Potential Driver Mutations Research Articles

Functional profiling of serine, threonine and tyrosine sites.

Systematic perturbation of amino acids at endogenous loci provides diverse insights into protein function. Here, we performed a genome-wide screen to globally assess the cell fitness dependency of serine, threonine and tyrosine residues. Using an adenine base editor, we designed a whole-genome library comprising 817,089 single guide RNAs to perturb 584,337 S, T and Y sites. We identified 3,467 functional substitutions affecting cell fitness and 677 of them involving phosphorylation, including numerous phosphorylation-mediated gain-of-function substitutions that regulate phosphorylation levels of itself or downstream factors. Furthermore, our findings highlight that specific substitution types, notably serine to proline, are crucial for maintaining domain structure broadly. Lastly, we demonstrate that 309 enriched hits capable of initiating cell overproliferation might be potential cancer driver mutations. This study represents an extensive functional profiling of S, T and Y residues and provides insights into the distinctive roles of these amino acids in biological mechanisms and tumor progression.

Are Next-Generation Pathogenicity Predictors Applicable to Cancer?

Next-generation pathogenicity predictors are designed to identify pathogenic mutations in genetic disorders but are increasingly used to detect driver mutations in cancer. Despite this, their suitability for cancer is not fully established. Here we have assessed the effectiveness of next-generation pathogenicity predictors when applied to cancer by using a comprehensive experimental benchmark of cancer driver and neutral mutations. Our findings indicate that state-of-the-art methods AlphaMissense and VARITY demonstrate commendable performance despite generally underperforming compared to cancer-specific methods. This is notable considering that these methods do not explicitly incorporate cancer-related data in their training and have made concerted efforts to prevent data leakage from the human-curated training and test sets. Nevertheless, it should be mentioned that a significant limitation of using pathogenicity predictors for cancer arises from their inability to detect cancer potential driver mutations specific for a particular cancer type.

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.

Singleton mutations in large-scale cancer genome studies: uncovering the tail of cancer genome.

Singleton or low-frequency driver mutations are challenging to identify. We present a domain driver mutation estimator (DOME) to identify rare candidate driver mutations. DOME analyzes positions analogous to known statistical hotspots and resistant mutations in combination with their functional and biochemical residue context as determined by protein structures and somatic mutation propensity within conserved PFAM domains, integrating the CADD scoring scheme. Benchmarked against seven other tools, DOME exhibited superior or comparable accuracy compared to all evaluated tools in the prediction of functional cancer drivers, with the exception of one tool. DOME identified a unique set of 32917 high-confidence predicted driver mutations from the analysis of whole proteome missense variants within domain boundaries across 1331 genes, including 1192 noncancer gene census genes, emphasizing its unique place in cancer genome analysis. Additionally, analysis of 8799 TCGA(The Cancer Genome Atlas) and in-house tumor samples revealed 847 potential driver mutations, with mutations in tyrosine kinase members forming the dominant burden, underscoring its higher significance in cancer. Overall, DOME complements current approaches for identifying novel, low-frequency drivers and resistant mutations in personalized therapy.

Mutation characteristics of angioimmunoblastic T-cell lymphoma: an analysis of 75 cases

Objective: To investigate the characteristics of gene mutations in angioimmunoblastic T-cell lymphoma (AITL). Methods: Seventy-five AITL cases diagnosed at the Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China from June 2021 to June 2023 were included. Their formalin-fixed and paraffin-embedded or fresh tissues were subject to targeted next generation sequencing (NGS). The sequencing data was collected, and the distribution and type of gene mutations were analyzed. Results: 492 potential driver mutations were identified in 74 out of the 84 genes. Targeted sequencing data for the 75 AITL patients showed that the genes with mutation frequencies of ≥10% were TET2 (89.3%), RHOA (57.3%), IDH2 (37.3%), DNMT3A (36.0%), KMT2C (21.3%), PLCG1 (12.0%), and KDM6B (10.7%). There were significant co-occurrence relationships between TET2 and RHOA, TET2 and IDH2, and RHOA and IDH2 gene mutations (P<0.05), respectively, while TET2 and KDM6B gene mutations were mutually exclusive (P<0.05). Conclusions: The study reveals the mutational characteristics of AITL patients using NGS technology, which would provide insights for molecular diagnosis and targeted therapy of AITL.

