Assessment of Capture and Amplicon-Based Approaches for the Development of a Targeted Next-Generation Sequencing Pipeline to Personalize Lymphoma Management.

Targeted next-generation sequencing panels are increasingly used to assess the value of gene mutations for clinical diagnostic purposes. For assay development, amplicon-based methods have been preferentially used on the basis of short preparation time and small DNA input amounts. However, capture sequencing has emerged as an alternative approach because of high testing accuracy. We compared capture hybridization and amplicon sequencing approaches using fresh-frozen and formalin-fixed, paraffin-embedded tumor samples from eight lymphoma patients. Next, we developed a targeted sequencing pipeline using a 32-gene panel for accurate detection of actionable mutations in formalin-fixed, paraffin-embedded tumor samples of the most common lymphocytic malignancies: chronic lymphocytic leukemia, diffuse large B-cell lymphoma, and follicular lymphoma. We show that hybrid capture is superior to amplicon sequencing by providing deep more uniform coverage and yielding higher sensitivity for variant calling. Sanger sequencing of 588 variants identified specificity limits of thresholds for mutation calling, and orthogonal validation on 66 cases indicated 93% concordance with whole-genome sequencing. The developed pipeline and assay identified at least one actionable mutation in 91% of tumors from 219 lymphoma patients and revealed subtype-specific mutation patterns and frequencies consistent with the literature. This pipeline is an accurate and sensitive method for identifying actionable gene mutations in routinely acquired biopsy materials, suggesting further assessment of capture-based assays in the context of personalized lymphoma management.

Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer.

In this work an integrated approach was used to identify functional miRNAs regulating gene pathway cross-talk in breast cancer (BC). We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes. For each pair of pathways, a score was derived from the distribution of gene expression levels by quantifying their pathway cross-talk. Random forest classification allowed the identification of pairs of pathways with high cross-talk. We assessed miRNAs regulating the identified gene pathways by a mutual information analysis. A Fisher test was applied to demonstrate their significance in the regulated pathways. Our results suggest interesting networks of pathways that could be key regulatory of target genes in BC, including stem cell pluripotency, coagulation, and hypoxia pathways and miRNAs that control these networks could be potential biomarkers for diagnostic, prognostic, and therapeutic development in BC. This work shows that standard methods of predicting normal and tumor classes such as differentially expressed miRNAs or transcription factors could lose intrinsic features; instead our approach revealed the responsible molecules of the disease.

Melanoma susceptibility genes and risk assessment.

Familial melanoma accounts for approximately a tenth of all melanoma cases. The most commonly known melanoma susceptibility gene is the highly penetrant CDKN2A (p16INK4a) locus, which is transmitted in an autosomal dominant fashion and accounts for approximately 20-50 % of familial melanoma cases. Mutated p16INK4a shows impaired capacity to inhibit the cyclin D1-CDK4 complex, allowing for unchecked cell cycle progression. Mutations in the second protein coded by CDKN2A, p14ARF, are much less common and result in proteasomal degradation of p53 with subsequent accumulation of DNA damage as the cell progresses through the cell cycle without a functional p53-mediated DNA damage response. Mutations in CDK4 that impair the inhibitory interaction with p16INK4a also increase melanoma risk but these mutations are extremely rare. Genes of the melanin biosynthetic pathway, including MC1R and MITF, have also been implicated in melanomagenesis. MC1R variants were traditionally thought to increase risk for melanoma secondary to intensified UV-mediated DNA damage in the setting of absent photoprotective eumelanin. Accumulation of pheomelanin, which appears to have a carcinogenic effect regardless of UV exposure, may be a more likely mechanism. Impaired SUMOylation of the E318K variant of MITF results in increased transcription of genes that confer melanocytes with a pro-malignant phenotype. Mutations in the tumor suppressor BAP1 enhance the metastatic potential of uveal melanoma and predispose to cutaneous/ocular melanoma, atypical melanocytic tumors, and other internal malignancies (COMMON syndrome). Genome-wide association studies have identified numerous low-risk alleles. Although several melanoma susceptibility genes have been identified, risk assessment tools have been developed only for the most common gene implicated with hereditary melanoma, CDKN2A. MelaPRO, a validated model that relies on Mendelian inheritance and Bayesian probability theories, estimates carrier probability for CDKN2A and future risk of melanoma taking into account a patient's family and past medical history of melanoma. Genetic testing for CDKN2A mutations is currently available but the Melanoma Genetics Consortium recommends offering such testing to patients only in the context of research protocols because clinical utility is uncertain.

Reverse engineering of modified genes by Bayesian network analysis defines molecular determinants critical to the development of glioblastoma.

In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and 'key genes' within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96-100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkß, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential 'hubs of activity'. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several 'key genes' may be required for the development of glioblastoma. Further studies are needed to validate these 'key genes' as useful tools for early detection and novel therapeutic options for these tumors.

Quantitative assessment of Wilms tumor 1 (WT1) gene transcripts in Egyptian acute lymphoblastic leukemia patients.

