The development of targeted therapies for antiestrogenresistant breast cancer requires a detailed understanding of its molecular characteristics. To further elucidate the molecular events underlying acquired resistance to the antiestrogens tamoxifen and fulvestrant, we established drug-resistant sublines from a single colony of hormonedependent breast cancer MCF7 cells. These model systems allowed us to examine the cellular and molecular changes induced by antiestrogens in the context of a uniform clonal background. Global changes in both basal and estrogeninduced gene expression profiles were determined in hormonesensitive and hormonal-resistant sublines using Affymetrix Human Genome U133 Plus 2.0 Arrays. Changes in DNA methylation were assessed by differential methylation hybridization, a high-throughput promoter CpG island microarray analysis. By comparative studies, we found distinct gene expression and promoter DNA methylation profiles associated with acquired resistance to fulvestrant versus tamoxifen. Fulvestrant resistance was characterized by pronounced upregulation of multiple growth-stimulatory pathways, resulting in estrogen receptor A (ERA)-independent, autocrineregulated proliferation. Conversely, acquired resistance to tamoxifen correlated with maintenance of the ERA-positive phenotype, although receptor-mediated gene regulation was altered. Activation of growth-promoting genes, due to promoter hypomethylation, was more frequently observed in antiestrogen-resistant cells compared with gene inactivation by promoter hypermethylation, revealing an unexpected insight into the molecular changes associated with endocrine resistance. In summary, this study provides an in-depth understanding of the molecular changes specific to acquired resistance to clinically important antiestrogens. Such knowledge of resistance-associated mechanisms could allow for identification of therapy targets and strategies for resensitization to these well-established antihormonal agents. (Cancer Res 2006; 66(24): 11954-66)

ImportanceSARS-CoV-2 infection is associated with persistent, relapsing, or new symptoms or other health effects occurring after acute infection, termed postacute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. Characterizing PASC requires analysis of prospectively and uniformly collected data from diverse uninfected and infected individuals.ObjectiveTo develop a definition of PASC using self-reported symptoms and describe PASC frequencies across cohorts, vaccination status, and number of infections.Design, Setting, and ParticipantsProspective observational cohort study of adults with and without SARS-CoV-2 infection at 85 enrolling sites (hospitals, health centers, community organizations) located in 33 states plus Washington, DC, and Puerto Rico. Participants who were enrolled in the RECOVER adult cohort before April 10, 2023, completed a symptom survey 6 months or more after acute symptom onset or test date. Selection included population-based, volunteer, and convenience sampling.ExposureSARS-CoV-2 infection.Main Outcomes and MeasuresPASC and 44 participant-reported symptoms (with severity thresholds).ResultsA total of 9764 participants (89% SARS-CoV-2 infected; 71% female; 16% Hispanic/Latino; 15% non-Hispanic Black; median age, 47 years [IQR, 35-60]) met selection criteria. Adjusted odds ratios were 1.5 or greater (infected vs uninfected participants) for 37 symptoms. Symptoms contributing to PASC score included postexertional malaise, fatigue, brain fog, dizziness, gastrointestinal symptoms, palpitations, changes in sexual desire or capacity, loss of or change in smell or taste, thirst, chronic cough, chest pain, and abnormal movements. Among 2231 participants first infected on or after December 1, 2021, and enrolled within 30 days of infection, 224 (10% [95% CI, 8.8%-11%]) were PASC positive at 6 months.Conclusions and RelevanceA definition of PASC was developed based on symptoms in a prospective cohort study. As a first step to providing a framework for other investigations, iterative refinement that further incorporates other clinical features is needed to support actionable definitions of PASC.

Purpose: Aberrant DNA methylation, now recognized as a contributing factor to neoplasia, often shows definitive gene/sequence preferences unique to specific cancer types. Correspondingly, distinct combinations of methylated loci can function as biomarkers for numerous clinical correlates of ovarian and other cancers. Experimental Design:We used a microarray approach to identify methylated loci prognostic for reduced progression-free survival (PFS) in advanced ovarian cancer patients.Two data set classification algorithms, Significance Analysis of Microarray and Prediction Analysis of Microarray, successfully identified 220 candidate PFS-discriminatory methylated loci. Of those, 112 were found capable of predicting PFS with 95% accuracy, by Prediction Analysis of Microarray, using an independent set of 40 advanced ovarian tumors (from 20 short-PFS and 20 long-PFS patients, respectively). Additionally, we showed the use of these predictive loci using two bioinformatics machine-learning algorithms, Support Vector Machine and Multilayer Perceptron. Conclusion: In this report, we show that highly prognostic DNA methylation biomarkers can be successfully identified and characterized, using previously unused, rigorous classifying algorithms. Such ovarian cancer biomarkers represent a promising approach for the assessment and management of this devastating disease.

Alternative splicing (AS) allows increased diversity and orthogonal regulation of the transcriptional products of mammalian genomes. To assess the distribution and variation of alternative splicing across cell lineages of the immune system, we comprehensively analyzed RNA sequencing and microarray data generated by the Immunological Genome Project Consortium. AS is pervasive: 60% of genes showed frequent AS isoforms in T or B lymphocytes, with 7,599 previously unreported isoforms. Distinct cell specificity was observed, with differential exon skipping in 5% of genes otherwise coexpressed in both B and T cells. The distribution of isoforms was mostly all or none, suggesting on/off switching as a frequent mode of AS regulation in lymphocytes. From the identification of differential exon use in the microarray data, clustering of exon inclusion/exclusion patterns across all Immunological Genome Project cell types showed that ∼70% of AS exons are distributed along a common pattern linked to lineage differentiation and cell cycling. Other AS events distinguished myeloid from lymphoid cells or affected only a small set of exons without clear lineage specificity (e.g., Ptprc). Computational analysis predicted specific associations between AS exons and splicing regulators, which were verified by detection of the hnRPLL/ Ptprc connection.A lternative splicing (AS), the process of selectively including or removing exons to create a variety of transcripts from the same pre-mRNA, plays an important role in amplifying the diversity and flexibility of genome-encoded molecules (1, 2). AS can result in different protein isoforms or generate mRNAs of identical coding sequence but varying in their stability, localization, susceptibility to translational control, or microRNA regulation. AS is frequent and ubiquitous, affecting 55-95% of multiexon genes in mammals in different estimates (3-6). It is involved in a wide range of biological phenomena, ranging from sex determination to apoptosis or tumor formation. It also allows evolutionary tinkering with transcript structure and gradual transitions in gene function (7).Splicing events are overrepresented in genes involved in signaling and transcriptional regulation (receptors, signaling transduction, and transcription factors) and immune and nervous system processes. It has been hypothesized that alternative splicing is particularly valuable in complex systems, where information is processed differently at different times (immune response) or fine-tuning of signal integration is important (5). In the immune system, the first instance of AS recognized was the now textbook case of differential processing of primary Ig transcripts generating either a membrane receptor in naïve B cells or a secreted protein after antigen-induced differentiation (8). Other notable examples are the splicing of transcripts encoding adhesion molecules such as PECAM1 or CD44, which modulate cell-stroma interactions, or the extracellular domain of the coinhibitory molecule CTLA4 (9). A particularly well-studie...

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