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Predictive Factors of Antibody Drug Conjugates (ADCs) Treatment in Metastatic Breast Cancer: A Narrative Review

A peer-reviewed version of this preprint was published in:
Cancers 2024, 16(23), 4082. https://doi.org/10.3390/cancers16234082

Submitted:

22 October 2024

Posted:

24 October 2024

You are already at the latest version

Abstract
Antibody-drug conjugates (ADCs) have revolutionized the treatment landscape for metastatic breast cancer (MBC), offering targeted delivery of cytotoxic agents with improved efficacy and tolerability compared to conventional chemotherapy. This narrative review explores key predictive factors influencing the efficacy of ADCs, focusing on HER2-targeted therapies such as trastuzumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd), as well as sacituzumab govitecan for triple-negative breast cancer (TNBC). HER2 expression, TROP-2 levels, hormone receptor (HR) status, and the tumor microenvironment emerge as critical biomarkers for patient selection and therapeutic outcomes. Additionally, we discuss resistance mechanisms, such as antigen loss, impaired drug internalization, and the role of circulating tumor DNA (ctDNA) in predicting ADC response. Finally, future perspectives on the sequential use of ADCs and potential combination therapies are highlighted, along with emerging agents targeting alternative antigens like HER3 and LIV-1. Overall, identifying predictive biomarkers and overcoming resistance mechanisms are essential for optimizing the use of ADCs in MBC, thereby improving patient outcomes.
Keywords: 
Antibody-drug conjugates
;  
metastatic breast cancer
;  
predictive factors
;  
HER2
;  
TROP-2
;  
trastuzumab emtansine
;  
trastuzumab deruxtecan
;  
sacituzumab govitecan
Subject: 
Medicine and Pharmacology  -   Oncology and Oncogenics

1. Introduction

Antibody-drug conjugates (ADCs) represent a major advance in breast cancer (BC) treatment, combining the specificity of monoclonal antibodies with the cytotoxic power of chemotherapy. By delivering cytotoxic payloads directly to cancer cells, ADCs minimize damage to normal tissues, offering a promising alternative to conventional treatments (Bhardwaj 2023; Chen 2024).
ADCs are composed of three key elements: a monoclonal antibody targeting cancer cell antigens, a linker, and a potent cytotoxic payload (Al Jarroudi 2023; Conte 2024). Some, like trastuzumab deruxetan (T-DXd), exhibit a “bystander effect,” where the payload affects neighboring cells lacking the target antigen (Bhardwaj 2023; Chen 2024). This selective delivery enhances tolerability and effectiveness compared to traditional chemotherapy (Grinda 2022).
The first FDA-approved ADC for metastatic breast cancer (MBC), trastuzumab emtansine (T-DM1) remains essential for HER2-positive MBC, particularly in patients progressing after trastuzumab-based therapies (Dieras 2017; Mamounas 2021; Krop 2017; Perez 2017). T-DXd has shown superior efficacy over T-DM1, especially in HER2-low and HER2-positive disease (Modi 2020; Modi 2022; Andrè 2023). Another notable ADC, sacituzumab govitecan, targets TROP-2 and has demonstrated substantial benefit in triple-negative breast cancer (TNBC), offering hope for heavily pretreated patients (Bardia 2021).
However, the success of ADCs varies among patients. Predictive factors, such as antigen expression, tumor microenvironment, and genetic mutations, are crucial for optimizing ADC use. Identifying reliable biomarkers and resistance mechanisms is essential for tailoring treatments to individual patients (Chen 2024; Saleh 2024). Emerging biomarkers, such as immune signatures, tumor mutation burden (TMB), and circulating tumor DNA (ctDNA), show potential for predicting ADC response and monitoring treatment resistance in real time (Bhardwaj 2023; Chen 2024; Cai 2024). These advancements hold promise for refining patient selection and improving outcomes in metastatic breast cancer.
This narrative review will explore the predictive factors that influence ADC efficacy in metastatic breast cancer.

