MoCoLo: a testing framework for motif co-localization.

Sequence-level data offers insights into biological processes through the interaction of two or more genomic features from the same or different molecular data types. Within motifs, this interaction is often explored via the co-occurrence of feature genomic tracks using fixed-segments or analytical tests that respectively require window size determination and risk of false positives from over-simplified models. Moreover, methods for robustly examining the co-localization of genomic features, and thereby understanding their spatial interaction, have been elusive. We present a new analytical method for examining feature interaction by introducing the notion of reciprocal co-occurrence, define statistics to estimate it and hypotheses to test for it. Our approach leverages conditional motif co-occurrence events between features to infer their co-localization. Using reverse conditional probabilities and introducing a novel simulation approach that retains motif properties (e.g. length, guanine-content), our method further accounts for potential confounders in testing. As a proof-of-concept, motif co-localization (MoCoLo) confirmed the co-occurrence of histone markers in a breast cancer cell line. As a novel analysis, MoCoLo identified significant co-localization of oxidative DNA damage within non-B DNA-forming regions that significantly differed between non-B DNA structures. Altogether, these findings demonstrate the potential utility of MoCoLo for testing spatial interactions between genomic features via their co-localization.

TTSBBC: triplex target site biomarkers and barcodes in cancer.

The technology of triplex-forming oligonucleotides (TFOs) provides an approach to manipulate genes at the DNA level. TFOs bind to specific sites on genomic DNA, creating a unique intermolecular triple-helix DNA structure through Hoogsteen hydrogen bonding. This targeting by TFOs is site-specific and the locations TFOs bind are referred to as TFO target sites (TTS). Triplexes have been observed to selectively influence gene expression, homologous recombination, mutations, protein binding, and DNA damage. These sites typically feature a poly-purine sequence in duplex DNA, and the characteristics of these TTS sequences greatly influence the formation of the triplex. We introduce TTSBBC, a novel analysis and visualization platform designed to explore features of TTS sequences to enable users to design and validate TTSs. The web server can be freely accessed at https://kowalski-labapps.dellmed.utexas.edu/TTSBBC/.

NBBC: a non-B DNA burden explorer in cancer.

Alternate (non-B) DNA-forming structures, such as Z-DNA, G-quadruplex, triplex have demonstrated a potential role in cancer etiology. It has been found that non-B DNA-forming sequences can stimulate genetic instability in human cancer genomes, implicating them in the development of cancer and other genetic diseases. While there exist several non-B prediction tools and databases, they lack the ability to both analyze and visualize non-B data within a cancer context. Herein, we introduce NBBC, a non-B DNA burden explorer in cancer, that offers analyses and visualizations for non-B DNA forming motifs. To do so, we introduce 'non-B burden' as a metric to summarize the prevalence of non-B DNA motifs at the gene-, signature- and genomic site-levels. Using our non-B burden metric, we developed two analyses modules within a cancer context to assist in exploring both gene- and motif-level non-B type heterogeneity among gene signatures. NBBC is designed to serve as a new analysis and visualization platform for the exploration of non-B DNA, guided by non-B burden as a novel marker.

A Case Series Exploration of Multi-Regional Expression Heterogeneity in Triple-Negative Breast Cancer Patients.

