Copy Number Data Research Articles

Abstract 2182: The evolution of high grade serous ovarian cancer under the pressure of non-cytotoxic and cytotoxic treatment

Abstract Introduction: High-grade serous ovarian cancer (HGSOC) is driven by loss of TP53 and genome instability . Despite the recent success of PARP inhibitors, advanced BRCA mutant and homologous recombination repair deficient (HRD) HGSOC, chemotherapy remains the first line treatment. Little is known about how chemotherapy exposure alters tumor heterogeneity and subsequent response to targeted therapies. Certain mutations may survive the exposure of chemotherapy better than others. The question of whether targeted therapies should be given before or after response to chemotherapy also remains unanswered. We use the principles of natural selection to investigate how HGSOC evolves over time and selection operates on clones in the context of cytotoxic/non-cytotoxic combination therapies, and what changes in genomes/transcriptomes at the single cell level drive tumor progression. Methods: Cell lines ID8 Trp53 −/−; Brca1 −/− and WT were used to represent defective/proficient homologous recombination were given intraperitoneally to C57B6 mice to develop HGSOC models. Transfected Luciferase expression in the cells used to monitor tumor response to olaparib (Ola)+/- Bevacizumab (BEV-various doses) +/- Atezolizumab (ATz) combinations by bioluminescence imaging (BLI). Ascitic fluid and mouse organs were harvested for the evidence of seeding and identification of biomarkers. In addition, 10 treatment naïve HGSOC PDX were developed in immunodeficient mice and treated with either cisplatin or olaparib. Single-cell whole-genome sequencing (scWGS) was performed using direct library preparation (DLP+). Hierarchical clustering and Sitka are used to identify the clonal structure of each condition following treatment. Phylogenetic tree was computed using copy number data. Results: In the BRCA WT HRp study group, the greatest response was seen in the triplet Ola+BEV+ATz combinations and interestingly no significant differences were observed using a lower dose of BEV. Furthermore, from scWGS data of PDX passages we captured initial clonal heterogeneity leading to emergent clones. We found evolving copy number changes on chromosome 19, 8, 3 and loss of heterozygosity of TP53. Conclusion: The triplet combination of low-dose-intensity bevacizumab with other non-cytotoxic drugs was an effective regimen for BRCA WT syngeneic mouse tumors. In HGSOC PDX, we are able to capture diversification between HGSOC PDX passages-specifically after drug exposures. Citation Format: Farhia Kabeer, Goldman Lam, Naila Adam, Maxwell Douglas, Amal El-Naggar, Forouh Kalantari, Mengke Han, Vinci Au, Michael Van Vliet, Cindy Shen, Sean Beaty, Daniel Lai, Andy Mungall, Richard Moore, Sam Aparicio, Andrew Roth, David Huntsman, Yvette Drew. The evolution of high grade serous ovarian cancer under the pressure of non-cytotoxic and cytotoxic treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2182.

Abstract 1413: Chromosome arm aneuploidies as genetic vulnerabilities of triple-negative breast cancer

Abstract Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. It has no approved targeted therapies due to the lack of the expression of key biomarkers, namely Estrogen and Progesterone receptors, and HER2 amplification. As a result, TNBC has the worst prognosis compared to other breast cancer subtypes. We previously showed that chromosome 4p (chr4p) loss is recurrent, correlates with poor prognosis, is an early event in tumor evolution, and confers a proliferative advantage. Here, we propose to leverage chr4p loss as a genetic vulnerability of TNBC by identifying its genetic interactions (GIs) with genes whose inactivation leads to synthetic lethality i.e. loss of viability of chr4p copy loss cells, but not of the chr4p copy neutral cells, or suppression i.e., positive GIs. We first classified breast cancer cell lines with TNBC enriched molecular subtype called basal-like, as chr4p copy loss (9) and chr4p copy neutral (7), using copy number data from CCLE. Associated with chr4p copy loss, the differential expression analysis carried out using CCLE data revealed transcriptomic changes that distinctly cluster the chr4p copy loss and chr4p copy neutral cell lines. We then used the publicly available CRISPR-based genome-wide gene inactivation data from the DepMap project and quantified chr4p loss-associated GIs using multiple scoring methods such as drugZ and MAGeCK. In total, we identified ~200 negative and ~70 positive statistically significant GIs involving genes annotated to biological processes such as translation, metabolism, and others. We have prioritized a subset of them for subsequent experimental validation using CRISPR-Cas9-based gene editing in TNBC cancer cell line models. Alongside, using the publicly available drug sensitivity data obtained from the PRISM project, we identified compounds that impair cell growth in a chr4p loss-specific manner, the strongest of which targeted redox balance. Collectively, the set of GIs, the compound sensitivities, and the computational methods we have generated are unique resources for developing precision oncology therapeutic strategies for TNBC, as well as for other cancers harboring chr4p loss. Citation Format: Rohan Dandage, Michael Schwartz, Lynn Karam, Alain Pacis, Traver Hart, Guillaume Bourque, Morag Park, Elena Kuzmin. Chromosome arm aneuploidies as genetic vulnerabilities of triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1413.

