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1.
Proc Natl Acad Sci U S A ; 118(3)2021 Jan 19.
Artigo em Inglês | MEDLINE | ID: mdl-33452133

RESUMO

The harsh microenvironment of ductal carcinoma in situ (DCIS) exerts strong evolutionary selection pressures on cancer cells. We hypothesize that the poor metabolic conditions near the ductal center foment the emergence of a Warburg Effect (WE) phenotype, wherein cells rapidly ferment glucose to lactic acid, even in normoxia. To test this hypothesis, we subjected low-glycolytic breast cancer cells to different microenvironmental selection pressures using combinations of hypoxia, acidosis, low glucose, and starvation for many months and isolated single clones for metabolic and transcriptomic profiling. The two harshest conditions selected for constitutively expressed WE phenotypes. RNA sequencing analysis of WE clones identified the transcription factor KLF4 as potential inducer of the WE phenotype. In stained DCIS samples, KLF4 expression was enriched in the area with the harshest microenvironmental conditions. We simulated in vivo DCIS phenotypic evolution using a mathematical model calibrated from the in vitro results. The WE phenotype emerged in the poor metabolic conditions near the necrotic core. We propose that harsh microenvironments within DCIS select for a WE phenotype through constitutive transcriptional reprogramming, thus conferring a survival advantage and facilitating further growth and invasion.

2.
Methods Mol Biol ; 2194: 143-175, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-32926366

RESUMO

High-throughput sequencing (HTS) has revolutionized researchers' ability to study the human transcriptome, particularly as it relates to cancer. Recently, HTS technology has advanced to the point where now one is able to sequence individual cells (i.e., "single-cell sequencing"). Prior to single-cell sequencing technology, HTS would be completed on RNA extracted from a tissue sample consisting of multiple cell types (i.e., "bulk sequencing"). In this chapter, we review the various bioinformatics and statistical methods used in the processing, quality control, and analysis of bulk and single-cell RNA sequencing methods. Additionally, we discuss how these methods are also being used to study tumor heterogeneity.


Assuntos
Biologia Computacional/métodos , Neoplasias/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Interpretação Estatística de Dados , Bases de Dados Genéticas , Perfilação da Expressão Gênica , Humanos , Controle de Qualidade , Neoplasias Cutâneas/genética
3.
Int J Cancer ; 148(2): 307-319, 2021 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-32851660

RESUMO

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.

4.
Front Pediatr ; 8: 549, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33117761

RESUMO

Background: A major challenge in implementing personalized medicine in pediatrics is identifying appropriate drug dosages for children. The majority of drug dosing studies have been based on adult populations, often with modification of the dosing for children based on size and weight. However, the growth and development experienced by children between birth and adulthood represents a dynamically changing biological system, with implications for effective drug dosing, efficacy as well as potential drug toxicity. The purpose of this study was to apply a metabolomics approach to gain preliminary insights into the ontogeny of liver function from newborn to adolescent. Methods: Metabolites were measured in 98 post-mortem pediatric liver samples in two experiments 3 batches of samples, allowing for both technical and biological validation. After extensive quality control, imputation and normalization, non-parametric tests were used to determine which metabolite levels differ between the four age groups (AG) ranging in age from newborn to adolescent (AG1-children <1 year; AG2-children with age between 1 and 6 years; AG3-children with age between 6 and 12 years; AG4-children with age between 12 and 18 years). To identify which metabolites had different concentration levels among the age groups, Kruskal-Wallis and Spearman correlation tests were conducted. Pathway analysis utilized the Gamma Method. Correction for multiple testing was completed using Bonferroni correction. Results: We found 41 metabolites (out of 884) that were biologically validated, and of those 25 were technically replicated, of which 24 were known metabolites. For the majority of these 24 metabolites, concentration levels were significantly lower in newborns than in the other age groups, many of which were long chain fatty acids or involved in pyrimidine or purine metabolism. Additionally, we found two KEGG pathways enriched for association with age: betaine metabolism and alpha linolenic acid and linoleic acid metabolism. Conclusions: Understanding the role that ontogeny of childhood liver plays may aid in determining better drug dosing algorithms for children.

