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Head and neck squamous cell carcinoma (HNSCC) has one of the most hypoxic and immunosuppressive tumor microenvironments (TME) among solid tumors. However, there is no proven therapeutic strategy to remodel the TME to be less hypoxic and proinflammatory. In this study, we classified tumors according to a Hypoxia-Immune signature, characterized the immune cells in each subgroup, and analyzed the signaling pathways to identify a potential therapeutic target that can remodel the TME. We confirmed that hypoxic tumors had significantly higher numbers of immunosuppressive cells, as evidenced by a lower ratio of CD8+ T cells to FOXP3+ regulatory T cells, compared with nonhypoxic tumors. Patients with hypoxic tumors had worse outcomes after treatment with pembrolizumab or nivolumab, anti-programmed cell death-1 inhibitors. Our expression analysis also indicated that hypoxic tumors predominantly increased the expression of the EGFR and TGFβ pathway genes. Cetuximab, an anti-EGFR inhibitor, decreased the expression of hypoxia signature genes, suggesting that it may alleviate the effects of hypoxia and remodel the TME to become more proinflammatory. Our study provides a rationale for treatment strategies combining EGFR-targeted agents and immunotherapy in the management of hypoxic HNSCC. Significance: While the hypoxic and immunosuppressive TME of HNSCC has been well described, comprehensive evaluation of the immune cell components and signaling pathways contributing to immunotherapy resistance has been poorly characterized. We further identified additional molecular determinants and potential therapeutic targets of the hypoxic TME to fully leverage currently available targeted therapies that can be administered with immunotherapy.

Background: Despite the immunogenic nature of many ovarian tumors, treatment with immune checkpoint therapies has not led to substantial improvements in ovarian cancer survival. To advance population-level research on the ovarian tumor immune microenvironment, it is critical to understand methodologic issues related to measurement of immune cells on tissue microarrays (TMA) using multiplex immunofluorescence (mIF) assays. Methods: In two prospective cohorts, we collected formalin-fixed, paraffin-embedded ovarian tumors from 486 cases and created seven TMAs. We measured T cells, including several sub-populations, and immune checkpoint markers on the TMAs using two mIF panels. We used Spearman correlations, Fisher exact tests, and multivariable-adjusted beta-binomial models to evaluate factors related to immune cell measurements in TMA tumor cores. Results: Between-core correlations of intratumoral immune markers ranged from 0.52 to 0.72, with more common markers (e.g., CD3+, CD3+CD8+) having higher correlations. Correlations of immune cell markers between the whole core, tumor area, and stromal area were high (range 0.69–0.97). In multivariable-adjusted models, odds of T-cell positivity were lower in clear cell and mucinous versus type II tumors (ORs, 0.13–0.48) and, for several sub-populations, were lower in older tissue (sample age > 30 versus ≤ 10 years; OR, 0.11–0.32). Conclusions: Overall, high correlations between cores for immune markers measured via mIF support the use of TMAs in studying ovarian tumor immune infiltration, although very old samples may have reduced antigenicity. Impact: Future epidemiologic studies should evaluate differences in the tumor immune response by histotype and identify modifiable factors that may alter the tumor immune microenvironment.

Background: Exposure to cigarette smoke, particularly in early life, is modestly associated with ovarian cancer risk and may impact systemic immunity and the tumor immune response. However, no studies have evaluated whether cigarette smoke exposure impacts the ovarian tumor immune microenvironment. Methods: Participants in the Nurses’ Health Study (NHS) and NHSII reported on early life exposure to cigarette smoke and personal smoking history on questionnaires (n = 165,760). Multiplex immunofluorescence assays were used to measure markers of T cells and immune checkpoints in tumor tissue from 385 incident ovarian cancer cases. We used Cox proportional hazards models to evaluate HRs and 95% confidence intervals (CI) for developing ovarian tumors with a low ( Results: Women exposed versus not to cigarette smoke early in life had a higher risk of developing ovarian cancer with low levels of T cells overall (CD3+: HR: 1.54, 95% CI: 1.08–2.20) and recently activated cytotoxic T cells (CD3+CD8+CD69+: HR: 1.45, 95% CI: 1.05–2.00). These findings were not statistically significant at the Bonferroni-corrected P value of 0.0083. Adult smoking was not significantly associated with tumor immune markers after Bonferroni correction. Conclusions: These results suggest early life cigarette smoke exposure may modestly increase risk of developing ovarian tumors with low abundance of total T cells and recently activated cytotoxic T cells. Impact: Future research should focus on understanding the impact of exposures throughout the life course on the ovarian tumor immune microenvironment.

