Mutations in BRCA1 and BRCA2 differentially affect the tumor microenvironment and response to checkpoint blockade immunotherapy

Abstract

Immune checkpoint blockade (ICB) has improved outcomes for patients with advanced cancer, but the determinants of response remain poorly understood. Here we report differential effects of mutations in the homologous recombination genes BRCA1 and BRCA2 on response to ICB in mouse and human tumors, and further show that truncating mutations in BRCA2 are associated with superior response compared to those in BRCA1. Mutations in BRCA1 and BRCA2 result in distinct mutational landscapes and differentially modulate the tumor-immune microenvironment, with gene expression programs related to both adaptive and innate immunity enriched in BRCA2-deficient tumors. Single-cell RNA sequencing further revealed distinct T cell, natural killer, macrophage, and dendritic cell populations enriched in BRCA2-deficient tumors. Taken together, our findings reveal the divergent effects of BRCA1 and BRCA2-deficiency on ICB outcome, and have significant implications for elucidating the genetic and microenvironmental determinants of response to immunotherapy.

Extended Data Fig. 1|. Sequence traces of Brca2^null cell lines demonstrating frameshift mutations in all alleles.

PCR amplification and TOPO-TA cloning of individual allele copies was performed surrounding the CRISPR target guide sites to confirm that all alleles contain a frameshift or truncating mutation in Exon 3 of 4T1 Brca2^null a, and CT26 Brca2^null b, cell lines. Arrows indicate primer or probe locations. c-d, qRT-PCR amplication of Brca2 WT-specific allele in cDNA generated from RNA isolated from cell lines using SYBR green based assay (c) and TaqMan based assay (d), n=3 technical replicates for c and d. Data are presented as mean values +/− SD

Extended Data Fig. 2 |. Characterization of the Brca2^null cell line.

a-b Representative images of parental (a) and Brca2^null (b) CT26 cell karyotype analysis demonstrating increased double strand breaks. c, Quantification of karyotype analysis shown in a representing n=100 metaphases analyzed demonstrating the percent of metaphase nuclei containing at least 1 of indicated abnormality. d, Quantification of karyotype analysis in 4T1 cells shown in Fig 2D representing n=100 metaphases analyzed demonstrating the percent of metaphase nuclei containing at least 1 of indicated abnormality. e, Quantification of immunofluorescent images of parental and Brca2^null CT26 murine colorectal adenocarcinoma cells 4 hours after 10 Gy irradiation stained with DAPI and antibodies to Rad51 and gamma-H2ax. f, In vitro relative viable cell count of parental and Brca2^null CT26 cell lines in the presence of PARP inhibitor olaparib at indicated concentrations after 96 hours in three independent assays in technical triplicate. Data are presented as mean values +/− SEM. g-h, Tumor growth curve of parental and additional Brca2^null clones with ICB treatment in both the 4T1(g) and CT26 models (h). (* p<0.05, ** p<0.005,*** p<0.0005, **** p<0.00005). All p values represent two-sided unpaired t test at respective timepoint. Data are presented as mean values +/− SEM

Extended Data Fig. 3 |. Characterization of the genomic alternation in 4T1 Brca2^null clones.

a, The 96 base substitution pattern for Brca2^null and Brca1^null single-cell clones after subtraction of background mutagenesis pattern derived from parental clones. Signature 3, previously associated with HRD (i.e. Signature 3), is provided for reference. b, Cosine similarity of BRCA2-null experimentally derived mutational signature to previously described mutational signature related to COSMIC Signature 3. c, Proportion of deletions with microhomology in 4T1 Brca2^null single-cell clones compared to parental single clones (two-sided Fisher’s exact test P<0.0001, for all mutant single cell clones compared to parental). d, Cosine similarity of Brca1^null experimentally derived mutational signature to previously described mutational signature related to COSMIC Signature 3. e, Proportion of deletions with microhomology Brca1^null single-cell clones compared to parental single clones using a two-sided Fisher’s exact test P<0.0001, for all mutant single cell clones compared to parental).