5.
Support Care Cancer ; 2020 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-32975643

RESUMO

OBJECTIVE: Identify predisposing, enabling, and reinforcing factors impacting genetic counseling/testing among ovarian cancer patients guided by Green and Kreuter's PRECEDE-PROCEED model. METHODS: Gynecologic oncology providers (N = 4), genetic counselors (N = 4), and ovarian cancer patients (N = 9) completed semi-structured qualitative interviews exploring participants' knowledge of and experiences with genetic counseling/testing. Interviews were audio recorded, transcribed verbatim, and analyzed using inductive content analysis by two independent raters. RESULTS: Thematic analysis identified predisposing, enabling, and reinforcing factors impacting referral for and uptake of genetic counseling/testing. Predisposing factors included participant's knowledge, beliefs, and attitudes related to genetic counseling/testing. Both patients and providers also cited that insurance coverage and out-of-pocket cost are major concerns for ovarian cancer patients considering genetic testing. Finally, both patients and providers emphasized that genetic counseling/testing would provide additional information to an ovarian cancer patient. While providers emphasized that genetic testing results were useful for informing a patient's personal treatment plan, patients emphasized that this knowledge would be beneficial for their family members. CONCLUSION: Barriers to genetic testing for ovarian cancer patients exist at multiple levels, including the patient (e.g., knowledge, attitudes), the provider (e.g., workload, availability of services), the institution (e.g., difficulty with referrals/scheduling), and the healthcare system (e.g., insurance/cost). Interventions aiming to increase genetic testing among ovarian cancer patients will likely need to target multiple levels of influence. Future quantitative studies are needed to replicate these results. This line of work will inform specific multilevel intervention strategies that are adaptable to different practice settings, ultimately improving guideline concordant care.

6.
J Geriatr Oncol ; 2020 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-32859560

RESUMO

OBJECTIVES: To establish whether clinicopathologic and genomic characteristics may explain the poor prognosis associated with advanced age in ER+/HER2- breast cancer. MATERIALS AND METHODS: The cohort included 271 consecutive post-menopausal patients with ER+/HER2- invasive breast cancer ages 55 years and older. Patients were categorized as "younger" (ages 55- < 75) and "older" (ages ≥75). The Kaplan-Meier method was used to estimate locoregional recurrence (LRR), recurrence-free interval (RFi), and overall survival (OS). Gene expression of tumor samples was assessed with Affymetrix Rosetta/Merck Human RSTA microarray platform. Differential gene expression analysis of tumor samples was performed using R package Limma. RESULTS: 271 breast cancer patients were identified, including 186 younger and 85 older patients. Older patients had higher rates of Luminal B subtype (53% vs 34%) and lower rates of Luminal A subtype (42% vs 58%, p = 0.02). Older patients were less likely to receive chemotherapy (9% vs 40%, p < 0.001) and hormone therapy (71% vs 89%, p < 0.001). For cases of grade 1-2 disease, older patients had a higher proportion of the luminal B subtype (49% vs. 30%, p = 0.014). Age ≥ 75 predicted for inferior OS (HR = 3.06, p < 0.001). The luminal B subtype predicted for inferior OS (HR = 2.12, p = 0.014), RFi (HR 5.02, p < 0.001), and LRR (HR = 3.12, p = 0.045). There were no significant differences in individual gene expression between the two groups. CONCLUSION: Women with ER+/HER2- breast cancer ≥75 years old had higher rates of the more aggressive luminal B subtype and inferior outcomes. Genomic testing of these patients should be strongly considered, and treatment should be intensified when appropriate.