2. Key Predictive Biomarkers for ADC Efficacy

2.1. HER2 Expression and Amplification

HER2 (human epidermal growth factor receptor 2) is a critical biomarker in breast cancer, found to be overexpressed in 15-20% of cases of MBC [Marra 2024]. This amplification leads to uncontrolled cell proliferation through the activation of downstream signaling pathways, particularly PI3K-AKT and MAPK, contributing to an aggressive clinical course. HER2 status, determined via immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH), serves as a key predictive factor for selecting patients who will benefit from HER2-targeted therapies (Table 1) (Rassy et al. 2022; Martin et al. 2024).
T-DM1 was approved by the FDA as a second-line treatment for HER2-positive MBC following the phase III EMILIA trial, which showed a significant improvement in median overall survival (mOS) (30.9 vs. 25.1 months, HR 0.65) and an ORR of 43.6% (vs. 30.8%) [Verma 2012]. T-DXd was FDA-approved in 2020 for advanced HER2-positive MBC after at least two prior therapies. The phase II DESTINY-Breast01 trial showed an ORR of 61.4% and median progression-free survival (mPFS) of 19.4 months [Modi 2020]. In the phase III DESTINY-Breast03 trial, T-DXd was superior to T-DM1, with a mPFS of 28.8 vs. 6.8 months (HR 0.33) and a higher ORR (79.7% vs. 34.2%) [Cortes 2022]. T-DXd also showed efficacy in HER2-low patients, with an ORR of 37% and mPFS of 11.1 months [Cortes 2022]. A recent updated analysis confirmed the efficacy of T-DXd over T-DM1 on mPFS (28.8 vs. 6.8 months, HR 0.33), as well as on mOS (not reached in either group, HR 0.64) [Hurvitz 2023]. The phase III DESTINY-Breast04 trial showed T-DXd’s superiority over chemotherapy in HER2-low MBC, with mPFS of 9.9 vs. 5.1 months (HR 0.50) and mOS of 23.4 vs. 16.8 months (HR 0.64) [14]. T-DXd also improved outcomes in HR-positive and triple-negative breast cancer subgroups [Modi 2022].
Overall, HER2 status remains a critical predictive biomarker for the response to T-DM1 and T-DXd. While T-DM1 is effective in HER2-positive tumors, T-DXd’s broader applicability to HER2-low cancers provides a significant advancement, particularly for patients with reduced HER2 expression or those who have developed resistance to earlier HER2-targeted therapies (Cai et al. 2024; Martin et al. 2024).

2.2. Trop-2 Expression in Triple-Negative Breast Cancer

Sacituzumab govitecan (SG) is an ADC comprising an anti-TROP2 mAb linked to the cytotoxic agent SN-38 via a cleavable linker (DAR, 7.6–8:1) [Corti 2022]. In April 2021, the FDA approved SG (10 mg/kg) for metastatic triple-negative breast cancer (TNBC) after ≥2 prior systemic therapies, based on the phase III ASCENT trial [Bardia 2021]. This trial compared SG to treatment of physician’s choice (TPC) in 468 patients, showing an ORR of 35% (vs. 5%), a longer mPFS (5.6 vs. 1.7 months; HR 0.41), and mOS (12.1 vs. 6.7 months; HR 0.48). Although TROP-2 expression was not required for enrollment, higher efficacy was seen in TROP-2-high and TROP-2-median tumors [Bardia 2021]. Indeed, an exploratory biomarker analysis from the ASCENT trial showed that patients with high and medium TROP-2 expression treated with SG had improved outcomes compared to those with low TROP-2 expression [Bardia 2021]. Specifically, patients with high TROP-2 expression had a median progression-free survival (mPFS) of 6.9 months compared to 2.5 months in the TPC arm, while those with low TROP-2 expression had a mPFS of 2.7 months (vs. 1.6 months in the TPC arm) [Bardia 2021]. Median overall survival (mOS) was also higher in patients with high and medium TROP-2 expression (14.2 and 14.9 months, respectively) compared to 9.3 months in patients with low TROP-2 expression [Bardia 2021]. Thus, while SG benefits all patients, it appears particularly effective in tumors with higher TROP-2 expression levels.

3. Other Predictive Factors (See Table 2)

3.1. Predictive Factors for T-DM1 Efficacy

While T-DM1 has demonstrated efficacy in HER2-positive MBC, response to treatment varies significantly across patients due to several predictive factors. Identifying these factors is crucial for optimizing patient selection and treatment outcomes.

3.1.1. HER2 Expression and Amplification

HER2 amplification remains the primary biomarker guiding the use of T-DM1. However, variations in HER2 levels can influence treatment outcomes. Studies have shown that patients with low HER2 expression or HER2 mutations are less likely to respond to T-DM1, leading to primary resistance (Sakai et al. 2018)​. A real-world study further supported this, showing that patients with stronger HER2 amplification demonstrated longer progression-free survival (PFS) and overall survival (OS) compared to those with lower HER2 expression (Baek et al. 2024)​.

