Integrated study of copy number states and genotype calls using high-density SNP arrays

We propose a statistical framework, named genoCN, to simultaneously dissect copy number states and genotypes using high-density SNP (single nucleotide polymorphism) arrays. There are at least two types of genomic DNA copy number differences: copy number variations (CNVs) and copy number aberrations (CNAs). While CNVs are naturally occurring and inheritable, CNAs are acquired somatic alterations most often observed in tumor tissues only. CNVs tend to be short and more sparsely located in the genome compared with CNAs. GenoCN consists of two components, genoCNV and genoCNA, designed for CNV and CNA studies, respectively. In contrast to most existing methods, genoCN is more flexible in that the model parameters are estimated from the data instead of being decided a priori. GenoCNA also incorporates two important strategies for CNA studies. First, the effects of tissue contamination are explicitly modeled. Second, if SNP arrays are performed for both tumor and normal tissues of one individual, the genotype calls from normal tissue are used to study CNAs in tumor tissue. We evaluated genoCN by applications to 162 HapMap individuals and a brain tumor (glioblastoma) dataset and showed that our method can successfully identify both types of copy number differences and produce high-quality genotype calls

Insulin Receptor Substrate Adaptor Proteins Mediate Prognostic Gene Expression Profiles in Breast Cancer

Therapies targeting the type I insulin-like growth factor receptor (IGF-1R) have not been developed with predictive biomarkers to identify tumors with receptor activation. We have previously shown that the insulin receptor substrate (IRS) adaptor proteins are necessary for linking IGF1R to downstream signaling pathways and the malignant phenotype in breast cancer cells. The purpose of this study was to identify gene expression profiles downstream of IGF1R and its two adaptor proteins. IRS-null breast cancer cells (T47D-YA) were engineered to express IRS-1 or IRS-2 alone and their ability to mediate IGF ligand-induced proliferation, motility, and gene expression determined. Global gene expression signatures reflecting IRS adaptor specific and primary vs. secondary ligand response were derived (Early IRS-1, Late IRS-1, Early IRS-2 and Late IRS-2) and functional pathway analysis examined. IRS isoforms mediated distinct gene expression profiles, functional pathways, and breast cancer subtype association. For example, IRS-1/2-induced TGFb2 expression and blockade of TGFb2 abrogated IGF-induced cell migration. In addition, the prognostic value of IRS proteins was significant in the luminal B breast tumor subtype. Univariate and multivariate analyses confirmed that IRS adaptor signatures correlated with poor outcome as measured by recurrence-free and overall survival. Thus, IRS adaptor protein expression is required for IGF ligand responses in breast cancer cells. IRS-specific gene signatures represent accurate surrogates of IGF activity and could predict response to anti-IGF therapy in breast cancer

Age-Specific Changes in Intrinsic Breast Cancer Subtypes: A Focus on Older Women

Breast cancer (BC) is a disease of aging and the number of older BC patients in the U.S. is rising. Immunohistochemical data show that with increasing age, the incidence of hormone receptor-positive tumors increases, whereas the incidence of triple-negative tumors decreases. Few data exist on the frequency of molecular subtypes in older women. Here, we characterize the incidence and outcomes of BC patients by molecular subtypes and age

Integrated DNA and RNA Sequencing Reveals Drivers of Endocrine Resistance in Estrogen Receptor Positive Breast Cancer

