Acyl-CoA synthetases (ACSs) are responsible for acyl-CoA synthesis from nonpolar hydrophilic fatty acids and play a vital role in many metabolic processes. As a category of ACS isozymes, members of ACS family (AACS, ACSF2-3, AASDH) participate in lipid metabolism; however, their expression patterns, regulatory mechanisms and effects in hepatocellular carcinoma (HCC) are poorly understood. Here, through evaluating the expression profiles of ACSF gene family, we found that upregulated AACS might be more significant and valuable in development and progression of HCC. Consequently, the mRNA expression levels of AACS and ACSF2 was accordantly increased in HCC. Kaplan-Meier plotter revealed that HCC patients with high level of AACS were highly related to a shorter overall survival time and relapse-free survival. Genetic alterations using cBioPortal revealed that the alteration rate of AACS were 5%. We also found that the functions of ACSF gene family were linked to several cancer-associated pathways, including long-term potentiation, phospholipase D signaling pathway and purine metabolism. TIMER database indicated that the AACS and ACSF2 had a strong relationship with the infiltration of six types of immune cells (macrophages, neutrophils, CD8+ T-cells, B-cells, CD4+ T-cells and dendritic cells). Next, Diseasemeth database revealed that the global methylation levels of ACSF2 was higher in HCC patients. In conclusion, this study firstly demonstrated that Acyl-CoA synthesis gene family, in particular, AACS, could be associated with immune microenvironment, thereby influencing the development and prognosis of patients with HCC.

Lung adenocarcinoma accounts for approximately 40% of lung cancer cases and poses a serious threat to human health. Therefore, there is an urgent need to identify central biomarkers in lung adenocarcinoma.

Immunotherapy has a significant effect on the treatment of many tumor types. However, prostate cancers generally fail to show significant responses to immunotherapy owing to their immunosuppressive microenvironments. To sustain progress towards more effective immunotherapy for prostate cancer, comprehensive analyses of the genetic characteristics of the immune microenvironment and novel therapeutic strategies are required.

Microsatellite instability-high (MSI-H) has gained considerable interests since it was approved as a tumor-agnostic biomarker in immunotherapy. However, the reported characteristics of MSI-H gastric cancer (GC) are inconsistent due to the biological complexity. Here, we aim to clarify the prevalence, risk factors, clinicopathological/molecular features and outcomes of MSI-H GC though a comprehensive review on 43246 patients from 134 cohorts. Overall, the proportion of MSI-H GC was 14.5% (95% CI, 13.3%-15.8%). Patients with MSI-H GC were less likely to have Epstein-Barr virus infection. High incidences of MSI-H GC were associated with female, older age, lower gastric body, Lauren intestinal histology, WHO tubular and mucinous subtypes, and early disease stage. Additionally, patients with MSI-H GC harbored more KRAS mutation, PD-L1 positivity, CD8 overexpression, and higher TMB, but less HER2 positivity and TP53 mutation. When treated with conventional strategy, the 5-year survival rates in MSI-H patients (70.3%) and MSI-L/MSS patients (43.7%) were significantly different (p<0.001). Patients with MSI-H GC derived larger benefit from immunotherapy in term of overall survival (pInteraction<0.001) and objective response (pInteraction=0.02). Since the prevalence of MSI-H GC is relatively high and associated with distinct clinicopathological and molecular characteristics, MSI testing should be conducted during standard diagnostical activity. Moreover, giving MSI-H tumors are often diagnosed at early stage and have favorable outcomes, less aggressive treatment strategies may be considered in clinical practice. In summary, this panoramic review may assist in design and/or interpretation of clinical trials, provide references in drug development, and constitute complementary information in drafting the clinical practice guideline.

