TYPE Review
PUBLISHED 17 August 2023
DOI 10.3389/fimmu.2023.1225704

OPEN ACCESSThe beneﬁts of clustering in TNF
receptor superfamily signaling

EDITED BY

Adam Zwolak,
Janssen Research and Development,
United States
REVIEWED BY

Alexander G. Gabibov,
Institute of Bioorganic Chemistry (RAS),
RussiaAmelie Heuer-Jungemann,
Max Planck Institute of Biochemistry,
Germany*CORRESPONDENCE

Denise L. Faustman
dfaustman@mgh.harvard.edu
RECEIVED 19 May 2023
ACCEPTED 02 August 2023
PUBLISHED 17 August 2023
CITATION

Vanamee ÉS and Faustman DL (2023)
The beneﬁts of clustering in TNF
receptor superfamily signaling.
Front. Immunol. 14:1225704.
doi: 10.3389/fimmu.2023.1225704

Éva S. Vanamee 1 and Denise L. Faustman 1,2*
1Immunobiology Department, Massachusetts General Hospital, Boston, MA, United States, 2 Harvard
Medical School, Boston, MA, United States

The tumor necrosis factor (TNF) receptor superfamily is a structurally andfunctionally related group of cell surface receptors that play crucial roles invarious cellular processes, including apoptosis, cell survival, and immune
regulation. This review paper synthesizes key ﬁndings from recent studies,
highlighting the importance of clustering in TNF receptor superfamily
signaling. We discuss the underlying molecular mechanisms of signaling, thefunctional consequences of receptor clustering, and potential therapeutic
implications of targeting surface structures of receptor complexes.
KEYWORDS

TNF receptor superfamily (TNFRSF), TNF signaling, receptor clustering, TNFR agonism
and antagonism, signal ampliﬁcation

COPYRIGHT© 2023 Vanamee and Faustman. This is an
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License (CC BY). The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
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reproduction is permitted which does notcomply with these terms.

Introduction
The TNF receptor superfamily (TNFRSF) comprises a diverse group of cell surface
receptors involved in regulating immune responses, inﬂammation, and cell survival (1).
Dysregulation of TNF signaling is implicated in various pathological conditions,
including cancer, autoimmune and allergic diseases. Recent studies have highlighted
the importance of receptor clustering in the activation and modulation of TNF receptor
signaling. In this review, we will summarize the key ﬁndings of TNFRSF signaling, thebeneﬁts of clustering in TNFRSF function and its implications fortherapeutics development.

Receptor classiﬁcation and mechanism of action
Members of the TNFRSF are type I, single pass membrane proteins with their Cterminal end anchored in the membrane. Their elongated ectodomains contain 1-6
cysteine rich domains (CRDs). TNF receptors can be grouped into three distinct groups(see Table 1): the ﬁrst group contains receptors with a death domain (DD), essential for the
initiation of apoptosis, though receptors in this group can also activate chronic
inﬂammatory pathways. The second group of TNFRSF members interact with TNF
receptor associated factors (TRAF) to initiate cell survival and proliferation via thecanonical or non-canonical NFkB pathways. The third group contains decoy receptors
that lack a functional cytoplasmic domain and instead act as decoys by binding to TNFSF

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TABLE 1 TNFRSF receptors, their ligands and intracellular binding partners.

TNFRSF Receptor(TNFRSF No.)

Numberof CRD

Intracellular Binding
Partner

TNFSF Ligand(TNFSF No.)

Receptor Stem Region (AA)Death Receptors
TNFR1 (1a)4

TRADD, FADD, RIP

TNF (2), LTa (1), LTb (3)197-211

Fas (6)3

FADD

FasL (6)167-173

TRAILR1 (10A)

3¶

FADD, TRADD, RIP

TRAIL/Apo2L (10)230-239TRAILR2 (10B)¶

3

FADD, TRADD, RIP

TRAIL/Apo2L (10)179-210NGFR (16)4NADE

NGF (not a TNFSF member)

191-250

DR3 (25 or 12)¶

4

TRADD, FADD

TL1A (15), TWEAK (12)193-199

DR6 (21)

4

TRADD, RIP

N-APP (not a TNFSF member)

212-349

EDAR¶

EDARADDEDA-A1

149-187

3

Receptors with TRAF-interacting motif
TNFR2 (1b)4

TRAF1-3

TNF (2), LTa (1)202-257

LTbR (3)4

TRAF2-4, TRAF5

LTa (1), LTb (3) as LTab2,, LTa2b

212-227

OX40 (4)¶4

TRAF1-3, TRAF5, TRAF6

OX40L (4)168-214

CD40 (5)4

TRAF1-3, TRAF5, TRAF6

CD40L (5)188-193

CD27 (7)3

TRAF2, TRAF3, TRAF5

CD27L (7)142-191

CD30 (8)6

TRAF1-3, TRAF5

CD30L (8)326-3854-1BB (9)4

TRAF1-3

4-1BBL (9)160-186RANK (11A)

