Alnawaz Rehemtulla

Resistance to CDK4/6 inhibitors (CDK4/6i) combined with endocrine therapy presents a major barrier to improving outcomes in ER ⁺ breast cancer. We identified FADD phosphorylation at Ser194 (phospho-FADD) as a mediator of CDK4/6i resistance in the models examined. Phospho-FADD acted as a pseudosubstrate inhibitor of the APC/C-Cdh1 complex, promoting G1/S transition and bypassing the canonical CDK4/6-Rb-E2F pathway. This CDK4/6-independent pathway was associated with PI3K hyperactivation. Clinical relevance of this bypass pathway was supported by increased phospho-FADD and pAKT in 73% of paired patient biopsies at posttreatment recurrence, while the remaining cases exhibited high baseline phospho-FADD and pAKT with intrinsic nonresponse. Inhibition of FADD phosphorylation with the CK1α degrader DEG-77, or PI3K inhibition, restored CDK4/6i sensitivity in resistant cells. In CDK4/6i-refractory xenografts, CK1α degradation combined with CDK4/6i resulted in profound tumor regressions and increased progression-free survival compared with either single agent, including complete tumor regressions in 92% of tumors. These findings support CK1α-mediated FADD phosphorylation as a targetable resistance mechanism in a subset of CDK4/6i-resistant ER ⁺ /HER2 ^– breast cancer.

Supplemental Figure 2. (A) Tumor growth inhibition analysis for Figure 2A conducted on day 13. Tumor growth inhibition was calculated [1-(average tumor volume of treated group/average tumor volume of control group)] x 100%. Mean tumor volume (MTV) ± standard deviation (SD) are denoted for each treatment group along with the calculated percent tumor growth inhibition (%TGI). (B) C57BL/6 mice with subcutaneous mT4 tumors were treated with αPD-L1 pre-, concurrent, or post-olaparib and radiation treatment. The different schedules are concurrent treatment with αPD-L1 (olaparib on days 1-5, and 8-12; radiation on day 1; αPD-L1 treatment on days 0 and 3), pre-treatment with αPD-L1 (olaparib on days 7-11 and 14-18; radiation on day 7; αPD-L1 treatment on days 0 and 3) and post-treatment with αPD-L1 (olaparib on days 0-4 and 7-11; radiation on day 0; αPD-L1 treatment on days 7 and 10). Data represent mean tumor volumes ± SEM from n= 10 (IgG), 20 (concurrent treatment), 20 (pre-treatment), and 20 (post-treatment) tumors per treatment group. (C) Serum was collected for each treatment condition on day 15 from 3 mice undergoing treatment in panel B. Complete blood cell count was conducted at the University of Michigan by the Unit for Laboratory Animal Medicine (RRID: SCR_025790) using a Heska HT5 Element. Percentage of white blood cells and lymphocytes from total serum are shown. (D) Tumor growth inhibition analysis for Figure 2B conducted on day 13. Tumor growth inhibition was calculated [1-(average tumor volume of treated group/average tumor volume of control group)] x 100%. MTV ± SD are denoted for each treatment group along with the calculated TGI. (E) Mouse weights monitored throughout treatment with olaparib, radiation, and αPD-L1. This data is from mice used Figure 2F. Data represent the average mouse weight (g) ± SEM from n= 6 (IgG), 7 (αPD-L1), 6 (olaparib+IgG), 7 (olaparib+αPD-L1), 8 (RT+IgG), 10 (RT+αPD-L1), 7 (olaparib+RT+IgG) and 9 (olaparib+RT+αPD-L1) mice per treatment group. (F) Individual tumor growth curves from mice used in Figure 2F. Data are represented as tumor volume and show n= 6 (IgG), 7 (αPD-L1), 6 (olaparib+IgG), 7 (olaparib+αPD-L1), 8 (RT+IgG), 10 (RT+αPD-L1), 7 (olaparib+RT+IgG), and 9 (olaparib+RT+αPD-L1) tumors per treatment group. (G, H) Tumor growth inhibition analysis for Figure 2D conducted on day 31 (G) and Figure 2F conducted on day 44 (H). Tumor growth inhibition was calculated [1-(average tumor volume of treated group/average tumor volume of control group)] x 100%. MTV ± SD are denoted for each treatment group along with the calculated TGI.

Supplemental Figure 6. (A, B) Tumor growth inhibition analysis for Figure 6A conducted on day 42 (A) and Figure 6C conducted on day 32 (B). Tumor growth inhibition was calculated [1-(average tumor volume of treated group/average tumor volume of control group)] x 100%. MTV ± SD are denoted for each treatment group along with the calculated TGI.