3.1.2. Circulating Tumor DNA (ctDNA) and Genetic Mutations

The presence of HER2 amplification in circulating tumor DNA (ctDNA) is emerging as a predictive biomarker for T-DM1 efficacy. In a study by Sakai et al. (2018), patients with detectable HER2 amplification in ctDNA prior to T-DM1 treatment had significantly better responses than those without such amplification (Sakai 2018). Moreover, patients harboring PIK3CA mutations in ctDNA were more likely to exhibit primary resistance to T-DM1, suggesting that genomic alterations in tumor DNA can serve as indicators of reduced efficacy​.

3.1.3. Hormone Receptor Status

The impact of hormone receptor (HR) status on T-DM1 efficacy is another important consideration. Patients with HR-positive, HER2-positive breast cancer often show a less favorable response to T-DM1 compared to HR-negative patients. Moinard et al. (2024) found that HR-positive status was associated with shorter PFS and OS in patients receiving T-DM1 as second-line therapy (Moinard 2024)​. Furthermore, ER positivity, in combination with lower HER2 levels, has been linked to primary resistance, as shown by Watanuki et al. (2020), further emphasizing the need for careful patient stratification based on HR status (Watanuki 2020)​​.

3.1.4. Pharmacokinetic Factors and Exposure-Response Relationships

Pharmacokinetic studies have indicated that patients with higher T-DM1 plasma exposure, particularly those with higher minimum concentrations (Cmin) after the first cycle, tend to have better outcomes in terms of PFS and OS (Chen et al. 2017)​. This relationship between T-DM1 exposure and efficacy suggests that optimizing dosage based on pharmacokinetic profiles could further personalize therapy. In contrast, Li et al. (2017) reported that patients in the lowest quartile of T-DM1 exposure had similar or better outcomes compared to controls, underscoring the complex nature of exposure-response relationships (Li 2017).

3.1.5. Previous Treatment and Resistance Mechanisms

Prior exposure to other HER2-targeted therapies, such as trastuzumab and pertuzumab, also affects T-DM1 efficacy. For instance, patients who progress on dual HER2 blockade often exhibit lower response rates to T-DM1, potentially due to cross-resistance mechanisms (Moinard et al. 2024)​. In this context, Sakai et al. (2018) highlighted the role of alternative signaling pathways, such as PI3K/AKT, which may drive resistance and diminish T-DM1 effectiveness (Sakai 2018)​.

3.2. Predictive Factors for T-DXd Efficacy

Several factors influence the efficacy of T-DXd, and understanding these predictors is critical for optimizing patient outcomes.

3.2.1. HER2 Expression and Amplification

In the phase II DAISY trial, T-DXd demonstrated a confirmed objective response rate (ORR) of 70.6% in patients with HER2-overexpressing mBC (HER2 IHC 3+ or ERBB2 in situ hybridization-positive) [Mosele 2023]. This efficacy extended to patients with lower HER2 expression, with an ORR of 37.5% in HER2-low mBC (IHC 1+ or IHC 2+/ISH-negative). Interestingly, even in HER2-non-expressing tumors (HER2 IHC 0), T-DXd elicited a confirmed ORR of 29.7%, demonstrating some activity in the absence of HER2 expression, although this rate was lower compared to HER2-expressing cohorts [Mosele 2023].
This heterogeneity in response highlights that while HER2 expression is a strong predictor of T-DXd efficacy, the drug’s activity may also rely on mechanisms beyond HER2 targeting, such as the "bystander effect," where the cytotoxic payload can kill neighboring cells not expressing HER2 [Wu 2024]. Nonetheless, higher HER2 expression correlates with better outcomes; in the DAISY trial, patients with HER2 IHC 3+ experienced superior progression-free survival (PFS) compared to those with HER2-low or HER2-negative tumors (median PFS: 11.1 months vs. 6.7 months and 4.2 months, respectively) [Mosele 2023].
These findings underscore the importance of HER2 testing in patient stratification for T-DXd therapy, especially as HER2-low patients represent a growing population that can benefit from this therapy, expanding its use beyond traditionally HER2-positive mBC [Wu 2024].

