Identification Of Genomic Aberrations Research Articles

Abstract 3409: Whole genome sequencing of liquid tumor biopsies (ctDNA) from men with metastatic castration resistant prostate cancer

Abstract Background: Prostate cancer (PC) is the fifth most lethal male malignancy worldwide, as advanced metastatic castration resistant PC (mCRPC) remains incurable. Genomic biomarkers that can predict treatment response are urgently needed to facilitate personalized mCRPC treatment. Such biomarkers can be identified by whole genome sequencing (WGS) of tumor biopsies. Blood plasma can serve as a non-invasive liquid tumor biopsy as it contains cell free DNA (cfDNA), a subset of which in cancer patients is tumor-derived (circulating tumor DNA; ctDNA). The biomarker discovery potential of WGS of cfDNA in mCRPC remains largely undescribed, as most WGS studies to date have focused on tissue biopsies. Thus, we here aimed to characterize the genomic tumor landscape of mCRPC using WGS of cfDNA. Methods: We previously performed low-pass WGS (mean coverage: 0.5X) of cfDNA sampled prior to initiation of first-line mCRPC treatment from 143 mCRPC patients (mean ctDNA fraction: 0.15). From these, 10 patients with high (>0.35) ctDNA fractions who received enzalutamide as first-line mCRPC treatment were selected for deeper WGS here. Matched germline DNA from buffy coat (peripheral blood mononuclear cells) was also sequenced. Single-nucleotide variants (SNVs) were called with Mutect2 and CaVEMan, indels with Mutect2 and Pindel, copy-number variants (CNVs) with ASCAT, and structural variants (SVs) with BRASS. For the final analysis, we considered only SNVs and indels called by both tools. Results: We sequenced germline samples to a mean coverage of 25X (range: 19-28X) and cfDNA samples to a mean coverage of 32X (range: 23-43X). We identified a median of 5,241 SNVs/indels (range: 3,422-48,314) per patient and the mean tumor mutation burden was 1.7 mutations/Mb. One sample had >9 times more SNVs/indels than the median, suggesting microsatellite instability. Among the most recurrently mutated genes were LRP1B (7/10 patients), ARSB (5/10 patients), and TP53 (4/10 patients). COSMIC mutational signature analysis revealed that the clock-like signatures 1, 5, and 40 were most frequent. In contrast, the hypermutated sample was driven primarily by the defective DNA mismatch repair signatures 15, 26, and 44. CNVs affected a mean of 40.9% of the genome. Common PC CNVs were observed, including gains at chromosome 8 (MYC) in 8/10 patients and losses at chromosome 10 (PTEN) in 5/10 patients. Recurrent focal amplifications (defined as >8 copies in regions <3 Mb) affected chromosome 15q11.2 in 3/10 patients, chromosome 22q11.21 in 3/10 patients, and chromosome Xq12, where AR is located, in 3/10 patients. Finally, we identified a median of 241 SVs (range: 92-525) per patient. SVs affecting TMPRSS2 were observed in 3/10 patients. Conclusion: This study highlights that WGS of cfDNA contributes to the identification of genomic aberrations that may serve as potential biomarkers to guide personalized treatment of mCRPC in the future. Citation Format: Simone Weiss, Philippe Lamy, Maibritt Nørgaard, Michael Knudsen, Jørgen B. Jensen, Jakob S. Pedersen, Michael Borre, Karina D. Sørensen. Whole genome sequencing of liquid tumor biopsies (ctDNA) from men with metastatic castration resistant prostate cancer [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 3409.

Predicting Panel of Metabolism and Immune-Related Genes for the Prognosis of Human Ovarian Cancer.

