Tumour mutation burden and infiltrating immune cell subtypes influenced the breast cancer prognosis.

Background: Most of its issues are still undecided on the relationship between tumour mutation burden (TMB) and immune-related genes in the breast cancer. This study explores their relationship based on gene mutation and transcription data in The Cancer Genome Atlas (TCGA) database, and the effects of immune cells in TMB and tumour microenvironments on prognosis of breast cancer patients. Methods: Cases were divided into low-TMB and high-TMB subgroups. Differentially expressed immune-related genes were identified in different TMB subgroups, and patient prognosis was predicted by gene function enrichment analysis, invasive immune cells and different clinical pathological features were compared among different TMB subgroups. Results: A total of 986 mutation data from breast cancer patients were obtained. Compared with low-TMB group, the survival period of high-TMB group was relatively longer. A total of 337 differential expression genes were identified in this study. Of these genes, seven differentially expressed immune-related genes were associated with prognosis. In the high-TMB group, activated CD4+ memory T cells and other cells had high expression, the expression ratio of memory B cells and other cells in low-TMB group was high. Conclusions: TMB-related immunological infiltration characteristics showed meaningful value for prognosis prediction for breast cancer patients. Differentially expressed immune-related genes in TMB subgroups provide important information on the survival prediction.

Comprehensive Bioinformatic Investigation of TP53 Dysregulation in Diverse Cancer Landscapes.

P53 overexpression plays a critical role in cancer pathogenesis by disrupting the intricate regulation of cellular proliferation. Despite its firmly established function as a tumor suppressor, elevated p53 levels can paradoxically contribute to tumorigenesis, influenced by factors such as exposure to carcinogens, genetic mutations, and viral infections. This phenomenon is observed across a spectrum of cancer types, including bladder (BLCA), ovarian (OV), cervical (CESC), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), diffuse large B-cell lymphoma (DLBC), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and uterine corpus endometrial carcinoma (UCEC). This broad spectrum of cancers is often associated with increased aggressiveness and recurrence risk. Effective therapeutic strategies targeting tumors with p53 overexpression require a comprehensive approach, integrating targeted interventions aimed at the p53 gene with conventional modalities such as chemotherapy, radiation therapy, and targeted drugs. In this extensive study, we present a detailed analysis shedding light on the multifaceted role of TP53 across various cancers, with a specific emphasis on its impact on disease-free survival (DFS). Leveraging data from the TCGA database and the GTEx dataset, along with GEPIA, UALCAN, and STRING, we identify TP53 overexpression as a significant prognostic indicator, notably pronounced in prostate adenocarcinoma (PRAD). Supported by compelling statistical significance (p < 0.05), our analysis reveals the distinct influence of TP53 overexpression on DFS outcomes in PRAD. Additionally, graphical representations of overall survival (OS) underscore the notable disparity in OS duration between tumors exhibiting elevated TP53 expression (depicted by the red line) and those with lower TP53 levels (indicated by the blue line). The hazard ratio (HR) further emphasizes the profound impact of TP53 on overall survival. Moreover, our investigation delves into the intricate TP53 protein network, unveiling genes exhibiting robust positive correlations with TP53 expression across 13 out of 27 cancers. Remarkably, negative correlations emerge with pivotal tumor suppressor genes. This network analysis elucidates critical proteins, including SIRT1, CBP, p300, ATM, DAXX, HSP 90-alpha, Mdm2, RPA70, 14-3-3 protein sigma, p53, and ASPP2, pivotal in regulating cell cycle dynamics, DNA damage response, and transcriptional regulation. Our study underscores the paramount importance of deciphering TP53 dynamics in cancer, providing invaluable insights into tumor behavior, disease-free survival, and potential therapeutic avenues.

Identification of methylation driver genes for predicting the prognosis of pancreatic cancer patients based on whole-genome DNA methylation sequencing technology.

