Li, Shenduo

e18149 Background: Laryngeal neuroendocrine carcinoma (LNEC) is rare and biologically heterogeneous. The independent prognostic roles of tumor differentiation and stage remain incompletely defined. Methods: Patients diagnosed with LNEC (2000–2022) were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) and cancer-specific survival (CSS) were estimated using a Kaplan–Meier analysis. Tumor differentiation (Diff) was harmonized across SEER grade fields: legacy Grade Recode (through 2017) was used when available; otherwise, Grade Clinical/Pathological (2018+) codes (1=well, 2=moderate, 3=poor, 4=undifferentiated) defined Diff. Multivariable Cox regression adjusted for stage, Diff, age, and sex. Cases with missing survival time, stage, or Diff were excluded (n=97). Results: The cohort included 157 patients (median age 63 years; 63% male). Diff was well in 4%, moderate in 29%, poor in 34%, and undifferentiated in 12% of patients. At diagnosis, 22% of patients had localized, 27% had regional, and 28% had distant disease. Treatments included surgery in 31%, chemotherapy in 42%, and adjuvant radiation in 13% of patients. Median OS differed significantly by Diff, ranging from 52.5 months (mo) for well, 90 mo for moderate, 12 mo for poor, and 17 mo for undifferentiated (p<0.001). Five-year OS was 50%, 58%, 23%, and 37%, respectively, with a similar gradient for CSS (p=0.001). Survival remained differentiation-associated within surgical (p=0.004) and chemotherapeutic subgroups (p<0.001). Median OS by stage was 96 mo for localized disease, 30 mo for regional nodes only, 8.5–7.5 mo for regional direct extension ± nodes, and 11 mo for distant disease. On multivariable analysis, stage and differentiation—driven primarily by poorly differentiated tumors—were independently associated with OS. Conclusions: Both tumor differentiation and stage independently predicted survival in LNEC, indicating that tumor biology and anatomic extent each contribute to prognosis. Outcomes remain suboptimal in poorly differentiated and advanced-stage LNEC, underscoring the need for treatment optimization and clinical trial development. Variable HR (95% CI) p Differentiation (Diff) Moderate vs Well 1.76 (0.49–6.31) 0.39 Poor vs Well 6.11 (1.63–22.93) 0.007 Undifferentiated vs Well 2.28 (0.60–8.76) 0.23 Stage Nodes only vs Localized 2.21 (1.14–4.38) 0.023 Direct extension only vs Localized 14.04 (2.44–80.97) 0.003 Direct + nodes vs Localized 7.49 (3.19–17.63) <0.001 Distant vs Localized 3.34 (1.63–6.83) 0.001 Male vs Female 2.28 (1.34–3.89) 0.002

