Journal: Cancer Science

Article Title: Alternative magnetic field exposure suppresses tumor growth via metabolic reprogramming

doi: 10.1111/cas.16243

Figure Lengend Snippet: Suppression of cancer cell proliferation by AMF at 227 kHz for more than 30 min. (A) The effect of different frequencies (kHz) of AMF (250 Amrs) on the proliferation of GB cell lines (U87 and LN229). XTT cell proliferation assays were conducted at various AMF frequencies (kHz) for 30 min, with evaluation occurring 24 h post‐AMF exposure ( n = 4, * p < 0.05, ** p < 0.01, *** p < 0.001 vs. 0 kHz). (B) The impact of varying electric current intensities (Arms) in AMF (227 kHz) on the proliferation of GBM cell lines (U87 and LN229) ( n = 4, ns, not significant, * p < 0.05, ** p < 0.01, *** p < 0.001 vs. 0 Arms). (C) The effect of different exposure durations (min) to AMF (227 kHz, 250 Amrs) on the proliferation of GBM cell lines (LN229, U251) ( n = 4, ns, not significant, * p < 0.05, ** p < 0.01, *** p < 0.001 vs. 0 min). (D) The influence of AMF (227 kHz, 250 Amrs) on other GB cell lines (U251, T98, and A172), a pancreatic cell line (PANC1), human breast cancer cell lines (MCF7, MDA‐MB‐231, MDA‐MB‐453), normal human astrocyte (NHA), human cardiac fibroblast (HCF), and human umbilical vein endothelial cells (HUVEC) ( n = 4, ns, not significant, * p < 0.05, ** p < 0.01, *** p < 0.001 vs. CTRL). (E, F) Continuous monitoring of cell growth with and without a 30‐min AMF exposure (227 kHz, 250 Arms) in U251 and LN229 cell lines. In vitro cell proliferation was measured using the xCELLigence Real‐Time Cellular Analysis system. (G) Cell cycle analysis 3 and 24 h post‐AMF exposure (227 kHz, 250 Arms, 30 min), revealing the inhibitory effect of AMF, notably the induction of S and G2 phase arrest ( n = 4, ns, not significant, ** p < 0.01, *** p < 0.001 vs. CTRL). (H) Immunoblot analysis of phosphorylated and unphosphorylated forms of p53, p21, CDK2, Cyclin A, Cyclin B1, Cyclin D1, Cyclin E, and GAPDH 24 h after a 30‐min AMF exposure (227 kHz, 250 Arms) ( n = 4, ns, not significant, ** p < 0.01, *** p < 0.001 vs. CTRL).

Article Snippet: T98G (T98, CRL‐1690), U‐87 MG (U87, HTB‐14), and LN‐229 (LN229, CRL‐2611) were purchased from American Type Culture Collection (ATCC, VA, USA).

Techniques: In Vitro, Cell Cycle Assay, Western Blot

Journal: Cancer Science

Article Title: Alternative magnetic field exposure suppresses tumor growth via metabolic reprogramming

doi: 10.1111/cas.16243

Figure Lengend Snippet: Anti‐cancer effects of AMF in mice subcutaneous and brain GBM models. (A) Changes in the volume (mm 3 ) of subcutaneous tumors (U87 and LN229 cells) over 14 days in the control group versus the AMF treatment (227 KHz, 250 Amrs, 30 min per session) group. (B) Photographs of tumors from subcutaneous implantation of U87 cells (control and AMF treatment groups). (C) Representative images of brain tumor sections following H&E staining and Ki‐67 staining. The left images are from the control group, and the right images are from the AMF treatment group ( n = 4). The graph shows the ratio of Ki‐67 positive cells in both the control and AMF treatment groups. White arrows indicate positive area. Calibration bar: 500 μm. (D) Schedule of AMF treatment for the mouse brain GBM model: 227 kHz, 250 Arms, 30 min per session, 5 times per week for a duration of 2 weeks. (E) Representative images from the in vivo imaging system (IVIS) images of mouse brains at 6, 11, 16, and 21 days post‐implantation of U87 cells. (F) Luminescent intensity comparison between the control and AMF treatment groups. The graph depicts the time course of tumor volume changes ( n = 6). (G) Overall survival curve of mice in the study. The blue line represents the survival percentage (%) in the AMF‐treated group, while the black line represents survival in the control group (without AMF treatment).

