Citations

1037 Background: TBCRC041, a randomized phase 2 trial of alisertib (A) ± fulvestrant (F) in women with HR+/HER2- MBC demonstrated promising clinical activity for alisertib (1). Interrogation of baseline (PreC1) and end of cycle 1 (EOC1) cfDNA and CTCs may identify biomarkers associated with response to A±F. Methods: Plasma cfDNA was sequenced using the Guardant INFINITY platform, which includes genomic and methylated tumor fraction (mTF) analysis. Pathogenic variants were determined using publicly available databases and Mayo Clinic annotation pipelines. CTCs were identified as nucleated, EpCAM+/ cytokeratin+/ CD45- cells and assessed for ER/HER2 staining (RareCyte, Seattle). PFS was defined as the time from randomization to progression or death. EOC1-PFS differs from PFS as time starts at C2D1. Stratified log-rank tests and conditional Cox modeling were used to assess whether PFS or EOC1-PFS differed by mutations in ESR1 or PIK3CA, pre-CTC ≥ 5, or mTF>1%. Results: Of the 91 eligible pts, 84 progressed, and 73 were deceased. In the 86 pts with PreC1-cfDNA results, variants were identified in ESR1 (42; 48.8%), PIK3CA (36; 41.9%), AKT1 (7; 8.1%), PTEN(7; 8.1%), BRCA1 (4; 4.7%), and BRCA2 (7; 8.1%). Pts with a PIK3CAmut had significantly decreased PFS (HR 1.8; 95%CI: 1.1 -2.9, p=0.014) but not by ESR1mut status (p=0.583). PreC1 and EOC1-mTF were determined for 78 and 76 pts, respectively. PreC1-mTF was 0-1% in 21; 1.1-10.0% in 27; and 10.1-100% in 30. mTF levels remained between 0-1% in 17 pts fell to 0-1% in 11 pts, and was 0-1% in 5 pts without a preC1-mTF determination. PFS did not differ with respect to PreC1-mTF (p=0.210), but EOC1-PFS was worse in pts with mTF >1% (HR 3.0; 95%CI: 1.6 -5.2, p<0.001). PreC1 and EOC1-CTC were determined for 78 and 76 pts. 36 (46.2%) pts had a PreC1 CTC count ≥ 5. EOC1-CTC levels remained at (n=17) or increased to (n=1) ≥ 5 and was ≥ 5 in 2 pts without a preC1-CTC determination. EOC1-PFS was not significantly different for EOC1-CTC ≥ 5 (p=0.065), but was significantly decreased in pts with PreC1-CTC≥5 (HR=1.8; 95%CI: 1.1-3.0; p=0.018). Broader cfDNA NGS panel and CTC-derived ER/HER2 staining results will be presented at the meeting. Conclusions: Among patients receiving A±F, PFS varied based on the PIK3CAmutation status. cfDNA and CTC assessment PreC1 and EOC1 provided complementary information. Further validation in larger datasets is needed. 1. JAMA Oncol 2023;9:815. Clinical trial information: NCT02860000 .

Introduction Subjectively experienced cognitive difficulties are common in youth with postural orthostatic tachycardia syndrome. The pathophysiological and psychological contributions of these cognitive impairments remain unclear. Method Participants were 96 adolescents and young adults diagnosed with postural orthostatic tachycardia syndrome and admitted to an intensive pain treatment program. Participants completed cognitive assessment and measures of postural orthostatic tachycardia syndrome symptoms, pain intensity, pain catastrophizing, anxiety, depression, and functional disability. Results Self-reported autonomic symptom intensity, but not severity of heart rate change, was associated with cognitive performance. Symptoms of depression were associated with decreases in most measures of cognitive functioning. Pain intensity, pain catastrophizing, and depression but not cognitive scores and physiological measures, were significant predictors of disability. Conclusion Depression appears to be a significant contributor to the cognitive difficulties in youth with postural orthostatic tachycardia syndrome. These findings highlight the importance of assessing and treating affective symptoms in this population along with medical and lifestyle approaches to treating postural orthostatic tachycardia syndrome symptoms.

