Aging increases ovarian cancer growth, metastasis, and immunosuppression that can be alleviated by inhibiting hedgehog signaling

Ovarian cancer incidence and mortality increase with age, yet the impact of physiological aging on tumor progression and the tumor immune microenvironment remains poorly defined. Here we show using orthotopic implantation of two syngeneic models representing distinct cellular origins (ovarian surface epithelial and fallopian tube -derived) in young versus aged mice, that aged hosts exhibit markedly higher tumor burden, ascites accumulation, and proliferation. Selective follicle depletion in young mice using VCD did not recapitulate these effects, indicating that age -associated microenvironmental changes beyond hormonal decline drive tumor growth. Spatial transcriptomics revealed distinct intratumoral heterogeneity in both age groups. Comparison of CD45 + cells between aged and young tumors showed Hedgehog signaling enrichment and immunosuppressive signatures in aged hosts, with elevated M2 macrophages and Foxp3 + regulatory T cells . Notably, pharmacologic inhibition of Hedgehog signaling with vismodegib in aged mice suppressed tumor growth, reduced metastatic spread, and decreased infiltration of CD206 + macrophages and Foxp3 + T cells while sparing CD8 + T cells. Our findings provide proof -of-concept that vismodegib can reduce tumor growth and specific immunosuppressive populations in aged hosts, suggesting Hedgehog inhibition as a potential immunomodulatory strategy for older ovarian cancer patients or those tumors that exhibit Hedgehog pathway activation. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 3

Age represents one of the strongest risk factors across most cancer types, with both cancer incidence and mortality rates increasing dramatically in patients over 65 years. However, the mechanisms by which physiological aging contributes to tumor progression remain incompletely understood. Aging is associated with broad alterations in the tissue microenvironment that include but are not limited to changes in extracellular matrix composition, accumulation of senescent cells, and shifts in immune cell populations, all of which may create a pro -tumorigenic environment. Ovarian cancer represents a particularly compelling model, as incidence and mortality increase sharply after menopause, with a 26% higher mortality among aged patients compared to other cancer types [1, 2]. In this context, hormonal decline has historically been considered a driver of increased susceptibility, yet whether broader age -associated microenvironmental changes contribute independently remains unclear. High- grade serous ovarian carcinoma (HGSOC), the most lethal gynecologic malignancy, often originates in the fallopian tube with preferential metastasis to the ovary, much like other ovarian cancer subtypes [3-5], making the aging ovarian microenvironment a potential key determinant of disease progression for this group of cancers. Despite this clinical reality, most preclinical ovarian cancer studies employ young animal mouse models, that bypass ovarian age -specific tumor -host interactions [11], limiting our understanding of how physiological aging influences tumor behavior. Older ovarian cancer patients also experience poorer outcomes, suggesting that age - associated changes in the ovarian and peritoneal cavity may contribute to tumor progression and treatment response to therapies [6]. Ovarian aging also extends beyond follicle decline, including extracellular matrix composition changes [7] accumulation of senescent and multinucleated ovarian stromal cells and macrophages [8] and significant shifts in immune cell populations. These immune shifts in mouse models , include higher levels of monocyte recruitment followed by increased alternatively activated macrophage (M2) populations [9] and a shift towards adaptive immunity [10]. T hese changes in the immune milieu may predispose aged ovaries to increased tumor burden. Whether hormonal decline alone accounts for age -associated tumor progression, or whether broader aging -related changes are required, remains unclear . Prior work in a 85 week old mouse model using intraperitoneal injections, showed increased tumor burden .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 4 and tumor infiltrating lymphocytes (TIL) with altered B cell related pathways in the peritoneal adipose tissues [11]. However, how tumor growth, metastasis, and the immune landscape differ in aged versus young ovarian microenvironments has not been systematically defined . Similarly, survival analysis in a genetically engineered mouse model indicate s that nulliparous aged mice had shorter survival compared to young and multiparous mice [12] indicating that parity, and the likely associated hormonal changes influence tumor outcomes. Here, w e compared tumor progression and immune composition differences and outcomes in 60-65 week-old female mice, which represent reproductive decline corresponding to menopause in women (~51 years) [13-15], versus young mice (controlling for parity) and follicle depleted mice. We find that menopausal hosts support tumor progression significantly more than younger hosts. Using spatial transcriptomics, we analyzed age-associated differences in the tumor immune microenvironment and identified Hedgehog signaling as a pathway enriched in immune cells from aged tumors. Aged tumors showed a significant increase in a spectrum of immunosuppressive cell populations. Notably, pharmacologic inhibition of Hedgehog signaling reduced tumor progression and the presence of the same immunosuppressive cell populations . These findings demonstrate that physiological aging, rather than follicular depletion alone, is associated with accelerated tumor growth and an immunosuppressive microenvironment and implicate Hedgehog signaling as a potential target for immune remodeling in post -menopausal hosts.

