Effects Of Copy Number Alterations Research Articles

High-grade serous ovarian carcinoma organoids as models of chromosomal instability.

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability, and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single-cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype, and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.

Abstract 6260: Identification of molecular imaging targets specific for head and neck squamous cell carcinoma by transcriptional adaptation to copy number alterations profiling: Digital data translated to protein expression

Abstract Objective: Head and neck squamous cell carcinoma (HNSCC) can intraoperatively be visualized by fluorescence molecular imaging (FMI) using fluorophores conjugated to HNSCC specific antibodies. Currently, the epidermal growth factor receptor (EGFR) is used as a target. Targets more specific for HNSCC would reduce background signal, resulting in a higher tumor to background ratio. We aimed to identify new potential targets for FMI in HNSCC. Methods: Publicly available transcriptomic data were collected. A biostatistical method known as Transcriptional Adaptation to Copy Number Alterations (TACNA) profiling was applied, which captures the downstream effects of copy number alterations (CNAs) on mRNA levels, which we used to predict the overexpression on the protein level. By comparing gene expression profiles of HNSCC and normal oral mucosa, genes overexpressed explicitly in HNSCC were identified. Potential targets were selected based on the degree of overexpression, plasma membrane expression, and cross expression in other tissues in the head and neck region. Next, the expression of potential targets of TACNA results on mRNA level were validated on the protein level and compared to EGFR expression using immunohistochemistry (IHC). Subsequently, paired biopsies of HNSCC, adjacent suspicious mucosa, and healthy mucosa of the same patients were stained. Receptor expression was evaluated using H-scores (i.e., percentage of positive cells combined with staining intensity). Results: TACNA profiling was applied on 111 samples of healthy oral mucosa and 410 HNSCC comparing expression levels of 19,635 genes. The newly identified membrane-bound targets were glucose transporter 1 (GLUT-1), placental cadherin (P-cadherin), and monocarboxylate transporter 1 (MCT-1). The three targets were evaluated by IHC in a total of 31 patients, of which 8 had oropharyngeal, 7 hypopharyngeal, and 16 laryngeal carcinomas. GLUT-1 had a median H-score of 175, P-cadherin 140, and MCT-1 40. GLUT-1 and P-cadherin were significantly higher compared to EGFR, with a median H-score of 90 (p < .001). GLUT-1 receptor expression was also seen on erythrocytes, while P-cadherin expression was seen in the basal layer of normal epithelium. This can complicate its use in FMI. Conclusion: TACNA profiling results were successfully validated in immunohistochemistry as a first step in the search for new specific FMI targets in HNSCC. GLUT-1 and P-cadherin show promising results with significantly higher receptor expression than EGFR. Citation Format: Jeroen E. van Schaik, Bert van der Vegt, Bernard F.A.M. van der Laan, Max J.H. Witjes, Sjoukje F. Oosting, Rudolf S. Fehrmann, Boudewijn E. Plaat. Identification of molecular imaging targets specific for head and neck squamous cell carcinoma by transcriptional adaptation to copy number alterations profiling: Digital data translated to protein expression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6260.

Abstract 13700: Combined Landscape of Single-Nucleotide Variants and Copy-Number Alterations in Clonal Hematopoiesis and Their Impact on Hematological and Cardiovascular Outcomes

Background: Clonal hematopoiesis (CH) in apparently healthy individuals has recently been highlighted and implicated in the development of hematological malignancies (HM) and cardiovascular diseases. In previous studies, CH has been investigated through detecting either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Methods: Here, we performed a combined analysis of CH-related SNVs/indels and CNAs in 11,234 individuals with a median age of 70, including 672 with subsequent HM events, to delineate their relationships and impacts on clinical outcomes. Results: Overall, CH-related SNV/indels or CNAs were detected in 40% of the subjects, and they significantly cooccurred in 16% of the CH-positive subjects. In addition to the largest effect of age on the prevalence of CH, male gender and cigarette smoking were also significantly associated with variable CH-related SNV/indels and CNAs while alcohol drinking was associated only with del(20q). As for clinical impacts, CH-related SNVs/indels and CNAs coordinately affected blood cell counts and the mortality from HM, depending on the maximum clone size and total number of both lesions (Figure 1). In particular, as is the case with those in myeloid neoplasms, SNVs/indels and CNAs affecting DNMT3A , TET2 , JAK2 , and TP53 significantly co-occurred, predicting a high HM mortality. CH-related SNV/indels were also associated with the risk of cardiovascular mortality and independently predicted the presence of hypertension in multivariate modeling (Figure 2). The association with cardiovascular mortality was more prominent when SNVs/indels were combined with CNAs (Figure 3), even though the effect of CNAs alone was not evident. Conclusion: These findings provided novel insight into the interplay between SNVs/indels and CNAs in CH, highlighting the importance of detecting both types of lesions in estimating the impact of CH on hematological and cardiovascular outcomes.