Article Snippet: T98G (T98, CRL‐1690), U‐87 MG (U87, HTB‐14), and LN‐229 (LN229, CRL‐2611) were purchased from American Type Culture Collection (ATCC, VA, USA).

Techniques: Control, Staining, In Vivo Imaging, Comparison

Journal: Cancer Science

Article Title: Alternative magnetic field exposure suppresses tumor growth via metabolic reprogramming

doi: 10.1111/cas.16243

Figure Lengend Snippet: Comprehensive analysis of protein expression and phosphorylation induced by AMF in GBM cells. (A) Timeline for conducting the microarray analysis. (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis illustrating pathways that are enriched with differentially expressed genes. Comparison made between proteins collected from U87 cells exposed to 30 min of AMF (250 kHz, 250 Arms) and those from U87 control cells (without AMF). (C) Timeline for the iTRAQ phosphorylated protein analysis. (D) Changes in protein expression induced by AMF (250 kHz, 250 Arms) in U87 cells. Histograms display the count of proteins whose phosphorylation levels were either upregulated (red) (>1.5‐fold) or downregulated (blue) (<1.5‐fold) following AMF exposure at 0.5, 1, and 2 h. (E) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showing pathways enriched with differentially expressed genes. Comparison made between proteins collected from U87 cells 0.5 h post‐AMF exposure and proteins from GBM cells not exposed to AMF.

Article Snippet: T98G (T98, CRL‐1690), U‐87 MG (U87, HTB‐14), and LN‐229 (LN229, CRL‐2611) were purchased from American Type Culture Collection (ATCC, VA, USA).

Techniques: Expressing, Phospho-proteomics, Microarray, Comparison, Control, Multiplex sample analysis

Journal: Cancer Science

Article Title: Alternative magnetic field exposure suppresses tumor growth via metabolic reprogramming

doi: 10.1111/cas.16243

Figure Lengend Snippet: AMF promotes ROS production and increases MnSOD. (A) Increase in mitochondrial membrane potential in U87 cells following 30 min of AMF exposure ( n = 4, ns, not significant, * p < 0.05, *** p < 0.001 vs. CTRL). (B) Measurement of ROS production in U87 cells at 0, 24, and 48 h post 30‐min AMF exposure ( n = 4, ns, not significant, * p < 0.05, ** p < 0.01, *** p < 0.001 vs. CTRL). (C) ROS production in U87 cells treated with 10 μM potassium cyanide (KCN) following 30 min of AMF exposure ( n = 4). (D) ROS production in U87 cells treated with 5 mM NAC following 30 min of AMF exposure ( n = 4). (E) Immunoblot analysis of MnSOD, Cu/ZnSOD, and cytochrome c protein expression in GBM cells (LN229) exposed to AMF for 30 min at various time points (0, 5, 15, 30 min, 1, 6, 12, 24, 48 h) ( n = 4). (F) Immunoblot analysis of MnSOD phosphorylation and protein expression 6 h post‐AMF exposure for 30 min, with or without 10 μM KCN in LN229 cells ( n = 4). (G) Immunoblot analysis of MnSOD phosphorylation and protein expression 6 h post‐AMF exposure for 30 min, with or without 5 mM NAC in LN229 cells ( n = 4). In all these experiments, the AMF was conducted under conditions of 227 kHz and 250 Arms.

Article Snippet: T98G (T98, CRL‐1690), U‐87 MG (U87, HTB‐14), and LN‐229 (LN229, CRL‐2611) were purchased from American Type Culture Collection (ATCC, VA, USA).

