Target Information

Target General Information

Target ID

T14592 (Former ID: TTDI02199)

Target Name

Apoptosis mediating surface antigen FAS (FAS)

Synonyms

Tumor necrosis factor receptor superfamily member 6; TNFRSF6; FASLG receptor; FAS1; CD95; Apoptosis-mediating surface antigen FAS; Apo-1 antigen; APT1

Click to Show/Hide

Gene Name

FAS

Target Type

Clinical trial target

[1]

Disease

[+] 2 Target-related Diseases

Brain cancer [ICD-11: 2A00]

Ovarian cancer [ICD-11: 2C73]

Function

The adapter molecule FADD recruits caspase-8 to the activated receptor. The resulting death-inducing signaling complex (DISC) performs caspase-8 proteolytic activation which initiates the subsequent cascade of caspases (aspartate-specific cysteine proteases) mediating apoptosis. FAS-mediated apoptosis may have a role in the induction of peripheral tolerance, in the antigen-stimulated suicide of mature T-cells, or both. The secreted isoforms 2 to 6 block apoptosis (in vitro). Receptor for TNFSF6/FASLG.

Click to Show/Hide

BioChemical Class

Cytokine receptor

UniProt ID

TNR6_HUMAN

Sequence

MLGIWTLLPLVLTSVARLSSKSVNAQVTDINSKGLELRKTVTTVETQNLEGLHHDGQFCH
KPCPPGERKARDCTVNGDEPDCVPCQEGKEYTDKAHFSSKCRRCRLCDEGHGLEVEINCT
RTQNTKCRCKPNFFCNSTVCEHCDPCTKCEHGIIKECTLTSNTKCKEEGSRSNLGWLCLL
LLPIPLIVWVKRKEVQKTCRKHRKENQGSHESPTLNPETVAINLSDVDLSKYITTIAGVM
TLSQVKGFVRKNGVNEAKIDEIKNDNVQDTAEQKVQLLRNWHQLHGKKEAYDTLIKDLKK
ANLCTLAEKIQTIILKDITSDSENSNFRNEIQSLV

Click to Show/Hide

3D Structure

Click to Show 3D Structure of This Target

AlphaFold

HIT2.0 ID

T57HGP

Drugs and Modes of Action

Top

Clinical Trial Drug(s)

[+] 4 Clinical Trial Drugs

VB-111

Drug Info

Phase 3

Malignant glioma

[2]

APG-101

Drug Info

Phase 2

Cerebrovascular ischaemia

[3]

DE-098

Drug Info

Phase 2

Rheumatoid arthritis

[4]

APO-010

Drug Info

Phase 1

Multiple myeloma

[5]

Mode of Action

[+] 3 Modes of Action

Modulator

[+] 1 Modulator drugs

VB-111

Drug Info

[1]

Inhibitor

[+] 2 Inhibitor drugs

APG-101

Drug Info

[6]

APG-103

Drug Info

[8]

Binder

[+] 1 Binder drugs

APO-010

Drug Info

[5]

Cell-based Target Expression Variations

Top

Cell-based Target Expression Variations

Cell-based Target Expression Variations Info

Different Human System Profiles of Target	Top
Human Similarity Proteins of target is determined by comparing the sequence similarity of all human proteins with the target based on BLAST. The similarity proteins for a target are defined as the proteins with E-value < 0.005 and outside the protein families of the target. A target that has fewer human similarity proteins outside its family is commonly regarded to possess a greater capacity to avoid undesired interactions and thus increase the possibility of finding successful drugs (Brief Bioinform, 21: 649-662, 2020). Human Tissue Distribution of target is determined from a proteomics study that quantified more than 12,000 genes across 32 normal human tissues. Tissue Specificity (TS) score was used to define the enrichment of target across tissues. The distribution of targets among different tissues or organs need to be taken into consideration when assessing the target druggability, as it is generally accepted that the wider the target distribution, the greater the concern over potential adverse effects (Nat Rev Drug Discov, 20: 64-81, 2021). Human Pathway Affiliation of target is determined by the life-essential pathways provided on KEGG database. The target-affiliated pathways were defined based on the following two criteria (a) the pathways of the studied target should be life-essential for both healthy individuals and patients, and (b) the studied target should occupy an upstream position in the pathways and therefore had the ability to regulate biological function. Targets involved in a fewer pathways have greater likelihood to be successfully developed, while those associated with more human pathways increase the chance of undesirable interferences with other human processes (Pharmacol Rev, 58: 259-279, 2006). Biological Network Descriptors of target is determined based on a human protein-protein interactions (PPI) network consisting of 9,309 proteins and 52,713 PPIs, which were with a high confidence score of ≥ 0.95 collected from STRING database. The network properties of targets based on protein-protein interactions (PPIs) have been widely adopted for the assessment of target’s druggability. Proteins with high node degree tend to have a high impact on network function through multiple interactions, while proteins with high betweenness centrality are regarded to be central for communication in interaction networks and regulate the flow of signaling information (Front Pharmacol, 9, 1245, 2018; Curr Opin Struct Biol. 44:134-142, 2017). Human Similarity Proteins Human Tissue Distribution Human Pathway Affiliation Biological Network Descriptors