Transcriptional effects of copy number alterations in a large set of human cancers

Copy number alterations (CNAs) can promote tumor progression by altering gene expression levels. Due to transcriptional adaptive mechanisms, however, CNAs do not always translate proportionally into altered expression levels. By reanalyzing >34,000 gene expression profiles, we reveal the degree of transcriptional adaptation to CNAs in a genome-wide fashion, which strongly associate with distinct biological processes. We then develop a platform-independent method—transcriptional adaptation to CNA profiling (TACNA profiling)—that extracts the transcriptional effects of CNAs from gene expression profiles without requiring paired CNA profiles. By applying TACNA profiling to >28,000 patient-derived tumor samples we define the landscape of transcriptional effects of CNAs. The utility of this landscape is demonstrated by the identification of four genes that are predicted to be involved in tumor immune evasion when transcriptionally affected by CNAs. In conclusion, we provide a novel tool to gain insight into how CNAs drive tumor behavior via altered expression levels.

Transcription Factor 2I Regulates Neuronal Development via TRPC3 in 7q11.23 Disorder Models

Williams syndrome (WS) and 7q11.23 duplication syndrome (Dup7q11.23) are neurodevelopmental disorders caused by the deletion and duplication, respectively, of ~ 25 protein-coding genes on chromosome 7q11.23. The general transcription factor 2I (GTF2I, protein TFII-I) is one of these proteins and has been implicated in the neurodevelopmental phenotypes of WS and Dup7q11.23. Here, we investigated the effect of copy number alterations in Gtf2i on neuronal maturation and intracellular calcium entry mechanisms known to be associated with this process. Mice with a single copy of Gtf2i (Gtf2i+/Del) had increased axonal outgrowth and increased TRPC3-mediated calcium entry upon carbachol stimulation. In contrast, mice with 3 copies of Gtf2i (Gtf2i+/Dup) had decreases in axon outgrowth and in TRPC3-mediated calcium entry. The underlying mechanism was that TFII-I did not affect TRPC3 protein expression, while it regulated TRPC3 membrane translocation. Together, our results provide novel functional insight into the cellular mechanisms that underlie neuronal maturation in the context of the 7q11.23 disorders.

Prognostic significance of copy number alterations detected by multi-link probe amplification of multiple genes in adult acute lymphoblastic leukemia.

The multiplex ligation-dependent probe amplification (MLPA) method was used to detect the copy number alterations (CNAs) of IKAROS family zinc finger 1 (IKZF1), paired box 5 (PAX5), ETS variant 6 (ETV6), RB transcriptional corepressor 1 (RB1), BTG anti-proliferation factor 1 (BTG1), early B-cell factor 1 (EBF1), cyclin dependent kinase inhibitor 2A/2B (CDKN2A/2B) and cytokine receptor like factor 2 (CRLF2) genes in 87 adults with acute lymphoblastic leukemia (ALL) in China. The effects of CNAs on prognosis were analyzed. Gene deletions were detected in 58/87 (66.7%) ALL patients. The most common deletions were observed in the following genes: IKZF1 (40.6%), CDKN2A (31.9%), CDKN2B (29%), PAX5 (21.7%), RB1 (14.5%) and BTG1 (10.1%). B cell-ALL (B-ALL) patients with CDKN2A/2B deletions exhibited poor 2-year overall survival (OS; P=0.055) and relapse-free survival (RFS; P=0.054) rates. CDKN2A/2B deletions were associated with poor 2-year OS (P=0.045) and RFS (P=0.071) rates in Philadelphia chromosome positive (Ph+) B-ALL patients, as well as in the high risk (HR) B-ALL group (P=0.037 and P=0.047, respectively). Patients with PAX5 deletions displayed poor 2-year OS (P=0.004) and RFS (P=0.016) rates in Philadelphia chromosome negative (Ph-) B-ALL patients. Patients with ≥3 gene deletions exhibited a poorer prognosis than other patients (OS, P=0.001; RFS, 0.002).