7.
Pediatr Blood Cancer ; 67(7): e28370, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32386107

RESUMO

BACKGROUND: The combination of gemcitabine and docetaxel is often used to treat patients with recurrent sarcoma. Nab-paclitaxel is a taxane modified to improve drug exposure and increase intratumoral accumulation and, in combination with gemcitabine, is standard therapy for pancreatic cancer. Applying the dosages and schedule used for pancreatic cancer, we performed a phase II trial to assess the response rate of gemcitabine and nab-paclitaxel in patients with relapsed Ewing sarcoma. PROCEDURE: Using a Simon's two-stage design to identify a response rate of ≥ 35%, patients received nab-paclitaxel 125 mg/m2 followed by gemcitabine 1000 mg/m2 i.v. on days 1, 8, and 15 of four-week cycles. Immunohistochemical analysis of archival tissue was performed to identify possible biomarkers of response. RESULTS: Eleven patients from four institutions enrolled, with a median age of 22 years (range, 14-27). Patients were heavily pretreated (median 3 prior regimens, range, 1-7). Thirty-five cycles were administered (median 2, range, 1-8). Accrual was stopped after 11 patients, due to only one confirmed partial response. Two other patients had partial responses after two cycles, but withdrew because of adverse effects or progression before confirmation of continued response. The predominant toxicity was myelosuppression, and four (36%) patients were removed due to hematologic toxicity despite pegfilgrastim and dose reductions. Expression of secreted protein, acidic and rich in cysteine (SPARC) and CAV-1 in archival tumors was not predictive of clinical benefit in this small cohort of patients. CONCLUSIONS: In patients with heavily pretreated Ewing sarcoma, the confirmed response rate of 9% was similar to multi-institutional studies of gemcitabine and docetaxel.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias Ósseas/tratamento farmacológico , Recidiva Local de Neoplasia/tratamento farmacológico , Sarcoma de Ewing/tratamento farmacológico , Adolescente , Adulto , Albuminas/administração & dosagem , Neoplasias Ósseas/patologia , Criança , Desoxicitidina/administração & dosagem , Desoxicitidina/análogos & derivados , Feminino , Seguimentos , Humanos , Masculino , Recidiva Local de Neoplasia/patologia , Paclitaxel/administração & dosagem , Prognóstico , Sarcoma de Ewing/patologia , Adulto Jovem
9.
Comput Biol Med ; 118: 103625, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31999549

RESUMO

Identification of novel molecular subtypes of disease using multi-source 'omics data is an active area of on-going research. Integrative clustering is a powerful approach to identify latent subtype structure inherent in the data sets accounting for both between and within data correlations. We propose a new integrative network-based clustering method using the non-negative matrix factorization, nNMF, for clustering multiple types of interrelated datasets assayed on same tumor-samples. nNMF utilizes the consensus matrices generated using the non-negative matrix factorization (NMF) algorithm on each type of data as networks among the patient samples. The multiple networks are then combined, and a comprehensive network structure is created optimizing the strengths of the relationships. A spectral clustering algorithm is then used on the final network data to determine the cluster groups. nNMF is a non-parametric method and therefore prior assumptions on the statistical distribution of data is not required. The application of the proposed nNMF method has been provided with simulated and the real-life datasets obtained from The Cancer Genome Atlas studies on glioblastoma, lower grade glioma and head and neck cancer. nNMF was found to be working competitively with previous methods and sometimes better as compared to previous NMF or model-based method especially when the signal to noise ratio is small. The novel nNMF method allows researchers to utilize such relationships to identify the latent subtype structure inherent in the data so that further association studies can be carried out. The R program for the nNMF will be available upon request.

