RESUMO
Panax ginseng C.A. Mey., known for its medicinal and dietary supplement properties, primarily contains pharmacologically active ginsenosides. However, the regulatory mechanisms linking ginseng root development with ginsenoside biosynthesis are still unclear. Root meristem growth factors (RGFs) are crucial for regulating plant root growth. In our study, we identified five ginseng RGF peptide sequences from the ginseng genome and transcriptome libraries. We treated Arabidopsis and ginseng adventitious roots with exogenous Panax ginseng RGFs (PgRGFs) to assess their activities. Our results demonstrate that PgRGF1 influences gravitropic responses and reduces lateral root formation in Arabidopsis. PgRGF1 has been found to restrict the number and length of ginseng adventitious root branches in ginseng. Given the medicinal properties of ginseng, We determined the ginsenoside content and performed transcriptomic analysis of PgRGF1-treated ginseng adventitious roots. Specifically, the total ginsenoside content in ginseng adventitious roots decreased by 19.98 % and 63.71 % following treatments with 1 µM and 10 µM PgRGF1, respectively, compared to the control. The results revealed that PgRGF1 affects the accumulation of ginsenosides by regulating the expression of genes associated with auxin transportation and ginsenoside biosynthesis. These findings suggest that PgRGF1, as a peptide hormone regulator in ginseng, can modulate adventitious root growth and ginsenoside accumulation.
RESUMO
The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somatic CNA data obtained from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), we implemented Kaplan-Meier estimators and Cox proportional hazards models to examine the association of CNA burden with patient's overall survival (OS) and disease specific survival (DSS). We also evaluated the association by considering patients' age and tumor subtypes using stratified Cox models. We delineated the distribution of CNA burden in sample genomes and highlighted chromosomes 1, 8, and 16 as the carriers of the highest CNA burden. We identified a strong association between CNA burden and age as well as CNA burden and breast cancer PAM50 subtypes. We found that controlling the effects of both age (bound by 45-year) and PAM50 subtypes on patient survival using stratified Cox models, would still result in significant association between CNA burden and patients overall survival in both Discovery and Validation data. The same trend was observed in disease specific survival when only PAM50 subtypes were controlled in the stratified Cox models. Our analysis showed that there is a significant association between CNA burden and breast cancer survival. This result is also validated by using TCGA (The Cancer Genome Atlas) data. CNA burden of breast cancer patients has a considerable potential to be used as a novel prognostic biomarker.
