Background: Prostate cancer (PCa) is one of the most prevalent cancers that occur in men worldwide. Autophagyrelated genes (ARGs) may play an essential role in multiple biological processes of prostate cancer. However, ARGs expression signature has rarely been used to investigate the association between autophagy and prognosis in PCa. This study aimed to identify and assess prognostic ARGs signature to predict overall survival (OS) and disease-free survival (DFS) in PCa patients. Methods: First, a total of 234 autophagy-related genes were obtained from The Human Autophagy Database. Then, differentially expressed ARGs were identified in prostate cancer patients based on The Cancer Genome Atlas (TCGA) database. The univariate and multivariate Cox regression analysis was performed to screen hub prognostic ARGs for overall survival and disease-free survival, and the prognostic model was constructed. Finally, the correlation between the prognostic model and clinicopathological parameters was further analyzed, including age, T status, N status, and Gleason score. Results: The OS-related prognostic model was constructed based on the five ARGs (FAM215A, FDD, MYC, RHEB, and ATG16L1) and significantly stratified prostate cancer patients into high-and low-risk groups in terms of OS (HR = 6.391, 95% CI = 1.581-25.840, P < 0.001). The area under the receiver operating characteristic curve (AUC) of the prediction model was 0.84. The OS-related prediction model values were higher in T3-4 than in T1-2 (P = 0.008), and higher in Gleason score > 7 than ≤ 7 (P = 0.015). In addition, the DFS-related prognostic model was constructed based on the 22 ARGs (ULK2,

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Among these, lung adenocarcinoma (LUAD) accounts for most cases. Due to the improvement of precision medicine based on molecular characterization, the treatment of LUAD underwent significant changes. With these changes, the prognosis of LUAD becomes diverse. N6-methyladenosine (m6A) is the most predominant modification in mRNAs, which has been a research hotspot in the field of oncology. Nevertheless, little has been studied to reveal the correlations between the m6A-related genes and prognosis in LUAD. Thus, we conducted a comprehensive analysis of m6A-related gene expressions in LUAD patients based on The Cancer Genome Atlas (TCGA) database by revealing their relationship with prognosis. Different expressions of the m6A-related genes in tumor tissues and non-tumor tissues were confirmed. Furthermore, their relationship with prognosis was studied via Consensus Clustering Analysis, Principal Components Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) Regression. Based on the above analyses, a m6A-based signature to predict the overall survival (OS) in LUAD was successfully established. Among the 479 cases, we found that most of the m6A-related genes were differentially expressed between tumor and non-tumor tissues. Six genes, HNRNPC, METTL3, YTHDC2, KIAA1429, ALKBH5, and YTHDF1 were screened to build a risk scoring signature, which is strongly related to the clinical features pathological stages (p<0.05), M stages (p<0.05), T stages (p < 0.05), gender (p=0.04), and survival outcome (p=0.02). Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor, revealing that the m6A-related genes signature has great predictive value. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database.

Purpose There is plenty of evidence showing that autophagy plays an important role in the biological process of cancer. The purpose of this study was to establish a novel autophagy-related prognostic marker for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Methods The mRNA microarray and clinical data in The Cancer Genome Atlas (TCGA) were analyzed by using a univariate Cox proportional regression model to select candidate autophagy-related prognostic genes. Bioinformatics analysis of gene function using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) platforms was performed. A multivariate Cox proportional regression model helped to develop a prognostic signature from the pool of candidate genes. On the basis of this prognostic signature, we could divide LUAD and LUSC patients into high-risk and low-risk groups. Further survival analysis demonstrated that high-risk patients had significantly shorter disease-free survival (DFS) than low-risk patients. The signature which contains six autophagy-related genes (EIF4EBP1, TP63, BNIP3, ATIC, ERO1A and FADD) showed good performance for predicting the survival of LUAD and LUSC patients by having a better Area Under Curves (AUC) than other clinical parameters. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database. Conclusion Collectively, the prognostic signature we proposed is a promising biomarker for monitoring the outcomes of LUAD and LUSC.

Background To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. Methods We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1, P value <0.05 by using package “limma” in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan–Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. Results A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. Conclusions Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.

BackgroundMutations of BRAFV600E and TERT promoters are associated with thyroid cancer development. This study further investigated association of these mutations with clinicopathological characteristics from patients with papillary thyroid carcinoma (PTC).MethodsTumor tissues from 342 PTC patients were obtained for DNA extraction and polymerase chain reaction amplification to detect the BRAFV600E mutation using amplification-refractory mutation system-polymerase chain reaction. TERT promoter mutations were assessed using Sanger DNA sequencing. The association of these gene mutations with clinicopathological characteristics was then statistically analyzed.ResultsTwo hundred and seventy of 342 (78.9%) PTC patients harbored the BRAFV600E mutation, which was associated with older age male patients. Moreover, TERT promoter mutations occurred in 12 of 342 (3.5 %) PTC patients, all of whom also had the BRAF mutation. One hundred thirty-three patients with papillary thyroid microcarcinoma (PTMC) had no TERT mutations. Statistically, the coexistence of BRAF and TERT promoter mutations were significantly associated with older age, larger tumor size, extrathyroidal extension, and advanced tumor stage, but not with central lymph node metastasis, lateral lymph node metastasis, numbers of lymph node metastasis >5, and numbers of involved/harvested lymph nodes (No. of LNs involved or harvested). The multivariate analyses showed older age (odds ratio [OR], 2.194; 95% CI: 1.117–4.311; p=0.023), larger tumor size (OR, 4.100; 95% CI: 2.257–7.450; p<0.001), and multiplicity (OR, 2.240; 95% CI: 1.309–3.831; p=0.003) were all independent predictors for high prevalence of extrathyroidal extension. However, there was no statistical association with any clinicopathological characteristics except for Hashimoto thyroiditis in PTMC.ConclusionThe current study demonstrated that the coexistence of BRAF and TERT promoter mutations were associated with the PTC aggressiveness, although these mutations were not associated with PTC lymph node metastasis or with PTMC.

