Marilyn Li

Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists

Widespread clinical laboratory implementation of next-generation sequencing-based cancer testing has highlighted the importance and potential benefits of standardizing the interpretation and reporting of molecular results among laboratories. A multidisciplinary working group tasked to assess the current status of next-generation sequencing-based cancer testing and establish standardized consensus classification, annotation, interpretation, and reporting conventions for somatic sequence variants was convened by the Association for Molecular Pathology with liaison representation from the American College of Medical Genetics and Genomics, American Society of Clinical Oncology, and College of American Pathologists. On the basis of the results of professional surveys, literature review, and the Working Groups subject matter expert consensus, a four-tiered system to categorize somatic sequence variations based on their clinical significances is proposed: tier I, variants with strong clinical significance; tier II, variants with potential clinical significance; tier III, variants of unknown clinical significance; and tier IV, variants deemed benign or likely benign. Cancer genomics is a rapidly evolving field; therefore, the clinical significance of any variant in therapy, diagnosis, or prognosis should be reevaluated on an ongoing basis. Reporting of genomic variants should follow standard nomenclature, with testing method and limitations clearly described. Clinical recommendations should be concise and correlate with histological and clinical findings.

Clinical application of amplicon-based next-generation sequencing in cancer

Next-generation sequencing (NGS) technology has revolutionized genomic research by decreasing the cost of sequencing while increasing the throughput. The focus now is on potential clinical applications of NGS technology for diagnostics and therapeutics. Clinical applications of NGS in cancer can detect clinically actionable genetic/genomic alterations that are critical for cancer care. These alterations can be of diagnostic, prognostic, or therapeutic significance. In certain cancers, patient risk and prognosis can be predicted based on the mutation profile identified by NGS. Many targeted therapies have been developed for cancer patients who bear specific mutations; however, choosing the right NGS technique for the appropriate clinical application can be challenging, especially in clinical oncology, where the material for NGS tests is often limited and the turnaround time (TAT) for cancer tests is constrained to a few days. Currently, amplicon-based NGS approaches have emerged as the best fit for clinical oncology. In this review, we focus on amplicon-based library preparation, sequencing, sequence data alignment and annotation, and post-analytic interpretation and reporting.

American College of Medical Genetics and Genomics technical standards and guidelines: microarray analysis for chromosome abnormalities in neoplastic disorders

Microarray methodologies, to include array comparative genomic hybridization and single-nucleotide polymorphism–based arrays, are innovative methods that provide genomic data. These data should be correlated with the results from the standard methods, chromosome and/or fluorescence in situ hybridization, to ascertain and characterize the genomic aberrations of neoplastic disorders, both liquid and solid tumors. Over the past several decades, standard methods have led to an accumulation of genetic information specific to many neoplasms. This specificity is now used for the diagnosis and classification of neoplasms. Cooperative studies have revealed numerous correlations between particular genetic aberrations and therapeutic outcomes. Molecular investigation of chromosomal abnormalities identified by standard methods has led to discovery of genes, and gene function and dysfunction. This knowledge has led to improved therapeutics and, in some disorders, targeted therapies. Data gained from the higher-resolution microarray methodologies will enhance our knowledge of the genomics of specific disorders, leading to more effective therapeutic strategies. To assist clinical laboratories in validation of the methods, their consistent use, and interpretation and reporting of results from these microarray methodologies, the American College of Medical Genetics and Genomics has developed the following professional standard and guidelines.Genet Med 2013:15(6):484–494

Classification of Multicolor Fluorescence In Situ Hybridization (M-FISH) Images With Sparse Representation

There has been a considerable interest in sparse representation and compressive sensing in applied mathematics and signal processing in recent years but with limited success to medical image processing. In this paper we developed a sparse representation-based classification (SRC) algorithm based on L1-norm minimization for classifying chromosomes from multicolor fluorescence in situ hybridization (M-FISH) images. The algorithm has been tested on a comprehensive M-FISH database that we established, demonstrating improved performance in classification. When compared with other pixel-wise M-FISH image classifiers such as fuzzy c-means (FCM) clustering algorithms and adaptive fuzzy c-means (AFCM) clustering algorithms that we proposed earlier the current method gave the lowest classification error. In order to evaluate the performance of different SRC for M-FISH imaging analysis, three different sparse representation methods, namely, Homotopy method, Orthogonal Matching Pursuit (OMP), and Least Angle Regression (LARS), were tested and compared. Results from our statistical analysis have shown that Homotopy based method is significantly better than the other two methods. Our work indicates that sparse representations based classifiers with proper models can outperform many existing classifiers for M-FISH classification including those that we proposed before, which can significantly improve the multicolor imaging system for chromosome analysis in cancer and genetic disease diagnosis.

