Precision therapy for driver gene mutations in breast cancer: Current landscape and future perspectives

Abstract

The high heterogeneity of breast cancer necessitates individualized treatment. The widespread application of next-generation sequencing has established driver gene mutation identification as the cornerstone of precision therapy in breast cancer. These mutations drive tumor development and progression by constitutively activating core signaling pathways, such as phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin, cell cycle regulation, and DNA damage repair. This article systematically reviews the biological functions, clinical detection methods, and corresponding targeted therapeutic strategies for key driver genes in breast cancer (e.g., PIK3CA, ESR1, BRCA1/2, and AKT1). In particular, the article focuses on key evidence from clinical trials for relevant targeted agents, such as alpelisib, olaparib, and elacestrant. Concurrently, it delves into the primary molecular mechanisms underlying acquired resistance and strategies for dynamic monitoring. The article prospectively explores future directions involving multi-omics integration, liquid biopsy, artificial intelligence, and novel therapeutic modalities in overcoming resistance and optimizing treatment sequences. Driver gene mutation-guided precision therapy is profoundly reshaping the therapeutic landscape of breast cancer, significantly improving the survival of patients.

Key Words: Breast cancer; Driver gene mutation; Precision therapy; Targeted therapy; Next-generation sequencing

Core Tip: This article delineates the paradigm of driver gene mutation-guided precision therapy in breast cancer. We synthesize the clinical application of targeting key mutations (e.g., PIK3CA, ESR1, BRCA1/2) and analyze the complex landscape of acquired resistance. Critically, we propose a forward-looking framework integrating multi-omics, liquid biopsy, and artificial intelligence to dynamically navigate treatment. The article underscores the necessity of evolving from static biomarker testing towards a proactive, digitally-enabled ecosystem to overcome resistance and optimize sequential therapy, ultimately aiming for sustained patient benefit.

INTRODUCTION

Breast cancer is the most common malignancy among women worldwide[1]. The high degree of molecular and clinical heterogeneity in breast cancer poses a major obstacle to effective treatment[2]. The traditional treatment paradigm based on pathological classification is progressively supplemented and revolutionized by precision medicine based on the molecular features of cancer. With the widespread clinical adoption of next-generation sequencing, identifying “driver gene mutations” involved in tumorigenesis, progression, and treatment resistance has become central to precision therapy in breast cancer[3]. These mutations promote tumor cell proliferation, survival, and metastasis by constitutively activating key signaling pathways, such as phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR), cell cycle regulation, and DNA damage repair[4].

This article aimed to provide a comprehensive overview of the current landscape of driver gene mutations in breast cancer and their implications for precision therapy. We conducted a literature search using PubMed/MEDLINE and Web of Science databases, focusing on articles published between January 2015 and December 2024. Key search terms included “breast cancer”, “driver gene mutation”, “PIK3CA”, “ESR1”, “BRCA”, “AKT1”, “targeted therapy”, “resistance”, and “next-generation sequencing”. Priority was given to pivotal clinical trials (phase II/III), large cohort studies, consensus guidelines, and high-impact reviews. This article systematically reviewed the biological functions, detection strategies, and advances in targeted therapy for key driver genes. It particularly appraised clinical evidence regarding PI3K inhibitors, poly ADP-ribose polymerase (PARP) inhibitors, selective estrogen receptor (ER) degraders, etc. Furthermore, this review explored the complex molecular mechanisms underlying acquired resistance and corresponding strategies. Specifically, it provided a focused perspective on the future of multi-omics integration, artificial intelligence, and innovative therapies in overcoming treatment resistance and optimizing overall disease management, hoping to serve as a reference for clinical practice and scientific research.

MAJOR DRIVER GENE MUTATIONS AND TARGETED THERAPEUTIC STRATEGIES

Molecular profiling of breast cancer has identified multiple driver gene mutations with clinical significance, providing a molecular foundation for the development and application of targeted drugs. Table 1 systematically summarizes the mutational characteristics of these key genes and corresponding targeted strategies[5-10].

Table 1 Major driver gene mutations and targeted therapy strategies in breast cancer.