4

TRAF1-3, TRAF5, TRAF6RANKL (11)

195-212

Fn14 (12A)1

TRAF2, TRAF6

TWEAK (12)68-80

TACI (13B)2

TRAF2-3, TRAF5, TRAF6APRIL (13)105-165

BAFFR (13C)

1

TRAF2, TRAF3, TRAF6

BAFF (13B/20)

36-78

HVEM (14)3

TRAF1-3, TRAF5

LIGHT (14), LT-a (1)163-202

BCMA (17)1

TRAF1-3, TRAF5, TRAF6APRIL (13),BAFF (13B/20)

42-54

GITR (18)3

TRAF1-3

GITRL (18)154-162

TROY (19)3¶

TRAF1-3, TRAF5

LTa (1)150-170

RELT (19L)

1

TRAF1

not known

110-162

XEDAR (27)3¶

TRAF1, TRAF3, TRAF6EDA-A2

119-138TRAILR3 (10C)

3¶

none

TRAIL/Apo2L (10)TRAILR4 (10D)

¶

3

none

TRAIL/Apo2L (10)OPG (11B)

4none

TRAIL/Apo2L (10), RANKL (11)DcR3 (6B)

4none

FasL (6), TL1A (15), LIGHT (14)Decoy receptors¶: Contains truncated CRD domains.

ligands and prevent them from binding to other functional
receptors. Ligands of the TNF superfamily (TNFSF) are type IImembrane proteins with their N-terminal end anchored in themembrane. They share 20-30% sequence homology and astructurally conserved TNF homology domain (THD) (2). TNFSF
ligands form non-covalent trimers and bind to three monomers of
their corresponding receptors (Figure 1A). Efﬁcient signaling in the

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TNFRSF requires that the receptors preassemble on the cell surface
to form hexagonal honeycomb clusters (4–6). In return, thedownstream signaling components assume the same hexagonalclustering geometry (7, 8). Free receptor monomers interact
through the so-called pre-ligand assembly domain (PLAD)
formed by the N-terminal and the CRD1 domains of the receptor(9–13). We have earlier proposed a uniform model that can apply to

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A

B

C

D

FIGURE 1

Illustration of the mechanism of signaling in the TNF receptor superfamily (A) Molecular representations of trimeric lymphotoxin (LTa) shown inmagenta (top view) and the LTa (magenta)-TNF receptor 1 (TNFR1, blue) complex (top view). (B) A TRAF-interacting TNFRSF receptor represented bya model of the TNF/TNFR2/TRAF2 signaling complex. In the quiescent state (top panel), the receptor antiparallel dimers (blue) are arranged in ahexagonal lattice. TNF (magenta) binding breaks up the dimer interface and activated TNFR2 trimers recruit TRAF2 (green) resulting in the
dimerization of the TRAF2 N-terminal RING domains (cyan) and activation of further downstream events. The hexagonal lattice of the downstream
components mirrors the hexagonal lattice of the receptors. (C) Death receptor 5 (DR5, blue) in complex with its ligand TRAIL also forms a hexagonalcluster. After DR5 activation, TRAIL-R2-DD (blue) dimerizes and recruits a FADD dimer (green) also forming a hexagonal lattice. (D) For receptors like
HVEM (blue) that are unable to dimerize on their own, hexagonal lattice formation is aided and controlled by the dimeric IgSF member, BTLA
(orange). Upon binding of the ligand (magenta) the activated receptors recruit a TRAF homolog resulting in RING dimerization and activation offurther downstream events. The program PyMOL was used for creating all molecular representations (3).

both the DD containing and TRAF-interacting receptors of the
TNFRSF (4) (Figures 1B, C). To brieﬂy summarize: the model
assumes that receptors initially assume a quiescent state on the cellsurface where trimers of antiparallel dimers form a hexagonal
honeycomb cluster. The antiparallel dimer form partially buries
the ligand binding surface and therefore unable to bind the ligand
until activated. The activated receptors maintain the sameclustering geometry and recruit the downstream signaling
partners. The major beneﬁt of this model is that the honeycomb
lattice of the surface receptors is the same as the assembled
honeycomb lattice of the downstream components so there is noneed for major movement in the membrane upon activation. Since
the downstream signaling partners form weak interactions,

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preassembly of the receptors on the cell surface enables thedownstream partners to bind more efﬁciently once the receptors
are activated by their ligands. This model accommodates both death
receptors and TRAF-interacting receptors into one model.
One potential issue with this model is that the number and sizeof the extracellular CRD domains of TNFRSFs vary and not all
members have been shown to be able to form interactions via their
PLAD. This raises the question whether the proposed model canhold for TNFRSF receptors that are unable to form stable dimers on
their own. The answer has been provided by the structure ofherpesvirus entry mediator (HVEM, TNFRSF14) in complex withthe regulatory protein B- and T-lymphocyte attenuator(BTLA) (14).

