Enhancing Diagnosis Through RNA Sequencing

Moving the Needle Forward in Genomically-Guided Precision Radiation Treatment

Radiation treatment (RT) is a mainstay treatment for many types of cancer. Recommendations for RT and the radiation plan are individualized to each patient, taking into consideration the patient's tumor pathology, staging, anatomy, and other clinical characteristics. Information on germline mutations and somatic tumor mutations is at present rarely used to guide specific clinical decisions in RT. Many genes, such as ATM, and BRCA1/2, have been identified in the laboratory to confer radiation sensitivity. However, our understanding of the clinical significance of mutations in these genes remains limited and, as individual mutations in such genes can be rare, their impact on tumor response and toxicity remains unclear. Current guidelines, including those from the National Comprehensive Cancer Network (NCCN), provide limited guidance on how genetic results should be integrated into RT recommendations. With an increasing understanding of the molecular underpinning of radiation response, genomically-guided RT can inform decisions surrounding RT dose, volume, concurrent therapies, and even omission to further improve oncologic outcomes and reduce risks of toxicities. Here, we review existing evidence from laboratory, pre-clinical, and clinical studies with regard to how genetic alterations may affect radiosensitivity. We also summarize recent data from clinical trials and explore potential future directions to utilize genetic data to support clinical decision-making in developing a pathway toward personalized RT.

Identification of potential feature genes in non-alcoholic fatty liver disease using bioinformatics analysis and machine learning strategies

The prevalence of non-alcoholic fatty liver disease (NAFLD) and NAFLD-associated hepatocellular carcinoma (HCC) has continuously increased in recent years. Machine learning is an effective method for screening the feature genes of a disease for prediction, prevention and personalized treatment. Here, we used the "limma" package and weighted gene co-expression network analysis (WGCNA) to screen 219 NAFLD-related genes and found that they were mainly enriched in inflammation-related pathways. Four feature genes (AXUD1, FOSB, GADD45B, and SOCS2) were screened by LASSO regression and support vector machine-recursive feature elimination (SVM-RFE) machine learning algorithms. Therefore, a clinical diagnostic model with an area under the curve (AUC) value of 0.994 was constructed, which was superior to other indicators of NAFLD. Significant correlations existed between feature genes expression and steatohepatitis histology or clinical variables. These findings were also validated in external datasets and a mouse model. Finally, we found that feature genes expression was significantly decreased in NAFLD-associated HCC and that SOCS2 may be a prognostic biomarker. Our findings may provide new insights into the diagnosis, prevention and treatment targets of NAFLD and NAFLD-associated HCC.

Blood-Based mRNA Tests as Emerging Diagnostic Tools for Personalised Medicine in Breast Cancer

Molecular diagnostic tests help clinicians understand the underlying biological mechanisms of their patients' breast cancer (BC) and facilitate clinical management. Several tissue-based mRNA tests are used routinely in clinical practice, particularly for assessing the BC recurrence risk, which can guide treatment decisions. However, blood-based mRNA assays have only recently started to emerge. This review explores the commercially available blood mRNA diagnostic assays for BC. These tests enable differentiation of BC from non-BC subjects (Syantra DX, BCtect), detection of small tumours <10 mm (early BC detection) (Syantra DX), detection of different cancers (including BC) from a single blood sample (multi-cancer blood test Aristotle), detection of BC in premenopausal and postmenopausal women and those with high breast density (Syantra DX), and improvement of diagnostic outcomes of DNA testing (variant interpretation) (+RNAinsight). The review also evaluates ongoing transcriptomic research on exciting possibilities for future assays, including blood transcriptome analyses aimed at differentiating lymph node positive and negative BC, distinguishing BC and benign breast disease, detecting ductal carcinoma in situ, and improving early detection further (expression changes can be detected in blood up to eight years before diagnosing BC using conventional approaches, while future metastatic and non-metastatic BC can be distinguished two years before BC diagnosis).

Overview of gene expression techniques with an emphasis on vitamin D related studies

Each cell controls when and how its genes must be expressed for proper function. Every function in a cell is driven by signaling molecules through various regulatory cascades. Different cells in a multicellular organism may express very different sets of genes, even though they contain the same DNA. The set of genes expressed in a cell determines the set of proteins and functional RNAs it contains, giving it its unique properties. Malfunction in gene expression harms the cell and can lead to the development of various disease conditions. The use of rapid high-throughput gene expression profiling unravels the complexity of human disease at various levels. Peripheral blood mononuclear cells (PBMC) have been used frequently to understand gene expression homeostasis in various disease conditions. However, more studies are required to validate whether PBMC gene expression patterns accurately reflect the expression of other cells or tissues. Vitamin D, which is responsible for a multitude of health consequences, is also an immune modulatory hormone with major biological activities in the innate and adaptive immune systems. Vitamin D exerts its diverse biological effects in target tissues by regulating gene expression and its deficiency, is recognized as a public health problem worldwide. Understanding the genetic factors that affect vitamin D has the potential benefit that it will make it easier to identify individuals who require supplementation. Different technological advances in gene expression can be used to identify and assess the severity of disease and aid in the development of novel therapeutic interventions. This review focuses on different gene expression approaches and various clinical studies of vitamin D to investigate the role of gene expression in identifying the molecular signature of the disease.

