563 Background: Breast cancer is inherently heterogeneous, posing challenges for effective treatment. Uncovering the relationship between imaging features and genomic profiles could improve patient stratification. In this study, we evaluated whether radiomic features can capture the underlying genomic complexity of breast tumors, potentially offering a non-invasive means to better characterize tumor heterogeneity. Methods: We analyzed 284 breast cancer patients using an integrated radiogenomic approach. MRI-derived radiomics features were extracted and clustered using unsupervised learning methods, resulting in 12 distinct clusters. We then analyzed these clusters against matched whole-genome sequencing and transcriptome data, focusing on heterogeneity-related radiomics features. Clustering was performed using dynamic tree cutting after hierarchical clustering of 10 principal components derived from 214 radiomic features. Results: We identified distinct patterns of tumor heterogeneity among the 12 identified clusters, named according to descending cluster size (range: 10-46). Clusters 9, 4, and 3 exhibited the highest homogeneity (in that order), with cluster 9 being the most homogeneous overall. Cluster 12, 11, 8, 7, and 5 showed varying degrees of heterogeneity, while clusters 1 and 2 were moderately heterogeneous. Cluster 1-3 were HER2-enriched (PAM50). Clusters 1 and 2 together had ERBB2 amplifications (33%; Fisher’s exact test, P = 0.056), whereas cluster 3 was HER2-positive (IHC) without amplifications. Cluster 1 leaned toward the basal-like subtype, while 3 leaned toward luminal A. Cluster 2 was enriched in luminal B (50%; P = 0.012). Cluster 1-3 were distinguishable by their degree of radiomics-quantified heterogeneity. Cluster 4 was enriched in high Myc expression (17%; P = 0.059). Cluster 5 was enriched in whole-genome-based HRD (40%; P = 0.01) and basal-like (52%; P = 0.001). Cluster 6 was deprived of TP53 mutations (37%; P = 0.04), had low tumor mutational burden, and was characterized by small volume but higher surface-volume ratio, suggesting irregular shape. Cluster 8 was enriched in PIK3CA mutations (60%, P = 0.046), cluster 10 was enriched in CHEK2 mutations (9%; P = 0.039), cluster 11 showed high TERT (40%, P = 0.005) and CDKN2A (40%; P = 0.048) expression, cluster 12 was predominantly post-menopausal (80%; P = 0.47), and both clusters 10 and 12 exhibited low ESR1 expression (20%; P = 0.035). Conclusions: This comprehensive radiogenomic analysis demonstrates that MRI-based radiomics features can effectively capture tumor heterogeneity patterns that correlate with specific genomic alterations in breast cancer. The identification of 12 distinct clusters, each with characteristic genomic features, provides new insights into the biological basis of tumor heterogeneity, potentially opening new avenues for breast cancer subtyping.

Adolescent idiopathic scoliosis (AIS) is the most common nondegenerative spinal abnormality. Research indicates a strong correlation between genetics and AIS, with heritability estimates of 87.5%. However, the rarity of shared causative genes among patients, and the difficulty of replication between studies suggest that AIS is a highly complex polygenic disease. In this study, we utilized whole-genome sequencing (WGS) to comprehensively explore the genetic landscape of 119 AIS patients from 103 families. We implemented an automated WGS analysis pipeline powered by RareVisionTM consisting of automated algorithms and manual curation. We identified clinically relevant candidate variants in 20/119 (16.8%) patients and potentially relevant strong or moderate candidate variants in another 73/119 (61.3%) patients. Candidate variants included coding and noncoding point mutations, along with structural variants and large indels, showing the utility of WGS. Candidate genes included AIS-associated genes (e.g. CHD7, COL11A1/2, FBN1/2, HSPG2, KIF7), as well as genes associated with other musculoskeletal and developmental syndromes where scoliosis is a known symptom (e.g. RYR1, GJB2, MYH2, MYH7). Association analysis showed 4 known AIS single nucleotide polymorphisms (rs12946942, rs10756785, rs3904778, rs7633294) also correlated with AIS in our cohort. Finally, through gene set enrichment analysis, we were able to identify 3 gene clusters involved in skeletal muscle contraction, extracellular matrix composition, and gene expression regulation. In summary, through scalable WGS-based familial testing we were able to (1) find clinically relevant genetic variations in the majority of our patients and (2) create a large dataset that allowed us to identify biological pathways relevant to AIS etiopathogenesis. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by a research grant of the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Information and Communication Technology, NRF-2021R1F1A1045417). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the Institutional Review Board of Shriners Hospitals for Children (IRB approval number: 9-21-2022) and adhered to the tenets of the Declaration of Helsinki. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data presented in this study are available on request from the corresponding authors. The data are not publicly available due to the ethical and privacy nature of the data.

