Screening and identification of potential biomarkers for pancreatic cancer: An integrated bioinformatics analysis

Jafari, Somayeh; Ravan, Milad; Karimi-Sani, Iman; Aria, Hamid; Hasan‐Abad, Amin Moradi; Bahar, Burhanuddin; Atapour, Amir; Sarab, Gholamreza Anani

doi:10.1016/j.prp.2023.154726

Cited by 13 publications

(8 citation statements)

References 69 publications

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“…RN7SKP255 was upregulated in lung adenocarcinoma compared with adjacent non-tumorous tissue [94]. RN7SKP80 has been found to play a contributing factor in distinguishing pancreatic cancer from normal tissue [95]. Overexpression of 7SK has been reported to induce apoptosis by inhibiting cell proliferation in kidney cancer [96].…”

Section: Miscellaneous Rnamentioning

confidence: 99%

Data-driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Nourbakhsh,

Tom,

Schrøder Lassen

et al. 2024

Preprint

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Acute lymphoblastic leukemia (ALL), the most common cancer in children, is overall divided into two subtypes, B-cell precursor ALL (B-ALL) and T-cell ALL (T-ALL), which have different molecular characteristics. Despite massive progress in understanding the disease trajectories of ALL, ALL remains a major cause of death in children. Thus, further research exploring the biological foundations of ALL is essential. Here, we examined the diagnostic, prognostic, and therapeutic potential of gene expression data in pediatric patients with ALL. We discovered a subset of expression markers differentiating B- and T-ALL:CCN2,VPREB3,NDST3,EBF1, RN7SKP185, RN7SKP291, SNORA73B, RN7SKP255, SNORA74A, RN7SKP48, RN7SKP80, LINC00114, a novel gene (ENSG00000227706), and 7SK. The expression level of these markers all demonstrated significant effects on survival of the patients, comparing the two subtypes. We also discovered four expression subgroups in the expression data with eight genes driving separation between two of these predicted subgroups. A subset of the 14 markers could separate B- and T-ALL in an independent cohort of patients with ALL. This study can enhance our knowledge of the transcriptomic profile of different ALL subtypes.

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Section: Miscellaneous Rnamentioning

confidence: 99%

Data-driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Nourbakhsh,

Tom,

Schrøder Lassen

et al. 2024

Preprint

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“…[12] In addition, multiple genetic biomarkers have been identi ed to be dysregulated and are commonly related to metabolism and hormone secretion pathways. [13][14][15] Furthermore, several T2DM polymorphisms have shown a possible relationship with PAAD and other kinds of cancers (e.g.,…”

Section: Introductionmentioning

confidence: 99%

Assessment of genetic alterations found in type 2 diabetes mellitus patients with pancreatic adenocarcinoma

Calderon-Martinez,

Zevallos-Delgado,

Gavilanes

et al. 2024

Preprint

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Purpose In this study, we aim to determine the prognostic effects of genetic mutations identified in pancreatic adenocarcinoma (PAAD) patients with type 2 diabetes mellitus.Method Gepia and cBioPortal were used to assess the TCGA data and other PAAD studies. CBioPortal showed 2963 patients in 14 related studies. Among these participants, 37 had a positive medical history of type 2 diabetes mellitus, while 104 did not.Results Fifteen genes (HTRA3, FANCA, IL4R, NRXN2, GRPEL1, KIAA0232, TTK, WFS1, TBC1D14, CCDC96, USP25, STOML2, TPI1, PLAA, and FASTKD2) have been identified to be involved in the prognosis of the disease based on the number of mutations and survival prognosis in this study. Furthermore, the adverse impact of diabetes mellitus and PAAD are linked to single nucleotide polymorphisms.Conclusion Several genetic alterations found in patients with PAAD and type 2 diabetes mellitus have an impact on the prognosis of PAAD patients.

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“…Cancer is well recognized as a prominent contributor to human mortality ( Sung et al, 2021 ; Malehmir et al, 2023a ; Jafari et al, 2023 ). The uncontrolled proliferation of malignant cells and their spread to other parts of the human body are linked to a variety of disorders known as cancer ( Keyvani et al, 2022 ; Mohammadi M. et al, 2023 ; Malehmir et al, 2023b ).…”

Section: Introductionmentioning

confidence: 99%

The application of peroxidase mimetic nanozymes in cancer diagnosis and therapy

Moradi Hasan-Abad,

Shabankare,

Atapour

et al. 2024

Front. Pharmacol.

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In recent decades, scholarly investigations have predominantly centered on nanomaterials possessing enzyme-like characteristics, commonly referred to as nanozymes. These nanozymes have emerged as viable substitutes for natural enzymes, offering simplicity, stability, and superior performance across various applications. Inorganic nanoparticles have been extensively employed in the emulation of enzymatic activity found in natural systems. Nanoparticles have shown a strong ability to mimic a number of enzyme-like functions. These systems have made a lot of progress thanks to the huge growth in nanotechnology research and the unique properties of nanomaterials. Our presentation will center on the kinetics, processes, and applications of peroxidase-like nanozymes. In this discourse, we will explore the various characteristics that exert an influence on the catalytic activity of nanozymes, with a particular emphasis on the prevailing problems and prospective consequences. This paper presents a thorough examination of the latest advancements achieved in the domain of peroxidase mimetic nanozymes in the context of cancer diagnosis and treatment. The primary focus is on their use in catalytic cancer therapy, alongside chemotherapy, phototherapy, sonodynamic therapy, radiation, and immunotherapy. The primary objective of this work is to offer theoretical and technical assistance for the prospective advancement of anticancer medications based on nanozymes. Moreover, it is anticipated that this will foster the investigation of novel therapeutic strategies aimed at achieving efficacious tumor therapy.

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Screening and identification of potential biomarkers for pancreatic cancer: An integrated bioinformatics analysis

Cited by 13 publications

References 69 publications

Data-driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Data-driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Assessment of genetic alterations found in type 2 diabetes mellitus patients with pancreatic adenocarcinoma

The application of peroxidase mimetic nanozymes in cancer diagnosis and therapy

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