ObjectiveOvarian cancer (OC) is a high deadly gynecologic cancer with a poor prognosis. The identification of genomic aberrations could predict the clinical prognosis of OC patients and may eventually develop new therapeutic strategies in the future. The purpose of this study is to create comprehensive co-expressed gene networks correlated with metabolism and the immune process of OC.MethodsThe transcriptome profiles of TCGA OC datasets and GSE26193 datasets were analyzed. The mRNA expression level, hub genomic alteration, patient’s survival status, and tumor cell immune microenvironment of metabolism-related genes were analyzed from TCGA, GTEX, Oncomine, Kaplan-Meier Plotter, cBioPortal, TIMER, ESTIMATE, and CIBERSORT databases. We further validated the mRNA and protein expression levels of these hub genes in OC cell lines and tissues using qRT-PCR and immunohistochemistry.ResultsThe LASSO-Cox regression analyses unveiled seven differently expressed metabolism-related genes, including GFPT2, DGKD, ACACB, ACSM3, IDO1, TPMT, and PGP. The Cox regression risk model could be served as an independent marker to predict the overall clinical survival of OC patients. The expression of GFPT2, DGKD, ACACB, and ACSM3 were downregulated in OC tissues, while IDO1, TPMT, and PGP were upregulated in OC tissues than in control. Moreover, DGKD and IDO1 were significantly associated with the human immune system.ConclusionThe differently expressed metabolism-related genes were identified to be a risk model in the prediction of the prognosis of OC. The identified hub genes related to OC prognosis may play important roles in influencing both human metabolism and the immune system.

Next generation sequencing in histopathology : Applications and methodological challenges

The enormous increase in sequencing capacity due to the development of next generation sequencing technologies opens up new opportunities in the fields of histopathology, research, and diagnostics, but also poses huge challenges.The identification of genomic aberrations (point mutations, small insertions and deletions, fusion transcripts, and tumor mutation burden (TMB)) have already become areliable part of routine molecular diagnostics. This will be supplemented by additional applications, namely gene amplifications, microsatellite instability, genomic signatures like homologous recombination deficiency (HRD), mRNA expression patterns, B‑ and T‑cell clonality, and DNAmethylation. Challenges in preanalytics and the evaluation of assay sensitivity and specificity as well as proper curation of identified aberrations, which requires anew type of specialist, are presented and discussed.

Phospho-Proteomic Profiling of T-Cell Acute Lymphoblastic Leukemia Identifies Targetable Kinase Activities and Novel Treatment Combination Strategies

Introduction Intensive multi-agent treatment has boosted survival up to 80% of pediatric T-cell acute lymphoblastic leukemia (T-ALL) patients. Nevertheless, relapsed patients have a poor prognosis due to acquired therapy resistance while most survivors have detrimental chemotherapy-induced side effects. Therefore, novel targeted therapies are urgently needed since further intensification of the current standard treatment regimen is not feasible for refractory/relapsed cases. Protein kinase inhibitors (PKIs) are amongst the most successful cancer treatments. Targetable kinases activated by gene fusions are rare in T-ALL and include subclonal NUP214-ABL1 fusion in 6% of cases or other rare clonal ABL1 fusions. Nevertheless, leukemic blasts rely on enhanced kinase signaling to sustain their dysregulated proliferation. Protein kinases can be hyper-activated even in the absence of defects in their genes. Thus, together with the identification of genomic aberrations, phospho-proteomics can provide information on pathway activation, signaling networks and aberrant kinase activities that offer important opportunities for targeted therapies. Aim Here, we aimed to identify and quantify kinase activation in T-ALL cell lines that may yield differential sensitivity to PKIs in vitro. This approach could pinpoint targetable leukemia vulnerabilities and provide effective (combination) treatment strategies. Methods Protein extracts from 11 T-ALL cell lines were enriched for phospho-peptides by titanium dioxide enrichment and anti-phospho tyrosine immunoprecipitation followed by liquid chromatography - tandem mass spectrometry (MS). Subsequently, the Integrative Inferred Kinase Activity (INKA) pipeline was used to rank activated kinases in our panel (Beekhof et al., 2019). Based on these data, selected kinase inhibitors were tested in vitro as single treatment or in combinations. Eventually, drugs of interest were further tested ex vivo in a cohort of T-ALL patient-derived xenografts (PDXs). Results MS-based phospho-proteome profiling of 11 T-ALL cell lines identified about 3700 tyrosine phospho-sites and more than 13300 serine/threonine phosphorylation sites. We found SRC-family kinases including LCK, SRC, FYN, and YES1 as most activated kinases in many T-ALL cell lines while ABL1, ZAP70, LYN, and FGR were detected only in specific lines. Additionally, other kinases including CDK1/2 and PAK1/2 were found to be activated in all the cell lines while activation of the INSR/IGF-1R axis was detected only in a subset of lines. We then tested cellular response to multiple clinically relevant PKIs based on predicted kinase activities. The in vitro drug screening showed an effective response and G1-arrest following treatment with the CDK1/2 inhibitor milciclib in all the cell lines tested, with IC50 values between 10nM and 1uM. Despite a general SRC-family kinases activation profile, dual SRC/ABL inhibitors like dasatinib reduced cellular viability only in cell lines with ABL1 fusions or LCK translocations (IC50 < 10nM) while other lines lacking ABL or LCK rearrangements were affected at much higher drug concentration (IC50 > 3uM, which is beyond the clinical achievable plasma concentration). Thus, PKIs were tested in combination with other relevant inhibitors based on additional kinase activities detected. Interestingly, the concomitant inhibition of the SRC-family kinases by dasatinib and the INSR/IGF-1R axis by BMS-754807 led to a drastic reduction of cell viability at nanomolar concentrations even in cell lines that did not respond to dasatinib, identifying a novel possible effective combination strategy for T-ALL. Eventually, we tested clinically relevant PKIs in 50 PDXs ex vivo and identified various T-ALL samples with a high sensitivity to dasatinib single treatment (IC50 < 100nM) as previously reported by others (Frismantas et al., 2017). Moreover, 70% of our PDXs efficiently responded to the broad spectrum kinase inhibitor midostaurin (IC50 < 1uM), highlighting the importance of targeting multiple signaling nodes simultaneously to tackle T-ALL vulnerabilities. Conclusions Ranking kinase activities and signaling networks from phospho-proteomic data can guide the use of PKIs as treatment option for T-ALL patients. Moreover, kinase activity profiling can provide insights for efficient treatment combination strategies to develop personalized medicine. Disclosures No relevant conflicts of interest to declare.