Abstract 90: Exploring the role of common circulating tumor cell-associated genes in estrogen receptor-positive breast cancer recurrence

Abstract Despite having the best survival among the molecular subtypes, estrogen receptor-positive (ER+) breast cancer has a tendency for late recurrence. Circulating tumor cells (CTCs) are responsible for disease recurrence by seeding tumors at secondary sites. We have previously developed a CTC signature of 90 common regions of gene copy number gain and demonstrated that this signature is significantly more widespread among cells in metastases than primary tumors.1,2 The objective of our current work is to establish whether the expression data from a 133 gene panel largely derived from the CTC signature can be used to assess the risk of recurrence (ROR) in early ER+ breast cancer patients to help guide treatment decisions following surgery. Formalin-fixed, paraffin-embedded (FFPE) ER+ breast tumor biopsies and linked normal (control) tissues from 192 patients are being analyzed with a custom NanoString nCounter probe set of our 133 CTC genes. From data gathered to date, several genes were shown to be significantly overexpressed in tumors compared to reference normal tissues. This includes MMP11, MKI67, LILRB4, UBE2T, BIRC5, CDC6, MYBL2, and NUF2, which had a log2 fold-change of at least 3.5 (n = 34, p < 0.01). The correlation of our CTC genes to ROR is being evaluated by comparison to the results of the Oncotype DX Breast Recurrence Score Test, a well-established clinical test for ROR in ER+ breast cancer, for each patient. So far, it has been shown that the intratumor heterogeneity (ITH) of CTC genes as established by DEPTH2, an ITH algorithm which evaluates mRNA levels, is significantly positively corelated to Oncotype DX score (n = 23, r = 0.41, p = 0.0495). Moving forward, we will create our own ROR scoring system based on gene expression and copy number data from the CTC gene panel and validate it by comparison to Oncotype DX score and other available clinical data for each of the 192 patient samples. The goal of our work is to gain a deeper understanding of the molecular mechanisms that drive metastasis and recurrence in ER+ breast cancer by focusing on CTCs which play a pivotal role in driving these events. 1. Kanwar N, Hu P, Bedard P, Clemons M, McCready D, Done SJ. Identification of genomic signatures in circulating tumor cells from breast cancer. International Journal of Cancer. 2015;137(2):332-344. doi:10.1002/ijc.29399 2. Kanwar N, Balde Z, Nair R, et al. Heterogeneity of Circulating Tumor Cell-Associated Genomic Gains in Breast Cancer and Its Association with the Host Immune Response. Cancer Research. 2021;81(24):6196-6206. doi:10.1158/0008-5472.can-21-1079‌ Citation Format: Martin Rotbauer, Melanie Dawe, Philippe Bedard, David Cescon, Susan Done. Exploring the role of common circulating tumor cell-associated genes in estrogen receptor-positive breast cancer recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 90.

Abstract 968: Evaluation of Her2 RNA expression as a potential predictive biomarker for anti-Her2 therapy