Different Human System Profiles of Target

Top

Human Similarity Proteins of target is determined by comparing the sequence similarity of all human proteins with the target based on BLAST. The similarity proteins for a target are defined as the proteins with E-value < 0.005 and outside the protein families of the target.

A target that has fewer human similarity proteins outside its family is commonly regarded to possess a greater capacity to avoid undesired interactions and thus increase the possibility of finding successful drugs (Brief Bioinform, 21: 649-662, 2020).

Human Tissue Distribution of target is determined from a proteomics study that quantified more than 12,000 genes across 32 normal human tissues. Tissue Specificity (TS) score was used to define the enrichment of target across tissues.

The distribution of targets among different tissues or organs need to be taken into consideration when assessing the target druggability, as it is generally accepted that the wider the target distribution, the greater the concern over potential adverse effects (Nat Rev Drug Discov, 20: 64-81, 2021).

Human Pathway Affiliation of target is determined by the life-essential pathways provided on KEGG database. The target-affiliated pathways were defined based on the following two criteria (a) the pathways of the studied target should be life-essential for both healthy individuals and patients, and (b) the studied target should occupy an upstream position in the pathways and therefore had the ability to regulate biological function.

Targets involved in a fewer pathways have greater likelihood to be successfully developed, while those associated with more human pathways increase the chance of undesirable interferences with other human processes (Pharmacol Rev, 58: 259-279, 2006).

Biological Network Descriptors of target is determined based on a human protein-protein interactions (PPI) network consisting of 9,309 proteins and 52,713 PPIs, which were with a high confidence score of ≥ 0.95 collected from STRING database.

The network properties of targets based on protein-protein interactions (PPIs) have been widely adopted for the assessment of target’s druggability. Proteins with high node degree tend to have a high impact on network function through multiple interactions, while proteins with high betweenness centrality are regarded to be central for communication in interaction networks and regulate the flow of signaling information (Front Pharmacol, 9, 1245, 2018; Curr Opin Struct Biol. 44:134-142, 2017).

Human Similarity Proteins

Human Tissue Distribution

Human Pathway Affiliation

Biological Network Descriptors

There is no similarity protein (E value < 0.005) for this target


Note: If a protein has TS (tissue specficity) scores at least in one tissue >= 2.5, this protein is called tissue-enriched (including tissue-enriched-but-not-specific and tissue-specific). In the plots, the vertical lines are at thresholds 2.5 and 4.

KEGG Pathway	Pathway ID	Affiliated Target
MAPK signaling pathway	hsa04010	Affiliated Target
Class: Environmental Information Processing => Signal transduction	Pathway Hierarchy
Cytokine-cytokine receptor interaction	hsa04060	Affiliated Target
Class: Environmental Information Processing => Signaling molecules and interaction	Pathway Hierarchy
p53 signaling pathway	hsa04115	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
Apoptosis	hsa04210	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
Necroptosis	hsa04217	Affiliated Target
Class: Cellular Processes => Cell growth and death	Pathway Hierarchy
Natural killer cell mediated cytotoxicity	hsa04650	Affiliated Target
Class: Organismal Systems => Immune system	Pathway Hierarchy
TNF signaling pathway	hsa04668	Affiliated Target
Class: Environmental Information Processing => Signal transduction	Pathway Hierarchy
Click to Show/Hide the Information of Affiliated Human Pathways