Transcriptome-Based Network Analysis Unveils Eight Immune-Related Genes as Molecular Signatures in the Immunomodulatory Subtype of Triple-Negative Breast Cancer.

Objective: Triple-negative breast cancer (TNBC) is a high heterogeneity cancer. The identification of genomic aberrations that drive each of the TNBC subtypes may predict the prognosis of patients with TNBC and provide novel therapeutic strategies in clinical practice. This study focuses on the transcriptome-based gene expression of TNBC and aims to generate comprehensive gene co-expression networks correlated with the immune-related subtype of TNBC.Methods: The transcriptome profiles of 107 female patients with TNBC were analyzed. Weighted gene co-expression network analysis (WGCNA) was applied to construct related networks and to sort hub-genes associated with the survival of TNBC patients. The data of the transcriptional expression, genomic alteration, survival status, and tumor immune microenvironment, which associated with hub-genes, were extracted, retrieved, and analyzed from Oncomine, UALCAN, TCGA, starBase, Kaplan–Meier Plotter, cBioPortal, and TIMER databases.Results: Immune-related hub-genes, including BIRC3, BTN3A1, CSF2RB, GIMAP7, GZMB, HCLS1, LCP2, and SELL, were found to be associated with clinical features of TNBC evaluated by WGCNA. These hub-genes belonged to the immunomodulatory subtype of TNBC and were upregulated in the TNBC cells. The protein expression of eight immune-related hub-genes was further confirmed to be upregulated in TNBC/CD8+ tissues detected by immunohistochemical staining. Survival analysis revealed that overexpression of eight immune-related hub-genes was in favor of the survival of patients with TNBC. Moreover, a positive correlation between eight immune-related hub-genes and immune cell infiltration was observed in TNBC patients. Furthermore, checkpoint inhibitor genes such as PD-L1, PD-1, and CTLA4 were more enrichment in the immunomodulatory subtype of TNBC and the expression of PD-L1, PD-1, and CTLA4 was positively correlated with eight immune-related hub-genes in the breast cancer dataset of TCGA.Conclusions: Eight immune-related hub-genes were identified to be molecular signatures in the immunomodulatory subtype of TNBC, which may provide therapeutic targets for the treatment of patients with breast cancer.