1615 Background: Immune checkpoint inhibitors (ICIs) have revolutionized lung cancer treatment but cause adverse events, including immune-related colitis (ir-colitis). Accurate identification of ir-colitis is critical for improving patient outcomes and clinical research. However, current methods relying on ICD codes have substantial limitations: non-specific categories that fail to capture the cases or distinguish cases from infectious or ischemic etiologies, as well as incomplete coding that leads to missed cases. Large language models (LLMs), with advanced natural language understanding capabilities, offer a scalable approach for automated phenotyping using unstructured clinical notes. We aimed to develop and evaluate an LLM-based approach for identifying ir-colitis in patients with lung cancer receiving ICIs and compare it with ICD code based method. Methods: We identified 5,278 lung cancer patients with ICI administration at Mayo Clinic (2012-2025). To investigate ir-colitis occurrence within two years after ICI initiation, patients were stratified into three ICD-based cohorts: (1) IR-Colitis, with clinician-assigned ir-colitis-specific diagnosis codes; (2) Non-IR Colitis, with colitis diagnosis codes excluding ir-colitis; and (3) No-Colitis, absent of any colitis-related codes. We used three open-source LLMs to process clinical notes : Llama4, MedGemma, and Qwen. Prompts were designed to extract both gold standard evidence (explicit ir-colitis terminology, such as "immune-mediated colitis" and "checkpoint inhibitor colitis") and supportive evidence (such as pathology and lab results). Results: Llama4 demonstrated superior accuracy among three LLMs in manual evaluation and was thus selected for all cohort analyses. Among ICD-based IR-Colitis patients (n = 339), 82.0% had confirmatory evidence while 18% lacked evidence, suggesting potential false-positive coding. In the Non-IR Colitis cohort (n = 297), LLM-based extraction identified 43.8% patients in fact had ir-colitis, demonstrating substantial misclassification. In the No-colitis cohort (n = 4,642, random sample of 996 for analysis), the LLM identified 10.7% with documented ir-colitis, revealing substantial missing by administrative coding. Conclusions: LLM-based phenotyping demonstrates superior sensitivity for identifying ir-colitis compared to ICD codes alone, successfully uncovering cases missed by administrative coding. This scalable approach enables more comprehensive case identification for immunotherapy safety research and clinical surveillance. ICD-Based Cohorts LLM-Identified ir-Colitis Gold Standard Evidence Supportive Evidence Any Evidence ir-Colitis (n = 339) 277/339 (81.7%) 275/339 (81.1%) 278/339 (82.0%) Non-ir-Colitis (n = 297) 129/297 (43.4%) 126/297 (42.4%) 130/297 (43.8%) No Colitis (n = 996) 106/996 (10.6%) 104/996 (10.4%) 107/996 (10.7%)

Abstract Background: Immune checkpoint inhibitors (ICIs) have improved survival in non-small-cell lung cancer (NSCLC), yet only a subset of patients benefits, and biomarkers like PD-L1 remain limited. Here, we introduce a deep learning-based pathomics framework that utilizes routine H&E-stained slides to predict therapeutic response and survival outcomes in ICI-treated metastatic NSCLC. Methods: The study included 797 ICI-treated NSCLC patients from MD Anderson, with external validation in 280 patients from Mayo Clinic, Gustave Roussy, and the Phase III ICI-naïve LUSC Lung-MAP S1400I trial receiving nivolumab with or without ipilimumab. Path-IO (Pathology-Driven Immunotherapy Optimization) comprised of four major steps: (1) pathologist-verified tissue classifier segmented WSIs into eight compartments—Background, Bronchi, Immune, Lung, Necrosis, Stroma, Tumor, and Vessel—and was validated on TCGA and CPTAC dataset; (2) a survival prediction module generating patient-level risk scores in the MD Anderson cohort and validated across external datasets; (3) integration of Path-IO risk scores with radiomics and clinical features to improve prognostic accuracy; and (4) biological interpretability analyses correlating Path-IO risk immune contexture from multiplex immunofluorescence and transcriptomic signatures from NanoString profiling. Results: Path-IO effectively stratified patients into high and low-risk groups with significant survival differences. In the MD Anderson cohort, it achieved HR = 2.11 (p &lt; 0.001) and HR = 2.51 (p &lt; 0.001) for OS in the discovery and validation sets, and HR = 2.34 (p &lt; 0.001) and HR = 1.87 (p &lt; 0.001) for PFS, respectively. In the multicenter Phase III Lung-MAP S1400I trial, Path-IO achieved HR = 1.78 (p = 0.016) for OS and HR = 2.76 (p = 0.006) for PFS. In external validation, it predicted outcomes in the Gustave Roussy (OS = 1.97, p = 0.003; PFS = 1.51, p = 0.046) and Mayo Clinic (OS = 2.46, p = 0.007; PFS = 2.45, p = 0.027) cohorts. Path-IO outperformed PD-L1 and remained an independent predictor in multivariate analysis (p &lt; 0.001). It enabled data-driven frontline selection between anti-PD-1 monotherapy and chemo-immunotherapy, offering guidance toward more personalized treatment decisions. Integration with radiomics and clinical features further improved predictive accuracy (OS 0.63→0.75; PFS C-index 0.58→0.70), while high Path-IO risk scores correlated with immune-cold phenotypes identified by multiplex immunofluorescence and NanoString transcriptomics. Conclusions: Path-IO demonstrates that deep learning models rooted in histopathologic architecture can generate interpretable and biologically informed survival predictions in NSCLC treated with ICIs. By integrating pathology, radiology, and clinical data, Path-IO provides complementary predictive value beyond established biomarkers such as PD-L1. Citation Format: Rukhmini Bandyopadhyay, Linghzi Hong, Mihaela Aldea, Shenduo Li, Lodovica Zullo, Frank R. Rojas, Maliazurina B. Saad, Maricel C. Marin, Muhammad Waqas, Jiexin Zhang, Eman Showkatian, Claudio A. Arrechedera, Xiaoyu Han, Yuliya Kitsel, Sherif Ismail, Muhammad Aminu, Bo Zhu, Carol C. Wu, Brett W. Carter, Joe Y Chang, Zhongxing Liao, Maria R. Ghigna, Davide Soldato, Hai T. Tran, Xiuning Le, Tina Cascone, Bingnan Zhang, Haniel A. Araujo, Mehmet Altan, Simon Heeke, David Jaffray, Don L. Gibbons, Ara Vaporciyan, J Jack Lee, Neda Kalhor, Cara Haymaker, Ignacio Wistuba, John V. Heymach, Yanyan Lou, Natalie Vokes, Luisa M. Solis Soto, Jianjun Zhang, Jia Wu. Path-IO: A deep learning pathomics framework for personalized immunotherapy selection and outcome prediction in metastatic non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4003.

