ABSTRACT
By informing timely targeted treatments, rapid whole-genome sequencing can improve the outcomes of seriously ill children with genetic diseases, particularly infants in neonatal and pediatric intensive care units (ICUs). The need for highly qualified professionals to decipher results, however, precludes widespread implementation. We describe a platform for population-scale, provisional diagnosis of genetic diseases with automated phenotyping and interpretation. Genome sequencing was expedited by bead-based genome library preparation directly from blood samples and sequencing of paired 100-nt reads in 15.5 hours. Clinical natural language processing (CNLP) automatically extracted children's deep phenomes from electronic health records with 80% precision and 93% recall. In 101 children with 105 genetic diseases, a mean of 4.3 CNLP-extracted phenotypic features matched the expected phenotypic features of those diseases, compared with a match of 0.9 phenotypic features used in manual interpretation. We automated provisional diagnosis by combining the ranking of the similarity of a patient's CNLP phenome with respect to the expected phenotypic features of all genetic diseases, together with the ranking of the pathogenicity of all of the patient's genomic variants. Automated, retrospective diagnoses concurred well with expert manual interpretation (97% recall and 99% precision in 95 children with 97 genetic diseases). Prospectively, our platform correctly diagnosed three of seven seriously ill ICU infants (100% precision and recall) with a mean time saving of 22:19 hours. In each case, the diagnosis affected treatment. Genome sequencing with automated phenotyping and interpretation in a median of 20:10 hours may increase adoption in ICUs and, thereby, timely implementation of precise treatments.
Subject(s)
Diabetic Ketoacidosis/genetics , Genomics/methods , Electronic Health Records , Female , Humans , Intensive Care Units/statistics & numerical data , Natural Language Processing , Retrospective StudiesABSTRACT
Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.
Subject(s)
DNA, Neoplasm/genetics , Gene Dosage/genetics , Genome, Human/genetics , Plasma/chemistry , Prostatic Neoplasms/blood , Prostatic Neoplasms/genetics , Aged , Aged, 80 and over , Androgen Antagonists/therapeutic use , Base Sequence , Biopsy , DNA Copy Number Variations/genetics , Gene Library , Genome-Wide Association Study , Humans , Male , Middle Aged , PTEN Phosphohydrolase/blood , PTEN Phosphohydrolase/genetics , Prostate/pathology , Prostatic Neoplasms/therapy , Recombinant Fusion Proteins/blood , Recombinant Fusion Proteins/genetics , Sequence Analysis, DNA , Serine Endopeptidases/blood , Serine Endopeptidases/genetics , Trans-Activators/blood , Trans-Activators/genetics , Transcriptional Regulator ERG , Treatment OutcomeABSTRACT
OBJECTIVES: Inherited genetic variability contributes to susceptibility to cervical cancer. We investigated the association of single nucleotide polymorphisms (SNPs) in the human epidermal growth factor receptor (ERBB) family with cervical cancer. METHODS: We used the transmission disequilibrium test (TDT) to look for excessive transmission of tag single nucleotide polymorphisms (tSNPs) in ERBB family members EGFR, ERBB2, ERBB3, and ERBB4 in a large sample of women with invasive and in situ cervical cancer and their biological parents (628 trios). The study used a discovery set of trios (244) analyzed by Illumina GoldenGate in which SNPs reaching a P<.05 were re-tested by TaqMan in the combined set of 628. We also explored collaborative effects of different ERBB alleles. RESULTS: Based on single SNP TDT tests we identified 16 significant SNPs in the discover stage and six of 14 SNPs that could be assayed by TaqMan were significantly overtransmitted in women with cervical cancer in the combined replication set. Four SNPs were located in intron 1 of EGFR and two SNPs in intron 24 of ERBB4. The EGFR variants are located near multiple enhancers, silencers, and the previously identified functional common polymorphisms in intron 1. CONCLUSIONS: Our data provide evidence for the involvement of intron 1 EGFR variants and intron 24 ERBB4 variants in modulating risk for the development of in situ and invasive cervical cancer. These variants should be examined in additional populations and functional studies would be needed to confirm this hypothesis.
