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Multi-omics (genomics, transcriptomics, epigenomics, proteomics, metabolomics, etc.) research approaches are vital for understanding the hierarchical complexity of human biology and have proven to be extremely valuable in cancer research and precision medicine. Emerging scientific advances in recent years have made high-throughput genome-wide sequencing a central focus in molecular research by allowing for the collective analysis of various kinds of molecular biological data from different types of specimens in a single tissue or even at the level of a single cell. Additionally, with the help of improved computational resources and data mining, researchers are able to integrate data from different multi-omics regimes to identify new prognostic, diagnostic, or predictive biomarkers, uncover novel therapeutic targets, and develop more personalized treatment protocols for patients. For the research community to parse the scientifically and clinically meaningful information out of all the biological data being generated each day more efficiently with less wasted resources, being familiar with and comfortable using advanced analytical tools, such as Google Cloud Platform becomes imperative. This project is an interdisciplinary, cross-organizational effort to provide a guided learning module for integrating transcriptomics and epigenetics data analysis protocols into a comprehensive analysis pipeline for users to implement in their own work, utilizing the cloud computing infrastructure on Google Cloud. The learning module consists of three submodules that guide the user through tutorial examples that illustrate the analysis of RNA-sequence and Reduced-Representation Bisulfite Sequencing data. The examples are in the form of breast cancer case studies, and the data sets were procured from the public repository Gene Expression Omnibus. The first submodule is devoted to transcriptomics analysis with the RNA sequencing data, the second submodule focuses on epigenetics analysis using the DNA methylation data, and the third submodule integrates the two methods for a deeper biological understanding. The modules begin with data collection and preprocessing, with further downstream analysis performed in a Vertex AI Jupyter notebook instance with an R kernel. Analysis results are returned to Google Cloud buckets for storage and visualization, removing the computational strain from local resources. The final product is a start-to-finish tutorial for the researchers with limited experience in multi-omics to integrate transcriptomics and epigenetics data analysis into a comprehensive pipeline to perform their own biological research.This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [16] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
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Computação em Nuvem , Epigenômica , Humanos , Epigenômica/métodos , Epigênese Genética , Transcriptoma , Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Software , Mineração de Dados/métodosRESUMO
Purpose: Exposure to radiation is a health concern within and beyond the Earth's atmosphere for aircrew and astronauts in their respective austere environments. The biological effects of radiation exposure from a multiomics standpoint are relatively unexplored and stand to shed light on tailored monitoring and treatment for those in these career fields. To establish a reference variable for genetic damage, biological age seems to be closely associated with the effect of radiation. Following a genetic-based study, this study explores the epigenetic landscape of radiation exposure along with its associative effects on aging processes. Methods: We imported the results of the genetics-based study that was a secondary analysis of five publicly available datasets (noted as Data1). The overlap of these genes with new data involving methylation data from two datasets (noted as Data2) following similar secondary analysis procedures is the basis of this study. We performed the standard statistical analysis on these datasets along with supervised and unsupervised learning to create preranked gene lists used for functional analysis in Ingenuity Pathway Analysis (IPA). Results: There were 664 genes of interest from Data1 and 577 genes from Data2. There were 40 statistically significant methylation probes within 500 base pairs of the gene's transcription start site and 10 probes within 100 base pairs, which are discussed in depth. IPA yielded 21 significant pathways involving metabolism, cellular development, cell death, and diseases. Compared to gold standards for gestational age, we observed relatively low error and standard deviation using newly identified biomarkers. Conclusion: We have identified 17 methylated genes that exhibited particular interest and potential in future studies. This study suggests that there are common trends in oxidative stress, cell development, and metabolism that indicate an association between aging processes and the effects of ionizing radiation exposure.