Purpose Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500's key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Adolescent idiopathic scoliosis (AIS) is a complex genetic disorder. This study used whole-genome sequencing (WGS) to investigate the genetic basis of AIS in 119 patients from 103 families. Our WGS analysis identified known pathogenic or protein-truncating variants in 15 probands, and other strong or moderate candidate variants in 69 additional patients. We found both coding and non-coding mutations, including structural variants. Candidate genes included known AIS genes (e.g., COL11A2, FBN1) and genes linked to other musculoskeletal disorders with scoliosis (e.g., RYR1). Association analysis confirmed four known AIS single-nucleotide polymorphisms in our cohort. Gene set enrichment analysis revealed four gene clusters related to skeletal muscle contraction, extracellular matrix, and gene expression regulation. This WGS-based approach identified clinically relevant genetic variations and biological pathways in AIS patients, offering valuable insights into its complex development.

554 Background: Homologous recombination deficiency (HRD) in breast cancer is an actionable target, with treatment efficacy potentially linked to timely detection. Notably, BRCA1 and BRCA2 are key genes implicated in HRD, and their pathogenic germline mutations are crucial criteria for the use of poly (ADP-ribose) polymerase inhibitors (PARPi). Although germline BRCA1/2 mutations are detectable in only a small fraction (1-5%) of breast cancers, recent whole-genome sequencing (WGS) studies have revealed that up to 22% of breast cancers also exhibit HRD-like genomic characteristics, suggesting a broader potential for HRD-targeted therapy. This has spurred the development of genomic-feature-based HRD identification methods. However, the invasive and costly nature of these methods poses a challenge. This has prompted our investigation into non-invasive image biomarkers for HRD identification. Methods: Invasive breast cancer patients were recruited from March 2021 to August 2022. Eligibility criteria included availability of fresh-frozen tumor tissue for WGS and suitability for dynamic contrast-enhanced (DCE) MRI to facilitate radiomics analysis. The association between HRD and radiomic features as well as clinicopathologic factors was investigated through rigorous genomic and statistical analysis. Results: This study encompassed 145 patients aged 20 to 69 years, of whom 16.6% (24 out of 145) were genomically identified as HRD. All patients harboring pathogenic germline mutations in BRCA1 (n=3) or BRCA2 (n=2), along with concomitant somatic LOH, exhibited HRD. A comprehensive analysis of 214 radiomic features revealed that tumor sphericity, informational measure of correlation 1 (IMC1), size-zone non-uniformity normalized (SZNN), and small area emphasis (SAE) derived from subtracted early dynamic T1-weighted imaging were significantly correlated with HRD. Moreover, these radiomic features demonstrated substantial diagnostic value, as evidenced by their ROC-AUC and PR-AUC performance against baseline models: Sphericity (ROC: 0.62, p=0.055; PR: 0.22, p=0.053), SAE (ROC: 0.63, p=0.052; PR: 0.32, p=0.007), SZNN (ROC: 0.63, p=0.04; PR: 0.30, p=0.007), and IMC1 (ROC: 0.62, p=0.067; PR: 0.29, p=0.02). Additionally, our findings suggest that these radiomic features are more directly related to HRD than to the triple-negative phenotype, which is commonly linked to HRD. Conclusions: We found that four radiomic features from MRI have significant predictive value for identifying HRD in breast cancer. Given their fair predictability and immediate availability, these features are ideally suited for a screening approach, potentially identifying more patients eligible for targeted treatment. This finding represents a significant advancement in the fields of radiology and precision oncology, opening new avenues for patient-specific treatment strategies.

