Citations

Abstract The radiation sensitivity index (RSI) and 12-chemokine gene expression signature (12CK GES) are two gene expression signatures (GES) that were previously developed to predict tumor radiation sensitivity or identify the presence of tertiary lymphoid structures in tumors, respectively. To advance the use of these GESs into clinical trial evaluation, their assays must be assessed within the context of the Clinical Laboratory Improvement Amendments (CLIA) process. Using HG-U133Plus2.0 arrays, we first established CLIA laboratory proficiency. Then the accuracy (limit of detection and macrodissection impact), precision (variability by time and operator), sample type (surgery vs. biopsy), and concordance with a reference laboratory were evaluated. RSI and 12CK GES were reproducible (RSI: 0.01 mean difference, 12CK GES: 0.17 mean difference) and precise with respect to time and operator. Taken together, the reproducibility analysis of the scores indicated a median RSI difference of 0.06 (6.47% of range) across samples and a median 12CK GES difference of 0.92 (12.29% of range). Experiments indicated that the lower limit of input RNA is 5 ng. Reproducibility with a second CLIA laboratory demonstrated reliability with the median RSI score difference of 0.065 (6% of full range) and 12CK GES difference of 0.93 (12% of observed range). Overall, under CLIA, RSI and 12CK GES were demonstrated by the Moffitt Cancer Center Advanced Diagnostic Laboratory to be reproducible GESs for clinical usage. Significance: The RSI and 12CK GES are two GESs that predict tumor radiation sensitivity or the presence of tertiary lymphoid structures in tumors, respectively. These GESs were assessed within the CLIA process for future clinical use. We established proficiency, reproducibility, and reliability characteristics for both signatures in a controlled setting, indicating these GESs are suitable for validation within future clinical trials.

Abstract Background 16S ribosomal RNA (rRNA) gene PCR and sequencing may serve as an adjunctive diagnostic tool in complex infections, identifying bacteria in patients on antibiotics whose cultures may be negative. Data on the optimal clinical settings for utilizing this type of testing are limited. This study reviews a single center's 16S rRNA PCR/sequencing experience in children to identify clinical syndromes and optimize specimen choice for higher yield, leading to testing of appropriate patients. Methods A retrospective study was performed at Mayo Clinic, Rochester involving children aged 0 to 18 years whose normally sterile tissue or fluid samples underwent 16S rRNA gene PCR/sequencing. The assay involved an up-front real-time PCR assay, reported as negative or submitted to Sanger or next-generation sequencing depending on Ct values. Data was collected on patient characteristics and results of 16S rRNA gene PCR/sequencing and conventional tests. Impact on clinical decision-making was assessed as to whether the advanced molecular diagnostic changed antimicrobial therapy. Results A total of 162 tests were performed on 124 patients, including 47% females (58/124) with a median age of 9.6 (range, 2.2-15.0) years. Overall, 33/162 (20%) of tests were positive in 24/124 (19%) patients. 58% of positive tests (19/33) were from samples with negative bacterial cultures. Cerebrospinal fluid was the most common specimen tested (n=38; 31%). Positive results were more likely from fluid compared to tissue samples (OR [95% CI]: 3.1 [1.3, 7.1], p=.007; OR [95% CI]: 0.3 [0.1, 0.8], p=.007, respectively). Testing was positive in 5/10 (50%) pleural fluids tested, a higher positivity rate than any other specimen type (OR [95% CI]: 5 [1.3, 19.0], p=.011). No significant changes in antibiotics were made within 24 hours of reporting positive 16S rRNA gene PCR/sequencing results. Conclusion This study highlights the importance of selecting appropriate sample types for 16S rRNA gene PCR/sequencing in pediatric patients. The assay is most likely to yield positive results in children with pleural effusion and in other fluid samples such as subdural and synovial fluid. Further implementation science research is needed to achieve impact on clinical practice. Disclosures Robin Patel, MD, a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, a: See above|MicuRx Pharmaceuticals and BIOFIRE: Grant/Research Support|PhAST, Day Zero Diagnostics, Abbott Laboratories, Sysmex, DEEPULL DIAGNOSTICS, S.L., Netflix, Oxford Nanopore Technologies and CARB-X: Advisor/Consultant|Up-to-Date and the Infectious Diseases Board Review Course.: Honoraria