Age-associated changes, rather than follicular depletion alone, promote ovarian cancer progression. To investigate how physiological ovarian aging affects tumor growth and metastasis in ovarian and fallopian tube- derived cancer , we compared tumor growth and metastasis in young (6- 8 weeks) versus aged (60-65 weeks) nulliparous C57BL/6 mice to eliminate physiological and hormonal changes associated with pregnancy [16]. Ovaries from a ged host mice showed predicted changes, including a 10.5- fold reduction in follicle count and decreased expression of .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 5 ovarian function markers (1.6- fold lower INHA and 3.4-fold lower AMH mRNA) compared to ovaries from young mice (Supplementary Figure 1A, i- iii). To quantify differences in tumor growth in the hosts w e orthotopically implanted two distinct tumor cell models, ID8Trp53−/− (ovarian surface epithelial -derived) and PPNM ( fallopian tube -derived cells) into the mice ovarian bursa. Tumor growth kinetics were monitored by bioluminescence imaging in ID8Trp53−/−implanted mice (Supplementary Fig ure 1B, i –ii) and by palpation in PPNM - implanted mice. Because mice were euthanized at a uniform endpoint, we quantified progr ession using a time -to-threshold analysis. The event was defined as the first attainment of ≥2.77 cm² peritoneal spread and yielded Kaplan Meier style estimates of the probability of remaining below threshold over time. Aged hosts reached this threshold significantly earlier, with a 3.7-fold higher hazard of progression. ( Supplementary Figure 1B, iii). At endpoint (day 55 for ID8Trp53−/−, day 42 for PPNM), aged mice displayed significantly greater tumor burden across all metastatic sites (Supplementary Fig ure 1B, v–vi). In the ID8Trp53−/− model, aged hosts showed increased ovarian and omental tumor mass (1.8- fold and 1.2-fold respectively), ascites volume (1.6- fold), and total peritoneal/mesenteric burden (1.8- fold) relative to young hosts (Figure 1A; Supplementary Figure 1C, i–ii). In the PPNM model, age -related differences were even more pronounced, with 2.3-fold greater ovarian tumor mass, 6.2-fold greater omental tumor mass, 9.1-fold higher ascites volume, and 2.7-fold higher total tumor burden in aged compared to young mice (Figure 1D; Supplementary Figure 1C, iii –iv). Histological analysis revealed that tumors from aged hosts had higher proliferation rates as determined by PCNA staining . Specifically, ovarian tumors were 1.6-fold more proliferative in both ID8Trp53−/−and PPNM, and omental tumors were 1.4-fold for ID8Trp53−/− and 1.2-fold for PPNM as compared to young hosts (Figure 1B-C, E-F). To determine whether follicular depletion and associated hormonal changes alone could account for increased tum or growth, we treated young mice with 4- vinylcyclohexene diepoxide (VCD), which selectively depletes ovarian follicles without other age -associated changes. VCD treatment successfully reduced follicle number by 3.7- fold and decreased AMH and INHA expression by 14- fold and 10- fold, respectively (Supplementary Figure 1D, i- iii). ID8Trp53−/− cells implanted into the ovarian bursa of follicle depleted ovaries (VCD pretreated) and follicle replete ovaries (vehicle- treated) showed no significant difference at endpoint (day 67 post - .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 6 implantation) (Supplementary Figure 1D, iv). We confirmed no significant differences in ovarian or omental tumor weights, ascites volume, or total tumor burden between groups (Supplementary Figure 1D, v-xi). These findings demonstrate that follicle depletion in the ovaries alone do es not support tumor growth; rather, physiological age in mice strongly accelerates tumor growth in the ovaries, and metastasis to the omentum and peritoneal cavity, thereby reducing overall survival. Spatial transcriptomics reveal distinct intratumoral heterogeneity patterns in ovarian tumors from young versus aged hosts To understand the spatial organization of the tumor microenvironment in young and aged hosts, and define intra and intertumoral differences, w e performed spatial transcriptomics using digital spatial profiling (DSP) . Regions from ovarian tumors from young and aged mice were segmented into tumor cells (CK8 +), immune cells (CD45 +), and endothelial cells (CD31 +) by multiplex immunofluorescence (Figure 2 A -B). Given the well -documented immune alterations associated with ovarian cancer and ovarian aging, and the critical role of immune cells in ovarian cancer tumor progression, we focused our analysis for this study on comparing CD45 + enriched regions versus CD45+ depleted regions (n=6 ROIs from each category ). Within young host tumors, CD45 + depleted regions showed enrichment in hallmark pathways associated with metabolic reprogramming, including adipogenesis, oxidative phosphorylation, and fatty acid metabolism (Figure 2C , i ). Top upregulated genes in these regions included Fxyd3 (FXYD Domain Containing Ion Transport Regulator 3), Prr15l (Proline Rich 15 Like), and Flrt1 (Fibronectin Leucine Rich Transmembrane Protein 1) (Supplementary Table A). KEGG pathway analysis revealed enrichment in glycan biosynthesis pathways (Supplementary Figure 2A , i). In contrast, CD45 + enriched regions in the same young tumors displayed allograft rejection, epithelial-mesenchymal transition (EMT), E2F targets, and inflammatory response hallmark pathways (Figure 2C , i). Top upregulated genes included Thbs1 (thrombospondin-1), Col8a1 (collagen type VIII alpha -1 chain), and Adgre1 (Adhesion G Protein- Coupled Receptor E1) (Supplementary Table A). KEGG pathways related to tuberculosis, malaria, and immune deficiency were enriched in these regions (Supplementary Figure 2A,ii). .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 7 In contrast to young tumors, aged host ovarian tumors displayed a distinct pattern of intratumoral heterogeneity. CD45+ cells depleted regions showed enrichment for MYC targets V1, cholesterol homeostasis, and mTORC1 signaling hallmark pathways (Figure 2C , ii). Top upregulated genes included Clu (Clusterin), GPC1 (Glypican-1), and TGFBI (Transforming Growth Factor Beta Induced) (Supplementary Table B). KEGG pathways related to protein processing were enriched in these regions (Supplementary Figure 2A , iii). CD45+ cells enriched regions in the same aged tumors were characterized by inflammatory response, allograft rejection, and KRAS signaling hallmark pathways (Figure 2C , ii). Top upregulated genes included HMGCS2 (3- Hydroxymethylglutaryl-CoA Synthase 2), Jchain (Joining Chain), and Lyz2 (Lysozyme 2) (Supplementary Table B). KEGG pathway analysis showed enrichment in chemokine signaling, cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and natural killer cell cytotoxicity pathways (Supplementary Figure 2A, iv). Comparison of CD45+ depleted regions between the young and old ovarian tumor groups revealed three common hallmark pathways: fatty acid metabolism, androgen response, and heme metabolism (Supplementary Figure 2A, v) implicating these pathways as host independent . CD45 + enriched regions from the young and old ovarian groups shared the inflammatory hallmark (Supplementary Figure 2A, vi ). However, even in the shared inflammatory signature, the genes driving this hallmark were non- overlapping, with 19 unique genes in each age group (Figure 2 D, i -ii). For example, young tumors expressed Cxcl10 , associated with anti -tumor immunity, whereas aged tumors expressed chemokines linked to immunosuppression, including Ccl5, Ccl22, and Ccl17 . These findings indicate that while both young and aged tumors exhibit intratumoral heterogeneity, the underlying molecular programs, particularly those governing inflammation are fundamentally distinct, suggesting age -associated differences in immune cell composition and function. Immune cells in aged tumors are immunosuppressive with Hedgehog pathway signatures. To determine whether these pathway differences reflect altered immune cell composition, we performed deconvolution using CIBERSORTX [17] . Young host tumors contained higher proportions of memory B cells and CD8 + T cells. In contrast, aged host tumors were dominated .