Identifying research gaps in PIK3CA-mutant breast cancer: a bibliometric analysis of evolving trends and clinical applications

Introduction

Breast cancer remains a major global health challenge, ranking as one of the leading causes of cancer-related mortality among women worldwide and imposing a substantial burden on healthcare systems and societies (1,2). Traditional treatment strategies include surgery, radiation, chemotherapy, and targeted therapies (3). However, recent advances have shifted the focus toward understanding the molecular mechanisms underlying tumorigenesis. Among these, the phosphatidylinositol 3-kinase (PI3K) pathway has emerged as a central area of investigation. Mutations in the phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha gene (PIK3CA), which encodes the catalytic subunit of PI3K, represent some of the most frequent genetic alterations in breast cancer. These mutations promote tumor development, progression, and resistance to standard endocrine therapies, particularly in hormone receptor-positive (HR⁺) and human epidermal growth factor receptor 2-negative (HER2⁻) breast cancers, by hyperactivating the PI3K pathway (4-6).

Breast cancer is a heterogeneous disease comprising multiple molecular subtypes, each with distinct therapeutic and prognostic implications. Molecular classification methods, such as gene expression profiling (e.g., PAM50 assay), and immunohistochemistry (IHC), categorize tumors into subtypes including Luminal A, Luminal B, HER2-enriched, Basal-like, and Normal-like. Among these, PIK3CA mutations are most prevalent in HR⁺/HER2⁻ subtypes, which are characterized by estrogen receptor (ER) and/or progesterone receptor (PR) positivity and the absence of HER2 overexpression. This subtype-specific prevalence underscores the need for tailored therapeutic approaches.

Importantly, triple-negative breast cancer (TNBC)—defined by the lack of ER, PR, and HER2 expression—represents an aggressive and clinically challenging subtype with limited targeted treatment options. Although less frequent than in HR⁺/HER2⁻ cancers, PI3K pathway alterations, including PIK3CA mutations and activation of alternative PI3K isoforms, have also been identified in TNBC (7). These alterations are increasingly recognized as potential therapeutic targets, and ongoing research is evaluating the efficacy of PI3K inhibitors and combination strategies in this setting. Thus, the PI3K pathway is relevant across multiple breast cancer subtypes, including TNBC, further highlighting its significance in breast cancer biology and treatment (8).

The clinical significance of PIK3CA mutations has been highlighted by the development and regulatory approval of PI3K-targeted therapies, such as alpelisib, which has improved outcomes for patients with HR⁺/HER2⁻ breast cancer harboring these mutations (4,9). As the field moves toward precision medicine, there is a growing need to integrate basic and clinical research, optimize PI3K-targeted strategies, and address ongoing challenges such as drug resistance and tumor heterogeneity. Despite significant advances, critical questions remain regarding the interplay between basic molecular discoveries, translational applications, and clinical implementation, and how these efforts collectively shape the evolving research landscape.

While narrative reviews and meta-analyses have summarized major trials and key developments in PIK3CA-related breast cancer research, they do not provide an integrated, quantitative mapping of how the global research landscape is structured and where important gaps persist. In particular, limited attention has been given to how research clusters evolve and interact over time, and to what extent they address critical clinical challenges such as the tumor microenvironment, therapeutic resistance, and the incorporation of PI3K-targeted therapies into clinical trials. To address this gap, this study employs bibliometric cluster analysis to systematically map global research trends, identify thematic clusters, and characterize the interplay between basic research, translational applications, and clinical implementation (10,11).

By uncovering both areas of convergence and underexplored topics across these domains, this study aims to identify research gaps and priority directions rather than to resolve them directly. The resulting evidence map is intended to support researchers and clinicians in better aligning preclinical discoveries with clinical applications and in designing studies that target the most pressing unanswered questions. Such a structured overview is critical for advancing precision medicine and ultimately improving outcomes for patients with PIK3CA-mutant breast cancer. We present this article in accordance with the BIBLIO reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2681/rc).