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Astronautas , Exposição à Radiação , Humanos , Atmosfera , Exposição à Radiação/efeitos adversos , Estresse Oxidativo , Envelhecimento/genéticaRESUMO
Multi-omics studies have emerged as powerful tools for tailoring individualized responses to various conditions, capitalizing on genome sequencing technologies' increasing affordability and efficiency. This paper delves into the potential of multi-omics in deepening our understanding of biological age, examining the techniques available in light of evolving technology and computational models. The primary objective is to review the relationship between ionizing radiation and biological age, exploring a wide array of functional, physiological, and psychological parameters. This comprehensive review draws upon an extensive range of sources, including peer-reviewed journal articles, government documents, and reputable websites. The literature review spans from fundamental insights into radiation effects to the latest developments in aging research. Ionizing radiation exerts its influence through direct mechanisms, notably single- and double-strand DNA breaks and cross links, along with other critical cellular events. The cumulative impact of DNA damage forms the foundation for the intricate process of natural aging, intersecting with numerous diseases and pivotal biomarkers. Furthermore, there is a resurgence of interest in ionizing radiation research from various organizations and countries, reinvigorating its importance as a key contributor to the study of biological age. Biological age serves as a vital reference point for the monitoring and mitigation of the effects of various stressors, including ionizing radiation. Ionizing radiation emerges as a potent candidate for modeling the separation of biological age from chronological age, offering a promising avenue for tailoring protocols across diverse fields, including the rigorous demands of space exploration.
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Purpose: One possible way to quantify each individual's response or damage from ionizing radiation is to estimate their accelerated biological age following exposure. Since there is currently no definitive way to know if biological age estimations are accurate, we aim to establish a rad-age association using genomics as its foundation. Methods: Two datasets were combined and used to empirically find the age cutoff between young and old patients. With age as both a categorical and continuous variable, two other datasets that included radiation exposure are used to test the interaction between radiation and age. The gene lists are oriented in preranked lists for both pathway and diseases analysis. Finally, these genes are used to evaluate another dataset on the clinical relevance in differentiating lung disease given ethnicity and sex using both pairwise t-tests and linear models. Results: Using 12 well-known genes associated with aging, a threshold of 29-years-old was found to be the difference between young and old patients. The two interaction tests yielded 234 unique genes such that pathway analysis flagged IL-1 signaling and PRPP biosynthesis as significant with high cell proliferation diseases and carcinomas being a common trend. LAPTM4B was the only gene with significant interaction among lung disease, ethnicity, and sex, with fold change greater than two. Conclusion: The results corroborate an initial association between radiation and age, given inflammation and metabolic pathways and multiple genes emphasizing mitochondrial function, oxidation, and histone modification. Being able to tie rad-age genes to lung disease supplements future work for risk assessment following radiation exposure.
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Pneumopatias , Voo Espacial , Humanos , Adulto , Diferenciação Celular , Transdução de Sinais , Genômica , Proteínas de Membrana , Proteínas OncogênicasRESUMO
African American (AA) women with breast cancer are more likely to have higher inflammation and a stronger overall immune response, which correlate with poorer outcomes. In this report, we applied the nanostring immune panel to identify differences in inflammatory and immune gene expression by race. We observed a higher expression of multiple cytokines in AA patients compared to EA patients, with high expression of CD47, TGFB1, and NFKB1 associated with the transcriptional repressor Kaiso. To investigate the mechanism associated with this expression pattern, we observed that Kaiso depletion results in decreased expression of CD47, and its ligand SIRPA. Furthermore, Kaiso appears to directly bind to the methylated sequences of the THBS1 promotor and repress gene expression. Similarly, Kaiso depletion attenuated tumor formation in athymic nude mice, and these Kaiso-depleted xenograft tissues showed significantly higher phagocytosis and increased infiltration of M1 macrophages. In vitro validation using MCF7 and THP1 macrophages treated with Kaiso-depleted exosomes showed a reduced expression of immune-related markers (CD47 and SIRPA) and macrophage polarization towards the M1 phenotype compared to MCF7 cells treated with exosomes isolated from high-Kaiso cells. Lastly, analysis of TCGA breast cancer patient data demonstrates that this gene signature is most prominent in the basal-like subtype, which is more frequently observed in AA breast cancer patients.
