Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs. Copy number variation, as well as epigenetic variation and extrachromosomal DNA distribution all contribute to the detected intra-cell-line heterogeneity. Using hypoxia treatment as an example, we demonstrate that transcriptomic heterogeneity could be reshaped by environmental stress. Overall, our study performs single-cell multi-omics of commonly used human cancer cell lines and offers mechanistic insights into the intra-cell-line heterogeneity and its dynamics, which would serve as an important resource for future cancer cell line-based studies.

DPF3, a component of the SWI/SNF chromatin remodeling complex, has been associated with clear cell renal cell carcinoma (ccRCC) in a genome-wide association study. However, the functional role of DPF3 in ccRCC development and progression remains unknown. In this study, we demonstrate that DPF3a, the short isoform of DPF3, promotes kidney cancer cell migration both in vitro and in vivo, consistent with the clinical observation that DPF3a is significantly upregulated in ccRCC patients with metastases. Mechanistically, DPF3a specifically interacts with SNIP1, via which it forms a complex with SMAD4 and p300 histone acetyltransferase (HAT), the major transcriptional regulators of TGF-β signaling pathway. Moreover, the binding of DPF3a releases the repressive effect of SNIP1 on p300 HAT activity, leading to the increase in local histone acetylation and the activation of cell movement related genes. Overall, our findings reveal a metastasis-promoting function of DPF3, and further establish the link between SWI/SNF components and ccRCC.

Epithelial–mesenchymal transition (EMT) is a fundamental cellular process frequently hijacked by cancer cells to promote tumor progression, especially metastasis. EMT is orchestrated by a complex molecular network acting at different layers of gene regulation. In addition to transcriptional regulation, posttranscriptional mechanisms may also play a role in EMT. Here, we performed a pooled CRISPR screen analyzing the influence of 1,547 RNA-binding proteins on cell motility in colon cancer cells and identified multiple core components of P-bodies (PB) as negative modulators of cancer cell migration. Further experiments demonstrated that PB depletion by silencing DDX6 or EDC4 could activate hallmarks of EMT thereby enhancing cell migration in vitro as well as metastasis formation in vivo. Integrative multiomics analysis revealed that PBs could repress the translation of the EMT driver gene HMGA2, which contributed to PB-meditated regulation of EMT. This mechanism is conserved in other cancer types. Furthermore, endoplasmic reticulum stress was an intrinsic signal that induced PB disassembly and translational derepression of HMGA2. Taken together, this study has identified a function of PBs in the regulation of EMT in cancer. Significance: Systematic investigation of the influence of posttranscriptional regulation on cancer cell motility established a connection between P-body–mediated translational control and EMT, which could be therapeutically exploited to attenuate metastasis formation.

Aberrant expression of Myc is one of the most common oncogenic events in human cancers. Scores of Myc inhibitors are currently under development for treating Myc-driven cancers. In addition to directly targeting tumor cells, Myc inhibition has been shown to modulate the tumor microenvironment to promote tumor regression. However, the effect of Myc inhibition on immune cells in the tumor microenvironment remains poorly understood. Here, we show that the adaptive immune system plays a vital role in the antitumor effect of pharmacologic inhibition of Myc. Combining genetic and pharmacologic approaches, we found that Myc inhibition enhanced CD8 T cell function by suppressing the homeostasis of regulatory T (Treg) cells and the differentiation of resting Treg (rTreg) cells to activated Treg (aTreg) cells in tumors. Importantly, we demonstrated that different Myc expression levels confer differential sensitivity of T cell subsets to pharmacologic inhibition of Myc. Although ablation of the Myc gene has been shown to suppress CD8 T cell function, Treg cells, which express much less Myc protein than CD8 T cells, are more sensitive to Myc inhibitors. The differential sensitivity of CD8 T and Treg cells to Myc inhibitors resulted in enhanced CD8 T cell function upon Myc inhibition. Our findings revealed that Myc inhibitors can induce an antitumor immune response during tumor progression.

CRISPR/Cas-based transcriptional activators can be enhanced by intrinsically disordered regions (IDRs). However, the underlying mechanisms are still debatable. Here, we examine 12 well-known IDRs by fusing them to the dCas9-VP64 activator, of which only seven can augment activation, albeit independently of their phase separation capabilities. Moreover, modular domains (MDs), another class of multivalent molecules, though ineffective in enhancing dCas9-VP64 activity on their own, show substantial enhancement in transcriptional activation when combined with dCas9-VP64-IDR. By varying the number of gRNA binding sites and fusing dCas9-VP64 with different IDRs/MDs, we uncover that optimal, rather than maximal, cis-trans cooperativity enables the most robust activation. Finally, targeting promoter-enhancer pairs yields synergistic effects, which can be further amplified via enhancing chromatin interactions. Overall, our study develops a versatile platform for efficient gene activation and sheds important insights into CRIPSR-based transcriptional activators enhanced with multivalent molecules.

The accurate annotation of transcription start sites (TSSs) and their usage are critical for the mechanistic understanding of gene regulation in different biological contexts. To fulfill this, specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner, and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences. Most of these computational tools cast the problem as a binary classification task on a balanced dataset, thus resulting in drastic false positive predictions when applied on the genome scale. Here, we present DeeReCT-TSS, a deep learning-based method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing data. We show that by effectively incorporating these two sources of information, DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types. Furthermore, we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types, which enables the identification of cell type-specific TSSs. Finally, we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin states. The source code for DeeReCT-TSS is available at https://github.com/JoshuaChou2018/DeeReCT-TSS_release and https://ngdc.cncb.ac.cn/biocode/tools/BT007316.