This study was based on the use of whole-genome DNA methylation sequencing technology to identify DNA methylation biomarkers in tumor tissue that can predict the prognosis of patients with pancreatic cancer (PCa). TCGA database was used to download PCa-related DNA methylation and transcriptome atlas data. Methylation driver genes (MDGs) were obtained using the MethylMix package. Candidate genes in the MDGs were screened for prognostic relevance to PCa patients by univariate Cox analysis, and a prognostic risk score model was constructed based on the key MDGs. ROC curve analysis was performed to assess the accuracy of the prognostic risk score model. The effects of PIK3C2B knockdown on malignant phenotypes of PCa cells were investigated in vitro. A total of 2737 differentially expressed genes were identified, with 649 upregulated and 2088 downregulated, using 178 PCa samples and 171 normal samples. MethylMix was employed to identify 71 methylation-driven genes (47 hypermethylated and 24 hypomethylated) from 185 TCGA PCa samples. Cox regression analyses identified eight key MDGs (LEF1, ZIC3, VAV3, TBC1D4, FABP4, MAP3K5, PIK3C2B, IGF1R) associated with prognosis in PCa. Seven of them were hypermethylated, while PIK3C2B was hypomethylated. A prognostic risk prediction model was constructed based on the eight key MDGs, which was found to accurately predict the prognosis of PCa patients. In addition, the malignant phenotypes of PANC-1 cells were decreased after the knockdown of PIK3C2B. Therefore, the prognostic risk prediction model based on the eight key MDGs could accurately predict the prognosis of PCa patients.

[Expression and prognostic significance of KAP1 gene in malignant pleural mesothelioma].

Objective: To explore the expression of KAP1 (KRAB-associated protein 1, KAP1) in Malignant pleural mesothelioma (MPM) based on the cancer genome atlas (TCGA) and clinical trials. And elucidate the correlation between the expression of KAP1 and the clinical pathological parameters of patients with MPM and its prognosis. Methods: In April 2022, Based on the second generation KAP1mRNA sequencing data and clinicopathological data of MPM patients downloaded from TCGA database, the correlation between KAP1mRNA expression and clinical parameters was analyzed, and the correlation between KAP1 protein expression and clinicopathological parameters and its prognostic value were analyzed based on Chuxiong data set cohort clinical samples. The expression of KAP1 mRNA in MPM samples and matched normal tumor adjacent tissues was detected by qRT-PCR, and the expression of KAP1 protein in MPM and normal pleural tissues was detected by immunohistochemistry and Westernblotting. To construct a Kaplan-Meier model to explore the effect of KAP1 expression on the prognosis of MPM patients, and to analyze the prognostic factors of MPM patients by Cox regression. Results: qRT-PCR and Western blotting detection showed that the expression levels of KAP1 gene in four different MPM cells (NCI-H28, NCI-H2052, NCI-H2452, and MTSO-211H) were significantly higher than those in normal pleural mesothelial cells Met-5A. qRT-PCR, Western blotting and IHC results demonstrated that the mRNA and protein expression levels of KAP1 in MPM tissues was significantly higher than that in matching normal mesothelial tissues, and the expression level of KAP1 protein was correlated with TP 53 protein expression levels and serum CEA levels (P<0.05) . The mRNA expression level was significantly correlated with the prognosis, The overall survival time of mesothelioma patients with high KAP1mRNA expression was significantly shorter (HR=3.7, Logrank P<0.001) . Tumor type, age and the mRNA expression were related to the prognosis of MPM patients (P<0.05) . Multivariate analysis showed that tumor type and KAP1 mRNA expression level were independent prognostic factors of MPM patients (P<0.05) . Conclusion: In this study, TCGA database and Chuxiong cohort experiment samples were used to collect the relevant information of KAP1 expression in malignant melanoma tissues. It was confirmed that KAP1 is highly expressed in MPM tissues. The mRNA expression level and pathological type are correlated with the prognosis of patients.

STRN3 promotes tumour growth in hepatocellular carcinoma by inhibiting the hippo pathway.

HCC is a globally high-incidence malignant tumour, and its pathogenesis is still unclear. Recently, STRN3 has been found to be elevated in various tumours, but its expression and biological functions in HCC have not been studied. In the study, clinical correlation analysis was performed on 371 liver cancer patients from TCGA database and liver cancer tissues and normal tissues from the GEO database. qRT-PCR and western blotting were used to detect relevant proteins in cells, and CCK8 and colony formation experiments were performed to analyse cell proliferation ability. Transwell and wound healing experiments were performed to detect cell invasion ability, and flow cytometry was used to detect cell apoptosis. Single-cell sequencing data and multiple immunofluorescence were analysed for the expression abundance and distribution of certain proteins. Immunohistochemistry was used to assess the expression of STRN3 in patients' tumour and adjacent non-cancerous tissues. The results indicated STRN3 was highly expressed in liver tumour tissues and was closely associated with poor prognosis. Knockdown of STRN3 could significantly inhibit cell proliferation and migration ability. At the same time, we found that STRN3 could inhibit the Hippo pathway and promote the entry of YAP protein into the nucleus. Our study first found that STRN3 could promote tumour growth by inhibiting the Hippo pathway. The study of STRN3 can promote the understanding and treatment of the occurrence and development of HCC.