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The human kidney is known to possess renal progenitor cells (RPCs) that can assist in the repair of acute tubular injury. The RPCs are sparsely located as single cells throughout the kidney. We recently generated an immortalized human renal progenitor cell line (HRTPT) that co-expresses PROM1/CD24 and expresses features expected on RPCs. This included the ability to form nephrospheres, differentiate on the surface of Matrigel, and undergo adipogenic, neurogenic, and osteogenic differentiation. These cells were used in the present study to determine how the cells would respond when exposed to nephrotoxin. Inorganic arsenite (iAs) was chosen as the nephrotoxin since the kidney is susceptible to this toxin and there is evidence of its involvement in renal disease. Gene expression profiles when the cells were exposed to iAs for 3, 8, and 10 passages (subcultured at 1:3 ratio) identified a shift from the control unexposed cells. The cells exposed to iAs for eight passages were then referred with growth media containing no iAs and within two passages the cells returned to an epithelial morphology with strong agreement in differential gene expression between control and cells recovered from iAs exposure. Results show within three serial passages of the cells exposed to iAs there was a shift in morphology from an epithelial to a mesenchymal phenotype. EMT was suggested based on an increase in known mesenchymal markers. We found RPCs can undergo EMT when exposed to a nephrotoxin and undergo MET when the agent is removed from the growth media.
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Arsenitos , Transição Epitelial-Mesenquimal , Humanos , Transição Epitelial-Mesenquimal/genética , Arsenitos/toxicidade , Osteogênese , Células-Tronco , Rim , Células EpiteliaisRESUMO
The Schlafen 12 (SLFN12) protein regulates triple-negative breast cancer (TNBC) growth, differentiation, and proliferation. SLFN12 mRNA expression strongly correlates with TNBC patient survival. We sought to explore SLFN12 overexpression effects on in vivo human TNBC tumor xenograft growth and performed RNA-seq on xenografts to investigate related SLFN12 pathways. Stable SLFN12 overexpression reduced tumorigenesis, increased tumor latency, and reduced tumor volume. RNA-seq showed that SLFN12 overexpressing xenografts had higher luminal markers levels, suggesting that TNBC cells switched from an undifferentiated basal phenotype to a more differentiated, less aggressive luminal phenotype. SLFN12-overexpressing xenografts increased less aggressive BC markers, HER2 receptors ERBB2 and EGFR expression, which are not detectable by immunostaining in TNBC. Two cancer progression pathways, the NAD signaling pathway and the superpathway of cholesterol biosynthesis, were downregulated with SLFN12 overexpression. RNA-seq identified gene signatures associated with SLFN12 overexpression. Higher gene signature levels indicated good survival when tested on four independent BC datasets. These signatures behaved differently in African Americans than in Caucasian Americans, indicating a possible biological difference between these races that could contribute to the worse survival observed in African Americans with BC. These results suggest an increased SLFN12 expression modulates TNBC aggressiveness through a gene signature that could offer new treatment targets.
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BACKGROUND: The intestinal lining renews itself in a programmed fashion that can be affected by adaptation to surgical procedures such as gastric bypass. METHODS: To assess adaptive mechanisms in the human intestine after Roux-en-Y gastric bypass (RYGB), we biopsied proximal jejunum at the anastomotic site during surgery to establish a baseline and endoscopically re-biopsied the same area 6-9 months after bypass for comparison. Laser microdissection was performed on pre- and post-RYGB biopsies to isolate enterocytes for RNA sequencing. RESULTS: RNA sequencing suggested significant decreases in gene expression associated with G2/M DNA damage checkpoint regulation of the cell cycle pathway, and significant increases in gene expression associated with the CDP-diacylglycerol biosynthesis pathway TCA cycle II pathway, and pyrimidine ribonucleotide salvage pathway after RYGB. Since Schlafen 12 (SLFN12) is reported to influence enterocytic differentiation, we stained mucosa for SLFN12 and observed increased SLFN12 immunoreactivity. We investigated SLFN12 overexpression in HIEC-6 and FHs 74 Int intestinal epithelial cells and observed similar increased expression of the following genes that were also increased after RYGB: HES2, CARD9, SLC19A2, FBXW7, STXBP4, SPARCL1, and UTS. CONCLUSIONS: Our data suggest that RYGB promotes SLFN12 protein expression, cellular mechanism and replication pathways, and genes associated with differentiation and restitution (HES2, CARD9, SLC19A2), as well as obesity-related genes (FBXW7, STXBP4, SPARCL1, UTS).
