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Supplemental Table 6: mRNA:miRNA pairs enriched in LNMs subtypes.

Purpose: Solid tumors that have grown two weeks or longer in mice and have diameters larger than 1 cm are histologically indistinguishable from autochthonous human cancers. When experimental tumors reach this clinically relevant size, they are usually refractory to most immunotherapies but may be destroyed by adoptive T-cell transfer. However, TCR-transgenic T cells and/or tumor cells overexpressing antigens are frequently used in these experiments. Here we studied the requirements for destroying clinical size, unmanipulated 8101 tumors by adoptive cell therapy.Experimental Design: 8101 arose in an old mouse after chronic exposure to UV light. A cancer line was established, which was never serially transplanted. The immunodominant CD8+ T cell-recognized antigen of this tumor is caused by a somatic tumor–specific mutation in the RNA helicase p68. 8101 tumors were treated with spleen cells from young naive, or young and old immunized mice to ascertain the characteristics of immune cells that lead to rejection.Results: Here we show that the mutant p68 peptide has an exceptionally high affinity to the presenting MHC class I molecule Kb and that spleen cells from immunized young syngeneic mice adoptively transferred to Rag−/− or cancer-suppressed euthymic mice eradicate 8101 tumors larger than 1 cm in average diameter and established for several weeks. Spleen cells from naive young mice or from old and boosted (reimmunized) mice were ineffective.Conclusions: Relapse-free destruction of large and long-established tumors expressing a genuine very high-affinity tumor-specific antigen can be achieved by using adoptive transfer of lymphocytes from immunized young individuals. Clin Cancer Res; 18(9); 2526–33. ©2012 AACR.

Supplemental Methods, Supplemental Tables 1, 3, 4, 6, 7, 8, Supplemental Figures 1-12 Supplemental Table 1. Overall patient characteristics. Supplemental Table 3. Patient Characteristics by lymph node molecular classification. Supplemental Table 4. Univariate and multivariate analysis for locoregional control. Supplemental Table 7. Accuracy of existing classifiers to predict Group 2 LNM subtype. Supplemental Table 8. 73 gene classifier Supplemental Figure 1. Patient selection. Supplemental Figure 2. Metrics of the 73 gene classifier. (A) Metrics of 73 gene classifier. (B) Misclassification error for C2 and C13 groups. (C) Misclassification of entire classifier. Supplemental Figure 3. Outcomes in HNSCC cohort.Kaplan-Meier analysis of: (A) Locoregional control. (B) Local-only control. (C) Relapse free survival. (D) Regional control. (E) Distant control. (F) Overall survival. Supplemental Figure 4. Outcomes by molecular subtypes of LNMs.Kaplan-Meier analysis of: (A) Regional control. (B) Distant control. Supplementary Figure 5: DEmiRNAsin LNMs subtypes. Supplemental Figure 6. Consensus clustering of pairwise DEGs for other predefined cluster numbers does not identify other LNMs subtypes that predict for disease recurrence. Supplemental Figure 7. Enrichment of KEGG pathways in LNMs subtypes. Supplemental Figure 8. Estimated abundance of immune cells. Supplemental Figure 9. LNMs subtypes cluster separately from non-metastatic lymph nodes in the same cohort. Supplemental Figure 10. LNMs subtypes cluster separately from normal lymph nodes derived from publically available microarray databases. Supplemental Figure 11. The transcriptome of lymph node metastasis better predicts for patients at higher risk of relapse or death. Supplemental Figure 12. Receiver-Operator Curve for 73 gene LNM-classifier.

PDF file, 33KB, Percentages and absolute numbers of regulatory CD4+ T cells (Treg) in the peripheral blood of young (5 month-old) and old (15 monthold) mice.

Supplemental Table 2. LN classification by iCluster and PAM classifier.

PDF file, 196KB, Loss of expression of the mutant p68 (mp68) rejection antigen by all 8101 variants that grew progressively in na�ve young mice but retention by 8101 tumor that developed in the old recipient.

PDF file, 163KB.

PDF file, 174KB, A cancer progressor variant is selected by a young mouse upon injection of cryopreserved 8101 original tumor fragments.

Supplemental Table 5. DEmRNAs and DEmiRNAs in LNMs.