e15044 Background: Circulating tumor DNA (ctDNA), a cell-free DNA (cfDNA) present in the plasma of cancer patients, originates from cancer cells and serves as a crucial biomarker during cancer treatment. Despite its importance, the current limit of detection (LoD) of conventional ctDNA assays is suboptimal (0.01%; 10-4) for detecting ctDNA from microscopic residual and recurrent cancer tissues. To address this, we integrated two cutting-edge techniques: whole-genome sequencing (WGS) of primary cancer tissue (a mutation capture step) and duplex DNA sequencing-based cfDNA sequencing (mutation recapture steps). Methods: Thirteen colorectal cancer patients participated in this study. Primary tumor tissues and matched normal blood tissues were collected for WGS in the mutation capture step, while plasma samples for cfDNA sequencing in the mutation recapture steps were obtained just prior to colorectal cancer surgery and 1-month post-surgery follow-up. Tumor DNA and germline DNA were analyzed using CancerVision, a CLIA-certified clinical-grade cancer WGS platform, in the mutation capture step. In the mutation recapture steps, somatically acquired mutations from the previous step were tracked in cfDNA samples using the Concatenating Original Duplex for Error Correction (CODEC) technique, a duplex DNA sequencing technique that examines both Watson and Crick strands of double-stranded DNA molecules to discern true mutations from sequencing noise. Results: The median WGS depth of tumor and germline tissues was 40x and 20x, respectively. The mean depth of cfDNA WGS with CODEC was 25x, with a median duplex sequencing rate of 70%. Overall, 4,828-301,434 somatic base substitutions (SBSs) per sample were discovered in the capture step. Four of the thirteen tumors exhibited hypermutator characteristics with microsatellite instability features. The CODEC technique demonstrated excellent capability in tracing cancer-specific mutations in cfDNA sequencing with a technical sequencing error rate of 4 x 10-7, defining the maximum technical LoD, which is 250-fold lower errors than conventional sequencing. In our sample cohort, tumor fractions in cfDNA sequencing were robustly estimated from 0.001% (10-5), below the LoD of conventional MRD methods. Conclusions: Our integration of tumor-WGS-informed duplex cfDNA sequencing methods significantly enhances the sensitivity of sequencing-based MRD assays, achieving a technical LoD limit of 10-7 for detecting ctDNA in cancer patients. These approaches represent a breakthrough in monitoring MRD in real-world cancer patients.