BackgroundCervical lymph node metastasis of papillary thyroid carcinoma (PTC) is common. However, whether undergoing prophylactic central lymph node (CLN) dissection or lateral lymph node (LLN) dissections to prevent metastasis is still controversial. This study aimed to retrospectively investigate the risk factors of LLN metastasis in clinical lymph node-negative (cN0) PTC patients.MethodsWe retrospectively studied 783 lymph node-negative (cN0) PTC patients who underwent total thyroidectomy plus CLN dissection and LLN dissection.ResultsThe rates of CLN and LLN metastases were 68.2 and 47.4%, respectively. Large tumor size (> 20 mm) had a fourfold higher risk of LLN metastasis compared with small tumor size (≤ 20 mm; OR = 4.082, 95% CI 2.646–6.289; P = 0.001). Patients with tumor in the upper lobe had ~ 3-fold higher risk of LLN metastasis compared with patients with tumor in other locations (OR = 2.874, 95% CI 1.916–4.310; P = 0.001). Multifocality and extrathyroidal extension indicated a twofold higher risk of LLN metastasis. Having ≥ 2 CLN metastases dramatically increased the risk of LLN metastasis, compared with those with < 2 CLN metastases (OR = 6.536, 95% CI 4.630–9.259; P = 0.001).ConclusionsLarge tumor size (> 20 mm), tumor located in the upper lobe, multifocality, extrathyroidal extension, and ≥ 2 CLN metastases may increase the risk of LLN metastasis in cN0 PTC patients.

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PurposeN6-methyladenosine (m6A) methylation plays a critical role in diverse biological processes. However, knowledge regarding the constitution of m6A on tumor microenvironment (TME) and tumor-infiltrating lymphocytes (TILs) across cancer types is still lacking. We performed comprehensive immuno-genomic analyses to reveal molecular characterization of the m6A regulators and immune-related genes (IRGs) across TME and TIL heterogeneity.MethodsWe comprehensively analyzed the properties of m6A regulators in genomic profiles from The Cancer Genome Atlas (TCGA) according to expression perturbations of crucial IRGs, CD274, CD8A, GZMA, and PRF1. The four IRGs were proved to be reliable biomarkers of TILs and TME via CIBERSORT and ESTIMATE analyses, and their co-expression relationship was certified by TIMER analysis. Based on their median values, the samples from the pan-cancer tissues (N = 11,057) were classified into eight TME types. The RNA expression levels of 13 m6A regulators were compared across TME subtypes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was also used to classify TME clusters, expression variants of IRGs and m6A regulators were verified among TME clusters. Meanwhile, the correlation between m6A regulators and tumor mutational burden (TMB) were tested. Finally, the impacts of IRGs and TME clusters in clinical characteristics and outcomes were revealed.ResultsCD274, CD8A, GZMA, and PRF1 showed similar TILs’ characteristics, of which the level of T cells CD8 and T cells CD4 memory activated are consistent with the expression levels of the four IRGs and higher immune infiltration. Besides, CD274, CD8A, GZMA, and PRF1 were positively correlated with the stromal score or immune score in almost all 33 tumor types. All of four IRGs showed impact between tumor pathological stages or clinical outcomes. Among TME type I to type IV, m6A regulators’ expression drift changed from high-level to low-level in ESCA, BLCA, HNSC, CESC, BRCA, and GBM. However among TME type V to type VIII, m6A regulators drew a shift from low-level to high-level expression in CESC, BLCA, ESCA, KIRP, HNSC, BRCA, KIRC, COAD, LAML, GBM, and KICH. In ssGSEA analyses, IRGs’ expression levels were elevated with the immune infiltration degree and m6A regulators’ expression level varied among three TIL subgroups. With different TMB levels, expression differences of m6A regulators were observed in BLCA, BRCA, COAD, LGG, LUAD, LUSC, STAD, THCA, and UCEC.ConclusionWe identified four crucial IRGs affecting TILs, TME characteristics and clinical parameters. Expression variants of m6A regulators among the subgroups of TME types and ssGSEA clusters suggested that m6A regulators may be essential factors for phenotypic modifications of IRGs and thus affecting TME characteristics across multiple tumor types.