Citations

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.

Background and Aims: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). Approach and Results: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP, rs9842969, (0.51, [0.40–0.65]); 5p15.33, TERT, rs2242652, (0.70, (0.62–0.79]); 19q13.11, TM6SF2, rs58542926, (1.49, [1.29–1.72]); 19p13.11 MAU2, rs58489806, (1.53, (1.33–1.75]); and 22q13.31, PNPLA3, rs738409, (1.66, [1.51–1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74–0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. Conclusions: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

AbstractBackgroundPatients with sinonasal malignancy (SNM) present with significant sinonasal quality of life (QOL) impairment. Global sinonasal QOL as measured by the 22‐item Sinonasal Outcomes Test (SNOT‐22) has been shown to improve with treatment. This study aims to characterize SNOT‐22 subdomain outcomes in SNM.MethodsPatients diagnosed with SNM were prospectively enrolled in a multi‐center patient registry. SNOT‐22 scores were collected at the time of diagnosis and through the post‐treatment period for up to 5 years. Multivariable regression analysis was used to identify drivers of variation in SNOT‐22 subdomains.ResultsNote that 234 patients were reviewed, with a mean follow‐up of 22 months (3 months–64 months). Rhinologic, psychological, and sleep subdomains significantly improved versus baseline (all p < 0.05). Subanalysis of 40 patients with follow‐up at all timepoints showed statistically significant improvement in rhinologic, extra‐nasal, psychological, and sleep subdomains, with minimal clinically important difference met between 2 and 5 years in sleep and psychological subdomains. Adjuvant chemoradiation was associated with worse outcomes in rhinologic (adjusted odds ratio (5.22 [1.69–8.66])), extra‐nasal (2.21 [0.22–4.17]) and ear/facial (5.53 [2.10–8.91]) subdomains. Pterygopalatine fossa involvement was associated with worse outcomes in rhinologic (3.22 [0.54–5.93]) and ear/facial (2.97 [0.32–5.65]) subdomains. Positive margins (5.74 [2.17–9.29]) and surgical approach—combined versus endoscopic (3.41 [0.78–6.05])—were associated with worse psychological outcomes. Adjuvant radiation (2.28 [0.18–4.40]) was associated with worse sleep outcomes.ConclusionsSinonasal QOL improvements associated with treatment of SNM are driven by rhinologic, extra‐nasal, psychological, and sleep subdomains.

AbstractBackgroundPatient‐reported outcome measures (PROMs) are gaining favor in clinical and research settings given their ability to capture a patient's symptom burden, functional status, and quality of life. Our objective in this systematic review was to summarize studies including PROMs assessed among older adults (age ≥ 65 years) after seeking emergency care.MethodsWith the assistance of a medical librarian, we searched Ovid MEDLINE, PubMed, Embase, CINAHL, Web of Science‐Core Collection, and Cochrane CENTRAL from inception through June 2023 for studies in which older adult ED patients had PROMs assessed in the post–emergency care time period. Independent reviewers performed title/abstract review, full‐text screening, data extraction, study characteristic summarization, and risk‐of‐bias (RoB) assessments.ResultsOur search strategy yielded 5153 studies of which 56 met study inclusion criteria. Within included studies, 304 unique PROM assessments were performed at varying time points after the ED visit, including 61 unique PROMs. The most commonly measured domain was physical function, assessed within the majority of studies (47/56; 84%), with measures including PROMs such as Katz activities of daily living (ADLs), instrumental ADLs, and the Barthel Index. PROMs were most frequently assessed at 1–3 months after an ED visit (113/304; 37%), greater than 6 months (91/304; 30%), and 4–6 months (88/304; 29%), with very few PROMs assessed within 1 month of the ED visit (12/304; 4%). Of the 16 interventional studies, two were determined to have a low RoB, four had moderate RoB, nine had high RoB, and one had insufficient information. Of the 40 observational studies, 10 were determined to be of good quality, 20 of moderate quality, and 10 of poor quality.ConclusionsPROM assessments among older adults following an ED visit frequently measured physical function, with very few assessments occurring within the first 1 month after an ED visit.

