Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

Prenatal whole exome sequencing identified two rare compound heterozygous variants in EVC2 causing Ellis-van Creveld syndrome

BACKGROUND

Pathogenic mutations in EVC or EVC2 gene can lead to Ellis-van Creveld (EvC) syndrome, which is a rare autosomal recessive skeletal dysplasia disorder. This study aimed to determine pathogenic gene variations associated with EvC syndrome in fetuses showing ultrasound anomalies.

METHODS

A 32-year-old pregnant woman from Quanzhou, China was investigated. In her pregnancy examination, the fetus exhibited multiple fetal malformations, including a narrow thorax, short limbs, postaxial polydactyly, cardiac malformations, and separation of double renal pelvis. Karyotype, chromosomal microarray analysis and whole exome sequencing were performed for prenatal genetic etiology analysis.

RESULTS

Chromosome abnormalities and copy number variants were not observed in the fetus using karyotype and chromosomal microarray analysis. Using whole exome sequencing, two compound heterozygous variants NM_147127.5:c.[2484G>A(p.Trp828Ter)];[871-2_894del] in EVC2 gene were identified in the fetus as pathogenic variants inherited from parents.

CONCLUSIONS

The study is the first to identify two rare compound variants in EVC2 gene in a Chinese family using whole exome sequencing. The application of whole-exome sequencing would be helpful in fetal etiological diagnosis with ultrasound anomalies.