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Diferenciação Celular , Enterócitos , Derivação Gástrica , Regulação da Expressão Gênica , Peptídeos e Proteínas de Sinalização Intracelular , Obesidade , Humanos , Diglicerídeos de Citidina Difosfato/metabolismo , Enterócitos/citologia , Enterócitos/metabolismo , Proteína 7 com Repetições F-Box-WD/metabolismo , Expressão Gênica , Intestinos , Proteínas de Membrana Transportadoras/metabolismo , Obesidade/genética , Obesidade/cirurgia , Obesidade/metabolismo , Análise de Sequência de RNA , Proteínas de Transporte Vesicular/metabolismo , Peptídeos e Proteínas de Sinalização Intracelular/genética , Diferenciação Celular/genéticaRESUMO
Women of African ancestry suffer higher rates of breast cancer mortality compared with all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated E3 ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER+ and ER- tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes.
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Neoplasias da Mama , Ubiquitina-Proteína Ligases , Neoplasias da Mama/genética , Neoplasias da Mama/metabolismo , Retículo Endoplasmático/metabolismo , Feminino , Humanos , Estudos Retrospectivos , Transdução de Sinais , Ubiquitina-Proteína Ligases/metabolismoRESUMO
The IARC classified arsenic (As) as "carcinogenic to humans." Despite the health consequences of arsenic exposure, there is no molecular signature available yet that can predict when exposure may lead to the development of disease. To understand the molecular processes underlying arsenic exposure and the risk of disease development, this study investigated the functional relationship between high arsenic exposure and disease risk using gene expression derived from human exposure. In this study, a three step analysis was employed: (1) the gene expression profiles obtained from two diverse arsenic-exposed Asian populations were utilized to identify differentially expressed genes associated with arsenic exposure in human subjects, (2) the gene expression profiles induced by arsenic exposure in four different myeloma cancer cell lines were used to define common genes and pathways altered by arsenic exposure, and (3) the genetic profiles of two publicly available human bladder cancer studies were used to test the significance of the common association of genes, identified in step 1 and step 2, to develop and validate a predictive model of primary bladder cancer risk associated with arsenic exposure. Our analysis shows that arsenic exposure to humans is mainly associated with organismal injury and abnormalities, immunological disease, inflammatory disease, gastrointestinal disease, and increased rates of a wide variety of cancers. In addition, arsenic exerts its toxicity by generating reactive oxygen species (ROS) and increasing ROS production causing the imbalance that leads to cell and tissue damage (oxidative stress). Oxidative stress activates inflammatory pathways leading to transformation of a normal cell to tumor cell specifically; there is significant evidence of the advancing changes in oxidative/nitrative stress during the progression of bladder cancer. Therefore, we examined the relation of differentially expressed genes due to exposure of arsenic in human and bladder cancer and developed a bladder cancer risk prediction model. In this study, integrin-linked kinase (ILK) was one of the most significant pathways identified between both arsenic exposed population which plays a key role in eliciting a protective response to oxidative damage in epidermal cells. On the other hand, several studies showed that arsenic trioxide (ATO) is useful for anticancer therapy although the mechanisms underlying its paradoxical effects are still not well understood. ATO has shown remarkable efficacy for the treatment of multiple myeloma; therefore, it will be helpful to understand the underlying cancer biology by which ATO exerts its inhibitory effect on the myeloma cells. Our study found that MAPK is one of the most active network between arsenic gene and ATO cell line which is involved in indicative of oxidative/nitrosative damage and well associated with the development of bladder cancer. The study identified a unique set of 147 genes associated with arsenic exposure and linked to molecular mechanisms of cancer. The risk prediction model shows the highest prediction ability for recurrent bladder tumors based on a very small subset (NKIRAS2, AKTIP, and HLA-DQA1) of the 147 genes resulting in AUC of 0.94 (95% CI: 0.744-0.995) and 0.75 (95% CI: 0.343-0.933) on training and validation data, respectively.