Techniques: Membrane, Western Blot, Expressing, Phospho-proteomics

Journal: Cellular signalling

Article Title: The gep proto-oncogene Gα 12 mediates LPA-stimulated activation of CREB in ovarian cancer cells

doi: 10.1016/j.cellsig.2013.08.012

Figure Lengend Snippet: A. Silencing of Gα12 in HeyA8 cells using Gα12-specific shRNA was monitored by immunoblot analysis using lysates of 25 µg protein derived from three distinct clones of Gα12-silenced cells along with cells from vector control clone. B. Gα12-shRNA-HeyA8 clones were analyzed by quantitative RT-PCR for Gα12 expression. The expression levels of Gα12 for each clone in relation to vector control cells are presented in the bar graph. C. Hey cells stably expressing shRNA against Gα12 or the vector alone (non-specific scrambled shRNA vector) were serumstarved overnight. The stably silenced Gα12 cells were treated with 20 µM of LPA for 16 hours along with one group of HeyA8 cells stably-expressing the vector alone. Additionally, one group of the vector control cells was left in serum-free media for the 16-hour treatment period. After the 16-hour treatment, nuclear lysate was obtained from each cell group and analyzed by a Protein/DNA array according to manufacturer’s protocol. Representative array data from two independent experiments are presented. Each spot on the array that corresponds to a specific transcription factor was identified according to manufacturer’s protocol. Transcription factors stimulated by LPA but absent or down-regulated in Gα12-silenced cells are scored. The arrows indicate the spots corresponding to CREB. The profiles of activated transcription factors as indicated by the binding of the respective transcription factors to the DNA-elements printed in the array were analyzed in serum-starved HeyA8 cells (Upper Panel), HeyA8 cells stimulated with LPA (Middle Panel), and LPA-stimulated HeyA8 cells in which the expression of Gα12 was silenced (Lower Panel).

Article Snippet: The nuclear lysate was then analyzed for transcription factor activation using an Affymetrix Combo Protein/DNA Array (MA1215; Santa Clara, CA) according to the manufacture’s instructions.

Techniques: shRNA, Western Blot, Derivative Assay, Clone Assay, Plasmid Preparation, Quantitative RT-PCR, Expressing, Stable Transfection, DNA Array, Binding Assay

Journal: Cellular signalling

Article Title: The gep proto-oncogene Gα 12 mediates LPA-stimulated activation of CREB in ovarian cancer cells

doi: 10.1016/j.cellsig.2013.08.012

Figure Lengend Snippet: LPA-stimulated and Gα 12 -dependent Transcription Factors in HeyA8 Cells Control HeyA8 cell expressing non-specific sh-vector or HeyA8 cells in which Gα 12 were stimulated with 20 µM LPA for 16 hrs. Nuclear extracts from these cells along with unstimulated controls were analyzed for the activation of different transcription factors using “Affymetrix Combo Protein/DNA Array” as described under Methods section. Representative array data from two independent experiments are presented here. Each spot on the array, which corresponds to a specific transcription factor, was identified using the template from the user manual. The intensities of the spots were quantified using Carestream Molecular Imaging Software version 5. Transcription factors stimulated by LPA but absent or down-regulated in Gα 12 -silenced cells were scored, quantified, and tabulated.

Article Snippet: The nuclear lysate was then analyzed for transcription factor activation using an Affymetrix Combo Protein/DNA Array (MA1215; Santa Clara, CA) according to the manufacture’s instructions.

Techniques: Expressing, Activation Assay, Imaging, Software, Inhibition, Binding Assay, Methylation

Journal: Molecular Plant Pathology

Article Title: Distinguishing bacterial pathogens of potato using a genome‐wide microarray approach

doi: 10.1111/j.1364-3703.2008.00482.x

Figure Lengend Snippet: Percentage of probes that recognized four bacterial species tested by microarray analysis.

Article Snippet: Image and data analysis Microarray slides were scanned with a GenePix 4200 AL scanner (Axon Instruments, Foster City, CA) using a pixel resolution of 5 μm.