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the two most common pathology subtypes of primary liver cancer (PLC). Identifying DNA methylation biomarkers for diagnosis of PLC and further distinguishing HCC from ICC plays a vital role in subsequent treatment options selection. To obtain potential diagnostic DNA methylation sites for PLC, differentially methylated CpG (DMC) sites were first screened by comparing the methylation data between normal liver samples and PLC samples (ICC samples and HCC samples). A random forest algorithm was then used to select specific DMC sites with top Gini value. To avoid overfitting, another cohort was taken as an external validation for evaluating the area under curves (AUCs) of different DMC sites combination. A similar model construction strategy was applied to distinguish HCC from ICC. In addition, we identified DNA Methylation-Driven Genes in HCC and ICC via MethylMix method and performed pathway analysis by utilizing MetaCore. Finally, we not only performed methylator phenotype based on independent prognostic sites but also analyzed the correlations between methylator phenotype and clinical factors in HCC and ICC, respectively. To diagnose PLC, we developed a model based on three PLC-specific methylation sites (cg24035245, cg21072795, and cg00261162), whose sensitivity and specificity achieved 98.8%,94.8% in training set and 97.3%,81% in validation set. Then, to further divide the PLC samples into HCC and ICC, we established another mode through three methylation sites (cg17769836, cg17591574, and cg07823562), HCC accuracy and ICC accuracy achieved 95.8%, 89.8% in the training set and 96.8%,85.4% in the validation set. In HCC, the enrichment pathways were mainly related to protein folding, oxidative stress, and glutathione metabolism. While in ICC, immune response, embryonic hepatocyte maturation were the top pathways. Both in HCC and ICC, methylator phenotype correlated well with overall survival time and clinical factors involved in tumor progression. In summary, our study provides the biomarkers based on methylation sites not only for the diagnosis of PLC but also for distinguishing HCC from ICC.

Homologous recombination deficiency (HRD) is a common molecular signature of genomic instability and has been shown to be a biomarker for targeted therapies. However, there is a lack of studies on the role of HRD changes in lung adenocarcinoma (LUAD) transcriptomics. HRD scores were determined using single nucleotide polymorphism (SNP) array data from LUAD patients from The Cancer Genome Atlas (TCGA) database. Transcriptional data from patients with different scores were analyzed to identify biomarkers associated with HRD. Candidate biomarkers were validated using Gene Expression Omnibus (GEO)-sourced datasets and an immunotherapy cohort. According to the bulk transcriptome and clinical characteristics of 912 LUAD patients and Single-cell RNA-seq of 9 LUAD patients from TCGA and GEO databases, we observed increased MS4A6A expression in HRD tumors; high MS4A6A expression predicted improved survival outcomes. Furthermore, a comprehensive analysis of the tumor immune microenvironment (TIME) revealed a positive correlation between MS4A6A expression and neoantigen loading and immune cell infiltration. Additionally, the immunotherapy cohort confirmed the possibility of using MS4A6A as a biomarker. Collectively, we suggest that MS4A6A is associated with HRD and provide a new perspective toward identifying promising biomarkers for immunotherapy.

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality, which makes the prognostic prediction challenging. Angiogenesis appears to be of critical importance in the progression and metastasis of HCC. Some of the angiogenesis-related genes promote this process, while other anti-angiogenesis genes suppress tumor growth and metastasis. Therefore, the comprehensive prognostic value of multiple angiogenesis-related genes in HCC needs to be further clarified. In this study, the mRNA expression profile of HCC patients and the corresponding clinical data were acquired from multiple public databases. Univariate Cox regression analysis was utilized to screen out differentially expressed angiogenesis-related genes with prognostic value. A multigene signature was established with the least absolute shrinkage and selection operator Cox regression in the Cancer Genome Atlas cohort, and validated through an independent cohort. The results suggested that a total of 16 differentially expressed genes (DEGs) were associated with overall survival (OS) and a 7-gene signature was constructed. The risk score of each patient was calculated using this signature, the median value of which was used to divide these patients into a high-risk group and a low-risk group. Compared with the low-risk group, the patients in the high-risk group had a poor prognosis. The risk score was an independent predictor for OS through multivariate Cox regression analysis. Then, unsupervised learning was used to verify the validity of this 7-gene signature. A nomogram by further integrating clinical information and the prognostic signature was utilized to predict prognostic risk and individual OS. Functional enrichment analyses demonstrated that these DEGs were enriched in the pathways of cell proliferation and mitosis, and the immune cell infiltration was significantly different between the two risk groups. In summary, a novel angiogenesis-related genes signature could be used to predict the prognosis of HCC and for targeted therapy.