Abstract Formalin-Fixed Paraffin-Embedded (FFPE) specimens, widely utilized in clinical cancer diagnostics, present significant challenges by introducing artifacts into genomic data. This study aimed to profile these FFPE-induced genomic alterations, with a particular focus on single-nucleotide variants (SNVs), small insertions and deletions (indels), and copy-number variations (CNVs), and to develop computational methods for filtering out such artifacts. Our primary focus was twofold: first, to comprehensively characterize the unique error profile of FFPE specimens observed through whole-genome sequencing (WGS), and second, to construct artifact classifiers and noise filters for SNV/indels and CNVs. We utilized machine learning (ML) and signal-processing techniques on a dataset of FFPE and matched fresh-frozen (FF) samples. The dataset of 52 FFPE-FF pairs were obtained from four different medical institutes and from various cancers including liver, breast, colon, stomach, and lung cancer, with varied FFPE archiving times. We also analyzed additional FFPE-only samples to refine our methods. Our methodology incorporated advanced computational approaches, including stacking ensemble, transfer learning, and wavelet transform, to enhance robustness and accuracy. The method's design was centered around the notion of not only achieving high performance in distinguishing true signals from FFPE-induced artifacts but also addressing the real-world challenges posed by the varying quality and conditions of clinical FFPE samples. In the analysis, we found peculiar patterns of FFPE-specific error profile, including well-known cytosine deamination and novel mutational signatures. The classifier, building on our findings, effectively differentiated true genomic variants from FFPE-induced artifacts for both SNVs and indels, demonstrating a sensitivity of 0.97, specificity of 0.87, and an F1 score of 0.94 for SNVs. For indels, it achieved a sensitivity of 0.91, specificity of 0.91, and an F1 score of 0.91. The CNV filter notably enhanced the signal-to-noise ratio (SNR) of CNV depth profiles, increasing it from 13dB to 17.5dB on average. Furthermore, we conducted evaluations on two critical measures in cancer and clinical genomics: homologous recombination deficiency (HRD) and tumor mutational burden (TMB), achieving post-filtering concordance rates of 0.99 for HRD—correctly identifying all 8 HRD-positive patients in our dataset—and 0.96 for SNV-based TMB and 0.87 for indel-based TMB. Additionally, a post hoc procedure for sensitive detection of cancer driver mutations resulted in concordance rates of 0.94 for SNVs, 0.91 for indels, and 0.95 for oncogene amplification. Taken together, our study advances FFPE WGS analysis in cancer diagnostics by effectively filtering artifacts and addressing challenges with older, degraded samples, enhancing clinical applicability. Citation Format: Joonoh Lim, Seongyeol Park, Won-Chul Lee, Ryul Kim, Sangmoon Lee, Jeong Seok Lee, Brian Baek-Lok Oh, Young Seok Ju. Enhancing genomic analysis in cancer diagnostics: A machine learning approach for removing artifacts in FFPE specimens [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 909.

Introduction:Breast cancer exhibits vast genomic diversity, leading to varied clinical manifestations. Integrating molecular subtyping with in-depth genomic profiling is pivotal for informed treatment choices and prognostic insights. Whole-genome clinical analysis provides a holistic view of genome-wide variations, capturing structural changes and affirming tumor suppressor gene loss of heterozygosity.Case Presentation:Here we detail four unique breast cancer cases from Seoul St. Mary's Hospital, highlighting the actionable benefits and clinical value of whole-genome sequencing (WGS). As an all-in-one test, WGS demonstrates significant clinical utility in these cases, including: (1) detecting homologous recombination deficiency with underlying somatic causal variants (case 1), (2) distinguishing double primary cancer from metastasis (case 2), (3) uncovering microsatellite instability (case 3), and (4) identifying rare germline pathogenic variants in TP53 gene (case 4). Our observations underscore the enhanced clinical relevance of WGS-based testing beyond pinpointing a few driver mutations in conventional targeted panel sequencing platforms.Conclusion:With genomic advancements and decreasing sequencing costs, WGS stands out as a transformative tool in oncology, paving the way for personalized treatment plans rooted in individual genetic blueprints.

The comprehensive genomic impact of ionizing radiation (IR), a carcinogen, on healthy somatic cells remains unclear. Using large-scale whole-genome sequencing (WGS) of clones expanded from irradiated murine and human single cells, we revealed that IR induces a characteristic spectrum of short insertions or deletions (indels) and structural variations (SVs), including balanced inversions, translocations, composite SVs (deletion-insertion, deletion-inversion, and deletion-translocation composites), and complex genomic rearrangements (CGRs), including chromoplexy, chromothripsis, and SV by breakage-fusion-bridge cycles. Our findings suggest that 1 Gy IR exposure causes an average of 2.33 mutational events per Gb genome, comprising 2.15 indels, 0.17 SVs, and 0.01 CGRs, despite a high level of inter-cellular stochasticity. The mutational burden was dependent on total irradiation dose, regardless of dose rate or cell type. The findings were further validated in IR-induced secondary cancers and single cells without clonalization. Overall, our study highlights a comprehensive and clear picture of IR effects on normal mammalian genomes.