C-type lectin 2D (CLEC2D) is upregulated in clear cell renal cell carcinoma (ccRCC) tissues and predicts poor prognosis.

Clear cell renal cell carcinoma (ccRCC) is known as the most common type of renal cancer. Recently, a series of advances have been made in targeted therapy for ccRCC. To combat this highly metastatic tumor, novel therapeutic targets still need to be developed. C-type lectins (CLECs) contain a characteristic C-type lectin-like domain and affect several physiological functions. The effects of C-type lectin 2D (CLEC2D) on cancer progression have been revealed in several types of cancers; however, its expression in ccRCC tissues, and the possible effects on the progression and metastasis of ccRCC, are still unclear. Herein, we found the high mRNA and protein levels of CLEC2D in ccRCC tissues. We further found that CLEC2D expression was correlated with the prognosis of ccRCC patients and correlated with the tumor size (p = 0.019*) of patients. In addition, CLEC2D affected tumor immune infiltration, confirmed by the further analysis. CLEC2D knockdown suppressed the proliferation of ccRCC cells in vitro and restrained ccRCC tumor growth and immune infiltration in mice. Therefore, we believe that CLEC2D has the potential to serve as a promising ccRCC therapeutic target.

Predictive value of immediate early response 5 like (IER5L) in the prognosis and immune checkpoint blockade therapy of non-small cell lung cancer patients.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a malignancy with high mortality. Immediate early response 5 like (IER5L) has been found to associate with worse prognosis in colorectal cancer patients. However, its role in the prognosis prediction of NSCLC has remained largely unknown. METHODS: The IER5L expression in NSCLC and normal tissues was analyzed in two public cohorts: TCGA-LUAD-LUSC and GSE159857. Additionally, functional enrichment, survival analysis, CIBERSORT and tumor mutation burden (TMB) were investigated between low- and high-IER5L level groups. The in vitro IER5L mRNA and protein levels were determined using RT-qPCR and western blot, respectively. RESULTS: The data from TCGA-LUAD-LUSC and GSE159857 cohorts showed a high IER5L mRNA expression in NSCLC tissue samples compared to normal controls. The increased expression of IER5L in NSCLC cells were also validated by RT-qPCR and western blot analysis. Additionally, NSCLC patients with high-IER5L level had significantly worse prognosis and IER5L could be used as an independent prognostic factor for NSCLC patients. Meanwhile, patients in the high-IER5L group had higher TMB level. IER5L expression was negatively correlated with the proportion of Monocytes and T cells CD4 memory resting, and was positively related to the proportion of Tregs and M0 macrophages in tumor tissues. Besides, transcription factors TFAP4 and ZNF692 may bind to the promoter region of IER5L, and then modulate IER5L gene transcription, thereby affecting IER5L gene expression. Furthermore, GSEA results showed that IER5L gene was closely related to MAPK, PI3K-Akt, NF-kappaB signaling pathways in NSCLC. CONCLUSION: Collectively, high IER5L expression may be a promising unfavorable prognostic biomarker and therapeutic target for NSCLC patients.

NAD+ Metabolism-Related Gene Profile Can Be a Relevant Source of Squamous Cell Carcinoma Biomarkers.

Poor survival rates of squamous cell carcinomas (SCCs) are associated with high recurrence, metastasis, and late diagnosis, due in part to a limited number of reliable biomarkers. Thus, the identification of signatures improving the diagnosis of different SCC types is mandatory. Considering the relevant role of NAD+ metabolism in SCC chemoprevention and therapy, the study aimed at identifying new biomarkers based on NAD+ metabolism-related gene (NMRG) expression. Gene expression of 18 NMRGs and clinical-pathological information for patients with head and neck SCC (HNSCC), lung SCC (LuSCC), and cervix SCC (CeSCC) from The Cancer Genome Atlas (TCGA) were analyzed by several bioinformatic tools. We identified a 16-NMRG profile discriminating 3 SCCs from 3 non-correlated tumors. We found several genes for HNSCC, LuSCC, and CeSCC with high diagnostic power. Notably, three NMRGs were SCC-type specific biomarkers. Furthermore, specific signatures displayed high diagnostic power for several clinical-pathological characteristics. Analyzing tumor-infiltrating immune cell profiles and PD-1/PD-L1 levels, we found that NMRG expression was associated with suppressive immune microenvironment mainly in HNSCC. Finally, the evaluation of patient survival identified specific genes for HNSCC, LuSCC, and CeSCC with potential prognostic power. Therefore, our analyses indicate NAD+ metabolism as an important source of SCC biomarkers and potential therapeutic targets.

