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Teppo, H.-R.

Publications and source records attributed to Teppo, H.-R..

2 recordsLinked to original sources

Pan-cancer scale screening reveals NRF2 associated immunoevasive characteristics in non-small cell lung cancer and squamous malignancies

The NRF2 pathway is frequently activated in various cancer types, yet a comprehensive analysis of its effects across different malignancies is currently lacking. We developed a robust NRF2 activity metric and utilized it to conduct a pan-cancer wide analysis of oncogenic NRF2 signaling. We identified a distinct immunoevasive phenotype where high NRF2 activity is associated with low interferon-gamma (IFN{gamma}), HLA-I expression and T-cell infiltration spanning non-small cell lung cancer (NSCLC) and squamous malignancies of head and neck area, cervix and esophagus. In squamous cell cancers, NRF2 overactive tumors comprise a molecular phenotype with SOX2/TP63 amplification, TP53 mutation and CDKN2A loss. These immune-cold NRF2 hyperactive diseases are associated with upregulation of immunomodulatory NAMPT, WNT5A, SPP1, SLC7A11 and SLC2A1 that represent candidate NRF2 target genes, suggesting direct modulation of the tumor immune milieu. Based on single-cell mRNA data, coupled with a priori information on intercellular ligand-receptor interactions, cancer cells of this subtype exhibit decreased expression of IFN{gamma} responsive ligands, and increased expression of immunosuppressive ligands NAMPT, SPP1 and WNT5A that mediate signaling in intercellular crosstalk. As we observed differential cytokine mRNA expression with IFN{gamma} treatment in NSCLC adenocarcinoma subtype, we explored the cytokine secretome in vitro. We found that secreted neutrophil chemoattractants interleukin-8 (CXCL8) and ENA-78 (CXCL5) are elevated in NRF2 overactive cells, suggesting contribution of immunosuppressive neutrophils in NRF2 driven immune escape. Importantly, as overactive NRF2 is associated with immune-cold characteristics, our results highlight the utility of NRF2 pathway activation as a putative biomarker for stratifying immune-checkpoint blockade responders and non-responders across NSCLC and squamous cancers. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/489654v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1f45782org.highwire.dtl.DTLVardef@9d40d0org.highwire.dtl.DTLVardef@a31a5org.highwire.dtl.DTLVardef@1418220_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Discrimination of melanoma cell lines with Fourier Transform Infrared (FTIR) spectroscopy

Among skin cancers, melanoma is the lethal form and the leading cause of death in humans. Melanoma begins in melanocytes and is curable at early stages. Thus, early detection and evaluation of its metastatic potential are crucial for effective clinical intervention. Fourier transform infrared (FTIR) spectroscopy has gained considerable attention due to its versatility in detecting biochemical and biological features present in the samples. Changes in these features are used to differentiate between samples at different stages of the disease. Previously, FTIR spectroscopy has been mostly used to distinguish between healthy and diseased conditions. With this study, we aim to discriminate between different melanoma cell lines based on their FTIR spectra. Formalin-fixed paraffin embedded samples from three melanoma cell lines (IPC-298, SK-MEL-30 and COLO-800) were used. Statistically significant differences were observed in the prominent spectral bands of three cell lines along with shifts in peak positions. A partial least square discriminant analysis (PLS-DA) model built for the classification of three cell lines showed an overall accuracy of 92.6% with a sensitivity of 85%, 95.75%, 96.54%, and specificity of 97.80%, 92.14%, 98.64% for the differentiation of IPC-298, SK-MEL-30, and COLO-800, respectively. The results suggest that FTIR spectroscopy can differentiate between different melanoma cell lines and thus potentially characterize the metastatic potential of melanoma. Sources of FundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

bioinformatics↗