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Abstract

Antibody-drug conjugates (ADCs) have revolutionized the care of advanced breast cancer. ADCs pair an antibody targeted against a tumor-associated antigen with a cytotoxic payload, aiming to deliver therapy more effectively and with fewer off-target toxicities. Given the growth of ADCs in the past few years, patients are now candidates for multiple agents sequentially. Optimal strategies for sequencing ADCs are not yet known. Here we review retrospective data on ADC sequencing, translational understanding of mechanisms of resistance, and novel ADCs and combination agents in the pipeline that aim to improve upon currently available care.

Plain language summary

Current understanding of sequencing antibody-drug conjugates (ADCs)

Antibody-drug conjugates (ADCs) are a new kind of cancer treatment that have made a big difference for people with breast cancer. What they do is combine a chemotherapy drug with an antibody that seeks out cancer cells. Because the antibody guides the chemo directly to the tumor, ADCs can kill cancer cells more effectively and cause fewer side effects than ordinary chemotherapy. However, doctors do not yet know the best order or timing for giving different ADCs one after the other. In this article, the authors review what patient studies tell us so far about sequencing ADCs, and also look at lab studies that explore how cancer cells become resistant. Finally, they talk about promising new ADCs in development.

Keywords

antibody-drug conjugates breast cancer drug resistance metastasis targeted therapy translational research treatment sequencing

Introduction

Breast cancer (BC) is the most frequently diagnosed cancer and the second leading cause of cancer deaths in women in the United States.¹ Even after curative-intent treatment, a significant percentage of patients will ultimately have a metastatic recurrence and require further treatment.² In the advanced setting, most patients ultimately receive cytotoxic chemotherapy and often experience progression on these agents and require multiple lines of chemotherapy.

Designed to improve outcomes upon traditional cytotoxic chemotherapy, antibody-drug conjugates (ADCs) have rapidly reshaped the treatment landscape across metastatic breast cancer (mBC). This novel class of therapies is composed of monoclonal antibodies with specificity for selected tumor-associated antigens, a cytotoxic payload, and a connecting linker. Highly targeted drug delivery is facilitated by binding specificity to tumor-associated antigens. This allows for highly targeted drug delivery, potentially delivering chemotherapy as much as 100–1000 times more concentrated than standard cytotoxic chemotherapy while still offering the promise of more tolerable therapy.³ In comparison with standard therapy, ADCs may also exert greater efficacy in patients with increased heterogeneity in pretreated tumors through the “bystander effect,” in which the cytotoxic payload may target not only antigen-expressing cells but also the tissues adjacent to those expressing the target antigen.

The human epidermal growth factor receptor 2 (HER2) is amplified or overexpressed in approximately 20% of BCs and is strongly associated with aggressive disease and an unfavorable prognosis. Targeted by the monoclonal antibody trastuzumab, HER2 also became the first target of the first ADC approved for BC, trastuzumab emtansine. Since the approval of this first-generation ADC in 2013 for HER2+ BC, next-generation ADCs have consistently demonstrated improvements in efficacy compared to traditional chemotherapy.⁴ Trastuzumab deruxtecan (T-DXd), also approved for HER2-positive mBC, shares the HER2-targeting antibody of T-DM1 but differs in its payload, linker, and drug-to-antibody ratio (DAR). T-DXd demonstrated a significant improvement in efficacy over T-DM1 in the DESTINY-Breast03 study, with long-term survival analysis showing a median progression-free survival (PFS) of 29.0 versus 7.2 months (hazard ratio (HR), 0.30; 95% confidence interval (CI), 0.24–0.38); the 36-month PFS for T-DXd versus T-DM1 was 45.7% versus 12.4%, respectively, and median overall survival (OS) was 52.6 versus 42.7 months, respectively (HR, 0.73, 95% CI, 0.56–0.94).⁵ The clinical benefit of ADCs now extends beyond HER2+ (defined as HER2 immunohistochemistry (IHC) 3+ or IHC2+ and FISH positive) disease to HER2-low (HER2 IHC 2+/FISH negative or HER2 1+ IHC) and other subtypes, including hormone receptor-positive (HR+) and triple-negative breast cancer (TNBC).^6,7 For patients with metastatic TNBC, the ASCENT trial demonstrated improved OS and PFS with sacituzumab govitecan (SG) compared to treatment of the physician’s choice across various trophoblast cell surface antigen 2 (TROP-2) expression levels, and those with medium or high TROP-2 expression demonstrated increased benefit.^8,9