A comparison analysis of the somatic mutations in early-onset gastric cancer and traditional gastric cancer.

BACKGROUND: Early onset gastric cancer (EOGC) has been on the rise in recent years and differs slightly in pathology from traditional gastric cancer (TGC). Somatic mutations have an essential role in the development of gastric cancer. We aimed to investigate these two types of gastric cancers at the level of somatic mutations and to further understanding of gastric cancer development. METHODS: Somatic mutation, copy number variation (CNV), and clinical information were obtained from TCGA and UCSC Xena. Samples were divided into EOGC (< 50 years old, N = 28) and TGC (≥ 50 years old, N = 395) groups based on age. R packages "maftools" and "sigminer" were used to identify mutation signatures, while CNV information was processed using GISTIC2.0. RESULTS: CDH1(21 %, P = 0.030) and ARID1A (28 %, P = 0.014) were more common in EOGC and TGC, respectively. The mutation frequency of ARID1A increased with age, while the opposite was true for CDH1. Sex, Lauren classifications, tumor mutation burden levels, mutation status of TP53, MUC6, NIPBL, KRAS, and copy number variation of the WOOX can affect the activity of the mutant signature. CONCLUSIONS: Early-onset gastric cancer and traditional gastric cancer have distinct somatic mutation signatures, each with its own relatively specific high-frequency mutated genes, and the gene's mutation frequency correlates with age. Several clinical factors and genetic status affect the activity of some mutational features in gastric cancer in both groups.

A prognostic model based on tumor microenvironment and immune cell in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the second leading cause of cancer-related death. Immunotherapy is one of the new options for cancer treatment. This study aimed to develop an immune-related signature associated with CRC. METHODS: We performed differential analysis to screen out the differentially expressed genes (DEGs) of The Cancer Genome Atlas-Colorectal Cancer (TCGA-CRC) datasets. Weighted gene co-expression network analysis (WGCNA) was performed to obtain the key module genes associated with differential immune cells. The candidate genes were obtained through overlapping key DEGs and key module genes. The univariate and multivariate Cox regression analyses were adopted to build a CRC prognostic signature. We further conducted immune feature estimation and chemotherapy analysis between two risk subgroups. Finally, we verified the expression of immune-related prognostic genes at the transcriptional level. RESULTS: A total of 61 candidate genes were obtained by overlapping key DEGs and key module genes associated with differential immune cells. Then, an immune-related prognostic signature was built based on the three prognostic genes (HAMP, ADAM8, and CD1B). The independent prognostic analysis suggested that age, stage, and RiskScore could be used as independent prognostic factors. Further, we found significantly higher expression of three prognostic genes in the CRC group compared with the normal group. Finally, real-time polymerase chain reaction verified the expression of three genes in patients with CRC. CONCLUSION: The prognostic signature comprising HAMP, ADAM8, and CD1B based on immune cells was established, providing a theoretical basis and reference value for the research of CRC.

Expression and Clinical Significance of MIS18BP1 in Bladder Cancer Tissues / 肿瘤防治研究

Objective To explore the expression, correlation with clinicopathologic parameters, and clinical significance of MIS18 binding protein 1 (MIS18BP1) in bladder cancer. Methods TCGA and GEO databases were used to analyze the mRNA expression of MIS18BP1 in tumors and controls, and the results were verified via qRT-PCR. UALCAN online database was utilized in the analysis of the expression of MIS18BP1 and its correlation with clinicopathological parameters and the degree of immune cell infiltration. Immunohistochemistry was employed to analyze the expression of MIS18BP1 in bladder cancer and its relationship with clinicopathological features. The ROC curve was applied to evaluate the diagnostic value of MIS18BP1 mRNA in bladder cancer. Results Bioinformatics analysis and qRT-PCR results revealed the increased expression of MIS18BP1 mRNA in bladder cancer compared with that in the control group (P<0.05). Immunohistochemistry unveiled the significantly high positive rate of MIS18BP1 protein in bladder cancer (P<0.05) and its correlation with the clinical stage of tumors, depth of invasion, and lymph node metastasis (P<0.05). The immune infiltration analysis showed the association of MIS18BP1 with immune cell infiltration in bladder cancer. Conclusion The increased expression level of MIS18BP1 gene and protein in bladder cancer may regulate the development of bladder cancer by influencing immune cell infiltration.