Abstract Trastuzumab deruxtecan (Enhertu) is effective in "HER2 Low" breast cancer, defined by 1+ or 2+ expression by immunohistochemistry (IHC). Interest has now turned toward defining a sub-population of IHC 0+ tumors that may have HER2 expression below the limit of IHC detection/quantification and may thus also be responsive. We previously validated a high dynamic range HER2 RNA expression assay run as part of our comprehensive genomic profiling test, StrataNGS. Herein, we evaluated the HER2 RNA expression data together with copy number and clinical outcome data from the Strata Clinical Molecular Database (SCMD) in advanced breast cancer (n = 3,063) and other advanced solid tumors (n = 26,715). As expected, HER2 gene expression was significantly higher in tumors with DNA amplification (>=6 copies; median: 13.9 vs. 10.0 in log2 units; p < 1e-100). Despite similar copy number levels in amplified breast vs. other cancers (median: 21.8 vs. 19.8 copies), HER2 expression levels were ~2-fold higher (median: 14.5 vs. 13.5; p = 1.3e-10). Similarly, HER2 expression levels were higher in non-amplified breast vs. other cancers (median: 10.7 vs. 9.9; p<1e-100), suggesting that DNA amplification and cell lineage affect HER2 expression. Using our previously validated HER2 threshold, among 75 eligible SCMD breast cancer patients treated with 1st or 2nd line systemic trastuzumab or pertuzumab containing therapy, HER2 RNA High patients (n=46, 59%) had significantly longer time to next therapy (TTNT) compared to HER2 RNA Not High patients (median TTNT 26.9 vs. 5.6 months, adjusted hazard ratio 0.31, p=0.005 when adjusted for 1st vs. 2nd line, pertuzumab inclusion, and inclusion of chemotherapy or hormonal therapy). In patients with available IHC data (n = 388), HER2 RNA expression trended with IHC across the 0-3+ range, however, while 3+ tumors had distinctly high RNA expression (median: 14.4), 0-2+ tumors had lower expression with overlapping distributions (median: 10.5, 10.9, 11.5, respectively), suggesting that 0-2+ tumors do not represent distinct biological groups, but rather a continuum of low expression. We defined a HER2 RNA Low threshold (>10.6), corresponding to the top 75% of IHC 1-2+ breast cancers. Importantly, at this threshold, nearly half (44.1%) of 0+ breast cancers were also classified as HER2 RNA Low. Additionally, 25.8% of all non-breast solid tumors were classified as HER2 RNA Low. Given that HER2 RNA High predicted benefit from 1st generation anti-HER2 therapies, future studies should consider HER2 RNA Low as an alternative biomarker to Her2 IHC Low, with the opportunity to further expand trastuzumab deruxtecan use into the IHC 0+ breast cancer population and potentially to additional solid tumors. Citation Format: Laura E. Lamb, Nickolay A. Khazanov, Daniel H. Hovelson, Kat Kwiatkowski, D. Bryan Johnson, Daniel R. Rhodes, Scott A. Tomlins. Evaluation of Her2 RNA expression as a potential predictive biomarker for anti-Her2 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 968.

Abstract 4307: Integrative molecular subtypes of acute myeloid leukemia

Abstract Introduction: Acute Myeloid Leukemia (AML) is a heterogenous disease characterized by distinct clinical course and prognosis based on genomics, epigenomics or transcriptomics profile. However, the multi-omics profiles have not been systematically integrated to define the integrative molecular subtypes of AML. There is a great clinical interest to identify the patterns across multi-omics profiles that could be used for prognosis and guiding targeted therapy in AML. Methods: To identify integrative molecular subtypes (iSubtypes) of AML, we performed an integrative clustering (iCluster) analysis of the AML multi-omics data (n=160) generated by The Cancer Genome Atlas (TCGA), which consisted of somatic mutation, DNA copy number, DNA methylation and RNA-seq gene expression data for 160 AML samples. We identified the multi-omics signatures that drove the molecular classification of AML. Based on the methylation and gene expression signatures, we derived a gene panel for classification of AML and verified the prognostic power of the gene panel using three independent AML datasets (n=1382). Results: We identified four iSubtypes of AML that featured distinct multi-omics signatures. At the DNA level, the iSubtype 1 was characterized by chromosomal abnormalities and high-frequency mutation of TP53 (30%) and RUNX1 (27%); the iSubtype 2 was characterized by chromosomal abnormalities and high-frequency mutation of CEBPA (20%) and FLT3 (26%); while the iSubtypes 3 and 4 were characterized by chromosomal normality and high-frequency mutation of FLT3 (34%, 41%), NPM1 (37%, 57%) and DNMT3A (20%, 41%). At the epigenomics level, the iSubtypes 1, 3 and 4 were characterized by hypomethylation of subtype driver genes, while the iSubtypes 2 was characterized by hypermethylation of subtype driver genes. At the transcriptomics level, the 4 iSubtypes were distinguished by differentially expressed genes involved in immune process, regulation of immune process, angiogenesis, leukocyte cell activation and migration, wound healing and cell structure organization, etc. The iSubtypes 1 and 4 had the worse overall survival (OS), while the iSubtype 3 had the best and the iSubtype 2 had the middle OS. Based on the subtype-driving methylation and transcription signatures, we derived a 571-gene panel for classification of AML. Using 3 independent AML transcriptomics datasets, we demonstrated that the excellent power of the gene panel in classifying AML into 4 gene expression subtypes with similar survival outcomes. Conclusions: iSubtypes of AML are jointly determined by multi-omics profiles. The subtype-driving methylation and transcription signature have excellent power in classifying AML into clinically relevant subtypes. This integrative analysis provides insights into the biological processes underling AML. Citation Format: Qianxing (Quincy) Mo, Seongseok Yun, David A. Sallman, Nicole Vincelette, Guang Peng, Ling Zhang, Jeffrey E. Lancet, Eric Padron. Integrative molecular subtypes of acute myeloid leukemia. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4307.

