OTHR-14 - Lucy Boyce Kennedy.mp4
An immunogenomic analysis of melanoma brain metastases (MBM) compared to extracranial metastases (ECM)
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Lucy Boyce Kennedy1, Amanda E.D. Van Swearingen1,2, Jeff Sheng3, Dadong Zhang3, Xiaodi Qin3, Eric Lipp1, Swaminathan Kumar4, Gao Zhang1, Brent Hanks1, Michael Davies4, Kouros Owzar3, Carey K. Anders1,2, April K.S. Salama1,2
1Duke Cancer Institute, Durham, NC, USA. 2Duke Center for Brain and Spine Metastasis, Durham, NC, USA. 3Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA. 4Department of Melanoma Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
Background: MBM have a unique molecular profile compared to ECM.
Methods: We analyzed a previously published dataset from MD Anderson Cancer Center, including RNA-seq on surgically resected, FFPE MBM and ECM from the same patients. STAR pipeline was used to estimate mRNA abundance. DESeq2 package was used to perform differential gene expression (DGE) analyses. Pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Paired DGE and GSEA compared MBM vs. lymph node (LN) metastases (n = 16) and MBM vs. skin mets (n = 10). CIBERSORTx estimated relative abundance of immune cell types in MBM and ECM. GATK Mutect2 pipeline was used to call somatic mutations using paired normal tumor samples. Mutations were annotated using the Ensembl Variant Effect Predictor and visualized using the Maftools package in R.
RNA-seq was available on 54 human primary cutaneous melanomas (CM). Gene Ontology or KEGG Pathway analysis was performed using goana function of limma package in R.
Results: Paired GSEA found that autophagy pathways may be up-regulated in MBM vs. LN and MBM vs. skin mets. On a single-gene level, the most strongly up-regulated genes in autophagy pathways were GFAP and HBB. Fold changes in other autophagy-related genes were low and did not reach significance. Comparison between CM which recurred in brain vs. CM which did not recur identified up-regulation of autophagy pathways. CIBERSORTx identified an increased proportion of immune suppressive M2 macrophages compared to tumor suppressive M1 macrophages in MBMs and ECMs.
Conclusion: Up-regulation of autophagy pathways was observed in patient-matched MBM vs. LN and skin mets. This finding was driven by up-regulation of GFAP and HBB, which could reflect changes in the tumor microenvironment. Higher M2:M1 ratio may contribute to an immune suppressive tumor microenvironment and may be targetable. Validation of our findings in an independent Duke dataset is ongoing.
Contact Presenter
Lucy Boyce Kennedy1, Amanda E.D. Van Swearingen1,2, Jeff Sheng3, Dadong Zhang3, Xiaodi Qin3, Eric Lipp1, Swaminathan Kumar4, Gao Zhang1, Brent Hanks1, Michael Davies4, Kouros Owzar3, Carey K. Anders1,2, April K.S. Salama1,2
1Duke Cancer Institute, Durham, NC, USA. 2Duke Center for Brain and Spine Metastasis, Durham, NC, USA. 3Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA. 4Department of Melanoma Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
Background: MBM have a unique molecular profile compared to ECM.
Methods: We analyzed a previously published dataset from MD Anderson Cancer Center, including RNA-seq on surgically resected, FFPE MBM and ECM from the same patients. STAR pipeline was used to estimate mRNA abundance. DESeq2 package was used to perform differential gene expression (DGE) analyses. Pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Paired DGE and GSEA compared MBM vs. lymph node (LN) metastases (n = 16) and MBM vs. skin mets (n = 10). CIBERSORTx estimated relative abundance of immune cell types in MBM and ECM. GATK Mutect2 pipeline was used to call somatic mutations using paired normal tumor samples. Mutations were annotated using the Ensembl Variant Effect Predictor and visualized using the Maftools package in R.
RNA-seq was available on 54 human primary cutaneous melanomas (CM). Gene Ontology or KEGG Pathway analysis was performed using goana function of limma package in R.
Results: Paired GSEA found that autophagy pathways may be up-regulated in MBM vs. LN and MBM vs. skin mets. On a single-gene level, the most strongly up-regulated genes in autophagy pathways were GFAP and HBB. Fold changes in other autophagy-related genes were low and did not reach significance. Comparison between CM which recurred in brain vs. CM which did not recur identified up-regulation of autophagy pathways. CIBERSORTx identified an increased proportion of immune suppressive M2 macrophages compared to tumor suppressive M1 macrophages in MBMs and ECMs.
Conclusion: Up-regulation of autophagy pathways was observed in patient-matched MBM vs. LN and skin mets. This finding was driven by up-regulation of GFAP and HBB, which could reflect changes in the tumor microenvironment. Higher M2:M1 ratio may contribute to an immune suppressive tumor microenvironment and may be targetable. Validation of our findings in an independent Duke dataset is ongoing.