Methods

Search strategies and data collection

The literature search was conducted using the Web of Science Core Collection (WoSCC), a widely used database for bibliometric studies due to its comprehensive coverage of peer-reviewed research articles and standardized indexing (12). The search formula was as follows: TS = (“Breast Neoplasm*” OR “Breast Tumor*” OR “Breast Cancer*” OR “Breast Carcinoma*” OR “Mammary Neoplasm*” OR “Mammary Tumor*” OR “Mammary Cancer*” OR “Mammary Carcinoma*”) AND TS = (“PIK3CA” OR “PI3KCA” OR “phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha” OR “phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha” OR “PI3K alpha catalytic subunit” OR “p110alpha” OR “p110α” OR “p110 alpha” OR “p110 α”). The search was limited to articles published in English. To minimize database discrepancies, the literature retrieval was conducted on July 15, 2024. Inclusion criteria were restricted to peer-reviewed articles, excluding abstracts, preprints, and conference proceedings due to their inconsistent indexing. While these exclusions may introduce some bias, this approach ensures the reliability of the data used for bibliometric visualization and analysis. All retrieved data, including publication counts, citations, titles, keywords, author affiliations, institutions, and countries, were exported for further analysis.

Statistical analysis

We employed a combination of bibliometric tools to process and analyze the data. R-bibliometrix (version 4.3.3) was used for descriptive statistics and trend visualization, such as the annual number of publications. VOSviewer (version 1.6.20) facilitated the visualization of collaboration networks, including co-authorship, institutional linkages, and journal coupling, as well as keyword co-occurrence networks. CiteSpace (version 6.3.R3) was used to identify and visualize keyword citation bursts, which highlight emerging trends and research frontiers. Visualization analyses were conducted using the following key parameters: (I) time slicing: January 2000 to August 2024; (II) node types: keywords, institutions, countries, and authors; (III) thresholds: a minimum of five occurrences per keyword (top N per segment); and 4. Pruning methods: Pathfinder and pruning merged networks. Node sizes represent publication counts, and link thickness indicates the strength of collaboration or co-occurrence. Different colors signify distinct research clusters, and total link strength quantifies the frequency of co-authorship or co-occurrence interactions. To further contextualize the results, we critically interpreted the collaboration networks, identifying areas of strong centralization and potential gaps in global research diversity. Additionally, the H-index was calculated to evaluate the academic impact of countries, institutions, authors, and journals, providing quantitative insights into their research contributions (10,11).

Results

Overview of research publications

A total of 2,135 publications from 450 journals were identified between 2000 and 2024 (Figure 1A). These studies involved 18,166 authors, with an average of 12.2 co-authors per article and an international co-authorship rate of 33.4%. The average publication age was 6.71 years, and each article received an average of 58.21 citations. A total of 2,834 unique keywords were extracted during the bibliometric analysis (Figure S1).

Figure 1 Flow chart of literature screening and selection. (A) Identification and screening of records from the Web of Science Core Collection. (B) Annual number of publications on PIK3CA and breast cancer (2000–2024). PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha.

The most cited article, “Comprehensive Molecular Portraits of Human Breast Tumors”, published in Nature [2012, impact factor (IF) =50.5], received 9,024 citations, followed by “Integrated Genomic Characterization of Endometrial Carcinoma”, also published in Nature (IF =50.5), with 3,654 citations. Publication output increased rapidly after 2004, with the second-highest peak observed in 2016 (171 articles) and a record high of 184 publications in 2021 (Figure 1B). Linear regression analysis demonstrated a strong correlation between publication count and year (y = 8.6838x − 27.49, R²=0.8838), suggesting a sustained growth trend likely to continue.

Countries and institutions

Geographically, the majority of research output originated from the USA (34.00%), China (17.28%), and the UK (4.68%) (Table 1, Figure S2). The USA also led in total citations (TCs) and demonstrated the highest total link strength [1,274] in the collaboration network, followed by Spain [575] and the UK [573] (Figure 2A, Table S1). At the institutional level, Harvard University ranked first in publication volume (n=597), followed by Unicancer (n=505) and the University of Texas System (n=387) (Figure S3). Collaboration analysis of 109 institutions (each with at least 12 publications) revealed seven main clusters with substantial cross-institutional interactions (Figure 2B). Memorial Sloan Kettering Cancer Center recorded the most collaborations [371], followed by Dana-Farber Cancer Institute [326] and Massachusetts General Hospital [274] (Table S2).

Figure 2 Collaboration networks in PIK3CA-related breast cancer research. (A) International collaboration network among countries/regions. (B) Collaboration network among institutions. PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha.

Authors and journals

The 20 most cited authors are summarized in Table 2. Gordon B. Mills led in TCs [2,246] and ranked second in total publications (26), while Jorge S. Reis-Filho published the most articles [48]. José Baselga achieved the highest H-index, underscoring his significant academic influence. The co-authorship network (Figure 3A) involving 110 authors (each with at least 9 articles) showed strong international collaboration, with Jorge S. Reis-Filho having the highest number of international collaborations [231], followed by Britta Weigelt [218] and Fresia Pareja [129] (Table S3).

