Somatic Copy Number Alterations Research Articles

Exploring the prognostic significance of arm-level copy number alterations in triple-negative breast cancer.

Somatic copy number alterations (SCNAs) are prevalent in cancer and play a significant role in both tumorigenesis and therapeutic resistance. While focal SCNAs have been extensively studied, the impact of larger arm-level SCNAs remains poorly understood. Here, we investigated the association between arm-level SCNAs and overall survival in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer lacking targeted therapies. We identified frequent arm-level SCNAs, including 21q gain and 7p gain, which correlated with poor overall survival in TNBC patients. Further, we identified the expression of specific genes within these SCNAs associated with survival. Notably, we found that the expression of RIPK4, a gene located on 21q, exhibited a strong correlation with poor overall survival. In functional assays, we demonstrated that targeting Ripk4 in a murine lung metastatic TNBC model significantly reduced tumor burden, improved survival, and increased CD4+ and CD8+ T cell infiltration. RIPK4 enhanced the survival of triple-negative breast cancer cells at secondary sites, thereby facilitating the formation of metastatic lesions. Our findings highlight the significance of arm-level SCNAs in breast cancer progression and identify RIPK4 as a putative driver of TNBC metastasis and immunosuppression.

TUBB, a robust biomarker with satisfying abilities in diagnosis, prognosis, and immune regulation via a comprehensive pan-cancer analysis

PurposeTUBB can encode a beta-tubulin protein. At present, the role of TUBB has not been ascertained in cancers. Hence, the importance of further systematic pan-cancer analyses is stressed to explore its value in the diagnosis, prognosis, and immune function of cancers.MethodsBy collecting and handling integrative data from the TCGA, Firehose, UCSC Xena, cBioPortal, GEO, CPTAC, TIMER2.0, TISCH, CellMiner, GDSC, and CTRP databases, we explored the potential diagnostic and prognostic roles of TUBB in pan-cancers from multiple angles. Moreover, the GSEA analysis was conducted to excavate the biological functions of TUBB in pan-cancers. In addition, survival profiles were described, and the differential expressions of TUBB in different molecular subtypes were discussed. Also, we utilized the cMAP function to search drugs or micro-molecules that have an impact on TUBB expressions.ResultsBased on the TCGA data, we found that TUBB was differentially expressed in a variety of tumors and showed an early-diagnostic value. Mutations, somatic copy number alterations, and DNA methylation would lead to its abnormal expression. TUBB expressions had relations with many clinical features. What’s more, TUBB expressions were validated to be related to many metabolism-related, metastasis-related, and immune-related pathways. High TUBB expressions were proved to have a great impact on the prognosis of various types of cancers and would affect the sensitivity of some drugs. We also demonstrated that the expression of TUBB was significantly correlated to immunoregulator molecules and biomarkers of lymphocyte subpopulation infiltration.ConclusionTUBB and its regulatory genes were systemically analyzed in this study, showing that TUBB had satisfying performances in disease diagnosing and prognosis predicting of multiple cancers. It could remodel the tumor microenvironment and play an integral role in guiding cancer therapies and forecasting responses to chemotherapy.

Abstract PO3-23-11: Multiomics analysis of ER+ breast cancer with matched primaries, lymph node metastases and recurrent cancers on adjuvant endocrine therapy

Abstract Background: 80% of all breast cancers (BCs) are ER-positive (ER+). A significant number develop endocrine therapy resistance (ETR) . Clones develop in lymph nodes (LNs) which differ from the primary and these are implicated in ETR. A multiomics analysis of primary ER+ breast cancers, matched LN metastasis (LN+), if present, and matched recurrences (primary, nodal or distant) has been performed. Patients and Methods: The patients included are: Cohort A: 95 patients with matched primary and recurrent ER+ BC on different endocrine therapies. 35% had involved LNs at diagnosis. Recurrences: local in 59/95, concurrent local and nodal in 33/95, LN-only in 3/95. Median time to recurrence 4.5 years. Cohort B: 18 patients with ER+ LN+ BC who developed multiple recurrences (local and/or nodal, >3 consecutive recurrences/patient) on different lines of sequential endocrine therapy. Cohort C: 7 patients with ER+ breast cancer with multiple involved LNs treated with 3-6 months of neoadjuvant ET before surgery. Biopsies of primary and matched LNs performed at diagnosis and throughout treatment (3-4 timepoints/patient). Clinical response by serial ultrasound. Primary and LN samples (mean 12 samples/patient) were analysed together with normal DNA. Targeted RNAseq and DNA exome sequencing and whole-genome expression analysis was performed. Somatic mutations and copy number alterations (CNA) were determined, and differential gene expression analysis was performed. Validation of pathways implicated in ETR was by spatial NanoString GeoMx. All patients have long term follow-up. Results: Cohort A: A mean of 6 potential driver mutations identified by DNA sequencing in each primary BC (range 1-16). Most commonly mutated genes were PIK3CA, TP53, ERBB4, MAP3K1 and ERBB3. Multiple aberrations and a highly diverse mutational landscape were observed in all recurrences. In the majority of recurrences significant changes in variant allele frequency (VAF) were identified across several ETR-implicated genes and in over 50% new gains/losses were identified. Most frequently, losses were seen in ERBB3, ARID1A, HRAS and FOXA1 with gains in CDH1, NF1, PIK3CA, ESR1, TBX3 and GATA3 in recurrences vs primaries. Transcriptomic analysis revealed differentially expressed pathways including ER, HER2, GATA3, AKT, RAS and p63 signalling. Integrated analysis revealed several driver mutations with corresponding changes in upstream pathway activity. 33 patients had concurrent local and nodal recurrences and 52% had similar somatic mutation profiles in both with only minor variance in VAF. In 48%, 1 or more new potential driver mutations was identified in axillary nodes compared to recurrent primary cancers with losses in AKT1, CDH1 and TP53 being most common. Multiomics profiling of Cohorts B and C is complete and analysis underway. Discussion: This multiomics study is the largest cohort to-date of matched early and recurrent ER+/HER2- cancers. It sheds new light on the complex somatic and transcriptomic changes in local and nodal recurrent disease. The mechanisms of ETR are diverse and underlying mechanisms and clinically meaningful biomarkers including potentially actionable mutations and targets have been identified. Cohort C will uniquely capture and compare clonal evolution of breast cancer in primary and multiple matched lymph during neoadjuvant ET. Citation Format: Carlos Martinez-Perez, Charlene Kay, Rebecca Swan, Lorna Renshaw, J Michael Dixon, Arran K Turnbull. Multiomics analysis of ER+ breast cancer with matched primaries, lymph node metastases and recurrent cancers on adjuvant endocrine therapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-23-11.