Techniques: Microarray

Journal: Molecular Plant Pathology

Article Title: Distinguishing bacterial pathogens of potato using a genome‐wide microarray approach

doi: 10.1111/j.1364-3703.2008.00482.x

Figure Lengend Snippet: Scanned images of the signals detected on the microarray. A view of the whole microarray with eight subarrays is shown in (A), whereas areas covered by c. 800 probes (of the total of 9676 probes of one subarray) are shown at higher magnification in B and C. Total DNA extracted from pure cultures of bacteria and pooled from several strains of each species was used for hybridization. (A) Two samples were hybridized on each of the eight subarrays. The sample labelled with Cy5 (red) in all eight subarrays was Pectobacterium atrosepticum. The other samples labelled with Cy3 (illustrated as green) were (1) Streptomyces scabies, (2) Dickeya sp., (3) P. carotovorum, (4) Clavibacter michiganensis, (5) P. atrosepticum and (6–8) S. turgidiscabies. The amount of DNA per sample was 500 ng in subarrays 1–6. Signals were clear also with 50 ng of sample DNA (dilution 1 : 10, subarray 7). The image shown here was scanned using constant laser power and detector gain, and signals in subarray 8 (5 ng of DNA; dilution 1 : 100) cannot be seen. However, using increased detector gain, the most species‐specific signals (highest signal intensity) could be detected on subarray 8. (B) Magnification of a part of subarray 5: two samples of P. atrosepticum labelled each with a different dye. Intensive yellow spots (equal hybridization) correspond to probes specific to P. atrosepticum, whereas the spots with faint signal indicate non‐specific hybridization. (C) Magnification of part of the subarray 1: P. atrosepticum labelled with Cy5 and S. scabies labelled with Cy3. A ‘black spot’ (no signal) indicates no hybridization with the probe. The probes were designed to be gene‐specific, taking the whole‐genome sequence information of the species into consideration. Results indicate that most probes detect only the respective species based on which the probes were designed.

Article Snippet: Image and data analysis Microarray slides were scanned with a GenePix 4200 AL scanner (Axon Instruments, Foster City, CA) using a pixel resolution of 5 μm.

Techniques: Microarray, Bacteria, Hybridization, Sequencing

Journal: Molecular Plant Pathology

Article Title: Distinguishing bacterial pathogens of potato using a genome‐wide microarray approach

doi: 10.1111/j.1364-3703.2008.00482.x

Figure Lengend Snippet: Pooled DNA of the strains of Clavibacter michiganensis ssp. sepedonicus (Cms) (labelled with Cy3) and Pectobacterium atrosepticum (Pat) (labelled with Cy5) analysed on the microarray. (A) Scatterplot shows signal intensities from each probe on the array. Signals for Cms are given on the x‐axis and those for Pat on the y‐axis. Data reveal that the samples are not detected with common probes giving high signal intensities. (B) The scatterplot presented in a logarithmic domain places the probes within four groups: (1) high signal intensities for both samples (very few probes); (2) non‐specific probes detecting both samples (relatively low signal intensities); (3) probes giving high signal intensities only for Pat; and (4) probes giving high signal intensities only for Cms. In (C) (Cms) and (D) (Pat), the histograms of the logarithmic signal intensities show three peaks (histograms smoothened by the kernel density method). A threshold value of ~10 separates the two right‐most peaks (II and III) corresponding to the non‐specific and specific probes, respectively, as shown in B. The threshold value corresponds to the raw (non‐logarithmic) intensity value of c. 1000. In (E) (Cms) and (F) (Pat) the hybridization signal intensities are indicated per groups of probes. In the boxplot, the horizontal line in the middle of the box indicates the median value of the data. The box itself shows the first and third quartile of data. Whiskers outside the box indicate the range of data up to 1.5× the box height from both ends. Data beyond these limits are shown as circles. The intensity values of all probes are shown; however, in the final classification, the probes with intensities below the threshold obtained from the intensity histogram would be eliminated. Abbreviations used in the probe group names: Pat, P. atrosepticum; Sca, S. scabies; Cms, C. michiganensis spp. sepedonicus; IGS, 16S–23S intergenic spacer; Pca, P. carotovorum; IGS Dic, probes to the IGS of Dickeya spp.; Stu, S. turgidiscabies; Rso, R. solanacearum; nip, gene for necrosis‐inducing protein; Dic Nip30‐Nip50, probes of different lengths (30–50 nt) designed for the nip gene of D. dadantii; PAI, pathogenicity island.

