Chromatin accessibility dynamics in colorectal cancer liver metastasis: Uncovering the liver tropism at single cell resolution.

Tumor metastasis causes over 90% of cancer related death and no currently available therapies target it. However, there is limited understanding regarding the epigenetic regulation of genes during this complex process. Here by integrating single-cell ATAC-seq (scATAC-seq), single-cell RNA-seq (scRNA-seq), microarray, bulk RNA-seq, immunohistochemistry (IHC) staining, as well as proteomics datasets from paired primary and liver metastatic colorectal cancer (CRC) patient-derived xenograft (PDX) model and patients, we discovered that liver metastatic CRC cells lose their colon-specific chromatin accessible sites yet gain liver-specific ones. Importantly, we observed elevated accessibility of HNF4A, a liver-specific transcription factor, in liver metastatic CRC cells. Subsequently, we performed clustering analysis of liver metastatic CRC cells together with cells involved in liver development, revealing significant heterogeneity among the liver metastatic CRC cells. Over 50% of the liver metastatic CRC cells exhibited characteristics similar to those of erythroid progenitors and hepatocytes, showing increased expression of genes involved in oxidative phosphorylation and glycolysis. Moreover, our discovery further revealed that the MHC and IFN response genes in these cells exhibit moderate epigenetic activity, which is significantly associated with the low objective response rates in checkpoint blockade immunotherapy. Our findings uncovered the critical roles of HNF4A and the cell populations within liver metastatic CRC cells might serve as crucial therapeutic targets for addressing liver metastasis and improving the immunotherapy response in patients with CRC.

Long non-coding RNA DARS-AS1 promotes tumor progression by directly suppressing PACT-mediated cellular stress.

Cancer cells evolve various mechanisms to overcome cellular stresses and maintain progression. Protein kinase R (PKR) and its protein activator (PACT) are the initial responders in monitoring diverse stress signals and lead to inhibition of cell proliferation and cell apoptosis in consequence. However, the regulation of PACT-PKR pathway in cancer cells remains largely unknown. Herein, we identify that the long non-coding RNA (lncRNA) aspartyl-tRNA synthetase antisense RNA 1 (DARS-AS1) is directly involved in the inhibition of the PACT-PKR pathway and promotes the proliferation of cancer cells. Using large-scale CRISPRi functional screening of 971 cancer-associated lncRNAs, we find that DARS-AS1 is associated with significantly enhanced proliferation of cancer cells. Accordingly, knocking down DARS-AS1 inhibits cell proliferation of multiple cancer cell lines and promotes cancer cell apoptosis in vitro and significantly reduces tumor growth in vivo. Mechanistically, DARS-AS1 directly binds to the activator domain of PACT and prevents PACT-PKR interaction, thereby decreasing PKR activation, eIF2α phosphorylation and inhibiting apoptotic cell death. Clinically, DARS-AS1 is broadly expressed across multiple cancers and the increased expression of this lncRNA indicates poor prognosis. This study elucidates the lncRNA DARS-AS1 directed cancer-specific modulation of the PACT-PKR pathway and provides another target for cancer prognosis and therapeutic treatment.

Genetic association and single-cell transcriptome analyses reveal distinct features connecting autoimmunity with cancers.

Autoimmune diseases (ADs) are at a significantly higher risk of cancers with unclear mechanism. By searching GWAS catalog database and Medline, susceptible genes for five common ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis, Sjögren syndrome, systemic sclerosis, and idiopathic inflammatory myopathies, were collected and then were overlapped with cancer driver genes. Single-cell transcriptome analysis was performed in the comparation between SLE and related cancer. We identified 45 carcinogenic autoimmune disease risk (CAD) genes, which were mainly enriched in T cell signaling pathway and B cell signaling pathway. Integrated single-cell analysis revealed immune cell signaling was significantly downregulated in renal cancer compared with SLE, while stemness signature was significantly enriched in both renal cancer or lymphoma and SLE in specific subpopulations. Drugs targeting CAD genes were shared between ADs and cancer. Our study highlights the common and specific features between ADs and related cancers, and sheds light on a new discovery of treatments.

Tumor immunological phenotype signature-based high-throughput screening for the discovery of combination immunotherapy compounds.

