Biology subjects

Liu, W.-H.

Publications and source records attributed to Liu, W.-H..

4 recordsLinked to original sources

bioRxiv2020

In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets

High-throughput sequencing describes multiple alterations in each tumor (1), but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient (2). Here, we established a Cre-ERT2-loxP based inducible RNAi-mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition was initiated in mice harboring orthotopic tumors. Fluorochrome guided, competitive in vivo trials identified a major tumor-maintaining potency of the MLL-AF4 fusion protein and validated MCL1 as vulnerability in some, but not all patients tumors. We could prove DUX4 to play an essential role in patients leukemias carrying the recently described DUX4-IGH translocation. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.

cancer biology↗

bioRxiv2019

KLF4 acts as a tumor suppressor in human B-cells and patients’ B-cell leukemias growing in mice

Clinic-close methods are not available that prioritize and validate potential therapeutic targets in individual tumors from the vast bulk of descriptive expression data. We developed a novel technique to express transgenes in established patient-derived xenograft (PDX) models in vivo to fill this gap. With this technique at hand, we analyzed the role of transcription factor Kruppel-like factor 4 (KLF4) in B-cell acute lymphoblastic leukemia (B-ALL) PDX models at different disease stages. In competitive pre-clinical in vivo trials, we found that re-expression of wild type KLF4 reduced leukemia load in PDX models of B-ALL, with strongest effects after conventional chemotherapy at minimal residual disease (MRD). A non-functional KLF4 mutant had no effect in this model. Re-expressing KLF4 sensitized tumor cells in the PDX model towards systemic chemotherapy in vivo. Of major translational relevance, Azacitidine upregulated KLF4 levels in the PDX model and a KLF4 knockout reduced Azacitidine-induced cell death, suggesting that Azacitidine can regulate KLF4 re-expression. These results support applying Azacitidine in patients with B-ALL to regulated KLF4 as a therapeutic option. Taken together, our novel technique allows studying the function of dysregulated genes in a highly clinic-related, translational context and testing clinically applicable drugs in a relevant pre-clinical model.

cancer biology↗

bioRxiv2019

Functional plasticity and reversible growth behavior of patients acute myeloid leukemia stem cells growing in mice

Resistance against chemotherapy remains a major obstacle in treating patients with acute myeloid leukemia (AML). Novel therapeutic concepts are especially desired to target and eliminate resistant AML stem cells. Here we show that AML stem cells harbor the plasticity to switch from a low-cycling, chemotherapy resistant state into an actively proliferating state associated with treatment response. We used patient-derived xenograft (PDX) cells from patients with high risk or relapsed AML, which were lentivirally transduced for marker expression, stained with the proliferation-sensitive dye Carboxyfluorescein succinimidyl ester (CFSE), and re-transplanted into next-recipient mice. A rare subpopulation of AML cells displayed reduced proliferation in vivo, associated with increased treatment resistance. The proportion of AML cells with stem cell potential was identical in both, the highly and lowly proliferative sub-fraction. In re-transplantation experiments, proliferation behavior proved reversible, and AML stem cells were able to switch between a high and low proliferation state. Our data indicate that AML stem cells display functional plasticity in vivo, which might be exploited for therapeutic purposes, to prevent AML relapse and ultimately improve the prognosis of patients with AML.

cancer biology↗

bioRxiv2017

Comparative genomic analyses highlight the contribution of pseudogenized protein-coding genes to human lincRNAs

BackgroundThe regulatory roles of long intergenic noncoding RNAs (lincRNAs) in humans have been revealed through the use of advanced sequencing technology. Recently, three possible scenarios of lincRNA origin have been proposed: de novo origination from intergenic regions, duplication from long noncoding RNA, and pseudogenization from protein. The first two scenarios are largely studied and supported, yet few studies focused on the evolution from pseudo genized protein-coding sequence to lincRNA. Due to the non-mutually exclusive nature that these three scenarios have, accompanied by the need of systematic investigation of lincRNA origination, we conduct a comparative genomics study to investigate the evolution of human lincRNAs.\n\nResultsCombining with syntenic analysis and stringent Blastn e-value cutoff, we found that the majority of lincRNAs are aligned to the intergenic regions of other species. Interestingly, 193 human lincRNAs could have protein-coding orthologs in at least two of nine vertebrates. Transposable elements in these conserved regions in human genome are much less than expectation. Moreover, 19% of these lincRNAs have overlaps with or are close to pseudogenes in the human genome.\n\nConclusionsWe suggest that a notable portion of lincRNAs could be derived from pseudogenized protein-coding genes. Furthermore, based on our computational analysis, we hypothesize that a subset of these lincRNAs could have potential to regulate their paralogs by functioning as competing endogenous RNAs. Our results provide evolutionary evidence of the relationship between human lincRNAs and protein-coding genes.

bioinformatics↗