Supplementary Figure S1-10 and Table S1

The molecular landscape and the intratumor heterogeneity (ITH) architecture of gastric linitis plastica (LP) are poorly understood. We performed whole-exome sequencing (WES) and T-cell receptor (TCR) sequencing on 40 tumor regions from four LP patients. The landscape and ITH at the genomic and immunological levels in LP tumors were compared with multiple cancers that have previously been reported. The lymphocyte infiltration was further assessed by immunohistochemistry (IHC) in LP tumors. In total, we identified 6339 non-silent mutations from multi-samples, with a median tumor mutation burden (TMB) of 3.30 mutations per Mb, comparable to gastric adenocarcinoma from the Cancer Genome Atlas (TCGA) cohort (P = 0.53). An extremely high level of genomic ITH was observed, with only 12.42%, 5.37%, 5.35%, and 30.67% of mutations detectable across 10 regions within the same tumors of each patient, respectively. TCR sequencing revealed that TCR clonality was substantially lower in LP than in multi-cancers. IHC using antibodies against CD4, CD8, and PD-L1 demonstrated scant T-cell infiltration in the four LP tumors. Furthermore, profound TCR ITH was observed in all LP tumors, with no T-cell clones shared across tumor regions in any of the patients, while over 94% of T-cell clones were restricted to individual tumor regions. The Morisita overlap index (MOI) ranged from 0.21 to 0.66 among multi-regions within the same tumors, significantly lower than that of lung cancer (P = 0.002). Our results show that LP harbored extremely high genomic and TCR ITH and suppressed T-cell infiltration, suggesting a potential contribution to the frequent recurrence and poor therapeutic response of this adenocarcinoma.

e15173 Background: Due to the dramatic decrease in cost of genome sequencing, we are entering the era of whole genome sequencing (WGS) at $100. Tumor mutational burden (TMB) and mutational signatures have been introduced as potential prognostic/predictive cancer biomarkers and mostly assessed by targeted cancer gene sequencing panels. However, they are truly whole genome-wide events and thus more accurately estimated by whole genome sequencing data. Methods: We analyzed WGS data produced by Genome Insight Inc. that encompass > 1,300 breast, lung, and hepatocellular carcinoma samples, collectively. Our genome-wide TMBs (wgsTMB) were systematically compared with the TMB estimates by targeted sequencing methods, such as conventional whole-exome sequencing (WES) and targeted panel sequencing from FoundationOne CDx (F1CDx). In parallel, we leveraged genome-wide somatic mutations for validating mutational signatures projected from the targeted sequencing methods. Results: Pembrolizumab is FDA approved for solid tumors with high TMB (≥ 10 mutations/Mb) assessed by F1CDx. This criterion classified that 546 of the tumors (41%) in our cohort as high F1CDx TMB (f1TMB), who may benefit from immunotherapy. However, the high f1TMB classification was inconsistent to the genome-wide TMB classification ( p < 2.2e-16). For example, 132 high f1TMB tumors (24.1%; 132/546) showed lower than the median wgsTMB estimate. On the flip side, 32% of the low f1TMB tumors (251/784) demonstrate higher than median wgsTMB estimate (see table). Although there is no approved criterion in WGS that defines hypermutators, our data illustrates that WGS will be helpful for redefining the criteria for selecting patients for immune checkpoint inhibitors. The wgsTMB was also an essential factor for accurate estimation of mutational signatures from targeted sequencing. For example, in high TMB tumors, mutational signature estimated from WES showed on average 0.87 cosine similarity with signatures from WGS. However, the correlation was substantially reduced in low TMB tumors, showing only ~0.64 on average. Particularly, ~12% of breast tumors with considerable levels of homologous recombination deficiency (HRD) signatures by WGS were not captured by whole-exome sequencing based approaches. Further exploration should be performed with WGS to select proper patients for targeted therapies, including PARP inhibitors. Conclusions: Despite the current guidelines depending on targeted sequencing in precision oncology, we showed that whole-genome sequencing can deliver more accurate cancer genome profiles, such as, but not limited to, TMB and mutational signatures. Given its more comprehensive capabilities and affordable cost, we believe that WGS-based precision oncology is medically necessary. [Table: see text]

