Identification of a cellular senescence-related-lncRNA (SRlncRNA) signature to predict the overall survival of glioma patients and the tumor immune microenvironment.

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma. Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan-Meier (K-M) analysis was performed to determine each cohort's survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT-qPCR and IHC were used to identify the consistency of the signature in tumor tissue. Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT-PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model. Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy.

The relationship between the prefrontal cortex and limb motor function in stroke: A study based on resting-state functional near-infrared spectroscopy.

BACKGROUND: With the ageing of the world population, the incidence of stroke has been increasing annually, becoming a public health problem affecting adult health. Limb motor dysfunction is one of the common complications of stroke and an important factor in disability. Therefore, restoring limb function is an important task in current rehabilitation. Accurate assessment of motor function in stroke patients is the basis for formulating effective rehabilitation strategies. With the development of neuroimaging technology, scholars have begun to study objective evaluation methods for limb motor dysfunction in stroke to determine reliable neural biomarkers to accurately identify brain functional activity and its relationship with limb motor function. The prefrontal cortex (PFC) plays an important role in motor control and in response to motor state changes. Our previous study found that the PFC network characteristics of stroke patients are related to their motor function status and the topological properties of the PFC network under resting state can predict the motor function of stroke patients to some extent. Therefore, this study used functional near-infrared spectroscopy (fNIRS) to evaluate prefrontal neuroplasticity markers and the relationships between such neural markers and limb motor function in stroke patients with limb motor dysfunction, which could be helpful to further clarify the relationship between brain neuroplasticity and cerebral haemodynamics. At the same time, through accurate and objective means of evaluation, it could be helpful for clinicians to formulate and optimize individualized rehabilitation treatment plans and accurately determine the rehabilitation efficacy and prognosis. METHODS: This study recruited 17 S patients with limb motor dysfunction and 9 healthy subjects. fNIRS was used to collect 22 channels of cerebral blood oxygen signals in the PFC in the resting state. The differences in prefrontal oxygenated haemoglobin (HbO) and deoxygenated haemoglobin (HbR) concentrations were analysed between stroke patients and healthy subjects, and the lateralization index (LI) of HbO in stroke patients was also calculated. Pearson's correlation analysis was performed between the LI and the scores of the Fugl-Meyer Assessment Scale (FMA) of motor function in stroke patients. RESULTS: The results found that the prefrontal HbO concentration was significantly decreased in stroke patients with limb motor dysfunction compared with healthy subjects, and there was a significant, positive correlation between the LI of the PFC and FMA scores in stroke patients. CONCLUSION: These study results showed that stroke can cause cerebral haemodynamic changes in the PFC, and the functional imbalance of the left and right PFC in the resting state is correlated with the severity of limb motor dysfunction. Furthermore, we emphasize that the cerebral haemodynamic activity reflected by fNIRS could be used as a reliable neural biomarker for assessing limb motor dysfunction in stroke.

Corrigendum: Developing an immune-related signature for predicting survival rate and the response to immune checkpoint inhibitors in patients with glioma.

[This corrects the article DOI: 10.3389/fgene.2022.899125.].

Developing an Immune-Related Signature for Predicting Survival Rate and the Response to Immune Checkpoint Inhibitors in Patients With Glioma.

Background: Glioma is one of the most aggressive cancer types affecting the central nerve system, with poor overall survival (OS) rates. The present study aimed to construct a novel immune-related signature to predict prognosis and the efficiency of immunotherapy in patients with glioma. Methods: The mRNA expression data and other clinical information of patients with glioblastoma multiforme (GBM) and low grade glioma (LGG) were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. The immune-related genes were obtained from the Immunology Database and Analysis Portal database. Subsequently, an immune-related signature was created following the results obtained from the Least Absolute Shrinkage and Selection Operator regression model. To validate the predictability of the signature, Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves were created. Moreover, both univariate and multivariate analyses were carried out using the OS between this signature and other clinicopathologic factors, and a nomogram was constructed. In addition, the association between signature, immune cell infiltration, tumor mutation burden and immunophenoscore were determined. Results: Results of the present study using 118 GBM and LGG samples uncovered 15 immune-related genes that were also differently expressed in glioma samples. These were subsequently used to construct the immune-related signature. This signature exhibits the ability to predict prognosis, the infiltration of immune cells in the tumor microenvironment and the response of patients with glioma to immunotherapy. Conclusion: Results of the present study demonstrated that the aforementioned novel immune-related signature may accurately predict prognosis and the response of patients with glioma to immunotherapy.