Advances in ADC development have significantly improved target specificity, payload potency, and linker stability, leading to both enhanced efficacy and broader clinical utility. Recent innovations include employing antibodies engineered for higher tumor-antigen selectivity, using payloads with increased cytotoxicity, and developing novel linkers that improve stability and release at the intended tumor site. These innovations continue to inform clinical success and drive the ongoing evolution of sequential ADC use in BC.^10–12

With the approvals of SG for metastatic HR+/HER2− BC and TNBC, as well as T-DXd for HER2-low mBC, many patients with mBC will ultimately become eligible for treatment with more than one ADC. There is no randomized data to guide optimal ADC sequencing strategies at this time. Therefore, institutional retrospective reviews provide insights that currently guide clinical practice. Given the many components of ADCs, there are multiple opportunities for resistance. Elucidating resistance mechanisms may help guide the development of novel ADCs as well as ADC combinations. In this article, we review existing clinical data to guide rational ADC sequencing, and we explore future directions to refine treatment strategies.

Methods

For this narrative review, we searched the PubMed database for published articles and ClinicalTrials.gov for clinical trials. Keywords such as “breast cancer” and “antibody–drug conjugate” were used. The initial search on ClinicalTrials.gov was conducted in March 2025, and approximately 150 active and recruiting trials were identified. Relevant articles subsequently underwent full-text review, and ADC post-ADC trials were summarized in this paper.

Current ADC clinical landscape: mBC

ADCs have dramatically improved outcomes in mBC across subtypes. For triple-negative disease, the ASCENT and OptiTROP-Breast01 trials demonstrated, respectively, a benefit of SG and sacituzumab tirumotecan (sac-TMT) for both PFS and OS over standard second- or third-line chemotherapy.^8,13 In a small exploratory analysis, the DESTINYBreast-4 trial also suggested a potential benefit of T-DXd in HER2-low TNBC. For endocrine-resistant, estrogen receptor (ER) positive/HER2-negative disease, the DESTINY-Breast04 and DESTINY-Breast06 trials demonstrated a PFS benefit with T-DXd compared with optimal first-line therapy or chemotherapy after more than one prior line, with DESTINY-Breast04 additionally showing an OS benefit. The TROPiCS-02 trial also demonstrated both PFS and OS benefit in the third line of therapy and beyond. In addition, the TROPION-01 trial showed that datopotamab deruxtecan (Dato-DXd) improved PFS over second-line chemotherapy, although no OS benefit was observed. At present, three ADCs are approved by the FDA for use in HER2-low and HER2-negative mBC: SG, T-DXd, and Dato-DXd. SG also holds approval for TNBC. T-DM1 and T-DXd share trastuzumab as the monoclonal antibody but have different payloads, linkers, and DARs. Dato-DXd and SG have a topoisomerase 1 inhibitor (TOP1i) as a payload and target TROP2, but differ in all other components. Table 1 synthesizes the major studies that led to the approval of TOP1 ADCs in HER2-negative mBC. Data remain limited to guide optimal sequencing. Current decisions must balance efficacy, risk of developing resistance, side effect profile, and cumulative toxicity. It is expected that further innovation in various biomarkers (e.g., HER2 level and circulating tumor DNA) will continue to refine patient selection and sequencing decisions.

Table 1.

Major studies leading to approval of TOP1 ADC options in HER2-negative mBC.

