Journal: Molecular Therapy. Nucleic Acids

Article Title: Overexpression of the mitochondrial anti-viral signaling protein, MAVS, in cancers is associated with cell survival and inflammation

doi: 10.1016/j.omtn.2023.07.008

Figure Lengend Snippet: MAVS overexpression in diverse types of cancer (A–C) Formalin-fixed and paraffin-embedded US-Biomax tissue microarray slides containing the indicated tissues from cancer patients (n = 20) and normal tissue (n = 5) were immunohistochemistry stained using anti-MAVS antibodies and hematoxylin stained, as described in . Representative images from sections of the different indicated tumors and corresponding healthy tissues are shown. The slides were incubated overnight at 4°C with anti-MAVS antibodies in PBS containing 1% BSA and then with secondary antibodies in PBS containing 1% BSA. The slides were subsequently treated with 3′3-diaminobenzidine tetra-hydrochloride (DAB) and counterstained with hematoxylin. Negative controls without primary antibody incubation were also performed. Sections of tissue were observed under an Leica microscope, and images were taken at 200× magnification with the same light intensity and exposure time. The percentage of the tumor sections stained at the intensity indicated on the scale above are presented. (D) Peripheral blood mononuclear cells (PBMCs) were obtained from chronic lymphocytic leukemia (CLL) patients (n = 16) and healthy donors (n = 13) using Ficoll-Paque PLUS (GE Healthcare, Israel) density gradient centrifugation, as described previously. Representative immunoblots of cell lysates of PBMCs derived from CLL patients and healthy donors subjected to SDS-PAGE and immunoblotting using anti-MAVS and anti-actin antibodies are shown. (E) Representative immunoblots using anti-MAVS antibodies of tissue lysates of lung cancer samples from tumor tissue (T, n = 22) and healthy tissue (H, n = 22), each derived from the same lung of a lung cancer patient. (F) Quantification of MAVS levels in CLL and lung cancer patients relative to healthy donors presented as fold change. The results are the mean ± SD. (G) HEK-293, Hela, SHSY-5Y, PC3, A549, MDA-MB-231, and UMUC3 cell lines were grown in the appropriate medium, and cell lysates (10 μg of protein) were subjected to SDS-PAGE and immunoblotting with anti-MAVS and citrate synthase (CS) antibodies (n = 3). (H) Quantitative analysis of MAVS and CS expression levels in the different cell lines were presented relative to the level in SHSY-5Y cells for MAVS and to A549 cells for CS. (I) T-REx-293 cells were transiently transfected with pcDNA3 or MAVS-pcDNA3 using metafectene as in the section. MAVS expression was analyzed by immunoblotting 48 h post transfection. (J) Schematic presentation of the bicistronic nature of the MAVS transcript depicting met1 (methionine1) and met142 (methionine142) as the two translation initiation sites.

Article Snippet: MAVS overexpression in diverse types of cancer (A–C) Formalin-fixed and paraffin-embedded US-Biomax tissue microarray slides containing the indicated tissues from cancer patients (n = 20) and normal tissue (n = 5) were immunohistochemistry stained using anti-MAVS antibodies and hematoxylin stained, as described in .

Techniques: Over Expression, Microarray, Immunohistochemistry, Staining, Incubation, Microscopy, Gradient Centrifugation, Western Blot, Derivative Assay, SDS Page, Expressing, Transfection

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: Identifying top transcription regulators by co-expression and motif analysis associated with the disease phenotypic status of neuroblastoma patients Unique transcription regulators differentiate neuroblastoma patients according to the risk (A), progression (B), and survival (C) in neuroblastoma patient dataset GEO: GSE49710 (n = 498). Transcription regulators in each group are highlighted in red dots and labeled on the plot. The x axis represents different regulons, whereas the y axis indicates rank for specific transcription regulators based on the regulon specificity scores.

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Expressing, Labeling

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: Differential expression analysis distinguishes the expression pattern of oncogene-like and tumor-suppressor-like transcription regulator signatures in neuroblastoma patients The heatmap shows the stratification ability of differentially expressed transcription regulators in neuroblastoma patients (GEO: GSE49710 ; n = 498). Oncogene-like transcription regulators associated with high risk, death, disease progression, and stage 4 are shown in the red box (mean expression: 0.680). Tumor-suppressor-like transcription regulators are shown in the blue box of the bottom cluster (mean expression: −0.303). The labels on the right indicate transcription regulators as official gene symbols, whereas red and blue color coding represents higher and lower expression levels. Annotation tracks are given in the color key at the bottom of the heatmap, reporting neuroblastoma risk, survival, progression, and stages.

