Key candidate genes and pathways in T lymphoblastic leukemia/lymphoma identified by bioinformatics and serological analyses

T-cell acute lymphoblastic leukemia (T-ALL)/T-cell lymphoblastic lymphoma (T-LBL) is an uncommon but highly aggressive hematological malignancy. It has high recurrence and mortality rates and is challenging to treat. This study conducted bioinformatics analyses, compared genetic expression profiles of healthy controls with patients having T-ALL/T-LBL, and verified the results through serological indicators. Data were acquired from the GSE48558 dataset from Gene Expression Omnibus (GEO). T-ALL patients and normal T cells-related differentially expressed genes (DEGs) were investigated using the online analysis tool GEO2R in GEO, identifying 78 upregulated and 130 downregulated genes. Gene Ontology (GO) and protein-protein interaction (PPI) network analyses of the top 10 DEGs showed enrichment in pathways linked to abnormal mitotic cell cycles, chromosomal instability, dysfunction of inflammatory mediators, and functional defects in T-cells, natural killer (NK) cells, and immune checkpoints. The DEGs were then validated by examining blood indices in samples obtained from patients, comparing the T-ALL/T-LBL group with the control group. Significant differences were observed in the levels of various blood components between T-ALL and T-LBL patients. These components include neutrophils, lymphocyte percentage, hemoglobin (HGB), total protein, globulin, erythropoietin (EPO) levels, thrombin time (TT), D-dimer (DD), and C-reactive protein (CRP). Additionally, there were significant differences in peripheral blood leukocyte count, absolute lymphocyte count, creatinine, cholesterol, low-density lipoprotein, folate, and thrombin times. The genes and pathways associated with T-LBL/T-ALL were identified, and peripheral blood HGB, EPO, TT, DD, and CRP were key molecular markers. This will assist the diagnosis of T-ALL/T-LBL, with applications for differential diagnosis, treatment, and prognosis

ONZIN Upregulation by Mutant p53 Contributes to Osteosarcoma Metastasis Through the CXCL5-MAPK Signaling Pathway

Background/Aims: Gain-of-function of mutant p53 is associated with a high rate of lung metastasis in osteosarcoma. To investigate the mechanism of mutant p53-induced osteosarcoma metastasis, expression array analysis was performed, comparing non-metastatic osteosarcomas from p53+/- mice with metastatic osteosarcomas from p53R172H/+ mice. Onzin (Plac8) was identified as one of the genes upregulated in p53R172H/+ mouse metastatic osteosarcomas. Accordingly, we investigated the role of ONZIN in human osteosarcoma metastasis. Methods: ONZIN function and its downstream targets were examined in osteosarcoma cell lines. Assays related to tumorigenesis and metastasis, including cell migration, invasion, clonogenic survival, and soft agar colony formation, were performed in osteosarcoma cells. Additionally, mouse xenograft models were used to examine the role of ONZIN overpression in tumorigenesis in vivo. Lastly, 87 osteosarcoma patients were recruited to investigate the clinical relevance of ONZIN overexpression in metastasis and prognosis. Results: ONZIN overexpression enhanced osteosarcoma cell proliferation, clonogenic survival, migration, and invasion independent of p53 status. Furthermore, ONZIN overexpression induced CXCL5 upregulation and resulted in increased ERK phosphorylation, which contributed to more aggressive osteosarcoma metastatic phenotypes. More importantly, overexpression of ONZIN in human osteosarcoma patients was closely associated with lung metastasis, poor prognoses, and survival. Conclusions: Overexpression of ONZIN promotes osteosarcoma progression and metastasis, and can serve as a clinical biomarker for osteosarcoma metastasis and prognosis

PLA2G16 Expression in Human Osteosarcoma Is Associated with Pulmonary Metastasis and Poor Prognosis

