TISIDB

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Basic function annotation. > Subcellular Location, Domain and Function > Gene Ontology > KEGG and Reactome Pathway

> Subcellular Location, Domain and Function [ TOP ]
Subcellular Location	-
Domain	-
Function	-

> Gene Ontology [ TOP ]
Biological Process	GO:0032259 methylation GO:0072331 signal transduction by p53 class mediator GO:1901796 regulation of signal transduction by p53 class mediator
Molecular Function	GO:0008168 methyltransferase activity GO:0008170 N-methyltransferase activity GO:0008757 S-adenosylmethionine-dependent methyltransferase activity GO:0016278 lysine N-methyltransferase activity GO:0016741 transferase activity, transferring one-carbon groups
Cellular Component	-

> KEGG and Reactome Pathway [ TOP ]
KEGG	-
Reactome	R-HSA-74160: Gene Expression R-HSA-212436: Generic Transcription Pathway R-HSA-5633007: Regulation of TP53 Activity R-HSA-6804760: Regulation of TP53 Activity through Methylation R-HSA-3700989: Transcriptional Regulation by TP53

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Literatures that report relations between SETD9 and anti-tumor immunity. The specific mechanism were also collected if the literature reports that a gene specifically promotes or inhibits the infiltration or function of T/NK cells.

> Text Mining [ TOP ]
There is no record.

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	High-throughput screening data (e.g. CRISPR-Cas9, shRNA and RNAi) for T cell-mediated killing. Genetic screen techniques can identify mechanisms of tumor cell resistance (e.g., PTPN2) and sensitivity (e.g., APLNR) to killing by cytotoxic T cells, the central effectors of anti-tumor immunity. After comprehensively searching, eight groups of screening data sets were collected in the current database. In this tab, users can check whether their selected genes cause resistance or increase sensitivity to T cell-mediated killing in various data sets.

> High-throughput Screening

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Statistical results of SETD9 in screening data sets for detecting immune reponses.

PMID	Screening System	Cancer Type	Cell Line	Data Set	Statistical Results	Relation to immunity
29301958	CRISPR-Cas9	melanoma	B16F10	Pmel-1 T cell	NA/NS	NA/NS
29301958	CRISPR-Cas9	melanoma	B16F10	OT-1 T cell	NA/NS	NA/NS
28783722	CRISPR-Cas9	melanoma	Mel624	2CT-CRISPR	Second most enriched score: 0.59	Sensitive to T cell-mediated killing
28723893	CRISPR-Cas9	melanoma	B16	GVAX+Anti-PD1	NA/NS	NA/NS
28723893	CRISPR-Cas9	melanoma	B16	GVAX	NA/NS	NA/NS
25691366	RNAi	Breast cancer	MCF7	Luc-CTL assay	NA/NS	NA/NS
24476824	shRNA	melanoma	B16	Primary screen	NA/NS	NA/NS
24476824	shRNA	melanoma	B16	Secondary screen	NA/NS	NA/NS

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Transcriptomic and genomic profiling of pre-treated tumor biopsies from responders and non-responders to immunotherapy. These data were used to identify signatures and mechanisms of response to checkpoint blockade (e.g., anti-PDL1 and anti-PD1). One example is that mutations in the gene PBRM1 benefit clinical survival of patients with clear cell renal cell carcinoma. After comprehensively searching, we collected 5 and 6 of transcriptomic and genomic data sets, respectively. In this tab, users can check whether their selected genes have significant difference of expression or mutation between responders and non-responders in various data sets. > Expression difference between responders and non-responders > Mutation difference between responders and non-responders

> Expression difference between responders and non-responders

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Points in the above scatter plot represent the expression difference of SETD9 in various data sets.

No	PMID	Cancer type	Group	Drug	# Res	# NRes	Log2 (Fold Change)	P value
1	26997480	Melanoma	all	Anti-PD-1 (pembrolizumab and nivolumab)	14	12	0.314	0.278
2	26997480	Melanoma	MAPKi	Anti-PD-1 (pembrolizumab and nivolumab)	6	5	0.035	0.975
3	26997480	Melanoma	non-MAPKi	Anti-PD-1 (pembrolizumab and nivolumab)	8	7	0.512	0.581
4	28552987	Urothelial cancer	all	Anti-PD-L1 (atezolizumab)	9	16	-0.425	0.285
5	28552987	Urothelial cancer	smoking	Anti-PD-L1 (atezolizumab)	5	9	-0.571	0.605
6	28552987	Urothelial cancer	non-smoking	Anti-PD-L1 (atezolizumab)	4	7	-0.245	0.844
7	29033130	Melanoma	all	Anti-PD-1 (nivolumab)	26	23	0.207	0.459
8	29033130	Melanoma	NIV3-PROG	Anti-PD-1 (nivolumab)	15	11	0.16	0.868
9	29033130	Melanoma	NIV3-NAIVE	Anti-PD-1 (nivolumab)	11	12	0.303	0.766
10	29301960	Clear cell renal cell carcinoma (ccRCC)	all	Anti-PD-1 (nivolumab)	4	8	-0.423	0.674
11	29301960	Clear cell renal cell carcinoma (ccRCC)	VEGFRi	Anti-PD-1 (nivolumab)	2	0	0	1
12	29301960	Clear cell renal cell carcinoma (ccRCC)	non-VEGFRi	Anti-PD-1 (nivolumab)	2	8	0.026	0.986
13	29443960	Urothelial cancer	all	Anti-PD-L1 (atezolizumab)	68	230	-0.086	0.383

> Mutation difference between responders and non-responders

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Points in the above scatter plot represent the mutation difference of SETD9 in various data sets.

