Necroptosis in both tumour and stromal compartments determines responsiveness to immunogenic cell death-based immunotherapy

Domain: chemistry
Published: 2026-03-06
Editorial outcome: major_revision

Abstract
Immunotherapy has transformed cancer treatment, including early triple-negative breast cancer (TNBC), yet most patients with advanced TNBC fail to respond to immune checkpoint blockade (ICB) plus chemotherapy. Durable control likely requires not only tumour cell killing but also immunogenic cell death (ICD) that activates antitumour immunity. Using a Brca1⁻/⁻p53⁻/⁻ organoid-derived TNBC model that recapitulates the immune landscapes of basal-like tumours, we show that RIPK1-driven ICD synergises with anti-PD-1 therapy to induce durable tumour control and immune memory in immune-infiltrated tumours. Mechanistically, both tumour-intrinsic and stromal necroptosis are required. Deletion of Ripk1 or Mlkl in tumour cells, or Mlkl in the stromal compartment, markedly impairs therapeutic efficacy. Moreover, immunologically “cold” tumours can be rendered responsive to ICD-based therapy by STING agonists. These findings demonstrate that the benefit of IAP antagonism with checkpoint blockade critically depends on coordinated necroptosis in both tumour and stromal cells, underscoring the need to integrate tumour microenvironmental context when designing ICD-targeted immunotherapies.

Introduction
Breast cancer remains a major health threat worldwide, accounting for 30% of all female cancer cases and 15% of female cancer-related deaths1. Breast cancer exhibits a high degree of inter-patient heterogeneity not only between the different subtypes of breast cancer but also within them, necessitating a more personalised approach to therapy. Additionally, the various breast cancer subtypes differ significantly in their tumour microenvironments, with triple-negative breast cancers (TNBC) and HER2-positive types being generally considered more immune-active ("hot tumours"), while ER+ luminal carcinomas are typically immune-deficient ("cold tumours").

TNBCs are primarily defined by the lack of expression of the estrogen receptor (ER), progesterone receptor (PR), and HER2 (ERBB2), which are typically present in other forms of the disease. Although there have been recent advancements in the targeted treatment of TNBC, including the use of PARP inhibitors in those with BRCA1/2 mutation or immunotherapy with anti PD1 or PD-L1 agents, many patients still do not respond to these treatments or develop resistance. Although immunotherapy has revolutionised anti-cancer therapies, treatment with immune checkpoint inhibitors (ICI) has limited efficiency in the majority of patients. Accordingly, single-agent ICI activity has been observed in <10% of patients with metastatic disease2-4. Moreover, it is difficult to predict who might respond as current biomarkers of ICI have several limitations5. Further, tumours may evolve resistance to immunotherapies, for example due to a lack of immunogenic tumour antigens, changes in cancer cell signaling pathways, the presence of inhibitory checkpoint molecules, and a 'cold' tumour microenvironment (TME) characterised by poor recruitment of tumour-infiltrating lymphocytes (TIL) and antigen presentation, along with immune-suppressive factors like myeloid-derived suppressor cells (MDSCs), M2-like macrophages, and the presence of regulatory T cells (Tregs)6-8.

Current immunotherapy approaches in breast cancer aim to address T-cell priming issues by combining chemotherapy with ICIs. Accordingly, Pembrolizumab, in combination with chemotherapy, has been incorporated into the standard-of-care treatment for patients with early TNBC, and both Pembrolizumab and Atezolizumab in patients with PD-L1-positive early or advanced TNBC9,10. The death of cancer cells plays a crucial role in the cancer immunity cycle11,12, as cancer cell death is required for efficient activation of the immune system. While induction of cancer cell death is critical for the uptake of tumour-associated antigens by antigen presenting cells, the death of cancer cells alone is not sufficient for the crosspriming of CD8+ T cells. In addition, efferocytosing antigen presenting cells, such as immature dendritic cells (DCs), must also be exposed to adjuvants that trigger their maturation13. Importantly, not every cell death modality is capable of providing the necessary immunological signals that can skew the maturation process of peripheral DCs towards an immunogenic fate. While apoptosis is the most prominent cell death pathway, apoptotic execution tends to be immunologically silent because the fast dismantling and clearance of the dying cell minimises the release of immunogenic signals14. Apoptotic caspases also cleave and incapacitate signalling molecules, such as cyclic GMP-AMP synthase (cGAS), Interferon regulatory factor 3 (IRF3) and receptor-interacting serine/threonine-protein kinase 1 (RIPK1), that would otherwise drive the production of immunogenic danger signals15,16. By contrast, cells that die by caspase-independent forms of cell death, such as necroptosis, release ‘alarmins’, which alert the immune system of danger11,12.

Necroptosis, which is an explosive form of cell death, is the body’s natural method of killing cells infected by pathogens. Cancer cells that die in this way provide both antigens and adjuvants for DCs, which in turn activate CD8+ T cells through antigen cross-priming17,18. Therefore, developing therapies that drive immunogenic necroptosis of breast cancer cells could (re)activate the immune system of a patient to attack cancer cells. Necroptosis is typically triggered by the activation of RIPK1, RIPK3, and mixed lineage kinase domain-like pseudokinase (MLKL), which ultimately facilitates the release of these inflammatory signals by causing plasma membrane rupture19-22. RIPK1 acts as a key stress sentinel, that operates downstream of many cytokine receptors and pattern recognition receptors (PRRs). RIPK1 can simultaneously coordinate transcriptional inflammatory gene expression with different cell death pathways, including immunogenic apoptosis, necroptosis and pyroptosis17,23-25.

Since RIPK1-mediated cell death is a highly immunogenic process, it is subject to tight regulatory control. Members of the Inhibitor of Apoptosis (IAP) protein family, such as cIAP1, cIAP2 and XIAP function as pivotal gatekeepers of RIPK1 and RIPK1-mediated complexes, such as the ripoptosome and necrosome, which mediate immunogenic cell death17,18,26,27. The three clinically relevant IAPs, cIAP1, cIAP2 and XIAP are frequently upregulated at the transcript and protein levels in breast cancer and contribute to treatment resistance and poor clinical outcomes 28-33. cIAP1/2, and to some extent XIAP, modulate ubiquitin-dependent pathways that prevents assembly of complex II/Ripoptosome/Necrosome – a cytosolic signalling platform responsible for the integration of cellular stress, innate immune signalling pathways as well as cell death17,33-37. In parallel, IAPs also regulate NFB and interferon-mediated production of inducible damage-associated molecular patterns (iDAMPs) that can stimulate recruitment and activation of DCs38,39, leading to efficient cross-priming of effector T cells18. Additionally, XIAP can effectively inhibit caspases 3, 7 and 9 by directly binding to their active sites36. To promote cell death, drugs that mimic natural IAP antagonists, such as second mitochondria-derived activator of caspases (Smac/DIABLO, frequently referred to as SMAC mimetics or IAP antagonists) were developed. Such IAP antagonists mediate most of their effects via acute activation of RIPK1, highlighting their potential to enhance anti-tumour responses through the modulation of RIPK1-driven apoptosis and necroptosis. Several IAP antagonists have entered clinical trials. The third generation IAP antagonist ASTX660 (Tolinapant), which is currently undergoing clinical testing40,41,42,43, offers balanced inhibition of cIAP1/2 and XIAP40,44. This is important as all three IAPs regulate RIPK1 in a redundant manner.

Activation of immunogenic forms of cell death has emerged as an attractive approach to stimulate an anti-tumour immune response. However, developing therapies that complement ICB is hindered by the use of immunocompromised mice in preclinical studies. Additionally, there is a distinct lack of suitable genetically engineered mouse models (GEMMs) capable of producing diverse, invasive TNBC, including the majority of basal-like breast carcinomas, with varying immune environments that reflect the human disease. Using a tumour organoid-based transplantation model in immunocompetent mice, which reliably mimics the range of tumour immune microenvironments (TIME) of human TNBC with short latency and a stable tumour micro-environment across passage, we have evaluated the response of ICI-resistant tumours to combination therapies that drive lytic forms of cell death. We demonstrate that ICI-resistant and immune-escaped tumours respond to RIPK1-driven immunogenic cell death in combination with anti-PD1 therapy, particularly under necroptotic conditions, with increased recruitment of CD8+ T cells and the development of immune memory. Importantly, we find that the efficacy of IAP antagonism with ICB critically depends on coordinated necroptosis in both tumour and stromal compartments to amplify immune activation, emphasizing that the therapeutic outcome of ICD-based immunotherapies is dictated by the cellular architecture and immune composition of the tumour microenvironment. Immunologically colder tumours, that do not respond to this treatment combination, can be sensitised to RIPK1-mediated immunogenic cell death through pathogen mimicry, such as STING agonism. Together, these findings indicate that the combination of RIPK1 activation with targeted immune-modulating therapies has the potential to overcome ICI resistance and enhance outcomes for patients with TNBC. However, it will be important to stratify patients based on their cellular composition and immune landscape of the tumour microenvironment.

Results
Brca1p53 deficient tumours display heterogenous architecture and immune landscape
To study how to boost anti-tumour immunity in TNBC, we developed a transplantation-based syngeneic mouse cancer model that faithfully and stably recapitulates the phenotypic diversity of the human disease. To achieve this, we utilised the Blg-Cre;Brca1f/fp53+/- mouse model45,46, subsequently referred to as BP. In this model, tumours develop stochastically over 8 to 16 months due to the deletion of the Brca1 gene and subsequent loss of p53 heterozygosity in mammary epithelial luminal progenitor (Fig. 1A-C)45,46. Histopathological analysis and multiplex immunofluorescent imaging demonstrated that Blg-Cre;Brca1f/fp53+/- females present with invasive carcinomas, most of no special type (NST)46. Although the same tumour suppressors were lost in the luminal progenitor cells of the mammary gland in every animal (Fig. 1B and Supplementary Fig. 1A,B), tumours from different animals showed differences in nuclear morphology and tissue microarchitecture, including tumour/stroma ratio, demonstrating substantial inter-tumour heterogeneity (Fig. 1D and Supplementary Fig. 1C). To facilitate pre-clinical experimentation, we derived primary tumour organoid lines (O) from each tumour (Fig. 1C).

Organoid-derived tumours faithfully recapitulate key features of their primary tumour of origin
We selected the organoid lines BP903, BP487 and BP962 for further characterisation as they were derived from tumours with distinct histopathological features (Fig. 1D and Supplementary Fig. 1C). The organoids derived from the primary BP903, BP487 and BP962 tumours retained their tumorigenic capacity as their orthotopic transplantation into naïve, immune competent C57BL/6J females gave rise to organoid-derived tumours (TO) within a 30 - 40 day period (Supplementary Fig. 2A). The respective primary organoids exhibited significant differences from each other (Fig. 2A). BP487 organoids formed highly organised and polarised structures with branching buds and hollow lumens (Fig. 2A). In addition, BP487 organoids had prominent E-cadherin localisation at cell-cell contacts, which is highly reminiscent to organoids derived from normal, healthy mammary glands. BP487 organoids were comparatively the most differentiated. In contrast, BP903 and BP962 organoids lacked polarity and did not form lumens. While BP903 organoids retained E-cadherin expression, localisation appeared to be abnormal, with strong staining within the cytoplasm as well as at cell membranes (Fig. 2A). BP962 organoids displayed two distinct populations of epithelioid and mesenchymal-like, spindle-shaped cells (Fig. 2A), which were also observed in vivo in the primary BP962 tumour (TP) and organoid-derived tumours (TO) (Fig. 2B). While the epithelioid cells were E-cadherin positive, the mesenchymal-like, spindle-shaped cells were negative for E-cadherin expression (Supplementary Fig. 2B). The spindle cells surrounded the periphery of the epithelioid clusters, protruding into the matrix in vitro (Fig. 2A). These mesenchymal-like subpopulations remained present over passaging, indicating that the BP962 line produces epithelial and metaplastic cancer cell populations, a feature that is often associated with the cellular programme of epithelial-mesenchymal transition (EMT) and confers drug resistance, metastatic capacity and poor prognosis in TNBC47,48.

Importantly, TOs retained the histological features of their parental tumour (TP) from which the organoid line was derived, faithfully recapitulating morphological features and stromal composition (Fig. 2B-D). BP487 TOs displayed the highest stroma to tumour ratio, and BP487 cancer cells were arranged in duct-like structures. Notably, the individual organoid lines remained stable and reproducible across passages, as evidenced by mRNA and mutational profiling, while some clonal and CNA differences relative to the parental tumours were observed, reflecting tumour heterogeneity and adaptation in culture (Fig. 2E,F).

Furthermore, the murine BP tumours exhibited multiple cytological and architectural features typically seen in human basal-like breast cancer (Fig. 2G) 45,46,49, including high mitotic count, nuclear pleomorphism, high nuclear-cytoplasmic ratio, and geographic necrosis (Fig. 2H and Supplementary Fig. 2C), which is consistent with a previous report50. mRNA abundance-based Absolute Assignment of Breast Cancer Intrinsic Molecular Subtype (AIMS) analysis demonstrated that the BP lines retained their basal-like features in vitro and in vivo (Supplementary Fig. 2D). Additionally, TPs and TOs of all three BP lines expressed CK14, a basal marker for myoepithelial cells in the mouse mammary gland, but which is commonly expressed in luminal progenitor-origin tumours acquiring a basal-like phenotype51 (Supplementary Fig. 2E,F). While BP487 and BP962 were negative for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2), BP903 showed weak but detectable expression for ER and PR staining (Supplementary Fig. 2E-G). This finding aligns with previous reports, indicating that approximately 19% of spontaneous tumours in Blg-Cre;Brca1f/fp53+/- mice are ER-positive46, while 10-36% of BRCA1 mutant patients present with ER+ tumours52. Despite some BP903 cells being ER+, ER receptor activity appeared not to be required for cell survival, as ER inhibition with fulvestrant and tamoxifen had no impact on organoid viability (Supplementary Fig. 2H).

High diversity in immune landscape of Brca1-/-p53-/- tumours is captured in organoid-derived tumours
BP903, BP487 and BP962 TOs had distinctly different profiles of infiltrating lymphocytes and myeloid cells, with BP903 tumours showing the lowest level of lymphocyte infiltration (Fig. 3A,B and Supplementary Fig. 3A). BP487 TOs had high infiltration of monocytes, particularly of the Ly6c+ subset, suggesting a ‘pro-inflammatory’ monocytic tumour immune microenvironment. In contrast to BP903 and BP487 tumours, BP962 TOs were highly infiltrated by dendritic cells (DCs), CD4+ and CD8+ T cells, B cells, neutrophils and macrophages. In silico deconvolution of cell types using CIBERSORTx indicated that BP962 tumours are rich in myeloid cells (Fig. 3C), which was confirmed using IHC analysis (Fig. 3D,E). Compared to BP903 and BP487, TOs from BP962 had greater frequency of F4/80+ cells (macrophages), that were sustained during tumour growth (Supplementary Fig. 3B). A high abundance of tumour associated macrophages (TAMs) was recently reported in TNBC patients, accounting for 50% of all cells of the tumour micro-environment (TME)53-55. Therefore, BP962 tumours may replicate a comparable immune environment to that observed in human disease. The TIL profiles of TOs were highly similar to their respective TPs, indicating that the organoids were capable of ‘recreating’ a tumour micro-environment that closely resembled the tumour from which they were derived. Gene set enrichment analysis (GSEA) showed significant enrichment of macrophage-specific transcripts in BP962 TOs, compared to BP903 and BP487 TOs (Fig. 3F), whereas BP903 and BP487 TOs had similar levels to each other (Supplementary Fig. 3C).