Background: In the last decade, a surge of advancements in and approvals of immunotherapies has revolutionized the treatment of non-small-cell lung cancer (NSCLC). Even as an increasing number of immune checkpoint inhibitors and antibody–drug conjugates gained FDA approval for the remarkable response and durable remission they imparted to some patients, persistent challenges of primary and acquired resistance, imperfect predictive biomarkers, and toxicity remain. Methods: This review identifies and summarizes the most significant emerging clinical data being reported for immunotherapies in NSCLC. Results: We found that the most recent clinical trials are centered on antibody–drug conjugates, bispecific and multispecific antibodies, cellular therapies, and immunocytokines, while other ongoing trials continue to explore new monoclonal antibodies as well as a variety of immunotherapy modalities. Conclusions: Immunotherapy in NSCLC remains an area of rapid advancement, with the potential for further improvements in safety and efficacy as monotherapy and in multimodal approaches.

Localized cutaneous squamous cell carcinoma (cSCC) has a favorable prognosis, unlike advanced disease, especially with clinical perineural invasion (PNI), which poses substantial management challenges due to aggressivity and higher recurrence, metastasis, and mortality risks. PNI, a high-risk staging feature, has worse outcomes, particularly when clinically evident rather than incidental. Clinical PNI (cPNI) is evident by clinical symptoms (such as pain, paresthesia, or motor deficits) or radiologic findings, whereas incidental PNI (iPNI) is identified only histologically without associated symptoms or radiologic evidence. PNI remains a novel area with varying practice patterns across institutions. Improving risk stratification and tailoring multidisciplinary approaches are critical for optimizing outcomes. Our review outlines clinical practice patterns at our institution, providing insights into managing cSCC with PNI, focusing on diagnosis, imaging, staging, and emerging immunotherapies. A structured search was conducted using the terms “perineural invasion,” “cutaneous squamous cell carcinoma,” and “immunotherapy.” cPNI has a poor prognosis and requires nuanced clinical decision-making. Surgery and radiation remain central to management. Adjuvant therapy offers substantial survival benefit in cSCC with PNI, with improved disease-free and overall survival compared with surgery alone, supporting its use in appropriately selected high-risk patients. Traditional systemic therapies, including cisplatin and cetuximab, remain foundational but have shown only moderate response rates and limited durability in advanced or neurotropic cSCC. In contrast, immunotherapy—now preferred for advanced or unresectable cases—has transformed management, with programmed cell death protein-1 (PD-1) inhibitors showing promising results (up to 69% response rate) and disease stabilization. Neoadjuvant immunotherapy may enable tumor downstaging, improve radiation planning, and reduce surgical morbidity. Imaging for squamous cell carcinoma (SCC) with PNI aids staging and surveillance, but symptoms remain key for detecting recurrence. Our multidisciplinary approach emphasizes personalized care. Larger trials are needed to define the optimal role and sequencing of immunotherapy in this high-risk patient population.