ADC trials in mBC	HR+/HER2− BC				TNBC
ADC trials in mBC	DESTINY-Breast06	DESTINY-Breast04	TROPION-Breast01	TROPiCS-02¹⁴	DESTINY-Breast04	ASCENT	OptiTROP-Breast01
Treatment arms	T-DXd (HER2) vs TPC	T-DXd (HER2) vs TPC	Dato-DXd (TROP2) vs TPC	SG (TROP2) vs TPC	T-DXd (HER2) vs TPC	SG (TROP2) vs TPC	S-TMT (TROP2) vs TPC
HER2 status	>0 <1+, 1+, 2+/ISH−	1+, 2+/ISH−	0, 1+, 2+/ISH−	0, 1+, 2+/ISH−	1+, 2+/ISH−	0, 1+, 2+/ISH−	0, 1+, 2+/ISH−
Prior chemotherapy for mBC	0	1–2	1–2	2–4	1–2	⩾1	⩾1
Median PFS	13.2 vs 8.1 mo.	10.1 vs 5.4 mo.	6.9 vs 4.9 mo.	5.5 vs 4.0 mo.	8.5 vs 2.9 mo.	4.8 vs 1.7 mo.	6.7 vs 2.5 mo.
HR (95% CI) PFS	HR 0.64 (0.54–0.76)	HR 0.37 (0.30–0.56)	HR 0.63 (0.52–0.76)	HR 0.66 (0.53–0.83)	HR 0.46 (0.24–0.89)	HR 0.41 (0.33–0.52)	HR 0.32 (0.22–0.44)
Median OS	NA	23.9 vs 17.5 mo.	NA	14.4 vs 11.2 mo.	18.2 vs 8.3 mo.	11.8 vs 6.9 mo.	Not reached vs 9.4 mo.
HR (95% CI) OS	HR 0.81 (0.66–1.01)	HR 0.64 (0.48–0.86)	HR 0.84 (0.62–1.14)	HR 0.79 (0.65–0.96)	HR 0.48 (0.24–0.95)	0.51 (0.42–0.63)	HR 0.53 (0.36–0.78)
ORR	57.3% vs 31.2%	52.6% vs 16.3%	36.4% vs 22.9%	21% vs 14%	50.0% vs 16.7%	31% vs 4%	45% vs 12%

ADC, antibody-drug conjugates; BC, breast cancer; CI, confidence interval; HER2, human epidermal growth factor receptor 2; HR, hazard ratio; mBC, metastatic breast cancer; NA, not available; ORR, objective response rate; OS, overall survival; PFS, progression-free survival; sac-TMT, sacituzumab tirumotecan; SG, sacituzumab govitecan; T-DXd, trastuzumab deruxtecan; TNBC, triple-negative breast cancer; TOP1, topoisomerase 1; TPC, treatment of physician’s choice; TROP2, trophoblast cell surface antigen 2.

Resistance mechanisms

There are many proposed resistance mechanisms to ADC, given the complex structure of these agents. Resistance may be conferred by mutations in the target antigen, tumor resistance to the payload, and increased payload efflux. Therefore, sequencing ADCs with similar payloads and antibody targets may be hampered by cross-resistance.¹⁵ For example, reduced or heterogeneous expression of HER2, a target of T-DM1, has been shown to limit efficacy and is associated with resistance. In addition, antigen modifications, such as dimerization, can also occur and limit efficacy. These may be overcome with combination therapy or bispecific or dual-payload ADCs. Certain ADCs, such as T-DXd, may be able to overcome resistance mechanisms with the bystander effect, by impacting cells neighboring target-positive cells despite their lack of target antigen expression.^16–18 Changes to internal cellular processes, such as changes in expression of efflux pumps, such as ATP-binding cassettes, may also govern resistance.¹⁶

The phase II DAISY trial evaluated T-DXd in patients with mBC across varying levels of HER2 expression, including cohorts of HER2-overexpressing (n = 72), HER2-low (n = 74), and HER2-non-expressing (n = 40). Whole exome sequencing was performed on baseline and matched resistance tumor biopsies to assess both primary and secondary resistance mechanisms. Genomic testing revealed that 3/21 samples had identified SLX4 mutations at resistance, and ERBB2 deletions were more common among T-DXd non-responders. HER2 expression decreased in most patients at resistance; however, it was not clear that reduced T-DXd uptake was the dominant driving force of resistance in this study. Four of six samples showcased intratumoral T-DXd distribution that was persistent at the time of resistance. These results highlight the multifactorial nature of resistance to ADCs, driven by both target-dependent and target-independent factors.¹⁹