<div><p>Background</p><p>Osteosarcoma is the most frequent type of malignant bone tumor in children and adolescents and is associated with a high propensity for lung metastasis. Recent experiments have indicated that PLA2G16 contributes to osteosarcoma progression and metastasis in both mouse and human osteosarcoma cell lines. The aim of this study was to compare the expression of PLA2G16 in non-metastatic and metastatic osteosarcomas to determine whether PLA2G16 expression can serve as a biomarker of osteosarcoma prognosis and metastasis.</p><p>Methods</p><p>Quantitative real-time PCR was used to examine <i>PLA2G16</i> mRNA in primary osteosarcoma patients (18 patients without metastases and 17 patients with metastases), and immunohistochemistry (IHC) staining of PLA2G16 was performed on tissue microarrays from 119 osteosarcoma patients. Tumor metastatic behavior and survival of the patients were followed up for a minimum of 36 months and a maximum of 171 months. The prognostic value of PLA2G16 expression was evaluated by the Kaplan–Meier method and a log-rank test. Multivariate Cox regression analysis was used to identify significant independent prognostic factors.</p><p>Results</p><p>Osteosarcoma patients with metastasis showed a higher expression of PLA2G16 at both the mRNA and protein levels (both at P values< 0.05) than did patients without metastasis. Osteosarcoma patients with positive IHC staining of PLA2G16 expression at primary sites had shorter overall survival and metastasis-free survival (both at P values <0.02). Moreover, multivariate Cox analysis identified PLA2G16 expression as an independent prognostic factor to predict poor overall survival and metastasis-free survival (both P values < 0.03).</p><p>Conclusions</p><p>This study indicated that PLA2G16 expression is a significant prognostic factor in primary osteosarcoma patients for predicting the development of metastases and poor survival.</p></div

Relationship between PLA2G16 and Clinicopathologic Factors of Patients.

<p>Abbreviation: PLA2G16, Group XVI phospholipase A₂.</p><p>Relationship between PLA2G16 and Clinicopathologic Factors of Patients.</p

Clinicopathologic patient characteristics and univariate survival analysis.

<p>Abbreviation: OS, Overall survival; MFS, Metastasis-free survival; PLA2G16, Group XVI phospholipase A₂.</p><p>Clinicopathologic patient characteristics and univariate survival analysis.</p

Positive PLA2G16 immunohistochemical staining was associated with poor prognosis and survival.

<p>(A) Overall survival (OS)and (B) metastasis-free survival (MFS) of PLA2G16 positive or negative patients was determined by Kaplan-Meier analysis.</p

PLA2G16 expression in osteosarcoma tumors with or without metastasis

<p>The PLA2G16 mRNA levels were determined by real-time quantitative PCR. *denote p values P<0.05.</p

DataSheet_1_Key candidate genes and pathways in T lymphoblastic leukemia/lymphoma identified by bioinformatics and serological analyses.docx

T-cell acute lymphoblastic leukemia (T-ALL)/T-cell lymphoblastic lymphoma (T-LBL) is an uncommon but highly aggressive hematological malignancy. It has high recurrence and mortality rates and is challenging to treat. This study conducted bioinformatics analyses, compared genetic expression profiles of healthy controls with patients having T-ALL/T-LBL, and verified the results through serological indicators. Data were acquired from the GSE48558 dataset from Gene Expression Omnibus (GEO). T-ALL patients and normal T cells-related differentially expressed genes (DEGs) were investigated using the online analysis tool GEO2R in GEO, identifying 78 upregulated and 130 downregulated genes. Gene Ontology (GO) and protein-protein interaction (PPI) network analyses of the top 10 DEGs showed enrichment in pathways linked to abnormal mitotic cell cycles, chromosomal instability, dysfunction of inflammatory mediators, and functional defects in T-cells, natural killer (NK) cells, and immune checkpoints. The DEGs were then validated by examining blood indices in samples obtained from patients, comparing the T-ALL/T-LBL group with the control group. Significant differences were observed in the levels of various blood components between T-ALL and T-LBL patients. These components include neutrophils, lymphocyte percentage, hemoglobin (HGB), total protein, globulin, erythropoietin (EPO) levels, thrombin time (TT), D-dimer (DD), and C-reactive protein (CRP). Additionally, there were significant differences in peripheral blood leukocyte count, absolute lymphocyte count, creatinine, cholesterol, low-density lipoprotein, folate, and thrombin times. The genes and pathways associated with T-LBL/T-ALL were identified, and peripheral blood HGB, EPO, TT, DD, and CRP were key molecular markers. This will assist the diagnosis of T-ALL/T-LBL, with applications for differential diagnosis, treatment, and prognosis.</p