Cyclin-dependent kinase 4/6 inhibitor (CDK4/6) therapy plus endocrine therapy (ET) is an effective treatment for patients with hormone receptor-positive/human epidermal receptor 2-negative metastatic breast cancer (HR+/HER2− MBC); however, resistance is common and poorly understood. A comprehensive genomic and transcriptomic analysis of pretreatment and post-treatment tumors from patients receiving palbociclib plus ET was performed to delineate molecular mechanisms of drug resistance. Tissue was collected from 89 patients with HR+/HER2− MBC, including those with recurrent and/or metastatic disease, receiving palbociclib plus an aromatase inhibitor or fulvestrant at Samsung Medical Center and Seoul National University Hospital from 2017 to 2020. Tumor biopsy and blood samples obtained at pretreatment, on-treatment (6 weeks and/or 12 weeks), and post-progression underwent RNA sequencing and whole-exome sequencing. Cox regression analysis was performed to identify the clinical and genomic variables associated with progression-free survival. Novel markers associated with poor prognosis, including genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four prognostic clusters with distinct molecular features were identified. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly to palbociclib plus ET. Comparisons of paired pre- and post-treatment samples revealed that tumors became enriched in APOBEC mutation signatures, and many switched to aggressive molecular subtypes with estrogen-independent characteristics. We identified frequent genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C. We identified novel molecular features associated with poor prognosis and molecular mechanisms that could be targeted to overcome resistance to CKD4/6 plus ET. ClinicalTrials.gov, NCT03401359. The trial was posted on 18 January 2018 and registered prospectively.

In recent decades, biomedical sensors based on surface-enhanced Raman spectroscopy (SERS), which reveals unique spectral features corresponding to individual molecular vibrational states, have attracted intensive attention. However, the lack of a system for precisely guiding biomolecules to active hotspot regions has impeded the broad application of SERS techniques. Herein, we demonstrate the irreversible active engineering of three-dimensional (3D) interior organo-hotspots via electrochemical (EC) deposition onto metal nanodimple (ECOMD) platforms with viral lysates. This approach enables organic seed-programmable Au growth and the spontaneous bottom-up formation of 3D interior organo-hotspots simultaneously. Because of the net charge effect on the participation rate of viral lysates, the number of interior organo-hotspots in the ECOMDs increases with increasingly positive polarity. The viral lysates embedded in the ECOMDs function as both a dielectric medium for field confinement and an analyte, enabling the highly specific and sensitive detection of SARS-CoV-2 lysates (SLs) at concentrations as low as 10–2 plaque forming unit/mL. The ECOMD platform was used to trace and detect the SLs in human saliva and diagnose severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); the results indicate that the proposed platform can provide point-of-care diagnoses of infectious diseases.