Somatic gene mutations involved in DNA damage response/Fanconi anemia signaling are tissue- and cell-type specific in human solid tumors.

With significant advancements in the study of DNA Damage Response (DDR) and Fanconi Anemia (FA) signaling, we previously introduced the term "FA signaling" to encompass "all signaling transductions involving one or more FA proteins." This network has now evolved into the largest cellular defense network, integrating over 30 key players, including ATM, ATR, BLM, HRR6, RAD18, FANCA, FANCB, FANCC, BRCA2, FANCD2, FANCE, FANCF, FANCG, FANCI, BRIP1, FANCL, FANCM, PALB2, RAD51C, SLX4, ERCC4, RAD51, BRCA1, UBE2T, XRCC2, MAD2L2, RFWD3, FAAP20, FAAP24, FAAP100, and CENPX. This system responds to both endogenous and exogenous cellular insults. However, the mutational signatures associated with this defense mechanism in non-FA human cancers have not been extensively explored. In this study, we report that different types of human cancers are characterized by distinct somatically mutated genes related to DDR/FA signaling, each accompanied by a unique spectrum of potential driver mutations. For example, in pan-cancer samples, ATM emerges as the most frequently mutated gene (5%) among the 31 genes analyzed, with the highest number of potential driver mutations (1714), followed by BRCA2 (4% with 970 putative driver mutations). However, this pattern is not universal across specific cancer types. For example, FANCT is the most frequently mutated gene in breast (14%) and liver (4%) cancers. In addition, the alteration frequency of DDR/FA signaling due to these mutations exceeds 70% in a subtype of prostate cancer, with each subtype of brain, breast, lung, and prostate cancers displaying distinct patterns of gene alteration frequency. Furthermore, these gene alteration patterns significantly impact patient survival and disease-free periods. Collectively, our findings not only enhance our understanding of cancer development and progression but also have significant implications for cancer patient care and prognosis, particularly in the development of effective therapeutic strategies.

Clonal selection of hematopoietic stem cells after gene therapy for sickle cell disease

Gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD); however, the occurrence of myeloid malignancies in GT clinical trials has prompted concern, with several postulated mechanisms. Here, we used whole-genome sequencing to track hematopoietic stem cells (HSCs) from six patients with SCD at pre- and post-GT time points to map the somatic mutation and clonal landscape of gene-modified and unmodified HSCs. Pre-GT, phylogenetic trees were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified among gene-modified or unmodified cells; however, an increased frequency of potential driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) was observed in both genetically modified and unmodified cells, suggesting positive selection of mutant clones during GT. This work sheds light on HSC clonal dynamics and the mutational landscape after GT in SCD, highlighting the enhanced fitness of some HSCs harboring pre-existing driver mutations. Future studies should define the long-term fate of mutant clones, including any contribution to expansions associated with myeloid neoplasms.

Investigating the interplay of hematological parameters, CD markers, genetic polymorphisms, and database mutations in the IL15 gene in acute myeloid leukemia patients.

Acute myeloid leukemia (AML) is a heterogeneous malignancy characterized by the clonal expansion of myeloid precursor cells in the bone marrow. In this study, we investigated the interplay of hematological parameters, CD markers, genetic polymorphisms, and database mutations in the interleukin 15 (IL15) gene in AML patients. We enrolled 59 newly diagnosed AML patients and analyzed their bone marrow specimens using flow cytometry and molecular techniques. The hematological parameters of the AML patients revealed a significant increase in platelet count and RBC, Hb, and HCT levels compared to healthy individuals. CD marker expression analysis revealed upregulation of CD33, CD45, CD13, CD117, CD38, HLA-DR, CD15, CD64, MPO, CD34, and CD11c in AML patients. Molecular analysis showed 15 mutations in different positions of exon 8 of the IL15 gene, with the most frequent mutation being a homozygous mutation resulting from a nucleotide substitution. Additionally, 10 novel heterozygous mutations were identified in different locations of chromosome 4, with a low variant rate. Finally, database analysis of gnomAD and Mutagene revealed a high number of potential driver mutations in the IL15 gene in leukemia patients. These results provide valuable insights into the genetic and immunophenotypic characteristics of AML patients and highlight the potential role of IL15 in AML pathogenesis.