Although the microenvironment of BP962 tumours exhibited substantial infiltration of pro-inflammatory immune cells, and appeared immunologically ‘hot’, the tumour cells had significantly increased expression of immune checkpoint proteins, including PD-L1 and T cell immunoreceptor with Ig and ITIM domains (TIGIT), when compared to other BP lines (Fig. 3G-I and Supplementary Fig. 3D). Furthermore, BP962 tumours showed a notably downregulated expression of genes associated with the MHC class I antigen presentation pathway (Supplementary Fig. 3E,F). Nevertheless, compared to BP903 and BP487, BP962 TOs were rich in the expression of NFB- and IFN-dependent target genes (Fig. 3J), which is frequently associated with aberrant cell survival, cell cycle progression, inflammation, metastasis, angiogenesis and regulatory T cell function56. Notably, such NFkB- and IFN signatures are also known to correlate with improved responsiveness to immune-checkpoint blockade-based therapies as both these signalling pathways influence bystander killing of tumour cells57,58. Accordingly, elevated NF-kB and IFN pathways correlates with improved responses to necroptosis. To address the role of the immune compartment on tumour growth, we inoculated immunocompetent C57BL/6J or immunocompromised (NSG) females with the three organoid lines. BP962-derived tumours showed a more aggressive phenotype when grown in NSG mice in comparison with immunocompetent C57BL/6J mice (Supplementary Fig. 4A). In contrast, BP487 and BP903 tumours grew at the same rate in NSG and C57BL/6J animals, suggesting that these tumours are poorly infiltrated by CD8+ T cells and do not actively engage host immunity that contributes to tumour control (Fig. 3A-C). Further, BP962 tumour-bearing C57BL/6J animals presented with enlarged spleens, when compared to controls, NSG mice or mice bearing BP903 tumours, suggesting that this secondary lymphoid organ participate in restraining the growth of BP962 cancer cells (Supplementary Fig. 4B,C). Intriguingly, we noticed that BP962 organoids and organoid-derived tumours produced high levels of cytokines such as CSF1 (Supplementary Fig. 4D), which can drive inflammation and immune cell proliferation. This cytokine production can lead to systemic inflammation, which causes the spleen to enlarge as it processes an increased load of immune cells and inflammatory signals59. However, additional tumour-related mechanisms may also contribute to spleen enlargement. Although host animals responded immunologically to the presence of BP962 cancer cells, BP962 tumours ultimately escape immune control. Therefore, BP962 tumours serve as an ideal model to study immune-escaped tumours, which represent a particular challenge for cancer immunotherapy60. Taken together, these data demonstrate that the BP model gives rise to tumours with very different immune landscapes. The high diversity in the immune environment of the different BP lines is comparable to that observed in the human disease of high-grade HR-deficient TNBC61. Whilst TOs generated from the different lines are distinct with respect to their tumour/stroma ratio and immune composition, the TOs are highly reproducible within each line, enabling the generation of large mouse ‘patient’ cohorts, in which to evaluate drug combinations aimed at triggering immunogenic cell death and driving more effective anti-tumour immune responses.

Targeting immune-escaped tumours by RIPK1-mediated cell death
Although the immune system can potentially be harnessed to drive anti-tumour responses, tumour evolution favours the survival of poorly immunogenic tumour clones and creates a microenvironment that suppresses effective anti-tumour immunity62. However, by inducing immunogenic cell death, it may be possible to counteract these evasion strategies, thereby enhancing the immune system's ability to recognise and eliminate tumour cells, and thus improving therapeutic outcomes26,27,60,63-66. To test whether it is possible to induce an anti-tumour immune response by targeting immunogenic cell death, we focussed on Receptor-interacting serine/threonine-protein kinase 1 (RIPK1), which functions as a critical stress sentinel, coordinating cellular survival, inflammatory responses and immunogenic cell death in the form of apoptosis, necroptosis and pyroptosis17,23-25. Activation of RIPK1 is tightly regulated by members of IAP protein family26,67-69, albeit RIPK1 is additionally regulated by further checkpoints26,70,71, including caspase-8 mediated cleavage72-75 (Fig. 4A). Small molecule IAP antagonists, such as ASTX660 (tolinapant), have been developed and are undergoing phase I clinical testing in combination with pembrolizumab (MK-3475) (ASTEROID, NCT05082259). While IAP antagonists were initially developed to promote tumour cell apoptosis, IAP antagonists also induce anti-tumour activity through modulation of innate and adaptive immunity, rejuvenating exhausted immune cells and driving immunogenic forms of cell death (Fig. 4A).

While RIPK1 was barely detectable in normal mammary glands, its expression was markedly elevated in cancer cells of primary BP tumours (Fig. 4B and Supplementary Fig. 5A), with BP962 cancer cells being among the highest RIPK1 expressers (Supplementary Fig. 5B). Intriguingly, IHC-based H-score quantification of RIPK1 protein expression specifically in cancer cells indicated that its expression was not uniform in cancer cells but varied across tumour cells of each BP line as well as between lines. In contrast to BP962 tumours, cancer cells from primary BP487 tumours had the lowest RIPK1 expression (H score of 5), which was comparable to the levels of RIPK1 in cells of normal mammary glands, including in the epithelial cells of the ducts. BP903 tumours had a RIPK1 H score of 115. The differences in RIPK1 expression between the different BP lines were maintained in their respective primary organoids (O) and TOs (Fig. 4C,D). Although the different BP organoid lines expressed different levels of components of the RIPK1 cell death signalling cascade (RIPK1, RIPK3, caspase-8 and MLKL), the BP903, BP487, and BP962 organoids, like EO771 TNBC-derived spheroids, readily died following treatment with necroptotic stimuli such as TNF/SM/emricasan (TNF/SM/E) and SM/E, whereby emricasan (E) represents a pan-capase inhibitor (Fig. 4E,F and Supplementary Fig. 5C-H). Treatment with either TNF, ASTX660 (IAP antagonist), emricasan or TNF/ASTX660 had no or little effect on organoid viability. Cell death upon treatment with SM/E and T/SM/E was suppressed by co-treatment with inhibitors of RIPK1, RIPK3 or genetic deletion of Mlkl (Fig. 4E,G and Supplementary Fig. 5D), indicating that IAP antagonism sensitises cells to RIPK1-mediated necroptosis. While normal mammary organoids were resistant to necroptosis (Fig. 4H), BP tumour organoids and E0771 TNBC spheroids were susceptible to this lytic form of cell death (Fig. 4E,I). Induction of necroptosis with two chemically distinct IAP antagonists, ASTX660 and SM164, produced comparable results (Fig 4E and Supplementary Fig. 5D), providing confidence that this effect is driven by an on-target mechanism.

Boosting immunotherapy by targeting IAPs
To test whether IAP blockade may help to maximize immunogenic cell death and the generation of an efficient adaptive immune response, we conducted co-clinical studies in immunocompetent C57BL/6J mice that resemble the treatment protocol employed in the ASTEROID phase I clinical trial (NCT05082259). ASTX660 is a small-molecule antagonist of all three clinically relevant IAPs (cIAP1, -2 and XIAP), which may offer advantages over first- and second-generation SMAC-mimetics, mainly by countering the redundancy of different IAPs in cancer cells. Pools of organoids (cell clusters) of the respective BP tumour organoids were injected orthotopically into the mammary fat pad of C57BL/6J females. When tumours reached 50 – 100 mm3, mice were either treated with vehicle or with ASTX660, PD-1 or ASTX660/PD-1 (Fig. 5A). Although ASTX660 and PD-1 had negligible effects as monotherapies, ASTX660/PD-1 achieved therapeutic responses in 45% of BP962-tumour bearing mice (Fig. 5B,C,D). Interestingly, the response to ASTX660/PD-1 was dramatically improved under necroptotic conditions in the presence of emricasan, with a 71% response rate, curing 8 out of 17 animals and causing significant partial responses in 4 animals (Fig. 5E,F,G and Supplementary Fig. 6A). Animals cured by ASTX660/E/PD-1 treatment were completely resistant to tumour re-challenge with BP962 tumour organoids (Fig. 5H,I,J), suggesting that these animals may have developed immune memory against tumour antigens. Immunologically protected animals also exhibited normal spleen weights, whereas BP962 tumour-bearing naïve mice displayed enlarged spleens (Fig 5K). Importantly, other tumour lines with similar high RIPK1 expression and substantial macrophage infiltration to BP962 show comparable sensitivity to the combination treatment of ASTX660/E/αPD-1 (Supplementary Fig. 6B-G), suggesting that elevated RIPK1 expression and pronounced macrophage infiltration may act as indicators of necroptotic responsiveness.

While treatment with ASTX660/PD-1 caused significant responses in immune-infiltrated BP962 tumours, particularly under necroptotic conditions, the same treatments had minimal to no effect on the immunologically ‘colder’ TOs (BP903 and BP 487) (Supplementary Fig. 7A-G). Co-treatment with an additional, second checkpoint inhibitor, anti-CTLA-4, provided no further benefit in BP487-tumour bearing animals (Supplementary Fig. 7H-K). Together, these data demonstrate that engaging necroptosis signalling significantly improves responses to immune checkpoint blockade-based treatments in immune-infiltrated/immune-escaped tumours (BP962), with high RIPK1 expression serving as potential biomarker. However, animals with less immune infiltrated tumours showed only a small but statistically significant benefit from such treatments, even under necroptotic settings and double immune checkpoint blockade, highlighting the importance of stratifying patients based on their tumour infiltrated lymphocytes and potentially RIPK1 levels.

To assess treatment-related changes in CD8+ T cells of BP962 tumours, BP962 TOs were exposed to a single treatment and harvested nine days after treatment (Fig. 5L). Treatment with ASTX660 stimulated a marked infiltration of CD3+ and CD8+ T cells into the tumour under necroptotic conditions, whereas they were largely excluded in the controls (Fig. 5M,N and Supplementary Fig. 7L). The increase in CD8+ T cells in treated tumours correlated with a decrease in immunosuppressive CD163+ M2-like macrophages in the peritumoral area, where they were most abundant (Fig. 5O,P). In conclusion, treatment with ASTX660 under necroptotic conditions significantly enhanced CD8+ T cell infiltration into BP962 tumours, which was associated with a reduction in CD163+ M2-like macrophages. This suggests that ASTX660 not only promotes immune cell infiltration but also alters the tumour microenvironment, potentially improving the efficacy of immunotherapy by shifting the balance towards a more immune-activating environment.

Boosting the immunogenicity of IAP antagonism through ‘viral mimicry’
To enhance the responsiveness of immunologically ‘cold’ tumours to IAP antagonism and ensure more potent anti-tumour immunity, we employed a strategy rooted in viral mimicry. Viral mimicry involves the activation of innate immune receptors to simulate an infection at the tumour site, thereby prompting an immune response. Such approaches include the provision of ligands for pattern recognition receptors (PRR). To this end we made use of the STING agonist diABZI76. STING agonists are emerging as powerful viral mimicry agents in cancer therapy, designed to activate the cGAS-STING pathway, thus triggering innate immune responses within tumours by simulating viral infection, thereby enhancing anti-tumour immunity77-79 (Fig. 6A). First, we evaluated the ability of diABZI to drive STING signalling in BP903 and BP487 organoids in vitro. Treatment with diABZI readily triggered activation of IRF3 and interferon signalling (STAT1 activation) in both organoids (Fig. 6B). However, STING agonist alone showed little cell death activity in vitro. Importantly, when combined with IAP antagonism and emricasan, which induces cell death, addition of STING agonist did not further enhance cell death (Fig. 6C), which is consistent with its reported signalling axis80. Next, we evaluated whether diABZI treatment could enhance the anti-tumour efficacy of ASTX660 in tumours that are poorly infiltrated by immune cells, such as BP903 and BP487 TOs. While treatment with diABZI alone had no effect on the growth rate of BP903 and BP487 tumours (Fig. 6D-G and Supplementary Fig. 8A-C), it significantly improved tumour control in combination with ASTX660, particularly under necroptotic conditions (Fig. 6D-J). This resulted in a survival benefit in both BP903 and BP487 TO-bearing animals, with one complete tumour regression in each cohort that remained tumour-free beyond 60 days (Fig. 6G,J). Addition of αPD-1 did not generate a durable immune response when combined with diABZI (Supplementary Fig. 8D-L), suggesting that additional contextual factors, such as the spatial distribution of macrophages, may be required for achieving sustained tumour control.

To assess treatment-related changes of the immune landscape, we treated BP903 tumours with diABZI/ASTX660/E and analysed its effect 12 days later (Fig. 6K). Tumour analysis revealed that co-treatment reshaped the tumour immune micro-environment under necroptotic conditions, promoting a marked increase in effector lymphocytes, such as CD8+ T cells,  T cells and NK cells (Fig. 6L,M and Supplementary Fig. 9A-E) that exhibited key features of activation (CD44+) (Fig. 6N). Accordingly, we observed a marked rise in IFN-γ-producing NK cells and CD8⁺ T cells within the tumour microenvironment following diABZI/ASTX660/E treatment in BP903 tumours (Fig. 6O). Importantly, we also observed an increased population of polyfunctional CD8⁺ T cells, co-expressing IFN-γ and TNF, indicative of enhanced effector function (Fig. 6O), although the frequencies of Perforin- or Granzyme B-expressing cytotoxic cells remained stable (Supplementary Fig. 9F-I). Moreover, diABZI/ASTX660/E also caused a clear reduction in immunosuppressive PD-1+ NK cells and regulatory T cells (Tregs) (PD-1+ as well as CD69+CD25+) (Fig. 6P,Q). Overall, the data point to a more activated and functionally potent anti-tumour immune response induced by diABZI/ASTX660/E treatment. Taken together, treatment with diABZI/ASTX660/E significantly altered the tumour immune microenvironment in 'cold' tumours, promoting the infiltration and activation of effector lymphocytes and reducing the presence of immunosuppressive cells. This indicates a shift towards a more immunostimulatory and less immunosuppressive tumour environment, thereby favouring anti-tumour immunity.

Necroptosis in tumour and stromal compartments is required to trigger effective anti-tumour immunity
To determine whether the therapeutic benefit of immunogenic cell death relies on necroptotic signalling within tumour cells and/or the stromal compartment following ASTX660/E/αPD-1, we deleted MLKL in each context. We also investigated the role of RIPK1 in tumour cells. To this end we generated BP962Ripk1-KO and BP962Mlkl-KO organoids using CRISPR/Cas9 (Supplementary Fig. 10A-D). Loss of Ripk1 profoundly impaired treatment efficacy with BP962Ripk1-KO tumours displaying a markedly blunted response to ASTX660/E/αPD-1, with no long-term survivors (Fig. 7A-C). In contrast, RIPK1-proficient BP962 tumours achieved durable tumour control under the same condition (see Fig. 5E-G), with 8/17 mice surviving long-term and showing evidence of immune memory (see Fig. 5H-J).

Next, we evaluated the role of MLKL-mediated necroptosis in tumour cells. Successful MLKL deletion and loss of necroptotic competence in BP962Mlkl-KO organoids were confirmed by Western blot and functional assays (Supplementary Fig. 10A,B). BP962Mlkl-KO tumours showed slightly slower growth in untreated mice, which was not apparent in BP962Ripk1-KO tumours (Supplementary Fig. 10C,D). Intriguingly, upon therapy, BP962Mlkl-KO tumours remained responsive to ASTX660/E, however, unlike necroptosis-proficient tumours, co-administration of αPD-1 did not improve survival beyond ASTX660/E alone (Fig. 7E-G). This indicates that tumour-cell MLKL activity is required for αPD-1-mediated immunological potentiation. To determine whether stromal necroptosis also contributes to therapeutic efficacy, BP962 organoids were transplanted into Mlkl-/- recipient mice. While ASTX660/E/αPD-1 still produced a measurable effect, its efficacy was substantially reduced in Mlkl-/- hosts, with no long-term survivors (Fig. 7H,I), compared to robust responses in WT mice (see Fig. 5E-G).