Figure 3 Author and journal networks. (A) Co-authorship network among authors. (B) Journal co-occurrence network. (C) Journal coupling network.

The 20 most prolific journals collectively published 874 articles, representing 40.94% of all included studies (Table 3). Clinical Cancer Research (IF =10.0) and Breast Cancer Research and Treatment (IF =3) were the most productive journals, together accounting for 10.21% (n=218) of publications. Among these, Annals of Oncology had the highest IF (IF =56.7), followed by the Journal of Clinical Oncology (IF =42.1). The journal co-occurrence network (Figure 3B) identified Clinical Cancer Research as having the highest total link strength [1,772], followed by Cancer Research [1,402] and Breast Cancer Research and Treatment [1,110]. In coupling network analysis (Figure 3C), Clinical Cancer Research also led [101,325], with Breast Cancer Research and Treatment [82,011] and Cancer Research [53,089] playing pivotal roles in topic centrality.

Analysis of the keywords

The keyword co-occurrence network (Figure 4A, Table S4) revealed that terms such as “breast cancer”, “expression”, “mutations”, and “PIK3CA mutations” were central to the research field. Over time, the research focus evolved from basic molecular mechanisms to clinical and translational topics, such as “therapy”, “survival”, and “liquid biopsy”.

Figure 4 Keyword analysis and research hotspots. (A) Keyword co-occurrence network over time (timeline view). (B) Keyword co-occurrence clusters. (C) Top 20 keywords with the strongest citation bursts.

Cluster analysis identified six major research themes (Figure 4B): cluster 1 (red), molecular mechanisms and signaling pathways. This cluster centers on intracellular signaling cascades and genetic alterations, including terms like “PI3K”, “activation”, “apoptosis”, and “gene mutations”. Cluster 2 (green), genomics and biomarker research. This cluster focuses on genetic drivers and molecular profiles, with keywords like “amplification”, “biomarkers”, “BRCA1”, and “genome”. Cluster 6 (light blue), tumor biology. This cluster encompasses the tumor development and histological classification, with keywords like “mammary tumors” and “solid tumors”.

Clinical and translational research themes: cluster 3 (blue), clinical trials and therapeutic strategies. This cluster highlights advancements in clinical trial designs and targeted therapies, including “alpelisib”, “fulvestrant”, and “combination treatments”. Cluster 4 (purple), cancer subtypes and drug resistance. This cluster is associated with breast cancer subtypes and mechanisms of resistance, with terms like “adenocarcinoma”, “EGFR”, and “mutations”. Cluster 5 (orange), tumor microenvironment and molecular targets. This cluster relates to the role of the tumor microenvironment and actionable molecular targets, such as “tumor suppressor” and “transcription” (Table 4).

The top 20 keywords with the strongest citation bursts (Figure 4C) reflect evolving research priorities. Early bursts (2000–2015) were prominent for terms like “phosphoinositide 3 kinase” and “PIK3CA gene”, indicating a focus on basic molecular research. Recent bursts (2018–2024) highlight clinical applications, including “liquid biopsy”, “triple-negative breast cancer”, and “advanced breast cancer”, signaling a growing emphasis on precision medicine and novel therapeutic strategies.

Discussion

General summary

This bibliometric analysis offers a comprehensive overview of research trends and collaboration patterns in the field of PIK3CA-mutant breast cancer from 2000 to 2024. Over the past two decades, global research output has markedly increased, with the USA, China, and the UK leading in publication volume and international collaboration. Influential institutions such as Harvard University and Unicancer, and key researchers including Gordon B. Mills and Jorge S. Reis-Filho, have shaped the field. Major journals like Clinical Cancer Research and Breast Cancer Research and Treatment are the principal outlets for PIK3CA-focused work.

Beyond documenting growth, our findings highlight persistent geographic and thematic imbalances. Although the USA and China both produce substantial output, their emphases differ: the USA is more oriented toward translational and clinical trial research, whereas China contributes disproportionately to basic molecular and preclinical studies. Collaboration networks are also unevenly distributed, with dense links among high-output countries and relatively sparse connections with low‑ and middle‑income regions. These structural patterns suggest opportunities to strengthen global collaboration and promote more equitable research participation.

