Breast cancer immunogenicity as a spectrum: evolving concepts and therapeutic implications

Immunotherapy has revolutionized the therapeutic landscape for many cancers, but its application in solid tumors has lagged. There is now evidence that immunotherapy can improve outcomes in triple-negative breast cancer, but hormone receptor–positive (HR⁺) breast cancer has traditionally been considered immunologically cold. However, emerging evidence challenges this binary paradigm, suggesting that a biologically relevant subset of HR⁺/human epidermal growth factor receptor 2–negative (HER2^–) tumors exhibit meaningful immunogenic features and clinically relevant sensitivity to immune-based treatment. In this Review we summarize the current understanding of immunogenicity and clinical use of immune-based treatments across breast cancer subtypes. We argue for a broader view of a spectrum of breast cancer immunogenicity and highlight the importance of host factors, including parity and lactation history, in shaping antitumor immunity. Improved identification of immunologically active subsets and deeper mechanistic insight will be essential to expand the therapeutic benefit of immunotherapy to broader patient cohorts and to refine care of patients with breast cancer.

Given the prognostic significance of immune infiltration in TNBC, coupled with the success of anti–PD-(L)1 immune checkpoint blockade (ICB) in other immunogenic malignancies, TNBC was an attractive option for ICB trials in breast cancer.

Initial studies in previously treated advanced and metastatic TNBC showed only modest response rates to anti–PD-1 monotherapy with pembrolizumab (objective response rate [ORR] 5%–6% in KEYNOTE-086) (30, 31) and no significant improvement compared to chemotherapy in KEYNOTE-119 (32). Despite these modest results, the long duration of response to treatment and longer overall survival in patients with tumors that were PD-L1 positive by IHC indicated that a subset of patients with TNBC may derive benefit from immunotherapy. The KEYNOTE-355 randomized, phase III study reported a statistically significant improvement in overall survival with the addition of pembrolizumab to first-line chemotherapy in metastatic, PD-L1–positive TNBC, leading to regulatory approvals for pembrolizumab for this indication (12). The anti–PD-L1 antibody atezolizumab is also approved in some regions for TNBC, based on similar results from the IMpassion130 trial (33). Other clinical trials in the metastatic setting have likewise observed some efficacy signals in PD-L1–positive cohorts. However, the overall response rates in the advanced setting remain minimal, and side effects remain a major challenge (Table 1).

Table 1

Key clinical trials evaluating immune checkpoint blockers in metastatic TNBC

Following these landmark trials, the combination of pembrolizumab and chemotherapy has been implemented in early-stage TNBC as well, with improved pCR rates, recurrence-free survival, and overall survival in the neoadjuvant setting. The KEYNOTE-522 trial was the first randomized, phase III trial to show a significant improvements in pCR event-free survival, and overall survival at the cost of increased treatment related toxicity in early-stage TNBC with a 5% increase in grade 3 treatment-related events (73% vs. 78%) (34). Importantly, these results were observed independent of the PD-L1 status of the patients. These results have since been reproduced in other similarly designed neoadjuvant clinical trials, establishing ICB as the standard of care for TNBC (Table 2). Improving the response rates further will require better understanding of biomarker inconsistencies across different trials and efforts to standardize assays in future applications (35).

Table 2

Key clinical trials evaluating immune checkpoint blockers in early-stage TNBC

Although high levels of TILs have been associated with improved response rates and favorable long-term outcomes in HER2⁺ BC (20, 36, 37), ICB is not currently part of the standard of care, likely reflecting the incredible efficacy of current and emerging HER2-targeted therapies (38). Treatment of HER2+ BC relies on HER2-directed therapies, including trastuzumab, often combined with pertuzumab and chemotherapy, HER2-directed tyrosine kinase inhibitors, and antibody-drug conjugates (ADCs) such as T-DM1 and T-DXd. Notably, many of these approaches have been shown to have immune-mediated mechanisms that contribute to their efficacy (39).

Several clinical trials have shown proof of concept that ICB can have activity in HER2⁺ BC (40–42). However, the addition of atezolizumab to neoadjuvant chemotherapy and dual HER2-targeted blockade did not significantly improve pCR rates in the IMpassion050 clinical trial (43). The reasons for this remain unclear. One possibility is that trastuzumab and pertuzumab already provide substantial priming (25, 44), limiting the potential benefit of the addition of atezolizumab. It is also possible that combining ICB with intense myelosuppressive combination chemotherapy increased toxicity and discontinuation rates and reduced the capacity to generate an effective immune response. As such, while the data suggest immunity is an important aspect of treatment response in HER2⁺ BC, more research is needed to identify the patient cohorts most likely to benefit and the optimal way to integrate immunotherapy with existing standard-of-care HER2-targeted agents.

HR⁺ BC represents the vast majority of diagnoses (6, 45), many of them in women under the age of 50 (2, 4). These tumors generally depend on ER signaling for growth and survival (46), though HR⁺ BC is also incredibly common in postmenopausal women (47).

In clinical practice, all HR⁺ tumors are classified under the same umbrella based on IHC testing and are often treated with the same regimens. However, HR⁺ BC subtypes have vastly different biologies and patient outcomes. PAM50 is a 50-gene signature that has been used to categorize breast cancers into five intrinsic subtypes that have distinct clinical outcomes (48). By PAM50 analysis, more than 60% of HR⁺ BCs are classified luminal A, with luminal B cancers making up the second most common subtype (~25%) (45). The minor remaining cases are made up of basal-like, HER2-enriched, and normal-like phenotypes (45, 48). Basal-like and luminal B subtypes are known to be more aggressive than luminal A tumors because of a gene signature that more closely resembles a TNBC-like phenotype, presenting with higher grade or stage (49, 50). Histologically, luminal A tumors can be categorized by high PR expression, low nuclear grade, and low Ki67 (proliferation marker), while luminal B tumors typically have lower PR expression, higher grade, and high Ki67, making them more proliferative and more likely to benefit from chemotherapy (49, 51).

In addition to heterogeneity based on molecular classification, other clinical factors appear to affect disease outcomes and may reflect different underlying disease biology. For example, younger women with HR⁺ BC have worse outcomes than their older counterparts, independent of genomic risk, with some data showing worse outcomes even when matched according to genomic risk scores (52, 53). The TAILORx and RxPONDER studies have also indicated that younger women may derive more benefit from chemotherapy rather than endocrine therapy alone compared with postmenopausal patients (54, 55). This suggests that the benefit from chemotherapy may be driven by early induction of menopause, rendering younger premenopausal women at higher risk of recurrences and mortality.

As noted above, HR⁺ BC has generally been considered nonimmunogenic, mostly based on direct comparisons with the other subtypes (56). However, given the vast heterogeneity of HR⁺ BCs, it is perhaps unsurprising that immune infiltration would also be highly heterogenous. Indeed, a subset of early-stage HR⁺ tumors exhibit a more TNBC-like phenotype, with lower ER expression, correlating with increased TILs (26, 57).

Although the median TILs in HR⁺/HER2^– BC is low compared with TNBC, a minority of HR⁺/HER2^– tumors have above 30% TILs (26, 58). Higher TIL levels are also associated with lower PR expression in HR⁺ BCs, increased lymph node involvement, and higher tumor grade, correlating to a more luminal B and biologically aggressive phenotype (Figure 1A) (58, 59). This is also true at the transcriptomic level, with expression of ESR1 negatively correlated with TILs and PD-L1 expression (60). Interestingly, spatial distribution of CD8⁺ TILs has a positive impact on ER⁺ BC patient outcomes (61). Other studies have also highlighted high spatial heterogeneity in the TIL landscape between HR⁺ samples (62), again challenging the notion that HR⁺ BC is a “cold” subtype and encouraging more in-depth characterization of the TME among this subtype.