ABSTRACT Symmetry refers to properties that remain invariant upon mathematical transformations. The principles of symmetry have guided numerous important discoveries in physics and chemistry but not in biology and medicine. Here, we aim to explore the presence of symmetry relationships at the gene expression level as a mean to distinguish between healthy and disease states. We deployed Learning-Based Invariant Feature Engineering - LIFE, a hybrid machine learning approach implemented with two symmetric invariant feature functions (IFFs) to identify Invariant Feature Genes (IFGs), which are gene pairs whose IFF single-value outputs remain invariant across individual samples in a given biological phenotype. Our multiclass classification results across the transcriptomes of 25 normal organs, 25 cancer types, and blood samples obtained from 4 different types of neurodegenerative diseases revealed the presence of unique phenotype-specific IFGs. We constructed networks using these IFGs (IF-Nets) and intriguingly, we demonstrated that the hubs could serve as information encoders, capable of reconstructing sample-wise expression values in relation to their counterpart genes. More importantly, we found that hubs of cancer IF-Nets were enriched with both approved and clinical trial drugs, highlighting “symmetry breaking” as a novel approach for treating diseases.

277 Background: While HER2-targeted therapies benefit patients (pts) with advanced HER2-positive mCRC, the development of resistance remains inevitable. This study aims to explore the landscape and frequency of genetic alterations putatively associated with acquired resistance to anti-HER2 therapy in HER2-positive mCRC. Methods: In this retrospective-multicenter international study involving Mayo Clinic, Duke Cancer Center and National Cancer Center Hospital East (Japan), we descriptively compared comprehensive genomic analyses from tissue or blood samples of pts with HER2-positive CRC pre-treatment and post-treatment with HER2-targeting agents. Results: A total of 36 pts were included in this study. 29 (80%) had HER2-positive mCRC as confirmed by immunohistochemistry (IHC) and fluorescent in situ hybridization (ISH), the remaining pts had HER2 amplification detected on blood or tissue . 34/36 (94%) pts were administered their first anti-HER2 agent after progressing on ≥2 prior lines of treatment. The most common anti-HER2 regimen administered was trastuzumab/pertuzumab (50%, 18/36), followed by trastuzumab-tyrosine kinase inhibitors (TKIs) (tucatinib or neratinib) (30%, 11/36) and trastuzumab deruxtecan (14%, 5/36). Putative genomic mechanisms of acquired resistance were detected in 72% (26/36), while the remaining pts lacked new genomic alterations that might explain resistance to anti-HER2 therapy, suggesting alternative escape mechanisms. Acquired alterations in downstream or alternate bypass pathways were identified in 72% (26/36) of pts; most commonly in the RAS/RAF pathway and in EGFR (34.6%, 9/26 each), followed by 27% (7/26) of pts with MET point mutations (mts) and amplification; activating muts in PI3K/AKT and in 27% (7/26), most commonly CDK12 (60%, 4/7) . HER2 receptor alterations were detected in 3 pts (8.3%), all of whom received trastuzumab-tucatinib and included HER2 L755S, HER2 V777L, HER2 D769Y, HER2 G727A and HER2 S310F, which are known to cause resistance to , however, information about tucatinib resistance is not yet available. Other altered pathways included AR, RB, NOTCH and HRD. Two pts lost HER2 expression on blood and tissue NGS post anti-HER2 therapy. Conclusions: The emergence of resistance might be in part related to acquired alterations that constitutively activate signaling pathways parallel or downstream of HER2, bypassing HER2 inhibition. Additional histologic studies, deep mutational scanning, larger populations and correlative analysis are needed to validate these findings.