Ongoing work is investigating combination therapies, incorporating ADCs with other treatments, such as tyrosine kinase inhibitors may help mitigate resistance, though there is no clear answer.²⁰ Similarly, one analysis evaluating the use of sequential SG followed by the poly(ADP-ribose) polymerase inhibitor (PARPi) talazoparib showcased a PFS of 7.6 months when dosed sequentially and an OS of 11.1 months. Adverse events were generally comparable to those observed in studies of SG monotherapy, and no patients had a dose-limiting toxicity with sequential administration of SG and PARPi.²¹

Sequential ADC studies

With randomized studies investigating ADC sequencing in progress, multiple institutions have reported retrospective studies evaluating the sequencing of ADCs. A key concern is that using the same payload may lead to cross-resistance, potentially limiting the success of sequential ADC therapy. This hypothesis is further supported by real-world data reporting limited PFS benefit when ADCs with the same payload class (e.g., TOP1i) are used sequentially. Recently published data from a large retrospective cohort of 1500 patients from the Flatiron database showed that those previously treated with SG and subsequently receiving T-DXd had shorter PFS compared with patients who had not been exposed to SG. This suggests that cross-resistance does occur between ADCs with the same anti-topo 1 payloads, such that when these agents are used in sequence, even targeting different receptors on the tumor, the level of efficacy is reduced. On the other hand, data from the phase III DESTINY-Breast02 trial show that T-DXd significantly improved mPFS versus physician’s choice in HER2-positive mBC patients after T-DM1 (17.8 vs 6.9 months; p < 0.05).²² This result may suggest that sequencing ADCs with different payloads is more effective; however, it should also be interpreted with caution, as these agents differ not only in their payloads but also in linker characteristics, DAR, and bystander effect.

Table 2 summarizes real-world retrospective data on ADC use after prior ADC exposure. Given the scarcity of randomized trials, these retrospective efforts are valuable for clinical decision-making, although they inherently limit the ability to draw causal conclusions. Most studies include both standard of care ADCs (T-DXd, SG, and Dato-DXd) as well as ADCs currently under investigation.^23–28 Overall, these analyses have demonstrated that patients experience a longer time on treatment with their first ADC compared to later-line ADCs. Some proposed clinical strategies, such as using traditional chemotherapy between ADCs, the “sandwich method,” have not proven clearly effective. However, this data has suggested that developing ADCs with novel components, particularly novel payloads, may allow for more successful ADC sequencing. Table 3 summarizes ongoing ADC-after-ADC clinical trials in mBC that are currently recruiting.

Table 2.

Real-world retrospective data on ADC post-ADC in mBC.