Gene/biomarker	Mutation type	Related pathway	Main subtype association	Targeted agent	Key clinical evidence
PIK3CA	Somatic hotspot mutations	PI3K/AKT/mTOR	HR+/HER2-	Alpelisib (PI3Kα inhibitor)	SOLAR-1 study: Significant PFS benefit[5]
ESR1	Acquired mutations	Estrogen signaling	HR+/HER2-	Elacestrant (SERD)	EMERALD study: Superior to standard endocrine therapy[6]
BRCA1/2	Germline/somatic mutations	Homologous recombination repair	TNBC, HR+/HER2-	Olaparib, talazoparib (PARP inhibitors)	OlympiAD, EMBRACA studies: PFS benefit[7,8]
AKT1	Somatic mutation (E17K)	PI3K/AKT/mTOR	HR+/HER2-	Capivasertib (AKT inhibitor)	CAPItello-291 study: Significant PFS benefit[9]
HER2 (ERBB2)	Somatic mutations	HER2 signaling	HR+/HER2- (non-amplified)	Neratinib (TKI, tyrosine kinase inhibitor)	SUMMIT basket trial: Demonstrated antitumor activity[10]

HR+: Hormone receptor-positive; HER2-: Human epidermal growth factor receptor 2-negative; PI3K: Phosphatidylinositol 3-kinase; AKT: Protein kinase B; mTOR: Mammalian target of rapamycin; SERD: Selective estrogen receptor degrader; TNBC: Triple-negative breast cancer; PARP: Poly ADP-ribose polymerase; TKI: Tyrosine kinase inhibitor; PFS: Progression-free survival.

PIK3CA mutations and PI3K pathway inhibition PIK3CA is one of the most frequently mutated genes in hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer. Mutations in its encoded p110α subunit can lead to constitutive activation of the PI3K/AKT/mTOR pathway, thereby promoting cell proliferation, survival, and metabolic reprogramming[4]. In the phase III SOLAR-1 study, the PI3Kα isoform-specific inhibitor alpelisib, combined with fulvestrant, significantly prolonged progression-free survival (PFS) in patients with PIK3CA-mutated HR+/HER2- advanced breast cancer, establishing this regimen as a standard of care for this population[5]. However, it is important to critically evaluate this finding. The benefit was primarily observed in patients subjected to prior endocrine therapy, and overall survival data were not statistically significant in the final analysis[11], highlighting PFS as a surrogate endpoint with limitations. Furthermore, cross-trial comparisons are challenging due to differences in patient populations. For instance, differences in prior treatments and the proportion of patients with visceral metastases can affect the outcomes. However, the clinical use of alpelisib is often limited by specific toxic effects, such as hyperglycemia and rash; therefore, enhanced patient selection and proactive management of adverse events are key to maximizing the clinical benefits of alpelisib[11].

ESR1 mutations and evolution of ER-targeted therapy ESR1 mutations represent one of the most common mechanisms underlying acquired resistance following treatment with aromatase inhibitors, causing conformational changes in the ER that lead to ligand-independent constitutive activation[12]. The third-generation oral selective ER degrader (SERD) elacestrant achieved a breakthrough in the phase III EMERALD study. It significantly prolonged PFS compared to standard endocrine therapy in patients with ER+/HER2- advanced breast cancer, and the benefits were particularly pronounced in the ESR1-mutant subgroup[6]. This marks the entry of endocrine therapy into a new SERD era targeting specific resistance mutations. A critical consideration is the sequencing of this agent. The EMERALD trial enrolled patients experiencing disease progression while receiving a cyclin-dependent kinase 4/6 (CDK4/6) inhibitor, establishing its role in later-line settings. Its comparative efficacy vs other SERDs or combination treatment strategies in earlier lines of treatment, and its activity in breast cancer with specific ESR1 mutation subtypes (e.g., Y537S vs D538G), remain areas of ongoing research.

BRCA1/2 mutations and the application of PARP inhibitors. Germline or somatic mutations of BRCA1/2 impair homologous recombination repair, rendering tumor cells highly dependent on the PARP-mediated single-strand DNA break repair pathway[13]. PARP inhibitors, such as olaparib and talazoparib, selectively kill homologous recombination repair-deficient tumor cells through a “synthetic lethal” effect[14]. Based on the results of key phase III studies, such as OlympiAD and EMBRACA, PARP inhibitors have become standard treatment options for patients with BRCA-mutated, HER2-negative advanced breast cancer[7,8], and their application is gradually expanding as neoadjuvant and adjuvant treatment options[15]. Critical analysis revealed differences between the two approved agents. While both improved PFS, talazoparib achieved a higher objective response rate in EMBRACA, with a different toxicity profile (more hematological toxicity) compared to olaparib. Furthermore, their real-world efficacy may be affected by the completeness of BRCA testing (germline vs somatic) and the management of treatment-emergent adverse events, which can affect adherence and duration of treatment.