Abstract 5593: Clonal mutation burden and evolutionary dynamics analysis in metastatic gastro-esophageal adenocarcinoma (GEA) by error corrected whole-exome circulating tumor DNA sequencing

Abstract Introduction: The evolution of metastatic cancers over time can be assessed in circulating tumor DNA (ctDNA) but sequencing and bioinformatics tools for ultra-deep ctDNA whole-exome sequencing (WES) analysis are lacking. Methods: We developed ctDNA WES that only requires 15ng DNA to achieve sequencing depths of 1000-2000x. Error correction with molecular barcodes and duplex DNA detection allowed calling of mutations ≥0.5% variant frequency (VF). This pilot study applied ctDNA WES to plasma from 20 EGA patients (pts) and standard WES to matched biopsies in order to assess ctDNA WES performance and whether clonal mutation burden (cMB), a critical immunotherapy biomarker and important for neoantigen vaccine designs, differed between ctDNA and biopsies. We furthermore established a mutation and copy number data analysis pipeline using Bayesian clustering to define subclones and track their evolution during therapy in 3pts. Results: The median age of pts was 71y, 95% had distant metastases and 5% locally advanced EGAs. At a median sequencing depth of ????x after de-duplication, VFs of mutations in pre-treatment ctDNA was low (<2% VF) in 8 pts, and intermediate (2-10%) to high (>10%) in 12. Whether cMB differed in biopsies vs ctDNA was assessed in 7 pts with high VFs in ctDNA and good cancer purity in matching biopsy WES. The median cMB was 82 in biopsies and 111 in ctDNA. The increase was driven by 3 cases with 30%, 35% and 59% higher cMB in ctDNA vs biopsies. In two pts, most mutations that only appeared clonal in ctDNA were subclonal rather than absent in the primary tumor, indicating the subclonal presence of the metastasis progenitor clone. Subclonal intermixing in primary tumors hence limits the accurate identification of mutations that are clonal in metastatic disease. Evolutionary dynamics analyses in 3 pts who had good responses to chemotherapy before progression showed a major clonal sweep in one, supporting monoclonal resistance, and evolution of small subclones in two, indicating polyclonal resistance. A MEK1 K57T mutation evolved at resistance in a HER2 amplified EGA treated with trastuzumab+chemotherapy, demonstrating the utility to identify mechanisms of acquired resistance. Conclusions: ctDNA WES can assess the genetics of entire metastatic cancer cell populations over time and deconvolute their evolutionary trajectories. 43% pts had higher cMB in ctDNA compared to biopsies. Liquid biopsy analyses by WES may be superior to tissue-based WES for mutation burden analysis and neoantigen vaccine designs. ctDNA WES identified distinct evolutionary modes of resistance. A larger cohort is being analyzed to define how these differ clinically and whether they can be predicted from pre-treatment ctDNA WES. Efforts to increase the ctDNA WES sensitivity are ongoing as 8 pts had low ctDNA VFs which increased false negative rates. Citation Format: Neil McCafferty, Caroline Fong, Louise J. Barber, Andrew Woolston, Dimitrios Kleftogiannis, Taqia Rana, Susan Cromarty, Shannon Kidd, Ruwaida Begum, Ian Chau, Naureen Starling, David Cunningham, Marco Gerlinger. Clonal mutation burden and evolutionary dynamics analysis in metastatic gastro-esophageal adenocarcinoma (GEA) by error corrected whole-exome circulating tumor DNA sequencing. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5593.

Identifying parental and cell-division origins of aneuploidy in the human blastocyst

Preimplantation genetic testing commonly employs simplistic copy-number analyses to screen for aneuploidy in blastocyst trophectoderm biopsies. Interpreting intermediate copy number alone as evidence of mosaicism has led to suboptimal estimation of its prevalence. Because mosaicism originates from mitotic nondisjunction, utilizing SNP microarray technology to identify the cell-division origins of aneuploidy might provide a more accurate estimation of its prevalence. The present study develops and validates a method of determining the cell-division origin of aneuploidy in the human blastocyst by using both genotyping and copy-number data in parallel. The concordance of predicted origins with expected results was demonstrated in a series of truth models (99%-100%). This included determination of X chromosome origins from a subset of normal male embryos, determination of the origins of translocation chromosome-related imbalances via embryos from couples with structural rearrangements, and prediction of either mitotic or meiotic origins via multiple rebiopsies of embryos with aneuploidy. In a cohort of blastocysts with parental DNA (n= 2,277), 71% were euploid, 27% were meiotic aneuploid, and 2% were mitotic aneuploid, indicating a low frequency of bona fide mosaicism in the human blastocyst (mean maternal age: 34.4). Chromosome-specific trisomies in the blastocyst were also consistent with observations previously established in products of conception. The ability to accurately identify mitotic-origin aneuploidy in the blastocyst could benefit and better inform individuals whose IVF cycle results in all aneuploid embryos. Clinical trials with this methodology might also help provide a definitive answer regarding the reproductive potential of bona fide mosaic embryos.

