Stoddard, Shawn M.

Image-derived artificial intelligence (AI) risk models have shown promise in short-term risk assessment for improving breast cancer (BC) screening. No image-derived long-term AI risk model for primary prevention has been developed and externally validated. Individuals aged 31 to 94 years were recruited between 2010 and 2020 in two population-based case cohorts (Olmsted County, Minnesota, US, and KARMA, Sweden) and one hospital-based case-control study (EMBED, Atlanta, US). Median follow-up in the case cohorts was 10 years, with BCs diagnosed through June 2022. Additional validation was performed in EMBED with 3-year follow-up. An AI risk model was developed in Sweden, and we report independent validation in Olmsted/KARMA/EMBED. Absolute 10-year risks were estimated at study entry. Time-dependent discriminatory performance [AUC( t )] and expected-to-observed events (E/O) were estimated. Comparisons were performed with clinical risk tools and the image-based Mirai tool. Across Olmsted/KARMA, 8696 individuals (mean age, 54.4±10.6) and 1633 individuals with incident BC (mean age, 57.0±10.6) were included. Average 10-year risks were 3.83 and 3.14%, and E/O ratios were 0.99 and 0.99. Ten-year AUC( t ) for invasive BCs were 0.72 in Olmsted and 0.72 in KARMA. Similar discriminatory results were observed in EMBED. Our AI risk tool performed significantly better than Mirai in Olmsted/KARMA/EMBED. In KARMA, in the top 10% of high-risk individuals, the AI risk tool predicted 33% of BCs compared with 23%/20%/24% predicted by Tyrer-Cuzick-v8/BCSC-v3/Mirai (all P < 0.01). The 10-year image-derived AI risk model showed significantly higher performance than clinical risk models and Mirai in diverse populations, supporting its clinical potential for primary prevention.

Abstract Background: Epidemiologic studies commonly obtain important exposure and outcome information from patient self-report although these may be influenced by imperfect understanding and/or faulty recall. The Voyage Study is a large-scale, prospective cohort study of long-term health outcomes among participants with a valid multi-target stool DNA (mt-sDNA) test order (N=150, 047). The purpose of this analysis was to evaluate the validity of participant reported mt-sDNA tests, colorectal cancer (CRC), and/or aerodigestive cancers (ADC, including cancers of the head, neck, oral, esophageal, lung, liver, stomach, pancreas, anus) among respondents. Methods: Participants from across the Unites States enrolled in the study completing questionnaires at enrollment and 1 year. The year 1 questionnaire collected data on completion and outcome of their mt-sDNA test, follow up colonoscopies and other procedures as well as a diagnosis of CRC or ADC. The study team contacts those who reported either CRC or ADC for permission to obtain copies of medical records. Records are then reviewed by a trained nurse abstractor and evaluated for validity. Mt-sDNA test results were available from Exact Sciences. Results: At the time of this analysis, year 1 questionnaire data were available on 135, 035 participants. Abnormal mt-sDNA results (n=12, 928) were self-reported by 13, 420 participants with 96.3% accuracy. Of the 111, 556 self-reported normal results, 93.4% (n=104, 150) were reported correctly. The validation process for the Voyage Study is ongoing with 860 self-reported CRC and 318 self-reported aerodigestive cancer diagnoses to date. Complete data are available on 155 individuals with a self-report of a new CRC diagnosis and 63 individuals with a self-report of aerodigestive cancer. Abstraction confirmed 47% (n=73) of those reported as true CRC diagnoses. Participants were better at correctly reporting at least one aerodigestive cancer (73%, n=46). Discussion and Conclusions: Patient reported medical record validation poses a unique challenge in today’s world. The process of requesting participant authorization followed by institutional requests to release the medical records to the research team is slow and painstaking. We found that patients are able to correctly report their mt-sDNA tests but found a relatively low proportion of reported cancer diagnoses reported correctly. This underscores the need to continue to validate key outcomes rather than relying solely on participant responses. As the number of outcomes validated increases, the study team will look at a variety of social and economic factors to better understand what contributes to or hinders an accurate self-report. Citation Format: Emily J. Kirsch, Jessica A. Grimm, Shawn M. Stoddard, Winnie Z. Fan, Kandace A. Bohn, Kathleen J. Yost, Lila J. Finney Rutten, Janet E. Olson. Patient reported outcome validation within the Voyage Study cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7354.