Study (author/year)	Population	Sequence	RR ADC1	RR ADC2	mTTF ADC1	mTTF ADC2	mPFS ADC1	mPFS ADC2	rwOS ADC1	rwOS ADC2
Peng, 2025	HER2+, n = 83 HER2-low, n = 28	AsPd	NA	NA	NA	NA	NA	6.8	NA	NA
		AsPs						2.7
Tarantino, 2025	HER2+, n = 884HR+/HER2−, n = 487 TNBC, n = 119	SG → T-DXd, n = 83	NA	NA	NA	NA	NA	3.4	NA	9.0
Huppert, 2025	HR+/HER2 low, n = 56	SG → T-DXd, n = 24	17/22 (77.3%)	8/23 (34.8%)	6.3	3.6	NA	NA	22.8	7.8
		T-DXd → SG, n = 32	15/32 (46.9%)	5/29 (17.2%)	5.3	2.1	NA	NA	17.7	5.8
	HR−/HER2-low (n = 28)	SG → TDXd, n = 25	17/25 (68.0%)	7/21 (33.3%)	7.5	2.8	NA	NA	16.5	6.5
		TDXd → SG, n = 3	1/3 (33.3%)	0/2 (0.0%)	Undetermined	Undetermined	NA	NA	Undetermined	Undetermined
Abelman, 2023	HR+/HER2− = 13, TNBC = 19, HER2 low = 22	Any	NA	NA	NA	NA	7.55 (3.22–10.25)	2.53 (1.38–4.14)	NA	NA
		Antibody target change	NA	NA	NA	NA	NA	3.25 (1.38, n/a)	NA	NA
		No antibody target change		NA	NA	NA	NA	2.30 (1.38, n/a)	NA	NA
Mai, 2024	HR+, n = 54TNBC, n = 31	SG → T-DXd, n = 33	NA	NA	NA	NA	5.1 (3.27–7.27)	3.5 (2.7–7.7)	NA	NA
		DXd → SG, n = 52	NA	NA	NA	NA	4.9 (3.27–5.7)	2.8 (2.6–3.7)	NA	NA
Chen, 2024	HER2+, n = 64	T-DM1 → T-DXd, n = 27	NA	NA	NA	NA	NA	5.37	NA	NA
		T-DM1 → RC48, n = 13	NA	NA	NA	NA	NA	3.30	NA	NA
		RC48 → T-DM1, n = 6	NA	NA	NA	NA	NA	6.47	NA	NA
		RC48 → T-DXd, n = 15	NA	NA	NA	NA	NA	1.83	NA	NA
		T-DXd → RC48, n = 8	NA	NA	NA	NA	NA	6.05 months	NA	NA
		T-DXd → T-DM1, n = 3	NA	NA	NA	NA	NA	0.93 months	NA	NA
Poumeaud, 2024	HR-HER low, n = 100HR+HER low, n = 71	SG → T-DXd, n=	NA	NA	NA	NA	NA	3.1 (2.6–3.6)	NA	NA
		T-DXd → SG, n=	NA	NA	NA	NA	NA	2.2 (1.9–2.7)	NA	NA

ADC, antibody-drug conjugates; HER2, human epidermal growth factor receptor 2; HR, hormone receptor positive; mBC, metastatic breast cancer; mPFS ADC1, median progression-free survival on first ADC; mPFS ADC2, median progression-free survival on second ADC; mTTF ADC1, median time to treatment failure on the first ADC; mTTF ADC2, median time to treatment failure on the second; NA, not available; RR ADC1, response rate to the first ADC; RR ADC2, response rate to the second ADC; rwOS ADC1, real-world overall survival on first ADC; rwOS ADC2, real-world overall survival on second ADC; SG, sacituzumab govitecan; T-DXd, trastuzumab deruxtecan; TNBC, triple-negative breast cancer.

Table 3.

ADC-after-ADC trials in mBC actively recruiting registered on ClinicalTrials.gov, searched on March 29.

ADC sequencing trials in mBC	TRADE-DXd (TBCRC 064)	SERIES (NCT06263543)	NCT06649331	ACE-Breast-03 (NCT04829604)	NCT06188559	SATEEN (NCT06100874)
Interventional model	Phase II, open-label, RCT	Phase II, open-label, single arm	Phase II, open-label, randomized parallel trial	Phase II, open-label, single-arm	Phase II, open-label, randomized parallel trial	Phase II, open-label, single-arm
Country	USA	USA	China	Multicenter	Multicenter	Multicenter
Treatment arms	T-DXd or Dato-DXd with crossover at progression	SG	SHR-A1811 or SHR-A1921 or SHR-A2009 or SHR-A2102	ARX788	BB-1701	SG + trastuzumab
HR status	HR+ or HR−	HR+	HR+ or HR−	N/R	HR+ or HR−	HR+ or HR−
HER2 status	HER2-low (IHC 1+ or 2+/ISH−)	HER2-low (IHC 1+ or 2+/ISH−)	N/R	HER2-positive (IHC 3+ or 2+/ISH+)	HER2-positive (IHC 3+ or 2+/ISH+) or HER2-low (IHC 1+ or 2+/ISH−)	HER2-positive (IHC 3+ or 2+/ISH+)
Prior therapy	0–1 prior lines. Prior topoisomerase I inhibitor allowed only in neoadjuvant/adjuvant setting if ⩾12 months since last dose to metastatic recurrence	Mandatory prior treatment with T-DXd. Endocrine-refractory and at least 1 but no more than 4 prior chemotherapy regimens in the metastatic setting.	Mandatory prior treatment with ADC. Participants with HR-positive breast cancer must have received prior CDK4/6 inhibitor.	Mandatory prior treatment with T-DXd. 0–5 5 prior regimens of systemic HER-2 targeting therapy or chemotherapy in the metastatic setting.	Mandatory prior treatment with T-DXd. 1–3 prior chemotherapy-based regimes in the unresectable or metastatic setting.	Mandatory prior treatment with a taxane, trastuzumab, and T-DXd.
Primary endpoint	ORR	ORR	ORR	ORR	ORR	ORR
Secondary endpoints	PFS, OS, CBR, TTOR, DOR	PFS, OS, CBR, DOR, QoL	PFS, OS, CBR, TTOR, DOR	PFS, OS, CBR, TTOR, DOR, BOR	PFS, OS, CBR, TTOR, DOR	PFS, OS, CBR, TTOR, DOR