Extensive intratumoral heterogeneity (ITH) is believed to contribute to therapeutic failure and tumor recurrence, as treatment-resistant cell clones can survive and expand. However, little is known about ITH in triple-negative breast cancer (TNBC) because of the limited number of single-cell sequencing studies on TNBC. In this study, we explored ITH in TNBC by evaluating gene expression-derived and imaging-derived multi-region differences within the same tumor. We obtained tissue specimens from 10 TNBC patients and conducted RNA sequencing analysis of 2-4 regions per tumor. We developed a novel analysis framework to dissect and characterize different types of variability: between-patients (inter-tumoral heterogeneity), between-patients across regions (inter-tumoral and region heterogeneity), and within-patient, between-regions (regional intratumoral heterogeneity). We performed a Bayesian changepoint analysis to assess and classify regional variability as low (convergent) versus high (divergent) within each patient feature (TNBC and PAM50 subtypes, immune, stroma, tumor counts and tumor infiltrating lymphocytes). Gene expression signatures were categorized into three types of variability: between-patients (108 genes), between-patients across regions (183 genes), and within-patients, between-regions (778 genes). Based on the between-patient gene signature, we identified two distinct patient clusters that differed in menopausal status. Significant intratumoral divergence was observed for PAM50 classification, tumor cell counts, and tumor-infiltrating T cell abundance. Other features examined showed a representation of both divergent and convergent results. Lymph node stage was significantly associated with divergent tumors. Our results show extensive intertumoral heterogeneity and regional ITH in gene expression and image-derived features in TNBC. Our findings also raise concerns regarding gene expression based TNBC subtyping. Future studies are warranted to elucidate the role of regional heterogeneity in TNBC as a driver of treatment resistance.

Genetic heterogeneity within collective invasion packs drives leader and follower cell phenotypes.

Collective invasion, the coordinated movement of cohesive packs of cells, has become recognized as a major mode of metastasis for solid tumors. These packs are phenotypically heterogeneous and include specialized cells that lead the invasive pack and others that follow behind. To better understand how these unique cell types cooperate to facilitate collective invasion, we analyzed transcriptomic sequence variation between leader and follower populations isolated from the H1299 non-small cell lung cancer cell line using an image-guided selection technique. We now identify 14 expressed mutations that are selectively enriched in leader or follower cells, suggesting a novel link between genomic and phenotypic heterogeneity within a collectively invading tumor cell population. Functional characterization of two phenotype-specific candidate mutations showed that ARP3 enhances collective invasion by promoting the leader cell phenotype and that wild-type KDM5B suppresses chain-like cooperative behavior. These results demonstrate an important role for distinct genetic variants in establishing leader and follower phenotypes and highlight the necessity of maintaining a capacity for phenotypic plasticity during collective cancer invasion.

Prognostic significance of an invasive leader cell-derived mutation cluster on chromosome 16q.

BACKGROUND: Intratumoral heterogeneity is defined by subpopulations with varying genotypes and phenotypes. Specialized, highly invasive leader cells and less invasive follower cells are phenotypically distinct subpopulations that cooperate during collective cancer invasion. Because leader cells are a rare subpopulation that would be missed by bulk sequencing, a novel image-guided genomics platform was used to precisely select this subpopulation. This study identified a novel leader cell mutation signature and tested its ability to predict prognosis in non-small cell lung cancer (NSCLC) patient cohorts. METHODS: Spatiotemporal genomic and cellular analysis was used to isolate and perform RNA sequencing on leader and follower populations from the H1299 NSCLC cell line, and it revealed a leader-specific mutation cluster on chromosome 16q. Genomic data from patients with lung squamous cell carcinoma (LUSC; n = 475) and lung adenocarcinoma (LUAD; n = 501) from The Cancer Genome Atlas were stratified by 16q mutation cluster (16qMC) status (16qMC+ vs 16qMC-) and compared for overall survival (OS), progression-free survival (PFS), and gene set enrichment analysis (GSEA). RESULTS: Poorer OS, poorer PFS, or both were found across all stages and among early-stage patients with 16qMC+ tumors within the LUSC and LUAD cohorts. GSEA revealed 16qMC+ tumors to be enriched for the expression of metastasis- and survival-associated gene sets. CONCLUSIONS: This represents the first leader cell mutation signature identified in patients and has the potential to better stratify high-risk NSCLC and ultimately improve patient outcomes.

Flt3L Treatment of Bone Marrow Donors Increases Graft Plasmacytoid Dendritic Cell Content and Improves Allogeneic Transplantation Outcomes.

