Cappellesso, R

Fassina, A

Nicolè, L

Sanavia, T

English

Institutional Research Information System University of Turin

Transcriptomics landscape of Necroptosis genes is associated with Dendritic cells infiltration: a pan-cancer study of 5,451 primary solid tumors. Data  Lorenzo Nicolè1, Tiziana Sanavia2, Rocco Cappellesso1, Ambrogio Fassina1  1Department of Medicine (DIMED), Surgical Pathology Unit, University of Padova, Padova - Italy 2Department of Biomedical Informatics, Harvard Medical School, Boston MA - USA BACKGROUND  v  Necroptosis (NPC) is a form of programmed cell death that culminates with the rupture of the cell membrane followed by the releasing of cellular elements1.   v  Evidence showed that tumors with high expression of NCP-related genes are associated with high cytotoxic CD8+ T-cell infiltrates, mediated by signaling from Dendritic (DC) and CD4+ T-cells2.  AIM v  Pan-cancer view of the relationship between NCP and immune infiltration and their prognostic relevance across 24 cancer types from The Cancer Genome Atlas.  v  Evaluate whether there are some immune populations able to interact more with NCP in specific cancer types. METHODS RNAseq	data	•  No	residual	tumor	after	surgery	•  No	previous	treatment		5,451	Primary		Solid	Tumors	Filter	Mixture	tissue	Transcriptome	Cell-type	Deconvolution	(TIMER)3		Dendritic	CD4+		T-cells	Macro-	phage	CD8+		T-cells	 B-cells	Immune	cell	specific	gene	signatures	Genes	Samples	Gene	Expression	Samples	Cell	Type	Proportion	Gene	Expression	>75% High <25% Low INFILTRATION	SCORE	(for	each	immune	population)	Differential	Gene	Expression		(Logistic	regression	with		Tumor	Purity	as	confounder)	Low		Infitration		High		Infitration		163	Genes	from		NCP	Pathway	RESULTS  v  Dendritic and CD4+ T-cells showed the highest number of cancer types (8) reporting more than half genes of NCP pathway significantly correlated with their infiltration. CD8+ T-cell infiltration correlated with >50% of NCP genes in 5 of these 8 cancer types: Kidney-Renal, Breast, Prostate, Pancreatic and Thyroid tumors. B-cells	 CD4-Tcells	 CD8-Tcells	 Macrophage	 Dendritic	0	 0.25	 0.50	 0.75	 1	 0	 0.25	 0.50	 0.75	 1	 0	 0.25	 0.50	 0.75	 1	 0	 0.25	 0.50	 0.75	 1	 0	 0.25	 0.50	 0.75	 1	ACC	BRCA	BLCA	CESC	CHOL	COAD	ESCA	GBM	HNSC	KICH	KIRC	KIRP	LIHC	LUAD	LUSC	OV	PAAD	PCPG	PRAD	SARC	SKCM	STAD	THCA	UCEC	Cancer	Types		Fraction	of	NCP	genes	significantly	correlated	with	the	Infiltration	Score	(FDR>5%)	v  Dendritic cells also showed the highest number of NCP genes (69) correlated with their infiltration in more than half of the analyzed cancer types, including the main genes involved in NCP execution: RIPK1, RIPK3, MLKL and CFLAR. 60 and 58 of these genes showed a prognostic relevance (p<5%) for overall and disease-free survival in at least one cancer type, respectively. 0	5	10	15	20	BIRC2	BIRC3	CAMK2D	CAMK2G	CAPN1	CAPN2	CASP1	CASP8	CFLAR	CHMP2B	CHMP5	CHMP7	CYBB	CYLD	EIF2AK2	FAS	FASLG	FTH1	GLUD2	GLUL	IFNAR1	IFNAR2	IFNG	IFNGR1	IFNGR2	IL1B	IRF9	JAK1	JAK2	JAK3	MAPK8	MAPK9	MLKL	NLRP3	PARP1	PARP3	PARP4	PYCARD	PYGB	PYGL	RIPK1	RIPK3	RNF31	SMPD1	SPATA2	STAT1	STAT2	STAT3	STAT4	STAT5A	STAT5B	STAT6	TICAM1	TICAM2	TLR3	TLR4	TNF	TNFAIP3	TNFRSF10A	TNFRSF10B	TNFRSF1A	TNFSF10	TRADD	TRAF2	TYK2	USP21	VPS4B	XIAP	ZBP1	NCP	Genes	Number	of	Cancer	Types	NCP has a relevant role in eliciting immune response against tumor through Dendritic cell-mediated immunity in specific cancer types, however validation studies on specific cancer type are needed. CONCLUSIONS Contacts:		lorenzo.nic86@gmail.com	REFERENCES 1.  Meng M, Wang H, Cui Y, et al. Necroptosis in tumorigenesis, activation of anti-tumor immunity, and cancer therapy. Oncotarget. 2016;7(35):57391.  2.  Aaes T, Kaczmarek A, Delvaeye T, et al. Vaccination with necroptotic cancer cells induces efficient anti-tumor immunity. Cell Reports. 2016;15(2):274-287.  3.  Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, Li B, Liu XS. TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells. Cancer Res. 2017;77(21):e108-e110 METHODS:	Computational	Analysis	–	Transcriptomics	data		Whole	RNAseq	data	•  No	residual	tumor	after	surgery	•  No	previous	treatment				Li	et	al.	Genome	Biology	2016;17(1):174.		TIMER	Deconvolution	5,451	Primary		Solid	Tumors	Filter	Mixture	tissue		Transcriptome	Immune	Cell		infiltration	score	>75th percentiles High infiltration Differential	Gene	Expression	(Logistic	regression	with	Tumor	Purity	as	confounder)	Low	Infitration		Genes	from	KEGG	Necroptosis	(163)	B-cells CD4 T-cells CD8 T-cells Macrophages Dendritic cells	<25th percentiles Low infiltration High	Infitration		METHODS: Gene expression RNA-seq data from 5,451 primary solid tumors were considered, excluding cases with treatments before surgery and with residual tumor. A deconvolution algorithm was used to estimate the level of tumor-infiltrating immune cells in each RNA-seq sample, considering the populations: B-cells, CD4 T-cells, CD8 T-cells, Macrophages and DC. For each immune population, the relative infiltration score was dichotomized at low and high infiltration using the 25th and 75h percentiles, respectively. Logistic regression and likelihood ratio test were applied to 163 genes belonging to Necroptosis pathway from KEGG database to test whether they are significantly associated to the infiltration of a specific immune population. FDR-adjusted p-values <5% were considered statistically significant. The prognostic relevance of the NCP genes significantly correlated with the infiltration was evaluated by Cox regression and log-rank test.  