Abstract PO2-07-06: Multimodal learning predictor of HER2-positive breast cancer therapy response in the randomized PREDIX HER2 trial

Abstract Background: The PREDIX HER2 trial, compared six courses of docetaxel, trastuzumab, and pertuzumab (DTP) vs. trastuzumab emtansine (T-DM1) as neoadjuvant treatment for HER2-positive breast cancer (BC). Similar rates of pathologic complete response (pCR) were seen. Methods: Clinicopathological, shallow whole-genome sequencing (CUTseq, n=176), whole exome sequencing (WES, n=192), and RNA-sequencing (RNA-seq, n=187) data were generated using fresh-frozen baseline core biopsies. Potential tumor intrinsic resistance factors and microenvironment components were quantified by multi-omics analysis, including BC-specific somatic mutations and copy number alterations (CNA), COSMIC mutational signatures, CNA-based chromosomal instability signatures (CIN), subclone percentage, PAM50 subtype, GGI/PIK3CA score, HER2DX score, immune profiles (Danaher signature score, TIDE score and immune repertoires). We assessed the association of biomarkers with pCR in each treatment arm using logistic regression adjusting for hormone receptor (HR) status, and evaluated their predictive value by adding the interaction term (biomarker x treatment arm). In addition, a machine learning (ML) analysis was conducted from different classifiers, comprising unimodal ML-based models from clinical, RNA and DNA information, respectively. Model performance was assessed using the mean and standard deviation (mean ± std) of the area under receiver operator characteristic curve (AUC), positive predictive value (PPV) and negative predictive value (NPV) using a nested stratified cross-validation (CV) schema of 200 outer shuffle splits and 100 inner 5-fold CV to mitigate potential risk of overfitting. Results: In DTP arm, patients with higher ERBB2 copy ratio (ORadj=1.98, p=0.004) or mRNA (ORadj=3.08, p< 0.001) or HER2-enriched subtype (PAM50) (ORadj=1.78, p=0.02) had higher pCR rates, while ESR1 gene expression (ORadj=0.59, p=0.07) predicted treatment resistance despite adjustment for HR status. Conversely, response to T-DM1 was less likely to depend on ERBB2 profiles and only PAM50 HER2 enriched subtype (ORadj=1.53, p=0.1) showed higher pCR rate (52% vs. 25%) than other subtypes. Both ESR1 (ORadj=0.4, p=0.008) and PGR (ORadj=0.5, p=0.03) gene expression were independent predictors of T-DM1 resistance. Pre-treatment immune exclusion metrics could predict resistance to DTP (endothelial cell, ORadj=0.67, p=0.07) and T-DM1 (neutrophils, ORadj=0.54, p=0.02; mast cells, ORadj=0.57, p=0.02; cancer-associated fibroblasts, ORadj=0.67, p=0.09)), respectively. Predefined metrics such as PIK3CA signature score (ORadj =1.67, p=0.04) and Taxane response score (ORadj =1.64, p=0.03) were positively related to pCR in DTP arm. Genome instability, involving CIN CX2 signature (impaired homologous recombination) (ORadj=1.71, p=0.05), COSMIC signature6 (ORadj =1.53, p=0.07) and signature13 (ORadj =1.57, p=0.05), predicted benefit from DTP. The biomarker-treatment interaction tests were significant for HER2DX (pinteraction=0.004) and COSMIC signature15 (defective DNA mismatch repair) (pinteraction=0.007): lower HERDX score (ORadj =0.73, p=0.14) or higher COSMIC signature15 score (ORadj =1.51, p=0.1) could identify patients benefiting from T-DM1, while being resistant to DTP (HERDX: ORadj =1.46, p=0.13; signature15: ORadj =0.70, p=0.1). In the ML models, clinical information yielded an AUC=0.62±0.07, PPV=0.64±0.12 and NPV=0.64±0.06; for DNA data, AUC was equal to 0.70±0.08, PPV=0.72±0.09 and NPV=0.71±0.07; an adaptive boosting ensemble learning on RNA reported slightly increased pCR prediction performance (AUC=0.72±0.06, PPV=0.64±0.06, NPV=0.80±0.09). Conclusion: This study demonstrates that antibody–drug conjugates and standard treatment harbor strikingly distinctive biomarkers across tumor ecosystem. Further external validation and integrated ML model comprising all unimodal models are ongoing. Citation Format: Kang Wang, Yajing Zhu, Ioannis Zerdes, Emmanouil Sifakis, Georgios Manikis, Dimitrios Salgkamis, Nikolaos Tsiknakis, Luuk Harbers, Nicola Crosetto, Jonas Bergh, Alexios Matikas, Thomas Hatschek, Theodoros Foukakis. Multimodal learning predictor of HER2-positive breast cancer therapy response in the randomized PREDIX HER2 trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-07-06.

Abstract PO1-15-11: Molecular and clinical disparities in breast cancer among East Asian populations

