Biology subjects

Kertalli, S.

Publications and source records attributed to Kertalli, S..

2 recordsLinked to original sources

bioRxiv2024

Transcriptional Dosage of Oncogenic KRAS Drives Lung Adenocarcinoma Cell States, Progression and Metastasis

Cancer cells display distinct, recurrent phenotypic cell states. Metastatic spreading correlates with tumor cell state evolution. However, the molecular mechanisms underlying metastasis remain elusive. Here, we demonstrate that the quantitative dosage of oncogenic KRAS drives lung adenocarcinoma progression and metastasis via the integration of external signaling and pioneer transcription factor dynamics into qualitative cell states. Combining mouse models, in vivo CRISPR activation screens, and fate mapping, we show that even mild transcriptional amplification of KRAS significantly fuels tumor progression and metastasis. Chromatin profiling and transcriptomics reveal that high and low KRAS dosages supersede and integrate inflammatory and TGF{beta} signaling to dictate mouse cancer cell states. Patient data show that KRAS dosages correlate with distinct survival outcomes, transcription factor activity, and cell states. Direct KRAS inhibition in xenografts limits the KRAS-high "proliferative" cell state but spares a minimal residual state mimicking the KRAS-low "ciliated-like" state. Thus, oncogenic KRAS dosage fuels tumor heterogeneity at the cell state level and drives a bimodal tumor evolution during metastasis, with implications for prognosis and treatment.

cancer biology↗

bioRxiv2022

Logical design of synthetic cis-regulatory DNA for genetic tracing of cell identities and state changes

Descriptive data are rapidly expanding in biomedical research. Instead, functional validation methods with sufficient complexity remain underdeveloped. Transcriptional reporters allow experimental characterization and manipulation of developmental and disease cell states, but their design lacks flexibility. Here, we report logical design of synthetic cis-regulatory DNA(LSD), a computational framework leveraging phenotypic biomarkers and trans-regulatory networks as input to design reporters marking the activity of selected cellular states and pathways. LSD uses bulk or single-cell biomarkers and a reference genome or custom cis-regulatory DNA datasets with user-defined boundary regions. By benchmarking validated reporters, we integrated LSD with a computational classifier to rank phenotypic specificity of putative cis-regulatory DNA. Experimentally, LSD-designed reporters targeting a wide range of cell states are functional without minimal promoters. In silico, an LSD-unsupervised mesenchymal glioblastoma reporter outperformed previously validated ones. In genome-scale CRISPRa screens, it discovered known and novel bona fide cell-state-drivers. Thus, LSD captures core principles of cis-regulation and is broadly applicable to studying complex cell states and mechanisms of transcriptional regulation.

bioengineering↗