10.
Gynecol Oncol ; 156(2): 459-466, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31839342

RESUMO

OBJECTIVE: Although ovarian cancer is a deadly disease, approximately a third of women survive ≥9 years after diagnosis. The factors associated with achieving long-term survival are not well understood. In this study, data from the Surveillance, Epidemiology, and End Results (SEER) program were used to determine predictors of survival trajectories among women with epithelial ovarian cancer and across histotype (high-grade serous carcinoma (HGSC) and non-HGSC). METHODS: Data on 35,868 women diagnosed with epithelial ovarian cancer in 2004-2016 were extracted from SEER. Extended Cox proportional hazards regression was used to estimate overall and histotype-specific associations between patient and tumor characteristics and all-cause mortality within each survival time (t) interval (t < 3, 3 ≤ t < 6, 6 ≤ t < 9, and 9 ≤ t < 13 years). RESULTS: Age at diagnosis, marital status, race/ethnicity, stage, and surgery were more strongly associated with mortality in the short-term survival period, and these associations waned with increasing survival time. Exceptions to this pattern were age >70 years at diagnosis, where a high risk of mortality was observed in both the t < 3 and t ≥ 9 year time periods, and non-Hispanic Asian/Pacific Islanders, where a more pronounced inverse association with mortality was observed in t ≥ 9 years after diagnosis. Similar associations were observed for HGSC, although the waning effect was not apparent for most characteristics. Mortality associations for non-HGSC were more pronounced for stage and race/ethnicity, primarily for non-Hispanic Asian/Pacific Islanders. CONCLUSIONS: Most patient and tumor characteristics were more strongly associated with mortality in the years following diagnosis, but have declining impact with increasing survival time. Given this waning effect, it is critical to identify factors impacting risk of mortality as ovarian cancer patients advance through the survival trajectory.


Assuntos
Carcinoma Epitelial do Ovário/mortalidade , Neoplasias Ovarianas/mortalidade , Grupo com Ancestrais do Continente Africano/estatística & dados numéricos , Idoso , Carcinoma Epitelial do Ovário/etnologia , Carcinoma Epitelial do Ovário/patologia , Grupo com Ancestrais do Continente Europeu/estatística & dados numéricos , Feminino , Humanos , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Grupo com Ancestrais Oceânicos/estatística & dados numéricos , Neoplasias Ovarianas/etnologia , Neoplasias Ovarianas/patologia , Prognóstico , Programa de SEER , Estados Unidos/epidemiologia
11.
Clin Genet ; 97(2): 370-375, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31600840

RESUMO

Germline mutations (eg, BRCA1/2) have prognostic and treatment implications for ovarian cancer (OVCA) patients. Thus, national guidelines recommend genetic testing for OVCA patients. The present study examines patterns and predictors of genetics referral in OVCA patients. Electronic medical record data were abstracted retrospectively from 557 OVCA patients treated from 1 January 2001 to 31 December 2015. Logistic regression models identified sociodemographic characteristics, disease/treatment characteristics, family history data, provider characteristics, and survival data that predicted genetics referral. Overall, 27.5% of patients received referral. Eleven variables predicting referral were selected during stepwise regression: younger age, White race, not having private insurance, professional school education, year of OVCA diagnosis, platinum sensitivity, female gynecologic oncologist, chemotherapy administered by a gynecologic oncologist, clinical trial enrollment, longer overall survival, and family history of OVCA. Genetics referral among OVCA patients was similar to rates reported nationwide. Unique predictive factors will contribute to quality improvement and should be validated at a multi-institutional level to ensure guideline concordant care is provided to all OVCA patients. Future research should identify both patient-level and provider-level factors associated with genetics referral.

12.
Semin Cancer Biol ; 61: 1-10, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-31437624

RESUMO

Rare cancers make of more than 20% of cancer cases. Due to the rare nature, less research has been conducted on rare cancers resulting in worse outcomes for patients with rare cancers compared to common cancers. The ability to study rare cancers is impaired by the ability to collect a large enough set of patients to complete an adequately powered genomic study. In this manuscript we outline analytical approaches and public genomic datasets that have been used in genomic studies of rare cancers. These statistical analysis approaches and study designs include: gene set / pathway analyses, pedigree and consortium studies, meta-analysis or horizontal integration, and integration of multiple types of genomic information or vertical integration. We also discuss some of the publicly available resources that can be leveraged in rare cancer genomic studies.