Extended Data Fig. 4 |. Bulk RNA-seq analysis between untreated Brca2^null and WT tumors yields gene expression programs related to adaptive and innate immune activation enriched in Brca2^null tumors.

a, Heatmap displaying all 4,637 genes significantly differentially expressed (FDR < 0.05) between untreated Brca2^null and Brca2-WT murine tumors from the 4T1 model. Data show drastic gene expression changes upon Brca2 inactivation in-vivo. P-values calculated from two-sided differential expression analysis using DESeq2 (Wald test) and corrected for multiple testing using the Benjamini-Hochberg method b, Pathway analysis on genes from a using GO pathways. Top enriched pathways in either Brca2^null or Brca2^WT tumors are shown. Color gradient of red to purple indicates decreasing adjusted p-value; circle size indicates number of genes in pathway. GeneRatio on x-axis indicates number of significantly differentially expressed genes from RNA-seq overlapping with genes in each pathway. P-values for overlap between input genes and pathway genesets calculated via two-sided hypergeometric test and corrected for multiple comparisons using the Benjamini Hochberg method. c, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05, two-sided Wald test from DESeq2) between Brca2^null and WT tumors from the Immune Response pathway. d, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05, two-sided Wald test from DESeq2) between Brca2^null and WT tumors from the T cell activation pathway. e, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05, two-sided Wald test from DESeq2) between Brca2^null and WT tumors from the Biocarta cytokines pathway. f, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05, two-sided Wald test from DESeq2) between Brca2^null and WT tumors from the Hallmark IFNA Signaling pathway. g, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05, two-sided Wald test from DESeq2) between Brca2^null or Brca2^WT tumors from the NK-mediated cytotoxicity pathway. For c-g, P-values calculated from two-sided differential expression analysis using DESeq2 (Wald test) and correct for multiple testing using the Benjamini-Hochberg method.

Extended Data Fig. 5 |. Bulk RNA-seq analysis between untreated Brca2^null and Brca1^null tumors yields gene expression programs related to adaptive and innate immunity enriched in Brca2^null tumors.

a, Heatmap displaying all 6,881 genes significantly differentially expressed (FDR < 0.05) between untreated Brca2^null and Brca1^null murine tumors from the 4T1 model. Data show drastic gene expression changes upon Brca2 inactivation. P-values calculated from two-sided differential expression analysis using DESeq2 (Wald test) and corrected for multiple testing using the Benjamini-Hochberg method. b, Pathway analysis on genes from a using GO pathways. Top enriched pathways in either Brca2^null or Brca1^null tumors are shown. Color gradient of red to purple indicates decreasing adjusted p-value; circle size indicates number of genes in pathway. GeneRatio on x-axis indicates number of significantly differentially expressed genes from RNA-seq overlapping with genes in each pathway. P-values for overlap between input genes and pathway genesets calculated via two-sided hypergeometric test and corrected for multiple comparisons using the Benjamini Hochberg method. c, Heatmap for genes significantly differentially expressed in a associated with interferon gamma signaling between Brca2^null and Brca1^null murine tumors from the 4T1 model. d, Heatmap displaying for genes significantly differentially expressed in a associated with T cell activation between Brca2^null and Brca1^null murine tumors from the 4T1 model. e, Heatmap for genes significantly differentially expressed in a associated with antigen presentation between Brca2^null and Brca1^null murine tumors from the 4T1 model. f, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05) between Brca2^null and Brca1^null tumors from the Kurozumi Response to Cytolytic Virus pathway, evaluated using GSEA (FDR P <= 0.05). g, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05) between Brca2^null and Brca1^null tumors from the Reactome chemokines pathway, evaluated using GSEA (FDR P <= 0.05).h, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05) between Brca2^null and Brca1^null tumors from the NK-mediated cytotoxicity pathway, evaluated using GSEA (FDR P <= 0.05). For c-h, P-values calculated from two-sided differential expression analysis using DESeq2 (Wald test) and correct for multiple testing using the Benjamini-Hochberg method. i, Heatmap of mean log-normalized expression of differentially expressed genes for genes promoting immune activity/evasion in between Brca1^null and Brca2^null deficient cell lines in vitro. For all GSEA analyses, p-values calculated using two-sided pre-ranked analysis using log fold changes as input.