Analysis and Prediction of Significant Genes in Gastric Cancer Based on TCGA Database.

OBJECTIVE: Use TCGA data to screen the significantly expressed genes in gastric cancer,then analyze the biological functions of characteristic genes.To identify potential targets for the diagnosis, prognosis and therapeutic monitoring of gastric cancer. METHODS: Download the high-throughput gastric cancer patient tissue mRNA expression data from the TCGA database, and used the edgeR software package to perform gene differences using the Rstudio software according to the |logFC|>1 and p<0.05 standards analysis, then performed enrichment analysis and constructed protein interaction network of the differently expressed genes to find the significant genes.Finally,analyzed the relationship between significant genes and gastric cancer patient prognosis. RESULTS: The RNA-seq expression data of 375 cases of gastric cancer and 32 adjacent tissues were obtained from the TCGA database. The differential analysis yielded 4320 differential genes, of which 2718 were highly expressed and 1602 were low expressed. Through enrichment analysis, it is found that the differential genes are mainly related to the neural active ligand-receptor interaction, calcium signaling pathway, Protein digestion and absorption, chemical carcinogenesis, and cytochrome P450 metabolism of foreign compounds. Further survival analysis screened out the five significant genes of ALB, AFP, IGFBP1, APOH, and TF are related to the prognosis of gastric cancer. CONCLUSION: The five significant genes screened by TCGA data may be related to the prognosis of gastric cancer and are expected to become prognostic biomarkers.

Transcription factor LHX9 (LIM Homeobox 9) enhances pyruvate kinase PKM2 activity to induce glycolytic metabolic reprogramming in cancer stem cells, promoting gastric cancer progression.

BACKGROUND: Glycolytic metabolic reprogramming is a phenomenon in which cells undergo altered metabolic patterns during malignant transformation, mainly involving various aspects of glycolysis, electron transport chain, oxidative phosphorylation, and pentose phosphate pathway. This reprogramming phenomenon can be used as one of the markers of tumorigenesis and development. Pyruvate kinase is the third rate-limiting enzyme in the sugar metabolism process by specifically catalyzing the irreversible conversion of PEP to pyruvate. PURPOSE: This study aimed to reveal the critical mediator(s) that regulate glycolytic metabolism reprogramming in gastric cancer and their underlying molecular mechanism and then explore the molecular mechanisms by which LHX9 may be involved in regulating gastric cancer (GC) progression. METHODS: Firstly, we downloaded the GC and glycolysis-related microarray datasets from TCGA and MSigDB databases and took the intersection to screen out the transcription factor LHX9 that regulates GC glycolytic metabolic reprogramming. Software packages were used for differential analysis, single gene predictive analysis, and Venn diagram. In addition, an enrichment analysis of the glycolytic pathway was performed. Immunohistochemical staining was performed for LHX9 and PKM2 protein expression in 90 GC patients, and the association between their expressions was evaluated by Spearman's correlation coefficient method. Three human GC cell lines (AGS, NCI-N87, HGC-27) were selected for in vitro experimental validation. Flow cytometry was utilized to determine the stem cell marker CD44 expression status in GCSCs. A sphere formation assay was performed to evaluate the sphere-forming capabilities of GCSCs. In addition, RT-qPCR and Western blot experiments were employed to investigate the tumor stem cell markers OCT4 and SOX2 expression levels in GCSCs. Furthermore, a lentiviral expression vector was constructed to assess the impact of downregulating LHX9 or PKM2 on the glycolytic metabolic reprogramming of GCSCs. The proliferation, migration, and invasion of GCSCs were then detected by CCK-8, EdU, and Transwell assays. Subsequently, the mutual binding of LHX9 and PKM2 was verified using chromatin immunoprecipitation and dual luciferase reporter genes. In vivo experiments were verified by establishing a subcutaneous transplantation tumor model in nude mice, observing the size and volume of tumors in vivo in nude mice, and obtaining fresh tissues for subsequent experiments. RESULTS: Bioinformatics analysis revealed that LHX9 might be involved in the occurrence and development of GC through regulating glycolytic metabolism. High LHX9 expression could be used as a reference marker for prognosis prediction of GC patients. Clinical tissue assays revealed that LHX9 and PKM2 were highly expressed in GC tissues. Meanwhile, GC tissues also highly expressed glycolysis-associated protein GLUT1 and tumor cell stemness marker CD44. In vitro cellular assays showed that LHX9 could enhance its activity and induce glycolytic metabolic reprogramming in GCSCs through direct binding to PKM2. In addition, the knockdown of LHX9 inhibited PKM2 activity and glycolytic metabolic reprogramming and suppressed the proliferation, migration, and invasive ability of GCSCs. In vivo animal experiments further confirmed that the knockdown of LHX9 could reduce the tumorigenic ability of GCSCs in nude mice by inhibiting PKM2 activity and glycolytic metabolic reprogramming. CONCLUSION: The findings suggest that both LHX9 and PKM2 are highly expressed in GCs, and LHX9 may induce the reprogramming of glycolytic metabolism through transcriptional activation of PKM2, enhancing the malignant biological properties of GCSCs and ultimately promoting GC progression.

Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database.

BACKGROUND: Researches have manifested that the disorder of iron metabolism is participated in Gastric cancer (GC), but whether iron metabolism-relevant genes (IMRGs) is related to the survival outcome of GC remain unknown. METHODS: Eleven tumor as well as nine adjacent normal tissues from GC patients were underwent mRNA sequencing, and the The Cancer Genome Atlas Stomach Cancer (TCGA-STAD) datasets were acquired from the TCGA database. Cox analyses and least absolute shrinkage and selection operator (LASSO) regression were applied to build a IMRGs signature. The relationship between signature genes and the infiltration profiling of 24 immune cells were investigated using single-sample GSEA (ssGSEA). Meanwhile, the potential biological significance, genes that act synergistically with signature genes, and the upstream regulatory targets were predicted. Finally, the abundance of the signature genes were measured via the quantitative real-time PCR (qRT-PCR). RESULTS: A IMRGs signature was constructed according to the expression and corresponding coefficient of DOHH, P4HA3 and MMP1 (The Schoenfeld individual test showed risk score was not significant with P values = 0.83). The prognostic outcome of patients in the high-risk group was terrible (p < 0.05). Receiver operating characteristic (ROC) curves confirmed that the IMRGs signature presented good efficiency for predicting GC prognosis (AUC > 0.6). The nomogram was performed well for clinical utilize (C-index = 0.60), and the MMP1 expression significantly increased in the cohorts at age > 60 and Stage II-IV (p < 0.05). The positive correlation of P4HA3 and MMP1 expression as well as the negative correlation of DOHH expression with risk score (p < 0.0001) and worse prognosis (p < 0.05) were detected as well. Furthermore, 11 differential immune cells were associated with these signature genes (most p < 0.01). Finally, qRT-PCR revealed that the abundance of DOHH, P4HA3 and MMP1 were high in tumor cases, indicating the complex mechanism between the high expression of DOHH as a protective factor and the high expression of P4HA3 and MMP1 as the risk factors in the development of GC. CONCLUSION: An iron metabolism-related signature was constructed and has significant values for foretelling the OS of GC.

DNA cytosine deamination is associated with recurrent Somatic Copy Number Alterations in stomach adenocarcinoma.

Stomach Adenocarcinoma (STAD) is a leading cause of death worldwide. Somatic Copy Number Alterations (SCNAs), which result in Homologous recombination (HR) deficiency in double-strand break repair, are associated with the progression of STAD. However, the landscape of frequent breakpoints of SCNAs (hotspots) and their functional impacts remain poorly understood. In this study, we aimed to explore the frequency and impact of these hotspots in 332 STAD patients and 1,043 cancer cells using data from the Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). We studied the rates of DSB (Double-Strand Breaks) loci in STAD patients by employing the Non-Homogeneous Poisson Distribution (λ), based on which we identified 145 DSB-hotspots with genes affected. We further verified DNA cytosine deamination as a critical process underlying the burden of DSB in STAD. Finally, we illustrated the clinical impact of the significant biological processes. Our findings highlighted the relationship between DNA cytosine deamination and SCNA in cancer was associated with recurrent Somatic Copy Number Alterations in STAD.

