TIGIT (T cell immunoreceptor with Ig and ITIM domains) is an inhibitory receptor on T cells and NK cells that competes with the co-stimulatory receptor CD226 (DNAM-1) for shared ligands (CD155/PVR and CD112/PVRL2). Dual blockade of TIGIT and PD‑1/PD‑L1 can restore CD226 signaling and augment antitumor T cell responses, with additional effects on myeloid cells and regulatory T cells (Tregs). Over the past five years, randomized trials and translational studies have reshaped expectations for the TIGIT class—first via compelling phase 2 signals in PD‑L1–positive non–small cell lung cancer (NSCLC), then through mixed-to-negative phase 3 readouts and deeper human mechanistic insight. Below is a curated review of the most influential studies, why they are landmark, and how they now guide biomarker strategy and next-generation trial design.
Landmark clinical trials: efficacy, safety, and what changed
Landmark status was assigned to studies that most clearly shaped the TIGIT field across clinical and translational dimensions, including pivotal randomized trials in NSCLC and SCLC, whether signal-generating or practice-changing in a negative direction; high-impact translational papers that clarified human mechanism, Fc requirements, and biomarker strategies with clinical correlation; and early-phase trials that established class safety, suggested antitumor activity, or informed key agent-engineering decisions. Priority was given to multinational studies and top-tier publications, including those in Lancet Oncology, Nature, and Annals of Oncology, while also incorporating major negative programs that materially redirected development. Where retrieved materials did not provide underlying data, as with selected vibostolimab phase 3 programs, that limitation is explicitly noted.
Table 1. Selected TIGIT-directed randomized trials and key outcomes (2021–2026)
| Trial | Setting / Population | Regimen | Primary endpoints | Key efficacy | Safety (selected) | Why landmark |
|---|---|---|---|---|---|---|
| CITYSCAPE (Phase 2) 7 | 1L PD‑L1+ (TPS≥1%) metastatic NSCLC | Tiragolumab + atezolizumab vs placebo + atezolizumab (Q3W) | ORR, PFS | ORR 31.3% vs 16.2% (p=0.031); PFS HR 0.57 (95% CI 0.37–0.90; p=0.015); longer follow-up: PFS HR 0.62; OS HR 0.69 17 | Serious TRAEs 21% vs 18%; grade≥3 lipase ↑ 9% vs 3%; 2 treatment-related deaths 7 | First randomized signal that anti‑TIGIT + PD‑L1 can improve outcomes in PD‑L1–selected NSCLC; catalyzed phase 3 programs and biomarker work. |
| SKYSCRAPER‑01 (Phase 3) 33 | 1L PD‑L1‑high (TPS≥50%) advanced NSCLC | Tiragolumab + atezolizumab vs placebo + atezolizumab | PFS, OS | PFS 7.0 vs 5.6 mo; HR 0.78 (95% CI 0.63–0.97; p=0.02); OS 23.1 vs 16.9 mo; HR 0.87 (95% CI 0.71–1.08; p=0.22); ORR 45.8% vs 35.1% | Grade 3–4 AEs 41.2% vs 33.8%; trt‑related grade 5 AEs 1.5% vs 0.8% 33 | Despite numerical improvements in PFS, OS, and ORR, the trial did not meet its dual primary endpoints. |
| SKYSCRAPER‑06 (Phase 2/3) 47 | 1L non‑squamous NSCLC (unselected PD‑L1), chemo‑IO backbone | Tiragolumab + atezolizumab + chemo vs pembrolizumab + chemo | PFS, OS | PFS HR 1.27 (95% CI 1.02–1.57); OS HR 1.33 (95% CI 1.02–1.73)—favoring control; study stopped for futility 47 | No new safety signals 47 | Practice‑changing negative: argued against indiscriminate TIGIT add‑on to chemo‑IO in broad NSCLC, emphasized backbone and selection matter. |
| SKYSCRAPER‑02 (Phase 3) 47 | 1L extensive‑stage SCLC | Tiragolumab + atezolizumab + carbo/etoposide vs placebo + atezolizumab + chemo | PFS, OS | No benefit in PFS or OS (interim); n≈490; negative trial 47 | Grade 3/4 TRAEs 52.3% vs 55.7%; grade 5 TRAEs 0.4% vs 2.0% 47 | Definitive negative in SCLC tempered cross‑tumor extrapolation from NSCLC signals. |