Transcriptomics landscape of Necroptosis genes is associated with Dendritic cells infiltration: a pan-cancer study of 5,451 primary solid tumors

207COMUNICAZIONI ORALIMOLECULAR EVALUATION OF CELL-OF-ORIGIN (COO) IN DIFFUSE LARGE B- CELL LYMPHOMASE. Forti, S. Manfredini, L. Liguori, M. Gozzoli, S. Pozzi, A. Bari, S. Sacchi, A. Maiorana, S. BettelliUniversità degli Studi di Modena e Reggio Emilia (UNIMORE), Diparti-mento di Scienze Mediche e Chirurgiche Materno-Infantili e dell’Adulto (SMECHIMAI)Background/Aims. Diffuse large B-cell lymphoma (DLBCL) is one of the most frequent and aggressive B-lymphomas. It represents an heterogeneous group in regard to morphologi-cal features, genetic alterations and clinical behaviour  1. Two distinct molecular subtypes, called Activated B- Cell -like (ABC) and Germinal Center B-cell -like (GCB), have been defined using gene expression profiling (GEP) on the basis of Cell-Of-Origin (COO). This classification acquires a prognostic and therapeutic value and therefore it is important for patient stratification 2. In standard practice, COO is defined by the im-munohistochemistry (IHC)-based Hans algorithm carried-out on formalin-fixed paraffin-embedded (FFPE) tissue  3. Recent technological improvements allow to apply GEP directly on RNA extracted from FFPE tissue. Aim of this study is to vali-date the GEP-approach comparing data obtained with the IHC method.Materials and Methods. A cohort of 83 DLBCL patients was collected for this study. Archival FFPE samples were obtained from the Department of Pathology-AUO Policlinico di Modena. IHC stainings were performed under an automated standardized protocol (Ventana Benchmarks; Ventana, Tucson, USA) using antibodies against CD10, BCL6 and MUM1. The IHC profiling was obtained in accordance with the Hans algo-rithm. mRNA from representative FFPE sections was extracted with an automatic method (Maxell, Promega) and quantified with Expose (Trinean). 50- 500 ngr of total RNA were used for GEP in a NanoString platform (Nanostring Tecnologies, Seattle, USA) with application of the Lymph2Cx panel that includes a 20 gene-code set, as described by Scott et al. 4. Data analysis was performed following the manufacturer’s protocol.Results. Application of Hans algorithm on IHC sections al-lowed to identify 46 ABC (46/83, 55%) and 37 GBC (37/83, 44%) whereas 1 case was Unclassified (1/83,1%). Nanostring Lymph2Cx algorithm identified 26 ABC (26/83, 31%), 43 GCB (43/83, 52%) and 13 Unclassified DLBCL (13/83, 16%). Among the 83 cases, only one failed to meet the required RNA quality for the test. Comparison between IHC- and Lymph2Cx-results showed 57 concordant cases (57/69, 83%) and 12 discordant cases (12/69, 17%), after exclusion of the Failed and molecularly Unclassified samples. In particular, 24 cases were defined as ABC and 33 as GBC by both IHC and Lymph2Cx. Among the 12 discordant results, 10 cases were identified as ABC by IHC examination whereas they were defined as GCB by Nanostring analysis. Moreover, Hans algorithm identified 11 ABC and 2 GBC among the 13 Nanostring Unclassified DLBCL.Conclusions. In summary, our study demonstrates a good de-gree of correlation between the IHC- based approach and GEP by Nanostring Platform. From a technical point of view, Lym-ph2Cx allows to assign the DLBCL subtype using low amounts of RNA, standardized protocols and rapid turn-around-time. Nanostring platform and Lymph2Cx panel could be useful tools for DLBCL patients’ stratification.References1 Martelli M, et al. Diffuse large B-cell lymphoma. Crit Rev Oncol Hematol 2013;87(2):146-71.2 Alizadeh