Comparisons with bibliometric analyses of other key breast cancer drivers, such as HER2 and BRCA genes, reveal both parallels and distinctions (13,14). For HER2, the literature evolved rapidly from gene amplification and trastuzumab development to wide clinical adoption and optimization of anti‑HER2 combinations. BRCA research has moved from susceptibility gene discovery to risk‑reducing strategies and PARP inhibitor–based precision therapy. PIK3CA research has followed a similar trajectory—from pathway discovery to targeted treatment—but with a relatively later and more heterogeneous transition into clinical application. The broader spread of basic science themes and slower clinical convergence underscores the complexity of PI3K/AKT/PTEN signaling and its integration with endocrine and HER2‑targeted therapies.

Research hotspots and thematic evolution

Keyword cluster analysis identified six interrelated themes, capturing the progression from fundamental biology to clinical translation.

Mechanism-related clusters (clusters 1, 2, and 6)

Cluster 1: molecular mechanisms and signaling pathways

This cluster is dominated by terms such as “PI3K/AKT/mTOR pathway”, “PTEN loss”, and “activation”, reflecting foundational work demonstrating how PIK3CA mutations hyperactivate PI3K signaling, driving proliferation, survival, and endocrine resistance—particularly in hormone receptor‑positive (HR⁺)/HER2-negative (HER2⁻) disease (4,5,15,16). These mechanistic insights underpinned the development of PI3K inhibitors such as alpelisib (17,18). However, cross‑talk between PI3K and other oncogenic cascades (e.g., RAS/RAF/MEK, WNT/βcatenin) remains only partially understood (19,20). The frequent co‑occurrence of “PI3K” and “resistance” highlights the need for integrative multi-omics and single-cell approaches to dissect network-level adaptations under therapeutic pressure.

Cluster 2: genomics and biomarker research

Keywords including “genome”, “biomarkers”, “TP53”, and “heterogeneity” emphasize the role of genomic profiling in characterizing co-alterations (e.g., TP53 mutations, PTEN loss) and their impact on prognosis and treatment response (21). The prominence of “heterogeneity” underscores the challenge of inter- and intra-tumor diversity for biomarker-guided therapy. Increasing focus on liquid biopsy and circulating tumor DNA (ctDNA) (22,23) reflects a shift toward dynamic, minimally invasive monitoring of PIK3CA status and resistance evolution.

Cluster 6: tumor biology and histologic context

This cluster, centered on “tumor biology”, “histology”, and “solid tumors”, captures efforts to integrate molecular alterations with morphologic subtypes (21,24,25). For example, invasive lobular carcinoma, which frequently harbors PIK3CA mutations, differs biologically and histologically from invasive ductal carcinoma, implying a need for subtype-tailored therapeutic strategies. Yet many trials group heterogeneous histologies together, limiting insight into subtype-specific benefits of PI3K-targeted therapies.

Clinical applications and translational clusters (clusters 3–5)

Cluster 3: clinical trials and therapeutic strategies

Keywords such as “alpelisib”, “fulvestrant”, “clinical trial”, and “combination therapy” reflect the translation of pathway biology into targeted interventions (17,18). Pivotal studies like SOLAR-1 and BYLieve demonstrated that alpelisib plus fulvestrant significantly prolongs progression-free survival (PFS) in HR⁺/HER2⁻, PIK3CA-mutant advanced breast cancer, and established PIK3CA mutation as an actionable biomarker. Terms such as “adverse events” and “hyperglycemia” indicate ongoing efforts to manage class-specific toxicities and optimize risk-benefit profiles. In contrast to HER2-targeted agents, where cardiotoxicity emerged as a central safety concern, PI3K inhibitors are particularly challenged by metabolic adverse events, which may affect long-term adherence and clinical uptake.

Cluster 4: breast cancer subtypes and drug resistance

This cluster encompasses keywords “ER⁺”, “HER2⁺”, “triple-negative breast cancer (TNBC)”, “tamoxifen”, “trastuzumab”, “mutations”, and “resistance”, underscoring the interaction between PIK3CA-driven signaling and subtype-specific treatment paradigms (26,27). Studies address resistance to endocrine therapy (e.g., tamoxifen, aromatase inhibitors), HER2-targeted agents (e.g., trastuzumab), and chemotherapy (e.g., cisplatin), as well as the contribution of concurrent PIK3CA mutations to intrinsic and acquired resistance. In line with HER2 and BRCA trends, interest in TNBC has accelerated, with increasing attention to PI3K pathway alterations and rational combination strategies (28-30). Notably, research on PI3K in breast cancer displays considerable overlap across subtypes rather than a clear bibliometric separation, reflecting a search for broadly applicable resistance‑modulating strategies.