Identification of genomic aberrations associated with overall survival in metastatic clear cell renal cell carcinoma (mccRCC).

745 Background: Tumor comprehensive genomic profiling (CGP) in addition to risk stratification by IMDC criteria may aid in improving risk stratification. The objective of this study was to assess the prognostic impact of somatic mutations in addition to IMDC risk criteria. Methods: All patients with mccRCC treated with first line with VEGFR-TKI with CGP data available through a CLIA certified lab were included. Kaplan-Meier methodology and Cox proportional hazard ratios were used to test the association of overall survival with genomic alterations present in at least 7% of the population in this dataset. Genomic data were correlated with outcome by univariate analysis and subsequent multivariate testing, integrating genomic data with IMDC risk criteria. Results: A total of 58 patients met eligibly. The presence of any mutation in VHL, PBRM1, and MLL2 were prognostic in terms of overall survival (Table). The mutation status for these three prognostic genes was added to the IMDC risk model to test for the prognostic correlation. The mutations status of these 3 genes significantly correlated with overall survival (VHL: 0.32 [95% CI 0.11-0.95], PBRM1: 0.36 [0.14-0.96], and MLL2: 7.60 [1.35-24.6]) independent of the IMDC risk criteria. Conclusions: In mccRCC, VHL, PBRM1, and MLL2 mutations each predict overall survival independent of IMDC criteria. Further studies are warranted to assess alterations with low prevalence in this data set. Upon external validation, these data provide the rationale for integration of mutation status of these three genes in to the IMDC risk criteria.[Table: see text]

Simultaneous detection of single-nucleotide variant, deletion/insertion, and fusion in lung and thyroid carcinoma using cytology specimen and an RNA-based next-generation sequencing assay.

Molecular testing for epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) and ROS proto-oncogene 1, receptor tyrosine kinase (ROS1) fusion is routinely performed in patients with stage IV lung adenocarcinoma to assess their eligibility for targeted therapy. Fine-needle aspiration (FNA)-derived material frequently is the only pathologic material available. The identification of genomic aberrations in thyroid nodules from FNA smears may help stratify cancer risk and spare patients from a second surgery. In the current study, the authors tested nucleic acid extracted from the cytology smears of lung and thyroid carcinomas for simultaneous detection of single-nucleotide variant, insertion/deletion, and gene fusion using an RNA-based next-generation sequencing assay. A total of 27 cases (17 lung and 10 thyroid carcinomas, the majority of which had known variants) were tested. Areas of interest were scrapped from stained smears using a scalpel. Total nucleic acid was extracted. Gene fusion and mutational analysis was performed using the Comprehensive Thyroid and Lung FusionPlex Assay. Data were analyzed using the analysis pipeline provided by the vendor. Eleven cases with available formalin-fixed, paraffin-embedded (FFPE) tissue were tested in parallel. Gene fusions were detected in 6 cases; common single-nucleotide variants in EGFR, RAS, and BRAF in 14 cases; and in-frame deletions within EGFR in 3 cases. A concordance rate of 100% was observed between FNA and FFPE tissue. Cytology preparations can be a reliable source for the detection of both DNA and RNA aberrations. The ability to simultaneously detect multiple types of genomic variants is crucial for patients with advanced cancer and maximizes the usefulness of cytology specimens. Cancer Cytopathol 2018;126:158-69. © 2018 American Cancer Society.

Identification of genomic aberrations in hemangioblastoma by droplet digital PCR and SNP microarray highlights novel candidate genes and pathways for pathogenesis.

BackgroundThe genetic mechanisms underlying hemangioblastoma development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays and droplet digital PCR analysis to detect copy number variations (CNVs) in total of 45 hemangioblastoma tumors.ResultsWe identified 94 CNVs with a median of 18 CNVs per sample. The most frequently gained regions were on chromosomes 1 (p36.32) and 7 (p11.2). These regions contain the EGFR and PRDM16 genes. Recurrent losses were located at chromosome 12 (q24.13), which includes the gene PTPN11.ConclusionsOur findings provide the first high-resolution genome-wide view of chromosomal changes in hemangioblastoma and identify 23 candidate genes: EGFR, PRDM16, PTPN11, HOXD11, HOXD13, FLT3, PTCH, FGFR1, FOXP1, GPC3, HOXC13, HOXC11, MKL1, CHEK2, IRF4, GPHN, IKZF1, RB1, HOXA9, and micro RNA, such as hsa-mir-196a-2 for hemangioblastoma pathogenesis. Furthermore, our data implicate that cell proliferation and angiogenesis promoting pathways may be involved in the molecular pathogenesis of hemangioblastoma.