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transmitted ﬁrst vertically after the binding of the ligand to theintracellular binding partners. For members of the TRAFinteracting receptors such as TNFR2 and HVEM, theircytoplasmic tails recruit TRAF homologs and it is TRAF
dimerization via the N-terminal RING domains that enables
cooperativity between signaling units (Figures 1B, D). TRAF
binding proteins such as cIAP1/2 can also dimerize and facilitate
cooperative signaling. In case of death receptors, such as CD95 (Fas)or death receptor 5 (DR5), their DDs recruit the Fas associateddeath domain (FADD) and it is FADD dimerization that enables
cooperativity between two signaling units as seen in Figure 1C. In all
instances, cooperativity requires that the two TNFRSF receptor
trimers on the cell surface are activated by their ligands to create alogical AND gate.
We have shown earlier that cooperative signaling networks can be
represented as planar graphs with nodes (n) and edges (e), where nrepresents the input signal and e the output signal (21). Cooperativity
requires that at least two n input nodes are placed near each other at theright distance to create an e output. This generates one output signal
from two input signals at a 50% loss of signaling efﬁciency. Even if
thousands of TNFRSF signaling pairs are added onto the cell surface
their efﬁciency remains at 0.5. However, if we order six input signaling
units into a closed loop we end up with equal number of nodes andedges where e/n = 1. This closed signaling unit can be represented by aregular hexagon. Further clustering can then be illustrated by tiled
regular hexagons. Tessellation or tiling refers to the process of covering asurface with one or more geometric shapes called tiles with no overlaps
and no gaps. Mathematically, it means that the graph representing such
system is a simple graph with no self-loops or multiple edges. A regularhexagon is one of only three regular polygons that can be tiled bythemselves in two-dimension, the other two regular polygons are
equilateral triangles and squares. As we have shown earlier, as thecluster size of tessellated polygons grow, the output/input signal ratio
increases but can never exceed 3 (21). The maximum is also inversely
proportional to the degree of the tiled polygon, therefore smallest in ahexagonal cluster and largest in a clustered system of tiled triangles
where it can reach 300% of the original amplitude leading to the
maximum value shown in Eq. 1, where e represents the sum of all edges
and n represents the sum of all nodes in the cluster:

Immunoglobulin superfamily
members aid TNFRSF clusteringand regulate function
BTLA is the member of the Immunoglobulin (Ig) superfamily(IgSF) that comprises of proteins that play crucial roles in the
immune system and other biological processes. These proteins arecharacterized by the presence of one or more Ig domains, which are
structurally conserved regions that contain about 70-110 aminoacids arranged in a sandwich-like structure (15). BTLA functions as
an inhibitory receptor on T lymphocytes similar to well-known IgSF
members such as cytotoxic T lymphocyte-associated antigen 4(CTLA-4) and programmed death 1 (PD-1). BTLA interacts with
the TNFRSF member HVEM that modulates B and T lymphocyte
activation (16), dendritic cell proliferation (17) and protects
mucosal epithelia from damage during inﬂammation (18). In thecytosol, HVEM interacts with several TRAF homologs including
TRAF2 to induce NFkB activation. LIGHT and LT- a are the twocanonical TNFSF ligands that activate HVEM. BTLA and CD160,
another IgSF protein, regulate HVEM function.
The crystal structure of the HVEM-BTLA complex is aheterotetramer consisting of an antiparallel dimer of HVEM on theoutside and a BTLA dimer on the inside (14) (Figure 1D). The
complex closely resembles the antiparallel dimer structure of TNFR1(19) and the modeled structure of TNFR2 shown in Figure 1B. Basedon these data, we have earlier proposed that the HVEM antiparallel
complex with BTLA may arrange in a hexagonal lattice on the cellsurface representing the receptor quiescent state similar to TNFR1/2(20). Since BTLA is a type I transmembrane protein similar to HVEM,
both can be co-expressed and anchored to the cell by their C-terminal
ends. In the cis conﬁguration BTLA does not interfere with LIGHT or
LT-a binding, instead it serves to facilitate HVEM oligomerization on
the cell surface and to inhibit the ligand independent activation of
HVEM. BTLA rather than being a true ligand of HVEM as previously
proposed, serves as a regulatory protein modulating HVEM
oligomerization and controls receptor activation. There are several
TNFRSF receptors with three or fewer CRD domains that could
potentially utilize a co-regulatory receptor to aid their oligomerizationon the cell surface (see Table 1) and the HVEM/BTLA complex
structure can serve as a template for such interactions.
We now have a uniﬁed model of TNFRSF that shows the receptors
arranged in a honeycomb cluster both in their free and ligand boundstates and this model can accommodate all members of the TNFRSF
regardless of function or the size of their ectodomains. The size of thehexagonal lattice may vary from receptor to receptor but is expected tobe the same for receptors that interact with the same downstream
signaling partners. Next, we are going to discuss how the formation of
the honeycomb cluster can improve signaling in the TNFRSF.