Extended Data Fig. 6 |. Bulk RNA-seq analysis between Brca2^null and Brca1^null tumors after treatment with anti-PD1 yields gene expression programs related to adaptive and innate immune activation enriched in treated Brca2 null tumors.

a, Heatmap displaying all genes significantly differentially expressed (FDR < 0.05) between Brca2^null and Brca1^null murine tumors from the 4T1 model after treatment with anti-PD1. Data show drastic gene expression changes upon Brca2 inactivation with treatment. P-values calculated from two-sided differential expression analysis using DESeq2 (Wald test) and corrected for multiple testing using the Benjamini-Hochberg method. b, Pathway analysis on genes from a using GO pathways. Top enriched pathways in either treated Brca2^null or treated Brca1^null tumors are shown. Color gradient of red to purple indicates decreasing adjusted p-value; circle size indicates number of genes in pathway. GeneRatio on x-axis indicates number of significantly differentially expressed genes from RNA-seq overlapping with genes in each pathway. P-values for overlap between input genes and pathway genesets calculated via hypergeometric test and corrected for multiple comparisons using the Benjamini Hochberg method. c, Heatmap displaying genes significantly differentially expressed in a associated with innate immunity between treated Brca2^null and Brca1^null murine tumors from the 4T1 model. d, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05) between Brca2^null and Brca1^null tumors from the Bosco interferon antiviral module pathway, evaluated using GSEA (FDR P <= 0.05). e, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05) between Brca2^null and Brca1^null tumors from the Brown myeloid cell development up pathway, evaluated using GSEA (FDR P <= 0.05). f, Heatmap showing significantly differentially expressed genes (FDR P <= 0.05) between Brca2^null and Brca1^null tumors from the Hecker IFNB1 targets pathway, evaluated using GSEA (FDR P <= 0.05). For c-f, p-values calculated from two-sided differential expression analysis using DESeq2 (Wald test) and correct for multiple testing using the Benjamini-Hochberg method. For all GSEA analyses, p-values calculated using two-sided pre-ranked analysis using log fold changes as input.

Extended Data Fig. 7 |. Whole exome sequencing analysis of BRCA2-mutant and BRCA1-mutant tumors from the TCGA breast cancer cohort

a, Principal component analysis (PCA) of ssGSEA scores for T cell populations for patients with either BRCA1 or BRCA2 germline or somatic biallelic mutations. P-value computed on separation between BRCA1 mutant and BRCA2 mutant samples using a two-sided PERMANOVA test. b, Principal component analysis (PCA) of ssGSEA scores for T cell populations for patients with either BRCA1 or BRCA2 germline or somatic biallelic mutations. P-value computed on separation between BRCA1 mutant and BRCA2 mutant samples using a two-sided PERMANOVA test. c. Oncoprint for 35 breast cancers with biallelic BRCA1 or BRCA2 mutations. Mutations in the top 20 most frequently mutated genes in breast cancer are illustrated, along with the mutational profile of each individual tumor. d, Comparison of indel, SNV, and neopeptide counts between triple negative BRCA1-mutant tumors (BRCA1 TN n=15, individual patients) vs all triple negative (All TN, n=153, individual patients) tumors. Data show no difference in mutation counts between BRCA1-mutant tumors and histology-matched control tumors. P-values calculated using two-sided Wilcoxon test, which is also used in e-i and l. For all the boxplot in this figure pannels d-h and l, the minima, maxima are plotted as the whiskers, 1st and 3rd quartiles are plotted as the bounds of the boxes, and medians are plotted as the center. e, Comparison of indel, SNV, and neopeptide counts between non-triple negative BRCA2-mutant tumors (BRCA2 NTN, n=17, individual patients) vs all non-triple negative (All NTN, n=700, individual patients) tumors. The same groups of patients, All TN (n=153), BRCA1 TN (n=15), ALL NTN (n=700), BRCA2 NTN (n=17) are used in the figure panel d-h and l. Data show increased levels of all alterations in BRCA2-mutant tumors compared to histology-matched control tumors. P-values calculated using two-sided Wilcoxon test. f, Comparison of fraction contribution of the six SNV substitutions between triple negative BRCA1-mutant tumors vs all triple negative tumors. P-values calculated using two-sided Wilcoxon test g, Comparison of fraction contribution of the six SNV substitutions between non-triple negative BRCA2-mutant tumors vs all non-triple negative tumors. The labels for p values are as the following: ns: p > 0.05, *: p <= 0.05, **: p <= 0.01, ***: p <= 0.001, ****: p <= 0.0001. h-i, Comparison of fraction contribution of COSMIC signature 3 (h) and distribution of microhomology mediated deletion (i) between BRCA1-mutated triple negative tumors or non-triple BRCA1-mutated negative tumors with their histology control. P-values calculated using two-sided Wilcoxon test j-k, Copy number plots for biallelic mutated BRCA1(j) and BRCA2 (k) tumors from TCGA breast cancer cohort. (L). Comparison of fraction copy number altered genome (FCNA) between BRCA1 and BRCA2-mutant tumors and histology-matched control tumors. Data show significantly higher FCNA in BRCA1-mutant tumors relative to histology-matched controls, while no such effect was observed for BRCA2-mutant tumors. P-values calculated using two-sided Wilcoxon test.