Figure 1

Immunogenicity spectrum within early-stage HR⁺ BC and host factors that may influence the TME. (A) The vast heterogeneity of HR⁺ BC leads to a broad spectrum for immunogenicity, which correlates with receptor expression, prognosis, and tumor grade. High-immunogenicity tumors can be more susceptible to ICB. (B) Numerous host factors affect tumor immunogenicity.

Homologous recombination deficiency (HRD) has also been linked to the immunogenicity of HR⁺ BCs and their biology (63). HRD refers to the loss of DNA damage proteins, such as BRCA1/2, RAD50/51, and PALB2, or associated genes, such as ATM and CHEK1/2, through either germline variants or acquired mutations within tumor cells (64–66). Patients harboring mutations in core homologous recombination pathways are highly responsive to DNA repair–targeted treatments, such as poly (ADP-ribose) polymerase (PARP) inhibition (67). HRD tumors have been associated with more inflamed and immunogenic TMEs in breast cancer (68, 69). This may be because HRD is correlated with increased tumor mutation burden (TMB) and thus higher neoantigen load (70). High TMB has been correlated with increased immunogenicity and with APOBEC-driven mutagenic signatures in breast cancers (71). Furthermore, deficiency in BRCA1/2 has also been correlated with high levels of large genomic rearrangements (72) that may increase the repertoire of potentially immunogenic alterations, including structural variants that are incompletely captured by conventional TMB measures. Neoantigen load and presentation via HLA molecules are essential for T cell engagement, potentially leading to a “hot” immune environment (73). Interestingly, HR⁺/HER2^– BCs have very high levels of HLA downregulation (74, 75), an established mechanism of immune escape (76), often as a result of strong immune activation (77). This could indicate that HR⁺ BCs induce a very strong immune reaction in the early stages of development, which then pressures immune escape and ultimately leads to a less inflamed microenvironment.

The prognostic role of TILs in HR⁺/HER2^– BCs has been somewhat controversial. While some studies have reported a lack of a correlation between TILs and disease-free survival outcomes in HR⁺ disease (19, 78), the association between higher TILs and more aggressive biology (luminal B, higher grade, and nodal involvement) needs to be considered.

Several early clinical trials evaluating ICB in pretreated HR⁺/HER2^– metastatic breast cancer failed to show clinically meaningful response rates, even in PD-L1–positive selected populations (Tables 3 and 4). Nonetheless, some signals for activity were observed, with an ORR of 19% in the ICON study in a cohort who received the anti-CTLA4 antibody ipilimumab in combination with the anti–PD-1 antibody nivolumab sequentially after chemotherapy (79). More recently, efforts have also focused on identifying subgroups more likely to benefit from ICB. The phase II Nimbus study evaluated a combination of ipilimumab and nivolumab in patients with high TMB (TMB > 9 mutations per megabase) in HER2^– metastatic breast cancer (both TNBC and HR⁺ BC), with an ORR of 20% (80).

Table 3

Key clinical trials evaluating immune checkpoint blockers in metastatic HR⁺/HER2^– BC

Table 4

Key clinical trials evaluating immune checkpoint blockers in early-stage HR⁺/HER2^– BC

Metastatic disease is associated with a more suppressive immune TME, as well as larger tumor burden. Multiomic analysis of matched primary and metastatic samples in the AURORA studies of relapse in metastatic breast cancer have highlighted the vast heterogeneity of metastatic TMEs, which are heavily context dependent on subtype and site (81, 82). For instance, lymph node or skin metastases were shown to have higher immune scores relative to other metastatic sites, such as the liver (81). Lymph node–only metastases have also been correlated with more durable responses to anti–PD-1 blockade (83), indicating the cellular composition of the metastatic site (particularly the immune cell composition) determines the level of efficacy of ICB. While this constrains our ability to identify broad biomarkers of immunogenicity in metastatic patients, there is also an opportunity to improve our understanding of metastatic TMEs in breast cancer and how best to harness immunity in late-stage disease.

Higher response rates to immunotherapy are seen in early-stage HR⁺ disease, similar to what has been observed in TNBC, particularly when it is administered in the neoadjuvant setting. The GIADA trial was one of the first trials that tested ICB as a neoadjuvant therapy in early-stage HR⁺/HER2^– disease (84). The trial showed moderate efficacy in a cohort of 43 luminal B–like early-stage breast cancers, with basal-like phenotypes showing the highest response rates to neoadjuvant nivolumab (84). Subsequently, two large, randomized, phase III studies have evaluated the efficacy of anti–PD-1 antibodies combined with neoadjuvant chemotherapy for HR⁺/HER2^– BC: CHECKMATE-7FL (28), evaluating nivolumab, and KEYNOTE-756 (29), evaluating pembrolizumab. Both studies recruited high-grade or lymph node–positive patients with high Ki67, and included patients with low ER expression, to capture this biologically aggressive phenotype. Both studies showed a statistically significant improvement in pCR rate compared with chemotherapy. Most astonishingly, subgroup analysis from CHECKMATE-7FL showed that the addition of nivolumab nearly doubled the pCR rate (24.5% vs. 13.8%) in a BC subtype historically viewed as immune “cold” (28). This is further supported by the PD-L1 subgroup analysis from the KEYNOTE-756 trial showing similarly impressive response rates in this group (29). These two independent studies indicate preexisting immunity that is highly sensitive to the addition of ICB to chemotherapy. The findings are notable because pCR rates in HR⁺ BC have historically remained low with chemotherapy, ADCs, and endocrine therapies. They point to an underappreciated role for T cell biology in shaping prognosis and treatment response and suggest a therapeutic opportunity in a subgroup with historically poor outcomes.

Moreover, the broad variation in TIL within this cohort suggests an opportunity to further sensitize patients to ICB through synergistic combinations. Several studies have explored combinations of ICB with other targeted therapies that appear to (through various mechanisms) contribute to immune priming, including PARP inhibitors, CDK4/6 inhibitors, and ADCs. PARP inhibitors are thought to promote a proimmune microenvironment by activating the cGAS-STING pathway (85), and research has reported synergy with ICB (86). For instance, in the metastatic setting, the MEDIOLA study on HER2^– disease showed promising efficacy in combining the PARP inhibitor olaparib with the anti–PD-L1 antibody durvalumab (87). In the early-stage setting, this combination was tested in one arm of the adaptive platform I-SPY2.2 study (88), and further evaluation of this strategy is ongoing in the OLIO trial (ACTRN12623000657628).

Immunomodulatory effects of CDK4/6 inhibitors have also been reported. Although mechanisms remain unclear, upregulation of antigen presentation machinery, downregulation of regulatory T cells, influx of CD8⁺ T cells, and induction of immunological memory have all been observed following treatment with CDK4/6 inhibitors (89–91). Preclinical studies and some limited clinical data have also shown synergy between CDK4/6 inhibitors and ICB (92). However, implementation of this approach has been limited by toxicity and questions of how best to harness the immunomodulatory effects of CDK4/6 inhibitors in the clinical setting.