CAR T-cell therapy has transformed the treatment of hematological malignancies of the B cell lineage. However, the quest to fulfil the same promise for solid tumors is still in its infancy. This review summarizes some of the challenges that the field is trying to overcome for effective treatment of human carcinomas, including tumor heterogeneity, the paucity of truly tumor-specific targets, immunosuppression and metabolic restrictions at solid tumor beds, and defective T-cell trafficking. All these barriers are being currently investigated and, in some cases, targeted, by multiple independent groups. With clinical interventions against multiple human malignancies and different platforms under accelerated clinical development, the next few years will see an array of cellular therapies, including CAR T-cells, progressively becoming routine interventions to eliminate currently incurable diseases, as it happened with some hematological malignancies.

GSEA of hallmark pathways in TCGA and Moffitt cohorts. TCGA (A–C) and Moffitt head and neck squamous cell carcinoma (D–F) cohorts. The gene expressions were compared for pathways enriched in: (A, D) Immune versus Hypoxia. Red: enriched in Immune, Blue: enriched in Hypoxia. B and E, Immune versus Mixture. Red: enriched in Immune, Blue: enriched in Mixture. C and F, Hypoxia versus Mixture. Red: enriched in Hypoxia, Blue: enriched in Mixture. Indicated are the top 10 most differentially expressed pathways in Cancer Hallmarks gene sets. NES: Normalized enrichment score.

Supplementary Table S1. TCGA Cohort

Patient characteristics in Moffitt cohort

(A, B) Representative mIHC images showing staining of nuclei (blue), tumor cell (orange - PCK) and selected immune checkpoint markers in each molecular subgroup. (A) Images show four lymphoid markers - CD3+ T-cells (Green), CD8+ cytotoxic T-cells (Yellow), CD69+ activated T-cells (Red) and CD103+ resident memory T-cells (Cyan). (B) Images show three myeloid markers – HLA-DR+ APCs (Green), MHCII+ APCs (Cyan) and CD163+ M2 macrophages (Yellow). (C) Linear model showing correlation between PD-L1 CPS and Immune, Mixture and Hypoxia subgroups. (D-E) Boxplots showing cell counts distribution of different immune markers among the primary (n = 63) and recurrent (n = 20) tumors in TMA mIHC cohort. Students t-tests were used to test for significant differences between the groups.

Hypoxia subgroup has immunosuppressive TME. Boxplots showing cell counts distribution of different immune markers CAIX+ cells representing hypoxia marker (A), CD3+ T cells (B), CD8+ cytotoxic T cells (C), PCK+ tumor cells expressing PD-L1 (D), HLA-DR+ APCs (E), and CD8+ T cells/FOXP3+ Tregs (F), among the three subgroups in the TMA mIHC cohort (n = 90). Statistical analysis was performed by ANOVA test and followed by Tukey post hoc tests. G, Representative mIHC images showing that the average numbers of immune cells expressing CD3+ T cells (green color), CD8+ cytotoxic T cells (yellow color), CD69+ activated T cells (red color), CD103+ resident memory T cells (cyan color) within 20 μm of a PCK+ cell (orange color) was statistically significantly lowest in the Hypoxia subgroup compared with the Mixture and Immune subgroups. Nuclei are shown in blue. Individual TMA core was considered as a region of interest (ROI). Bottom panel represents the zoom-in distance proximity and spatial distribution between a tumor cell and an immune cell within the TME.

Hypoxia subgroup has an enrichment of EGFR pathway. Pearson correlation coefficient for the TIMEx scores for the EGFR pathway and the Hypoxia gene signature among the TCGA (A), CPTAC (B), and Moffitt (C) HNSCC datasets. Expression distribution of EGFR RNA (D), protein (E), and phosphoprotein (F) levels among the three subgroups in the CPTAC HNSCC cohort.

Cetuximab treatment benefits Hypoxia subgroup. A, Heatmap of gene expression data from pre- and post-cetuximab (CTX) treated patient samples. RNA expression data (GSE109756) was z-normalized, each row represents a single gene in the hypoxia-immune signature gene list, each column represents a patient sample. Hierarchical clustering was performed as detailed in Materials and Methods. Samples were reordered according to its molecular subgroup: Immune (blue), mixture (black), and Hypoxia (red) with pre-cetuximab treated samples labeled BC and post-cetuximab labeled OC. TIMEx scores for the Hypoxia gene signature among the 15 patients classified into the three subgroups (B) and GSEA comparing gene expression changes in the pre- and post-cetuximab data using CIBERSORT gene sets: higher in post-cetuximab (red) and higher in pre-ceuximab (blue) (C).