Abstract Mutations in the EGFR gene or transcript fusion involving EML4-ALK result in oncogenic activation of these oncogenes driving lung adenocarcinoma growth in tumors carrying such an alteration. For lung adenocarcinoma with these genetic changes, small-molecule tyrosine kinase inhibitors have been highly effective at reducing tumor burden and improve the outcome of the patients. Unfortunately, drug resistance eventually develops in these tumors and challenges remain in controlling lung cancer recurrence after targeted therapy. To overcome recurrence, we initiated a prove-of-principle study to evaluate the feasibility of an integrated strategy utilizing genomic profiles of the tumor and patient-specific tumor xenografts derived (PDX) from biopsies for ex vivo evaluation of antitumor drugs to help guide personalized treatment of lung cancer in patients who have developed resistance to targeted therapy drugs. Our study has three main objectives. 1) Use tumor biopsies obtained at the time of recurrence for oncogene mutation and RNAseq analyses to identify molecular changes in oncogenes and gene pathways that can be potentially targeted. 2) Evaluate drug efficacy and optimize personalized therapy for each patient using PDX models. 3) Assess clinical feasibility and our experience using integrated approaches for lung cancer patients who failed targeted therapy. This study was approved by the Mayo Clinic Institutional Review Board (IRB) and utilizes both clinical and research biopsies. A dedicated nurse study coordinator reviews clinical patient list and history on weekly basis and informs the study team of each potential candidate patient. A total of 30 patients having ALK positive lung cancers have been identified and followed up from nearly 500 potentially ALK positive cases between April 2014 to Sept. 2015. Most patients were never smokers but six were former smokers and two were current smokers. Age at diagnoses ranged from 27-78 years (median = 61). Seven patients (23%) were 45 years or younger at the time of diagnosis. A total of 22 patients are currently being treated with crizotinib while eight are on ceritinib or alectinib. For each biopsy, tumor tissues are obtained using a 20 gauge needle, transferred on ice in preserving media and implanted within one hour into 6-8 week old NOD/SCID mice. Many patients have been on treatment for 2-3 years with stable disease so they do not require biopsy. Using a similar strategy, we also obtained biopsies from patients with EGFR gene mutations in their tumors and have progressed while on targeted therapy. A total of seven cases have been implanted. We will report our experiences in patient selection, clinical follow up, patient consent, PDX development, time from biopsy to tumor establishment, and the results of molecular analyses. Our study enabled us to gain new insights regarding the molecular changes associated with recurring tumors after they have failed targeted therapy as well as clinical experiences on how to utilize state-of-the art approaches and comprehensive genomic information to further improve cancer patient care upon disease progression. Acknowledgements: This work is supported in part by the Hillsberg Award from the National Foundation for Cancer Research and by the Biomarker Discovery Program at the Mayo Clinic Center for Individualized Medicine. Citation Format: Jin Jen, Aaron Mansfield, Patrick W. Eiken, Shawn Stoddard, Karlyn Pierson, Xiaonan Hou, Hong Zheng Ren, Julian Molina, Joanne Yi, Ping Yang. Integrated Approaches to Treating Lung Adenocarcinoma Resistant to Targeted Therapy. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr B34.

54 Background: After diagnosis and treatment, lung cancer survivors do not return to a health-related quality of life (QOL) and function comparable to pre-diagnosis levels as observed in other adult cancer survivors. We hypothesize that inadequate attention has been paid to addressing and improving QOL and function among lung cancer survivors. Our primary goal is to evaluate existing symptoms and QOL deficits among lung cancer survivors. Methods: We are evaluating patterns of QOL deficits (scored 5 or less on the scale from 0 [worst] to 10 [best]) in relation to time of lung cancer diagnosis, treatments, progression and/or recurrence, and health-related conditions. We are collecting and analyzing relevant health care utilization for selected QOL deficits, and identifying availability, accessibility, and effectiveness of evidence-based interventions. The expected outcomes will be new knowledge on patterns of QOL deficits, quality-adjusted life years in relation to the availability, accessibility, and adequacy of needed care and the effectiveness of interventions targeting improvement in QOL and symptoms. Results: In our initial analysis, among 3,707 lung cancer survivors who were diagnosed in 1999 to 2010, post-cancer treatment, and followed through 2011, 39% (1,442) reported deficits in overall QOL, 71% fatigue, 60% dyspnea, 41% being sedentary, 17% low spiritual well-being (SWB), and 10% currently smoking cigarettes. Among the 1,442 lung cancer survivors with a deficit in overall QOL, 97.5% reported severe fatigue or dyspnea, being sedentary or smoking, or having low SWB. In the remaining 36 of the 1,442, 24 had pain, cough, poor appetite, or other symptoms; only 12 (<1%) did not report deficit in any of the measured QOL domains. Analyses are ongoing. Conclusions: Based on evidence gained to date, we are developing and testing interventions targeting symptoms and QOL deficits. We expect to gain strong evidence for recommendations in redefining and delivering care and support that are necessary for improving the health and QOL of lung cancer survivors.