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 8 by regulatory T cells (18% vs 4% in young) and CD4 + follicular T helper cells (Figure 2 E). Notably, tumor associated M2 macrophages (TAM), that are known drivers of immunosuppression in ovarian cancer [18, 19] were markedly elevated in aged tumors (5% vs 1% in young). To investigate the functional programs active in these immune populations, we performed GSEA on CD45 + cells themselves . In a ged host tumors CD45 + cells were characterized by IFN -α, IFN -γ, inflammatory response, and Hedgehog signaling pathways (Figure 2F, i-iv). In contrast, CD45 + cells from young host tumors showed enrichment in EMT, Notch signaling, and estrogen response early, though these did not reach statistical significance. Consistent with these compositional differences, the top upregulated genes in CD45 + cells from young tumors include GSK3A, TXNDC5, and ITGA5 ; genes that are associated with B cell infiltration and prolonged survival in ovarian cancer patients (Supplementary Figure 2B , Figure 2G, i-iii). Conversely, top upregulated genes in CD45 + cells from aged tumors include PRM1, IHH (Indian Hedgehog), and TUBG1 , are associated with M2 macrophage infiltration as shown in other models previously [20, 21] and poor survival outcomes in ovarian cancer patients (Supplementary Figure 2B, Figure 2G, iv-vi). Together, these analyses reveal that aged host tumors harbor immunosuppressive cell populations with Hedgehog ligand and pathways , identifying this as a potential modifiable target. Aged tumors are enriched for immunosuppressive macrophages and regulatory T cells. To phenotypically validate CIBERSORTX predictions, we quantified immunosuppressive cell populations in ovarian and omental tumors , the later being a preferred metastatic site in ovarian cancer [22]. We first assessed CD45 +Arg1+ double- positive cells as a marker of immunosuppressive immune populations [23, 24]. In aged hosts, ovarian tumors showed 2.8-fold higher CD45 +Arg1+ cells in the ID8 Trp53−/− model (Figure 3A) and 2.42- fold higher in the PPNM model (Figure 3B) compared to ovarian tumors in young hosts. Similarly, omental tumors from aged hosts showed 3.52- fold ( ID8Trp53−/−, Figure 3I) and 2.08- fold (PPNM, Figure 3J ) higher CD45 +Arg1+ cells. Total CD45 + infiltration followed similar trends (Supplementary Figure 3A -B). Since Arg1 + expressing monocytes/macrophages (CD68 +) promote tumor progression and immune evasion in ovarian and other cancers [25, 26], we specifically quantified .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 9 CD68+Arg1+ cells. Ovarian tumors in aged hosts showed 3.7-fold and 2-fold higher CD68+Arg1+ cells compared to young hosts in ID8Trp53−/− and PPNM models , respectively (ID8Trp53−/−, Figure 3C, PPNM, Figure 3D). CD68+Arg1+ cells were also numerically higher in aged omental tumors, reaching statistical significance in the PPNM model ( Figure 3L). The balance between M1 (CD80+) and M2 (CD206 +) macrophages is crucial in determining local immune milieu and prognosis in ovarian cancer [27, 28]. Aged host tumors showed 2.69-fold higher CD206+ cells in ovarian tumors (ID8Trp53−/−, Figure 3E) and 2.26-fold higher in the PPNM model (Figure 3F ). Omental tumors showed similar elevations in CD206 + cells in aged hosts (Figures 3M, 3N ). Supporting these findings, ascites fluid from aged mice (ID8Trp53 −/− model) showed a 2.9- fold higher ratio of CD206+ to CD80+ macrophages (Supplementary Figure 3C). We next evaluated regulatory T cells, a critical population known to inhibit effective anti- tumor immunity [29] and predicted to be elevated from our deconvolution analysis (Figure 3H). Foxp3+ cells were 3 to 3.4-fold higher in aged host ovarian tumors across both models (Figures 3G, 3H) and 2.28 -fold higher in omental tumors (Figures 3O , 3P). Consistent with tumor tissue findings, ascites fluid from aged mice showed 2.5- fold higher CD25 +Foxp3+ cells (Supplementary Figure 3D). Together, these findings demonstrate that the aged tumor microenvironment is dominated by immunosuppressive cell populations including M2 macrophages and regulatory T cells , across primary (ovary) and metastatic (omentum) sites, providing a cellular basis for the enhanced tumor growth observed in aged hosts. Hedgehog inhibition suppresses ovarian tumor growth and metastasis in aged models. Based on the immune suppressive cell populations, accelerated tumor growth and predominance of Hedgehog signaling in immune cells from aged host tumors, we aimed to test the therapeutic benefit of inhibiting Hedgehog (Hh) signaling in older hosts using Vismodegib (Figures 4A,4B). As mice were euthanized at a uniform endpoint, disease progression was assessed using a time- to-threshold probability analysis of disease progression using abdominal girth changes. This yielded Kaplan-Meier style estimates of the p robability of remaining below the abdominal girth threshold. Vismodegib- treated mice showed delayed disease progression, remaining below threshold until day 41 compared to day 16 in vehicle -treated mice (Figure 4C). Vismodegib .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 10 treatment reduced metastatic burden , the number of mice that developed measurable ascites volume (33.3% of vismodegib vs 88.8% of vehicle-treated, Figure 4D) , diaphragmatic metastases (66.6 % of vismodegib vs 87.5% of vehicle- treated mice Figure 4E), and peritoneal wall metastases ( 22.2 % of vismodegib mice vs 50 % of vehicle -treated mice Figure 4F). Ovarian and omental tumor weights trended lower in vismodegib treated mice, ovarian weights did not reach statistical significance (Figure 4G -H). However, tumor proliferation was markedly reduced as PCNA-positive cells were 1.47- fold lower in ovarian tumors and 1.86- fold lower in omental tumors, with corresponding reductions in staining intensity (1.5- fold and 2.15- fold, respectively, Figure 4G ,4H). These findings demonstrate that Hh inhibition delays tumor progression and reduces metastatic spread in aged hosts. Hedgehog inhibition reduces immunosuppressive macrophages and regulatory T cells in aged tumors. Given the enrichment of Hedgehog signaling in immune cells from aged tumors, we next asked whether the therapeutic effects (Figure 4) were accompanied by changes in immunosuppressive cell populations in ovarian and omental tumors. In ovarian tumors, vismodegib treatment reduced total CD45 + cells by 1.85- fold (Supplementary Figure 5A) and CD45 +Arg1+ cells by 1.28-fold (Figure 5A), although the latter did not reach statistical significance. Omental tumors showed only marginal changes in these populations (Supplementary Figure 5B, Figure 5B ). Hh inhibition has been shown to modulate macrophage polarization in other cancer types [30, 31]. Consistent with this, CD206 + M2 macrophages were 2.4- fold lower in vismodegib- treated ovarian tumors (Figure 5E) but did not reach statistical significance in vismodegib -treated omental tumors (Figure 5 F). Flow cytometry analysis of mice ovaries supported these findings, showing trends toward higher M1 (F4/80 +CD80+) and lower M2 (F4/80 +CD206+) macrophages in vismodegib- treated mice (Supplementary Figure 4C, i -ii). However, the CD68 +Arg1+ monocytic population was not significantly altered in either ovarian or omental tumors (Figures 5C, 5D). Hh signaling can also modulate T cell responses in breast cancer [32] . We found that Foxp3 + regulatory T cells were markedly reduced in vismodegib- treated mice leading to 2.89- fold reduction in ovarian tumors (Figure 5G) and 1.91-fold lower in omental tumors (Figure 5H) as compared to vehicle treated mice. Together, these findings demonstrate that pharmacologic .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 11 inhibition of Hh signaling in aged hosts suppresses ovarian tumor growth and metastatic spread, accompanied by reductions in CD206+ M2 macrophages and Foxp3+ regulatory T cells. Notably, Hh inhibition effectively reduced these key immunosuppressive populations, suggesting that Hh inhibition selectively targets immunosuppressive rather than effector populations in these models.