Identification of Genomic Aberrations in Cancer Subclones from Heterogeneous Tumor Samples.

Tumor samples are usually heterogeneous, containing admixture of more than one kind of tumor subclones. Studies of genomic aberrations from heterogeneous tumor data are hindered by the mixed signal of tumor subclone cells. Most of the existing algorithms cannot distinguish contributions of different subclones from the measured single nucleotide polymorphism (SNP) array signals, which may cause erroneous estimation of genomic aberrations. Here, we have introduced a computational method, Cancer Heterogeneity Analysis from SNP-array Experiments (CHASE), to automatically detect subclone proportions and genomic aberrations from heterogeneous tumor samples. Our method is based on HMM, and incorporates EM algorithm to build a statistical model for modeling mixed signal of multiple tumor subclones. We tested the proposed approach on simulated datasets and two real datasets, and the results show that the proposed method can efficiently estimate tumor subclone proportions and recovery the genomic aberrations.

Abstract PR16: Targeting cancer-specific kinase dependency for precision therapy

Abstract Precision/ personalized cancer therapy based on clinical sequencing is premised on the identification of genomic aberrations in actionable therapeutic targets. Protein kinases represent the most accessible therapeutic targets across cancers, albeit only very small subsets of cancers harbor canonical targetable aberrations in kinases. Considering that kinases represent the predominant drivers of oncogenesis, functioning directly or downstream of other oncogenic aberrations, we hypothesize that most cancers harbor distinct “kinase dependencies” and thus provide a potent therapeutic avenue in individual cancers. Here, we test the hypothesis that the kinase(s) that display an “off the chart” Outlier Expression in individual cancer samples, impart a dependency on growth and survival that can be exploited therapeutically. Analyzing RNA-Seq data from a compendium of 482 cancer and benign samples belonging to 25 different tissue types we defined sample-specific ‘kinome’ expression profiles. Comparing the expression of kinases within a sample and across sample sets, we identified distinct ‘outlier kinases’ in individual samples, defined as genes showing the highest statistically significant levels of absolute and differential expression. Frequently observed outlier kinases in breast cancer included known therapeutic targets like ERBB2 and FGFR4, distinct from MET, AKT2, and PLK2 in pancreatic cancer. Outlier kinases imparted sample-specific dependencies in various cell lines as assessed by siRNA knockdown or pharmacologic inhibition in vitro and in vivo. Outlier expression of polo-like kinases (PLKs) observed in a subset of KRAS-dependent pancreatic cancer cell lines conferred increased sensitivity to the PLK inhibitor BI 6727. Together, our results suggest that outlier kinases represent effective personalized therapeutic targets that are readily identifiable through RNA-sequencing of tumors. Next, to help translate these observations into treatment options, we are optimizing ex vivo culture of tumor tissues from surgical resections that will be used to test combinations of therapeutics including outlier kinase inhibitors. This abstract is also presented as Poster B21. Citation Format: Vishal Kothari, Wei Iris, Sunita Shankar, Shanker Kalyana-Sundaram, Lidong Wang, Linda W. Ma, Pankaj Vats, Catherine S. Grasso, Dan R. Robinson, Yi-Mi Wu, Xuhong Cao, Diane M. Simeone, Arul M. Chinnaiyan, Chandan Kumar-Sinha. Targeting cancer-specific kinase dependency for precision therapy. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Synthetic Lethal Approaches to Cancer Vulnerabilities; May 17-20, 2013; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(5 Suppl):Abstract nr PR16.