output signal e= ≤3
input signaln

The formula derived in Eq. 1 is the consequence of Euler’s
polyhedron formula (22). It illustrates that the signal in a clusterednetwork can be ampliﬁed. We have also shown that theampliﬁcation depends on cluster size and clustering geometry andit can broadly apply to all clustered cooperative signaling systems
beyond the TNFRSF regardless of their molecular makeup (21).
In Figure 2 we provide examples of signal ampliﬁcation inhexagonal clustering relevant to the TNFRSF. Ligand boundactivated receptors represent the input signal that can beillustrated by the vertices or nodes. The dimerization of the TRAF
RING domains or DD dimerization represent the output signal thatis illustrated by the edges of the hexagon. The signal amplitudedepends on the geometry of the honeycomb cluster. Tiling thehexagons in a more or less symmetrical fashion in each direction is

Clustering enables cooperativity andleads to signal ampliﬁcation
Cooperativity in the TNFRSF requires that at least two signaling
trimers are placed close enough for an interaction to occur. Signal is

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the most efﬁcient, leading to the highest e/n or input/output signal
ratio compared to hexagons tiled in a linear fashion. This is because
the e/n ratio is maximized when most hexagons are surrounded byother hexagons (21).
As the cluster size grows the e/n ratio increases and reaches aplateau. For hexagonal clusters 90% of the maximum signal
ampliﬁcation can be achieved in a cluster of 100 signaling units,
and 400 units are required to reach 95% signal ampliﬁcation. This isimportant because experimental data indicates that signaling
receptors tend to form small clusters on the cell surface around300-500 nm in diameter (23–25). Optimal cluster size may also
dependent on the size of the cell-to-cell interface.

edges in the cluster) is calculated for 50% initial occupancy (redline) and 95% initial occupancy (blue line). The program thenrandomly activates a certain percentage of remaining inactive nodes
until all are activated. When soluble ligands bind to their receptors,
they bind more or less randomly with low overall amplitude. This isbecause even at 50% occupancy, not all activated receptor will beconnected to other active trimers to create an output signal. Whenthe ligands are bound to the membrane with the same geometry as
the receptors (Figure 3B), the ligand trimers are going to line up
with the receptor trimers and a much higher portion of receptors
will be activated creating a strong signal similar to what is seen athigh occupancy. The membrane bound ligands will generate anarrow and high amplitude, digital-like ON signal for activation.
The soluble ligands on the other hand generate a low amplitude
signal spread out over time as illustrated in Figure 3C. This is inremarkable agreement with experimental data using a DNA origami
platform with immobilized FasL ligands arranged in different
geometries to test the effect of ligand clustering on apoptosis
efﬁciency in cells overexpressing the Fas receptor. Hexagonallyarranged ligands generated a high amplitude signal in contrast to
the low amplitude, broad signal generated by ligands with thewrong geometry (26). Super-resolution imaging has conﬁrmed
the importance of clustering in vivo in a Fas/FasL model but
there is disagreement of the state of the ligand-free receptors (27).
The Fas receptors appear largely monomeric and dimeric in theligand-free state as observed by ﬂuorescence energy transfer studiesof C-terminal labeled Fas-ﬂuorescence protein (Fas-FP) receptors.
Fas-FP could appear monomeric even in the clustered state because
the C-terminal ends of receptors in the ligand-free state maybe
separated by a distance larger than the Förster distance of the
FP pairs.
A low amplitude signal may not reach the threshold ofactivation and may result in not just quantitatively but