Clonal origin and development of high hyperdiploidy in childhood acute lymphoblastic leukaemia

High hyperdiploid acute lymphoblastic leukemia (HeH ALL), one of the most common childhood malignancies, is driven by nonrandom aneuploidy (abnormal chromosome numbers) mainly comprising chromosomal gains. In this study, we investigate how aneuploidy in HeH ALL arises. Single cell whole genome sequencing of 2847 cells from nine primary cases and one normal bone marrow reveals that HeH ALL generally display low chromosomal heterogeneity, indicating that they are not characterized by chromosomal instability and showing that aneuploidy-driven malignancies are not necessarily chromosomally heterogeneous. Furthermore, most chromosomal gains are present in all leukemic cells, suggesting that they arose early during leukemogenesis. Copy number data from 577 primary cases reveals selective pressures that were used for in silico modeling of aneuploidy development. This shows that the aneuploidy in HeH ALL likely arises by an initial tripolar mitosis in a diploid cell followed by clonal evolution, in line with a punctuated evolution model.

The use of copy number loads to designate mosaicism in blastocyst stage PGT-A cycles: fewer is better.

The use of copy number loads to designate mosaicism in blastocyst stage PGT-A cycles: fewer is better.

Systematic in vitro analysis of therapy resistance in glioblastoma cell lines by integration of clonogenic survival data with multi-level molecular data

Despite intensive basic scientific, translational, and clinical efforts in the last decades, glioblastoma remains a devastating disease with a highly dismal prognosis. Apart from the implementation of temozolomide into the clinical routine, novel treatment approaches have largely failed, emphasizing the need for systematic examination of glioblastoma therapy resistance in order to identify major drivers and thus, potential vulnerabilities for therapeutic intervention. Recently, we provided proof-of-concept for the systematic identification of combined modality radiochemotherapy treatment vulnerabilities via integration of clonogenic survival data upon radio(chemo)therapy with low-density transcriptomic profiling data in a panel of established human glioblastoma cell lines. Here, we expand this approach to multiple molecular levels, including genomic copy number, spectral karyotyping, DNA methylation, and transcriptome data. Correlation of transcriptome data with inherent therapy resistance on the single gene level yielded several candidates that were so far underappreciated in this context and for which clinically approved drugs are readily available, such as the androgen receptor (AR). Gene set enrichment analyses confirmed these results, and identified additional gene sets, including reactive oxygen species detoxification, mammalian target of rapamycin complex 1 (MTORC1) signaling, and ferroptosis/autophagy-related regulatory circuits to be associated with inherent therapy resistance in glioblastoma cells. To identify pharmacologically accessible genes within those gene sets, leading edge analyses were performed yielding candidates with functions in thioredoxin/peroxiredoxin metabolism, glutathione synthesis, chaperoning of proteins, prolyl hydroxylation, proteasome function, and DNA synthesis/repair. Our study thus confirms previously nominated targets for mechanism-based multi-modal glioblastoma therapy, provides proof-of-concept for this workflow of multi-level data integration, and identifies novel candidates for which pharmacological inhibitors are readily available and whose targeting in combination with radio(chemo)therapy deserves further examination. In addition, our study also reveals that the presented workflow requires mRNA expression data, rather than genomic copy number or DNA methylation data, since no stringent correlation between these data levels could be observed. Finally, the data sets generated in the present study, including functional and multi-level molecular data of commonly used glioblastoma cell lines, represent a valuable toolbox for other researchers in the field of glioblastoma therapy resistance.

Integrating copy number data of 64 iAMP21 BCP-ALL patients narrows the common region of amplification to 1.57 Mb.

