Although 70-80% of newly diagnosed ovarian cancer patients respond to first-line therapy, almost all relapse and five-year survival remains below 50%. One strategy to increase five-year survival is prolonging time to relapse by improving first-line therapy response. However, no biomarker today can accurately predict individual response to therapy. In this study, we present analytical and prospective clinical validation of a new test that utilizes primary patient tissue in 3D cell culture to make patient-specific response predictions prior to initiation of treatment in the clinic. Test results were generated within seven days of tissue receipt from newly diagnosed ovarian cancer patients obtained at standard surgical debulking or laparoscopic biopsy. Patients were followed for clinical response to chemotherapy. In a study population of 44, the 32 test-predicted Responders had a clinical response rate of 100% across both adjuvant and neoadjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p < 0.0001). The test also functioned as a prognostic readout with test-predicted Responders having a significantly increased progression-free survival compared to test-predicted Non-Responders, p = 0.01. This correlative accuracy establishes the test's potential to benefit ovarian cancer patients through accurate prediction of patient-specific response before treatment.

Inflammatory cytokines and lncRNAs are closely associated with tumorigenesis. Herein, we reveal inflammatory cytokines IL6 cooperates with long noncoding RNA CUDR to trigger the malignant transformation of human embryonic stem cells-derived hepatocyte-like stem cells. Mechanistically, IL6 cooperates with CUDR to cause MELLT3 to interact with SUV39h1 mRNA3'UTR and promote SUV39h1 expression. Moreover, the excessive SUV39h1 also increases tri-methylation of histone H3 on nineth lysine (H3K9me3). Intriguingly, under inflammatory conditions, H3K9me3 promotes the excessive expression and phosphorylation of NF-κB, and in turn, phorsphorylated NF-κB promotes the expression and phosphorylation of Stat3. Furthermore, that the phosphorylated Stat3 loads onto the promoter region of miRs and lncRNAs. Ultimately, the abnormal expression of miRs and lncRNAs increased telomerase activity, telomere length and microsatellite instability (MSI), leading to malignant transformation of hepatocyte-like stem cells.

As patient derived xenograft (PDX) models are increasingly used for preclinical drug development, strategies to account for the nonhuman component of PDX RNA expression data are critical to its interpretation. A bioinformatics pipeline to separate donor tumor and mouse stroma transcriptome profiles was devised and tested. To examine the molecular fidelity of PDX versus donor tumors, we compared mRNA differences between paired PDX-donor tumors from nine ovarian cancer patients. 1,935 differentially expressed genes were identified between PDX and donor tumors. Over 90% (n = 1767) of these genes were down-regulated in PDX models and enriched in stroma-specific functions. Several protein kinases were also differentially expressed in PDX tumors, e.g. PDGFRA, PDGFRB and CSF1R. Upon in silico removal of these PDX-donor tumor differentially expressed genes, a stronger transcriptional resemblance between PDX-donor tumor pairs was seen (average correlation coefficient increases from 0.91 to 0.95). We devised and validated an effective bioinformatics strategy to separate mouse stroma expression from human tumor expression for PDX RNAseq. In addition, we showed most of the PDX-donor differentially expressed genes were implicated in stromal components. The molecular similarities and differences between PDX and donor tumors have implications in future therapeutic trial designs and treatment response evaluations using PDX models.

The dysregulation of lncRNAs has increasingly been linked to many human diseases, especially in cancers. Our results demonstrate HULC, MALAT1 and TRF2 are highly expressed in human hepatocellular carcinoma tissues, and HULC plus MALAT1 overexpression drastically promotes the growth of liver cancer stem cells. Mechanistically, both HULC and MALAT1 overexpression enhanced RNA polII, P300, CREPT to load on the promoter region of telomere repeat-binding factor 2(TRF2), triggering the overexpression, phosphorylation and SUMOylation of TRF2. Strikingly, the excessive TRF2 interacts with HULC or MALAT1 to form the complex that loads on the telomeric region, replacing the CST/AAF and recruiting POT1, pPOT1, ExoI, SNM1B, HP1 α. Accordingly, the telomere is greatly protected and enlonged. Furthermore, the excessive HULC plus MALAT1 reduced the methylation of the TERC promoter dependent on TRF2, increasing the TERC expression that causes the increase of interplay between TRET and TERC. Ultimately, the interaction between RFC and PCNA or between CDK2 and CyclinE, the telomerase activity and the microsatellite instability (MSI) are significantly increased in the liver cancer stem cells. Our demonstrations suggest that haploinsufficiency of HULC/MALAT1 plays an important role in malignant growth of liver cancer stem cell.