Model of ligand activation ofclustered receptors
Now that we understand the optimal arrangement of receptor
clusters on the cell surface, we can examine how ligand binding
affects receptor activation and signaling. Ligands of the TNFSF are
expressed as transmembrane proteins with their N terminal end
anchored in the membrane. The ligands are cleaved to create asoluble form that is generally less effective than the membranebound ligand across most of TNFSF. For instance, membranebound TNF (memTNF) can activate TNFR2 very effectively but
soluble TNF (sTNF) is a weak activator of TNFR2. We can illustrate
how clustering can potentially explain these differences. Figure 3A
illustrates a hexagonal lattice with receptor trimers represented as
nodes in a hexagonal honeycomb grid. In this example, eachactivated (ligand bound) node is shown in dark blue, inactive
nodes are in light blue, dark blue edges connect two active nodes,
while all other edges are shown in light blue. In Figure 3C theamplitude (the ratio of the active edges over the total number of

FIGURE 2

Illustration of signal ampliﬁcation in hexagonal clusters. (A) Signal ampliﬁcation represented by the e/n ratio is calculated for two examples of regulartiled hexagons with different geometries and plotted against n. It is higher in a hexagonal lattice that grows equally in both direction in the plane(shown in red) over a lattice tiled in only one direction (yellow). The red shaded area illustrates that 90-95% of the maximum signal ampliﬁcation canbe achieved with a cluster of 100-400 receptors in agreement with experimental data on the average size of receptor nano clusters in cells.

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FLIP has three functionally different isoforms. In addition to
FLIP(L), two shorter isoforms FLIP(R) and FLIP(S) also exist andtogether they play a pivotal role in switching between cell survival,
apoptosis and necroptosis. While FLIP(L) plays an important rolein modulating apoptosis, FLIP(s) is important for assembling thenecrosome to induce necroptosis. Necroptosis is the caspaseindependent regulated inﬂammatory form of cell death via cell
lysis and necrosis. Receptor-interacting serine/threonine protein
kinase-1 and 3 (RIPK1/3) and mixed lineage kinase domain–like(MLKL) are central mediators of TNF induced necrosis via TNF
receptor 1 (TNFR1). Interestingly, TNFR1 internalization is an
important ﬁrst step in necroptosis (29). As we discussed earlier,
receptor clustering and cluster stabilization can inﬂuence receptor
internalization and therefore may also affect necroptosis. The
ultimate outcome of cell fate is the result of a complex interplayof different cellular components and the activation or inhibition ofseveral pathways. We believe that receptor clustering and thedifferential activation of clustered receptors play an important but
not yet appreciated role in these processes.
Clustering may not explain all the differences between
membrane and soluble TNFSF ligands regarding their ability toactivate the receptor. The stem (or stalk) region of the receptor plays
an important role as well. In most cases, the stem region is deﬁned
by the sequence between the last CRD domain and thetransmembrane domain of the receptor. When the stem regionsof TNFR1 and TNFR2 are switched, sTNF can readily activate
TNFR2 but not TNFR1 (30). TNFR1 has a short stem region (15AA), while TNFR2 has a longer proline rich stem region (56 AA)(Figure 4A). sTRAIL can also more easily activate DR4 that have ashort stem region but not DR5 that has a longer stem (Figure 4A)(31). LTbR with a short stem region also belongs to receptors thatare known to be readily activated by their respective soluble ligand.
On the other hand, OX40, CD27, 4-1BB and TACI have longer
proline rich stems and are less readily activated by their respective
soluble ligands (30). Table 1 lists the stem size for all TNFRSF
members and there seems to be a clear correlation between stem
size, rigidity and responsiveness to soluble TNFSF ligand. In thequiescent state model, trimers of antiparallel dimers setup thehoneycomb cluster. The antiparallel dimer acts as a ruler toposition receptor trimers at the right distance away from eachother and to also sequester the ligand binding site. The dimer
interactions are needed to create the right lattice of the honeycomb
cluster. In the inactive, lateral state the stem region of each receptor
is exposed and may directly interact with the TNFSF ligand (solubleof membrane bound) to initiate the conformational transition of thereceptor from horizontal (inactive) to vertical (active) position(Figure 4B). This kind of transition is not unusual. In Munc13
that also forms hexagonal clusters, the Munc13 core (Munc13C)transitions between upright (open) conformation to lateral (closed)(32). We believe it warrants further research to address how the size
and rigidity of the stem region may affect receptor activation by
TNFSF ligands for other members of the TNFRSF.
We are now going to illustrate how taking into account thenatural 3D structure of an antigen on the cell surface can guide thesuccessful development of therapeutics with examples fromthe TNFRSF.