CDK4/6 inhibitors such as palbociclib in combination with endocrine therapy (ET) have remarkablyimproved the outcome of patients with ER+/HER2- metastatic breast cancer (MBC). However, manypatients are intrinsically resistant to CDK4/6i therapy, and those who respond eventually acquireresistance. Although high baseline CCNE1 expression and rare alterations in RB1 and FAT1 geneshave been shown to be associated with CDK4/6i resistance, the molecular mechanisms of CDK4/6iresistance are complex and remain poorly understood. To better understand and overcome CDK4/6iresistance, we performed multi-omics profiling of paired tumor biopsies from ER+/HER2- MBCpatients treated with palbociclib combined with ET. Tumor biopsies taken at pre-treatment, on-treatment, and progressive disease (PD) from 71 patients were profiled using whole-exomesequencing (WES), whole-transcriptome sequencing (RNA-Seq) and IHC analysis. Ourcomprehensive analysis identified several tumor intrinsic molecular markers associated with worsePFS, including the Luminal B subtype (p=0.012, HR=2.593), BRCA1/2 pathogenic mutation (p=0.012,HR=2.67) and mutation signatures linked to APOBEC enzymatic activity (p=0.002, HR=3.19).Conversely, the estrogen response signature (p=0.006, HR=0.43) was associated with favorableprognosis. Unsupervised analysis revealed a cluster of tumors enriched in homologousrecombination deficiency (HRD) linked genomic scars that was associated with poor prognosis(p=0.005, HR=2.49). Of note, these HRD-high tumors responded even more poorly to treatment whenco-occurring with TP53 somatic mutations. Integrative analysis further identified three poorprognosis clusters (IC2-4) enriched in Luminal B, proliferative and HRD features when compared tothe favorable prognosis cluster (IC1).Comparing baseline vs. PD samples, we observed a pattern of post-treatment enrichment for the poorprognosis markers. In addition, breast cancer-associated genes such as BRCA1/2, TP53 and PTENharbored a higher prevalence of genomic alterations including somatic mutation, amplification,. deletion and gene fusion at PD. Cell cycle gene expression and signatures also markedly increased atPD compared to baseline whereas estrogen response signatures decreased. Upon diseaseprogression, tumors had frequently switched to molecular subtypes with aggressive and estrogenindependent characteristics, demonstrating high plasticity in response to CDK4/6i and ET treatment.These patterns of acquired resistance were validated by IHC analysis of cyclins E1 and E2, Ki67 andpRb. To investigate the genomic alterations responsible for acquired resistance, we compared 21paired baseline and PD samples. We observed that PD-specific RB1 loss-of-function events occurredwith higher prevalence than previously reported, underscoring a major role of cell cycle de-regulation in conferring resistance to CDK4/6 inhibition. In this prospective longitudinal multi-omicsstudy, we identified novel candidate biomarkers that can be used to improve prediction of responseto CDK4/6i. In addition, we derived new insights into the molecular mechanisms of drug resistanceto palbociclib plus ET that will help guide therapeutic strategies and drug development inHR+/HER2− MBC. Citation Format: Zhengyan Kan, Seock-Ah Im, Kyunghee Park, Ji Wen, Kyung-Hun Lee, Yoon-La Choi, Won-Chul Lee, Ahrum Min, Vinicius Bonato, Seri Park, Sripad Ram, Dae-Won Lee, Ji-Yeon Kim, Su Kyeong Lee, Won-Woo Lee, Jisook Lee, Miso Kim, Scott L. Weinrich, Han Suk Ryu, Tae Yong Kim, Stephen Dann, Diane Fernandez, Jiwon Koh, Song Yi Park, Shibing Deng, Eric Powell, Rupesh Kanchi Ravi, Jadwiga Bienkowska, Paul A. Rejto, Woong-Yang Park, Yeon Hee Park. Serial genomic profiling reveals molecular mechanisms of breast cancer resistance to palbociclib [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD2-08.

Simultaneous detection of biomolecules with high sensitivity and selectivity is highly demanded for point-of-care diagnosis. Here, a simple solution-based surface-enhanced Raman spectroscopy (SERS) method is presented to facilitate rapid and direct ternary detections of ascorbic acid (AA), dopamine (DA) and uric acid (UA) in urine. The approach focuses on in situ surface modification of Au nanopillar electrode by Au electrodeposition in the presence of target molecules. Formation of new plasmonic nanostructures on the nanopillar array effectively perturbs the biomolecules adsorbed on the Au surface and confines the target molecules in solution into active regions of the generated hotspots, resulting in the significant amplifications of Raman signals within 60 s. The method enabled reliable label-free detections of AA, DA, and UA at relevant physiological ranges with detection limits of 1, 0.1 and 1 nM, respectively. To the best of our knowledge, this is the first demonstration of simultaneous detection and quantification of the biomolecules by SERS. The practical applicability of this novel method was ascertained by the analysis with non-pretreated human urine.

