A signature of 13 autophagy‑related gene pairs predicts prognosis in hepatocellular carcinoma

Transmembrane protein 147, as a potential Sorafenib target, could expedite cell cycle process and confer adverse prognosis in hepatocellular carcinoma

TMEM147 was identified as a core component of ribosome-bound translocon complex at ER/NE. So far, sparse studies reported its expression profiling and oncological implications in hepatocellular carcinoma (HCC) patients. Here we inspected TMEM147 expression levels in HCC cohorts from public databases and tumor tissues. TMEM147 was augmented at transcriptional levels (p < 0.001) and protein levels in HCC patients. A series of bioinformatics tools implemented in R studio were orchestrated in TCGA-LIHC to evaluate the prognostic significance, compile relevant gene clusters, and explore the oncological functions and therapy responses. It is suggested that TMEM147 could predict poor clinical outcomes effectively and independently (p < 0.001, HR = 2.231 for overall survival (OS) vs. p = 0.04, HR = 2.296 for disease-specific survival), and was related to risk factors including advanced histologic tumor grade (p < 0.001), AFP level (p < 0.001) and vascular invasion (p  = 0.007). Functional enrichment analyses indicated that TMEM147 was involved in cell cycle, WNT/MAPK signaling pathways and ferroptosis. Expression profiling in HCC cell lines, mouse model, and a clinical trial revealed that TMEM147 was a considerable target and marker for adjuvant therapy in vitro and in vivo. Subsequentially, in vitro wet-lab experimentation authenticated that TMEM147 would be downregulated by Sorafenib administration in hepatoma cells. Lentivirus-mediated overexpression of TMEM147 could promote cell cycle progression from S phase into G2/M phase, and enhance cell proliferation, thus attenuating drug efficacy and sensitivity of Sorafenib. Further explorations into TMEM147 may inspire a fresh perspective to predict clinical outcomes and improve therapeutic efficacy for HCC patients.

Identification of a new five-gene risk score for risk stratification and prognosis prediction in HCC

Approximately 80% of primary liver cancer (PLC) is hepatocellular carcinoma (HCC), and the prognosis of HCC patients is unfavorable. Further studies are required to develop new prognostic tools for predicting the HCC patients' prognosis. The univariate Cox and LASSO regression were utilized to develop the multi-gene risk score. Single-sample Gene Set Enrichment Analysis (ssGSEA) was employed to assess differences of immune functions and cells. The model performance was evaluated by calibration curve and receiver operating characteristic curve (ROC). And qRT-PCR was utilized to evaluate the genes expression in clinical samples. Finally, a novel five-gene (KIF20A, CENPA, HMMR, G6PD, and ADH4) risk score was developed. Based on the median value of patients' risk scores, patients were divided into two groups: high-risk group and low-risk group. The Overall survival (OS) of patients in high-risk group was obviously poorer than that in the low-risk group. And the five-gene risk score was an independent risk factor correlated with patients' OS. Besides, a nomogram consisting of TNM stage and risk score was established. The results of decision curve, calibration curve, and ROC presented that the prognostic risk score and the nomogram had great predictive capability. Besides, ADH4's mRNA was reduced in HCC tissues, while the mRNA of KIF20A, CENPA, HMMR, and G6PD were overexpressed in HCC tissues. We developed a novel five-gene risk score that could predict HCC patients' prognosis. And these five genes could be promising therapeutic targets for HCC. The five-gene risk score and nomogram may be useful prognostic tools for HCC.

A 25 Immune-Related Gene Pair Signature Predicts Overall Survival in Cervical Cancer

Mounting evidence suggests that the tumor microenvironment plays an important role in the occurrence and development of cancer, with immune system dysfunction being closely related to malignant cancers. We aimed to screen immune-related genes (IRGs) to generate an IRG pair (IRGP)-based prognostic signature for cervical cancer (CC). Datasets were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases and used as training and validation cohorts, respectively. Using the ImmPort database, IRGs in control and CC samples were compared, and differentially expressed genes were identified to construct an IRGP prognostic signature. Based on this analysis, 25 IRGPs were identified as important factors for the prognosis of CC. Univariate and multivariate Cox regression analyses further showed that the IRGP signature was an independent prognostic factor of overall survival. In summary, we successfully constructed an IRGP prognostic signature of CC, providing insights into immunotherapy for CC.

