Microenvironment and tumors-a nurturing relationship

Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer

Objective

The mortality rate of ovarian cancer (OC) is the highest among all gynecologic cancers. To predict the prognosis and the efficacy of immunotherapy, we identified new biomarkers.

Methods

The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used to extract ovarian cancer transcriptomes. By performing the co-expression analysis, we identified necroptosis-associated long noncoding RNAs (lncRNAs). We used the least absolute shrinkage and selection operator (LASSO) to build the risk model. The qRT-PCR assay was conducted to confirm the differential expression of lncRNAs in the ovarian cancer cell line SK-OV-3. Gene Set Enrichment Analysis, Kaplan-Meier analysis, and the nomogram were used to determine the lncRNAs model. Additionally, the risk model was estimated to evaluate the efficacy of immunotherapy and chemotherapy. We classified necroptosis-associated IncRNAs into two clusters to distinguish between cold and hot tumors.

Results

The model was constructed using six necroptosis-associated lncRNAs. The calibration plots from the model showed good consistency with the prognostic predictions. The overall survival of one, three, and five-year areas under the ROC curve (AUC) was 0.691, 0.678, and 0.691, respectively. There were significant differences in the IC50 between the risk groups, which could serve as a guide to systemic treatment. The results of the qRT-PCR assay showed that AL928654.1, AL133371.2, AC007991.4, and LINC00996 were significantly higher in the SK-OV-3 cell line than in the Iose-80 cell line (P < 0.05). The clusters could be applied to differentiate between cold and hot tumors more accurately and assist in accurate mediation. Cluster 2 was more vulnerable to immunotherapies and was identified as the hot tumor.

Conclusion

Necroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors.

VPS34 suppression reverses osimertinib resistance via simultaneously inhibiting glycolysis and autophagy

Autophagy and glycolysis are associated with osimertinib resistance. The energy complement and dynamic balance between these two processes make it difficult to block the process of drug resistance; breaking the complementary relationship between them may effectively overcome drug resistance. However, the exact mechanisms and the key players for regulating autophagy and glycolysis remain unclear. In this study, we demonstrate that autophagy and glycolysis levels in osimertinib-resistant cells were markedly higher than parental cells, and a dynamic balance existed between them. Inhibition of the class III phosphoinositide 3-kinase vacuolar protein sorting 34 (VPS34) with 3-methyladenine or small interfering RNA can not only inhibit abnormally enhanced autophagy but also inhibit glycolysis by inhibiting the location of epidermal growth factor receptor (EGFR) and the expression of hexokinase II. By demonstrating that VPS34 is the key player controlling autophagy and glycolysis simultaneously, our study may provide a new strategy for overcoming osimertinib resistance for treatment of EGFR-mutant non-small cell lung cancer patients.

3-Methyladenine-enhanced susceptibility to sorafenib in hepatocellular carcinoma cells by inhibiting autophagy

As an effective targeted therapy for advanced hepatocellular carcinoma (HCC), sorafenib resistance has been frequently reported in recent years, with the activation of autophagy by cancer cells under drug stress being one of the crucial reasons. Sorafenib treatment could enhance autophagy in HCC cells and autophagy is also considered as an important mechanisms of drug resistance. Therefore, the inhibition of autophagy is a potential way to improve the sensitivity and eliminate drug resistance to restore their efficacy. To determine whether autophagy is involved in sorafenib resistance and investigate its role in the regulation of HepG2 cells' (an HCC cell line) chemosensitivity to sorafenib, we simultaneously treated HepG2 with sorafenib and 3-Methyladenine (3-MA) (a common autophagy inhibitor). First, by performing cell counting kit 8 cell viability assay, Hoechst 33342 apoptosis staining, and Annexin V-fluorescein isothiocyanate/propidium iodide apoptosis kit detection, we found that both sorafenib and 3-MA effectively inhibitted the proliferative activity of HepG2 cells and induced their apoptosis to a certain extent. This effect was significantly enhanced after these two drugs were combined, which was also confirmed by the increased expression of apoptosis-related proteins. Subsequently, by using AAV-GFP-LC3 transfection methods and transmission electron microscopy, we found that both the number and activity of autophagosomes in HepG2 cells in sorafenib and 3-MA group were significantly reduced, suggesting that autophagy activity was inhibited, and this result was consistent with the expression results of autophagy-related proteins. Therefore, we conclude that 3-MA may attenuate the acquired drug resistance of sorafenib by counteracting its induction of autophagy activity, thus enhancing its sensitivity to advanced HCC therapy.

ANXA6 Contributes to Radioresistance by Promoting Autophagy via Inhibiting the PI3K/AKT/mTOR Signaling Pathway in Nasopharyngeal Carcinoma

Radiotherapy is a conventional and effective treatment method for nasopharyngeal carcinoma (NPC), although it can fail, mainly because radioresistance results in residual or recurrent tumors. However, the mechanisms and predictive markers of NPC radioresistance are still obscure. In this study, we identified Annexin A6 (ANXA6) as a candidate radioresistance marker by using Tandem Mass Tag quantitative proteomic analysis of NPC cells and gene chip analysis of NPC clinical samples with different radiosensitivities. It was observed that a high expression level of ANXA6 was positively correlated with radioresistance of NPC and that inhibition of ANXA6 by siRNA increased the radiosensitivity. The incidence of autophagy was enhanced in the established radioresistant NPC cells in comparison with their parent cells, and silencing autophagy with LC3 siRNA (siLC3) sensitized NPC cells to irradiation. Furthermore, ANXA6 siRNA (siANXA6) suppressed cellular autophagy by activating the PI3K/AKT/mTOR pathway, ultimately leading to radiosensitization. The combination of siANXA6 and CAL101 (an inhibitor of PI3K, p-AKT, and mTOR, concurrently) significantly reversed the above siANAX6-reduced autophagy. Suppression of PI3K/AKT/mTOR by CAL101 also increased the expression of ANXA6 in a negative feedback process. In conclusion, this study revealed for the first time that ANXA6 could promote autophagy by inhibiting the PI3K/AKT/mTOR pathway and that it thus contributes to radioresistance of NPC. The significance of this is that ANXA6 could be applied as a new predictive biomarker of NPC prognosis after radiotherapy.

