RBBP6 maintains glioblastoma stem cells through CPSF3-dependent alternative polyadenylation.

Glioblastoma is one of the most lethal malignant cancers, displaying striking intratumor heterogeneity, with glioblastoma stem cells (GSCs) contributing to tumorigenesis and therapeutic resistance. Pharmacologic modulators of ubiquitin ligases and deubiquitinases are under development for cancer and other diseases. Here, we performed parallel in vitro and in vivo CRISPR/Cas9 knockout screens targeting human ubiquitin E3 ligases and deubiquitinases, revealing the E3 ligase RBBP6 as an essential factor for GSC maintenance. Targeting RBBP6 inhibited GSC proliferation and tumor initiation. Mechanistically, RBBP6 mediated K63-linked ubiquitination of Cleavage and Polyadenylation Specific Factor 3 (CPSF3), which stabilized CPSF3 to regulate alternative polyadenylation events. RBBP6 depletion induced shortening of the 3'UTRs of MYC competing-endogenous RNAs to release miR-590-3p from shortened UTRs, thereby decreasing MYC expression. Targeting CPSF3 with a small molecular inhibitor (JTE-607) reduces GSC viability and inhibits in vivo tumor growth. Collectively, RBBP6 maintains high MYC expression in GSCs through regulation of CPSF3-dependent alternative polyadenylation, providing a potential therapeutic paradigm for glioblastoma.

An Investigation on the Most Likely Failure Locations in the BEoL Stack of a 20 nm Chip Due to Chip Package Interaction with the Use of Novel Semi-Elliptical Cracks.

The era of 20 nm integrated circuits has arrived. There exist abundant heterogeneous micro/nano structures, with thicknesses ranging from hundreds of nanometers to sub-microns in the IC back end of the line stack, which put stringent demands on the reliability of the device. In this paper, the reliability issues of a 20 nm chip due to chip-package interaction during the reflow process is studied. A representative volume element of the detailed complex BEoL structure has been analyzed to obtain mechanical properties of the BEoL stack by adopting a sub-model analysis. For the first time, semi-elliptical cracks were used in conjunction with J-integral techniques to analyze the failure caused by Chip-to-Package Interaction for a 20 nm chip. The Energy Release Rate(ERR)for cracks at various interfaces and locations in the BEoL stack were calculated to predict the most likely mode and location of failure. We found that the ERR of interfacial cracks at the bottom surface of the interconnects are, on average, more than double those at the sidewalls, which are in turn more than double the number of cracks in the low-k inter-layer dielectric. A total of 500 cycles of thermal shock were conducted, which verified the predictions of the finite element simulations.

Analysis of the Overpressure Fields in a Shock Tube with Multi-Point Initiation.

Shock tubes can carry out dynamic mechanical impact tests on civil engineering structures. The current shock tubes mostly use an explosion with aggregate charge to obtain shock waves. Limited effort has been made to study the overpressure field in shock tubes with multi-point initiation. In this paper, the overpressure fields in a shock tube under the conditions of single-point initiation, multi-point simultaneous initiation, and multi-point delayed initiation have been analyzed by combining experiments and numerical simulations. The numerical results match well with the experimental data, which indicates that the computational model and method used can accurately simulate the blast flow field in a shock tube. For the same charge mass, the peak overpressure at the exit of the shock tube with the multi-point simultaneous initiation is smaller than that with single-point initiation. As the shock waves are focused on the wall, the maximum overpressure on the wall of the explosion chamber near the explosion zone is not reduced. The maximum overpressure on the wall of the explosion chamber can be effectively reduced by a six-point delayed initiation. When the interval time is less than 10 ms, the peak overpressure at the nozzle outlet decreases linearly with the interval of the explosion. When the interval time is greater than 10 ms, the overpressure peak remains unchanged.

Discussion on Static Resistance of Granite under Penetration.