Abstract Background Breast Cancer (BC) is a complex disease with profound genomic aberrations. However, the underlying molecular disparity influenced by age and ethnicity remains elusive. Method We aimed to investigate the molecular properties of 843 primary and metastatic BC patients enrolled in the K-MASTER program. We explored the unique molecular profiles of breast cancer patients by categorizing them into two distinct age subgroups. The first subgroup comprised young breast cancer (YBC) patients, defined as women under the age of 40, while the second subgroup consisted of older breast cancer (OBC) patients. Our study aimed to characterize the molecular differences between these age-defined groups, providing insights into the underlying mechanisms of breast cancer in different age cohorts. Additionally, we leveraged large-scale genomic data from the TCGA and MSK-IMPACT studies to examine the ethnic-driven molecular and clinical disparities. Results The K-MASTER patients were mainly comprised of triple-negative breast cancer (TNBC) and HER2-positive tumors, while the TCGA and MSK-IMPACT cohorts exhibited a predominance of hormone receptor-positive (HR+) subtype. We observed a high prevalence of PI3KCA mutations in K-MASTER HER2+ tumors, particularly in older patients. Moreover, we identified increased mutation rates in DNA damage response molecules, including ARID1A, MSH6, and MLH1. Importantly, GATA3 mutations were less frequently observed in East Asian patients, which correlated with poor clinical outcomes. Our analysis also revealed specific associations between genomic aberrations, organotropisms, and metastatic breast cancer. In addition to characterizing the molecular disparities, we developed a gradient-boosting multivariable model to identify a new molecular signature that could predict the therapeutic response to platinum-based chemotherapy. Conclusion Our findings collectively provide unprecedented insights into the significance of age and ethnicity on the molecular and clinical characteristics of BC patients. Figure 1. Genomic landscape of KM BRCA. (A) Overall characteristic of KM BRCA sample and clinical data. Clinical features of KM BRCA sample. (B) Genomic landscape of somatic mutations and copy number alterations of BRCA by age group. Figure 2. Genomic landscape of KM BRCA: Significantly mutated genes by age group in KM BRCA. Figure 3. Survival Curve Utilizing a curated Gene Set Developed by a Gradient-Boosting Multivariable Model (A) OS of platinum-based therapy treated KM with curated Gene set. (B) OS of platinum-based therapy treated MSK with curated Gene set. Citation Format: Kim Ju Won, LEE JIWON, Kyong Hwa Park, Seung Pil Jung, Jason Sa, SHIN SANG WON, An Jung Seok. Molecular and clinical disparities in breast cancer among East Asian populations [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-11.

High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue

Somatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we perform multi-region, single-cell DNA sequencing to characterize the SCNA landscape across tumor-rich and normal tissue in two male patients with localized prostate cancer. We identify two distinct karyotypes: ‘pseudo-diploid’ cells harboring few SCNAs and highly aneuploid cells. Pseudo-diploid cells form numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones. In contrast, aneuploid cells do not form subclones and are detected throughout the prostate, including normal tissue regions. Highly localized pseudo-diploid subclones are confined within tumor-rich regions and carry deletions in multiple tumor-suppressor genes. Our study reveals that SCNAs are widespread in normal and tumor regions across the prostate in localized prostate cancer patients and suggests that a subset of pseudo-diploid cells drive tumorigenesis in the aging prostate.

Abstract LB206: The progression of chromosomal instability and aberrant DNA methylation during colorectal cancer development

Abstract Chromosomal instability (CIN) and aberrant DNA methylation play a pivotal role in the pathogenesis of colorectal cancer (CRC). Mapping both of these cancer hallmarks during the progression of the disease can help identify potential targets for pharmacological intervention and improve the management of CRC metastasis. In a set of 27 patients diagnosed with either high-grade colorectal adenoma or advanced metastatic CRC disease, high-throughput DNA methylation and/or DNA somatic copy number alterations (SCNAs) analyses were performed. Global genome methylation profiles and the most frequent hot-spot regions harboring SCNAs, identified in the patients' DNA, were verified in a validation set of eight CRC patients through whole-exome sequencing, genome-wide DNA methylation measurement, and gene expression profiling.The study is currently ongoing; however, a panel of 29 cancer-relevant genes, amplified in more than 50% of investigated adenoma tissues (such as PTK6, SRC, MALAT1, BRCA2), was identified. Chromosomal loci amplified in primary tumors were highly concordant with those in liver metastases. An increase in CIN was detected in all metastases, representing mostly gains of Chr7q, 8q, 13q, 20q, and the small arm of ChrX, while the lost chromosomal loci included Chr8p, 17p, and the entire Chr18. A gain unique to metastases was located on Chr6 (p25.1-p22.3), encoding the oncogene DEK. All metastases exhibited an increase in hypomethylated and a decrease in hypermethylated CpGs. The gene enrichment analysis of the differently methylated gene promoters showed the olfactory receptors pathway as the most frequently represented (FDR-adjusted P value=1.06E-8), with all the identified promoters (n=120) less methylated in metastases. Taken together, several genomic hot-spot regions with SCNAs, possibly important during the development of adenoma and also during the metastatic process, were identified. Furthermore, a decrease in methylation within promoters of odorant receptors was the most prominent epigenetic alteration occurring in our set of metastases. The study was funded by the Ministry of Health of the Czech Republic (NU22J-03-00028) and GACR 21-27902S. Citation Format: Katerina Saskova, Mattias Landfors, Josef Horak, Katerina Honkova, Kristyna Tomasova, Jana Drabova, Fernanda Schäfer Hackenhaar, Jitka Pavlikova, Ludmila Vodickova, Torbjörn Nilsson, Sanja Farkas, Veronika Vymetalkova, Pavel Vodicka, Sofie Degerman, Michal Kroupa. The progression of chromosomal instability and aberrant DNA methylation during colorectal cancer development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB206.

Abstract LB286: Extrachromosomal DNA in lung cancer from never smokers

Abstract Extrachromosomal DNA (ecDNA), circular DNA that resides outside of the linear chromosome, is a potent form of oncogene amplification in cancer. The structure and properties of ecDNA are markedly different from those of linear DNA, characterized by features like non-Mendelian inheritance and an altered epigenetic landscape. A prior pan-cancer analysis ​​indicated patients with cancers harboring ecDNA have statistically worse overall survival when compared to cancer patients with other types of focal amplification. Moreover, its unique characteristics also make it a promising target for therapy. Recently, efforts have intensified to profile ecDNA across many cancer types, yet comprehensive studies of ecDNA in lung cancer in never smokers (LCINS) is lacking. Given that LCINS is partially driven by somatic copy number alterations, we hypothesized that ecDNA-driven focal amplifications significantly influence LCINS tumor evolution. As part of the Sherlock-Lung project (current data freeze, 1217 samples), we comprehensively profiled 871 treatment-naive samples using a robust computational pipeline that refined copy number segmentation by accounting for tumor purity and ploidy. ecDNA was present in 151 (17.3%) of tumor samples, with a third of ecDNA-positive samples harboring more than one distinct ecDNA amplicon. Consistent with prior reports, no ecDNA was found in bulk sequenced blood or matched normal lung tissues. These ecDNA often included genes (84%), frequently overlapping with known oncogenes like MDM2, TERT, and MYC, which showed higher expression levels compared to non-amplified or other amplified genes. Notably, most MDM2 amplifications (36/45) were on ecDNA. ecDNA was significantly associated with whole genome doubling, tumor stage, and several endogenous mutational signatures, including APOBEC (SBS2 and SBS13), and clock-like signature (SBS1). Intriguingly, ecDNA-positive tumors were associated with significantly worse survival compared to tumors without any focal amplifications, though tumors with other amplification types (e.g. breakage-fusion-bridge, linear amplification, or complex events) had similar survival impacts. The unprecedented size of our cohort and the integration of clinical, epidemiologic, and multi-omics data allowed us to perform the first in-depth characterization of ecDNA in LCINS. We reconstructed the genomic regions involved in ecDNA and revealed the full spectrum of simple and complex ecDNAs across cancer histologies as well as the clinical and functional impact of ecDNA on LCINS. Citation Format: Azhar Khandekar, Tongwu Zhang, Marcos Diaz-Gay, Jens Luebeck, Ludmil Alexandrov, Maria Landi. Extrachromosomal DNA in lung cancer from never smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB286.