Together, these findings demonstrate that MLKL-mediated necroptosis in stromal cells is critical for durable anti-tumour immunity, and that tumour-cell necroptosis is additionally required for full therapeutic benefit. Thus, necroptosis in both tumour and stromal compartments acts cooperatively to enable a maximally effective immune response to ASTX660/E/αPD-1.

Methods
All research reported in this study was approved by the Animal Welfare Ethical Review Body (AWERB), and conducted within the guidelines of UK Home Office in accordance with Animals (Scientific Procedure) Act (ASPA) 1986, amended 2012 and the institutional guidelines of the Institute of Cancer Research. Further, all animal experiments were conducted in accordance with the Animal Research: Reporting of In vivo Experiments (ARRIVE) guidelines to ensure reproducibility and transparency113.

Reagents, chemicals and antibodies
See Supplementary Data 1.

Generation of organoid lines
Organoid lines were generated using an adaptation of a previously described method (Duarte et al. 2018). Organoids were derived from tumours that had spontaneously developed in Blg-Cre;Brca1f/fp53+/- mice. Tumours were excised once they reached a maximum diameter of 8–12 mm and were then mechanically disaggregated using scalpel blades. Subsequently, they were digested in RPMI medium containing enzymes from the Tumour Dissociation Kit for 41 minutes at 37°C, with the GentleMACS Octodissociator (Miltenyi) set to varying rotation speeds. The digested suspension was filtered through a 70 µm cell strainer (Falcon), then centrifuged at 1400 rpm for 10 minutes. The pellet was washed twice in basal ADDF+++ media (Advanced DMEM/F12 supplemented with 10 mM HEPES, 1% GlutaMAX, and 1% penicillin/streptomycin), then resuspended in mouse mammary gland organoid medium ADDF+++ media, supplemented with 2% B27 supplement (Gibco), 125 µM N-acetyl-L-cysteine (Sigma), and 50 ng/mL mEGF (Thermo Fisher Scientific), mixed 1:1 with Growth Factor reduced Matrigel (SLS). The organoid:matrigel mix were seeded into 40 µl domes per well into a 24-well suspension plates (Greiner Bio-One). After incubation at 37°C for 30 minutes, 500-750 µl of ADDF+++ media containing 10 µM ROCKi (Medkoo) was added per well. Healthy mammary tissue organoids were derived using an adaption of the previously described method114 and the dissociation of mouse mammary tissue using EpiCultTM-B. Specifically, mammary fat pads were isolated from C57BL/6J mice and minced to a paste using scapels before digesting in EpiCultTM-B digestion medium containing 1x Collagenase/hyaluronidase (Stemcell Technologies, #07919), 5% FBS and 1% penicillin/streptomycin during a 41 minute incubation at 37°C, with varying rates of rotation in the GentleMACS Octodissociator (Miltenyi). After digestion, the suspension was mechanically disrupted with a 1 ml pipette tip and pelleted at 350xg for 5 minutes and filtered through a 70 µm cell strainer (Falcon). The suspension was centrifuged at 1400 rpm for 10 minutes and washed twice in basal ADDF media before resuspension in Normal Mammary media of which the composition was based as described before115 with Neuregulin substituted with mEGF (ADDF+++ media; supplemented with 2% B27, 1% N2 (Thermo Fisher Scientific), 10 ng/ml mEGF, 10 ng/ml FGF basic (Peprotech), 4 µg/ml Heparin (Sigma) mixed 1:1 with Growth Factor reduced Matrigel (Corning, #356237). The organoid:matrigel mix were seeded into 40 µl domes per well into a 24-well suspension plates (Greiner Bio-One). After incubation at 37°C for 30 minutes, 500-750 µl of Normal mammary media containing 10 µM ROCKi was added per well.

Maintenance of organoid lines
Once established, organoids were cultured in a humidified incubator with 5% CO2 at 37°C. Organoids were passaged as required at a ratio of 1:2-1:10, depending on the line. To passage, organoids were extracted from Matrigel and dissociated to single cells in TrypLE for 10 minutes at 37°C. Single cells were centrifuged at 1400 rpm for 4 minutes and the cell pellet was resuspended in either a 50% or 75% Matrigel:ADDF+++ mix and then plated as described above. Organoids were frozen 72 h post passage in FBS supplemented with 10% DMSO. For all experiments, organoids were used between passages 5 and 25. The E0771 cell line was cultured in RPMI1640 (Gibco), supplemented with 1% penicillin/streptomycin and 10% FBS. All organoids were screened for pathogens by an external provider (Charles River, UK), using the ‘Charles River Mouse/Rat Comprehensive CLEAR Panel w/ C. bovis’. All cells and organoids were regularly screened for mycoplasma using the MycoAlert Mycoplasma Detection Kit (Lonza).

Generation of CRISPR knockout Organoids
Guide RNA preparation was described before63. For MLKL knockout, organoids were broken down into single cells using TrypLe and 1x106 cells were seeded per well into Matrigel coated 6 well plates. After 24 h, cells were transiently transfected with Lipofectamine 3000 (Invitrogen). After 48 h, GFP positive cells were FACS sorted, seeded back into Matrigel and screened for gene knockout. For RIPK1 knockout, annealing of relevant guides and ATTO-550 tracer (IDT) was performed through annealing in a 95°C - RT ramp program, over the course of 30’, according to manufacturer’s instructions. RNP complex formation was performed by supplementing Cas9 at a final concentration of 63µM, for 20’ at RT, before electroporation. Single suspensions of 2x105 cells were resuspended in 27µL of Neon Resuspension R buffer (Invitrogen), 3µL of RNP complex and 6µL of Nuclease-Free Duplex Buffer (IDT) and then electroporated using 10µL Neon NxT tips (Invitrogen) under a program of 1 pulse at 1700V and 20ms pulse width program. Immediately after electroporation cells were seeded in P/S-free ADDF medium, spun down, and replated in 3D O/N. The following day, cells were freed from Matrigel through TrypLe digestion, FACS sorted for ATTO-550 positivity, and re-plated in 3D. Cells were cultured for one week in presence of P/S-free ADDF medium, before validation by Western Blot.

PCR genotyping
Organoids were homogenised using a Qiashredder (Qiagen). For ex vivo mouse tissues, samples were snap frozen immediately after dissection, then a 20-30 mg fragment of tissue was disrupted and homogenised using a Precellys bead mill (Bertin). DNA was extracted from the homogenised samples using the Dneasy Blood and Tissue Kit (Qiagen), as per manufacturer instructions. PCR reactions were performed according to the mouse genotyping protocols published by The Jackson Laboratory (Jackson Laboratories 2019), using the KAPA2G Fast HotStart PCR Kit (Kapa Biosystems), with primers (see Supplementary Data 1). DNA electrophoresis was run in 2.5% agarose gels (Invitrogen) and gels were imaged using a ChemiDoc Touch Imaging System (Bio-Rad).

RT-qPCR
RT-qPCR was performed using two TaqMan assays (Thermo Fisher Scientific); one with the target sequence in exon 19 (present in all alleles) and one with the target sequence in exon 22 (which is present if the floxing event has not occur red, and absent if the floxing event has occurred)46. RT-qPCR was performed on RNA extracted from tail tips of wild-type C57BL/6J mice, organoids, and organoid-derived tumours. Prior to RNA extraction, mouse tissues (tumours and tail tips) were mechanically disrupted and homogenised using a Precellys 24 tissue homogeniser (Bertin). For organoids 1x106 cells were collected and homogenised using a Qiashredder (Qiagen). RNA was extracted from homogenised samples using the RNeasy Mini Kit (Qiagen) as per manufacturer instructions. RNA quantity and quality were measured using a NanoDrop 8000 Spectrophotometer (Thermo Fisher Scientific). cDNA was synthesised from RNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). For Brca1 exon 19 and exon 22, qPCR was performed using TaqMan Gene Expression Assays (Applied Biosystems) as previously described46. RT-qPCR results were analysed using the DDCt method. Ct values were calculated from triplicate repeats for each sample. The Ct value of a housekeeping gene (Actin) was subtracted from the Ct value of each sample, to calculate the DCt value. The DCt value for each sample was then normalised to a control sample by subtraction to calculate DDCt. The fold change in expression was calculated as the negative exponent of this value (2-DDCt). RNA was extracted from homogenised BP903 tumour fragments using the Allprep DNA/RNA Micro kit (Qiagen) and converted to cDNA using QuantiTect Reverse Transcription Kit (Qiagen), according to manufacturer’s instructions. RT-qPCR and data analysis were performed as previous described116. For BP903 TOs, mRNA was extracted 12 days post treatment with a single injection of vehicle control or diABZI/ASTX660/E. The relative mRNA expression of indicated genes was measured using Taqman probes (Thermo Fisher Scientific): Actb (House-keeping gene (Mm00607939_s1), Ifng (Mm01168134_m1), Perforin (Mm00812512_m1), and Ccl5 (Mm01302427_m1).

Bulk RNA-seq
RNA was extracted using the Allprep DNA/RNA Micro kit (Qiagen) from snap frozen samples of the primary tumour, early passage established normal and tumour organoids (passage number 10-20), organoid-derived tumours, as well as normal murine mammary fat pads (excluding lymph nodes). Three independent samples were analysed per group, except for the primary tumour, for which a single sample was analysed. For organoids, 1x106 cells were collected and homogenised using a Qiagen Qiashredder. For mouse tissue, samples were snap frozen immediately after dissection, then a 20-30 mg fragment of tissue was disrupted and homogenised using a Precellys bead mill (Bertin). RNA quantity and quality were determined using the Nanodrop spectrophotometer (Thermo Fisher Scientific). Strand-specific mRNA libraries were prepared using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEBNext Poly(A) mRNA Magnetic Isolation Module; New England Biolabs), from 500 ng of RNA per sample. The quantity and quality of the libraries were analysed using the 2100 Bioanalyzer system (Agilent). Sequencing was performed using the Illumina NovaSeq 6000, on an S1 100 bp PE Nova flowcell, to achieve 7.5 Gigabases per sample.

Copy-number analysis
Copy-number aberrations were calculated using CNVkit (v0.9.9117) and Control-FREEC (v11.5118). For CNVKit, gains/amplifications and losses/deletions were defined as log2ratio > 0.5 and log2ratio < -0.3, respectively. For Control-FREEC, default gain/amplification and loss/deletion filters were used. Results from the two callers were converted to R GRanges objects and subsequently intersected keeping the common copy-number calls only. Preprocessing of whole exome sequencing dataset was performed as previously described119 using the mouse reference genome (GRCm38).

Computational analysis of RNA sequencing data
For raw sequence quality control, FastQC and FastQ Screen were run on all sample FASTQ files, and a summarised report was generated using MultiQC120,121. FASRTQ reads were trimmed using Trim Galore (v0.6.6). Paired-end reads (100 bp long) were aligned to the mouse reference genome (version GRCm38), using STAR (v2.7.6a) with quantMode GeneCounts and twopassMode Basic alignment settings122. The annotation file used for feature quantifications was downloaded from GENCODE (v17) in GTF file format. Differential mRNA abundance analysis was performed using the edgeR package123 in R (version 3.6.0). Results were annotated using ENSEMBL gene annotations from R package org.Mm.eg.db. Genes were considered statistically significant if the log2 fold change was greater than 1, and the false discovery rate-adjusted p value was below 0.05. Principal component analysis (PCA) was performed using custom libraries in R statistical environment (v.3.6.0). Normalised data was used for PCA using R function FactoMineR::PCA for plotting PC1 and PC2. Differences in the expression of stromal elements was interrogated using the stroma-derived prognostic predictor (SDPP) gene set124. Samples were classified into breast cancer subtypes based on their gene expression profiles using the AIMS gene classifier125. A mouse-specific mammary tumour classifier was created using centroids of a previously published microarray dataset126. The MHC class I antigen presentation pathway was analysed by comparing the differential expression of various organoids, using a gene list from Nanostring's pan-cancer/immune gene sets (https://nanostring.com/products/ncounter-assays-panels/oncology/pancancer-immune-profiling/) (Supplementary Data 2). The immune checkpoint gene expression was analysed by comparing the differential expression of the indicated organoids.

Gene set enrichment analyses (GSEA)
Macrophage-related gene sets were obtained from MSigDB127 by querying mouse collections for the keyword "macrophage" and further filtering to include only those containing the term in their name. Gene Set Enrichment Analysis (GSEA) was performed in R 4.2.1 with ClusterProfiler using fold-change values from differential expression comparisons of different TOs (Supplementary Data 2).

Cell type deconvolution with CIBERSORTx
To perform cell type deconvolution of bulk RNA samples, cell-type specific transcriptomes were obtained from the Brca1-/-p53-/- TNBC mouse model128. scRNA-seq counts were converted to transcripts per million (tpm) and the dataset was down sampled to 2500 cells to increase computing efficiency. A signature matrix was then created using a CIBERSORTx129 singularity container with default settings. Subsequently, fractions mode was employed for cell type proportion deconvolution using relative-mode, 100 per mutations, rmbatchSmode and disabling quantile normalisation.

Lysate preparation and Western blot analysis
Organoids embedded in Matrigel were washed with PBS and frozen at -80°C overnight. Once thawed at room temperature, the organoids and Matrigel domes were lysed using S-Buffer (20 mM Tris pH 8.0, 40 mM Na pyrophosphate, 50 mM NaF, 5 mM MgCl2, 100 µm NaVanadate, 10 mM EGTA, 1% Triton-X-100, 0.5% NaDOC) containing protease inhibitor cocktail and phosphatase inhibitors. Organoids and Matrigel were mechanically disrupted by pipetting and spun down at 13,200xg at 4°C for 10 minutes to coalesce the Matrigel. 6x sample buffer (350 mM Tris pH 6.8, 35% glycerol, 10% SDS, 0.6 M DTT, 180 µM bromophenol blue) was added to the supernatant and the samples were heated to 85°C for 5 minutes and then resolved on NuPAGE Novex 4–12% Tris-Gly 1.0 mm gels in Tris-Glycine buffer (ThermoFisher). After transfer onto polyvinylidene difluoride (PVDF), membranes were blocked with 5% BSA and then probed with antibodies as indicated.

