Several genes involved in the JAK-STAT pathway may act as prognostic markers in pancreatic cancer identified by microarray data analysis

Interplay between signal transducers and activators of transcription (STAT) proteins and cancer: involvement, therapeutic and prognostic perspective

Signal transducers and activators of transcription or STAT are proteins that consist of various transcription factors that are responsible for activating genes regarding cell proliferation, differentiation, and apoptosis. They commonly activate several cytokine, growth, or hormone factors via the JAK-STAT signaling pathway by tyrosine phosphorylation which are responsible for giving rise to numerous immune responses. Mutations within the Janus-Kinases (JAKs) or the STATs can set off the commencement of various malfunctions of the immune system of the body; carcinogenesis being an inevitable outcome. STATs are known to act as both oncogenes and tumor suppressor genes which makes it a hot topic of investigation. Various STATs related mechanisms are currently being investigated to analyze its potential of serving as a therapeutic base for numerous immune diseases and cancer; a deeper understanding of the molecular mechanisms involved in the signaling pathways can contribute to the same. This review will throw light upon each STAT member in causing cancer malignancies by affecting subsequent signaling pathways and its genetic and epigenetic associations as well as various inhibitors that could be used to target these pathways thereby devising new treatment options. The review will also focus upon the therapeutic advances made in cancers that most commonly affect people and discuss how STAT genes are identified as prognostic markers.

How cancer cells make and respond to interferon-I

Acute exposure of cancer cells to high concentrations of type I interferon (IFN-I) drives growth arrest and apoptosis, whereas chronic exposure to low concentrations provides important prosurvival advantages. Tyrosine-phosphorylated IFN-stimulated gene (ISG) factor 3 (ISGF3) drives acute deleterious responses to IFN-I, whereas unphosphorylated (U-)ISGF3, lacking tyrosine phosphorylation, drives essential constitutive prosurvival mechanisms. Surprisingly, programmed cell death-ligand 1 (PD-L1), often expressed on the surfaces of tumor cells and well recognized for its importance in inactivating cytotoxic T cells, also has important cell-intrinsic protumor activities, including dampening acute responses to cytotoxic high levels of IFN-I and sustaining the expression of the low levels that benefit tumors. More thorough understanding of the newly recognized complex roles of IFN-I in cancer may lead to the identification of novel therapeutic strategies.

Identification of glycolysis related pathways in pancreatic adenocarcinoma and liver hepatocellular carcinoma based on TCGA and GEO datasets

BACKGROUND

Abnormal energy metabolism is one of the characteristics of tumor cells, and it is also a research hotspot in recent years. Due to the complexity of digestive system structure, the frequency of tumor is relatively high. We aim to clarify the prognostic significance of energy metabolism in digestive system tumors and the underlying mechanisms.

METHODS

Gene set variance analysis (GSVA) R package was used to establish the metabolic score, and the score was used to represent the metabolic level. The relationship between the metabolism and prognosis of digestive system tumors was explored using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Volcano plots and gene ontology (GO) analyze were used to show different genes and different functions enriched between different glycolysis levels, and GSEA was used to analyze the pathway enrichment. Nomogram was constructed by R package based on gene characteristics and clinical parameters. qPCR and Western Blot were applied to analyze gene expression. All statistical analyses were conducted using SPSS, GraphPad Prism 7, and R software. All validated experiments were performed three times independently.

RESULTS

High glycolysis metabolism score was significantly associated with poor prognosis in pancreatic adenocarcinoma (PAAD) and liver hepatocellular carcinoma (LIHC). The STAT3 (signal transducer and activator of transcription 3) and YAP1 (Yes1-associated transcriptional regulator) pathways were the most critical signaling pathways in glycolysis modulation in PAAD and LIHC, respectively. Interestingly, elevated glycolysis levels could also enhance STAT3 and YAP1 activity in PAAD and LIHC cells, respectively, forming a positive feedback loop.

CONCLUSIONS

Our results may provide new insights into the indispensable role of glycolysis metabolism in digestive system tumors and guide the direction of future metabolism-signaling target combined therapy.

Mining database for the expression and clinical significance of STAT family in head and neck squamous cell carcinomas

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Head and neck squamous cell carcinomas (HNSC) is one of the most common malignant tumors with high incidence, relapse and mortality rate.

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STAT proteins are implicated in various biological processes, including cell proliferation, metastasis, and immune regulation.

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The mRNA level of STAT1/2/4/5A/6 were significantly upregulated in HNSC tissues. Genetic alteration revealed that STAT1/2/3/4/5A/5B/6 were altered in the queried TCGA HNSC samples.

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Immune infiltrations analysis suggested a significant association between STAT5A expression and the abundance of specific immune cells.

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Several kinase targets and transcription factor targets of STAT5A in HNSC were also identified.

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Enrichment analysis suggested that STAT5A and co-expression genes were mainly responsible for adaptive immune response, T cell activation, cytokine-cytokine receptor interaction, chemokine signaling pathway, cell adhesion molecules, ribosome, and RNA transport.

Background

Head and neck squamous cell carcinomas (HNSC) are among the most common malignant tumors with high incidence, relapse, and mortality rate. STAT proteins are implicated in various biological processes, including cell proliferation, metastasis, and immune regulation.