An Oxidative Stress-Related Gene Pair (CCNB1/PKD1), Competitive Endogenous RNAs, and Immune-Infiltration Patterns Potentially Regulate Intervertebral Disc Degeneration Development

Oxidative stress (OS) irreversibly affects the pathogenesis of intervertebral disc degeneration (IDD). Certain non-coding RNAs act as competitive endogenous RNAs (ceRNAs) that regulate IDD progression. Analyzing the signatures of oxidative stress-related gene (OSRG) pairs and regulatory ceRNA mechanisms and immune-infiltration patterns associated with IDD may enable researchers to distinguish IDD and reveal the underlying mechanisms. In this study, OSRGs were downloaded and identified using the Gene Expression Omnibus database. Functional-enrichment analysis revealed the involvement of oxidative stress-related pathways and processes, and a ceRNA network was generated. Differentially expressed oxidative stress-related genes (De-OSRGs) were used to construct De-OSRG pairs, which were screened, and candidate De-OSRG pairs were identified. Immune cell-related gene pairs were selected via immune-infiltration analysis. A potential long non-coding RNA-microRNA-mRNA axis was determined, and clinical values were assessed. Eighteen De-OSRGs were identified that were primarily related to intricate signal-transduction pathways, apoptosis-related biological processes, and multiple kinase-related molecular functions. A ceRNA network consisting of 653 long non-coding RNA-microRNA links and 42 mRNA-miRNA links was constructed. Three candidate De-OSRG pairs were screened out from 13 De-OSRG pairs. The abundances of resting memory CD4+ T cells, resting dendritic cells, and CD8+ T cells differed between the control and IDD groups. CD8+ T cell infiltration correlated negatively with cyclin B1 (CCNB1) expression and positively with protein kinase D1 (PKD1) expression. CCNB1-PKD1 was the only pair that was differentially expressed in IDD, was correlated with CD8+ T cells, and displayed better predictive accuracy compared to individual genes. The PKD1-miR-20b-5p-AP000797 and CCNB1-miR-212-3p-AC079834 axes may regulate IDD. Our findings indicate that the OSRG pair CCNB1-PKD1, which regulates oxidative stress during IDD development, is a robust signature for identifying IDD. This OSRG pair and increased infiltration of CD8+ T cells, which play important roles in IDD, were functionally associated. Thus, the OSRG pair CCNB1-PKD1 is promising target for treating IDD.

A new prognostic risk model based on autophagy-related genes in kidney renal clear cell carcinoma

This study aimed to explore the potential role of autophagy-related genes in kidney renal clear cell carcinoma (KIRC) and develop a new prognostic-related risk model. In our research, we used multiple bioinformatics methods to perform a pan-cancer analysis of the CNV, SNV, mRNA expression, and overall survival of autophagy-related genes, and displayed the results in the form of heat maps. We then performed cluster analysis and LASSO regression analysis on these autophagy-related genes in KIRC. In the cluster analysis, we successfully divided patients with KIRC into five clusters and found that there was a clear correlation between the classification and two clinicopathological features: tumor, and stage. In LASSO regression analysis, we used 13 genes to create a new prognostic-related risk model in KIRC. The model showed that the survival rate of patients with KIRC in the high-risk group was significantly lower than that in the low-risk group, and that there was a correlation between this grouping and the patients’ metastasis, tumor, stage, grade, and fustat. The results of the ROC curve suggested that this model has good prediction accuracy. The results of multivariate Cox analysis show that the risk score of this model can be used as an independent risk factor for patients with KIRC. In summary, we believe that this research provides valuable data supporting future clinical treatment and scientific research.

Pinocembrin suppresses proliferation and enhances apoptosis in lung cancer cells in vitro by restraining autophagy

Lung cancer is one of the leading causes of human death, and the 5-year survival rate for lung cancer patients remains a relative low level. Pinocembrin (Pino) was reported to play an important role in the inhibition of cancer development, so this study was designed to explore the role of pino in lung cancer. A549 cells were treated with different concentration of Pino (25, 50, 100, 150 and 200 µM) for 24, 48 and 72, respectively to detect cell viability by Cell counting kit-8 (CCK-8) assay. Then, the proliferation, apoptosis and autophagy of A549 cells under pino exposure were detected using colony formation, TUNEL and immunofluorescence staining, respectively. Western blot was used to analyze proliferation-, apoptosis-, and autophagy-related proteins. To measure the effects of pino on cell autophagy, the above-mentioned functional assays were conducted again in A549 cells treated with pino and 20 µM autophagy activator rapamycin (RAPA). Declined trends in cell viability, proliferation, and autophagy were found in A549 cells treated with increasing doses of pino, by contrast with those without any treatment. Additionally, the apoptosis of A549 cells was enhanced upon pino exposure, accompanied by elevated caspase3 activity. However, RAPA reversed the anti-proliferative, anti-autophagic and pro-apoptotic properties of pino in A549 cells. In conclusion, this paper is the first to verify that pino suppresses the proliferation and enhances the apoptosis of lung cancer cells by restraining autophagy, indicating that pino has potential therapeutic effects on the treatment of lung cancer.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.

