RePhine: An Integrative Method for Identification of Drug Response-related Transcriptional Regulators

HBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol

Liver cancer is the third leading cause of cancer-related death worldwide, and hepatocellular carcinoma (HCC) accounts for a relatively large proportion of all primary liver malignancies. Among the several known risk factors, hepatitis B virus (HBV) infection is one of the important causes of HCC. In this study, we demonstrated that the HBV-infected HCC patients could be robustly classified into three clinically relevant subgroups, i.e. Cluster1, Cluster2 and Cluster3, based on consistent differentially expressed mRNAs and proteins, which showed better generalization. The proposed three subgroups showed different molecular characteristics, immune microenvironment and prognostic survival characteristics. The Cluster1 subgroup had near-normal levels of metabolism-related proteins, low proliferation activity and good immune infiltration, which were associated with its good liver function, smaller tumor size, good prognosis, low alpha-fetoprotein (AFP) levels and lower clinical stage. In contrast, the Cluster3 subgroup had the lowest levels of metabolism-related proteins, which corresponded with its severe liver dysfunction. Also, high proliferation activity and poor immune microenvironment in Cluster3 subgroup were associated with its poor prognosis, larger tumor size, high AFP levels, high incidence of tumor thrombus and higher clinical stage. The characteristics of the Cluster2 subgroup were between the Cluster1 and Cluster3 groups. In addition, MCM2-7, RFC2-5, MSH2, MSH6, SMC2, SMC4, NCPAG and TOP2A proteins were significantly upregulated in the Cluster3 subgroup. Meanwhile, abnormally high phosphorylation levels of these proteins were associated with high levels of DNA repair, telomere maintenance and proliferative features. Therefore, these proteins could be identified as potential diagnostic and prognostic markers. In general, our research provided a novel analytical protocol and insights for the robust classification, treatment and prevention of HBV-infected HCC.

Discovery of Targets for Immune-Metabolic Antitumor Drugs Identifies Estrogen-Related Receptor Alpha

Drugs that kill tumors through multiple mechanisms have the potential for broad clinical benefits. Here, we first developed an in silico multiomics approach (BipotentR) to find cancer cell-specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway and then used it to identify 38 candidate immune-metabolic regulators. We show the tumor activities of these regulators stratify patients with melanoma by their response to anti-PD-1 using machine learning and deep neural approaches, which improve the predictive power of current biomarkers. The topmost identified regulator, ESRRA, is activated in immunotherapy-resistant tumors. Its inhibition killed tumors by suppressing energy metabolism and activating two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization, and (ii) antigen-presentation stimulation, recruiting CD8+ T cells into tumors. We also demonstrate a wide utility of BipotentR by applying it to angiogenesis and growth suppressor evasion pathways. BipotentR (http://bipotentr.dfci.harvard.edu/) provides a resource for evaluating patient response and discovering drug targets that act simultaneously through multiple mechanisms.

SIGNIFICANCE

BipotentR presents resources for evaluating patient response and identifying targets for drugs that can kill tumors through multiple mechanisms concurrently. Inhibition of the topmost candidate target killed tumors by suppressing energy metabolism and effects on two immune mechanisms. This article is highlighted in the In This Issue feature, p. 517.

Single-Cell Transcriptome Identifies Drug-Resistance Signature and Immunosuppressive Microenvironment in Metastatic Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a deadly neuroendocrine malignancy with high metastasis. However, the heterogeneity of metastatic SCLC at the single-cell level remains elusive. The single-cell transcriptome of a total of 24 081 cells in metastatic lymph node samples from seven SCLC patients via endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is examined. Genomic alterations are also examined by whole exome sequencing (WES) and the immune infiltration between SCLC and non-SCLC (NSCLC) is compared using public single-cell RNA sequencing (scRNA-seq) data. It is identified that malignant cells in lymph-node metastatic SCLC have inter-patient and intra-tumor heterogeneity characterized by distinct ASCL1 and NEUROD1 expression patterns. High expression of genes such as FZD8 in WNT pathway is associated with drug resistance in malignant cells. Compared to NSCLC, SCLC harbors a unique immunosuppressive tumor microenvironment. Malignant cells exhibit a pattern of attenuated MHC-I antigen presentation-related gene expression, which is associated with relatively low proportion of exhausted T cells. Natural killer (NK) cells display impaired antitumor function with high expression of TGFBR2. This work characterizes the inter-patient and intra-tumor heterogeneity of metastatic SCLC and uncovers the exhaustion signatures in NK cells, which may pave the way for novel treatments for SCLC including immune checkpoint blockade-based immunotherapy.

Transcription Elongation Machinery Is a Druggable Dependency and Potentiates Immunotherapy in Glioblastoma Stem Cells

Glioblastoma (GBM) is the most lethal primary brain cancer characterized by therapeutic resistance, which is promoted by GBM stem cells (GSC). Here, we interrogated gene expression and whole-genome CRISPR/Cas9 screening in a large panel of patient-derived GSCs, differentiated GBM cells (DGC), and neural stem cells (NSC) to identify master regulators of GSC stemness, revealing an essential transcription state with increased RNA polymerase II-mediated transcription. The YY1 and transcriptional CDK9 complex was essential for GSC survival and maintenance in vitro and in vivo. YY1 interacted with CDK9 to regulate transcription elongation in GSCs. Genetic or pharmacologic targeting of the YY1-CDK9 complex elicited RNA m⁶A modification-dependent interferon responses, reduced regulatory T-cell infiltration, and augmented efficacy of immune checkpoint therapy in GBM. Collectively, these results suggest that YY1-CDK9 transcription elongation complex defines a targetable cell state with active transcription, suppressed interferon responses, and immunotherapy resistance in GBM. SIGNIFICANCE: Effective strategies to rewire immunosuppressive microenvironment and enhance immunotherapy response are still lacking in GBM. YY1-driven transcriptional elongation machinery represents a druggable target to activate interferon response and enhance anti-PD-1 response through regulating the m⁶A modification program, linking epigenetic regulation to immunomodulatory function in GBM.This article is highlighted in the In This Issue feature, p. 275.