RESISTANCE MECHANISMS AND COPING STRATEGIES

Despite the remarkable success of targeted therapies, acquired resistance remains an almost inevitable clinical challenge, representing tumor cell escape through clonal evolution under drug selection pressure[16]. A deep and systematic understanding of resistance mechanisms is crucial for formulating precision treatment strategies and prolonging the survival of patients[17].

Resistance mechanisms and subsequent strategies for major targeted therapies. The clinical application of targeted drugs has significantly improved the prognosis of patients with breast cancer; however, the emergence of acquired resistance is often the primary reason behind treatment failure. The development of resistance is a dynamic evolutionary process involving complex molecular mechanisms. Table 2 summarizes common acquired resistance mechanisms stratified by clinical validation level and corresponding subsequent management strategies for major targeted drugs, including CDK4/6 inhibitors, PI3Kα inhibitors, PARP inhibitors, and SERDs[5,9,18-23].

Table 2 Acquired resistance mechanisms and subsequent management strategies for major targeted therapies in breast cancer.

Prior therapy	Category of resistance mechanism	Specific molecular event	Biological consequence	Potential subsequent strategy	Clinical evidence/considerations	Validation level
CDK4/6 inhibitors (e.g., palbociclib)	Cell cycle pathway alteration	RB1 gene loss/mutation	Loss of key downstream brake, uncontrolled cell cycle	Switch to chemotherapy; ADCs (e.g., sacituzumab govitecan)	Poor prognosis, reduced response to subsequent endocrine therapy[18]	Clinically validated
CDK4/6 inhibitors (e.g., palbociclib)	Upstream pathway activation	Acquired PIK3CA or AKT1 mutations	Activation of alternative pathways, bypassing G1 arrest	Combine with or switch to pathway inhibitors (e.g., alpelisib, capivasertib)	SOLAR-1, CAPItello-291 studies show PFS benefit[5,9]	Clinically validated
CDK4/6 inhibitors (e.g., palbociclib)	Other mechanisms	Cyclin E (CCNE1/2) amplification; CDK2 upregulation	Direct drive into S phase, independent of CDK4/6	Investigational CDK2 inhibitors; novel SERDs	Clear preclinical evidence, clinical trials ongoing[19]	Emerging clinical/preclinical
PI3Kα inhibitor (e.g., alpelisib)	Target up/downstream alteration	PTEN loss; AKT1 E17K mutation	Enhanced pathway signaling output	Switch to AKT inhibitor (capivasertib)	CAPItello-291 study confirms capivasertib efficacy[9]	Clinically validated
PI3Kα inhibitor (e.g., alpelisib)	Bypass activation	ERBB2/HER2, FGFR, MET amplification/overexpression	Reactivation of downstream signaling via RTKs	Corresponding RTK inhibitors (e.g., neratinib) in combination	Requires identification via NGS; mostly in trials[20]	Emerging clinical/preclinical
PARP inhibitor (e.g., olaparib)	HRR function restoration	BRCA1/2 reversion mutations	Restores HRR, abolishes “synthetic lethality”	Switch to platinum-based chemotherapy; DNA damaging agents	Common cross-resistance with platinum; clinical evidence[21]	Clinically validated
Selective ER degrader (e.g., elacestrant)	Continued ER activation	De novo or clonally expanded ESR1 mutations (e.g., Y537S)	Insensitivity to existing SERDs, constitutive activation	Switch to chemotherapy; explore next-gen SERDs or PROTACs	Different ESR1 mutations have varying SERD sensitivity[24]	Clinically validated
Selective ER degrader (e.g., elacestrant)	Bypass pathway activation	PIK3CA, AKT1 mutations	Provides ER-independent growth signals	Combine with PI3K/AKT/mTOR pathway inhibitors	A common mechanism for endocrine therapy resistance[26]	Emerging clinical

CDK4/6: Cyclin-dependent kinase 4/6; ADC: Antibody-drug conjugate; HRR: Homologous recombination repair; PROTAC: Proteolysis targeting chimera; RTK: Receptor tyrosine kinase; SERD: Selective estrogen receptor degrader; PFS: Progression-free survival; NGS: Next-generation sequencing; ER: Estrogen receptor; PARP: Poly ADP-ribose polymerase; PI3K: Phosphatidylinositol 3-kinase; AKT: Protein kinase B; mTOR: Mammalian target of rapamycin.

This table systematically organizes current knowledge and provides a clear framework for clinical decision-making.