Cell death assay with organoids
Organoids were seeded as single cells into 384 well plates (Greiner, #781091), containing 5x103 cells embedded in 4-5 mg/ml Matrigel, ADDF+++ media mix per well and cultured for at least 72 h before drug treatments. Drug concentrations used: TNF (10 ng/ml), IAP antagonist (SM164, 1 μM, and ASTX660, 1 μM or 10 μM), Emricasan (5 μM), RIPK1 inhibitor (GSK’693, 100 nM), RIPK3 inhibitor (GSK’872, 10 μM) and STING agonist (diABZI, 10 μM). ASTX660 was used throughout, except for Fig. 4F,H,I and Supplementary Fig. 5D and 10B, where SM164 was used. At experimental endpoints, wells were supplemented with propidium iodide (PI) (1 μg/mL, Sigma-Aldrich), and Hoechst-33342 (H) (0.5 μg /mL) (Thermo Fisher Scientific) and incubated at 37C for 1 h. To image cell death (PI uptake) of organoids, we used the ImageXpress Confocal High-Content Imaging System (Molecular Devices) with a Nikon Plan Fluor Ph1 DLL 10x/ 0.3 NA air objective. The system is equipped with Ra Lumencor LED light source and an Oxford Nanoinstruments Zyla camera. Images of the Hoesht (405 nm ex/461 nm em) and PI (560 nm ex/ 615 nm em) were captured at 400 ms and 300 ms exposures, respectively, with 2 or 4 fields of view imaged per well and a z-stack of 5 μm steps over ~150 μm range, which was subsequently compressed to 2D maximum intensity projections with each field of view typically capturing ~20-50 organoids, with each organoid consisting of ~100 cells). A custom module workflow was built using the MetaXpress analysis software (Molecular Devices). The workflow consisted of 9 steps. Step 1: ‘Setup’ module defined the channels used for analysis, ‘DAPI’ and ‘Texas Red’. Step 2: ‘Simple Threshold’ module to segment the organoid structures using the DAPI channel to create an object mask of the organoid total area. The threshold was adjusted as required depending on signal intensity. Step 3: ‘Filter Mask’ module determined the size of organoid structures (or objects) to be included for analysis, and enabled exclusion of debris or single cells and adjusted as required between experiments. Step 4: ‘Grow Objects’ module followed by Step 5: ‘Fill Holes' module improved segmentation by merging nuclei and filling in any space created by the presence of a lumen, to create complete objects for the mask. For the Grow objects, we consistently increased by 3 pixels. Step 6: ‘Remove Round Objects’ module removed all partially segmented organoids obstructed by the edge of the imaging field of view to complete the first organoid mask. Step 7: ‘Find Round Objects’ module was used to segment PI positive nuclei using thresholding on channel 2 to create the second mask of organoid cell death. Step 8: ‘Grow Objects’ module expanded the segmented PI positive objects by 3 pixels. Step 9: ‘Measure Mask’ module measured the total area of PI stain overlayed within the defined segmented total viable objects from channel 1. The above analysis pipeline outputs a large table containing the total area measurement for both the first organoid mask (total organoid area) and second organoid cell death mask (PI area only) for every object measured, as well as other related data. To automate and streamline the analysis, a python script was written in Jupyter Notebook to clean up the data table, calculate the mean PI/DAPI ratio per field of view and export the rearranged table into a format suitable for downstream analysis. One well typically corresponds to two or more three-dimensional fields of view within Matrigel. For each field, the mean PI/DAPI staining ratio was calculated across all quantified organoids. Organoid viability was measured using CellTiter-GLO assay (Promega). Briefly, organoids were seeded as single cells into 384 well plates (Greiner, #781091), containing 5x103 cells embedded in 4-5 mg/ml Matrigel, ADDF+++ media mix per well and cultured for at least 72 h before treatment with titrated Tamoxifen and Fulvestrant for 7 days. Media was refreshed after 3 days with media containing freshly prepared drugs. At experimental end point media was aspirated and 50ul neat CTG reagent was added per well and the plate was rocked gently for 1 h. Luminescence was measured using Victor X plate reader (PerkinElmer) and Data was normalised to the DMSO control to calculate cell viability.

Flow cytometry analysis
To determine immune infiltration, tumours were harvested and single cell suspensions were prepared. To this end, tumours were perfused with 1 mL/200 mg digest buffer (1 mg/ml Collagenase II (Merck), 0.1 mg/ml DNAse I (Merck), and 0.1% BSA in RPMI) before being minced into 1-2 mm pieces and incubated at 37°C for 1 h shaking at 180 rpm. Digestion was inactivated with 20 mL MACS buffer (Miltenyi autoMACS running buffer Miltenyi, 130-091-221), and tissue suspension aggravated through a 70 µm filter. Cell suspensions were spun down at 350 rpm for 15 minutes at 4°C, and supernatant aspirated. Cell pellets were resuspended in 500 ml red blood cell lysis buffer (1x BD PharmLyse 555899 in H2O) and incubated at RT for 2 minutes. Lysis was inactivated with 2 mL HBSS and cells pelleted at 350 rpm for 6 minutes at 4°C, before aspiration of supernatant. Pelleted cells were resuspended in 500 µl viability dye (1:2000 dilution eBioscience™ Fixable Viability Dye eFluor™ 506, Thermofisher 65-0866-14 in HBSS) and incubated in the dark at RT for 20 minutes. Cells were washed with 2 mL MACS buffer and pelleted at 350 rpm for 6 minutes at 4°C, before aspiration of supernatant. Pelleted cells were resuspended in 50 µl Fc block (1:50 dilution in MACS buffer of Purified Rat Anti-mouse CD16/CD32, BD Biosciences 553142), and incubated in the dark at 4°C for 20 minutes. Antibody cocktail was prepared in a staining volume of 50 µl MACS buffer and added directly to cells in Fc block, prior to a further 30 minutes incubation. Stained cells were washed with 300 µl MACS buffer and pelleted as before. Cell pellets were fixed in 2% PFA in MACS buffer, in the dark at 4°C for 20 minutes. Finally, cells were washed as before, and resuspended in MACS buffer for flow cytometry analysis. 123 count eBeads (Thermofisher 01-1234-42) were added to each sample to calculate cell counts. To quantify changes in the immune landscape following treatment, tumours were harvested in ice-cold PBS from mice 12 days after treatment. Tumours were mechanically dissociated with scissors and enzymatically digested (30 minutes, 37°C), in PBS containing Trypsin-Versene (in house), 0.5 mg/ml Collagenase type I (Sigma, cat# C2674 ), 400 µg/ml Dispase type II (Sigma, cat# D4693), 1 mg/ml DNase type I (Roche, cat# 10104159001). Tumour suspensions were passed through a cell strainer (70 µm) into PBS (2% FBS & 2 mM EDTA), before centrifugation (1500 rpm, 10 minutes, 4°C). Pellets were resuspended in PBS-FBS 2% + Fc block (1:100, CD16/CD32, BD Biosciences cat# 553142) for 10 minutes (4°C), before surface staining for 30 minutes at 4°C with the appropriate antibody cocktail containing the viability dye (1:1000 eBioscience™ Fixable Viability Dye eFluor™ 780, cat# 65-0865-18). Cells were either fixed in 2% PFA for 20 minutes or fixed and permeabilised following the manufactured protocol (eBioscience, cat# 00-5523-00) prior staining with anti-Granzyme B, anti-Foxp3 and Ki67 antibodies. Flow cytometric analyses were carried out with a FACSymphony A5 (BD Biosciences) with FACSDiva software. 123 count eBeads (ThermoFisher, cat# 01-1234-42) were added to each sample to calculate cell counts. Data were analysed with FCS Express 7 software. The full list of antibodies used in this study can be found in the supplementary resources table.

Immunofluorescence
Immunofluorescence analysis was conducted as described previously130. Briefly, organoids were seeded as single cells into 96 well plates (Greiner, #G655090), containing 5x103 cells embedded in 4-5 mg/ml Matrigel, ADDF+++ media mix per well and cultured for 7 days (tumour organoids) or 12 days (Mammary fat pad organoids) before fixing with 4% PFA for 30 min. Organoids were blocked and permeablised with Blocking Buffer (0.3% Triton X100, 1% BSA in PBS) for 1hr. All primary and secondary antibodies were used at 1:100 dilution in Blocking Buffer. DAPI was used at 1:1000 in Blocking Buffer. Antibodies used can be found in Supplementary Data 1. Organoids were fixed and Immunofluorecent labeling of FFPE sections was conducted as previously described131. Confocal imaging was performed using a Leica SP8 confocal microscope. Images were acquired at a resolution of 2048 × 2048 pixels with an 8-bit depth and a scan speed of 400. Imaging was conducted using a 20X0.8NA air objective (zoom 2.16) for BP487, BP903, and WTO samples, and a 40X1.3NA oil objective (zoom 1.5) for BP962 samples. Z-stack images were collected for all conditions. Maximum intensity projections were generated from z-stacks using Fiji software for presentation as two-dimensional images.

Opal 6-plex
3 m FFPE tissue sections were baked for 1 h and run on the Leica Bond Rx platform. Several cycles of sequential staining were conducted by using Epitope Retrieval solution 1 for 20 minutes between each antibody, apart for the last antibody in the sequence where Epitope Retrieval solution 2 was used for 30 minutes. Antibodies were applied with Opal pairings in the following order: Panel 1 – Lyve1 (ab33682) 1:1500 with Opal 520 1:300, F4/80 (ab300421) 1:1000 with Opal 690 1:150, CD31 (ab182981) 1:1000 with Opal 480 1:100, Ki67 (ab15580) 1:1000 with Opal 570 1:300, CD45 (70257S) 1:100 with Opal 620 1:300 and CD19 (ab245235) 1:200 with TSA-DIG 1:100 followed by anti-DIG-Opal780 1:25. Panel 2 – Ly6G (87048S) 1:100 with Opal 520 1:300, F4/80 (ab300421) 1:1000 with Opal 690 1:150, SMA (M0851) 1:250 with Opal 570 1:300, CD3 (ab134096) 1:500 with Opal 480 1:100, CD45 (70257S) 1:100 with Opal 620 1:300 and CD19 (ab245235) 1:200 with TSA-DIG 1:100 followed by anti-DIG-Opal780 1:25. Bond anti-rabbit Polymer was used as the secondary antibody for antibodies raised in rabbit. Horse anti-Mouse IgG (Rat adsorbed)-Biotinylated secondary antibody (BA-2001) 1:400 and Streptavidin-Peroxidase (P0397) 1:500 were used as the secondary antibodies for antibodies raised in mouse. Slides were scanned using the PhenoImager HT (formerly Vectra Polaris). Spectral unmixing and auto-fluorescence removal were performed using the Phenochart and Inform softwares.

Histopathology, sample preparation and staining
Tumour material was fixed in 10% neutral buffered formalin for 24 h. Subsequently, tumours were washed in PBS followed by processing from 50% EtOH through to embedding in paraffin wax. Organoids were fixed in 10% neutral buffered formalin for 15 minutes, embedded in Histogel (Richard-Allan Scientific) then processed to wax embedding as above. For IHC staining, 4 µm sections were cut onto adhesive slides, air dried and baked at 60°C to enhance adhesion and stored at 4°C prior to staining. Prior to IHC staining, heat induced epitope retrieval (HIER) and deparaffinisation was performed using the Dako PT LINK module for 20 minutes at 97°C with a 20 minutes warmup and then 20 minutes cooldown to 65°C, in either pH 6 or pH 9 Dako Target Retrieval Solution (Agilent Technologies). Endogenous peroxidases were blocked using Agilent REAL peroxide block. All staining was performed on the Dako Link48 or Ventana Discovery Ultra automated immunostaining platform, which, for RIPK1, was similar to the one described in132. For staining carried out on the Link48 platform: For primary antibodies raised in mouse, endogenous mouse immunoglobulin was blocked using M.O.M. (Mouse on Mouse) Blocking Reagent (Vector Laboratories) and non-specific interactions blocked using Dako Protein Block (Agilent) prior to application of the primary antibody. Rat primary antibodies were detected using Rat Histofine Reagent (Nichirei Biosciences), rabbit primary antibodies using ImmPRESS HRP Horse anti-Rabbit IgG (Vector Laboratories), and the mouse primary antibody using EnVision anti-mouse-HRP reagent (Agilent). For staining carried out on the Ventana Discovery slides were deparaffinised using Roche Discovery Wash and HIER was performed for 64 minutes at 95OC using CC1 (high pH) buffer. Endogenous peroxidase was blocked using ChromoMap Inhibitor CM (Roche). Primary antibodies were diluted in Ventana Primary Antibody Diluent with casein protein block (Roche) and applied manually. Slides were incubated at room temperature for 32 minutes before incubation with UltraMap anti-Rabbit HRP secondary multimer for 8 minutes. Slides were visualised using Roche ChromoMap and haematoxylin counterstain. Slides were digitised using a Nanozoomer XR (Hamamatsu) using a 20X dry objective and the ndpi images imported into QuPath133 for digital analysis.

Histopathology analysis
Morphological assessment of essential pathological features of primary and organoid-derived tumours was made on digital scans of H&E sections. Features defining tumour grade (tubule formation, nuclear pleomorphism, mitotic count) were evaluated along guidelines for clinical purposes, as defined by the Royal College of Pathologists (RCPath). Additional characteristics of the tumour and tumour microenvironment, including tumour necrosis, stromal features and immune infiltrates, were also assessed. A semi-quantitative assessment of RIPK1 expression on primary tumours and normal lobules was carried out by applying the H-score method, which incorporates both staining intensity and percentage of stained cells at each intensity level as follows: H-score = (0 x % negative cells) + (1 x % weak positive cells) + (2 x % moderate positive cells) + (3 x % strong positive cells), with overall score ranging from 0 to 300. For semi-quantitative assessment of ER and PR expression, the Allred score (0-8 Quick score) was employed, in keeping with the recommended by the RCPath method for clinical practice (score for proportion: 0 = no staining, 1 = < 1% nuclei staining, 2 = 1–10% nuclei staining, 3 = 11–33% nuclei staining, 4 = 34–66% nuclei staining, 5 = 67–100% nuclei staining; score for intensity: 0 = no staining, 1 = weak staining, 2 = moderate staining, 3 = strong staining). Current consensus is that the recommended cut-off point for positivity versus negativity for ER status is ≥1% of tumour cells. For HER2 expression, the semi-quantitative method, which is based on the intensity of staining and percentage of membrane positive cells, recommended by RCPath was employed. This method gives a score range of 0 to 3+, with samples scoring 3+ regarded as positive, and those scoring 0/1+ as negative. Borderline scores (2+) are regarded as equivocal. For the QuPath quantification of stroma to tumour ratio on primary and organoid-derived tumours, H&E stained images were manually annotated with areas of “Stroma” and “Tumour.” Whitespace was classified as “*Ignore”. These annotations were used to train a pixel classifier using Random Trees at a resolution of 1.81 µm/pixel and utilising all multiscale features. The area occupied by each was used to calculate the stroma to tumour ratio in each specimen. The luminal space was calculated by subtracting the area classified as “Tumour” and the area classified as “Stroma” from the parent annotation area. For the QuPath quantification of infiltration of organoid-derived tumours by F4/80 positive cells, IHC images had their haematoxylin and DAB colour vectors automatically calculated, and the DAB channel was threshold at an Optical Density of 0.1 to create a binary mask. The tumours were manually annotated to include only tumour mass and exclude surrounding tissues. The total area of tumour occupied by positive pixels was calculated. For the QuPath quantification of infiltration of organoid-derived tumours by CD163 or CD8 positive cells, IHC images had their haematoxylin and DAB colour vectors automatically calculated and the stains deconvoluted. The tumour boundary was annotated manually using the polygon annotation tool and surrounding tissues and necrotic regions were excluded. The number of positive cells within the tumour mass (intratumoral area) was quantified using Positive cell detection plug-in. The sum optical density (OD) channel was used for cell detection at a threshold of 0.1. Cells were classified as Positive when the mean DAB OD exceeded 0.07. To count positive cells surrounding the tumour boundary (peritumoral area), the tumour boundary annotation was expanded by 100 µm and 50 µm for CD8 and CD163, respectively. For the QuPath quantification of PD-L1 positive cells, the DAB mean is the average of DAB stain optical density values (at a 2 µm resolution per pixel) across the annotation area (not multiple fields of view). The annotation area for these scans was the area covered by tumour cells, leaving out the surrounding tissue (adipose/lymph node etc).

Human tumour samples
Human tumour samples used for histological comparison in Fig. 2G consisted of three independent cases (n = 3). Samples were analysed by H&E staining and used for qualitative comparison with mouse tumours to assess histopathological similarity. The samples were derived from female patients diagnosed with triple-negative breast cancer, aged 38–68 years at the time of diagnosis. Samples were obtained from a cohort established at the Institute for Oncology and Radiology of Serbia (IORS), a national comprehensive cancer centre, between 2009 and 2013. The retrospective use of biological material for research purposes was approved by the IORS Ethics Committee (Belgrade; approval date: 10 February 2013). All patients had provided written informed consent for treatment at the time of care. No participant compensation was provided.