No	PMID	Cancer type	Group	Drug	# Res	# NRes	% Mut/Res	% Diff (R vs NR)	Pval
1	25765070	Non-small cell lung cancer (NSCLC)	all	Anti-PD-1 (pembrolizumab)	14	17	0	0	1
2	25765070	Non-small cell lung cancer (NSCLC)	smoking	Anti-PD-1 (pembrolizumab)	10	3	0	0	1
3	25765070	Non-small cell lung cancer (NSCLC)	non-smoking	Anti-PD-1 (pembrolizumab)	4	14	0	0	1
4	26359337	Melanoma	all	Anti-CTLA-4 (ipilimumab)	27	73	0	0	1
5	26359337	Melanoma	BRAFi	Anti-CTLA-4 (ipilimumab)	0	14	0	0	1
6	26359337	Melanoma	non-BRAFi	Anti-CTLA-4 (ipilimumab)	27	59	0	0	1
7	26997480	Melanoma	all	Anti-PD-1 (pembrolizumab and nivolumab)	21	17	0	0	1
8	26997480	Melanoma	MAPKi	Anti-PD-1 (pembrolizumab and nivolumab)	8	6	0	0	1
9	26997480	Melanoma	non-MAPKi	Anti-PD-1 (pembrolizumab and nivolumab)	13	11	0	0	1
10	28552987	Urothelial cancer	all	Anti-PD-L1 (atezolizumab)	9	16	11.1	11.1	0.36
11	28552987	Urothelial cancer	smoking	Anti-PD-L1 (atezolizumab)	5	9	0	0	1
12	28552987	Urothelial cancer	non-smoking	Anti-PD-L1 (atezolizumab)	4	7	25	25	0.364
13	29033130	Melanoma	all	Anti-PD-1 (nivolumab)	38	27	0	0	1
14	29033130	Melanoma	NIV3-PROG	Anti-PD-1 (nivolumab)	22	13	0	0	1
15	29033130	Melanoma	NIV3-NAIVE	Anti-PD-1 (nivolumab)	16	14	0	0	1
16	29301960	Clear cell renal cell carcinoma (ccRCC)	all	Anti-PD-1 (nivolumab)	11	13	0	0	1
17	29301960	Clear cell renal cell carcinoma (ccRCC)	VEGFRi	Anti-PD-1 (nivolumab)	6	1	0	0	1
18	29301960	Clear cell renal cell carcinoma (ccRCC)	non-VEGFRi	Anti-PD-1 (nivolumab)	5	12	0	0	1

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Relations between abundance of tumor-infiltrating lymphocytes (TILs) and expression, copy number, methylation, or mutation of SETD9. The immune-related signatures of 28 TIL types from Charoentong's study, which can be viewed in the download page. For each cancer type, the relative abundance of TILs were inferred by using gene set variation analysis (GSVA) based on gene expression profile. In this tab, users can examine which kinds of TILs might be regulated by the current gene.

> Lymphocyte [ TOP ]

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Relations between three kinds of immunomodulators and expression, copy number, methylation, or mutation of SETD9. These immunomo-dulators were collected from Charoentong's study. In this tab, users can examine which immunomodulators might be regulated by SETD9. > Immunoinhibitor > Immunostimulator > MHC molecule

> Immunoinhibitor [ TOP ]

> Immunostimulator [ TOP ]

> MHC molecule [ TOP ]

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Relations between chemokines (or receptors) and expression, copy number, methylation, or mutation of SETD9. In this tab, users can examine which chemokines (or receptors) might be regulated by the current gene. > Chemokine > Receptor

> Chemokine [ TOP ]

> Receptor [ TOP ]

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Distribution of SETD9 expression across immune and molecular subtypes. > Immune subtype > Molecular subtype

> Immune subtype [ TOP ]

> Molecular subtype [ TOP ]

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Associations between SETD9 and clinical features. > Overall survival analysis > Cancer stage > Tumor grade

> Overall survival [ TOP ]

> Stage [ TOP ]

> Grade [ TOP ]

Summary
Symbol	SETD9
Name	SET domain containing 9
Aliases	MGC33648; C5orf35; chromosome 5 open reading frame 35; SET domain-containing protein 9
Chromosomal Location	5q11.2
External Links	HGNC, NCBI, Ensembl, Uniprot, GeneCards
Content	Drugs targeting SETD9 collected from DrugBank database.

> Drugs from DrugBank database [ TOP ]
There is no record.

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