Spindle assembly checkpoint MAD2 and CDC20 overexpressions and cell-in-cell formation in gastric cancer and its precursor lesions

Mechanisms and significance of entosis for tumour growth and progression

To date, numerous mechanisms have been identified in which one cell engulfs another, resulting in the creation of 'cell-in-cell' (CIC) structures, which subsequently cause cell death. One of the mechanisms of formation of these structures is entosis, which is presumably associated with possible carcinogenesis and tumour progression. The peculiarity of the process is that entotic cells themselves actively invade the host cell, and afterwards have several possible variants of fate. Entotic formations are structures where one cell is engulfed by another cell, creating a cell-in-cell structure. The nucleus of the outer cell has a crescent shape, while the inner cell is surrounded by a large entotic vacuole. These characteristics differentiate entosis from cell cannibalism. It's worth noting that entotic formations are not necessarily harmful and may even be beneficial in some cases. In this article we will consider the mechanism of entosis and variants of entotic cell death, and also put forward hypothesis about possible variants of participation of this process on the formation and progression of cancer. This article also presents our proposed classification of functional forms of entosis.

The potential role of CDC20 in tumorigenesis, cancer progression and therapy: A narrative review

The cell division cycle 20 homologue (CDC20) is known to regulate the cell cycle. Many studies have suggested that dysregulation of CDC20 is associated with various pathological processes in malignant solid tumors, including tumorigenesis, progression, chemoradiotherapy resistance, and poor prognosis, providing a biomarker for cancer diagnosis and prognosis. Some researchers have demonstrated that CDC20 also regulates apoptosis, immune microenvironment, and tumor angiogenesis. In this review, we have systematically summarized the biological functions of CDC20 in solid cancers. Furthermore, we briefly synthesized multiple medicines that inhibited CDC20. We anticipate that CDC20 will be a promising and effective biomarker and therapeutic target for the treatment of human cancer.

The positive feedback loop of MAD2L1/TYK2/STAT3 induces progression in B-cell acute lymphoblastic leukaemia

PURPOSE

Mitotic arrest deficient 2 like 1 (MAD2L1) has been extensively studied in several malignancies; however, its role in B-cell acute lymphoblastic leukaemia (B-ALL) remains unclear.

METHODS

The expression of MAD2L1 was evaluated by real-time quantitative polymerase chain reaction. The biological functions of MAD2L1 in B-ALL were explored through Cell Counting Kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine assay (EDU), transwell assay, flow cytometry and xenograft models. The Western blotting and co-immunoprecipitation were utilized to evaluate the interplay between MAD2L1 and the TYK2/STAT3 pathway. The luciferase reporter and chromatin immunoprecipitation (ChIP) assay were employed to identify interactions between STAT3 and MAD2L1.

RESULTS

We demonstrated that MAD2L1 was markedly upregulated in B-ALL, and its expression level not only correlated with the relapse and remission of the condition but also with a poor prognosis. MAD2L1 promoted the proliferation, migration and invasion of B-ALL cells in vitro and in vivo, whereas MAD2L1 knockdown had the opposite effects. Mechanistically, MAD2L1 induces the progression of B-ALL by activating the TYK2/STAT3 signaling pathway to phosphorylate. Interestingly, STAT3 induces the expression of MAD2L1 by binding directly to its promoter region, resulting in a positive-feedback loop of MAD2L1/TYK2/STAT3.

CONCLUSION

This study uncovered a reciprocal loop of MAD2L1/TYK2/STAT3, which contributed to the development of B-ALL. Therefore, MAD2L1 can be considered a potential diagnostic biomarker as well as a novel therapeutic target for B-ALL.

An innovative pyroptosis-related long-noncoding-RNA signature predicts the prognosis of gastric cancer via affecting immune cell infiltration landscape