Mice and in vivo treatments
All animal procedures were conducted within the guidelines of UK Home Office in accordance with Animals (Scientific Procedure) Act (ASPA) 1986, amended 2012 and the institutional guidelines of the Institute of Cancer Research. The Animal Welfare Ethical Review Body (AWERB) reviewed the protocols within the project license. All the animal experiments were conducted in accordance with the Animal Research: Reporting of In vivo Experiments (ARRIVE) guidelines to ensure reproducibility and transparency113. Mice were housed in ambient temperatures of 19-23C, humidity between 40 and 70% and 12 hours light/dark cycles. Blg-Cre;Brca1fl/flp53+/- mice (C57BL/6) were aged until 12 to 15 months, with some mice undergoing at least one round of pregnancy and assessed for spontaneous tumour development in the mammary glands. Mice were culled when the tumours reached an average size of 12 to 15 mm and were processed to generate organoids as described above. Female C57BL/6J, C57BL/6J-Mlkl-/- and NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) mice, aged between 6 to 8 weeks were used for tumour studies, including therapeutic interventions (C57BL/6J and C57BL/6J-Mlkl-/-). Mice were purchased from Charles River (C57BL/6J and NSG) or obtained by in-house breeding (C57BL/6J-Mlkl-/-) and enrolled in the study post an acclimatization period of at least one week. Mice were injected in the 4th right mammary fat pad with 5 x 104 organoids. Tumour growth was measured twice a week (blinding) using a digital calliper and volumes (in mm3) were calculated with the formula 0.52 x length x width x width. Mice were treated when tumours reached a volume of 50 – 100 mm3 and randomized into different treatment groups based on their average tumour volumes. Mice were culled when tumours reached a mean diameter of 15 mm. IAP antagonist ASTX660 (A) (3 mM/injection), Emricasan (E) (1 mM/injection) and diABZI (1 µg/injection) were administered intratumorally (solubilised in Captisol), and PD-1 was administered intraperitoneally as indicated in Fig. 5, 6 and Supplementary Fig. 6, 7. For the dose optimisation of diABZI, mice were treated intratumorally with diABZI at 1 µg, 5 µg and 10 µg per injection (Supplementary Fig. 8). Based on their treatment responses, mice were categorised under complete response (tumour free for at least 60 days), partial response (tumour volume reduces to <100 mm3) and progression (no response). p values were calculated using Fisher’s exact test comparing responders (complete and partial) with non-responders. Mice that were tumour free for at least 2 months (cured mice) were rechallenged to assess their immune memory. Naïve and cured mice were injected with 5 x 104 BP962 organoids in the left 4th mammary fat pad and monitored as described above. To assess early changes in tumours post treatment, mice were given a single injection and tumours harvested post treatment as indicated in Fig. 5, 6. In Fig. 3, S3 and S4 spleens and tumours with the following tumour sizes, <5 x 5 mm, 6 to 10 mm and 15 x 15 mm, were harvested from mice for histology and immunohistochemical analysis. Tumour growth was monitored throughout the study, and no animal exceeded the ethically permitted tumour size of 15 x 15 mm.

