Genentech Submits IPO Prospectus for TraCe-seq Platform to Decipher Transcriptional Basis of Cancer Drug Response

Targeted therapies against oncogenic driver gene mutations have provided significant clinical benefits to cancer patients, offering great hope for precision medicine. However, not all cancer patients respond to treatment, and other pre-existing and acquired resistance mechanisms pose substantial challenges to overall patient response and the durability of therapeutic efficacy. In recent years, targeted protein degradation, a novel mechanism of action (MOA), has garnered widespread attention. Unlike traditional occupancy-based targeted inhibition, heterobifunctional targeted protein degraders can simultaneously recruit E3 ubiquitin ligases to the target site and induce targeted degradation of the target molecule via ubiquitin-mediated proteolysis, and have been shown to outperform enzyme inhibition alone in specific scenarios. Nevertheless, it remains unclear whether dual-action inhibitor-degraders confer a universal advantage.

To address these challenges, a research team at Genentech, Inc. in the United States has developed a system named TraCe-seq (Tracking differential clonal response by scRNA-seq), which can simultaneously track tumor origins and compare the immediate responses of tumor cells to different therapies, significantly accelerating research into drug response or resistance mechanisms. Recently, this research was published online under the title “Identifying transcriptional programs underlying cancer drug response with TraCe-seq” inNature Biotechnology。

Published inNature Biotechnology 

To develop TraCe-seq, the research team constructed a lentiviral barcode library compatible with 3′-end single-cell RNA sequencing (scRNA-seq). Each barcode consists of 30 nucleotides, providing over 100,000 unique combinations. Additionally, the researchers designed an 8-nucleotide sublibrary index to flexibly control the total library size. Following successful transduction, the lentiviral vector stably integrates into the host genome, enabling constitutive expression of the selection marker, puromycin resistance, and enhanced green fluorescent protein (eGFP).

Figure 1. Schematic diagram of TraCe-seq construction and mechanism of action. Image source:Nature Biotechnology 

EGFR-targeted therapy represents a paradigmatic approach in precision oncology; therefore, researchers sought to employ TraCe-seq to better elucidate the unique mechanisms of action (MOAs) underlying EGFR-mediated therapeutic efficacy. While small-molecule strategies targeting EGFR have primarily focused on inhibiting its enzymatic activity, the downstream consequences of EGFR degradation remain poorly understood relative to those of enzyme inhibition. To this end, the research team developed GNE-104, a heterobifunctional degrader incorporating the EGFR inhibitor erlotinib.

To conduct the TraCe-seq experiment, the research team randomly selected 600 PC9 cells carrying unique barcodes, expanded them 12-fold, and performed single-cell transcriptome sequencing analysis on a subset of the cells with approximately 30x barcode coverage to record baseline transcriptional profiles and relative clonal abundances. Data analysis revealed that,GNE-104 treatment was less effective in reducing the absolute number and diversity of TraCe-seq barcodes.. Furthermore, although similar MAPK pathway inhibition was observed under all treatment conditions, the cell cycle arrest induced by erlotinib and GNE-069 was significantly greater than that induced by GNE-104, indicatingGNE-104 treatment allows more cells to persist under MAPK pathway inhibition.。

Figure 2. Poor efficacy of dual EGFR inhibitor-degrader. Image source:Nature Biotechnology 

To further investigate the differential responses of PC9 cells to these treatments at the clonal level, the research team classified the TraCe-seq barcodes and found that they were enriched in the treated population compared to the untreated population, and were categorized into three types of drug-resistant clones. Specifically,Compared with kinase inhibitor treatment, GNE-104 treatment resulted in the overexpression of a distinct set of TraCe-seq barcodes, which was classified as an anti-degradation property.。 

Figure 3. TraCe-seq reveals different types of drug-resistant clones. Image source:Nature Biotechnology 

Researchers explored the differences in baseline gene expression between drug-sensitive and drug-resistant clones. A comparison of baseline gene expression between kinase inhibitor-resistant and sensitive clones revealed that, prior to treatment, VIM and AXL were significantly upregulated in kinase inhibitor-resistant cells, confirming thatTraCe-seq successfully captures the expected drug-resistant subpopulations and associated molecular markers.. Degradation-resistant clones exhibited increased AXL expression only, without VIM upregulation, indicating that they are indeed transcriptionally distinct from kinase inhibitor-resistant clones. Furthermore, in these degradation-resistant clones,Compared with GNE-104 treatment, protein processing in the endoplasmic reticulum pathway induced by erlotinib treatment was the most enriched and significant pathway.。

Figure 4. Transcriptome-based analysis of distinct evolutionary trajectories. Source:Nature Biotechnology 

To further validate the role of endoplasmic reticulum stress in the efficacy of EGFR kinase inhibitors, researchers utilized the experimental inhibitor ISRIB to specifically block the overactivation of pro-death genes downstream of endoplasmic reticulum stress. In PC9 and NCI-H1975 cells,ISRIB treatment indeed attenuated the activation of ATF4, DDIT3, and PPP1R15A induced by EGFR kinase inhibitors and reduced cytotoxic efficacy.. Conversely, at extremely low non-toxic concentrations,The addition of an endoplasmic reticulum (ER) stress inducer significantly induced the expression of ER stress genes and enhanced the cytotoxic activity of the degrader GNE-104 in PC9 cells.。

Taken together, the TraCe-seq platform can identify pre-existing and adaptive transcriptional signatures that influence distinct therapeutic outcomes. By tracking responding and persisting cells following exposure to different EGFR-targeted therapies, and conducting differential gene expression analysis alongside pseudotemporal trajectory comparisons, the research team uncovered differences in the cellular mechanisms underlying EGFR-targeted drugs with distinct mechanisms of action (MOAs). This revealed an exciting and previously underappreciated aspect of the response to EGFR inhibitors: the induction of endoplasmic reticulum (ER) stress triggered by the inhibition of bound EGFR is critical for achieving optimal therapeutic efficacy.