| ARC‑7 (Phase 2) 34 | 1L PD‑L1‑high (TPS≥50%) metastatic NSCLC | Zimberelimab (Z) vs domvanalimab + Z (DZ) vs etrumadenant + domvanalimab + Z (EDZ) | PFS | ORR: 27% (Z), 41% (DZ), 40% (EDZ); median PFS 5.4 (Z), 12.0 (DZ), 10.9 (EDZ) mo; HR vs Z: 0.55 (DZ), 0.65 (EDZ) 34 | Grade≥3 TEAEs: 58% (Z), 47% (DZ), 52% (EDZ) 34 | First randomized signal that an Fc‑silent anti‑TIGIT (domvanalimab) can add to PD‑1, sustaining interest despite tiragolumab setbacks. |
| ARC‑10 Part 1 (randomized) 47 | 1L PD‑L1‑high NSCLC | Domvanalimab + zimberelimab vs zimberelimab vs chemotherapy | OS (primary) | OS HR 0.64 for domvanalimab + zimberelimab vs zimberelimab; 12‑mo OS: 68% (DZ), 57% (Z), 50% (chemo); additional PFS/ORR signals favored DZ (values not fully reported) 47 | Grade≥3 TRAEs: 21.1% (DZ), 15.0% (Z), 47.1% (chemo) 47 | Reinforced ARC‑7 signals; kept Fc‑silent strategy viable pending phase 3 readouts. |
| AdvanTIG‑204 (Phase 2) 35 | 1L limited‑stage SCLC (cCRT) | Ociperlimab + tislelizumab + cCRT vs tislelizumab + cCRT vs cCRT | PFS | Median PFS: 12.6 (A), 13.2 (B), 9.5 (C) mo; HR A vs C 0.84; B vs C 0.80; ORR numerically higher with ICIs; OS NR; no clear distant metastasis benefit 35 | All patients had ≥1 treatment-related TEAE; grade ≥3 treatment-related TEAEs were 73.2%, 78.6%, and 65.1% in arms A, B, and C; no new safety signals.35 | Suggested ICI+cCRT activity; adding TIGIT (ociperlimab) did not clearly improve over PD‑1 alone; foreshadowed futility in NSCLC. |
| AdvanTIG‑302 (Phase 3) 36 | 1L PD‑L1‑high NSCLC | Ociperlimab + tislelizumab vs control | OS | Program halted at futility analysis; unlikely to meet OS; details not reported 36 | — | Program discontinuation in NSCLC signaled class headwinds and the need for tighter selection. |
Early-phase class-defining studies
In the first-in-human study of vibostolimab (NCT02964013), activity in NSCLC appeared to depend strongly on treatment context. The objective response rate reached 26% when vibostolimab was combined with pembrolizumab in patients who were PD-(L)1-naïve, whereas responses were only 3% in PD-(L)1-refractory disease, whether vibostolimab was given alone or in combination. Safety was considered acceptable, and the study helped establish that vibostolimab had limited activity as monotherapy while suggesting that any meaningful clinical value would likely come from combination use 6.
In the phase 1a/b first-in-human study of etigilimab, no dose-limiting toxicities were observed up to 20 mg/kg, and grade 3 or higher treatment-related adverse events occurred in six patients. Clinical activity with etigilimab alone was limited, although preliminary antitumor activity emerged when it was combined with nivolumab, alongside evidence of dose-dependent target engagement. Subsequent cohort-level signals in other tumor types, including associations with PVR expression, further informed ligand-based biomarker hypotheses, even though the retrieved materials did not demonstrate NSCLC-specific efficacy 3 47.
How these trials changed expectations
CITYSCAPE raised hopes for broad first‑line NSCLC benefit, particularly in PD‑L1‑high subsets; SKYSCRAPER‑01 showed that PFS/ORR gains may not guarantee OS improvement, while SKYSCRAPER‑06 and SKYSCRAPER‑02 were definitively negative in unselected NSCLC and ES‑SCLC, respectively 73347. ARC‑7/ARC‑10 revived optimism for Fc‑silent strategies with PD‑L1‑high enrichment 3447.
Across programs, safety was generally consistent with PD‑(L)1 backbones; serious immune‑related AEs were manageable; chemo‑containing regimens drove higher grade ≥3 TEAEs 7333447. No new safety signals emerged to preclude development, but tiragolumab + atezolizumab had higher grade 3–4 AEs and discontinuations than PD‑L1 alone in SKYSCRAPER‑01 33.