Abstract LB336: The African Cancer Atlas: Leveraging African data to diversify precision oncology

Abstract Africa has some of the highest age adjusted cancer mortality rates globally and cancer incidence in Africa is expected to double by 2040. Despite this disproportionate burden of disease, African cancer patients are woefully understudied along the cancer continuum. People of African descent are significantly underrepresented in cancer research, accounting for less than 3% of globally available genomic data and are often the least well served by advances in precision medicine.To address this gap, we have initiated the African Cancer Atlas project. This is an Africa-centred approach to overcoming cancer inequities - providing much needed biological and clinical data, but also seeking to identify and address the social determinants of inequities both within the continent and between high and low-middle income countries (LMIC). We have established an oncology partner network across 9 geographically dispersed African countries (Senegal, Côte d’Ivoire, Ghana, Nigeria, Kenya, Uganda, Zimbabwe, South Africa, and Tunisia). We have developed LMIC-specific standardised protocols and best practices for sample collection and processing across multiple sites and continue to build a well-annotated bank of tissue, plasma, bone marrow and PBMC from individuals with breast, prostate, gastrointestinal cancers, liver, urinogenital and pediatric cancers that will be unrivalled in its diversity. So far, 1800 cancer samples have been collected and banked. We have also built a unique cloud-based clinical data management platform to facilitate the collection of longitudinal clinical metadata into a unified clinico-demographic database. We have initiated extensive genomic and molecular profiling of African-specific cancers using whole exome/genome sequencing (WES/WGS) of paired germline and tumour samples as well as RNA- sequencing of tumors. We have so far completed the first 200 WES, representing the first cancer samples sequenced entirely on the African continent. Ongoing work is investigating how population-specific genetic variation contributes to cancer risk, identifying driver mutations, somatic copy number alterations (SCNAs) and mutational signatures that can point to disease-relevant environmental exposures or impaired core biological pathways. Comparative analysis with existing cancer genomics cohorts will determine the prevalence of known hotspot mutations, cancer drivers and or common SCNAs in African cancer genomes. By comparing with available data for African Americans and other diasporan Africans, we will provide better understanding of cancer aetiology related to African ancestry applicable to the broader African diasporic communities in other regions of the world. We are also collecting data to assess socio-economic and health system factors affecting access to cancer care and survival across all study sites. Socio-demographic data collection is integrated with tissue/biodata collection creating digital longitudinal hospital-based cohorts. We will develop systems that integrate genomics, molecular demographics and clinical data with machine learning and a publicly accessible portal for data access and analytics will be available for the broader scientific community. Ultimately, this project will contribute towards better understanding of cancer among people of African descent and make precision oncology more effective for diverse populations. Citation Format: Yaw Bediako, Joyce Ngoi, Ruth Kiome, Seth Agyemang, Stephen Darkoh, Audrey Lemacon, Aida Manu, Frank Onyambu, Kanny Diallo, Lily Paemka, David Hutchful, Emmanuella Amoako, Abdoulaye Diallo. The African Cancer Atlas: Leveraging African data to diversify precision oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB336.

Abstract LB097: Sensitive detection of central nervous system tumors using a sequencing based cerebrospinal fluid test

Abstract The current approach to diagnosing and monitoring tumors of the central nervous system relies almost exclusively on radiographic imaging and neurosurgical procedures. Cerebrospinal fluid (CSF) is appealing for diagnosis because it is already part of the standard of care for the diagnosis or management of several types of CNS disease, including cancer, and the tumor DNA is more highly concentrated inside the blood brain barrier than in plasma or other bodily fluids. Even though cytology is widely used, sensitivity remains low ranging from 2% to 50%, depending on cancer type. We report an analytic technique that efficiently introduces identical molecular barcodes to both strands of CSF template DNA molecules for the identification of cancer specific somatic mutations and copy number alterations. We apply this approach to 126 CSF samples obtained from individuals with known primary or metastatic tumors involving the brain and 36 CSF samples obtained from individuals with non-neoplastic neurological conditions such as multiple sclerosis and another neurologic conditions. We correctly detect 91% of cancers at a specificity of 94.5%. In cases (n=20) where standard of care cytology was available, cytology detected 25% of cancers while our molecular assay detected 90%. Our approach has the capacity to be used in combination with other clinical, radiologic, and laboratory-based data to inform the diagnosis and management of patients with suspected cancers of the brain. Positives n= Sensitivity GBM 42 46 91.3% Lymphoma 22 24 91.7% Medulloblastoma 14 16 87.5% Metastases 37 40 92.5% Citation Format: Christopher B. Douville, Chetan Bettegowda. Sensitive detection of central nervous system tumors using a sequencing based cerebrospinal fluid test [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB097.

Systematic analysis of cuproptosis abnormalities and functional significance in cancer.