Disease control given pembrolizumab or nivolumab monotherapy in Moffitt retrospective study cohort

Molecular classification and validation of hypoxia-immune signature in HNSCC. A, Heatmap of molecular subgroups in the Moffitt (n = 228) HNSCC cohort. RNA expression data were z-normalized, each row represents a single gene in the hypoxia-immune signature gene list, each column represents a patient sample. Samples were reordered according to its molecular subgroup: Immune (blue), Mixture (black), and Hypoxia (red). B, Kaplan–Meier survival plots for overall survival stratified according to the Hypoxia-Immune signature for the Moffitt (n = 184) HNSCC patient cohort.

Head and neck squamous cell carcinoma (HNSCC) has one of the most hypoxic and immunosuppressive tumor microenvironments (TME) among solid tumors. However, there is no proven therapeutic strategy to remodel the TME to be less hypoxic and proinflammatory. In this study, we classified tumors according to a Hypoxia-Immune signature, characterized the immune cells in each subgroup, and analyzed the signaling pathways to identify a potential therapeutic target that can remodel the TME. We confirmed that hypoxic tumors had significantly higher numbers of immunosuppressive cells, as evidenced by a lower ratio of CD8+ T cells to FOXP3+ regulatory T cells, compared with nonhypoxic tumors. Patients with hypoxic tumors had worse outcomes after treatment with pembrolizumab or nivolumab, anti-programmed cell death-1 inhibitors. Our expression analysis also indicated that hypoxic tumors predominantly increased the expression of the EGFR and TGFβ pathway genes. Cetuximab, an anti-EGFR inhibitor, decreased the expression of hypoxia signature genes, suggesting that it may alleviate the effects of hypoxia and remodel the TME to become more proinflammatory. Our study provides a rationale for treatment strategies combining EGFR-targeted agents and immunotherapy in the management of hypoxic HNSCC.Significance:While the hypoxic and immunosuppressive TME of HNSCC has been well described, comprehensive evaluation of the immune cell components and signaling pathways contributing to immunotherapy resistance has been poorly characterized. We further identified additional molecular determinants and potential therapeutic targets of the hypoxic TME to fully leverage currently available targeted therapies that can be administered with immunotherapy.

(A, B) Representative mIHC images showing staining of nuclei (blue), tumor cell (orange - PCK) and selected immune checkpoint markers in each molecular subgroup. (A) Images show four lymphoid markers - CD3+ T-cells (Green), CD8+ cytotoxic T-cells (Yellow), CD69+ activated T-cells (Red) and CD103+ resident memory T-cells (Cyan). (B) Images show three myeloid markers – HLA-DR+ APCs (Green), MHCII+ APCs (Cyan) and CD163+ M2 macrophages (Yellow). (C) Linear model showing correlation between PD-L1 CPS and Immune, Mixture and Hypoxia subgroups. (D-E) Boxplots showing cell counts distribution of different immune markers among the primary (n = 63) and recurrent (n = 20) tumors in TMA mIHC cohort. Students t-tests were used to test for significant differences between the groups.

Supplementary Table S2. CPTAC Cohort

The networks of transcription factors (TFs) that control intestinal-resident memory CD8 + T (T RM ) cells, including multipotency and effector programs, are poorly understood. In this work, we investigated the role of the TF Bcl11b in T RM cells during infection with Listeria monocytogenes using mice with post-activation, conditional deletion of Bcl11b in CD8 + T cells. Conditional deletion of Bcl11b resulted in increased numbers of intestinal T RM cells and their precursors as well as decreased splenic effector and circulating memory cells and precursors. Loss of circulating memory cells was in part due to increased intestinal homing of Bcl11b −/− circulating precursors, with no major alterations in their programs. Bcl11b −/− T RM cells had altered transcriptional programs, with diminished expression of multipotent/multifunctional (MP/MF) program genes, including Tcf7 , and up-regulation of the effector program genes, including Prdm1. Bcl11b also limits the expression of Ahr, another TF with a role in intestinal CD8 + T RM cell differentiation. Deregulation of T RM programs translated into a poor recall response despite T RM cell accumulation in the intestine. Reduced expression of MP/MF program genes in Bcl11b −/− T RM cells was linked to decreased chromatin accessibility and a reduction in activating histone marks at these loci. In contrast, the effector program genes displayed increased activating epigenetic status. These findings demonstrate that Bcl11b is a frontrunner in the tissue residency program of intestinal memory cells upstream of Tcf1 and Blimp1, promoting multipotency and restricting the effector program.