ADCs are a novel drug class showing efficacy in HR⁺ BC as monotherapy with various targets (93, 94). ADCs with topoisomerase 1 inhibitor (Topo1i) cytotoxic payloads (including T-DXd and Dato-Dxd) have been shown to induce immunogenic cell death (95, 96), and remarkable clinical activity for the combination of Topo1i ADCs and ICB has been observed (97). The I-SPY2.2 trial evaluated this approach in the neoadjuvant setting for patients with early-stage breast cancer, including a cohort of HR⁺/HER2^– BC, and showed promising efficacy, particularly in patients with higher immune scores (98).

Overall, it is likely that ICB responses have been modest in past HR⁺/HER2^– trials because of design limitations in patient selection. Treatment-related toxicities and the risk of overtreatment of patients who would not benefit from ICB are also key challenges, which must be noted. Multiple biomarkers of immunogenicity, such as TILs and HRD, have been used to highlight immune-active patient populations. However, the integration of these biomarkers into the clinic for the management of HR⁺/HER2^– disease has been relatively slow, and will be imperative in improving patient selection (35), as discussed above for TNBC. It is becoming evident that not all HR⁺/HER2^– tumors have equivalent TMEs, and there is a clear opportunity for ICB in the clinical management of selected subgroups of HR⁺/HER2^– disease, specifically high-risk patients with poorer outcomes under the current clinical management guidelines.

Understanding the mechanisms that govern the balance between immune activation and suppression is critical, particularly in HR⁺/HER2^– disease, where these pathways may identify patients most likely to benefit from immune-based therapies. Tumor-intrinsic factors like genomic instability, neoantigen burden, and oncogenic signaling pathways can intersect with tumor-extrinsic influences, including stromal composition, endocrine signaling, and systemic host factors like age and immune fitness. Together these factors are key biological mechanisms shaping tumor immunity and can either enable or restrain immunogenicity in HR⁺/HER2^– BC. By dissecting these pathways, we can potentially identify opportunities to enhance immunotherapeutic responsiveness in this historically “cold” subtype.

ER signaling has been implicated in shaping the immune microenvironment of HR⁺/HER2^– BC, often promoting immune evasion through modulation of antigen presentation and cytokine networks (99). Immune cells including B, T, and myeloid cells express ERs and can respond directly to estrogen signaling (100). There are two broad classes of ERs, α (ESR1) and β (ESR2), both of which can be expressed in immune cells (100).

ERα (ESR1) response pathways have been shown to suppress antitumor immunity and promote a “colder” immune microenvironment (101). ESR1 signaling can drive immunosuppressive myeloid programs, which in turn inhibit T cell activation (102, 103). In contrast, blockade of ESR1 signaling can improve immunogenicity in HR⁺ models of breast cancer and promote T cell recruitment (104) and pro-inflammatory myeloid responses (105). This provides strong evidence for the synergistic combination of hormone blockers and ICB in HR⁺/HER2^– BCs. Indeed, emerging results from preclinical models of HR⁺ disease show promising activity with the combination of ICB and hormone-targeted therapy (106).

Interestingly, the opposite seems to be true for ERβ (ESR2). While the role of ESR2 in immune cells remains incompletely defined, recent evidence in murine models suggests that ESR2 activation in CD8⁺ T cells can enhance T cell receptor signaling and produce a more potent T cell response, which enhances responses to PD-1 blockade (107). However, ESR2 antagonist monotherapy did not show efficacy in early preclinical testing (108), indicating that ESR2 signaling alone is unlikely to be sufficient to activate antitumor immunity, though it may have potential for immune priming.

Progesterone has also been implicated in immune regulation. Signals driven by progesterone can act in an immunosuppressive manner systemically, driving antiinflammatory mechanisms in T cells and other cell types (109). In animal models, PR stimulation and overexpression led to increased mammary tumors and reduced intratumoral immunity (110, 111). In line with these data, antiprogesterone treatment can improve T cell fitness (112), which again may have synergistic properties in the context of immunotherapy. Current studies are testing the efficacy of progesterone inhibition and pembrolizumab combination with promising early results (113), though more research is needed to fully understand the interplay of PR signaling and the immune microenvironment.

Endocrine treatment can also influence antigen presentation. Antiestrogen therapy has been shown to increase HLA expression in HR⁺ cancers (114). Similarly, PR signaling can also downregulate HLA expression in mammary tumors (115). The repertoire of antigens presented by HLA appear to be subtype specific, with tumor-specific antigens (including neoantigens) being more prevalent in TNBC compared with HR⁺/HER2^– BC (116). To date, common neoantigens are only prognostic in TNBC (116), suggesting that HR⁺/HER2^– BCs may have a distinct antigen presentation landscape. For example, NY-ESO-1 and WT1 antigens are more highly expressed in TNBC (117), whereas MUC1 (118) and PIK3CA (119) have been associated with increased immunogenicity in HR⁺/HER2^– disease. Better characterization of the breast cancer immunopeptidome will be highly beneficial for defining subtype-specific immune vulnerabilities and for developing more precise immunotherapeutic strategies.

In addition, environmental and host factors can affect immunogenicity in HR⁺/HER2^– disease. Age, and specifically systemic immune aging, has been correlated with improved outcomes of ICB monotherapy in TNBC (30). Given the importance of age in HR⁺ BC outcome, this factor and its influence on systemic immunity should be considered alongside efficacy data of any new targeting agent that can modulate the immune system. Early studies support this, as high CD8⁺ T cell infiltration was associated with improved survival in HR⁺ disease in premenopausal women, but not postmenopausal women (120). Importantly, endogenous estrogen levels are not the only variable at play. While systemic levels of estrogen decline with age and menopause, aromatase expression within tumors can still lead to an estrogen-rich TME in older patients (121).

Other host factors, such as exercise (122) and nutrition (123), can improve CD8⁺ T cell “fitness” and sensitize tumors to ICB. Parity and lactation duration have also recently been shown to remodel the immune landscape of the normal cancer-unaffected breast and maternal systemic immunity establishing a long-lived population of breast-resident CD8⁺ T cells. (124). In TNBC, reproductive history was associated with increased immune infiltration and favorable outcome, providing a potential mechanistic link between breastfeeding and the established reduction in long-term TNBC risk (124). Importantly, these data provide a biological mechanism for the long-observed association between longer breastfeeding duration and lower risk of TNBC and suggest that an important component of antitumor immunity in breast cancer has been underappreciated. Although the exact mechanisms underlying this immunogenicity remain to be defined, it is plausible these reproductive events also affect immunogenicity of the HR⁺ proliferative breast cancer subtypes, warranting further research. Genetic host factors such as germline variants in BRCA1 may likewise impact both tumor-intrinsic and systemic immune fitness in carriers (125–127).

Another conceptual shift of importance has come from two recent studies that repositioned the thymus from a pediatric immune organ to an active determinant of immunotherapy efficacy (128, 129), challenging the long-held belief that thymic involution with age renders the organ largely nonfunctional in adults. These findings may have implications for breast cancer, introducing another host-related variable, in this case thymic reserve, that could independently shape the TME.

The association among thymic health, parity history, and T cell receptor clonal diversity raises the possibility that breast cancer immunogenicity may be shaped upstream of the tumor-immune interface. Together, these findings support a model in which host factors are important determinants of immune surveillance and immunotherapy response in breast cancer (Figure 1B), alongside tumor-intrinsic biomarkers, such as TILs, PD-L1, and TMB. Better understanding of how all these factors may drive or restrict immunity, in addition to standardizing ways to quantify them, will be paramount to improve patient stratification in the clinic and avoid the risk of over- or undertreatment.