Statistics & Reproducibility
Graphs and statistical analysis were performed using GraphPad Prism v9.5.1. The statistical analysis performed for each data set is described in the corresponding figure legend. Error bars indicate standard deviation (SD) or standard error of the mean (SEM), as indicated. All statistical tests were two-sided, and no statistical methods were used to predetermine sample size. No data were excluded from the analyses unless stated otherwise. Adjustment for multiple comparisons was performed unless indicated in the figure legends.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript by Clucas et al focused on the potential role necroptotic death may have in enhancing response of breast cancer to immunotherapy via checkpoint blockade. They developed murine breast cancer models to mimic human TNBC. Half of the manuscript was devoted to the characterization of their breast cancer organoids. They studied three of these organoid lines, one of which is immunologically hot whereas the other two were considered to be immunologically cold. These are very interesting models that can be used to study the response of breast cancers to immunotherapy. Overall, these are well conducted studies, but this reviewer has some concerns that should be addressed.\nMajor concerns:\n1. The main conclusion is that the BP962 organoid line when treated with a regimen to shift the response in tumor cells to necroptosis, there was better response to anti-PD1. While the regimen used is known to lead to necroptosis, the conclusion will be stronger if the authors can show a couple of things.\nA. If they use Mlkl-/- BP962 tumors, the enhanced response to anti-PD1 is lost. This will show that it is necroptosis in the tumor cells and not in the stromal cells that is having this effect. It is possible that AXT660/E is causing necroptosis in the stromal cells in the TME, and this may have some role. They were able to delete Mlkl in the 903 line. They should do this with the 962 line and conduct the same treatment experiments as in Fig 5e-g.\nB. Show that necroptosis is occurring within the tumor tissue for e.g., by staining tumor sections with anti-phospho-MLKL.\n2. Why are the organoids and E0771 not dying with TNF+AXT660? They should be undergoing RDA (Ripk1-dependent apoptosis). Is this due to the assay used, which is PI exclusion? Would authors see cleaved Casp8 or cleaved Casp3 if they perform western blots? ASTX660 appears to have some effect in combo with anti-PD1 in Fig 5C.\n3. Do the cold tumors, 903 and 487, benefit from combination of STING agonist, ASTX660, Emricasan and anti-PD1?\nMinor concerns:\n4. Authors kept referring to using Pembrolizumab in the text on page 13. They are not using pembrolizumab, which is specific for human PD1. They are using anti-mouse PD1 clone RMP1-14. This should be changed.\n5. Is TNF coming from the tumor or from the host immune cells that is driving the response? Because the tumors are able to die in vitro with just AXT660 and emricasan, they are likely producing TNF? Authors should discuss this.\n6. 903 and 487 can undergo necroptosis and seem to be better at undergoing necroptosis than 962 (Fig 4e), yet they don’t respond in vivo (Fig S6 c,f). This would suggest that necroptosis is not a determinant of the response to anti-PD1. Something else needs to also be present. Authors should temper their conclusions a bit – necroptosis is only helpful if other conditions are already in place. Something else is already present to make that tumor ‘hot’ to begin with and provoking necroptosis is useful only when those conditions are in place. This would also fit with their data in Fig 6 with the STING agonist.", "reviewer_2": "Clucas J, Fernando W and colleagues investigate the significance of necroptosis-mediated immune modulation in enhancing immunotherapy in triple-negative breast cancer. Authors use BLG-Cre; Brca1f/fp53+/- mouse model derived tumors to construct organoids. Subsequently, the authors validated that the organoids derived from different mice resembled human triple-negative breast cancer (TNBC) but also exhibited significant heterogeneity. The organoids were re-implanted into mice, stably recapitulating the histological and microenvironmental characteristics of the primary tumor. The authors constructed three mice cohorts for efficacy testing and analysis by selecting three organoid lines, two of which were inclined towards \"cold tumors\" and one towards \"hot tumors\". The authors validated that ASTX660-mediated immunogenic cell death enhanced the efficacy of immunotherapy in the \"hot tumor\" mice cohort, while it had limited effect on the \"cold tumor\" cohort. For \"cold tumors,\" the authors demonstrated that combining the induction of immunogenic cell death with the activation of innate immunity through a STING agonist was necessary to achieve significant therapeutic efficacy.\nOverall, the authors try to validate the known antitumor effects of necrotic apoptosis combined with immunotherapy by constructing mice cohorts. But my interest in this paper was limited by the following concerns.\n1. This paper is not innovative enough. The ability of BLG-Cre; Brca1f/fp53+/- mouse model to produce a heterogeneous but similar phenotype to human basal-type breast cancer has been demonstrated (PMID: 20804975). Moreover, the ability to stably reproduce the characteristics of primary tumors through organoid transfer in mice has been reported as a well-established method (PMID: 32690957). And the enhancing effect of necroptosis on immunotherapy, including the combination regimen of ASTX660 and immunotherapy used in the text, has also been reported (PMID: 31900279, PMID: 30393585 and PMID: 39560995).The \"hot tumors\" identified in the study lacks a positive control.\n2. The article's logic needs to be improved. Fig. 3J lacks strong relevance to the surrounding context, making it feel abrupt to the reader. Additionally, the introduction of the STING pathway seems forced, with no data to support the connection.\n3. The detection of CSF1 in Fig. 4D seems selective. There are many reasons for tumor-induced spleen enlargement; was there a thorough exclusion process to confirm that CSF1 is the primary cause?\n4. The abbreviations in the figures, such as SM and A/E, should be defined in the figure legend or in the main text.\n5. In the analysis of the therapeutic effects of ASTX660/pembrolizumab on the “cold” and “hot” tumor cohorts, it seems that the lack of statistical significance in “cold tumors” cohorts is due to the different number of mice in each cohort.\n6. The rigor of the conclusions stated in the article needs to be improved. For example, the sentence \"However, animals with less immune infiltrated tumors do not benefit from such treatments, even under necroptotic settings and double immune checkpoint blockade\" should be revised. The conclusion should state that there is some benefit, but it is not significant enough. The sentence \"First, we evaluated the ability of diABZI to drive STING signaling in BP903 and BP487 organoids in vitro. While treatment with diABZI readily triggered activation of IRF3 and interferon signaling (STAT1 activation) in both organoids, the STING agonist showed little cell death activity in vitro, alone or in combination with IAP antagonism\" also needs a more nuanced statement.\n7. For Fig. 6E and F, including a group with \"A/E\" would allow for a better comparison of the antitumor effects of the combination of diABZI and \"A/E.\"\n8. In Fig. 6O, the improvement in antitumor function should be assessed using flow cytometry to detect IFN-γ and perforin, which is better than measuring their mRNA levels.", "reviewer_3": "Summary of noteworthy results:\nThis study established tumor organoid lines from Brca1/p53 mouse models of human triple-negative breast cancer and generated orthotopic mammary tumors in immunocompetent mice.\nUsing this as a platform, they identified one tumor organoid line with both high immune infiltration and high expression of RIPK1, a mediator of apoptosis/necroptosis cell death, and used it to demonstrate the efficacy of RIPK1-induced immunogenic cell death. Specifically, double treatment with a cell-death-inducing agent (ASTX660, an IAP antagonist) and anti-PD1 (pembrolizumab) delayed BP962 tumor progression, whereas triple treatment (adding emricasan, a pan-caspase inhibitor) to promote necroptosis over apoptosis further enhanced the anti-tumor effect, leading to complete cure of the mice and immune memory against subsequent re-inoculation of tumor cells. The treated tumors showed increased T cell and decreased macrophage infiltration. In contrast. the same anti-tumor effect was not seen in tumors induced from two other organoid lines with lower RIPK1 levels and less immune infiltration. The authors therefore proposed RIPK1 as a biomarker for necroptosis-based enhancement of immune checkpoint blockade therapy in immune-infiltrated tumors.\nThe authors further showed that immune-cold tumors (derived from two organoid lines, BP903 and BP487) can be sensitized to necroptosis-induced cell death (ASTX660/emricasan) by cGAS-STING activation (via diABZI) that activates immune infiltration through viral mimicry. The treatment reshaped the tumor immune microenvironment with more effector lymphocytes and fewer immunosuppressive cells.\nOverall assessment:\nThis study provides interesting and exciting findings that suggest a new potential approach to enhance immunotherapy efficacy for patients with triple-negative breast cancer. This is not the first study to use Brca1/p53-mutant mammary tumor organoids and orthotopic transplantation to study drug response and resistance (see http://pubmed.ncbi.nlm.nih.gov/29256493/ for example). However, this study used these organoids in an immunocompetent host setting, and the findings of the anti-tumor effect of necroptosis in combination with immune-modulating treatment are novel and promising.\nThe methodology, analysis, and interpretation are sound. However, more data are needed to strengthen the current conclusion, which is drawn based on the comparison between only one single tumor organoid line (BP962, with high RIPK1 and high immune infiltration) versus two other lines (RIPK-low and/or poor immune infiltration). The experiments should be repeated on additional tumor organoid line(s) with a similar profile to BP962 to establish that the findings are generalizable.\nMajor comments:\n- Does other tumor organoid line(s) with similar RIPK1 expression and immune infiltration to BP962 show the same sensitivity to the combination treatment(s) using ASTX660/pembrolizumab or ASTX660/pembrolizumab/E treatment?\n- Is RIPK1 necessary and sufficient for the anti-tumor effects of ASTX660/pembrolizumab or ASTX660/pembrolizumab/E treatment in immune-infiltrated tumors? For example, does knockdown/knockout of RIPK1 in a RIPK1-high tumor organoid line (e.g. BP962) abolish the anti-tumor effects of such combo treatment(s)? Alternatively, can overexpression of RIPK1 in RIPK1-low/immune high tumors enable the anti-tumor effect of such combination treatment(s)?\n- What drives the heterogenous expression of RIPK1 in these primary tumors and their derivative tumor organoid lines? Can the authors provide data to suggest a potential mechanism, or at least discuss some speculation in the text?\n- It would make the paper even stronger if the authors could provide complementary data from humans to reinforce at least some of their conclusions drawn in mouse models.\nMinor points:\n- “Notably, the individual organoid lines remained stable, and their respective TOs were highly reproducible within each line, as evidenced by mRNA analysis and mutational profiling (Fig. 2e,f)”. Figure 2f showed CNAs present in primary tumors and absent in organoids and vice versa, potentially due to the expansion of clonal subpopulation and/or acquired CNA in culture. The authors should modify their language about stability and reproducibility to reflect these differences between primary tumors and organoid lines.\n- Figure 2h: Scale bars representing different sizes should be more clearly labeled.\n- Figure 3a-b: Are the “normal mammary glands” analyzed after the lymph nodes have been removed? The author should clarify in the figure legend and/or methods section.\n- Figure 3j: genes should be labeled in the heatmaps.\n- Figure S5c schematic indicates that cells were stained with PI and Hoechst, whereas the data panels (Fig. 4e,g,h,i, and S5d) show PI and DAPI. Please clarify."}, "author_response": "Response to reviewers comments\nNature Communica.ons manuscript NCOMMS-25-01910\nWe would like to thank you and the referees for the construc4ve and helpful comments on our\nmanuscript. We were delighted to see that the reviewers thought that our study was well performed.\nWe have followed the reviewers’ sugges4ons and have considerably expanded our manuscript with\nextensive new experiments (using an addi4onal 430 animals), which have corroborated our exis4ng\ndata and significantly strengthened our ms. The new data includes 53 new panels, which we have\nincorporated into our response to reviewer’s comments for ease of access. The data of these addi4onal\nexperiments have been fully embedded into our revised ms. Addi4onal new panels have been framed\nwith red boxes in the figures of our revised manuscript, for ease of access.\nOverall, our new data have addressed the following points:\n1. We provide new evidence demonstrating that necroptosis enhances treatment responses\nboth within tumour cells (BP962Ripk1-KO and BP962Mlkl-KO) and in the tumour microenvironment\n(Mlkl-/- mice) (new Fig. 7 and Suppl. Fig. S10).\n2. We now show that necroptosis indeed occurs within the tumour tissue (new Suppl. Fig.\nS6A).\n3. We clarify why cells do not undergo death in response to TNF/ASTX660 treatment (new\nSuppl. Fig. S5E–H).\n4. We provide additional data evaluating whether “cold” tumours benefit from combined\nSTING agonist/ASTX660/emricasan and anti-PD-1 treatment (new Suppl. Fig. S8D–L).\n5. We introduce an additional tumour model that closely recapitulates the BP962 phenotype\n(new Suppl. Fig. S6B–G).\n6. We increased animal numbers in cohorts with weaker phenotypes to assess statistical\nsignificance (new Suppl. Fig. S7A–G).\n7. We incorporated additional controls (new Fig. 6D–J) and extended immune-cell\ncharacterisation using FACS analysis (new Fig. 6O and Suppl. Fig. S9).\n8. We addressed all remaining reviewer comments, revising the text for clarity and precision\nthroughout. We further emphasise and clarify the novelty and conceptual advances of our\nstudy.\nPlease find below a point-by-point response to the reviewers’ comments, with the reviewers’\ncomments in blue boxes and our response in ‘plain text’.\nFurther, we are attaching a private, Reviewer-Only link to all the DNA and RNA data sets:\nh_ps://dataview.ncbi.nlm.nih.gov/object/PRJNA1211523?reviewer=dv9lauhkbtjablad5pvegh6c5\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThis manuscript by Clucas et al focused on the potential role necroptotic death may have in\nenhancing response of breast cancer to immunotherapy via checkpoint blockade. They developed\nmurine breast cancer models to mimic human TNBC. Half of the manuscript was devoted to the\ncharacterization of their breast cancer organoids. They studied three of these organoid lines, one of\nwhich is immunologically hot whereas the other two were considered to be immunologically cold.\nThese are very interesting models that can be used to study the response of breast cancers to\nimmunotherapy. Overall, these are well conducted studies, but this reviewer has some concerns that\nshould be addressed.\nMajor concerns:\n1. The main conclusion is that the BP962 organoid line when treated with a regimen to shift the\nresponse in tumor cells to necroptosis, there was better response to anti-PD1. While the regimen\nused is known to lead to necroptosis, the conclusion will be stronger if the authors can show a\ncouple of things.\nA. If they use Mlkl-/- BP962 tumors, the enhanced response to anti-PD1 is lost. This will show that it\nis necroptosis in the tumor cells and not in the stromal cells that is having this effect. It is possible\nthat AXT660/E is causing necroptosis in the stromal cells in the TME, and this may have some role. They were able to delete Mlkl in the 903 line. They should do this with the 962 line and conduct the\nsame treatment experiments as in Fig 5e-g.\nB. Show that necroptosis is occurring within the tumor tissue for e.g., by staining tumor sections\nwith anti-phospho-MLKL.\n1A: The role of Mlkl in tumour cells vs stroma.\nThis is an excellent point, which we have now addressed comprehensively in the revised manuscript\nwith an addi4onal new Figure (new Fig. 7).\nWe fully agree that elucida4ng how immunogenic cell death is ini4ated within the tumour, and\ndetermining whether this response originates from cancer cells or stromal components, is of key\nmechanis4c importance.\nTo directly address this, we implemented a two-pronged experimental strategy (new Fig. 7 and Suppl.\nFig. S10):\n1. Tumour: We generated a BP962 tumour organoid line deficient in MLKL (BP962Mlkl-KO) and\ncompared its treatment response to that of isogenic controls (new Fig. 7D-G). Addi4onally, we\nalso assessed the role of RIPK1 (new Fig. 7A-C).\n2. Stroma: We evaluated the treatment effect in vivo using recipient mice that were either wild-\ntype (WT) or Mlkl-/- (new Fig. 7H,I).\n1. BP962Mlkl-KO: To directly test the requirement of MLKL in BP962 cancer cells, we generated BP962Mlkl-\nKO organoid lines using Cas9/CRISPR-mediated genome editing. Successful deletion of MLKL protein\nand resulting resistance to necroptosis were confirmed by Western blot and functional analysis (new\nSuppl. Fig. S10A,B), a_ached below. Compared with parental BP962 organoids, BP962Mlkl-KO cells\nformed tumours at a slightly reduced growth rate in the absence of treatment, resul4ng in delayed\nmortality in tumour-bearing mice (new Suppl. Fig. S10C,D). Nevertheless, upon treatment, BP962Mlkl-\nKO tumours significantly responded to ASTX660/EC. However, addition of aPD-1 did not provide any\nfurther survival benefit beyond ASTX660/EC alone (new Fig. 7E-G). This contrasts with necroptosis-\nproficient BP962 tumours, where aPD-1 co-treatment enhances the survival benefit of ASTX660/EC\n(Fig. 5E-G), suggesting that MLKL-dependent necroptosis contributes to the immunological\npotentiation of this combination therapy.\n2. The role of stromal cell necroptosis: To assess the contribution of stromal necroptosis to therapy\nresponse, BP962 organoids were transplanted into Mlkl-/- recipient mice. While ASTX660/EC/aPD-1\ntreatment produced a measurable effect, its efficacy was significantly reduced in Mlkl-/- hosts\ncompared to WT animals, with no surviving animals observed in the Mlkl-/- group (compare new Figure\n7H,I with previous Fig. 5E-G (WT host)).\nTogether, these findings indicate that necroptosis within stromal cells plays a critical role in mediating\nthe therapeutic effect. In addition, necroptosis of tumour cells, and the release of tumour-associated\nantigens and DAMPs, appears essential for a response to aPD-1. Therefore, necroptosis of both\nstromal and tumour compartments is required to elicit a fully effective anti-tumour immune response.\nNew Fig. 7. Cancer cell intrinsic and tumour micro-environmental necroptosis contributes to the an;-tumour\neffect. (A) Tumour growth curves of BP962 Ripk1KO in C57BL/6J mice: Control (n = 8), A/E (n=6) and A/E/aPD-1\n(n=9). Each line represents one animal and thick lines represent average tumour growth. Curves represent one\nindependent experiment. (B) Kaplan-Meier survival curves of BP962Ripk1-KO TO tumour-bearing animals. (C) Pie\ncharts depicRng the proporRon of mice, which progressed, parRally responded, or fully responded to the\nindicated treatments. (D) SchemaRc representaRon depicRng the experimental setup to evaluate the\ncontribuRon of tumour versus stromal necroptosis. The treatment regimen is depicted on the right. (E) Tumour\ngrowth curves of BP962Mlkl-KO TOs: Control (n = 8), A/E (n = 12) and A/E/αPD-1 (n = 12). Each line represents one\nanimal and thick lines represent average tumour growth. Curves represent one independent experiment. (F)\nKaplan-Meier survival curves of BP962Mlkl-KO tumour-bearing animals, treated as in (D). (G) Pie charts depicRng\nthe proporRon of mice from (F), which progressed, parRally responded, or fully responded to the indicated\ntreatments. (H) Tumour growth curves of BP962 TOs grown in Mlkl-/- animals (see Fig. 5E-G for WT control).\nTreatments: Control (n = 6) and A/E/αPD-1 (n = 9). Each line represents one animal and thick lines represent\naverage tumour growth. Curves represent two independent experiments. (I) Kaplan-Meier survival curves of\nBP962 tumour-bearing Mlkl-KO animals, treated as in (D). A=ASTX660; E=emricasan;\nNew Suppl. Fig. S10. Genera;on and characterisa;on of BP962RIPK1-KO and BP962Mlkl-KO tumours. (A) Western\nblot validaRon of CRISPR-mediated RIPK1 and MLKL deleRon in BP962 organoids. (B) Cell death assay confirming\nnecroptosis deficiency in BP962MlklKO organoids. (C) Tumour growth comparison of the indicated organoid lines\nin C57BL/6 mice. (D) Kaplan-Meier survival curves of the indicated tumour-bearing animals from (C).