Combination immunotherapy is promising to overcome the limited objective response rates of immune checkpoint blockade (ICB) therapy. Here, a tumor immunological phenotype (TIP) gene signature and high-throughput sequencing-based high-throughput screening (HTS2) were combined to identify combination immunotherapy compounds. We firstly defined a TIP gene signature distinguishing "cold" tumors from "hot" tumors. After screening thousands of compounds, we identified that aurora kinase inhibitors (AKIs) could reprogram the expression pattern of TIP genes in triple-negative breast cancer (TNBC) cells. AKIs treatments up-regulate expression of chemokine genes CXCL10 and CXCL11 through inhibiting aurora kinase A (AURKA)-signal transducer and activator of transcription 3 (STAT3) signaling pathway, which promotes effective T cells infiltrating into tumor microenvironment and improves anti-programmed cell death 1 (PD-1) efficacy in preclinical models. Our study established a novel strategy to discover combination immunotherapy compounds and suggested the therapeutic potential of combining AKIs with ICB for the treatment of TNBC.

A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines.

Coronavirus disease-2019 (COVID-19) has become a major global epidemic. Facilitated by HTS2 technology, we evaluated the effects of 578 herbs and all 338 reported anti-COVID-19 TCM formulae on cytokine storm-related signaling pathways, and identified the key targets of the relevant pathways and potential active ingredients in these herbs. This large-scale transcriptional study innovatively combines HTS2 technology with bioinformatics methods and computer-aided drug design. For the first time, it systematically explores the molecular mechanism of TCM in regulating the COVID-19-related cytokine storm, providing an important scientific basis for elucidating the mechanism of action of TCM in treating COVID-19.

An immune-related gene signature for predicting survival and immunotherapy efficacy in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) ranks the fourth in terms of cancer-related mortality globally. Herein, in this research, we attempted to develop a novel immune-related gene signature that could predict survival and efficacy of immunotherapy for HCC patients. METHODS: The transcriptomic and clinical data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) and GSE14520 datasets, followed by acquiring immune-related genes from the ImmPort database. Afterwards, an immune-related gene-based prognostic index (IRGPI) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Kaplan-Meier survival curves as well as time-dependent receiver operating characteristic (ROC) curve were performed to evaluate its predictive capability. Besides, both univariate and multivariate analyses on overall survival for the IRGPI and multiple clinicopathologic factors were carried out, followed by the construction of a nomogram. Finally, we explored the possible correlation of IRGPI with immune cell infiltration or immunotherapy efficacy. RESULTS: Analysis of 365 HCC samples identified 11 differentially expressed immune-related genes, which were selected to establish the IRGPI. Notably, it can predict the survival of HCC patients more accurately than published biomarkers. Furthermore, IRGPI can predict the infiltration of immune cells in the tumor microenvironment of HCC, as well as the response of immunotherapy. CONCLUSION: Collectively, the currently established IRGPI can accurately predict survival, reflect the immune microenvironment, and predict the efficacy of immunotherapy among HCC patients.

Oncogenic lncRNA LINC00973 promotes Warburg effect by enhancing LDHA enzyme activity.

Aerobic glycolysis, also known as the Warburg effect, is a hallmark of cancer and essential for metabolism in malignancies, but its regulation and modulation in cancer cells remain poorly understood. Here, using large-scale functional screening, we identified a tumor-associated and broadly expressed oncogenic long noncoding RNA LINC00973. Notably, knocking down LINC00973 significantly inhibits the proliferation of multiple types of cancer cells and reduces tumor growth in vivo. Mechanistically, LINC00973 directly binds to lactate dehydrogenase A (LDHA), an essential glycolytic enzyme, and enhances its enzymatic activity, thereby promoting glycolysis. Clinically, high expression of LINC00973 is significantly associated with poor prognosis in many types of human cancers. This work demonstrates that LINC00973 modulates cancer-specific regulation of the Warburg effect, and may represent a potential target for broad-acting anti-cancer therapies.

Guizhi Fuling Decoction inhibiting the PI3K and MAPK pathways in breast cancer cells revealed by HTS2 technology and systems pharmacology.