Cluster 5: tumor microenvironment and emerging molecular targets

Keywords such as “immune cells,” “tumor microenvironment”, “extracellular matrix”, “tumor-suppressor”, and “transcription” highlight growing recognition that PI3K signaling is shaped by, and in turn shapes, the microenvironment (31,32). For instance, PI3K activation in tumor-associated macrophages can promote immunosuppression and dampen anti-tumor immunity, while stromal and transcriptional regulators within the microenvironment are emerging as complementary targets. Compared with HER2 and BRCA bibliometrics, which are more tumor‑intrinsic in focus, the PIK3CA landscape is increasingly oriented toward microenvironmental modulation as a therapeutic frontier.

Evolution of research frontiers: citation burst analysis

Citation burst analysis illustrates a chronological shift from basic discovery to clinical translation. Early bursts (2000–2015) were driven by seminal work on PI3K/PIK3CA biology, oncogenic activation, and preclinical models (33). From approximately 2016 onward, emerging bursts around terms such as “heterogeneity”, “progression”, and “double-blind” indicate intensified attention to clinical trial design, prognostic stratification, and precision oncology (13,14,20). In the most recent period (2018–2024), bursts in “liquid biopsy”, “triplenegative breast cancer”, and “advanced breast cancer” signal both technological advances and the unmet clinical need in aggressive subtypes (22,23,26,27). This trajectory parallels HER2 and BRCA fields, where discovery-driven bursts transitioned to therapy‑focused bursts following the introduction of trastuzumab or PARP inhibitors. However, in PIK3CA‑related breast cancer, the continued rise of “liquid biopsy”, “combination”, and “heterogeneity”—even after alpelisib approval—suggests that adaptive, real-time management of resistance and clonal evolution is a more prominent and persistent theme than in earlier HER2 or BRCA research.

Clinical implications: from second‑line rescue to first-line combination and pathway-level targeting

The bibliometric trends align closely with evolving clinical practice. Initially, PIK3CA mutations were primarily viewed as markers of poor prognosis and endocrine resistance, with PI3K inhibition considered mainly after endocrine therapy failure. The SOLAR-1 trial and subsequent guidelines established alpelisib plus fulvestrant as a second-line option for HR⁺/HER2⁻, PIK3CA-mutant advanced breast cancer, moving the field toward biomarker-guided “rescue” therapy (9,17,18).

More recent evidence points to further strategic shifts. The INAVO120 study evaluated first‑line triplet therapy with the PI3K inhibitor inavolisib, the CDK4/6 inhibitor palbociclib, and fulvestrant in HR⁺/HER2⁻, PIK3CAmutant disease, demonstrating a substantial PFS benefit (e.g., improvement from approximately 7.3 to 15.0 months; hazard ratio ≈0.43) and supporting earlier pathway blockade in selected patients (34). This represents a conceptual transition from “second-line salvage” to “front-line combination,” raising new questions about optimal patient selection, sequencing with CDK4/6 inhibitors, and management of long‑term toxicity.

Concurrently, pathway targeting has broadened from PIK3CA alone to the wider PI3K/AKT/PTEN axis. The CAPItello-291 trial, for example, showed that the AKT inhibitor capivasertib combined with fulvestrant prolonged PFS in patients with alterations in PIK3CA, AKT1, or PTEN, including those pretreated with CDK4/6 inhibitors (35). This provides an alternative strategy for patients with broader pathway aberrations or who are intolerant or resistant to PI3K-specific inhibitors, and underscores the need for molecularly guided selection among PI3K versus AKT blockade.

For HER2-positive disease, co-targeting HER2 and PI3K is an attractive approach to overcome resistance to anti-HER2 agents, although definitive phase III data and optimized regimens remain limited (36). In TNBC, where heterogeneity and the lack of hormone or HER2 targets pose major challenges, current trials are exploring PI3K pathway inhibitors in combination with chemotherapy, immune checkpoint inhibitors, or antibody–drug conjugates (26,27,29,30). These strategies are informed by the emerging bibliometric emphasis on combination therapy, immune modulation, and advanced disease (22,23).

Liquid biopsy and ctDNA monitoring exemplify the convergence of technological hotspots and clinical applications. Guidelines increasingly recommend PIK3CA testing before systemic therapy in HR⁺/HER2⁻ advanced disease, prioritizing tumor tissue and using plasma ctDNA when tissue is unavailable. However, ctDNA-tissue concordance for PIK3CA can be modest (around 50–60%), leading to false-negative results and residual uncertainty in negative cases, for which retesting of tissue is still advised (37). This gap between conceptual enthusiasm and practical limitations is clearly reflected in the recent citation bursts and suggests that further methodological refinement is required before liquid biopsy can fully support real-time treatment adaptation.