Abstract Lung adenocarcinoma is the most common type of primary lung cancer. Previous studies have shown that gene expression signatures may predict clinical outcome. In this study, we used a systems biology approach, weighted gene co-expression network analysis (WGCNA), to identify survival related networks and gene signatures. We first analyzed whole genome gene expression profiles in 82 lung adenocarcinoma tumor tissues from never smokers (smoked &lt;100 cigarettes lifetime) and found a significant correlation of an expression module with tumor grade of differentiation (r=0.38, p=4×10−4) and overall survival (OS, p =0.027, HR, 1.71; 95% CI, 1.06-2.74) after adjusting for potential confounders (age and tumor grade). When this module signature was incorporated and compared to the conventional model consisting of clinical variables only, the survival prediction accuracy was increased from 0.70 to 0.75. Gene Ontology (GO) enrichment analysis indicated this module was significantly enriched in biological process GO term “cell cycle” (p = 2.1×10−53). To explore the effect of this network module at germline level, we performed the WGCNA on normal lung tissues derived from 78 of the 82 patients and observed significant association of an expression module with OS (adjusted p=3×10−4, HR=1.98; 95% CI, 1.36-2.87). Interestingly, this module was also significantly enriched in cell cycle-related genes (p=4.1×10−41). To further validate this result, we analyzed an independent microarray gene expression dataset including 442 lung adenocarcinoma patients from NCI Director's Challenge Consortium. We found the same association: the cell cycle-enriched module was correlated with tumor grade of cell differentiation (r=0.55, p-value=5×10−37) and OS (adjusted p=7.4×10−3; HR, 1.20; 95% CI, 1.05-1.37). We further identified 30 genes in the OS-related module that overlapped between the discovery and validation data sets. Furthermore, all these 30 genes were found to be up-regulated in adenocarcinoma compared to adjacent normal lung tissues in the discovery data set. Of the 30 genes, three key genes, UBE2C, TPX2 and MELK, were identified with highest connectivity in cell cycle-enriched module; their expression levels were significantly associated with OS in both discovery and validation sets. UBE2C and TPX2 have been reported as gene signatures for human lung cancer prognosis in vitro lung carcinogenesis system; MELK was identified as a key regulator of the proliferation of malignant brain tumors and malignant grade in human astrocytomas, and was also associated with breast cancer prognosis. Our results suggest that genes involved in cell-cycle are likely related with tumor aggressiveness and therefore can predict survival in lung adenocarcinoma. Further studies are needed to validate the key genes that could improve survival prediction and provide potential new targets to intervene progression of lung adenocarcinoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5060. doi:10.1158/1538-7445.AM2011-5060

Abstract The contribution of emphysema to lung cancer risk has been recognized, but the effect size needs to be further defined. In this study, 565 primary lung cancer cases were enrolled though a prospective lung cancer cohort at Mayo Clinic, and 450 controls were smokers participating in a lung cancer screening study in the same institution using spiral computed tomography (CT). Cases and controls were frequency matched on age, gender, race, smoking status, and residential region. CT imaging using standard protocol at the time of lung cancer diagnosis (case) or during the study (control) was assessed for emphysema by visual scoring CT analysis as a percentage of lung tissue destroyed. The clinical definition of emphysema was the diagnosis recorded in the medical documentation. Using multiple logistic regression models, emphysema (≥5% on CT) was found to be associated with a 3.8-fold increased lung cancer risk in Caucasians, with higher risk in subgroups of younger (&lt;65 years old, OR = 4.64), heavy smokers (≥40 pack-years, OR = 4.46), and small-cell lung cancer (OR = 5.62). When using &gt;0% or ≥10% emphysema on CT, lung cancer risk was 2.79-fold or 3.33-fold higher than controls. Compared with CT evaluation (using criterion ≥5%), the sensitivity, specificity, positive and negative predictive values, and the accuracy of the clinical diagnosis for emphysema in controls were 19%, 98%, 73%, 84%, and 83%, respectively. These results imply that an accurate evaluation of emphysema could help reliably identify individuals at greater risk of lung cancer among smokers. Cancer Prev Res; 4(1); 43–50. ©2010 AACR.