Purpose:In advanced stage head and neck squamous cell cancers (HNSCC), approximately half of the patients with lymph node metastases (LNM) are not cured. Given the heterogeneous outcomes in these patients, we profiled the expression patterns of LNMs to identify the biological factors associated with patient outcomes.Experimental Design: We performed mRNAseq and miRNAseq on 72 LNMs and 29 matched primary tumors from 34 patients with HNSCC. Clustering identified molecular subtypes in LNMs and in primary tumors. Prediction Analysis of Microarrays algorithm identified a 73-gene classifier that distinguished LNM subtypes. Gene-set enrichment analysis identified pathways upregulated in LNM subtypes.Results:Integrative clustering identified three distinct LNM subtypes: (i) an immune subtype (Group 1), (ii) an invasive subtype (Group 2), and (iii) a metabolic/proliferative subtype (Group 3). Group 2 subtype was associated with significantly worse locoregional control and survival. LNM-specific subtypes were not observed in matched primary tumor specimens. In HNSCCs, breast cancers, and melanomas, a 73-gene classifier identified similar Group 2 LNM subtypes that were associated with worse disease control and survival only when applied to lymph node sites, but not when applied to other primary tumors or metastatic sites. Similarly, previously proposed prognostic classifiers better distinguished patients with worse outcomes when applied to the transcriptional profiles of LNMs, but not the profiles of primary tumors.Conclusions:The transcriptional profiles of LNMs better predict outcomes than transcriptional profiles of primary tumors. The LNMs display site-specific subtypes associated with worse disease control and survival across multiple cancer types.

Supplemental Table 9. Breast cancer characteristics

Supplemental Table 10. Melanoma characteristics.

Supplemental Methods, Tables 1-9 and Figures 1-9. Supplemental Methods: Animals; Sleeping Beauty transposon mapping; Reagents and antibodies; HPV recombination, T2/Onc excision and Hras mutation specific PCRs. Supplemental Table 1: Mouse strains used in this study. Supplemental Table 2: Primers used in the generation of insertional mutagenesis libraries. Supplemental Table 3: Common insertion sites (CIS) in DMBA and 4-NQO treated HPV-positive and HPV-negative tumors. Supplemental Table 4: Characterizations of Notch1 insertions. Supplemental Table 5: Transposon orientation and frequency for candidate genes in Figure 3B. Supplemental Table 6: Differentially expressed genes in KHR compared to KHR-N-/- and KHR-N+/- tumors. Supplemental Table 7: Differentially expressed genes in KHR-N-/- compared to KHRNICD tumors. Supplemental Table 8: Comparison of pathway analysis for KHR-N+/- and KHR-N-/- tumors compared to KR-N-/- tumors. Supplemental Table 9: Summary of GSEA Hallmark gene sets significantly enriched in KHRNICD and KHR-N-/- tumors. Supplemental Figure 1. LSL-HPV recombination, T2/Onc transposition and Ha-Ras mutations in HPV-positive and HPV-negative tumors. Supplemental Figure 2. Sleeping Beauty insertional mutagenesis accelerated tumorigenesis in 4-NQO treated HPV-positive and HPV-negative mice. Supplemental Figure 3. Tumors with activating T2/Onc insertions have higher Notch1 expression compared to tumors with inactivating T2/Onc insertions. Supplemental Figure 4. Validation of NICD expression in KHRNICD oral tumors. Supplemental Figure 5. KHRNICD oral tumors had increased Hes1 and Hey1 nuclear expression. Supplemental Figure 6. KHR and KHRNICD oral tumors had similar CK14 expression. Supplemental Figure 7. KHR and KHR-Notch1+/- and KHR-Notch1-/- oral tumors had similar CK14 expression. Supplemental Figure 8. KHR, KHR-Notch+/- and KHR-Notch-/- oral tumors have invasive components. Supplemental Figure 9. NOTCH1 somatic mutations in ALTCL, CESC and HNSC patients.

Purpose: In advanced stage head and neck squamous cell cancers (HNSCC), approximately half of the patients with lymph node metastases (LNM) are not cured. Given the heterogeneous outcomes in these patients, we profiled the expression patterns of LNMs to identify the biological factors associated with patient outcomes. Experimental Design: We performed mRNAseq and miRNAseq on 72 LNMs and 29 matched primary tumors from 34 patients with HNSCC. Clustering identified molecular subtypes in LNMs and in primary tumors. Prediction Analysis of Microarrays algorithm identified a 73-gene classifier that distinguished LNM subtypes. Gene-set enrichment analysis identified pathways upregulated in LNM subtypes. Results: Integrative clustering identified three distinct LNM subtypes: (i) an immune subtype (Group 1), (ii) an invasive subtype (Group 2), and (iii) a metabolic/proliferative subtype (Group 3). Group 2 subtype was associated with significantly worse locoregional control and survival. LNM-specific subtypes were not observed in matched primary tumor specimens. In HNSCCs, breast cancers, and melanomas, a 73-gene classifier identified similar Group 2 LNM subtypes that were associated with worse disease control and survival only when applied to lymph node sites, but not when applied to other primary tumors or metastatic sites. Similarly, previously proposed prognostic classifiers better distinguished patients with worse outcomes when applied to the transcriptional profiles of LNMs, but not the profiles of primary tumors. Conclusions: The transcriptional profiles of LNMs better predict outcomes than transcriptional profiles of primary tumors. The LNMs display site-specific subtypes associated with worse disease control and survival across multiple cancer types.