Checkpoint inhibitors are now part of standard-of-care treatment for TNBC and provide clear proof of principle that immunotherapy can improve outcomes in breast cancer. Ongoing advances, including a better understanding of host determinants such as parity and thymic reserve, together with the development of new immune-based strategies, including bispecific approaches, are likely to further expand this benefit.

At the same time, the longstanding characterization of HR⁺/HER2^– BC as nonimmunogenic is no longer accurate. Emerging evidence clearly demonstrates that immunogenicity exists along a broad spectrum, and there is a subset of HR⁺/HER2^–, high-grade disease that exhibits substantial immune activity. Better understanding and improved stratification of this immunologically active subgroup are essential for improved patient selection and more effective treatment. Moving forward, the key challenge is no longer determining whether immunotherapy has a role in HR⁺/HER2^– disease but in precisely identifying which patients are most likely to benefit from it and how this underappreciated immunogenic potential can be most effectively harnessed.

• SL is a National Breast Cancer Foundation of Australia Endowed Chair.
• SL is supported by the Breast Cancer Research Foundation, New York.

Copyright: © 2026, Kay et al. This is an open access article published under the terms of the Creative Commons Attribution 4.0 International License.

Reference information: J Clin Invest. 2026;136(19):e207634. https://doi.org/10.1172/JCI207634.