Abstract Background: Non-small cell lung cancer (NSCLC) makes up ~85% of lung cancers, and its major subtypes are adenocarcinoma (AD) and squamous cell carcinoma (SC). The histology classification of NSCLC has significant therapeutic and prognostic implications. As liquid biopsies are rapid and non-invasive, computational methods to classify NSCLC subtypes using cell-free DNA (cfDNA) are desired. Methods: Using The Cancer Genome Atlas (TCGA) NSCLC methylation data, we developed a method to classify AD and SC subtypes from cfDNA samples. We mapped TCGA methylation data to Guardant Infinity’s promoter regions and transformed them to allow for the transfer of the TCGA trained model to Infinity cfDNA epigenomic data. An advantage of this approach is that TCGA training data originates from the primary tumor, while cfDNA samples have low tumor fraction (TF) and may also contain signals from metastatic tumors. We trained a penalized Logistic Regression model with LASSO. To better fit the model to Infinity cfDNA data, we performed region filtering. Results: Our model effectively classified AD and SC subtypes from TCGA samples (AUC 0.97) (10-fold cross validation; Table 1). When evaluating on cfDNA samples with epigenomic TF ≥ 1%, the final model shows reasonable performance (AUC 0.94) (Table 1); the performance decreases when reduced to TF &gt; 0.05% (AUC 0.89) as expected (Table 1). When evaluating cfDNA from uncategorized lung samples, the predicted AD probabilities have significant association with KRAS mutations (p-value = 0.027). Conclusion: Our results show that the penalized Logistic Regression model trained with tissue TCGA methylation data through mapping, transformation, and region selection can classify NSCLC subtypes from cfDNA samples. This method may offer a fast, non-invasive tool to inform subtype-based clinical decisions, especially in the setting of poorly-differentiated carcinomas, and to identify subtype switches upon resistance to targeted therapies. Table 1: Model evaluation on tissue TCGA samples and cfDNA Infinity samples (different TF cutoffs) Sample type N samples AUC Accuracy Sensitivity Specificity Precision F1 score tissue TCGA 907 0.97 0.93 0.94 +/- 0.02 0.93 +/- 0.02 0.94 +/- 0.02 0.94 +/- 0.01 cfDNA Infinity 17 (TF ≥ 1%) 0.94 0.88 0.83 +/- 0.3 0.91 +/- 0.17 0.83 +/- 0.3 0.83 +/- 0.21 cfDNA Infinity 29 (TF &gt; 0.05%) 0.89 0.83 0.88 +/- 0.23 0.81 +/- 0.17 0.64 +/- 0.28 0.74 +/- 0.2 Citation Format: Laura Tung, Denis Tolkunov, Catalin Barbacioru, Deepika Kale, Scott Shell, Jill Tsai, Leylah Drusbosky, Kaushal Parikh, Han-Yu Chuang. Non-small cell lung cancer (NSCLC) histology classification using DNA methylation data captured from liquid biopsies [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 3499.

Chronic myeloid leukemia (CML) is defined by the presence of Philadelphia chromosome resulting from a reciprocal translocation between chromosomes 9 and 22 [t9;22] that gives rise to a BCR::ABL1 fusion gene. CML occurs in 3 different phases (chronic, accelerated, and blast phase) and is usually diagnosed in the chronic phase in developed countries. Tyrosine kinase inhibitor (TKI) therapy is a highly effective treatment option for patients with chronic phase–CML. The primary goal of TKI therapy in patients with chronic phase–CML is to prevent disease progression to accelerated phase–CML or blast phase–CML. Discontinuation of TKI therapy with careful monitoring is feasible in selected patients. This manuscript discusses the recommendations outlined in the NCCN Guidelines for the diagnosis and management of patients with chronic phase–CML.

