention to 61/255 women invited. Mean age was 58 ± 12 years. Mean time since breast cancer diagnosis was 2.5 ± 1.3 years. Forty-three women (71%) were on adjuvant endocrine therapy. Of 58 women who completed T1 assessment, 56 (97%) found the intervention to be useful. FCR severity decreased significantly at T1 (F = 18.5, effect size = 0.39, P < .0001) and T2 (F = 24, effect size = 0.68, P < .0001) compared with baseline. There were no changes in unmet need or depression or anxiety. Mean consultation length was 22 minutes (range, 7-47 minutes), and mean intervention length was 8 minutes (range, 2-20 minutes). The intervention was perceived as useful and feasible by oncologists.CONCLUSION: A brief oncologist-delivered intervention to address FCR is useful and feasible, and has preliminary efficacy in reducing FCR. Plans for a cluster randomized trial are underway.

PURPOSE: Over the past 15 years, the landscape of early phase clinical trials (EPCTs) has undergone a remarkable expansion in both quantity and intricacy. The proliferation of sites, trials, sponsors, and contract research organizations has surged exponentially, marking a significant shift in research conduct. However, EPCT operations suffer from numerous inefficiencies, such as cumbersome start-up processes, which are particularly critical when drug safety and the recommended phase II dose need to be established in a timely manner. Networks and consortia may overcome some of these challenges of enrolling suitable patients and streamlining start-up, particularly when distance and disease trajectory come into play. DESIGN: In this article, we provide an overview of EPCT consortia in adult oncology across different continents assembled through systematic review of the literature and snowball sampling methodology. We illustrate their scope, structure, funding, and achievements. RESULTS: Fifteen EPCT consortia were identified including two in the United States, three in Europe, five in Asia-Pacific, two intercontinental consortia, and three within private oncology networks. These consortia vary in their scope, funding, and structure from government-funded models such as the National Cancer Institute Experimental Therapeutics Clinical Trials Networks through charitably funded and private research organizations. EPCT consortia play a role in collaborative research, molecular tumor boards to provide patient-centric biomarker-matched treatments, and streamlining trial conduct to improve timelines and cost efficiency. CONCLUSION: The growth in EPCT activity and complexity has resulted in expansion in the number of EPCT consortia globally. By actively engaging with regulatory bodies and pharmaceutical and contract research organization industries, consortia have an opportunity to address the evolving challenges faced in this field and to accelerate the translation of scientific discoveries into clinical practice.

Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a federated deep learning approach (ProCanFDL), training local models on simulated sites containing data from a pan-cancer cohort (n = 1,260) and 29 cohorts held behind private firewalls (n = 6,265), representing 19,930 replicate data-independent acquisition mass spectrometry runs. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain on the hold-out test set (n = 625) in 14 cancer subtyping tasks compared with local models and matching centralized model performance. The approach’s generalizability was demonstrated by retraining the global model with data from two external, data-independent acquisition mass spectrometry cohorts (n = 55) and eight acquired by tandem mass tag proteomics (n = 832). ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data, for example, for discovering predictive biomarkers or treatment targets while maintaining data privacy. Significance: A federated deep learning approach applied to human proteomic data, acquired using two distinct proteomic technologies from 40 tumor cohorts across eight countries, enabled accurate cancer histopathologic subtyping while preserving data privacy. This approach will enable the privacy-compliant development of large-scale proteomic artificial intelligence models, including foundation models, across institutions globally.