BC

FIGURE 3

Illustration of simulated signal amplitudes with soluble ormembrane-bound ligands. (A) Representation of a honeycomb
receptor cluster with 50% occupancy. Activated receptors are
represented as dark blue nodes, inactive receptors shown as light
blue nodes. Edges between active nodes are shown in dark blue
while all other edges are colored light blue. (B) In cell-to-cellinteractions, clustered ligands attached to the membrane allow thesimultaneous activation of clustered receptors with the same
geometry, resulting in maximum signaling efﬁciency. (C) The
amplitude is calculated as the ratio of active/inactive edges for 50%
and 95% occupancies. High occupancy, illustrating membranebound ligand activation results in a sharp, high amplitude signal,
while lower occupancy by soluble ligands results in a low amplitude
signal spread out over time.

qualitatively different signaling outcomes. This could explain how
activation of the same receptor can result in different outcomes in
the TNFRSF. Interestingly a recent paper on DR5 signaling provides
an explanation of how the long isoform of the FLICE-like inhibitory
protein (FLIP(L)) can act as both an inhibitor and promoter of
caspase-8 at the death-inducing signaling complex (DISC) (28). The
outcomes depend on the ratio of FLIP(L):caspase-8. When caspase8 concentration is higher than FLIP(L) concentration apoptosis isaccelerated. This can be explained by the proposed model ofreceptor activation of DR5 and the different outcomes generated
by low vs high occupancy receptor clusters. Procaspase-8 binding to
the DR5-DD-FADD complex activates caspase-8 and simultaneous
activation of clustered DR5 with memTRAIL will lead to muchhigher concentrations of activated caspase-8 and a higher amplitude
signal. Random activation of the receptor by sTRAIL could lead tomuch lower active concentrations of caspase-8 tilting the ratio infavor of FLIP(L) and result in apoptosis blockade.

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A

B

FIGURE 4

The size and rigidity of the stem region plays a role in receptor activation by the ligand. (A) The stem regions of several TNF receptors are listed.
Soluble TNF can more readily activate TNFR1 and LTbR with short stem regions than TNFR2 that has a long stem sequence. Similarly, TRAIL canmore readily activate DR4 with a short stem than DR5 that has a longer stem. (B) In the TNFR activation model the stem regions shown in light blue
are exposed and may directly interact with the ligand or play an otherwise important role in receptor activation. The structures ligand boundcomplexes are shown in 50% transparency to indicate the ﬁnal state after conformational change.

that adalimumab stabilizes membrane TNF at the cell surface andprevents recycling or cleavage to soluble TNF” (34). In the context
of clustering, we propose that adalimumab may aid the formationand stabilization of TNF clusters on the cell surface that in turn may
facilitate better signaling via the also clustered TNFR2 on thesurface of cells. This is in agreement with experimental data
showing the higher order complexes of anti-TNF antibodies incomplex with TNF (35). Before this information became available, it
was widely believed that TNF blockade and not TNFR2 activation
was responsible for Treg expansion. On the receptor side, it has beenchallenging to create therapeutic antibodies against the TNFRSF.
Antibodies against the TNFRSF can either block signaling andfunction as antagonists or promote signaling to function as agonists.
It is only during the last few years that we have begun to understandhow antibodies binding to different epitopes and surface structures
can achieve these opposing functions (4–6, 36, 37).
For agonism, the stabilization of the hexagonal cluster of
upright (free or ligand bound) receptors by antibodies that bindon the outside of the receptor, opposite the ligand binding site, may
provide the best solution (6, 38) (Figure 5A). This strategy has been
observed in an agonist antibody targeting DR5 (6) and also by anagonist targeting TNFR2 (38), highlighting that these strategies may
be uniform regardless of the receptor type and their downstream
partners. These antibodies link two receptor trimers together

Understanding the surface structuresof the TNFRSF can aid thedevelopment of better therapeutics
It is important to highlight that early antibody development wasdone in the absence of high-resolution structures of the target
antigen. Often, the exact mechanism of action of the therapeutic
antibodies were unknown as well resulting in surprises decades
later. Over the years research has shown that the target epitope caninﬂuence the function of antibodies and they can act both as
agonists or antagonists. To untangle this relationship requires amore detailed understanding of the antigen structure and therelationship between the target epitope and antibody function.
While several very successful anti-TNF therapeutics have beenlaunched to treat rheumatoid arthritis, psoriatic arthritis andother autoimmune conditions (33), their mechanism of action
still holds surprises even two decades after development. As an
example, the anti-TNF antibody, adalimumab has only recently
been shown to paradoxically function as a TNFR2 agonist (34).
Adalimumab not only has been shown to bind to TNF but
surprisingly to increase its expression on the surface ofmonocytes. As the authors wrote: “The mechanism that may
underlie this surprising result is unclear, but one possibility is