Cuproptosis is a recently discovered type of cell death, but the role and behavior of cuproptosis-related genes (CuRGs) in cancers remain unclear. This paper aims to address these issues by analyzing the multi-omics characteristics of cancer-related genes (CuRGs) across various types of cancer. To investigate the impact of somatic copy number alterations (SCNA) and DNA methylation on CRG expression, we will analyze the correlation between these factors. We developed a cuproptosis index (CPI) model to measure the level of cuproptosis and investigate its functional roles. Using this model, we assessed the clinical prognosis of colorectal cancer patients and analyzed genetic changes and immune infiltration features in different CPI levels. The study's findings indicate that the majority of cancer-related genes (CuRGs) were suppressed in tumors and had a positive correlation with somatic copy number alterations (SCNA), while having a negative correlation with DNA methylation. This suggests that both SCNA and DNA methylation have an impact on the expression of CuRGs. The CPI model is a reliable predictor of survival outcomes in patients with colorectal cancer and can serve as an independent prognostic factor. Patients with a higher CPI have a worse prognosis. We conducted a deeper analysis of the genetic alterations and immune infiltration patterns in both CPI positive and negative groups. Our findings revealed significant differences, indicating that CuRGs may play a crucial role in tumor immunity mechanisms. Additionally, we have noticed a positive correlation between CuRGs and various crucial pathways that are linked to the occurrence, progression, and metastasis of tumors. Overall, our study systematically analyzes cuproptosis and its regulatory genes, emphasizing the potential of using cuproptosis as a basis for cancer therapy.

Not Only RET but NF1 and Chromosomal Instability Are Seen in Young Patients with Sporadic Medullary Thyroid Carcinoma.

Genetic analysis of sporadic medullary thyroid carcinoma (MTC) has revealed somatic variants in RET, RAS, and occasionally other genes. However, around 20% of patients with sporadic MTC lack a known genetic driver. To uncover potential new somatic or germline drivers, we analyze a distinct cohort of patients with sporadic, very early-onset, and aggressive MTC. Germline and somatic DNA exome sequencing was performed in 19 patients, previously tested negative for germline RET variants. Exome sequencing of 19 germline samples confirmed the absence of RET and identified an NF1 pathogenic variant in 1 patient. Somatic sequencing was successful in 15 tumors revealing RET variants in 80%, predominantly p.Met918Thr, which was associated with disease aggressiveness. In RET-negative tumors, pathogenic variants were found in HRAS and NF1. The NF1 germline and somatic variants were observed in a patient without a prior clinical diagnosis of neurofibromatosis type 1, demonstrating that the loss of heterozygosity of NF1 functions as a potential MTC driver. Somatic copy number alterations analysis revealed chromosomal alterations in 53.3% of tumors, predominantly in RET-positive cases, with losses in chromosomes 9 and 22 being the most prevalent. This study reveals that within a cohort of early-onset nonhereditary MTC, RET remains the major driver gene. In RET-negative tumors, NF1 and RAS are drivers of sporadic MTC. In addition, in young patients without a RET germline mutation, a careful clinical evaluation with a consideration of germline NF1 gene analysis is ideal to exclude Neurofibromatosis type 1 (NF1).

Abstract 6941: Transcriptomic effects of retinoblastoma progression-related somatic copy number alteration (SCNA)

Abstract Retinoblastoma is a pediatric retinal cancer that initiates in response to biallelic RB1 loss or MYCN amplification in a cone precursor cell of origin. After initial emergence, RB1-/- retinoblastomas progress to more aggressive forms by accumulation of single nucleotide variants (SNVs) and highly recurrent somatic copy number alterations including 1q+, 2p+, 6p+ and 16q- (RB SCNAs), resulting in heterogeneous mixtures of subclonal cell populations. SCNAs are enriched in highly evolved and aggressive tumor subtypes and show prognostic value in retinoblastoma liquid biopsies. However, the transcriptomic effects of retinoblastoma SCNAs are poorly understood. Single cell methods may enable comparison of tumor subclones within emerging retinoblastoma tumors and thereby provide insight into tumor progression. We retrieved single cell RNA sequencing data for 25 retinoblastoma tumors and inferred SCNAs and subclone phylogenies from scRNAseq information using a recently published tool, Numbat. We identified tumors with clonal variation in RB SCNAs and excluded samples with poor transcriptome quality or excessive additional SCNAs. We proceeded with analysis of 11 tumors with subclonal heterogeneity for an SCNA of interest, including 10 with 1q+, eight with 2p+, four with 6p+, and six with 16q-. After removal of nontumor cells, we defined cell clusters, cluster marker genes, and cell cycle phase gene signatures, and we compared cell state distributions for subclones with an acquired SCNA relative to their immediate antecedents. These analyses revealed recurrently discriminated transcriptomic clusters corresponding to six discrete cell cycle states (post-mitotic G1, G1, G1/S, S, S/G2, G2/M) and variable cell stress states, including a cluster with hypoxia and heat shock related marker gene expression in all samples. In each tumor, SCNA-defined tumor subclones had a distinct cell state distribution. Tumor subclones with acquired 1q+ were enriched in G2 states and depleted in G1 states. Subclones with 2p+ were enriched in G2 states. Subclones with 6p+ were enriched in S phase states. Subclones with 16q- were diminished in post-mitotic cell states. Tumor clones with 1q+ and 16q- were most strongly enriched for G2 phase cells. Such 1q+/16q- tumor cells were significantly differentially distributed in three tumor replicates. Tumor clones with other RB SCNAs were enriched over diploid clones in proliferating G2 cells without SCNA specific effects. To identify candidate drivers of SCNA-specific transcriptomic effects we measured RB SCNA clonal variation in gene expression within and across transcriptomic states. We identified recurrently differentially expressed in-segment genes in 1q+, 2p+, 6p+, and 16q-, as well as out-of-segment genes. Finally, we propose molecular mechanisms underlying SCNA recurrence that may enable tumor evolution in retinoblastoma. Citation Format: Kevin Stachelek, David E. Cobrinik. Transcriptomic effects of retinoblastoma progression-related somatic copy number alteration (SCNA) [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 6941.