A higher number of donor plasmacytoid dendritic cells (pDCs) is associated with increased survival and reduced graft-versus-host disease (GVHD) in human recipients of unrelated donor bone marrow (BM) grafts, but not granulocyte colony-stimulating factor (G-CSF)-mobilized peripheral blood grafts. We show that in murine models, donor BM pDCs are associated with increased survival and decreased GVHD compared with G-CSF-mobilized pDCs. To increase the content of pDCs in BM grafts, we studied the effect of FMS-like tyrosine kinase 3 ligand (Flt3L) treatment of murine BM donors on transplantation outcomes. Flt3L treatment (300 µg/kg/day) resulted in a schedule-dependent increase in the content of pDCs in the BM. Mice treated on days -4 and -1 had a >5-fold increase in pDC content without significant changes in numbers of HSCs, T cells, B cells, and natural killer cells in the BM graft. In an MHC-mismatched murine transplant model, recipients of Flt3L-treated T cell-depleted (TCD) BM (TCD F-BM) and cytokine-untreated T cells had increased survival and decreased GVHD scores with fewer Th1 and Th17 polarized T cells post-transplantation compared with recipients of equivalent numbers of untreated donor TCD BM and T cells. Gene array analyses of pDCs from Flt3L-treated human and murine donors showed up-regulation of adaptive immune pathways and immunoregulatory checkpoints compared with pDCs from untreated BM donors. Transplantation of TCD F-BM plus T cells resulted in no loss of the graft-versus-leukemia (GVL) effect compared with grafts from untreated donors in 2 murine GVL models. Thus, Flt3L treatment of BM donors is a novel method for increasing the pDC content in allografts, improving survival, and decreasing GVHD without diminishing the GVL effect.

Distinct Gene Expression Profiles Define Anaplastic Grade in Retinoblastoma.

Morbidity and mortality associated with retinoblastoma have decreased drastically in recent decades, in large part owing to better prediction of high-risk disease and appropriate treatment stratification. High-risk histopathologic features and severe anaplasia both predict the need for more aggressive treatment; however, not all centers are able to assess tumor samples easily for the degree of anaplasia. Instead, identification of genetic signatures that are able to distinguish among anaplastic grades and thus predict high- versus low-risk retinoblastoma would facilitate appropriate risk stratification in a wider patient population. A better understanding of genes dysregulated in anaplasia also would yield valuable insights into pathways underlying the development of more severe retinoblastoma. Here, we present the histopathologic and gene expression analysis of 28 retinoblastoma cases using microarray analysis. Tumors of differing anaplastic grade show clear differential gene expression, with significant dysregulation of unique genes and pathways in severe anaplasia. Photoreceptor and nucleoporin expression in particular are identified as highly dysregulated in severe anaplasia and suggest particular cellular processes contributing to the development of increased retinoblastoma severity. A limited set of highly differentially expressed genes also are able to predict severe anaplasia accurately in our data set. Together, these data contribute to the understanding of the development of anaplasia and facilitate the identification of genetic markers of high-risk retinoblastoma.

Gliosarcoma: distinct molecular pathways and genomic alterations identified by DNA copy number/SNP microarray analysis.

PURPOSE: Gliosarcoma is a histologic variant of glioblastoma (GBM), and like GBM carries a poor prognosis. Median survival is less than one (1) year with less than 5% of patients alive after 5 years. Although there is no cure, standard treatment includes surgery, radiation and chemotherapy. While very similar to GBM, gliosarcoma exhibits several distinct differences, morphologically and molecularly. Therefore, we report a comprehensive analysis of DNA copy number changes in gliosarcoma using a cytogenomic DNA copy number (CN) microarray (OncoScan®). METHODS: Cytogenomic DNA copy number microarray (OncoScan®) was performed on 18 cases of gliosarcoma. MetaCore™ enrichment was applied to the array results to detect associated molecular pathways. RESULTS: The most frequent alteration was copy number loss, comprising 57% of total copy number changes. The number of losses far exceeded the number of amplifications (***, < 0.001) and loss of heterozygosity events (***, < 0.001). Amplifications were infrequent (4.6%), particularly for EGFR. Chromosomes 9 and 10 had the highest number of losses; a large portion of which correlated to CDKN2A/B loss. Copy number gains were the second most common alteration (26.2%), with the majority occurring on chromosome 7. MetaCore™ enrichment detected notable pathways for copy number gains including: HOXA, Rho family of GTPases, and EGFR; copy number loss including: WNT, NF-kß, and CDKN2A; and copy number loss of heterozygosity including: WNT and p53. CONCLUSIONS: The pathways and copy number alterations detected in this study may represent key drivers in gliosarcoma oncogenesis and may provide a starting point toward targeted oncologic analysis with therapeutic potential.