Esophageal cancer (EC) represents a human malignancy, diagnosed often at the advanced stage of cancer and resulting in high morbidity and mortality. The development of precision medicine allows for the identification of more personalized therapeutic strategies to improve cancer treatment. By implanting primary cancer tissues into immunodeficient mice for expansion, patient-derived xenograft (PDX) models largely maintain similar histological and genetic representations naturally found in patients' tumor cells. PDX models of EC (EC-PDX) provide fine platforms to investigate the tumor microenvironment, tumor genomic heterogeneity, and tumor response to chemoradiotherapy, which are necessary for new drug discovery to combat EC in addition to optimization of current therapeutic strategies for EC. In this review, we summarize the methods used for establishing EC-PDX models and investigate the utilities of EC-PDX in screening predictive biomarkers and potential therapeutic targets. The challenge of this promising research tool is also discussed.

Osteosarcoma is the most common primary malignant bone tumor that mostly affects young people's health. The prognosis of patients with unresectable or recurrent osteosarcoma still remains dismal. Based on gene integration analysis from GEO and TARGET databases by R language, the differentially expressed genes of osteosarcoma patients were identified. Biological molecular function analysis indicated that these genes were importantly enriched in the process of cell adhesion molecule binding. Gene significance highly-related to clinical traits of osteosarcoma was found by weighted gene co-expression network analysis. Additionally, receiver operating characteristic curve analysis was conducted to find prognostic markers in LASSO Cox regression model. Two candidate biomarkers, ANXA1 and PSAT1, for the prognosis of osteosarcoma were detected separately on the basis of WGCNA and LASSO model. Of note, their expression profiles were interrelated with an important therapeutic target HSPA5. In vitro pharmaceutical experiments were performed to explore the biological role and prognostic benefit of candidates. Suppression of HSPA5 effectively upregulated ANXA1 and inhibited PSAT1, resulting in osteosarcoma cell proliferation arrest and apoptosis. These findings suggest that HSPA5 serves as a core molecule for osteosarcoma therapy due to its bidirectional regulation of candidate prognostic biomarkers ANXA1 and PSAT1.

Diffuse gliomas are the most common malignant brain tumors, and immune checkpoint inhibitors have limited therapeutic effects against this cancer. Three oncogenic pathways are altered in diffuse gliomas: the RTK/Ras/PI3K/AKT signaling, TP53, and RB pathways. Although these pathways may affect the tumor immune microenvironment, their association with immunotherapy biomarkers remains unclear.

Pancreatic carcinoma (PC) is a severe disease associated with high mortality. Although strategies for cancer therapy have made great progress, outcomes of pancreatic carcinoma patients remain extremely poor. Therefore, it is urgent to find novel biomarkers and therapeutic targets. To identify biomarkers for early diagnosis and therapy, three mRNA microarray datasets and two miRNA datasets were selected, and combinative analysis was performed by GEO2R. Functional and pathway enrichment analysis were performed using DAVID database. MiRTarBase, miRWalk and Diana Tools were used to get key genes. TCGA, HPA and western blotting were used to verify diagnostic and prognostic value of key genes. By integrating mRNA and miRNA expression profiles, we identified 114 differentially expressed genes and 114 differentially expressed miRNAs, respectively. Then, three overlapping key genes, RUNX2, LAMC2 and FBXO32, were found. Their protein levels in pancreatic tissue from PC patients and normal people were analyzed by immunohistochemical staining and western blotting. RUNX2 showed a potential property to identify PC. Aberrant over-expression of LAMC2 was associated with poor prognosis of PC patients, tumor status and subtypes. In summary, our current study identified that RUNX2 and LAMC2 may be promising targets for early diagnosis and therapy of PC patients.