Genomic Characterization of Low and High Grade Cervical Intraepithelial Neoplasia in Comparison to Cervical Cancer

Screening reduces incidence of cervical cancer (CC) through identification and treatment of cervical intraepithelial neoplasia (CIN). Triage of CIN must balance between overtreatment versus progression as invasive therapies increase the risk of side effects including obstetric complications. The majority of CIN 1-2 lesions regress and a subset of CIN 3 lesions progress, however, due to inability to differentiate lesions likely to progress, the majority of CIN 2-3 lesions are treated with resection. Improved genomic and molecular identifiers of disease represent an urgent unmet clinical need. Using next generation sequencing of a targeted exome panel of 1109 genes (previously validated), we characterized somatic mutations in 36 CIN (14 CIN 1, 11 CIN 2, 11 CIN 3) and 13 CC samples. Sequencing of CIN samples was performed on exfoliated cervical cells. CIN diagnosis and grade was confirmed on biopsy. Mutation profiles between CIN grades and CC were compared to identify genomic patterns that distinguish these groups. Across the 49 samples sequenced, we identified a total of 5142 somatic mutations, including 2178 missense, 2522 synonymous, 171 nonsense, 62 splice site, 135 inframe indels, and 74 frameshift mutations. The mutation frequency was significantly higher in CC vs CIN1-3 (Table), p<0.01 (Wilcoxon signed-rank test). The difference in mutation frequency and type (Table) was not significant between CIN grades 1, 2 and 3 (p = 0.07, Kruskal-Wallis test). Cancer related pathway signatures were analyzed for the percentage of CC vs CIN samples with at least one altered variant as follows: RTK-RAS (92% vs 31%), PI3K (92% vs 17%), NOTCH (100% vs 39%), WNT (85% vs 14%) and cell cycle (53% vs 3%). Ninety percent of CC samples versus only 30% of CINs had nonsynonymous variants in the RTK-RAS and NOTCH pathways as well as the PI3K pathway which is implicated as a late event in cervical carcinogenesis. We observed recurrent missense variants in ABL1, IGF1R, TSC2 in the CIN2, CIN3 and CC samples, particularly in genes that belong to the RTK-RAS, PI3K, NOTCH pathway signatures. Potential driver mutations in EGFR, PIK3CA, ERBB4, MTOR, CSF1R genes were exclusive to CC samples. Our results show that there is a clear distinction of mutational burden and type between cervical cancer and CIN1-3. However, the pathologic grading of CIN is not consistently associated with dynamic changes in overall mutation burden, type, or specific genes with escalating CIN grade. This data supports the hypothesis that late genetic events in CIN accompany a transition to invasive cervical cancer.

347. LASER CAPTURE MICRODISSECTION AND WHOLE GENOME SEQUENCING OF ESOPHAGEAL ADENOCARCINOMA SAMPLES WITH MINIMAL TUMOUR

Abstract Background Esophageal adenocarcinoma (EAC) samples, particularly biopsies, can have low tumour cellularity, which limits their use for sequencing. Previous studies have focused on untreated resection specimens with high cellularity (i.e. TCGA requiring 60% cellularity on histology). Laser capture microdissection (LCM) is a method to enrich tumour cells from histological specimens and has been successfully used in other samples. We hypothesize that LCM can enrich for tumour from biopsies and resection specimens with very low cellularity. Methods Biopsy and resection EAC specimens were subjected to laser capture microdissection and whole genome sequencing (N = 49 biopsies and N = 15 resections) as part of the MOCHA trial (NCT04219137). LCM samples were reviewed by a board-certified pathologist to quantify tumour cellularity prior to LCM. Matched germline DNA was extracted from patient blood. Samples were processed using an in-house pipeline to call somatic single nucleotide variants (SNVs), insertions, deletions, copy number changes, and structural variants. Post LCM tumour cellularity was estimated from the WGS data. Results We had slightly higher WGS tumour cellularity for biopsies (66.2% +/− 16.8) and resections (71.3% +/− 18.0) than TCGA (58.1% +/− 17.5), while our histological cellularity was much lower than TCGA’s 60% cutoff at 32.2% +/− 24.5 for biopsies and 31.0% +/− 22.7 for resections. Overall, our LCM strategy led to an increase of 35.4 +/− 25.1% for cellularity by WGS compared to the histology. Finally, we observed a similar tumour ploidy and SNV composition as TCGA, which further verified that our tumour enrichment strategy was successful. Conclusion We have successfully applied an LCM strategy to enrich for tumour cells from low cellularity specimens. For example, we have successfully enriched for tumour cells from specimens with as low as 1% histological cellularity. We are currently exploring the results of this dataset including clinical correlations, changes in potential driver mutations from biopsy to resection, and comparing our results to treatment response.