Article Snippet: Image and data analysis Microarray slides were scanned with a GenePix 4200 AL scanner (Axon Instruments, Foster City, CA) using a pixel resolution of 5 μm.

Techniques: Microarray, Hybridization

Journal: Molecular Plant Pathology

Article Title: Distinguishing bacterial pathogens of potato using a genome‐wide microarray approach

doi: 10.1111/j.1364-3703.2008.00482.x

Figure Lengend Snippet: Pooled DNA of the strains of Streptomyces scabies (Sca) and S. turgidiscabies (Stu) analysed on the microarray. (A) Scatterplot showing signal intensities from each probe on the array. Signals for Sca are given on the x‐axis and those for Stu on the y‐axis. (B) The scatterplot presented on a logarithmic scale places the probes within four groups: (1) high signal intensities for both samples [of the total of 3894 probes designed to target genes of Sca, 1462 probes (c. 40%) show high signal intensities also for Stu]; (2) non‐specific probes giving relatively weak signals for both samples; (3) probes giving high signals only for Stu; and (4) probes giving high signals only for Sc. In (C) (Sca) and (D) (Stu), the histograms of the logarithmic signal intensities show three peaks corresponding to the groups of probes in B, as explained in Fig. 2. In (E) (Sca) and (F) (Stu) the hybridization signal intensities are indicated per three groups of probes. Interpretation of the boxplots is as in Fig. 1. The data indicate that the probes targeting the 16S–23S intergenic spacer (IGS) can be used to distinguish the two species.

Article Snippet: Image and data analysis Microarray slides were scanned with a GenePix 4200 AL scanner (Axon Instruments, Foster City, CA) using a pixel resolution of 5 μm.

Techniques: Microarray, Hybridization

Journal: Nucleic Acids Research

Article Title: Array-based evolution of DNA aptamers allows modelling of an explicit sequence-fitness landscape

doi: 10.1093/nar/gkn899

Figure Lengend Snippet: Schematic of the CLADE approach. CLADE as utilized in this study starts at the top of the schematic with an initial choice of DNA sequences. These sequences may be generated entirely in silico , or optionally, as with some of the sequences here, utilizing prior knowledge generated in vitro . These sequences are synthesized on a custom microarray and bound with the chosen ligand, here the APC protein. Analysis of binding intensities gives a distribution of fitnesses; the frequency distribution of Generation 1 binding to APC protein is shown by way of example. Some of these sequences are selected in silico , based on the in vitro score distribution, here using tournament selection (see Materials and methods section). These sequences are then mutated in silico to generate a new sequence set which can then be synthesised in vitro , and so on round the cycle as often as is required. The final aptamer set offers a greatly increased binding affinity to the ligand.

Article Snippet: Image analysis used Combimatrix Microarray Imager ( https://webapps.combimatrix.com/customarray/customarrayHome.jsp ).

Techniques: Generated, In Silico, In Vitro, Synthesized, Microarray, Protein Binding, Binding Assay, Selection, Sequencing

Journal: Cancer Cell

Article Title: Human Tumor-Associated Macrophage and Monocyte Transcriptional Landscapes Reveal Cancer-Specific Reprogramming, Biomarkers, and Therapeutic Targets

doi: 10.1016/j.ccell.2019.02.009

Figure Lengend Snippet:

Article Snippet: Migration was recorded every hour for 72 hr using the IncuCyte system (Essen Bioscience) and number of cells migrated was calculated using IncuCyte quantification software.