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Expressing

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: Regulon specificity score analysis prioritizes SAP30 for association with mortality, disease progression, high risk, and stage 4 in neuroblastoma patients (A) The heatmap prioritizes transcription regulators based on the regulon specificity scores obtained from the neuroblastoma patient dataset GEO: GSE49710 (n = 498). The transcription regulators with high priority are given at the top, while low priority is given at the bottom. SAP30 has the highest priority score and is shown with a red arrow. The labels on the right indicate transcription regulators as official gene symbols, whereas red and blue color coding represent higher and lower regulon specificity score levels. Annotation tracks are given in the color key at the bottom of the heatmap, reporting neuroblastoma MYCN amplification status, age, sex, survival status, progression, risk, and stages. (B) The heatmap shows the regulon specificity score numbers and the prioritization of transcription regulators associated with different disease phenotypes obtained from the neuroblastoma patient dataset GEO: GSE49710 (n = 498). The transcription regulators with high priority are given at the top, while low priority is given at the bottom. SAP30 has the highest priority score and is shown with a red arrow. The labels on the right indicate transcription regulators as official gene symbols, whereas red and blue color coding represent a higher and lower expression of different regulons. Annotation tracks (aggregates [agg] and priority [pri]) are given at the bottom of the heatmap, reporting neuroblastoma disease phenotypes.

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Amplification, Expressing

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: The distribution pattern of transcription regulators in neuroblastoma patients Violin plots show the distribution of transcription regulators expression in different stages of neuroblastoma, in patient datasets GEO: GSE45547 , n = 649 (A), and EMBL: E-MTAB-179 , n = 709 (C). The significance of the differences between different stage patients was determined by an unpaired t test (B and D).

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Expressing

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: SAP30 associates with high-risk status and poor survival in neuroblastoma patients (A and B) Immunofluorescence (A) and western blotting (B) image of SAP30 in low- and high-risk neuroblastoma patients (A), and MYCN -amplified, diagnosis- and progression-specific patient-derived xenograft (PDX) tumors (B). (C and D) Kaplan-Meier curves show the correlation between expression of SAP30 and overall survival (C) or event-free survival (D) from two independent patient datasets GEO: GSE49710 , n = 498 (left), and PMID: 32825087 , n = 786 (right). Patients with higher SAP30 had a shorter survival.

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Immunofluorescence, Western Blot, Amplification, Derivative Assay, Expressing

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: Cisplatin resistant patient-derived xenograft tumors cells express higher SAP30 (A and B) Molecular surface (A) and schematic representation (B) of SAP30’s DNA domain, with residues (R, arginine; K, lysine; H, histidine) comprising the nucleolar localization sequence that mediate DNA binding highlighted. (C and D) CRISPR-Cas9 essentiality screen data of neuroblastoma cells show resistance to cisplatin (C) but sensitivity to BRD4 inhibitor drugs (D). (E) Western blotting image of SAP30 in two cisplatin-resistant neuroblastoma cells derived from patient-derived xenograft tumors.

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Derivative Assay, Sequencing, Binding Assay, CRISPR, Western Blot

Journal: Molecular Therapy. Nucleic Acids

Article Title: SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

doi: 10.1016/j.omtn.2022.03.014

Figure Lengend Snippet: SAP30 knockdown inhibits cell viability, induces cell death and mitochondrial membrane potential in neuroblastoma cells in vitro , and reduces tumor burden in vivo in a mouse xenograft model of neuroblastoma (A–D) A representative (A) western blotting image of SAP30 showing the knockdown efficiency, (B) quantification graph of cell viability assay evaluating the effect of SAP30 silencing on cell proliferation, and (C and D) flow cytometry pictures and quantification graphs of (C) cell death analysis and (D) mitochondrial membrane potential in neuroblastoma cells upon stable knockdown of SAP30 using two different shRNAs. (E and F) Tumor burden in (E) NOD/SCID mice receiving a subcutaneous injection of SK-N-B(E)2c cells with SAP30 stably silenced using two different shRNAs and (F) images of the excised tumors of the mice from various treatment groups are given. The data presented are the mean ± SD of three independent experiments. p values were calculated using two-tailed unpaired t tests between SAP30 knockdown and control cells. ∗p < 0.05.

Article Snippet: De-identified formalin-fixed and embedded paraffin blocks of neuroblastoma patient tissue microarray (no. NB642a) were obtained from US Biomax (26 patients’ samples, in duplicates).

Techniques: Membrane, In Vitro, In Vivo, Western Blot, Viability Assay, Flow Cytometry, Injection, Stable Transfection, Two Tailed Test