Identification of personalized dysregulated pathways in hepatocellular carcinoma

A glycosylation-related signature predicts survival in pancreatic cancer

BACKGROUND

Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models.

MATERIALS AND METHODS

The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan-Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature.

RESULTS

Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines.

CONCLUSION

This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.

The oncogenic role of tubulin alpha-1c chain in human tumours

Tubulin alpha-1c chain (TUBA1C), a subtype of α-tubulin, has been shown to be involved in cell proliferation and cell cycle progression in several cancers and to influence cancer development and prognosis. However, a pancancer analysis of TUBA1C to reveal its immunological and prognostic roles has not been performed. In this study, we first downloaded raw data on TUBA1C expression in cancers from The Cancer Genome Atlas (TCGA) database and multiple other databases and analysed these data with R software to investigate the prognostic and immunological value of TUBA1C in cancers. Immunohistochemical analysis was performed in gliomas to further validate our findings. Overall, TUBA1C was overexpressed in most cancers, and overexpression of TUBA1C was linked to poor prognosis and higher tumour grade in patients. In addition, TUBA1C expression was associated with tumour mutation burden (TMB), microsatellite instability (MSI), the tumour microenvironment (TME) and the infiltration of immune cells. TUBA1C was also coexpressed with most immune-related genes and influenced immune-related pathways. Immunohistochemical analysis showed that TUBA1C expression was highest in glioblastoma (GBM) tissues, second highest in low-grade glioma (LGG) tissues and lowest in normal tissues. Our study indicated that TUBA1C might be a biomarker for predicting the immune status and prognosis of cancers, offering new ideas for cancer treatment.

TUBA1C is a Prognostic Marker in Low-grade Glioma and Correlates with Immune Cell Infiltration in the Tumor Microenvironment

TUBA1C, a microtubule component, contributes to the development of several cancers. Our purpose was to study the expression of TUBA1C, its potential prognostic value, and its effects on the infiltration of immune cells of low-grade glioma (LGG). Through applying multiple bioinformatics analyses, we extracted and analyzed datasets from TCGA, TIMER, GTEx, GEPIA, and HPA to investigate the potential oncogenic mechanisms of TUBA1C, including the correlation between TUBA1C and prognosis, immune-checkpoints, tumor microenvironment (TME), and infiltration of immune cells in LGG. GO functional annotations and KEGG pathway analyses were further applied to investigate the potential action of TUBA1C in LGG. We revealed that the mRNA levels of TUBA1C were increased in LGG tumor tissues than in normal tissues. Additionally, TUBA1C was up-regulated in the grade III of LGG than in grade II. Moreover, we found that TUBA1C may be an independent prognostic factor of LGG, and high TUBA1C expression correlated to a poor prognosis of LGG. TUBA1C expression was positively associated with the infiltration of B cells, CD8 T+ cells, CD4⁺ T cells, macrophages, dendritic cells, and neutrophils. TUBA1C was also verified to be co-expressed with immune-related genes and immune-checkpoints. GO and KEGG pathway analyses indicated that TUBA1C may potentially regulate the pathogenesis of LGG through immune-related pathways, including chemokine pathway; JAK-STAT pathway; natural killer cell mediated cytotoxicity; T cell receptor pathway; leukocyte migration; negative regulation of immune system process; regulation of lymphocyte activation; T cell activation and other pathways. In conclusion, TUBA1C expression is increased in LGG and high TUAB1C expression is related to a poor prognosis. TUBA1C may influence tumor development by regulating the tumor-infiltrating cells in the TME. TUBA1C may be a potential target for immunotherapy.

Upregulated Expression of TUBA1C Predicts Poor Prognosis and Promotes Oncogenesis in Pancreatic Ductal Adenocarcinoma via Regulating the Cell Cycle

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant disease and has the worst prognosis and survival rate. TUBA1C is a microtubule component implicated in multiple cancers, however, the clinical significance and biological functions of TUBA1C in the progression of PDAC remain unexplored.

Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) data were employed to detect the TUBA1C mRNA expression and the relation between TUBA1C expression and overall survival (OS) in PDAC. Then, bioinformatic analysis was employed to determine the potential pathway and genes related to TUBA1C. Human pancreatic cancer tissue and adjacent non-tumor tissues samples were detected by immunochemistry (IHC) staining, and the correlation between TUBA1C expression and the clinicopathological features were investigated. Meanwhile, TUBA1C expression in PDAC cell lines was evaluated by western blotting. Furthermore, functional assays including cell viability, apoptosis, cell cycle, transwell assay, wound healing assay, and a xenograft tumor model were performed to determine the oncogenic role of TUBA1C in PDAC, respectively.

Results: TUBA1C was overexpressed in the PDAC tissues and cells. IHC analysis showed that the TUBA1C overexpression was associated with short OS. Bioinformatic analysis indicated that TUBA1C overexpression was mainly associated with cell cycle regulation. The downregulation of TUBA1C significantly suppressed cell proliferation, induced cell apoptosis and cycle arrest, and inhibited invasion and migration in PDAC cells. Furthermore, TUBA1C downregulation also inhibited tumor growth in vivo.

Conclusion: These findings suggested that TUBA1C downregulation suppressed PDAC aggressiveness via cell cycle pathway and that TUBA1C may serve as a potential prognostic marker for PDAC therapy.

Identification of Differently Expressed Genes Associated With Prognosis and Growth in Colon Adenocarcinoma Based on Integrated Bioinformatics Analysis

Latest statistics showed that the morbidity and mortality of colon adenocarcinoma (COAD) ranked fourth and fifth, respectively, around the world. COAD was a heterogeneous disease, and the high rates of recurrence, metastasis, and drug resistance still posed great challenges for treatment, which needs to further develop therapeutic and prognostic targets. In this study, we got the top 3,075 differentially expressed genes (DEGs) and 1,613 potential prognostic genes by GEPIA 2 and identified 1,166 fitness genes in COAD based on genome-scale CRISPR-Cas9 knockout (GeCKO) screening data. Excluding the genes already reported in the literatures, a total of nine DEGs overlapping with prognostic and fitness genes were further analyzed. High expression of CCT6A, RHOQ, and RRP12 promoted COAD cell growth and were relative to lower survival rate of COAD patients, while high expression of UTP18, DDOST, YRDC, ACTG1, RFT1, and NLE1 also promoted COAD cell growth, but were relative to higher survival rate. In addition, CCT6A, UTP18, YRDC, RRP12, RFT1, NLE1, as well as DDOST were essential genes across pan-cancer including COAD cells, and ACTG1 and RHOQ were less essential genes in cancer cells. In a word, we discovered nine novel potential genes that could serve as anticancer targets and prognostic markers in COAD and its subtypes.

Aneuploidy: Cancer strength or vulnerability?

Aneuploidy is a very rare and tissue‐specific event in normal conditions, occurring in a low number of brain and liver cells. Its frequency increases in age‐related disorders and is one of the hallmarks of cancer. Aneuploidy has been associated with defects in the spindle assembly checkpoint (SAC). However, the relationship between chromosome number alterations, SAC genes and tumor susceptibility remains unclear. Here, we provide a comprehensive review of SAC gene alterations at genomic and transcriptional level across human cancers and discuss the oncogenic and tumor suppressor functions of aneuploidy. SAC genes are rarely mutated but frequently overexpressed, with a negative prognostic impact on different tumor types. Both increased and decreased SAC gene expression show oncogenic potential in mice. SAC gene upregulation may drive aneuploidization and tumorigenesis through mitotic delay, coupled with additional oncogenic functions outside mitosis. The genomic background and environmental conditions influence the fate of aneuploid cells. Aneuploidy reduces cellular fitness. It induces growth and contact inhibition, mitotic and proteotoxic stress, cell senescence and production of reactive oxygen species. However, aneuploidy confers an evolutionary flexibility by favoring genome and chromosome instability (CIN), cellular adaptation, stem cell‐like properties and immune escape. These properties represent the driving force of aneuploid cancers, especially under conditions of stress and pharmacological pressure, and are currently under investigation as potential therapeutic targets. Indeed, promising results have been obtained from synthetic lethal combinations exploiting CIN, mitotic defects, and aneuploidy‐tolerating mechanisms as cancer vulnerability.