1. Arnold M, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. Breast. 2022;66:15–23.
   View this article via: CrossRef PubMed Google Scholar
2. Giaquinto AN, et al. Breast cancer statistics 2024. CA Cancer J Clin. 2024;74(6):477–495.
   View this article via: PubMed Google Scholar
3. Sung H, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–249.
   View this article via: PubMed Google Scholar
4. Ugai T, et al. Is early-onset cancer an emerging global epidemic? Current evidence and future implications. Nat Rev Clin Oncol. 2022;19(10):656–673.
   View this article via: CrossRef PubMed Google Scholar
5. Asleh K, et al. Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications. J Exp Clin Cancer Res. 2022;41(1):265.
   View this article via: CrossRef PubMed Google Scholar
6. Harbeck N, et al. Breast cancer. Nat Rev Dis Primers. 2019;5(1):66.
   View this article via: CrossRef PubMed Google Scholar
7. Schmid P, et al. Pembrolizumab for early triple-negative breast cancer. N Engl J Med. 2020;382(9):810–821.
   View this article via: CrossRef PubMed Google Scholar
8. Waks AG, Winer EP. Breast cancer treatment: a review. JAMA. 2019;321(3):288–300.
   View this article via: CrossRef PubMed Google Scholar
9. Harris MA, et al. Towards targeting the breast cancer immune microenvironment. Nat Rev Cancer. 2024;24(8):554–577.
   View this article via: CrossRef PubMed Google Scholar
10. Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov. 2022;12(1):31–46.
    View this article via: CrossRef PubMed Google Scholar
11. Smyth MJ. Multiple approaches to immunotherapy - the new pillar of cancer treatment. Immunol Cell Biol. 2017;95(4):323–324.
    View this article via: CrossRef PubMed Google Scholar
12. Cortes J, et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer (KEYNOTE-355): a randomised, placebo-controlled, double-blind, phase 3 clinical trial. Lancet. 2020;396(10265):1817–1828.
    View this article via: CrossRef PubMed Google Scholar
13. Emens LA, et al. First-line atezolizumab plus nab-paclitaxel for unresectable, locally advanced, or metastatic triple-negative breast cancer: IMpassion130 final overall survival analysis. Ann Oncol. 2021;32(8):983–993.
    View this article via: CrossRef PubMed Google Scholar
14. Mittendorf EA, et al. Neoadjuvant atezolizumab in combination with sequential nab-paclitaxel and anthracycline-based chemotherapy versus placebo and chemotherapy in patients with early-stage triple-negative breast cancer (IMpassion031): a randomised, double-blind, phase 3 trial. Lancet. 2020;396(10257):1090–1100.
    View this article via: CrossRef PubMed Google Scholar
15. Sistrunk WE, Maccarty WC. Life expectancy following radical amputation for carcinoma of the breast: a clinical and pathologic study of 218 cases. Ann Surg. 1922;75(1):61–69.
    View this article via: PubMed Google Scholar
16. Rayson VC, et al. The anti-cancer immune response in breast cancer: current and emerging biomarkers and treatments. Trends Cancer. 2024;10(6):490–506.
    View this article via: CrossRef PubMed Google Scholar
17. Aaltomaa S, et al. Lymphocyte infiltrates as a prognostic variable in female breast cancer. Eur J Cancer. 1992;28A(4–5):859–864.
    View this article via: CrossRef PubMed Google Scholar
18. Denkert C, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol. 2010;28(1):105–113.
    View this article via: CrossRef PubMed Google Scholar
19. Denkert C, et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: a pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 2018;19(1):40–50.
    View this article via: CrossRef PubMed Google Scholar
20. Loi S, et al. Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: results from the FinHER trial. Ann Oncol. 2014;25(8):1544–1550.
    View this article via: CrossRef PubMed Google Scholar
21. Gao ZH, et al. Predictive and prognostic role of tumour-infiltrating lymphocytes in breast cancer patients with different molecular subtypes: a meta-analysis. BMC Cancer. 2020;20(1):1150.
    View this article via: CrossRef PubMed Google Scholar
22. Leon-Ferre RA, et al. Tumor-infiltrating lymphocytes in triple-negative breast cancer. JAMA. 2024;331(13):1135–1144.
    View this article via: CrossRef PubMed Google Scholar
23. Loi S, et al. Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98. J Clin Oncol. 2013;31(7):860–867.
    View this article via: CrossRef PubMed Google Scholar
24. Loi S, et al. Tumor-infiltrating lymphocytes and prognosis: a pooled individual patient analysis of early-stage triple-negative breast cancers. J Clin Oncol. 2019;37(7):559–569.
    View this article via: CrossRef PubMed Google Scholar
25. Yang T, et al. Immunotherapy for HER-2 positive breast cancer. Front Oncol. 2023;13:1097983.
    View this article via: CrossRef PubMed Google Scholar
26. Voorwerk L, et al. Immune landscape of breast tumors with low and intermediate estrogen receptor expression. NPJ Breast Cancer. 2023;9(1):39.
    View this article via: CrossRef PubMed Google Scholar
27. Fukui R, et al. An increase in tumor-infiltrating lymphocytes after treatment is significantly associated with a poor response to neoadjuvant endocrine therapy for estrogen receptor-positive/HER2-negative breast cancers. Breast Cancer. 2023;30(5):703–713.
    View this article via: CrossRef PubMed Google Scholar
28. Loi S, et al. Neoadjuvant nivolumab and chemotherapy in early estrogen receptor-positive breast cancer: a randomized phase 3 trial. Nat Med. 2025;31(2):433–441.
    View this article via: CrossRef PubMed Google Scholar
29. Cardoso F, et al. Pembrolizumab and chemotherapy in high-risk, early-stage, ER⁺/HER2^– breast cancer: a randomized phase 3 trial. Nat Med. 2025;31(2):442–448.
    View this article via: CrossRef PubMed Google Scholar
30. Adams S, et al. Pembrolizumab monotherapy for previously untreated, PD-L1-positive, metastatic triple-negative breast cancer: cohort B of the phase II KEYNOTE-086 study. Ann Oncol. 2019;30(3):405–411.
    View this article via: CrossRef PubMed Google Scholar
31. Adams S, et al. Pembrolizumab monotherapy for previously treated metastatic triple-negative breast cancer: cohort A of the phase II KEYNOTE-086 study. Ann Oncol. 2019;30(3):397–404.
    View this article via: CrossRef PubMed Google Scholar
32. Winer EP, et al. Pembrolizumab versus investigator-choice chemotherapy for metastatic triple-negative breast cancer (KEYNOTE-119): a randomised, open-label, phase 3 trial. Lancet Oncol. 2021;22(4):499–511.
    View this article via: CrossRef PubMed Google Scholar
33. Schmid P, et al. Atezolizumab plus nab-paclitaxel as first-line treatment for unresectable, locally advanced or metastatic triple-negative breast cancer (IMpassion130): updated efficacy results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2020;21(1):44–59.
    View this article via: CrossRef PubMed Google Scholar
34. Schmid P, et al. Pembrolizumab for early triple-negative breast cancer. N Engl J Med. 2020;382(9):810–821.
    View this article via: CrossRef PubMed Google Scholar
35. Salgado R, et al. How current assay approval policies are leading to unintended imprecision medicine. Lancet Oncol. 2020;21(11):1399–1401.
    View this article via: CrossRef PubMed Google Scholar
36. Xu T, et al. The predictive and prognostic role of stromal tumor-infiltrating lymphocytes in HER2-positive breast cancer with trastuzumab-based treatment: a meta-analysis and systematic review. J Cancer. 2017;8(18):3838–3848.
    View this article via: CrossRef PubMed Google Scholar
37. Salgado R, et al. Tumor-infiltrating lymphocytes and associations with pathological complete response and event-free survival in HER2-positive early-stage breast cancer treated with lapatinib and trastuzumab: a secondary analysis of the NeoALTTO trial. JAMA Oncol. 2015;1(4):448–454.
    View this article via: CrossRef PubMed Google Scholar
38. Mercogliano MF, et al. Emerging targeted therapies for HER2-positive breast cancer. Cancers (Basel). 2023;15(7):1987.
    View this article via: CrossRef PubMed Google Scholar
39. Bianchini G, Gianni L. The immune system and response to HER2-targeted treatment in breast cancer. Lancet Oncol. 2014;15(2):e58–e68.
    View this article via: CrossRef PubMed Google Scholar
40. Loi S, et al. Pembrolizumab plus trastuzumab in trastuzumab-resistant, advanced, HER2-positive breast cancer (PANACEA): a single-arm, multicentre, phase 1b-2 trial. Lancet Oncol. 2013;20(3):371–382.
    View this article via: CrossRef PubMed Google Scholar