Background: To compare conventional smears (CSs) and liquid-based preparations (LBPs) for diagnosing thyroid malignant or suspicious lesions. Methods: Studies in the PubMed, SCOPUS, Embase, Web of Science, and Cochrane database published up to December 2023. We reviewed 17 studies, including 15,861 samples. Results: The diagnostic odds ratio (DOR) for CS was 23.6674. The area under the summary receiver operating characteristic curve (AUC) was 0.879, with sensitivity, specificity, negative predictive value, and positive predictive value of 0.8266, 0.8668, 0.8969, and 0.7841, respectively. The rate of inadequate specimens was 0.1280. For LBP, the DOR was 25.3587, with an AUC of 0.865. The sensitivity, specificity, negative predictive value, and positive predictive value were 0.8190, 0.8833, 0.8515, and 0.8562. The rate of inadequate specimens was 0.1729. For CS plus LBP, the AUC was 0.813, with a lower DOR of 9.4557 compared to individual methods. Diagnostic accuracy did not significantly differ among CS, LBP, and CS plus LBP. Subgroup analysis was used to compare ThinPrep and SurePath. The DORs were 29.1494 and 19.7734. SurePath had a significantly higher AUC. Conclusions: There was no significant difference in diagnostic accuracy or proportion of inadequate smears between CS and LBP. SurePath demonstrated higher diagnostic accuracy than ThinPrep. Recommendations for fine-needle aspiration cytology should consider cost, feasibility, and accuracy.

686 Background: Immune checkpoint inhibitors (ICI) have been used to treat advanced muscle invasive and/or metastatic bladder cancer. However, ICIs are only effective in 30-40% of cases. In light of potentially significant IRAE’s, tools to predict individual patient level benefits are desirable. AI technology offers the opportunity to apply computational methods to predict outcomes from readily available digitized pathology slides. We investigated the utility of an AI platform integrating computational biomarkers based on morphological characterization of digitized H&E slide whole images (WSI) to predict response to ICI. Methods: We analyzed H&E-stained whole slide images (WSI) of bladder tumor tissue collected from transurethral resection of bladder tumor (TURBT) from 116 patients with advanced or metastatic bladder cancer at a single institution between 2015-2020. Adjacent multiplex IHC stained specimens were analyzed myeloid and lymphoid marker panels. 20 patients from the overall cohort treated with ICI were designated ‘responders’ (complete response, partial response, stable disease) and 20 patients were identified as non-responders (progressive disease) based on ICI best clinical/radiographic response. WSIs were divided into small non-overlapping image patches. These image tiles were processed into multiple AI encoder models to extract morphological features. The tile morphological features, represented by high dimensional vectors, were combined by an aggregation model to represent the whole slide morphology and then used to classify the patients into responders vs non-responders to immunotherapy. Area-under-the-receiver operating characteristic (AUC) was used to measure the performance of response prediction. Results: Our method shows AUC of 0.708 at classification of the patients (n=40) into responder and non-responder groups. With a cutoff that identifies the top 50% patients (n=20) of high probability of responding to immunotherapy predicted by our models, 75% of them are responders. In the bottom 50% patients (n=20) of the low scores, 75% of them are non-responders. . Multiplex IHC (myeloid and lymphoid panel) was performed using adjacent sections and were characterized yielding deeper mechanistic insight into the inflammatory populations driving predictive morphologic patterns. Conclusions: By applying innovative AI morphological analysis on patient WSIs, we generated a computational biomarker that shows promising ability to predict patient response to immunotherapy in bladder cancer. This approach merits future prospective validation and additional patient level analysis in broader cohorts. [Table: see text]