Modulating native GABAA receptors in medulloblastoma with positive allosteric benzodiazepine-derivatives induces cell death.

PURPOSE: Pediatric brain cancer medulloblastoma (MB) standard-of-care results in numerous comorbidities. MB is comprised of distinct molecular subgroups. Group 3 molecular subgroup patients have the highest relapse rates and after standard-of-care have a 20% survival. Group 3 tumors have high expression of GABRA5, which codes for the α5 subunit of the γ-aminobutyric acid type A receptor (GABAAR). We are advancing a therapeutic approach for group 3 based on GABAAR modulation using benzodiazepine-derivatives. METHODS: We performed analysis of GABR and MYC expression in MB tumors and used molecular, cell biological, and whole-cell electrophysiology approaches to establish presence of a functional 'druggable' GABAAR in group 3 cells. RESULTS: Analysis of expression of 763 MB tumors reveals that group 3 tumors share high subgroup-specific and correlative expression of GABR genes, which code for GABAAR subunits α5, ß3 and γ2 and 3. There are ~ 1000 functional α5-GABAARs per group 3 patient-derived cell that mediate a basal chloride-anion efflux of 2 × 109 ions/s. Benzodiazepines, designed to prefer α5-GABAAR, impair group 3 cell viability by enhancing chloride-anion efflux with subtle changes in their structure having significant impact on potency. A potent, non-toxic benzodiazepine ('KRM-II-08') binds to the α5-GABAAR (0.8 µM EC50) enhancing a chloride-anion efflux that induces mitochondrial membrane depolarization and in response, TP53 upregulation and p53, constitutively phosphorylated at S392, cytoplasmic localization. This correlates with pro-apoptotic Bcl-2-associated death promoter protein localization. CONCLUSION: GABRA5 expression can serve as a diagnostic biomarker for group 3 tumors, while α5-GABAAR is a therapeutic target for benzodiazepine binding, enhancing an ion imbalance that induces apoptosis.

Gene integrated set profile analysis: a context-based approach for inferring biological endpoints.

The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an 'integrate by intersection' (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance.

Fatigue is associated with inflammation in patients with head and neck cancer before and after intensity-modulated radiation therapy.

Patients with head and neck cancer (HNC) receiving intensity-modulated radiation therapy (IMRT) have particularly high rates of fatigue, and pre- and post-radiotherapy fatigue are prognostic factors for pathologic tumor responses and poor survival. Although inflammation has been proposed as one of the potential mechanisms of fatigue in cancer patients, findings have not been consistent, and there is a dearth of longitudinal studies. Accordingly, we conducted a prospective study in 46 HNC patients pre- and one-month post-IMRT. Fatigue was measured by the Multidimensional Fatigue Inventory (MFI)-20 at both time points along with the assessment of peripheral blood inflammatory markers including interleukin (IL)-6, soluble tumor necrosis factor receptor 2, and C-reactive protein (CRP) and gene expression. Generalized estimating equations were used to examine the association between inflammatory markers and fatigue. Gene enrichment analysis using MetaCore software was performed using up-regulated genes that were significantly associated with IMRT and fatigue. Significant associations between fatigue and IL-6 as well as CRP, which were independent of time, were observed. In addition the change in fatigue from pre- to post-IMRT was positively associated with the change in IL-6 and CRP. Analysis of up-regulated gene transcripts as a function of IMRT and fatigue revealed overrepresentation of transcripts related to the defense response and nuclear factor kappa B. In conclusion, our findings support the hypotheses that inflammation is associated with fatigue over time in HNC patients. Future studies on how inflammation contributes to fatigue as well as strategies targeting inflammation to reduce fatigue are warranted.

Rank-preserving regression: a more robust rank regression model against outliers.

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd.

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd.