41. Loi S, et al. 301MO Primary efficacy results of tremelimumab and durvalumab in combination with trastuzumab in trastuzumab resistant advanced HER2-positive breast cancer: BCT1703 DIAmOND. ESMO Open. 2025;10(suppl 4):104873.
    View this article via: CrossRef Google Scholar
42. Emens LA, et al. Trastuzumab emtansine plus atezolizumab versus trastuzumab emtansine plus placebo in previously treated, HER2-positive advanced breast cancer (KATE2): a phase 2, multicentre, randomised, double-blind trial. Lancet Oncol. 2020;21(10):1283–1295.
    View this article via: CrossRef PubMed Google Scholar
43. Huober J, et al. Atezolizumab with neoadjuvant anti-human epidermal growth factor receptor 2 therapy and chemotherapy in human epidermal growth factor receptor 2-positive early breast cancer: primary results of the randomized phase III IMpassion050 trial. J Clin Oncol. 2022;40(25):2946–2956.
    View this article via: CrossRef PubMed Google Scholar
44. Holgado E, et al. Is there a role for immunotherapy in HER2-positive breast cancer? NPJ Breast Cancer. 2018;41:21.
    View this article via: CrossRef PubMed Google Scholar
45. Veerla S, et al. Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer. NPJ Breast Cancer. 2023;9(1):83.
    View this article via: CrossRef PubMed Google Scholar
46. Miziak P, et al. Estrogen receptor signaling in breast cancer. Cancers (Basel). 2023;15(19):4689.
    View this article via: CrossRef PubMed Google Scholar
47. Carleton N, et al. Personalising therapy for early-stage oestrogen receptor-positive breast cancer in older women. Lancet Healthy Longev. 2022;3(1):e54–e66.
    View this article via: CrossRef PubMed Google Scholar
48. Perou CM, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–752.
    View this article via: CrossRef PubMed Google Scholar
49. Parker JS, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160–1167.
    View this article via: CrossRef PubMed Google Scholar
50. Prat A, et al. Clinical implications of the intrinsic molecular subtypes of breast cancer. Breast. 2015;24 Suppl 2:S26–S35.
    View this article via: CrossRef PubMed Google Scholar
51. Hammond ME, et al. American Society of Clinical Oncology/College Of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol. 2010;28(16):2784–2795.
    View this article via: CrossRef PubMed Google Scholar
52. Kim HJ, et al. The impact of young age at diagnosis (age < 40 years) on prognosis varies by breast cancer subtype: A U.S. SEER database analysis. Breast. 2022;61:77–83.
    View this article via: CrossRef PubMed Google Scholar
53. Brown LC, et al. Evaluation of PAM50 intrinsic subtypes and risk of recurrence (ROR) scores in premenopausal women with early-stage HR⁺ breast cancer: A secondary analysis of the SOFT trial. J Clin Oncol. 2023;41(suppl 16):504.
    View this article via: CrossRef Google Scholar
54. Sparano JA, et al. Clinical and genomic risk to guide the use of adjuvant therapy for breast cancer. N Engl J Med. 2019;380(25):2395–2405.
    View this article via: CrossRef PubMed Google Scholar
55. Kalinsky K, et al. 21-gene assay to inform chemotherapy benefit in node-positive breast cancer. N Engl J Med. 2021;385(25):2336–2347.
    View this article via: CrossRef PubMed Google Scholar
56. Nicolini A, et al. The breast cancer tumor microenvironment and precision medicine: immunogenicity and conditions favoring response to immunotherapy. J Natl Cancer Cent. 2024;4(1):14–24.
    View this article via: PubMed Google Scholar
57. Rozenblit M, et al. PD-L1 protein expression in relation to recurrence score values in early-stage ER + breast cancer. Breast Cancer Res Treat. 2022;196(1):221–227.
    View this article via: CrossRef PubMed Google Scholar
58. Ohara M, et al. Association between tumor-infiltrating lymphocytes and oncotype DX estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 single gene scores in hormone receptor-positive/HER2-negative breast cancer. Front Oncol. 2026;16:1677929.
    View this article via: CrossRef PubMed Google Scholar
59. Criscitiello C, et al. Tumor-infiltrating lymphocytes (TILs) in ER⁺/HER2^– breast cancer. Breast Cancer Res Treat. 2020;183(2):347–354.
    View this article via: CrossRef PubMed Google Scholar
60. Hanamura T, et al. Expression of hormone receptors is associated with specific immunological profiles of the breast cancer microenvironment. Breast Cancer Res. 2023;25(1):13.
    View this article via: CrossRef PubMed Google Scholar
61. Walker AE, et al. Prognostic significance of CD8⁺ T cell Spatial Biomarkers in ER⁺ and ER^– breast cancer: A retrospective cohort study. PLoS Med. 2025;22(10):e1004647.
    View this article via: CrossRef PubMed Google Scholar
62. Jain D, et al. Heterogeneity and immune microenvironment of early invasive estrogen receptor-positive breast cancer reveal an immune-rich subset. NPJ Breast Cancer. 2026;12(1):56.
    View this article via: CrossRef PubMed Google Scholar
63. Ballot E, et al. Molecular intrinsic subtypes, genomic, and immune landscapes of BRCA-proficient but HRD-high ER-positive/HER2-negative early breast cancers. Breast Cancer Res. 2022;24(1):80.
    View this article via: CrossRef PubMed Google Scholar
64. Knijnenburg TA, et al. Genomic and molecular landscape of DNA damage repair deficiency across The Cancer Genome Atlas. Cell Rep. 2018;23(1):239–254.
    View this article via: CrossRef PubMed Google Scholar
65. Nguyen L J WMM, et al. Pan-cancer landscape of homologous recombination deficiency. Nat Commun. 2020;11(1):5584.
    View this article via: CrossRef PubMed Google Scholar
66. Heeke AL, et al. Prevalence of homologous recombination-related gene mutations across multiple cancer types. JCO Precis Oncol. 2018;2018:PO.17.00286.
    View this article via: PubMed Google Scholar
67. McCabe N, et al. Deficiency in the repair of DNA damage by homologous recombination and sensitivity to poly(ADP-ribose) polymerase inhibition. Cancer Res. 2006;66(16):8109–8115.
    View this article via: CrossRef PubMed Google Scholar
68. Budczies J, et al. Homologous recombination deficiency is inversely correlated with microsatellite instability and identifies immunologically cold tumors in most cancer types. J Pathol Clin Res. 2022;8(4):371–382.
    View this article via: CrossRef PubMed Google Scholar
69. Wen WX, Leong CO. Association of BRCA1- and BRCA2-deficiency with mutation burden, expression of PD-L1/PD-1, immune infiltrates, and T cell-inflamed signature in breast cancer. PLoS One. 2019;14(4):e0215381.
    View this article via: CrossRef PubMed Google Scholar
70. Ko HC, et al. Effect of homologous recombination deficient (HRD) breast cancers on a distinct immune marker phenotype by comprehensive genomic and immune profiling (CGIP). J Clin Oncol. 2023;41(16_suppl):1029.
    View this article via: CrossRef Google Scholar
71. Vougiouklakis T, et al. Genomic characterization of tumor mutational burden-high breast carcinomas. NPJ Precis Oncol. 2025;9(1):277.
    View this article via: CrossRef PubMed Google Scholar
72. Jones MA, et al. The landscape of BRCA1 and BRCA2 large rearrangements in an international cohort of over 20 000 ovarian tumors identified using next-generation sequencing. Genes Chromosomes Cancer. 2023;62(10):589–596.
    View this article via: CrossRef PubMed Google Scholar
73. Zou XL, et al. Prognostic value of neoantigen load in immune checkpoint inhibitor therapy for cancer. Front Immunol. 2021;12:689076.
    View this article via: CrossRef PubMed Google Scholar
74. Sinn BV, et al. Human leucocyte antigen class I in hormone receptor-positive, HER2-negative breast cancer: association with response and survival after neoadjuvant chemotherapy. Breast Cancer Res. 2019;21(1):142.
    View this article via: CrossRef PubMed Google Scholar
75. Torigoe T, et al. Establishment of a monoclonal anti-pan HLA class I antibody suitable for immunostaining of formalin-fixed tissue: unusually high frequency of down-regulation in breast cancer tissues. Pathol Int. 2012;62(5):303–308.
    View this article via: CrossRef PubMed Google Scholar
76. Das B, et al. The Trojan Horse within: mechanisms of immune evasion in breast cancer. Cancer Heterog Plast. 2025;3(1):0001.
    View this article via: CrossRef PubMed Google Scholar
77. Weeden CE, et al. Early immune pressure initiated by tissue-resident memory T cells sculpts tumor evolution in non-small cell lung cancer. Cancer Cell. 2023;41(5):837–852.
    View this article via: CrossRef PubMed Google Scholar