Growing studies have reported that pseudogenes play key roles in multiple human cancers. However, expression and roles of pseudogenes in renal cell carcinoma remains absent.

Colorectal cancer (CRC) accounts for the highest fatality rate among all malignant tumors. Immunotherapy has shown great promise in management of many malignant tumors, necessitating the need to explore its role in CRC.

MYC overexpression is a common phenomenon in gastric carcinogenesis. In this study, we identified genes differentially expressed with a downregulated profile in gastric cancer (GC) cell lines with silenced MYC. The TTLL12, CDKN3, CDC16, PTPRA, MZT2B, UBE2T genes were validated using qRT-PCR, western blot and immunohistochemistry in tissues of 213 patients with diffuse and intestinal GC. We identified high levels of TTLL12, MZT2B, CDC16, UBE2T, associated with early and advanced stages, lymph nodes, distant metastases and risk factors such as H. pylori. Our results show that in the diffuse GC the overexpression of CDC16 and UBE2T indicate markers of poor prognosis higher than TTLL12. That is, patients with overexpression of these two genes live less than patients with overexpression of TTLL12. In the intestinal GC, patients who overexpressed CDC16 had a significantly lower survival rate than patients who overexpressed MZT2B and UBE2T, indicating in our data a worse prognostic value of CDC16 compared to the other two genes. PTPRA and CDKN3 proved to be important for assessing tumor progression in the early and advanced stages. In summary, in this study, we identified diagnostic and prognostic biomarkers of GC under the control of MYC, related to the cell cycle and the neoplastic process.

Breast cancer is an invasive disease with complex molecular mechanisms. Prognosis-related biomarkers are still urgently needed to predict outcomes of breast cancer patients.

Long noncoding RNAs (lncRNAs), such as LINC00462, HOTAIR, and MALAT1, are significantly upregulated in hepatocellular carcinoma (HCC) tissues. However, lncRNA expression in the serum of HCC patients is still unclear. To identify candidate lncRNAs for HCC diagnosis, we purified exosomal total RNA from the serum of healthy volunteers (controls) and hepatitis, cirrhosis, and HCC patients. To assess the function of lncRNAs, small interfering RNAs and overexpression vectors were designed and cell viability and cell apoptosis assays conducted. The exosomes of the control group had a larger number of lncRNAs with a high amount of alternative splicing compared to hepatic disease patients. qPCR assays showed that lnc-FAM72D-3, lnc-GPR89B-15, lncZEB2-19, and lnc-EPC1-4 are differentially expressed in HCC. Furthermore, the expression level of lnc-EPC1-4 correlated with age. While the expression levels of lnc-GPR89B-15 and lnc-EPC1-4 correlated with serum alpha-fetoprotein level. lnc-FAM72D-3 knockdown decreased cell viability and promoted cell apoptosis, indicating that lnc-FAM72D-3 functions as an oncogene in HCC. In contrast, lnc-EPC1-4 overexpression inhibited cell proliferation and induced cell apoptosis, indicating that it functions as a tumor suppressor gene. Collectively, these findings show that lnc-FAM72D-3 and lnc-EPC1-4 play a novel role that might contribute to hepatocarcinogenesis and identify potential candidate biomarkers for HCC diagnosis.