13.
Bioinformatics ; 36(1): 257-263, 2020 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-31199438

RESUMO

MOTIVATION: Missingness in label-free mass spectrometry is inherent to the technology. A computational approach to recover missing values in metabolomics and proteomics datasets is important. Most existing methods are designed under a particular assumption, either missing at random or under the detection limit. If the missing pattern deviates from the assumption, it may lead to biased results. Hence, we investigate the missing patterns in free mass spectrometry data and develop an omnibus approach GMSimpute, to allow effective imputation accommodating different missing patterns. RESULTS: Three proteomics datasets and one metabolomics dataset indicate missing values could be a mixture of abundance-dependent and abundance-independent missingness. We assess the performance of GMSimpute using simulated data (with a wide range of 80 missing patterns) and metabolomics data from the Cancer Genome Atlas breast cancer and clear cell renal cell carcinoma studies. Using Pearson correlation and normalized root mean square errors between the true and imputed abundance, we compare its performance to K-nearest neighbors' type approaches, Random Forest, GSimp, a model-based method implemented in DanteR and minimum values. The results indicate GMSimpute provides higher accuracy in imputation and exhibits stable performance across different missing patterns. In addition, GMSimpute is able to identify the features in downstream differential expression analysis with high accuracy when applied to the Cancer Genome Atlas datasets. AVAILABILITY AND IMPLEMENTATION: GMSimpute is on CRAN: https://cran.r-project.org/web/packages/GMSimpute/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Biologia Computacional , Espectrometria de Massas , Viés , Análise por Conglomerados , Biologia Computacional/métodos , Limite de Detecção , Metabolômica , Proteômica
14.
Clin Pharmacol Ther ; 107(3): 563-570, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31549389

RESUMO

A risk mitigation strategy was implemented to determine if a higher prophylactic voriconazole dosage in patients with CYP2C19 rapid metabolizer neutropenic acute myeloid leukemia (AML) reduces the incidence of subtherapeutic trough concentrations. Patients with AML (n = 263) were preemptively genotyped for CYP2C19*2, *3, and *17 alleles as part of a single-center prospective, interventional, quality improvement study. CYP2C19 rapid metabolizers (CYP2C19*1/*17) were recommended to receive interventional voriconazole 300 mg twice daily, ultrarapid metabolizers (CYP2C19*17/*17) were recommended to avoid voriconazole, and all others received the standard prophylactic dosage of 200 mg twice daily. In this real-world setting, 202 patients (76.8%) were prescribed prophylactic voriconazole, and of these patients 176 (87.1%) received CYP2C19-guided prophylactic dosing. Voriconazole trough concentrations were obtained for 41 of the 58 (70.7%) CYP2C19 rapid metabolizers prescribed prophylactic voriconazole. Interventional voriconazole resulted in higher plasma trough concentrations (median 2.7 µg/mL) compared with the standard prophylactic dosage (median 0.6 µg/mL; P = 0.001). Subtherapeutic concentrations were avoided in 83.8% of CYP2C19 rapid metabolizers receiving interventional dosage compared to 46.2% receiving standard dosage (P = 0.02). CYP2C19 genotyping to preemptively guide prophylactic voriconazole dosing is feasible and may be a potential strategy for reducing the risk of subtherapeutic trough concentrations that potentiate breakthrough fungal infections.


Assuntos
Antifúngicos/administração & dosagem , Citocromo P-450 CYP2C19/genética , Leucemia Mieloide Aguda/complicações , Micoses/prevenção & controle , Voriconazol/administração & dosagem , Adulto , Idoso , Idoso de 80 Anos ou mais , Alelos , Antifúngicos/farmacocinética , Relação Dose-Resposta a Droga , Feminino , Genótipo , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Neutropenia/etiologia , Estudos Prospectivos , Gestão de Riscos , Voriconazol/farmacocinética , Adulto Jovem
15.
Sci Rep ; 9(1): 14421, 2019 10 08.
Artigo em Inglês | MEDLINE | ID: mdl-31594982