ADC, antibody-drug conjugate; CBR, clinical benefit rate; Dato-DXd, datopotamab deruxtecan; HER2, human epidermal growth factor receptor 2; HR, hormone receptor; IHC, immunohistochemistry; mBC, metastatic breast cancer; ORR, objective response rate; OS, overall survival; PFS, progression-free survival; T-DXd, Trastuzumab deruxtecan; BOR, best overall response; DOR, duration of response; TTOR, time to objective response.

Biomarkers and patient selection

In the absence of randomized data, ADC sequencing for individual patients is guided by retrospective data as well as review of previously administered therapies. Standard biomarkers include hormone receptor (ER and progesterone receptor [PR)] as well as HER2 status. However, the role of biomarkers to customize ADC selection is actively evolving. Tumor-associated antigens, particularly those that are actively targeted by ADCs (such as TROP2 or HER2), are of particular interest. Another strategy of interest is using ctDNA to predict ADC sensitivity and guide selection of later-line ADCs at the time of resistance to the first ADC.²⁹

Safety, tolerability, cumulative dose

Common toxicities from ADCs often include nausea, fatigue, alopecia, and cytopenias. However, each ADC often carries its own unique toxicity profile. T-DM1 commonly causes thrombocytopenia, hepatotoxicity, and neuropathy³⁰ while T-DXd can cause nausea, fatigue, alopecia, and more severe interstitial lung disease (ILD) or pneumonitis.³¹ Grade 3 or higher adverse events seen with SG were neutropenia (51%), leukopenia (10%), diarrhea (10%), anemia (8%), and febrile neutropenia (6%).³² Lastly, Dato-DXd was more commonly associated with stomatitis.³³

While ADCs are generally well tolerated relative to conventional chemotherapy, sequential ADC use may heighten the risk of side effects. Considering each agent’s safety profile will be important when considering sequential ADC use. Those with an overlapping risk of ILD or previous ADC-induced ILD could be predisposed to more significant toxicity with subsequent ADCs. Cautious monitoring, dose modifications, and prophylactic therapies when indicated will be important to mitigate any potential heightened toxicity risks.

Next-generation ADCs

There is great urgency in developing novel ADCs and ADC combinations to improve upon the current standard of care options. Many agents under investigation build upon the current understanding of ADC resistance and provide the possibility of more successful sequencing of ADC options (Table 4).

Table 4.

Select phase Ia/b ADC clinical trials reporting efficacy outcomes, identified on PubMed (search on July 9, 2025; Filter: 2022–Present).