Identification of TRPC6 as a possible candidate target gene within an amplicon at 11q21-q22.2 for migratory capacity in head and neck squamous cell carcinomas

BackgroundCytogenetic and gene expression analyses in head and neck squamous cell carcinomas (HNSCC) have allowed identification of genomic aberrations that may contribute to cancer pathophysiology. Nevertheless, the molecular consequences of numerous genetic alterations still remain unclear.MethodsTo identify novel genes implicated in HNSCC pathogenesis, we analyzed the genomic alterations present in five HNSCC-derived cell lines by array CGH, and compared high level focal gene amplifications with gene expression levels to identify genes whose expression is directly impacted by these genetic events. Next, we knocked down TRPC6, one of the most highly amplified and over-expressed genes, to characterize the biological roles of TRPC6 in carcinogenesis. Finally, real time PCR was performed to determine TRPC6 gene dosage and mRNA levels in normal mucosa and human HNSCC tissues.ResultsThe data showed that the HNSCC-derived cell lines carry most of the recurrent genomic abnormalities previously described in primary tumors. High-level genomic amplifications were found at four chromosomal sites (11q21-q22.2, 18p11.31-p11.21, 19p13.2-p13.13, and 21q11) with associated gene expression changes in selective candidate genes suggesting that they may play an important role in the malignant behavior of HNSCC. One of the most dramatic alterations of gene transcription involved the TRPC6 gene (located at 11q21-q22.2) which has been recently implicated in tumour invasiveness. siRNA-induced knockdown of TRPC6 expression in HNSCC-derived cells dramatically inhibited HNSCC-cell invasion but did not significantly alter cell proliferation. Importantly, amplification and concomitant overexpression of TRPC6 was also found in HNSCC tumour samples.ConclusionsAltogether, these data show that TRPC6 is likely to be a target for 11q21–22.2 amplification that confers enhanced invasive behavior to HNSCC cells. Therefore, TRPC6 may be a promising therapeutic target in the treatment of HNSCC.

DNA Fragmentation Simulation Method (FSM) and Fragment Size Matching Improve aCGH Performance of FFPE Tissues

Whole-genome copy number analysis platforms, such as array comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) arrays, are transformative research discovery tools. In cancer, the identification of genomic aberrations with these approaches has generated important diagnostic and prognostic markers, and critical therapeutic targets. While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations. Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues. Using self-hybridizations of a single DNA sample we observed that aCGH performance is significantly improved by accurate DNA size determination and the matching of test and reference DNA samples so that both possess similar fragment sizes. Based on this observation, we developed a novel DNA fragmentation simulation method (FSM) that allows customized tailoring of the fragment sizes of test and reference samples, thereby lowering array failure rates. To validate our methods, we combined FSM with Universal Linkage System (ULS) labeling to study a cohort of 200 tumor samples using Agilent 1 M feature arrays. Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA). This study demonstrates that rigorous control of DNA fragment size improves aCGH performance. This methodological advance will permit the routine analysis of FFPE tumor samples for clinical trials and in daily clinical practice.

Identification of Genomic Aberrations by Array Comparative Genomic Hybridization in Patients with Aortic Dissections

BackgroundThe aim of the present study was to identify chromosomal loci that contribute to the pathogenesis of aortic dissection (AD) in a Korean population using array comparative genomic hybridization (CGH) and to confirm the results using real-time polymerase chain reaction (PCR).Materials and MethodsEighteen patients with ADs were enrolled in this study. Genomic DNA was extracted from individual blood samples, and array CGH analyses were performed. Four corresponding genes with obvious genomic changes were analyzed using real-time PCR in order to assess the level of genomic imbalance identified by array CGH.ResultsGenomic gains were most frequently detected at 8q24.3 (56%), followed by regions 7q35, 11q12.2, and 15q25.2 (50%). Genomic losses were most frequently observed at 4q35.2 (56%). Real-time PCR confirmed the results of the array CGH studies of the COL6A2, DGCR14, PCSK6, and SDHA genes.ConclusionThis is the first study to identify candidate regions by array CGH in patients with ADs. The identification of genes that may predispose an individual to AD may lead to a better understanding of the mechanism of AD formation. Further multicenter studies comparing cohorts of patients of different ethnicities are warranted.