Intrachromosomal amplification of chromosome 21 (iAMP21) is a rare subtype of B-cell precursor acute lymphoblastic leukaemia (BCP-ALL). It is unknown how iAMP21 contributes to leukaemia. The currently known commonly amplified region is 5.1 Mb. We aimed to narrow down the common region of amplification by using high resolution techniques. Array comparative genomic hybridization (aCGH) was used to determine copy number aberrations, Affymetrix U133 Plus2 expression arrays were used to determine gene expression. Genome-wide expression correlations were evaluated using Globaltest. We narrowed down the common region of amplification by combining copy number data from 12 iAMP21 cases with 52 cases from literature. The combined common region of amplification was 1.57 Mb, located from 36.07 to 37.64 Mb (GRCh38). This region is located telomeric from, but not including, RUNX1, which is the locus commonly used to diagnose iAMP21. This narrow region, which falls inside the Down Syndrome critical region, includes 13 genes of which the expression of eight genes was significantly upregulated compared with 143 non-iAMP21 B-other cases. Among these, transcriptional repressor RIPPLY3 (also known as DSCR6) was the highest overexpressed gene (fold change = 4.2, FDR < 0.001) and most strongly correlated (R = 0.58) with iAMP21-related genome-wide expression changes. The more precise definition of the common region of amplification could be beneficial in the diagnosis of iAMP21 based on copy number analysis from DNA sequencing or arrays as well as stimulate functional research into the role of the included genes in iAMP21 biology.

Human Satellite 1A analysis provides evidence of pericentromeric transcription

BackgroundPericentromeric regions of human chromosomes are composed of tandem-repeated and highly organized sequences named satellite DNAs. Human classical satellite DNAs are classified into three families named HSat1, HSat2, and HSat3, which have historically posed a challenge for the assembly of the human reference genome where they are misrepresented due to their repetitive nature. Although being known for a long time as the most AT-rich fraction of the human genome, classical satellite HSat1A has been disregarded in genomic and transcriptional studies, falling behind other human satellites in terms of functional knowledge. Here, we aim to characterize and provide an understanding on the biological relevance of HSat1A.ResultsThe path followed herein trails with HSat1A isolation and cloning, followed by in silico analysis. Monomer copy number and expression data was obtained in a wide variety of human cell lines, with greatly varying profiles in tumoral/non-tumoral samples. HSat1A was mapped in human chromosomes and applied in in situ transcriptional assays. Additionally, it was possible to observe the nuclear organization of HSat1A transcripts and further characterize them by 3′ RACE-Seq. Size-varying polyadenylated HSat1A transcripts were detected, which possibly accounts for the intricate regulation of alternative polyadenylation.ConclusionAs far as we know, this work pioneers HSat1A transcription studies. With the emergence of new human genome assemblies, acrocentric pericentromeres are becoming relevant characters in disease and other biological contexts. HSat1A sequences and associated noncoding RNAs will most certainly prove significant in the future of HSat research.

Modulation of gene expression associated with copy number variation identifies key regulatory programs in high-grade serous ovarian carcinoma

High grade serous ovarian carcinoma (HGSOC) is a systemic malignancy characterized by metastatic lesions that spread within the peritoneal cavity. Despite initial sensibility to platinum-based chemotherapy, more than 80% of patients experience a relapse and acquire chemoresistance. From a genomic point of view, HGSOC shows a high level of inter- and intra-tumor heterogeneity. A better understanding of molecular mechanisms of this disease and the identification of driving genetic alterations could provide relevant indications for diagnostic and prognostic evaluation. Here, we accomplished a double-tier omic-analysis by integrating copy number variation data with matched gene expression profiling of multiple lesions in a cohort of 7 patients. We identified potential driver genes contained in amplified regions whose behavior seem to impact on gene expression program. They represent a distinctive signature that can segregate biopsies of different patients. Moreover, a further analysis highlighted ZNF696, ASPSCR1 and RHPN1 as key drivers, whose regulatory program is confirmed in TCGA cohort. In conclusion, exploration of gene expression program in HSGOC by integrating copy number and transcriptomic data from spatially separated samples obtained from seven patients led to the identification of genes whose amplification is significantly correlated to specific gene expression modules and are related to survival.

Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes

Cancer subtyping delivers valuable insights into the study of cancer heterogeneity and fulfills an essential step toward personalized medicine. For example, studies in breast cancer have shown that cancer subtypes based on molecular differences are associated with different patient survival and treatment responses. However, recent studies have suggested inconsistent breast cancer subtype classifications using alternative approaches, suggesting that current methods are yet to be optimized. Existing computation-based methods have also been limited by their dependency on incomplete prior knowledge and ineffectiveness in handling high-dimensional data beyond gene expression. Here, we propose a novel deep-learning-based algorithm, Moanna, that is trained to integrate multi-omics data for predicting breast cancer subtypes. Moanna’s architecture consists of a semi-supervised Autoencoder attached to a multi-task learning network for generalizing the combination of gene expression, copy number and somatic mutation data. We trained Moanna on a subset of the METABRIC breast cancer dataset and evaluated the performance on the remaining hold-out METABRIC samples and a fully independent cohort of TCGA samples. We evaluated our use of Autoencoder against other dimensionality reduction techniques and demonstrated its superiority in learning patterns associated with breast cancer subtypes. The overall Moanna model also achieved high accuracy in predicting samples’ ER status (96%), differentiating basal-like samples (98%), and classifying samples into PAM50 subtypes (85%). Moreover, Moanna’s predicted subtypes show a stronger correlation with patient survival when compared to the original PAM50 subtypes.

A novel method to identify and characterize personalized functional driver lncRNAs in cancer samples

Cancer is a highly heterogeneous disease, and different individuals of the same cancer type can display different therapeutic effects and prognosis. Genetic variation of long non-coding RNA is the key factor driving tumor development, and plays an important role in genetic and biological heterogeneity. Therefore, it is of great significance to identify lncRNA as a driving factor in the non-coding region and explain its function in tumors for revealing the pathogenesis of cancer. In this study, we developed an integrated method to identify Personalized Functional Driver lncRNAs (PFD-lncRNAs) by integrating the DNA copy number data, gene expression data, and the biological subpathways information. Then, we applied the method to identify 2695 PFD-lncRNAs in 5334 samples across 19 cancer types. We performed an analysis of the association between PFD-lncRNAs and drug sensitivity, which provides medication guidance in disease therapy and drug discovery in the individual. Our research is of great significance for elucidating the biological roles of lncRNA genetic variation in cancer, revealing the related mechanism of cancer, and providing novel insights for individualized medicine.

Clonal Elimination of the Pathogenic Allele as Diagnostic Pitfall in SAMD9L-Associated Neuropathy

Heterozygous gain-of-function variants in SAMD9L are associated with ataxia-pancytopenia syndrome (ATXPC) and monosomy 7 myelodysplasia and leukemia syndrome-1 (M7MLS1). Association with peripheral neuropathy has rarely been described. Whole-exome sequencing (WES) from DNA extracted from peripheral blood was performed in a 10-year-old female presenting with demyelinating neuropathy, her similarly affected mother and the unaffected maternal grandparents. In addition to evaluation of single nucleotide variants, thorough work-up of copy number and exome-wide variant allele frequency data was performed. Combined analysis of the mother's and daughter's duo-exome data and analysis of the mother's and her parents' trio-exome data initially failed to detect a disease-associated variant. More detailed analysis revealed a copy number neutral loss of heterozygosity of 7q in the mother and led to reanalysis of the exome data for respective sequence variants. Here, a previously reported likely pathogenic variant in the SAMD9L gene on chromosome 7q (NM_152703.5:c.2956C>T; p.(Arg986Cys)) was identified that was not detected with standard filter settings because of a low percentage in blood cells (13%). The variant also showed up in the daughter at 32%, a proportion well below the expected 50%, which in each case can be explained by clonal selection processes in the blood due to this SAMD9L variant. The report highlights the specific pitfalls of molecular genetic analysis of SAMD9L and, furthermore, shows that gain-of-function variants in this gene can lead to a clinical picture associated with the leading symptom of peripheral neuropathy. Due to clonal hematopoietic selection, displacement of the mutant allele occurred, making diagnosis difficult.

Computational Analysis Reveals the Temporal Acquisition of Pathway Alterations during the Evolution of Cancer

Cancer metastasis is the lethal developmental step in cancer, responsible for the majority of cancer deaths. To metastasise, cancer cells must acquire the ability to disseminate systemically and to escape an activated immune response. Here, we endeavoured to investigate if metastatic dissemination reflects acquisition of genomic traits that are selected for. We acquired mutation and copy number data from 8332 tumours representing 19 cancer types acquired from The Cancer Genome Atlas and the Hartwig Medical Foundation. A total of 827,344 non-synonymous mutations across 8332 tumour samples representing 19 cancer types were timed as early or late relative to copy number alterations, and potential driver events were annotated. We found that metastatic cancers had a significantly higher proportion of clonal mutations and a general enrichment of early mutations in p53 and RTK/KRAS pathways. However, while individual pathways demonstrated a clear time-separated preference for specific events, the relative timing did not vary between primary and metastatic cancers. These results indicate that the selective pressure that drives cancer development does not change dramatically between primary and metastatic cancer on a genomic level, and is mainly focused on alterations that increase proliferation.