216 Background: PCa harbors recurrent FOXA1 alterations, yet distinct alteration types may drive divergent consequences. Here, we established several classes of FOXA1 alterations and evaluated their clinical outcomes, molecular correlates, and immunologic landscape in a large cohort of primary and metastatic PCa samples from Caris Life Sciences. Methods: We interrogated the Caris DNA (592-gene/whole exome) and RNA (whole transcriptome) NGS databases. FOXA1 alterations were annotated based on amino acid (a.a.) location and prior functional studies (Table). Real-world overall survival (OS) was determined from insurance claims data using Kaplan-Meier estimates. Gene set enrichment analyses (GSEA) was used to estimate signaling pathway activity. Immune-cell fractions were inferred from bulk RNA-seq using quanTIseq. All comparisons are made relative to FOXA1 WT cases. Results: The overall prevalence of FOXA1 alterations was 16%, with no enrichment in metastatic PCa samples (15.5%). Class 2 mutations were enriched in histologic NEPC, were associated with a classical NEPC mRNA signature, and showed poor survival with ADT (HR 5.6, 95% CI: 2.5–12.5, p<0.001). Conversely, metastatic PCa patients with Class 1B mutations had numerically improved survival with ADT (HR 0.76, 95% CI: 0.50–1.14, p=0.18). All FOXA1 alterations (except Class 2) resulted in increased FOXA1 transcripts, with 1B and 1C having the greatest effects (q<0.0001). Class 0 and 3 alterations had 2–5 fold higher frequency of TMB-high and MSI-high status (q<0.05). Conversely, Class 1B exhibited lower TMB and markedly fewer TP53 mutations (35.7% vs 20.3%, q<0.001) and TMPRSS2-ERG fusions (34.5% vs 4.6%, q<0.001). Class 1B was depleted of AR transcriptional signatures (q=0.01) but enriched of MYC signaling in GSEA analysis (FDR<0.001), and showed reduced expression of B7-H3. On immune-cell deconvolution analysis, Class 1B showed reduced dendritic cells, but increased B cells and neutrophils (DC: 1.96% vs 0.01%, B cell: 4.27% vs 5.29%, neutrophils: 5.05% vs 8.00%, each q<0.001). Conclusions: Different FOXA1 alterations exhibit divergent molecular and clinical features, and should not be interpreted in aggregate. In particular, Class 1B mutations are associated with a unique molecular and immunological landscape with potentially better outcomes to ADT, while Class 2 mutations are associated with NEPC phenotype with inferior ADT sensitivity. [Table: see text]

Abstract Immune checkpoint inhibitors (ICIs) have demonstrated remarkable response rates in relapsed or refractory Hodgkin lymphoma (HL). Still, most patients eventually progress. Patterns of progression after ICIs are not well described and are essential to defining the role of local therapies in combination with ICIs. We identified patients who received ICIs for HL between 2013 and 2022. Fludeoxyglucose-18 positron emission tomography (FDG-PET) before initiating ICI and at progression on/after ICI were reviewed, and areas of active HL were recorded. An exploratory analysis of treatable progression included patients with ≤5 sites of disease on pre-ICI FDG-PET and progression only at pre-ICI sites. Ninety patients were identified; 69 had complete records, and of these, 32 (52%) had relapsed at ICI initiation, 17 (25%) were refractory, and 16 (23%) received ICI as first-line therapy. Forty-five of 69 patients had ≤5 sites of disease (limited) on pre-ICI FDG-PET. Patients with &gt;5 sites of disease had a higher risk of progression, and every site of disease &gt;5 sites conferred an additional 1.2x higher chance of progression. At a median follow-up of 4.0 years, 41 of 69 patients had progressed on/after ICIs (cumulative incidence 66.4%), and of these, 22 of 41 patients progressed only at pre-ICI sites (cumulative incidence 39.4%). In an exploratory analysis, the cumulative incidence of a treatable progression among 45 patients with limited disease was 34%. The cumulative incidence of any progression among this cohort was 58.9%. More than one-third of patients with limited disease before ICIs experienced progression only at pre-ICI sites of disease. These patients could be candidates for radiation during or after ICIs.