Study (NCT)	Agent	MOA	Population	ORR %, 95% CI	DCR %, 95% CI	CBR %, 95% CI	mPFS, months 95% CI	mDoR, months 95% CI	OS, months 95% CI
NCT04152499³⁴	sac-TMT	Anti-TROP2	mTNBC, n = 59	37.3 (25.0–50.9)	NR	NR	5.8 (2.4–9.1)^a; 5.5 (3.7–10.0)	11.5 (3.7–22.1+)	12.1 (6.1–18.9)^a; 17.1 (12.7–NR)
			HR+/HER2 mBC, n = 41	31.7 (18.1–48.1)	NR	NR	8.0 (5.6–11.1)^b	9.5 (4.2–17.0+)	13.9 (10.5–NR)^b
NCT04892342³⁵	ESG401	Anti-trop2	mBC HR+HER2−, n = 18mBC TNBC, n = 18mBC HER2+, n = 2Endometrial cancer, n = 1Adenoid cystic carcinoma, n = 1	34.2% (19.6–51.4)	65.8 (48.6–80.4)	50.0 (33.4–66.6)	5.1 (1.9–8.2)	6.3 (2.8–8.5)	NR
NCT03944499³⁶	FS-1502	Anti-HER2	mBC HER2+, n = 145Other HER2+ solid tumors, n = 5	37.5% (25.8–50.0)^c	88.1 (77.8–94.7)		15.5 (4.6–NR)	NR	NR
NCT04039230²¹	Concurrent SG + TZP, n = 7Sequential SG + TZP, n = 23	Anti-TOP1 + PARPi	mTNBC, n = 30	NR	NR	Concurrent SG + TZP: 3/7Sequential SG + TZP: 15/19	Concurrent SG + TZP: 2.3Sequential SG + TZP: 7.6	NR	Concurrent SG + TZP: 4.3Sequential SG + TZP: 11.1
NCT04146610³⁷	DP303c	Anti-HER2	HER2+ advanced BC, n = 68HER2+ advanced colorectal cancer, n = 10HER2+ advanced gastric cancer, n = 9	51.5^c 40.9^d	77.3^c 63.6 (40.7–82.8)^d	NR	6.4 (95% CI 4.1–8.5)^c	11.0 (4.0–NR)	NR
NCT03284723³⁸	PF-06804103	Anti-HER2	HER2+ mBC, n = 71HER2+ gastric cancer, n = 22	29.1^c (19.4–40.4)	83.5 (73.5–90.9)	NR	NR	NR	NR

Data from 4-mg/kg group.

Data from 5-mg/kg group.

Data from BC subgroup.

Data from BC with prior treatment with anti-HER2 ADC subgroup.

ADC, antibody-drug conjugate; CBR, clinical benefit rate; CI, confidence interval; DCR, disease control rate; HER2, human epidermal growth factor receptor 2; HR, hormone receptor; mBC, metastatic breast cancer; mDoR, median duration of response; MOA, mechanism of action; mPFS, median progression-free survival; NR, not reported; ORR, objective response rate; OS, overall survival; PARPi, poly(ADP-ribose) polymerase (PARP) inhibition; sac-TMT, sacituzumab tirumotecan; SG, sacituzumab govitecan; TNBC, triple-negative breast cancer; TOP1, topoisomerase 1; TROP2, trophoblast cell surface antigen 2; TZP, talazoparib.

Platinum-based regimens as well as PARPi are common in the treatment of BC; however, resistance is also common. ADCs targeting B7-H4 have shown promise in targeting the immune checkpoint proteins, which are commonly overexpressed in BCs. Of particular clinical interest is the ability of these agents to elicit antitumor activity in models resistant to platinum and PARPi, as this highlights their possible utility in overcoming a common existing therapeutic resistance mechanism.^39,40

Sacituzumab tirumotecan (sac-TMT) is a novel ADC targeting Trop-2 and has demonstrated efficacy in advanced TNBC. The phase III OptiTROP-Breast-01 study compared sac-TMT to chemotherapy in patients with advanced TNBC who had received at least two prior lines of therapy. Median PFS in the cohort treated with sac-TMT was significantly longer at 5.7 versus 2.3 months in those who received chemotherapy (p = <0.00001).⁴¹ The phase Ia study assessing the novel Trop-2 directed ADC with the moderately toxic SN38 payload, ESG401, demonstrated safety and tolerability as well as a favorable toxicity profile in a cohort of patients with advanced HR+HER2—negative disease as well as TNBC. ESG401 demonstrated promising efficacy with an objective response rate (ORR) of 34.5% and 35.1% in late-stage HR+/HER2− and TNBC, respectively. Three of four patients who had been previously treated with ADCs focused on other targets also showed a notable response or disease stabilization with ESG401, highlighting its potential effectiveness when used sequentially (ClinicalTrials.gov identifier: NCT04892342).^35,42

