Whole-exome sequencing has been successful in identifying genetic factors contributing to familial or sporadic Parkinson’s disease (PD). However, this approach has not been applied to explore the impact of de novo mutations on PD pathogenesis. Here, we sequenced the exomes of 39 early onset patients, their parents, and 20 unaffected siblings to investigate the effects of de novo mutations on PD. We identified 12 genes with de novo mutations (MAD1L1,NUP98,PPP2CB,PKMYT1,TRIM24,CEP131,CTTNBP2,NUS1,SMPD3,MGRN1,IFI35, andRUSC2), which could be functionally relevant to PD pathogenesis. Further analyses of two independent case-control cohorts (1,852 patients and 1,565 controls in one cohort and 3,237 patients and 2,858 controls in the other) revealed thatNUS1harbors significantly more rare nonsynonymous variants (P= 1.01E-5, odds ratio = 11.3) in PD patients than in controls. Functional studies inDrosophilademonstrated that the loss ofNUS1could reduce the climbing ability, dopamine level, and number of dopaminergic neurons in 30-day-old flies and could induce apoptosis in fly brain. Together, our data suggest that de novo mutations could contribute to early onset PD pathogenesis and identifyNUS1as a candidate gene for PD.

Fully elucidating the molecular mechanisms of non-coding RNAs (ncRNAs), including micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs), underlying hepatocarcinogenesis is challenging. We characterized the expression profiles of ncRNAs and constructed a regulatory mRNA-lncRNA-miRNA (MLMI) network based on transcriptome sequencing (RNA-seq) of hepatocellular carcinoma (HCC, n = 9) patients. Of the identified miRNAs (n = 203) and lncRNAs (n = 1,090), we found 16 significantly differentially expressed (DE) miRNAs and three DE lncRNAs. The DE RNAs were highly enriched in 21 functional pathways implicated in HCC (p < 0.05), including p53, MAPK, and NAFLD signaling. Potential pairwise interactions between DE ncRNAs and mRNAs were fully characterized using in silico prediction and experimentally-validated evidence. We for the first time constructed a MLMI network of reciprocal interactions for 16 miRNAs, three lncRNAs, and 253 mRNAs in HCC. The predominant role of MEG3 in the MLMI network was validated by its overexpression in vitro that the expression levels of a proportion of MEG3-targeted miRNAs and mRNAs was changed significantly. Our results suggested that the comprehensive MLMI network synergistically modulated carcinogenesis, and the crosstalk of the network provides a new avenue to accurately describe the molecular mechanisms of hepatocarcinogenesis.

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Paclitaxel (Taxol) is an effective chemotherapeutic agent for treating breast cancer patients. However, chemoresistance is a major obstacle in cancer treatment. Here, we showed that overexpression of miR-16 promoted Taxol-induced cytotoxicity and apoptosis in breast cancer cells. Furthermore, IκB kinase β (IKBKB) was identified as a direct target of miR-16. Up-regulation of IKBKB suppressed Taxol-induced apoptosis and led to an increased resistance to Taxol, and restoring IKBKB expression in miR-16-overexpressing breast cancer cells recovered Taxol resistance. Moreover, miR-16 was highly expressed in Taxol-sensitive breast cancer tissues compared with Taxol-resistant tissues, and there was an inverse correlation between miR-16 expression and IKBKB expression in breast cancer tissues. The expression levels of miR-16 were negatively associated with T stages, whereas the expression of IKBKB was positively correlated with T stages, lymph node metastasis and clinical stages. Taken together, our data demonstrates that miR-16 sensitizes breast cancer cells to Taxol through the suppression of IKBKB expression, and targeting miR-16/IKBKB axis will be a promising strategy for overcoming Taxol resistance in breast cancer.

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and it remains a challenge to understand the genetic mechanisms underlying hepatocarcinogenesis. A global gene network of differential expression profiles in HCC has yet to be fully characterized. In the present study, we performed transcriptome sequencing (mRNA and lncRNA) in liver cancer and cirrhotic tissues of nine HCC patients. We identified differentially expressed genes (DEGs) and constructed a weighted gene co-expression network for the DEGs. In total, 755 DEGs (747 mRNA and eight lncRNA) were identified, and several co-expression modules were significantly associated with HCC clinical traits, including tumor location, tumor grade, and the α-fetoprotein (AFP) level. Of note, we identified 15 hub genes in the module associated with AFP level, and three (SPX, AFP and ADGRE1) of four hub genes were validated in an independent HCC cohort (n=78). Identification of hub genes for HCC clinical traits has implications for further understanding of the molecular genetic basis of HCC.