Holistic strategies to overcome treatment resistance. To address the complex and diverse resistance mechanisms outlined above, it is urgently needed to develop proactive and systematic holistic strategies. Dynamic monitoring and preemptive intervention form the cornerstone of such holistic strategies. Utilizing liquid biopsy for minimal residual disease monitoring and molecular relapse prediction makes it possible to intervene against emerging resistant clones before radiologically detectable recurrence. This strategy may be more effective than waiting for clinical progression[24]. Second, a dual approach of “vertical blockade” and “intelligent combination” should be adopted when designing a treatment strategy, combining inhibitors targeting upstream and downstream components of the same pathway. In addition, based on an understanding of signaling network crosstalk, inhibitors of different pathways from the outset can be combined to prevent bypass activation-driven resistance[25]. Third, treatment must be viewed as a dynamic process, implementing mechanism-based sequential therapy. Analysis of the genomic vulnerabilities of the tumor before treatment initiation not only helps plan the first-line regimen but also contributes to the prediction of resistance pathways. Furthermore, this strategy can help devise second-line treatment and subsequent strategies, forming a clear “treatment roadmap”[26]. Finally, to overcome the resistance deadlock, continuous exploration of agents with novel mechanisms of action is essential. For instance, protein degradation technologies and allosteric inhibitors targeting “undruggable” targets offer new hope as the next line of treatment[27]. In summary, resistance should no longer be viewed as the endpoint of treatment, but rather as a critical decision point within the precision medicine workflow. Systematic analysis of resistance mechanisms and leveraging advanced detection technologies can help potentially transform post-resistance “trial-and-error” into “evidence-guided”, precise sequential therapy.

CLINICAL DECISION FRAMEWORK AND INTEGRATION

A clear decision framework is essential to translate molecular insights into actionable clinical practice. The integration of driver gene testing should follow a structured approach throughout the disease course.

Initial diagnosis (early-stage)

For high-risk early breast cancer (e.g., triple-negative, high-grade HR+), germline BRCA1/2 testing is standard to guide the use of adjuvant PARP inhibitors (e.g., OlympiA trial) and surgical decisions[15]. Tumor-based next-generation sequencing (NGS) may be considered in selected cases to identify rare actionable mutations.

Advanced/metastatic setting (first-line): For HR+/HER2- advanced breast cancer, tumor tissue NGS (or liquid biopsy if tissue unavailable) is recommended to identify actionable alterations (PIK3CA, AKT1, and ESR1) before initiating first-line treatment with a CDK4/6 inhibitor + endocrine therapy. This allows for the planning of subsequent lines of treatment based on the molecular profile.

Progression and resistance (second-line and beyond)

Upon progression, repeat biopsy (preferably of a metastatic site) or liquid biopsy is critical to identify the mechanisms underlying acquired resistance (e.g., ESR1 mutations after treatment with aromatase inhibitors or PIK3CA mutations after CDK4/6 inhibition). This strategy guides the selection of next-line targeted therapy choices (e.g., elacestrant for ESR1 mutant cancer, alpelisib for PIK3CA mutant cancer).

HER2-negative advanced breast cancer

Germline and somatic BRCA1/2 testing is mandatory for all patients to determine eligibility for PARP inhibitors. Tumor NGS can also help identify other alterations (e.g., AKT1 and HER2 mutations) for clinical trial consideration or off-label use in later lines of treatment. This sequential, biomarker-driven approach ensures that treatment decisions are grounded in the evolving molecular landscape of the tumor, moving beyond a one-time test to a dynamic management strategy.

CHALLENGES AND FUTURE PERSPECTIVES

Although driver gene mutation-guided precision therapy has brought unprecedented survival benefits to patients with breast cancer, it still faces serious challenges at the levels of basic research, clinical translation, and widespread application.

Current major challenges

Despite significant progress in driver gene-guided precision therapy, its clinical translation and broad application face systemic challenges. These challenges span technical and management platforms, the intrinsic nature of tumor biology, and clinical practice, undermining the full potential of precision medicine. Table 3 organizes the core challenges facing precision therapy for driver genes in breast cancer and summarizes their specific impacts on clinical practice, clearly and systematically outlining the full scope of current difficulties[11,28-32].

Table 3 Core challenges in precision therapy for driver genes in breast cancer.