Techniques: Recombinant, Enzyme-linked Immunosorbent Assay, CCK-8 Assay, Chemotaxis Assay, Microarray, Software

Journal: Bioactive Materials

Article Title: Amphiphilic cytokine traps remodel marrow adipose tissue for hematopoietic microenvironment amelioration

doi: 10.1016/j.bioactmat.2024.08.032

Figure Lengend Snippet: Changes, especially browning, in the expression of proteins about adipocyte metabolism in marrow induced by AC-gelatin composites. (A) Fluorescence colocalization imaging of the UCP1 + adipocytes through represented by UCP1 and Plin (white triangles); all scale bars are 200 μm. (B) MAT browning promotion by AC-gelatin at 5 weeks in statistics of Fig. A. (C) Protein expression tests of osteo-organoid and bone marrow by Western blotting; β-tubulin, a protein expressed stably in adipocytes, was used as the internal reference. (D) Protein expression tests of whole marrow by protein microarray (Proteome Profiler Mouse Adipokine Array Kit, R&D Systems) and the quantified data (E). Error bars: mean ± SD; n = 2 (Fig. E, number of wells) or 3 (the others, number of mice); * p < 0.05, ** p < 0.01, **** p < 0.0001, two-way ANOVA.

Article Snippet: Changes, especially browning, in the expression of proteins about adipocyte metabolism in marrow induced by AC-gelatin composites. (A) Fluorescence colocalization imaging of the UCP1 + adipocytes through represented by UCP1 and Plin (white triangles); all scale bars are 200 μm. (B) MAT browning promotion by AC-gelatin at 5 weeks in statistics of Fig. A. (C) Protein expression tests of osteo-organoid and bone marrow by Western blotting; β-tubulin, a protein expressed stably in adipocytes, was used as the internal reference. (D) Protein expression tests of whole marrow by protein microarray (Proteome Profiler Mouse Adipokine Array Kit, R&D Systems) and the quantified data (E).

Techniques: Expressing, Fluorescence, Imaging, Western Blot, Stable Transfection, Microarray

Journal: Nature

Article Title: Human germinal centres engage memory and naïve B cells after influenza vaccination

doi: 10.1038/s41586-020-2711-0

Figure Lengend Snippet: a) Binding of group 1–binding mAbs generated from singly sorted PBs and GC B cells that overlapped clonally (purple) or did not overlap (red and blue) for PB and GC B cells, respectively, from participant 05 using an influenza virus protein microarray (IVPM). Scale bar is median fluorescence intensity. Vaccine strains in bold type; underlined strains circulated in humans in participants’ lifetimes. b) Percentages of mAbs that bound two or more HA strains from participants 04, 05, and 11 from GC clones that did not participate in the early PB response (blue) and from PB and shared clones (red). P -values from Fisher’s exact test. The number of mAbs is indicated in the middle of the charts. c) Polyclonal epitopes of Fabs from plasma at indicated timepoints from participants 04, 05, and 11 with HA from A/Michigan/45/2015. Epitopes were determined by 3D reconstructions and/or 2D class averages (images to bottom right of 3D reconstructions). HA proteins shown in grey; Fabs shown in multiple colors. d) Monoclonal and polyclonal epitopes of immune complexes with HA from A/Michigan/45/2015 and Fabs generated from the indicated GC mAbs (blue) and plasma pAbs (red). Fabs with dashed outlines have predicted epitopes due to limited particle representation. e) Protection of GC mAbs 1B05 and 2C09 in a mouse influenza virus challenge model. Mice received 5 mg/kg of the indicated mAb intraperitoneally 1 day before intranasal challenge with A/California/04/2009 E3 (H1N1), and were weighed daily; 7 mice were used for 1B05 and 1G01, 6 for 2C09 and isotype control, and 5 for uninfected. Error bars indicate mean ±SEM.

Article Snippet: Arrays were imaged and analyzed with a Vidia microarray scanner (Indevr) using an exposure time of 1000 ms to measure spot median fluorescence.