78. Ali HR, et al. Association between CD8⁺ T-cell infiltration and breast cancer survival in 12,439 patients. Ann Oncol. 2014;25(8):1536–1543.
    View this article via: CrossRef PubMed Google Scholar
79. Andresen NK, et al. Ipilimumab and nivolumab combined with anthracycline-based chemotherapy in metastatic hormone receptor-positive breast cancer: a randomized phase 2b trial. J Immunother Cancer. 2024;12(1):e007990.
    View this article via: CrossRef PubMed Google Scholar
80. Barroso-Sousa R, et al. Nivolumab plus low-dose ipilimumab in hypermutated HER2-negative metastatic breast cancer: a phase II trial (NIMBUS). Nat Commun. 2025;16(1):4430.
    View this article via: CrossRef PubMed Google Scholar
81. Aftimos P, et al. Genomic and transcriptomic analyses of breast cancer primaries and matched metastases in AURORA, the Breast International Group (BIG) Molecular Screening Initiative. Cancer Discov. 2021;11(11):2796–2811.
    View this article via: CrossRef PubMed Google Scholar
82. Garcia-Recio S, et al. Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis. Nat Cancer. 2023;4(1):128–147.
    View this article via: PubMed Google Scholar
83. Gorshein E, et al. Durable response to PD1 inhibitor pembrolizumab in a metastatic, metaplastic breast cancer. Case Rep Oncol. 2021;14(2):931–937.
    View this article via: CrossRef PubMed Google Scholar
84. Dieci MV, et al. Neoadjuvant chemotherapy and immunotherapy in luminal B-like breast cancer: results of the phase II GIADA trial. Clin Cancer Res. 2022;28(2):308–317.
    View this article via: CrossRef PubMed Google Scholar
85. Shen J, et al. PARPi triggers the STING-dependent immune response and enhances the therapeutic efficacy of immune checkpoint blockade independent of BRCAness. Cancer Res. 2019;79(2):311–319.
    View this article via: CrossRef PubMed Google Scholar
86. Wu Z, et al. The synergistic effect of PARP inhibitors and immune checkpoint inhibitors. Clin Med Insights Oncol. 2021;15:1179554921996288.
    View this article via: CrossRef PubMed Google Scholar
87. Domchek SM, et al. Olaparib and durvalumab in patients with germline BRCA-mutated metastatic breast cancer (MEDIOLA): an open-label, multicentre, phase 1/2, basket study. Lancet Oncol. 2020;21(9):1155–1164.
    View this article via: CrossRef PubMed Google Scholar
88. Pusztai L, et al. Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: results from the adaptively randomized I-SPY2 trial. Cancer Cell. 2021;39(7):989–998.
    View this article via: CrossRef PubMed Google Scholar
89. Deng J, et al. CDK4/6 inhibition augments antitumor immunity by enhancing T-cell activation. Cancer Discov. 2018;8(2):216–233.
    View this article via: CrossRef PubMed Google Scholar
90. Goel S, et al. CDK4/6 inhibition triggers anti-tumour immunity. Nature. 2017;548(7668):471–475.
    View this article via: CrossRef PubMed Google Scholar
91. Lelliott EJ, et al. CDK4/6 inhibition promotes antitumor immunity through the induction of T-cell memory. Cancer Discov. 2021;11(10):2582–2601.
    View this article via: CrossRef PubMed Google Scholar
92. Mayer EL, et al. PACE: a randomized phase II study of fulvestrant, palbociclib, and avelumab after progression on cyclin-dependent kinase 4/6 inhibitor and aromatase inhibitor for hormone receptor-positive/human epidermal growth factor receptor-negative metastatic breast cancer. J Clin Oncol. 2024;42(17):2050–2060.
    View this article via: CrossRef PubMed Google Scholar
93. Pistilli B, et al. Patritumab deruxtecan in HR⁺HER2^- advanced breast cancer: a phase 2 trial. Nat Med. 2025;31(10):3492–3503.
    View this article via: CrossRef PubMed Google Scholar
94. Curigliano G, et al. Trastuzumab deruxtecan in hormone receptor-positive, HER2-low/-ultralow metastatic breast cancer (DESTINY-Breast06): outcome analyses by time to progression on prior first-line endocrine therapy with CDK4/6 inhibitor and baseline burden of disease. Ann Oncol. 2026;37(6):849–860.
    View this article via: CrossRef PubMed Google Scholar
95. Schulte N, Ikuta M, Mertes A, Kanchev I, Deguchi T, Polier G. Abstract 2160: Trastuzumab deruxtecan induces immunogenic cell death, immune cell activation and -migration in viable human breast cancer slices. Cancer Res. 2025;85(8_suppl_1):2160.
96. Forveille S, et al. Datopotamab deruxtecan induces hallmarks of immunogenic cell death. Cell Stress. 2025;9:194–200.
    View this article via: CrossRef PubMed Google Scholar
97. Schmid P, et al. BEGONIA: phase 1b/2 study of durvalumab (D) combinations in locally advanced/metastatic triple-negative breast cancer (TNBC)—Initial results from arm 1, d+paclitaxel (P), and arm 6, d+trastuzumab deruxtecan (T-DXd). J Clin Oncol. 2021;39(15_suppl):1023.
    View this article via: CrossRef Google Scholar
98. Shatsky RA, et al. Datopotamab-deruxtecan plus durvalumab in early-stage breast cancer: the sequential multiple assignment randomized I-SPY2.2 phase 2 trial. Nat Med. 2024;30(12):3737–3747.
    View this article via: CrossRef PubMed Google Scholar
99. Chakraborty B, et al. Estrogen receptor signaling in the immune system. Endocr Rev. 2023;44(1):117–141.
    View this article via: CrossRef PubMed Google Scholar
100. Phiel KL, et al. Differential estrogen receptor gene expression in human peripheral blood mononuclear cell populations. Immunol Lett. 2005;97(1):107–113.
     View this article via: CrossRef PubMed Google Scholar
101. Liu B, et al. Overexpression of TFF3 is associated with immune infiltration, molecular subtypes, and clinical progression in breast cancer. Curr Med Sci. 2026;46(2):441–458.
     View this article via: CrossRef PubMed Google Scholar
102. Svoronos N, et al. Tumor cell-independent estrogen signaling drives disease progression through mobilization of myeloid-derived suppressor cells. Cancer Discov. 2017;7(1):72–85.
     View this article via: CrossRef PubMed Google Scholar
103. Hu C, et al. Myeloid-derived suppressor cells are regulated by estradiol and are a predictive marker for IVF outcome. Front Endocrinol (Lausanne). 2019;10:521.
     View this article via: CrossRef PubMed Google Scholar
104. Hazlett J, et al. Oestrogen deprivation induces chemokine production and immune cell recruitment in in vitro and in vivo models of oestrogen receptor-positive breast cancer. Breast Cancer Res. 2021;23(1):95.
     View this article via: CrossRef PubMed Google Scholar
105. Lambert KC, et al. Estrogen receptor-alpha deficiency promotes increased TNF-alpha secretion and bacterial killing by murine macrophages in response to microbial stimuli in vitro. J Leukoc Biol. 2004;75(6):1166–1172.
     View this article via: CrossRef PubMed Google Scholar
106. Rojas-Jimenez E, et al. Evaluation of targeted and immune combination therapies in a rat model of hormone receptor-positive breast cancer. Proc Natl Acad Sci U S A. 2026;123(6):e2501052123.
     View this article via: CrossRef PubMed Google Scholar
107. Yuan B, et al. Estrogen receptor beta signaling in CD8⁺ T cells boosts T cell receptor activation and antitumor immunity through a phosphotyrosine switch. J Immunother Cancer. 2021;9(1):e001932.
     View this article via: CrossRef PubMed Google Scholar
108. Marcho LM, et al. Potent estrogen receptor β agonists with inhibitory activity in vitro, fail to suppress xenografts of endocrine-resistant cyclin-dependent kinase 4/6 inhibitor-resistant breast cancer cells. Front Oncol. 2025;15:1441896.
     View this article via: CrossRef PubMed Google Scholar
109. Zwahlen M, Stute P. Impact of progesterone on the immune system in women: a systematic literature review. Arch Gynecol Obstet. 2024;309(1):37–46.
     View this article via: CrossRef PubMed Google Scholar
110. Werner LR, et al. Progesterone promotes immunomodulation and tumor development in the murine mammary gland. J Immunother Cancer. 2021;9(5):e001710.
     View this article via: CrossRef PubMed Google Scholar
111. Xiao Y, et al. Progesterone receptor impairs immune respond and down-regulates sensitivity to anti-LAG3 in breast cancer. Transl Res. 2024;271:68–78.
     View this article via: CrossRef PubMed Google Scholar
112. Li Y, Li L, Li S, He C. Mifepristone modulates the polarization of Th1/Th2 by inducing the mature of monocyte-derived dendritic Cells. Adv Therap. 2024;7(2):2300245.
     View this article via: CrossRef Google Scholar
113. Chen N, et al. Phase II study of pembrolizumab plus mifepristone in patients with advanced HER2-negative breast cancer. J Clin Oncol. 2023;41(16_suppl):1095.
     View this article via: CrossRef Google Scholar