Predicting prognosis and immunotherapeutic response of clear cell renal cell carcinoma.

Immune checkpoint inhibitors have emerged as a novel therapeutic strategy for many different tumors, including clear cell renal cell carcinoma (ccRCC). However, these drugs are only effective in some ccRCC patients, and can produce a wide range of immune-related adverse reactions. Previous studies have found that ccRCC is different from other tumors, and common biomarkers such as tumor mutational burden, HLA type, and degree of immunological infiltration cannot predict the response of ccRCC to immunotherapy. Therefore, it is necessary to further research and construct corresponding clinical prediction models to predict the efficacy of Immune checkpoint inhibitors. We integrated PBRM1 mutation data, transcriptome data, endogenous retrovirus data, and gene copy number data from 123 patients with advanced ccRCC who participated in prospective clinical trials of PD-1 inhibitors (including CheckMate 009, CheckMate 010, and CheckMate 025 trials). We used AI to optimize mutation data interpretation and established clinical prediction models for survival (for overall survival AUC: 0.931; for progression-free survival AUC: 0.795) and response (ORR AUC: 0.763) to immunotherapy of ccRCC. The models were internally validated by bootstrap. Well-fitted calibration curves were also generated for the nomogram models. Our models showed good performance in predicting survival and response to immunotherapy of ccRCC.

Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data.

Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data. We identified 672, 555, 531, 361 CNA-driven enhancer-gene pairs and 280, 189, 113 and 98 CNA-driven enhancer-lncRNA pairs in the Basal-like, Her2, LumA and LumB subtypes, respectively. We then reconstructed a CNV-driven enhancer-lncRNA-mRNA regulatory network in each subtype. Functional analysis showed CNA-driven enhancers play an important role in the progression of breast cancer subtypes by influencing P53 signaling pathway, PPAR signaling pathway, systemic lupus erythematosus and MAPK signaling pathway in the Basal-like, Her2, LumA and LumB subtypes, respectively. We characterized the potentially prognostic value of target genes of CNV-driven enhancer and lncRNA-mRNA pairs in the subtype-specific network. We identified MUM1 and AC016876.1 as prognostic biomarkers in LumA and Basal-like subtypes, respectively. Higher expression of MUM1 with an amplified enhancer exhibited poorer prognosis in LumA patients. Lower expression of AC016876.1 with a deleted enhancer exhibited poorer survival outcomes of Basal-like patients. We also identified enhancer-related lncRNA-mRNA pairs as prognostic biomarkers, including AC012313.2-MUM1 in the LumA, AC026471.4-PLK5 in the LumB, AC027307.2-OAZ1 in the Basal-like and AC022431.1-HCN2 in the Her2 subtypes. Finally, our results highlighted target genes of CNA-driven enhancers and enhancer-related lncRNA-mRNA pairs could act as prognostic markers and potential therapeutic targets in breast cancer subtypes.

Genomic landscape of endometrial carcinomas of no specific molecular profile

AbstractEndometrial carcinomas (ECs) classified by The Cancer Genome Atlas (TCGA) as copy number-low (also referred to as “no specific molecular profile” [NSMP]) have a prognosis intermediate between POLE-mutated and copy number-high ECs. NSMP-ECs are a heterogeneous group, however, comprising both relatively indolent and aggressive ECs. We identified a total of 472 NSMP-ECs among 1,239 ECs that underwent clinical sequencing of 410–468 cancer-related genes. Somatic mutation and copy number alteration data were subjected to unsupervised hierarchical clustering, which identified three genomic clusters. Random sampling with stratification was used to choose ~80 endometrioid ECs from each cluster, resulting in a study size of 240 endometrioid ECs as well as an additional 44 non-endometrioid NSMP-ECs. Cluster 1 (C1, n = 80) consisted primarily of NSMP-ECs with PTEN and PIK3R1 mutations, Cluster 2 (C2, n = 81) of tumors with PTEN and PIK3CA mutations and Cluster 3 (C3, n = 79) of NSMP-ECs with chromosome 1q high-level gain and lack of PTEN mutations. The majority (72.7%) of non-endometrioid NSMP-ECs mapped to C3. NSMP-ECs from C3 were more likely to be FIGO grade 3 (30%), estrogen receptor-negative/weak (54.5%) and FIGO stages III or IV. In multivariate analysis, molecular clusters were associated with worse overall survival outcomes with C3 tumors having the worst (hazard ratio: 4) and C1 tumors having the best outcome. In conclusion, NSMP-ECs are a heterogenous group of tumors and comprise both aggressive and clinically low-risk ECs that can be identified based on mutation and copy number data.