\n1B. Show that necroptosis is occurring within the tumor tissue for e.g., by staining tumor sections with\nanti-phospho-MLKL.\nWe followed the reviewer’s suggestion and attempted to detect p-MLKL in tumour tissue. To this end,\nwe analysed tumour lysates from treated (n = 6) and untreated (m = 4) mice by western blotting. As\nshown in new Suppl. Fig. S6A, clear induction of p-RIPK1 and p-MLKL was detected 24 hours after\nASTX660/EC treatment, confirming necroptosis activation in the tumour. Together with the data\nshown in new Fig. 7, these findings support the conclusion that ASTX660/EC indeed induces\nnecroptosis.\nWe also a_empted to detect p-MLKL in tissue sections by IHC. However, despite extensive\noptimisation to make the anti-phospho-MLKL antibody (CST37333) work in tissue sections by IHC, we\nwere unfortunately unable to detect a specific signal in control samples.\nNew Suppl. Figure S6A. ASTX660/EC induces necroptosis in the tumour. (A) Western blot analysis of lysates\nfrom BP962 tumour bearing-C57BL/6J mice, treated with captisol or ASTX660/EC. Tumours were harvested 24\nhrs after treatment. Each lane represents an individual tumour (T1-10).\n2. Why are the organoids and E0771 not dying with TNF+AXT660? They should be undergoing RDA\n(Ripk1-dependent apoptosis). Is this due to the assay used, which is PI exclusion? Would authors see\ncleaved Casp8 or cleaved Casp3 if they perform western blots? ASTX660 appears to have some\neffect in combo with anti-PD1 in Fig 5C.\nWe thank the reviewer for raising this point.\nWe have addressed this experimentally by performing complementary viability and cell death assays.\nDuring the characterisa4on of the organoids, we carried out CellTiter-Glo (CTG) assays to assess\nviability, as well as ImageXpress/Celigo (PI/Hoechst) assays to evaluate cell death.\nTreatment of organoids with ASTX660, either alone or in combina4on with TNF, did not result in a\nsignificant reduc4on in viability. However, as the CTG assay has limited sensi4vity, we cannot exclude\nthe possibility that low-level apoptosis occurred but remained below the detec4on threshold of PI-\nbased methods. In addi4on, it is worth no4ng that caspase-8/cFLIP heterodimers can suppress RIPK1-\ndependent cell death downstream of IAP antagonists by cleaving RIPK1, which could contribute to the\nlimited cytotoxic response observed under these condi4ons. Accordingly, western blot analysis of\ntreated organoids indicates that TNF/ASTX660 treatment indeed results in detectable caspase-8\nactivation and RIPK1 cleavage (new Suppl. Fig. S5E-H). This could either result in low level apoptosis\ninduction or caspase-8-mediated suppression of RIPK1-dependent apoptosis.\nNew Suppl. Fig. S5E-H. Western blot analysis of treated organoids and EO771 cells. (E-H) Western blot\nanalysis of lysates from the indicated cells, treated with the respective agents.\n3. Do the cold tumors, 903 and 487, benefit from combination of STING agonist, ASTX660, Emricasan\nand anti-PD1?\nWe have expanded our experiments to treatment combination.\nInterestingly, while STING agonist treatment “heated up” BP903 and BP487 tumours and enhanced\nthe anti-tumour efficacy of ASTX660/EC, the addition of αPD-1 did not confer further therapeutic\nbenefit (New Suppl. Fig. S8). These findings suggest that, although STING activation effectively\nincreases tumour kill, this enhancement alone is insufficient to sustain or amplify the immune\nresponse when combined with αPD-1 therapy.\nNew Suppl. Fig. S8D-L. Effect of aPD-1 on A/E/STING treatment. (D) SchemaRc representaRon depicRng the\ntreatment regimen. (E) Tumour growth curves of BP903 TOs: Control (n = 7), diABZI/E (n = 8), diABZI/αPD-1 (n =\n8), diABZI/A/E (n = 10) and diABZI/A/E/aPD-1 (n = 10). Each line represents one animal and thick lines represent\naverage tumour growth. Curves represent one independent experiment. (F) Tumour growth kineRcs (days 0-28)\nof mice treated as in (D), measured by the area under the curve (AUC). Each point represents the AUC of\nindividual mice from (E). (G) Kaplan-Meier survival curves of BP903 TO tumour-bearing animals, treated as in (D).\n(H) Pie charts depicRng the proporRon of mice from (B), which progressed, parRally responded, or fully\nresponded to the indicated treatments. (I) Tumour growth curves of BP487 TOs: Control (n = 9), diABZI/A/E (n =\n9) and diABZI/A/E/aPD-1 (n = 9). Each line represents one animal and thick lines represent average tumour\ngrowth. Curves represent one independent experiment. (J) Tumour growth kineRcs (days 0-25) of mice treated\nas in (D), measured by the area under the curve (AUC). Each point represents the AUC of individual mice from\n(F). (K) Kaplan-Meier survival curves of BP487 TO tumour-bearing animals, treated as in (D). (L) Pie charts\ndepicRng the proporRon of mice from (K), which progressed, parRally responded, or fully responded to the\nindicated treatments.\nMinor concerns:\n4. Authors kept referring to using Pembrolizumab in the text on page 13. They are not using\npembrolizumab, which is specific for human PD1. They are using anti-mouse PD1 clone RMP1-14.\nThis should be changed.\nWe apologise for this oversight. This has been corrected accordingly.\n5. Is TNF coming from the tumor or from the host immune cells that is driving the response? Because\nthe tumors are able to die in vitro with just AXT660 and emricasan, they are likely producing TNF?\nAuthors should discuss this.\nWe have expanded our revised ms to discuss the potential source of TNF.\nWe now state in the discussion:\nOur data raise an important question regarding the cellular origin of TNF that fuels the anti-tumour\nresponse upon IAP inhibition. In vitro, BP962 tumour organoids undergo cell death when treated with\nASTX660 and emricasan, even in the absence of immune cells, suggesting that tumour cells themselves\ncan produce TNF in an autocrine manner. This is consistent with previous reports demonstrating that\nIAP antagonists can trigger tumour-intrinsic TNF production, creating a self-amplifying death loop\nthrough RIPK1 activation. However, in vivo, immune-derived TNF is likely to play an additional and\nsignificant role. CD8⁺ T cells and myeloid cells are well-established sources of TNF in the tumour\nmicroenvironment, particularly after checkpoint blockade. Given that αPD-1 enhances T-cell\nactivation, the therapeutic effect of ASTX660/αPD-1 is likely reinforced by TNF derived from infiltrating\nimmune cells. The observation that αPD-1 improves efficacy only in necroptosis-competent tumours\nfurther supports the notion that immune-derived TNF amplifies inflammatory cell death and cross-\npriming in vivo. Together, these findings suggest a dual-source model in which tumour-intrinsic TNF\nmay initiate RIPK1-dependent immunogenic cell death, while immune-cell-derived TNF further\namplifies this response within the tumour microenvironment. Future studies using cell-type-specific\nTNF perturbation will be required to dissect the relative contribution of tumour- versus immune-\nderived TNF to treatment efficacy.\n6. 903 and 487 can undergo necroptosis and seem to be better at undergoing necroptosis than 962\n(Fig 4e), yet they don’t respond in vivo (Fig S6 c,f). This would suggest that necroptosis is not a\ndeterminant of the response to anti-PD1. Something else needs to also be present. Authors should\ntemper their conclusions a bit – necroptosis is only helpful if other conditions are already in place.\nSomething else is already present to make that tumor ‘hot’ to begin with and provoking necroptosis\nis useful only when those conditions are in place. This would also fit with their data in Fig 6 with the\nSTING agonist.\nWe fully agree with the reviewer’s insightful comment. This is indeed an important point, and we are\nactively investigating how stromal and tumour compartments communicate to establish a tumour-\nspecific microenvironment.\nInterestingly, we observed a strong correlation between RIPK1 expression levels and the composition\nof the tumour microenvironment. BP962-derived tumours exhibit high RIPK1 expression, whereas\nBP487 and BP903 tumours express much lower levels. However, in the corresponding organoids in\nvitro, all three lines display comparable RIPK1 expression, indicating that these differences arise only\nafter engraftment and tumour formation in vivo.\nThese findings suggest that the reconstituted tumours faithfully recapitulate key features of the\noriginal “patient” tumours. Although the precise factors driving this adaptation remain unclear, it is\nevident that the stroma is remodelled in a tumour-intrinsic manner according to the organoid’s\ngenetic and epigenetic profile. BP962 tumours develop an immune-rich microenvironment with dense\nmacrophage infiltration and direct macrophage-tumour interactions, whereas BP903 and BP487\nrepresent “cold” tumour phenotypes, with macrophages restricted to connective tissue regions or\n“tumour highways.”\nImportantly, loss of key regulatory control points, such as through inactivation of IAPs or caspase-8\nactivity, can prime cancer cells for necroptosis. However, in the absence of a microenvironment rich\nin TNF and interferon, necroptosis cannot be effectively engaged. This suggests that additional factors,\nsuch as the availability of cytokine ligands and interferon-driven upregulation of MLKL, which\nsensitises cells to TNF-mediated cytotoxicity, are also required.\nOur data further support the notion that stromal necroptosis contributes more prominently to the\nanti-tumour response than tumour-cell necroptosis alone, although both are required. As\nmacrophages are the principal source of TNF within the tumour, their abundance and spatial\ndistribution likely determine the extent of necroptosis activation and, consequently, responsiveness\nto immune checkpoint inhibition (ICI).\nConsistent with this, the E0771 model closely mirrors the BP962 phenotype (see reviewer 3, point 1\nbelow), displaying a similarly macrophage-rich microenvironment and responding even more robustly\nto combined ASTX/EC/αPD-1 therapy—likely reflecting its greater susceptibility to necroptosis.\nWe have expanded our manuscript to discuss this point.\nReviewer #2 (Remarks to the Author):\nClucas J, Fernando W and colleagues investigate the significance of necroptosis-mediated immune\nmodulation in enhancing immunotherapy in triple-negative breast cancer. Authors use BLG-Cre;\nBrca1f/fp53+/- mouse model derived tumors to construct organoids. Subsequently, the authors\nvalidated that the organoids derived from different mice resembled human triple-negative breast\ncancer (TNBC) but also exhibited significant heterogeneity. The organoids were re-implanted into\nmice, stably recapitulating the histological and microenvironmental characteristics of the primary\ntumor. The authors constructed three mice cohorts for efficacy testing and analysis by selecting\nthree organoid lines, two of which were inclined towards \"cold tumors\" and one towards \"hot\ntumors\". The authors validated that ASTX660-mediated immunogenic cell death enhanced the\nefficacy of immunotherapy in the \"hot tumor\" mice cohort, while it had limited effect on the \"cold\ntumor\" cohort. For \"cold tumors,\" the authors demonstrated that combining the induction of\nimmunogenic cell death with the activation of innate immunity through a STING agonist was\nnecessary to achieve significant therapeutic efficacy.\nOverall, the authors try to validate the known antitumor effects of necrotic apoptosis combined with\nimmunotherapy by constructing mice cohorts. But my interest in this paper was limited by the\nfollowing concerns.\n1. This paper is not innovative enough. The ability of BLG-Cre; Brca1f/fp53+/- mouse model to\nproduce a heterogeneous but similar phenotype to human basal-type breast cancer has been\ndemonstrated (PMID: 20804975). Moreover, the ability to stably reproduce the characteristics of\nprimary tumors through organoid transfer in mice has been reported as a well-established method\n(PMID: 32690957). And the enhancing effect of necroptosis on immunotherapy, including the\ncombination regimen of ASTX660 and immunotherapy used in the text, has also been reported\n(PMID: 31900279, PMID: 30393585 and PMID: 39560995).The \"hot tumors\" identified in the study\nlacks a positive control.\nWe thank the reviewer for their constructive feedback and believe that by addressing all comments\nby all reviewers, we have substantially improved our manuscript and clarified the novelty of our work.\nWe agree that both the BLG-Cre; Brca1f/f; p53+/- model (PMID: 20804975) and organoid-based\ntumour recons4tu4on methods (PMID: 32690957) are established in the field. However, the novelty\nof our study lies in integra4ng these systems to generate a diverse organoid biobank from Brca1/p53-\ndeficient tumours and in func4onally linking tumour-intrinsic necropto4c suscep4bility to the\ncomposi.on and immune ac.va.on state of the resul.ng tumour microenvironment in vivo.\nOur project was initiated with the goal of improving therapeutic strategies of breast cancer patients.\nA major limitation in the field is that much of the current data, including that in breast cancer research,\nrelies heavily on established cell lines that do not accurately recapitulate the complexity of primary\ntumours. In Molyneux et al., 2010 (PMID: 20804975), the authors demonstrated that Brca1-associated\nbasal-like breast cancers arise from luminal progenitors rather than basal stem cells. Loss of Brca1/p53\nin these cells produced tumours that phenotypically copy human Brca1/p53-deficient cancers. Building\non these findings, our aim was to establish organoid lines from Brca1/p53-deficient tumours that more\nfaithfully model human breast cancer. Further our aim was to develop a corresponding in vivo “mouse\nclinic” placorm to address heterogeneity and explore therapeu4c vulnerabili4es.\nWe worked closely with Ma_ Smalley, a co-author of our study, who originally developed the\nBrca1/p53 mouse model. Notably, organoid lines were not established from these tumours in the\noriginal study (PMID: 20804975). Thus, our work represents the first systemic deriva4on and\ncharacteriza4on of such organoids.\nThe development of organoid protocols from diverse tumour types has transformed the field, bringing\npreclinical models closer to human disease complexity. The study by Padmanaban et al., 2020 (PMID:\n32690957) provided a valuable step-by-step protocol for isolating organoids from murine and human\ntumours, preserving tumour heterogeneity and enabling studies of tumour biology and drug\nresponses. We adapted and refined such approaches to generate organoids from our Brca1/p53\nmodel. Unlike MMTV-PyMT mouse mammary tumour model used by Padmanaban and colleagues,\nwhich has been criticized for its limited resemblance of human breast cancer, our Brca1/p53 system\ntargets tumour suppressor loss and recapitulate the genetic and phenotypic diversity observed in\nhuman Brca1-deficient tumours. This inherent heterogeneity poses technical challenges for organoid\nisolation and maintenance, which we described in detail to provide a resource for other researchers.\nOur goal was both to describe this complexity and to investigate the mechanism that drives\nimmunogenic cell death in tumours derived from these organoids, elucidating why certain tumours\nrespond to necroptotic stimuli while other do not.\nPrevious studies using IAP antagonists such ASTX660 (PMID: 31900279, PMID: 30393585) have shown\npromising an4tumour results. The first-in-human study of ASTX660 (PMID: 31900279) established\nsafety, pharmacokine4cs, and cIAP1 target engagement across heterogeneous human cancers. We\nfound no discrepancies with these findings. Indeed, we are currently conduc4ng phase I clinical trial\ncombining ASTX660 with pembrolizumab in pa4ents with breast and other cancers, with data now\nsubmi_ed for publica4on. Such clinical inves4ga4ons are essen4al to advancing this therapeu4c\nstrategy in the complex context of human disease.\nIn our manuscript, we demonstrate that inducing necroptosis in gene4cally and phenotypically\nheterogeneous breast tumours does not uniformly result in an immunogenic response. Using gene4c\nmodels, we show that the outcome of necropto4c signalling is largely determined by the tumour\nmicroenvironment that is driven by the tumour cells. Iden4fying which tumours are likely to respond\nto necropto4c therapies is therefore cri4cal for transla4ng this approach into clinical benefit, and to\nour knowledge, has not yet been addressed elsewhere.\nAs the reviewer correctly noted, necroptosis induc4on in cancer has been previously demonstrated.\nHowever, several of these studies-including the above men4oned PMID: 39560995-employed\ntransgenic systems in which RIPK3 ac4va4on (oven driven by ar4ficial RIPK3 oligomeriza4on and not\npathway driven) within cancer cells directly triggers necroptosis. While this approach effec4vely\ninduces necroptosis, we believe that true immunogenicity requires engagement of upstream innate\nimmune receptors to induce DAMPs to ini4ate a produc4ve an4tumour immune response.\nFurthermore, our data reveal that effec4ve therapy must target not only tumour cells but also the\nsurrounding stroma, as stromal necroptosis plays a pivotal role in shaping the overall immune\nresponse.\n2. The article's logic needs to be improved. Fig. 3J lacks strong relevance to the surrounding context,\nmaking it feel abrupt to the reader. Additionally, the introduction of the STING pathway seems\nforced, with no data to support the connection.\nWe thank the reviewer for this comment and have revised the text to clarify the logic linking Fig. 3J to\nthe surrounding context. As demonstrated in our rebuttal, the stromal compartment is a key\ndeterminant of the response to necroptosis-based therapy. Figure 3 now provides a more coherent\nframework for interpreting this complexity.\nSpecifically, Figure 3J depicts the transcrip.onal ac.va.on of NF-κB and IFN pathways across three\ntumour types. These signatures are known to correlate with improved responsiveness to immune-\ncheckpoint blockade-based therapies as both these signalling pathways influence bystander killing of\ntumour cells. Accordingly, elevated NF-kB and IFN pathways correlates with improved responses to\nnecroptosis and we believe that this observation represents an important component of the overall\nmechanism.\nThe inclusion of the STING pathway was not arbitrary but mechanistically driven. Its activation is\nknown to enhance NF-κB and type I IFN signalling, pathways already implicated by our data (Fig. 3J).\nHowever, as shown in our additional experiments (new Suppl. Fig. S8), STING agonism did not\ngenerate a durable immune response when combined with αPD-1, suggesting that additional\ncontextual factors, such as the spatial distribution of macrophages, are essential for achieving\nsustained tumour control.\nTogether, these clarifications strengthen the logical connection between Fig. 3J and the broader\nnarrative of our study.\nNew Suppl. Fig. S8D-L. Effect of aPD-1 on diABZI/A/E treatment. (D) SchemaRc representaRon depicRng the\ntreatment regimen. (E) Tumour growth curves of BP903 TOs: Control (n = 7), diABZI/E (n = 8), diABZI/αPD-1 (n =\n8), diABZI/A/E (n = 10) and diABZI/A/E/aPD-1 (n = 10). Each line represents one animal and thick lines represent\naverage tumour growth. Curves represent one independent experiment. (F) Tumour growth kineRcs (days 0-28)\nof mice treated as in (D), measured by the area under the curve (AUC). Each point represents the AUC of\nindividual mice from (E). (G) Kaplan-Meier survival curves of BP903 TO tumour-bearing animals, treated as in (D).\n(H) Pie charts depicRng the proporRon of mice from (E), which progressed, parRally responded, or fully\nresponded to the indicated treatments. (I) Tumour growth curves of BP487 TOs: Control (n = 9), diABZI/A/E (n =\n9) and diABZI/A/E/aPD-1 (n = 9). Each line represents one animal and thick lines represent average tumour\ngrowth. Curves represent one independent experiment. (J) Tumour growth kineRcs (days 0-25) of mice treated\nas in (D), measured by the area under the curve (AUC). Each point represents the AUC of individual mice from\n(I). (K) Kaplan-Meier survival curves of BP487 TO tumour-bearing animals, treated as in (D). (L) Pie charts\ndepicRng the proporRon of mice from (K), which progressed, parRally responded, or fully responded to the\nindicated treatments.\n3. The detection of CSF1 in Fig. 4D seems selective. There are many reasons for tumor-induced\nspleen enlargement; was there a thorough exclusion process to confirm that CSF1 is the primary\ncause?\nWe thank the reviewer for raising this point. We are actively pursuing this line of investigation, and\ncurrent evidence supports a central role for macrophages in this context. Our data indicate that BP962\ntumour cells secrete soluble factors that recruit macrophages and promote epithelial-to-\nmesenchymal transition (EMT). Although this represents an ongoing and separate study, our\npreliminary results suggest that CSF1 is among the key cytokines contributing to macrophage\nrecruitment and activation within the tumour microenvironment.