Supplemental Figure 5. (A) C57BL/6 mice with subcutaneous mT4 tumors were treated as illustrated in Figure 2E tumors were harvested at day 4. Tumors were analyzed via flow cytometry for presence of Ki67+. Data represent mean ± SEM (n=5 tumors per treatment group) and are represented as percentage from CD8a+ cells.

Supplemental Figure 1. (A-S) Pancreatic cancer cells were treated with olaparib (5 µmol/L) one hour before radiation treatment (8 Gy) and collected 72 hours after treatment for analysis via flow cytometry, qRT-PCR or ELISA, unless otherwise denoted. (A) Panc-1 cells stably expressing IFNβ1-promoter GFP-reporter were treated with radiation and/or talazoparib (10 nmol/L or 30 nmol/L). Analyzed via flow cytometry for mean fluorescence intensity (MFI) of GFP. Data are the mean of 3 independent experiments. (B) KPC2 cells were treated with olaparib (3µmol/L or 5µmol/L) and/or radiation (8 Gy) and collected at 24 hours, 48 hours, and 72 hours after radiation treatment. qRT-PCR was conducted for Ifnβ. Data are the mean fold change ± SEM relative to control treatment for each time point and represent 1 independent experiment performed in technical triplicate. (C) Panc-1 cells in which cGAS was knocked out using a CRISPR/Cas9 system were treated with olaparib and/or radiation and harvested for analysis via western blot for pTBK1, pSTAT1, STAT1 and Actin. (D-F) KPC2 cells were treated with olaparib (3µmol/L or 5µmol/L) and/or radiation (8 Gy) and collected at 24 hours, 48 hours, and 72 hours after radiation treatment. qRT-PCR was conducted for Cxcl9 (D), Cxcl10 (E), and Mx1 (F). Data are the mean fold change ± SEM relative to control treatment for each time point and represent 1 independent experiment performed in technical triplicate. (G-I) KPC2 cells were treated with olaparib (5µmol/L) one hour before various doses of radiation (2 Gy, 4 Gy, 6 Gy, 8 Gy, 10 Gy, 2 GyX3). Cells were collected 72 hours after treatment and RNA was extracted. qRT-PCR was conducted for Ifnβ (G), Cxcl9 (H), and Cxcl10 (I). Data are the mean fold change ± SEM relative to control treatment and represent 3 independent experiments performed in technical triplicate. (J, K) qRT-PCR targeting Mx1 in KPC2 (J) and mT4 (K) cells. Data are shown as mean fold change ± SEM relative to the control treatment and represent 4 (J) or 3 (K) independent experiments performed in technical triplicate. (L, M) Protein abundance quantification of CXCL9 (L) and CXCL10 (M) via ELISA in the media from KPC2 cells 72 hours after treatment with olaparib (3µmol/L or 5µmol/L) and/or radiation. Herring testis DNA (HS DNA) was transfected into cells (2µg) as a positive control. Data are average protein abundance ± SD. The graphs presented are representative of 2 independent experiments run in technical triplicate. (N) KPC2 cells treated in the absence or presence of IFNAR1 blocking antibody (5 µg/mL). Cells were collected 72 hours later and analyzed via flow cytometry for surface PD-L1 expression. Data are shown as MFI ± SEM relative to control treatment and represent 3 independent experiments performed in technical triplicate. (O-S) Flow cytometry analysis of PD-L1 (O, P) or MHC-I (Q-S) surface expression on MiaPaCa2 (O, R), AsPC-1 (P, S), and Panc-1 (Q). Data are shown as MFI ± SEM relative to control treatment and represent 1 (P, S), 2 (O, R) or 3 (Q) independent experiments performed in technical triplicate. Statistical significance was determined by a one-way ANOVA test (N) or a two-tailed, unpaired t test (A, G-I, J). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001

Supplemental Figure 3. (A) UMAP projections of all cell clusters from harvested subcutaneous mT4 tumors following 5 days of treatment. Mice were treated with 1 dose (8 Gy) radiation on day 0, five doses olaparib (50 mg/kg) on days 0-4, and two doses of αPD-L1 (100 µg) on days -1, and 2. Tumors were harvested on day 4. (B) Dotplot showing an incomplete list of markers used to name cell clusters. The size of the circle represents the percentage of cells within that cluster that express the given gene. The color represents the average fold change expression of that gene within that cluster. (C) Gene signature analysis conducted on all cells for the listed immune signaling pathways. Enrichment module (EM) scores were calculated from gene signature scores using the following equation: (1/2 x Q2) + (1/4 x Q1) + (1/4 x Q3). EM scores for the indicated pathways were combined to create the resultant heatmap. (D, G) PDAC (D) and myeloid (G) cell clusters colored by corresponding treatment group (D) or by cell identity (G). (E) Gene signature analysis on PDAC cells for immune signaling pathways. Gene signature module scores were averaged and combined for each of the listed pathways to make the resultant heat map. (F, H) GSEAplots of important pathways which showed enrichment in PDAC cell comparisons (F) or myeloid cell comparisons (H) following GSEA. These include G2M checkpoint, interferon alpha response, interferon gamma response, and UV response down for the comparison between olaparib+radiation+αPD-L1 PDAC cells and radiation+αPD-L1 PDAC cells (F), interferon gamma response and interferon alpha response for the comparison between olaparib+radiation+αPD-L1 myeloid cells and control treatment myeloid cells, and TGFβ signaling and oxidative phosphorylation for the comparison between olaparib+radiation+αPD-L1 myeloid cells and radiation+αPD-L1 myeloid cells (H). (I) Violin plots displaying gene signature analysis conducted on macrophages for M2 macrophage phenotype and phagocytosis. Statistical significance was determined by Wilcoxon test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001