In addition, early-phase data suggest that combining PI3K pathway inhibitors with immune checkpoint blockade may enhance anti-tumor immune responses, particularly in TNBC and other difficult-to-treat subtypes (31,32,38). The increasing prominence of keywords such as “double-blind”, “combination”, and “placebo” in our burst analysis reflects a maturation of clinical trial design toward robust, evidence-based, subtype-specific strategies.

Identified research gaps and future directions

Consistent with the nature of bibliometric analysis, this study does not directly “bridge” existing gaps but rather maps the evidence landscape and identifies underexplored areas. Integrating our quantitative results with recent clinical advances, several key research gaps and priorities emerge.

Optimizing first-line use of PI3K-targeted combinations

Most landmark trials of PI3K inhibition, typified by SOLAR1, have evaluated PI3K inhibitors such as alpelisib in the second-line or later setting after endocrine therapy resistance (39). However, new evidence from first-line triplet regimens, including inavolisib in combination with CDK4/6 inhibitors and endocrine therapy (e.g., INAVO120), is shifting the therapeutic paradigm toward earlier and more intensive pathway blockade. This transition raises several questions that have not yet been sufficiently addressed. First, optimal patient selection and sequencing strategies remain unclear. It is not known which clinical features and molecular profiles, such as disease burden, patterns of visceral involvement, or co-alterations in ESR1, TP53, and BRCA1/2, should guide the decision to deploy PI3K-based triplets upfront versus deferring PI3K inhibition to later lines (40). How these triplets should be sequenced relative to CDK4/6 inhibitor plus endocrine therapy alone also remains uncertain. Second, resistance mechanisms under first‑line, multi‑agent pathway blockade may differ fundamentally from those observed after endocrine monotherapy or laterline PI3K inhibition. Distinguishing these patterns will require prospective trials that systematically incorporate serial tissue biopsies and longitudinal liquid biopsy to track clonal evolution and adaptive signaling (41). Third, extended first-line exposure to PI3K inhibition raises concerns about cumulative metabolic toxicity, quality of life, and survivorship outcomes that are only partially captured in existing datasets. Together, these uncertainties at the interface of trial design and real-world application represent clear research gaps that must be addressed if first-line PI3K-based combinations are to be safely and effectively integrated into standard care.

Pathway-level targeting and molecular stratification

Our bibliometric analysis confirms that PIK3CA mutations occupy a central position in the research landscape; however, recent clinical evidence, such as the CAPItello-291 trial, extends the therapeutic scope to alterations across the broader PI3K/AKT/PTEN axis. This shift from single-gene targeting to pathway-level inhibition introduces new stratification challenges. One unresolved issue is how to choose between PI3K and AKT inhibitors for individual patients with different combinations of PIK3CA, AKT1, and PTEN alterations. It is uncertain whether these agents are interchangeable for specific genotypes or whether distinct molecular contexts favor one class over the other. The potential for additive, synergistic, or antagonistic effects when PI3K and AKT blockade are applied sequentially or in combination has also not been systematically explored. Additionally, most current trials rely on single‑gene mutation status as the primary biomarker for patient selection. There is a need to develop composite biomarkers that integrate mutational burden, copy-number variation, pathway activation signatures, and microenvironmental features to improve the prediction of benefit from PI3K- versus AKT-directed therapy. Finally, as CDK4/6 inhibitors, PARP inhibitors, and antibody-drug conjugates become embedded in various lines of therapy, the optimal integration of PI3K/AKT/PTEN-directed agents into this increasingly complex therapeutic ecosystem is not defined. Prospective, comparative, and biomarker-driven studies are therefore required to translate pathway-level insights into practical, evidence-based treatment algorithms.