Background: Gastric cancer (GC) is a worldwide popular malignant tumor. However, the survival rate of advanced GC remains low. Pyroptosis and long non-coding RNAs (lncRNAs) are important in cancer progression. Thus, we aimed to find out a pyroptosis-related lncRNAs (PRLs) signature and use it to build a practical risk model with the purpose to predict the prognosis of patients with GC. Methods: Univariate Cox regression analysis was used to identify PRLs linked to GC patient's prognosis. Subsequently, to construct a PRLs signature, the least absolute shrinkage and selection operator regression, and multivariate Cox regression analysis were used. Kaplan-Meier analysis, principal component analysis, and receiver operating characteristic curve analysis were performed to assess our novel lncRNA signature. The correlation between risk signature and clinicopathological features was also examined. Finally, the relationship of pyroptosis and immune cells were evaluated through the CIBERSORT tool and single-sample lncRNA set enrichment analysis (ssGSEA). Results: A PRLs signature comprising eight lncRNAs was discerned as a self-determining predictor of prognosis. GC patients were sub-divided into high-risk and low-risk groups via this risk-model. Stratified analysis of different clinical factors also displayed that the PRLs signature was a good prognosis factor. According to the risk score and clinical characteristics, a nomogram was established. Moreover, the difference between the groups is significance in immune cells and immune pathways. Conclusion: This study established an effective prognostic signature consist of eight PRLs in GC, and constructed an efficient nomogram model. Further, the PRLs correlated with immune cells and immune pathways.

Common Core Genes Play Vital Roles in Gastric Cancer With Different Stages

Background: Owing to complex molecular mechanisms in gastric cancer (GC) oncogenesis and progression, existing biomarkers and therapeutic targets could not significantly improve diagnosis and prognosis. This study aims to identify the key genes and signaling pathways related to GC oncogenesis and progression using bioinformatics and meta-analysis methods.

Methods: Eligible microarray datasets were downloaded and integrated using the meta-analysis method. According to the tumor stage, GC gene chips were classified into three groups. Thereafter, the three groups’ differentially expressed genes (DEGs) were identified by comparing the gene data of the tumor groups with those of matched normal specimens. Enrichment analyses were conducted based on common DEGs among the three groups. Then protein–protein interaction (PPI) networks were constructed to identify relevant hub genes and subnetworks. The effects of significant DEGs and hub genes were verified and explored in other datasets. In addition, the analysis of mutated genes was also conducted using gene data from The Cancer Genome Atlas database.

Results: After integration of six microarray datasets, 1,229 common DEGs consisting of 1,065 upregulated and 164 downregulated genes were identified. Alpha-2 collagen type I (COL1A2), tissue inhibitor matrix metalloproteinase 1 (TIMP1), thymus cell antigen 1 (THY1), and biglycan (BGN) were selected as significant DEGs throughout GC development. The low expression of ghrelin (GHRL) is associated with a high lymph node ratio (LNR) and poor survival outcomes. Thereafter, we constructed a PPI network of all identified DEGs and gained 39 subnetworks and the top 20 hub genes. Enrichment analyses were performed for common DEGs, the most related subnetwork, and the top 20 hub genes. We also selected 61 metabolic DEGs to construct PPI networks and acquired the relevant hub genes. Centrosomal protein 55 (CEP55) and POLR1A were identified as hub genes associated with survival outcomes.

Conclusion: The DEGs, hub genes, and enrichment analysis for GC with different stages were comprehensively investigated, which contribute to exploring the new biomarkers and therapeutic targets.

Key Candidate Prognostic Biomarkers Correlated with Immune Infiltration in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, which causes ~800,000 deaths annually world-wide. Immune checkpoint inhibitor (ICI) has reformed cancer therapy and achieved unprecedented results in various malignancies, including HCC. However, the response rate of immunotherapy is very low in HCC. Considereing the complicated and unique immune status in liver, we hypothesize that critical molecules will affect prognosis and correlate with immune context in the tumor microenvironment of HCC.

Methods

Using Kaplan–Meier plotter, GEPIA2 and Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB), survival genes and their prognostic value were estimated in HCC. Based on Tumor Immune Estimation Resource (TIMER), association between survival genes and immune infiltration was examined in HCC. FunRich and STRING were used to analyze gene ontology and protein–protein interaction (PPI) Network, qRT-PCR was used to measure mRNA level of candidates; and a Cell Counting Kit-8 was used to measure proliferation of HCC cell line.

Results

Using multiple databases, we identified 36 key prognostic genes highly expressed in HCC and associated with poor survival of patients. Meanwhile, the 36 gene signatures correlated with immune infiltration in HCC. Moreover, these genes were significantly associated with exhausted T cells and polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) in HCC. Among the 36 key genes, SKA3, SGOL2, SPINDOC, TEDC2, TMCO3 and NUP205 were highly expressed in tumor samples compared with adjacent normal tissues in our HCC cohort (n=22). Additionally, proliferation of SMMC7721 cell line was inhibited when it interfered with SiRNA of each gene.