Age is among the strongest risk factors for ovarian cancer, with incidence and mortality rising sharply after menopause, and older patients experiencing poorer outcomes compared to younger patients [33-35]. While follicle depletion is a hallmark of ovarian aging, whether this change alone accounts for increased tumor susceptibility or whether additional age-associated alterations are required has remained unclear. Using orthotopic implantation of two distinct tumor models in young and aged mice , the latter corresponding approximately to human perimenopausal age, we found that aged hosts exhibited significantly higher tumor burden, increased ascites accumulation, and elevated tumor proliferation (Figure 1 A-F), though direct clinical translation requires validation in patient samples . Our data further identified enrichment of Hedgehog signaling in immune cells from aged tumors and demonstrated that pharmacologic inhibition of this pathway reduces tumor burden and immunosuppressive cell populations, suggesting a potential immunomodulatory strategy for older patients with ovarian cancer (Figure 2F). Ovarian aging encompasses far more than follicular decline, including extracellular matrix remodeling, accumulation of senescent stromal cells, significant shifts in immune composition, and elevated pro- inflammatory cytokines contributing to 'inflammaging'[36]. W e used 4-vinylcyclohexene diepoxide (VCD), which selectively destroys primordial and primary follicles, reducing estrogen, progesterone, AMH, and Inhibin A while leaving the young microenvironment otherwise intact [37].VCD- treated young mice showed no increase in tumor burden compared to controls, indicating that tumor -promoting effects in aged hosts arise from microenvironmental changes beyond hormonal decline (Supplementary Figure 1D). Prior studies using VCD or ovariectomy in ovarian cancer contexts have yielded variable results. VCD - .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 12 induced follicle depletion in TgCAG -LS-TAg mice or ovariectomy before SKOV3/OVCAR3 intraperitoneal implantation resulted in slower tumor growth, effects attributed to elevated gonadotropins [38] . In contrast, VCD treatment followed by carcinogen exposure induced ovarian neoplasms [39]. These studies used intraperitoneal injections or carcinogen -based approaches rather than orthotopic implantation into the ovarian microenvironment, which provides insight into how the aged ovarian niche itself shapes tumor growth. Our orthotopic studies establish that follicular depletion is insufficient but do not identify which specific age - associated changes are necessary or sufficient. The relative contributions of the local ovarian microenvironment versus systemic aging effects, including alterations in circulating immune cells, remain to be determined. Spatial transcriptomics of the tumors revealed that b oth age groups displayed heterogeneous tumor landscapes with distinct CD45 + enriched and depleted regions; however, the pathway signatures defining these regions differed substantially between age groups. In young host tumors, CD45 + depleted regions showed hallmarks of metabolic reprogramming while CD45 + enriched regions exhibited epithelial -mesenchymal transition (EMT) signatures. Emerging evidence indicates that EMT can serve as a tumor escape mechanism in response to anti-tumor immune pressure, enabling tumor cells to evade T cell-mediated killing through MHC class I downregulation and immune checkpoint upregulation (Figure 2C, i) [40-42]. The presence of EMT signatures in immune -enriched regions of young tumors, alongside anti -tumor chemokines such as Cxcl10 , suggests that tumors in young hosts may face greater immune pressure and utilize EMT as an adaptive response. In contrast, aged host tumors showed MYC targets and cholesterol homeostasis enrichment in CD45 + depleted regions, and inflammatory response signatures in CD45 + enriched regions (Figure 2C, ii). Notably, while both young and aged tumors exhibited inflammatory hallmarks in immune -enriched regions, the genes driving these signatures were entirely non-overlapping (Figure 2D). This distinction has functional implications such as with Cxcl10, enriched in young tumors, which is associated with anti-tumor immunity and a favorable prognosis in ovarian cancer [43], whereas chemokines enriched in aged tumors, including Ccl5, Ccl22, and Ccl17 promote immunosuppression through regulatory T cell recruitment and are associated with chemoresistance and poor response to immunotherapy [44-47]. These findings reveal that similarly labeled inflammatory signatures obscure .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 13 fundamentally different immune programs indicating that young tumors appear to face active anti-tumor immunity necessitating escape mechanisms, whereas aged tumors exhibit signatures consistent with an already established immunosuppressive microenvironment. Whether EMT - targeted approaches could enhance anti -tumor immunity specifically in younger patients, or whether reversing the immunosuppressive chemokine milieu could benefit older patients, warrants further investigation. Consistent with our transcriptomic findings, aged host tumors exhibited significantly higher infiltration of immunosuppressive populations across both tumor models, including CD45+Arg1+ cells, which were significantly higher in aged ovarian and omental tumors compared to young hosts (Figures 3A,3B,3I,3J) . This enrichment was driven by CD68 +Arg1+ monocytes and CD206 + tumor- associated macrophages (TAMs), both of which were significantly elevated as well in aged tumors. TAMs, particularly those with M2 polarization, are established drivers of immunosuppression in ovarian cancer and are associated with poor prognosis, therapy resistance, and tumor progression [18, 48, 49]. The balance between M1 (anti- tumor) and M2 (pro-tumor) macrophages is critical in shaping the local immune milieu , and our finding of a higher CD206+/CD80+ ratio in ascites from aged mice further supports a shift toward immunosuppressive macrophage polarization in aged hosts (Supplementary Figure 3C) . In parallel, Foxp3+ regulatory T cells were more abundant in aged tumors across both ovarian and omental sites (Figures 3G,3H,3O,3P). Regulatory T cells inhibit effective anti- tumor immunity and have been associated with poor survival , specifically in ovarian cancer , compared to other malignancies [50]. The concurrent enrichment of M2 macrophages and regulatory T cells in aged tumors suggests that these populations may cooperate to establish an immunosuppressive microenvironment that permits accelerated tumor growth. Whether this immunosuppressive state reflects intrinsic properties of aged immune cells, tumor or stroma mediated reprogramming of infiltrating immune cells, or altered recruitment patterns driven by the aged host remains to be determined. The Hedgehog pathway, while best known for its roles in embryonic development and tissue homeostasis, has emerged as an important modulator of immune function in the tumor microenvironment [51, 52] . Recent studies in breast cancer have begun to elucidate how .