How we approach genetics in the diagnosis and management of vascular anomalies

Vascular anomalies are a heterogeneous group of disorders that are currently classified based on their clinical and histological characteristics. Over the past decade, there have been significant advances in molecular genetics that have led to identification of genetic alterations associated with vascular tumors, vascular malformations, and syndromes. Here, we describe known genetic alterations in vascular anomalies, discuss when and how to test, and examine how identification of causative genetic mutations provides for better management of these disorders through improved understanding of their pathogenesis and increasing use of targeted therapeutic agents in order to achieve better outcomes for our patients.

Molecular Diagnoses of X-Linked and Other Genetic Hypophosphatemias: Results From a Sponsored Genetic Testing Program

X-linked hypophosphatemia (XLH), a dominant disorder caused by pathogenic variants in the PHEX gene, affects both sexes of all ages and results in elevated serum fibroblast growth factor 23 (FGF23) and below-normal serum phosphate. In XLH, rickets, osteomalacia, short stature, and lower limb deformity may be present with muscle pain and/or weakness/fatigue, bone pain, joint pain/stiffness, hearing difficulty, enthesopathy, osteoarthritis, and dental abscesses. Invitae and Ultragenyx collaborated to provide a no-charge sponsored testing program using a 13-gene next-generation sequencing panel to confirm clinical XLH or aid diagnosis of suspected XLH/other genetic hypophosphatemia. Individuals aged ≥6 months with clinical XLH or suspected genetic hypophosphatemia were eligible. Of 831 unrelated individuals tested between February 2019 and June 2020 in this cross-sectional study, 519 (62.5%) individuals had a pathogenic or likely pathogenic variant in PHEX (PHEX-positive). Among the 312 PHEX-negative individuals, 38 received molecular diagnoses in other genes, including ALPL, CYP27B1, ENPP1, and FGF23; the remaining 274 did not have a molecular diagnosis. Among 319 patients with a provider-reported clinical diagnosis of XLH, 88.7% (n = 283) had a reportable PHEX variant; 81.5% (n = 260) were PHEX-positive. The most common variant among PHEX-positive individuals was an allele with both the gain of exons 13-15 and c.*231A>G (3'UTR variant) (n = 66/519). Importantly, over 80% of copy number variants would have been missed by traditional microarray analysis. A positive molecular diagnosis in 41 probands (4.9%; 29 PHEX positive, 12 non-PHEX positive) resulted in at least one family member receiving family testing. Additional clinical or family member information resulted in variant(s) of uncertain significance (VUS) reclassification to pathogenic/likely pathogenic (P/LP) in 48 individuals, highlighting the importance of segregation and clinical data. In one of the largest XLH genetic studies to date, 65 novel PHEX variants were identified and a high XLH diagnostic yield demonstrated broad insight into the genetic basis of XLH. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Loss of Gene Information: Discrepancies between RNA Sequencing, cDNA Microarray, and qRT-PCR

Molecular analyses of normal and diseased cells give insight into changes in gene expression and help in understanding the background of pathophysiological processes. Years after cDNA microarrays were established in research, RNA sequencing (RNA-seq) became a key method of quantitatively measuring the transcriptome. In this study, we compared the detection of genes by each of the transcriptome analysis methods: cDNA array, quantitative RT-PCR, and RNA-seq. As expected, we found differences in the gene expression profiles of the aforementioned techniques. Here, we present selected genes that exemplarily demonstrate the observed differences and calculations to reveal that a strong RNA secondary structure, as well as sample preparation, can affect RNA-seq. In summary, this study addresses an important issue with a strong impact on gene expression analysis in general. Therefore, we suggest that these findings need to be considered when dealing with data from transcriptome analyses.

From Transcriptomics to Treatment in Inherited Optic Neuropathies

Inherited optic neuropathies, including Leber Hereditary Optic Neuropathy (LHON) and Dominant Optic Atrophy (DOA), are monogenetic diseases with a final common pathway of mitochondrial dysfunction leading to retinal ganglion cell (RGC) death and ultimately loss of vision. They are, therefore, excellent models with which to investigate this ubiquitous disease process-implicated in both common polygenetic ocular diseases (e.g., Glaucoma) and late-onset central nervous system neurodegenerative diseases (e.g., Parkinson disease). In recent years, cellular and animal models of LHON and DOA have matured in parallel with techniques (such as RNA-seq) to determine and analyze the transcriptomes of affected cells. This confluence leaves us at a particularly exciting time with the potential for the identification of novel pathogenic players and therapeutic targets. Here, we present a discussion of the importance of inherited optic neuropathies and how transcriptomic techniques can be exploited in the development of novel mutation-independent, neuroprotective therapies.