254 Background: SLFN11 was recently identified as a dominant determinant of response to DNA-damaging anticancer agents. Several studies showed SLFN11 expression led to better sensitivity to topoisomerase inhibitors and PARP inhibitors. However, clinical evidence in mCRC has been lacking. Methods: Two independent cohorts (CALGB/SWOG 80405 trial and a real-world patient [Caris CODEai] cohort) were included in this study. Patients were stratified into SLFN11 -high and -low groups based on the median SLFN11 gene expression levels. Survival outcomes were compared between SLFN11 -high and SLFN11 -low in irinotecan-treated and oxaliplatin-treated patients. Median time was estimated using Kaplan-Meier method and Cox models were used for covariate adjustment. Endpoints of interest were progression-free survival (PFS) and overall survival (OS). Results: In the CALGB/SWOG 80405 trial cohort, 433 patients were included (110 treated with FOLFIRI-based chemotherapy and 323 treated with FOLFOX-based chemotherapy). In patients treated with FOLFIRI-based chemotherapy, SLFN11 -low patients exhibited numerically better PFS (median PFS, 13.4 vs 11.2 months, log-rank p = 0.03, adjusted hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.55-1.39, p = 0.50) and OS (median OS, 39.6 vs 30.3 months, log-rank p = 0.02, adjusted HR = 0.73, 95% CI 0.46-1.16, p = 0.19) compared to SLFN11 -high patients. In patients treated with FOLFOX-based chemotherapy, SLFN11 -low patients exhibited numerically better PFS (median PFS 11.2 vs 9.8 months, log-rank p = 0.03, adjusted HR = 0.83, 95% CI 0.65-1.05, p = 0.12) and OS (31.1 vs 26.1 months, log-rank p = 0.07, adjusted HR = 0.84, 95% CI 0.65-1.08, p = 0.16) compared to SLFN11 -high patients. No significant interaction was observed between treatment and SLFN11 expression in terms of PFS ( p = 0.69) and OS ( p = 0.44). In the Caris CODEai cohort, a better OS in SLFN11 -low patients than in SLFN11 -high patients was observed in irinotecan-treated patients ( N = 2906) (median OS, 25.5 vs 21.7 months, HR = 0.90, 95% CI 0.82-1.00, p = 0.048). However, no significant difference in OS between SLFN11 -low and SLFN11-high was observed in oxaliplatin-treated patients ( N = 4428) (median OS, 39.5 vs 35.8 months, HR = 0.98, 95% CI 0.90-1.06, p = 0.56). Conclusions: Low SLFN11 expression showed a potential for better prognosis in mCRC patients receiving irinotecan- and oxaliplatin-containing chemotherapies. These findings are not consistently aligned with preclinical data and clinical evidence in other cancer types previously reported. Further investigation is warranted to better understand the biological role and clinical implication of SLFN11 in mCRC.

AbstractBackgroundPatterns of regional atrophy and hypometabolism have been observed in dementia with Lewy bodies (DLB). However, determinants of regional vulnerability to structural and functional neurodegeneration remain largely unexplored. First, we investigated the association between regional gene expression and grey matter volumes in probable DLB patients. Since hypometabolism presumably precedes overt brain atrophy, we additionally investigate the association between regional gene expression and hypometabolism in DLB.MethodTo investigate the association between gene expression and regional volumes, 165 DLB patients along with 165 age‐ and sex‐matched healthy controls from three European centres and the Mayo Clinic (USA) were included. Regional volumes were quantified from MRI using SPM12 in 112 cortical, subcortical, and cerebellar brain regions, and compared between groups, using w‐scores. Regional expression data of seven genes involved in the formation and degradation of pathological protein aggregates (APOE, APP, BIN1, GBA, MAPT, SNCA, TMEM175) was extracted from six healthy donors from the Allen Human Brain Atlas and correlated with regional volumetric w‐scores. To assess the predictive value of regional gene expression on regional volumes we used Gaussian stepwise backwards linear regression including all seven genes as predictors. To investigate the association between gene expression and hypometabolism, we are currently applying the same analysis pipeline to FDG‐PET data of 139 DLB patients from 8 European centres.ResultMost brain regions showed lower volumes in DLB patients compared to healthy controls, with differences being most pronounced in occipital and parietal lobes. Regional expression of APOE correlated positively with regional volumes in DLB. Conversely, regional expression of MAPT correlated negatively with regional volumes. Both APOE and MAPT gene expression were significant predictors of regional volumes in the regression analysis. None of the other gene expression values was significantly associated with regional volumes in DLB.ConclusionOur findings show that regional expression of genes associated with the abnormal accumulation of amyloid and tau, common co‐pathologies in DLB, partially account for the brain atrophy pattern observed in DLB patients. Analyses are ongoing for the hypometabolism pattern. Our finding emphasises the relevance of co‐pathologies in predicting atrophy progression and identifying potential targets for future disease‐modifying treatments.

