15169 results for "cancer studies using rna-seq"

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• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• Sequencing of Coding and Non-coding Regions in Primary Breast Cancers and Patient-matched Controls

  Genomic analysis of tumor samples has led to the identification of hundreds of cancer genes based on the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here, we performed deep sequencing in 360 primary breast cancers and developed computational methods to identify significantly mutated promoters. Clear signals were found in the promoters of four genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbors a mutational hotspot in its promoter that leads to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that alter protein binding to the promoter and impact expression levels. Overall, our study shows that recurrent mutations in or near gene promoters in cancers have functional consequences. Power analyses indicate that more such genes remain to be discovered through deep sequencing of adequately sized patient cohorts.

  Study phs001250

• PD1-targeted delivery of an IL-2 variant induces a multifaceted anti-tumoral T cell response in human lung cancer

  To explore PD1-IL2v-specific effects on CD8 and CD4 T cells at a transcriptomic level, we performed single-cell RNA sequencing of patient-derived tumor fragments (PDTFs) which were treated with either Isotype (DP47), Isotype-IL2v (DP47-IL2v), anti-PD1 (PembroPGLALA) or PD1-IL2v (PembroPGLALA-IL2v) for 48 hours.

  Study EGAS50000000396

• RNA and whole-exome sequencing of 22 patients with non-small cell lung cancer

  Whole exome sequencing from pre-treatment samples and matched blood normals from 22 patients. Of these individuals, on-treatment samples are available for a subset of 18 patients. RNA sequencing from pre-treatment samples from 21 patients. Of these individuals, on-treatment samples are available for a subset of 15 patients.

  Dataset EGAD00001008733

• Sex Chromosome Aneuploidy Effects on Human Gene Expression

  Sex chromosome aneuploidy (SCA) syndromes are defined by the presence of a sex chromosome complement other than the typical XX for females and XY for males. SCAs are collectively common and increase risks for diverse immune, metabolic, and neuropsychiatric illnesses. Understanding genome-wide transcriptomic changes in SCAs is critical for clarifying the biological underpinnings of their clinical phenotypes. Assessments of sex chromosome dosage (SCD) effects on gene expression in humans have often been confined to the use of a few SCA subtypes (e.g., XO or XXY) - precluding analysis of the same SCD change in different contexts. Our study used RNA-seq data from lymphoblastoid cell lines in 197 individuals representing diverse SCA karyotypes (49 XX, 24 XXX, 39 XY, 39 XXY, 23 XXYY, 23 XYY) to assess expression changes for 25,075 genes in multiple pairwise SCD group comparisons. The paper reporting our findings has been cited below.

  Study phs003278

• Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

  In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has killed hundreds of thousands of people, including >23,000 in New York City (NYC) alone. The pandemic's sudden emergence highlights the clinical need to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we provide large-scale shotgun metatranscriptomics (total-RNA-seq) for host, viral, and microbial profiling. In version 1, we sequenced a total of 732 clinical specimens (nasopharyngeal (NP) swabs) gathered from 669 unique patients in New York City during the first two months of the outbreak. In version 2, we sequenced an additional 168 clinical specimens from autopsy tissues (lung, heart, kidney, liver, and lymph node) from 60 patients, yielding a broad molecular portrait of the emerging COVID-19 disease across 900 clinical specimens and 729 patients.

  Study phs002258

• Transcriptomic profiles of tumor samples from patients with stage I-III TNBC treated with anthracycline-taxane chemotherapy plus fasting-mimicking diet plus/minus metformin in the context of the BREAKFAST trial (NCT04248998)

  BREAKFAST is a randomized, non-comparative, phase II trial enrolling stage I-III (cT>1cm) TNBC pts treated with neoadjuvant doxorubicin-cyclophosphamide q3w for 4 cycles, followed by weekly paclitaxel for 12 cycles. Pts were randomized 1:1 to receive: CT + triweekly 5-day FMD cycles (arm A), or CT + FMD + daily metformin (1700 mg) (arm B). The primary study objective was to investigate if one or both experimental treatments were able to increase pCR rates when compared to anthracycline-taxane CT alone according to historical data. Secondary/exploratory endpoints included biomarker analyses based on tumor transcriptomics analyses. Specifically, we collected fresh-frozen tumor samples at baseline and 14-21 days after the first treament cycle and we analyzed the RNA-seq profiles to identify early predictors of treatment activity.

  Study EGAS50000000690

• Transcriptome of human trophoblast stem cells derived from normal and HDP placentas

  Hypertensive disorders of pregnancy (HDP) is a disease driven by abnormal placenta formation, which is a leading cause of maternal and fetal death. For investigation of genetic and epigenetic regulation of human trophoblast differentiation, we have previously established human trophoblast stem cells (hTSCs) from first-trimester placentas. Those hTSCs were able to differentiate into extravillous trophoblasts (EVTs) and syncytiotrophoblasts (STs), and their transcriptome was similar to that of cytotrophoblasts in human placenta. However, since HDP happens in the second half of pregnancy, the conventional hTSC derivation method was not enough to investigate the nature of HDP trophoblasts. In this analysis, we improved the derivation method and successfully established the hTSCs from normal and HDP term placentas after delivery. We performed RNA-seq of normal and HDP hTSCs, and HDP hTSCs recapitulated abnormalities in gene expression reported in HDP placentas.

  Study JGAS000660

• Network-based systems pharmacology identifies heterogeneity in LCK and BCL2 signaling and differential vulnerability of T-cell acute lymphoblastic leukemia to targeted therapy

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and novel therapeutics are much needed. Profiling patient leukemia’ drug sensitivities ex vivo, we discovered striking inter-patient variability in T-ALL response to a panel of targeted agents. Applying network-based systems pharmacology analyses, by integrating ex vivo pharmacotyping, bulk and single-cell RNA-seq, genomics, phospho-proteomics, and genome-wide CRISPR screening data, to examine signal circuitry, we identified the pharmacogenomic basis of T-ALL drug response and revealed a therapeutic vulnerability that is directly related to the developmental stage of leukemia cells. In conclusion, our results indicate that heterogeneity in the differentiation of T-ALL drives activation of key signaling pathways in this leukemia, providing unique opportunities for targeted therapy.

  Study EGAS00001004700

• Adaptive Therapy Exploits Fitness Deficits in Chemotherapy-Resistant Ovarian Cancer to Achieve Long-Term Tumor Control Open Access

  Drug resistance results in poor outcomes for cancer patients. Adaptive therapy is a potential strategy to address drug resistance that exploits competitive interactions between sensitive and resistant subclones. Here, we showed that adapting carboplatin dose according to tumor response (adaptive therapy) significantly prolonged survival of murine ovarian cancer models compared to standard carboplatin dosing, without increasing mean daily drug dose or toxicity. Platinum resistant ovarian cancer cells exhibited diminished fitness when drug was absent in vitro and in vivo, which caused selective decline of resistant populations due to reduced proliferation and increased apoptosis. Conversely fitter, sensitive cells re-grew when drug was withdrawn. Using a bioinformatics pipeline that exploits copy number changes to quantify the emergence of treatment resistance, analysis of cell‐free DNA obtained longitudinally from ovarian cancer patients during treatment showed subclonal selection through therapy, and measurements of resistant population growth correlated strongly with disease burden. These preclinical findings pave the way for future clinical testing of personalized adaptive therapy regimens tailored to the evolution of carboplatin resistance in individual ovarian cancer patients.

  Study EGAS50000001142