Extended Data Fig. 8 |. Single cell library sizes, replicates, and proportions of clusters across ICB-untreated Brca2^null and Brca1^null tumors and parental tumors.

a, Library size distribution for ICB-untreated single cells b, Library size distribution for ICB-treated single cells. c, Number of cells for each replicate used in scRNA-seq analyses. d, Proportion of all cells attributed to each T cell cluster from Fig 5 (ICB-untreated mice) from Brca2^null, Brca1^null, and parental tumors. e, Proportion of all myeloid cells attributed to each myeloid cell cluster from Fig 5 (ICB-untreated mice) from Brca2^null, Brca1^null, and parental tumors. Stars represent FDR p-value < 0.05 from two-sided Fisher’s exact test comparing cluster proportions in Brca2^null and Brca1^null mice.

Extended Data Fig. 9 |. Experimental validation of sc-RNA-seq and bulk RNA-seq results on untreated 4T1 Brca1^null and Brca2^null tumors.

a. Flow cytometry validation of several key immune cell populations including the Gmzb+ activated Cd8+ and Cd4+ T cells, CD206+ suppressive TAM, pDC and Cd103+ conventional DC, n=5 independent biological replicates. b. QRT-PCR validation of the most upregulated inflammation related genes in Brca1^null vs Brca2^null tumors, n=5 independent biological replicates. Data are presented as mean values +/− SEM.

Extended Data Fig. 10 |. Single cell RNA-seq analysis reveals marked heterogeneity within 4T1 murine tumors and enrichment of distinct T cell populations in post anti-PD1 antibody therapy Brca1^null and Brca2^null tumors.

a, t-SNE plot after dimensionality reduction and Phenograph clustering yields 31 distinct clusters afrom post-treated Brca1^null and Brca2^null tumors as well as parental tumor. b, t-SNE plots from a overlaid with log-normalized expression of select markers spanning T cell and NK cell clusters. c, t-SNE plots from a overlaid with log-normalized expression of select markers spanning myeloid cell clusters. d, Proportion of all cells attributed to each T cell cluster from a (ICB-untreated mice) from Brca1^null, Brca2^null and parental tumors, for clusters with more than 100 cells. e, Proportion of all cells attributed to each T cell cluster from a (ICB-untreated mice) from Brca1^null, Brca2^null, and parental tumors, for clusters with more than 100 cells. Stars represent FDR P < 0.05 from two-sided Fisher’s exact test comparing cluster proportions in Brca2^null mice and Brca1^null mice.

Fig 1:. Immunogenomic analyses of the association of homologous recombination deficiency with response to immune checkpoint inhibitors.

a, Association of truncating somatic mutations in genes from 52 KEGG pathways sequenced by the MSK-IMPACT gene panel and improved survival after immune checkpoint inhibitor (ICB) administration. Hazard ratios and p values calculated using Cox proportional hazards model comparing survival for patients with a truncating mutation in each pathway vs. those without a mutation. Selected pathways are shown in blue. An HR pathway mutation was associated with an improved OS (hazard ratio 0.55, p = 0.005, FDR < 0.10, two-sided log-rank test). Analysis was performed on 2195 patients. Plot shows nominal unadjusted p-values. b, Schematic of experimental design. Whole genome, targeted panel, and bulk and single cell transcriptomic sequencing from murine and human tumors were used to analyze the effect of mutations in BRCA1 and BRCA2 on the tumor-immune microenvironment and response to ICB.