Abstract 1200: A novel algorithm for deconvolving cancer allele-specific clone copy number and copy number evolution

Abstract Both single nucleotide variants (SNVs) and somatic copy number alterations (SCNAs) accumulate in cancer cells during tumor development, fuelling clonal evolution. However, accurate inference of their coevolution from bulk DNA sequencing is challenging. We present ALPACA (ALlele-specific Phylogenetic Analysis of clone Copy number Alterations), a novel algorithm to allow the practical inference of SNV and SCNA coevolution. ALPACA is framed as an optimisation problem, that takes as input bulk tumor sample copy number mixtures and the tumor phylogenetic tree constructed from SNVs, and deconvolves the optimal, allele-specific integer copy number profiles for every distinct clone present in the tumor. To circumvent the challenge of joint SNV/SCNA inference, we postulate that in high mutation burden tumors all relevant SCNA clones are identifiable by their unique SNVs, hence ALPACA leverages phylogenetic trees constructed from bulk tumor sequencing data using SNVs. Secondly, to restrict the clone-specific copy number search space, ALPACA leverages constraints imposed by multisample sequencing, specifically in cases where clones are present across multiple samples or clones from different samples are phylogenetically related. Finally, ALPACA relies on parsimony and biologically informed constraints to further guide the deconvolution process. We demonstrate that ALPACA infers the copy number evolution of complex simulated tumors with higher accuracy than current state-of-the-art methods. We apply ALPACA to the large, multisample non-small cell lung cancer (NSCLC) cohort from the recent longitudinal, prospective TRACERx421 study, and show that ALPACA uncovers loss of heterozygosity and amplification events in minor subclones that were previously missed using standard approaches. ALPACA's assignment of SCNA driver events to branches of the phylogenetic tree reveals the evolutionary ordering of SNVs and SCNAs during NSCLC tumor evolution, such as late focal amplifications affecting the TERT gene locus occurring in subclones which expand and dominate a tumor sample. ALPACA enables an in-depth analysis of the coevolution of mutations and SCNAs in the tumor’s evolutionary history, revealing distinct patterns of copy number evolution. Notably, ALPACA identifies common patterns of copy number changes across the genome characterizing metastatic seeding clones, revealing that they harbor an increased number of SCNAs compared to clones that do not metastasize. Additionally, ALPACA uncovers subclonal enrichment for CCND1 amplification in primary tumor subclones that seed metastasis, and an overall increase of SCNA events occurring in both tumors with polyclonal seeding and extrathoracic metastases. Clone-level results obtained with ALPACA can offer new clinical insights and enable new types of analysis, e.g. copy number signature analysis including temporal order of SCNA acquisition. Citation Format: Piotr Pawlik, Kristiana K. Grigoriadis, Abigail Bunkum, Simone Zaccaria, Nicholas McGranahan, Charles Swanton. A novel algorithm for deconvolving cancer allele-specific clone copy number and copy number evolution [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 1200.

Abstract 2268: CREDAC: Copy number-based reference-free expression deconvolution analysis of cancers

Abstract Introduction: Analyses of bulk RNA sequencing data are central to most large-scale tumor sequencing studies. Bulk expression data represent population averages and its interpretation is confounded by both normal cell contamination and somatic copy number alterations. Several computational methods to deconvolve have been developed recently. However, these methods often rely on a set of cell-type-specific reference signatures and ignore the effect of copy number changes. Methods: To address these issues, we have developed a method that formalizes the relationship between allele-specific copy number, expression and sample purity to deconvolve the expression profiles of tumor and normal cells from bulk RNA-seq in an unbiased manner. Our method was applied to sequencing data produced by the TRACERx consortium, a longitudinal study with multi-region whole-exome and RNA-seq of non-small-cell lung cancers. A total of 414 primary tumor regions and 140 adjacent normal tissue samples from 140 patients with matched DNA and RNA-seq data were processed. Results: We were able to directly deconvolve a median of ~2,000 genes per sample and indirectly infer tumor and normal expression profiles of ~10,000 genes using an scaled and weighted mean approach. The accuracy of the deconvolution was validated using (1) in-silico mixtures of patient-derived tumor and normal cells, (2) pseudo-bulk scRNAseq and (3) in regions with loss of heterogeneity (LOH) directly on the bulk sequencing data, where the total fraction of expression attributed to tumor cells can be computed directly using somatic mutations. CREDAC allows for single sample bulk-level tumor-normal differential expression analysis and revealed a strong and constitutive genome-wide overexpression in cancer compared to admixed normal cells, with a more pronounced overexpression in lung squamous cell carcinoma than lung adenocarcinoma (p<0.001). CREDAC adjusts for variations in copy number, thus facilitating the investigation of cancer-specific dosage compensatory responses triggered by aneuploidy. We revealed that a majority of genes (~65%) exhibit proportionality to copy number alterations, while a substantial proportion (~35%) shows anti-scaling or dosage compensation strategies. We show an enrichment of genes involved in cell cycle and expression processes within the dosage compensated group and revealed methylation as a key mechanism driving this compensatory process. Conclusion: Overall, our results suggest that CREDAC is able to accurately disentangle the expression of tumor and normal cells from bulk RNA-seq without any previous knowledge. It has potential applications in many studies that include matched RNA-seq and copy number data and can provide new insights functional characterization, the taxonomy of cancer, and tumor evolution. Citation Format: Carla Castignani, Jonas Demeulemeester, Oriol Pich, Tom Lesluyes, Robert E. Hynds, David R. Pearce, Elizabeth Larose Cadieux, Stefan C. Dentro, TRACERx Consortium, Nnenna Kanu, Charles Swanton, Peter Van Loo. CREDAC: Copy number-based reference-free expression deconvolution analysis of cancers [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 2268.

Abstract 401: The impact of DNA structural variants on PRKN gene function and colorectal cancer pathogenesis