RESUMO

Cancer cell lines (CCLs) have been widely used to study of cancer. Recent studies have called into question the reliability of data collected on CCLs. Hence, we set out to determine CCLs that tend to be overly sensitive or resistant to a majority of drugs utilizing a nonlinear mixed-effects (NLME) modeling framework. Using drug response data collected in the Cancer Cell Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC), we determined the optimal functional form for each drug. Then, a NLME model was fit to the drug response data, with the estimated random effects used to determine sensitive or resistant CCLs. Out of the roughly 500 CCLs studies from the CCLE, we found 17 cell lines to be overly sensitive or resistant to the studied drugs. In the GDSC, we found 15 out of the 990 CCLs to be excessively sensitive or resistant. These results can inform researchers in the selection of CCLs to include in drug studies. Additionally, this study illustrates the need for assessing the dose-response functional form and the use of NLME models to achieve more stable estimates of drug response parameters.


Assuntos
Linhagem Celular Tumoral/efeitos dos fármacos , Desenho de Fármacos , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Neoplasias/tratamento farmacológico , Biomarcadores Farmacológicos/análise , Linhagem Celular Tumoral/classificação , Relação Dose-Resposta a Droga , Genômica , Humanos , Neoplasias/patologia , Dinâmica não Linear
16.
Cancer Epidemiol Biomarkers Prev ; 28(7): 1117-1126, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-30948450

RESUMO

BACKGROUND: Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk. METHODS: CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression. RESULTS: Three CNVRs were associated (P < 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10-5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10-47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10-2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10-5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10-7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10-5). CONCLUSIONS: Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression. IMPACT: Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.


Assuntos
Carcinoma Epitelial do Ovário/genética , Variações do Número de Cópias de DNA/genética , Estudo de Associação Genômica Ampla/métodos , Estudos de Casos e Controles , Feminino , Humanos
17.
Leukemia ; 33(1): 205-216, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-30026572

RESUMO

Chronic myelomonocytic leukemia (CMML) is a clinically heterogeneous neoplasm in which JAK2 inhibition has demonstrated reductions in inflammatory cytokines and promising clinical activity. We hypothesize that annotation of inflammatory cytokines may uncover mutation-independent cytokine subsets associated with novel CMML prognostic features. A Luminex cytokine profiling assay was utilized to profile cryopreserved peripheral blood plasma from 215 CMML cases from three academic centers, along with center-specific, age-matched plasma controls. Significant differences were observed between CMML patients and healthy controls in 23 out of 45 cytokines including increased cytokine levels in IL-8, IP-10, IL-1RA, TNF-α, IL-6, MCP-1/CCL2, hepatocyte growth factor (HGF), M-CSF, VEGF, IL-4, and IL-2RA. Cytokine associations were identified with clinical and genetic features, and Euclidian cluster analysis identified three distinct cluster groups associated with important clinical and genetic features in CMML. CMML patients with decreased IL-10 expression had a poor overall survival when compared to CMML patients with elevated expression of IL-10 (P = 0.017), even when adjusted for ASXL1 mutation and other prognostic features. Incorporating IL-10 with the Mayo Molecular Model statistically improved the prognostic ability of the model. These established cytokines, such as IL-10, as prognostically relevant and represent the first comprehensive study exploring the clinical implications of the CMML inflammatory state.


Assuntos
Biomarcadores Tumorais/genética , Citocinas/sangue , Mediadores da Inflamação/sangue , Leucemia Mielomonocítica Crônica/patologia , Mutação , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , Feminino , Seguimentos , Humanos , Leucemia Mielomonocítica Crônica/sangue , Leucemia Mielomonocítica Crônica/classificação , Leucemia Mielomonocítica Crônica/genética , Masculino , Pessoa de Meia-Idade , Prognóstico , Taxa de Sobrevida
18.
Br J Haematol ; 184(5): 735-743, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30548250

