Analytic validation of an -focused cell-free DNA liquid biopsy assay (FGFR-Dx).

Commercial liquid biopsy assays are routinely used by oncologists to monitor disease response and resistance to therapy. Additionally, in cases where tumor tissue is not available, clinicians may rely on cell-free DNA (cfDNA) testing as a surrogate for comprehensive tumor testing. While some gene rearrangements are well detected, current commercial liquid biopsy assays exhibit low sensitivity for fibroblast growth factor receptor ( ) rearrangements.

Genomic and Transcriptomic Characterization of Relapsed SCLC Through Rapid Research Autopsy.

Introduction: Relapsed SCLC is characterized by therapeutic resistance and high mortality rate. Despite decades of research, mechanisms responsible for therapeutic resistance have remained elusive owing to limited tissues available for molecular studies. Thus, an unmet need remains for molecular characterization of relapsed SCLC to facilitate development of effective therapies.

Characterization of Clonal Evolution in Microsatellite Unstable Metastatic Cancers through Multiregional Tumor Sequencing.

Microsatellites are short, repetitive segments of DNA, which are dysregulated in mismatch repair-deficient (MMRd) tumors resulting in microsatellite instability (MSI). MSI has been identified in many human cancer types with varying incidence, and microsatellite instability-high (MSI-H) tumors often exhibit increased sensitivity to immune-enhancing therapies such as PD-1/PD-L1 inhibition. Next-generation sequencing (NGS) has permitted advancements in MSI detection, and recent computational advances have enabled characterization of tumor heterogeneity via NGS.

Detection of Microsatellite Instability Biomarkers via Next-Generation Sequencing.

A high level of microsatellite instability (MSI-H+) is an emerging predictive and prognostic biomarker for immunotherapy response in cancer. Recently, MSI-H+ has been detected in a variety of cancer types, in addition to the classical cancers associated with Lynch Syndrome. Clinical testing for MSI-H+ is currently performed primarily through traditional polymerase chain reaction (PCR) or immunohistochemistry (IHC) assays.

Tumor heterogeneity and acquired drug resistance in FGFR2-fusion-positive cholangiocarcinoma through rapid research autopsy.

Cholangiocarcinoma is a highly aggressive and lethal malignancy, with limited treatment options available. Recently, FGFR inhibitors have been developed and utilized in FGFR-mutant cholangiocarcinoma; however, resistance often develops and the genomic determinants of resistance are not fully characterized. We completed whole-exome sequencing (WES) of 11 unique tumor samples obtained from a rapid research autopsy on a patient with FGFR-fusion-positive cholangiocarcinoma who initially responded to the pan-FGFR inhibitor, INCB054828.

Characterization of a KLK2-FGFR2 fusion gene in two cases of metastatic prostate cancer.

Background: The fibroblast growth factor receptor (FGFR) signaling pathway is activated in multiple tumor types through gene amplifications, single base substitutions, or gene fusions. Multiple small molecule kinase inhibitors targeting FGFR are currently being evaluated in clinical trials for patients with FGFR chromosomal translocations. Patients with novel gene fusions involving FGFR may represent candidates for kinase inhibitors.

Genomic characterization of metastatic ultra-hypermutated interdigitating dendritic cell sarcoma through rapid research autopsy.

Interdigitating dendritic cell sarcoma (IDCS) is an extremely rare cancer of dendritic cell origin that lacks a standardized treatment approach. Here, we performed genomic characterization of metastatic IDCS through whole exome sequencing (WES) of tumor tissues procured from a patient who underwent research autopsy. WES was also performed on a treatment-naïve tumor biopsy sample obtained from prior surgical resection.

Rapid Research Autopsy: Piecing the Puzzle of Tumor Heterogeneity.

Tumor heterogeneity decreases the effectiveness of anticancer therapies and is an important topic in translational cancer research, given its relevance in clinical oncology. Here, we discuss how rapid research autopsy of cancer patients can elucidate heterogeneity-associated processes including cancer evolution and acquired therapeutic resistance. In practice, rapid research autopsy is performed shortly after a patient's passing to procure multiple metastatic tumor samples for genomic studies through next-generation sequencing and development of patient-derived xenografts or organoids.

