Identification of CAF-related lncRNAs at the pan-cancer level represents a potential carcinogenic risk.

Cancer-associated fibroblasts (CAFs) are increasingly recognized as playing a crucial role in regulating cancer progression and metastasis. These cells can be activated by long non-coding RNAs (lncRNAs), promoting the malignant biological processes of tumor cells. Therefore, it is essential to understand the regulatory relationship between CAFs and lncRNAs in cancers. Here, we identified CAF-related lncRNAs at the pan-cancer level to systematically predict their potential regulatory functions. The identified lncRNAs were also validated using various external data at both tissue and cellular levels. This study has revealed that these CAF-related lncRNAs exhibit expression perturbations in cancers and are highly correlated with the infiltration of stromal cells, particularly fibroblasts and endothelial cells. By prioritizing a list of CAF-related lncRNAs, we can further distinguish patient subtypes that show survival and molecular differences. In addition, we have developed a web server, CAFLnc (https://46906u5t63.zicp.fun/CAFLnc/), to visualize our results. In conclusion, CAF-related lncRNAs hold great potential as a valuable resource for comprehending lncRNA functions and advancing the identification of biomarkers for cancer progression and therapeutic targets in cancer treatment.

LncTarD: a manually-curated database of experimentally-supported functional lncRNA-target regulations in human diseases.

Long non-coding RNAs (lncRNAs) are associated with human diseases. Although lncRNA-disease associations have received significant attention, no online repository is available to collect lncRNA-mediated regulatory mechanisms, key downstream targets, and important biological functions driven by disease-related lncRNAs in human diseases. We thus developed LncTarD (http://biocc.hrbmu.edu.cn/LncTarD/ or http://bio-bigdata.hrbmu.edu.cn/LncTarD), a manually-curated database that provides a comprehensive resource of key lncRNA-target regulations, lncRNA-influenced functions, and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD offers (i) 2822 key lncRNA-target regulations involving 475 lncRNAs and 1039 targets associated with 177 human diseases; (ii) 1613 experimentally-supported functional regulations and 1209 expression associations in human diseases; (iii) important biological functions driven by disease-related lncRNAs in human diseases; (iv) lncRNA-target regulations responsible for drug resistance or sensitivity in human diseases and (v) lncRNA microarray, lncRNA sequence data and transcriptome data of an 11 373 pan-cancer patient cohort from TCGA to help characterize the functional dynamics of these lncRNA-target regulations. LncTarD also provides a user-friendly interface to conveniently browse, search, and download data. LncTarD will be a useful resource platform for the further understanding of functions and molecular mechanisms of lncRNA deregulation in human disease, which will help to identify novel and sensitive biomarkers and therapeutic targets.

Combined homologous recombination repair deficiency and immune activation analysis for predicting intensified responses of anthracycline, cyclophosphamide and taxane chemotherapy in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is a clinically aggressive disease with abundant variants that cause homologous recombination repair deficiency (HRD). Whether TNBC patients with HRD are sensitive to anthracycline, cyclophosphamide and taxane (ACT), and whether the combination of HRD and tumour immunity can improve the recognition of ACT responders are still unknown. METHODS: Data from 83 TNBC patients in The Cancer Genome Atlas (TCGA) was used as a discovery cohort to analyse the association between HRD and ACT chemotherapy benefits. The combined effects of HRD and immune activation on ACT chemotherapy were explored at both the genome and the transcriptome levels. Independent cohorts from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO) were adopted to validate our findings. RESULTS: HRD was associated with a longer ACT chemotherapy failure-free interval (FFI) with a hazard ratio of 0.16 (P = 0.004) and improved patient prognosis (P = 0.0063). By analysing both HRD status and ACT response, we identified patients with a distinct TNBC subtype (ACT-S&HR-P) that showed higher tumour lymphocyte infiltration, IFN-γ activity and NK cell levels. Patients with ACT-S&HR-P had significantly elevated immune inhibitor levels and presented immune activation associated with the increased activities of both innate immune cells and adaptive immune cells, which suggested treatment with immune checkpoint blockade as an option for this subtype. Our analysis revealed that the combination of HRD and immune activation enhanced the efficiency of identifying responders to ACT chemotherapy (AUC = 0.91, P = 1.06e-04) and synergistically contributed to the clinical benefits of TNBC patients. A transcriptional HRD signature of ACT response-related prognostic factors was identified and independently validated to be significantly associated with improved survival in the GEO cohort (P = 0.0038) and the METABRIC dataset (P < 0.0001). CONCLUSIONS: These findings highlight that HR deficiency prolongs FFI and predicts intensified responses in TNBC patients by combining HRD and immune activation, which provides a molecular basis for identifying ACT responders.