Abstract A182: Apobec-mutagenesis drives mutational heterogeneity while copy number alterations drive transcriptomic and proteogenomic heterogeneity in metastatic lung adenocarcinoma and thymic carcinoma

Abstract Background: Molecular characterization of metastatic tumors to investigate intra- and intertumor heterogeneity has proven more difficult than early stage disease as opportunities for surgical removal are limited. Rapid/warm autopsy programs that are conducted soon after death minimize tissue ischemia, thereby enabling procurement of high-quality viable tissue. To our knowledge, integrated proteo-genomics studies to characterize tumor heterogeneity of metastatic lung adenocarcinoma and thymic carcinoma are lacking. Methods: We sought to characterize and decipher mechanisms of intra- and intertumor heterogeneity of Stage IV lung adenocarcinoma and thymic carcinoma through whole exome sequencing, RNA sequencing, copy number estimation, and mass spectrometry-based proteomics of 38 tumors from five rapid/warm autopsy patients. The autopsy procedure was initiated between 2-4 hours of death. Results: One lung adenocarcinoma (RA003) and one thymic carcinoma (RA006) patient had high mutation burden and extreme mutational (SNV) heterogeneity. This was likely driven by APOBEC-mutagenesis. We constructed phylogenetic trees showing truncal, shared, and private SNVs and copy number alterations (CNAs). Interestingly, we discovered a pattern of recurrent, parallel but opposite arm level CNAs in different metastatic branches within a subset of patients (RA000, RA004, and RA006). In contrast, RA003 had only truncal CNAs and the least heterogeneity at the CNA level. Assessment of intra- and intertumor heterogeneity at the transcriptomic and proteomic levels revealed high concordance in gene expression and protein abundance within tumors from patient RA003 compared to patient RA004, potentially reflecting the downstream effect of CNA vs. APOBEC-induced mutations. Further analysis of cis vs. trans effects of CNA on gene expression and protein abundance in all the metastatic tumors revealed many trans-acting hot spots and limited cis effects, which is contrary to copy number effects on gene expression in primary lung adenocarcinoma tumors. Trans-acting hot spots differed between two major metastatic lineage of patient RA004, suggesting copy number changes may be responsible for high intermetastatic proteomic heterogeneity in this patient. Conclusions: Our results demonstrate ongoing mutational and chromosomal instability throughout the metastatic process of lung adenocarcinoma and thymic carcinoma. APOBEC mutagenesis was likely the primary driver of SNV heterogeneity. However, intertumor heterogeneity of metastatic disease at the level of the transcriptome and proteome occurred in association with CNA rather than mutational heterogeneity. APOBEC mutagenesis and CNA are complementary mechanisms of tumor evolution and heterogeneity affecting tumor metastasis. Citation Format: Nitin Roper, James Gao, Rouf Banday, Tapan Maity, Xu Zhang, Abhilash Venugopalan, Rajesh Patidar, Sivasish Sindiri, Constance Cultraro, Alexandr Goncearenco, Anna Panchenko, Romi Biswas, Jing Wang, Stephen Hewitt, David Kleiner, Bing Zhang, Javed Khan, Ludmila Prokunina-Olsson, Udayan Guha. Apobec-mutagenesis drives mutational heterogeneity while copy number alterations drive transcriptomic and proteogenomic heterogeneity in metastatic lung adenocarcinoma and thymic carcinoma [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A182.

Interaction-Based Feature Selection for Uncovering Cancer Driver Genes Through Copy Number-Driven Expression Level.

Driver gene selection is crucial to understand the heterogeneous system of cancer. To identity cancer driver genes, various statistical strategies have been proposed, especially the L1-type regularization methods have drawn a large amount of attention. However, the statistical approaches have been developed purely from algorithmic and statistical point, and the existing studies have applied the statistical approaches to genomic data analysis without consideration of biological knowledge. We consider a statistical strategy incorporating biological knowledge to identify cancer driver gene. The alterations of copy number have been considered to driver cancer pathogenesis processes, and the region of strong interaction of copy number alterations and expression levels was known as a tumor-related symptom. We incorporate the influence of copy number alterations on expression levels to cancer driver gene-selection processes. To quantify the dependence of copy number alterations on expression levels, we consider [Formula: see text] and [Formula: see text] effects of copy number alterations on expression levels of genes, and incorporate the symptom of tumor pathogenesis to gene-selection procedures. We then proposed an interaction-based feature-selection strategy based on the adaptive L1-type regularization and random lasso procedures. The proposed method imposes a large amount of penalty on genes corresponding to a low dependency of the two features, thus the coefficients of the genes are estimated to be small or exactly 0. It implies that the proposed method can provide biologically relevant results in cancer driver gene selection. Monte Carlo simulations and analysis of the Cancer Genome Atlas (TCGA) data show that the proposed strategy is effective for high-dimensional genomic data analysis. Furthermore, the proposed method provides reliable and biologically relevant results for cancer driver gene selection in TCGA data analysis.