Conclusion

The 36 genes may serve as potential prognostic biomarkers and molecular targets to ameliorate tumor immune microenvironment (TIME) in HCC and therefore represent a novel avenue for individualized immunotherapy in HCC.

The effect of key DNA methylation in different regions on gene expression in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common cancer with high morbidity and mortality. As we all know, the alteration of DNA methylation has a crucial impact on the occurrence of HCC. However, the mechanism of the effect of DNA methylation in different regions on gene expression is still unclear. Here, by computing and analyzing the distribution of differential methylation in 12 different regions in HCC tissues and adjacent normal tissues, not only the hypermethylation of CpG islands and global hypomethylation were found, but also a stable distribution pattern of differential methylation in HCC was found. Then the correlations between DNA methylations in different regions and gene expressions were calculated, and the diversity of correlations in different regions was determined. The key genes of differential methylation and differential expression related to the survival of HCC patients were obtained by using Cox regression analysis, a four-gene prognostic risk scoring model was constructed, and the prognostic performance was well verified. The regions of the differentially methylated CpG sites corresponding to the four key genes were located and their influences on the expression were analyzed. The results indicate that the promoter, first exon, 5'UTR, sixth exon, N_Shore, and S_Shore hypomethylation promotes the expression of key oncogenes, which together lead to the occurrence of HCC. These results might help to study the role of DNA methylation in HCC and provide potential biomarkers for the diagnosis of HCC.

Reg3A (regenerating family member 3 alpha) acts as a tumor suppressor by targeting DMBT1 (deleted in malignant brain tumors 1) in gastric cancer

Regenerating family member 3 alpha (Reg3A) encodes a pancreatic secretory protein that may be involved in cell proliferation or differentiation. However, the function and downstream regulatory mechanism of Reg3A in gastric cancer (GC) remains elusive. This study aimed to clarify the function and mechanism of Reg3A regulating cell proliferation in GC. The expression levels of Reg3A were confirmed in GC patients and cells using qRT-PCR and western blotting. TCGA datasets and clinical samples were used to explore the correlation between Reg3A and clinicopathologic features in GC. Cell viability, colony formation, and xenograft tumorigenesis assays were performed to detect the function of Reg3A on cell proliferation. Besides, we predicted the correlated genes of Reg3A by analyzing TCGA datasets, and further investigated the downstream regulatory mechanism of Reg3A in GC. Our results demonstrated that Reg3A is down-regulated in vitro and vivo (P < 0.05). Reg3A expression are negatively correlated with TNM classification (P < 0.001), lymph node (P < 0.001) in GC. Reg3A significantly suppresses cell proliferation in GC (P < 0.05). Bioinformatic analysis and experimental results confirmed that Reg3A positively regulates the expression of deleted in malignant brain tumor 1 (DMBT1, P < 0.05). Besides, Reg3A and DMBT1 all prolong the overall survival (OS, P < 0.01), post-progression survival (PPS, P < 0.05), and first progression survival (FP, P < 0.01). The function of Reg3A inhibiting cell proliferation is abolished by DMBT1 siRNA in GC (P < 0.05). In conclusion, Reg3A may act as a novel tumor suppressor by promoting DMBT1 expression, which may be a potential therapeutic target in patients with GC.

Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

BACKGROUND

The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.

METHODS

GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.

CONCLUSIONS

Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.

RNA sequencing identified novel target genes for Adansonia digitata in breast and colon cancer cells

Adansonia digitata exhibits numerous beneficial effects. In the current study, we investigated the anti-cancer effects of four different extracts of A. digitata (polar and non-polar extracts of fruit powder and fibers) on the proliferation of human colon cancer (HCT116), human breast cancer (MCF-7), and human ovarian cancer (OVCAR-3 and OVCAR-4) cell lines. RNA sequencing revealed the influence of the effective A. digitata fraction on the gene expression profiles of responsive cells. The results indicated that only the polar extract of the A. digitata fibers exhibited anti-proliferative activities against HCT116 and MCF-7 cells, but not ovarian cancer cells. Moreover, the polar extract of the fibers resulted in the modulation of the expression of multiple genes in HCT116 and MCF-7 cells. We propose that casein kinase 2 alpha 3 (CSNK2A3) is a novel casein kinase 2 (CSNK2) isoform in HCT116 cells and report, for the first time, the potential involvement of FYVE, RhoGEF, and PH domain-containing 3 (FGD3) in colon cancer. Together, these findings provide evidence supporting the anti-cancer potential of the polar extract of A. digitata fibers in this experimental model of breast and colon cancers.

Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

Background

Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.

Methods

Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs.

Results

Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.

Conclusions

We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08358-7.

Identification of the hub genes and prognostic indicators of gastric cancer and correlation of indicators with tumor-infiltrating immune cell levels

Aims: To identify the hub genes and prognostic indicators of gastric cancer (GC) and determine the correlation between prognostic indicators and the tumor-infiltrating immune cell levels so as to provide useful information for future GC diagnosis and treatment. Methods: The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset and two microarray datasets were used to screen the overlapping differentially expressed genes (DEGs) between normal gastric and GC tissue samples. Hub genes were screened via protein-protein interaction networks and module analysis of the overlapping DEGs. Their expression was validated at the cell level and tissue level using the ONCOMINE database. The prognostic indicators of overall survival (OS) and disease-free survival was identified by Cox proportional hazards regression analysis based on tumor grade and cancer stage. The expression of hub genes was validated at the cell level. The correlation of prognostic indicators with the tumor-infiltrating immune cell levels was analyzed using Tumor IMmune Estimation Resource. Results: Ten hub genes, namely CDC6, CDC20, BUB1B, TOP2A, CDK1, AURKA, CCNA2, CCNB1, MAD2L1, and KIF11, were screened and their upregulation in the GC tissue was verified. Three prognostic factors, namely LUM, VCAN, and EFNA4, were identified; their expression was higher in GC cells than in normal cells. LUM, VCAN, and EFNA4 were correlated with tumor-infiltrating immune cell levels in GC. Significance: The identified hub genes and prognostic indicators of GC could be useful indicators for future GC diagnosis and treatment.

CDC20 promotes the progression of hepatocellular carcinoma by regulating epithelial‑mesenchymal transition

Hepatocellular carcinoma (HCC) is a type of primary liver cancer, which is associated with high mortality. HCC is one of the most common malignant tumors worldwide. Cell division cycle 20 (CDC20) has been reported to be associated with the development of various malignant tumors and epithelial-mesenchymal transition (EMT) has been reported to be involved in the malignant metastasis of HCC. Therefore, the present study hypothesized that CDC20 may participate in the malignant biological behavior of HCC via EMT. The present study analyzed the expression levels of CDC20 in HCC and the association between CDC20 and poor prognosis. Furthermore, the effects of CDC20 on the proliferation, invasion and migration of HCC cells were examined using proliferation, migration and invasion assays. Finally, alterations in EMT were analyzed. The results revealed that CDC20 was highly expressed in HCC and HCC cell lines (P<0.05), and its high expression level was significantly associated with poor prognosis in patients with HCC (P<0.05). CDC20 silencing inhibited the proliferation, migration and invasion of HCC cells. Furthermore, CDC20 silencing increased the expression levels of E-cadherin, and decreased the expression levels of N-cadherin, vimentin and Ki-67. In conclusion, the present study reported that CDC20 may be a novel therapeutic target in HCC and CDC20 could promote the progression of HCC by regulating EMT.

Connection Between CDC20 Expression and Hepatocellular Carcinoma Prognosis

Background

Hepatocellular carcinoma (HCC) occurs frequently in China, with high morbidity and mortality. Cell division cycle 20 homolog (CDC20) is reportedly related to many cancers. In this study, we discuss a potential link of CDC20 expression to HCC patients’ prognoses.

Material/Methods

Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to assess CDC20 expression in HCC and the paired noncancerous tissues. Chi-square analysis was used to assess potential association of CDC20 expression with clinicopathologic profiles among HCC patients. The overall survival for HCC patients with different CDC20 expressions was assessed using the Kaplan-Meier method. To evaluate the prognostic value for HCC patients, Cox regression analyses were performed.

Results

The expression of CDC20 was elevated among HCC specimens compared with adjacent noncancerous ones (P<0.05). The expression of CDC20 was significantly related to differentiation (P<0.001), tumor node metastasis stage (P<0.001), and lymphatic metastasis (P<0.001). Moreover, HCC patients with high CDC20 expression had dismal overall survival rates compared with low CDC20 expression (P<0.05). CDC20 alone could forecast HCC prognoses according to multivariable Cox regression analysis (hazard ratio=2.354, 95% confidence interval=1.177–4.709, P=0.016).