Comprehensive analysis of long noncoding RNA (lncRNA)-chromatin interactions reveals lncRNA functions dependent on binding diverse regulatory elements.

Over the past decade, thousands of long noncoding RNAs (lncRNAs) have been identified, many of which play crucial roles in normal physiology and human disease. LncRNAs can interact with chromatin and then recruit protein complexes to remodel chromatin states, thus regulating gene expression. However, how lncRNA-chromatin interactions contribute to their biological functions is largely unknown. Here, we collected and constructed an atlas of 188,647 lncRNA-chromatin interactions in human and mouse. All lncRNAs showed diverse epigenetic modification patterns at their binding sites, especially the marks of enhancer activity. Functional analysis of lncRNA target genes further revealed that lncRNAs could exert their functions by binding to both promoter and distal regulatory elements, especially the distal regulatory elements. Intriguingly, many important pathways were observed to be widely regulated by lncRNAs through distal binding. For example, NEAT1, a cancer lncRNA, controls 13.3% of genes in the PI3K-AKT signaling pathway by interacting with distal regulatory elements. In addition, "two-gene" signatures composed of a lncRNA and its distal target genes, such as HOTAIR-CRIM1, provided significant clinical benefits relative to the lncRNA alone. In summary, our findings underscored that lncRNA-distal interactions were essential for lncRNA functions, which would provide new clues to understand the molecular mechanisms of lncRNAs in complex disease.

Identifying bifurcated paths with differential function impact in glioblastomas evolution.

The evolutionary dynamics of human cancers has been investigated popularly and several bifurcated paths in cancer evolutionary trajectories are revealed to be with differential outcomes and phenotypes. However, whether such bifurcated paths exist in glioblastoma (GBM) remains unclear. In 385 GBM samples, through determining the clonal status of cancer driver events and inferring their temporal order, we constructed a temporal map of evolutionary trajectories at the patient population level. By investigating the differential impact on clinical outcome, we identified four key bifurcated paths, namely, "chromosome 10 copy number loss (ie, 10 loss) → chromosome 19 copy number gain (ie, 19 gain): 10 loss → 13q loss"; "10 loss → 19 gain: 10 loss → 15q loss"; "10 loss → 19 gain: 10 loss → 6q loss" and "10 loss → 19 gain: 10 loss → 16q loss". They formed a core multibranches path, with 10 loss being regarded as the common earliest event followed by 19 gain and four other departure events (13q loss, 15q loss, 6q loss and 16q loss), which may account for their difference in genome instability and patient survival time. Compared to "10 loss → 19 gain", the patients with "10 loss → 13q loss" had higher telomerase activity. Notably, there were obvious discrepancies in immune activity and immune cell infiltration level between patients with "10 loss → 13q/16q loss" and "10 loss → 19 gain", highlighting the bifurcated paths' effect on tumor immune microenvironment. In summary, our study identifies four key bifurcated paths in GBM for the first time, suggesting the feasibility of patient stratification and prognosis prediction based on key bifurcated paths.

Three-dimensional characterization of debris clouds under hypervelocity impact with pulsed digital inline holography.

The increasing space debris poses a great threat to in-orbit spacecraft and satellites, because its hypervelocity impact can bring about fatal mechanical and electrical damage to them. This work applies pulsed digital inline holography (DIH) to measure three-dimensional (3D) positions and shapes of the debris clouds generated by the hypervelocity impact in the Whipple shield. Detailed operation procedures of synchronizing the pulse DIH system with the impact event and removing the strong plasma radiation are presented, ensuring the successful capture of the transient state of ultrafast ejecta. Experiments on a 2.25 mm aluminum sphere impacting a 0.5 mm thickness aluminum target plate with a velocity of 3.6 km/s are carried out at the Hypervelocity Impact Research Center of the China Aerodynamics Research and Development Center, and results show that the holographic fringes are clearly recorded and the debris fragments are reconstructed and located accurately, agreeing well with the results measured by laser shadowgraph. This work demonstrates the powerful capability and great potential of DIH in the diagnostics of hypervelocity impact.