AbstractBackgroundAlzheimer’s disease (AD) patients have decline in cognitive domains including memory, language, visuospatial, and/or executive function and brain pathology including amyloid‐β and tau deposition, neurodegeneration, and frequent vascular co‐pathologies detectable by neuroimaging and/or cerebrospinal fluid biomarkers. However, molecular disease mechanisms are complex and heterogeneous. It is necessary to develop cost‐effective blood‐based biomarkers reflecting brain molecular perturbations in AD. We identified blood‐based gene and co‐expression network level changes associated with AD/mild cognitive impairment (MCI) diagnosis and AD‐related phenotypes.MethodWe performed differential gene expression and weighted gene co‐expression network analysis, followed by meta‐analysis, using blood transcriptome data of 391 participants from the Mayo Clinic Study of Aging and 654 participants from the Alzheimer's Disease Neuroimaging Initiative. The neuroimaging phenotypes include microhemorrhages, infarcts, amyloid burden, hippocampal volume, and white matter hyperintensities. The cognitive phenotypes include standardized cognitive subtest scores and composite scores for memory, language, visuospatial, and executive function.ResultFive out of 18 modules(M) are significantly associated with diagnosis or cognition (FDR‐adjusted p<0.05). M1 and M15 both positively associates with memory, M1 positively associated with language and M15 with visuospatial function. M1 and M15 are enriched in differentially expressed genes (DEGs) associated with language and executive function, respectively. M2 negatively associates with logical memory delayed recall scores(LMDR), memory, executive, and language functions and is enriched in DEGs for these phenotypes. M8 negatively associates with memory, language and executive functions and is enriched in DEGs for memory and language. M12 positively associates with LMDR. M1 and M15 are down‐regulated while M2 and M8 are up‐regulated in AD/MCI patients. Cell‐type enrichment analysis showed M2 is enriched in monocytes and neutrophils; M8 in monocytes; M15 in B cells (FDR <0.05). Gene ontology terms enriched in these modules indicated broad consistency with their cell types.ConclusionWe identified five modules significantly associated with AD/MCI or cognitive phenotypes using blood transcriptome data. These findings nominate blood transcriptome changes and their enriched biological processes as potential pathomechanisms in cognitive decline and AD/MCI development. We aim to investigate these blood transcripts as potential biomarkers for AD or AD‐related phenotypes and therapeutic targets through additional replication and experimental validation studies.