A preclinical study assessing a next-generation anti-HER2 ADC, ARX788, demonstrated potent activity in both T-DM1-sensitive and resistant HER2-positive BC. In vitro, it showed increased cytotoxicity when compared to T-DM1 in various cell lines, including cell lines with T-DM1 resistance. ARX788 was also shown to suppress tumor growth with improved survival outcomes in xenograft models.⁴³ In the ACE-Breast-02 study, a randomized phase II/III study of ARX788 was shown to have a significantly prolonged median PFS of 11.33 months compared to lapatinib plus capecitabine, which had a median PFS of 8.25 months (p = 0.0006).⁴⁴

Additionally, a phase Ia/b trial evaluated the novel HER2-targeted ADC, FS-1502, in patients with metastatic HER2-positive tumors, mainly in BC. FS-1502 demonstrated a manageable safety profile, with common AEs of elevated liver enzymes, hypokalemia, and mild-to-moderate ocular toxicities. It also demonstrated an ORR of 53.7% and a disease control rate of 88.1%, showing promising tolerability and antitumor activity.³⁶

Next-generation ADCs represent a promising step in expanding therapeutic options to treat various BC subtypes. Various novel ADCs have shown encouraging preclinical and clinical efficacy and offer potential solutions to overcome resistance mechanisms to current treatments. As these novel agents come into clinical use, ongoing work is needed to determine if they can extend the time on treatment with ADCs. Finally, ongoing translational research is needed to establish resistance mechanisms that allow for discovery of future therapeutic options.

Conclusion

ADCs have transformed the treatment landscape across all subtypes of mBC. Although sequential ADC use is increasingly common in clinical practice, data guiding optimal sequencing remain limited, and predictive biomarkers of response and resistance are urgently needed. Key unanswered questions include whether a particular order of ADCs yields superior efficacy and how mechanisms of resistance, whether related to the payload or antibody target, should inform sequencing decisions. Strategies such as incorporating cytotoxic chemotherapy between ADCs (the “sandwich” method) have not yet demonstrated clear clinical benefit. Clinical considerations such as performance status, prior therapies, and receptor status may help guide ADC sequencing. Translational work evaluating biospecimens from patients treated with sequential ADCs has suggested that cross-resistance may limit ADC sequencing in some cases, raising the urgency for the development of ADCs with novel targets and payloads.

Our review of the literature suggests that patients generally experience shorter durations of benefit with a second ADC and that sequencing ADCs with different payloads, particularly when targeting the same antigen, may improve PFS relative to using agents with similar cytotoxic mechanisms. Clinical variables such as performance status, prior therapies, and receptor subtype also remain important considerations in guiding ADC selection. Translational studies of biospecimens from patients treated sequentially indicate that cross-resistance may limit the efficacy of back-to-back ADCs, underscoring the need for continued development of agents with novel targets and payloads.

Ongoing prospective studies, such as TRADE-DXd, are designed to address these questions directly. TRADE-DXd investigates both the clinical efficacy and biological mechanisms underlying ADC sequencing, evaluating whether treatment with T-DXd before or after Dato-DXd influences outcomes in HER2-low mBC, while also incorporating comprehensive biomarker analyses to elucidate mechanisms of resistance. These prospective data will hopefully provide identify predictive biomarkers and help guide clinical practice.

As more ADCs enter clinical development, it will be critical to determine whether patients truly experience a durable benefit from sequenced treatments. Emerging agents and rational ADC combinations hold promise for extending response durations and improving outcomes. Concurrent biomarker analyses may further refine patient selection and optimize therapeutic sequencing. Together, these innovations offer hope for a future in which development of novel ADCs continues to advance survival and quality of life for patients with BC, a goal shared across the oncology community.

Footnotes

Acknowledgements

None.

Declarations

ORCID iDs

Shannon McLaughlin

Arielle J. Medford

Rachel O. Abelman

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Current landscape of sequencing ADCs in metastatic breast cancer

Abstract

Plain language summary

Keywords

Introduction

Methods

Current ADC clinical landscape: mBC

Resistance mechanisms

Sequential ADC studies

Biomarkers and patient selection

Safety, tolerability, cumulative dose

Next-generation ADCs

Conclusion

Footnotes

Acknowledgements

Declarations

ORCID iDs

References