Challenge dimension	Specific problem	Impact on clinical practice
Technology and management	Lack of standardization: Non-uniform gene coverage and bioinformatics pipelines across NGS panels	Poor comparability of results, affecting reliability of treatment decisions and clinical trial enrollment[31]
Technology and management	VUS interpretation dilemma: Interpretation of “VUS” highly dependent on expert experience	Leads to clinical decision hesitancy, potentially causing patient anxiety or missed treatment opportunities[32]
Tumor biology	Spatiotemporal heterogeneity: Significant clonal evolution between primary and metastatic sites, and pre-/post-treatment	Single biopsy fails to represent the whole tumor landscape, leading to treatment failure based on localized information[34]
Tumor biology	Complex resistance mechanisms: Involve on-target mutations, bypass activation, histological transformation, etc.	Makes subsequent treatment selection extremely complex, often requiring re-biopsy for dynamic assessment[35]
Clinical translation	Drug toxicity management: e.g., hyperglycemia with alpelisib	Affects patient quality of life and treatment adherence[11]
Clinical translation	Optimization of combination strategies and sequencing: Unclear optimal order of targeted agents	Difficult to maximize efficacy and delay resistance; most combinations remain exploratory[35]

NGS: Next-generation sequencing; VUS: Variant of uncertain significance.

Future directions and strategic outlook

Future efforts must focus on near-term, actionable strategies with clear translational potential to address the aforementioned challenges and build upon the clinical decision framework. Multi-omics integration is central to constructing the next generation of predictive biomarkers. Beyond single mutations, integrating transcriptomic (e.g., immune signatures) and proteomic data can help better identify subgroups sensitive to existing treatment options, like immunotherapy or specific drug combinations, which is a more achievable goal than targeting undruggable genes[33]. In addition, the role of liquid biopsy is poised for expansion and deepening. Its most impactful near-term applications in driver gene contexts are: (1) Dynamic monitoring of acquired resistance mutations (e.g., ESR1) to guide SERD therapy; and (2) Assessing tumor mutational burden and microsatellite instability for selecting immunotherapeutic agents[32]. Moreover, artificial intelligence can empower precision medicine primarily through histopathology image analysis and genomic data to predict mutation status and outcomes. Artificial intelligence can also help manage complex NGS data to prioritize actionable alterations[34]. Finally, the clinical translation of innovative treatment modalities is key to overcoming current challenges. To tackle resistance, the most promising and relevant strategies are as follows.

Next-generation antibody-drug conjugates: Drugs like trastuzumab deruxtecan (for HER2-low disease) and sacituzumab govitecan (for triple-negative breast cancer) are already changing practice by delivering cytotoxic payloads irrespective of specific driver mutations, effectively targeting heterogeneous and resistant tumors[35].

Novel endocrine therapies: The development of oral SERDs beyond elacestrant and complete ER antagonists can help overcome diverse ESR1 mutations.

Rational combinations: Intelligently combining targeted agents (e.g., CDK4/6i + PI3Ki/AKTi) based on molecular profiles to preempt resistance is a critical near-term research focus[25].

Furthermore, future innovative therapeutic strategies, such as next-generation antibody-drug conjugates and novel drug delivery systems, show great promise in addressing core challenges like multi-mechanism resistance and tumor heterogeneity (Table 4).

Table 4 Future innovative therapeutic strategies to address current challenges.

Current challenge	Future innovative strategy	Representative technology/drug class	Potential advantage and mechanism
Multi-mechanism resistance	ADCs	T-DXd, SG	Deliver high-potency cytotoxic agents precisely to tumor cells via a “biological missile” approach, potentially overcoming resistance from bypass activation, etc.
Tumor heterogeneity and drug targeting	Novel drug delivery systems	Nanocarriers, prodrugs	Increase drug concentration at tumor sites, enable tumor microenvironment-specific activation, thereby reducing systemic exposure and adverse effects

ADCs: Antibody-drug conjugates; T-DXd: Trastuzumab deruxtecan; SG: Sacituzumab govitecan.

Focusing on these actionable avenues, including better biomarkers, dynamic monitoring, AI-assisted analysis, the next wave of antibody-drug conjugates, and rational combinations, will provide more immediate benefits to patients and refine the clinical decision framework.

CONCLUSION

The discovery of driver gene mutations and the application of corresponding targeted therapies represent a milestone in the history of breast cancer treatment, marking its formal entry into the era of precision medicine. The identification of key driver genes, such as PIK3CA, ESR1, and BRCA1/2, and the application of targeted agents, like alpelisib, elacestrant, and PARP inhibitors, have significantly improved the outcomes of patients with specific molecular subtypes. However, tumor heterogeneity and acquired resistance remain persistent challenges. Future efforts must focus on strengthening the critical appraisal of clinical evidence, implementing dynamic biomarker-guided clinical decision pathways, and prioritizing the development of near-term translational strategies, such as next-generation antibody-drug conjugates and rational combination regimens, and other innovative approaches outlined in Table 4. The ultimate goal is to achieve truly individualized, precision management throughout the disease course, improving long-term survival and enhancing the quality of life of all patients with breast cancer.