Actionability of comprehensive genomic profiling compared to the tissue-based and plasma-based assay in patients with metastatic breast cancer: A real-world study.

1101 Background: Comprehensive genomic profiling (CGP) was officially approved in August 2021 in Japan under the national health insurance system with three CGP tests in June 2019: FoundationOne CDx (F1CDx), OncoGuide NCC Oncopanel (NCC), which are tissue-based assay (TBA), and FoundationOne Liquid CDx (F1LCDx, starting in August 2021) which is plasma-based panel (PBA). The Center for Cancer Genomics and Advanced Therapeutics (C-CAT) has collected genomic and clinical data of 2,617 Japanese breast cancer patients as of October 2022. Here we assess these PBA and TBA to detect pathogenic or driver alterations informative for matched therapy in patients with metastatic breast cancer (mBC). Methods: We queried consecutive mBC patient clinical-genomic data through the C-CAT Research-Use Portal from June 2019 to October 2022 were categorized based on PBA or TBA. We used ClinVar to identify if the called somatic alterations were pathogenic or likely pathogenic, and BoostDM (https://www.intogen.org/boostdm/search) to identify potential driver mutations of breast cancer. The proposed rate of matched therapy was determined. The incidence rates were compared using the Pearson χ2 test. Results: Of 2,617 pts who underwent the CGP test, 2,259 (86%) received TBA (74% F1CDx and 12% NCC). The proportion of pts with ≥1 pathogenic variant with PBA and TBA was not significant (71.5%vs.72.7%; p=0.88), but the proportion of pts with ≥1 driver mutation was significantly higher with PBA than TBA (75.4% vs. 69.8%; p = 0.03). Regarding the proportion of pts who matched therapy or clinical trials presented among the pts for whom data were available, PBA was significantly lower than TBA (27.7% vs.38.5%, p &lt; 0.001). Although data on post-treatment is still being collected, the proportion of tested patients that received matched therapies recommended by molecular tumor boards of each institute was significantly lower for PBA (4.2%vs. 8.3%; p = 0.007). Conclusions: This study is the first analysis of CGP for mBC in Japan using the C-CAT utilization program. Although significant alterations were well-detected in PBA, the proportion of pts who received matched-therapy post-testing was low for PBA. Possible causes include that PBA has fewer companion diagnoses than TBA in Japan and that PBA is more often used in later lines.

Exploring the Potential Driver Gene Mutations That Promote Renal Cancer Cell Metastasis and Implantation Based on Circulating Tumor Cells Culture.

Studies have shown that the circulating tumor cell (CTC) is a necessary condition for the invasion and distant metastasis of renal cell carcimona (RCC). However, few CTCs-related gene mutations have been developed which could promote the metastasis and implantation of RCC. The objective of this study is to explore the potential driver gene mutations that promote RCC metastasis and implantation based on CTCs culture. Fifteen patients with primary mRCC and three healthy subjects were included, and peripheral blood was obtained. After the preparation of synthetic biological scaffolds, peripheral blood CTCs were cultured. Successful cultured CTCs were applied to construct CTCs-derived xenograft (CDX) models, followed by DNA extraction, whole exome sequencing (WES) and bioinformatics analysis. Synthetic biological scaffolds were constructed based on previously applied techniques, and peripheral blood CTCs culture was successfully performed. We then constructed CDX models and performed WES, and explored the potential driver gene mutations that may promote RCC metastasis and implantation. Bioinformatics analysis showed that KAZN and POU6F2 may be closely related to the prognosis of RCC. We successfully performed the culture of peripheral blood CTCs and, on this basis we initially explored the potential driver mutations for the metastasis and implantation of RCC.

Genomic alterations dissection revealed MUC4 mutation as a potential driver in lung adenocarcinoma local recurrence.