Liquid biopsy: bottlenecks and next-generation approaches

The prominent citation bursts for “liquid biopsy” and “ctDNA” in our analysis underscore strong enthusiasm for noninvasive PIK3CA detection and dynamic resistance monitoring (22,23). Nevertheless, several technical and clinical bottlenecks currently limit the full realization of this potential. Plasma ctDNA assays for PIK3CA exhibit only moderate concordance with tissue genotyping, with reported agreement rates around 50–60%, which translates into a significant risk of false-negative results and uncertainty in ctDNAnegative cases. This limitation directly affects therapeutic decisionmaking, as current guidelines often recommend confirmatory tissue testing when ctDNA fails to detect PIK3CA mutations in patients with a high pre-test probability of alteration [American Society of Clinical Oncology (ASCO)/Chinese Society of Clinical Oncology (CSCO) guidelines] (42,43). Furthermore, there is no universally accepted standard for assay platforms, reporting thresholds, or the timing and frequency of sampling specifically for PIK3CA-focused monitoring, complicating cross‑study comparison and harmonization of clinical practice. Although ctDNA is increasingly incorporated into clinical trials, its role as a primary or co‑primary endpoint to trigger early treatment modification remains under development, and genuinely ctDNA-guided adaptive trial designs are still uncommon.

Future work should therefore prioritize improvement of analytical sensitivity and specificity and the exploration of additional analytes beyond conventional ctDNA. Emerging data suggest that extracellular vesicle DNA (EV-DNA) and other circulating nucleic acid compartments may complement ctDNA and provide a more comprehensive view of spatial and temporal tumor heterogeneity (44,45). Longitudinal studies combining ctDNA and EV-DNA profiling with imaging and clinical outcomes are needed to define actionable thresholds for treatment escalation, de‑escalation, or regimen switching, including the early detection of resistance mutations such as PIK3CA subclonal variants or ESR1 alterations. Standardized frameworks and consensus guidelines for integrating dynamic molecular monitoring into routine care and trial endpoints will be critical to move liquid biopsy from a bibliometric hotspot to a robust decision-making tool in PIK3CA-mutant breast cancer.

Understudied subgroups: TNBC and HER2-positive disease

Although TNBC and HER2-positive disease emerge as recurrent topics and recent citation bursts in our analysis, large, dedicated trials specifically targeting PIK3CA-altered TNBC or HER2-positive subgroups remain limited (26-30). In TNBC, most available studies are small, early-phase, and exploratory, often combining PI3K pathway inhibitors with chemotherapy or immune checkpoint blockade in biologically heterogeneous patient populations. As a result, robust evidence for the efficacy of PI3K-directed strategies in genomically defined PIK3CA-mutant TNBC subgroups is still lacking. Similarly, in HER2-positive breast cancer, preclinical and translational data support PI3K pathway activation as a key mechanism of resistance to anti-HER2 therapies, and co-targeting HER2 and PI3K has a strong biological rationale. However, optimal clinical regimens, sequencing strategies, and predictive biomarkers for dual HER2/PI3K or HER2/AKT inhibition have not yet been established. Addressing these gaps will require subtype-specific, biomarker‑driven trials that explicitly stratify patients by PIK3CA/AKT/PTEN status and systematically evaluate rational combinations with standard HER2-targeted regimens and immunotherapeutic agents. Such studies are essential to extend the benefits of pathway targeting beyond the currently dominant HR⁺/HER2⁻ context.

Tumor microenvironment and immuno-oncology integration

Our cluster analysis indicates growing scientific interest in tumor-microenvironment interactions in the context of PIK3CA-mutant breast cancer, yet most clinical trials still focus primarily on tumor-intrinsic genomic markers. Preclinical data suggest that PI3K activation in immune and stromal compartments, including tumor-associated macrophages and other myeloid subsets, can promote immune evasion and influence sensitivity to both PI3K pathway inhibitors and immune checkpoint blockade (31,32,38). However, the precise mechanisms by which microenvironmental PI3K signaling shapes response to PI3K, AKT, and checkpoint inhibitors remain insufficiently defined, particularly in aggressive subtypes such as TNBC and in heavily pre‑treated populations. Future research should therefore move beyond single‑compartment analyses and develop combinatorial strategies that simultaneously modulate tumor‑intrinsic signaling and microenvironmental immunity. This will require incorporating microenvironment‑related biomarkers—such as immune gene signatures, markers of myeloid cell polarization, and spatial profiling of immune–tumor cell interactions—into trial design and patient selection. By embedding these parameters prospectively into clinical studies, the emerging microenvironment theme identified in our bibliometric analysis could evolve from a conceptual hotspot into an actionable framework for designing next‑generation combination therapies in PIK3CA‑mutant breast cancer.