Integrated genomic profiling identifies microRNA‐92a regulation of IQGAP2 in locally advanced rectal cancer

Locally advanced rectal cancer (LARC) is treated with chemoradiation prior to surgical excision, leaving residual tumors altered or completely absent. Integrating layers of genomic profiling might identify regulatory pathways relevant to rectal tumorigenesis and inform therapeutic decisions and further research. We utilized formalin-fixed, paraffin-embedded pre-treatment LARC biopsies (n=138) and compared copy number, mRNA, and miRNA expression with matched normal rectal mucosa. An integrative model was used to predict regulatory interactions to explain gene expression changes. These predictions were evaluated in vitro using multiple colorectal cancer cell lines. The Cancer Genome Atlas (TCGA) was also used as an external cohort to validate our genomic profiling and predictions. We found differentially expressed mRNAs and miRNAs that characterize LARC. Our integrative model predicted the upregulation of miR-92a, miR-182, and miR-221 expression to be associated with downregulation of their target genes after adjusting for the effect of copy number alterations. Cell line studies using miR-92a mimics and inhibitors demonstrate that miR-92a expression regulates IQGAP2 expression. We show that endogenous miR-92a expression is inversely associated with endogenous KLF4 expression in multiple cell lines, and that this relationship is also present in rectal cancers of TCGA. Our integrative model predicted regulators of gene expression change in LARC using pre-treatment FFPE tissues. Our methodology implicated multiple regulatory interactions, some of which are corroborated by independent lines of study, while others indicate new opportunities for investigation.

TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile.

The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X2 distributions that can be obtained using permutation with scaled X2 approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (<2.8 × 10−5), including the PTEN pathway (7.8 × 10−7), the gene set up-regulated under heat shock (3.6 × 10−6), the gene sets involved in the immune profile for rejection of kidney transplantation (9.2 × 10−6) and for transcriptional control of leukocytes (2.2 × 10−5), and the ganglioside biosynthesis pathway (2.7 × 10−5). In conclusion, we present a new method for pathway analyses of copy number data, and causal mechanisms of the five pathways require further study.

Estimating Conditional Probabilities for the Detection of Unfavorable Copy Number Alterations in a Targeted Therapy

Emerging targeted therapies have shown benefits such as less toxicity and higher effectiveness in specific types of cancer treatment; however, the accessibility of these advantages may rely on correct identification of suitable patients, which remains highly immature. We assume that copy number profiles, being accessible genomic data via microarray techniques, can provide useful information regarding drug response and shed light on personalized therapy. Based on the mechanism of action (MOA) of trastuzumab in the HER2 signaling pathway, a Bayesian network model in which copy number alterations (CNAs) serve as latent parents modifying signal transduction is applied. Two model parameters M-score and R -value which stand for the qualitative and quantitative effects of CNAs on drug effectiveness and are functions of conditional probabilities (CPs), are defined. An expectation-maximization (EM) algorithm is developed for estimating CPs, M-scores, and R-values from continuous measures, such as microarray data. We show through simulations that the EM algorithm can outperform classical threshold-based methods in the estimation of CPs and thereby provide improved performance for the detection of unfavorable CNAs. Several candidates of unfavorable CNAs to the trastuzumab therapy in breast cancer are provided in a real data example.