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer, of which genomic alterations play a major role in tumorigenesis. The prognosis of LUAD has been improved these years but nearly half of the patients still develop recurrence even after radical resection. The underlying mechanism driving LUAD recurrence especially genomic alterations is complicated and worth exploring. Forty-one primary tumors and 43 recurrent tumors were collected from 41 LUAD patients who received surgery resection after recurrence. Whole exon sequencing (WES) was performed to make genomic landscapes. WES data were aligned to genome and further analyzed for somatic mutation, copy number variation and structure variation. MutsigCV was used to identify significantly mutated genes and recurrence specific genes. Significantly mutated genes including EGFR, MUC4 and TP53 were identified in primary and recurrent tumors. Some were found to be more specifically mutated in recurrent tumors, such as the MUC17, KRAS and ZNF families. In recurrent tumors, ErbB signaling pathway, MAPK pathway and cell cycle pathway were highly activated, which maybe the mechanism driving recurrence. The adjuvant therapy would affect tumor evolution and molecular features during recurrence. MUC4 was highly mutated in this study cohort, and it was a potential driver gene in LUAD recurrence by activating ErbB signaling pathway as a ligand of ERBB2. Genomic alteration landscape was changing during LUAD recurrence to construct a more suitable environment for the survival of tumor cells. Several potential driver mutations and targets during LUAD recurrence were identified, such as MUC4, and more investigation was needed to verify the specific functions and roles.

Abstract 6508: Eclipse, an automated CRISPR platform for the large-scale generation of cell models

Abstract Major advances in gene editing using CRISPR have improved accessibility for the creation of disease relevant in vitro models, allowing researchers to readily interrogate oncogenic driver mutations and elucidate novel targets to overcome challenges within cancer research such as drug resistance. Despite this, the rapid generation of disease relevant cell lines at the scale needed for successful and efficient therapeutic development remains challenging in part due to the sheer number of potential oncogenic driver mutations and cancer targets along with using traditional manual approaches. Specific challenges include: the efficient generation of gene knockouts and corresponding loss of protein; efficient knock-in of gene tags and single nucleotide variants; and controlling the zygosity of these genetic outcomes. To address these limitations, we describe the use of our automated, high throughput CRISPR editing platform, ECLIPSE, for the rapid generation of cell models such as immortalized cells and induced pluripotent stem cells. We leveraged our chemically modified synthetic sgRNAs, optimized nucleofection methods, and automated pipelines for the generation of CRISPR-edited cells at various scales to address the needs of researchers. This scale ranges from individual edited cell clones for drug target validation to the generation of hundreds of knockout cell pools in a ready-to-assay arrayed format for gene target identification in drug screening. The utilization of automated systems such as the ECLIPSE platform are critical catalysts for the rapid generation of engineered cell lines at relevant scales to address the challenges of cancer research. Citation Format: Peter Deng, Matthew Rowe, Anna King, Dana Sailor, Antinea Chair, Montse Morell, Andreia G. Sommer, Kevin Holden. Eclipse, an automated CRISPR platform for the large-scale generation of cell models [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 6508.

LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution

BackgroundLongitudinal single-cell sequencing experiments of patient-derived models are increasingly employed to investigate cancer evolution. In this context, robust computational methods are needed to properly exploit the mutational profiles of single cells generated via variant calling, in order to reconstruct the evolutionary history of a tumor and characterize the impact of therapeutic strategies, such as the administration of drugs. To this end, we have recently developed the LACE framework for the Longitudinal Analysis of Cancer Evolution.ResultsThe LACE 2.0 release aimed at inferring longitudinal clonal trees enhances the original framework with new key functionalities: an improved data management for preprocessing of standard variant calling data, a reworked inference engine, and direct connection to public databases.ConclusionsAll of this is accessible through a new and interactive Shiny R graphical interface offering the possibility to apply filters helpful in discriminating relevant or potential driver mutations, set up inferential parameters, and visualize the results. The software is available at: github.com/BIMIB-DISCo/LACE.