Fig 2:. Enhanced response to checkpoint blockade immunotherapy in syngeneic mouse models of Brca2 deficiency.

a, Representative immunofluorescence images of parental (left) and Brca2^null (right) 4T1 murine breast carcinoma cells 4 hours after 10 Gy irradiation stained with DAPI and antibodies to Rad51 (green) and gamma-H2ax (red). b, Quantification of immunofluorescence analysis described in a. P value represents two-sided Fisher’s exact test of the relative proportion of nuclei containing greater than 5 Rad51 foci in parental compared to Brca2^null cells n=173 and 109 cells analyzed, respectively c, In vitro relative viable cell count in the presence of PARP inhibitor olaparib at indicated concentrations after 96 hours in three independent assays. Data are presented as mean values +/− SEM. d, Representative images of parental (left) and Brca2^null (right) 4T1 cell karyotype analysis demonstrating increased double strand breaks. e, Counts of whole-genome SNVs and indels in 4T1 Brca2^null and two parental single cell clones after 4 months in culture. f, Distribution of deletion size of indels in two single cell 4T1 Brca2^null clones and two parental clones. Both Brca2^null clones (n = 1183 and 1344 deletions for SC1 and SC2 respectively) had significantly larger deletions compared to parental clone SC1 (n = 815 deletions, p < 0.0001 for both, two-sided Wilcoxon test), g, Left: Representative flow cytometry plots demonstrating percent Cd4⁺ and Cd8a⁺ of Cd45⁺ tumor infiltrating lymphocytes in 4T1 parental and Brca2^null mammary fat pad tumors. Right: Quantification of single experiment data with n=3 animals as shown in g. P value represents one-sided unpaired t test. h, Growth curves demonstrating tumor volumes at indicated time points from start of treatment in 4T1 parental (left) and Brca2^null cells (right) implanted in the mammary fat pad treated with the indicated antibodies. N=15 mice per group. P values indicate two-sided t tests at respective time points (* p<0.05, ** p<0.005,*** p<0.0005, **** p<0.00005). Data are presented as mean values +/− SEM. i, Growth curves demonstrating tumor volumes at indicated time points from start of treatment in CT26 parental (left) and Brca2^null (right) flank tumors treated with the indicated antibodies. P values indicate two-sided t tests at respective time points (* p<0.05, ** p<0.005,*** p<0.0005, **** p<0.00005). Error bars represent mean ± standard error. j Representative immunofluorescent images stained with Cd3-Alexa647 (Yellow) and DAPI (blue) in the indicated tumors and treatment groups. k, Quantification right of n=5 high powered fields (HPF, 40X) from independent tumors by observer blinded to treatment group for Cd3 positive cells as well as Cd3+Cd4+ and Cd3+Cd8a+. P values represent two-sided t test. Data are presented as mean values +/− SEM.

Fig 3:. Differential response of Brca1^null and Brca2^null tumors to treatment with immune checkpoint inhibitors and modulation of the tumor-immune microenvironment.