Limitations

This study represents the first bibliometric analysis to systematically investigate the relationship between PIK3CA and breast cancer using extensive unstructured data. Nonetheless, several important limitations should be acknowledged. First, the analysis relied exclusively on the WoSCC database. While WoSCC is widely used in bibliometric research due to its standardized indexing and broad coverage, it does not encompass all scientific publications. Relying on a single database may introduce selection bias, as relevant studies indexed only in other databases—such as PubMed, Scopus, or Embase—may be omitted. Such omissions could affect the representativeness of the dataset, especially regarding research published in less prominent journals or by emerging research communities. Second, this study included only literature published in English. This language restriction potentially introduces language bias, as significant research published in other languages may be excluded. As a result, perspectives and findings from non-English-speaking regions may be underrepresented, thereby limiting the completeness and global generalizability of the results. Third, the use of mathematical models to project publication trends is subject to inherent uncertainty. Rapid growth in the field, the emergence of new research fronts, or delayed indexing could result in actual publication trends deviating from model projections, making it challenging to capture the full scope of relevant literature in real time. Finally, bibliometric analyses are inherently limited by the quality and completeness of available metadata and may not fully capture nuances such as the depth of collaboration, research quality, or clinical impact.

To address these limitations, future research should incorporate large-scale, cross-platform literature data from multiple databases and consider the inclusion of non-English publications. Employing advanced analytical tools and systematic methodologies will further enhance the comprehensiveness and accuracy of bibliometric studies, providing a more holistic and nuanced understanding of the evolving research landscape.

Conclusions

This bibliometric analysis systematically mapped the research landscape of PIK3CA in breast cancer over the past two decades, highlighting how current evidence is organized and where important gaps remain. We identified six major research hotspots that span both basic and clinical domains. Basic research clusters include: cluster 1, molecular mechanisms and signaling pathways; cluster 2, genomics and biomarker research; and cluster 6, tumor biology. Clinical and translational clusters are represented by: cluster 3, clinical trials and therapeutic strategies; cluster 4, cancer subtypes and drug resistance; and cluster 5, tumor microenvironment and molecular targets.

The temporal evolution of these clusters from mechanism-focused studies to precision medicine-oriented applications allowed us to pinpoint underexplored topics, rather than directly “bridge” them. Early efforts primarily addressed fundamental mechanisms, such as the role of PIK3CA mutations in the PI3K/AKT/mTOR pathway and their genomic context. More recent work has prioritized clinical applications, including the development of PI3K inhibitors like alpelisib, the use of liquid biopsy for real-time mutation monitoring, and targeted therapies for advanced subtypes such as TNBC. However, our mapping shows that several clinically relevant areas remain insufficiently characterized.

For scientists, the clustering of keywords such as “tumor microenvironment”, “immune cells”, and “PI3K/AKT/mTOR” reveals a clear gap in the mechanistic understanding of how PI3K pathway activation interacts with immune modulation and stromal dynamics in different breast cancer subtypes. Experimental studies dissecting PI3K signaling in tumor-associated immune cells and the extracellular matrix could clarify mechanisms of immune evasion and resistance, and support rational combinations of PI3K inhibitors with immunotherapy. Likewise, the recurrent co-occurrence of “resistance”, “HER2”, and “PI3K” indicates a need for deeper investigation of dual-pathway targeting strategies in HER2-positive and endocrine-resistant disease, where evidence is still fragmented compared with HR⁺/HER2⁻ tumors.

For clinicians, our findings emphasize that PIK3CA-guided treatment is currently concentrated in HR⁺/HER2⁻ advanced breast cancer, with far fewer clinical trials and real-world studies in PIK3CA-driven TNBC and HER2-positive subtypes. The bibliometric patterns, therefore, point to a shortage of subtype-specific, prospective trials testing PI3K inhibitors in combination with chemotherapy, HER2-targeted agents, or immune checkpoint inhibitors in these more aggressive settings. Additionally, although “liquid biopsy” and “ctDNA” have emerged as high-burst keywords, their integration into routine practice for dynamic treatment adaptation remains inconsistent across health-care systems, highlighting a gap between technological potential and implementation.

By linking bibliometric evidence to concrete biological and clinical questions, this study does not itself resolve these gaps but provides a structured overview that can guide their prioritization. Future work should focus on mechanistic studies at the interface of PI3K signaling, the tumor microenvironment, and immune regulation; subtype-specific clinical trials in TNBC and HER2-positive disease using rational PI3K-based combinations; and the standardized incorporation of liquid biopsy and multi-omics profiling into prospective studies. Addressing these underexplored areas will be essential to translate the accumulated knowledge on PIK3CA into more equitable and effective precision-oncology strategies for patients with breast cancer.

Acknowledgments

None.

Footnote

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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2681/coif). The authors have no conflicts of interest to declare.

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