Abstract Background: Cancer is caused by somatic DNA alterations, such as single nucleotide variants, somatic copy number alterations and structural variants (SVs). PRKN is among the genes most frequently affected by SVs in colorectal cancer (CRC), with 37% of primary cancers and 56% of metastatic lesions having focal deletions in PRKN. PRKN encodes the E3 ubiquitin ligase Parkin, which regulates the biological activity and degradation of substrates via post-translational modifications. The genomic location of PRKN is within a common fragile site. Therefore, it remains unclear whether the high frequency of SVs in PRKN are passenger events due to genomic instability or driver events of CRC pathogenesis. Aim: Our study aims to investigate the impact of SVs on the functionality of Parkin in CRC pathogenesis. Methods: We used publicly available DNA deep whole genome sequencing (WGS) and tumor-matched RNA sequencing data (n=394) to estimate the impact of SVs in PRKN on tumor biology. For this, the transcriptome-wide p-value distribution generated by differential expression analysis was used as a measure of biological impact. The HCT116-MLH1-repaired cell line and patient-derived adenoma organoids were genetically modified using CRISPR/Cas9 to mimic the SVs observed in patient material and analyze their impact. RNA-sequencing, whole proteome and ubiquitin remnant-specific proteomics were used to assess the effect of SVs on gene function and identify altered biological processes. Results: Analysis of WGS and RNA sequencing of patient material showed that SVs in PRKN have a large impact on CRC biology, comparable to the impact of mutations in TP53 (impact score 0.379 vs 0.332). The most pronounced effects are seen in the ubiquitin-like, RING0 and RING1 domains. These domains are important for recognition and/or binding to ubiquitin, E2 ubiquitin-conjugating enzymes and substrates. In the HCT116-MLH1-repaired CRC cell line, hemizygous introduction of an SV in PRKN had minimal effects on genome-wide gene expression. In contrast, homozygous deletion altered the expression of nearly 2000 genes. Analyses of ubiquitin motif remnants showed differential ubiquitination of proteins involved in DNA repair following the introduction of an SV in PRKN in the CRC cell line. These proteins include TOP2A (Log2 fold change (L2FC) = -3.69, P = 5.71−5), RAD18 (L2FC = -4.55, P = 1.35−4) and Spartan (SPRTN; L2FC = -2.57, P = 7.43−4). Conclusion: SVs in PRKN have a high impact on tumor biology and result in aberrant gene expression and post-translational modifications of proteins related to DNA repair. Further research will expand to the patient-derived adenoma organoids and focus on understanding if these recurrent somatic alterations contribute to genomic instability and the development of CRC pathogenesis. Citation Format: Elisabeth J. van Bree, Soufyan Lakbir, Carmen Rubio-Alarcón, Renske de Wit, Anne Bolijn, Pien Delis-van Diemen, Marianne Tijssen, Ellen Stelloo, Harma Feitsma, Gerrit A. Meijer, Beatriz Carvalho, Sanne Abeln, Remond J. Fijneman. The impact of DNA structural variants on PRKN gene function and colorectal cancer pathogenesis [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 401.

Abstract 869: Single-cell DNA replication dynamics in genomically unstable cancers

Abstract Background: DNA replication and cell cycle regulation are frequently disrupted as part of a cancer’s progression toward uncontrolled proliferation, generating somatic copy number alterations (CNAs) and producing intratumoral heterogeneity that drives subsequent evolution. Structural variation and CNAs have been shown to impact epigenetic and chromatin states, but our ability to assess their impact on DNA replication timing (RT) and cell proliferation rates remains limited. Single-cell whole genome sequencing (scWGS) is a powerful method for studying clonal heterogeneity and CNAs, and has the potential to provide greater insight into DNA replication dynamics in aneuploid populations. However, computational identification of S-phase cells and distinguishing inherited somatic CNAs from transient DNA replication changes remain challenging. Methods: We present a new method, PERT, which uses a Bayesian framework to model read depth as a combination of somatic copy number, replication, and sequencing bias, enabling estimation of DNA replication profiles and cell cycle phase from scWGS data. Unlike previous approaches, PERT provides unbiased estimates of RT and cell cycle phase which allows for analysis of previously uncharacterized cell types using any scWGS platform. These unique properties enable PERT to perform novel analysis such as estimating clone-specific proliferation rates and studying the interplay between RT and somatic CNAs during tumor evolution. We applied PERT to a cohort of >50,000 scWGS cells obtained from a collection of genomically unstable breast and ovarian cell lines, xenografts and primary cancer tissues. Results: Clone RT profiles correlated with future copy number changes in serially passaged cell lines. Cell type was the strongest determinant of RT heterogeneity, while whole genome doubling (WGD) and mutational signature had weaker RT associations but were associated with accumulation of late S-phase cells. Recurrent CNAs affecting chromosome X had striking impact on RT, with loss of the inactive X allele shifting replication earlier, and loss of inactive Xq resulting in reactivation of Xp. Analysis of time series xenografts illustrated that cell cycle distributions approximate clone proliferation. This relationship enabled us to observe that highly proliferative clones were the most chemosensitive in cisplatin-treated xenografts and, separately, present novel evidence that WGD leads to slower proliferation. Conclusions: Our analysis implicates cell type as the strongest determinant of RT with chrX being the locus of highest RT variation due to X-inactivation. Separately, quantification of S-phase cells enables interrogation of the on- and off-treatment fitness of genetically distinct subclones. This work leads to better understanding of how DNA replication dynamics drive and are further modulated by genomic instability. Citation Format: Adam C. Weiner, Marc Williams, Hongyu Shi, Ignacio Vazquez-Garcia, Sohrab Salehi, Nicole Rusk, Sohrab P. Shah, Andrew McPherson. Single-cell DNA replication dynamics in genomically unstable cancers [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 869.

Abstract 2423: Linking liquids: cfDNA in urine and plasma as informative allies in metastasized prostate cancer

Abstract Background: Liquid biopsy has become a cornerstone of non-invasive cancer diagnostics. While the major analyte for detecting and monitoring tumors has been blood, examining other body fluids, such as urine or saliva, is increasingly shifting into focus. Urine is a particularly valuable specimen due to its easy accessibility. Particularly in urologic cancers, the sensitivity of liquid biopsy could be improved by proximal sampling. While there is already evidence that cell-free DNA from urine (ucfDNA) can add to the diagnostic sensitivity in renal and bladder cancer, less is known about ucfDNA in prostate cancer patients. In this study, we aimed to determine the presence, levels, and potential clinical applications of ucfDNA in patients with metastatic prostate cancer. Moreover, we compared the findings with information obtained from plasma cell-free DNA (cfDNA). Methods: Urine was collected and stabilized using the PAXgene Urine Liquid Biopsy Set or STRECK as a preservative. The collection and stabilization using PAXgene Urine Liquid Biopsy Set allows a standardized collection and stabilization of urine with fixed volumes of urine and preservatives. Blood was collected in PAXgene Blood ccfDNA Tubes (PreAnalytiX). Matched blood and urine cfDNA samples from 122 metastatic prostate cancer patients were isolated using the QIAsymphony platform. Tumor fraction and presence of somatic copy number alterations (SCNA) were assessed from shallow whole genome sequencing data using the ichorCNA algorithm. Results: In 22/122 (18%) of patients SCNAs could be detected in both, urine and blood. Although the copy number profile was highly concordant in those patients, tumor fractions varied between plasma and urines on an individual patient level. In addition, in 52/122 (43%) and 48/122 (39%) patients, tumor-derived DNA was detected only in plasma or urine. Considering the entire cohort, neither the absolute cfDNA concentration nor tumor fraction did significantly differ between urine and plasma samples. Conclusion: Our data demonstrate that ucfDNA can provide complementary information to blood about prostate tumors, which would be missed by the sole analysis of plasma cfDNA. Taking this into account and adding that urine represents a non-invasive specimen type that can be collected at great ease, ucfDNA holds promise in the clinical management of prostate cancer. Citation Format: Tina Moser, Anna Eberhard, Matthias J. Moser, Lisa Glawitsch, Sabrina Hammer, Georgios Vlachos, Isaac Lazzeri, Leandra Ziegler, Emil Bauernhofer, Nina Monsberger, Jochen B. Geigl, Thomas Bauernhofer, Ellen Heitzer. Linking liquids: cfDNA in urine and plasma as informative allies in metastasized prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2423.