a, Western blot of Brca1 in 4T1 Parental cell lines as well as two CRISPR-Cas9 edited subclones deficient in Brca1. Representative blot of 3 experiments performed with similar results. b, In vitro relative viable cell count in the presence of PARP inhibitor olaparib at indicated concentrations after 96 hours in three independent assays. c, Counts of SNVs and indels in two 4T1 Brca1^null and parental single cell clones after 4 months in culture. d, Distribution of deletion size of indels in two single cell 4T1 Brca1^null clones and two parental clones (n=4 cell lines). Both 4T1 Brca1^null clones (703 and 892 deletions in SC1 and SC2 respectively) have larger deletions compared to parental clone SC1 (815 deletions, p < 0.0001, two-sided Wilcoxon test) e, Growth curves demonstrating tumor volumes at indicated time points from start of treatment in 4T1 parental (left) and Brca1^null cells (middle and right) implanted in the mammary fat pad treated with the indicated antibodies. n = 15 mice per group. Data are presented as mean values +/− SEM. f, Principal component analysis of single sample gene set enrichment analysis (ssGSEA) scores for immune cells across Brca2^null and Brca1^null 4T1 mice (N = 5 biological replicates each). g, Heatmap of significantly differentially expressed genes from the TCR Signaling pathway from MSigDB, evaluating all differentially expressed genes (FDR P < 0.05, two-sided Wald test from DESeq2) between Brca2^null (n = 5 biological replicates) and Brca1^null 4T1 mice (n = 5 biological replicates). h, Heatmap of significantly differentially expressed genes from the Th1 Cytotoxic pathway from MSigDB, evaluating all differentially expressed genes (FDR P < 0.05, two-sided Wald test from DESeq2) between Brca2^null (n = 5 biological replicates) and Brca1^null (n = 5 biological replicates) 4T1 mice. i, GSEA enrichment plot of the immunoregulatory gene set evaluating all differentially expressed genes between 4T1 Brca2^null and Brca1^null cells in culture, indicating significant enrichment in Brca1^null cells. P-values calculated via two-sided GSEA pre-ranked analysis with log fold changes as input. Only one gene set (immunoregulatory gene set) was analyzed, and thus no correction for multiple testing was performed.

Fig 4:. BRCA1 and BRCA2 mutations differentially modulate the tumor-immune microenvironment and response to immune checkpoint inhibitors in the TCGA breast cancer cohort and MSK-IMPACT.

a, Principal component analysis (PCA) of ssGSEA scores for innate immune cells for patients with either BRCA1 or BRCA2 germline or somatic biallelic mutations. P-value computed on separation between BRCA1 mutant (n = 17) and BRCA2 mutant (n = 18) samples using a two-sided PERMANOVA test. b, GSEA enrichment plot of the immunoregulatory gene set evaluating all differentially expressed genes between BRCA2 and BRCA1-mutant tumors, indicating significant enrichment in BRCA1-mutant tumors. c, GSEA enrichment plot of the immunoregulatory gene set evaluating all differentially expressed genes between triple negative BRCA1-mutant and wild-type triple negative tumors, indicating significant enrichment in TN BRCA1-mutant tumors. d, GSEA enrichment plot of the immunoregulatory gene set evaluating all differentially expressed genes between non-triple negative BRCA2-mutant and wild-type non-triple negative tumors, indicating no significant enrichment. e, GSEA enrichment plot of the immunoregulatory gene set evaluating all differentially expressed genes between BRCA1-mutant and BRCA2-mutant tumors in the METABRIC cohort, indicating significant enrichment in BRCA1-mutant tumors. For b-e, p-values calculated via two-sided GSEA pre-ranked analysis with log fold changes as input. Only one gene set (immunoregulatory gene set) was analyzed, and thus no correction for multiple testing was performed. f, Proportion of patients with pathogenic identifiable BRCA2 mutations deriving clinical benefit from ICI in MSK-IMPACT. (PR- partial response, SD- stable disease (greater than 6 months), PD-progressive disease, and CR- complete response) g, Overall survival of patients from anonymized MSK-IMPACT with pathogenic BRCA2 and BRCA1 mutations after ICB administration. P-value calculated using log-rank test. h, Multivariable analysis of the effect of BRCA2 mutations on response to ICB when controlling for tumor mutation burden (TMB) and cancer type. Number of patients for TMB listed as N/A since TMB was tested as a continuous variable. P-value = 5.25e-06 for TMB. HR-associated cancers were defined as breast, prostate, pancreatic, or ovarian cancers. P-value for Non-HR-associated listed as N/A since it is the reference level. P-values are unadjusted and calculated from multivariable cox regression.