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Arsênio/efeitos adversos , Transcriptoma/genética , Neoplasias da Bexiga Urinária/induzido quimicamente , Povo Asiático , HumanosRESUMO
Damage to proximal tubules due to exposure to toxicants can lead to conditions such as acute kidney injury (AKI), chronic kidney disease (CKD) and ultimately end-stage renal failure (ESRF). Studies have shown that kidney proximal epithelial cells can regenerate particularly after acute injury. In the previous study, we utilized an immortalized in vitro model of human renal proximal tubule epithelial cells, RPTEC/TERT1, to isolate HRTPT cell line that co-expresses stem cell markers CD133 and CD24, and HREC24T cell line that expresses only CD24. HRTPT cells showed most of the key characteristics of stem/progenitor cells; however, HREC24T cells did not show any of these characteristics. The goal of this study was to further characterize and understand the global gene expression differences, upregulated pathways and gene interaction using scRNA-seq in HRTPT cells. Affymetrix microarray analysis identified common gene sets and pathways specific to HRTPT and HREC24T cells analysed using DAVID, Reactome and Ingenuity software. Gene sets of HRTPT cells, in comparison with publicly available data set for CD133+ infant kidney, urine-derived renal progenitor cells and human kidney-derived epithelial proximal tubule cells showed substantial similarity in organization and interactions of the apical membrane. Single-cell analysis of HRTPT cells identified unique gene clusters associated with CD133 and the 92 common gene sets from three data sets. In conclusion, the gene expression analysis identified a unique gene set for HRTPT cells and narrowed the co-expressed gene set compared with other human renal-derived cell lines expressing CD133, which may provide deeper understanding in their role as progenitor/stem cells that participate in renal repair.
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Células Epiteliais/metabolismo , Túbulos Renais Proximais/citologia , Túbulos Renais Proximais/fisiologia , Regeneração , Fatores Etários , Biomarcadores , Linhagem Celular , Biologia Computacional/métodos , Células Epiteliais/citologia , Perfilação da Expressão Gênica , Regulação da Expressão Gênica , Ontologia Genética , Humanos , Imunofenotipagem , Transdução de Sinais , Análise de Célula Única , Células-Tronco/citologia , Células-Tronco/metabolismo , TranscriptomaRESUMO
The use of digital pathology for the histomorphologic profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States. Multiplex multivariate analysis of the association of Kaiso's subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso's role in breast cancer progression.