PURPOSE: Endocrine therapy resistance (ETR) remains the greatest challenge in treating patients with hormone receptor–positive breast cancer. We set out to identify molecular mechanisms underlying ETR through in-depth genomic analysis of breast tumors. EXPERIMENTAL DESIGN: We collected pre-treatment and sequential on-treatment tumor samples from 35 patients with estrogen receptor–positive breast cancer treated with neoadjuvant then adjuvant endocrine therapy; 3 had intrinsic resistance, 19 acquired resistance, and 13 remained sensitive. Response was determined by changes in tumor volume neoadjuvantly and by monitoring for adjuvant recurrence. Twelve patients received two or more lines of endocrine therapy, with subsequent treatment lines being initiated at the time of development of resistance to the previous endocrine therapy. DNA whole-exome sequencing and RNA sequencing were performed on all samples, totalling 169 unique specimens. DNA mutations, copy-number alterations, and gene expression data were analyzed through unsupervised and supervised analyses to identify molecular features related to ETR. RESULTS: Mutations enriched in ETR included ESR1 and GATA3. The known ESR1 D538G variant conferring ETR was identified, as was a rarer E380Q variant that confers endocrine hypersensitivity. Resistant tumors which acquired resistance had distinct gene expression profiles compared with paired sensitive tumors, showing elevated pathways including ER, HER2, GATA3, AKT, RAS, and p63 signaling. Integrated analysis in individual patients highlighted the diversity of ETR mechanisms. CONCLUSIONS: The mechanisms underlying ETR are multiple and characterized by diverse changes in both somatic genetic and transcriptomic profiles; to overcome resistance will require an individualized approach utilizing genomic and genetic biomarkers and drugs tailored to each patient

Reduced expression of a gene proliferation signature is associated with enhanced malignancy in colon cancer

The association between cell proliferation and the malignant potential of colon cancer is not well understood. Here, we evaluated this association using a colon-specific gene proliferation signature (GPS). The GPS was derived by combining gene expression data obtained from the analysis of a cancer cell line model and a published colon crypt profile. The GPS was overexpressed in both actively cycling cells in vitro and the proliferate compartment of colon crypts. K-means clustering was used to independantly stratify two cohorts of colon tumours into two groups with high and low GPS expression. Notably, we observed a significant association between reduced GPS expression and an increased likelihood of recurrence (P<0.05), leading to shorter disease-free survival in both cohorts. This finding was not a result of methodological bias as we verified the well-established association between breast cancer malignancy and increased proliferation, by applying our GPS to public breast cancer data. In this study, we show that reduced proliferation is a biological feature characterizing the majority of aggressive colon cancers. This contrasts with many other carcinomas such as breast cancer. Investigating the reasons underlying this unusual observation may provide important insight into the biology of colon cancer progression and putative novel therapy options

Depressive and anxiety disorders and antidepressant prescriptions among insured children and young adults with congenital adrenal hyperplasia in the United States

BackgroundDysfunction in the hypothalamic-pituitary-adrenal axis has been associated with depressive and anxiety disorders. Little is known about the risk for these disorders among individuals with congenital adrenal hyperplasia (CAH), a form of primary adrenal insufficiency.ObjectiveWe investigated the prevalence of depressive and anxiety disorders and antidepressant prescriptions in two large healthcare databases of insured children, adolescents, and young adults with CAH in the United States.MethodsWe conducted a retrospective cohort study using administrative data from October 2015 through December 2019 for individuals aged 4–25 years enrolled in employer-sponsored or Medicaid health plans.ResultsAdjusting for age, the prevalence of depressive disorders [adjusted prevalence ratio (aPR) = 1.7, 95% confidence interval (CI): 1.4-2.0, p&lt;0.001], anxiety disorders [aPR = 1.7, 95% CI: 1.4-1.9, p&lt;0.001], and filled antidepressant prescriptions [aPR = 1.7, 95% CI: 1.4-2.0, p&lt;0.001] was higher among privately insured youth with CAH as compared to their non-CAH peers. Prevalence estimates were also higher among publicly insured youth with CAH for depressive disorders [aPR = 2.3, 95% CI: 1.9-2.9, p&lt;0.001], anxiety disorders [aPR = 2.0, 95% CI: 1.6-2.5, p&lt;0.001], and filled antidepressant prescriptions [aPR = 2.5, 95% CI: 1.9-3.1, p&lt;0.001] as compared to their non-CAH peers.ConclusionsThe elevated prevalence of depressive and anxiety disorders and antidepressant prescriptions among youth with CAH suggests that screening for symptoms of depression and anxiety among this population might be warranted

Integrated Analyses of microRNAs Demonstrate Their Widespread Influence on Gene Expression in High-Grade Serous Ovarian Carcinoma

The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets.Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3'-untranslated region (with less frequency observed for coding sequence and 5'-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability.This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers

An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

INTRODUCTION. Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation. METHODS. We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies. RESULTS. We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient. CONCLUSIONS. Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.V Foundation for Cancer Research (Partners in Excellence grant