BACKGROUND: Accurate assessment of minimal residual disease (MRD) in acute lymphoblastic leukemia (ALL) patients after initial chemotherapy is essential to evaluate the efficacy of therapeutic regimens. Wilms tumor 1 (WT1) is a pan-leukemic marker used for identification of the leukemic clone rather than the use of individual specific molecular aberration of ALL. METHODS: Using a real-time quantitative polymerase chain reaction, bone marrow samples from 41 newly diagnosed Egyptian ALL patients; 22 adults and 19 children were examined for WT1 expression. After induction therapy, WT1 expression was reestimated in 20 ALL patients. RESULTS: WT1 was overexpressed in adult and pediatric ALL patients (95.4% and 89.4%, respectively). WT1 expression at diagnosis had no statistically significant impact on disease-free survival of patients (P = 0.054). However, WT1 expression increased after induction chemotherapy in the 3 pediatric patients who had relapse. CONCLUSIONS: WT1 is a leukemia-associated molecular marker that may be used for the diagnosis and for monitoring clinical progress in ALL; it also can be used as a molecular target for adoptive immunotherapy.

Recurrent copy number alterations in BRCA1-mutated ovarian tumors alter biological pathways.

Array CGH was used to identify recurrent copy number alterations (RCNA) characteristic of either BRCA1-related or sporadic ovarian cancer. After preprocessing, both groups of patients were modeled using a recurrent Hidden Markov Model to detect RCNA. RCNA with a probability higher than 80% were called. After removing RCNA present in both groups, the genes present in the remaining RCNA were investigated for enrichment of pathways from external databases. More RCNA were observed in the BRCA1 group, and they display more losses than gains compared to the sporadic group. When focusing on the type of RCNA, no significant difference in length was seen for the gains, but there was a statistically significant difference for the losses. In the sporadic group, a great proportion of the altered regions contain genes known to have a function in cell adhesion and complement activation, whereas the BRCA1 samples are characterized by alterations in the HOX genes, metalloproteinases, tumor suppressor genes, and the estrogen-signaling pathways. We conclude that BRCA1 ovarian tumors present a different type, number, and length of RCNA; a huge amount of the genome is lost, resulting in important genomic instability. Moreover, important biological pathways are altered differentially when compared to the sporadic group.

Determining joint carrier probabilities of cancer-causing genes using Markov chain Monte Carlo methods.

In genetic counseling for cancer risk, the probability of carrying a mutation of a cancer-causing gene plays an important role. Family history of various cancers is important in calculating this probability. BRCAPRO is a widely used software for calculating the probability of carrying mutations in BRCA1 and BRCA2 genes given the family history of breast and ovarian cancer in first- and second-degree relatives. BRCAPRO uses an analytical (exact) calculational procedure. Using Markov chain Monte Carlo (MCMC) methods, we extend BRCAPRO to handle, in principle, any type of cancer, family history, any number of genes and alleles that each gene may have. When the information used in this MCMC approach is the same as for BRCAPRO (two genes: BRCA1 and BRCA2; two cancers: breast and ovarian; first- and second-degree relatives only), the two approaches give essentially the same answer. Extending the model to include (1) prostate cancer, (2) two mutated alleles of BRCA2, namely, mutations in Ovarian Cancer Cluster Region (OCCR) and non-OCCR region, and (3) relatives of degree greater than second-degree, leads to different carrier probabilities. The MCMC approach is a useful tool in building a comprehensive model to give accurate estimates of carrier probabilities. Such an approach will be even more important as additional information about the genetics of various cancers becomes available.

Rapid mutation detection in complex genes by heteroduplex analysis with capillary array electrophoresis.

Mutational analysis of large multiexon genes without prevalent mutations is a laborious undertaking that requires the use of a high-throughput scanning technique. The Human Genome Project has enabled the development of powerful techniques for mutation detection in large multiexon genes. We have transferred heteroduplex analysis (HA) by conformation-sensitive gel electrophoresis of the two major breast cancer (BC) predisposing genes, BRCA1 and BRCA2, to a multicapillary DNA sequencer in order to increase the throughput of this technique. This new method that we have called heteroduplex analysis by capillary array electrophoresis (HA-CAE) is based on the use of multiplex-polymerase chain reaction (PCR), different fluorescent labels and HA in a 16-capillary DNA sequencer. To date, a total of 114 different DNA sequence variants (19 insertions/deletions and 95 single-nucleotide substitutions - SNS) of BRCA1 and BRCA2 from 431 unrelated BC families have been successfully detected by HA-CAE. In addition, we have optimized the multiplex-PCR conditions for the colorectal cancer genes MLH1 and MSH2 in order to analyze them by HA-CAE. Both genes have been amplified in 13 multiplex groups, which contain the 35 exons, and their corresponding flanking intronic sequences. MLH1 and MSH2 have been analyzed in nine hereditary nonpolyposis colorectal cancer patients, and we have found six different DNA changes: one complex deletion/insertion mutation in MLH1 exon 19 and another five SNS. Only the complex mutation and one SNS may be classified as cancer-prone mutations. Our experience has revealed that HA-CAE is a simple, fast, reproducible and sensitive method to scan the sequences of complex genes.