Abstract PD10-09: PD10-09 Multiomics analysis of matched ER+ primary and recurrent breast cancers on or after adjuvant endocrine therapy

Abstract Background: 80% of all breast cancers (BCs) are ER-positive (ER+). Not all respond to adjuvant endocrine therapy (aET) and a significant number develop endocrine resistance and recur. The basis for primary and acquired endocrine resistance is poorly understood. A multiomics analysis of primary ER+ BCs matched with recurrences on or after completion of aET has been performed. Patients: A unique cohort of 520 women with matched primary and recurrent ER+, HER2-negative (HER2-) BC is being analysed. In the first subset of 75, all had surgery to clear margins, followed by aET. The endocrine therapy given was tamoxifen (66%), aromatase inhibitors (AI) (28%: 17% letrozole, 6% anastrozole, 2% exemestane, and 3% a succession of 2 different AIs), or a combination of tamoxifen and an AI (6%). aET duration was 5 years, unless the patient stopped treatment or developed a recurrence sooner. 16/75 patients (21%) had positive lymph nodes. All patients developed recurrences: local in 59/75, concurrent local and nodal in 13/75 and lymph node-only in 3/75. Median time to recurrence was 4.1 years (range: 0.7-29 years). 62% of patients were on aET at the time of recurrence. All patients have long-term follow-up. Methods: DNA and RNA were extracted from matched primary and recurrence BC tissue samples. Targeted DNA-exome and whole-genome expression analyses were performed. A custom targeted DNA panel was used to study genes implicated in endocrine therapy resistance (ETR): this included 73 different targets, selected based on our previous full-exome sequencing of sequential ET recurrences and those implicated in the literature and in curated somatic and cancer mutation databases. Somatic mutations and copy number alterations (CNA) were determined. Differential gene expression analysis was performed using two-class unpaired Significance Analysis of Microarrays (SAM). Validation of pathways implicated in ETR using NanoString GeoMx protein analysis is ongoing. Results: Targeted DNA-exome profiling identified 1 or 2 potential driver mutations in all but a few primary samples. Multiple aberrations and a highly diverse mutational landscape were observed in all the recurrences. Matched breast and lymph node samples from synchronous recurrences had very similar somatic profiles. Changes significantly enriched in recurrent samples included somatic aberrations in well-established drivers such as MAP3K1, PIK3CA, TP53 and CDH1, as well as ESR1. Aberrations were also common in PTEN and in ER-associated factors FOXA1 and GATA3. Transcriptomic analysis revealed a number of pathways implicated in resistance, including ER, HER2, GATA3, AKT, RAS and p63 signalling. A panel-based, targeted DNA sequencing approach for mutational profiling allowed capture of relevant mutational profiles linked to ETR in a cost-effective manner compared with traditional whole-exome sequencing. Ongoing analysis has linked mutational profiles to specific endocrine agents and has allowed us to demonstrate significant differences between recurrences on aET compared with those after completion of aET. Multiomics profiling of the remaining samples in the cohort is underway. Discussion: This multiomics study provides the largest cohort to-date of matched early and recurrent ER+/HER2- BCs. It has shed new light on how different adjuvant endocrine agents can affect primary drivers and lead to complex somatic and transcriptomic changes in recurrent disease. This work confirms that the mechanisms of endocrine resistance are diverse and has already identified mechanisms underlying ETR and clinically meaningful biomarkers of ETR, including potentially actionable mutations and targets. Citation Format: Carlos Martinez-Perez, Charlene Kay, James Meehan, J Michael Dixon, Arran K Turnbull. PD10-09 Multiomics analysis of matched ER+ primary and recurrent breast cancers on or after adjuvant endocrine therapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD10-09.

RNA-Sequencing Combined With Genome-Wide Allele-Specific Expression Patterning Identifies ZNF44 Variants as a Potential New Driver Gene for Pediatric Neuroblastoma.

Neuroblastoma (NB) is one of the children's most common solid tumors, accounting for approximately 8% of pediatric malignancies and 15% of childhood cancer deaths. Somatic mutations in several genes, such as ALK, have been associated with NB progression and can facilitate the discovery of novel therapeutic strategies. However, the differential expression of mutated and wild-type alleles on the transcriptome level is poorly studied. This study analyzed 219 whole-exome sequencing datasets with somatic mutations detected by MuTect from paired normal and tumor samples. We prioritized mutations in 8 candidate genes (RIMS4, RUSC2, ALK, MYCN, PTPN11, ALOX12B, ZNF44, and CNGB1) as potential driver mutations. We further confirmed the presence of allele-specific expression of the somatic mutations in NB with integrated analysis of 127 RNA-seq samples (of which 85 also had DNA-seq data available), including MYCN, ALK, and PTPN11. The allele-specific expression of mutations suggests that the same somatic mutation may have different effects on the clinical outcomes of tumors. Our study suggests 2 novel variants of ZNF44 as a novel candidate driver gene for NB.