Implementing precision cancer medicine in the genomic era.

The utilization of genomic data to direct treatment for cancer patients represents the central tenet in precision oncology, in which a patient is matched to a specific drug or therapy based on the genetic drivers detected in his or her tumor rather than the tumor's histologic classification. The expected but not always realized outcomes of molecularly matched therapies include increased response rates, more durable responses, deeper responses, and decreased number of therapy-related side effects. In this review, we will discuss different facets of utilizing genomic data to direct the increasingly complex care of cancer patients.

IntLIM: integration using linear models of metabolomics and gene expression data.

Background: Integration of transcriptomic and metabolomic data improves functional interpretation of disease-related metabolomic phenotypes, and facilitates discovery of putative metabolite biomarkers and gene targets. For this reason, these data are increasingly collected in large (> 100 participants) cohorts, thereby driving a need for the development of user-friendly and open-source methods/tools for their integration. Of note, clinical/translational studies typically provide snapshot (e.

Transcription factor-associated combinatorial epigenetic pattern reveals higher transcriptional activity of TCF7L2-regulated intragenic enhancers.

Background: Recent studies have suggested that combinations of multiple epigenetic modifications are essential for controlling gene expression. Despite numerous computational approaches have been developed to decipher the combinatorial epigenetic patterns or "epigenetic code", none of them has explicitly addressed the relationship between a specific transcription factor (TF) and the patterns.

Methods: Here, we developed a novel computational method, T-cep, for annotating chromatin states associated with a specific TF.

Landscape of Microsatellite Instability Across 39 Cancer Types.

Purpose: Microsatellite instability (MSI) is a pattern of hypermutation that occurs at genomic microsatellites and is caused by defects in the mismatch repair system. Mismatch repair deficiency that leads to MSI has been well described in several types of human cancer, most frequently in colorectal, endometrial, and gastric adenocarcinomas. MSI is known to be both predictive and prognostic, especially in colorectal cancer; however, current clinical guidelines only recommend MSI testing for colorectal and endometrial cancers.

Performance evaluation for rapid detection of pan-cancer microsatellite instability with MANTIS.

In current clinical practice, microsatellite instability (MSI) and mismatch repair deficiency detection is performed with MSI-PCR and immunohistochemistry. Recent research has produced several computational tools for MSI detection with next-generation sequencing (NGS) data; however a comprehensive analysis of computational methods has not yet been performed. In this study, we introduce a new MSI detection tool, MANTIS, and demonstrate its favorable performance compared to the previously published tools mSINGS and MSISensor.

Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.

Recent genome-wide profiling reveals highly complex regulation networks among ERα and its targets. We integrated estrogen (E2)-stimulated time-series ERα ChIP-seq and gene expression data to identify the ERα-centered transcription factor (TF) hubs and their target genes, and inferred the time-variant hierarchical network structures using a Bayesian multivariate modeling approach. With its recurrent motif patterns, we determined three embedded regulatory modules from the ERα core transcriptional network.

A hidden Markov model to identify combinatorial epigenetic regulation patterns for estrogen receptor α target genes.

Motivation: Many studies have shown that epigenetic changes, such as altered DNA methylation and histone modifications, are linked to estrogen receptor α (ERα)-positive tumors and disease prognoses. Several recent studies have applied high-throughput technologies such as ChIP-seq and MBD-seq to interrogate the altered architectures of ERα regulation in tamoxifen (Tam)-resistant breast cancer cells. However, the details of combinatorial epigenetic regulation of ERα target genes in breast cancers with acquired Tam resistance have not yet been fully examined.

High resolution detection and analysis of CpG dinucleotides methylation using MBD-Seq technology.

Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis.

W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data.

Unlabelled: ChIP-based technology is becoming the leading technology to globally profile thousands of transcription factors and elucidate the transcriptional regulation mechanisms in living cells. It has evolved rapidly in recent years, from hybridization with spotted or tiling microarray (ChIP-chip), to pair-end tag sequencing (ChIP-PET), to current massively parallel sequencing (ChIP-seq). Although there are many tools available for identifying binding sites (peaks) for ChIP-chip and ChIP-seq, few of them are available as easy-accessible online web tools for processing both ChIP-chip and ChIP-seq data for the ChIP-based user community.