170 Background: KRAS-mutant colorectal cancer (CRC) has a worse prognosis and greater resistance to therapy, attracting tremendous efforts to develop both allele-specific and pan-KRAS targeting agents including KRAS G12C and G12D inhibitors. CRC has demonstrated both primary and acquired resistance to KRAS G12C inhibitors, which can be better evaluated by circulating tumor DNA (ctDNA)-based next generation sequencing (NGS) methods without tissue sampling bias. Here, we utilized clinical ctDNA data to delineate the landscape of candidate alterations associated with primary resistance to KRAS G12D targeting in CRC. Methods: Samples from advanced CRC patients with Guardant360 data in 2021 were categorized into a KRAS G12D group and comparator groups of KRAS G12C and KRAS not detected (ND) according to KRAS mutation status. Demographics, MSI-H status, and blood tumor mutational burden (bTMB) were summarized and compared between groups using t-test for continuous variables and Fisher’s exact test for categorical variables. Co-occurrence patterns of alterations between KRAS and other genes were assessed. Primary resistance mutations were inferred by acquired resistance findings to KRAS G12C inhibitors reported by Awad et al. N Engl J Med. 2021 and Tanaka et al. Cancer Discov. 2021. Results: Among approximately 2500 samples, 16.8% had KRAS G12D, the most common KRAS mutation in CRC. The mean allele frequency of KRAS G12D (11.4%) is comparable to that of KRAS G12C (10.9%). Mean age (61.6 years), MSI-H frequency (3.8%), and mean bTMB (14.2 Mut/Mb) of KRAS G12D group is comparable to those of KRAS ND group. This contrasts with KRAS G12C with significantly lower mean age (60.2 years, p=0.01), lower MSI-H frequency (0.56%, p=0.03), and higher mean bTMB (16.3 Mut/Mb, p=0.02) compared to KRAS ND. Both KRAS G12D and G12C significantly co-occur with APC, PIK3CA, and SMAD4 alterations. FBXW7, AR, and KEAP1 alterations were unique co-occurrences to KRAS G12D, while KIT was unique to KRAS G12C. Candidate alterations associated with primary resistance in KRAS G12D CRC included simultaneously present mutations of KRAS Q61H (14.1%), G12V (6.4%), G12C (5.9%), G13D (3.6%), BRAF V600E (2.7%) and others, amplification of MET (2%), MYC (1.6%), and KRAS (1.4%), and FGFR3-TACC3 translocation (Table). Conclusions: KRAS G12D is associated with unique co-occurring molecular alterations compared to KRAS G12C in CRC. ctDNA-based NGS platforms can survey candidate alterations associated with primary resistance to KRAS G12D targeting in CRC. Further validation in preclinical models is needed. [Table: see text]

The incidence and mortality of hepatocellular carcinoma (HCC) in Sub-Saharan Africa is projected to increase sharply by 2040 against a backdrop of limited diagnostic and therapeutic options. Two large South African-based case control studies have developed a serum-based miRNome for Hepatitis B-associated hepatocellular carcinoma (HBV-HCC), as well as identifying their gene targets and pathways. Using a combination of RNA sequencing, differential analysis and filters including a unique molecular index count (UMI) ≥ 10 and log fold change (LFC) range > 2: <−0.5 (p < 0.05), 91 dysregulated miRNAs were characterized including 30 that were upregulated and 61 were downregulated. KEGG analysis, a literature review and other bioinformatic tools identified the targeted genes and HBV-HCC pathways of the top 10 most dysregulated miRNAs. The results, which are based on differentiating miRNA expression of cases versus controls, also develop a serum-based miRNA diagnostic panel that indicates 95.9% sensitivity, 91.0% specificity and a Youden Index of 0.869. In conclusion, the results develop a comprehensive African HBV-HCC miRNome that potentially can contribute to RNA-based diagnostic and therapeutic options.

SummaryBackgroundRacial and ethnic disparities exist for hepatitis C virus (HCV) treatment and hepatocellular carcinoma (HCC) survival.AimTo evaluate the impact of HCV treatment on such disparities.MethodsIn a retrospective cohort study, we analysed 6069 patients with HCV‐related HCC (54.2% Asian, 30.1% White, 8.5% Black, and 7.3% Hispanic) from centres in the United States and Asia.ResultsThe mean age was 61, 60, 59 and 68, respectively, for White, Black, Hispanic and Asian patients. Black patients were most likely to have Barcelona Clinic Liver Cancer stage D, vascular invasion and distant metastasis (23% vs. 5%–15%, 20% vs. 10%–17% and 10% vs. 5%–7%, respectively; all p < 0.0001). Treatment rate with direct‐acting antiviral agents (DAA) was 35.9% for Asian, 34.9% for White, 30.3% for Hispanic (30.3%), and 18.7% for Black patients (p < 0.0001). Among those untreated or without sustained virologic response (SVR), 10‐year survival rates were 35.4, 27.5, 19.3 and 14.0, respectively, for Asian, Hispanic, White and Black patients (p < 0.0001). There were no statistically significant differences among those with SVR (p = 0.44). On multivariable analysis adjusted for relevant confounders, there was no statistically significant association between survival and being Hispanic (aHR: 0.68, p = 0.26) or Black (aHR: 1.18, p = 0.60) versus White. There was a significant association between being Asian American and survival (aHR: 0.24, p = 0.001; non‐U.S. Asian: aHR: 0.66, p = 0.05), and for SVR (aHR: 0.30, p < 0.0001).ConclusionDAA treatment rates were suboptimal. Racial and ethnic disparities resolved with HCV cure. Early diagnosis and improved access to HCV treatment is needed for all patients with HCV infection.