3.2.2. Brain Metastases

Brain metastases (BMs) are a common complication in MBC, affecting up to 50% of patients, and significantly influence prognosis and treatment outcomes [Hurvitz 2024; Harbeck 2024]. T-DXd has demonstrated substantial intracranial activity in both clinical trials and real-world studies, providing a new therapeutic avenue for patients with HER2-positive mBC and BMs. In the DESTINY-Breast03 trial, T-DXd significantly improved PFS in patients with brain metastases compared to T-DM1, with a median PFS of 15.0 months versus 3.0 months (HR 0.25) [Hurvitz 2024]. Moreover, T-DXd achieved an intracranial objective response rate (ORR) of 65.7% in this population, compared to 34.3% for T-DM1 [Hurvitz 2024]. Further supporting these findings, the pooled analysis of the DESTINY-Breast01, 02, and 03 trials demonstrated a similar ORR of 45.5% in patients with untreated/active BMs and 45.2% in those with treated/stable BMs [Andrè 2024]. The median central nervous system (CNS) PFS in these groups was 18.5 months for untreated BMs and 12.3 months for treated BMs, showing that T-DXd is highly effective across different BM treatment statuses [Andrè 2024]. The TUXEDO-1 trial, focusing on patients with HER2-positive mBC and active BMs, showed even more striking results, with a median PFS of 21 months and an intracranial ORR of 73.3%, further underscoring the drug’s efficacy in controlling brain lesions [Bartsch 2024]. Additionally, real-world studies, such as the one by Dannehl et al. (2024), have shown that T-DXd achieved an intracranial disease control rate (icDCR) of 88% in patients with stable and active BMs, with a median intracranial PFS of 11.2 months [Dannehl 2024].
Data from the DEBBRAH trial also provide insight into T-DXd’s efficacy in HER2-low mBC BM, a population with limited treatment options. In patients with active BMs, the intracranial ORR was 33.3%, and the median intracranial duration of response was 7.2 months, demonstrating that T-DXd may offer benefit even in HER2-low disease [Vaz Batista 2024].
Collectively, these findings position T-DXd as a key systemic therapy for patients with HER2-positive mBC and brain metastases, offering durable intracranial control and survival benefits, even in patients with untreated or progressing brain lesions [Harbeck 2024; Nakayama 2024].

3.2.3. Hormone Receptor Status

The HR status significantly influences the response to T-DXd. In the DE-REAL study, which included 143 patients, 75% had HR-positive/HER2-positive tumors, and 25% had HR-negative/HER2-positive disease. The efficacy of T-DXd was consistent regardless of HR status, with a median progression-free survival (PFS) of 17 months for HR-positive and 15 months for HR-negative patients, indicating no statistically significant difference (HR 0.92; 95% CI, 0.51-1.67; P = 0.78) [Botticelli 2024].
Furthermore, the overall response rate (ORR) was comparable between the two groups, with no substantial variation in disease control. This suggests that T-DXd’s effectiveness in treating HER2-positive mBC is robust across different HR statuses, offering a reliable therapeutic option for both HR-positive and HR-negative patients. These findings highlight T-DXd’s broad applicability in diverse patient populations, emphasizing its utility as a key treatment option irrespective of hormone receptor expression.

3.3. Predictive Factors for Sacituzumab Govitecan Efficacy

3.3.1. Previous Therapy

In the phase I/II IMMU-132-01 trial, SG demonstrated an objective response rate (ORR) of 31.5%, a median progression-free survival (PFS) of 5.5 months, and a median overall survival (OS) of 12.0 months in patients with HR+/HER2- mBC who had progressed on prior endocrine and chemotherapy treatments [Kalinsky 2020]. Additionally, it exhibited a favorable safety profile, with neutropenia being the most common grade 3 or higher adverse event [Kalinsky 2020].

3.3.2. Brain Metastasis

Real-world evidence and retrospective analyses have also highlighted the efficacy of SG in mBC patients with brain metastases (BM). In a multicenter real-world study, SG achieved an intracranial disease control rate of 42% in patients with BM, with a median intracranial progression-free survival of 2.7 months, demonstrating some intracranial efficacy even in heavily pretreated patients [Dannehl 2024].