ABSTRACT Background As head and neck cancer survival rates improve, there is growing demand for quality survivorship care and tools to predict patient adherence; this study aims to evaluate an advanced practice provider ( APP )‐led survivorship clinic and assess these key metrics. Methods We performed a retrospective review of 213 head and neck cancer patients treated with curative radiation therapy between 2016 and 2023, to assess follow‐up adherence in an advanced practice provider–led survivorship clinic. Results With a median follow‐up of 2.4 years, follow‐up care metrics identified high completion percentages (> 90%) for lung cancer screening, smoking cessation, thyroid screening, dental evaluation, xerostomia, dysphagia, and dysgeusia. The HOUsing ‐based SocioEconomic Status ( HOUSES ) index at diagnosis showed a significant adherence difference (median percentile, 78% vs. 55%, adherent vs. nonadherent; p = 0.03). Conclusions High adherence rates with guideline‐defined care metrics are achievable in an advanced practice provider‐led head and neck cancer survivorship clinic. The HOUSES index may assist in predicting nonadherence; however, further studies are needed.

e16610 Background: Adrenocortical carcinoma (ACC) is a rare malignancy with an incidence of 1-2 per million per year. The optimal treatment remains unclear as does the benefit of chemotherapy (chemo) in patients (pts) with resectable ACC. Methods: The SEER database (2000–2021) was used to identify ACC pts > 18 years. Variables of interest included age, race, household income, rural-urban classification, stage, chemo, radiation therapy (RT), and surgery. Statistical analyses were conducted using ANOVA, Kruskal-Wallis, and Kaplan-Meier methods to compare survival outcomes according to variables of interest. Results: Of the 2,598 pts identified, 1,564 (60%) were female. The majority of pts (85%) were white, followed by black (9%). Most pts (87%) resided in metropolitan areas. Pts with localized, regional, or distant metastatic disease comprised 25%, 17% and 36% of the group, respectively. 40% of pts underwent radical or total surgical removal of the primary site disease while 9%, 2%, and 1% underwent partial surgical removal, excision, or debulking surgery, respectively, and 30% did not undergo surgery. 34% of pts received chemo and 8% received RT. The median overall survival (mOS) for the entire cohort was 15 months (m) (95% CI: 14–17 m). No significant differences in OS were observed among pts of different races or household incomes. Distant metastatic disease was significantly associated with worse mortality when compared with regional or localized diseases (mOS: 5 m vs. 20 m vs 60.6 m, respectively, p < 0.001). Surgical intervention of any kind was associated with longer survival when compared to those who did not undergo surgery (18 m vs. 3 m, HR 0.33, p < 0.0001). Among the 971 pts with distant metastatic disease, pts who received chemo had a superior mOS compared to those who did not receive chemo or with unknown chemo status (8 m vs. 2 m, p < 0.0001). This OS advantage remained significant even after excluding pts who underwent surgery (5 m vs. 2 m, p < 0.0001). While chemo was also associated with longer mOS (29 m vs. 27 m, p < 0.0001) in localized disease, this survival advantage was not present in pts with localized disease managed with surgery (27 m vs. 27 m, p = 0.061). Although chemo was associated with numerically longer mOS in pts with regional disease, the difference was not significant. Conclusions: ACC with distant metastatic disease carries a poor prognosis yet demonstrates superior survival in pts who receive chemo. Surgery is associated with better survival outcomes, but there is no additive benefit from chemo in those with localized disease managed with surgical resection.

