Identification of hypoxia-related gene signatures based on multi-omics analysis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and one of the malignancies with the highest incidence rate and mortality worldwide. Hypoxia is a typical feature of tumour microenvironment (TME), which affects the progression of LUAD from multiple molecular levels. However, the underlying molecular mechanisms behind LUAD hypoxia are not fully understood. In this study, we estimated the level of hypoxia by calculating a score based on 15 hypoxia genes. The hypoxia scores were relatively high in LUAD patients with poor prognosis and were bound up with tumour node metastasis (TNM) stage, tumour size, lymph node, age and gender. By comparison of high hypoxia score group and low hypoxia score group, 1820 differentially expressed genes were identified, among which up-regulated genes were mainly about cell division and proliferation while down-regulated genes were primarily involved in cilium-related biological processes. Besides, LUAD patients with high hypoxia scores had higher frequencies of gene mutations, among which TP53, TTN and MUC16 had the highest mutation rates. As for DNA methylation, 1015 differentially methylated probes-related genes were found and may play potential roles in tumour-related neurobiological processes and cell signal transduction. Finally, a prognostic model with 25 multi-omics features was constructed and showed good predictive performance. The area under curve (AUC) values of 1-, 3- and 5-year survival reached 0.863, 0.826 and 0.846, respectively. Above all, our findings are helpful in understanding the impact and molecular mechanisms of hypoxia in LUAD.

A prognostic nomogram based on risk assessment for invasive micropapillary carcinoma of the breast after surgery.

PURPOSE: Invasive micropapillary carcinoma (IMPC) is one of the rare subtypes of breast cancer. This study aimed to explore a predictive nomogram model for IMPC prognosis. METHODS: A total of 1855 IMPC patients diagnosed after surgery between 2004 and 2014 were identified from the Surveillance, Epidemiology and End Results (SEER) database to build and validate nomogram. A nomogram was created based on univariate and multivariate Cox proportional hazards regression analysis. Receiver operating characteristic (ROC) curves were used to demonstrate the accuracy of the prognostic model. Decision curve analysis (DCA) was performed to evaluate the safety of the model in the range of clinical applications, while calibration curves were used to validate the prediction consistency. RESULTS: Cox regression analysis indicated that age ≥62 at diagnosis, negative ER status, and tumor stage were considered adverse independent factors for overall survival (OS), while patients who were married, white or of other races, received chemotherapy or radiotherapy, had a better postoperative prognosis. The nomogram accurately predicted OS with high internal and external validation consistency index (C index) (0.756 and 0.742, respectively). The areas under the ROC curve (AUCs) of the training group were 0.787, 0.774 and 0.764 for 3, 5 and 10 years, respectively, while those of the validation group were 0.756, 0.766 and 0.762, respectively. The results of both DCA and calibration curves demonstrated the good performance of the model. CONCLUSIONS: A nomogram for IMPC of the breast patients after surgery was developed to estimate 3, 5 and 10 years-OS based on independent risk factors. This model has good accuracy and consistency in predicting prognosis and has clinical application value.

Roles and mechanisms of phosphoglycerate kinase 1 in cancer.

Phosphoglycerate kinase 1 (PGK1) catalyzes the conversion of 1,3-bisphosphoglyceride (1,3-BPG) and ADP into 3-phosphate (3-PG) and ATP, which is a key process of glycolysis. PGK1 is considered a major regulator of various events, including one-carbon metabolism, serine biosynthesis and cell redox regulation. In the past decade, PGK1 has been found to be closely associated with various malignancies, making it a potential therapeutic target. PGK1 is involved in a series of biological processes related to tumorigenesis through post-translational modifications and various signaling pathways. PGK1 not only can participate in glucose metabolism but also acts as a protein kinase to participate in EMT, autophagy, angiogenesis, DNA replication and other processes related to tumor development. However, PGK1 also acts as a disulfide reductase to inhibit tumor by affecting angiogenesis. Exploring the structure, function and posttranslational modification of PGK1 will be helpful in further understanding the effect of metabolism on tumor progression. This manuscript reviews the role and mechanism of PGK1 in human malignancies, providing the theoretical basis for PGK1 as a possible clinical anticancer target.

Regulatory Network Analysis of Mutated Genes Based on Multi-Omics Data Reveals the Exclusive Features in Tumor Immune Microenvironment Between Left-Sided and Right-Sided Colon Cancer.

Left-sided colon cancer (LCC) and right-sided colon cancer (RCC) have distinct characteristics in tumor immune microenvironment (TIME). Although existing studies have shown a strong association between gene mutations and TIME, whether the regulatory mechanisms between gene mutations and TIME are different between RCC and LCC is still unclear. In this study, we showed the fractions of CD8+ T cells were higher while those of regulatory T cells were lower in RCC. Besides, a stronger association between gene mutations and TIME was observed in RCC. Specifically, using multi-omics data, we demonstrated the mutations of most top mutated genes (TMGs) including BRAF, PCLO, MUC16, LRP2, ANK3, KMT2D, RYR2 made great contributions to elevated fraction of immune cells by up-regulating immune-related genes directly or indirectly through miRNA and DNA methylation, whereas the effects of APC, TP53 and KRAS mutations on TIME were reversed in RCC. Remarkably, we found the expression levels of several immune checkpoint molecules such as PD-1 and LAG3 were correlated with corresponding DNA methylation levels, which were associated with the mutations of TMGs in RCC. In contrast, the associations between gene mutations and TIME were less significant in LCC. Besides, survival analyses showed APC mutation had adverse impact on immunotherapy while patients with BRAF mutation were more suitable for immunotherapy in colon cancer. We hope that our results will provide a deeper insight into the sophisticated mechanism underlying the regulation between mutations and TIME, and thus boost the discovery of differential immunotherapeutic strategies for RCC and LCC.