3.3.3. Sequence of Treatment

The sequential use of SG and T-DXd in HER2-low mBC, though currently recommended, has yielded limited clinical benefit in most patients. A retrospective analysis (ADC-Low study) showed that median PFS was short, with 2.7 months for SG when used after T-DXd in HER2-low patients, indicating that while sequential administration is feasible, additional research is needed to identify patients who may benefit from these ADCs when used sequentially [Poumeaud 2024].
Table 2. Other predictive factors influencing the efficacy of antibody-drug conjugates (T-DM1, T-DXd, and sacituzumab govitecan) in the treatment of MBC.
Table 2. Other predictive factors influencing the efficacy of antibody-drug conjugates (T-DM1, T-DXd, and sacituzumab govitecan) in the treatment of MBC.
Predictive Factor Key Details Key Details References
HER2 Expression & Amplification High HER2 expression (IHC 3+) is linked to better outcomes. Low HER2 or mutations may lead to resistance. Strong predictor for T-DM1 efficacy. T-DXd shows activity in HER2-low and HER2-negative tumors. Sakai et al. 2018; Baek et al. 2024; Mosele et al. 2023
Circulating Tumor DNA HER2 amplification in ctDNA predicts better responses. PIK3CA mutations in ctDNA signal resistance. ctDNA analysis helps predict T-DM1 efficacy and resistance. Sakai et al. 2018
HR Status HR-positive patients show shorter PFS/OS compared to HR-negative. ER-positive, low HER2 expression leads to resistance. T-DM1 efficacy is reduced in HR-positive patients. T-DXd efficacy unaffected by HR status. Moinard et al. 2024; Botticelli et al. 2024
Pharmacokinetics Higher T-DM1 plasma exposure is linked to better outcomes. Complex relationship between dose and response. Personalizing dosage based on pharmacokinetic profiles may optimize outcomes. Chen et al. 2017; Li et al. 2017
Previous HER2-targeted Therapies ​ Prior exposure to trastuzumab and pertuzumab reduces T-DM1 efficacy due to cross-resistance. Alternative signaling pathways may reduce efficacy after dual HER2 blockade. Moinard et al. 2024; Sakai et al. 2018
Brain Metastases T-DXd significantly improves PFS and intracranial activity in HER2-positive and HER2-low patients with brain metastases. Key factor influencing T-DXd efficacy. Substantial intracranial control with T-DXd. Hurvitz et al. 2024; Bartsch et al. 2024
TROP-2 Expression Higher TROP-2 expression correlates with better responses, but low TROP-2 expression also benefits. Predictor of sacituzumab govitecan efficacy, especially in TNBC. Bardia et al. 2021
Sequential ADC Treatment Limited clinical benefit for sacituzumab govitecan after T-DXd in HER2-low patients. More research needed for sequential use of ADCs. Poumeaud et al. 2024

4. Future Perspectives and Lines of Research

The future of ADCs in MBC treatment focuses on overcoming challenges related to the tumor microenvironment (TME), resistance mechanisms, and optimizing therapeutic sequencing and combination strategies (Table 3) [Chen 2024; Saleh 2024; Corti 2023; Bosi 2023; Saltamacchia 2024; Nucera 2024]. Emerging ADCs also hold significant promise for expanding treatment options.

4.1. Role of the Tumor Microenvironment

The TME plays a crucial role in the efficacy of ADCs, influencing both drug delivery and immune response [Bosi 2023; Nucera 2024]. Tumor heterogeneity, varying antigen expression, and the presence of stromal components can limit ADC penetration. Components like stromal fibroblasts, tumor-associated macrophages, and extracellular matrix can act as physical barriers that hinder ADC efficacy.

4.2. Resistance to ADCs

Resistance to ADCs remains a significant hurdle [Saleh 2023]. Mechanisms include antigen loss or downregulation, alterations in drug internalization, and efflux of cytotoxic payloads. Resistance to T-DM1 and T-DXd, for instance, may be linked to lower HER2 expression or mutations in HER2 itself, as well as upregulation of drug efflux transporters like ABCG2. Efforts to mitigate resistance include designing ADCs with improved linkers and payloads that bypass common resistance mechanisms, such as payloads that are less dependent on target internalization.

4.3. Sequential Treatment of ADCs

Sequencing ADCs with different mechanisms of action is a critical research area [Chen 2024; Saltamacchia 2024]. Changing the payload (e.g., switching from T-DM1 to T-DXd) may outcomes, with some evidence showing better progression-free survival (PFS) when using distinct ADCs sequentially. However, cross-resistance remains a concern, particularly when ADCs share similar targets or mechanisms of action. The optimal sequence and combination of ADCs, especially in HER2-low and HER2-positive populations, remains a major goal for future research.

4.4. Combination Strategies and Emerging ADCs

Combining ADCs with other therapeutic agents, such as immune checkpoint inhibitors, PARP inhibitors, and cyclin-dependent kinase 4/6 (CDK4/6) inhibitors, offers an avenue to improve response rates and overcome resistance [Corti 2023]. Additionally, co-targeting TME components along with ADCs is an emerging strategy to boost anti-tumor efficacy.
Furthermore, new ADCs targeting antigens beyond HER2 and TROP-2, such as HER3, LIV-1, B7-H4, and nectin-4, are in various stages of development. These next-generation ADCs utilize innovative linkers and cytotoxic agents, expanding therapeutic possibilities to additional subtypes of breast cancer, including TNBC and hormone receptor-positive, HER2-negative subtypes.