Supplemental Figure 4. (A-D) Workflow of CD8+ T cell isolation. All T cells (excluding cycling T cells) were isolated (A) and CD8+, CD4+, and NK status was determined (B). CD8+ T cells were further isolated and clustered (C). CD8+ only status was confirmed via violin plots of Cd8a, Cd4, and Fcer1g (D). (E) UMAP projection of CD8+ T cell clusters split by treatment group. (F) Bar plot displaying the percentage of total cells sequenced identified as B cells. (G) GSEAplots of important pathways found to be enriched in CD8+ T cell comparisons following GSEA including interferon alpha response, interferon gamma response, IL2/STAT5 signaling, and G2M checkpoint for the comparison between olaparib+radiation+αPD-L1 CD8+ T cells and radiation+αPD-L1 CD8+ T cells.

PARP inhibitors sensitize pancreatic ductal adenocarcinoma (PDAC) to radiation by inducing DNA damage and replication stress. These mechanisms also have the potential to enhance radiation-induced type I interferon (T1IFN)–mediated antitumoral immune responses. We hypothesized that the PARP inhibitor olaparib would also potentiate radiation-induced T1IFN to promote antitumor immune responses and sensitization of otherwise resistant PDAC to immunotherapy. To test this hypothesis, we assessed the effects of olaparib and radiation on T1IFN production and sensitivity to αPD-L1 immunotherapy, as well as on the tumor microenvironment by single-cell RNA sequencing. We found that olaparib enhanced T1IFN production after radiation and had superior therapeutic efficacy in immunocompetent models. Olaparib and radiation treatment sensitized PDAC tumors to αPD-L1, resulting in decreased tumor burden and a 33% complete response rate. Combination treatment provided durable immune responses as shown by tumor rejection upon tumor rechallenge of previously cured mice. Furthermore, single-cell RNA sequencing analysis revealed that combination treatment induced an immunogenic tumor microenvironment characterized by interferon (IFN) responses in both PDAC and myeloid cell populations, macrophage polarization, and increased CD8+ terminal effector T-cell frequency and activity, findings which were confirmed by IHC and flow cytometry. Furthermore, CD8+ T cells and T1IFN signaling were required for therapeutic efficacy as host depletion of CD8+ T cells or the T1IFN receptor diminished treatment responses. Overall, our results indicate that olaparib enhances radiation-induced T1IFN-mediated immune signaling and subsequently an adaptive immune response, thus sensitizing pancreatic cancer to αPD-L1 therapy, supporting an ongoing clinical trial of this therapy in patients with PDAC. See related commentary by Buchsbaum, p. 840

Adipose tissue macrophage (ATM) infiltration is associated with adipose tissue dysfunction and insulin resistance in mice and humans. Recent single-cell data highlight increased ATM heterogeneity in obesity but do not provide a spatial context for ATM phenotype dynamics. We integrated single-cell RNA-Seq, spatial transcriptomics, and imaging of murine adipose tissue in a time course study of diet-induced obesity. Overall, proinflammatory immune cells were predominant in early obesity, whereas nonresident antiinflammatory ATMs predominated in chronic obesity. A subset of these antiinflammatory ATMs were transcriptomically intermediate between monocytes and mature lipid-associated macrophages (LAMs) and were consistent with a LAM precursor (pre-LAM). Pre-LAMs were spatially associated with early obesity crown-like structures (CLSs), which indicate adipose tissue dysfunction. Spatial data showed colocalization of ligand-receptor transcripts related to lipid signaling among monocytes, pre-LAMs, and LAMs, including Apoe, Lrp1, Lpl , and App . Pre-LAM expression of these ligands in early obesity suggested signaling to LAMs in the CLS microenvironment. Our results refine understanding of ATM diversity and provide insight into the dynamics of the LAM lineage during development of metabolic disease.