AbstractBackgroundAlzheimer’s disease (AD) is characterized by the accumulation of neurofibrillary tangles (NFTs), comprised primarily of microtubule‐associated protein tau. NFTs are defining hallmarks of AD and its accumulation into pathological oligomers and fibrils has been associated with cognitive decline in AD and other tauopathies. Despite its pivotal role in the disease process, we still have a poor understanding of how their formation, toxicity, and spread across brain regions is regulated via tau‐associated proteins that regulate the oligomerization, pathological accumulation, and seeding of tau in affected cell types and vulnerable brain regions.MethodWe have established two proximity‐dependent biotin‐identification (BioID) models as novel approaches to identify the composition and proximal molecular environment of tau aggregates. Using an in vitro and ex vivo model approach coupled with mass spectrometry, we have identified proteins that were primarily associated with mutant tau aggregates vs. soluble wildtype tau and stratified them based on significance, molecular pathway and druggability. Immunoblotting and immunofluorescence were performed to assess the interaction of endogenous and overexpressed top candidates with tau, along with visualization with NFTs in the context of human AD pathology to assess their impact on tau‐aggregate formation and toxicity.ResultTo determine the physiological and aggregate specific interacting partners of tau, we are comparing wild type tau (TauWT) with mutant tau (Tau3xMUT) carrying three tauopathy‐associated mutations (A152T/P301L/S320F). The proteomic analysis from our combined proteomic datasets revealed that significantly changed proteins included candidates involved in RNA processing, as well as protein ubiquitination and proteasome degradation. We have begun validating proteins that are enriched in mutant tau in human tissue of AD, as well as primary tauopathies, that may be druggable targets for tauopathies.ConclusionThis study provides novel insights into cellular pathways and molecular mechanisms of neurodegeneration, by identifying in the context of living neurons and brain tissue different functional classes of tau‐associated proteins with relevance for AD pathophysiology. These are expected to include proteins that may mediate the toxic effect of NFTs, facilitate the formation or degradation of pathological tau aggregates, and catalyze posttranslational modifications of tau oligomers and associated proteins.

AbstractBackgroundTwo major risk factors of Alzheimer’s disease (AD) are advanced age and the APOE‐ε4 risk allele. However, despite having these risk factors, some individuals escape from developing AD or have slower cognitive decline. In this study we hypothesized that “resilient” individuals, defined as those who remain cognitively normal despite being >80 years‐old and carrying at least one copy of the APOE‐ε4 allele, have concerted changes in their blood transcriptomes that are associated with resilience to AD.MethodWe generated blood RNA‐sequence data from 105 APOE‐ε4 carriers from the Mayo Clinic Study of Aging (MCSA) who remained cognitively normal after age 80 (resilient), or who developed mild cognitive impairment (MCI) or AD (non‐resilient). Weighted gene co‐expression network analysis (WGCNA) was performed to evaluate the association of the blood co‐expression network with primary phenotypes of resilience and memory scores. To validate our findings, we constructed a consensus co‐expression network using both MCSA and a replication cohort of blood microarray data from 91 Alzheimer’s Disease Neuroimaging Initiative (ADNI) study participants who had a similar demographic profile. We annotated the consensus modules for their enrichment of cell types, biological processes, genes within previously published genome‐wide significant (GWS) AD‐associated loci, and genes that reside in consensus modules built from seven brain regions across three different autopsy cohorts. To identify genetic variants regulating blood consensus module co‐expression, we performed module quantitative trait locus (modQTL) analysis.ResultWe found co‐expression modules significantly (q<0.05) correlated with the memory phenotype, logical memory delayed recall, across both MCSA and ADNI cohorts. Some of these modules were enriched with blood cell types and biological processes, including telomere maintenance, mitochondrial functions, and immune response. We found 1 module significantly (q<0.05) enriched with genes near GWS AD‐associated loci and 4 modules with genes in brain consensus modules. Lastly, we found 8 modQTLs significantly (Bonferroni‐p<0.05) associated with the co‐expression of 5 different modules.ConclusionWe identified blood co‐expression modules, biological pathways and specific genetic variants associated with cognitive resilience in the presence of AD risk factors. This study provides novel insights into the potential role of peripheral blood in the development of and resilience to AD.