Abstract 1762: Characterization of somatic copy number deletion of chromosome 22q in papillary thyroid carcinoma

Abstract Deletion in the long arm of chromosome 22 (22qDEL) is the most prevalent somatic copy number alteration (SCNA) observed in papillary thyroid carcinoma (PTC). Despite its recurrence, the specific characteristics and role of 22qDEL in PTC have not been fully studied. We conducted a pooled analysis of 22qDEL by integrating patient and clinical information and molecular profiles from 1,094 primary PTC tumors across four major published PTC genomic studies: The Cancer Genome Atlas (TCGA) PTC profile study, the National Cancer Institute (NCI) post-Chornobyl PTC study, the Memorial Sloan Kettering Cancer Center Integrated Mutation Profiling of Actionable Cancer Targets (MSKCC-IMPACT) PTC cases, and the Seoul National University (SNU) thyroid cancer profile study. The majority of PTC with 22qDEL demonstrated arm-level loss of heterozygosity (86%). Even in PTC cases with partial 22qDEL, we observed a loss across 70% of chromosome 22, encompassing regions 22q12 and 22q13, which harbors known cancer genes (NF2 and CHEK2). More than 90% of 22qDEL co-occurred with established oncogenic drivers of PTC, though a full assessment of PTC drivers was not available for all cases. 22qDEL occurred more frequently with RAS point mutations (50.4%) than other drivers (9.3%). A higher fraction of 22qDEL was clonal in RAS-driven PTCs (78.3%), suggesting 22qDEL occurs early in RAS-driven tumor development. We did not observe any association between 22qDEL and established PTC risk factors such as age, sex, and radiation, nor with clinical features including tumor size, multifocality, and metastasis (p-values>0.22). RNA sequencing gene expression analysis based on 22qDEL status revealed downregulation of most genes residing on chromosome 22q and significant differential expression activity of immune-related genes, further implicating a role of immune dysregulation in PTC. Our study suggests that 22qDEL may not act as a primary driver of PTC but plays an important role as a co-factor of RAS point mutations, which could further drive PTC development. Citation Format: Olivia W. Lee, Danielle Karyadi, Stephen Hartley, Weyin Zhou, Mitchell Machiela, Mykola Tronko, Tetiana Bogdanova, Liudmyla Zurnadzhy, Lindsay Morton, Stephen Chanock. Characterization of somatic copy number deletion of chromosome 22q in papillary thyroid carcinoma [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 1762.

Abstract 4358: Genomic profiling of residual kidney structures in dialysis patients

Abstract Background: Chronic kidney disease is frequently associated with persistent inflammation, which results in fibrosis in the stroma, a reduced number of renal tubules, the formation of multiple cystic lesions, ultimately terminating in renal failure and hemodialysis. The high incidence of renal cell carcinoma (RCC) in hemodialysis patients suggests a relationship between tissue remodeling by chronic inflammation and carcinogenesis. However, little is known about the genetic background of cancer development from remaining tubules and cystic lesions in hemodialysis patients. Methods: We enrolled 5 patients under hemodialysis who were accompanied by acquired cystic kidney disease and who underwent total nephrectomy for renal cancer. Surgical specimens were fixed with alcohol-based solution and paraffin-embedded, and after H&E staining, subjected to laser capture microdissection (LCM) to collect remaining tubules and cysts containing approximately 200 cells. DNA was extracted and analyzed for somatic mutations and copy number alteration by whole-exome sequencing. Results: In total, we collected 161 LCM samples, including 118 from proximal tubules, 17 from collecting ducts, and 26 from cysts. The median variant allele frequencies of detected mutations were 0.237 in proximal tubules, 0.133 in collecting duct, and 0.381 in cysts, indicating larger clonal expansion in proximal tubules and cysts than in collecting ducts. Proximal tubules and cysts contained recurrent mutations in FAT1 (11% and 8%, respectively), STAG2 (5% and 8%), and PTEN (3% and 4%), whereas no recurrent driver mutations were identified in collecting ducts. In copy number analysis, 26% of proximal tubules, 35% of collecting ducts, and 80% of cysts had copy number alterations. Of note, samples from cysts had more copy number alterations compared to remaining tubules (on average, 2.3 vs. 1.1). Proximal tubules had recurrent copy number gains of chromosomes 3, 7, 10, 18, and 20, and loss of chromosome 22 and samples from collecting ducts showed gains of chromosome 7 and loss of chromosome 18. In cysts, gains of chromosomes 2, 3, 7, 10, 12, and 16 and loss of chromosomes 15, 16, 21, and 22 were frequently observed. Copy number profile in cysts was similar to that of papillary RCC and acquired cystic disease-associated RCC. Conclusion: In the end-stage cystic kidney, both proximal tubules and cysts exhibited an enrichment of driver mutations commonly found in papillary RCC and RCC with acquired cystic disease, reflecting the fact that the incidence of these two types of RCC increases as the duration of dialysis becomes longer. In addition, clear cell RCC drivers, such as VHL mutation and loss of chromosome 3, were not observed, possibly explaining the rare occurrence of clear cell RCC in hemodialysis patients. Since cysts had more frequent copy number alterations than remaining tubules, cysts in the end-stage kidney might be precursor lesions of RCC. Citation Format: Kosuke Ieiri, Nobuyuki Kakiuchi, Tomonori Hirano, Koichi Watanabe, Hirona Maeda, Hiroko Tanaka, Satoru Miyano, Dai Takamatsu, Takashi Matsumoto, Keisuke Monji, Masaki Shiota, Junichi Inokuchi, Hideki Makishima, Masatoshi Eto, Seishi Ogawa. Genomic profiling of residual kidney structures in dialysis patients [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 4358.