Conclusions

Overexpressed CDC20 may act as a reliable biomarker for dismal prognoses among HCC patients.

Increase in non-professional phagocytosis during the progression of cell cycle

Homotypic or heterotypic internalization of another, either living or necrotic cell is currently in the center of research interest. The active invasion of a living cell called entosis and cannibalism of cells by rapidly proliferating cancers are prominent examples. Additionally, normal healthy tissue cells are capable of non-professional phagocytosis. This project studied the relationship between non-professional phagocytosis, individual proliferation and cell cycle progression. Three mesenchymal and two epithelial normal tissue cell lines were studied for homotypic non-professional phagocytosis. Homotypic dead cells were co-incubated with adherent growing living cell layers. Living cells were synchronized by mitotic shake-off as well as Aphidicolin-treatment and phagocytotic activity was analyzed by immunostaining. Cell cycle phases were evaluated by flow cytometry. Mesenchymal and epithelial normal tissue cells were capable of internalizing dead cells. Epithelial cells had much higher non-professional phagocytotic rates than mesenchymal cells. Cells throughout the entire cell cycle were able to phagocytose. The phagocytotic rate significantly increased with progressing cell cycle phases. Mitotic cells regularly phagocytosed dead cells, this was verified by Nocodazole and Colcemid treatment. Taken together, our findings indicate the ability of human tissue cells to phagocytose necrotic neighboring cells in confluent cell layers. The origin of the cell line influences the rate of cell-in-cell structure formation. The higher cell-in-cell structure rates during cell cycle progression might be influenced by cytoskeletal reorganization during this period or indicate an evolutionary anchorage of the process. Recycling of nutrients during cell growth might also be an explanation.

miR-139-5p Inhibits Lung Adenocarcinoma Cell Proliferation, Migration, and Invasion by Targeting MAD2L1

BACKGROUND

miR-139-5p is lowly expressed in various human cancers and exerts its antitumor effect through different molecular mechanisms, yet the molecular mechanism of miR-139-5p in lung adenocarcinoma (LUAD) remains to be further elucidated. The study is aimed at investigating the role and the regulatory mechanism of miR-139-5p in LUAD progression.

METHODS

Differential analysis was performed on miRNA expression data in the TCGA-LUAD dataset. qRT-PCR was employed to detect the transcription levels of miR-139-5p and MAD2L1 in LUAD cells, while western blot was carried out for the detection of MAD2L1 protein expression. CCK-8 and Transwell assays were implemented to assess LUAD cell proliferation, migration, and invasion. A dual-luciferase reporter gene assay was conducted to verify the direct targeting relationship between miR-139-5p and MAD2L1.

RESULTS

miR-139-5p was significantly downregulated in LUAD cells in comparison with that in human normal bronchial epithelial cells. Overexpressing miR-139-5p inhibited LUAD cell proliferation, migration, and invasion, while opposite results could be observed when miR-139-5p was inhibited. MAD2L1 was identified as a direct target of miR-139-5p in LUAD. Besides, the inhibitory effect of miR-139-5p overexpression on LUAD cell proliferation, migration, and invasion was attenuated by overexpressing MAD2L1.

CONCLUSION

Our study suggests that miR-139-5p is lowly expressed in LUAD cells and inhibits LUAD cell proliferation, migration, and invasion by targeted suppressing MAD2L1 expression. It is of potential significance for the prognosis and treatment of LUAD.

Identification of crucial genes associated with lung adenocarcinoma by bioinformatic analysis