Method

Various bioinformatics tools were used to explore the role of the STAT family in HNSC.

Result

The mRNA levels of STAT1/2/4/5A/6 were significantly upregulated in HNSC tissues. The levels of STAT1/2/4/5A/6 could be used for the detection of HNSC. HNSC patients with a high level of STAT5A had a poor overall survival and relapse-free survival. A moderate to high correlation was obtained between the STAT family and HNSC. Genetic alteration revealed that STAT1/2/3/4/5A/5B/6 were altered in 6%, 5%, 7%, 8%, 6%, 6%, and 4% of the queried TCGA HNSC samples, respectively. Immune infiltrations analysis suggested a significant association between STAT5A expression and abundance of specific immune cells. Further, copy number alteration of STAT5A could certainly inhibit infiltration level. Moreover, a close correlation was obtained between STAT5A level and the expression of immune markers in HNSC. Several kinase targets and transcription factor targets of STAT5A in HNSC were also identified. Enrichment analysis suggested that STAT5A and co-expression genes were mainly responsible for adaptive immune response, T cell activation, cytokine-cytokine receptor interaction, chemokine signaling pathway, cell-adhesion molecules, and ribosome and RNA transport.

Conclusion

Our results provided additional data for the expression and clinical significance of the STAT family in HNSC, and further study should be performed to verify these.

Mechanisms of T-Cell Exhaustion in Pancreatic Cancer

T-cell exhaustion is a phenomenon that represents the dysfunctional state of T cells in chronic infections and cancer and is closely associated with poor prognosis in many cancers. The endogenous T-cell immunity and genetically edited cell therapies (CAR-T) failed to prevent tumor immune evasion. The effector T-cell activity is perturbed by an imbalance between inhibitory and stimulatory signals causing a reprogramming in metabolism and the high levels of multiple inhibitory receptors like programmed cell death protein-1 (PD-1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), T cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), and Lymphocyte-activation gene 3 (Lag-3). Despite the efforts to neutralize inhibitory receptors by a single agent or combinatorial immune checkpoint inhibitors to boost effector function, PDAC remains unresponsive to these therapies, suggesting that multiple molecular mechanisms play a role in stimulating the exhaustion state of tumor-infiltrating T cells. Recent studies utilizing transcriptomics, mass cytometry, and epigenomics revealed a critical role of Thymocyte selection-associated high mobility group box protein (TOX) genes and TOX-associated pathways, driving T-cell exhaustion in chronic infection and cancer. Here, we will review recently defined molecular, genetic, and cellular factors that drive T-cell exhaustion in PDAC. We will also discuss the effects of available immune checkpoint inhibitors and the latest clinical trials targeting various molecular factors mediating T-cell exhaustion in PDAC.

High TXLNA Expression Predicts Favourable Outcome for Pancreatic Adenocarcinoma Patients

TXLNA (taxilin alpha), a binding partner of the syntaxin family, was identified as a key factor in the coordination of intracellular vesicle trafficking and highly expressed in various tumor cells. However, the accurate relation between TXLNA and tumorigenesis and progression of pancreatic adenocarcinoma (PAAD) is still unclear. The present study was designed to examine the expression profile of TXLNA and explore its prognostic significance in PAAD patients and the possible molecular regulatory mechanism by analyzing a series of data from databases, including GEPIA, LOGpc, STRING, and GeneMANIA. The results indicate that TXLNA mRNA and protein were remarkably increased in PAAD tissues compared with normal pancreatic tissues. The high TXLNA expression was significantly correlated with superior overall survival (OS), disease-free interval (DFI), disease specific survival (DSS), and progression-free interval (PFI) for PAAD patients. In summary, high TXLNA expression could predict favourable OS, DFI, DSS, and PFI for PAAD patients, and it might be as potential prognostic biomarkers and targets for PAAD.

Next Generation Techniques for Determination of Protein-Protein Interactions: Beyond the Crystal Structure

PURPOSE OF REVIEW

We discuss recent advancements in structural biology methods for investigating sites of protein-protein interactions. We will inform readers outside the field of structural biology about techniques beyond crystallography, and how these different technologies can be utilized for drug development.

RECENT FINDINGS

Advancements in cryo-electron microscopy (cryoEM) and micro-electron diffraction (microED) may change how we view atomic resolution structural biology, such that well-ordered macrocrystals of protein complexes are not required for interface identification. However, some drug discovery applications, such as lead peptide compound generation, may not require atomic resolution; mass spectrometry techniques can provide an expedited path to generation of lead compounds. New crosslinking compounds, more user-friendly data analysis, and novel protocols such as protein painting can advance drug discovery programs, even in the absence of atomic resolution structural data. Finally, artificial intelligence and machine learning methods, while never truly replacing experimental methods, may provide rational ways to stratify potential druggable regions identified with mass spectrometry into higher and lower priority candidates.

SUMMARY

Electron diffraction of nanocrystals combines the benefits of both x-ray diffraction and cryoEM, and may prove to be the next generation of atomic resolution protein-protein interface identification. However, in situations such as peptide drug discovery, mass spectrometry techniques supported by advancements in computational methods will likely prove sufficient to support drug discovery efforts. In addition, these methods can be significantly faster than any crystallographic or cryoEM methods for identification of interacting regions.