Fig 5:. Single cell RNA-seq analysis reveals marked heterogeneity within 4T1 murine tumors and enrichment of distinct T cell populations in Brca1^null and Brca2^null tumors.

a, t-SNE plot after dimensionality reduction and Phenograph clustering yields 25 distinct clusters across 53136 cells from untreated Brca1^null and Brca2^null tumors as well as parental tumors. Top significantly differentially expressed genes and manual phenotype (or ambiguous, for clusters that could not be assigned a known phenotype) assignment are shown as annotations for each cluster. b, Violin plots showing log-normalized expression of lineage-defining immune cell markers across all clusters. Markers for T cells (Cd3d), myeloid cells (Cd14), B cells (Cd79a), and NK cells (Ncr1) are shown. c, t-SNE plots from a overlaid with log-normalized expression of select markers spanning cytotoxic, exhausted, memory, and proliferative T cell states. d, Heatmap of mean log-normalized expression of top differentially expressed genes per cluster, for T cell clusters. e, Cluster enrichments for T cell clusters and the NK cell cluster C24 in untreated tumors. Each replicate is plotted within each genotype, and barplots show mean proportion across all replicates within a genotype. n = 3 biologically independent samples for Brca2 null and Parental mice, and n = 2 biologically independent samples for Brca1 null mice. P-values calculated via two-sided Fisher’s exact test comparing T cell/NK cluster proportions in Brca2 null and Brca1 null mice. C9: FDR P = 4.19e-12, C5: FDR P = 1.07e-21, C6: 6.86e-17, C0: 9.97e-10, C24: 5.81e-12. All p-values were adjusted for multiple comparisons using the Benjamini-Hochberg method.

Fig 6:. Single cell RNA-seq analysis reveals enrichment of distinct myeloid populations in Brca1^null and Brca2^null tumors.

a, t-SNE plot after reclustering of all Cd3^– Cd14⁺ cells from Fig. 5a after dimensionality reduction and Phenograph clustering yields 11 distinct clusters across 5390 cells from untreated Brca1 and Brca2-deficient tumors as well as parental tumors. Top significantly differentially expressed genes and manual phenotype (or ambiguous, for clusters that could not be assigned a known phenotype) assignment are shown as annotations for each cluster. b, Violin plots showing log-normalized expression of lineage-defining immune cell markers across all clusters. Markers for monocytes (Cd16), macrophages (Csf1r), and dendritic cells (Flt3). c, t-SNE plots from a overlaid with log-normalized expression of select markers spanning pro- and anti-inflammatory myeloid cell states. d, Heatmap of mean log-normalized expression of top differentially expressed genes per cluster, for myeloid cell clusters C0-C9 e, Cluster enrichments (presented as fraction of all myeloid cells) in untreated tumors. Each replicate is plotted within each genotype, and barplots show mean proportion across all replicates within a genotype. n = 3 biologically independent samples for Brca2 null and Parental mice, and n = 2 biologically independent samples for Brca1 null mice. P-values calculated via two-sided Fisher’s exact test comparing cluster proportions in Brca2 null and Brca1 null mice. C3: FDR P = 9.58e-05, C4: FDR P = 8.76e-47, C5: FDR P = 9.58e-05, C6: FDR P = 6.47e-05, C8: FDR P = 7.46e-07. All p-values were adjusted for multiple comparisons using the Benjamini-Hochberg method.

Fig 7:. Single cell RNA-seq analysis reveals enrichment of distinct myeloid populations in Brca1^null and Brca2^null tumors treated with ICB.

a, Heatmap of mean log-normalized expression of top differentially expressed genes per cluster for T cell clusters b, Heatmap of mean log-normalized expression of top differentially expressed genes per cluster for myeloid clusters c, Cluster enrichments in ICB-treated tumors. Each replicate is plotted within each genotype, and barplots show mean proportion across all replicates within a genotype. n = 2 biologically independent samples for Brca1 null, Brca2 null and Parental mice, P-values calculated via two-sided Fisher’s exact test comparing cluster proportions in Brca2 null and Brca1 null mice. C10: FDR P = 4.24e-25, C8: FDR P = 2.73e-13, C0: FDR P = 1.04e-11, C5: FDR P = 1.60e-05, C20: FDR P = 2.06e-06. All p-values were adjusted for multiple comparisons using the Benjamini-Hochberg method.