Clinicopathologic and genomic characterizations of brain metastases using a comprehensive genomic panel.

Central nervous system (CNS) metastasis is the most common brain tumor type in adults. Compared to their primary tumors, these metastases undergo a variety of genetic changes to be able to survive and thrive in the complex tissue microenvironment of the brain. In clinical settings, the majority of traditional chemotherapies have shown limited efficacy against CNS metastases. However, the discovery of potential driver mutations, and the development of drugs specifically targeting affected signaling pathways, could change the treatment landscape of CNS metastasis. Genetic studies of brain tumors have so far focused mainly on common cancers in western populations. In this study, we performed Next Generation Sequencing (NGS) on 50 pairs of primary tumors, including but not limited to colorectal, breast, renal and thyroid tumors, along with their brain metastatic tumor tissue counterparts, from three different local tertiary centers in Saudi Arabia. We identified potentially clinically relevant mutations in brain metastases that were not detected in corresponding primary tumors, including mutations in the PI3K, CDK, and MAPK pathways. These data highlight the differences between primary cancers and brain metastases and the importance of acquiring and analyzing brain metastatic samples for further clinical management.

Identification of potential driver mutations in glioblastoma using machine learning.

Glioblastoma is a fast and aggressively growing tumor in the brain and spinal cord. Mutation of amino acid residues in targets proteins, which are involved in glioblastoma, alters the structure and function and may lead to disease. In this study, we collected a set of 9386 disease-causing (drivers) mutations based on the recurrence in patient samples and experimentally annotated as pathogenic and 8728 as neutral (passenger) mutations. We observed that Arg is highly preferred at the mutant sites of drivers, whereas Met and Ile showed preferences in passengers. Inspecting neighboring residues at the mutant sites revealed that the motifs YP, CP and GRH, are preferred in drivers, whereas SI, IQ and TVI are dominant in neutral. In addition, we have computed other sequence-based features such as conservation scores, Position Specific Scoring Matrices (PSSM) and physicochemical properties, and developed a machine learning-based method, GBMDriver (GlioBlastoma Multiforme Drivers), for distinguishing between driver and passenger mutations. Our method showed an accuracy and AUC of 73.59% and 0.82, respectively, on 10-fold cross-validation and 81.99% and 0.87 in a blind set of 1809 mutants. The tool is available at https://web.iitm.ac.in/bioinfo2/GBMDriver/index.html. We envisage that the present method is helpful to prioritize driver mutations in glioblastoma and assist in identifying therapeutic targets.

Molecular Characterization of Circulating Tumor DNA in Pediatric Rhabdomyosarcoma: A Feasibility Study.

Rhabdomyosarcomas (RMS) are rare neoplasms affecting children and young adults. Efforts to improve patient survival have been undermined by a lack of suitable disease markers. Plasma circulating tumor DNA (ctDNA) has shown promise as a potential minimally invasive biomarker and monitoring tool in other cancers; however, it remains underexplored in RMS. We aimed to determine the feasibility of identifying and quantifying ctDNA in plasma as a marker of disease burden and/or treatment response using blood samples from RMS mouse models and patients. We established mouse models of RMS and applied quantitative polymerase chain reaction (PCR) and droplet digital PCR (ddPCR) to detect ctDNA within the mouse plasma. Potential driver mutations, copy-number alterations, and DNA breakpoints associated with PAX3/7-FOXO1 gene fusions were identified in the RMS samples collected at diagnosis. Patient-matched plasma samples collected from 28 patients with RMS before, during, and after treatment were analyzed for the presence of ctDNA via ddPCR, panel sequencing, and/or whole-exome sequencing. Human tumor-derived DNA was detectable in plasma samples from mouse models of RMS and correlated with tumor burden. In patients, ctDNA was detected in 14/18 pretreatment plasma samples with ddPCR and 7/7 cases assessed by sequencing. Levels of ctDNA at diagnosis were significantly higher in patients with unfavorable tumor sites, positive nodal status, and metastasis. In patients with serial plasma samples (n = 18), fluctuations in ctDNA levels corresponded to treatment response. Comprehensive ctDNA analysis combining high sensitivity and throughput can identify key molecular drivers in RMS models and patients, suggesting potential as a minimally invasive biomarker. Preclinical assessment of treatments using mouse models and further patient testing through prospective clinical trials are now warranted.