Augustin, Ryan C.

Recent advances in gastroesophageal cancer highlight the continued evolution of systemic therapy across disease stages, including refinements in perioperative strategies and expansion of biomarker‐directed treatment in advanced disease. Emerging therapeutic approaches, including next‐generation antibodies and combination strategies, are expected to further shape treatment selection and improve outcomes.

The traditional combined hematology and oncology fellowship model is increasingly strained by accelerating subspecialization and therapeutic complexity. This commentary focuses on structural reforms within fellowship training to better align education with contemporary clinical practice and evolving workforce demands. We propose standardized, career-aligned tracks, earlier subspecialty focus within fellowship, and redesigned continuity clinic models that preserve foundational breadth while enabling depth of expertise. We further highlight how emerging assessment reforms and educational tools can support these structural changes. By aligning fellowship training with both real-world clinical demands and established educational science, we can ensure a more sustainable and effective pathway for preparing future hematologists and oncologists.

THE 2025 American Society of Clinical Oncology (ASCO) Annual Meeting underscored a key principle: in today’s complex and rapidly evolving cancer landscape, the application of knowledge, not just its acquisition, is our most powerful tool for progress. Robin Zon’s presidential theme, “Driving Knowledge to Action: Building a Better Future,” was brought to life across the plenary sessions and data presentations that spanned tumor types, geographies, and therapeutic modalities. Two dominant motifs emerged from the most practice-changing studies: the use of large-scale, well-designed clinical trials to validate transformative interventions, and a growing effort to repurpose effective therapies earlier in the disease course, challenging historical treatment sequences. These principles reflect the essence of oncology’s future: evidence-powered, patient-centered, and accessible to all.

Cancer immunotherapy—including immune checkpoint inhibition (ICI) and adoptive cell therapy (ACT)—has become a standard, potentially curative treatment for a subset of advanced solid and liquid tumors. However, most patients with cancer do not benefit from the rapidly evolving improvements in the understanding of principal mechanisms determining cancer immune responsiveness (CIR); including patient-specific genetically determined and acquired factors, as well as intrinsic cancer cell biology. Though CIR is multifactorial, fundamental concepts are emerging that should be considered for the design of novel therapeutic strategies and related clinical studies. Recent advancements as well as novel approaches to address the limitations of current treatments are discussed here, with a specific focus on ICI and ACT.

Abstract The field of oncology has been transformed by immune checkpoint inhibitors (ICI) and other immune-based agents; however, many patients do not receive a durable benefit. While biomarker assessments from pivotal ICI trials have uncovered certain mechanisms of resistance, results thus far have only scraped the surface. Mechanisms of resistance are as complex as the tumor microenvironment (TME) itself, and the development of effective therapeutic strategies will only be possible by building accurate models of the tumor-immune interface. With advancement of multi-omic technologies, high-resolution characterization of the TME is now possible. In addition to sequencing of bulk tumor, single-cell transcriptomic, proteomic, and epigenomic data as well as T-cell receptor profiling can now be simultaneously measured and compared between responders and nonresponders to ICI. Spatial sequencing and imaging platforms have further expanded the dimensionality of existing technologies. Rapid advancements in computation and data sharing strategies enable development of biologically interpretable machine learning models to integrate data from high-resolution, multi-omic platforms. These models catalyze the identification of resistance mechanisms and predictors of benefit in ICI-treated patients, providing scientific foundation for novel clinical trials. Moving forward, we propose a framework by which in silico screening, functional validation, and clinical trial biomarker assessment can be used for the advancement of combined immunotherapy strategies.

Acral melanoma (AM) has distinct characteristics as compared with cutaneous melanoma and exhibits poor response to immune checkpoint inhibitors (ICIs). Tumor-intrinsic mechanisms of immune exclusion have been identified in many cancers but less studied in AM. We characterized clinically annotated tumors from patients diagnosed with AM at our institution in correlation with ICI response using whole transcriptome RNAseq, whole exome sequencing, CD8 immunohistochemistry, and multispectral immunofluorescence imaging. A defined interferon-γ-associated T cell-inflamed gene signature was used to categorize tumors into non-T cell-inflamed and T cell-inflamed phenotypes. In combination with AM tumors from two published studies, we systematically assessed the immune landscape of AM and detected differential gene expression and pathway activation in a non-T cell-inflamed tumor microenvironment (TME). Two single-cell(sc) RNAseq AM cohorts and 11 bulk RNAseq cohorts of various tumor types were used for independent validation on pathways associated with lack of ICI response. In total, 892 specimens were included in this study. 72.5% of AM tumors showed low expression of the T cell-inflamed gene signature, with 23.9% of total tumors categorized as the non-T cell-inflamed phenotype. Patients of low CD3 + CD8 + PD1 + intratumoral T cell density showed poor prognosis. We identified 11 oncogenic pathways significantly upregulated in non-T cell-inflamed relative to T cell-inflamed TME shared across all three acral cohorts (MYC, HGF, MITF, VEGF, EGFR, SP1, ERBB2, TFEB, SREBF1, SOX2, and CCND1). scRNAseq analysis revealed that tumor cell-expressing pathway scores were significantly higher in low versus high T cell-infiltrated AM tumors. We further demonstrated that the 11 pathways were enriched in ICI non-responders compared with responders across cancers, including AM, cutaneous melanoma, triple-negative breast cancer, and non-small cell lung cancer. Pathway activation was associated with low expression of interferon stimulated genes, suggesting suppression of antigen presentation. Across the 11 pathways, fatty acid synthase and CXCL8 were unifying downstream target molecules suggesting potential nodes for therapeutic intervention. A unique set of pathways is associated with immune exclusion and ICI resistance in AM. These data may inform immunotherapy combinations for immediate clinical translation.