A three-dimensional hot-volume plasmonic gold nanoreactor array (3D HPNRA) composed of gold nanodimples decorated with high-density gold nanoparticles on a 3D curved surface is developed for ultrasensitive immunoassays. The 3D HPNRA generates volumetric hotspots inside the 3D space, and a significant plasmonic coupling effect is created, forming an inclusion complex with probe gold nanoparticles (AuNP probes coated with a detection antibody (Ab). Due to multiple plasmonic coupling effects inside 3D spaces, the 3D HPNRA is utilized as an ultrasensitive SERS-based detection platform after functionalization of the 1st Ab for cardiac troponin I (cTnI), which is selected as a model antigen for immunoassay demonstration. After integration of the 3D HPNRA with a 3D-printed well plate, ELISA is performed using the AuNP probes, and a portable Raman instrument is subsequently used for quantitative immunoassays. As a result, the 3D HPNRA coupled with the AuNP probes showed similar to 400-fold enhanced sensitivities of 22.9 and 27.8 fg/mL for cTnI spiked in PBS and FBS, respectively, compared to conventional ELISA. The developed 3D HPNRA with the coupling of AuNP probes is expected to be applied for ultrasensitive immunoassays, especially for early disease diagnosis and the discovery of biomarkers that exist in an ultralow concentration range.

The sensitivity and limit-of-detection (LOD) of the traditional surface-enhanced Raman spectroscopy (SERS) platform suffer from the requirement of precise positioning of small analytes, including DNAs and bacteria, into narrow hotspots. In this study, a novel SERS sensor was developed using electrochemical deposition onto metal nanopillars (ECOMPs) combined with complementary DNAs (cDNAs) for the detection of pathogenic bacteria. Applying a redox potential to AuCl4- ions actively engineered the organometallic hotspots based on the cDNAs in a short time (<10 min) and simultaneously produced SERS signals. Because of the influence of potential-driven morphological properties on the SERS efficiency in the cDNA domains and the resonant coupling of internal fields with the fields confined between adjacent ECOMPs-cDNAs, the optimum growth time was determined to be 5 min. The EC-SERS detection and discrimination of Enterococcus faecium and Staphylococcus aureus were successfully carried out because of the DNA complementarity. Compared with plasmonic metal nanopillars (MPs)-cDNAs, the enhancement factor of the ECOMPs-cDNAs was estimated to be ∼2.0 × 103. A quantitative investigation revealed that a highly linear progression in the target DNA concentration range (0.05-100 nM) and a LOD of ∼0.035 nM were achieved. The specificity of the ECOMPs-cDNAs was validated by cross-hybridization. The platform was also used to assay human whole blood containing 0.1 nM bacterial DNAs. The proposed strategy provides the potential for highly sensitive SERS-based multiplex DNA detection in clinical diagnostics.

Plasmonic silver nanoparticles (AgNPs) arranged on polyimide (PI) nanopillars (AgNP/PI) were developed as a stable photothermal surface-enhanced Raman spectroscopy (SERS) platform. The AgNP/PI substrates were prepared via maskless plasma etching and metal deposition using an in situ vacuum sputtering system. The AgNP/ PI with high periodicity and high areal density led to high sensitivity, with a SERS enhancement factor (EF) of 2.2 x 10(8), and excellent reproducibility (relative standard deviation of 7.6%), as evaluated using the highprecision Raman mapping technique. To support the high SERS EF and sensitivity, the near-field enhancements of the dense AgNP array were calculated using a finite-difference time domain method. Notably, compared with AgNPs on polyethylene terephthalate (PET) nanopillar substrates, the AgNPs formed on the thermally stable PI nanopillar substrates exhibited excellent photothermal stability under illumination with a high-powered laser. The PI and PET surface changes induced by photoinduced local heating were investigated in terms of the glasstransition temperature, coefficient of thermal expansion, and thermal conductivity. The new plasmonic SERS platform has strong potential for reliable molecular detection in practical sensing applications with highpowered laser illuminations.