The treatment paradigms for head and neck squamous cell cancer (HNSCC) are changing due to the emergence of human papillomavirus (HPV)-associated tumors possessing distinct molecular profiles and responses to therapy. Although patients with HNSCCs are often treated with radiotherapy, preclinical models are limited by the ability to deliver precise radiation to orthotopic tumors and to monitor treatment responses accordingly. To better model this clinical scenario, we developed a novel autochthonous HPV-positive oral tumor model to track responses to small molecules and image-guided radiation. We used a tamoxifen-regulated Cre recombinase system to conditionally express the HPV oncogenes E6 and E7 as well as a luciferase reporter (iHPV-Luc) in the epithelial cells of transgenic mice. In the presence of activated Cre recombinase, luciferase activity, and by proxy, HPV oncogenes were induced to 11-fold higher levels. In triple transgenic mice containing the iHPV-Luc, K14-CreERtam, and LSL-Kras transgenes, tamoxifen treatment resulted in oral tumor development with increased bioluminescent activity within 6 days that reached a maximum of 74.8-fold higher bioluminescence compared with uninduced mice. Oral tumors expressed p16 and MCM7, two biomarkers associated with HPV-positive tumors. After treatment with rapamycin or image-guided radiotherapy, tumors regressed and possessed decreased bioluminescence. Thus, this novel system enables us to rapidly visualize HPV-positive tumor growth to model existing and new interventions using clinically relevant drugs and radiotherapy techniques. Cancer Res; 74(7); 2073–81. ©2014 AACR.

Pancreatic cancer patients often fail to respond to immunotherapy, such as vaccines or checkpoint inhibitors. It is unknown if an immune phenotype predicts the efficacy of immunotherapy for pancreatic cancer and what standard modalities are required to facilitate the response of pancreatic cancer to immunotherapy. We examined prognostic markers of immune cell infiltration in pancreatic cancer. Pancreatic cancer patients with low CD8+ T cell infiltration and high PD-L1 expression (CD8+ TloPD-L1hi) experienced worse outcomes compared to patients whose tumors demonstrate CD8+ TloPD-L1lo, CD8+ ThiPD-L1hi or CD8+ ThiPD-L1lo profiles. To understand how to improve tumor control in CD8+ TloPD-L1hi pancreatic cancers, we developed a mouse tumor fragment model with a trackable model antigen (SIYRYYGL or SIY) to mimic CD8+ TloPD-L1hi pancreatic cancers. Similar to pancreatic cancers, tumors arising from fragments contained few T cells, even after vaccination. Fragment tumors responded poorly to PD-L1 blockade, SIY vaccination or radiation as individual treatments. By contrast, local ionizing radiation coupled with vaccination increased CD8+ T cell infiltration that was associated with upregulation of CXCL10 and CCL5 chemokines in the tumor, but demonstrated modest inhibition of tumor growth. The addition of an anti-PD-L1 antibody enhanced the effector function of tumor-infiltrating T cells, leading to significantly improved tumor regression and increased survival compared to vaccination and radiation. These results indicate that combination of radiation, vaccination and checkpoint blockade could convert non-T cell-inflamed cancers to T cell-inflamed cancers, and thus effectively treat established pancreatic tumors with an initial CD8+ TloPD-L1hi phenotype. This suggests a novel immunostimulatory role for radiotherapy in the treatment of pancreatic cancer. Citation Format: Wenxin Zheng, Kinga B. Skowron, Jukes P. Namm, Byron Burnette, Christian Fernandez, Ainhoa Arina, Hua Liang, Michael T. Spiotto, Mitchell C. Posner, Yang-Xin Fu, Ralph R. Weichselbaum. Radiotherapy sensitizes pancreatic cancer to immunotherapy by promoting T cell infiltration. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-251.