Metabolic regulation of cell growth and proliferation

Cellular metabolism is at the foundation of all biological activities. The catabolic processes that support cellular bioenergetics and survival have been well studied. By contrast, how cells alter their metabolism to support anabolic biomass accumulation is less well understood. During the commitment to cell proliferation, extensive metabolic rewiring must occur in order for cells to acquire sufficient nutrients such as glucose, amino acids, lipids and nucleotides, which are necessary to support cell growth and to deal with the redox challenges that arise from the increased metabolic activity associated with anabolic processes. Defining the mechanisms of this metabolic adaptation for cell growth and proliferation is now a major focus of research. Understanding the principles that guide anabolic metabolism may ultimately enhance ways to treat diseases that involve deregulated cell growth and proliferation, such as cancer.

Drosophila melanogaster: A Model Organism to Study Cancer

Cancer is a multistep disease driven by the activation of specific oncogenic pathways concomitantly with the loss of function of tumor suppressor genes that act as sentinels to control physiological growth. The conservation of most of these signaling pathways in Drosophila, and the ability to easily manipulate them genetically, has made the fruit fly a useful model organism to study cancer biology. In this review we outline the basic mechanisms and signaling pathways conserved between humans and flies responsible of inducing uncontrolled growth and cancer development. Second, we describe classic and novel Drosophila models used to study different cancers, with the objective to discuss their strengths and limitations on their use to identify signals driving growth cell autonomously and within organs, drug discovery and for therapeutic approaches.

Autophagy and Tumorigenesis in Drosophila

The resurgence of Drosophila as a recognized model for carcinogenesis has contributed greatly to our conceptual advance and mechanistic understanding of tumor growth in vivo. With its powerful genetics, Drosophila has emerged as a prime model organism to study cell biology and physiological functions of autophagy. This has enabled exploration of the contributions of autophagy in several tumor models. Here we review the literature of autophagy related to tumorigenesis in Drosophila. Functional analysis of core autophagy components does not provide proof for a classical tumor suppression role for autophagy alone. Autophagy both serve to suppress or support tumor growth. These effects are context-specific, depending on cell type and oncogenic or tumor suppressive lesion. Future delineation of how autophagy impinges on tumorigenesis will demand to untangle in detail, the regulation and flux of autophagy in the respective tumor models. The downstream tumor-regulative roles of autophagy through organelle homeostasis, metabolism, selective autophagy or alternative mechanisms remain largely unexplored.

Identifying autophagy gene-associated module biomarkers through construction and analysis of an autophagy-mediated ceRNA‑ceRNA interaction network in colorectal cancer

Autophagy is crucial in cellular homeostasis and has been implicated in the development of malignant tumors. However, the regulatory function of autophagy in cancer remains to be fully elucidated. In the present study, the autophagy-mediated competing endogenous RNA (ceRNA)-ceRNA interaction networks in colorectal cancer (CRC) were constructed by integrating systematically expression profiles of long non-coding RNAs and mRNAs. It was found that a large proportion of autophagy genes were inclined to target hub nodes, including a fraction of autophagy genes, by comparing with other genes within ceRNA networks, and showed preferential interaction with themselves. The present study also revealed that autophagy genes may be used as prognostic markers for cancer therapy. A risk score model based on multivariable Cox regression analysis was then used to capture novel biomarkers in connection with lncRNA for the prognosis of CRC. These biomarkers were confirmed in the test dataset and an additional independent dataset. Furthermore, the prognostic value of biomarkers is independent of conventional clinical factors. These results provide improved understanding of autophagy-mediated ceRNA regulatory mechanisms in CRC and provide novel potential molecular therapeutic targets for the diagnosis and treatment of CRC.

Autophagy mediates glucose starvation-induced glioblastoma cell quiescence and chemoresistance through coordinating cell metabolism, cell cycle, and survival

Metabolic reprogramming is pivotal to sustain cancer growth and progression. As such dietary restriction therapy represents a promising approach to starve and treat cancers. Nonetheless, tumors are dynamic and heterogeneous populations of cells with metabolic activities modulated by spatial and temporal contexts. Autophagy is a major pathway controlling cell metabolism. It can downregulate cell metabolism, leading to cancer cell quiescence, survival, and chemoresistance. To understand treatment dynamics and provide rationales for better future therapeutic strategies, we investigated whether and how autophagy is involved in the chemo-cytotoxicity and -resistance using two commonly used human glioblastoma (GBM) cell lines U87 and U251 together with primary cancer cells from the GBM patients. Our results suggest that autophagy mediates chemoresistance through reprogramming cancer cell metabolism and promoting quiescence and survival. Further unbiased transcriptome profiling identified a number of clinically relevant pathways and genes, strongly correlated with TCGA data. Our analyses have not only reported many well-known tumor players, but also uncovered a number of genes that were not previously implicated in cancers and/or GBM. The known functions of these genes are highly suggestive. It would be of high interest to investigate their potential involvement in GBM tumorigenesis, progression, and/or drug resistance. Taken together, our results suggest that autophagy inhibition could be a viable approach to aid GBM chemotherapy and combat drug resistance.