A total of 9 tests were carried out with 30 mm and 78 mm caliber scaled projectiles penetrating into granite targets. The penetration depth, crater diameter, and mass loss rate were examined and discussed. The results indicate that the dimensionless penetration depth of large-caliber projectiles is 20% greater than small-caliber projectiles. Based on the description of static resistance Ra in the Forrestal semi-empirical formula, the size effect of dimensionless penetration depth can be attributed to the size effect of static resistance Ra, and it can be seen that the penetration static resistance of projectile A is 40% higher than that of projectile B. Numerical simulations of projectile penetration into granite targets were conducted using the finite element program ANSYS/LS-DYNA. In terms of penetration depth and crater damage, the numerical simulation results agree well with the test data. This suggests that the selection of parameters was reasonable. The influence of compressive strength, projectile striking velocity, mass, diameter, and caliber-radius-head (CRH) ratio on the static resistance Ra were studied by RHT model parameterization. Based on the numerical results from the parametric study, an empirical formula was derived to predict the static resistance Ra.

Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma.

The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gene regulatory features of ccRCC have not been fully characterized. Here, we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to generate transcriptional and epigenomic landscapes of ccRCC. We identified tumor cell-specific regulatory programs mediated by four key transcription factors (TFs) (HOXC5, VENTX, ISL1, and OTP), and these TFs have prognostic significance in The Cancer Genome Atlas (TCGA) database. Targeting these TFs via short hairpin RNAs (shRNAs) or small molecule inhibitors decreased tumor cell proliferation. We next performed an integrative analysis of chromatin accessibility and gene expression for CD8+ T cells and macrophages to reveal the different regulatory elements in their subgroups. Furthermore, we delineated the intercellular communications mediated by ligand-receptor interactions within the tumor microenvironment. Taken together, our multiomics approach further clarifies the cellular heterogeneity of ccRCC and identifies potential therapeutic targets.

Spindle pole body component 24 homolog potentiates tumor progression via regulation of SRY-box transcription factor 2 in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of human kidney cancer with a high probability of metastasis. To understand the molecular processing essential for ccRCC tumorigenicity, we conducted an integrative in silico analysis of The Cancer Genome Atlas (TCGA) ccRCC dataset and clustered randomly interspersed short palindromic repeats (CRISPR) screening dataset of ccRCC cell lines from Depmap. We identified spindle pole body component 24 homolog (SPC24) as an essential gene for ccRCC cell lines with prognostic significance in the TCGA database. Targeting SPC24 by CRISPR/Cas9-mediated gene knockout attenuated ccRCC proliferation, metastasis, and in vivo tumor growth. Furthermore, we found that SPC24 regulates metastasis genes expression in a SRY-box transcription factor 2 (SOX2)-dependent manner. The anti-proliferative effects of SPC24 knockout were strengthened with SOX2 knockdown. Collectively, our findings suggest SPC24 has a pivotal function in promoting ccRCC progression, providing a new insight for the treatment of ccRCC.

SARS-CoV-2 exacerbates proinflammatory responses in myeloid cells through C-type lectin receptors and Tweety family member 2.

Despite mounting evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) engagement with immune cells, most express little, if any, of the canonical receptor of SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2). Here, using a myeloid cell receptor-focused ectopic expression screen, we identified several C-type lectins (DC-SIGN, L-SIGN, LSECtin, ASGR1, and CLEC10A) and Tweety family member 2 (TTYH2) as glycan-dependent binding partners of the SARS-CoV-2 spike. Except for TTYH2, these molecules primarily interacted with spike via regions outside of the receptor-binding domain. Single-cell RNA sequencing analysis of pulmonary cells from individuals with coronavirus disease 2019 (COVID-19) indicated predominant expression of these molecules on myeloid cells. Although these receptors do not support active replication of SARS-CoV-2, their engagement with the virus induced robust proinflammatory responses in myeloid cells that correlated with COVID-19 severity. We also generated a bispecific anti-spike nanobody that not only blocked ACE2-mediated infection but also the myeloid receptor-mediated proinflammatory responses. Our findings suggest that SARS-CoV-2-myeloid receptor interactions promote immune hyperactivation, which represents potential targets for COVID-19 therapy.