Techniques: Binding Assay, Generated, Virus, Microarray, Fluorescence, Clone Assay, Clinical Proteomics, Control

Journal: bioRxiv

Article Title: Identification of senescence-associated drivers of tumour growth and progression using a novel microarray platform

doi: 10.64898/2025.12.20.695739

Figure Lengend Snippet: Microenvironment microarray (MEMA) facilitates identification of senescence secretory phenotype factors (SASPs) involved in promoting proliferation of human mammary epithelial cells (HMECs) and alveolar lung adenocarcinoma A549 cells. (a) SASP as a driver of pre-neoplastic cell growth and progression. Following unrepairable stress or damage, cells can become senescent and drive expansion of preneoplastic cells through SASP. The exact SASP factors that are most responsible for driving this growth remain incompletely understood. (b) Spot cell count for HMEC cells showing conditions that enhance cell numbers (c) Spot cell count for A549 cells showing conditions that enhance cell numbers. (d) EdU positive proportion, ranked by ligand from low to high, for the HMEC cells. (e) EdU positive proportion, ranked by ECM from low to high, for the A549 cells.

Article Snippet: For tumour imaging of in vivo experiments, A549-Luc2 cells was obtained from ATCC and cultured using the same condition as A549 cells.

Techniques: Microarray, Cell Counting

Journal: bioRxiv

Article Title: Identification of senescence-associated drivers of tumour growth and progression using a novel microarray platform

doi: 10.64898/2025.12.20.695739

Figure Lengend Snippet: Targets identified from MEMA are validated using colony formation and live IncuCyte imaging assays. (a) HMEC were treated with different MEMA-identified hits with results for colony formation in cells immortalized cells derived from old vs. young donors showing significant enhancement of colony formation, particularly with TGF-β1 treatment in cells from aged donors. (b) Crystal violet quantification of colony numbers in control vs. TGF-β1 treated 237D1MYL HMEC cells. Triplicate samples were run and mean ± S.D. was plotted; * indicates p<0.05 by t-test. (c) Heat map summarizing the effects of IL-6, HGF, ANG TGF-β1, and TGF-β2 in 5 different HMEC cell strains tested. Strains are grouped by patient age as pre-menopausal (age 18-21) or post-menopausal (age 55-66), and individual cell lines names are color-coded by their mutational progression status; see Sup. Table 1 for cell line details. * indicates significantly different (p<0.05) from control cells by ANOVA. (d) Example of IL-6 enhanced growth of primary cells (153L; left panel) vs. immortalized but not normal HMEC cells (153LD1MY; right panel) in live cell imaging experiments. All live cell imaging experiments were performed with four replicates and mean ± S.E.M. was plotted. **** indicates p<0.001 by t-test. (e-f) Validation of MEMA hits in normal human bronchial epithelial cells (HBECs) (left panels) or A549 (right panels). Data of 3-4 biological replicates are shown as mean ± S.E.M. * indicates p<0.05 and ** indicates p<0.01 by t-test.

Article Snippet: For tumour imaging of in vivo experiments, A549-Luc2 cells was obtained from ATCC and cultured using the same condition as A549 cells.

Techniques: Imaging, Derivative Assay, Control, Live Cell Imaging, Biomarker Discovery

Journal: bioRxiv

Article Title: Identification of senescence-associated drivers of tumour growth and progression using a novel microarray platform