Overexpression of XRCC1 is Associated with Poor Survival in Patients with Head and Neck Squamous Carcinoma and Has Potential to Be Used as Targeted Therapy by Synthetic Lethality.

Background: Head neck squamous cell carcinoma (HNSC) is globally prevalent cancer attributed to tobacco habit. Despite the significant advances in early diagnosis and treatment of HNSC chemo-radio resistance are routinely observed in patients. Aberrant DNA repair mechanisms mainly microhomology mediated DNA end joining (MMEJ) pathway causing deleterious mutations and is implicated in treatment resistance. X-ray cross complimenting group 1 (XRCC1) has recently been shown to play an essential role in MMEJ making XRCC1 a potential therapeutic target to render tumors chemo-radiosensitive. This study analyzes the correlation between the expression level of XRCC1 gene with survival, regulation by miRNA and synthetic lethality partners in HNSCC. Materials and Methods: XRCC1 gene expression was evaluated in 520 HNSC patients and 44 of normal tissues using the UALCAN (TCGA) database and its correlation with survival outcome of HNSC patients was analyzed by Kaplan-Meier plot. Infiltration of immune cells in tumors was analyzed by "Tumor-Infiltrating Immune Estimation Resource (TIMER) and promoter methylation status of XRCC1 in samples was analysed by UALCAN. STRING was used to find gene interacting partners of XRCC1.  Results: XRCC1 was significantly overexpressed in primary tumor of HNSCC and significantly increased with tumor stages and grade and associated with poor survival rate. High XRCC1 expression in HNSC was positively correlated with infiltration level of B cells naïsve, CD4+ and macrophages. Conclusion: These results indicate that XRCC1 is a prognostic marker for predicting survival in HNSC patients. Understanding how XRCC1 leads to treatment resistance and modulate immune response can lead to development of targeted therapy.

The involvement of PDIA2 gene in the progression of renal cell carcinoma is potentially through regulation of JNK signaling pathway

Renal cell carcinoma (RCC) with poor prognosis and high incidence rate is a common malignant disease. Current therapies could bring little benefit for the patients with advanced-stage RCC. PDIA2 is an isomerase responsible for protein folding and its role in cancer including RCC is under investigation. In this study, we found that PDIA2 was expressed much higher in RCC tissues than the control but the methylation level of PDIA2 promoter was lower based on the TCGA data. Patients with higher PDIA2 expression exerted worse survival. In clinical specimen, PDIA2 expression was correlated to patients’ clinical factors such as TNM stage (I/II vs III/IV, p = 0.025) and tumor size (≤ 7 cm vs > 7 cm, p = 0.004). Moreover, K-M analysis showed that PDIA2 was associated with patients’ survival in RCC. PDIA2 was expressed much higher in cancer cells A498 than 786-O than that in 293 T cells. After PDIA2 was knocked down, cell proliferation, migration and invasion was potently inhibited. But cell apoptotic rate increased reversely. Furthermore, the efficacy of Sunitinib on RCC cells was strengthened after PDIA2 knockdown. In addition, knockdown of PDIA2 gene leaded to downregulation of levels of JNK1/2, phosphorylated JNK1/2, c-JUN, and Stat3. But this inhibition was partially released when JNK1/2 was overexpressed. In consistent, cell proliferation was also partially recovered. In summary, PDIA2 plays important role in progression of RCC and JNK signaling pathway might be regulated by PDIA2. This study suggests PDIA2 as a candidate target for therapy of RCC (AU)

A study on metabolic characteristics and metabolic markers of gastrointestinal tumors.

Tumor cells have significant heterogeneity in metabolism and are closely related to prognosis, gene mutation, and subtype. However, this association has not been demonstrated in reports of gastrointestinal tumors. In this study, we constructed four metabolic subtypes and identified four gene signatures using the expression data and clinical information of 252 metabolism-related genes from TCGA and NCBI databases for gastric adenocarcinoma (STAD) and colorectal cancer (COAD and READ). MC1 had the worst prognosis compared to other classifications. GSig1 was mainly related to drug metabolism and was the highest in MC1 with the worst prognosis, while the other subtypes were mainly related to glucose metabolism pathways. This difference also existed in other different malignant tumors. In addition, metabolic typing was associated with chemotherapeutic drug response and tumor heterogeneity, which indicated that monitoring metabolic typing could contribute to drug efficacy and gene-targeted therapy. In conclusion, we identified differences among subtypes in clinical characteristics such as prognosis and revealed the potential function of metabolic subtype in response to chemotherapeutic agents and oncogene mutations. This work highlighted the potential clinical meaning of metabolic subtype and characteristics in drug therapy and prognosis assessment of malignant tumors.