Landmark translational studies: mechanism, Fc biology, and biomarkers
Table 2. High‑impact translational studies and their contributions
| Study | Core mechanistic insights | Predictive biomarkers | Design implications |
|---|---|---|---|
| CITYSCAPE translational program (Nature 2024) 117 | Fc‑active anti‑TIGIT required for optimal activity; macrophage/monocyte remodeling; shift of CD8+ T cells from exhaustion to memory‑like states; synergy with PD‑L1 blockade lost with Fc‑silent anti‑TIGIT | Baseline TAM and Treg enrichment predicted OS benefit with tiragolumab + atezolizumab (TAM HR 0.35; Treg HR 0.31); high CD274 (PD‑L1) gene expression predicted stronger benefit (PFS HR 0.42; OS HR 0.18); on‑treatment 11‑protein myeloid signature and sCD163 rise associated with improved PFS/OS 117 | Supports Fc‑competent engineering for myeloid/Treg effects; motivates baseline immune‑contexture and on‑treatment serum proteomics to enrich/stratify; design adaptive enrichment using early myeloid signatures. |
| PD‑1/TIGIT convergence on CD226 (DNAM‑1) 15 | PD‑1 and TIGIT converge to suppress CD226 co‑stimulation; TIGIT extracellular domain blocks PVR–CD226 interaction; dual blockade needed for full CD226 restoration | Intratumoral CD226 expression correlated with improved OS/PFS across atezolizumab trials (BIRCH, OAK, POPLAR) 15 | CD226 emerges as a candidate predictive marker for response to PD‑(L)1 and potentially TIGIT co‑blockade; select for CD226‑rich T cell states. |
| Co‑blockade promotes expansion of multipotent, non‑exhausted CD8+ T cells 16 | TIGIT/PD‑L1 co‑blockade drives CD226‑dependent clonal expansion from stem‑like CD8+ cells in draining lymph nodes; limits entry into exhaustion; trafficking to tumor is critical | Gene signatures (Ccr7.3, Slamf6, Ifit, Ccl5, Cytotox) tracked with clinical responses and OS in CITYSCAPE; composite CCL5/CXCR3/CXCR6 score associated with improved OS on tiragolumab + atezolizumab 16 | Tissue‑rich trial designs should sample lymph node–blood–tumor axes and incorporate trafficking‑related signatures as biomarkers. |
| Fc‑dependent Treg depletion and ADCC/ADCP (EOS‑448 preclinical) 21 | Tregs display highest TIGIT density; Fc‑enabled anti‑TIGIT mediates ADCC/ADCP leading to Treg depletion; can directly kill TIGIT+ tumor cells in hematologic models | — | Provides a mechanistic rationale for Fc‑competent designs to modulate suppressive compartments; balance efficacy vs toxicity when engineering Fc. |
| Expert reviews and syntheses 141819202830 | Consolidate TIGIT biology across T cells, NK cells, and myeloid compartments; underscore CD226 dependence and synergy with PD‑(L)1; discuss resistance via alternative checkpoints and tumor‑intrinsic factors | Point to PD‑L1 high, CD226+, and myeloid‑rich contexts as candidate enrichments; highlight need for robust, prospectively validated predictive biomarkers 14182030 | Advocate tissue‑rich, biomarker‑enabled, mechanism‑tethered trials with adaptive features rather than unselected, large add‑on studies. |
What changed Multiple datasets converged on the CD226 axis as the fulcrum of co‑blockade benefit and on Fc‑competent antibodies as amplifiers of myeloid/Treg reprogramming and memory‑like CD8+ differentiation 1517. However, clinical signals with an Fc‑silent anti‑TIGIT (domvanalimab) suggest that strong PD‑1 co‑inhibition of CD226 plus TIGIT–ligand blockade can still yield benefit in PD‑L1‑high disease 3447.
The most reproducible enrichments to date are PD‑L1 high status, baseline TAM/Treg‑rich immune contextures, CD226‑rich T cell states, and on‑treatment myeloid activation signatures (e.g., sCD163) 11517. These are now informing enrichment and adaptive designs.
Biomarker strategy and patient selection: lessons learned
PD‑L1 enrichment matters but is insufficient alone. CITYSCAPE and ARC‑7/ARC‑10 focused on PD‑L1‑high or PD‑L1‑positive populations and saw the clearest signals there 73447. Yet SKYSCRAPER‑01’s failure to significantly improve OS despite PFS/ORR gains shows PD‑L1 alone is not an optimal predictive biomarker for TIGIT combinations 33.
Immune contexture as a predictive layer. In CITYSCAPE, high intratumoral macrophages and Tregs at baseline were associated with OS benefit from tiragolumab + atezolizumab, consistent with Fc‑dependent remodeling of suppressive compartments 117.
CD226 state as a mechanistic predictor. CD226 expression in effector/trm CD8+ cells correlated with improved outcomes on PD‑L1 therapy and underpins the rationale for dual TIGIT/PD‑(L)1 blockade to fully restore co‑stimulation 1516.
On‑treatment serum myeloid signatures as early indicators. An 11‑protein myeloid composite and sCD163 increases at cycle 2 day 1 predicted better PFS/OS on tiragolumab + atezolizumab; these could support early adaptation or continuation rules in trials 117.