AA, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000;403(6769):503-11.3 Hans CP, et al. Confirmation of the molecular classification of dif-fuse large B-cell lymphoma by immunohistochemistry using a tissue microarray. Blood 2004;103(1):275-82.4 Scott DW, et al. Determining cell-of-origin subtypes of diffuse large B-cell lymphoma using gene expression in formalin-fixed paraffin embedded tissue. Blood 2014;123(8):1214-7.TRANSCRIPTOMICS LANDSCAPE OF NECROPTOSIS GENES IS ASSOCIATED WITH DENDRITIC CELLS INFILTRATION: A PAN-CANCER STUDY OF 5,451 PRIMARY SOLID TUMORSLorenzo Nicolè1*, Tiziana Sanavia2*, Rocco Cappellesso1 and Ambrogio Fassina11 Department of Medicine (DIMED), Surgical Pathology Unit, University of Padua, Padua, Italy; 2 Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; * Equal contributionObjective. Necroptosis (NPC) is a form of programmed cell death that culminates with the rupture of the cell membrane fol-lowed by the releasing of cellular elements. Evidence showed that tumors with high expression of NCP-related genes are as-sociated with high cytotoxic CD8+ T-cell infiltrates, mediated by signaling from Dendritic (DC) and CD4+ T-cells. This study shows a pan-cancer view of the relationship between NCP and immune infiltration and their prognostic relevance across 24 cancer types from The Cancer Genome Atlas (TCGA).Materials and methods. Gene expression RNA-seq data from 5,451 primary solid tumors were considered, excluding cases with treatments before surgery and with residual tumor. A deconvolution algorithm was used to estimate the level of tumor-infiltrating immune cells in each RNA- seq sample, considering the populations: B-cells, CD4 T-cells, CD8 T-cells, Macrophages and DC. For each immune population, the relative infiltration score was dichotomized at low and high infiltration using the 25th and 75h percentiles, respectively. Logistic regression and likelihood ratio test were applied to 163 genes belonging to Necroptosis pathway from KEGG database to test whether they are significantly associated to the infiltra-tion of a specific immune population. FDR-adjusted p-values <0.05 were considered statistically significant. The prognostic relevance of the NCP genes significantly correlated with the infiltration was evaluated by Cox regression and log-rank test.Results. DC and CD4+ T-cells showed the highest number of cancer types (8) reporting more than half genes of NCP path-way significantly correlated with their infiltration. CD8+ T-cell infiltration correlated with >50% of NCP genes in 5 of these 8 cancer types: Kidney-Renal, Breast, Prostate, Pancreatic and Thyroid tumors. DC also showed the highest number of NCP genes (69) correlated with their infiltration in more than half of the analyzed cancer types, including the main genes involved in NCP execution: RIPK1, RIPK3, MLKL and CFLAR. 60 and 58 of these genes showed a prognostic relevance (p<0.05) for overall and disease-free survival in at least one cancer type, respectively.Conclusions. NCP has a relevant role in eliciting immune response against tumor through DC- mediated immunity in specific cancer types. In the new incoming era of immunother-apy, immune profiling of tumor from high throughput-derived transcriptomics and genomics data, holds a great potential in order do define specific biomarkers for prognostic or predictive purposes.

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Transcriptomics landscape of Necroptosis genes is associated with Dendritic cells infiltration: a pan-cancer study of 5,451 primary solid tumors

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