MET inhibitor, capmatinib overcomes osimertinib resistance via suppression of MET/Akt/snail signaling in non-small cell lung cancer and decreased generation of cancer-associated fibroblasts.

BACKGROUND: Patients with non-small cell lung cancer (NSCLC) initially responding to tyrosine kinase inhibitors (TKIs) eventually develop resistance due to accumulating mutations in the EGFR and additional lesser investigated mechanisms such as the participation of the tumor microenvironment (TME). METHODS: Here, we examined the potential for MET inhibitor capmatinib for the treatment of osimertinib-resistant NSCLCs and normalizing the TME. RESULTS: We first established that HCC827 and H1975 cells showed increased resistance against osimertinib when co-cultured with CAFs isolated from osimertinib-resistant patients. Additionally, we showed that CAFs promoted epithelial-mesenchymal transition (EMT) and self-renewal ability in both HCC827 and H1975 cells. We subsequently found that both CAF-cultured HCC827 and H1975 showed a significantly higher expression of MET, Akt, Snail and IL-1ß, which were associated with survival and inflammatory responses. These cells in turn, promoted the generation of CAFs from normal lung fibroblasts. Subsequently, we observed that the treatment of capmatinib resulted in the re-sensitization of CAF-co-cultured H1975 and HCC827 to osimertinib, in association with reduced EMT and self-renewal ability. MET-silencing experiment using siRNA supported the observations made with capmatinib while with a greater magnitude. MET-silenced cell exhibited a severely hindered expression of inflammatory markers, IL-1ß and NF-κB; EMT markers, Snail and Vimentin, while increased E-cadherin. Finally, we demonstrated that the combination of capmatinib and osimertinib led to an increased tumor inhibition and significantly lower number of CAFs within the patient derived xenograft (PDX) model. CONCLUSION: Taken together, our findings suggested that an increased MET/Akt/Snail signaling was induced between the NSCLC cells and their TME (CAFs), resulting in osimertinib resistance. Suppression of this pathway by capmatinib may bypass the EGFR activating mutation and overcomes osimertinib resistance by targeting both tumor cells and CAFs.

Circular RNA circHECTD1 facilitates glioma progression by regulating the miR-296-3p/SLC10A7 axis.

Glioma is the most common type of primary brain tumor. Treatment options for recurrent gliomas include surgery, chemotherapy, and radiation therapy, but the clinical outcome is usually limited. In recent years, circular RNAs have been found to play a vital role in several human cancers. Gene Expression Omnibus database was utilized to verify the differentially expressed circRNAs. Then we detected that the expression of circular RNA circHECTD1 was significantly increased. The expression and function of circHECDT1 has not yet been reported in glioma. Then we confirmed that the level of circHECTD1 was significantly increased both in glioma tissues and cell lines, which is negatively correlated with the overall survival of patients. Knockdown of circHECTD1 inhibited proliferation and invasion in vitro, and also reduced the growth of tumor and prolonged the prognosis in vivo. Knockdown of circHECTD1 significantly elevated the miR-296-3p expression in LN229 and T98G cells. Luciferase reports and RNA immunoprecipitation data indicated that miR-296-3p was a direct target of circHECTD1 and that the miR-296-3p expression negatively regulated SLC10A7. Rescue experiments showed that the overexpression of SLC10A7 could impede the effects of circHECTD1 silencing on the proliferation and invasion of glioma cells. In this study, we identified that circHECTD1 regulates SLC10A7 by interacting with miR-296-3p in glioma cells. In conclusion, this study investigated a novel biomarker panel consisting of the circHECTD1/miR-296-3p/SLC10A7 axis, which is critical for glioma tumorigenesis and invasiveness and may represent a novel therapeutic target for intervening in glioma progression.