Systematic Assessment of Transcriptomic Biomarkers for Immune Checkpoint Blockade Response in Cancer Immunotherapy.

BACKGROUND: Immune checkpoint blockade (ICB) therapy has yielded successful clinical responses in treatment of a minority of patients in certain cancer types. Substantial efforts were made to establish biomarkers for predicting responsiveness to ICB. However, the systematic assessment of these ICB response biomarkers remains insufficient. METHODS: We collected 22 transcriptome-based biomarkers for ICB response and constructed multiple benchmark datasets to evaluate the associations with clinical response, predictive performance, and clinical efficacy of them in pre-treatment patients with distinct ICB agents in diverse cancers. RESULTS: Overall, "Immune-checkpoint molecule" biomarkers PD-L1, PD-L2, CTLA-4 and IMPRES and the "Effector molecule" biomarker CYT showed significant associations with ICB response and clinical outcomes. These immune-checkpoint biomarkers and another immune effector IFN-gamma presented predictive ability in melanoma, urothelial cancer (UC) and clear cell renal-cell cancer (ccRCC). In non-small cell lung cancer (NSCLC), only PD-L2 and CTLA-4 showed preferable correlation with clinical response. Under different ICB therapies, the top-performing biomarkers were usually mutually exclusive in patients with anti-PD-1 and anti-CTLA-4 therapy, and most of biomarkers presented outstanding predictive power in patients with combined anti-PD-1 and anti-CTLA-4 therapy. CONCLUSIONS: Our results show these biomarkers had different performance in predicting ICB response across distinct ICB agents in diverse cancers.

Identifying Cancer Driver lncRNAs Bridged by Functional Effectors through Integrating Multi-omics Data in Human Cancers.

The accumulation of somatic driver mutations in the human genome enables cells to gradually acquire a growth advantage and contributes to tumor development. Great efforts on protein-coding cancer drivers have yielded fruitful discoveries and clinical applications. However, investigations on cancer drivers in non-coding regions, especially long non-coding RNAs (lncRNAs), are extremely scarce due to the limitation of functional understanding. Thus, to identify driver lncRNAs integrating multi-omics data in human cancers, we proposed a computational framework, DriverLncNet, which dissected the functional impact of somatic copy number alteration (CNA) of lncRNAs on regulatory networks and captured key functional effectors in dys-regulatory networks. Applying it to 5 cancer types from The Cancer Genome Atlas (TCGA), we portrayed the landscape of 117 driver lncRNAs and revealed their associated cancer hallmarks through their functional effectors. Moreover, lncRNA RP11-571M6.8 was detected to be highly associated with immunotherapeutic targets (PD-1, PD-L1, and CTLA-4) and regulatory T cell infiltration level and their markers (IL2RA and FCGR2B) in glioblastoma multiforme, highlighting its immunosuppressive function. Meanwhile, a high expression of RP11-1020A11.1 in bladder carcinoma was predictive of poor survival independent of clinical characteristics, and CTD-2256P15.2 in lung adenocarcinoma responded to the sensitivity of methyl ethyl ketone (MEK) inhibitors. In summary, this study provided a framework to decipher the mechanisms of tumorigenesis from driver lncRNA level, established a new landscape of driver lncRNAs in human cancers, and offered potential clinical implications for precision oncology.

CancerSEA: a cancer single-cell state atlas.