Chromosome instability in diffuse large B cell lymphomas is suppressed by activation of the noncanonical NF-κB pathway.

Diffuse large B cell lymphoma (DLBCL) is the most common form of lymphoma in the United States. DLBCL comprises biologically distinct subtypes including germinal center-like (GCB) and activated-B-cell-like DLBCL (ABC). The most aggressive type, ABC-DLBCL, displays dysregulation of both canonical and noncanonical NF-κB pathway as well as genomic instability. Although, much is known about the tumorigenic roles of the canonical NF-kB pathway, the precise role of the noncanonical NF-kB pathway remains unknown. Here we show that activation of the noncanonical NF-κB pathway regulates chromosome stability, DNA damage response and centrosome duplication in DLBCL. Analysis of 92 DLBCL samples revealed that activation of the noncanonical NF-κB pathway is associated with low levels of DNA damage and centrosome amplification. Inhibiting the noncanonical pathway in lymphoma cells uncovered baseline DNA damage and prevented doxorubicin-induced DNA damage repair. In addition, it triggered centrosome amplification and chromosome instability, indicated by anaphase bridges, multipolar spindles and chromosome missegregation. We determined that the noncanonical NF-κB pathway execute these functions through the regulation of GADD45α and REDD1 in a p53-independent manner, while it collaborates with p53 to regulate cyclin G2 expression. Furthermore, this pathway regulates GADD45α, REDD1 and cyclin G2 through direct binding of NF-κB sites to their promoter region. Overall, these results indicate that the noncanonical NF-κB pathway plays a central role in maintaining genome integrity in DLBCL. Our data suggests that inhibition of the noncanonical NF-kB pathway should be considered as an important component in DLBCL therapeutic approach.

Isolated clonal cytogenetic abnormalities after high-dose therapy.

Therapy-related myeloid neoplasms (t-MN) are well-recognized complications of high-dose cytotoxic therapy (HDT), such as autologous stem cell transplantation (ASCT). Clonal marrow cytogenetic abnormalities (CMCA) in the setting of normal bone marrow pathology have also been reported after HDT, but their significance remains unclear. We retrospectively evaluated occurrences of CMCA and t-MN in 785 patients treated with HDT at Johns Hopkins University between 1997 and 2007. Most patients received ASCT, but 106 patients who received high-dose cyclophosphamide without ASCT were also included in this study, as this is our institutional standard for malignant and nonmalignant lymphoproliferative disorders in need of HDT. Twenty-two patients developed t-MN, with an estimated cumulative incidence of 3.5% at 4 years. Eleven patients developed isolated CMCA, either transient or persistent without pathologic evidence of t-MN. Altogether, only 20 of the patients with reported CMCA subsequently developed t-MN during the follow-up period. Therefore, in the absence of pathologic evidence of t-MN, CMCA should not be considered diagnostic of t-MN.

A model and nomogram to predict tumor site origin for squamous cell cancer confined to cervical lymph nodes.

BACKGROUND: The current study was conducted to develop a multifactorial statistical model to predict the specific head and neck (H&N) tumor site origin in cases of squamous cell carcinoma confined to the cervical lymph nodes ("unknown primaries"). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was analyzed for patients with an H&N tumor site who were diagnosed between 2004 and 2011. The SEER patients were identified according to their H&N primary tumor site and clinically positive cervical lymph node levels at the time of presentation. The SEER patient data set was randomly divided into 2 data sets for the purposes of internal split-sample validation. The effects of cervical lymph node levels, age, race, and sex on H&N primary tumor site were examined using univariate and multivariate analyses. Multivariate logistic regression models and an associated set of nomograms were developed based on relevant factors to provide probabilities of tumor site origin. RESULTS: Analysis of the SEER database identified 20,011 patients with H&N disease with both site-level and lymph node-level data. Sex, race, age, and lymph node levels were associated with primary H&N tumor site (nasopharynx, hypopharynx, oropharynx, and larynx) in the multivariate models. Internal validation techniques affirmed the accuracy of these models on separate data. CONCLUSIONS: The incorporation of epidemiologic and lymph node data into a predictive model has the potential to provide valuable guidance to clinicians in the treatment of patients with squamous cell carcinoma confined to the cervical lymph nodes.