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therefore both Fab arms are necessary. Stabilizing the receptor
cluster may allow prolonged ligand binding and receptor activationor may directly activate the receptors in the absence of exogenous
ligand. An additional potential beneﬁt maybe the inhibition ofreceptor cleavage and/or receptor internalization. This seems to be
the case in a recently developed artiﬁcial protein scaffold (39) thatuses an inducible two-component system to produce hexagonalarrays to which receptors can be attached, thus allowing the study ofgeometry on signaling behavior. An important ﬁnding of the study
is that the artiﬁcial protein scaffolds can modulate theinternalization of the attached receptors with array size playing
an important role in inhibiting endocytosis (39). A naturally
occurring receptor also appears to employ this mechanism. In theepidermal growth factor receptor (EGFR) the transmembrane
GxxxG motif plays an important role in oligomerization induced
internalization and signal attenuation (40). The artiﬁcial 2D scaffold
blocks receptor oligomerization and inhibits receptor

internalization without inducing signaling (39), which could be
important for therapeutic applications. Interestingly, several, but
not all, TNFR members also contain the transmembrane GxxxG
motif (41) that could play a similar role in modulating receptor
internalization and signal attenuation in these members of the
TNFRSF. Therefore, agonist antibodies against TNFRSF membersthat cross-link neighboring receptors greatly improve receptor
stability and signaling (6, 38), and may inhibit receptor
internalization by maintaining the separation of individual
receptor trimers in the hexagonal lattice.
There are conﬂicting data in the literature on the need for Fcg
recruitment but it is not an absolute requirement for receptor
agonism (4, 6, 38, 42–44). Neither the anti-DR5 nor the antiTNFR2 agonist antibodies require Fcg engagement for agonism (6,38). Further examples include anti-CD40 and anti-Fn14 agonist
antibodies that similarly do not require Fcg engagement (45, 46). At
times antibodies that function via Fcg recruitment have been

A

B

FIGURE 5

Antibody targeting strategies of TNF receptors (A) Agonist antibodies stabilize the hexagonal signaling complex TNF (magenta)-TNFR2 (blue)
complexes are arranged on the cell surface in a hexagonal lattice. After receptor activation downstream TRAF signaling partners (shown in green andcyan) are recruited with matching hexagonal geometry. Agonist antibodies (shown in yellow and orange) stabilize the receptor clusters and improvesignaling. (B) Antagonist antibodies stabilize the quiescent state and block the activation of receptors. Receptor dimers (blue) in the quiescent state
are arranged in a hexagonal lattice on the cell surface. Antagonist antibodies shown in purple and violet lock in the ligand-free state and block ligand
binding, receptor activation and the recruitment of downstream signaling partners.

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designated as agonists despite clearly blocking ligand binding.
These antibodies should be more properly designated astherapeutics functioning via antibody dependent cell cytotoxicity(ADCC) and their function should be separated from true receptor
agonism that does not depend on Fcg involvement.
Historically, it has been difﬁcult to create effective antagonist
antibodies against the TNFRSF. For those working in the ﬁeld, it isbroadly appreciated by trial and error that the natural ligands to the
TNFRSF not only have high afﬁnity but also high avidity and can, in
most cases, successfully compete against antagonist antibodies inchallenge assays. For instance, antagonist antibodies raised against
TNFR2 can block TNF binding with different effectiveness (36).
Characterization of several antagonist antibodies to TNFR2 haveshown that strong (or dominant) antagonists targeting the CRD3CRD4 domain could effectively block TNFR2 signaling even in thepresence of increasing concentrations of TNF, while weak (orrecessive) antagonist antibodies target the CRD1-CRD2 domain
and compete poorly with TNF (36). Further characterization
revealed that, only the full antibody or the F(ab’)2 structure isable to successfully block TNF binding. The data supports amechanism where the best antagonists bind to the antiparallel
dimer form of the receptor locking in the non-signaling form of
the receptor (4, 36) (Figure 5B). To highlight the case that structural
homology can translate these ﬁndings to other members of the
TNFRSF, an antagonist antibody to CD40 has also been shown tobind to the antiparallel dimer form of the receptor (47). In this case,the antibody binds as a single Fab domain making interactions to
CRD1 of both CD40 monomers in the dimer. Interestingly, amutation that abolishes binding to the antiparallel dimer form
and results in the mutant antibody binding to a single CD40
monomer turns this antibody into a functional agonist provingthat binding to the antiparallel dimer form is required forantagonistic activity (47).
Several groups have mapped the surface of TNF receptors to see
how the epitopes inﬂuence function. As the above examples show,
there is no clear connection between the epitopes position on the
CRD and agonism or antagonism. However, the consensus that
seems to be emerging is that the best agonists are bivalent or
multivalent antibodies that cross-link and stabilize receptor
complexes in the hexagonal cluster (6, 38) and the best
antagonists are stabilizing the antiparallel form of the receptor(36, 47).
The antibody isotype can also have a huge inﬂuence on thefunction of antibodies both for agonism and antagonism. Several
anti-CD40 agonist antibodies have been shown to beneﬁt fromisotype switching from the IgG1 to IgG2 isotype (48, 49). The IgG2
isotype has also improved the function of an anti-TNFR2 antagonist
antibody (50). Structural and biophysical studies have shown that
the IgG2 isotype is the most rigid of all the IgG isotypes with anarrower range in Fab movement and separation distance (51, 52).
These studies suggest that both agonism and antagonism canbeneﬁt from the IgG2 isotype presumably by better stabilizing thehexagonal cluster with a less ﬂexible antibody.