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 14 Hedgehog signaling shapes immunosuppressive cell populations. Hedgehog signaling regulates macrophage metabolism and polarization, promoting the M2 phenotype through altered O - GlcNAcylation and mitochondrial dynamics [20] . Additionally, Hedgehog signaling promotes Treg differentiation and activity, and its inhibition can drive Treg -to-Th17 conversion through metabolic rewiring [32]. These mechanistic insights from breast cancer models suggest potential pathways through which Hedgehog activation in aged ovarian tumors could sustain immunosuppressive M2 macrophages and Tregs. O ur data demonstrate correlation , and whether Hedgehog activation directly drives immunosuppressive cell polarization in aged ovarian tumors, or whether it represents a consequence of the altered aged microenvironment, remains to be determined. Inhibition of Hedgehog signaling using Vismodegib delayed disease progression in older mice and decreased infiltration of CD206 + M2 macrophages and Foxp3 + regulatory T cells , the two immunosuppressive populations most enriched in aged tumors. CD68 +Arg1+ monocytes however were not significantly affected, suggesting Hedgehog inhibition may preferentially target specific immunosuppressive subsets rather than broadly depleting myeloid cells (Figure 5). These findings contrast with a phase II clinical trial in which vismodegib failed to improve progression-free survival as maintenance therapy in ovarian cancer patients in second or third complete remission [53]. Several factors may account for this discrepancy. First, patients in that trial were not selected based on age or profiled for Hedgehog pathway activation; our data suggest Hedgehog signaling is specifically enriched in the aged tumor microenvironment, and patients without pathway activation may derive little benefit. Second, the clinical trial employed vismodegib as maintenance therapy after achieving remission, whereas our intervention began early after tumor implantation when the immunosuppressive microenvironment was actively developing. Perhaps most importantly, the immunomodulatory effects we observe suggest that Hedgehog inhibition may be best suited not as monotherapy but in combination with immune checkpoint inhibitors. By reducing M2 macrophages and Tregs, Hedgehog inhibition could potentially render tumors more responsive to checkpoint blockade , a combinatorial strategy that warrants future investigation, particularly in older patients whose tumors may be most dependent on this pathway. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 15 In summary, we demonstrate that physiological aging creates an immunosuppressive ovarian tumor microenvironment characterized by M2 macrophage and Treg infiltration, with Hedgehog signaling emerging as a potential mediator. These findings have several implications for future investigation. Parabiosis or bone marrow transplantation experiments could distinguish local from systemic contributions to age-associated tumor promotion. The distinct immune landscapes in young versus aged tumors , active immune engagement and potential for EMT-mediated escape in young hosts versus pre -established immunosuppression in aged hosts suggest that age- stratified therapeutic approaches may be warranted. Most immediately, our data provides rationale for clinical investigation of Hedgehog inhibitors in combination with immune checkpoint blockade, with patient selection based on age and tumor Hedgehog pathw ay activation status.

Cell lines, reagents and media: PPNM (p53 −/−l R172H Pten−/−Nf1−/−MycOE) cells were kindly provided by Dr. Robert A Weinberg, Whitehead Institute for Biomedical Research, Cambridge, MA, USA, through an MTA and were cultured as described here [54]. For ID8 Trp53−/−- Luc, ID8Trp53−/−cells [55] were transduced with Luc FUW -firefly luciferase -EGFP (FUW -FFLuc- eGFP) lentiviral construct gene, generously gifted by Dr. Stewart, Department of Cell Biology and Physiology, Washington University School of Medicine, St Louis, to generate ID8Trp53−/− Luc cells as described [56]. ID8Trp53−/− cells were cultured in Dulbecco’s modified Eagle’s medium supplemented with 4% fetal bovine albumin, 100U penicillin , and streptomycin, 5 μg/mL of insulin, 5 μg/mL of transferrin, and 5 ng/mL of sodium selenite . Both cell lines were maintained at 37 °C with 5% CO2 in a humidified incubator, routinely checked for mycoplasma and experiments were conducted within 3–6 passages, depending on the cell line. Animals: All animal procedures were conducted in accordance with Institutional Animal Care and Use Committee (IACUC) guidelines at the University of Alabama at Birmingham (UAB), USA. C57BL/6J (Cat no. 000664; The Jackson Laboratory, Farmington, CT, USA,) or C57BL/6N (National Institute of Aging, Bethesda, MD, USA)) nulliparous females aged 6 or 65 weeks, were used in this study. All animals were housed in the Wallace Tumor Institute animal .