Lung cancer is the world's most common malignancies and ranks first among all cancer-related deaths. Lung adenocarcinoma (LUAD) is the most frequent histological type in lung cancer. Its pathogenesis has not yet been fully elucidated, so it is of great significance to explore related genes for elucidating the molecular mechanism involved in occurrence and development of LUAD.To explore the crucial genes associated with LUAD development and progression, microarray datasets GSE7670, GSE10072, and GSE31547 were acquired from the Gene Expression Omnibus (GEO) database. R language Limma package was adopted to screen the differentially expressed genes (DEGs). The clusterProfiler package was used for enrichment analysis and annotation of the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways for DEGs. The Search Tool for the Retrieval of Interacting Genes database (STRING) was used to construct the protein interaction network for DEGs, while Cytoscape was adopted to visualize it. The functional module was screened with Cytoscape's MCODE (The Molecular Complex Detection) plugin. The crucial genes associated with LUAD were identified by cytoHubba plugin. Kaplan-Meier plotter online tool was used to perform survival analysis of the hub gene.Three hundred twenty-one DEGs in total were screened, of which 105 were upregulated and 216 were downregulated. It was found that some GO terms and pathways (e.g., collagen trimer, extracellular structure organization, heparin binding, complement and coagulation cascades, malaria, protein digestion and absorption, and PPAR signaling pathway) were considerably enriched in DEGs. UBE2C, TOP2A, RRM2, CDC20, CCNB2, KIAA0101, BUB1B, TPX2, PRC1, and CDK1 were identified as crucial genes. Survival analysis showed that the overexpression of UBE2C, TOP2A, RRM2, CDC20, CCNB2, KIAA0101, BUB1B, TPX2, and PRC1 significantly reduced the overall survival of LUAD patients. One of the crucial genes: UBE2C was validated by immunohistochemistry to be upregulated in LUAD tissues.This study screened out potential biomarkers of LUAD, providing a theoretical basis for elucidating the pathogenesis and evaluating the prognosis of LUAD.

Cell-in-cell phenomenon associates with aggressive characteristics and cancer-related mortality in early oral tongue cancer

Background

Cell-in-cell structures (caused by cell cannibalistic activity) have been related to prognosis of many cancers. This is the first multi-institutional study to assess the prognostic impact of cell-in-cell structures in a large cohort of early oral tongue squamous cell carcinomas (OTSCC).

Methods

A total of 308 cases from five Finnish University Hospitals and from the A.C. Camargo Cancer Center, São Paulo, Brazil, were included in this study. Cell-in-cell structures were evaluated on surgical postoperative sections that stained with hematoxylin and eosin staining.

Results

We found that cell-in-cell structures associated with cancer-related mortality in univariable analysis with a hazard ratio (HR) of 2.99 (95%CI 1.52–5.88; P = 0.001). This association was confirmed in multivariable analysis (HR 2.22, 95%CI 1.12–4.44; P = 0.024). In addition, statistically significant associations were observed between the cell-in-cell structures and other adverse histopathologic characteristics including deep invasion (P <  0.001), high index of tumor budding (P = 0.007), worst pattern of invasion (P <  0.001), perineural invasion (P = 0.01), and stroma-rich pattern (P = 0.001).

Conclusions

Our findings demonstrate a significant relationship between cell-in-cell formation and aggressive characteristics of early OTSCC. Cell-in-cell structures have a distinct impact as a novel prognostic indicator in early OTSCC and they can be easily assessed during routine pathology practice.

Upregulated expression of SAC3D1 is associated with progression in gastric cancer

SAC3 domain containing 1 (SAC3D1) has been reported to be involved in numerous types of cancer. However, the role of SAC3D1 in GC has not yet been elucidated. In the present study, the mRNA expression level of SAC3D1 between GC and normal tissues were assessed with a continuous variable meta-analysis based on multiple datasets from public databases. The protein expression level of SAC3D1 in GC and normal tissues was assessed by an in-house immunohistochem-istry (IHC). The association between SAC3D1 expression and some clinical parameters was assessed based on the TCGA and IHC data. Survival analysis was performed to assess the association between SAC3D1 expression and the survival of GC patients. The co-expressed genes of SAC3D1 were determined by integrating three online tools, and the enrichment analyses were performed to determine SAC3D1-related pathways and hub co-expressed genes. SAC3D1 was significantly upregulated in GC tumor tissues in comparison to normal tissues with the SMD being 0.45 (0.12, 0.79). The IHC results also indicated that SAC3D1 protein expression in GC tissues was markedly higher than in normal tissues. The SMD following the addition of the IHC data was 0.59 (0.11, 1.07). The protein levels of SAC3D1 were positively associated with the histological grade, T stage and N stage of GC (P<0.001). The TCGA data also revealed that the SAC3D1 mRNA level was significantly associated with the N stage (P<0.001). Moreover, prognosis analysis indicated that SAC3D1 was closely associated with the prognosis of patients with GC. Moreover, 410 co-expressed genes of SAC3D1 were determined, and these genes were mainly enriched in the cell cycle. In total, 4 genes (CDK1, CCNB1, CCNB2 and CDC20) were considered key co-expressed genes. On the whole, these findings demonstrate that SAC3D1 is highly expressed in GC and may be associated with the progression of GC.