Evaluating Dynamic Effects of Copy Number Alterations on Gene Expression Using a Single Transcription Model

DNA copy number alterations (CNAs) are known to be related to genetic diseases, including cancer. The unlimited transcription (UT) model, in which transcription occurs permissively with a simple activation probability, has been proposed to investigate long-term effects of CNAs on gene expression values. Queueing theory was applied, and the copy-number-gene-expression relationship has been shown to be generally nonlinear in the UT model. However, the dynamic effects of CNAs on transcription and the underlying disorders related to diseases remain greatly unknown. Since most genes in a single cell are permissively transcribed in short periods of time interspersed by long periods of limited transcription, an alternative model for transcription in the restrictive state is needed for unraveling the effects of CNAs on gene expression levels with time. To address these issues, herein a single transcription (ST) model is proposed, in which bound TFs are assumed to be unloaded immediately after stimulating a transcription. Using the Laplace-Stieltjes transform and numerical analysis, the relationship between DNA copy number and gene expression level is evaluated. Dynamic modeling reveals that CNAs would potentially alter, or even reverse, the burst-like gene expression modifications while shifting from the ST model to the UT model. Moreover, functional disorders in transcriptional oscillation due to CNAs are shown via simulation. This paper demonstrates how mathematical theories could be helpful to interpret statistical findings from real data and achieve a better understanding of cancer biology.

19q13.11 cryptic deletion: description of two new cases and indication for a role of WTIP haploinsufficiency in hypospadias

Developmental delay/intellectual disabilities, speech disturbance, pre- and postnatal growth retardation, microcephaly, signs of ectodermal dysplasia, and genital malformations in males (hypospadias) represent the phenotypic core of the recent emerging 19q13.11 deletion syndrome. Using array-CGH for genome-wide screening we detected an interstitial deletion of chromosome band 19q13.11 in two patients exhibiting the recognizable pattern of malformations as described in other instances of this submicroscopic genomic imbalance. The deletion detected in our patients has been compared with previously reported cases leading to the refinement of the minimal overlapping region (MOR) for this microdeletion syndrome to 324 kb. This region encompasses five genes: four zinc finger (ZNF) genes belonging to the KRAB-ZNF subfamily (ZNF302, ZNF181, ZNF599, and ZNF30) and LOC400685. On the basis of our male patient 1 and on further six male cases of the literature, we also highlighted that larger 19q13.11 deletions including the Wilms tumor interacting protein (WTIP) gene, proximal to the MOR, results in hypospadias making this gene a possible candidate for this genital abnormality due to its well-known interaction with WT1. Although the mechanism underlying the phenotypic effects of copy number alterations involving KRAB-ZNF genes at 19q13.11 has not clearly been established, we suggest their haploinsufficiency as the most likely candidate for the phenotypic core of the 19q13.11 deletion syndrome. In addition, we hypothesized WTIP gene haploinsufficiency as responsible for hypospadias.

Integration of DNA Copy Number and Gene Expression Alterations Reveal Novel Insights into the Molecular Pathogenesis and Prognosis of Multiple Myeloma

Multiple myeloma (MM) is characterized by a profound genomic instability and a highly variable clinical course. To comprehensively analyze the effects of copy number alterations on gene activity and prognosis, we applied novel bioinformatics and computational approaches to integrate high-resolution aCGH data (Agilent 244K array) and gene expression profiling data (Affymetrix U133Plus2.0 array) from CD138-selected plasma cells from 92 newly diagnosed MM treated with high-dose therapy and stem cell transplantation. We identified what we have termed the “atom region” (AR). ARs are found throughout the genome and define recurrent breakpoint boundaries of sub-chromosomal loss or gain. Genes coding for miRNAs were significantly enriched in regions of the genome defined by ARs. Although many AR-related breakpoints lie in intergenic regions, and thus capture whole genes, a substantial number were identified within genes, making these genes strong candidate disease genes. We found that gain of 1q and loss of 1p represent the most significant copy number alterations linked to early disease-related death. Importantly, 1q gains and 1p loss were significantly linked to a recently described 70-gene expression model of high-risk disease predominated by increased expression of genes mapping to 1q and reduced expression of genes mapping to 1p (1). Gain of 1q and loss of 1p were also highly correlated with a gene-expression-based proliferation index widely used across many tumor types. We provide evidence that gain of 8q24 was also highly correlated with the 70-gene high-risk score, but not the proliferation index. 8q24 gains and survival were linked to elevated expression of EIF2C2/AGO2, a master regulator of microRNA expression and maturation and an overexpressed gene previously identified in our 70-gene high-risk model (1). Interestingly, although the expression of MYC, which also maps to 8q24, was related to copy number changes, its expression was not related to survival. Given the importance of AGO2 in B-cell development (2), and miRNAs in cancer, detailed functional studies of the potential role of AGO2 in MM are underway.