Supplemental Table 1 shows the correlations of percentages of the markers in the tumor.

Supplemental Figure 1 provides representative images from the T cell panel for high-grade serous, endometrioid, clear cell, and mucinous tumors.

Supplemental Figure 2 provides representative images from the immune checkpoint panel for high-grade serous, endometrioid, clear cell, and mucinous tumors.

Supplemental Table 2 shows the distribution of presence/absence of percentage of the marker in the tumor, by age of sample for type I and type II tumors

Supplemental Table 3 shows case characteristics included on tissue microarrays in NHS and NHSII

Supplemental Table 4 shows beta binomial models, odds ratios and 95% confidence intervals for marker positivity in the tumor, by tumor and participant characteristics

Background:Despite the immunogenic nature of many ovarian tumors, treatment with immune checkpoint therapies has not led to substantial improvements in ovarian cancer survival. To advance population-level research on the ovarian tumor immune microenvironment, it is critical to understand methodologic issues related to measurement of immune cells on tissue microarrays (TMA) using multiplex immunofluorescence (mIF) assays.Methods:In two prospective cohorts, we collected formalin-fixed, paraffin-embedded ovarian tumors from 486 cases and created seven TMAs. We measured T cells, including several sub-populations, and immune checkpoint markers on the TMAs using two mIF panels. We used Spearman correlations, Fisher exact tests, and multivariable-adjusted beta-binomial models to evaluate factors related to immune cell measurements in TMA tumor cores.Results:Between-core correlations of intratumoral immune markers ranged from 0.52 to 0.72, with more common markers (e.g., CD3+, CD3+CD8+) having higher correlations. Correlations of immune cell markers between the whole core, tumor area, and stromal area were high (range 0.69–0.97). In multivariable-adjusted models, odds of T-cell positivity were lower in clear cell and mucinous versus type II tumors (ORs, 0.13–0.48) and, for several sub-populations, were lower in older tissue (sample age > 30 versus ≤ 10 years; OR, 0.11–0.32).Conclusions:Overall, high correlations between cores for immune markers measured via mIF support the use of TMAs in studying ovarian tumor immune infiltration, although very old samples may have reduced antigenicity.Impact:Future epidemiologic studies should evaluate differences in the tumor immune response by histotype and identify modifiable factors that may alter the tumor immune microenvironment.

Supplemental Table 5 shows beta binomial models, odds ratios and 95% confidence intervals for marker positivity in the tumor, by population characteristics

Supplementary Tables 1, 2, and 3

Fragility of regulatory T (Treg) cells manifested by the loss of neuropilin-1 (NRP1) and expression of IFNγ undermines the immune suppressive functions of Treg cells and contributes to the success of immune therapies against cancers. Intratumoral Treg cells somehow avoid fragility; however, the mechanisms by which Treg cells are protected from fragility in the tumor microenvironment are not well understood. Here, we demonstrate that the IFNAR1 chain of the type I IFN (IFN1) receptor was downregulated on intratumoral Treg cells. Downregulation of IFNAR1 mediated by p38α kinase protected Treg cells from fragility and maintained NRP1 levels, which were decreased in response to IFN1. Genetic or pharmacologic inactivation of p38α and stabilization of IFNAR1 in Treg cells induced fragility and inhibited their immune suppressive and protumorigenic activities. The inhibitor of sumoylation TAK981 (Subasumstat) upregulated IFNAR1, eliciting Treg fragility and inhibiting tumor growth in an IFNAR1-dependent manner. These findings describe a mechanism by which intratumoral Treg cells retain immunosuppressive activities and suggest therapeutic approaches for inducing Treg fragility and increasing the efficacy of immunotherapies.

Supplementary Figure from Protection of Regulatory T Cells from Fragility and Inactivation in the Tumor Microenvironment

Supplementary Data from Protection of Regulatory T Cells from Fragility and Inactivation in the Tumor Microenvironment

Supplementary Figure Legends

Supplemental Information and Legends

S3. Serial quantification of serum IL6 from a patient with prolonged subjectove myalgia post IT injection of mRNA c-Met CAR T cells.

S1. Clinical trial schema. S2. Representative immunohistochemistry (IHC). S3. Histology and IHC of tumor tissue pre and post intratumoral injection of RNA CAR T c- Met from one patient. S4. Histology and IHC of tumor tissue pre and post intratumoral injection with lidocaine (1 mL) and RNA CAR T c-Met (1 mL) from another patient. S5. Characterization of CD68+ tumor infiltrated immune cells using multiplex IHC analyses as described (1) in pre and post IT injection of RNA CAR T c-Met tumor tissue sections from two patients.