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Simple Summary: Primary hepatocytes constitute the majority of liver cells and are responsible for many liver-related diseases, including cancer. However, the lack of robust methods for engineering primary hepatocytes ex vivo has hindered their versatile application in disease modeling. Here, we worked to enable genome manipulation in primary mouse hepatocytes in both monolayer culture and organoids, and achieved up to 80% and 20% single gene knockout efficiency, respectively. Using genome engineering of human pluripotent stem cell-derived hepatocytes, we developed a spectrum of isogenic cellular models of hepatocarcinoma with various single or combined oncogenic alterations, and demonstrated that the introduction of these alterations initiated malignant transformation, accelerated cancer growth, and altered transcriptomic profiles and pathway activities. These results reveal that oncogenic alterations dominate cancer characteristics and highlight a powerful genome-engineering-based platform for cancer mechanism studies. Genome editing has demonstrated its utility in generating isogenic cell-based disease models, enabling the precise introduction of genetic alterations into wild-type cells to mimic disease phenotypes and explore underlying mechanisms. However, its application in liver-related diseases has been limited by challenges in genetic modification of mature hepatocytes in a dish. Here, we conducted a systematic comparison of various methods for primary hepatocyte culture and gene delivery to achieve robust genome editing of hepatocytes ex vivo. Our efforts yielded editing efficiencies of up to 80% in primary murine hepatocytes cultured in monolayer and 20% in organoids. To model human hepatic tumorigenesis, we utilized hepatocytes differentiated from human pluripotent stem cells (hPSCs) as an alternative human hepatocyte source. We developed a series of cellular models by introducing various single or combined oncogenic alterations into hPSC-derived hepatocytes. Our findings demonstrated that distinct mutational patterns led to phenotypic variances, affecting both overgrowth and transcriptional profiles. Notably, we discovered that the PI3KCA E542K mutant, whether alone or in combination with exogenous c-MYC, significantly impaired hepatocyte functions and facilitated cancer metabolic reprogramming, highlighting the critical roles of these frequently mutated genes in driving liver neoplasia. In conclusion, our study demonstrates genome-engineered hepatocytes as valuable cellular models of hepatocarcinoma, providing insights into early tumorigenesis mechanisms. [ABSTRACT FROM AUTHOR]

Understanding the effects of genetic perturbations on the cellular state has been challenging using traditional pooled screens, which typically rely on the delivery of a single perturbation per cell and unidimensional phenotypic readouts. Here, we use barcoded open reading frame overexpression libraries coupled with single-cell RNA sequencing to assay cell state and fitness, a technique we call SEUSS (scalable functional screening by sequencing). Using SEUSS, we perturbed hPSCs with a library of developmentally critical transcription factors (TFs) and assayed the impact of TF overexpression on fitness and transcriptomic states. We further leveraged the versatility of the ORF library approach to assay mutant genes and whole gene families. From the transcriptomic responses, we built genetic co-regulatory networks to identify altered gene modules and found that KLF4 and SNAI2 drive opposing effects along the epithelial-mesenchymal transition axis. From the fitness responses, we identified ETV2 as a driver of reprogramming toward an endothelial-like state.

The metabolic pathways fueling tumor growth have been well characterized, but the specific impact of transforming events on network topology and enzyme essentiality remains poorly understood. To this end, we performed combinatorial CRISPR-Cas9 screens on a set of 51 carbohydrate metabolism genes that represent glycolysis and the pentose phosphate pathway (PPP). This high-throughput methodology enabled systems-level interrogation of metabolic gene dispensability, interactions, and compensation across multiple cell types. The metabolic impact of specific combinatorial knockouts was validated using 13C and 2H isotope tracing, and these assays together revealed key nodes controlling redox homeostasis along the KEAP-NRF2 signaling axis. Specifically, targeting KEAP1 in combination with oxidative PPP genes mitigated the deleterious effects of these knockouts on growth rates. These results demonstrate how our integrated framework, combining genetic, transcriptomic, and flux measurements, can improve elucidation of metabolic network alterations and guide precision targeting of metabolic vulnerabilities based on tumor genetics.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies.

Hair loss affects millions of people at some time in their life, and safe and efficient treatments for hair loss are a significant unmet medical need. We report that topical delivery of quercetin (Que) stimulates resting hair follicles to grow with rapid follicular keratinocyte proliferation and replenishes perifollicular microvasculature in mice. We construct dynamic single-cell transcriptome landscape over the course of hair regrowth and find that Que treatment stimulates the differentiation trajectory in the hair follicles and induces an angiogenic signature in dermal endothelial cells by activating HIF-1α in endothelial cells. Skin administration of a HIF-1α agonist partially recapitulates the pro-angiogenesis and hair-growing effects of Que. Together, these findings provide a molecular understanding for the efficacy of Que in hair regrowth, which underscores the translational potential of targeting the hair follicle niche as a strategy for regenerative medicine, and suggest a route of pharmacological intervention that may promote hair regrowth. [ABSTRACT FROM AUTHOR]

Affecting the repair function of RAD51 can effectively reverse tumor resistance to chemotherapy and radiotherapy. There is interaction between RAD51181−200 and BRCA1846−871. Using the computer to simulate single mutation of lysine at 862 position of BRCA1846−871, six BRCA1846−871 mutants with significant interaction with RAD51181−200 were screened out. These mutant peptides were obtained by 9-fluorenylmethyloxycarbonyl (Fmoc) solid-phase peptide synthesis (SPPS) method. All peptides were purified and characterized by liquid chromatography and ESI-MS. In this study, the interaction between RAD51181−200 and BRCA1846−871 or mutant peptides was investigated using circular dichroism spectroscopy (CD) and fluorescence spectroscopy. The CD results shown that the secondary structure change of RAD51181−200 induced by BRCA1846−871, BRCA1846−871 K862F (F), BRCA1846−871 K862G (G), BRCA1846−871 K862E (E) and BRCA1846−871 K862N (N) was obvious, which the α-helix content of RAD51181−200 decreased from 58.3–36.1%, 58.3–36.2%, 58.3–36.4%, 58.3–36.5% and 58.3–36.0%, respectively. While, the addition of BRCA1846−871 K862P (P) and BRCA1846−871 K862Y (Y) hardly changed the α-helix content of RAD51181−200. From the fluorescence results, the binding constants of F and Y are 1.00 × 105 M−1 and 1.16 × 105 M−1 respectively, which were both larger than that of BRCA1846−871 (9.01 × 102 M−1). The binding constant of RAD51181−200 with E (7.45 × 103 M−1) is slightly higher than that of BRCA1846−871. The binding constants of RAD51181−200 with P (1.24 × 103 M−1) and N (1.26 × 103 M−1) are similar to that of BRCA1846−871. However, the Kb value of G (1.51 × 102 M−1) is less than that of BRCA1846−871. Comparing all spectral data, F is the most significant one interacting with RAD51181−200. These findings could provide direction for peptide processing and application. [ABSTRACT FROM AUTHOR]