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 16 facility at UAB with food and water ad libitum in groups of 5 mice per cage at 24°C under a 12- hour light/dark cycle. Establishment of follicle depleted ovaries : Young female mice (6 weeks old) were randomly divided into two groups (n = 5 per group): 4- vinylcyclohexene diepoxide (VCD, Cat no. 94956, Sigma-Aldrich)) treated and vehicle control. The VCD group received intraperitoneal injections at 160 mg/kg in sesame oil for 15 consecutive days [57] while control mice received sesame oil alone, following VCD treatment, mice were aged until postnatal day 60, at which point ovaries were collected for histological analysis and qRTPCR. Intrabursal implantation of ovarian cancer cells: 2x10 6 ID8Trp53−/− or PPNM cells suspended in 8µl phosphate-buffered saline were injected into the bursa of the left mouse ovary. M ice were anesthetized prior to implantation using 2.5% isoflurane mixed with 2L/min oxygen and administered buprenorphine 0.07 mg/kg as ana lgesic pre- and post -surgery for up to 48 hours following institutional guidelines. Vismodegib treatment: Aged female mice (65 weeks old) were gavaged with 100µl (3mg/mouse) of Vismodegib (GDC-0449) (Selleckchem, Cat no. S1082 ) or DMSO as vehicle, three times a week as described previously [20] after 48 hours of ID8 Trp53−/− cell i njection in the ovaries. Mice were closely monitored for post -surgical recovery over 5 days, and tumor growth was tracked every 10 days using whole -body bioluminescence imaging (BLI) on a Perkin Xenogen IVIS Imaging System following intraperitoneal injection of luciferin (50 mg/kg). Time-to-Threshold Disease Progression Analysis (Fixed Biological Threshold) : Disease progression in comparing young versus old mice was quantified using a time -to-threshold framework in which the event was defined as the first attainment of a pre -specified biological disease burden. For peritoneal dissemination studies, the threshold was defined a priori as ≥2.77 cm² peritoneal spread or a corresponding abdominal girth criterion reflecting maximum tolerable tumor burden. For each mouse, time to reach this threshold was recorded as the event. Kaplan – Meier curves were generated and compared using the log -rank test, with hazard ratios estimated by Cox proportional hazards modeling. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 17 Time-to-Threshold Disease Progression Analysis (Control -Derived Reference Threshold) : In studies using abdominal girth as the progression metric, a control -derived reference threshold was employed. The threshold was defined exclusively from the control cohort as the mean change in abdominal girth from baseline to endpoint. This control -derived benchmark was then applied uniformly to both control and treatment groups. For each mouse, the time to reach this benchmark was scored as the event . Kaplan Meier curves were generated and compared using the log-rank test, with hazard ratios estimated using Cox proportional hazards regression. Spatial Nanostring GeomMx analysis of Ovarian tumors : RNA profiling of ovarian tumors from young and aged mice was performed using the mouse Whole Transcriptome Atlas probes using GeoMx™ DSP Nanostring technology per manufacturer’s guidelines. In brief, paraffin- embedded 5µm ovarian sections were baked at 60°C for 1 hour. They were stained with labeled Goat anti-mouse CD45 (Cat no. AF114 1:100, Novus biologicals) primary antibody using FITC Conjugation Kit (Cat no. ab188285, Abcam) and Labeled Rat anti -mouse CK8 primary antibody (Cat no. Sc 8010, 1:100, Santa Cruz Biotechnology) using APC Conjugation Kit (Cat no. ab201807, Abcam) for immune and tumor cells detection respectively. Following primary antibodies incubation for 2 hours at room temperature, nuclei were stained with Syto TM 82, Orange fluorescent Nucleic acid stain (Cat no. S11363, Sigma). Regions of interest (ROIs) were selected using a combination of immunofluorescent staining and H&E staining. ROIs were classified as general areas to obtain an un biased overview of the microenvironment such as tumor cells (CK8+) or immune cells (CD45+). Upon ROI collection on the GeoMx Digital Spatial Profiler (DSP), libraries were prepared and sequenced on the Illumina NovaSeq instrument (UAB, Genomics core facility). FASTQ files were uploaded to the Base Space Illumina hub and converted to digital count conversion (dcc) files using the GeoMx® NGS Pipeline (v2.0.21) on Illumina DRAGEN. The analysis was performed in R following the manufacturer’s analysis code (https://www.bioconductor.org/packages/release/workflows/vignettes/GeoMxWorkflows/inst/do c/GeomxTools_RNA-NGS_Analysis.html). ROIs with less than 80% sequencing alignment or less than 50% sequencing saturation were removed from further analysis. The Grubbs outlier test was used to identify outlier probes. The limit of quantification (LOQ) was defined as two standard deviations above the geometric mean of the negative probes. ROIs were then divided .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 18 into general areas, and CD45 + immune cell genes below LOQ in at least 10% of ROIs were removed from further analysis. Normalization was performed using a signal -based quartile normalization method, where individual counts are normalized against the 75th percentile of signal from their ROI. Group comparisons were done using a mixed linear model as previously described. Normalized counts can be accessed here: doi: 10.17632/j4f8r6z3b3.1.. Normalized gene counts were used for Gene Set Enrichment Analysis (GSEA) using GSEA 4.3.3 (Broad Institute, UCSD, San Diego) [58], and immune cell abundances analysis CIBERSORTX was used after converting gene IDs from mouse to human on SynGO (Synaptic Gene Ontologies and annotations) [17, 59]. Immune infiltration association with ovarian cancer patient survival was performed using Timer 2.0 [60]. Heat maps were generated using Heatmapper2 [61] and KEGG pathway analysis was performed using the SRPlot platform [62]. Immunohistochemistry: Ovarian and omental tumor sections were stained as previously described [55]. Antigen retrieval was performed by boiling the section in sodium citrate buffer (pH 6.0) for 30 minutes, followed by incubation in 3% hydrogen peroxide at room temperature for 15 minutes to block endogenous peroxide activity; sections were then washed twice in PBS for 5 minutes each and blocked with Background Punisher (BioCare, Cat. no. BP974) for 15 minutes at room temperature. Sections were then incubated at 4°C overnight in primary antibodies for Proliferation cell nuclear antigen PCNA (586, PC10, 1:500), and CD206 (24595, E6T5JXP,1:200) diluted in Da Vinci Green diluent (BioCare Cat no. PD900). Detection was performed using the MACH4 universal HRP-polymer (BioCare, cat no. MACH 4™) kit followed by the Betazoid DAB Chromogen Kit (BioCare, cat no BDB2004) as per manufacturer’s instructions. Sections were counterstained with hematoxylin for 1 minute, dehydrated through ethanol gradients (70%, 90%, and 100%), and cleared in Xylene for 1 minute, followed by mounting in Fisher Chemical TM Paramount TM mounting medium (SP15-100) for microscopic analysis. A minimum of five regions per tumor core from each mouse were analyzed using QuPath (v0.5.0) Bioimage analysis software [63] and presented as a percentage of total cells. Immunofluorescence: For Immunofluorescent detection of immune cells, Ovarian and omental sections were processed similarly to IHC until antigen blocking, omitting peroxidase treatment. Sections were incubated overnight at 4°C with primary antibodies, including Goat anti -mouse .