Pronecrotic mixed lineage kinase domain-like protein expression is a prognostic biomarker in patients with early-stage resected pancreatic adenocarcinoma.

BACKGROUND: Mixed lineage kinase domain-like protein (MLKL) is a necrosome component mediating programmed necrosis that may be an important determinant of cancer cell death. The goal of the current study was to evaluate the prognostic value of MLKL expression in patients with pancreatic adenocarcinoma (PAC). METHODS: Tissue from 80 patients was collected from a prospectively maintained database of patients with PAC who underwent pancreaticoduodenectomy between January 2000 and October 2008. Immunohistochemistry analysis was performed and scored using an established scoring system. Kaplan-Meier survival curves were generated for recurrence-free survival (RFS) and overall survival (OS) for all patients and for patients receiving adjuvant chemotherapy. MLKL scores were correlated with RFS and OS using univariate and multivariate Cox regression analyses incorporating clinically relevant covariates. RESULTS: The median age of the patients was 63 years and 53% were men. Low MLKL expression was associated with decreased OS (6 months vs 17 months; P = .006). In the subset of 59 patients who received adjuvant chemotherapy, low MLKL expression was associated with decreased RFS (5 months vs 15 months; P = .006) and decreased OS (6 months vs 19 months; P < .0001). On multivariate analysis, low MLKL expression was associated with poor OS in all patients (hazards ratio, 4.6 [95% confidence interval, 1.6-13.8]; P = .006) and in patients receiving adjuvant chemotherapy (hazards ratio, 8.1 [95% confidence interval, 2.2-29.2]; P = .002). CONCLUSIONS: Low expression of MLKL is associated with decreased OS in patients with resected PAC and decreased RFS and OS in the subset of patients with resected PAC who receive adjuvant chemotherapy. The use of this biomarker in patients with PAC may provide important prognostic information.

myCMIE: My cancer molecular information exchange.

Molecular profiling reports (MPRs) are critical for determining treatment options for cancer patients. They include several pages of information on genomic findings, drugs, and trial options that are challenging to synthesize for effectively and expeditiously informing on treatment. Xu and Kowalski present a web application, myCMIE, that synthesizes MPR content to define a patient-centric, information system in which molecular profiles are exchanged between a query case(s) and public resources or user-input case series for context-informed treatment and conjecture with therapeutic implication. myCMIE offers an interactive build of coordinately connected digital-twin communities to expand our understanding of treatment context with multiple visuals to stimulate discussions among diverse stakeholders in care.

Whole-Exome Sequencing Reveals High Mutational Concordance between Primary and Matched Recurrent Triple-Negative Breast Cancers.

PURPOSE: Triple-negative breast cancer (TNBC) is a molecularly complex and heterogeneous breast cancer subtype with distinct biological features and clinical behavior. Although TNBC is associated with an increased risk of metastasis and recurrence, the molecular mechanisms underlying TNBC metastasis remain unclear. We performed whole-exome sequencing (WES) analysis of primary TNBC and paired recurrent tumors to investigate the genetic profile of TNBC. METHODS: Genomic DNA extracted from 35 formalin-fixed paraffin-embedded tissue samples from 26 TNBC patients was subjected to WES. Of these, 15 were primary tumors that did not have recurrence, and 11 were primary tumors that had recurrence (nine paired primary and recurrent tumors). Tumors were analyzed for single-nucleotide variants and insertions/deletions. RESULTS: The tumor mutational burden (TMB) was 7.6 variants/megabase in primary tumors that recurred (n = 9); 8.2 variants/megabase in corresponding recurrent tumors (n = 9); and 7.3 variants/megabase in primary tumors that did not recur (n = 15). MUC3A was the most frequently mutated gene in all groups. Mutations in MAP3K1 and MUC16 were more common in our dataset. No alterations in PI3KCA were detected in our dataset. CONCLUSIONS: We found similar mutational profiles between primary and paired recurrent tumors, suggesting that genomic features may be retained during local recurrence.