Rutin attenuates Sorafenib-induced Chemoresistance and Autophagy in Hepatocellular Carcinoma by regulating BANCR/miRNA-590-5P/OLR1 Axis

Rutin, the main component of Potentilla discolor Bunge, was proven to exhibit anti-tumor properties. Sorafenib (SO) is conventionally used in chemotherapy against hepatocellular carcinoma (HCC), but acquired resistance developed during long-term therapy limits its benefits. This study aimed to explore the molecular mechanism of rutin in SO-induced autophagy and chemoresistance in HCC. Sixty-eight paired HCC patients who received the same chemotherapy treatment were obtained. We also established two SO resistance cell lines and then utilized high-throughput RNA sequencing to explore their long non-coding RNA (lncRNA) expression profiles. The target microRNA (miRNA) and downstream mRNA were also explored. Our results indicated that rutin treatment attenuates autophagy and BANCR expression in SO resistance cells. Transmission electron microscopy clearly showed a significantly decreased number of autophagosomes after rutin-treated HepG2/SO and HCCLM3/SO cells. BANCR knockdown promotes the sensitivity of SO resistance cells to SO. Further study found that BANCR acts as a molecular sponge of miR-590-5P to sequester miR-590-5P away from oxidized low-density lipoprotein receptor 1 (OLR1) in HCC cells. Furthermore, in vivo study demonstrated that rutin could inhibit autophagy through the BANCR/miRNA-590-5P/OLR1 axis. Our findings suggest that rutin could regulate autophagy by regulating BANCR/miRNA-590-5P/OLR1 axis.

Identification of an Autophagy-Related Pair Signature for Predicting Prognoses and Immune Activity in Pancreatic Adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) spreads quickly and has a poor prognosis. Autophagy research on PAAD could reveal new biomarkers and targets for diagnosis and treatment.

METHODS

Autophagy-related genes were translated into autophagy-related gene pairs, and univariate Cox regression was performed to obtain overall survival (OS)-related IRGPs (P<0.001). LASSO Cox regression analyses were performed to construct an autophagy-related gene pair (ARGP) model for predicting OS. The Cancer Genome Atlas (TCGA)-PAAD cohort was set as the training group for model construction. The model predictive value was validated in multiple external datasets. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Tumor microenvironments and immune infiltration were compared between low- and high-risk groups with ESTIMATE and CIBERSORT. Differentially expressed genes (DEGs) between the groups were further analyzed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used to identify potential small-molecule compounds in L1000FWD.

RESULTS

Risk scores were calculated as follows: ATG4B|CHMP4C×(-0.31) + CHMP2B|MAP1LC3B×(0.30) + CHMP6|RIPK2 ×(-0.33) + LRSAM1|TRIM5×(-0.26) + MAP1LC3A|PAFAH1B2×(-0.15) + MAP1LC3A|TRIM21×(-0.08) + MET|MFN2×(0.38) + MET|MTDH×(0.47) + RASIP1|TRIM5×(-0.23) + RB1CC1|TPCN1×(0.22). OS was significantly shorter in the high-risk group than the low-risk group in each PAAD cohort. The ESTIMATE analysis showed no difference in stromal scores but a significant difference in immune scores (p=0.0045) and ESTIMATE scores (p=0.014) between the groups. CIBERSORT analysis showed higher naive B cell, Treg cell, CD8 T cell, and plasma cell levels in the low-risk group and higher M1 and M2 macrophage levels in the high-risk group. In addition, the results showed that naive B cells (r=-0.32, p<0.001), Treg cells (r=-0.31, p<0.001), CD8 T cells (r=-0.24, p=0.0092), and plasma cells (r=-0.2, p<0.026) were statistically correlated with the ARGP risk score. The top 3 enriched GO-BPs were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched KEGG pathways were the insulin secretion, dopaminergic synapse, and NF-kappa B signaling pathways. Several potential small-molecule compounds targeting ARGs were also identified.

CONCLUSION

Our results demonstrate that the ARGP-based model may be a promising prognostic indicator for identifying drug targets in patients with PAAD.