Clear cell renal cell carcinoma (ccRCC) is an extremely common kind of kidney cancer in adults. Immunotherapy and targeted therapy are particularly effective at treating ccRCC. In this study, weighted gene co-expression network analysis and a deconvolution algorithm that quantifies the cellular composition of immune cells were used to analyze ccRCC expression data from the Gene Expression Omnibus database, and identify modules related to CD8+ T cells. Ten hub genes (LCK, CD2, CD3D, CD3G, IRF1, IFNG, CCR5, CD8A, CCL5, and CXCL9) were identified by co-expression network and protein-protein interactions network analysis. Datasets obtained from The Cancer Genome Atlas were analyzed and the data revealed that the hub genes were meaningfully up-regulated in tumor tissues and correlated with promotion of tumor progression. After Kaplan-Meier analysis and Oncomine meta-analysis, CCL5 was selected as a prognostic biomarker. Finally, the experimental results show that reduced expression of CCL5 decreased cell proliferation and invasion in the ccRCC cell line. Various analyses were performed and verified, CCL5 is a potential biomarker and therapeutic target which related to CD8+ T cell infiltration in ccRCC.

Cervical squamous cell carcinoma (CSCC) is one of the most commonly occurring gynecological malignancies. Because CSCC is a biologically heterogeneous disease, its prognosis varies. Therefore, identifying prognostic biomarkers that reflect its biological heterogeneity could lead to better interventions for patients with a poor prognosis. This study used the ESTIMATE algorithm to identify immune related prognostic genes within the tumor microenvironment of CSCC. The results revealed that high immune scores were associated with better overall survival (P = 0.029). Differential expression analysis revealed 384 intersection genes influencing both the immune and stromal scores. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed the 384 intersection genes to be mainly enriched for T cell activation, the region of the membrane, carbohydrate binding, and cytokine-cytokine receptor interaction. Among them, 149 immune genes were predictive of overall survival in CSCC. These findings provide a more comprehensive understanding of immune genes within the tumor microenvironment as well as a list of immune genes prognostic in CSCC.

The period (PER) and cryptochrome (CRY) families play critical roles in circadian rhythms. The imbalance of circadian factors may lead to the occurrence of cancer. Expressions of PER and CRY family members decrease in various cancers. Nevertheless, expression levels, genetic variations, and molecular mechanisms of PER and CRY family members in lung adenocarcinoma (LUAD) and their correlations with prognoses and immune infiltration in LUAD patients are still unclear. In this study, to identify their biological functions in LUAD development, comprehensive high-throughput techniques were applied to analyze the relationships of expressions of PER and CRY family members with genetic variations, molecular mechanisms, and immune infiltration. The present results showed that transcription levels of PER1 and CRY2 in LUAD were significantly downregulated. High expression levels of PER2, PER3, CRY1, and CRY2 indicated longer overall survival. Some cancer signaling pathways were related to PER and CRY family members, such as cell-cycle, histidine metabolism, and progesterone-mediated oocyte maturation pathways. Expressions of PER and CRY family members significantly affected the infiltration of different immune cells. In conclusion, our findings may help better understand the molecular basis of LUAD, and provide new perspectives of PER and CRY family members as novel biomarkers for LUAD.

Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to tumor development and metastasis. The aim of this study was to develop an anoikis-based stratified model, and a multivariable-based nomogram for guiding clinical therapy for LUAD. Through differentially expressed analysis, univariate Cox, LASSO Cox regression, and random forest algorithm analysis, we established a 4 anoikis-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of LUAD patients in the TCGA and GEO databases, respectively. The low and high-risk score LUAD patients stratified by the model showed different tumor mutation burden, tumor microenvironment, gemcitabine sensitivity and immune checkpoint expressions. Through immunohistochemical analysis of clinical LUAD samples, we found that the 4 anoikis-related genes (PLK1, SLC2A1, ANGPTL4, CDKN3) were highly expressed in the tumor samples from clinical LUAD patients, and knockdown of these genes in LUAD cells by transfection with small interfering RNAs significantly inhibited LUAD cell proliferation and migration, and promoted anoikis. In conclusion, we developed an anoikis-based stratified model and a multivariable-based nomogram of LUAD, which could predict the survival of LUAD patients and guide clinical treatment.