114. Song IH, et al. The association of estrogen receptor activity, interferon signaling, and MHC Class I expression in breast cancer. Cancer Res Treat. 2022;54(4):1111–1120.
     View this article via: CrossRef PubMed Google Scholar
115. Tinoco JC, et al. Progesterone receptor-dependent downregulation of MHC class I promotes tumor immune evasion and growth in breast cancer. J Immunother Cancer. 2025;13(3):e010179.
     View this article via: CrossRef PubMed Google Scholar
116. Kina E, et al. Breast cancer immunopeptidomes contain numerous shared tumor antigens. J Clin Invest. 2023;134(1):e166740.
     View this article via: JCI CrossRef PubMed Google Scholar
117. Curigliano G, et al. Expression of tumor-associated antigens in breast cancer subtypes. Breast. 2020;49:202–209.
     View this article via: CrossRef PubMed Google Scholar
118. Hosseinzadeh A, et al. MUC1 is a potential target to overcome trastuzumab resistance in breast cancer therapy. Cancer Cell Int. 2022;22(1):110.
     View this article via: CrossRef PubMed Google Scholar
119. Sobral-Leite M, et al. Cancer-immune interactions in ER-positive breast cancers: PI3K pathway alterations and tumor-infiltrating lymphocytes. Breast Cancer Res. 2019;21(1):90.
     View this article via: CrossRef PubMed Google Scholar
120. Egelston CA, et al. Tumor-infiltrating exhausted CD8⁺ T cells dictate reduced survival in premenopausal estrogen receptor-positive breast cancer. JCI Insight. 2022;7(3):e153963.
     View this article via: JCI Insight CrossRef PubMed Google Scholar
121. Chumsri S, et al. Aromatase, aromatase inhibitors, and breast cancer. J Steroid Biochem Mol Biol. 2011;125(1–2):13–22.
     View this article via: CrossRef PubMed Google Scholar
122. Gomes-Santos IL, et al. Exercise training improves tumor control by increasing CD8(+) T-cell Infiltration via CXCR3 Signaling and Sensitizes Breast Cancer to Immune Checkpoint Blockade. Cancer Immunol Res. 2021;9(7):765–778.
     View this article via: CrossRef PubMed Google Scholar
123. Oswald BM, et al. Dietary restriction reprograms CD8⁺ T cell fate to enhance anti-tumour immunity and immunotherapy responses. Nat Metab. 2025;7(12):2489–2509.
     View this article via: CrossRef PubMed Google Scholar
124. Virassamy B, et al. Parity and lactation induce T-cell-mediated breast cancer protection. Nature. 2025;649(8096):449–459.
     View this article via: CrossRef PubMed Google Scholar
125. Inthanachai T, et al. Transient mRNA-based CD117 CAR T cells effectively target acute myeloid leukemia in vitro for potential use as a preconditioning strategy. Immunooncol Technol. 2026;29:101584.
     View this article via: CrossRef PubMed Google Scholar
126. Samstein RM, et al. Mutations in BRCA1 and BRCA2 differentially affect the tumor microenvironment and response to checkpoint blockade immunotherapy. Nat Cancer. 2021;1(12):1188–1203.
     View this article via: CrossRef PubMed Google Scholar
127. Wu B, et al. BRCA1 deficiency in mature CD8⁺ T lymphocytes impairs antitumor immunity. J Immunother Cancer. 2023;11(2):e005852.
     View this article via: CrossRef PubMed Google Scholar
128. Bernatz S, et al. Thymic health consequences in adults. Nature. 2026;652(8111):986–994.
     View this article via: CrossRef PubMed Google Scholar
129. Bernatz S, et al. Thymic health and immunotherapy outcomes in patients with cancer. Nature. 2026;652(8111):995–1003.
     View this article via: CrossRef PubMed Google Scholar
130. Loi S, et al. Association between biomarkers and clinical outcomes of pembrolizumab monotherapy in patients with metastatic triple-negative breast cancer: KEYNOTE-086 exploratory analysis. JCO Precis Oncol. 2023;7:e2200317.
     View this article via: CrossRef PubMed Google Scholar
131. Nanda R, et al. Pembrolizumab in patients with advanced triple-negative breast cancer: phase Ib KEYNOTE-012 study. J Clin Oncol. 2016;34(21):2460–2467.
     View this article via: CrossRef PubMed Google Scholar
132. Cortes J, et al. Pembrolizumab plus chemotherapy in advanced triple-negative breast cancer. N Engl J Med. 2022;387(3):217–226.
     View this article via: CrossRef PubMed Google Scholar
133. Voorwerk L, et al. Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial. Nat Med. 2019;25(6):920–928.
     View this article via: CrossRef PubMed Google Scholar
134. Schmid P, et al. Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer. N Engl J Med. 2018;379(22):2108–2121.
     View this article via: CrossRef PubMed Google Scholar
135. Bachelot T, et al. Durvalumab compared to maintenance chemotherapy in metastatic breast cancer: the randomized phase II SAFIR02-BREAST IMMUNO trial. Nat Med. 2021;27(2):250–255.
     View this article via: CrossRef PubMed Google Scholar
136. Ignatiadis M, et al. Adjuvant atezolizumab for early triple-negative breast cancer: the ALEXANDRA/IMpassion030 randomized clinical trial. JAMA. 2025;333(13):1150–1160.
     View this article via: CrossRef PubMed Google Scholar
137. Sharma P, et al. Clinical and biomarker findings of neoadjuvant pembrolizumab and carboplatin plus docetaxel in triple-negative breast cancer: NeoPACT phase 2 clinical trial. JAMA Oncol. 2024;10(2):227–235.
     View this article via: CrossRef PubMed Google Scholar
138. Loibl S, et al. Neoadjuvant durvalumab improves survival in early triple-negative breast cancer independent of pathological complete response. Ann Oncol. 2022;33(11):1149–1158.
     View this article via: CrossRef PubMed Google Scholar
139. Loibl S, et al. A randomised phase II study investigating durvalumab in addition to an anthracycline taxane-based neoadjuvant therapy in early triple-negative breast cancer: clinical results and biomarker analysis of GeparNuevo study. Ann Oncol. 2019;30(8):1279–1288.
     View this article via: CrossRef PubMed Google Scholar
140. Conte PF, et al. A-BRAVE trial: a phase III randomized trial with anti-PD-L1 avelumab in high-risk triple-negative early breast cancer patients. Ann Oncol. 2025;36(12):1492–1502.
     View this article via: CrossRef PubMed Google Scholar
141. Gianni L, et al. Pathologic complete response (pCR) to neoadjuvant treatment with or without atezolizumab in triple-negative, early high-risk and locally advanced breast cancer: NeoTRIP Michelangelo randomized study. Ann Oncol. 2022;33(5):534–543.
     View this article via: CrossRef PubMed Google Scholar
142. Nanda R, et al. Effect of pembrolizumab plus neoadjuvant chemotherapy on pathologic complete response in women with early-stage breast cancer: an analysis of the ongoing phase 2 adaptively randomized I-SPY2 trial. JAMA Oncol. 2020;6(5):676–684.
     View this article via: CrossRef PubMed Google Scholar
143. Zdenkowski N, et al. Timing of nivolumab with neoadjuvant carboplatin and paclitaxel for early triple-negative breast cancer (BCT1902/IBCSG 61-20; Neo-N): a non-comparative, open-label, randomised, phase 2 trial. Lancet Oncol. 2025;26(3):367–377.
     View this article via: CrossRef PubMed Google Scholar
144. Rugo HS, et al. Safety and antitumor activity of pembrolizumab in patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer. Clin Cancer Res. 2018;24(12):2804–2811.
     View this article via: CrossRef PubMed Google Scholar
145. Dirix LY, et al. Avelumab, an anti-PD-L1 antibody, in patients with locally advanced or metastatic breast cancer: a phase 1b JAVELIN Solid Tumor study. Breast Cancer Res Treat. 2018;167(3):671–686.
     View this article via: CrossRef PubMed Google Scholar
146. Santa-Maria CA, et al. A pilot study of durvalumab and tremelimumab and immunogenomic dynamics in metastatic breast cancer. Oncotarget. 2018;9(27):18985–18996.
     View this article via: CrossRef PubMed Google Scholar
147. Ho AY, et al. PEARL: a phase Ib/II biomarker study of adding radiation therapy to pembrolizumab before neoadjuvant chemotherapy in human epidermal growth factor receptor 2-negative breast cancer. J Clin Oncol. 2024;42(36):4282–4293.
     View this article via: CrossRef PubMed Google Scholar
148. Devaux A, et al. Evaluation of short-course durvalumab combined with dose-dense EC in the neoadjuvant setting for locally advanced luminal B/HER2(-) or triple-negative breast cancer. Breast Cancer Res. 2025;27(1):212.
     View this article via: CrossRef PubMed Google Scholar
149. Jerusalem G, et al. Neoadjuvant nivolumab + palbociclib + anastrozole for oestrogen receptor-positive/human epidermal growth factor receptor 2-negative primary breast cancer: results from CheckMate 7A8. Breast. 2023;72:103580.
     View this article via: CrossRef PubMed Google Scholar