Characterization of a Cryptic 3.3 Mb Deletion in a Patient With a “Balanced t(15;22) Translocation” Using High Density Oligo Array CGH and Gene Expression Arrays

Patients with an apparently balanced translocation and an abnormal phenotype may carry a cryptic deletion/duplication at their translocation breakpoints that may explain their abnormalities. Using microarray CGH (aCGH) and gene expression arrays we studied a child with t(15;22)(q26.1;q11.2), developmental delay and mild dysmorphic features. A high density aCGH study with 244,000 oligo probes demonstrated a 3.3 Mb deletion immediately adjacent to the 15q breakpoint. Gene expression studies with 44,000 oligos displayed an approximately 50% reduction of the expression of IGF1R gene that was translocated to the der(22). There are 18 known or hypothetical protein coding genes within the deleted region according to UniProt, RefSeq, and GenBank mRNA (UCSC HG17, May 2004). Although two of these genes, RGMA and ST8SIA2, play an important role in neural development, the mild phenotype of our patient indicates that loss of one copy of these genes may not be critical developmentally. The 50% reduction of IGF1R expression could be responsible for the growth deficiency in the patient. Reviewing the few 15q26 microdeletion cases that have been characterized by aCGH, we discovered that deletion of the segment including distal 15q26.2 to the proximal part of 15q26.3 is associated with severe phenotypes. Our experience demonstrates that high‐density oligonucleotide‐based aCGH is a quick and precise way to identify cryptic copy number changes in “balanced translocations.” Expression studies can also add valuable information regarding gene expression changes due to a chromosomal rearrangement. Both approaches can assist in the elucidation of the etiology of unexplained phenotypic differences in cases such as this one.

Characterization of germline copy number variation in high-risk African American families with prostate cancer

Prostate cancer is a complex multi‐allelic disease and the most common malignancy in men. The incidence of prostate cancer in African American men is more than twice as high as that of any other race. Despite the high prevalence of prostate cancer amongst African American men, this population has been under represented in genetic studies of prostate cancer. Although genomic copy number variations (CNVs) have been detected in prostate tumors, this is the first study describing germline CNVs in African American hereditary prostate cancer families.

Prenatal diagnosis of CLOVES syndrome confirmed by detection of a mosaic PIK3CA mutation in cultured amniocytes.

Congenital lipomatous asymmetric overgrowth of the trunk, lymphatic, capillary, venous, and combined‐type vascular malformations, epidermal nevi, skeletal and spinal anomalies (CLOVES) syndrome, a segmental overgrowth syndrome, is caused by post zygotic somatic mutations in PIK3CA, a gene involved in the receptor tyrosine kinase phosphatidylinositol 3‐kinase (PI3)‐AKT growth‐signaling pathway. Prenatal ultrasound findings of lymphovascular malformations, segmental overgrowth and skeletal defects can raise suspicion for CLOVES syndrome, but molecular confirmation of PIK3CA mutations on prenatally obtained samples is challenging because of somatic mosaicism. We detected a mosaic disease‐causing mutation in PIK3CA by sequencing of DNA extracted from cultured amniotic cells, but not from DNA directly prepared from an amniotic fluid sample in a fetus with prenatally suspected CLOVES syndrome. The infant was born prematurely and displayed severe lymphovascular malformations and segmental overgrowth consistent with a clinical diagnosis of CLOVES syndrome; he passed away at 29 days of life. We discuss the complexities and limitations of genetic testing for somatic mosaic mutations in the prenatal period and highlight the potential need for multiple approaches to arrive at a molecular diagnosis.

Design of a smartphone application to monitor stress, asthma symptoms, and asthma inhaler use