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Neoplasias da Mama/metabolismo , Proteínas Associadas aos Microtúbulos/metabolismo , Fatores de Transcrição/metabolismo , Microambiente Tumoral , Automação Laboratorial , Neoplasias da Mama/genética , Neoplasias da Mama/mortalidade , Neoplasias da Mama/patologia , Linhagem Celular Tumoral , Feminino , Imunofluorescência , Regulação Neoplásica da Expressão Gênica , Humanos , Interpretação de Imagem Assistida por Computador , Microscopia de Fluorescência , Proteínas Associadas aos Microtúbulos/genética , Prognóstico , Estudos Retrospectivos , Medição de Risco , Fatores de Risco , Transdução de Sinais , Fatores de Tempo , Análise Serial de Tecidos , Fatores de Transcrição/genética , Evasão Tumoral , Estados Unidos/epidemiologiaRESUMO
Cadmium (Cd2+) is an environmental toxicant and a human carcinogen. Several studies show an association of Cd2+ exposure to the development of breast cancer. Previously, we have transformed the immortalized non-tumorigenic cell line MCF-10A with Cd2+ and have demonstrated that the transformed cells have anchorage independent growth. In a separate study, we showed that transformation of the immortalized urothelial cells with the environmental carcinogen arsenite (As3+) results in an increase in expression of genes associated with the basal subtype of bladder cancer. In this study, we determined if transformation of the MCF-10A cells with Cd2+ would have a similar effect on the expression of basal genes. The results of our study indicate that there is a decrease in expression of genes associated with keratinization and cornification and this gene signature includes the genes associated with the basal subtype of breast cancer. An analysis of human breast cancer databases indicates an increased expression of this gene signature is associated with a positive correlation to patient survival whereas a reduced expression/absence of this gene signature is associated with poor patient survival. Thus, our study suggests that transformation of the MCF-10A cells with Cd2+ produces a decreased basal gene expression profile that correlates to patient outcome.
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Schlafen 12 (SLFN12) is an intermediate human Schlafen that induces differentiation in enterocytes, prostate, and breast cancer. We hypothesized that SLFN12 influences lung cancer biology. We investigated survival differences in high versus low SLFN12-expressing tumors in two databases. We then adenovirally overexpressed SLFN12 (AdSLFN12) in HCC827, H23, and H1975 cells to model lung adenocarcinoma (LUAD), and in H2170 and HTB-182 cells representing lung squamous cell carcinoma (LUSC). We analyzed proliferation using a colorimetric assay, mRNA expression by RT-qPCR, and protein by Western blot. To further explore the functional relevance of SLFN12, we correlated SLFN12 with seventeen functional oncogenic gene signatures in human tumors. Low tumoral SLFN12 expression predicted worse survival in LUAD patients, but not in LUSC. AdSLFN12 modulated expression of SCGB1A1, SFTPC, HOPX, CK-5, CDH1, and P63 in a complex fashion in these cells. AdSLFN12 reduced proliferation in all LUAD cell lines, but not in LUSC cells. SLFN12 expression inversely correlated with expression of a myc-associated gene signature in LUAD, but not LUSC tumors. SLFN12 overexpression reduced c-myc protein in LUAD cell lines but not in LUSC, by inhibiting c-myc translation. Our results suggest SLFN12 improves prognosis in LUAD in part via a c-myc-dependent slowing of proliferation.
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PURPOSE: Compared with their European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. This disparity is greatest in hormone receptor-positive subtypes. Here we uncover biological factors underlying this disparity by comparing functional expression and prognostic significance of master transcriptional regulators of luminal differentiation. EXPERIMENTAL DESIGN: Data and biospecimens from 262 AA and 293 EA patients diagnosed with breast cancer from 2001 to 2010 at a major medical center were analyzed by IHC for functional biomarkers of luminal differentiation, including estrogen receptor (ESR1) and its pioneer factors, FOXA1 and GATA3. Integrated comparison of protein levels with network-level gene expression analysis uncovered predictive correlations with race and survival. RESULTS: Univariate or multivariate HRs for overall survival, estimated from digital IHC scoring of nuclear antigen, show distinct differences in the magnitude and significance of these biomarkers to predict survival based on race: ESR1 [EA HR = 0.47; 95% confidence interval (CI), 0.31-0.72 and AA HR = 0.77; 95% CI, 0.48-1.18]; FOXA1 (EA HR = 0.38; 95% CI, 0.23-0.63 and AA HR = 0.53; 95% CI, 0.31-0.88), and GATA3 (EA HR = 0.36; 95% CI, 0.23-0.56; AA HR = 0.57; CI, 0.56-1.4). In addition, we identify genes in the downstream regulons of these biomarkers highly correlated with race and survival. CONCLUSIONS: Even within clinically homogeneous tumor groups, regulatory networks that drive mammary luminal differentiation reveal race-specific differences in their association with clinical outcome. Understanding these biomarkers and their downstream regulons will elucidate the intrinsic mechanisms that drive racial disparities in breast cancer survival.