Frontiers in Immunology

For ligand-based therapeutics targeting the TNFRSF,
approaches that mimic the membrane-bound form result inmuch improved signaling. For a good review on different
strategies see De Miguel et al. (53). The minimum requirement is
the stabilization of the ligands by creating stable covalent trimers by
various methods (54–56). This improves half-life andbioavailability. Generating a more stable and rigid ligand may
also aid in the activation step of the receptors highlighted in
Figure 4B. Linking two trimeric ligands can further improvesignaling by activating neighboring receptors in the cluster (57–62). Several other ligand-fusion complexes have been created withimproved signaling (53, 63–68). However, improvements insignaling by fusion constructs have to be carefully balanced
against the risk of immunogenicity by unnatural looking
complexes that the immune system may recognize as foreign.
Indeed, many ligand constructs that have shown promise in thelab have never made it to the clinic for this reason.

Conclusions
We have reviewed the current state of our understanding of
TNFRSF signaling mechanism. We have shown that TNFRSF
signaling can be described by a uniﬁed model that orders thereceptors and ligands into a honeycomb cluster. The hexagonallattice of TNF receptors is optimized for signal transduction as itprovides the most economical way to build a stable scaffold.
Clustering also results in signal ampliﬁcation that depends oncluster size and geometry in agreement with experimental data
showing TNF receptors are arranged in small nanoclusters on thecell surface. We have shown that high occupancy of a receptor
cluster by ligands leads to a sharp, high amplitude signal, while
random occupancy leads to broad low amplitude signal that is
directly proportional to the concentration of RING dimers or
caspase-8 generated and could explain differences in signaling
outcomes between membrane and soluble TNFSF ligands.
Building of more detailed signaling models in the futurecombined with experiments will further improve ourunderstanding of the intricacies of TNFRSF signaling.
Beyond the TNFRSF, there are a growing number of hexagonal
biological systems that indicate this may be a common arrangementof signaling networks in general. In addition to TNF receptors andtheir downstream signaling partners, chemo- or phototaxis
receptors also cluster into hexagonal core complexes, consisting oftrimers of dimers that further assemble to form large hexagonalarrays (69–71). Signal ampliﬁcation has been observed in thesesystems and it has been proposed that the ampliﬁcation is the resultof cooperativity in the clustered arrays (71–73). Mimicking natural
receptor clustering, artiﬁcial two-dimensional scaffolds have now
been developed that utilize hexagonal lattices to modulate cell
responses (39). The numerous available examples indicate theordered clustering of surface proteins is more frequent inbiological systems than previously appreciated, and most likely

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10.3389/fimmu.2023.1225704

represents the rule and not the exception. It can also provide an
optimal solution to the processing of biological information (21).
As the examples have shown a better understanding of receptor
conformations on the cell surface can lead to the development of
more effective therapeutics. Beyond antibody- and ligand-based
therapeutics, the detailed knowledge of cell surface structures could
also aid the development of small molecule drugs. Due to the highstructural homology among members of the TNFRSF, strategies
that work for the targeting of one receptor can be applied to others.

Conﬂict of interest
The authors declare that the research was conducted in theabsence of any commercial or ﬁnancial relationships that could beconstrued as a potential conﬂict of interest.

Publisher’s noteAll claims expressed in this article are solely those of the authorsand do not necessarily represent those of their afﬁliatedorganizations, or those of the publisher, the editors and thereviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.

Author contributions
EV and DF contributed to the design, writing and revision of
the article. EV and DF approved the ﬁnal content of the article.

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