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies of the head and neck squamous cell carcinoma (HNSCC). HNSCC is recognized as the eighth most commonly occurring cancer globally in men. It is essential to distinguish between cancers arising in the head and neck regions due to significant differences in their etiologies, treatment approaches, and prognoses. As the Cancer Genome Atlas (TCGA) dataset is available in HNSCC, the survival analysis prognosis of OSCC patients based on the TCGA dataset for discovering gene expression-based prognostic biomarkers is limited. To address this paucity, we aimed to provide comprehensive evidence by recruiting studies that have reported new biomarkers/signatures to establish a prognostic model to predict the survival of OSCC patients. Using PubMed search, we have identified 34 studies that have been using the least absolute shrinkage and selection operator (LASSO)-based Cox regression analyses to establish signature prognosis that related to different pathways in OSCC from the past 4 years. Our review was focused on summarizing these signatures and implications for targeted therapy using FDA-approved drugs. Furthermore, we conducted an analysis of the LASSO Cox regression gene signatures. Our findings revealed 13 studies that correlated a greater number of regulatory T cells (Tregs) cells in protective gene signatures with increased recurrence-free and overall survival rates. Conversely, two studies displayed an opposing trend in cases of OSCC. We will also explore how the dysregulation of these signatures impacts immune status, promoting tumor immune evasion or, conversely, enhancing immune surveillance. Overall, this review will provide new insight for future anti-cancer therapies based on the potential gene that is associated with poor prognosis in OSCC.

Background: The incidence and mortality of anal squamous cell carcinoma (ASCC) are rising, with greater than 80% of cases linked to human papillomavirus (HPV), primarily HPV16. Post-treatment surveillance can be challenging due to the limitations of anoscopy, digital anal rectal exam (DARE), and imaging. Plasma tumor tissue modified viral (TTMV)-HPV DNA has shown strong sensitivity, specificity, and predictive value in detecting the recurrence of HPV-driven oropharyngeal cancer. Here, we investigate the ability of TTMV-HPV DNA for the early recurrence detection of ASCC. Methods: This retrospective clinical case series included 117 patients with HPV-driven ASCC across 7 U.S. centers, monitored with TTMV-HPV DNA during routine clinical care between March 2020 and June 2024. Physician-reported clinical data and biomarker testing data were combined to create a comprehensive, longitudinal dataset for evaluating test performance metrics. Results: Patients had a median age of 63 years and median post-diagnosis follow-up of 19 months. HPV status was primarily confirmed by TTMV-HPV DNA (52%) or p16 immunohistochemistry (39%). Of those tested for TTMV-HPV DNA pretreatment, 85% had a positive result. TTMV-HPV DNA clearance during or within three months post-treatment was associated with significantly better recurrence-free survival. The per-patient surveillance sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 82.8%, 98.4%, 96.0%, and 92.5%. Of 24 patients with a documented recurrence and a positive TTMV-HPV DNA test, the test was the first evidence of recurrence in 14 patients (58.3%), with a median lead time of 59 days (range: 10–536). TTMV-HPV DNA accurately resolved 94.3% of cases with indeterminate clinical findings. Conclusions: TTMV-HPV DNA testing provides a sensitive and specific approach for detecting patients with recurrent ASCC and resolving the status of patients with indeterminate clinical findings.

ABSTRACT Hypoxic stress responses are essential for cellular and organismal survival and drive gene regulation across diverse biological pathways, including cell cycle progression and energy metabolism. Here, we show that topoisomerase IIβ (TOP2B) regulates DNA topology and transcription of hypoxia-inducible genes (HIGs) in a DNA-dependent protein kinase (DNA-PK)-dependent manner. Integrated cellular, biochemical, and genomic analyses reveal an antagonistic yet correlated relationship between TOP2B and DNA-PK activities. Under normoxic conditions, TOP2B associates with HIGs and represses transcription by suppressing DNA negative supercoiling formation and accessibility. Under hypoxic exposure, TOP2B dissociates from HIGs, while DNA-PK and HIF1α are recruited to activate HIGs. Notably, DNA-PK is required for the repressive function of TOP2B, as DNA-PK knockout abrogates TOP2B release and activity, resulting in elevated expression of a number of HIGs. Mechanistically, DNA-PK phosphorylates TOP2B at T1403, stimulating its catalytic activity to restrain DNA unwinding and accessibility, thereby suppressing HIG transcription. Collectively, these findings identify a novel role for TOP2B and DNA-PK-mediated regulation of TOP2B as key transcriptional regulators of HIG expression. We propose that phosphorylation-dependent modulation of TOP2B activity is coordinated with transcriptional states and determines DNA topology to regulate Pol II transcription.