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População Negra/genética , Neoplasias da Mama/mortalidade , Receptor alfa de Estrogênio/metabolismo , Fator de Transcrição GATA3/metabolismo , Regulação Neoplásica da Expressão Gênica , Fator 3-alfa Nuclear de Hepatócito/metabolismo , População Branca/genética , Biomarcadores Tumorais/metabolismo , Neoplasias da Mama/etnologia , Neoplasias da Mama/metabolismo , Neoplasias da Mama/patologia , Feminino , Disparidades nos Níveis de Saúde , Humanos , Imuno-Histoquímica/métodos , Pessoa de Meia-Idade , Taxa de Sobrevida , Estados UnidosRESUMO
[This corrects the article DOI: 10.1371/journal.pone.0053292.].
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Until recently, an elevated disease risk has been ascribed to a genetic predisposition, however, exciting progress over the past years has discovered alternate elements of inheritance that involve epigenetic regulation. Epigenetic changes are heritably stable alterations that include DNA methylation, histone modifications and RNA-mediated silencing. Aberrant DNA methylation is a common molecular basis for a number of important human diseases, including breast cancer. Changes in DNA methylation profoundly affect global gene expression patterns. What is emerging is a more dynamic and complex association between DNA methylation and gene expression than previously believed. Although many tools have already been developed for analyzing genome-wide gene expression data, tools for analyzing genome-wide DNA methylation have not yet reached the same level of refinement. Here we provide an in-depth analysis of DNA methylation in parallel with gene expression data characteristics and describe the particularities of low-level and high-level analyses of DNA methylation data. Low-level analysis refers to pre-processing of methylation data (i.e. normalization, transformation and filtering), whereas high-level analysis is focused on illustrating the application of the widely used class comparison, class prediction and class discovery methods to DNA methylation data. Furthermore, we investigate the influence of DNA methylation on gene expression by measuring the correlation between the degree of CpG methylation and the level of expression and to explore the pattern of methylation as a function of the promoter region.
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Neoplasias da Mama/genética , Metilação de DNA/genética , DNA/metabolismo , Regulação Neoplásica da Expressão Gênica/genética , Mapeamento Cromossômico , Ilhas de CpG/genética , Epigênese Genética , Feminino , Expressão Gênica , Humanos , Análise de Sequência com Séries de Oligonucleotídeos , Regiões Promotoras Genéticas/genética , Transcrição Gênica/genéticaRESUMO
Radiotherapy is a mainstay of cancer treatment, used in either a curative or palliative manner to treat approximately 50% of patients with cancer. Normal tissue toxicity limits the doses used in standard radiation therapy protocols and impedes improvements in radiotherapy efficacy. Damage to surrounding normal tissues can produce reactions ranging from bothersome symptoms that negatively affect quality of life to severe life-threatening complications. Improved ways of predicting, before treatment, the risk for development of normal tissue toxicity may allow for more personalized treatment and reduce the incidence and severity of late effects. There is increasing recognition that the cause of normal tissue toxicity is multifactorial and includes genetic factors in addition to radiation dose and volume of exposure, underlying comorbidities, age, concomitant chemotherapy or hormonal therapy, and use of other medications. An understanding of the specific genetic risk factors for normal tissue response to radiation has the potential to enhance our ability to predict adverse outcomes at the treatment-planning stage. Therefore, the field of radiogenomics has focused upon the identification of genetic variants associated with normal tissue toxicity resulting from radiotherapy. Innovative analytic methods are being applied to the discovery of risk variants and development of integrative predictive models that build on traditional normal tissue complication probability models by incorporating genetic information. Results from initial studies provide promising evidence that genetic-based risk models could play an important role in the implementation of precision medicine for radiation oncology through enhancing the ability to predict normal tissue reactions and thereby improve cancer treatment.