Expression analysis, clinical significance and potential function of PLXNB2 in acute myeloid leukaemia.

BACKGROUND: The overall survival (OS) rate of adult patients suffering from acute myeloid leukaemia (AML) remains unsatisfactory at less than 40%. Current risk stratification systems fail to provide accurate guidelines for precise treatment. Novel biomarkers for predicting prognosis are urgently needed. Plexin B2 (PLXNB2), a functional receptor of angiogenin (ANG), has been found to be aberrantly expressed in multitudinous tumours. We detected overexpression of PLXNB2 mRNA in AML via transcriptome microarray analysis. This study aims to explore the potential role of PLXNB2 as a biomarker of prognosis and a prospective target of AML. METHODS: qRT‒PCR was conducted to verify the expression of PLXNB2 mRNA in bone marrow mononuclear cells from AML patients. Immunohistochemical and immunofluorescence staining were performed and confirmed increased expression of PLXNB2 protein in AML bone marrow tissues. Data on PLXNB2 expression, prognosis and clinical features were accessed from multiple bioinformatic databases, including The Cancer Genome Atlas (TCGA). Genes coexpressed and correlated with PLXNB2 were identified and analysed in the TCGA AML cohort. Metascape was applied for functional and pathway enrichment analysis of genes related to PLXNB2. Small molecular agents and traditional Chinese medicines potentially targeting genes related to PLXNB2 were screened via the Connectivity Map, TCMSP and HIT databases. RESULTS: PLXNB2 mRNA and protein levels are higher in AML samples than in normal controls. Overexpression of PLXNB2 is associated with worse OS in AML. Patients with high PLXNB2 expression might benefit more from haematopoietic stem cell transplantation (HSCT) (indicated by prolonged OS) than those with only chemotherapy treatment. Differentially expressed genes between the high and low PLXNB2 expression groups were overlapped with PLXNB2-coexpressed genes, and genes that overlapped were enriched in immune functions, endothelial cell regulation and cell interaction gene sets, indicating the potential function of PLXNB2 in AML. A total of 36 hub genes were identified from the differentially expressed genes, and MRC1, IL10, CD163 and CCL22 had significant prognostic value for AML. Analysis of the connectivity map and traditional agents revealed that honokiol, morphines, triptolide and paeoniflorin could be potential treatment regimens. CONCLUSIONS: The overexpression of PLXNB2 is an adverse prognostic factor in adult AML patients and could be used as a potential biomarker. PLXNB2 might exert an oncogenic role by modulating immune functions, endothelial cell functions and cell interactions. AML patients with high PLXNB2 expression could benefit more from HSCT.

SOCS1 as a Biomarker Candidate for HPV Infection and Prognosis of Head and Neck Squamous Cell Carcinomas.

The pathogenesis of head and neck squamous cell carcinoma (HNSCC) is associated with human papillomavirus (HPV) infection. However, the molecular mechanisms underlying the interactions between HNSCC and HPV remain unclear. Bioinformatics was used to analyze the gene expression dataset of HPV-associated HNSCC based on the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) in HPV-positive and HPV-negative HNSCC were screened. Gene function enrichment, protein-protein interactions (PPI), survival analysis, and immune cell infiltration of DEGs were performed. Furthermore, the clinical data of HNSCC tissue samples were analyzed using immunohistochemistry. In total, 194 DEGs were identified. A PPI network was constructed and 10 hub genes (EREG, PLCG1, ERBB4, HBEGF, ZFP42, CBX6, NFKBIA, SOCS1, ATP2B2, and CEND1) were identified. Survival analysis indicated that low expression of SOCS1 was associated with worse overall survival. Immunohistochemistry demonstrated that SOCS1 expression was higher in HPV-negative HNSCC than in HPV-positive HNSCC, and there was a positive correlation between SOCS1 expression and patient survival. This study provides new information on biological targets that may be relevant to the molecular mechanisms underpinning the occurrence and development of HNSCC. SOCS1 may play an important role in the interaction between HPV and HNSCC and serve as a potential biomarker for future therapeutic targets.