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 19 CD45 (Cat no. AF114 1:100, Novus biologicals) for immune cells , anti -rabbit Arginine1(93668, D4E3MTM XP,1:100) and rat anti -mouse CD68 (MCA341, FA -11,1:100) for macrophage detection and Foxp3 (D6O8R) 12653 (1:100) for regulatory T cells. Antibodies were diluted in Da Vinci Green diluent (Biocare Cat no. PD900). Following primary antibody incubation, sections were washed twice in PBS with 1% tween -20 for 5 minutes and incubated with secondary antibodies, Goat anti -Rabbit IgG Alexa Fluor ™ 594 (A11012), Goat anti -Rabbit IgG 488 (A11008), and Donkey anti -rat IgG 488 (A48269TR), at 1:500 each for 2 hours at room temperature. Nuclei were counterstained with DAPI for 5 minutes, and sections were mounted using ProLong™ Gold Antifade Mountant (Cat no. P36930). Multiple Immunofluorescence images (3-5 per tumor core from each mouse) were analyzed using QuPath (v0.5.0) Bioimage analysis software[28]. Double-positive cells were manually counted using Fiji (ImageJ) software [29] by an investigator blinded to the study. Results were presented as the percentage of total positive cells. Flow cytometry: A scites fluid was collected from the mice's peritoneal cavity, and cells were separated from fluid after centrifugation at 1200 rpm at 4°C. Red blood cells were lysed using RBC lysis with incubation at room temperature for 10 minutes. For the Vismodegib inhibition experiment ovaries and omentum were collected at endpoints (Day 42), after perfusing mice with PBS, digested using Collagenase II (Thermo Fisher Cat no.17101015, 1.0   mg/mL), and DNase I (Sigma Cat no. 10104159001, 25  μg/mL) for 30 minutes at 37°C, passed through 70µm nylon mesh and RBCs were lysed as described above. Freshly isolated cells were stained sequentially with Live/Dead (Zombie Yellow TM, Cat no, 423103, Biolegend) for 15 minutes at room temperature followed by Fc -receptor blockade (rat ani -mouse CD16/CD32, Cat no 553141) for 10 minutes on ice and fluorophore -labeled antibodies: PerCP/Cyanine5.5- labeled, anti -mouse CD45 Cat no. 103131 or FITC -labeled anti -mouse CD45 Cat no. 147709, PerCP /Cyanine5.5 labeled anti-mouse F4/80 Cat no.123107, APC -labeled anti-mouse CD80 Cat no. 104714, APC - labeled anti-mouse CD206 Cat no.141706, PerCP /Cyanine5.5- labeled anti-mouse CD3 Cat no. 100218, PE/Cy7-labeled anti-mouse CD4 Cat no. 100422, APC labeled anti -mouse CD8 Cat no. 10071, APC -labeled anti -mouse CD25 Cat no. 102012, PE -labeled anti -mouse Foxp3 cat no. 126403 for 30 minutes on ice in flow cytometry buffer (FACS) containing 2% fetal bovine serum in PBS at recommended concentrations. For Foxp3, intracellular staining, cells were .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 20 permeabilized using True -Nuclear™ Transcription Factor buffer kit (Cat no. 424401, Biolegend). Post -staining, cells were resuspended in FACS buffer and analy zed on BD FACSymphony flow cytometer, and data were analyzed using FlowJo TM v10 software (TreeStar Inc., Ashland, OR USA). Statistical analysis : All data were compared using unpaired Student t- tests and presented as mean ± SEM. Data was analyzed using Graph Pad Prism 9.0 (La Jolla, CA, USA), and statistical significance was considered at p < 0.05.

Funding for this work was provided in part by NIHR01CA219495 and O’Neal Invests grant to Mythreye Karthikeyan (KM). This study was supported by National Institutes of Health (NIH) award NIHR00AG068309 an AFAR Grant for Junior Faculty awardee to Daniel Tyrrell (DJT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript . We want to acknowledge the UAB flow cytometry core facility, (AI027767), O’Neal Cancer Center, P30CA013148, and shared instrument grant S100D032296. We also acknowledge the Preclinical Imaging Shared Facility (P30CA013148, 1S10OD021697), High Resolution Imaging Facility and the Pathology Core Research Lab at UAB for assistance with processing the histological specimens . Schematics were made using Biorender (licensed agreement to KM and UAB) . We thank Manan Nayyar and Emily O’Brian for technical assistance, Dr. Arend for sharing cell lines and Dr. Darshan Shimoga Chandrashekar for helpful discussions. Author contributions Conceptualization: KM, AK. Investigation: AK, CM. MHE, RR, KS, MM, LMQ, DJ T, LAS, CMM, RR, AK, LQM, SS, FM, MC. Analysis: KM, CM, AK, KS, Reagents: AK, KF, DJ T, LAS Resources/Supervision: KM, CM, DT, LAS . Writing : original draft: AK, KM Writing: .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint 21 review & editing: all authors. Funding acquisition as described in acknowledgements and project administration: KM Data availability statement GeoMx data are available at doi: 10.17632/j4f8r6z3b3.1. Additional data are available from the corresponding author upon reasonable request.

Aging, Ovarian cancer, menopausal changes, vasculatures, Angiogenesis

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QuPath: Open source software for digital pathology image analysis. Scientific Reports. 2017; 7(1):16878. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint Figure 1. ( A)(i)&(iv) Representative images of tumor burden in the ovaries and omentum of mice of the indicated age groups. (ii) Quantification of ovar y weights (iii) ascites fluid volume (v) omental weights (vi) total tumor burden, on day 55 post intrabursal implantation of ID8Trp53−/−cells in young and aged mice ovaries (n=9). (B-C) Immunohistochemical analysis of proliferating nuclear antigen (PCNA) in (B)(i) ovarian and (C)(i) omental tumors from young and aged mice in ID8Trp53−/−model, (ii)&(iii) Percentage of PCNA-positive cells in ovarian and omental tumors ( n=3). (D)(i)&(iv) Representative images of tumor burden in the ovaries and omentum of mice of the indicated age groups. ( ii) Quantification of ovary weights (iii) ascites .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint fluid volume (v) omental weights (vi) tota l tumor burden on day 42 following intrabursal implantation of murine fallopian tube -derived PPNM cells in young and aged mice ovaries (n=8). PCNA immunohistochemistry of (E)(i) ovarian and (F)(i) omental tumors from young and aged mice in the PPNM model, showing (ii) & (iii) percentage and intensity of PCNA -positive cells in ovarian and omental tumors (n= 3). Color codes and symbols in the graphs represent the number of images analyzed per mouse. All data are presented as mean±SEM, *p<0.05,**p<0.01, ***p<0.001, ****p<0.0001, unpaired t test. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint Figure 2. (A-B) Representative multiplex immunofluorescence images of an ovarian tumor from young or aged hosts. Tumor cells are identified as CK8⁺(yellow), immune cells as CD45⁺ (white), endothelial cells as CD31⁺(red) , and nuclei (blue). Magnified panels highlight representative regions of interest (ROIs) selected from CD45⁺depleted or CD45⁺enriched areas for Spatial GeoMx analysis (n=3). (C) Intra-tumoral Gene Set Enrichment Analysis (GSEA) comparing CD45⁺depleted or CD45⁺-enriched regions from (i) young and (ii) aged hosts tumors using normalized enrichment scores (NES) against MSigDB Hallmark gene set s (FDR<0.05). (D) Heatmaps depicting unique inflammatory genes contributing to the ‘Inflammatory Hallmark’ enrichment in ovarian tumors from (i ) young (i i) aged hosts . ( E) CD45 + cells deconvolution using CIBERSORTX from young and aged host tumors . (F)(i-iv) GSEA of CD45⁺ -enriched regions compared between young and aged hosts using Hallmark gene sets ( FDR<0.05). (G) (i- iii) The top three upregulated genes in aged host ovarian tumors are associated with higher B cells and prolonged survival of high- grade ovarian cancer patients , and (i v-vi) The top three upregulated genes in aged host ovarian tumors are associated with higher M2 macrophages and lower survival of high-grade serous ovarian cancer patients. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint Figure 3 . (A-B) Representative i mmunofluorescence images from ovarian tumors (A)(i) ID8Trp53−/− (B)(i) PPNM cells in ovarian tumors showing CD45+(green), Arg1+(red), and DAPI (blue). Adjacent graphs ( A)(ii) and (B)(ii) showing quantification of percentage CD45+Arg1+ cells in ovar ian tumors from both models . (C-D) Representative immunofluorescen ce images from (C)(i) ID8Trp53−/− (D)(i) PPNM cells in ovarian tumors showing CD68+(green), Arg1+(red), and DAPI ( blue) cells. Quantification of percentage C D68+Arg1+ cells (C)(ii) and (D)(ii) showing ovarian tumors from both models . (E-F) Immunohistochemistry of ovarian tumors showing CD206 + cells (E)(i) ID8 Trp53−/− (F)(i) PPNM cells in ovarian tumors. Quantification of percentage CD206 +cells. (E)(ii) and (F)(ii) in both models . (G-H) Representative immunofluorescence images of Foxp3 +(red) and DAPI (bl ue) immunostaining(G)(i) ID8Trp53−/− (H)(i) PPNM in ovarian tumor. Graphs (G)(ii) and (H)(ii) showing quantification of percentage Foxp3+ cells in both models. (I-J) Representative immunofluorescence images from (I) (i) ID8Trp53−/− (J)(i) PPNM cells in omental tumors showing CD45+(green), Arg1+(red), and DAPI(blue). Adjacent graphs (I)(ii) and (J)(ii) showing quantification of percentage CD45+Arg1+ cells in omental tumors from both models. (K-L) Representative i mmunofluorescence images from (K) (i) ID8Trp53−/− (L)(i) PPNM cells in omental tumors showing CD68 +(green), Arg1+(red), and DAPI ( blue) cells. (K) (ii) and (L)(ii) Quantification of percentage CD68 +Arg1+ cells showing omental tumors from both models in (p=0.169 and p<0.05, respectively). (M-N) Immunohistochemistry images of omental tumors showing CD206+ cells (M)(i) ID8Trp53−/− (N)(i) PPNM cells in o mental tumors. (M)(ii) and (N)(ii) Quantification of percentage CD206 + cells in both models. (O-P) Representative immunofluorescence images of Foxp3 +(red) and DAPI ( blue) immunostaining ( O)(i) ID8Trp53−/−(P)(i) PPNM in omental tumor. Adjacent graphs (O)(ii) and (P)(ii) showing quantification of percentage Foxp3 + cells in both models. Color codes and symbols indicate the number of images analyzed per mouse in each group. All data are m eant SEM (n=3), *p<0.05, **p<0.01, *** p<0.001, ****p<0.0001, unpaired t test. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint Figure 4. (A) Schematic of Hedgehog pathway (B) Treatment regimen of Vismodegib post ID8Trp53−/−cell implantation in the left ovaries of aged mice . (C) Probability plot based on abdominal girth changes showing probability of remaining below control derived threshold (n=9). (D) Ascites fluid collected from both groups at the endpoint. (i) vehicle (ii) vismodegib, showing percentage of mice with or without ascites ( E) Representative images of diaphragmatic mets (i) v ehicle (ii) vismodegib, (iii)&(iv) showing percentage of mice with or without diaphragmatic Mets in each group . (F) Representative images of m ets on peritoneal wall (i) Vehicle (ii) Vismodegib, (iii)&(iv) showing percentage of mice with or without peritoneal wall .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint mets in each group (G) Representative images of (i) ovaries and (ii) ovary weights at end points (p=0.179) (iii) Representative images of PCNA Immunohistochemistry in ovarian sections (iv) & (v) %PCNA, positive cells (n=3). (H) Representative images of (i) omentum (ii) omental weights at endpoint (iii) Representative images of PCNA Immunohistochemistry in omental sections (iv)&(v) %PCNA, positive cells. All data are meant SEM(n=3), *p<0.05, **p<0.01, ***p<0.001, ***p<0.0001, unpaired t test Figure 5. (A-B) Representative immunofluorescence images of CD45 +(green), Arg1+(red), and DAPI (blue) in (A)(i) ovarian (B)(i) omental tumors from vismodegib and vehicle treated mice. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint Adjacent graphs showing percentage of CD45 +Arg1+cells in (A)(ii) ovarian tumors (p=0.062) and (B)(ii) in omentum (p=0.372). (C-D) Representative immunofluorescence images of CD68+(green), Arg1+(red), and DAPI (Blue) in (C)(i) ovarian or (D)(i) omental tumors from vismodegib and vehicle treated mice. Adjacent graphs showing percentage of CD 68+Arg1+cells in (C)(ii) ovaries (p=0.502), (D)(ii) in omentum (p=0.317). (E-F) Immunohistochemistry of CD206+ cells in (E)(i) ovarian (F)(i) oment al tumors. Adjacent graph showing percentage CD206+ cells (E)(ii) in ovaries and (F)(ii) in omentum (p=0.624). (G-H) Representative immunofluorescence images of Foxp3 + (red) and DAPI (Blue) cells (G)(i) ovarian (H)(i) omental tumors. Adjacent graph showing percentage Foxp3 + cells in (G)(ii) ovarian and (H) (ii) omental tumors. Color codes and symbols indicate the number of images analyzed per mouse in each group. All data are presented as mean±SEM (n=3), *p<0.05, **p<0.01, ***p<0.001, ***p<0.0001, unpaired t test. .CC-BY 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted December 27, 2025. ; https://doi.org/10.64898/2025.12.23.695206doi: bioRxiv preprint