\nWhile we have not yet formally excluded all alternative mechanisms underlying tumour-induced\nspleen enlargement, our current findings point to CSF1-driven macrophage expansion as a potential\ncontributing factor. We have amended our manuscript indicating that additional tumour-related\nmechanisms may also contribute to spleen enlargement.\n4. The abbreviations in the figures, such as SM and A/E, should be defined in the figure legend or in\nthe main text.\nAll abbrevia4ons used in the figures are now clearly defined in the corresponding figure legends for\nclarity and consistency.\n5. In the analysis of the therapeutic effects of ASTX660/pembrolizumab on the “cold” and “hot”\ntumor cohorts, it seems that the lack of statistical significance in “cold tumors” cohorts is due to the\ndifferent number of mice in each cohort.\nWe thank the reviewer for this valuable comment and have carefully considered the statistical aspects\nraised. In designing our experiments, we aimed to balance the ethical use of animals with the need\nfor robust and interpretable data. The number of mice per group was initially sufficient to detect large\ntreatment effects; however, given that the observed responses were more modest, we have now\nincreased the cohort size in both control and ASTX/EC/αPD-1 treatment groups for the BP903 and\nBP487 models.\nIn the revised dataset (new Suppl. Fig. 7A-G, see below), a small but statistically significant treatment\neffect was observed in both tumour types. Consistent with our earlier findings, BP487 tumours\nexhibited a more pronounced response than BP903 tumours, which remained largely refractory.\nImportantly, no complete regressions were detected in either cohort, in contrast to BP962, confirming\nthat therapeutic efficacy in these models is inherently limited.\nWe also evaluated αPD-1 in combination with STING agonist treatment, but this failed to further\nimprove outcomes. Together, these data reinforce that BP903 and BP487 tumours differ intrinsically\nin their susceptibility to necroptosis-based therapies, consistent with their underlying tumour\nmicroenvironmental context.\nNew Suppl Fig. S7A-G. Effect of αPD-1 on ASTX660/E treatment of BP487 Tos and BP903 TOs. (A) SchemaRc\nrepresentaRon depicRng the treatment regimen of BP903 tumour bearing-C57BL/6J mice. (B) Tumour growth\ncurves of BP903 TOs: Control (n = 15), ASTX660/E (n=6), αPD-1 (n=6) and ASTX660/E/αPD-1 (n=17). Each line\nrepresents one animal and thick lines represent average tumour growth. Curves represent two independent\nexperiments. (C) Kaplan-Meier survival curves of BP903 TO tumour-bearing animals, treated as in (A). (D) Pie\ncharts depicRng the proporRon of mice from (B), which progressed, parRally responded, or fully responded to\nthe indicated treatments. (E) Tumour growth curves of BP487 TOs: Control (n = 15), ASTX660/E (n=7), αPD-1 (n=7)\nand ASTX660/E/αPD-1 (n=17). Each line represents one animal and thick lines represent average tumour\ngrowth. Curves represent two independent experiments. (F) Kaplan-Meier survival curves of BP487 TO tumour-\nbearing animals, treated as in (A). (G) Pie charts depicRng the proporRon of mice from (E), which progressed,\nparRally responded, or fully responded to the indicated treatments.\n6. The rigor of the conclusions stated in the article needs to be improved. For example, the sentence\n\"However, animals with less immune infiltrated tumors do not benefit from such treatments, even\nunder necroptotic settings and double immune checkpoint blockade\" should be revised. The\nconclusion should state that there is some benefit, but it is not significant enough. The sentence\n\"First, we evaluated the ability of diABZI to drive STING signaling in BP903 and BP487 organoids in\nvitro. While treatment with diABZI readily triggered activation of IRF3 and interferon signaling\n(STAT1 activation) in both organoids, the STING agonist showed little cell death activity in vitro,\nalone or in combination with IAP antagonism\" also needs a more nuanced statement.\nWe would like to thank the reviewer for highlighting these suggestions. We have modified our ms\naccordingly.\n7. For Fig. 6E and F, including a group with \"A/E\" would allow for a better comparison of the\nantitumor effects of the combination of diABZI and \"A/E.\"\nWe have followed the reviewer’s suggestion and have updated our ms to include the A/E treatment\ngroup (new Fig. 6D-J).\nNew Fig. 6D-J. Effect of STING-driven necroptosis on BP487 and BP903 Tos. (D) SchemaRc representaRon\ndepicRng the treatment regimen of BP487 and BP903 tumour bearing-C57BL/6J mice. (E) Tumour growth curves\nof BP487 TOs, treated as indicated. Control (n=12), diABZI (n=9), ASTX660/E (n=7), diABZI/ASTX660 (n=9),\ndiABZI/E (n=10) or diABZI/ASTX660/E (n=6). Each line represents one animal and thick lines represent average\ntumour growth. Curves represent one independent experiment. (F) Kaplan-Meier survival curves of BP487\ntumour-bearing animals, treated as in (D). (G) Pie charts depicRng the proporRon of mice from (e), which\nprogressed, parRally responded, or fully responded to the indicated treatments. (H) Tumour growth curves for\nBP903 TOs, treated as indicated in (D): Control (n = 13), ASTX660/E (6), diABZI/ASTX660 (n = 11),\ndiABZI/ASTX660/E (n = 9). Each line represents one animal and thick lines represent average tumour growth.\nCurves represent one independent experiment. (I) Kaplan-Meier survival curves of BP903-tumour bearing\nanimals, treated as in (D). (J) Pie charts depicRng the proporRon of mice from (H), which progressed, parRally\nresponded, or fully responded to the indicated treatment.\n8. In Fig. 6O, the improvement in antitumor function should be assessed using flow cytometry to\ndetect IFN-γ and perforin, which is better than measuring their mRNA levels.\nFollowing the reviewer’s sugges4on, we assessed the an4-tumour func4on of T cells and NK cells by\nflow cytometry. Our new analysis revealed a marked rise in IFN-γ-producing NK cells and CD8⁺ T cells\nwithin the tumour microenvironment following diABZI/ASTX660/E treatment in BP903 tumours.\nImportantly, we also observed an increased popula4on of polyfunc4onal CD8⁺ T cells, co-expressing\nIFN-γ and TNF, indica4ve of enhanced effector func4on (new Fig. 6O). Although the frequencies of\nPerforin- or Granzyme B-expressing cytotoxic cells remained stable (new Suppl. Fig. S9), the data\noverall point to a more ac4vated and func4onally potent an4-tumour immune response induced by\ndiABZI/ASTX660/E treatment.\nNew Figure 6O. Effect of diABZI/ASTX660/E on anti-tumour function of T cells and NK cells. (O)\ndiABZI/ASTX660/E treatment causes an increase in the indicated cell types.\nNew Suppl. Figure S9F,G,H. (F-H) Effect of diABZI/ASTX660/E on the indicated NK, CD4+ T and CD8+ T cells.\nTumour were treated and cell populations were analysed by FACS.\nReviewer #3 (Remarks to the Author):\nSummary of noteworthy results:\nThis study established tumor organoid lines from Brca1/p53 mouse models of human triple-negative\nbreast cancer and generated orthotopic mammary tumors in immunocompetent mice.\nUsing this as a platform, they identified one tumor organoid line with both high immune infiltration\nand high expression of RIPK1, a mediator of apoptosis/necroptosis cell death, and used it to\ndemonstrate the efficacy of RIPK1-induced immunogenic cell death. Specifically, double treatment\nwith a cell-death-inducing agent (ASTX660, an IAP antagonist) and anti-PD1 (pembrolizumab)\ndelayed BP962 tumor progression, whereas triple treatment (adding emricasan, a pan-caspase\ninhibitor) to promote necroptosis over apoptosis further enhanced the anti-tumor effect, leading to\ncomplete cure of the mice and immune memory against subsequent re-inoculation of tumor cells.\nThe treated tumors showed increased T cell and decreased macrophage infiltration. In contrast. the\nsame anti-tumor effect was not seen in tumors induced from two other organoid lines with lower\nRIPK1 levels and less immune infiltration. The authors therefore proposed RIPK1 as a biomarker for\nnecroptosis-based enhancement of immune checkpoint blockade therapy in immune-infiltrated\ntumors.\nThe authors further showed that immune-cold tumors (derived from two organoid lines, BP903 and\nBP487) can be sensitized to necroptosis-induced cell death (ASTX660/emricasan) by cGAS-STING\nactivation (via diABZI) that activates immune infiltration through viral mimicry. The treatment\nreshaped the tumor immune microenvironment with more effector lymphocytes and fewer\nimmunosuppressive cells.\nOverall assessment:\nThis study provides interesting and exciting findings that suggest a new potential approach to\nenhance immunotherapy efficacy for patients with triple-negative breast cancer. This is not the first\nstudy to use Brca1/p53-mutant mammary tumor organoids and orthotopic transplantation to study\ndrug response and resistance (see http://pubmed.ncbi.nlm.nih.gov/29256493/ for example).\nHowever, this study used these organoids in an immunocompetent host setting, and the findings of\nthe anti-tumor effect of necroptosis in combination with immune-modulating treatment are novel\nand promising.\nThe methodology, analysis, and interpretation are sound. However, more data are needed to\nstrengthen the current conclusion, which is drawn based on the comparison between only one single\ntumor organoid line (BP962, with high RIPK1 and high immune infiltration) versus two other lines\n(RIPK-low and/or poor immune infiltration). The experiments should be repeated on additional\ntumor organoid line(s) with a similar profile to BP962 to establish that the findings are\ngeneralizable.\nMajor comments:\n- Does other tumor organoid line(s) with similar RIPK1 expression and immune infiltration to BP962\nshow the same sensitivity to the combination treatment(s) using ASTX660/pembrolizumab or\nASTX660/pembrolizumab/E treatment?\nThis is an excellent question. Indeed, elevated RIPK1 expression\nand pronounced immune infiltration may act as indicators of\nnecroptotic responsiveness within the tumour microenvironment.\nBoth BP649 and E0771-derived tumours exhibit high levels of\nRIPK1 expression and substantial macrophage infiltration,\nproviding complementary models to investigate this hypothesis.\nWhen establishing BP649 organoids in vivo, we observed a longer\nlatency period (>3 months) and variable tumour growth dynamics,\nwhich prevented us from completing the analysis within the\nrevision timeframe. In parallel, we analysed E0771-derived\ntumours, which also display strong RIPK1 expression and abundant\nmacrophage infiltration, which is highly reminiscent to the one of\nBP962 tumours (Suppl. Fig. S6A-G). Notably, ASTX660/E/αPD-1\ntreatment in this model resulted in 100% complete responses.\nTogether, these findings support the notion that high RIPK1\nSuppl. Fig. S5. RIPK1 levels. Stacked\nexpression correlates with necroptotic competence and suggest\nhistogram of RIPK1 protein expression in\nthat both tumour-intrinsic factors and the stromal compartment\ncancer cells of TPs, ranked in order of their\ncontribute to the therapeutic outcome. Hscores\nNew Suppl. Fig. 6B-G. (B) E0771-derived tumours express high levels of RIPK1 and exhibit substanRal\nmacrophage infiltraRon, which are similar to the characteristics of BP962. RepresentaRve IHC images of F4/80+\nand RIPK1 expression of the indicated tumours. Scale bar = 100 μm. (C) SchemaRc representaRon depicRng the\ntreatment regimen of E0771 tumour bearing-C57BL/6J mice. (D) Tumour growth curves of E0771 derived\ntumours: Control (n = 8), A/E (n=9) and A/E/aPD-1 (n=10). Each line represents one animal and thick lines\nrepresent average tumour growth. Curves represent two independent experiments. (E) Tumour growth kineRcs\n(days 0-38) of mice treated as in (C), measured by the area under the curve (AUC). Each point represents the\nAUC of individual mice from (D). (F) Kaplan-Meier survival curves of E0771 tumour-bearing animals, treated as\nin (C). G) Pie charts depicRng the proporRon of mice from (C), which progressed, parRally responded, or fully\nresponded to the indicated treatments.\n- Is RIPK1 necessary and sufficient for the anti-tumor effects of ASTX660/pembrolizumab or\nASTX660/pembrolizumab/E treatment in immune-infiltrated tumors? For example, does\nknockdown/knockout of RIPK1 in a RIPK1-high tumor organoid line (e.g. BP962) abolish the anti-\ntumor effects of such combo treatment(s)? Alternatively, can overexpression of RIPK1 in RIPK1-\nlow/immune high tumors enable the anti-tumor effect of such combination treatment(s)?\nTo investigate the role of RIPK1, we used CRISPR/Cas9 to target Ripk1 in BP962 (new Fig. 7A-C and\nSuppl. Fig. S10). When BP962RIPK1-KO tumour organoids were treated with ASTX660/E, the anti-tumour\neffect was strongly attenuated, albeit remained statistically significant. However, the additional\nbenefit of αPD-1 co-treatment was lost. This demonstrates that tumour-cell-intrinsic RIPK1 expression\nis critical for full therapeutic efficacy.\nInterestingly, Ripk1 loss had a more pronounced impact than Mlkl deletion in BP962, indicating that\nRIPK1 fulfils additional signalling roles beyond the execution of necroptosis. These may involve the\ninduction of DAMPs that facilitate cDC1 cross-priming (PMID: 26405229), thereby enhancing adaptive\nimmune activation and responsiveness to αPD-1 therapy.\nTogether with BP962Mlkl-KO and Mlkl⁻/⁻ mouse data (new Fig. 7D-I), these findings indicate that\nnecropto4c competence in both tumour and stromal compartments is required for op4mal\ntherapeu4c response.\nNew Fig. 7. Cancer cell intrinsic and tumour micro-environmental necroptosis contributes to the an;-tumour\neffect. (A) Tumour growth curves of BP962 Ripk1KO in C57BL/6J mice: Control (n = 8), A/E (n=6) and A/E/aPD-1\n(n=9). Each line represents one animal and thick lines represent average tumour growth. Curves represent one\nindependent experiment. (B) Kaplan-Meier survival curves of BP962Ripk1-KO TO tumour-bearing animals. (C) Pie\ncharts depicRng the proporRon of mice, which progressed, parRally responded, or fully responded to the\nindicated treatments. (D) SchemaRc representaRon depicRng the experimental setup to evaluate the\ncontribuRon of tumour versus stromal necroptosis. The treatment regimen is depicted on the right. (E) Tumour\ngrowth curves of BP962Mlkl-KO TOs: Control (n = 8), A/E (n = 12) and A/E/αPD-1 (n = 12). Each line represents one\nanimal and thick lines represent average tumour growth. Curves represent one independent experiment. (F)\nKaplan-Meier survival curves of BP962Mlkl-KO tumour-bearing animals, treated as in (D). (G) Pie charts depicRng\nthe proporRon of mice from (F), which progressed, parRally responded, or fully responded to the indicated\ntreatments. (H) Tumour growth curves of BP962 TOs grown in Mlkl-/- animals (see Fig. 5E-G for WT control).\nTreatments: Control (n = 6) and A/E/αPD-1 (n = 9). Each line represents one animal and thick lines represent\naverage tumour growth. Curves represent two independent experiments. (I) Kaplan-Meier survival curves of\nBP962 tumour-bearing Mlkl-KO animals, treated as in (D). A=ASTX660; E=emricasan.\nNew Suppl Fig S10. Genera;on and characterisa;on of BP962RIPK1-KO and BP962Mlkl-KO tumours. (A) Western blot\nvalidaRon of CRISPR-mediated RIPK1 and MLKL deleRon in BP962 organoids. (B) Cell death assay confirming\nnecroptosis deficiency in BP962MlklKO organoids. (C) Tumour growth comparison of the indicated organoid lines\nin C57BL/6 mice. (D) Kaplan-Meier survival curves of the indicated tumour-bearing animals from (C).\n- What drives the heterogenous expression of RIPK1 in these primary tumors and their derivative\ntumor organoid lines? Can the authors provide data to suggest a potential mechanism, or at least\ndiscuss some speculation in the text?\nThis is indeed an intriguing ques4on. We observe a clear correla4on between macrophage infiltra4on\nand elevated RIPK1 expression. BP962 organoids appear to secrete factors that drive a macrophage-\nrich tumour microenvironment. We speculate that macrophage-produced cytokines, such as TNF, may\ns4mulate compensatory upregula4on of RIPK1 to protect tumour cells from cell death. While elevated\nRIPK1 levels may provide resistance to death ligands under basal condi4ons, they may also ‘prime’\nthese tumours for necropto4c ac4va4on upon appropriate triggers (ASTX660/E).\nWe have expanded our ‘Discussion’ to discuss this point.\n- It would make the paper even stronger if the authors could provide complementary data from\nhumans to reinforce at least some of their conclusions drawn in mouse models.\nWe fully agree with the reviewer. Indeed, we do have complementary clinical data from our\ninves4gator-led ASTEROID Phase I trial (see below) that supports our conclusions. However, these data\nare substan4al and are therefore beyond the scope of the current ms and will be reported in a separate\nms. Results from our ASTEROID Phase I trial (TargeDng IAPs potenDates immune checkpoint blockade\nin advanced solid tumors) confirm a similar scenario in humans. In the ASTEROID trial, we combined\nthe IAP antagonist ASTX660 with pembrolizumab (aPD-1) in pa4ents with advanced solid tumours.\nExci4ngly, this combina4on is not only well tolerated but also showed early signs of efficacy, including\nlong-las4ng an4-tumour immune responses in several cancer pa4ents typically resistant to immune\ncheckpoint blockade. This manuscript is currently under evalua4on at Nature Medicine.\nMinor points:\n- “Notably, the individual organoid lines remained stable, and their respective TOs were\nhighly reproducible within each line, as evidenced by mRNA analysis and mutational profiling (Fig.\n2e,f)”. Figure 2f showed CNAs present in primary tumors and absent in organoids and vice versa,\npotentially due to the expansion of clonal subpopulation and/or acquired CNA in culture. The\nauthors should modify their language about stability and reproducibility to reflect these differences\nbetween primary tumors and organoid lines.\nWe agree that some CNAs differ between the primary tumours and their derived organoids, likely\nreflecting the expansion of specific subclones and/or acquisition of CNAs during culture. We have\ntherefore revised the text to clarify that the term “stable and reproducible” refers to consistency\nwithin each organoid line across passages, rather than complete genomic identity with the\ncorresponding primary tumour.\nThe revised text now reads:\n“Notably, the individual organoid lines remained stable and reproducible across passages, as\nevidenced by mRNA and mutational profiling, while some clonal and CNA differences relative to the\nparental tumours were observed, reflecting tumour heterogeneity and adaptation in culture (Fig.\n2E,F).”\n- Figure 2h: Scale bars representing different sizes should be more clearly labeled.\nWe have updated the figures to clearly indicate the differences in the scale bars.\n- Figure 3a-b: Are the “normal mammary glands” analyzed after the lymph nodes have been\nremoved? The author should clarify in the figure legend and/or methods section.\nWe have updated the text in materials and methods.\n- Figure 3j: genes should be labeled in the heatmaps.\nWe have updated Fig 3j to include the genes names\n- Figure S5c schematic indicates that cells were stained with PI and Hoechst, whereas the data panels\n(Fig. 4e,g,h,i, and S5d) show PI and DAPI. Please clarify.\nWe have corrected this oversight. We have used Hoechst for death assays and DAPI for\nimmunofluorescence.\n22"}, {"round": 2, "reviewer_comments": {"reviewer_1": "This revised manuscript by Clucas et al has undergone significant revision with the inclusion of several pieces of additional data. They have done an admirable job addressing the concern of this reviewer. A major takeaway is that despite these tumors all arising from the same oncogenic drivers in a mouse model, they developed into a heterogenous group of tumors with different behaviour to immune/pharmacological interventions. It further illustrates the challenge of treating human patients where the genetic diversity is even greater. This reviewer has no further concerns.", "reviewer_2": "The authors have comprehensively addressed all my previous concerns through extensive revisions, including strengthened experimental design and clarified textual. The incorporation of substantial new data has convincingly supported their original conclusions. Importantly, the study now presents novel insights that significantly elevate the overall impact and novelty of the work. I have no remaining issues and support its publication in its current form.", "reviewer_3": "The authors have significantly improved their manuscript and have addressed all the concerns I raised in the first round of review."}, "author_response": "Nature Communications manuscript NCOMMS-25-01910A\nWe would like to thank you and the referees for finding our revised ms much improved.\nThe referees did not raise and additional comments that needed addressing.\nBest wishes\nPascal Meier\n1"}]

Decision letter