Degree	18	Degree centrality	1.93E-03	Betweenness centrality	6.87E-04
Closeness centrality	2.51E-01	Radiality	1.44E+01	Clustering coefficient	3.46E-01
Neighborhood connectivity	4.77E+01	Topological coefficient	8.56E-02	Eccentricity	11
Download	Click to Download the Full PPI Network of This Target

Target Regulators

Top

Target-regulating microRNAs

Target-regulating microRNAs Info

Target-regulating Transcription Factors

Target-regulating Transcription Factors Info

Target-interacting Proteins

Target-interacting Proteins Info

Target Profiles in Patients

Top

Target Expression
Profile (TEP)

Target Expression Profile Info

Target Affiliated Biological Pathways		Top
KEGG Pathway	[+] 20 KEGG Pathways	+
1	MAPK signaling pathway
2	Cytokine-cytokine receptor interaction
3	p53 signaling pathway
4	Apoptosis
5	Natural killer cell mediated cytotoxicity
6	TNF signaling pathway
7	Non-alcoholic fatty liver disease (NAFLD)
8	Type I diabetes mellitus
9	Alzheimer's disease
10	Chagas disease (American trypanosomiasis)
11	African trypanosomiasis
12	Hepatitis B
13	Measles
14	Influenza A
15	Herpes simplex infection
16	Pathways in cancer
17	Proteoglycans in cancer
18	Autoimmune thyroid disease
19	Allograft rejection
20	Graft-versus-host disease
NetPath Pathway	[+] 2 NetPath Pathways	+
1	IL2 Signaling Pathway
2	TCR Signaling Pathway
Panther Pathway	[+] 3 Panther Pathways	+
1	Apoptosis signaling pathway
2	FAS signaling pathway
3	p53 pathway
PID Pathway	[+] 6 PID Pathways	+
1	p73 transcription factor network
2	FAS (CD95) signaling pathway
3	Direct p53 effectors
4	HIV-1 Nef: Negative effector of Fas and TNF-alpha
5	Caspase Cascade in Apoptosis
6	Validated transcriptional targets of TAp63 isoforms
Reactome	[+] 1 Reactome Pathways	+
1	FasL/ CD95L signaling
WikiPathways	[+] 13 WikiPathways	+
1	DNA Damage Response
2	TCR Signaling Pathway
3	Apoptosis Modulation by HSP70
4	MAPK Signaling Pathway
5	FAS pathway and Stress induction of HSP regulation
6	Apoptosis
7	Integrated Pancreatic Cancer Pathway
8	Adipogenesis
9	Allograft Rejection
10	Alzheimers Disease
11	Extrinsic Pathway for Apoptosis
12	Apoptosis Modulation and Signaling
13	miRNA Regulation of DNA Damage Response

References

Top

REF 1

Phase I dose-escalation study of VB-111, an antiangiogenic virotherapy, in patients with advanced solid tumors.Clin Cancer Res.2013 Jul 15;19(14):3996-4007.

REF 2

Clinical pipeline report, company report or official report of the Pharmaceutical Research and Manufacturers of America (PhRMA)

REF 3

ClinicalTrials.gov (NCT01071837) APG101 in Glioblastoma. U.S. National Institutes of Health.

REF 4

Trusted, scientifically sound profiles of drug programs, clinical trials, safety reports, and company deals, written by scientists. Springer. 2015. Adis Insight (drug id 800016731)

REF 5

APO010, a synthetic hexameric CD95 ligand, induces human glioma cell death in vitro and in vivo. Neuro Oncol. 2011 Feb;13(2):155-64.

REF 6

Pharmacokinetics, pharmacodynamics, safety and tolerability of APG101, a CD95-Fc fusion protein, in healthy volunteers and two glioma patients. Int Immunopharmacol. 2012 May;13(1):93-100.

REF 7

ARG098, a novel anti-human Fas antibody, suppresses synovial hyperplasia and prevents cartilage destruction in a severe combined immunodeficient-HuRAg mouse model. BMC Musculoskeletal Disorders 2010,11:221.

REF 8

URL: http://www.guidetopharmacology.org Nucleic Acids Res. 2015 Oct 12. pii: gkv1037. The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. (Target id: 1875).

If You Find Any Error in Data or Bug in Web Service, Please Kindly Report It to Dr. Zhou and Dr. Zhang.

Prof. Yuzong CHEN

Prof. Feng ZHU