5. Concluding Remarks

ADCs represent a significant advancement in the treatment of MBC, particularly in subtypes like HER2-positive, HER2-low, and TNBC. Predictive biomarkers such as HER2 and TROP-2 expression, hormone receptor status, and the tumor microenvironment are crucial in guiding therapy and optimizing treatment outcomes. Novel ADCs like T-DXd and SG have shown promising efficacy, even in heavily pretreated patients, expanding the therapeutic arsenal. However, challenges such as drug resistance, the role of the tumor microenvironment, and optimal sequencing of ADC therapies remain. Future research focusing on predictive factors, resistance mechanisms, and innovative combination strategies will be pivotal in refining patient selection and enhancing the effectiveness of ADCs in MBC. These efforts aim to improve the personalization of care, ultimately benefiting a broader range of patients.

Funding

None.

Acknowledgments

None.

Conflicts of Interest/Competing Interests

None.

Availability of Data and Material

Not applicable.

Authors’ Contributions

Study conception and design: G.G.C, L.G., P.F.; collection and interpretation of data: All; manuscript drafting: G.G.C, L.G., P.F.; manuscript editing: All; approval to submit: All.

Conflicts of Interest/Competing Interests

None.

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Table 1. Summary of key findings from pivotal clinical trials evaluating T-DM1 and T-DXd in HER2-positive and HER2-low MBC.
Table 1. Summary of key findings from pivotal clinical trials evaluating T-DM1 and T-DXd in HER2-positive and HER2-low MBC.
Study Trial Name Therapy Patient Population Key Findings References
Verma et al. (2012) EMILIA (Phase III) T-DM1 HER2-positive MBC, previously treated - mOS: 30.9 vs. 25.1 months (HR 0.65)
- ORR: 43.6% vs. 30.8%		 [Verma 2012]
Modi et al. (2020) DESTINY-Breast01 (Phase II) T-DXd Advanced HER2-positive MBC, ≥2 prior therapies - ORR: 61.4%
- mPFS: 19.4 months		 [Modi 2020]
Cortes et al. (2022) DESTINY-Breast03 (Phase III) T-DXd vs. T-DM1 HER2-positive MBC, previously treated - mPFS: 28.8 vs. 6.8 months (HR 0.33)
- ORR: 79.7% vs. 34.2%
- HER2-low ORR: 37%, mPFS: 11.1 months		 [Cortes 2022]
Hurvitz et al. (2023) DESTINY-Breast03 (Update) T-DXd vs. T-DM1 HER2-positive MBC - mPFS: 28.8 vs. 6.8 months (HR 0.33)
- mOS: Not reached in either group (HR 0.64)		 [Hurvitz 2023]
Modi et al. (2022) DESTINY-Breast04 (Phase III) T-DXd HER2-low MBC - mPFS: 9.9 vs. 5.1 months (HR 0.50)
- mOS: 23.4 vs. 16.8 months (HR 0.64)		 [Modi 2022]
Table 3. Open lines of research on ADCs in MBC.
Table 3. Open lines of research on ADCs in MBC.
Key Concept Details
Tumor Microenvironment The TME influences ADC efficacy by affecting drug delivery and immune response. Stromal components such as fibroblasts, macrophages, and extracellular matrix act as barriers to ADC penetration.
Resistance Mechanisms Resistance arises from antigen loss/downregulation, impaired drug internalization, and upregulation of efflux transporters (e.g., ABCG2). Resistance to T-DM1 and T-DXd can be caused by decreased HER2 expression or mutations.
Sequential ADC Treatment Sequencing ADCs with different mechanisms (e.g., switching from T-DM1 to T-DXd) may improve outcomes. However, cross-resistance is a concern, particularly when ADCs share similar targets or mechanisms.
Combination Strategies Combining ADCs with agents like immune checkpoint inhibitors, PARP inhibitors, and CDK4/6 inhibitors may enhance efficacy and overcome resistance. Co-targeting the TME is another promising strategy.
Emerging ADCs New ADCs targeting antigens such as HER3, LIV-1, B7-H4, and nectin-4 are under development. These ADCs have innovative linkers and cytotoxic agents, offering therapeutic potential for TNBC and HER2-negative breast cancers.
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