e20141 Background: TET are rare and challenging entities in clinical practice. Prospective trials in thymoma and thymic carcinoma (TC) are scarce. Limited number of small trials investigated the role of ICI in TET, and showed some clinical efficacy, but also with immune related adverse events (irAE). Guidelines list ICI as a treatment option in the 2 nd line, although no FDA approval was granted. Aside from the small trials, there is limited real world data about the efficacy and toxicity of ICI in TET. Methods: We performed a retrospective chart review of the medical records of all patients (pts) with TET who were treated with ICI between 3/25/2011 and 11/30/2024 at 5 Mayo Clinic sites. We collected data about baseline characteristics, diagnosis, irAE, and outcomes. Kaplan-Meier method was used to calculate median progression free survival (mPFS), and hazard ratio (HR) with Cox proportional hazards regression. Results: 30 pts were included, 28 diagnosed with TC, and 2 with malignant thymoma. 70% of pts were male. Median age at time of diagnosis was 61 years (range: 15 to 82), and median ECOG at the time of diagnosis was 0. 29 pts received Pembrolizumab, and one received Durvalumab. Prior to ICI, 86.67% of patients received chemotherapy. 70% of pts discontinued ICI use, 60% due to progression, and 10% due to irAE. Overall response rate (ORR) was 23.33%, with 3.33% complete response, and 20% partial response. Disease control rate (DCR) was 63.33%. The mPFS was 10.13 months. At the time of analysis 60% of pts were still alive. 40% of patients had irAE. While the two patients with thymoma experienced irAE, only 33.33% of those with TC had these events. 26.67% of pts had thyroiditis. Pancreatitis, pneumonitis, dermatitis, and encephalitis each occurred in 3.33% of pts. The median time to irAE onset was 75 days. 25% of irAE were grade 1, 66.67% grade 2, 0% grade 3, and 8.33% grade 4, represented by the case of encephalitis. Resolution of irAE occurred in 33.33% of cases. When stratified according to the occurrence of irAE, the mPFS was the same in both groups, with or without irAE, being 10.13 months, HR=0.99 (95% CI 0.39 – 2.54). Conclusions: In this real-world cohort of pts with TET, efficacy of ICI matched what has been previously reported, with similar ORR and DCR, but with longer mPFS. However, irAE incidence was higher, but with less grade 3/4 events. Differently than what has been suggested in other diseases, irAE occurrence did not correlate with better outcomes. These results validate the role of ICI in the treatment of TET, especially TC. Nonetheless, improving patient selection, and developing other therapeutic strategies, including combinations of ICI and other drugs, for these malignancies remain essential. Importantly, the high incidence of irAE indicates that future investigations must also focus on safety of interventions and supportive care in TET.

Lung cancer remains the leading cause of cancer-related mortality worldwide. Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer, with nearly half of all patients diagnosed at an advanced stage. Immune checkpoint inhibitors (ICIs) harness the host immune system to combat malignant cells. ICIs, which target programmed death-ligand 1 (PD-L1), programmed cell death 1 (PD-1), and cytotoxic T-cell lymphocyte-4 (CTLA-4), have transformed the treatment landscape for advanced NSCLC. While a subset of patients experiences a long-term durable response, most patients will develop disease progression. New drugs targeting novel pathways are being tested in clinical trials to improve the efficacy of immunotherapy and overcome resistance patterns. This review aims to summarize the currently available ICIs for advanced NSCLC and describe emerging immunotherapies with recently published data from phase I/II clinical trials.

The emergence of immunotherapy has ushered in a new era in the management of non-small cell lung cancer (NSCLC). Various immune check point inhibitors have demonstrated significant benefit in the management of locally advanced NSCLC that are treated with either surgery or concurrent chemoradiation. We provide a comprehensive and up-to-date review of data from key studies, discuss the challenging clinical issue regarding the timing and duration of immunotherapy in patients undergoing surgery, and highlight the unmet needs and future directions of immunotherapy in NSCLC.