Comparative assessment of the diagnostic efficacy of [18F]AlF-NOTA-FAPI-04 and [18F]FDG PET/CT imaging for detecting postoperative recurrence in gastric cancer patients: a pilot study.

Purpose: This study aimed to compare the efficacy of [18F]AlF-NOTA-FAPI-04 PET/CT with that of [18F]FDG PET/CT for detecting postoperative recurrence in patients with gastric cancer. Methods: This single-center retrospective clinical study was performed at Hunan Cancer Hospital between December 2020 and June 2022. The participants underwent both [18F]AlF-NOTA-FAPI-04 and [18F]FDG within 14 days. Histopathologic examination, morphological imaging, and/or follow-up imaging were used as a reference for the final diagnosis. We recorded the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of [18F]AlF-NOTA-FAPI-04 and [18F]FDG PET/CT for detecting local recurrence, lymph node metastasis and distant metastasis. The SUVmax and background ratio (TBR) of local recurrence and metastases between [18F]FDG and [18F]AlF-NOTA-FAPI-04 PET/CT were compared using paired-sample t tests. Results: Forty-seven patients (27 males, aged 25-68 years) with gastric cancer after curative resection (27 with adenocarcinoma, 17 with signet ring cell carcinoma and 4 with mucinous adenocarcinoma) were included in the study. [18F]AlF-NOTA-FAPI-04 accumulation was significantly greater than that of [18F]FDG in terms of local recurrence (SUVmax, 11.65 vs 3.48, p< 0.0001; TBR, 12.93 vs 2.94, p< 0.0001), lymph node metastasis (SUVmax, 13.45 vs 3.05, p=0.003875; TBR, 12.43 vs 2.21, p=0.001661), and distant metastasis (SUVmax, 11.89 vs 2.96, p < 0.0001; TBR, 13.32 vs 2.32, p< 0.0001). Despite no statistical comparison was made with [18F]FDG, [18F]AlF-NOTA-FAPI-04 imaging exhibited high levels of sensitivity, specificity, PPV, NPV, and accuracy for detecting postoperative local recurrence, lymph node metastasis, and distant metastasis in patients with gastric cancer. Conclusion: [18F]AlF-NOTA-FAPI-04 has demonstrated potential for more accurate tumor re-evaluation in GC, thus enhancing treatment decision-making.

Applicability of Anticancer Drugs for the Triple-Negative Breast Cancer Based on Homologous Recombination Repair Deficiency.

Triple-negative breast cancer (TNBC) is a highly aggressive disease with historically poor outcomes, primarily due to the lack of effective targeted therapies. Here, we established a drug sensitivity prediction model based on the homologous recombination deficiency (HRD) using 83 TNBC patients from TCGA. Through analyzing the effect of HRD status on response efficacy of anticancer drugs and elucidating its related mechanisms of action, we found rucaparib (PARP inhibitor) and doxorubicin (anthracycline) sensitive in HR-deficient patients, while paclitaxel sensitive in the HR-proficient. Further, we identified a HRD signature based on gene expression data and constructed a transcriptomic HRD score, for analyzing the functional association between anticancer drug perturbation and HRD. The results revealed that CHIR99021 (GSK3 inhibitor) and doxorubicin have similar expression perturbation patterns with HRD, and talazoparib (PARP inhibitor) could kill tumor cells by reversing the HRD activity. Genomic characteristics indicated that doxorubicin inhibited tumor cells growth by hindering the process of DNA damage repair, while the resistance of cisplatin was related to the activation of angiogenesis and epithelial-mesenchymal transition. The negative correlation of HRD signature score could interpret the association of doxorubicin pIC50 with worse chemotherapy response and shorter survival of TNBC patients. In summary, these findings explain the applicability of anticancer drugs in TNBC and underscore the importance of HRD in promoting personalized treatment development.