As one of the classical traditional Chinese medicine (TCM) prescriptions in treating gynecological tumors, Guizhi Fuling Decoction (GFD) has been used to treat breast cancer (BRCA). Nonetheless, the potential molecular mechanism remains unclear so far. Therefore, systems pharmacology was used in combination with high throughput sequencing-based high throughput screening (HTS2) assay and bioinformatic technologies in this study to investigate the molecular mechanisms of GFD in treating BRCA. By computationally analyzing 76 active ingredients in GFD, 38 potential therapeutic targets were predicted and significantly enriched in the "pathways in cancer". Meanwhile, experimental analysis was carried out to examine changes in the expression levels of 308 genes involved in the "pathways in cancer" in BRCA cells treated by five herbs of GFD utilizing HTS2 platform, and 5 key therapeutic targets, including HRAS, EGFR, PTK2, SOS1, and ITGB1, were identified. The binding mode of active compounds to these five targets was analyzed by molecular docking and molecular dynamics simulation. It was found after integrating the computational and experimental data that, GFD possessed the anti-proliferation, pro-apoptosis, and anti-angiogenesis activities mainly through regulating the PI3K and the MAPK signaling pathways to inhibit BRCA. Besides, consistent with the TCM theory about the synergy of Cinnamomi Ramulus (Guizhi) by Cortex Moutan (Mudanpi) in GFD, both of these two herbs acted on the same targets and pathways. Taken together, the combined application of computational systems pharmacology techniques and experimental HTS2 platform provides a practical research strategy to investigate the functional and biological mechanisms of the complicated TCM prescriptions.

Tissue-specific transcription reprogramming promotes liver metastasis of colorectal cancer.

Metastasis, the development of secondary malignant growths at a distance from a primary tumor, is the cause of death for 90% of cancer patients, but little is known about how metastatic cancer cells adapt to and colonize new tissue environments. Here, using clinical samples, patient-derived xenograft (PDX) samples, PDX cells, and primary/metastatic cell lines, we discovered that liver metastatic colorectal cancer (CRC) cells lose their colon-specific gene transcription program yet gain a liver-specific gene transcription program. We showed that this transcription reprogramming is driven by a reshaped epigenetic landscape of both typical enhancers and super-enhancers. Further, we identified that the liver-specific transcription factors FOXA2 and HNF1A can bind to the gained enhancers and activate the liver-specific gene transcription, thereby driving CRC liver metastasis. Importantly, similar transcription reprogramming can be observed in multiple cancer types. Our data suggest that reprogrammed tissue-specific transcription promotes metastasis and should be targeted therapeutically.

A comprehensive evaluation of connectivity methods for L1000 data.

The methodologies for evaluating similarities between gene expression profiles of different perturbagens are the key to understanding mechanisms of actions (MoAs) of unknown compounds and finding new indications for existing drugs. L1000-based next-generation Connectivity Map (CMap) data is more than a thousand-fold scale-up of the CMap pilot dataset. Although several systematic evaluations have been performed individually to assess the accuracy of the methodologies for the CMap pilot study, the performance of these methodologies needs to be re-evaluated for the L1000 data. Here, using the drug-drug similarities from the Drug Repurposing Hub database as a benchmark standard, we evaluated six popular published methods for the prediction performance of drug-drug relationships based on the partial area under the receiver operating characteristic (ROC) curve at false positive rates of 0.001, 0.005 and 0.01 (AUC0.001, AUC0.005 and AUC0.01). The similarity evaluating algorithm called ZhangScore was generally superior to other methods and exhibited the highest accuracy at the gene signature sizes ranging from 10 to 200. Further, we tested these methods with an experimentally derived gene signature related to estrogen in breast cancer cells, and the results confirmed that ZhangScore was more accurate than other methods. Moreover, based on scoring results of ZhangScore for the gene signature of TOP2A knockdown, in addition to well-known TOP2A inhibitors, we identified a number of potential inhibitors and at least two of them were the subject of previous investigation. Our studies provide potential guidelines for researchers to choose the suitable connectivity method. The six connectivity methods used in this report have been implemented in R package (https://github.com/Jasonlinchina/RCSM).

Chemical genomics reveals inhibition of breast cancer lung metastasis by Ponatinib via c-Jun.

Metastasis is the leading cause of human cancer deaths. Unfortunately, no approved drugs are available for anti-metastatic treatment. In our study, high-throughput sequencing-based high-throughput screening (HTS2) and a breast cancer lung metastasis (BCLM)-associated gene signature were combined to discover anti-metastatic drugs. After screening of thousands of compounds, we identified Ponatinib as a BCLM inhibitor. Ponatinib significantly inhibited the migration and mammosphere formation of breast cancer cells in vitro and blocked BCLM in multiple mouse models. Mechanistically, Ponatinib represses the expression of BCLM-associated genes mainly through the ERK/c-Jun signaling pathway by inhibiting the transcription of JUN and accelerating the degradation of c-Jun protein. Notably, JUN expression levels were positively correlated with BCLM-associated gene expression and lung metastases in breast cancer patients. Collectively, we established a novel approach for the discovery of anti-metastatic drugs, identified Ponatinib as a new drug to inhibit BCLM and revealed c-Jun as a crucial factor and potential drug target for BCLM. Our study may facilitate the therapeutic treatment of BCLM as well as other metastases.