Negative settings sharpen selection. Lack of benefit in ES‑SCLC (SKYSCRAPER‑02) and in broad, chemo‑IO NSCLC (SKYSCRAPER‑06) cautions against unselected add‑on strategies; the limited incremental value of adding ociperlimab to tislelizumab + cCRT in LS‑SCLC further supports more focused selection 3547.
Trial design implications and future directions
What changed in design choices
- Indication prioritization: Focus has shifted toward PD‑L1‑high NSCLC with biomarker enrichment (PD‑L1 high plus myeloid/Treg‑high or CD226‑rich signatures) rather than SCLC or unselected NSCLC chemo‑IO backbones 7333447.
- Backbone selection: PD‑(L)1 backbones remain standard; chemotherapy backbones may dilute or obscure TIGIT contribution and increase toxicity, as illustrated by SKYSCRAPER‑06 47. Combinations with adenosine pathway blockers (etrumadenant in ARC‑7) are being explored but need clearer incremental benefit 34.
- Agent engineering: Fc‑competent antibodies (e.g., tiragolumab) may leverage macrophage/Treg biology and serum myeloid biomarkers 117, whereas Fc‑silent agents (domvanalimab) can still add efficacy via TIGIT–ligand blockade with PD‑1, potentially with a different AE profile 3447. Direct head‑to‑head data are not available in the retrieved materials.
- Endpoints and powering: Given OS fragility in SKYSCRAPER‑01, co‑primary OS with hierarchical testing, and pre‑specified, biomarker‑enriched subgroup analyses are warranted. Incorporating on‑treatment biomarker endpoints (e.g., sCD163) could support adaptive designs 3317.
- Tissue‑rich, mechanism‑tethered studies: The most informative translational findings came from designs that integrated single‑cell, spatial, and serum proteomics with clinical outcomes (CITYSCAPE). Future trials should prospectively embed such analyses across lymph node–blood–tumor compartments to track CD226 states and trafficking 161730.
Hypotheses for next‑generation studies (clearly labeled as hypotheses)
- Enrichment: Prospectively select PD‑L1‑high patients with baseline TAM/Treg‑high or CD226‑rich signatures and validate on‑treatment myeloid composites (e.g., sCD163, MARCO, CSF‑1R) as early pharmacodynamic response markers 11517.
- Setting: Emphasize PD‑L1‑high NSCLC and potentially neoadjuvant/adjuvant contexts where clonal priming and trafficking from lymph nodes can be leveraged; avoid unselected chemo‑IO backbones 1647.
- Combinations: Explore TIGIT + PD‑1 with agents that enhance co‑stimulation or T cell trafficking (e.g., chemokine axis) or that modulate suppressive myeloid niches; triple combinations should demonstrate incremental biology over dual blockade in tissue‑rich cohorts before phase 3 1630.
- Engineering: Test whether Fc‑competent anti‑TIGIT confers superior efficacy in biomarker‑defined, myeloid‑rich tumors versus Fc‑silent formats; weigh efficacy against potential increases in immune‑related AEs—no direct clinical comparison was found in the retrieved materials 1734.
Important data gaps in the retrieved materials
- No peer‑reviewed, full‑text results for KEYVIBE‑006 (vibostolimab + pembrolizumab in 1L PD‑L1‑high NSCLC) were found; broader vibostolimab randomized phase 3 data are missing here 47.
- Biomarker subgroup forest plots and Kaplan–Meier curves for several trials (e.g., ARC‑10) were not available; some results are interim 3447.
- For ociperlimab’s phase 3 futility in NSCLC (AdvanTIG‑302), detailed efficacy and biomarker analyses were not provided in the retrieved announcement 36.
Conclusion: Practical implications for ongoing development
At present, the most consistent clinical activity for TIGIT-directed therapy has been observed in first-line PD-L1–selected NSCLC, particularly PD-L1–high disease, in combination with PD-(L)1 blockade, although definitive overall survival benefit remains to be confirmed in biomarker-enabled phase 3 trials. By contrast, negative results in SCLC and in broadly unselected chemo-immunotherapy NSCLC argue against indiscriminate add-on strategies. Future trials should consider PD-L1–high disease as an entry population and prospectively test enrichment using candidate biomarkers such as TAM/Treg-high or CD226-associated immune states, while embedding serial serum proteomics and tissue-rich single-cell or spatial profiling. Current evidence also favors careful selection of treatment backbone and prospective biomarker-stratified analyses with adaptive decision rules. Mechanistically, next-generation programs should build on CD226-centered biology and lymph node–tumor trafficking, while prospectively evaluating when Fc-competent versus Fc-silent anti-TIGIT formats are best matched to tumor immune contexture and desired myeloid or Treg modulation.