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Neoplasias/radioterapia , Polimorfismo de Nucleotídeo Único/efeitos da radiação , Lesões por Radiação/prevenção & controle , HumanosRESUMO
CD4⺠T cells are critical regulators of immune responses, but their functional role in human breast cancer is relatively unknown. The goal of this study was to produce an image of CD4⺠T cells infiltrating breast tumors using limited ex vivo manipulation to better understand the in vivo differences associated with patient prognosis. We performed comprehensive molecular profiling of infiltrating CD4⺠T cells isolated from untreated invasive primary tumors and found that the infiltrating T cell subpopulations included follicular helper T (Tfh) cells, which have not previously been found in solid tumors, as well as Th1, Th2, and Th17 effector memory cells and Tregs. T cell signaling pathway alterations included a mixture of activation and suppression characterized by restricted cytokine/chemokine production, which inversely paralleled lymphoid infiltration levels and could be reproduced in activated donor CD4⺠T cells treated with primary tumor supernatant. A comparison of extensively versus minimally infiltrated tumors showed that CXCL13-producing CD4⺠Tfh cells distinguish extensive immune infiltrates, principally located in tertiary lymphoid structure germinal centers. An 8-gene Tfh signature, signifying organized antitumor immunity, robustly predicted survival or preoperative response to chemotherapy. Our identification of CD4⺠Tfh cells in breast cancer suggests that they are an important immune element whose presence in the tumor is a prognostic factor.
Assuntos
Neoplasias da Mama/imunologia , Linfócitos T Auxiliares-Indutores/imunologia , Antígenos CD/metabolismo , Neoplasias da Mama/mortalidade , Neoplasias da Mama/patologia , Estudos de Casos e Controles , Citocinas/genética , Citocinas/metabolismo , Feminino , Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Estimativa de Kaplan-Meier , Análise de Sequência com Séries de Oligonucleotídeos , Receptores de Antígenos de Linfócitos T/metabolismo , Transdução de Sinais/imunologia , Linfócitos T Auxiliares-Indutores/metabolismo , Linfócitos T Reguladores/imunologia , Linfócitos T Reguladores/metabolismo , TranscriptomaRESUMO
The phosphatidylinositol 3' kinase (PI3K) pathway is commonly activated in breast cancer and aberrations such as PI3K mutations are common. Recent exciting clinical trial results in advanced estrogen receptor-positive (ER) breast cancer support mTOR activation is a major means of estrogen-independent tumor growth. Hence the means to identify a responsive breast cancer population that would most benefit from these compounds in the adjuvant or earlier stage setting is of high interest. Here we study PIK3CA genotype as well as a previously reported PI3K/mTOR-pathway gene signature (PIK3CA-GS) and their ability to estimate the level of PI3K pathway activation in two clinical trials of newly diagnosed ER-positive breast cancer patients- a total of 81 patients- one of which was randomized between letrozole and placebo vs letrozole and everolimus. The main objectives were to correlate the baseline PIK3CA genotype and GS with the relative change from baseline to day 15 in Ki67 (which has been shown to be prognostic in breast cancer) and phosphorylated S6 (S240) immunohistochemistry (a substrate of mTOR). In the randomized dataset, the PIK3CA-GS could identify those patients with the largest relative decreases in Ki67 to letrozole/everolimus (R = -0.43, p = 0.008) compared with letrozole/placebo (R = 0.07, p = 0.58; interaction test p = 0.02). In a second dataset of pre-surgical everolimus alone, the PIK3CA-GS was not significantly correlated with relative change in Ki67 (R = -0.11, p = 0.37) but with relative change in phosphorlyated S6 (S240) (R = -0.46, p = 0.028). PIK3CA genotype was not significantly associated with any endpoint in either datasets. Our results suggest that the PIK3CA-GS has potential to identify those ER-positive BCs who may benefit from the addition of everolimus to letrozole. Further evaluation of the PIK3CA-GS as a predictive biomarker is warranted as it may facilitate better selection of responsive patient populations for mTOR inhibition in combination with letrozole.