RESUMO

Combined lenalidomide and dexamethasone is a standard-of-care therapy for the treatment of older adults with multiple myeloma. Lenalidomide monotherapy has not been evaluated in newly diagnosed myeloma patients. We conducted a phase II study, evaluating a response-adapted therapy for older adults newly diagnosed with multiple myeloma without high-risk features who were ineligible for high-dose therapy and stem cell transplant. Patients were started on single-agent lenalidomide, and low-dose dexamethasone was added in the event of progressive disease, in a response-adapted approach. The primary endpoint was progression-free survival (PFS), and the International Myeloma Working Group's uniform response criteria were used to assess response and progression. Twenty-seven patients were enrolled, and 20 (74%) experienced a partial response or better to this response-adapted therapy. After a median follow-up of 69 months, the median PFS was 36 months [95% confidence interval (CI), 29·8 to not reached], and the median overall survival was 65 months (95% CI, 35·3 to not reached). Grade 3/4 adverse events were mainly haematological in nature. This response-adapted therapy in this patient population is feasible and results in durable responses that compare favourably with concurrent lenalidomide and dexamethasone. These results should be validated in prospective studies.


Assuntos
Lenalidomida/administração & dosagem , Mieloma Múltiplo/tratamento farmacológico , Mieloma Múltiplo/mortalidade , Idoso , Idoso de 80 Anos ou mais , Intervalo Livre de Doença , Feminino , Seguimentos , Humanos , Masculino , Fatores de Risco , Taxa de Sobrevida
19.
Hum Mol Genet ; 28(8): 1331-1342, 2019 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-30576442

RESUMO

X chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women's cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10-10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of residual disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.


Assuntos
Carcinoma Epitelial do Ovário/genética , Genes Ligados ao Cromossomo X/genética , Inativação do Cromossomo X/fisiologia , Idoso , Alelos , Carcinoma Epitelial do Ovário/metabolismo , Cromossomos Humanos X/genética , Análise por Conglomerados , Metilação de DNA/genética , Epigênese Genética/genética , Feminino , Regulação da Expressão Gênica/genética , Frequência do Gene/genética , Estudos de Associação Genética/métodos , Genótipo , Humanos , Pessoa de Meia-Idade , Neoplasias Ovarianas/genética , Regiões Promotoras Genéticas/genética , RNA Longo não Codificante , Fatores de Transcrição/genética , Inativação do Cromossomo X/genética
20.
BMC Bioinformatics ; 19(1): 474, 2018 Dec 12.
Artigo em Inglês | MEDLINE | ID: mdl-30541426

RESUMO

BACKGROUND: Unsupervised clustering represents one of the most widely applied methods in analysis of high-throughput 'omics data. A variety of unsupervised model-based or parametric clustering methods and non-parametric clustering methods have been proposed for RNA-seq count data, most of which perform well for large samples, e.g. N ≥ 500. A common issue when analyzing limited samples of RNA-seq count data is that the data follows an over-dispersed distribution, and thus a Negative Binomial likelihood model is often used. Thus, we have developed a Negative Binomial model-based (NBMB) clustering approach for application to RNA-seq studies. RESULTS: We have developed a Negative Binomial Model-Based (NBMB) method to cluster samples using a stochastic version of the expectation-maximization algorithm. A simulation study involving various scenarios was completed to compare the performance of NBMB to Gaussian model-based or Gaussian mixture modeling (GMM). NBMB was also applied for the clustering of two RNA-seq studies; type 2 diabetes study (N = 96) and TCGA study of ovarian cancer (N = 295). Simulation results showed that NBMB outperforms GMM applied with different transformations in majority of scenarios with limited sample size. Additionally, we found that NBMB outperformed GMM for small clusters distance regardless of sample size. Increasing total number of genes with fixed proportion of differentially expressed genes does not change the outperformance of NBMB, but improves the overall performance of GMM. Analysis of type 2 diabetes and ovarian cancer tumor data with NBMB found good agreement with the reported disease subtypes and the gene expression patterns. This method is available in an R package on CRAN named NB.MClust. CONCLUSION: Use of Negative Binomial model based clustering is advisable when clustering over dispersed RNA-seq count data.


Assuntos
Modelos Estatísticos , Distribuição Normal , Transcriptoma/imunologia , Análise por Conglomerados , Feminino , Humanos , Masculino
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