High functional heterogeneity of cancer cells poses a major challenge for cancer research. Single-cell sequencing technology provides an unprecedented opportunity to decipher diverse functional states of cancer cells at single-cell resolution, and cancer scRNA-seq datasets have been largely accumulated. This emphasizes the urgent need to build a dedicated resource to decode the functional states of cancer single cells. Here, we developed CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/ or http://202.97.205.69/CancerSEA/), the first dedicated database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level. CancerSEA portrays a cancer single-cell functional state atlas, involving 14 functional states (including stemness, invasion, metastasis, proliferation, EMT, angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, hypoxia, inflammation and quiescence) of 41 900 cancer single cells from 25 cancer types. It allows querying which functional states are associated with the gene (or gene list) of interest in different cancers. CancerSEA also provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single-cell datasets. In summary, CancerSEA provides a user-friendly interface for comprehensively searching, browsing, visualizing and downloading functional state activity profiles of tens of thousands of cancer single cells and the corresponding PCGs/lncRNAs expression profiles.

Capturing functional long non-coding RNAs through integrating large-scale causal relations from gene perturbation experiments.

Characterizing functions of long noncoding RNAs (lncRNAs) remains a major challenge, mostly due to the lack of lncRNA-involved regulatory relationships. A wide array of genome-wide expression profiles generated by gene perturbation have been widely used to capture causal links between perturbed genes and response genes. Through annotating >600 gene perturbation profiles, over 354,000 causal relationships between perturbed genes and lncRNAs were identified. This large-scale resource of causal relations inspired us to develop a novel computational approach LnCAR for inferring lncRNAs' functions, which showed a higher accuracy than the co-expression based approach. By application of LnCAR to the cancer hallmark processes, we identified 38 lncRNAs involved in distinct carcinogenic processes. The "activating invasion & metastasis" related lncRNAs were strongly associated with metastatic progression in various cancer types and could act as a predictor of cancer metastasis. Meanwhile, the "evading immune destruction" related lncRNAs showed significant associations with immune infiltration of various immune cells and, importantly, can predict response to anti-PD-1 immunotherapy, suggesting their potential roles as biomarkers for immune therapy. Taken together, our approach provides a novel way to systematically reveal functions of lncRNAs, which will be helpful for further experimental exploration and clinical translational research of lncRNAs.

TIP: A Web Server for Resolving Tumor Immunophenotype Profiling.

: Systematically tracking the tumor immunophenotype is required to understand the mechanisms of cancer immunity and improve clinical benefit of cancer immunotherapy. However, progress in current research is hindered by the lack of comprehensive immune activity resources and easy-to-use tools for biologists, clinicians, and researchers to conveniently evaluate immune activity during the "cancer-immunity cycle." We developed a user-friendly one-stop shop web tool called TIP to comprehensively resolve tumor immunophenotype. TIP has the capability to rapidly analyze and intuitively visualize the activity of anticancer immunity and the extent of tumor-infiltrating immune cells across the seven-step cancer-immunity cycle. Also, we precalculated the pan-cancer immunophenotype for 11,373 samples from 33 The Cancer Genome Atlas human cancers that allow users to obtain and compare immunophenotype of pan-cancer samples. We expect TIP to be useful in a large number of emerging cancer immunity studies and development of effective immunotherapy biomarkers. TIP is freely available for use at http://biocc.hrbmu.edu.cn/TIP/. SIGNIFICANCE: TIP is a one-stop shop platform that can help biologists, clinicians, and researchers conveniently evaluate anticancer immune activity with their own gene expression data.See related commentary by Hirano, p. 6536.

Preparation of PV dF-based electrospun membranes and their application as separators.

A one-step method preparing of poly(vinylidene fluoride)-based electrospun membranes (PEMs) containing TiO2 has been developed. The effect of TiO2 on the morphology, degree of crystallization and electrochemical behavior of PEMs was investigated by scanning electron microscopy (SEM), atomic force microscopy (AFM), differential scanning calorimetry (DSC) and electrochemical measurements. The PEMs containing TiO2 show improved ionic conductivity and cycling performance compared with pure PEMs.