Advances in the treatment and prevention of asthma have curtailed deaths, hospitalizations, and increases in prevalence rates over the past thirty years.1 Nevertheless, the effectiveness of long-term asthma management is mediated by behavioral factors such as adherence to medication and psychosocial stress. In a study using ecological momentary assessment to monitor asthma inhaler use, half of all non-adherence cases occurred while participants were with their peers.2 However, the study relied on subjective reports of adherence. Associations between stress and asthma symptoms have been observed, but these have relied on retrospective self-report, potentially introducing recall bias. Laboratory studies have demonstrated causal relationships between stress and biological markers of immune responses related to asthma.3, 4 However, these settings may not represent real-world situations. Furthermore, both laboratory and longitudinal studies to date have not captured the effect of daily variations in adherence, stress, and symptoms. Advancements in technology have led to commercial availability of low-cost personal computing devices (smartphones) capable of executing advanced health-related applications (“apps”) and communicating with external sensors via short-wave radio signals (Bluetooth).5 Ecological momentary assessment (EMA) using smartphones is a method of capturing real-time data that maintains ecological validity, reduces recall bias, preserves within-day changes, and captures objective data from external devices to reduce social desirability bias.6 This letter describes the design of a smartphone application that integrates EMA and Bluetooth-enabled sensors for asthma inhalers. This technology can measure real-time asthma symptomology, social and physical context, behavior, stress, and inhaler use. Development of the application was a collaborative effort from a multidisciplinary team of researchers and computer scientists. The application was installed on Samsung Galaxy Y (Model S5460) smartphones running the latest available version of Google’s Android operating system and loaned to participants. Study personnel conducted iterative development (alpha) testing before initiating pilot (beta) testing using a small (N=20) English-speaking convenience sample of Hispanic middle and high school students (ages 12–17) enrolled in a mobile asthma management clinic for low-income families.7 Written parental consent and child assent were obtained at enrollment; the study was approved by the Institutional Review Board at the University of Southern California. Physicians assisted at enrollment to inform participants that the application was not a replacement for treatment. The application uses signal-contingent (i.e, randomly-timed) and event-contingent (i.e., context-sensitive) EMA sampling triggered by asthma inhaler use. Inhaler use is detected when the phone receives a signal from a Bluetooth sensor on the participant’s quick-relief and controller medications. The signal-contingent EMA component of the software prompts the user with an electronic survey at a random time within each of seven designated time windows: 7–9 AM, 9–11 AM, 11 AM–1 PM, 1 – 3 PM, 3 – 5 PM, 5–7 PM, and 7–9 PM. No surveys are deployed prior to 3 PM on weekdays (during school time). After receiving a prompt (eFigure 1), the participants are presented with a set of questions querying current levels of positive and negative affect, stress, energy, and fatigue, as well as the type of activity currently being performed, and information about social and physical contexts (eTable 1). Additionally, participants are asked to recall stressful events, asthma symptoms, and asthma coping-related behaviors occurring since the last survey (or in the past four hours if the last survey was completed more than four hours prior) (eTable 1).8,9,10 The event-contingent (i.e., context-sensitive) EMA component of the application runs a background service that monitors all incoming Bluetooth connections. Participants are provided with two small, button-like devices that attach to the tops of quick relief (i.e., rescue) and controller metered dose inhalers (Propeller sensor, provided at no cost by Propeller Health; Madison, WI) designed to transmit a Bluetooth signal to the phone when the inhaler is actuated. Approximately 5 minutes after the background service captures a Bluetooth sensor signal, the app initiates a real-time self-report survey. The first question in this survey asks whether the participant used a rescue inhaler, control inhaler, or neither (i.e., inhaler actuated unintentionally). If a participant reports any inhaler usage, the survey subsequently queries the severity of asthma symptoms experienced, the type of activity performed, and social and physical contexts encountered just before the inhaler use. Questions also ask about stressful events experienced since the last survey (or in the past four hours if the last survey was completed more than four hours prior) (eTable 1). To reduce burden on participants, EMA surveys contain logical question branching for question subsets. With the exception of questions related to performed activity type, a randomized selection algorithm was used for signal-contingent question subsets such that each subset had a 60% chance of appearing on any given survey. Data from all surveys are uploaded to a secure file transfer protocol (SFTP) server at the end of the day. At the completion of testing, the phones are retrieved from participants and the phone features are restored to factory settings. During pilot testing, participants received a daily average of 3.2 (SD = 0.9, range = 1 – 4.57) signal-contingent and 2.1 (SD= 2.6, range = 0.1 – 7.8) event-contingent prompts across all seven days. EMA prompt adherence rates ranged from 20% to 100% (M = 51.4%, SD = 21.8%). Users reported general satisfaction and ease of use, while some reported difficulty with answering surveys that interrupted them in the middle of the night (Table 1). Table 1 Sample Demographics and Usage Satisfaction in Pilot Testing (N=20) Once rigorously tested, the EMA portion of the application (source code) will be made publicly available (at no cost) to researchers. Open-source Android applications allow for localization to languages other than English and installation on participant-owned devices or loaned phones, thereby reducing cost. Furthermore, the application also allows for monitoring using other sensors (e.g. built in motion and location sensors, external personal ozone monitors). Future studies should seek to improve adherence rates, generalize to non-Hispanic sub-populations, and assess health adolescent health literacy. This application has the potential to assist researchers and clinicians to better understand real-time experiences of adolescent patients with asthma, increase adherence to asthma treatment regimens, tailor treatments to their specific needs, and enhance patient-provider communication.

Mobile health care operations and return on investment in predominantly underserved children with asthma: the breathmobile program.

Underserved populations have limited access to care. Improved access to effective asthma care potentially improves quality of life and reduces costs associated with emergency department (ED) visits. The purpose of this study is to examine return on investment (ROI) for the Breathmobile Program in terms of improved patient quality-adjusted life years saved and reduced costs attributed to preventable ED visits for 2010, with extrapolation to previous years of operation. It also examines cost-benefit related to reduced morbidity (ED visits, hospitalizations, and school absenteeism) for new patients to the Breathmobile Program during 2008-2009 who engaged in care (≥3 visits). This is a retrospective analysis of data for 15,986 pediatric patients, covering 88,865 visits, participating in 4 Southern California Breathmobile Programs (November 16, 1995-December 31, 2010). The ROI calculation expressed the cost-benefit ratio as the net benefits (ED costs avoided+relative value of quality-adjusted life years saved) over the per annum program costs (∼

Differentiating Between Burkitt Lymphoma and CD10+ Diffuse Large B-Cell Lymphoma: The Role of Commonly Used Flow Cytometry Cell Markers and the Application of a Multiparameter Scoring System

500,000 per mobile). The ROI across the 4 California programs in 2010 was