Identification of Hub Genes Associated With Hepatocellular Carcinoma Using Robust Rank Aggregation Combined With Weighted Gene Co-expression Network Analysis.

BACKGROUND: Bioinformatics provides a valuable tool to explore the molecular mechanisms underlying pathogenesis of hepatocellular carcinoma (HCC). To improve prognosis of patients, identification of robust biomarkers associated with the pathogenic pathways of HCC remains an urgent research priority. METHODS: We employed the Robust Rank Aggregation method to integrate nine qualified HCC datasets from the Gene Expression Omnibus. A robust set of differentially expressed genes (DEGs) between tumor and normal tissue samples were screened. Weighted gene co-expression network analysis was applied to cluster DEGs and the key modules related to clinical traits identified. Based on network topology analysis, novel risk genes derived from key modules were mined and biological verification performed. The potential functions of these risk genes were further explored with the aid of miRNA-mRNA regulatory networks. Finally, the prognostic ability of these genes was assessed by constructing a clinical prediction model. RESULTS: Two key modules showed significant association with clinical traits. In combination with protein-protein interaction analysis, 29 hub genes were identified. Among these genes, 19 from one module showed a pattern of upregulation in HCC and were associated with the tumor node metastasis stage, and 10 from the other module displayed the opposite trend. Survival analyses indicated that all these genes were significantly related to patient prognosis. Based on the miRNA-mRNA regulatory network, 29 genes strongly linked to tumor activity were identified. Notably, five of the novel risk genes, ABAT, DAO, PCK2, SLC27A2, and HAO1, have rarely been reported in previous studies. Gene set enrichment analysis for each gene revealed regulatory roles in proliferation and prognosis of HCC. Least absolute shrinkage and selection operator regression analysis further validated DAO, PCK2, and HAO1 as prognostic factors in an external HCC dataset. CONCLUSION: Analysis of multiple datasets combined with global network information presents a successful approach to uncover the complex biological mechanisms of HCC. More importantly, this novel integrated strategy facilitates identification of risk hub genes as candidate biomarkers for HCC, which could effectively guide clinical treatments.

GABA-Aα5 Might Be Involved in Learning-Memory Dysfunction in the Offsprings of Chronic Ethanol-Treated Rats via GABA-Aα5 Histone H3K9 Acetylation.

Recently, numerous studies have been focused on the relationship between GABA-A receptors and alcohol-induced spatial learning and memory deficits. GABA-Aα5, a subunit of GABA-A receptors, is considered to play an important role in alcohol-induced cognitive impairment, however, the mechanism remains obscure. In this study, we found that the expression of GABA-Aα5 increased in rats treated with chronic ethanol via histone H3K9 acetylation. Furthermore, this epigenetic modification could be inherited by the next generations, which eventually exhibit similar spatial learning and memory deficits in the offsprings. In summary, our results suggested that GABA-Aα5 might be involved in chronic ethanol treatment-induced learning-memory dysfunction and for the first time proved that learning-memory dysfunction could be inherited by the offsprings via histone H3K9 acetylation. Hopefully, in the near future, GABA-Aα5 inhibitors would be an effective way to treat alcohol-induced cognition impairment.

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.

Chronic Alcohol Treatment-Induced GABA-Aα5 Histone H3K4 Trimethylation Upregulation Leads to Increased GABA-Aα5 Expression and Susceptibility to Alcohol Addiction in the Offspring of Wistar Rats.

Gamma-aminobutyric acid (GABA)-Aα5 is considered to be associated with alcohol-induced memory deficits. However, whether it participates in the formation of alcohol addiction or in the regulation of its susceptibility is unknown. Here, we used a chronic alcohol treatment model to obtain alcohol-addicted Wistar rats. Long-term alcoholism increased the expression of prefrontal cortex GABA-Aα5 by inducing its histone H3K4 trimethylation, and these changes could be hereditary and lead to increased vulnerability to alcohol addiction in offspring. This study indicates the risk of long-term alcoholism in future generations, emphasizes the importance of GABA-Aα5 in the formation of alcohol addiction and the regulation of its susceptibility, and provides new evidence regarding the mechanisms underlying alcohol addiction.