Based on Integrated Bioinformatics Analysis Identification of Biomarkers in Hepatocellular Carcinoma Patients from Different Regions

Accumulating statistics have shown that liver cancer causes the second highest mortality rate of cancer-related deaths worldwide, of which 80% is hepatocellular carcinoma (HCC). Given the underlying molecular mechanism of HCC pathology is not fully understood yet, identification of reliable predictive biomarkers is more applicable to improve patients' outcomes. The results of principal component analysis (PCA) showed that the grouped data from 1557 samples in Gene Expression Omnibus (GEO) came from different populations, and the mean tumor purity of tumor tissues was 0.765 through the estimate package in R software. After integrating the differentially expressed genes (DEGs), we finally got 266 genes. Then, the protein-protein interaction (PPI) network was established based on these DEGs, which contained 240 nodes and 1747 edges. FOXM1 was the core gene in module 1 and highly associated with FOXM1 transcription factor network pathway, while FTCD was the core gene in module 2 and was enriched in the metabolism of amino acids and derivatives. The expression levels of hub genes were in line with The Cancer Genome Atlas (TCGA) database. Meanwhile, there were certain correlations among the top ten genes in the up- and downregulated DEGs. Finally, Kaplan–Meier curves and receiver operating characteristic (ROC) curves were plotted for the top five genes in PPI. Apart from CDKN3, the others were closely concerned with overall survival. In this study, we detected the potential biomarkers and their involved biological processes, which would provide a new train of thought for clinical diagnosis and treatment.

Subtype-Based Prognostic Analysis of Cell-in-Cell Structures in Early Breast Cancer

Though current pathological methods are greatly improved, they provide rather limited functional information. Cell-in-cell structures (CICs), arising from active cell–cell interaction, are functional surrogates of complicated cell behaviors within heterogeneous cancers. In light of this, we performed the subtype-based CIC profiling in human breast cancers by the “EML” multiplex staining method, and accessed their values as prognostic factors by Cox univariate, multivariate, and nomogram analysis. CICs were detected in cancer specimens but not in normal breast tissues. A total of five types of CICs were identified with one homotypic subtype (91%) and four heterotypic subtypes (9%). Overall CICs (oCICs) significantly associated with patient overall survival (OS) (P = 0.011) as an independent protective factor (HR = 0.423, 95% CI, 0.227–0.785; P = 0.006). Remarkably, three CICs subtypes (TiT, TiM, and MiT) were also independent prognostic factors. Among them, higher TiT, from homotypic cannibalism between tumor cells, predicted longer patient survival (HR = 0.529, 95% CI, 0.288–0.973; P = 0.04) in a way similar to that of oCICs and that (HR = 0.524, 95% CI, 0.286–0.962; P = 0.037) of heterotypic TiM (tumor cell inside macrophage); conversely, the presence of MiT (macrophage inside tumor cell) predicted a death hazard of 2.608 (95% CI, 1.344–5.063; P = 0.05). Moreover, each CIC subtype tended to preferentially affect different categories of breast cancer, with TiT (P < 0.0001) and oCICs (P = 0.008) targeting luminal B (Her2⁺), TiM (P = 0.011) targeting HR⁻ (Her2⁺/HR⁻ and TNBC), and MiT targeting luminal A (P = 0.017) and luminal B (Her⁻) (P = 0.006). Furthermore, nomogram analysis suggested that CICs impacted patient outcomes in contributions comparable (for oCICs, TiT, and TiM), or even superior (for MiT), to TNM stage and breast cancer subtype, and incorporating CICs improved nomogram performance. Together, we propose CICs profiling as a valuable way for prognostic analysis of breast cancer and that CICs and their subtypes, such as MiT, may serve as a type of novel functional markers assisting clinical practices.

Aneuploidy and oncoviruses

Seven oncogenic viruses are known for tumorigenesis and contribute to 12% of all human cancers. The oncogenic factors, the target tissue, and pathology of cancer vary among these viruses with several mechanisms proposed for the initiation and development of cancer. Aneuploidy in cells is associated with anomalies in chromosome number that can be a hallmark of cancer, a disease defined by expanded proliferative potential. In this review, we summarize the different mechanisms of aneuploidy and furthermore discuss recent findings of the role of viral oncoproteins in inducing cellular aneuploidy that might facilitate tumorigenesis. Improved understanding of viral oncogenesis may help to find new strategies for controlling virus-associated cancers.