doi: 10.64898/2025.12.20.695739

Figure Lengend Snippet: Senescent conditioned media (CM) promote growth of A549 cells through SASP factor EGF1. (a) Growth promotion of A549 cells by senescent CM compared to control CM of human pulmonary fibroblasts – adult (HPF-a). Cells were seeded at a density of 25,000 cells per well in a 24-well plate the day before treated with indicated CM. Real-time cell growth was monitored using IncuCyte® SX5 Live-Cell Analysis Instrument (Sartorius AG) for 3-5 days. Cell growth was analysed using the IncuCyte® software and manifested as percentage over the baseline confluence. Data of 6 biological replicates are shown as mean ± SD. **indicates significant difference (p<0.01) from cells treated with Ctrl CM as determined by ANOVA analysis. (b-c) Secretome analysis of CM from control or senescent HPF-a. CM were harvested after 72-h incubation with corresponding HPF-a and the components were evaluated using Proteome Profiler Human XL Cytokine Array kit (#ARY022B, R&D Systems). VCAM-1, vascular cell adhesion molecule 1. The original blots (b) and quantification results are shown as heatmap (c) . (d) Validation of EGF1 level in CM with ELISA. The CM were harvested and subjected to ELISA (#DEG00, R&D Systems) for determining the amounts of EGF1 with normalization based on cell contents. Data of 6 biological replicates are shown as mean ± SD. *p < 0.05; ** p < 0.01 as determined by ANOVA analysis. ns, not statistically significant. (e) Reversion of CM-enhanced cell growth by EGF receptor blocker gefitinib (Gef). A549 cells were cotreated with CM from control or senescent HPF-a with or without gefitinib (2.5 μM) before subjected to IncuCyte® SX5 Live-Cell Analysis Instrument (Sartorius AG) for 3-5 days. Representative data of 3 independent biological repeats are shown as mean ± SD. **** p < 0.0001 as determined by ANOVA analysis. (f-h) Reversion of CM-enhanced colony formation by EGF receptor blocker gefitinib (Gef). A549 cells were seeded at a density of 750 cells per well in a 6-well plate the day before treatment with designated HPF-a CM and/or gefitinib for 15 days. Treatment was refreshed every 2-3 days. Colonies were stained with crystal violet and images were scanned for quantification as described in the methodology. Representative images (f) , colony count (g) , and OD595 (h) of 3-4 independent biological replicates are shown as mean ± SD. *p < 0.05; ** p < 0.01; *** p < 0.001 as determined by ANOVA analysis.

Article Snippet: For tumour imaging of in vivo experiments, A549-Luc2 cells was obtained from ATCC and cultured using the same condition as A549 cells.

Techniques: Control, Cell Analysis, Software, Incubation, Biomarker Discovery, Enzyme-linked Immunosorbent Assay, Staining

Journal: bioRxiv

Article Title: Identification of senescence-associated drivers of tumour growth and progression using a novel microarray platform

doi: 10.64898/2025.12.20.695739

Figure Lengend Snippet: Context-dependent gene expression profiles in response to SASP factors. Cells were treated with corresponding SASP factors for 6 h before subjected to RNA extraction and subsequent RNAseq. Heatmaps for lung ( a ) and HMEC ( b ) cells showing the genes with the largest differential expression as a result of treatment with the indicated ligands. GSEA analysis using KEGG databases show significantly altered pathways and processes in A549 cells treated with IL-6 ( c ) and EGF ( d ). GSEA analysis using KEGG databases show significantly altered pathways and processes in 122L, 153L, or 240L HMEC cell lines treated with IL-6 ( e ) or TGF-β1 ( f ). Dot size indicates number of genes within a given set and colour indicated adjusted p-value.

Article Snippet: For tumour imaging of in vivo experiments, A549-Luc2 cells was obtained from ATCC and cultured using the same condition as A549 cells.

Techniques: Gene Expression, RNA Extraction, Quantitative Proteomics

Journal: bioRxiv

Article Title: Identification of senescence-associated drivers of tumour growth and progression using a novel microarray platform

doi: 10.64898/2025.12.20.695739

Figure Lengend Snippet: Systematic in vivo blockade of EGF receptor alleviates the tumour growth promoted by senescent microenvironment. ( a ) Work scheme of mice model bearing xenografts with A549-Luc2 cells alone or co-injected with control or senescent HPF-a. IVIS, in vivo imaging system. ( b-c ) Tumor measures prior to treatment with gefitinib. Total tumor volumes were calculated based on calliper measurement ( b ) whilst the tumor growth attributed to A549-Luc2 cells was evaluated using D-Luciferin and IVIS Spectrum Xenogen imaging system (Caliper Life Sciences) and analysed with Living Image ® software (ver 4.5.5) ( c ). p values are determined using ANOVA analysis. ( d-e ) Representative images ( d ) and quantification results ( e ) of tumor development after completing gefitinib treating regimen. Data are shown as mean ± SD with each data point representing per tumor. One-sided t-test was used to evaluate statistically the effect of senescent HPF-a on promoting the tumour growth and gefitinib on reversing such enhancement.

Article Snippet: For tumour imaging of in vivo experiments, A549-Luc2 cells was obtained from ATCC and cultured using the same condition as A549 cells.

Techniques: In Vivo, Injection, Control, In Vivo Imaging, Imaging, Software